Metamodel-based inverse method for parameter identification: elastic-plastic damage model

NASA Astrophysics Data System (ADS)

Huang, Changwu; El Hami, Abdelkhalak; Radi, Bouchaïb

2017-04-01

This article proposed a metamodel-based inverse method for material parameter identification and applies it to elastic-plastic damage model parameter identification. An elastic-plastic damage model is presented and implemented in numerical simulation. The metamodel-based inverse method is proposed in order to overcome the disadvantage in computational cost of the inverse method. In the metamodel-based inverse method, a Kriging metamodel is constructed based on the experimental design in order to model the relationship between material parameters and the objective function values in the inverse problem, and then the optimization procedure is executed by the use of a metamodel. The applications of the presented material model and proposed parameter identification method in the standard A 2017-T4 tensile test prove that the presented elastic-plastic damage model is adequate to describe the material's mechanical behaviour and that the proposed metamodel-based inverse method not only enhances the efficiency of parameter identification but also gives reliable results.

Multi-scale signed envelope inversion

NASA Astrophysics Data System (ADS)

Chen, Guo-Xin; Wu, Ru-Shan; Wang, Yu-Qing; Chen, Sheng-Chang

2018-06-01

Envelope inversion based on modulation signal mode was proposed to reconstruct large-scale structures of underground media. In order to solve the shortcomings of conventional envelope inversion, multi-scale envelope inversion was proposed using new envelope Fréchet derivative and multi-scale inversion strategy to invert strong contrast models. In multi-scale envelope inversion, amplitude demodulation was used to extract the low frequency information from envelope data. However, only to use amplitude demodulation method will cause the loss of wavefield polarity information, thus increasing the possibility of inversion to obtain multiple solutions. In this paper we proposed a new demodulation method which can contain both the amplitude and polarity information of the envelope data. Then we introduced this demodulation method into multi-scale envelope inversion, and proposed a new misfit functional: multi-scale signed envelope inversion. In the numerical tests, we applied the new inversion method to the salt layer model and SEG/EAGE 2-D Salt model using low-cut source (frequency components below 4 Hz were truncated). The results of numerical test demonstrated the effectiveness of this method.

Genotyping the factor VIII intron 22 inversion locus using fluorescent in situ hybridization.

PubMed

Sheen, Campbell R; McDonald, Margaret A; George, Peter M; Smith, Mark P; Morris, Christine M

2011-02-15

The factor VIII intron 22 inversion is the most common cause of hemophilia A, accounting for approximately 40% of all severe cases of the disease. Southern hybridization and multiplex long distance PCR are the most commonly used techniques to detect the inversion in a diagnostic setting, although both have significant limitations. Here we describe our experience establishing a multicolor fluorescent in situ hybridization (FISH) based assay as an alternative to existing methods for genetic diagnosis of the inversion. Our assay was designed to apply three differentially labelled BAC DNA probes that when hybridized to interphase nuclei would exhibit signal patterns that are consistent with the normal or the inversion locus. When the FISH assay was applied to five normal and five inversion male samples, the correct genotype was assignable with p<0.001 for all samples. When applied to carrier female samples the assay could not assign a genotype to all female samples, probably due to a lower proportion of informative nuclei in female samples caused by the added complexity of a second X chromosome. Despite this complication, these pilot findings show that the assay performs favourably compared to the commonly used methods. Copyright © 2010 Elsevier Inc. All rights reserved.

Dependence of paracentric inversion rate on tract length.

PubMed

York, Thomas L; Durrett, Rick; Nielsen, Rasmus

2007-04-03

We develop a Bayesian method based on MCMC for estimating the relative rates of pericentric and paracentric inversions from marker data from two species. The method also allows estimation of the distribution of inversion tract lengths. We apply the method to data from Drosophila melanogaster and D. yakuba. We find that pericentric inversions occur at a much lower rate compared to paracentric inversions. The average paracentric inversion tract length is approx. 4.8 Mb with small inversions being more frequent than large inversions. If the two breakpoints defining a paracentric inversion tract are uniformly and independently distributed over chromosome arms there will be more short tract-length inversions than long; we find an even greater preponderance of short tract lengths than this would predict. Thus there appears to be a correlation between the positions of breakpoints which favors shorter tract lengths. The method developed in this paper provides the first statistical estimator for estimating the distribution of inversion tract lengths from marker data. Application of this method for a number of data sets may help elucidate the relationship between the length of an inversion and the chance that it will get accepted.

Dependence of paracentric inversion rate on tract length

PubMed Central

York, Thomas L; Durrett, Rick; Nielsen, Rasmus

2007-01-01

Background We develop a Bayesian method based on MCMC for estimating the relative rates of pericentric and paracentric inversions from marker data from two species. The method also allows estimation of the distribution of inversion tract lengths. Results We apply the method to data from Drosophila melanogaster and D. yakuba. We find that pericentric inversions occur at a much lower rate compared to paracentric inversions. The average paracentric inversion tract length is approx. 4.8 Mb with small inversions being more frequent than large inversions. If the two breakpoints defining a paracentric inversion tract are uniformly and independently distributed over chromosome arms there will be more short tract-length inversions than long; we find an even greater preponderance of short tract lengths than this would predict. Thus there appears to be a correlation between the positions of breakpoints which favors shorter tract lengths. Conclusion The method developed in this paper provides the first statistical estimator for estimating the distribution of inversion tract lengths from marker data. Application of this method for a number of data sets may help elucidate the relationship between the length of an inversion and the chance that it will get accepted. PMID:17407601

Error analysis applied to several inversion techniques used for the retrieval of middle atmospheric constituents from limb-scanning MM-wave spectroscopic measurements

NASA Technical Reports Server (NTRS)

Puliafito, E.; Bevilacqua, R.; Olivero, J.; Degenhardt, W.

1992-01-01

The formal retrieval error analysis of Rodgers (1990) allows the quantitative determination of such retrieval properties as measurement error sensitivity, resolution, and inversion bias. This technique was applied to five numerical inversion techniques and two nonlinear iterative techniques used for the retrieval of middle atmospheric constituent concentrations from limb-scanning millimeter-wave spectroscopic measurements. It is found that the iterative methods have better vertical resolution, but are slightly more sensitive to measurement error than constrained matrix methods. The iterative methods converge to the exact solution, whereas two of the matrix methods under consideration have an explicit constraint, the sensitivity of the solution to the a priori profile. Tradeoffs of these retrieval characteristics are presented.

GENERATING FRACTAL PATTERNS BY USING p-CIRCLE INVERSION

NASA Astrophysics Data System (ADS)

Ramírez, José L.; Rubiano, Gustavo N.; Zlobec, Borut Jurčič

2015-10-01

In this paper, we introduce the p-circle inversion which generalizes the classical inversion with respect to a circle (p = 2) and the taxicab inversion (p = 1). We study some basic properties and we also show the inversive images of some basic curves. We apply this new transformation to well-known fractals such as Sierpinski triangle, Koch curve, dragon curve, Fibonacci fractal, among others. Then we obtain new fractal patterns. Moreover, we generalize the method called circle inversion fractal be means of the p-circle inversion.

Simultaneous inversion of seismic velocity and moment tensor using elastic-waveform inversion of microseismic data: Application to the Aneth CO2-EOR field

NASA Astrophysics Data System (ADS)

Chen, Y.; Huang, L.

2017-12-01

Moment tensors are key parameters for characterizing CO2-injection-induced microseismic events. Elastic-waveform inversion has the potential to providing accurate results of moment tensors. Microseismic waveforms contains information of source moment tensors and the wave propagation velocity along the wavepaths. We develop an elastic-waveform inversion method to jointly invert the seismic velocity model and moment tensor. We first use our adaptive moment-tensor joint inversion method to estimate moment tensors of microseismic events. Our adaptive moment-tensor inversion method jointly inverts multiple microseismic events with similar waveforms within a cluster to reduce inversion uncertainty for microseismic data recorded using a single borehole geophone array. We use this inversion result as the initial model for our elastic-waveform inversion to minimize the cross-correlated-based data misfit between observed data and synthetic data. We verify our method using synthetic microseismic data and obtain improved results of both moment tensors and seismic velocity model. We apply our new inversion method to microseismic data acquired at a CO2-enhanced oil recovery field in Aneth, Utah, using a single borehole geophone array. The results demonstrate that our new inversion method significantly reduces the data misfit compared to the conventional ray-theory-based moment-tensor inversion.

Viscoelastic material inversion using Sierra-SD and ROL

DOE Office of Scientific and Technical Information (OSTI.GOV)

Walsh, Timothy; Aquino, Wilkins; Ridzal, Denis

2014-11-01

In this report we derive frequency-domain methods for inverse characterization of the constitutive parameters of viscoelastic materials. The inverse problem is cast in a PDE-constrained optimization framework with efficient computation of gradients and Hessian vector products through matrix free operations. The abstract optimization operators for first and second derivatives are derived from first principles. Various methods from the Rapid Optimization Library (ROL) are tested on the viscoelastic inversion problem. The methods described herein are applied to compute the viscoelastic bulk and shear moduli of a foam block model, which was recently used in experimental testing for viscoelastic property characterization.

A direct-inverse method for transonic and separated flows about airfoils

NASA Technical Reports Server (NTRS)

Carlson, K. D.

1985-01-01

A direct-inverse technique and computer program called TAMSEP that can be sued for the analysis of the flow about airfoils at subsonic and low transonic freestream velocities is presented. The method is based upon a direct-inverse nonconservative full potential inviscid method, a Thwaites laminar boundary layer technique, and the Barnwell turbulent momentum integral scheme; and it is formulated using Cartesian coordinates. Since the method utilizes inverse boundary conditions in regions of separated flow, it is suitable for predicing the flowfield about airfoils having trailing edge separated flow under high lift conditions. Comparisons with experimental data indicate that the method should be a useful tool for applied aerodynamic analyses.

A direct-inverse method for transonic and separated flows about airfoils

NASA Technical Reports Server (NTRS)

Carlson, Leland A.

1990-01-01

A direct-inverse technique and computer program called TAMSEP that can be used for the analysis of the flow about airfoils at subsonic and low transonic freestream velocities is presented. The method is based upon a direct-inverse nonconservative full potential inviscid method, a Thwaites laminar boundary layer technique, and the Barnwell turbulent momentum integral scheme; and it is formulated using Cartesian coordinates. Since the method utilizes inverse boundary conditions in regions of separated flow, it is suitable for predicting the flow field about airfoils having trailing edge separated flow under high lift conditions. Comparisons with experimental data indicate that the method should be a useful tool for applied aerodynamic analyses.

EIT image reconstruction based on a hybrid FE-EFG forward method and the complete-electrode model.

PubMed

Hadinia, M; Jafari, R; Soleimani, M

2016-06-01

This paper presents the application of the hybrid finite element-element free Galerkin (FE-EFG) method for the forward and inverse problems of electrical impedance tomography (EIT). The proposed method is based on the complete electrode model. Finite element (FE) and element-free Galerkin (EFG) methods are accurate numerical techniques. However, the FE technique has meshing task problems and the EFG method is computationally expensive. In this paper, the hybrid FE-EFG method is applied to take both advantages of FE and EFG methods, the complete electrode model of the forward problem is solved, and an iterative regularized Gauss-Newton method is adopted to solve the inverse problem. The proposed method is applied to compute Jacobian in the inverse problem. Utilizing 2D circular homogenous models, the numerical results are validated with analytical and experimental results and the performance of the hybrid FE-EFG method compared with the FE method is illustrated. Results of image reconstruction are presented for a human chest experimental phantom.

Large Airborne Full Tensor Gradient Data Inversion Based on a Non-Monotone Gradient Method

NASA Astrophysics Data System (ADS)

Sun, Yong; Meng, Zhaohai; Li, Fengting

2018-03-01

Following the development of gravity gradiometer instrument technology, the full tensor gravity (FTG) data can be acquired on airborne and marine platforms. Large-scale geophysical data can be obtained using these methods, making such data sets a number of the "big data" category. Therefore, a fast and effective inversion method is developed to solve the large-scale FTG data inversion problem. Many algorithms are available to accelerate the FTG data inversion, such as conjugate gradient method. However, the conventional conjugate gradient method takes a long time to complete data processing. Thus, a fast and effective iterative algorithm is necessary to improve the utilization of FTG data. Generally, inversion processing is formulated by incorporating regularizing constraints, followed by the introduction of a non-monotone gradient-descent method to accelerate the convergence rate of FTG data inversion. Compared with the conventional gradient method, the steepest descent gradient algorithm, and the conjugate gradient algorithm, there are clear advantages of the non-monotone iterative gradient-descent algorithm. Simulated and field FTG data were applied to show the application value of this new fast inversion method.

Micro-seismic waveform matching inversion based on gravitational search algorithm and parallel computation

NASA Astrophysics Data System (ADS)

Jiang, Y.; Xing, H. L.

2016-12-01

Micro-seismic events induced by water injection, mining activity or oil/gas extraction are quite informative, the interpretation of which can be applied for the reconstruction of underground stress and monitoring of hydraulic fracturing progress in oil/gas reservoirs. The source characterises and locations are crucial parameters that required for these purposes, which can be obtained through the waveform matching inversion (WMI) method. Therefore it is imperative to develop a WMI algorithm with high accuracy and convergence speed. Heuristic algorithm, as a category of nonlinear method, possesses a very high convergence speed and good capacity to overcome local minimal values, and has been well applied for many areas (e.g. image processing, artificial intelligence). However, its effectiveness for micro-seismic WMI is still poorly investigated; very few literatures exits that addressing this subject. In this research an advanced heuristic algorithm, gravitational search algorithm (GSA) , is proposed to estimate the focal mechanism (angle of strike, dip and rake) and source locations in three dimension. Unlike traditional inversion methods, the heuristic algorithm inversion does not require the approximation of green function. The method directly interacts with a CPU parallelized finite difference forward modelling engine, and updating the model parameters under GSA criterions. The effectiveness of this method is tested with synthetic data form a multi-layered elastic model; the results indicate GSA can be well applied on WMI and has its unique advantages. Keywords: Micro-seismicity, Waveform matching inversion, gravitational search algorithm, parallel computation

Mini-batch optimized full waveform inversion with geological constrained gradient filtering

NASA Astrophysics Data System (ADS)

Yang, Hui; Jia, Junxiong; Wu, Bangyu; Gao, Jinghuai

2018-05-01

High computation cost and generating solutions without geological sense have hindered the wide application of Full Waveform Inversion (FWI). Source encoding technique is a way to dramatically reduce the cost of FWI but subject to fix-spread acquisition setup requirement and slow convergence for the suppression of cross-talk. Traditionally, gradient regularization or preconditioning is applied to mitigate the ill-posedness. An isotropic smoothing filter applied on gradients generally gives non-geological inversion results, and could also introduce artifacts. In this work, we propose to address both the efficiency and ill-posedness of FWI by a geological constrained mini-batch gradient optimization method. The mini-batch gradient descent optimization is adopted to reduce the computation time by choosing a subset of entire shots for each iteration. By jointly applying the structure-oriented smoothing to the mini-batch gradient, the inversion converges faster and gives results with more geological meaning. Stylized Marmousi model is used to show the performance of the proposed method on realistic synthetic model.

Approximated Stable Inversion for Nonlinear Systems with Nonhyperbolic Internal Dynamics. Revised

NASA Technical Reports Server (NTRS)

Devasia, Santosh

1999-01-01

A technique to achieve output tracking for nonminimum phase nonlinear systems with non- hyperbolic internal dynamics is presented. The present paper integrates stable inversion techniques (that achieve exact-tracking) with approximation techniques (that modify the internal dynamics) to circumvent the nonhyperbolicity of the internal dynamics - this nonhyperbolicity is an obstruction to applying presently available stable inversion techniques. The theory is developed for nonlinear systems and the method is applied to a two-cart with inverted-pendulum example.

Bayesian Inference in Satellite Gravity Inversion

NASA Technical Reports Server (NTRS)

Kis, K. I.; Taylor, Patrick T.; Wittmann, G.; Kim, Hyung Rae; Torony, B.; Mayer-Guerr, T.

2005-01-01

To solve a geophysical inverse problem means applying measurements to determine the parameters of the selected model. The inverse problem is formulated as the Bayesian inference. The Gaussian probability density functions are applied in the Bayes's equation. The CHAMP satellite gravity data are determined at the altitude of 400 kilometer altitude over the South part of the Pannonian basin. The model of interpretation is the right vertical cylinder. The parameters of the model are obtained from the minimum problem solved by the Simplex method.

Electromagnetic Inverse Methods and Applications for Inhomogeneous Media Probing and Synthesis.

NASA Astrophysics Data System (ADS)

Xia, Jake Jiqing

The electromagnetic inverse scattering problems concerned in this thesis are to find unknown inhomogeneous permittivity and conductivity profiles in a medium from the scattering data. Both analytical and numerical methods are studied in the thesis. The inverse methods can be applied to geophysical medium probing, non-destructive testing, medical imaging, optical waveguide synthesis and material characterization. An introduction is given in Chapter 1. The first part of the thesis presents inhomogeneous media probing. The Riccati equation approach is discussed in Chapter 2 for a one-dimensional planar profile inversion problem. Two types of the Riccati equations are derived and distinguished. New renormalized formulae based inverting one specific type of the Riccati equation are derived. Relations between the inverse methods of Green's function, the Riccati equation and the Gel'fand-Levitan-Marchenko (GLM) theory are studied. In Chapter 3, the renormalized source-type integral equation (STIE) approach is formulated for inversion of cylindrically inhomogeneous permittivity and conductivity profiles. The advantages of the renormalized STIE approach are demonstrated in numerical examples. The cylindrical profile inversion problem has an application for borehole inversion. In Chapter 4 the renormalized STIE approach is extended to a planar case where the two background media are different. Numerical results have shown fast convergence. This formulation is applied to inversion of the underground soil moisture profiles in remote sensing. The second part of the thesis presents the synthesis problem of inhomogeneous dielectric waveguides using the electromagnetic inverse methods. As a particular example, the rational function representation of reflection coefficients in the GLM theory is used. The GLM method is reviewed in Chapter 5. Relations between modal structures and transverse reflection coefficients of an inhomogeneous medium are established in Chapter 6. A stratified medium model is used to derive the guidance condition and the reflection coefficient. Results obtained in Chapter 6 provide the physical foundation for applying the inverse methods for the waveguide design problem. In Chapter 7, a global guidance condition for continuously varying medium is derived using the Riccati equation. It is further shown that the discrete modes in an inhomogeneous medium have the same wave vectors as the poles of the transverse reflection coefficient. An example of synthesizing an inhomogeneous dielectric waveguide using a rational reflection coefficient is presented. A summary of the thesis is given in Chapter 8. (Copies available exclusively from MIT Libraries, Rm. 14-0551, Cambridge, MA 02139-4307. Ph. 617-253-5668; Fax 617-253-1690.).

Domain identification in impedance computed tomography by spline collocation method

NASA Technical Reports Server (NTRS)

Kojima, Fumio

1990-01-01

A method for estimating an unknown domain in elliptic boundary value problems is considered. The problem is formulated as an inverse problem of integral equations of the second kind. A computational method is developed using a splice collocation scheme. The results can be applied to the inverse problem of impedance computed tomography (ICT) for image reconstruction.

Determination of adsorption isotherms of chlorinated hydrocarbons on halloysite adsorbent by inverse gas chromatography.

PubMed

Czech, K; Słomkiewicz, P M

2013-05-03

Inverse gas chromatographic methods of isotherm determination peak maximum (PM) and peak division (PD) were compared. These methods were applied to determine adsorption isotherms of dichloroethylene, trichloroethylene and tetrachloroethylene on acid-activated halloysite and adsorption enthalpy. Copyright © 2013 Elsevier B.V. All rights reserved.

A simple approach to the joint inversion of seismic body and surface waves applied to the southwest U.S.

NASA Astrophysics Data System (ADS)

West, Michael; Gao, Wei; Grand, Stephen

2004-08-01

Body and surface wave tomography have complementary strengths when applied to regional-scale studies of the upper mantle. We present a straight-forward technique for their joint inversion which hinges on treating surface waves as horizontally-propagating rays with deep sensitivity kernels. This formulation allows surface wave phase or group measurements to be integrated directly into existing body wave tomography inversions with modest effort. We apply the joint inversion to a synthetic case and to data from the RISTRA project in the southwest U.S. The data variance reductions demonstrate that the joint inversion produces a better fit to the combined dataset, not merely a compromise. For large arrays, this method offers an improvement over augmenting body wave tomography with a one-dimensional model. The joint inversion combines the absolute velocity of a surface wave model with the high resolution afforded by body waves-both qualities that are required to understand regional-scale mantle phenomena.

Waveform inversion with source encoding for breast sound speed reconstruction in ultrasound computed tomography.

PubMed

Wang, Kun; Matthews, Thomas; Anis, Fatima; Li, Cuiping; Duric, Neb; Anastasio, Mark A

2015-03-01

Ultrasound computed tomography (USCT) holds great promise for improving the detection and management of breast cancer. Because they are based on the acoustic wave equation, waveform inversion-based reconstruction methods can produce images that possess improved spatial resolution properties over those produced by ray-based methods. However, waveform inversion methods are computationally demanding and have not been applied widely in USCT breast imaging. In this work, source encoding concepts are employed to develop an accelerated USCT reconstruction method that circumvents the large computational burden of conventional waveform inversion methods. This method, referred to as the waveform inversion with source encoding (WISE) method, encodes the measurement data using a random encoding vector and determines an estimate of the sound speed distribution by solving a stochastic optimization problem by use of a stochastic gradient descent algorithm. Both computer simulation and experimental phantom studies are conducted to demonstrate the use of the WISE method. The results suggest that the WISE method maintains the high spatial resolution of waveform inversion methods while significantly reducing the computational burden.

On the inversion of geodetic integrals defined over the sphere using 1-D FFT

NASA Astrophysics Data System (ADS)

García, R. V.; Alejo, C. A.

2005-08-01

An iterative method is presented which performs inversion of integrals defined over the sphere. The method is based on one-dimensional fast Fourier transform (1-D FFT) inversion and is implemented with the projected Landweber technique, which is used to solve constrained least-squares problems reducing the associated 1-D cyclic-convolution error. The results obtained are as precise as the direct matrix inversion approach, but with better computational efficiency. A case study uses the inversion of Hotine’s integral to obtain gravity disturbances from geoid undulations. Numerical convergence is also analyzed and comparisons with respect to the direct matrix inversion method using conjugate gradient (CG) iteration are presented. Like the CG method, the number of iterations needed to get the optimum (i.e., small) error decreases as the measurement noise increases. Nevertheless, for discrete data given over a whole parallel band, the method can be applied directly without implementing the projected Landweber method, since no cyclic convolution error exists.

Geoelectric Characterization of Thermal Water Aquifers Using 2.5D Inversion of VES Measurements

NASA Astrophysics Data System (ADS)

Gyulai, Á.; Szűcs, P.; Turai, E.; Baracza, M. K.; Fejes, Z.

2017-03-01

This paper presents a short theoretical summary of the series expansion-based 2.5D combined geoelectric weighted inversion (CGWI) method and highlights the advantageous way with which the number of unknowns can be decreased due to the simultaneous characteristic of this inversion. 2.5D CGWI is an approximate inversion method for the determination of 3D structures, which uses the joint 2D forward modeling of dip and strike direction data. In the inversion procedure, the Steiner's most frequent value method is applied to the automatic separation of dip and strike direction data and outliers. The workflow of inversion and its practical application are presented in the study. For conventional vertical electrical sounding (VES) measurements, this method can determine the parameters of complex structures more accurately than the single inversion method. Field data show that the 2.5D CGWI which was developed can determine the optimal location for drilling an exploratory thermal water prospecting well. The novelty of this research is that the measured VES data in dip and strike direction are jointly inverted by the 2.5D CGWI method.

3D first-arrival traveltime tomography with modified total variation regularization

NASA Astrophysics Data System (ADS)

Jiang, Wenbin; Zhang, Jie

2018-02-01

Three-dimensional (3D) seismic surveys have become a major tool in the exploration and exploitation of hydrocarbons. 3D seismic first-arrival traveltime tomography is a robust method for near-surface velocity estimation. A common approach for stabilizing the ill-posed inverse problem is to apply Tikhonov regularization to the inversion. However, the Tikhonov regularization method recovers smooth local structures while blurring the sharp features in the model solution. We present a 3D first-arrival traveltime tomography method with modified total variation (MTV) regularization to preserve sharp velocity contrasts and improve the accuracy of velocity inversion. To solve the minimization problem of the new traveltime tomography method, we decouple the original optimization problem into two following subproblems: a standard traveltime tomography problem with the traditional Tikhonov regularization and a L2 total variation problem. We apply the conjugate gradient method and split-Bregman iterative method to solve these two subproblems, respectively. Our synthetic examples show that the new method produces higher resolution models than the conventional traveltime tomography with Tikhonov regularization. We apply the technique to field data. The stacking section shows significant improvements with static corrections from the MTV traveltime tomography.

Nonlinear adaptive inverse control via the unified model neural network

NASA Astrophysics Data System (ADS)

Jeng, Jin-Tsong; Lee, Tsu-Tian

1999-03-01

In this paper, we propose a new nonlinear adaptive inverse control via a unified model neural network. In order to overcome nonsystematic design and long training time in nonlinear adaptive inverse control, we propose the approximate transformable technique to obtain a Chebyshev Polynomials Based Unified Model (CPBUM) neural network for the feedforward/recurrent neural networks. It turns out that the proposed method can use less training time to get an inverse model. Finally, we apply this proposed method to control magnetic bearing system. The experimental results show that the proposed nonlinear adaptive inverse control architecture provides a greater flexibility and better performance in controlling magnetic bearing systems.

Application of Carbonate Reservoir using waveform inversion and reverse-time migration methods

NASA Astrophysics Data System (ADS)

Kim, W.; Kim, H.; Min, D.; Keehm, Y.

2011-12-01

Recent exploration targets of oil and gas resources are deeper and more complicated subsurface structures, and carbonate reservoirs have become one of the attractive and challenging targets in seismic exploration. To increase the rate of success in oil and gas exploration, it is required to delineate detailed subsurface structures. Accordingly, migration method is more important factor in seismic data processing for the delineation. Seismic migration method has a long history, and there have been developed lots of migration techniques. Among them, reverse-time migration is promising, because it can provide reliable images for the complicated model even in the case of significant velocity contrasts in the model. The reliability of seismic migration images is dependent on the subsurface velocity models, which can be extracted in several ways. These days, geophysicists try to obtain velocity models through seismic full waveform inversion. Since Lailly (1983) and Tarantola (1984) proposed that the adjoint state of wave equations can be used in waveform inversion, the back-propagation techniques used in reverse-time migration have been used in waveform inversion, which accelerated the development of waveform inversion. In this study, we applied acoustic waveform inversion and reverse-time migration methods to carbonate reservoir models with various reservoir thicknesses to examine the feasibility of the methods in delineating carbonate reservoir models. We first extracted subsurface material properties from acoustic waveform inversion, and then applied reverse-time migration using the inverted velocities as a background model. The waveform inversion in this study used back-propagation technique, and conjugate gradient method was used in optimization. The inversion was performed using the frequency-selection strategy. Finally waveform inversion results showed that carbonate reservoir models are clearly inverted by waveform inversion and migration images based on the inversion results are quite reliable. Different thicknesses of reservoir models were also described and the results revealed that the lower boundary of the reservoir was not delineated because of energy loss. From these results, it was noted that carbonate reservoirs can be properly imaged and interpreted by waveform inversion and reverse-time migration methods. This work was supported by the Energy Resources R&D program of the Korea Institute of Energy Technology Evaluation and Planning (KETEP) grant funded by the Korea government Ministry of Knowledge Economy (No. 2009201030001A, No. 2010T100200133) and the Brain Korea 21 project of Energy System Engineering.

A three-step Maximum-A-Posterior probability method for InSAR data inversion of coseismic rupture with application to four recent large earthquakes in Asia

NASA Astrophysics Data System (ADS)

Sun, J.; Shen, Z.; Burgmann, R.; Liang, F.

2012-12-01

We develop a three-step Maximum-A-Posterior probability (MAP) method for coseismic rupture inversion, which aims at maximizing the a posterior probability density function (PDF) of elastic solutions of earthquake rupture. The method originates from the Fully Bayesian Inversion (FBI) and the Mixed linear-nonlinear Bayesian inversion (MBI) methods , shares the same a posterior PDF with them and keeps most of their merits, while overcoming its convergence difficulty when large numbers of low quality data are used and improving the convergence rate greatly using optimization procedures. A highly efficient global optimization algorithm, Adaptive Simulated Annealing (ASA), is used to search for the maximum posterior probability in the first step. The non-slip parameters are determined by the global optimization method, and the slip parameters are inverted for using the least squares method without positivity constraint initially, and then damped to physically reasonable range. This step MAP inversion brings the inversion close to 'true' solution quickly and jumps over local maximum regions in high-dimensional parameter space. The second step inversion approaches the 'true' solution further with positivity constraints subsequently applied on slip parameters using the Monte Carlo Inversion (MCI) technique, with all parameters obtained from step one as the initial solution. Then the slip artifacts are eliminated from slip models in the third step MAP inversion with fault geometry parameters fixed. We first used a designed model with 45 degree dipping angle and oblique slip, and corresponding synthetic InSAR data sets to validate the efficiency and accuracy of method. We then applied the method on four recent large earthquakes in Asia, namely the 2010 Yushu, China earthquake, the 2011 Burma earthquake, the 2011 New Zealand earthquake and the 2008 Qinghai, China earthquake, and compared our results with those results from other groups. Our results show the effectiveness of the method in earthquake studies and a number of advantages of it over other methods. The details will be reported on the meeting.

Estimating surface acoustic impedance with the inverse method.

PubMed

Piechowicz, Janusz

2011-01-01

Sound field parameters are predicted with numerical methods in sound control systems, in acoustic designs of building and in sound field simulations. Those methods define the acoustic properties of surfaces, such as sound absorption coefficients or acoustic impedance, to determine boundary conditions. Several in situ measurement techniques were developed; one of them uses 2 microphones to measure direct and reflected sound over a planar test surface. Another approach is used in the inverse boundary elements method, in which estimating acoustic impedance of a surface is expressed as an inverse boundary problem. The boundary values can be found from multipoint sound pressure measurements in the interior of a room. This method can be applied to arbitrarily-shaped surfaces. This investigation is part of a research programme on using inverse methods in industrial room acoustics.

Pseudo 2D elastic waveform inversion for attenuation in the near surface

NASA Astrophysics Data System (ADS)

Wang, Yue; Zhang, Jie

2017-08-01

Seismic waveform propagation could be significantly affected by heterogeneities in the near surface zone (0 m-500 m depth). As a result, it is important to obtain as much near surface information as possible. Seismic attenuation, characterized by QP and QS factors, may affect seismic waveform in both phase and amplitude; however, it is rarely estimated and applied to the near surface zone for seismic data processing. Applying a 1D elastic full waveform modelling program, we demonstrate that such effects cannot be overlooked in the waveform computation if the value of the Q factor is lower than approximately 100. Further, we develop a pseudo 2D elastic waveform inversion method in the common midpoint (CMP) domain that jointly inverts early arrivals for QP and surface waves for QS. In this method, although the forward problem is in 1D, by applying 2D model regularization, we obtain 2D QP and QS models through simultaneous inversion. A cross-gradient constraint between the QP and Qs models is applied to ensure structural consistency of the 2D inversion results. We present synthetic examples and a real case study from an oil field in China.

Superresolution radar imaging based on fast inverse-free sparse Bayesian learning for multiple measurement vectors

NASA Astrophysics Data System (ADS)

He, Xingyu; Tong, Ningning; Hu, Xiaowei

2018-01-01

Compressive sensing has been successfully applied to inverse synthetic aperture radar (ISAR) imaging of moving targets. By exploiting the block sparse structure of the target image, sparse solution for multiple measurement vectors (MMV) can be applied in ISAR imaging and a substantial performance improvement can be achieved. As an effective sparse recovery method, sparse Bayesian learning (SBL) for MMV involves a matrix inverse at each iteration. Its associated computational complexity grows significantly with the problem size. To address this problem, we develop a fast inverse-free (IF) SBL method for MMV. A relaxed evidence lower bound (ELBO), which is computationally more amiable than the traditional ELBO used by SBL, is obtained by invoking fundamental property for smooth functions. A variational expectation-maximization scheme is then employed to maximize the relaxed ELBO, and a computationally efficient IF-MSBL algorithm is proposed. Numerical results based on simulated and real data show that the proposed method can reconstruct row sparse signal accurately and obtain clear superresolution ISAR images. Moreover, the running time and computational complexity are reduced to a great extent compared with traditional SBL methods.

Nonlinear inversion of borehole-radar tomography data to reconstruct velocity and attenuation distribution in earth materials

USGS Publications Warehouse

Zhou, C.; Liu, L.; Lane, J.W.

2001-01-01

A nonlinear tomographic inversion method that uses first-arrival travel-time and amplitude-spectra information from cross-hole radar measurements was developed to simultaneously reconstruct electromagnetic velocity and attenuation distribution in earth materials. Inversion methods were developed to analyze single cross-hole tomography surveys and differential tomography surveys. Assuming the earth behaves as a linear system, the inversion methods do not require estimation of source radiation pattern, receiver coupling, or geometrical spreading. The data analysis and tomographic inversion algorithm were applied to synthetic test data and to cross-hole radar field data provided by the US Geological Survey (USGS). The cross-hole radar field data were acquired at the USGS fractured-rock field research site at Mirror Lake near Thornton, New Hampshire, before and after injection of a saline tracer, to monitor the transport of electrically conductive fluids in the image plane. Results from the synthetic data test demonstrate the algorithm computational efficiency and indicate that the method robustly can reconstruct electromagnetic (EM) wave velocity and attenuation distribution in earth materials. The field test results outline zones of velocity and attenuation anomalies consistent with the finding of previous investigators; however, the tomograms appear to be quite smooth. Further work is needed to effectively find the optimal smoothness criterion in applying the Tikhonov regularization in the nonlinear inversion algorithms for cross-hole radar tomography. ?? 2001 Elsevier Science B.V. All rights reserved.

Inverse kinematics of a dual linear actuator pitch/roll heliostat

NASA Astrophysics Data System (ADS)

Freeman, Joshua; Shankar, Balakrishnan; Sundaram, Ganesh

2017-06-01

This work presents a simple, computationally efficient inverse kinematics solution for a pitch/roll heliostat using two linear actuators. The heliostat design and kinematics have been developed, modeled and tested using computer simulation software. A physical heliostat prototype was fabricated to validate the theoretical computations and data. Pitch/roll heliostats have numerous advantages including reduced cost potential and reduced space requirements, with a primary disadvantage being the significantly more complicated kinematics, which are solved here. Novel methods are applied to simplify the inverse kinematics problem which could be applied to other similar problems.

A direct method for nonlinear ill-posed problems

NASA Astrophysics Data System (ADS)

Lakhal, A.

2018-02-01

We propose a direct method for solving nonlinear ill-posed problems in Banach-spaces. The method is based on a stable inversion formula we explicitly compute by applying techniques for analytic functions. Furthermore, we investigate the convergence and stability of the method and prove that the derived noniterative algorithm is a regularization. The inversion formula provides a systematic sensitivity analysis. The approach is applicable to a wide range of nonlinear ill-posed problems. We test the algorithm on a nonlinear problem of travel-time inversion in seismic tomography. Numerical results illustrate the robustness and efficiency of the algorithm.

Genome-wide association tests of inversions with application to psoriasis

PubMed Central

Ma, Jianzhong; Xiong, Momiao; You, Ming; Lozano, Guillermina; Amos, Christopher I.

2014-01-01

Although inversions have occasionally been found to be associated with disease susceptibility through interrupting a gene or its regulatory region, or by increasing the risk for deleterious secondary rearrangements, no association study has been specifically conducted for risks associated with inversions, mainly because existing approaches to detecting and genotyping inversions do not readily scale to a large number of samples. Based on our recently proposed approach to identifying and genotyping inversions using principal components analysis (PCA), we herein develop a method of detecting association between inversions and disease in a genome-wide fashion. Our method uses genotype data for single nucleotide polymorphisms (SNPs), and is thus cost-efficient and computationally fast. For an inversion polymorphism, local PCA around the inversion region is performed to infer the inversion genotypes of all samples. For many inversions, we found that some of the SNPs inside an inversion region are fixed in the two lineages of different orientations and thus can serve as surrogate markers. Our method can be applied to case-control and quantitative trait association studies to identify inversions that may interrupt a gene or the connection between a gene and its regulatory agents. Our method also offers a new venue to identify inversions that are responsible for disease-causing secondary rearrangements. We illustrated our proposed approach to case-control data for psoriasis and identified novel associations with a few inversion polymorphisms. PMID:24623382

A full potential inverse method based on a density linearization scheme for wing design

NASA Technical Reports Server (NTRS)

Shankar, V.

1982-01-01

A mixed analysis inverse procedure based on the full potential equation in conservation form was developed to recontour a given base wing to produce density linearization scheme in applying the pressure boundary condition in terms of the velocity potential. The FL030 finite volume analysis code was modified to include the inverse option. The new surface shape information, associated with the modified pressure boundary condition, is calculated at a constant span station based on a mass flux integration. The inverse method is shown to recover the original shape when the analysis pressure is not altered. Inverse calculations for weakening of a strong shock system and for a laminar flow control (LFC) pressure distribution are presented. Two methods for a trailing edge closure model are proposed for further study.

Breast ultrasound computed tomography using waveform inversion with source encoding

NASA Astrophysics Data System (ADS)

Wang, Kun; Matthews, Thomas; Anis, Fatima; Li, Cuiping; Duric, Neb; Anastasio, Mark A.

2015-03-01

Ultrasound computed tomography (USCT) holds great promise for improving the detection and management of breast cancer. Because they are based on the acoustic wave equation, waveform inversion-based reconstruction methods can produce images that possess improved spatial resolution properties over those produced by ray-based methods. However, waveform inversion methods are computationally demanding and have not been applied widely in USCT breast imaging. In this work, source encoding concepts are employed to develop an accelerated USCT reconstruction method that circumvents the large computational burden of conventional waveform inversion methods. This method, referred to as the waveform inversion with source encoding (WISE) method, encodes the measurement data using a random encoding vector and determines an estimate of the speed-of-sound distribution by solving a stochastic optimization problem by use of a stochastic gradient descent algorithm. Computer-simulation studies are conducted to demonstrate the use of the WISE method. Using a single graphics processing unit card, each iteration can be completed within 25 seconds for a 128 × 128 mm2 reconstruction region. The results suggest that the WISE method maintains the high spatial resolution of waveform inversion methods while significantly reducing the computational burden.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Chen, Yu; Gao, Kai; Huang, Lianjie

Accurate imaging and characterization of fracture zones is crucial for geothermal energy exploration. Aligned fractures within fracture zones behave as anisotropic media for seismic-wave propagation. The anisotropic properties in fracture zones introduce extra difficulties for seismic imaging and waveform inversion. We have recently developed a new anisotropic elastic-waveform inversion method using a modified total-variation regularization scheme and a wave-energy-base preconditioning technique. Our new inversion method uses the parameterization of elasticity constants to describe anisotropic media, and hence it can properly handle arbitrary anisotropy. We apply our new inversion method to a seismic velocity model along a 2D-line seismic data acquiredmore » at Eleven-Mile Canyon located at the Southern Dixie Valley in Nevada for geothermal energy exploration. Our inversion results show that anisotropic elastic-waveform inversion has potential to reconstruct subsurface anisotropic elastic parameters for imaging and characterization of fracture zones.« less

Towards "Inverse" Character Tables? A One-Step Method for Decomposing Reducible Representations

ERIC Educational Resources Information Center

Piquemal, J.-Y.; Losno, R.; Ancian, B.

2009-01-01

In the framework of group theory, a new procedure is described for a one-step automated reduction of reducible representations. The matrix inversion tool, provided by standard spreadsheet software, is applied to the central part of the character table that contains the characters of the irreducible representation. This method is not restricted to…

Fast inversion of gravity data using the symmetric successive over-relaxation (SSOR) preconditioned conjugate gradient algorithm

NASA Astrophysics Data System (ADS)

Meng, Zhaohai; Li, Fengting; Xu, Xuechun; Huang, Danian; Zhang, Dailei

2017-02-01

The subsurface three-dimensional (3D) model of density distribution is obtained by solving an under-determined linear equation that is established by gravity data. Here, we describe a new fast gravity inversion method to recover a 3D density model from gravity data. The subsurface will be divided into a large number of rectangular blocks, each with an unknown constant density. The gravity inversion method introduces a stabiliser model norm with a depth weighting function to produce smooth models. The depth weighting function is combined with the model norm to counteract the skin effect of the gravity potential field. As the numbers of density model parameters is NZ (the number of layers in the vertical subsurface domain) times greater than the observed gravity data parameters, the inverse density parameter is larger than the observed gravity data parameters. Solving the full set of gravity inversion equations is very time-consuming, and applying a new algorithm to estimate gravity inversion can significantly reduce the number of iterations and the computational time. In this paper, a new symmetric successive over-relaxation (SSOR) iterative conjugate gradient (CG) method is shown to be an appropriate algorithm to solve this Tikhonov cost function (gravity inversion equation). The new, faster method is applied on Gaussian noise-contaminated synthetic data to demonstrate its suitability for 3D gravity inversion. To demonstrate the performance of the new algorithm on actual gravity data, we provide a case study that includes ground-based measurement of residual Bouguer gravity anomalies over the Humble salt dome near Houston, Gulf Coast Basin, off the shore of Louisiana. A 3D distribution of salt rock concentration is used to evaluate the inversion results recovered by the new SSOR iterative method. In the test model, the density values in the constructed model coincide with the known location and depth of the salt dome.

Multiple Frequency Contrast Source Inversion Method for Vertical Electromagnetic Profiling: 2D Simulation Results and Analyses

NASA Astrophysics Data System (ADS)

Li, Jinghe; Song, Linping; Liu, Qing Huo

2016-02-01

A simultaneous multiple frequency contrast source inversion (CSI) method is applied to reconstructing hydrocarbon reservoir targets in a complex multilayered medium in two dimensions. It simulates the effects of a salt dome sedimentary formation in the context of reservoir monitoring. In this method, the stabilized biconjugate-gradient fast Fourier transform (BCGS-FFT) algorithm is applied as a fast solver for the 2D volume integral equation for the forward computation. The inversion technique with CSI combines the efficient FFT algorithm to speed up the matrix-vector multiplication and the stable convergence of the simultaneous multiple frequency CSI in the iteration process. As a result, this method is capable of making quantitative conductivity image reconstruction effectively for large-scale electromagnetic oil exploration problems, including the vertical electromagnetic profiling (VEP) survey investigated here. A number of numerical examples have been demonstrated to validate the effectiveness and capacity of the simultaneous multiple frequency CSI method for a limited array view in VEP.

Three-dimensional inversion of multisource array electromagnetic data

NASA Astrophysics Data System (ADS)

Tartaras, Efthimios

Three-dimensional (3-D) inversion is increasingly important for the correct interpretation of geophysical data sets in complex environments. To this effect, several approximate solutions have been developed that allow the construction of relatively fast inversion schemes. One such method that is fast and provides satisfactory accuracy is the quasi-linear (QL) approximation. It has, however, the drawback that it is source-dependent and, therefore, impractical in situations where multiple transmitters in different positions are employed. I have, therefore, developed a localized form of the QL approximation that is source-independent. This so-called localized quasi-linear (LQL) approximation can have a scalar, a diagonal, or a full tensor form. Numerical examples of its comparison with the full integral equation solution, the Born approximation, and the original QL approximation are given. The objective behind developing this approximation is to use it in a fast 3-D inversion scheme appropriate for multisource array data such as those collected in airborne surveys, cross-well logging, and other similar geophysical applications. I have developed such an inversion scheme using the scalar and diagonal LQL approximation. It reduces the original nonlinear inverse electromagnetic (EM) problem to three linear inverse problems. The first of these problems is solved using a weighted regularized linear conjugate gradient method, whereas the last two are solved in the least squares sense. The algorithm I developed provides the option of obtaining either smooth or focused inversion images. I have applied the 3-D LQL inversion to synthetic 3-D EM data that simulate a helicopter-borne survey over different earth models. The results demonstrate the stability and efficiency of the method and show that the LQL approximation can be a practical solution to the problem of 3-D inversion of multisource array frequency-domain EM data. I have also applied the method to helicopter-borne EM data collected by INCO Exploration over the Voisey's Bay area in Labrador, Canada. The results of the 3-D inversion successfully delineate the shallow massive sulfides and show that the method can produce reasonable results even in areas of complex geology and large resistivity contrasts.

Identification of polymorphic inversions from genotypes

PubMed Central

2012-01-01

Background Polymorphic inversions are a source of genetic variability with a direct impact on recombination frequencies. Given the difficulty of their experimental study, computational methods have been developed to infer their existence in a large number of individuals using genome-wide data of nucleotide variation. Methods based on haplotype tagging of known inversions attempt to classify individuals as having a normal or inverted allele. Other methods that measure differences between linkage disequilibrium attempt to identify regions with inversions but unable to classify subjects accurately, an essential requirement for association studies. Results We present a novel method to both identify polymorphic inversions from genome-wide genotype data and classify individuals as containing a normal or inverted allele. Our method, a generalization of a published method for haplotype data [1], utilizes linkage between groups of SNPs to partition a set of individuals into normal and inverted subpopulations. We employ a sliding window scan to identify regions likely to have an inversion, and accumulation of evidence from neighboring SNPs is used to accurately determine the inversion status of each subject. Further, our approach detects inversions directly from genotype data, thus increasing its usability to current genome-wide association studies (GWAS). Conclusions We demonstrate the accuracy of our method to detect inversions and classify individuals on principled-simulated genotypes, produced by the evolution of an inversion event within a coalescent model [2]. We applied our method to real genotype data from HapMap Phase III to characterize the inversion status of two known inversions within the regions 17q21 and 8p23 across 1184 individuals. Finally, we scan the full genomes of the European Origin (CEU) and Yoruba (YRI) HapMap samples. We find population-based evidence for 9 out of 15 well-established autosomic inversions, and for 52 regions previously predicted by independent experimental methods in ten (9+1) individuals [3,4]. We provide efficient implementations of both genotype and haplotype methods as a unified R package inveRsion. PMID:22321652

Rigorous Approach in Investigation of Seismic Structure and Source Characteristicsin Northeast Asia: Hierarchical and Trans-dimensional Bayesian Inversion

NASA Astrophysics Data System (ADS)

Mustac, M.; Kim, S.; Tkalcic, H.; Rhie, J.; Chen, Y.; Ford, S. R.; Sebastian, N.

2015-12-01

Conventional approaches to inverse problems suffer from non-linearity and non-uniqueness in estimations of seismic structures and source properties. Estimated results and associated uncertainties are often biased by applied regularizations and additional constraints, which are commonly introduced to solve such problems. Bayesian methods, however, provide statistically meaningful estimations of models and their uncertainties constrained by data information. In addition, hierarchical and trans-dimensional (trans-D) techniques are inherently implemented in the Bayesian framework to account for involved error statistics and model parameterizations, and, in turn, allow more rigorous estimations of the same. Here, we apply Bayesian methods throughout the entire inference process to estimate seismic structures and source properties in Northeast Asia including east China, the Korean peninsula, and the Japanese islands. Ambient noise analysis is first performed to obtain a base three-dimensional (3-D) heterogeneity model using continuous broadband waveforms from more than 300 stations. As for the tomography of surface wave group and phase velocities in the 5-70 s band, we adopt a hierarchical and trans-D Bayesian inversion method using Voronoi partition. The 3-D heterogeneity model is further improved by joint inversions of teleseismic receiver functions and dispersion data using a newly developed high-efficiency Bayesian technique. The obtained model is subsequently used to prepare 3-D structural Green's functions for the source characterization. A hierarchical Bayesian method for point source inversion using regional complete waveform data is applied to selected events from the region. The seismic structure and source characteristics with rigorously estimated uncertainties from the novel Bayesian methods provide enhanced monitoring and discrimination of seismic events in northeast Asia.

Development of an inverse heat conduction model and its application to determination of heat transfer coefficient during casting solidification

NASA Astrophysics Data System (ADS)

Zhang, Liqiang; Reilly, Carl; Li, Luoxing; Cockcroft, Steve; Yao, Lu

2014-07-01

The interfacial heat transfer coefficient (IHTC) is required for the accurate simulation of heat transfer in castings especially for near net-shape processes. The large number of factors influencing heat transfer renders quantification by theoretical means a challenge. Likewise experimental methods applied directly to temperature data collected from castings are also a challenge to interpret because of the transient nature of many casting processes. Inverse methods offer a solution and have been applied successfully to predict the IHTC in many cases. However, most inverse approaches thus far focus on use of in-mold temperature data, which may be a challenge to obtain in cases where the molds are water-cooled. Methods based on temperature data from the casting have the potential to be used however; the latent heat released during the solidification of the molten metal complicates the associated IHTC calculations. Furthermore, there are limits on the maximum distance the thermocouples can be placed from the interface under analysis. An inverse conduction based method have been developed, verified and applied successfully to temperature data collected from within an aluminum casting in proximity to the mold. A modified specific heat method was used to account for latent heat evolution in which the rate of change of fraction solid with temperature was held constant. An analysis conducted with the inverse model suggests that the thermocouples must be placed no more than 2 mm from the interface. The IHTC values calculated for an aluminum alloy casting were shown to vary from 1,200 to 6,200 Wm-2 K-1. Additionally, the characteristics of the time-varying IHTC have also been discussed.

2D Seismic Imaging of Elastic Parameters by Frequency Domain Full Waveform Inversion

NASA Astrophysics Data System (ADS)

Brossier, R.; Virieux, J.; Operto, S.

2008-12-01

Thanks to recent advances in parallel computing, full waveform inversion is today a tractable seismic imaging method to reconstruct physical parameters of the earth interior at different scales ranging from the near- surface to the deep crust. We present a massively parallel 2D frequency-domain full-waveform algorithm for imaging visco-elastic media from multi-component seismic data. The forward problem (i.e. the resolution of the frequency-domain 2D PSV elastodynamics equations) is based on low-order Discontinuous Galerkin (DG) method (P0 and/or P1 interpolations). Thanks to triangular unstructured meshes, the DG method allows accurate modeling of both body waves and surface waves in case of complex topography for a discretization of 10 to 15 cells per shear wavelength. The frequency-domain DG system is solved efficiently for multiple sources with the parallel direct solver MUMPS. The local inversion procedure (i.e. minimization of residuals between observed and computed data) is based on the adjoint-state method which allows to efficiently compute the gradient of the objective function. Applying the inversion hierarchically from the low frequencies to the higher ones defines a multiresolution imaging strategy which helps convergence towards the global minimum. In place of expensive Newton algorithm, the combined use of the diagonal terms of the approximate Hessian matrix and optimization algorithms based on quasi-Newton methods (Conjugate Gradient, LBFGS, ...) allows to improve the convergence of the iterative inversion. The distribution of forward problem solutions over processors driven by a mesh partitioning performed by METIS allows to apply most of the inversion in parallel. We shall present the main features of the parallel modeling/inversion algorithm, assess its scalability and illustrate its performances with realistic synthetic case studies.

A combined direct/inverse three-dimensional transonic wing design method for vector computers

NASA Technical Reports Server (NTRS)

Weed, R. A.; Carlson, L. A.; Anderson, W. K.

1984-01-01

A three-dimensional transonic-wing design algorithm for vector computers is developed, and the results of sample computations are presented graphically. The method incorporates the direct/inverse scheme of Carlson (1975), a Cartesian grid system with boundary conditions applied at a mean plane, and a potential-flow solver based on the conservative form of the full potential equation and using the ZEBRA II vectorizable solution algorithm of South et al. (1980). The accuracy and consistency of the method with regard to direct and inverse analysis and trailing-edge closure are verified in the test computations.

Randomly iterated search and statistical competency as powerful inversion tools for deformation source modeling: Application to volcano interferometric synthetic aperture radar data

NASA Astrophysics Data System (ADS)

Shirzaei, M.; Walter, T. R.

2009-10-01

Modern geodetic techniques provide valuable and near real-time observations of volcanic activity. Characterizing the source of deformation based on these observations has become of major importance in related monitoring efforts. We investigate two random search approaches, simulated annealing (SA) and genetic algorithm (GA), and utilize them in an iterated manner. The iterated approach helps to prevent GA in general and SA in particular from getting trapped in local minima, and it also increases redundancy for exploring the search space. We apply a statistical competency test for estimating the confidence interval of the inversion source parameters, considering their internal interaction through the model, the effect of the model deficiency, and the observational error. Here, we present and test this new randomly iterated search and statistical competency (RISC) optimization method together with GA and SA for the modeling of data associated with volcanic deformations. Following synthetic and sensitivity tests, we apply the improved inversion techniques to two episodes of activity in the Campi Flegrei volcanic region in Italy, observed by the interferometric synthetic aperture radar technique. Inversion of these data allows derivation of deformation source parameters and their associated quality so that we can compare the two inversion methods. The RISC approach was found to be an efficient method in terms of computation time and search results and may be applied to other optimization problems in volcanic and tectonic environments.

Force sensing using 3D displacement measurements in linear elastic bodies

NASA Astrophysics Data System (ADS)

Feng, Xinzeng; Hui, Chung-Yuen

2016-07-01

In cell traction microscopy, the mechanical forces exerted by a cell on its environment is usually determined from experimentally measured displacement by solving an inverse problem in elasticity. In this paper, an innovative numerical method is proposed which finds the "optimal" traction to the inverse problem. When sufficient regularization is applied, we demonstrate that the proposed method significantly improves the widely used approach using Green's functions. Motivated by real cell experiments, the equilibrium condition of a slowly migrating cell is imposed as a set of equality constraints on the unknown traction. Our validation benchmarks demonstrate that the numeric solution to the constrained inverse problem well recovers the actual traction when the optimal regularization parameter is used. The proposed method can thus be applied to study general force sensing problems, which utilize displacement measurements to sense inaccessible forces in linear elastic bodies with a priori constraints.

Joint Inversion of 1-D Magnetotelluric and Surface-Wave Dispersion Data with an Improved Multi-Objective Genetic Algorithm and Application to the Data of the Longmenshan Fault Zone

NASA Astrophysics Data System (ADS)

Wu, Pingping; Tan, Handong; Peng, Miao; Ma, Huan; Wang, Mao

2018-05-01

Magnetotellurics and seismic surface waves are two prominent geophysical methods for deep underground exploration. Joint inversion of these two datasets can help enhance the accuracy of inversion. In this paper, we describe a method for developing an improved multi-objective genetic algorithm (NSGA-SBX) and applying it to two numerical tests to verify the advantages of the algorithm. Our findings show that joint inversion with the NSGA-SBX method can improve the inversion results by strengthening structural coupling when the discontinuities of the electrical and velocity models are consistent, and in case of inconsistent discontinuities between these models, joint inversion can retain the advantages of individual inversions. By applying the algorithm to four detection points along the Longmenshan fault zone, we observe several features. The Sichuan Basin demonstrates low S-wave velocity and high conductivity in the shallow crust probably due to thick sedimentary layers. The eastern margin of the Tibetan Plateau shows high velocity and high resistivity in the shallow crust, while two low velocity layers and a high conductivity layer are observed in the middle lower crust, probably indicating the mid-crustal channel flow. Along the Longmenshan fault zone, a high conductivity layer from 8 to 20 km is observed beneath the northern segment and decreases with depth beneath the middle segment, which might be caused by the elevated fluid content of the fault zone.

Simulating contrast inversion in atomic force microscopy imaging with real-space pseudopotentials

NASA Astrophysics Data System (ADS)

Lee, Alex J.; Sakai, Yuki; Chelikowsky, James R.

2017-02-01

Atomic force microscopy (AFM) measurements have reported contrast inversions for systems such as Cu2N and graphene that can hamper image interpretation and characterization. Here, we apply a simulation method based on ab initio real-space pseudopotentials to gain an understanding of the tip-sample interactions that influence the inversion. We find that chemically reactive tips induce an attractive binding force that results in the contrast inversion. We find that the inversion is tip height dependent and not observed when using less reactive CO-functionalized tips.

Output Tracking for Systems with Non-Hyperbolic and Near Non-Hyperbolic Internal Dynamics: Helicopter Hover Control

NASA Technical Reports Server (NTRS)

Devasia, Santosh

1996-01-01

A technique to achieve output tracking for nonminimum phase linear systems with non-hyperbolic and near non-hyperbolic internal dynamics is presented. This approach integrates stable inversion techniques, that achieve exact-tracking, with approximation techniques, that modify the internal dynamics to achieve desirable performance. Such modification of the internal dynamics is used (1) to remove non-hyperbolicity which an obstruction to applying stable inversion techniques and (2) to reduce large pre-actuation time needed to apply stable inversion for near non-hyperbolic cases. The method is applied to an example helicopter hover control problem with near non-hyperbolic internal dynamic for illustrating the trade-off between exact tracking and reduction of pre-actuation time.

Inverse models: A necessary next step in ground-water modeling

USGS Publications Warehouse

Poeter, E.P.; Hill, M.C.

1997-01-01

Inverse models using, for example, nonlinear least-squares regression, provide capabilities that help modelers take full advantage of the insight available from ground-water models. However, lack of information about the requirements and benefits of inverse models is an obstacle to their widespread use. This paper presents a simple ground-water flow problem to illustrate the requirements and benefits of the nonlinear least-squares repression method of inverse modeling and discusses how these attributes apply to field problems. The benefits of inverse modeling include: (1) expedited determination of best fit parameter values; (2) quantification of the (a) quality of calibration, (b) data shortcomings and needs, and (c) confidence limits on parameter estimates and predictions; and (3) identification of issues that are easily overlooked during nonautomated calibration.Inverse models using, for example, nonlinear least-squares regression, provide capabilities that help modelers take full advantage of the insight available from ground-water models. However, lack of information about the requirements and benefits of inverse models is an obstacle to their widespread use. This paper presents a simple ground-water flow problem to illustrate the requirements and benefits of the nonlinear least-squares regression method of inverse modeling and discusses how these attributes apply to field problems. The benefits of inverse modeling include: (1) expedited determination of best fit parameter values; (2) quantification of the (a) quality of calibration, (b) data shortcomings and needs, and (c) confidence limits on parameter estimates and predictions; and (3) identification of issues that are easily overlooked during nonautomated calibration.

Probability density of spatially distributed soil moisture inferred from crosshole georadar traveltime measurements

NASA Astrophysics Data System (ADS)

Linde, N.; Vrugt, J. A.

2009-04-01

Geophysical models are increasingly used in hydrological simulations and inversions, where they are typically treated as an artificial data source with known uncorrelated "data errors". The model appraisal problem in classical deterministic linear and non-linear inversion approaches based on linearization is often addressed by calculating model resolution and model covariance matrices. These measures offer only a limited potential to assign a more appropriate "data covariance matrix" for future hydrological applications, simply because the regularization operators used to construct a stable inverse solution bear a strong imprint on such estimates and because the non-linearity of the geophysical inverse problem is not explored. We present a parallelized Markov Chain Monte Carlo (MCMC) scheme to efficiently derive the posterior spatially distributed radar slowness and water content between boreholes given first-arrival traveltimes. This method is called DiffeRential Evolution Adaptive Metropolis (DREAM_ZS) with snooker updater and sampling from past states. Our inverse scheme does not impose any smoothness on the final solution, and uses uniform prior ranges of the parameters. The posterior distribution of radar slowness is converted into spatially distributed soil moisture values using a petrophysical relationship. To benchmark the performance of DREAM_ZS, we first apply our inverse method to a synthetic two-dimensional infiltration experiment using 9421 traveltimes contaminated with Gaussian errors and 80 different model parameters, corresponding to a model discretization of 0.3 m × 0.3 m. After this, the method is applied to field data acquired in the vadose zone during snowmelt. This work demonstrates that fully non-linear stochastic inversion can be applied with few limiting assumptions to a range of common two-dimensional tomographic geophysical problems. The main advantage of DREAM_ZS is that it provides a full view of the posterior distribution of spatially distributed soil moisture, which is key to appropriately treat geophysical parameter uncertainty and infer hydrologic models.

Methods to control phase inversions and enhance mass transfer in liquid-liquid dispersions

DOEpatents

Tsouris, Constantinos; Dong, Junhang

2002-01-01

The present invention is directed to the effects of applied electric fields on liquid-liquid dispersions. In general, the present invention is directed to the control of phase inversions in liquid-liquid dispersions. Because of polarization and deformation effects, coalescence of aqueous drops is facilitated by the application of electric fields. As a result, with an increase in the applied voltage, the ambivalence region is narrowed and shifted toward higher volume fractions of the dispersed phase. This permits the invention to be used to ensure that the aqueous phase remains continuous, even at a high volume fraction of the organic phase. Additionally, the volume fraction of the organic phase may be increased without causing phase inversion, and may be used to correct a phase inversion which has already occurred. Finally, the invention may be used to enhance mass transfer rates from one phase to another through the use of phase inversions.

Inversion of particle-size distribution from angular light-scattering data with genetic algorithms.

PubMed

Ye, M; Wang, S; Lu, Y; Hu, T; Zhu, Z; Xu, Y

1999-04-20

A stochastic inverse technique based on a genetic algorithm (GA) to invert particle-size distribution from angular light-scattering data is developed. This inverse technique is independent of any given a priori information of particle-size distribution. Numerical tests show that this technique can be successfully applied to inverse problems with high stability in the presence of random noise and low susceptibility to the shape of distributions. It has also been shown that the GA-based inverse technique is more efficient in use of computing time than the inverse Monte Carlo method recently developed by Ligon et al. [Appl. Opt. 35, 4297 (1996)].

Inverse simulation system for evaluating handling qualities during rendezvous and docking

NASA Astrophysics Data System (ADS)

Zhou, Wanmeng; Wang, Hua; Thomson, Douglas; Tang, Guojin; Zhang, Fan

2017-08-01

The traditional method used for handling qualities assessment of manned space vehicles is too time-consuming to meet the requirements of an increasingly fast design process. In this study, a rendezvous and docking inverse simulation system to assess the handling qualities of spacecraft is proposed using a previously developed model-predictive-control architecture. By considering the fixed discrete force of the thrusters of the system, the inverse model is constructed using the least squares estimation method with a hyper-ellipsoidal restriction, the continuous control outputs of which are subsequently dispersed by pulse width modulation with sensitivity factors introduced. The inputs in every step are deemed constant parameters, and the method could be considered as a general method for solving nominal, redundant, and insufficient inverse problems. The rendezvous and docking inverse simulation is applied to a nine-degrees-of-freedom platform, and a novel handling qualities evaluation scheme is established according to the operation precision and astronauts' workload. Finally, different nominal trajectories are scored by the inverse simulation and an established evaluation scheme. The scores can offer theoretical guidance for astronaut training and more complex operation missions.

anisotropic microseismic focal mechanism inversion by waveform imaging matching

NASA Astrophysics Data System (ADS)

Wang, L.; Chang, X.; Wang, Y.; Xue, Z.

2016-12-01

The focal mechanism is one of the most important parameters in source inversion, for both natural earthquakes and human-induced seismic events. It has been reported to be useful for understanding stress distribution and evaluating the fracturing effect. The conventional focal mechanism inversion method picks the first arrival waveform of P wave. This method assumes the source as a Double Couple (DC) type and the media isotropic, which is usually not the case for induced seismic focal mechanism inversion. For induced seismic events, the inappropriate source and media model in inversion processing, by introducing ambiguity or strong simulation errors, will seriously reduce the inversion effectiveness. First, the focal mechanism contains significant non-DC source type. Generally, the source contains three components: DC, isotropic (ISO) and the compensated linear vector dipole (CLVD), which makes focal mechanisms more complicated. Second, the anisotropy of media will affect travel time and waveform to generate inversion bias. The common way to describe focal mechanism inversion is based on moment tensor (MT) inversion which can be decomposed into the combination of DC, ISO and CLVD components. There are two ways to achieve MT inversion. The wave-field migration method is applied to achieve moment tensor imaging. This method can construct elements imaging of MT in 3D space without picking the first arrival, but the retrieved MT value is influenced by imaging resolution. The full waveform inversion is employed to retrieve MT. In this method, the source position and MT can be reconstructed simultaneously. However, this method needs vast numerical calculation. Moreover, the source position and MT also influence each other in the inversion process. In this paper, the waveform imaging matching (WIM) method is proposed, which combines source imaging with waveform inversion for seismic focal mechanism inversion. Our method uses the 3D tilted transverse isotropic (TTI) elastic wave equation to approximate wave propagating in anisotropic media. First, a source imaging procedure is employed to obtain the source position. Second, we refine a waveform inversion algorithm to retrieve MT. We also use a microseismic data set recorded in surface acquisition to test our method.

Frozen Gaussian approximation for 3D seismic tomography

NASA Astrophysics Data System (ADS)

Chai, Lihui; Tong, Ping; Yang, Xu

2018-05-01

Three-dimensional (3D) wave-equation-based seismic tomography is computationally challenging in large scales and high-frequency regime. In this paper, we apply the frozen Gaussian approximation (FGA) method to compute 3D sensitivity kernels and seismic tomography of high-frequency. Rather than standard ray theory used in seismic inversion (e.g. Kirchhoff migration and Gaussian beam migration), FGA is used to compute the 3D high-frequency sensitivity kernels for travel-time or full waveform inversions. Specifically, we reformulate the equations of the forward and adjoint wavefields for the purpose of convenience to apply FGA, and with this reformulation, one can efficiently compute the Green’s functions whose convolutions with source time function produce wavefields needed for the construction of 3D kernels. Moreover, a fast summation method is proposed based on local fast Fourier transform which greatly improves the speed of reconstruction as the last step of FGA algorithm. We apply FGA to both the travel-time adjoint tomography and full waveform inversion (FWI) on synthetic crosswell seismic data with dominant frequencies as high as those of real crosswell data, and confirm again that FWI requires a more sophisticated initial velocity model for the convergence than travel-time adjoint tomography. We also numerically test the accuracy of applying FGA to local earthquake tomography. This study paves the way to directly apply wave-equation-based seismic tomography methods into real data around their dominant frequencies.

An alternative empirical likelihood method in missing response problems and causal inference.

PubMed

Ren, Kaili; Drummond, Christopher A; Brewster, Pamela S; Haller, Steven T; Tian, Jiang; Cooper, Christopher J; Zhang, Biao

2016-11-30

Missing responses are common problems in medical, social, and economic studies. When responses are missing at random, a complete case data analysis may result in biases. A popular debias method is inverse probability weighting proposed by Horvitz and Thompson. To improve efficiency, Robins et al. proposed an augmented inverse probability weighting method. The augmented inverse probability weighting estimator has a double-robustness property and achieves the semiparametric efficiency lower bound when the regression model and propensity score model are both correctly specified. In this paper, we introduce an empirical likelihood-based estimator as an alternative to Qin and Zhang (2007). Our proposed estimator is also doubly robust and locally efficient. Simulation results show that the proposed estimator has better performance when the propensity score is correctly modeled. Moreover, the proposed method can be applied in the estimation of average treatment effect in observational causal inferences. Finally, we apply our method to an observational study of smoking, using data from the Cardiovascular Outcomes in Renal Atherosclerotic Lesions clinical trial. Copyright © 2016 John Wiley & Sons, Ltd. Copyright © 2016 John Wiley & Sons, Ltd.

Comparison of adjoint and analytical Bayesian inversion methods for constraining Asian sources of carbon monoxide using satellite (MOPITT) measurements of CO columns

NASA Astrophysics Data System (ADS)

Kopacz, Monika; Jacob, Daniel J.; Henze, Daven K.; Heald, Colette L.; Streets, David G.; Zhang, Qiang

2009-02-01

We apply the adjoint of an atmospheric chemical transport model (GEOS-Chem CTM) to constrain Asian sources of carbon monoxide (CO) with 2° × 2.5° spatial resolution using Measurement of Pollution in the Troposphere (MOPITT) satellite observations of CO columns in February-April 2001. Results are compared to the more common analytical method for solving the same Bayesian inverse problem and applied to the same data set. The analytical method is more exact but because of computational limitations it can only constrain emissions over coarse regions. We find that the correction factors to the a priori CO emission inventory from the adjoint inversion are generally consistent with those of the analytical inversion when averaged over the large regions of the latter. The adjoint solution reveals fine-scale variability (cities, political boundaries) that the analytical inversion cannot resolve, for example, in the Indian subcontinent or between Korea and Japan, and some of that variability is of opposite sign which points to large aggregation errors in the analytical solution. Upward correction factors to Chinese emissions from the prior inventory are largest in central and eastern China, consistent with a recent bottom-up revision of that inventory, although the revised inventory also sees the need for upward corrections in southern China where the adjoint and analytical inversions call for downward correction. Correction factors for biomass burning emissions derived from the adjoint and analytical inversions are consistent with a recent bottom-up inventory on the basis of MODIS satellite fire data.

Probabilistic joint inversion of waveforms and polarity data for double-couple focal mechanisms of local earthquakes

NASA Astrophysics Data System (ADS)

Wéber, Zoltán

2018-06-01

Estimating the mechanisms of small (M < 4) earthquakes is quite challenging. A common scenario is that neither the available polarity data alone nor the well predictable near-station seismograms alone are sufficient to obtain reliable focal mechanism solutions for weak events. To handle this situation we introduce here a new method that jointly inverts waveforms and polarity data following a probabilistic approach. The procedure called joint waveform and polarity (JOWAPO) inversion maps the posterior probability density of the model parameters and estimates the maximum likelihood double-couple mechanism, the optimal source depth and the scalar seismic moment of the investigated event. The uncertainties of the solution are described by confidence regions. We have validated the method on two earthquakes for which well-determined focal mechanisms are available. The validation tests show that including waveforms in the inversion considerably reduces the uncertainties of the usually poorly constrained polarity solutions. The JOWAPO method performs best when it applies waveforms from at least two seismic stations. If the number of the polarity data is large enough, even single-station JOWAPO inversion can produce usable solutions. When only a few polarities are available, however, single-station inversion may result in biased mechanisms. In this case some caution must be taken when interpreting the results. We have successfully applied the JOWAPO method to an earthquake in North Hungary, whose mechanism could not be estimated by long-period waveform inversion. Using 17 P-wave polarities and waveforms at two nearby stations, the JOWAPO method produced a well-constrained focal mechanism. The solution is very similar to those obtained previously for four other events that occurred in the same earthquake sequence. The analysed event has a strike-slip mechanism with a P axis oriented approximately along an NE-SW direction.

Radiation characteristics and effective optical properties of dumbbell-shaped cyanobacterium Synechocystis sp.

NASA Astrophysics Data System (ADS)

Heng, Ri-Liang; Pilon, Laurent

2016-05-01

This study presents experimental measurements of the radiation characteristics of unicellular freshwater cyanobacterium Synechocystis sp. during their exponential growth in F medium. Their scattering phase function at 633 nm average spectral absorption and scattering cross-sections between 400 and 750 nm were measured. In addition, an inverse method was used for retrieving the spectral effective complex index of refraction of overlapping or touching bispheres and quadspheres from their absorption and scattering cross-sections. The inverse method combines a genetic algorithm and a forward model based on Lorenz-Mie theory, treating bispheres and quadspheres as projected area and volume-equivalent coated spheres. The inverse method was successfully validated with numerically predicted average absorption and scattering cross-sections of suspensions consisting of bispheres and quadspheres, with realistic size distributions, using the T-matrix method. It was able to retrieve the monomers' complex index of refraction with size parameter up to 11, relative refraction index less than 1.3, and absorption index less than 0.1. Then, the inverse method was applied to retrieve the effective spectral complex index of refraction of Synechocystis sp. approximated as randomly oriented aggregates consisting of two overlapping homogeneous spheres. Both the measured absorption cross-section and the retrieved absorption index featured peaks at 435 and 676 nm corresponding to chlorophyll a, a peak at 625 nm corresponding to phycocyanin, and a shoulder around 485 nm corresponding to carotenoids. These results can be used to optimize and control light transfer in photobioreactors. The inverse method and the equivalent coated sphere model could be applied to other optically soft particles of similar morphologies.

Adjoint Sensitivity Method to Determine Optimal Set of Stations for Tsunami Source Inversion

NASA Astrophysics Data System (ADS)

Gusman, A. R.; Hossen, M. J.; Cummins, P. R.; Satake, K.

2017-12-01

We applied the adjoint sensitivity technique in tsunami science for the first time to determine an optimal set of stations for a tsunami source inversion. The adjoint sensitivity (AS) method has been used in numerical weather prediction to find optimal locations for adaptive observations. We implemented this technique to Green's Function based Time Reverse Imaging (GFTRI), which is recently used in tsunami source inversion in order to reconstruct the initial sea surface displacement, known as tsunami source model. This method has the same source representation as the traditional least square (LSQ) source inversion method where a tsunami source is represented by dividing the source region into a regular grid of "point" sources. For each of these, Green's function (GF) is computed using a basis function for initial sea surface displacement whose amplitude is concentrated near the grid point. We applied the AS method to the 2009 Samoa earthquake tsunami that occurred on 29 September 2009 in the southwest Pacific, near the Tonga trench. Many studies show that this earthquake is a doublet associated with both normal faulting in the outer-rise region and thrust faulting in the subduction interface. To estimate the tsunami source model for this complex event, we initially considered 11 observations consisting of 5 tide gauges and 6 DART bouys. After implementing AS method, we found the optimal set of observations consisting with 8 stations. Inversion with this optimal set provides better result in terms of waveform fitting and source model that shows both sub-events associated with normal and thrust faulting.

Identification of moving sinusoidal wave loads for sensor structural configuration by finite element inverse method

NASA Astrophysics Data System (ADS)

Zhang, B.; Yu, S.

2018-03-01

In this paper, a beam structure of composite materials with elastic foundation supports is established as the sensor model, which propagates moving sinusoidal wave loads. The inverse Finite Element Method (iFEM) is applied for reconstructing moving wave loads which are compared with true wave loads. The conclusion shows that iFEM is accurate and robust in the determination of wave propagation. This helps to seek a suitable new wave sensor method.

2D data-space cross-gradient joint inversion of MT, gravity and magnetic data

NASA Astrophysics Data System (ADS)

Pak, Yong-Chol; Li, Tonglin; Kim, Gang-Sop

2017-08-01

We have developed a data-space multiple cross-gradient joint inversion algorithm, and validated it through synthetic tests and applied it to magnetotelluric (MT), gravity and magnetic datasets acquired along a 95 km profile in Benxi-Ji'an area of northeastern China. To begin, we discuss a generalized cross-gradient joint inversion for multiple datasets and model parameters sets, and formulate it in data space. The Lagrange multiplier required for the structural coupling in the data-space method is determined using an iterative solver to avoid calculation of the inverse matrix in solving the large system of equations. Next, using model-space and data-space methods, we inverted the synthetic data and field data. Based on our result, the joint inversion in data-space not only delineates geological bodies more clearly than the separate inversion, but also yields nearly equal results with the one in model-space while consuming much less memory.

Time-lapse joint AVO inversion using generalized linear method based on exact Zoeppritz equations

NASA Astrophysics Data System (ADS)

Zhi, L.; Gu, H.

2017-12-01

The conventional method of time-lapse AVO (Amplitude Versus Offset) inversion is mainly based on the approximate expression of Zoeppritz equations. Though the approximate expression is concise and convenient to use, it has certain limitations. For example, its application condition is that the difference of elastic parameters between the upper medium and lower medium is little and the incident angle is small. In addition, the inversion of density is not stable. Therefore, we develop the method of time-lapse joint AVO inversion based on exact Zoeppritz equations. In this method, we apply exact Zoeppritz equations to calculate the reflection coefficient of PP wave. And in the construction of objective function for inversion, we use Taylor expansion to linearize the inversion problem. Through the joint AVO inversion of seismic data in baseline survey and monitor survey, we can obtain P-wave velocity, S-wave velocity, density in baseline survey and their time-lapse changes simultaneously. We can also estimate the oil saturation change according to inversion results. Compared with the time-lapse difference inversion, the joint inversion has a better applicability. It doesn't need some assumptions and can estimate more parameters simultaneously. Meanwhile, by using the generalized linear method, the inversion is easily realized and its calculation amount is small. We use the Marmousi model to generate synthetic seismic records to test and analyze the influence of random noise. Without noise, all estimation results are relatively accurate. With the increase of noise, P-wave velocity change and oil saturation change are stable and less affected by noise. S-wave velocity change is most affected by noise. Finally we use the actual field data of time-lapse seismic prospecting to process and the results can prove the availability and feasibility of our method in actual situation.

A computationally efficient parallel Levenberg-Marquardt algorithm for highly parameterized inverse model analyses

NASA Astrophysics Data System (ADS)

Lin, Youzuo; O'Malley, Daniel; Vesselinov, Velimir V.

2016-09-01

Inverse modeling seeks model parameters given a set of observations. However, for practical problems because the number of measurements is often large and the model parameters are also numerous, conventional methods for inverse modeling can be computationally expensive. We have developed a new, computationally efficient parallel Levenberg-Marquardt method for solving inverse modeling problems with a highly parameterized model space. Levenberg-Marquardt methods require the solution of a linear system of equations which can be prohibitively expensive to compute for moderate to large-scale problems. Our novel method projects the original linear problem down to a Krylov subspace such that the dimensionality of the problem can be significantly reduced. Furthermore, we store the Krylov subspace computed when using the first damping parameter and recycle the subspace for the subsequent damping parameters. The efficiency of our new inverse modeling algorithm is significantly improved using these computational techniques. We apply this new inverse modeling method to invert for random transmissivity fields in 2-D and a random hydraulic conductivity field in 3-D. Our algorithm is fast enough to solve for the distributed model parameters (transmissivity) in the model domain. The algorithm is coded in Julia and implemented in the MADS computational framework (http://mads.lanl.gov). By comparing with Levenberg-Marquardt methods using standard linear inversion techniques such as QR or SVD methods, our Levenberg-Marquardt method yields a speed-up ratio on the order of ˜101 to ˜102 in a multicore computational environment. Therefore, our new inverse modeling method is a powerful tool for characterizing subsurface heterogeneity for moderate to large-scale problems.

Efficient combination of a 3D Quasi-Newton inversion algorithm and a vector dual-primal finite element tearing and interconnecting method

NASA Astrophysics Data System (ADS)

Voznyuk, I.; Litman, A.; Tortel, H.

2015-08-01

A Quasi-Newton method for reconstructing the constitutive parameters of three-dimensional (3D) penetrable scatterers from scattered field measurements is presented. This method is adapted for handling large-scale electromagnetic problems while keeping the memory requirement and the time flexibility as low as possible. The forward scattering problem is solved by applying the finite-element tearing and interconnecting full-dual-primal (FETI-FDP2) method which shares the same spirit as the domain decomposition methods for finite element methods. The idea is to split the computational domain into smaller non-overlapping sub-domains in order to simultaneously solve local sub-problems. Various strategies are proposed in order to efficiently couple the inversion algorithm with the FETI-FDP2 method: a separation into permanent and non-permanent subdomains is performed, iterative solvers are favorized for resolving the interface problem and a marching-on-in-anything initial guess selection further accelerates the process. The computational burden is also reduced by applying the adjoint state vector methodology. Finally, the inversion algorithm is confronted to measurements extracted from the 3D Fresnel database.

A general rough-surface inversion algorithm: Theory and application to SAR data

NASA Technical Reports Server (NTRS)

Moghaddam, M.

1993-01-01

Rough-surface inversion has significant applications in interpretation of SAR data obtained over bare soil surfaces and agricultural lands. Due to the sparsity of data and the large pixel size in SAR applications, it is not feasible to carry out inversions based on numerical scattering models. The alternative is to use parameter estimation techniques based on approximate analytical or empirical models. Hence, there are two issues to be addressed, namely, what model to choose and what estimation algorithm to apply. Here, a small perturbation model (SPM) is used to express the backscattering coefficients of the rough surface in terms of three surface parameters. The algorithm used to estimate these parameters is based on a nonlinear least-squares criterion. The least-squares optimization methods are widely used in estimation theory, but the distinguishing factor for SAR applications is incorporating the stochastic nature of both the unknown parameters and the data into formulation, which will be discussed in detail. The algorithm is tested with synthetic data, and several Newton-type least-squares minimization methods are discussed to compare their convergence characteristics. Finally, the algorithm is applied to multifrequency polarimetric SAR data obtained over some bare soil and agricultural fields. Results will be shown and compared to ground-truth measurements obtained from these areas. The strength of this general approach to inversion of SAR data is that it can be easily modified for use with any scattering model without changing any of the inversion steps. Note also that, for the same reason it is not limited to inversion of rough surfaces, and can be applied to any parameterized scattering process.

Density-to-Potential Inversions to Guide Development of Exchange-Correlation Approximations at Finite Temperature

NASA Astrophysics Data System (ADS)

Jensen, Daniel; Wasserman, Adam; Baczewski, Andrew

The construction of approximations to the exchange-correlation potential for warm dense matter (WDM) is a topic of significant recent interest. In this work, we study the inverse problem of Kohn-Sham (KS) DFT as a means of guiding functional design at zero temperature and in WDM. Whereas the forward problem solves the KS equations to produce a density from a specified exchange-correlation potential, the inverse problem seeks to construct the exchange-correlation potential from specified densities. These two problems require different computational methods and convergence criteria despite sharing the same mathematical equations. We present two new inversion methods based on constrained variational and PDE-constrained optimization methods. We adapt these methods to finite temperature calculations to reveal the exchange-correlation potential's temperature dependence in WDM-relevant conditions. The different inversion methods presented are applied to both non-interacting and interacting model systems for comparison. Sandia National Laboratories is a multi-program laboratory managed and operated by Sandia Corporation, a wholly owned subsidiary of Lockheed Martin Corporation, for the U.S. Department of Energy's National Security Administration under contract DE-AC04-94.

Parameterizations for ensemble Kalman inversion

NASA Astrophysics Data System (ADS)

Chada, Neil K.; Iglesias, Marco A.; Roininen, Lassi; Stuart, Andrew M.

2018-05-01

The use of ensemble methods to solve inverse problems is attractive because it is a derivative-free methodology which is also well-adapted to parallelization. In its basic iterative form the method produces an ensemble of solutions which lie in the linear span of the initial ensemble. Choice of the parameterization of the unknown field is thus a key component of the success of the method. We demonstrate how both geometric ideas and hierarchical ideas can be used to design effective parameterizations for a number of applied inverse problems arising in electrical impedance tomography, groundwater flow and source inversion. In particular we show how geometric ideas, including the level set method, can be used to reconstruct piecewise continuous fields, and we show how hierarchical methods can be used to learn key parameters in continuous fields, such as length-scales, resulting in improved reconstructions. Geometric and hierarchical ideas are combined in the level set method to find piecewise constant reconstructions with interfaces of unknown topology.

Estimation of Uncertainties of Full Moment Tensors

DTIC Science & Technology

2017-10-06

Nevada Test Site (tab. 1 of Ford et al., 2009). Figure 1 shows the three regions and the stations used within the moment tensor inversions . For the...and additional bandpass filtering, were applied during the moment tensor inversions . We use high-frequency P waves for the Uturuncu and NTS events...reliable when we align the P waves on the observed P arrival time. 3.2 Methods Seismic moment tensor inversion requires specifying a misfit function

Applications of He's semi-inverse method, ITEM and GGM to the Davey-Stewartson equation

NASA Astrophysics Data System (ADS)

Zinati, Reza Farshbaf; Manafian, Jalil

2017-04-01

We investigate the Davey-Stewartson (DS) equation. Travelling wave solutions were found. In this paper, we demonstrate the effectiveness of the analytical methods, namely, He's semi-inverse variational principle method (SIVPM), the improved tan(φ/2)-expansion method (ITEM) and generalized G'/G-expansion method (GGM) for seeking more exact solutions via the DS equation. These methods are direct, concise and simple to implement compared to other existing methods. The exact solutions containing four types solutions have been achieved. The results demonstrate that the aforementioned methods are more efficient than the Ansatz method applied by Mirzazadeh (2015). Abundant exact travelling wave solutions including solitons, kink, periodic and rational solutions have been found by the improved tan(φ/2)-expansion and generalized G'/G-expansion methods. By He's semi-inverse variational principle we have obtained dark and bright soliton wave solutions. Also, the obtained semi-inverse variational principle has profound implications in physical understandings. These solutions might play important role in engineering and physics fields. Moreover, by using Matlab, some graphical simulations were done to see the behavior of these solutions.

Joint Inversion of Source Location and Source Mechanism of Induced Microseismics

NASA Astrophysics Data System (ADS)

Liang, C.

2014-12-01

Seismic source mechanism is a useful property to indicate the source physics and stress and strain distribution in regional, local and micro scales. In this study we jointly invert source mechanisms and locations for microseismics induced in fluid fracturing treatment in the oil and gas industry. For the events that are big enough to see waveforms, there are quite a few techniques can be applied to invert the source mechanism including waveform inversion, first polarity inversion and many other methods and variants based on these methods. However, for events that are too small to identify in seismic traces such as the microseismics induced by the fluid fracturing in the Oil and Gas industry, a source scanning algorithms (SSA for short) with waveform stacking are usually applied. At the same time, a joint inversion of location and source mechanism are possible but at a cost of high computation budget. The algorithm is thereby called Source Location and Mechanism Scanning Algorithm, SLMSA for short. In this case, for given velocity structure, all possible combinations of source locations (X,Y and Z) and source mechanism (Strike, Dip and Rake) are used to compute travel-times and polarities of waveforms. Correcting Normal moveout times and polarities, and stacking all waveforms, the (X, Y, Z , strike, dip, rake) combination that gives the strongest stacking waveform is identified as the solution. To solve the problem of high computation problem, CPU-GPU programing is applied. Numerical datasets are used to test the algorithm. The SLMSA has also been applied to a fluid fracturing datasets and reveal several advantages against the location only method: (1) for shear sources, the source only program can hardly locate them because of the canceling out of positive and negative polarized traces, but the SLMSA method can successfully pick up those events; (2) microseismic locations alone may not be enough to indicate the directionality of micro-fractures. The statistics of source mechanisms can certainly provide more knowledges on the orientation of fractures; (3) in our practice, the joint inversion method almost always yield more events than the source only method and for those events that are also picked by the SSA method, the stacking power of SLMSA are always higher than the ones obtained in SSA.

Remarks on a financial inverse problem by means of Monte Carlo Methods

NASA Astrophysics Data System (ADS)

Cuomo, Salvatore; Di Somma, Vittorio; Sica, Federica

2017-10-01

Estimating the price of a barrier option is a typical inverse problem. In this paper we present a numerical and statistical framework for a market with risk-free interest rate and a risk asset, described by a Geometric Brownian Motion (GBM). After approximating the risk asset with a numerical method, we find the final option price by following an approach based on sequential Monte Carlo methods. All theoretical results are applied to the case of an option whose underlying is a real stock.

Application of linearized inverse scattering methods for the inspection in steel plates embedded in concrete structures

NASA Astrophysics Data System (ADS)

Tsunoda, Takaya; Suzuki, Keigo; Saitoh, Takahiro

2018-04-01

This study develops a method to visualize the state of steel-concrete interface with ultrasonic testing. Scattered waves are obtained by the UT pitch-catch mode from the surface of the concrete. Discrete wavelet transform is applied in order to extract echoes scattered from the steel-concrete interface. Then Linearized Inverse Scattering Methods are used for imaging the interface. The results show that LISM with Born and Kirchhoff approximation provide clear images for the target.

Inverse Calibration Free fs-LIBS of Copper-Based Alloys

NASA Astrophysics Data System (ADS)

Smaldone, Antonella; De Bonis, Angela; Galasso, Agostino; Guarnaccio, Ambra; Santagata, Antonio; Teghil, Roberto

2016-09-01

In this work the analysis by Laser Induced Breakdown Spectroscopy (LIBS) technique of copper-based alloys having different composition and performed with fs laser pulses is presented. A Nd:Glass laser (Twinkle Light Conversion, λ = 527 nm at 250 fs) and a set of bronze and brass certified standards were used. The inverse Calibration-Free method (inverse CF-LIBS) was applied for estimating the temperature of the fs laser induced plasma in order to achieve quantitative elemental analysis of such materials. This approach strengthens the hypothesis that, through the assessment of the plasma temperature occurring in fs-LIBS, straightforward and reliable analytical data can be provided. With this aim the capability of the here adopted inverse CF-LIBS method, which is based on the fulfilment of the Local Thermodynamic Equilibrium (LTE) condition, for an indirect determination of the species excitation temperature, is shown. It is reported that the estimated temperatures occurring during the process provide a good figure of merit between the certified and the experimentally determined composition of the bronze and brass materials, here employed, although further correction procedure, like the use of calibration curves, can be demanded. The reported results demonstrate that the inverse CF-LIBS method can be applied when fs laser pulses are used even though the plasma properties could be affected by the matrix effects restricting its full employment to unknown samples provided that a certified standard having similar composition is available.

Absolute mass scale calibration in the inverse problem of the physical theory of fireballs.

NASA Astrophysics Data System (ADS)

Kalenichenko, V. V.

A method of the absolute mass scale calibration is suggested for solving the inverse problem of the physical theory of fireballs. The method is based on the data on the masses of the fallen meteorites whose fireballs have been photographed in their flight. The method may be applied to those fireballs whose bodies have not experienced considerable fragmentation during their destruction in the atmosphere and have kept their form well enough. Statistical analysis of the inverse problem solution for a sufficiently representative sample makes it possible to separate a subsample of such fireballs. The data on the Lost City and Innisfree meteorites are used to obtain calibration coefficients.

Development of direct-inverse 3-D methods for applied transonic aerodynamic wing design and analysis

NASA Technical Reports Server (NTRS)

Carlson, Leland A.

1989-01-01

An inverse wing design method was developed around an existing transonic wing analysis code. The original analysis code, TAWFIVE, has as its core the numerical potential flow solver, FLO30, developed by Jameson and Caughey. Features of the analysis code include a finite-volume formulation; wing and fuselage fitted, curvilinear grid mesh; and a viscous boundary layer correction that also accounts for viscous wake thickness and curvature. The development of the inverse methods as an extension of previous methods existing for design in Cartesian coordinates is presented. Results are shown for inviscid wing design cases in super-critical flow regimes. The test cases selected also demonstrate the versatility of the design method in designing an entire wing or discontinuous sections of a wing.

Quantifying uncertainty in geoacoustic inversion. II. Application to broadband, shallow-water data.

PubMed

Dosso, Stan E; Nielsen, Peter L

2002-01-01

This paper applies the new method of fast Gibbs sampling (FGS) to estimate the uncertainties of seabed geoacoustic parameters in a broadband, shallow-water acoustic survey, with the goal of interpreting the survey results and validating the method for experimental data. FGS applies a Bayesian approach to geoacoustic inversion based on sampling the posterior probability density to estimate marginal probability distributions and parameter covariances. This requires knowledge of the statistical distribution of the data errors, including both measurement and theory errors, which is generally not available. Invoking the simplifying assumption of independent, identically distributed Gaussian errors allows a maximum-likelihood estimate of the data variance and leads to a practical inversion algorithm. However, it is necessary to validate these assumptions, i.e., to verify that the parameter uncertainties obtained represent meaningful estimates. To this end, FGS is applied to a geoacoustic experiment carried out at a site off the west coast of Italy where previous acoustic and geophysical studies have been performed. The parameter uncertainties estimated via FGS are validated by comparison with: (i) the variability in the results of inverting multiple independent data sets collected during the experiment; (ii) the results of FGS inversion of synthetic test cases designed to simulate the experiment and data errors; and (iii) the available geophysical ground truth. Comparisons are carried out for a number of different source bandwidths, ranges, and levels of prior information, and indicate that FGS provides reliable and stable uncertainty estimates for the geoacoustic inverse problem.

Spectral-element simulations of wave propagation in complex exploration-industry models: Imaging and adjoint tomography

NASA Astrophysics Data System (ADS)

Luo, Y.; Nissen-Meyer, T.; Morency, C.; Tromp, J.

2008-12-01

Seismic imaging in the exploration industry is often based upon ray-theoretical migration techniques (e.g., Kirchhoff) or other ideas which neglect some fraction of the seismic wavefield (e.g., wavefield continuation for acoustic-wave first arrivals) in the inversion process. In a companion paper we discuss the possibility of solving the full physical forward problem (i.e., including visco- and poroelastic, anisotropic media) using the spectral-element method. With such a tool at hand, we can readily apply the adjoint method to tomographic inversions, i.e., iteratively improving an initial 3D background model to fit the data. In the context of this inversion process, we draw connections between kernels in adjoint tomography and basic imaging principles in migration. We show that the images obtained by migration are nothing but particular kinds of adjoint kernels (mainly density kernels). Migration is basically a first step in the iterative inversion process of adjoint tomography. We apply the approach to basic 2D problems involving layered structures, overthrusting faults, topography, salt domes, and poroelastic regions.

Objective function analysis for electric soundings (VES), transient electromagnetic soundings (TEM) and joint inversion VES/TEM

NASA Astrophysics Data System (ADS)

Bortolozo, Cassiano Antonio; Bokhonok, Oleg; Porsani, Jorge Luís; Monteiro dos Santos, Fernando Acácio; Diogo, Liliana Alcazar; Slob, Evert

2017-11-01

Ambiguities in geophysical inversion results are always present. How these ambiguities appear in most cases open to interpretation. It is interesting to investigate ambiguities with regard to the parameters of the models under study. Residual Function Dispersion Map (RFDM) can be used to differentiate between global ambiguities and local minima in the objective function. We apply RFDM to Vertical Electrical Sounding (VES) and TEM Sounding inversion results. Through topographic analysis of the objective function we evaluate the advantages and limitations of electrical sounding data compared with TEM sounding data, and the benefits of joint inversion in comparison with the individual methods. The RFDM analysis proved to be a very interesting tool for understanding the joint inversion method of VES/TEM. Also the advantage of the applicability of the RFDM analyses in real data is explored in this paper to demonstrate not only how the objective function of real data behaves but the applicability of the RFDM approach in real cases. With the analysis of the results, it is possible to understand how the joint inversion can reduce the ambiguity of the methods.

Joint inversion of multiple geophysical and petrophysical data using generalized fuzzy clustering algorithms

NASA Astrophysics Data System (ADS)

Sun, Jiajia; Li, Yaoguo

2017-02-01

Joint inversion that simultaneously inverts multiple geophysical data sets to recover a common Earth model is increasingly being applied to exploration problems. Petrophysical data can serve as an effective constraint to link different physical property models in such inversions. There are two challenges, among others, associated with the petrophysical approach to joint inversion. One is related to the multimodality of petrophysical data because there often exist more than one relationship between different physical properties in a region of study. The other challenge arises from the fact that petrophysical relationships have different characteristics and can exhibit point, linear, quadratic, or exponential forms in a crossplot. The fuzzy c-means (FCM) clustering technique is effective in tackling the first challenge and has been applied successfully. We focus on the second challenge in this paper and develop a joint inversion method based on variations of the FCM clustering technique. To account for the specific shapes of petrophysical relationships, we introduce several different fuzzy clustering algorithms that are capable of handling different shapes of petrophysical relationships. We present two synthetic and one field data examples and demonstrate that, by choosing appropriate distance measures for the clustering component in the joint inversion algorithm, the proposed joint inversion method provides an effective means of handling common petrophysical situations we encounter in practice. The jointly inverted models have both enhanced structural similarity and increased petrophysical correlation, and better represent the subsurface in the spatial domain and the parameter domain of physical properties.

Classifying the Sizes of Explosive Eruptions using Tephra Deposits: The Advantages of a Numerical Inversion Approach

NASA Astrophysics Data System (ADS)

Connor, C.; Connor, L.; White, J.

2015-12-01

Explosive volcanic eruptions are often classified by deposit mass and eruption column height. How well are these eruption parameters determined in older deposits, and how well can we reduce uncertainty using robust numerical and statistical methods? We describe an efficient and effective inversion and uncertainty quantification approach for estimating eruption parameters given a dataset of tephra deposit thickness and granulometry. The inversion and uncertainty quantification is implemented using the open-source PEST++ code. Inversion with PEST++ can be used with a variety of forward models and here is applied using Tephra2, a code that simulates advective and dispersive tephra transport and deposition. The Levenburg-Marquardt algorithm is combined with formal Tikhonov and subspace regularization to invert eruption parameters; a linear equation for conditional uncertainty propagation is used to estimate posterior parameter uncertainty. Both the inversion and uncertainty analysis support simultaneous analysis of the full eruption and wind-field parameterization. The combined inversion/uncertainty-quantification approach is applied to the 1992 eruption of Cerro Negro (Nicaragua), the 2011 Kirishima-Shinmoedake (Japan), and the 1913 Colima (Mexico) eruptions. These examples show that although eruption mass uncertainty is reduced by inversion against tephra isomass data, considerable uncertainty remains for many eruption and wind-field parameters, such as eruption column height. Supplementing the inversion dataset with tephra granulometry data is shown to further reduce the uncertainty of most eruption and wind-field parameters. We think the use of such robust models provides a better understanding of uncertainty in eruption parameters, and hence eruption classification, than is possible with more qualitative methods that are widely used.

A computationally efficient parallel Levenberg-Marquardt algorithm for highly parameterized inverse model analyses

DOE Office of Scientific and Technical Information (OSTI.GOV)

Lin, Youzuo; O'Malley, Daniel; Vesselinov, Velimir V.

Inverse modeling seeks model parameters given a set of observations. However, for practical problems because the number of measurements is often large and the model parameters are also numerous, conventional methods for inverse modeling can be computationally expensive. We have developed a new, computationally-efficient parallel Levenberg-Marquardt method for solving inverse modeling problems with a highly parameterized model space. Levenberg-Marquardt methods require the solution of a linear system of equations which can be prohibitively expensive to compute for moderate to large-scale problems. Our novel method projects the original linear problem down to a Krylov subspace, such that the dimensionality of themore » problem can be significantly reduced. Furthermore, we store the Krylov subspace computed when using the first damping parameter and recycle the subspace for the subsequent damping parameters. The efficiency of our new inverse modeling algorithm is significantly improved using these computational techniques. We apply this new inverse modeling method to invert for random transmissivity fields in 2D and a random hydraulic conductivity field in 3D. Our algorithm is fast enough to solve for the distributed model parameters (transmissivity) in the model domain. The algorithm is coded in Julia and implemented in the MADS computational framework (http://mads.lanl.gov). By comparing with Levenberg-Marquardt methods using standard linear inversion techniques such as QR or SVD methods, our Levenberg-Marquardt method yields a speed-up ratio on the order of ~10 1 to ~10 2 in a multi-core computational environment. Furthermore, our new inverse modeling method is a powerful tool for characterizing subsurface heterogeneity for moderate- to large-scale problems.« less

A computationally efficient parallel Levenberg-Marquardt algorithm for highly parameterized inverse model analyses

DOE PAGES

Lin, Youzuo; O'Malley, Daniel; Vesselinov, Velimir V.

2016-09-01

Inverse modeling seeks model parameters given a set of observations. However, for practical problems because the number of measurements is often large and the model parameters are also numerous, conventional methods for inverse modeling can be computationally expensive. We have developed a new, computationally-efficient parallel Levenberg-Marquardt method for solving inverse modeling problems with a highly parameterized model space. Levenberg-Marquardt methods require the solution of a linear system of equations which can be prohibitively expensive to compute for moderate to large-scale problems. Our novel method projects the original linear problem down to a Krylov subspace, such that the dimensionality of themore » problem can be significantly reduced. Furthermore, we store the Krylov subspace computed when using the first damping parameter and recycle the subspace for the subsequent damping parameters. The efficiency of our new inverse modeling algorithm is significantly improved using these computational techniques. We apply this new inverse modeling method to invert for random transmissivity fields in 2D and a random hydraulic conductivity field in 3D. Our algorithm is fast enough to solve for the distributed model parameters (transmissivity) in the model domain. The algorithm is coded in Julia and implemented in the MADS computational framework (http://mads.lanl.gov). By comparing with Levenberg-Marquardt methods using standard linear inversion techniques such as QR or SVD methods, our Levenberg-Marquardt method yields a speed-up ratio on the order of ~10 1 to ~10 2 in a multi-core computational environment. Furthermore, our new inverse modeling method is a powerful tool for characterizing subsurface heterogeneity for moderate- to large-scale problems.« less

Elastic-Waveform Inversion with Compressive Sensing for Sparse Seismic Data

DOE Office of Scientific and Technical Information (OSTI.GOV)

Lin, Youzuo; Huang, Lianjie

2015-01-28

Accurate velocity models of compressional- and shear-waves are essential for geothermal reservoir characterization and microseismic imaging. Elastic-waveform inversion of multi-component seismic data can provide high-resolution inversion results of subsurface geophysical properties. However, the method requires seismic data acquired using dense source and receiver arrays. In practice, seismic sources and/or geophones are often sparsely distributed on the surface and/or in a borehole, such as 3D vertical seismic profiling (VSP) surveys. We develop a novel elastic-waveform inversion method with compressive sensing for inversion of sparse seismic data. We employ an alternating-minimization algorithm to solve the optimization problem of our new waveform inversionmore » method. We validate our new method using synthetic VSP data for a geophysical model built using geologic features found at the Raft River enhanced-geothermal-system (EGS) field. We apply our method to synthetic VSP data with a sparse source array and compare the results with those obtained with a dense source array. Our numerical results demonstrate that the velocity models produced with our new method using a sparse source array are almost as accurate as those obtained using a dense source array.« less

On the calibration process of film dosimetry: OLS inverse regression versus WLS inverse prediction.

PubMed

Crop, F; Van Rompaye, B; Paelinck, L; Vakaet, L; Thierens, H; De Wagter, C

2008-07-21

The purpose of this study was both putting forward a statistically correct model for film calibration and the optimization of this process. A reliable calibration is needed in order to perform accurate reference dosimetry with radiographic (Gafchromic) film. Sometimes, an ordinary least squares simple linear (in the parameters) regression is applied to the dose-optical-density (OD) curve with the dose as a function of OD (inverse regression) or sometimes OD as a function of dose (inverse prediction). The application of a simple linear regression fit is an invalid method because heteroscedasticity of the data is not taken into account. This could lead to erroneous results originating from the calibration process itself and thus to a lower accuracy. In this work, we compare the ordinary least squares (OLS) inverse regression method with the correct weighted least squares (WLS) inverse prediction method to create calibration curves. We found that the OLS inverse regression method could lead to a prediction bias of up to 7.3 cGy at 300 cGy and total prediction errors of 3% or more for Gafchromic EBT film. Application of the WLS inverse prediction method resulted in a maximum prediction bias of 1.4 cGy and total prediction errors below 2% in a 0-400 cGy range. We developed a Monte-Carlo-based process to optimize calibrations, depending on the needs of the experiment. This type of thorough analysis can lead to a higher accuracy for film dosimetry.

Quantifying Uncertainty in Near Surface Electromagnetic Imaging Using Bayesian Methods

NASA Astrophysics Data System (ADS)

Blatter, D. B.; Ray, A.; Key, K.

2017-12-01

Geoscientists commonly use electromagnetic methods to image the Earth's near surface. Field measurements of EM fields are made (often with the aid an artificial EM source) and then used to infer near surface electrical conductivity via a process known as inversion. In geophysics, the standard inversion tool kit is robust and can provide an estimate of the Earth's near surface conductivity that is both geologically reasonable and compatible with the measured field data. However, standard inverse methods struggle to provide a sense of the uncertainty in the estimate they provide. This is because the task of finding an Earth model that explains the data to within measurement error is non-unique - that is, there are many, many such models; but the standard methods provide only one "answer." An alternative method, known as Bayesian inversion, seeks to explore the full range of Earth model parameters that can adequately explain the measured data, rather than attempting to find a single, "ideal" model. Bayesian inverse methods can therefore provide a quantitative assessment of the uncertainty inherent in trying to infer near surface conductivity from noisy, measured field data. This study applies a Bayesian inverse method (called trans-dimensional Markov chain Monte Carlo) to transient airborne EM data previously collected over Taylor Valley - one of the McMurdo Dry Valleys in Antarctica. Our results confirm the reasonableness of previous estimates (made using standard methods) of near surface conductivity beneath Taylor Valley. In addition, we demonstrate quantitatively the uncertainty associated with those estimates. We demonstrate that Bayesian inverse methods can provide quantitative uncertainty to estimates of near surface conductivity.

A Computationally Efficient Parallel Levenberg-Marquardt Algorithm for Large-Scale Big-Data Inversion

NASA Astrophysics Data System (ADS)

Lin, Y.; O'Malley, D.; Vesselinov, V. V.

2015-12-01

Inverse modeling seeks model parameters given a set of observed state variables. However, for many practical problems due to the facts that the observed data sets are often large and model parameters are often numerous, conventional methods for solving the inverse modeling can be computationally expensive. We have developed a new, computationally-efficient Levenberg-Marquardt method for solving large-scale inverse modeling. Levenberg-Marquardt methods require the solution of a dense linear system of equations which can be prohibitively expensive to compute for large-scale inverse problems. Our novel method projects the original large-scale linear problem down to a Krylov subspace, such that the dimensionality of the measurements can be significantly reduced. Furthermore, instead of solving the linear system for every Levenberg-Marquardt damping parameter, we store the Krylov subspace computed when solving the first damping parameter and recycle it for all the following damping parameters. The efficiency of our new inverse modeling algorithm is significantly improved by using these computational techniques. We apply this new inverse modeling method to invert for a random transitivity field. Our algorithm is fast enough to solve for the distributed model parameters (transitivity) at each computational node in the model domain. The inversion is also aided by the use regularization techniques. The algorithm is coded in Julia and implemented in the MADS computational framework (http://mads.lanl.gov). Julia is an advanced high-level scientific programing language that allows for efficient memory management and utilization of high-performance computational resources. By comparing with a Levenberg-Marquardt method using standard linear inversion techniques, our Levenberg-Marquardt method yields speed-up ratio of 15 in a multi-core computational environment and a speed-up ratio of 45 in a single-core computational environment. Therefore, our new inverse modeling method is a powerful tool for large-scale applications.

Fast Nonlinear Generalized Inversion of Gravity Data with Application to the Three-Dimensional Crustal Density Structure of Sichuan Basin, Southwest China

NASA Astrophysics Data System (ADS)

Wang, Jun; Meng, Xiaohong; Li, Fang

2017-11-01

Generalized inversion is one of the important steps in the quantitative interpretation of gravity data. With appropriate algorithm and parameters, it gives a view of the subsurface which characterizes different geological bodies. However, generalized inversion of gravity data is time consuming due to the large amount of data points and model cells adopted. Incorporating of various prior information as constraints deteriorates the above situation. In the work discussed in this paper, a method for fast nonlinear generalized inversion of gravity data is proposed. The fast multipole method is employed for forward modelling. The inversion objective function is established with weighted data misfit function along with model objective function. The total objective function is solved by a dataspace algorithm. Moreover, depth weighing factor is used to improve depth resolution of the result, and bound constraint is incorporated by a transfer function to limit the model parameters in a reliable range. The matrix inversion is accomplished by a preconditioned conjugate gradient method. With the above algorithm, equivalent density vectors can be obtained, and interpolation is performed to get the finally density model on the fine mesh in the model domain. Testing on synthetic gravity data demonstrated that the proposed method is faster than conventional generalized inversion algorithm to produce an acceptable solution for gravity inversion problem. The new developed inversion method was also applied for inversion of the gravity data collected over Sichuan basin, southwest China. The established density structure in this study helps understanding the crustal structure of Sichuan basin and provides reference for further oil and gas exploration in this area.

Separating inverse spin Hall voltage and spin rectification voltage by inverting spin injection direction

NASA Astrophysics Data System (ADS)

Zhang, Wenxu; Peng, Bin; Han, Fangbin; Wang, Qiuru; Soh, Wee Tee; Ong, Chong Kim; Zhang, Wanli

2016-03-01

We develop a method for universally resolving the important issue of separating the inverse spin Hall effect (ISHE) from the spin rectification effect (SRE) signal. This method is based on the consideration that the two effects depend on the spin injection direction: The ISHE is an odd function of the spin injection direction while the SRE is independent on it. Thus, the inversion of the spin injection direction changes the ISHE voltage signal, while the SRE voltage remains. It applies generally to analyzing the different voltage contributions without fitting them to special line shapes. This fast and simple method can be used in a wide frequency range and has the flexibility of sample preparation.

Full-Physics Inverse Learning Machine for Satellite Remote Sensing Retrievals

NASA Astrophysics Data System (ADS)

Loyola, D. G.

2017-12-01

The satellite remote sensing retrievals are usually ill-posed inverse problems that are typically solved by finding a state vector that minimizes the residual between simulated data and real measurements. The classical inversion methods are very time-consuming as they require iterative calls to complex radiative-transfer forward models to simulate radiances and Jacobians, and subsequent inversion of relatively large matrices. In this work we present a novel and extremely fast algorithm for solving inverse problems called full-physics inverse learning machine (FP-ILM). The FP-ILM algorithm consists of a training phase in which machine learning techniques are used to derive an inversion operator based on synthetic data generated using a radiative transfer model (which expresses the "full-physics" component) and the smart sampling technique, and an operational phase in which the inversion operator is applied to real measurements. FP-ILM has been successfully applied to the retrieval of the SO2 plume height during volcanic eruptions and to the retrieval of ozone profile shapes from UV/VIS satellite sensors. Furthermore, FP-ILM will be used for the near-real-time processing of the upcoming generation of European Sentinel sensors with their unprecedented spectral and spatial resolution and associated large increases in the amount of data.

Strategies to Enhance the Model Update in Regions of Weak Sensitivities for Use in Full Waveform Inversion

NASA Astrophysics Data System (ADS)

Nuber, André; Manukyan, Edgar; Maurer, Hansruedi

2014-05-01

Conventional methods of interpreting seismic data rely on filtering and processing limited portions of the recorded wavefield. Typically, either reflections, refractions or surface waves are considered in isolation. Particularly in near-surface engineering and environmental investigations (depths less than, say 100 m), these wave types often overlap in time and are difficult to separate. Full waveform inversion is a technique that seeks to exploit and interpret the full information content of the seismic records without the need for separating events first; it yields models of the subsurface at sub-wavelength resolution. We use a finite element modelling code to solve the 2D elastic isotropic wave equation in the frequency domain. This code is part of a Gauss-Newton inversion scheme which we employ to invert for the P- and S-wave velocities as well as for density in the subsurface. For shallow surface data the use of an elastic forward solver is essential because surface waves often dominate the seismograms. This leads to high sensitivities (partial derivatives contained in the Jacobian matrix of the Gauss-Newton inversion scheme) and thus large model updates close to the surface. Reflections from deeper structures may also include useful information, but the large sensitivities of the surface waves often preclude this information from being fully exploited. We have developed two methods that balance the sensitivity distributions and thus may help resolve the deeper structures. The first method includes equilibrating the columns of the Jacobian matrix prior to every inversion step by multiplying them with individual scaling factors. This is expected to also balance the model updates throughout the entire subsurface model. It can be shown that this procedure is mathematically equivalent to balancing the regularization weights of the individual model parameters. A proper choice of the scaling factors required to balance the Jacobian matrix is critical. We decided to normalise the columns of the Jacobian based on their absolute column sum, but defining an upper threshold for the scaling factors. This avoids particularly small and therefore insignificant sensitivities being over-boosted, which would produce unstable results. The second method proposed includes adjusting the inversion cell size with depth. Multiple cells of the forward modelling grid are merged to form larger inversion cells (typical ratios between forward and inversion cells are in the order of 1:100). The irregular inversion grid is adapted to the expected resolution power of full waveform inversion. Besides stabilizing the inversion, this approach also reduces the number of model parameters to be recovered. Consequently, the computational costs and the memory consumption are reduced significantly. This is particularly critical when Gauss-Newton type inversion schemes are employed. Extensive tests with synthetic data demonstrated that both methods stabilise the inversion and improve the inversion results. The two methods have some redundancy, which can be seen when both are applied simultaneously, that is, when scaling of the Jacobian matrix is applied to an irregular inversion grid. The calculated scaling factors are quite balanced and span a much smaller range than in the case of a regular inversion grid.

A new optimization method using a compressed sensing inspired solver for real-time LDR-brachytherapy treatment planning

NASA Astrophysics Data System (ADS)

Guthier, C.; Aschenbrenner, K. P.; Buergy, D.; Ehmann, M.; Wenz, F.; Hesser, J. W.

2015-03-01

This work discusses a novel strategy for inverse planning in low dose rate brachytherapy. It applies the idea of compressed sensing to the problem of inverse treatment planning and a new solver for this formulation is developed. An inverse planning algorithm was developed incorporating brachytherapy dose calculation methods as recommended by AAPM TG-43. For optimization of the functional a new variant of a matching pursuit type solver is presented. The results are compared with current state-of-the-art inverse treatment planning algorithms by means of real prostate cancer patient data. The novel strategy outperforms the best state-of-the-art methods in speed, while achieving comparable quality. It is able to find solutions with comparable values for the objective function and it achieves these results within a few microseconds, being up to 542 times faster than competing state-of-the-art strategies, allowing real-time treatment planning. The sparse solution of inverse brachytherapy planning achieved with methods from compressed sensing is a new paradigm for optimization in medical physics. Through the sparsity of required needles and seeds identified by this method, the cost of intervention may be reduced.

A new optimization method using a compressed sensing inspired solver for real-time LDR-brachytherapy treatment planning.

PubMed

Guthier, C; Aschenbrenner, K P; Buergy, D; Ehmann, M; Wenz, F; Hesser, J W

2015-03-21

This work discusses a novel strategy for inverse planning in low dose rate brachytherapy. It applies the idea of compressed sensing to the problem of inverse treatment planning and a new solver for this formulation is developed. An inverse planning algorithm was developed incorporating brachytherapy dose calculation methods as recommended by AAPM TG-43. For optimization of the functional a new variant of a matching pursuit type solver is presented. The results are compared with current state-of-the-art inverse treatment planning algorithms by means of real prostate cancer patient data. The novel strategy outperforms the best state-of-the-art methods in speed, while achieving comparable quality. It is able to find solutions with comparable values for the objective function and it achieves these results within a few microseconds, being up to 542 times faster than competing state-of-the-art strategies, allowing real-time treatment planning. The sparse solution of inverse brachytherapy planning achieved with methods from compressed sensing is a new paradigm for optimization in medical physics. Through the sparsity of required needles and seeds identified by this method, the cost of intervention may be reduced.

Detection of Natural Fractures from Observed Surface Seismic Data Based on a Linear-Slip Model

NASA Astrophysics Data System (ADS)

Chen, Huaizhen; Zhang, Guangzhi

2018-03-01

Natural fractures play an important role in migration of hydrocarbon fluids. Based on a rock physics effective model, the linear-slip model, which defines fracture parameters (fracture compliances) for quantitatively characterizing the effects of fractures on rock total compliance, we propose a method to detect natural fractures from observed seismic data via inversion for the fracture compliances. We first derive an approximate PP-wave reflection coefficient in terms of fracture compliances. Using the approximate reflection coefficient, we derive azimuthal elastic impedance as a function of fracture compliances. An inversion method to estimate fracture compliances from seismic data is presented based on a Bayesian framework and azimuthal elastic impedance, which is implemented in a two-step procedure: a least-squares inversion for azimuthal elastic impedance and an iterative inversion for fracture compliances. We apply the inversion method to synthetic and real data to verify its stability and reasonability. Synthetic tests confirm that the method can make a stable estimation of fracture compliances in the case of seismic data containing a moderate signal-to-noise ratio for Gaussian noise, and the test on real data reveals that reasonable fracture compliances are obtained using the proposed method.

Inversion-based propofol dosing for intravenous induction of hypnosis

NASA Astrophysics Data System (ADS)

Padula, F.; Ionescu, C.; Latronico, N.; Paltenghi, M.; Visioli, A.; Vivacqua, G.

2016-10-01

In this paper we propose an inversion-based methodology for the computation of a feedforward action for the propofol intravenous administration during the induction of hypnosis in general anesthesia. In particular, the typical initial bolus is substituted with a command signal that is obtained by predefining a desired output and by applying an input-output inversion procedure. The robustness of the method has been tested by considering a set of patients with different model parameters, which is representative of a large population.

Inverse kinematics problem in robotics using neural networks

NASA Technical Reports Server (NTRS)

Choi, Benjamin B.; Lawrence, Charles

1992-01-01

In this paper, Multilayer Feedforward Networks are applied to the robot inverse kinematic problem. The networks are trained with endeffector position and joint angles. After training, performance is measured by having the network generate joint angles for arbitrary endeffector trajectories. A 3-degree-of-freedom (DOF) spatial manipulator is used for the study. It is found that neural networks provide a simple and effective way to both model the manipulator inverse kinematics and circumvent the problems associated with algorithmic solution methods.

2.5D transient electromagnetic inversion with OCCAM method

NASA Astrophysics Data System (ADS)

Li, R.; Hu, X.

2016-12-01

In the application of time-domain electromagnetic method (TEM), some multidimensional inversion schemes are applied for imaging in the past few decades to overcome great error produced by 1D model inversion when the subsurface structure is complex. The current mainstream multidimensional inversion for EM data, with the finite-difference time-domain (FDTD) forward method, mainly implemented by Nonlinear Conjugate Gradient (NLCG). But the convergence rate of NLCG heavily depends on Lagrange multiplier and maybe fail to converge. We use the OCCAM inversion method to avoid the weakness. OCCAM inversion is proven to be a more stable and reliable method to image the subsurface 2.5D electrical conductivity. Firstly, we simulate the 3D transient EM fields governed by Maxwell's equations with FDTD method. Secondly, we use the OCCAM inversion scheme with the appropriate objective error functional we established to image the 2.5D structure. And the data space OCCAM's inversion (DASOCC) strategy based on OCCAM scheme were given in this paper. The sensitivity matrix is calculated with the method of time-integrated back-propagated fields. Imaging result of example model shown in Fig. 1 have proven that the OCCAM scheme is an efficient inversion method for TEM with FDTD method. The processes of the inversion iterations have shown the great ability of convergence with few iterations. Summarizing the process of the imaging, we can make the following conclusions. Firstly, the 2.5D imaging in FDTD system with OCCAM inversion demonstrates that we could get desired imaging results for the resistivity structure in the homogeneous half-space. Secondly, the imaging results usually do not over-depend on the initial model, but the iteration times can be reduced distinctly if the background resistivity of initial model get close to the truthful model. So it is batter to set the initial model based on the other geologic information in the application. When the background resistivity fit the truthful model well, the imaging of anomalous body only need a few iteration steps. Finally, the speed of imaging vertical boundaries is slower than the speed of imaging the horizontal boundaries.

Eruption mass estimation using infrasound waveform inversion and ash and gas measurements: Evaluation at Sakurajima Volcano, Japan

NASA Astrophysics Data System (ADS)

Fee, David; Izbekov, Pavel; Kim, Keehoon; Yokoo, Akihiko; Lopez, Taryn; Prata, Fred; Kazahaya, Ryunosuke; Nakamichi, Haruhisa; Iguchi, Masato

2017-12-01

Eruption mass and mass flow rate are critical parameters for determining the aerial extent and hazard of volcanic emissions. Infrasound waveform inversion is a promising technique to quantify volcanic emissions. Although topography may substantially alter the infrasound waveform as it propagates, advances in wave propagation modeling and station coverage permit robust inversion of infrasound data from volcanic explosions. The inversion can estimate eruption mass flow rate and total eruption mass if the flow density is known. However, infrasound-based eruption flow rates and mass estimates have yet to be validated against independent measurements, and numerical modeling has only recently been applied to the inversion technique. Here we present a robust full-waveform acoustic inversion method, and use it to calculate eruption flow rates and masses from 49 explosions from Sakurajima Volcano, Japan. Six infrasound stations deployed from 12-20 February 2015 recorded the explosions. We compute numerical Green's functions using 3-D Finite Difference Time Domain modeling and a high-resolution digital elevation model. The inversion, assuming a simple acoustic monopole source, provides realistic eruption masses and excellent fit to the data for the majority of the explosions. The inversion results are compared to independent eruption masses derived from ground-based ash collection and volcanic gas measurements. Assuming realistic flow densities, our infrasound-derived eruption masses for ash-rich eruptions compare favorably to the ground-based estimates, with agreement ranging from within a factor of two to one order of magnitude. Uncertainties in the time-dependent flow density and acoustic propagation likely contribute to the mismatch between the methods. Our results suggest that realistic and accurate infrasound-based eruption mass and mass flow rate estimates can be computed using the method employed here. If accurate volcanic flow parameters are known, application of this technique could be broadly applied to enable near real-time calculation of eruption mass flow rates and total masses. These critical input parameters for volcanic eruption modeling and monitoring are not currently available.

Absolute calibration of the mass scale in the inverse problem of the physical theory of fireballs

NASA Astrophysics Data System (ADS)

Kalenichenko, V. V.

1992-08-01

A method of the absolute calibration of the mass scale is proposed for solving the inverse problem of the physical theory of fireballs. The method is based on data on the masses of fallen meteorites whose fireballs have been photographed in flight. The method can be applied to fireballs whose bodies have not experienced significant fragmentation during their flight in the atmosphere and have kept their shape relatively well. Data on the Lost City and Innisfree meteorites are used to calculate the calibration coefficients.

Simulating contrast inversion in atomic force microscopy imaging with real-space pseudopotentials

NASA Astrophysics Data System (ADS)

Lee, Alex; Sakai, Yuki; Chelikowsky, James

Atomic force microscopy measurements have reported contrast inversions for systems such as Cu2N and graphene that can hamper image interpretation and characterization. Here, we apply a simulation method based on ab initio real-space pseudopotentials to gain an understanding of the tip-sample interactions that influence the inversion. We find that chemically reactive tips induce an attractive binding force that results in the contrast inversion. The inversion is tip height dependent and not observed when using less reactive CO-functionalized tips. Work is supported by the DOE under DOE/DE-FG02-06ER46286 and by the Welch Foundation under Grant F-1837. Computational resources were provided by NERSC and XSEDE.

Reconstruction of local perturbations in periodic surfaces

NASA Astrophysics Data System (ADS)

Lechleiter, Armin; Zhang, Ruming

2018-03-01

This paper concerns the inverse scattering problem to reconstruct a local perturbation in a periodic structure. Unlike the periodic problems, the periodicity for the scattered field no longer holds, thus classical methods, which reduce quasi-periodic fields in one periodic cell, are no longer available. Based on the Floquet-Bloch transform, a numerical method has been developed to solve the direct problem, that leads to a possibility to design an algorithm for the inverse problem. The numerical method introduced in this paper contains two steps. The first step is initialization, that is to locate the support of the perturbation by a simple method. This step reduces the inverse problem in an infinite domain into one periodic cell. The second step is to apply the Newton-CG method to solve the associated optimization problem. The perturbation is then approximated by a finite spline basis. Numerical examples are given at the end of this paper, showing the efficiency of the numerical method.

Applications of the JARS method to study levee sites in southern Texas and southern New Mexico

USGS Publications Warehouse

Ivanov, J.; Miller, R.D.; Xia, J.; Dunbar, J.B.

2007-01-01

We apply the joint analysis of refractions with surface waves (JARS) method to several sites and compare its results to traditional refraction-tomography methods in efforts of finding a more realistic solution to the inverse refraction-traveltime problem. The JARS method uses a reference model, derived from surface-wave shear-wave velocity estimates, as a constraint. In all of the cases JARS estimates appear more realistic than those from the conventional refraction-tomography methods. As a result, we consider, the JARS algorithm as the preferred method for finding solutions to the inverse refraction-tomography problems. ?? 2007 Society of Exploration Geophysicists.

Group-theoretic models of the inversion process in bacterial genomes.

PubMed

Egri-Nagy, Attila; Gebhardt, Volker; Tanaka, Mark M; Francis, Andrew R

2014-07-01

The variation in genome arrangements among bacterial taxa is largely due to the process of inversion. Recent studies indicate that not all inversions are equally probable, suggesting, for instance, that shorter inversions are more frequent than longer, and those that move the terminus of replication are less probable than those that do not. Current methods for establishing the inversion distance between two bacterial genomes are unable to incorporate such information. In this paper we suggest a group-theoretic framework that in principle can take these constraints into account. In particular, we show that by lifting the problem from circular permutations to the affine symmetric group, the inversion distance can be found in polynomial time for a model in which inversions are restricted to acting on two regions. This requires the proof of new results in group theory, and suggests a vein of new combinatorial problems concerning permutation groups on which group theorists will be needed to collaborate with biologists. We apply the new method to inferring distances and phylogenies for published Yersinia pestis data.

Angle-domain inverse scattering migration/inversion in isotropic media

NASA Astrophysics Data System (ADS)

Li, Wuqun; Mao, Weijian; Li, Xuelei; Ouyang, Wei; Liang, Quan

2018-07-01

The classical seismic asymptotic inversion can be transformed into a problem of inversion of generalized Radon transform (GRT). In such methods, the combined parameters are linearly attached to the scattered wave-field by Born approximation and recovered by applying an inverse GRT operator to the scattered wave-field data. Typical GRT-style true-amplitude inversion procedure contains an amplitude compensation process after the weighted migration via dividing an illumination associated matrix whose elements are integrals of scattering angles. It is intuitional to some extent that performs the generalized linear inversion and the inversion of GRT together by this process for direct inversion. However, it is imprecise to carry out such operation when the illumination at the image point is limited, which easily leads to the inaccuracy and instability of the matrix. This paper formulates the GRT true-amplitude inversion framework in an angle-domain version, which naturally degrades the external integral term related to the illumination in the conventional case. We solve the linearized integral equation for combined parameters of different fixed scattering angle values. With this step, we obtain high-quality angle-domain common-image gathers (CIGs) in the migration loop which provide correct amplitude-versus-angle (AVA) behavior and reasonable illumination range for subsurface image points. Then we deal with the over-determined problem to solve each parameter in the combination by a standard optimization operation. The angle-domain GRT inversion method keeps away from calculating the inaccurate and unstable illumination matrix. Compared with the conventional method, the angle-domain method can obtain more accurate amplitude information and wider amplitude-preserved range. Several model tests demonstrate the effectiveness and practicability.

Accuracy improvement in measurement of arterial wall elasticity by applying pulse inversion to phased-tracking method

NASA Astrophysics Data System (ADS)

Miyachi, Yukiya; Arakawa, Mototaka; Kanai, Hiroshi

2018-07-01

In our studies on ultrasonic elasticity assessment, minute change in the thickness of the arterial wall was measured by the phased-tracking method. However, most images in carotid artery examinations contain multiple-reflection noise, making it difficult to evaluate arterial wall elasticity precisely. In the present study, a modified phased-tracking method using the pulse inversion method was examined to reduce the influence of the multiple-reflection noise. Moreover, aliasing in the harmonic components was corrected by the fundamental components. The conventional and proposed methods were applied to a pulsated tube phantom mimicking the arterial wall. For the conventional method, the elasticity was 298 kPa without multiple-reflection noise and 353 kPa with multiple-reflection noise on the posterior wall. That of the proposed method was 302 kPa without multiple-reflection noise and 297 kPa with multiple-reflection noise on the posterior wall. Therefore, the proposed method was very robust against multiple-reflection noise.

A stress-constrained geodetic inversion method for spatiotemporal slip of a slow slip event with earthquake swarm

NASA Astrophysics Data System (ADS)

Hirose, H.; Tanaka, T.

2017-12-01

Geodetic inversions have been performed by using GNSS data and/or tiltmeter data in order to estimate spatio-temporal fault slip distributions. They have been applied for slow slip events (SSEs), which are episodic fault slip lasting for days to years (e.g., Ozawa et al., 2001; Hirose et al., 2014). Although their slip distributions are important information in terms of inferring strain budget and frictional characteristics on a subduction plate interface, inhomogeneous station coverage generally yields spatially non-uniform slip resolution, and in a worse case, a slip distribution can not be recovered. It is known that an SSE which accompanies an earthquake swarm around the SSE slip area, such as the Boso Peninsula SSEs (e.g., Hirose et al., 2014). Some researchers hypothesize that these earthquakes are triggered by a stress change caused by the accompanying SSE (e.g., Segall et al., 2006). Based on this assumption, it is possible that a conventional geodetic inversion which impose a constraint on the stress change that promotes earthquake activities may improve the resolution of the slip distribution. Here we develop an inversion method based on the Network Inversion Filter technique (Segall and Matthews, 1997), incorporating a constraint on a positive change in Coulomb failure stress (Delta-CFS) at the accompanied earthquakes. In addition, we apply this new method to synthetic data in order to check the effectiveness of the method and the characteristics of the inverted slip distributions. The results show that there is a case in which the reproduction of a slip distribution is better with earthquake information than without it. That is, it is possible to improve the reproducibility of a slip distribution of an SSE with this new inversion method if an earthquake catalog for the accompanying earthquake activity can be used when available geodetic data are insufficient.

Analysing 21cm signal with artificial neural network

NASA Astrophysics Data System (ADS)

Shimabukuro, Hayato; a Semelin, Benoit

2018-05-01

The 21cm signal at epoch of reionization (EoR) should be observed within next decade. We expect that cosmic 21cm signal at the EoR provides us both cosmological and astrophysical information. In order to extract fruitful information from observation data, we need to develop inversion method. For such a method, we introduce artificial neural network (ANN) which is one of the machine learning techniques. We apply the ANN to inversion problem to constrain astrophysical parameters from 21cm power spectrum. We train the architecture of the neural network with 70 training datasets and apply it to 54 test datasets with different value of parameters. We find that the quality of the parameter reconstruction depends on the sensitivity of the power spectrum to the different parameter sets at a given redshift and also find that the accuracy of reconstruction is improved by increasing the number of given redshifts. We conclude that the ANN is viable inversion method whose main strength is that they require a sparse extrapolation of the parameter space and thus should be usable with full simulation.

Tracing of paleo-shear zones by self-potential data inversion: case studies from the KTB, Rittsteig, and Grossensees graphite-bearing fault planes

NASA Astrophysics Data System (ADS)

Mehanee, Salah A.

2015-01-01

This paper describes a new method for tracing paleo-shear zones of the continental crust by self-potential (SP) data inversion. The method falls within the deterministic inversion framework, and it is exclusively applicable for the interpretation of the SP anomalies measured along a profile over sheet-type structures such as conductive thin films of interconnected graphite precipitations formed on shear planes. The inverse method fits a residual SP anomaly by a single thin sheet and recovers the characteristic parameters (depth to the top h, extension in depth a, amplitude coefficient k, and amount and direction of dip θ) of the sheet. This method minimizes an objective functional in the space of the logarithmed and non-logarithmed model parameters (log( h), log( a), log( k), and θ) successively by the steepest descent (SD) and Gauss-Newton (GN) techniques in order to essentially maintain the stability and convergence of this inverse method. Prior to applying the method to real data, its accuracy, convergence, and stability are successfully verified on numerical examples with and without noise. The method is then applied to SP profiles from the German Continental Deep Drilling Program (Kontinentales Tiefbohrprogramm der Bundesrepublik Deutschla - KTB), Rittsteig, and Grossensees sites in Germany for tracing paleo-shear planes coated with graphitic deposits. The comparisons of geologic sections constructed in this paper (based on the proposed deterministic approach) against the existing published interpretations (obtained based on trial-and-error modeling) for the SP data of the KTB and Rittsteig sites have revealed that the deterministic approach suggests some new details that are of some geological significance. The findings of the proposed inverse scheme are supported by available drilling and other geophysical data. Furthermore, the real SP data of the Grossensees site have been interpreted (apparently for the first time ever) by the deterministic inverse scheme from which interpretive geologic cross sections are suggested. The computational efficiency, analysis of the numerical examples investigated, and comparisons of the real data inverted here have demonstrated that the developed deterministic approach is advantageous to the existing interpretation methods, and it is suitable for meaningful interpretation of SP data acquired elsewhere over graphitic occurrences on fault planes.

Extracting Low-Frequency Information from Time Attenuation in Elastic Waveform Inversion

NASA Astrophysics Data System (ADS)

Guo, Xuebao; Liu, Hong; Shi, Ying; Wang, Weihong

2017-03-01

Low-frequency information is crucial for recovering background velocity, but the lack of low-frequency information in field data makes inversion impractical without accurate initial models. Laplace-Fourier domain waveform inversion can recover a smooth model from real data without low-frequency information, which can be used for subsequent inversion as an ideal starting model. In general, it also starts with low frequencies and includes higher frequencies at later inversion stages, while the difference is that its ultralow frequency information comes from the Laplace-Fourier domain. Meanwhile, a direct implementation of the Laplace-transformed wavefield using frequency domain inversion is also very convenient. However, because broad frequency bands are often used in the pure time domain waveform inversion, it is difficult to extract the wavefields dominated by low frequencies in this case. In this paper, low-frequency components are constructed by introducing time attenuation into the recorded residuals, and the rest of the method is identical to the traditional time domain inversion. Time windowing and frequency filtering are also applied to mitigate the ambiguity of the inverse problem. Therefore, we can start at low frequencies and to move to higher frequencies. The experiment shows that the proposed method can achieve a good inversion result in the presence of a linear initial model and records without low-frequency information.

Integration of Electrical Resistivity and Seismic Refraction using Combine Inversion for Detecting Material Deposits of Impact Crater at Bukit Bunuh, Lenggong, Perak

NASA Astrophysics Data System (ADS)

Yusoh, R.; Saad, R.; Saidin, M.; Muhammad, S. B.; Anda, S. T.

2018-04-01

Both electrical resistivity and seismic refraction profiling has become a common method in pre-investigations for visualizing subsurface structure. The encouragement to use these methods is that combined of both methods can decrease the obscure inherent to the distinctive use of these methods. Both method have their individual software packages for data inversion, but potential to combine certain geophysical methods are restricted; however, the research algorithms that have this functionality was exists and are evaluated personally. The interpretation of subsurface were improve by combining inversion data from both method by influence each other models using closure coupling; thus, by implementing both methods to support each other which could improve the subsurface interpretation. These methods were applied on a field dataset from a pre-investigation for archeology in finding the material deposits of impact crater. There were no major changes in the inverted model by combining data inversion for this archetype which probably due to complex geology. The combine data analysis shows the deposit material start from ground surface to 20 meter depth which the class separation clearly separate the deposit material.

Lithological and Surface Geometry Joint Inversions Using Multi-Objective Global Optimization Methods

NASA Astrophysics Data System (ADS)

Lelièvre, Peter; Bijani, Rodrigo; Farquharson, Colin

2016-04-01

Geologists' interpretations about the Earth typically involve distinct rock units with contacts (interfaces) between them. In contrast, standard minimum-structure geophysical inversions are performed on meshes of space-filling cells (typically prisms or tetrahedra) and recover smoothly varying physical property distributions that are inconsistent with typical geological interpretations. There are several approaches through which mesh-based minimum-structure geophysical inversion can help recover models with some of the desired characteristics. However, a more effective strategy may be to consider two fundamentally different types of inversions: lithological and surface geometry inversions. A major advantage of these two inversion approaches is that joint inversion of multiple types of geophysical data is greatly simplified. In a lithological inversion, the subsurface is discretized into a mesh and each cell contains a particular rock type. A lithological model must be translated to a physical property model before geophysical data simulation. Each lithology may map to discrete property values or there may be some a priori probability density function associated with the mapping. Through this mapping, lithological inverse problems limit the parameter domain and consequently reduce the non-uniqueness from that presented by standard mesh-based inversions that allow physical property values on continuous ranges. Furthermore, joint inversion is greatly simplified because no additional mathematical coupling measure is required in the objective function to link multiple physical property models. In a surface geometry inversion, the model comprises wireframe surfaces representing contacts between rock units. This parameterization is then fully consistent with Earth models built by geologists, which in 3D typically comprise wireframe contact surfaces of tessellated triangles. As for the lithological case, the physical properties of the units lying between the contact surfaces are set to a priori values. The inversion is tasked with calculating the geometry of the contact surfaces instead of some piecewise distribution of properties in a mesh. Again, no coupling measure is required and joint inversion is simplified. Both of these inverse problems involve high nonlinearity and discontinuous or non-obtainable derivatives. They can also involve the existence of multiple minima. Hence, one can not apply the standard descent-based local minimization methods used to solve typical minimum-structure inversions. Instead, we are applying Pareto multi-objective global optimization (PMOGO) methods, which generate a suite of solutions that minimize multiple objectives (e.g. data misfits and regularization terms) in a Pareto-optimal sense. Providing a suite of models, as opposed to a single model that minimizes a weighted sum of objectives, allows a more complete assessment of the possibilities and avoids the often difficult choice of how to weight each objective. While there are definite advantages to PMOGO joint inversion approaches, the methods come with significantly increased computational requirements. We are researching various strategies to ameliorate these computational issues including parallelization and problem dimension reduction.

Regularization of soft-X-ray imaging in the DIII-D tokamak

DOE PAGES

Wingen, A.; Shafer, M. W.; Unterberg, E. A.; ...

2015-03-02

We developed an image inversion scheme for the soft X-ray imaging system (SXRIS) diagnostic at the DIII-D tokamak in order to obtain the local soft X-ray emission at a poloidal cross-section from the spatially line-integrated image taken by the SXRIS camera. The scheme uses the Tikhonov regularization method since the inversion problem is generally ill-posed. The regularization technique uses the generalized singular value decomposition to determine a solution that depends on a free regularization parameter. The latter has to be chosen carefully, and the so called {\\it L-curve} method to find the optimum regularization parameter is outlined. A representative testmore » image is used to study the properties of the inversion scheme with respect to inversion accuracy, amount/strength of regularization, image noise and image resolution. Moreover, the optimum inversion parameters are identified, while the L-curve method successfully computes the optimum regularization parameter. Noise is found to be the most limiting issue, but sufficient regularization is still possible at noise to signal ratios up to 10%-15%. Finally, the inversion scheme is applied to measured SXRIS data and the line-integrated SXRIS image is successfully inverted.« less

The Effect of Flow Velocity on Waveform Inversion

NASA Astrophysics Data System (ADS)

Lee, D.; Shin, S.; Chung, W.; Ha, J.; Lim, Y.; Kim, S.

2017-12-01

The waveform inversion is a velocity modeling technique that reconstructs accurate subsurface physical properties. Therefore, using the model in its final, updated version, we generated data identical to modeled data. Flow velocity, like several other factors, affects observed data in seismic exploration. Despite this, there is insufficient research on its relationship with waveform inversion. In this study, the generated synthetic data considering flow velocity was factored in waveform inversion and the influence of flow velocity in waveform inversion was analyzed. Measuring the flow velocity generally requires additional equipment. However, for situations where only seismic data was available, flow velocity was calculated by fixed-point iteration method using direct wave in observed data. Further, a new waveform inversion was proposed, which can be applied to the calculated flow velocity. We used a wave equation, which can work with the flow velocities used in the study by Käser and Dumbser. Further, we enhanced the efficiency of computation by applying the back-propagation method. To verify the proposed algorithm, six different data sets were generated using the Marmousi2 model; each of these data sets used different flow velocities in the range 0-50, i.e., 0, 2, 5, 10, 25, and 50. Thereafter, the inversion results from these data sets along with the results without the use of flow velocity were compared and analyzed. In this study, we analyzed the results of waveform inversion after flow velocity has been factored in. It was demonstrated that the waveform inversion is not affected significantly when the flow velocity is of smaller value. However, when the flow velocity has a large value, factoring it in the waveform inversion produces superior results. This research was supported by the Basic Research Project(17-3312, 17-3313) of the Korea Institute of Geoscience and Mineral Resources(KIGAM) funded by the Ministry of Science, ICT and Future Planning of Korea.

Joint two dimensional inversion of gravity and magnetotelluric data using correspondence maps

NASA Astrophysics Data System (ADS)

Carrillo Lopez, J.; Gallardo, L. A.

2016-12-01

Inverse problems in Earth sciences are inherently non-unique. To improve models and reduce the number of solutions we need to provide extra information. In geological context, this information could be a priori information, for example, geological information, well log data, smoothness, or actually, information of measures of different kind of data. Joint inversion provides an approach to improve the solution and reduce the errors due to suppositions of each method. To do that, we need a link between two or more models. Some approaches have been explored successfully in recent years. For example, Gallardo and Meju (2003), Gallardo and Meju (2004, 2011), and Gallardo et. al. (2012) used the directions of properties to measure the similarity between models minimizing their cross gradients. In this work, we proposed a joint iterative inversion method that use spatial distribution of properties as a link. Correspondence maps could be better characterizing specific Earth systems due they consider the relation between properties. We implemented a code in Fortran to do a two dimensional inversion of magnetotelluric and gravity data, which are two of the standard methods in geophysical exploration. Synthetic tests show the advantages of joint inversion using correspondence maps against separate inversion. Finally, we applied this technique to magnetotelluric and gravity data in the geothermal zone located in Cerro Prieto, México.

Linear sampling method applied to non destructive testing of an elastic waveguide: theory, numerics and experiments

NASA Astrophysics Data System (ADS)

Baronian, Vahan; Bourgeois, Laurent; Chapuis, Bastien; Recoquillay, Arnaud

2018-07-01

This paper presents an application of the linear sampling method to ultrasonic non destructive testing of an elastic waveguide. In particular, the NDT context implies that both the solicitations and the measurements are located on the surface of the waveguide and are given in the time domain. Our strategy consists in using a modal formulation of the linear sampling method at multiple frequencies, such modal formulation being justified theoretically in Bourgeois et al (2011 Inverse Problems 27 055001) for rigid obstacles and in Bourgeois and Lunéville (2013 Inverse Problems 29 025017) for cracks. Our strategy requires the inversion of some emission and reception matrices which deserve some special attention due to potential ill-conditioning. The feasibility of our method is proved with the help of artificial data as well as real data.

Bayesian ISOLA: new tool for automated centroid moment tensor inversion

NASA Astrophysics Data System (ADS)

Vackář, Jiří; Burjánek, Jan; Gallovič, František; Zahradník, Jiří; Clinton, John

2017-08-01

We have developed a new, fully automated tool for the centroid moment tensor (CMT) inversion in a Bayesian framework. It includes automated data retrieval, data selection where station components with various instrumental disturbances are rejected and full-waveform inversion in a space-time grid around a provided hypocentre. A data covariance matrix calculated from pre-event noise yields an automated weighting of the station recordings according to their noise levels and also serves as an automated frequency filter suppressing noisy frequency ranges. The method is tested on synthetic and observed data. It is applied on a data set from the Swiss seismic network and the results are compared with the existing high-quality MT catalogue. The software package programmed in Python is designed to be as versatile as possible in order to be applicable in various networks ranging from local to regional. The method can be applied either to the everyday network data flow, or to process large pre-existing earthquake catalogues and data sets.

In search of best fitted composite model to the ALAE data set with transformed Gamma and inversed transformed Gamma families

NASA Astrophysics Data System (ADS)

Maghsoudi, Mastoureh; Bakar, Shaiful Anuar Abu

2017-05-01

In this paper, a recent novel approach is applied to estimate the threshold parameter of a composite model. Several composite models from Transformed Gamma and Inverse Transformed Gamma families are constructed based on this approach and their parameters are estimated by the maximum likelihood method. These composite models are fitted to allocated loss adjustment expenses (ALAE). In comparison to all composite models studied, the composite Weibull-Inverse Transformed Gamma model is proved to be a competitor candidate as it best fit the loss data. The final part considers the backtesting method to verify the validation of VaR and CTE risk measures.

Three-dimensional imaging of buried objects in very lossy earth by inversion of VETEM data

USGS Publications Warehouse

Cui, T.J.; Aydiner, A.A.; Chew, W.C.; Wright, D.L.; Smith, D.V.

2003-01-01

The very early time electromagnetic system (VETEM) is an efficient tool for the detection of buried objects in very lossy earth, which allows a deeper penetration depth compared to the ground-penetrating radar. In this paper, the inversion of VETEM data is investigated using three-dimensional (3-D) inverse scattering techniques, where multiple frequencies are applied in the frequency range from 0-5 MHz. For small and moderately sized problems, the Born approximation and/or the Born iterative method have been used with the aid of the singular value decomposition and/or the conjugate gradient method in solving the linearized integral equations. For large-scale problems, a localized 3-D inversion method based on the Born approximation has been proposed for the inversion of VETEM data over a large measurement domain. Ways to process and to calibrate the experimental VETEM data are discussed to capture the real physics of buried objects. Reconstruction examples using synthesized VETEM data and real-world VETEM data are given to test the validity and efficiency of the proposed approach.

Trans-dimensional and hierarchical Bayesian approaches toward rigorous estimation of seismic sources and structures in the Northeast Asia

NASA Astrophysics Data System (ADS)

Kim, Seongryong; Tkalčić, Hrvoje; Mustać, Marija; Rhie, Junkee; Ford, Sean

2016-04-01

A framework is presented within which we provide rigorous estimations for seismic sources and structures in the Northeast Asia. We use Bayesian inversion methods, which enable statistical estimations of models and their uncertainties based on data information. Ambiguities in error statistics and model parameterizations are addressed by hierarchical and trans-dimensional (trans-D) techniques, which can be inherently implemented in the Bayesian inversions. Hence reliable estimation of model parameters and their uncertainties is possible, thus avoiding arbitrary regularizations and parameterizations. Hierarchical and trans-D inversions are performed to develop a three-dimensional velocity model using ambient noise data. To further improve the model, we perform joint inversions with receiver function data using a newly developed Bayesian method. For the source estimation, a novel moment tensor inversion method is presented and applied to regional waveform data of the North Korean nuclear explosion tests. By the combination of new Bayesian techniques and the structural model, coupled with meaningful uncertainties related to each of the processes, more quantitative monitoring and discrimination of seismic events is possible.

Identification of material constants for piezoelectric transformers by three-dimensional, finite-element method and a design-sensitivity method.

PubMed

Joo, Hyun-Woo; Lee, Chang-Hwan; Rho, Jong-Seok; Jung, Hyun-Kyo

2003-08-01

In this paper, an inversion scheme for piezoelectric constants of piezoelectric transformers is proposed. The impedance of piezoelectric transducers is calculated using a three-dimensional finite element method. The validity of this is confirmed experimentally. The effects of material coefficients on piezoelectric transformers are investigated numerically. Six material coefficient variables for piezoelectric transformers were selected, and a design sensitivity method was adopted as an inversion scheme. The validity of the proposed method was confirmed by step-up ratio calculations. The proposed method is applied to the analysis of a sample piezoelectric transformer, and its resonance characteristics are obtained by numerically combined equivalent circuit method.

Total-variation based velocity inversion with Bregmanized operator splitting algorithm

NASA Astrophysics Data System (ADS)

Zand, Toktam; Gholami, Ali

2018-04-01

Many problems in applied geophysics can be formulated as a linear inverse problem. The associated problems, however, are large-scale and ill-conditioned. Therefore, regularization techniques are needed to be employed for solving them and generating a stable and acceptable solution. We consider numerical methods for solving such problems in this paper. In order to tackle the ill-conditioning of the problem we use blockiness as a prior information of the subsurface parameters and formulate the problem as a constrained total variation (TV) regularization. The Bregmanized operator splitting (BOS) algorithm as a combination of the Bregman iteration and the proximal forward backward operator splitting method is developed to solve the arranged problem. Two main advantages of this new algorithm are that no matrix inversion is required and that a discrepancy stopping criterion is used to stop the iterations, which allow efficient solution of large-scale problems. The high performance of the proposed TV regularization method is demonstrated using two different experiments: 1) velocity inversion from (synthetic) seismic data which is based on Born approximation, 2) computing interval velocities from RMS velocities via Dix formula. Numerical examples are presented to verify the feasibility of the proposed method for high-resolution velocity inversion.

LAI inversion from optical reflectance using a neural network trained with a multiple scattering model

NASA Technical Reports Server (NTRS)

Smith, James A.

1992-01-01

The inversion of the leaf area index (LAI) canopy parameter from optical spectral reflectance measurements is obtained using a backpropagation artificial neural network trained using input-output pairs generated by a multiple scattering reflectance model. The problem of LAI estimation over sparse canopies (LAI < 1.0) with varying soil reflectance backgrounds is particularly difficult. Standard multiple regression methods applied to canopies within a single homogeneous soil type yield good results but perform unacceptably when applied across soil boundaries, resulting in absolute percentage errors of >1000 percent for low LAI. Minimization methods applied to merit functions constructed from differences between measured reflectances and predicted reflectances using multiple-scattering models are unacceptably sensitive to a good initial guess for the desired parameter. In contrast, the neural network reported generally yields absolute percentage errors of <30 percent when weighting coefficients trained on one soil type were applied to predicted canopy reflectance at a different soil background.

Bayesian linearized amplitude-versus-frequency inversion for quality factor and its application

NASA Astrophysics Data System (ADS)

Yang, Xinchao; Teng, Long; Li, Jingnan; Cheng, Jiubing

2018-06-01

We propose a straightforward attenuation inversion method by utilizing the amplitude-versus-frequency (AVF) characteristics of seismic data. A new linearized approximation equation of the angle and frequency dependent reflectivity in viscoelastic media is derived. We then use the presented equation to implement the Bayesian linear AVF inversion. The inversion result includes not only P-wave and S-wave velocities, and densities, but also P-wave and S-wave quality factors. Synthetic tests show that the AVF inversion surpasses the AVA inversion for quality factor estimation. However, a higher signal noise ratio (SNR) of data is necessary for the AVF inversion. To show its feasibility, we apply both the new Bayesian AVF inversion and conventional AVA inversion to a tight gas reservoir data in Sichuan Basin in China. Considering the SNR of the field data, a combination of AVF inversion for attenuation parameters and AVA inversion for elastic parameters is recommended. The result reveals that attenuation estimations could serve as a useful complement in combination with the AVA inversion results for the detection of tight gas reservoirs.

Structural-change localization and monitoring through a perturbation-based inverse problem.

PubMed

Roux, Philippe; Guéguen, Philippe; Baillet, Laurent; Hamze, Alaa

2014-11-01

Structural-change detection and characterization, or structural-health monitoring, is generally based on modal analysis, for detection, localization, and quantification of changes in structure. Classical methods combine both variations in frequencies and mode shapes, which require accurate and spatially distributed measurements. In this study, the detection and localization of a local perturbation are assessed by analysis of frequency changes (in the fundamental mode and overtones) that are combined with a perturbation-based linear inverse method and a deconvolution process. This perturbation method is applied first to a bending beam with the change considered as a local perturbation of the Young's modulus, using a one-dimensional finite-element model for modal analysis. Localization is successful, even for extended and multiple changes. In a second step, the method is numerically tested under ambient-noise vibration from the beam support with local changes that are shifted step by step along the beam. The frequency values are revealed using the random decrement technique that is applied to the time-evolving vibrations recorded by one sensor at the free extremity of the beam. Finally, the inversion method is experimentally demonstrated at the laboratory scale with data recorded at the free end of a Plexiglas beam attached to a metallic support.

Inverse Planning Approach for 3-D MRI-Based Pulse-Dose Rate Intracavitary Brachytherapy in Cervix Cancer

DOE Office of Scientific and Technical Information (OSTI.GOV)

Chajon, Enrique; Dumas, Isabelle; Touleimat, Mahmoud B.Sc.

2007-11-01

Purpose: The purpose of this study was to evaluate the inverse planning simulated annealing (IPSA) software for the optimization of dose distribution in patients with cervix carcinoma treated with MRI-based pulsed-dose rate intracavitary brachytherapy. Methods and Materials: Thirty patients treated with a technique using a customized vaginal mold were selected. Dose-volume parameters obtained using the IPSA method were compared with the classic manual optimization method (MOM). Target volumes and organs at risk were delineated according to the Gynecological Brachytherapy Group/European Society for Therapeutic Radiology and Oncology recommendations. Because the pulsed dose rate program was based on clinical experience with lowmore » dose rate, dwell time values were required to be as homogeneous as possible. To achieve this goal, different modifications of the IPSA program were applied. Results: The first dose distribution calculated by the IPSA algorithm proposed a heterogeneous distribution of dwell time positions. The mean D90, D100, and V100 calculated with both methods did not differ significantly when the constraints were applied. For the bladder, doses calculated at the ICRU reference point derived from the MOM differed significantly from the doses calculated by the IPSA method (mean, 58.4 vs. 55 Gy respectively; p = 0.0001). For the rectum, the doses calculated at the ICRU reference point were also significantly lower with the IPSA method. Conclusions: The inverse planning method provided fast and automatic solutions for the optimization of dose distribution. However, the straightforward use of IPSA generated significant heterogeneity in dwell time values. Caution is therefore recommended in the use of inverse optimization tools with clinical relevance study of new dosimetric rules.« less

A unified inversion scheme to process multifrequency measurements of various dispersive electromagnetic properties

NASA Astrophysics Data System (ADS)

Han, Y.; Misra, S.

2018-04-01

Multi-frequency measurement of a dispersive electromagnetic (EM) property, such as electrical conductivity, dielectric permittivity, or magnetic permeability, is commonly analyzed for purposes of material characterization. Such an analysis requires inversion of the multi-frequency measurement based on a specific relaxation model, such as Cole-Cole model or Pelton's model. We develop a unified inversion scheme that can be coupled to various type of relaxation models to independently process multi-frequency measurement of varied EM properties for purposes of improved EM-based geomaterial characterization. The proposed inversion scheme is firstly tested in few synthetic cases in which different relaxation models are coupled into the inversion scheme and then applied to multi-frequency complex conductivity, complex resistivity, complex permittivity, and complex impedance measurements. The method estimates up to seven relaxation-model parameters exhibiting convergence and accuracy for random initializations of the relaxation-model parameters within up to 3-orders of magnitude variation around the true parameter values. The proposed inversion method implements a bounded Levenberg algorithm with tuning initial values of damping parameter and its iterative adjustment factor, which are fixed in all the cases shown in this paper and irrespective of the type of measured EM property and the type of relaxation model. Notably, jump-out step and jump-back-in step are implemented as automated methods in the inversion scheme to prevent the inversion from getting trapped around local minima and to honor physical bounds of model parameters. The proposed inversion scheme can be easily used to process various types of EM measurements without major changes to the inversion scheme.

Regularized inversion of controlled source audio-frequency magnetotelluric data in horizontally layered transversely isotropic media

NASA Astrophysics Data System (ADS)

Zhou, Jianmei; Wang, Jianxun; Shang, Qinglong; Wang, Hongnian; Yin, Changchun

2014-04-01

We present an algorithm for inverting controlled source audio-frequency magnetotelluric (CSAMT) data in horizontally layered transversely isotropic (TI) media. The popular inversion method parameterizes the media into a large number of layers which have fixed thickness and only reconstruct the conductivities (e.g. Occam's inversion), which does not enable the recovery of the sharp interfaces between layers. In this paper, we simultaneously reconstruct all the model parameters, including both the horizontal and vertical conductivities and layer depths. Applying the perturbation principle and the dyadic Green's function in TI media, we derive the analytic expression of Fréchet derivatives of CSAMT responses with respect to all the model parameters in the form of Sommerfeld integrals. A regularized iterative inversion method is established to simultaneously reconstruct all the model parameters. Numerical results show that the inverse algorithm, including the depths of the layer interfaces, can significantly improve the inverse results. It can not only reconstruct the sharp interfaces between layers, but also can obtain conductivities close to the true value.

The Earthquake‐Source Inversion Validation (SIV) Project

USGS Publications Warehouse

Mai, P. Martin; Schorlemmer, Danijel; Page, Morgan T.; Ampuero, Jean-Paul; Asano, Kimiyuki; Causse, Mathieu; Custodio, Susana; Fan, Wenyuan; Festa, Gaetano; Galis, Martin; Gallovic, Frantisek; Imperatori, Walter; Käser, Martin; Malytskyy, Dmytro; Okuwaki, Ryo; Pollitz, Fred; Passone, Luca; Razafindrakoto, Hoby N. T.; Sekiguchi, Haruko; Song, Seok Goo; Somala, Surendra N.; Thingbaijam, Kiran K. S.; Twardzik, Cedric; van Driel, Martin; Vyas, Jagdish C.; Wang, Rongjiang; Yagi, Yuji; Zielke, Olaf

2016-01-01

Finite‐fault earthquake source inversions infer the (time‐dependent) displacement on the rupture surface from geophysical data. The resulting earthquake source models document the complexity of the rupture process. However, multiple source models for the same earthquake, obtained by different research teams, often exhibit remarkable dissimilarities. To address the uncertainties in earthquake‐source inversion methods and to understand strengths and weaknesses of the various approaches used, the Source Inversion Validation (SIV) project conducts a set of forward‐modeling exercises and inversion benchmarks. In this article, we describe the SIV strategy, the initial benchmarks, and current SIV results. Furthermore, we apply statistical tools for quantitative waveform comparison and for investigating source‐model (dis)similarities that enable us to rank the solutions, and to identify particularly promising source inversion approaches. All SIV exercises (with related data and descriptions) and statistical comparison tools are available via an online collaboration platform, and we encourage source modelers to use the SIV benchmarks for developing and testing new methods. We envision that the SIV efforts will lead to new developments for tackling the earthquake‐source imaging problem.

Centroid-moment tensor inversions using high-rate GPS waveforms

NASA Astrophysics Data System (ADS)

O'Toole, Thomas B.; Valentine, Andrew P.; Woodhouse, John H.

2012-10-01

Displacement time-series recorded by Global Positioning System (GPS) receivers are a new type of near-field waveform observation of the seismic source. We have developed an inversion method which enables the recovery of an earthquake's mechanism and centroid coordinates from such data. Our approach is identical to that of the 'classical' Centroid-Moment Tensor (CMT) algorithm, except that we forward model the seismic wavefield using a method that is amenable to the efficient computation of synthetic GPS seismograms and their partial derivatives. We demonstrate the validity of our approach by calculating CMT solutions using 1 Hz GPS data for two recent earthquakes in Japan. These results are in good agreement with independently determined source models of these events. With wider availability of data, we envisage the CMT algorithm providing a tool for the systematic inversion of GPS waveforms, as is already the case for teleseismic data. Furthermore, this general inversion method could equally be applied to other near-field earthquake observations such as those made using accelerometers.

Dynamics of Genome Rearrangement in Bacterial Populations

PubMed Central

Darling, Aaron E.; Miklós, István; Ragan, Mark A.

2008-01-01

Genome structure variation has profound impacts on phenotype in organisms ranging from microbes to humans, yet little is known about how natural selection acts on genome arrangement. Pathogenic bacteria such as Yersinia pestis, which causes bubonic and pneumonic plague, often exhibit a high degree of genomic rearrangement. The recent availability of several Yersinia genomes offers an unprecedented opportunity to study the evolution of genome structure and arrangement. We introduce a set of statistical methods to study patterns of rearrangement in circular chromosomes and apply them to the Yersinia. We constructed a multiple alignment of eight Yersinia genomes using Mauve software to identify 78 conserved segments that are internally free from genome rearrangement. Based on the alignment, we applied Bayesian statistical methods to infer the phylogenetic inversion history of Yersinia. The sampling of genome arrangement reconstructions contains seven parsimonious tree topologies, each having different histories of 79 inversions. Topologies with a greater number of inversions also exist, but were sampled less frequently. The inversion phylogenies agree with results suggested by SNP patterns. We then analyzed reconstructed inversion histories to identify patterns of rearrangement. We confirm an over-representation of “symmetric inversions”—inversions with endpoints that are equally distant from the origin of chromosomal replication. Ancestral genome arrangements demonstrate moderate preference for replichore balance in Yersinia. We found that all inversions are shorter than expected under a neutral model, whereas inversions acting within a single replichore are much shorter than expected. We also found evidence for a canonical configuration of the origin and terminus of replication. Finally, breakpoint reuse analysis reveals that inversions with endpoints proximal to the origin of DNA replication are nearly three times more frequent. Our findings represent the first characterization of genome arrangement evolution in a bacterial population evolving outside laboratory conditions. Insight into the process of genomic rearrangement may further the understanding of pathogen population dynamics and selection on the architecture of circular bacterial chromosomes. PMID:18650965

Stochastic Gabor reflectivity and acoustic impedance inversion

NASA Astrophysics Data System (ADS)

Hariri Naghadeh, Diako; Morley, Christopher Keith; Ferguson, Angus John

2018-02-01

To delineate subsurface lithology to estimate petrophysical properties of a reservoir, it is possible to use acoustic impedance (AI) which is the result of seismic inversion. To change amplitude to AI, removal of wavelet effects from the seismic signal in order to get a reflection series, and subsequently transforming those reflections to AI, is vital. To carry out seismic inversion correctly it is important to not assume that the seismic signal is stationary. However, all stationary deconvolution methods are designed following that assumption. To increase temporal resolution and interpretation ability, amplitude compensation and phase correction are inevitable. Those are pitfalls of stationary reflectivity inversion. Although stationary reflectivity inversion methods are trying to estimate reflectivity series, because of incorrect assumptions their estimations will not be correct, but may be useful. Trying to convert those reflection series to AI, also merging with the low frequency initial model, can help us. The aim of this study was to apply non-stationary deconvolution to eliminate time variant wavelet effects from the signal and to convert the estimated reflection series to the absolute AI by getting bias from well logs. To carry out this aim, stochastic Gabor inversion in the time domain was used. The Gabor transform derived the signal’s time-frequency analysis and estimated wavelet properties from different windows. Dealing with different time windows gave an ability to create a time-variant kernel matrix, which was used to remove matrix effects from seismic data. The result was a reflection series that does not follow the stationary assumption. The subsequent step was to convert those reflections to AI using well information. Synthetic and real data sets were used to show the ability of the introduced method. The results highlight that the time cost to get seismic inversion is negligible related to general Gabor inversion in the frequency domain. Also, obtaining bias could help the method to estimate reliable AI. To justify the effect of random noise on deterministic and stochastic inversion results, a stationary noisy trace with signal-to-noise ratio equal to 2 was used. The results highlight the inability of deterministic inversion in dealing with a noisy data set even using a high number of regularization parameters. Also, despite the low level of signal, stochastic Gabor inversion not only can estimate correctly the wavelet’s properties but also, because of bias from well logs, the inversion result is very close to the real AI. Comparing deterministic and introduced inversion results on a real data set shows that low resolution results, especially in the deeper parts of seismic sections using deterministic inversion, creates significant reliability problems for seismic prospects, but this pitfall is solved completely using stochastic Gabor inversion. The estimated AI using Gabor inversion in the time domain is much better and faster than general Gabor inversion in the frequency domain. This is due to the extra number of windows required to analyze the time-frequency information and also the amount of temporal increment between windows. In contrast, stochastic Gabor inversion can estimate trustable physical properties close to the real characteristics. Applying to a real data set could give an ability to detect the direction of volcanic intrusion and the ability of lithology distribution delineation along the fan. Comparing the inversion results highlights the efficiency of stochastic Gabor inversion to delineate lateral lithology changes because of the improved frequency content and zero phasing of the final inversion volume.

pyGIMLi: An open-source library for modelling and inversion in geophysics

NASA Astrophysics Data System (ADS)

Rücker, Carsten; Günther, Thomas; Wagner, Florian M.

2017-12-01

Many tasks in applied geosciences cannot be solved by single measurements, but require the integration of geophysical, geotechnical and hydrological methods. Numerical simulation techniques are essential both for planning and interpretation, as well as for the process understanding of modern geophysical methods. These trends encourage open, simple, and modern software architectures aiming at a uniform interface for interdisciplinary and flexible modelling and inversion approaches. We present pyGIMLi (Python Library for Inversion and Modelling in Geophysics), an open-source framework that provides tools for modelling and inversion of various geophysical but also hydrological methods. The modelling component supplies discretization management and the numerical basis for finite-element and finite-volume solvers in 1D, 2D and 3D on arbitrarily structured meshes. The generalized inversion framework solves the minimization problem with a Gauss-Newton algorithm for any physical forward operator and provides opportunities for uncertainty and resolution analyses. More general requirements, such as flexible regularization strategies, time-lapse processing and different sorts of coupling individual methods are provided independently of the actual methods used. The usage of pyGIMLi is first demonstrated by solving the steady-state heat equation, followed by a demonstration of more complex capabilities for the combination of different geophysical data sets. A fully coupled hydrogeophysical inversion of electrical resistivity tomography (ERT) data of a simulated tracer experiment is presented that allows to directly reconstruct the underlying hydraulic conductivity distribution of the aquifer. Another example demonstrates the improvement of jointly inverting ERT and ultrasonic data with respect to saturation by a new approach that incorporates petrophysical relations in the inversion. Potential applications of the presented framework are manifold and include time-lapse, constrained, joint, and coupled inversions of various geophysical and hydrological data sets.

Efficient realization of 3D joint inversion of seismic and magnetotelluric data with cross gradient structure constraint

NASA Astrophysics Data System (ADS)

Luo, H.; Zhang, H.; Gao, J.

2016-12-01

Seismic and magnetotelluric (MT) imaging methods are generally used to characterize subsurface structures at various scales. The two methods are complementary to each other and the integration of them is helpful for more reliably determining the resistivity and velocity models of the target region. Because of the difficulty in finding empirical relationship between resistivity and velocity parameters, Gallardo and Meju [2003] proposed a joint inversion method enforcing resistivity and velocity models consistent in structure, which is realized by minimizing cross gradients between two models. However, it is extremely challenging to combine two different inversion systems together along with the cross gradient constraints. For this reason, Gallardo [2007] proposed a joint inversion scheme that decouples the seismic and MT inversion systems by iteratively performing seismic and MT inversions as well as cross gradient minimization separately. This scheme avoids the complexity of combining two different systems together but it suffers the issue of balancing between data fitting and structure constraint. In this study, we have developed a new joint inversion scheme that avoids the problem encountered by the scheme of Gallardo [2007]. In the new scheme, seismic and MT inversions are still separately performed but the cross gradient minimization is also constrained by model perturbations from separate inversions. In this way, the new scheme still avoids the complexity of combining two different systems together and at the same time the balance between data fitting and structure consistency constraint can be enforced. We have tested our joint inversion algorithm for both 2D and 3D cases. Synthetic tests show that joint inversion better reconstructed the velocity and resistivity models than separate inversions. Compared to separate inversions, joint inversion can remove artifacts in the resistivity model and can improve the resolution for deeper resistivity structures. We will also show results applying the new joint seismic and MT inversion scheme to southwest China, where several MT profiles are available and earthquakes are very active.

Imaging Crustal Structure with Waveform and HV Ratio of Body-wave Receiver Function

NASA Astrophysics Data System (ADS)

Chong, J.; Chu, R.; Ni, S.; Meng, Q.; Guo, A.

2017-12-01

It is known that receiver function has less constraint on the absolute velocity, and joint inversion of receiver function and surface wave dispersion has been widely applied to reduce the non-uniqueness of velocity and interface depth. However, some studies indicate that the receiver function itself is capable for determining the absolute shear wave velocity. In this study, we propose to measure the receiver function HV ratio which takes advantage of the amplitude information of the radial and vertical receiver functions to constrain the shear-wave velocity. Numerical analysis indicates that the receiver function HV ratio is sensitive to the average shear wave velocity in the depth range it samples, and can help to reduce the non-uniqueness of receiver function waveform inversion. A joint inversion scheme has been developed, and both synthetic tests and real data application proved the feasibility of the joint inversion. The method has been applied to the dense seismic array of ChinArray program in SE Tibet during the time period from August 2011 to August 2012 in SE Tibet (ChinArray-Himalaya, 2011). The measurements of receiver function HV ratio reveals the lateral variation of the tectonics in of the study region. And main features of the velocity structure imagined by the new joint inversion method are consistent with previous studies. KEYWORDS: receiver function HV ratio, receiver function waveform inversion, crustal structure ReferenceChinArray-Himalaya. 2011. China Seismic Array waveform data of Himalaya Project. Institute of Geophysics, China Earthquake Administration. doi:10.12001/ChinArray.Data. Himalaya. Jiajun Chong, Risheng Chu*, Sidao Ni, Qingjun Meng, Aizhi Guo, 2017. Receiver Function HV Ratio, a New Measurement for Reducing Non-uniqueness of Receiver Function Waveform Inversion. (under revision)

Joint inversion of teleseismic receiver functions and magnetotelluric data using a genetic algorithm: Are seismic velocities and electrical conductivities compatible?

NASA Astrophysics Data System (ADS)

Moorkamp, M.; Jones, A. G.; Eaton, D. W.

2007-08-01

Joint inversion of different kinds of geophysical data has the potential to improve model resolution, under the assumption that the different observations are sensitive to the same subsurface features. Here, we examine the compatibility of P-wave teleseismic receiver functions and long-period magnetotelluric (MT) observations, using joint inversion, to infer one-dimensional lithospheric structure. We apply a genetic algorithm to invert teleseismic and MT data from the Slave craton; a region where previous independent analyses of these data have indicated correlated layering of the lithosphere. Examination of model resolution and parameter trade-off suggests that the main features of this area, the Moho, Central Slave Mantle Conductor and the Lithosphere-Asthenosphere boundary, are sensed to varying degrees by both methods. Thus, joint inversion of these two complementary data sets can be used to construct improved models of the lithosphere. Further studies will be needed to assess whether the approach can be applied globally.

A Bayesian inversion for slip distribution of 1 Apr 2007 Mw8.1 Solomon Islands Earthquake

NASA Astrophysics Data System (ADS)

Chen, T.; Luo, H.

2013-12-01

On 1 Apr 2007 the megathrust Mw8.1 Solomon Islands earthquake occurred in the southeast pacific along the New Britain subduction zone. 102 vertical displacement measurements over the southeastern end of the rupture zone from two field surveys after this event provide a unique constraint for slip distribution inversion. In conventional inversion method (such as bounded variable least squares) the smoothing parameter that determines the relative weight placed on fitting the data versus smoothing the slip distribution is often subjectively selected at the bend of the trade-off curve. Here a fully probabilistic inversion method[Fukuda,2008] is applied to estimate distributed slip and smoothing parameter objectively. The joint posterior probability density function of distributed slip and the smoothing parameter is formulated under a Bayesian framework and sampled with Markov chain Monte Carlo method. We estimate the spatial distribution of dip slip associated with the 1 Apr 2007 Solomon Islands earthquake with this method. Early results show a shallower dip angle than previous study and highly variable dip slip both along-strike and down-dip.

Appraisal of an Array TEM Method in Detecting a Mined-Out Area Beneath a Conductive Layer

NASA Astrophysics Data System (ADS)

Li, Hai; Xue, Guo-qiang; Zhou, Nan-nan; Chen, Wei-ying

2015-10-01

The transient electromagnetic method has been extensively used for the detection of mined-out area in China for the past few years. In the cases that the mined-out area is overlain by a conductive layer, the detection of the target layer is difficult with a traditional loop source TEM method. In order to detect the target layer in this condition, this paper presents a newly developed array TEM method, which uses a grounded wire source. The underground current density distribution and the responses of the grounded wire source TEM configuration are modeled to demonstrate that the target layer is detectable in this condition. The 1D OCCAM inversion routine is applied to the synthetic single station data and common middle point gather. The result reveals that the electric source TEM method is capable of recovering the resistive target layer beneath the conductive overburden. By contrast, the conductive target layer cannot be recovered unless the distance between the target layer and the conductive overburden is large. Compared with inversion result of the single station data, the inversion of common middle point gather can better recover the resistivity of the target layer. Finally, a case study illustrates that the array TEM method is successfully applied in recovering a water-filled mined-out area beneath a conductive overburden.

Inversion of residual stress profiles from ultrasonic Rayleigh wave dispersion data

NASA Astrophysics Data System (ADS)

Mora, P.; Spies, M.

2018-05-01

We investigate theoretically and with synthetic data the performance of several inversion methods to infer a residual stress state from ultrasonic surface wave dispersion data. We show that this particular problem may reveal in relevant materials undesired behaviors for some methods that could be reliably applied to infer other properties. We focus on two methods, one based on a Taylor-expansion, and another one based on a piecewise linear expansion regularized by a singular value decomposition. We explain the instabilities of the Taylor-based method by highlighting singularities in the series of coefficients. At the same time, we show that the other method can successfully provide performances which only weakly depend on the material.

Nonlinear PP and PS joint inversion based on the exact Zoeppritz equations: a two-stage procedure

NASA Astrophysics Data System (ADS)

Zhi, Lixia; Chen, Shuangquan; Song, Baoshan; Li, Xiang-yang

2018-04-01

S-velocity and density are very important parameters in distinguishing lithology and estimating other petrophysical properties. A reliable estimate of S-velocity and density is very difficult to obtain, even from long-offset gather data. Joint inversion of PP and PS data provides a promising strategy for stabilizing and improving the results of inversion in estimating elastic parameters and density. For 2D or 3D inversion, the trace-by-trace strategy is still the most widely used method although it often suffers from a lack of clarity because of its high efficiency, which is due to parallel computing. This paper describes a two-stage inversion method for nonlinear PP and PS joint inversion based on the exact Zoeppritz equations. There are several advantages for our proposed methods as follows: (1) Thanks to the exact Zoeppritz equation, our joint inversion method is applicable for wide angle amplitude-versus-angle inversion; (2) The use of both P- and S-wave information can further enhance the stability and accuracy of parameter estimation, especially for the S-velocity and density; (3) The two-stage inversion procedure proposed in this paper can achieve a good compromise between efficiency and precision. On the one hand, the trace-by-trace strategy used in the first stage can be processed in parallel so that it has high computational efficiency. On the other hand, to deal with the indistinctness of and undesired disturbances to the inversion results obtained from the first stage, we apply the second stage—total variation (TV) regularization. By enforcing spatial and temporal constraints, the TV regularization stage deblurs the inversion results and leads to parameter estimation with greater precision. Notably, the computation consumption of the TV regularization stage can be ignored compared to the first stage because it is solved using the fast split Bregman iterations. Numerical examples using a well log and the Marmousi II model show that the proposed joint inversion is a reliable method capable of accurately estimating the density parameter as well as P-wave velocity and S-wave velocity, even when the seismic data is noisy with signal-to-noise ratio of 5.

A three-step maximum a posteriori probability method for InSAR data inversion of coseismic rupture with application to the 14 April 2010 Mw 6.9 Yushu, China, earthquake

NASA Astrophysics Data System (ADS)

Sun, Jianbao; Shen, Zheng-Kang; Bürgmann, Roland; Wang, Min; Chen, Lichun; Xu, Xiwei

2013-08-01

develop a three-step maximum a posteriori probability method for coseismic rupture inversion, which aims at maximizing the a posterior probability density function (PDF) of elastic deformation solutions of earthquake rupture. The method originates from the fully Bayesian inversion and mixed linear-nonlinear Bayesian inversion methods and shares the same posterior PDF with them, while overcoming difficulties with convergence when large numbers of low-quality data are used and greatly improving the convergence rate using optimization procedures. A highly efficient global optimization algorithm, adaptive simulated annealing, is used to search for the maximum of a posterior PDF ("mode" in statistics) in the first step. The second step inversion approaches the "true" solution further using the Monte Carlo inversion technique with positivity constraints, with all parameters obtained from the first step as the initial solution. Then slip artifacts are eliminated from slip models in the third step using the same procedure of the second step, with fixed fault geometry parameters. We first design a fault model with 45° dip angle and oblique slip, and produce corresponding synthetic interferometric synthetic aperture radar (InSAR) data sets to validate the reliability and efficiency of the new method. We then apply this method to InSAR data inversion for the coseismic slip distribution of the 14 April 2010 Mw 6.9 Yushu, China earthquake. Our preferred slip model is composed of three segments with most of the slip occurring within 15 km depth and the maximum slip reaches 1.38 m at the surface. The seismic moment released is estimated to be 2.32e+19 Nm, consistent with the seismic estimate of 2.50e+19 Nm.

Design optimization of axial flow hydraulic turbine runner: Part I - an improved Q3D inverse method

NASA Astrophysics Data System (ADS)

Peng, Guoyi; Cao, Shuliang; Ishizuka, Masaru; Hayama, Shinji

2002-06-01

With the aim of constructing a comprehensive design optimization procedure of axial flow hydraulic turbine, an improved quasi-three-dimensional inverse method has been proposed from the viewpoint of system and a set of rotational flow governing equations as well as a blade geometry design equation has been derived. The computation domain is firstly taken from the inlet of guide vane to the far outlet of runner blade in the inverse method and flows in different regions are solved simultaneously. So the influence of wicket gate parameters on the runner blade design can be considered and the difficulty to define the flow condition at the runner blade inlet is surmounted. As a pre-computation of initial blade design on S2m surface is newly adopted, the iteration of S1 and S2m surfaces has been reduced greatly and the convergence of inverse computation has been improved. The present model has been applied to the inverse computation of a Kaplan turbine runner. Experimental results and the direct flow analysis have proved the validation of inverse computation. Numerical investigations show that a proper enlargement of guide vane distribution diameter is advantageous to improve the performance of axial hydraulic turbine runner. Copyright

Improved preconditioned conjugate gradient algorithm and application in 3D inversion of gravity-gradiometry data

NASA Astrophysics Data System (ADS)

Wang, Tai-Han; Huang, Da-Nian; Ma, Guo-Qing; Meng, Zhao-Hai; Li, Ye

2017-06-01

With the continuous development of full tensor gradiometer (FTG) measurement techniques, three-dimensional (3D) inversion of FTG data is becoming increasingly used in oil and gas exploration. In the fast processing and interpretation of large-scale high-precision data, the use of the graphics processing unit process unit (GPU) and preconditioning methods are very important in the data inversion. In this paper, an improved preconditioned conjugate gradient algorithm is proposed by combining the symmetric successive over-relaxation (SSOR) technique and the incomplete Choleksy decomposition conjugate gradient algorithm (ICCG). Since preparing the preconditioner requires extra time, a parallel implement based on GPU is proposed. The improved method is then applied in the inversion of noisecontaminated synthetic data to prove its adaptability in the inversion of 3D FTG data. Results show that the parallel SSOR-ICCG algorithm based on NVIDIA Tesla C2050 GPU achieves a speedup of approximately 25 times that of a serial program using a 2.0 GHz Central Processing Unit (CPU). Real airborne gravity-gradiometry data from Vinton salt dome (southwest Louisiana, USA) are also considered. Good results are obtained, which verifies the efficiency and feasibility of the proposed parallel method in fast inversion of 3D FTG data.

Application of the concept of dynamic trim control and nonlinear system inverses to automatic control of a vertical attitude takeoff and landing aircraft

NASA Technical Reports Server (NTRS)

Smith, G. A.; Meyer, G.

1981-01-01

A full envelope automatic flight control system based on nonlinear inverse systems concepts has been applied to a vertical attitude takeoff and landing (VATOL) fighter aircraft. A new method for using an airborne digital aircraft model to perform the inversion of a nonlinear aircraft model is presented together with the results of a simulation study of the nonlinear inverse system concept for the vertical-attitude hover mode. The system response to maneuver commands in the vertical attitude was found to be excellent; and recovery from large initial offsets and large disturbances was found to be very satisfactory.

Some practical aspects of prestack waveform inversion using a genetic algorithm: An example from the east Texas Woodbine gas sand

DOE Office of Scientific and Technical Information (OSTI.GOV)

Mallick, S.

1999-03-01

In this paper, a prestack inversion method using a genetic algorithm (GA) is presented, and issues relating to the implementation of prestack GA inversion in practice are discussed. GA is a Monte-Carlo type inversion, using a natural analogy to the biological evolution process. When GA is cast into a Bayesian framework, a priori information of the model parameters and the physics of the forward problem are used to compute synthetic data. These synthetic data can then be matched with observations to obtain approximate estimates of the marginal a posteriori probability density (PPD) functions in the model space. Plots of thesemore » PPD functions allow an interpreter to choose models which best describe the specific geologic setting and lead to an accurate prediction of seismic lithology. Poststack inversion and prestack GA inversion were applied to a Woodbine gas sand data set from East Texas. A comparison of prestack inversion with poststack inversion demonstrates that prestack inversion shows detailed stratigraphic features of the subsurface which are not visible on the poststack inversion.« less

Four dimensional data assimilation (FDDA) impacts on WRF performance in simulating inversion layer structure and distributions of CMAQ-simulated winter ozone concentrations in Uintah Basin

NASA Astrophysics Data System (ADS)

Tran, Trang; Tran, Huy; Mansfield, Marc; Lyman, Seth; Crosman, Erik

2018-03-01

Four-dimensional data assimilation (FDDA) was applied in WRF-CMAQ model sensitivity tests to study the impact of observational and analysis nudging on model performance in simulating inversion layers and O3 concentration distributions within the Uintah Basin, Utah, U.S.A. in winter 2013. Observational nudging substantially improved WRF model performance in simulating surface wind fields, correcting a 10 °C warm surface temperature bias, correcting overestimation of the planetary boundary layer height (PBLH) and correcting underestimation of inversion strengths produced by regular WRF model physics without nudging. However, the combined effects of poor performance of WRF meteorological model physical parameterization schemes in simulating low clouds, and warm and moist biases in the temperature and moisture initialization and subsequent simulation fields, likely amplified the overestimation of warm clouds during inversion days when observational nudging was applied, impacting the resulting O3 photochemical formation in the chemistry model. To reduce the impact of a moist bias in the simulations on warm cloud formation, nudging with the analysis water mixing ratio above the planetary boundary layer (PBL) was applied. However, due to poor analysis vertical temperature profiles, applying analysis nudging also increased the errors in the modeled inversion layer vertical structure compared to observational nudging. Combining both observational and analysis nudging methods resulted in unrealistically extreme stratified stability that trapped pollutants at the lowest elevations at the center of the Uintah Basin and yielded the worst WRF performance in simulating inversion layer structure among the four sensitivity tests. The results of this study illustrate the importance of carefully considering the representativeness and quality of the observational and model analysis data sets when applying nudging techniques within stable PBLs, and the need to evaluate model results on a basin-wide scale.

Relationship between strong-motion array parameters and the accuracy of source inversion and physical waves

USGS Publications Warehouse

Iida, M.; Miyatake, T.; Shimazaki, K.

1990-01-01

We develop general rules for a strong-motion array layout on the basis of our method of applying a prediction analysis to a source inversion scheme. A systematic analysis is done to obtain a relationship between fault-array parameters and the accuracy of a source inversion. Our study of the effects of various physical waves indicates that surface waves at distant stations contribute significantly to the inversion accuracy for the inclined fault plane, whereas only far-field body waves at both small and large distances contribute to the inversion accuracy for the vertical fault, which produces more phase interference. These observations imply the adequacy of the half-space approximation used throughout our present study and suggest rules for actual array designs. -from Authors

Sharp Boundary Inversion of 2D Magnetotelluric Data using Bayesian Method.

NASA Astrophysics Data System (ADS)

Zhou, S.; Huang, Q.

2017-12-01

Normally magnetotelluric(MT) inversion method cannot show the distribution of underground resistivity with clear boundary, even if there are obviously different blocks. Aiming to solve this problem, we develop a Bayesian structure to inverse 2D MT sharp boundary data, using boundary location and inside resistivity as the random variables. Firstly, we use other MT inversion results, like ModEM, to analyze the resistivity distribution roughly. Then, we select the suitable random variables and change its data format to traditional staggered grid parameters, which can be used to do finite difference forward part. Finally, we can shape the posterior probability density(PPD), which contains all the prior information and model-data correlation, by Markov Chain Monte Carlo(MCMC) sampling from prior distribution. The depth, resistivity and their uncertainty can be valued. It also works for sensibility estimation. We applied the method to a synthetic case, which composes two large abnormal blocks in a trivial background. We consider the boundary smooth and the near true model weight constrains that mimic joint inversion or constrained inversion, then we find that the model results a more precise and focused depth distribution. And we also test the inversion without constrains and find that the boundary could also be figured, though not as well. Both inversions have a good valuation of resistivity. The constrained result has a lower root mean square than ModEM inversion result. The data sensibility obtained via PPD shows that the resistivity is the most sensible, center depth comes second and both sides are the worst.

A Joint Method of Envelope Inversion Combined with Hybrid-domain Full Waveform Inversion

NASA Astrophysics Data System (ADS)

CUI, C.; Hou, W.

2017-12-01

Full waveform inversion (FWI) aims to construct high-precision subsurface models by fully using the information in seismic records, including amplitude, travel time, phase and so on. However, high non-linearity and the absence of low frequency information in seismic data lead to the well-known cycle skipping problem and make inversion easily fall into local minima. In addition, those 3D inversion methods that are based on acoustic approximation ignore the elastic effects in real seismic field, and make inversion harder. As a result, the accuracy of final inversion results highly relies on the quality of initial model. In order to improve stability and quality of inversion results, multi-scale inversion that reconstructs subsurface model from low to high frequency are applied. But, the absence of very low frequencies (< 3Hz) in field data is still bottleneck in the FWI. By extracting ultra low-frequency data from field data, envelope inversion is able to recover low wavenumber model with a demodulation operator (envelope operator), though the low frequency data does not really exist in field data. To improve the efficiency and viability of the inversion, in this study, we proposed a joint method of envelope inversion combined with hybrid-domain FWI. First, we developed 3D elastic envelope inversion, and the misfit function and the corresponding gradient operator were derived. Then we performed hybrid-domain FWI with envelope inversion result as initial model which provides low wavenumber component of model. Here, forward modeling is implemented in the time domain and inversion in the frequency domain. To accelerate the inversion, we adopt CPU/GPU heterogeneous computing techniques. There were two levels of parallelism. In the first level, the inversion tasks are decomposed and assigned to each computation node by shot number. In the second level, GPU multithreaded programming is used for the computation tasks in each node, including forward modeling, envelope extraction, DFT (discrete Fourier transform) calculation and gradients calculation. Numerical tests demonstrated that the combined envelope inversion + hybrid-domain FWI could obtain much faithful and accurate result than conventional hybrid-domain FWI. The CPU/GPU heterogeneous parallel computation could improve the performance speed.

Computational analysis for biodegradation of exogenously depolymerizable polymer

NASA Astrophysics Data System (ADS)

Watanabe, M.; Kawai, F.

2018-03-01

This study shows that microbial growth and decay in a biodegradation process of exogenously depolymerizable polymer are controlled by consumption of monomer units. Experimental outcomes for residual polymer were incorporated in inverse analysis for a degradation rate. The Gauss-Newton method was applied to an inverse problem for two parameter values associated with the microbial population. A biodegradation process of polyethylene glycol was analyzed numerically, and numerical outcomes were obtained.

Responsiveness-informed multiple imputation and inverse probability-weighting in cohort studies with missing data that are non-monotone or not missing at random.

PubMed

Doidge, James C

2018-02-01

Population-based cohort studies are invaluable to health research because of the breadth of data collection over time, and the representativeness of their samples. However, they are especially prone to missing data, which can compromise the validity of analyses when data are not missing at random. Having many waves of data collection presents opportunity for participants' responsiveness to be observed over time, which may be informative about missing data mechanisms and thus useful as an auxiliary variable. Modern approaches to handling missing data such as multiple imputation and maximum likelihood can be difficult to implement with the large numbers of auxiliary variables and large amounts of non-monotone missing data that occur in cohort studies. Inverse probability-weighting can be easier to implement but conventional wisdom has stated that it cannot be applied to non-monotone missing data. This paper describes two methods of applying inverse probability-weighting to non-monotone missing data, and explores the potential value of including measures of responsiveness in either inverse probability-weighting or multiple imputation. Simulation studies are used to compare methods and demonstrate that responsiveness in longitudinal studies can be used to mitigate bias induced by missing data, even when data are not missing at random.

Visualizing bacterial tRNA identity determinants and antideterminants using function logos and inverse function logos

PubMed Central

Freyhult, Eva; Moulton, Vincent; Ardell, David H.

2006-01-01

Sequence logos are stacked bar graphs that generalize the notion of consensus sequence. They employ entropy statistics very effectively to display variation in a structural alignment of sequences of a common function, while emphasizing its over-represented features. Yet sequence logos cannot display features that distinguish functional subclasses within a structurally related superfamily nor do they display under-represented features. We introduce two extensions to address these needs: function logos and inverse logos. Function logos display subfunctions that are over-represented among sequences carrying a specific feature. Inverse logos generalize both sequence logos and function logos by displaying under-represented, rather than over-represented, features or functions in structural alignments. To make inverse logos, a compositional inverse is applied to the feature or function frequency distributions before logo construction, where a compositional inverse is a mathematical transform that makes common features or functions rare and vice versa. We applied these methods to a database of structurally aligned bacterial tDNAs to create highly condensed, birds-eye views of potentially all so-called identity determinants and antideterminants that confer specific amino acid charging or initiator function on tRNAs in bacteria. We recovered both known and a few potentially novel identity elements. Function logos and inverse logos are useful tools for exploratory bioinformatic analysis of structure–function relationships in sequence families and superfamilies. PMID:16473848

Development of a database for the verification of trans-ionospheric remote sensing systems

NASA Astrophysics Data System (ADS)

Leitinger, R.

2005-08-01

Remote sensing systems need verification by means of in-situ data or by means of model data. In the case of ionospheric occultation inversion, ionosphere tomography and other imaging methods on the basis of satellite-to-ground or satellite-to-satellite electron content, the availability of in-situ data with adequate spatial and temporal co-location is a very rare case, indeed. Therefore the method of choice for verification is to produce artificial electron content data with realistic properties, subject these data to the inversion/retrieval method, compare the results with model data and apply a suitable type of “goodness of fit” classification. Inter-comparison of inversion/retrieval methods should be done with sets of artificial electron contents in a “blind” (or even “double blind”) way. The set up of a relevant database for the COST 271 Action is described. One part of the database will be made available to everyone interested in testing of inversion/retrieval methods. The artificial electron content data are calculated by means of large-scale models that are “modulated” in a realistic way to include smaller scale and dynamic structures, like troughs and traveling ionospheric disturbances.

On the Development of Multi-Step Inverse FEM with Shell Model

NASA Astrophysics Data System (ADS)

Huang, Y.; Du, R.

2005-08-01

The inverse or one-step finite element approach is increasingly used in the sheet metal stamping industry to predict strain distribution and the initial blank shape in the preliminary design stage. Based on the existing theory, there are two types of method: one is based on the principle of virtual work and the other is based on the principle of extreme work. Much research has been conducted to improve the accuracy of simulation results. For example, based on the virtual work principle, Batoz et al. developed a new method using triangular DKT shell elements. In this new method, the bending and unbending effects are considered. Based on the principle of extreme work, Majlessi and et al. proposed the multi-step inverse approach with membrane elements and applied it to an axis-symmetric part. Lee and et al. presented an axis-symmetric shell element model to solve the similar problem. In this paper, a new multi-step inverse method is introduced with no limitation on the workpiece shape. It is a shell element model based on the virtual work principle. The new method is validated by means of comparing to the commercial software system (PAMSTAMP®). The comparison results indicate that the accuracy is good.

Getting in shape: Reconstructing three-dimensional long-track speed skating kinematics by comparing several body pose reconstruction techniques.

PubMed

van der Kruk, E; Schwab, A L; van der Helm, F C T; Veeger, H E J

2018-03-01

In gait studies body pose reconstruction (BPR) techniques have been widely explored, but no previous protocols have been developed for speed skating, while the peculiarities of the skating posture and technique do not automatically allow for the transfer of the results of those explorations to kinematic skating data. The aim of this paper is to determine the best procedure for body pose reconstruction and inverse dynamics of speed skating, and to what extend this choice influences the estimation of joint power. The results show that an eight body segment model together with a global optimization method with revolute joint in the knee and in the lumbosacral joint, while keeping the other joints spherical, would be the most realistic model to use for the inverse kinematics in speed skating. To determine joint power, this method should be combined with a least-square error method for the inverse dynamics. Reporting on the BPR technique and the inverse dynamic method is crucial to enable comparison between studies. Our data showed an underestimation of up to 74% in mean joint power when no optimization procedure was applied for BPR and an underestimation of up to 31% in mean joint power when a bottom-up inverse dynamics method was chosen instead of a least square error approach. Although these results are aimed at speed skating, reporting on the BPR procedure and the inverse dynamics method, together with setting a golden standard should be common practice in all human movement research to allow comparison between studies. Copyright © 2018 Elsevier Ltd. All rights reserved.

Scaling of plane-wave functions in statistically optimized near-field acoustic holography.

PubMed

Hald, Jørgen

2014-11-01

Statistically Optimized Near-field Acoustic Holography (SONAH) is a Patch Holography method, meaning that it can be applied in cases where the measurement area covers only part of the source surface. The method performs projections directly in the spatial domain, avoiding the use of spatial discrete Fourier transforms and the associated errors. First, an inverse problem is solved using regularization. For each calculation point a multiplication must then be performed with two transfer vectors--one to get the sound pressure and the other to get the particle velocity. Considering SONAH based on sound pressure measurements, existing derivations consider only pressure reconstruction when setting up the inverse problem, so the evanescent wave amplification associated with the calculation of particle velocity is not taken into account in the regularized solution of the inverse problem. The present paper introduces a scaling of the applied plane wave functions that takes the amplification into account, and it is shown that the previously published virtual source-plane retraction has almost the same effect. The effectiveness of the different solutions is verified through a set of simulated measurements.

Inverse kinematic solution for near-simple robots and its application to robot calibration

NASA Technical Reports Server (NTRS)

Hayati, Samad A.; Roston, Gerald P.

1986-01-01

This paper provides an inverse kinematic solution for a class of robot manipulators called near-simple manipulators. The kinematics of these manipulators differ from those of simple-robots by small parameter variations. Although most robots are by design simple, in practice, due to manufacturing tolerances, every robot is near-simple. The method in this paper gives an approximate inverse kinematics solution for real time applications based on the nominal solution for these robots. The validity of the results are tested both by a simulation study and by applying the algorithm to a PUMA robot.

Using Inverse Problem Methods with Surveillance Data in Pneumococcal Vaccination

PubMed Central

Sutton, Karyn L.; Banks, H. T.; Castillo-Chavez, Carlos

2010-01-01

The design and evaluation of epidemiological control strategies is central to public health policy. While inverse problem methods are routinely used in many applications, this remains an area in which their use is relatively rare, although their potential impact is great. We describe methods particularly relevant to epidemiological modeling at the population level. These methods are then applied to the study of pneumococcal vaccination strategies as a relevant example which poses many challenges common to other infectious diseases. We demonstrate that relevant yet typically unknown parameters may be estimated, and show that a calibrated model may used to assess implemented vaccine policies through the estimation of parameters if vaccine history is recorded along with infection and colonization information. Finally, we show how one might determine an appropriate level of refinement or aggregation in the age-structured model given age-stratified observations. These results illustrate ways in which the collection and analysis of surveillance data can be improved using inverse problem methods. PMID:20209093

Decoupled Method for Reconstruction of Surface Conditions From Internal Temperatures On Ablative Materials With Uncertain Recession Model

NASA Technical Reports Server (NTRS)

Oliver, A. Brandon

2017-01-01

Obtaining measurements of flight environments on ablative heat shields is both critical for spacecraft development and extremely challenging due to the harsh heating environment and surface recession. Thermocouples installed several millimeters below the surface are commonly used to measure the heat shield temperature response, but an ill-posed inverse heat conduction problem must be solved to reconstruct the surface heating environment from these measurements. Ablation can contribute substantially to the measurement response making solutions to the inverse problem strongly dependent on the recession model, which is often poorly characterized. To enable efficient surface reconstruction for recession model sensitivity analysis, a method for decoupling the surface recession evaluation from the inverse heat conduction problem is presented. The decoupled method is shown to provide reconstructions of equivalent accuracy to the traditional coupled method but with substantially reduced computational effort. These methods are applied to reconstruct the environments on the Mars Science Laboratory heat shield using diffusion limit and kinetically limited recession models.

The effects of core-reflected waves on finite fault inversion with teleseismic body wave data

NASA Astrophysics Data System (ADS)

Qian, Y.; Ni, S.; Wei, S.

2016-12-01

Reliable estimation of rupture processes for a large earthquake is valuable for post-seismic rescue, tsunami alert, seismotectonic studies, as well as earthquake physics. Finite-fault inversion has been widely accepted to reconstruct the spatial-temporal distribution of rupture processes, which can be obtained by individual or jointly inversion of seismic, geodetic and tsunami data sets. Among the above observations, teleseismic (30° 90°) body waves, usually P and SH waves, have been used extensively in such inversions because their propagation are well understood and readily available for large earthquakes with good coverages of slowness and azimuth. However, finite fault inversion methods usually assume turning P and SH waves without inclusion of core-reflected waves when calculating the synthetic waveforms, which may result in systematic error in finite-fault inversions. For the core-reflected SH wave ScS, it is expected to be strong due to total reflection from Core-Mantle-Boundary. Moreover, the time interval between direct S and ScS could be smaller than the duration of large earthquakes for large epicentral distances. In order to improve the accuracy of finite fault inversion with teleseismic body waves, we develop a procedure named multitel3 to compute Greens' functions that contain both turning waves (P, pP, sP, S, sS et al.) and core-reflected phases (PcP and ScS) and apply it to finite fault inversions. This ray-based method can rapidly calculate teleseismic body wave synthetics with flexibility for path calibration of 3D mantle structure. The new Green's function is plugged into finite fault inversion package to replace the original Green's function with only turning P and SH waves. With the 2008 Mw7.9 Wenchuan earthquake as example, a series of numerical tests conducted on synthetic data are used to assess the performance of our approach. We also explore this new procedure's stability when there are discrepancies between the parameters of input model and the priori information of inverse model, such as strike, dip of finite fault and so on. With the quantified code, we apply it to study rupture process of the 2016 Mw7.8 Sumatra earthquake.

Coupled Hydrogeophysical Inversion and Hydrogeological Data Fusion

NASA Astrophysics Data System (ADS)

Cirpka, O. A.; Schwede, R. L.; Li, W.

2012-12-01

Tomographic geophysical monitoring methods give the opportunity to observe hydrogeological tests at higher spatial resolution than is possible with classical hydraulic monitoring tools. This has been demonstrated in a substantial number of studies in which electrical resistivity tomography (ERT) has been used to monitor salt-tracer experiments. It is now accepted that inversion of such data sets requires a fully coupled framework, explicitly accounting for the hydraulic processes (groundwater flow and solute transport), the relationship between solute and geophysical properties (petrophysical relationship such as Archie's law), and the governing equations of the geophysical surveying techniques (e.g., the Poisson equation) as consistent coupled system. These data sets can be amended with data from other - more direct - hydrogeological tests to infer the distribution of hydraulic aquifer parameters. In the inversion framework, meaningful condensation of data does not only contribute to inversion efficiency but also increases the stability of the inversion. In particular, transient concentration data themselves only weakly depend on hydraulic conductivity, and model improvement using gradient-based methods is only possible when a substantial agreement between measurements and model output already exists. The latter also holds when concentrations are monitored by ERT. Tracer arrival times, by contrast, show high sensitivity and a more monotonic dependence on hydraulic conductivity than concentrations themselves. Thus, even without using temporal-moment generating equations, inverting travel times rather than concentrations or related geoelectrical signals themselves is advantageous. We have applied this approach to concentrations measured directly or via ERT, and to heat-tracer data. We present a consistent inversion framework including temporal moments of concentrations, geoelectrical signals obtained during salt-tracer tests, drawdown data from hydraulic tomography and flowmeter measurements to identify mainly the hydraulic-conductivity distribution. By stating the inversion as geostatistical conditioning problem, we obtain parameter sets together with their correlated uncertainty. While we have applied the quasi-linear geostatistical approach as inverse kernel, other methods - such as ensemble Kalman methods - may suit the same purpose, particularly when many data points are to be included. In order to identify 3-D fields, discretized by about 50 million grid points, we use the high-performance-computing framework DUNE to solve the involved partial differential equations on midrange computer cluster. We have quantified the worth of different data types in these inference problems. In practical applications, the constitutive relationships between geophysical, thermal, and hydraulic properties can pose a problem, requiring additional inversion. However, not well constrained transient boundary conditions may put inversion efforts on larger (e.g. regional) scales even more into question. We envision that future hydrogeophysical inversion efforts will target boundary conditions, such as groundwater recharge rates, in conjunction with - or instead of - aquifer parameters. By this, the distinction between data assimilation and parameter estimation will gradually vanish.

Inverse problems with nonnegative and sparse solutions: algorithms and application to the phase retrieval problem

NASA Astrophysics Data System (ADS)

Quy Muoi, Pham; Nho Hào, Dinh; Sahoo, Sujit Kumar; Tang, Dongliang; Cong, Nguyen Huu; Dang, Cuong

2018-05-01

In this paper, we study a gradient-type method and a semismooth Newton method for minimization problems in regularizing inverse problems with nonnegative and sparse solutions. We propose a special penalty functional forcing the minimizers of regularized minimization problems to be nonnegative and sparse, and then we apply the proposed algorithms in a practical the problem. The strong convergence of the gradient-type method and the local superlinear convergence of the semismooth Newton method are proven. Then, we use these algorithms for the phase retrieval problem and illustrate their efficiency in numerical examples, particularly in the practical problem of optical imaging through scattering media where all the noises from experiment are presented.

Integrated seismic stochastic inversion and multi-attributes to delineate reservoir distribution: Case study MZ fields, Central Sumatra Basin

NASA Astrophysics Data System (ADS)

Haris, A.; Novriyani, M.; Suparno, S.; Hidayat, R.; Riyanto, A.

2017-07-01

This study presents the integration of seismic stochastic inversion and multi-attributes for delineating the reservoir distribution in term of lithology and porosity in the formation within depth interval between the Top Sihapas and Top Pematang. The method that has been used is a stochastic inversion, which is integrated with multi-attribute seismic by applying neural network Probabilistic Neural Network (PNN). Stochastic methods are used to predict the probability mapping sandstone as the result of impedance varied with 50 realizations that will produce a good probability. Analysis of Stochastic Seismic Tnversion provides more interpretive because it directly gives the value of the property. Our experiment shows that AT of stochastic inversion provides more diverse uncertainty so that the probability value will be close to the actual values. The produced AT is then used for an input of a multi-attribute analysis, which is used to predict the gamma ray, density and porosity logs. To obtain the number of attributes that are used, stepwise regression algorithm is applied. The results are attributes which are used in the process of PNN. This PNN method is chosen because it has the best correlation of others neural network method. Finally, we interpret the product of the multi-attribute analysis are in the form of pseudo-gamma ray volume, density volume and volume of pseudo-porosity to delineate the reservoir distribution. Our interpretation shows that the structural trap is identified in the southeastern part of study area, which is along the anticline.

Mixed linear-nonlinear fault slip inversion: Bayesian inference of model, weighting, and smoothing parameters

NASA Astrophysics Data System (ADS)

Fukuda, J.; Johnson, K. M.

2009-12-01

Studies utilizing inversions of geodetic data for the spatial distribution of coseismic slip on faults typically present the result as a single fault plane and slip distribution. Commonly the geometry of the fault plane is assumed to be known a priori and the data are inverted for slip. However, sometimes there is not strong a priori information on the geometry of the fault that produced the earthquake and the data is not always strong enough to completely resolve the fault geometry. We develop a method to solve for the full posterior probability distribution of fault slip and fault geometry parameters in a Bayesian framework using Monte Carlo methods. The slip inversion problem is particularly challenging because it often involves multiple data sets with unknown relative weights (e.g. InSAR, GPS), model parameters that are related linearly (slip) and nonlinearly (fault geometry) through the theoretical model to surface observations, prior information on model parameters, and a regularization prior to stabilize the inversion. We present the theoretical framework and solution method for a Bayesian inversion that can handle all of these aspects of the problem. The method handles the mixed linear/nonlinear nature of the problem through combination of both analytical least-squares solutions and Monte Carlo methods. We first illustrate and validate the inversion scheme using synthetic data sets. We then apply the method to inversion of geodetic data from the 2003 M6.6 San Simeon, California earthquake. We show that the uncertainty in strike and dip of the fault plane is over 20 degrees. We characterize the uncertainty in the slip estimate with a volume around the mean fault solution in which the slip most likely occurred. Slip likely occurred somewhere in a volume that extends 5-10 km in either direction normal to the fault plane. We implement slip inversions with both traditional, kinematic smoothing constraints on slip and a simple physical condition of uniform stress drop.

Elastic Cherenkov effects in transversely isotropic soft materials-I: Theoretical analysis, simulations and inverse method

NASA Astrophysics Data System (ADS)

Li, Guo-Yang; Zheng, Yang; Liu, Yanlin; Destrade, Michel; Cao, Yanping

2016-11-01

A body force concentrated at a point and moving at a high speed can induce shear-wave Mach cones in dusty-plasma crystals or soft materials, as observed experimentally and named the elastic Cherenkov effect (ECE). The ECE in soft materials forms the basis of the supersonic shear imaging (SSI) technique, an ultrasound-based dynamic elastography method applied in clinics in recent years. Previous studies on the ECE in soft materials have focused on isotropic material models. In this paper, we investigate the existence and key features of the ECE in anisotropic soft media, by using both theoretical analysis and finite element (FE) simulations, and we apply the results to the non-invasive and non-destructive characterization of biological soft tissues. We also theoretically study the characteristics of the shear waves induced in a deformed hyperelastic anisotropic soft material by a source moving with high speed, considering that contact between the ultrasound probe and the soft tissue may lead to finite deformation. On the basis of our theoretical analysis and numerical simulations, we propose an inverse approach to infer both the anisotropic and hyperelastic parameters of incompressible transversely isotropic (TI) soft materials. Finally, we investigate the properties of the solutions to the inverse problem by deriving the condition numbers in analytical form and performing numerical experiments. In Part II of the paper, both ex vivo and in vivo experiments are conducted to demonstrate the applicability of the inverse method in practical use.

Parsimony and goodness-of-fit in multi-dimensional NMR inversion

NASA Astrophysics Data System (ADS)

Babak, Petro; Kryuchkov, Sergey; Kantzas, Apostolos

2017-01-01

Multi-dimensional nuclear magnetic resonance (NMR) experiments are often used for study of molecular structure and dynamics of matter in core analysis and reservoir evaluation. Industrial applications of multi-dimensional NMR involve a high-dimensional measurement dataset with complicated correlation structure and require rapid and stable inversion algorithms from the time domain to the relaxation rate and/or diffusion domains. In practice, applying existing inverse algorithms with a large number of parameter values leads to an infinite number of solutions with a reasonable fit to the NMR data. The interpretation of such variability of multiple solutions and selection of the most appropriate solution could be a very complex problem. In most cases the characteristics of materials have sparse signatures, and investigators would like to distinguish the most significant relaxation and diffusion values of the materials. To produce an easy to interpret and unique NMR distribution with the finite number of the principal parameter values, we introduce a new method for NMR inversion. The method is constructed based on the trade-off between the conventional goodness-of-fit approach to multivariate data and the principle of parsimony guaranteeing inversion with the least number of parameter values. We suggest performing the inversion of NMR data using the forward stepwise regression selection algorithm. To account for the trade-off between goodness-of-fit and parsimony, the objective function is selected based on Akaike Information Criterion (AIC). The performance of the developed multi-dimensional NMR inversion method and its comparison with conventional methods are illustrated using real data for samples with bitumen, water and clay.

Joint time/frequency-domain inversion of reflection data for seabed geoacoustic profiles and uncertainties.

PubMed

Dettmer, Jan; Dosso, Stan E; Holland, Charles W

2008-03-01

This paper develops a joint time/frequency-domain inversion for high-resolution single-bounce reflection data, with the potential to resolve fine-scale profiles of sediment velocity, density, and attenuation over small seafloor footprints (approximately 100 m). The approach utilizes sequential Bayesian inversion of time- and frequency-domain reflection data, employing ray-tracing inversion for reflection travel times and a layer-packet stripping method for spherical-wave reflection-coefficient inversion. Posterior credibility intervals from the travel-time inversion are passed on as prior information to the reflection-coefficient inversion. Within the reflection-coefficient inversion, parameter information is passed from one layer packet inversion to the next in terms of marginal probability distributions rotated into principal components, providing an efficient approach to (partially) account for multi-dimensional parameter correlations with one-dimensional, numerical distributions. Quantitative geoacoustic parameter uncertainties are provided by a nonlinear Gibbs sampling approach employing full data error covariance estimation (including nonstationary effects) and accounting for possible biases in travel-time picks. Posterior examination of data residuals shows the importance of including data covariance estimates in the inversion. The joint inversion is applied to data collected on the Malta Plateau during the SCARAB98 experiment.

Comparative Study of Three Data Assimilation Methods for Ice Sheet Model Initialisation

NASA Astrophysics Data System (ADS)

Mosbeux, Cyrille; Gillet-Chaulet, Fabien; Gagliardini, Olivier

2015-04-01

The current global warming has direct consequences on ice-sheet mass loss contributing to sea level rise. This loss is generally driven by an acceleration of some coastal outlet glaciers and reproducing these mechanisms is one of the major issues in ice-sheet and ice flow modelling. The construction of an initial state, as close as possible to current observations, is required as a prerequisite before producing any reliable projection of the evolution of ice-sheets. For this step, inverse methods are often used to infer badly known or unknown parameters. For instance, the adjoint inverse method has been implemented and applied with success by different authors in different ice flow models in order to infer the basal drag [ Schafer et al., 2012; Gillet-chauletet al., 2012; Morlighem et al., 2010]. Others data fields, such as ice surface and bedrock topography, are easily measurable with more or less uncertainty but only locally along tracks and interpolated on finer model grid. All these approximations lead to errors on the data elevation model and give rise to an ill-posed problem inducing non-physical anomalies in flux divergence [Seroussi et al, 2011]. A solution to dissipate these divergences of flux is to conduct a surface relaxation step at the expense of the accuracy of the modelled surface [Gillet-Chaulet et al., 2012]. Other solutions, based on the inversion of ice thickness and basal drag were proposed [Perego et al., 2014; Pralong & Gudmundsson, 2011]. In this study, we create a twin experiment to compare three different assimilation algorithms based on inverse methods and nudging to constrain the bedrock friction and the bedrock elevation: (i) cyclic inversion of friction parameter and bedrock topography using adjoint method, (ii) cycles coupling inversion of friction parameter using adjoint method and nudging of bedrock topography, (iii) one step inversion of both parameters with adjoint method. The three methods show a clear improvement in parameters knowledge leading to a significant reduction of flux divergence of the model before forecasting.

The application of the pilot points in groundwater numerical inversion model

NASA Astrophysics Data System (ADS)

Hu, Bin; Teng, Yanguo; Cheng, Lirong

2015-04-01

Numerical inversion simulation of groundwater has been widely applied in groundwater. Compared to traditional forward modeling, inversion model has more space to study. Zones and inversing modeling cell by cell are conventional methods. Pilot points is a method between them. The traditional inverse modeling method often uses software dividing the model into several zones with a few parameters needed to be inversed. However, distribution is usually too simple for modeler and result of simulation deviation. Inverse cell by cell will get the most actual parameter distribution in theory, but it need computational complexity greatly and quantity of survey data for geological statistical simulation areas. Compared to those methods, pilot points distribute a set of points throughout the different model domains for parameter estimation. Property values are assigned to model cells by Kriging to ensure geological units within the parameters of heterogeneity. It will reduce requirements of simulation area geological statistics and offset the gap between above methods. Pilot points can not only save calculation time, increase fitting degree, but also reduce instability of numerical model caused by numbers of parameters and other advantages. In this paper, we use pilot point in a field which structure formation heterogeneity and hydraulics parameter was unknown. We compare inversion modeling results of zones and pilot point methods. With the method of comparative analysis, we explore the characteristic of pilot point in groundwater inversion model. First, modeler generates an initial spatially correlated field given a geostatistical model by the description of the case site with the software named Groundwater Vistas 6. Defining Kriging to obtain the value of the field functions over the model domain on the basis of their values at measurement and pilot point locations (hydraulic conductivity), then we assign pilot points to the interpolated field which have been divided into 4 zones. And add range of disturbance values to inversion targets to calculate the value of hydraulic conductivity. Third, after inversion calculation (PEST), the interpolated field will minimize an objective function measuring the misfit between calculated and measured data. It's an optimization problem to find the optimum value of parameters. After the inversion modeling, the following major conclusion can be found out: (1) In a field structure formation is heterogeneity, the results of pilot point method is more real: better fitting result of parameters, more stable calculation of numerical simulation (stable residual distribution). Compared to zones, it is better of reflecting the heterogeneity of study field. (2) Pilot point method ensures that each parameter is sensitive and not entirely dependent on other parameters. Thus it guarantees the relative independence and authenticity of parameters evaluation results. However, it costs more time to calculate than zones. Key words: groundwater; pilot point; inverse model; heterogeneity; hydraulic conductivity

Inversion method based on stochastic optimization for particle sizing.

PubMed

Sánchez-Escobar, Juan Jaime; Barbosa-Santillán, Liliana Ibeth; Vargas-Ubera, Javier; Aguilar-Valdés, Félix

2016-08-01

A stochastic inverse method is presented based on a hybrid evolutionary optimization algorithm (HEOA) to retrieve a monomodal particle-size distribution (PSD) from the angular distribution of scattered light. By solving an optimization problem, the HEOA (with the Fraunhofer approximation) retrieves the PSD from an intensity pattern generated by Mie theory. The analyzed light-scattering pattern can be attributed to unimodal normal, gamma, or lognormal distribution of spherical particles covering the interval of modal size parameters 46≤α≤150. The HEOA ensures convergence to the near-optimal solution during the optimization of a real-valued objective function by combining the advantages of a multimember evolution strategy and locally weighted linear regression. The numerical results show that our HEOA can be satisfactorily applied to solve the inverse light-scattering problem.

Frequency and time domain three-dimensional inversion of electromagnetic data for a grounded-wire source

NASA Astrophysics Data System (ADS)

Sasaki, Yutaka; Yi, Myeong-Jong; Choi, Jihyang; Son, Jeong-Sul

2015-01-01

We present frequency- and time-domain three-dimensional (3-D) inversion approaches that can be applied to transient electromagnetic (TEM) data from a grounded-wire source using a PC. In the direct time-domain approach, the forward solution and sensitivity were obtained in the frequency domain using a finite-difference technique, and the frequency response was then Fourier-transformed using a digital filter technique. In the frequency-domain approach, TEM data were Fourier-transformed using a smooth-spectrum inversion method, and the recovered frequency response was then inverted. The synthetic examples show that for the time derivative of magnetic field, frequency-domain inversion of TEM data performs almost as well as time-domain inversion, with a significant reduction in computational time. In our synthetic studies, we also compared the resolution capabilities of the ground and airborne TEM and controlled-source audio-frequency magnetotelluric (CSAMT) data resulting from a common grounded wire. An airborne TEM survey at 200-m elevation achieved a resolution for buried conductors almost comparable to that of the ground TEM method. It is also shown that the inversion of CSAMT data was able to detect a 3-D resistivity structure better than the TEM inversion, suggesting an advantage of electric-field measurements over magnetic-field-only measurements.

The time-lapse AVO difference inversion for changes in reservoir parameters

NASA Astrophysics Data System (ADS)

Longxiao, Zhi; Hanming, Gu; Yan, Li

2016-12-01

The result of conventional time-lapse seismic processing is the difference between the amplitude and the post-stack seismic data. Although stack processing can improve the signal-to-noise ratio (SNR) of seismic data, it also causes a considerable loss of important information about the amplitude changes and only gives the qualitative interpretation. To predict the changes in reservoir fluid more precisely and accurately, we also need the quantitative information of the reservoir. To achieve this aim, we develop the method of time-lapse AVO (amplitude versus offset) difference inversion. For the inversion of reservoir changes in elastic parameters, we apply the Gardner equation as the constraint and convert the three-parameter inversion of elastic parameter changes into a two-parameter inversion to make the inversion more stable. For the inversion of variations in the reservoir parameters, we infer the relation between the difference of the reflection coefficient and variations in the reservoir parameters, and then invert reservoir parameter changes directly. The results of the theoretical modeling computation and practical application show that our method can estimate the relative variations in reservoir density, P-wave and S-wave velocity, calculate reservoir changes in water saturation and effective pressure accurately, and then provide reference for the rational exploitation of the reservoir.

Full-Physics Inverse Learning Machine for Satellite Remote Sensing of Ozone Profile Shapes and Tropospheric Columns

NASA Astrophysics Data System (ADS)

Xu, J.; Heue, K.-P.; Coldewey-Egbers, M.; Romahn, F.; Doicu, A.; Loyola, D.

2018-04-01

Characterizing vertical distributions of ozone from nadir-viewing satellite measurements is known to be challenging, particularly the ozone information in the troposphere. A novel retrieval algorithm called Full-Physics Inverse Learning Machine (FP-ILM), has been developed at DLR in order to estimate ozone profile shapes based on machine learning techniques. In contrast to traditional inversion methods, the FP-ILM algorithm formulates the profile shape retrieval as a classification problem. Its implementation comprises a training phase to derive an inverse function from synthetic measurements, and an operational phase in which the inverse function is applied to real measurements. This paper extends the ability of the FP-ILM retrieval to derive tropospheric ozone columns from GOME- 2 measurements. Results of total and tropical tropospheric ozone columns are compared with the ones using the official GOME Data Processing (GDP) product and the convective-cloud-differential (CCD) method, respectively. Furthermore, the FP-ILM framework will be used for the near-real-time processing of the new European Sentinel sensors with their unprecedented spectral and spatial resolution and corresponding large increases in the amount of data.

Viscoacoustic anisotropic full waveform inversion

NASA Astrophysics Data System (ADS)

Qu, Yingming; Li, Zhenchun; Huang, Jianping; Li, Jinli

2017-01-01

A viscoacoustic vertical transverse isotropic (VTI) quasi-differential wave equation, which takes account for both the viscosity and anisotropy of media, is proposed for wavefield simulation in this study. The finite difference method is used to solve the equations, for which the attenuation terms are solved in the wavenumber domain, and all remaining terms in the time-space domain. To stabilize the adjoint wavefield, robust regularization operators are applied to the wave equation to eliminate the high-frequency component of the numerical noise produced during the backward propagation of the viscoacoustic wavefield. Based on these strategies, we derive the corresponding gradient formula and implement a viscoacoustic VTI full waveform inversion (FWI). Numerical tests verify that our proposed viscoacoustic VTI FWI can produce accurate and stable inversion results for viscoacoustic VTI data sets. In addition, we test our method's sensitivity to velocity, Q, and anisotropic parameters. Our results show that the sensitivity to velocity is much higher than that to Q and anisotropic parameters. As such, our proposed method can produce acceptable inversion results as long as the Q and anisotropic parameters are within predefined thresholds.

Large-scale 3D inversion of marine controlled source electromagnetic data using the integral equation method

NASA Astrophysics Data System (ADS)

Zhdanov, M. S.; Cuma, M.; Black, N.; Wilson, G. A.

2009-12-01

The marine controlled source electromagnetic (MCSEM) method has become widely used in offshore oil and gas exploration. Interpretation of MCSEM data is still a very challenging problem, especially if one would like to take into account the realistic 3D structure of the subsurface. The inversion of MCSEM data is complicated by the fact that the EM response of a hydrocarbon-bearing reservoir is very weak in comparison with the background EM fields generated by an electric dipole transmitter in complex geoelectrical structures formed by a conductive sea-water layer and the terranes beneath it. In this paper, we present a review of the recent developments in the area of large-scale 3D EM forward modeling and inversion. Our approach is based on using a new integral form of Maxwell’s equations allowing for an inhomogeneous background conductivity, which results in a numerically effective integral representation for 3D EM field. This representation provides an efficient tool for the solution of 3D EM inverse problems. To obtain a robust inverse model of the conductivity distribution, we apply regularization based on a focusing stabilizing functional which allows for the recovery of models with both smooth and sharp geoelectrical boundaries. The method is implemented in a fully parallel computer code, which makes it possible to run large-scale 3D inversions on grids with millions of inversion cells. This new technique can be effectively used for active EM detection and monitoring of the subsurface targets.

Building a 3D faulted a priori model for stratigraphic inversion: Illustration of a new methodology applied on a North Sea field case study

NASA Astrophysics Data System (ADS)

Rainaud, Jean-François; Clochard, Vincent; Delépine, Nicolas; Crabié, Thomas; Poudret, Mathieu; Perrin, Michel; Klein, Emmanuel

2018-07-01

Accurate reservoir characterization is needed all along the development of an oil and gas field study. It helps building 3D numerical reservoir simulation models for estimating the original oil and gas volumes in place and for simulating fluid flow behaviors. At a later stage of the field development, reservoir characterization can also help deciding which recovery techniques need to be used for fluids extraction. In complex media, such as faulted reservoirs, flow behavior predictions within volumes close to faults can be a very challenging issue. During the development plan, it is necessary to determine which types of communication exist between faults or which potential barriers exist for fluid flows. The solving of these issues rests on accurate fault characterization. In most cases, faults are not preserved along reservoir characterization workflows. The memory of the interpreted faults from seismic is not kept during seismic inversion and further interpretation of the result. The goal of our study is at first to integrate a 3D fault network as a priori information into a model-based stratigraphic inversion procedure. Secondly, we apply our methodology on a well-known oil and gas case study over a typical North Sea field (UK Northern North Sea) in order to demonstrate its added value for determining reservoir properties. More precisely, the a priori model is composed of several geological units populated by physical attributes, they are extrapolated from well log data following the deposition mode, but usually a priori model building methods respect neither the 3D fault geometry nor the stratification dips on the fault sides. We address this difficulty by applying an efficient flattening method for each stratigraphic unit in our workflow. Even before seismic inversion, the obtained stratigraphic model has been directly used to model synthetic seismic on our case study. Comparisons between synthetic seismic obtained from our 3D fault network model give much lower residuals than with a "basic" stratigraphic model. Finally, we apply our model-based inversion considering both faulted and non-faulted a priori models. By comparing the rock impedances results obtain in the two cases, we can see a better delineation of the Brent-reservoir compartments by using the 3D faulted a priori model built with our method.

Fast inverse scattering solutions using the distorted Born iterative method and the multilevel fast multipole algorithm

PubMed Central

Hesford, Andrew J.; Chew, Weng C.

2010-01-01

The distorted Born iterative method (DBIM) computes iterative solutions to nonlinear inverse scattering problems through successive linear approximations. By decomposing the scattered field into a superposition of scattering by an inhomogeneous background and by a material perturbation, large or high-contrast variations in medium properties can be imaged through iterations that are each subject to the distorted Born approximation. However, the need to repeatedly compute forward solutions still imposes a very heavy computational burden. To ameliorate this problem, the multilevel fast multipole algorithm (MLFMA) has been applied as a forward solver within the DBIM. The MLFMA computes forward solutions in linear time for volumetric scatterers. The typically regular distribution and shape of scattering elements in the inverse scattering problem allow the method to take advantage of data redundancy and reduce the computational demands of the normally expensive MLFMA setup. Additional benefits are gained by employing Kaczmarz-like iterations, where partial measurements are used to accelerate convergence. Numerical results demonstrate both the efficiency of the forward solver and the successful application of the inverse method to imaging problems with dimensions in the neighborhood of ten wavelengths. PMID:20707438

Linear distributed source modeling of local field potentials recorded with intra-cortical electrode arrays.

PubMed

Hindriks, Rikkert; Schmiedt, Joscha; Arsiwalla, Xerxes D; Peter, Alina; Verschure, Paul F M J; Fries, Pascal; Schmid, Michael C; Deco, Gustavo

2017-01-01

Planar intra-cortical electrode (Utah) arrays provide a unique window into the spatial organization of cortical activity. Reconstruction of the current source density (CSD) underlying such recordings, however, requires "inverting" Poisson's equation. For inter-laminar recordings, this is commonly done by the CSD method, which consists in taking the second-order spatial derivative of the recorded local field potentials (LFPs). Although the CSD method has been tremendously successful in mapping the current generators underlying inter-laminar LFPs, its application to planar recordings is more challenging. While for inter-laminar recordings the CSD method seems reasonably robust against violations of its assumptions, is it unclear as to what extent this holds for planar recordings. One of the objectives of this study is to characterize the conditions under which the CSD method can be successfully applied to Utah array data. Using forward modeling, we find that for spatially coherent CSDs, the CSD method yields inaccurate reconstructions due to volume-conducted contamination from currents in deeper cortical layers. An alternative approach is to "invert" a constructed forward model. The advantage of this approach is that any a priori knowledge about the geometrical and electrical properties of the tissue can be taken into account. Although several inverse methods have been proposed for LFP data, the applicability of existing electroencephalographic (EEG) and magnetoencephalographic (MEG) inverse methods to LFP data is largely unexplored. Another objective of our study therefore, is to assess the applicability of the most commonly used EEG/MEG inverse methods to Utah array data. Our main conclusion is that these inverse methods provide more accurate CSD reconstructions than the CSD method. We illustrate the inverse methods using event-related potentials recorded from primary visual cortex of a macaque monkey during a motion discrimination task.

Linear distributed source modeling of local field potentials recorded with intra-cortical electrode arrays

PubMed Central

Schmiedt, Joscha; Arsiwalla, Xerxes D.; Peter, Alina; Verschure, Paul F. M. J.; Fries, Pascal; Schmid, Michael C.; Deco, Gustavo

2017-01-01

Planar intra-cortical electrode (Utah) arrays provide a unique window into the spatial organization of cortical activity. Reconstruction of the current source density (CSD) underlying such recordings, however, requires “inverting” Poisson’s equation. For inter-laminar recordings, this is commonly done by the CSD method, which consists in taking the second-order spatial derivative of the recorded local field potentials (LFPs). Although the CSD method has been tremendously successful in mapping the current generators underlying inter-laminar LFPs, its application to planar recordings is more challenging. While for inter-laminar recordings the CSD method seems reasonably robust against violations of its assumptions, is it unclear as to what extent this holds for planar recordings. One of the objectives of this study is to characterize the conditions under which the CSD method can be successfully applied to Utah array data. Using forward modeling, we find that for spatially coherent CSDs, the CSD method yields inaccurate reconstructions due to volume-conducted contamination from currents in deeper cortical layers. An alternative approach is to “invert” a constructed forward model. The advantage of this approach is that any a priori knowledge about the geometrical and electrical properties of the tissue can be taken into account. Although several inverse methods have been proposed for LFP data, the applicability of existing electroencephalographic (EEG) and magnetoencephalographic (MEG) inverse methods to LFP data is largely unexplored. Another objective of our study therefore, is to assess the applicability of the most commonly used EEG/MEG inverse methods to Utah array data. Our main conclusion is that these inverse methods provide more accurate CSD reconstructions than the CSD method. We illustrate the inverse methods using event-related potentials recorded from primary visual cortex of a macaque monkey during a motion discrimination task. PMID:29253006

Nonlinear refraction and reflection travel time tomography

USGS Publications Warehouse

Zhang, Jiahua; ten Brink, Uri S.; Toksoz, M.N.

1998-01-01

We develop a rapid nonlinear travel time tomography method that simultaneously inverts refraction and reflection travel times on a regular velocity grid. For travel time and ray path calculations, we apply a wave front method employing graph theory. The first-arrival refraction travel times are calculated on the basis of cell velocities, and the later refraction and reflection travel times are computed using both cell velocities and given interfaces. We solve a regularized nonlinear inverse problem. A Laplacian operator is applied to regularize the model parameters (cell slownesses and reflector geometry) so that the inverse problem is valid for a continuum. The travel times are also regularized such that we invert travel time curves rather than travel time points. A conjugate gradient method is applied to minimize the nonlinear objective function. After obtaining a solution, we perform nonlinear Monte Carlo inversions for uncertainty analysis and compute the posterior model covariance. In numerical experiments, we demonstrate that combining the first arrival refraction travel times with later reflection travel times can better reconstruct the velocity field as well as the reflector geometry. This combination is particularly important for modeling crustal structures where large velocity variations occur in the upper crust. We apply this approach to model the crustal structure of the California Borderland using ocean bottom seismometer and land data collected during the Los Angeles Region Seismic Experiment along two marine survey lines. Details of our image include a high-velocity zone under the Catalina Ridge, but a smooth gradient zone between. Catalina Ridge and San Clemente Ridge. The Moho depth is about 22 km with lateral variations. Copyright 1998 by the American Geophysical Union.

2D Inversion of Transient Electromagnetic Method (TEM)

NASA Astrophysics Data System (ADS)

Bortolozo, Cassiano Antonio; Luís Porsani, Jorge; Acácio Monteiro dos Santos, Fernando

2017-04-01

A new methodology was developed for 2D inversion of Transient Electromagnetic Method (TEM). The methodology consists in the elaboration of a set of routines in Matlab code for modeling and inversion of TEM data and the determination of the most efficient field array for the problem. In this research, the 2D TEM modeling uses the finite differences discretization. To solve the inversion problem, were applied an algorithm based on Marquardt technique, also known as Ridge Regression. The algorithm is stable and efficient and it is widely used in geoelectrical inversion problems. The main advantage of 1D survey is the rapid data acquisition in a large area, but in regions with two-dimensional structures or that need more details, is essential to use two-dimensional interpretation methodologies. For an efficient field acquisition we used in an innovative form the fixed-loop array, with a square transmitter loop (200m x 200m) and 25m spacing between the sounding points. The TEM surveys were conducted only inside the transmitter loop, in order to not deal with negative apparent resistivity values. Although it is possible to model the negative values, it makes the inversion convergence more difficult. Therefore the methodology described above has been developed in order to achieve maximum optimization of data acquisition. Since it is necessary only one transmitter loop disposition in the surface for each series of soundings inside the loop. The algorithms were tested with synthetic data and the results were essential to the interpretation of the results with real data and will be useful in future situations. With the inversion of the real data acquired over the Paraná Sedimentary Basin (PSB) was successful realized a 2D TEM inversion. The results indicate a robust geoelectrical characterization for the sedimentary and crystalline aquifers in the PSB. Therefore, using a new and relevant approach for 2D TEM inversion, this research effectively contributed to map the most promising regions for groundwater exploration. In addition, there was the development of new geophysical software that can be applied as an important tool for many geological/hydrogeological applications and educational purposes.

The Cagniard Method in Complex Time Revisited

DTIC Science & Technology

1991-04-04

make the p-integral take the form of a forward Laplace transform, so that the cascade of the two integrals can be identified as a forward and inverse ... transform , thereby making the actual integration unnecessary. Typically, the method is applied to an integral that represents one body wave plus other

Joint Geophysical Inversion With Multi-Objective Global Optimization Methods

NASA Astrophysics Data System (ADS)

Lelievre, P. G.; Bijani, R.; Farquharson, C. G.

2015-12-01

Pareto multi-objective global optimization (PMOGO) methods generate a suite of solutions that minimize multiple objectives (e.g. data misfits and regularization terms) in a Pareto-optimal sense. Providing a suite of models, as opposed to a single model that minimizes a weighted sum of objectives, allows a more complete assessment of the possibilities and avoids the often difficult choice of how to weight each objective. We are applying PMOGO methods to three classes of inverse problems. The first class are standard mesh-based problems where the physical property values in each cell are treated as continuous variables. The second class of problems are also mesh-based but cells can only take discrete physical property values corresponding to known or assumed rock units. In the third class we consider a fundamentally different type of inversion in which a model comprises wireframe surfaces representing contacts between rock units; the physical properties of each rock unit remain fixed while the inversion controls the position of the contact surfaces via control nodes. This third class of problem is essentially a geometry inversion, which can be used to recover the unknown geometry of a target body or to investigate the viability of a proposed Earth model. Joint inversion is greatly simplified for the latter two problem classes because no additional mathematical coupling measure is required in the objective function. PMOGO methods can solve numerically complicated problems that could not be solved with standard descent-based local minimization methods. This includes the latter two classes of problems mentioned above. There are significant increases in the computational requirements when PMOGO methods are used but these can be ameliorated using parallelization and problem dimension reduction strategies.

Near-real-time processing of a ceilometer network assisted with sun-photometer data: monitoring a dust outbreak over the Iberian Peninsula

NASA Astrophysics Data System (ADS)

Cazorla, Alberto; Andrés Casquero-Vera, Juan; Román, Roberto; Guerrero-Rascado, Juan Luis; Toledano, Carlos; Cachorro, Victoria E.; Orza, José Antonio G.; Cancillo, María Luisa; Serrano, Antonio; Titos, Gloria; Pandolfi, Marco; Alastuey, Andres; Hanrieder, Natalie; Alados-Arboledas, Lucas

2017-10-01

The interest in the use of ceilometers for optical aerosol characterization has increased in the last few years. They operate continuously almost unattended and are also much less expensive than lidars; hence, they can be distributed in dense networks over large areas. However, due to the low signal-to-noise ratio it is not always possible to obtain particle backscatter coefficient profiles, and the vast number of data generated require an automated and unsupervised method that ensures the quality of the profiles inversions. In this work we describe a method that uses aerosol optical depth (AOD) measurements from the AERONET network that it is applied for the calibration and automated quality assurance of inversion of ceilometer profiles. The method is compared with independent inversions obtained by co-located multiwavelength lidar measurements. A difference smaller than 15 % in backscatter is found between both instruments. This method is continuously and automatically applied to the Iberian Ceilometer Network (ICENET) and a case example during an unusually intense dust outbreak affecting the Iberian Peninsula between 20 and 24 February 2016 is shown. Results reveal that it is possible to obtain quantitative optical aerosol properties (particle backscatter coefficient) and discriminate the quality of these retrievals with ceilometers over large areas. This information has a great potential for alert systems and model assimilation and evaluation.

Ambient Seismic Source Inversion in a Heterogeneous Earth: Theory and Application to the Earth's Hum

NASA Astrophysics Data System (ADS)

Ermert, Laura; Sager, Korbinian; Afanasiev, Michael; Boehm, Christian; Fichtner, Andreas

2017-11-01

The sources of ambient seismic noise are extensively studied both to better understand their influence on ambient noise tomography and related techniques, and to infer constraints on their excitation mechanisms. Here we develop a gradient-based inversion method to infer the space-dependent and time-varying source power spectral density of the Earth's hum from cross correlations of continuous seismic data. The precomputation of wavefields using spectral elements allows us to account for both finite-frequency sensitivity and for three-dimensional Earth structure. Although similar methods have been proposed previously, they have not yet been applied to data to the best of our knowledge. We apply this method to image the seasonally varying sources of Earth's hum during North and South Hemisphere winter. The resulting models suggest that hum sources are localized, persistent features that occur at Pacific coasts or shelves and in the North Atlantic during North Hemisphere winter, as well as South Pacific coasts and several distinct locations in the Southern Ocean in South Hemisphere winter. The contribution of pelagic sources from the central North Pacific cannot be constrained. Besides improving the accuracy of noise source locations through the incorporation of finite-frequency effects and 3-D Earth structure, this method may be used in future cross-correlation waveform inversion studies to provide initial source models and source model updates.

Identification of complex stiffness tensor from waveform reconstruction

NASA Astrophysics Data System (ADS)

Leymarie, N.; Aristégui, C.; Audoin, B.; Baste, S.

2002-03-01

An inverse method is proposed in order to determine the viscoelastic properties of composite-material plates from the plane-wave transmitted acoustic field. Analytical formulations of both the plate transmission coefficient and its first and second derivatives are established, and included in a two-step inversion scheme. Two objective functions to be minimized are then designed by considering the well-known maximum-likelihood principle and by using an analytic signal formulation. Through these innovative objective functions, the robustness of the inversion process against high level of noise in waveforms is improved and the method can be applied to a very thin specimen. The suitability of the inversion process for viscoelastic property identification is demonstrated using simulated data for composite materials with different anisotropy and damping degrees. A study of the effect of the rheologic model choice on the elastic property identification emphasizes the relevance of using a phenomenological description considering viscosity. Experimental characterizations show then the good reliability of the proposed approach. Difficulties arise experimentally for particular anisotropic media.

Controlling bridging and pinching with pixel-based mask for inverse lithography

NASA Astrophysics Data System (ADS)

Kobelkov, Sergey; Tritchkov, Alexander; Han, JiWan

2016-03-01

Inverse Lithography Technology (ILT) has become a viable computational lithography candidate in recent years as it can produce mask output that results in process latitude and CD control in the fab that is hard to match with conventional OPC/SRAF insertion approaches. An approach to solving the inverse lithography problem as a nonlinear, constrained minimization problem over a domain mask pixels was suggested in the paper by Y. Granik "Fast pixel-based mask optimization for inverse lithography" in 2006. The present paper extends this method to satisfy bridging and pinching constraints imposed on print contours. Namely, there are suggested objective functions expressing penalty for constraints violations, and their minimization with gradient descent methods is considered. This approach has been tested with an ILT-based Local Printability Enhancement (LPTM) tool in an automated flow to eliminate hotspots that can be present on the full chip after conventional SRAF placement/OPC and has been applied in 14nm, 10nm node production, single and multiple-patterning flows.

3D CSEM inversion based on goal-oriented adaptive finite element method

NASA Astrophysics Data System (ADS)

Zhang, Y.; Key, K.

2016-12-01

We present a parallel 3D frequency domain controlled-source electromagnetic inversion code name MARE3DEM. Non-linear inversion of observed data is performed with the Occam variant of regularized Gauss-Newton optimization. The forward operator is based on the goal-oriented finite element method that efficiently calculates the responses and sensitivity kernels in parallel using a data decomposition scheme where independent modeling tasks contain different frequencies and subsets of the transmitters and receivers. To accommodate complex 3D conductivity variation with high flexibility and precision, we adopt the dual-grid approach where the forward mesh conforms to the inversion parameter grid and is adaptively refined until the forward solution converges to the desired accuracy. This dual-grid approach is memory efficient, since the inverse parameter grid remains independent from fine meshing generated around the transmitter and receivers by the adaptive finite element method. Besides, the unstructured inverse mesh efficiently handles multiple scale structures and allows for fine-scale model parameters within the region of interest. Our mesh generation engine keeps track of the refinement hierarchy so that the map of conductivity and sensitivity kernel between the forward and inverse mesh is retained. We employ the adjoint-reciprocity method to calculate the sensitivity kernels which establish a linear relationship between changes in the conductivity model and changes in the modeled responses. Our code uses a direcy solver for the linear systems, so the adjoint problem is efficiently computed by re-using the factorization from the primary problem. Further computational efficiency and scalability is obtained in the regularized Gauss-Newton portion of the inversion using parallel dense matrix-matrix multiplication and matrix factorization routines implemented with the ScaLAPACK library. We show the scalability, reliability and the potential of the algorithm to deal with complex geological scenarios by applying it to the inversion of synthetic marine controlled source EM data generated for a complex 3D offshore model with significant seafloor topography.

An Inverse Interpolation Method Utilizing In-Flight Strain Measurements for Determining Loads and Structural Response of Aerospace Vehicles

NASA Technical Reports Server (NTRS)

Shkarayev, S.; Krashantisa, R.; Tessler, A.

2004-01-01

An important and challenging technology aimed at the next generation of aerospace vehicles is that of structural health monitoring. The key problem is to determine accurately, reliably, and in real time the applied loads, stresses, and displacements experienced in flight, with such data establishing an information database for structural health monitoring. The present effort is aimed at developing a finite element-based methodology involving an inverse formulation that employs measured surface strains to recover the applied loads, stresses, and displacements in an aerospace vehicle in real time. The computational procedure uses a standard finite element model (i.e., "direct analysis") of a given airframe, with the subsequent application of the inverse interpolation approach. The inverse interpolation formulation is based on a parametric approximation of the loading and is further constructed through a least-squares minimization of calculated and measured strains. This procedure results in the governing system of linear algebraic equations, providing the unknown coefficients that accurately define the load approximation. Numerical simulations are carried out for problems involving various levels of structural approximation. These include plate-loading examples and an aircraft wing box. Accuracy and computational efficiency of the proposed method are discussed in detail. The experimental validation of the methodology by way of structural testing of an aircraft wing is also discussed.

C–IBI: Targeting cumulative coordination within an iterative protocol to derive coarse-grained models of (multi-component) complex fluids

DOE PAGES

de Oliveira, Tiago E.; Netz, Paulo A.; Kremer, Kurt; ...

2016-05-03

We present a coarse-graining strategy that we test for aqueous mixtures. The method uses pair-wise cumulative coordination as a target function within an iterative Boltzmann inversion (IBI) like protocol. We name this method coordination iterative Boltzmann inversion (C–IBI). While the underlying coarse-grained model is still structure based and, thus, preserves pair-wise solution structure, our method also reproduces solvation thermodynamics of binary and/or ternary mixtures. In addition, we observe much faster convergence within C–IBI compared to IBI. To validate the robustness, we apply C–IBI to study test cases of solvation thermodynamics of aqueous urea and a triglycine solvation in aqueous urea.

Angular dependence of multiangle dynamic light scattering for particle size distribution inversion using a self-adapting regularization algorithm

NASA Astrophysics Data System (ADS)

Li, Lei; Yu, Long; Yang, Kecheng; Li, Wei; Li, Kai; Xia, Min

2018-04-01

The multiangle dynamic light scattering (MDLS) technique can better estimate particle size distributions (PSDs) than single-angle dynamic light scattering. However, determining the inversion range, angular weighting coefficients, and scattering angle combination is difficult but fundamental to the reconstruction for both unimodal and multimodal distributions. In this paper, we propose a self-adapting regularization method called the wavelet iterative recursion nonnegative Tikhonov-Phillips-Twomey (WIRNNT-PT) algorithm. This algorithm combines a wavelet multiscale strategy with an appropriate inversion method and could self-adaptively optimize several noteworthy issues containing the choices of the weighting coefficients, the inversion range and the optimal inversion method from two regularization algorithms for estimating the PSD from MDLS measurements. In addition, the angular dependence of the MDLS for estimating the PSDs of polymeric latexes is thoroughly analyzed. The dependence of the results on the number and range of measurement angles was analyzed in depth to identify the optimal scattering angle combination. Numerical simulations and experimental results for unimodal and multimodal distributions are presented to demonstrate both the validity of the WIRNNT-PT algorithm and the angular dependence of MDLS and show that the proposed algorithm with a six-angle analysis in the 30-130° range can be satisfactorily applied to retrieve PSDs from MDLS measurements.

Bessel smoothing filter for spectral-element mesh

NASA Astrophysics Data System (ADS)

Trinh, P. T.; Brossier, R.; Métivier, L.; Virieux, J.; Wellington, P.

2017-06-01

Smoothing filters are extremely important tools in seismic imaging and inversion, such as for traveltime tomography, migration and waveform inversion. For efficiency, and as they can be used a number of times during inversion, it is important that these filters can easily incorporate prior information on the geological structure of the investigated medium, through variable coherent lengths and orientation. In this study, we promote the use of the Bessel filter to achieve these purposes. Instead of considering the direct application of the filter, we demonstrate that we can rely on the equation associated with its inverse filter, which amounts to the solution of an elliptic partial differential equation. This enhances the efficiency of the filter application, and also its flexibility. We apply this strategy within a spectral-element-based elastic full waveform inversion framework. Taking advantage of this formulation, we apply the Bessel filter by solving the associated partial differential equation directly on the spectral-element mesh through the standard weak formulation. This avoids cumbersome projection operators between the spectral-element mesh and a regular Cartesian grid, or expensive explicit windowed convolution on the finite-element mesh, which is often used for applying smoothing operators. The associated linear system is solved efficiently through a parallel conjugate gradient algorithm, in which the matrix vector product is factorized and highly optimized with vectorized computation. Significant scaling behaviour is obtained when comparing this strategy with the explicit convolution method. The theoretical numerical complexity of this approach increases linearly with the coherent length, whereas a sublinear relationship is observed practically. Numerical illustrations are provided here for schematic examples, and for a more realistic elastic full waveform inversion gradient smoothing on the SEAM II benchmark model. These examples illustrate well the efficiency and flexibility of the approach proposed.

Inverse targeting —An effective immunization strategy

NASA Astrophysics Data System (ADS)

Schneider, C. M.; Mihaljev, T.; Herrmann, H. J.

2012-05-01

We propose a new method to immunize populations or computer networks against epidemics which is more efficient than any continuous immunization method considered before. The novelty of our method resides in the way of determining the immunization targets. First we identify those individuals or computers that contribute the least to the disease spreading measured through their contribution to the size of the largest connected cluster in the social or a computer network. The immunization process follows the list of identified individuals or computers in inverse order, immunizing first those which are most relevant for the epidemic spreading. We have applied our immunization strategy to several model networks and two real networks, the Internet and the collaboration network of high-energy physicists. We find that our new immunization strategy is in the case of model networks up to 14%, and for real networks up to 33% more efficient than immunizing dynamically the most connected nodes in a network. Our strategy is also numerically efficient and can therefore be applied to large systems.

3D linear inversion of magnetic susceptibility data acquired by frequency domain EMI

NASA Astrophysics Data System (ADS)

Thiesson, J.; Tabbagh, A.; Simon, F.-X.; Dabas, M.

2017-01-01

Low induction number EMI instruments are able to simultaneously measure a soil's apparent magnetic susceptibility and electrical conductivity. This family of dual measurement instruments is highly useful for the analysis of soils and archeological sites. However, the electromagnetic properties of soils are found to vary over considerably different ranges: whereas their electrical conductivity varies from ≤ 0.1 to ≥ 100 mS/m, their relative magnetic permeability remains within a very small range, between 1.0001 and 1.01 SI. Consequently, although apparent conductivity measurements need to be inverted using non-linear processes, the variations of the apparent magnetic susceptibility can be approximated through the use of linear processes, as in the case of the magnetic prospection technique. Our proposed 3D inversion algorithm starts from apparent susceptibility data sets, acquired using different instruments over a given area. A reference vertical profile is defined by considering the mode of the vertical distributions of both the electrical resistivity and of the magnetic susceptibility. At each point of the mapped area, the reference vertical profile response is subtracted to obtain the apparent susceptibility variation dataset. A 2D horizontal Fourier transform is applied to these variation datasets and to the dipole (impulse) response of each instrument, a (vertical) 1D inversion is performed at each point in the spectral domain, and finally the resulting dataset is inverse transformed to restore the apparent 3D susceptibility variations. It has been shown that when applied to synthetic results, this method is able to correct the apparent deformations of a buried object resulting from the geometry of the instrument, and to restore reliable quantitative susceptibility contrasts. It also allows the thin layer solution, similar to that used in magnetic prospection, to be implemented. When applied to field data it initially delivers a level of contrast comparable to that obtained with a non-linear 3D inversion. Over four different sites, this method is able to produce, following an acceptably short computation time, realistic values for the lateral and vertical variations in susceptibility, which are significantly different to those given by a point-by-point 1D inversion.

Neuronal couplings between retinal ganglion cells inferred by efficient inverse statistical physics methods

PubMed Central

Cocco, Simona; Leibler, Stanislas; Monasson, Rémi

2009-01-01

Complexity of neural systems often makes impracticable explicit measurements of all interactions between their constituents. Inverse statistical physics approaches, which infer effective couplings between neurons from their spiking activity, have been so far hindered by their computational complexity. Here, we present 2 complementary, computationally efficient inverse algorithms based on the Ising and “leaky integrate-and-fire” models. We apply those algorithms to reanalyze multielectrode recordings in the salamander retina in darkness and under random visual stimulus. We find strong positive couplings between nearby ganglion cells common to both stimuli, whereas long-range couplings appear under random stimulus only. The uncertainty on the inferred couplings due to limitations in the recordings (duration, small area covered on the retina) is discussed. Our methods will allow real-time evaluation of couplings for large assemblies of neurons. PMID:19666487

Determination of Adsorption Equations for Chloro Derivatives of Aniline on Halloysite Adsorbents Using Inverse Liquid Chromatography.

PubMed

Słomkiewicz, Piotr M; Szczepanik, Beata; Garnuszek, Magdalena; Rogala, Paweł; Witkiewicz, Zygfryd

2017-11-01

Chloro derivatives of aniline are commonly used in the production of dyes, pharmaceuticals, and agricultural agents. They are toxic compounds with a large accumulation ability and low natural biodegradability. Halloysite is known as an efficient adsorbent of toxic compounds, such as phenols or herbicides, from wastewater. Inverse LC was applied to measure the adsorption of aniline and 2-chloroaniline (2-CA), 3-chloroaniline (3-CA), and 4-chloroaniline (4-CA) on halloysite adsorbents. A peak division (PD) method was used to determine a Langmuir equation in accordance with the adsorption measurement results. The values of adsorption equilibrium constants and enthalpy were determined and compared by breakthrough curve and PD methods. The physical sense of the calculated adsorption enthalpy values was checked by applying Boudart's entropy criteria. Of note, adsorption enthalpy values for halloysite adsorbents decreased in the following order: aniline > 4-CA > 2-CA > 3-CA.

A methodology for using borehole temperature-depth profiles under ambient, single and cross-borehole pumping conditions to estimate fracture hydraulic properties

NASA Astrophysics Data System (ADS)

Klepikova, Maria V.; Le Borgne, Tanguy; Bour, Olivier; Davy, Philippe

2011-09-01

SummaryTemperature profiles in the subsurface are known to be sensitive to groundwater flow. Here we show that they are also strongly related to vertical flow in the boreholes themselves. Based on a numerical model of flow and heat transfer at the borehole scale, we propose a method to invert temperature measurements to derive borehole flow velocities. This method is applied to an experimental site in fractured crystalline rocks. Vertical flow velocities deduced from the inversion of temperature measurements are compared with direct heat-pulse flowmeter measurements showing a good agreement over two orders of magnitudes. Applying this methodology under ambient, single and cross-borehole pumping conditions allows us to estimate fracture hydraulic head and local transmissivity, as well as inter-borehole fracture connectivity. Thus, these results provide new insights on how to include temperature profiles in inverse problems for estimating hydraulic fracture properties.

The Collaborative Seismic Earth Model: Generation 1

NASA Astrophysics Data System (ADS)

Fichtner, Andreas; van Herwaarden, Dirk-Philip; Afanasiev, Michael; SimutÄ--, SaulÄ--; Krischer, Lion; ćubuk-Sabuncu, Yeşim; Taymaz, Tuncay; Colli, Lorenzo; Saygin, Erdinc; Villaseñor, Antonio; Trampert, Jeannot; Cupillard, Paul; Bunge, Hans-Peter; Igel, Heiner

2018-05-01

We present a general concept for evolutionary, collaborative, multiscale inversion of geophysical data, specifically applied to the construction of a first-generation Collaborative Seismic Earth Model. This is intended to address the limited resources of individual researchers and the often limited use of previously accumulated knowledge. Model evolution rests on a Bayesian updating scheme, simplified into a deterministic method that honors today's computational restrictions. The scheme is able to harness distributed human and computing power. It furthermore handles conflicting updates, as well as variable parameterizations of different model refinements or different inversion techniques. The first-generation Collaborative Seismic Earth Model comprises 12 refinements from full seismic waveform inversion, ranging from regional crustal- to continental-scale models. A global full-waveform inversion ensures that regional refinements translate into whole-Earth structure.

Decomposing Large Inverse Problems with an Augmented Lagrangian Approach: Application to Joint Inversion of Body-Wave Travel Times and Surface-Wave Dispersion Measurements

NASA Astrophysics Data System (ADS)

Reiter, D. T.; Rodi, W. L.

2015-12-01

Constructing 3D Earth models through the joint inversion of large geophysical data sets presents numerous theoretical and practical challenges, especially when diverse types of data and model parameters are involved. Among the challenges are the computational complexity associated with large data and model vectors and the need to unify differing model parameterizations, forward modeling methods and regularization schemes within a common inversion framework. The challenges can be addressed in part by decomposing the inverse problem into smaller, simpler inverse problems that can be solved separately, providing one knows how to merge the separate inversion results into an optimal solution of the full problem. We have formulated an approach to the decomposition of large inverse problems based on the augmented Lagrangian technique from optimization theory. As commonly done, we define a solution to the full inverse problem as the Earth model minimizing an objective function motivated, for example, by a Bayesian inference formulation. Our decomposition approach recasts the minimization problem equivalently as the minimization of component objective functions, corresponding to specified data subsets, subject to the constraints that the minimizing models be equal. A standard optimization algorithm solves the resulting constrained minimization problems by alternating between the separate solution of the component problems and the updating of Lagrange multipliers that serve to steer the individual solution models toward a common model solving the full problem. We are applying our inversion method to the reconstruction of the·crust and upper-mantle seismic velocity structure across Eurasia.· Data for the inversion comprise a large set of P and S body-wave travel times·and fundamental and first-higher mode Rayleigh-wave group velocities.

Resolving Isotropic Components from Regional Waves using Grid Search and Moment Tensor Inversion Methods

NASA Astrophysics Data System (ADS)

Ichinose, G. A.; Saikia, C. K.

2007-12-01

We applied the moment tensor (MT) analysis scheme to identify seismic sources using regional seismograms based on the representation theorem for the elastic wave displacement field. This method is applied to estimate the isotropic (ISO) and deviatoric MT components of earthquake, volcanic, and isotropic sources within the Basin and Range Province (BRP) and western US. The ISO components from Hoya, Bexar, Montello and Junction were compared to recently well recorded recent earthquakes near Little Skull Mountain, Scotty's Junction, Eureka Valley, and Fish Lake Valley within southern Nevada. We also examined "dilatational" sources near Mammoth Lakes Caldera and two mine collapses including the August 2007 event in Utah recorded by US Array. Using our formulation we have first implemented the full MT inversion method on long period filtered regional data. We also applied a grid-search technique to solve for the percent deviatoric and %ISO moments. By using the grid-search technique, high-frequency waveforms are used with calibrated velocity models. We modeled the ISO and deviatoric components (spall and tectonic release) as separate events delayed in time or offset in space. Calibrated velocity models helped the resolution of the ISO components and decrease the variance over the average, initial or background velocity models. The centroid location and time shifts are velocity model dependent. Models can be improved as was done in previously published work in which we used an iterative waveform inversion method with regional seismograms from four well recorded and constrained earthquakes. The resulting velocity models reduced the variance between predicted synthetics by about 50 to 80% for frequencies up to 0.5 Hz. Tests indicate that the individual path-specific models perform better at recovering the earthquake MT solutions even after using a sparser distribution of stations than the average or initial models.

Automatic detection of multiple UXO-like targets using magnetic anomaly inversion and self-adaptive fuzzy c-means clustering

NASA Astrophysics Data System (ADS)

Yin, Gang; Zhang, Yingtang; Fan, Hongbo; Ren, Guoquan; Li, Zhining

2017-12-01

We have developed a method for automatically detecting UXO-like targets based on magnetic anomaly inversion and self-adaptive fuzzy c-means clustering. Magnetic anomaly inversion methods are used to estimate the initial locations of multiple UXO-like sources. Although these initial locations have some errors with respect to the real positions, they form dense clouds around the actual positions of the magnetic sources. Then we use the self-adaptive fuzzy c-means clustering algorithm to cluster these initial locations. The estimated number of cluster centroids represents the number of targets and the cluster centroids are regarded as the locations of magnetic targets. Effectiveness of the method has been demonstrated using synthetic datasets. Computational results show that the proposed method can be applied to the case of several UXO-like targets that are randomly scattered within in a confined, shallow subsurface, volume. A field test was carried out to test the validity of the proposed method and the experimental results show that the prearranged magnets can be detected unambiguously and located precisely.

Three-dimensional cross-gradient joint inversion of gravity and normalized magnetic source strength data in the presence of remanent magnetization

NASA Astrophysics Data System (ADS)

Zhou, Junjie; Meng, Xiaohong; Guo, Lianghui; Zhang, Sheng

2015-08-01

Three-dimensional cross-gradient joint inversion of gravity and magnetic data has the potential to acquire improved density and magnetization distribution information. This method usually adopts the commonly held assumption that remanent magnetization can be ignored and all anomalies present are the result of induced magnetization. Accordingly, this method might fail to produce accurate results where significant remanent magnetization is present. In such a case, the simplification brings about unwanted and unknown deviations in the inverted magnetization model. Furthermore, because of the information transfer mechanism of the joint inversion framework, the inverted density results may also be influenced by the effect of remanent magnetization. The normalized magnetic source strength (NSS) is a transformed quantity that is insensitive to the magnetization direction. Thus, it has been applied in the standard magnetic inversion scheme to mitigate the remanence effects, especially in the case of varying remanence directions. In this paper, NSS data were employed along with gravity data for three-dimensional cross-gradient joint inversion, which can significantly reduce the remanence effects and enhance the reliability of both density and magnetization models. Meanwhile, depth-weightings and bound constraints were also incorporated in this joint algorithm to improve the inversion quality. Synthetic and field examples show that the proposed combination of cross-gradient constraints and the NSS transform produce better results in terms of the data resolution, compatibility, and reliability than that of separate inversions and that of joint inversions with the total magnetization intensity (TMI) data. Thus, this method was found to be very useful and is recommended for applications in the presence of strong remanent magnetization.

Joint inversion of NMR and SIP data to estimate pore size distribution of geomaterials

NASA Astrophysics Data System (ADS)

Niu, Qifei; Zhang, Chi

2018-03-01

There are growing interests in using geophysical tools to characterize the microstructure of geomaterials because of the non-invasive nature and the applicability in field. In these applications, multiple types of geophysical data sets are usually processed separately, which may be inadequate to constrain the key feature of target variables. Therefore, simultaneous processing of multiple data sets could potentially improve the resolution. In this study, we propose a method to estimate pore size distribution by joint inversion of nuclear magnetic resonance (NMR) T2 relaxation and spectral induced polarization (SIP) spectra. The petrophysical relation between NMR T2 relaxation time and SIP relaxation time is incorporated in a nonlinear least squares problem formulation, which is solved using Gauss-Newton method. The joint inversion scheme is applied to a synthetic sample and a Berea sandstone sample. The jointly estimated pore size distributions are very close to the true model and results from other experimental method. Even when the knowledge of the petrophysical models of the sample is incomplete, the joint inversion can still capture the main features of the pore size distribution of the samples, including the general shape and relative peak positions of the distribution curves. It is also found from the numerical example that the surface relaxivity of the sample could be extracted with the joint inversion of NMR and SIP data if the diffusion coefficient of the ions in the electrical double layer is known. Comparing to individual inversions, the joint inversion could improve the resolution of the estimated pore size distribution because of the addition of extra data sets. The proposed approach might constitute a first step towards a comprehensive joint inversion that can extract the full pore geometry information of a geomaterial from NMR and SIP data.

Designing stellarator coils by a modified Newton method using FOCUS

DOE Office of Scientific and Technical Information (OSTI.GOV)

Zhu, Caoxiang; Hudson, Stuart R.; Song, Yuntao

To find the optimal coils for stellarators, nonlinear optimization algorithms are applied in existing coil design codes. However, none of these codes have used the information from the second-order derivatives. In this paper, we present a modified Newton method in the recently developed code FOCUS. The Hessian matrix is calculated with analytically derived equations. Its inverse is approximated by a modified Cholesky factorization and applied in the iterative scheme of a classical Newton method. Using this method, FOCUS is able to recover the W7-X modular coils starting from a simple initial guess. Results demonstrate significant advantages.

Designing stellarator coils by a modified Newton method using FOCUS

NASA Astrophysics Data System (ADS)

Zhu, Caoxiang; Hudson, Stuart R.; Song, Yuntao; Wan, Yuanxi

2018-06-01

To find the optimal coils for stellarators, nonlinear optimization algorithms are applied in existing coil design codes. However, none of these codes have used the information from the second-order derivatives. In this paper, we present a modified Newton method in the recently developed code FOCUS. The Hessian matrix is calculated with analytically derived equations. Its inverse is approximated by a modified Cholesky factorization and applied in the iterative scheme of a classical Newton method. Using this method, FOCUS is able to recover the W7-X modular coils starting from a simple initial guess. Results demonstrate significant advantages.

Designing stellarator coils by a modified Newton method using FOCUS

DOE PAGES

Zhu, Caoxiang; Hudson, Stuart R.; Song, Yuntao; ...

2018-03-22

To find the optimal coils for stellarators, nonlinear optimization algorithms are applied in existing coil design codes. However, none of these codes have used the information from the second-order derivatives. In this paper, we present a modified Newton method in the recently developed code FOCUS. The Hessian matrix is calculated with analytically derived equations. Its inverse is approximated by a modified Cholesky factorization and applied in the iterative scheme of a classical Newton method. Using this method, FOCUS is able to recover the W7-X modular coils starting from a simple initial guess. Results demonstrate significant advantages.

4D inversion of time-lapse magnetotelluric data sets for monitoring geothermal reservoir

NASA Astrophysics Data System (ADS)

Nam, Myung Jin; Song, Yoonho; Jang, Hannuree; Kim, Bitnarae

2017-06-01

The productivity of a geothermal reservoir, which is a function of the pore-space and fluid-flow path of the reservoir, varies since the properties of the reservoir changes with geothermal reservoir production. Because the variation in the reservoir properties causes changes in electrical resistivity, time-lapse (TL) three-dimensional (3D) magnetotelluric (MT) methods can be applied to monitor the productivity variation of a geothermal reservoir thanks to not only its sensitivity to the electrical resistivity but also its deep depth of survey penetration. For an accurate interpretation of TL MT-data sets, a four-dimensional (4D) MT inversion algorithm has been developed to simultaneously invert all vintage data considering time-coupling between vintages. However, the changes in electrical resistivity of deep geothermal reservoirs are usually small generating minimum variation in TL MT responses. Maximizing the sensitivity of inversion to the changes in resistivity is critical in the success of 4D MT inversion. Thus, we further developed a focused 4D MT inversion method by considering not only the location of a reservoir but also the distribution of newly-generated fractures during the production. For the evaluation of the 4D MT algorithm, we tested our 4D inversion algorithms using synthetic TL MT-data sets.

An accurate, fast, and scalable solver for high-frequency wave propagation

NASA Astrophysics Data System (ADS)

Zepeda-Núñez, L.; Taus, M.; Hewett, R.; Demanet, L.

2017-12-01

In many science and engineering applications, solving time-harmonic high-frequency wave propagation problems quickly and accurately is of paramount importance. For example, in geophysics, particularly in oil exploration, such problems can be the forward problem in an iterative process for solving the inverse problem of subsurface inversion. It is important to solve these wave propagation problems accurately in order to efficiently obtain meaningful solutions of the inverse problems: low order forward modeling can hinder convergence. Additionally, due to the volume of data and the iterative nature of most optimization algorithms, the forward problem must be solved many times. Therefore, a fast solver is necessary to make solving the inverse problem feasible. For time-harmonic high-frequency wave propagation, obtaining both speed and accuracy is historically challenging. Recently, there have been many advances in the development of fast solvers for such problems, including methods which have linear complexity with respect to the number of degrees of freedom. While most methods scale optimally only in the context of low-order discretizations and smooth wave speed distributions, the method of polarized traces has been shown to retain optimal scaling for high-order discretizations, such as hybridizable discontinuous Galerkin methods and for highly heterogeneous (and even discontinuous) wave speeds. The resulting fast and accurate solver is consequently highly attractive for geophysical applications. To date, this method relies on a layered domain decomposition together with a preconditioner applied in a sweeping fashion, which has limited straight-forward parallelization. In this work, we introduce a new version of the method of polarized traces which reveals more parallel structure than previous versions while preserving all of its other advantages. We achieve this by further decomposing each layer and applying the preconditioner to these new components separately and in parallel. We demonstrate that this produces an even more effective and parallelizable preconditioner for a single right-hand side. As before, additional speed can be gained by pipelining several right-hand-sides.

Efficient Monte Carlo sampling of inverse problems using a neural network-based forward—applied to GPR crosshole traveltime inversion

NASA Astrophysics Data System (ADS)

Hansen, T. M.; Cordua, K. S.

2017-12-01

Probabilistically formulated inverse problems can be solved using Monte Carlo-based sampling methods. In principle, both advanced prior information, based on for example, complex geostatistical models and non-linear forward models can be considered using such methods. However, Monte Carlo methods may be associated with huge computational costs that, in practice, limit their application. This is not least due to the computational requirements related to solving the forward problem, where the physical forward response of some earth model has to be evaluated. Here, it is suggested to replace a numerical complex evaluation of the forward problem, with a trained neural network that can be evaluated very fast. This will introduce a modeling error that is quantified probabilistically such that it can be accounted for during inversion. This allows a very fast and efficient Monte Carlo sampling of the solution to an inverse problem. We demonstrate the methodology for first arrival traveltime inversion of crosshole ground penetrating radar data. An accurate forward model, based on 2-D full-waveform modeling followed by automatic traveltime picking, is replaced by a fast neural network. This provides a sampling algorithm three orders of magnitude faster than using the accurate and computationally expensive forward model, and also considerably faster and more accurate (i.e. with better resolution), than commonly used approximate forward models. The methodology has the potential to dramatically change the complexity of non-linear and non-Gaussian inverse problems that have to be solved using Monte Carlo sampling techniques.

3-D linear inversion of gravity data: method and application to Basse-Terre volcanic island, Guadeloupe, Lesser Antilles

NASA Astrophysics Data System (ADS)

Barnoud, Anne; Coutant, Olivier; Bouligand, Claire; Gunawan, Hendra; Deroussi, Sébastien

2016-04-01

We use a Bayesian formalism combined with a grid node discretization for the linear inversion of gravimetric data in terms of 3-D density distribution. The forward modelling and the inversion method are derived from seismological inversion techniques in order to facilitate joint inversion or interpretation of density and seismic velocity models. The Bayesian formulation introduces covariance matrices on model parameters to regularize the ill-posed problem and reduce the non-uniqueness of the solution. This formalism favours smooth solutions and allows us to specify a spatial correlation length and to perform inversions at multiple scales. We also extract resolution parameters from the resolution matrix to discuss how well our density models are resolved. This method is applied to the inversion of data from the volcanic island of Basse-Terre in Guadeloupe, Lesser Antilles. A series of synthetic tests are performed to investigate advantages and limitations of the methodology in this context. This study results in the first 3-D density models of the island of Basse-Terre for which we identify: (i) a southward decrease of densities parallel to the migration of volcanic activity within the island, (ii) three dense anomalies beneath Petite Plaine Valley, Beaugendre Valley and the Grande-Découverte-Carmichaël-Soufrière Complex that may reflect the trace of former major volcanic feeding systems, (iii) shallow low-density anomalies in the southern part of Basse-Terre, especially around La Soufrière active volcano, Piton de Bouillante edifice and along the western coast, reflecting the presence of hydrothermal systems and fractured and altered rocks.

FWT2D: A massively parallel program for frequency-domain full-waveform tomography of wide-aperture seismic data—Part 1: Algorithm

NASA Astrophysics Data System (ADS)

Sourbier, Florent; Operto, Stéphane; Virieux, Jean; Amestoy, Patrick; L'Excellent, Jean-Yves

2009-03-01

This is the first paper in a two-part series that describes a massively parallel code that performs 2D frequency-domain full-waveform inversion of wide-aperture seismic data for imaging complex structures. Full-waveform inversion methods, namely quantitative seismic imaging methods based on the resolution of the full wave equation, are computationally expensive. Therefore, designing efficient algorithms which take advantage of parallel computing facilities is critical for the appraisal of these approaches when applied to representative case studies and for further improvements. Full-waveform modelling requires the resolution of a large sparse system of linear equations which is performed with the massively parallel direct solver MUMPS for efficient multiple-shot simulations. Efficiency of the multiple-shot solution phase (forward/backward substitutions) is improved by using the BLAS3 library. The inverse problem relies on a classic local optimization approach implemented with a gradient method. The direct solver returns the multiple-shot wavefield solutions distributed over the processors according to a domain decomposition driven by the distribution of the LU factors. The domain decomposition of the wavefield solutions is used to compute in parallel the gradient of the objective function and the diagonal Hessian, this latter providing a suitable scaling of the gradient. The algorithm allows one to test different strategies for multiscale frequency inversion ranging from successive mono-frequency inversion to simultaneous multifrequency inversion. These different inversion strategies will be illustrated in the following companion paper. The parallel efficiency and the scalability of the code will also be quantified.

Nanoemulsions prepared by a low-energy emulsification method applied to edible films

USDA-ARS?s Scientific Manuscript database

Catastrophic phase inversion (CPI) was used as a low-energy emulsification method to prepare oil-in-water (O/W) nanoemulsions in a lipid (Acetem)/water/nonionic surfactant (Tween 60) system. CPIs in which water-in-oil emulsions (W/O) are transformed into oil-in-water emulsions (O/W) were induced by ...

Joint inversion of seismic refraction and resistivity data using layered models - applications to hydrogeology

NASA Astrophysics Data System (ADS)

Juhojuntti, N. G.; Kamm, J.

2010-12-01

We present a layered-model approach to joint inversion of shallow seismic refraction and resistivity (DC) data, which we believe is a seldom tested method of addressing the problem. This method has been developed as we believe that for shallow sedimentary environments (roughly <100 m depth) a model with a few layers and sharp layer boundaries better represents the subsurface than a smooth minimum-structure (grid) model. Due to the strong assumption our model parameterization implies on the subsurface, only a low number of well resolved model parameters has to be estimated, and provided that this assumptions holds our method can also be applied to other environments. We are using a least-squares inversion, with lateral smoothness constraints, allowing lateral variations in the seismic velocity and the resistivity but no vertical variations. One exception is a positive gradient in the seismic velocity in the uppermost layer in order to get diving rays (the refractions in the deeper layers are modeled as head waves). We assume no connection between seismic velocity and resistivity, and these parameters are allowed to vary individually within the layers. The layer boundaries are, however, common for both parameters. During the inversion lateral smoothing can be applied to the layer boundaries as well as to the seismic velocity and the resistivity. The number of layers is specified before the inversion, and typically we use models with three layers. Depending on the type of environment it is possible to apply smoothing either to the depth of the layer boundaries or to the thickness of the layers, although normally the former is used for shallow sedimentary environments. The smoothing parameters can be chosen independently for each layer. For the DC data we use a finite-difference algorithm to perform the forward modeling and to calculate the Jacobian matrix, while for the seismic data the corresponding entities are retrieved via ray-tracing, using components from the RAYINVR package. The modular layout of the code makes it straightforward to include other types of geophysical data, i.e. gravity. The code has been tested using synthetic examples with fairly simple 2D geometries, mainly for checking the validity of the calculations. The inversion generally converges towards the correct solution, although there could be stability problems if the starting model is too erroneous. We have also applied the code to field data from seismic refraction and multi-electrode resistivity measurements at typical sand-gravel groundwater reservoirs. The tests are promising, as the calculated depths agree fairly well with information from drilling and the velocity and resistivity values appear reasonable. Current work includes better regularization of the inversion as well as defining individual weight factors for the different datasets, as the present algorithm tends to constrain the depths mainly by using the seismic data. More complex synthetic examples will also be tested, including models addressing the seismic hidden-layer problem.

Electron transport in electrically biased inverse parabolic double-barrier structure

NASA Astrophysics Data System (ADS)

M, Bati; S, Sakiroglu; I, Sokmen

2016-05-01

A theoretical study of resonant tunneling is carried out for an inverse parabolic double-barrier structure subjected to an external electric field. Tunneling transmission coefficient and density of states are analyzed by using the non-equilibrium Green’s function approach based on the finite difference method. It is found that the resonant peak of the transmission coefficient, being unity for a symmetrical case, reduces under the applied electric field and depends strongly on the variation of the structure parameters.

Bayesian inference for disease prevalence using negative binomial group testing

PubMed Central

Pritchard, Nicholas A.; Tebbs, Joshua M.

2011-01-01

Group testing, also known as pooled testing, and inverse sampling are both widely used methods of data collection when the goal is to estimate a small proportion. Taking a Bayesian approach, we consider the new problem of estimating disease prevalence from group testing when inverse (negative binomial) sampling is used. Using different distributions to incorporate prior knowledge of disease incidence and different loss functions, we derive closed form expressions for posterior distributions and resulting point and credible interval estimators. We then evaluate our new estimators, on Bayesian and classical grounds, and apply our methods to a West Nile Virus data set. PMID:21259308

Nitrous oxide emissions estimated with the Carbon Tracker Lagrange regional inversion framework suggest the North American source comes predominantly from agricultural regions

NASA Astrophysics Data System (ADS)

Nevison, C. D.; Andrews, A. E.; Thoning, K. W.; Saikawa, E.; Dlugokencky, E. J.; Sweeney, C.; Benmergui, J. S.

2016-12-01

The Carbon Tracker Lagrange (CTL) regional inversion framework is used to estimate North American nitrous oxide (N2O) emissions of 1.6 ± 0.4 Tg N/yr over 2008-2013. More than half of the North American emissions are estimated to come from the central agricultural belt, extending from southern Canada to Texas, and are strongest in spring and early summer, consistent with a nitrogen fertilizer-driven source. The estimated N2O flux from the Midwestern corn/soybean belt and the more northerly wheat belt corresponds to 5% of synthetic + organic N fertilizer applied to those regions. While earlier regional atmospheric inversion studies have suggested that global inventories such as EDGAR may be underestimating U.S. anthropogenic N2O emissions by a factor of 3 or more, our results, integrated over a full calendar year, are generally consistent with those inventories and with global inverse model results and budget constraints. The CTL framework is a Bayesian method based on footprints from the Stochastic Time-Inverted Lagrangian Transport (STILT) model applied to atmospheric N2O data from the National Oceanic and Atmospheric Administration (NOAA) Global Greenhouse Gas Reference Network, including surface, aircraft and tall tower platforms. The CTL inversion results are sensitive to the prescribed boundary condition or background value of N2O, which is estimated based on a new Empirical BackGround (EBG) product derived from STILT back trajectories applied to NOAA data. Analysis of the N2O EBG products suggests a significant, seasonally-varying influence on surface N2O data due to the stratospheric influx of N2O-depleted air. Figure 1. Posterior annual mean N2O emissions for 2010 estimated with the CTL regional inversion framework. The locations of NOAA surface and aircraft data used in the inversion are superimposed as black circles and grey triangles, respectively. Mobile surface sites are indicated with asterisks.

Efficient option valuation of single and double barrier options

NASA Astrophysics Data System (ADS)

Kabaivanov, Stanimir; Milev, Mariyan; Koleva-Petkova, Dessislava; Vladev, Veselin

2017-12-01

In this paper we present an implementation of pricing algorithm for single and double barrier options using Mellin transformation with Maximum Entropy Inversion and its suitability for real-world applications. A detailed analysis of the applied algorithm is accompanied by implementation in C++ that is then compared to existing solutions in terms of efficiency and computational power. We then compare the applied method with existing closed-form solutions and well known methods of pricing barrier options that are based on finite differences.

A Non-linear Geodetic Data Inversion Using ABIC for Slip Distribution on a Fault With an Unknown dip Angle

NASA Astrophysics Data System (ADS)

Fukahata, Y.; Wright, T. J.

2006-12-01

We developed a method of geodetic data inversion for slip distribution on a fault with an unknown dip angle. When fault geometry is unknown, the problem of geodetic data inversion is non-linear. A common strategy for obtaining slip distribution is to first determine the fault geometry by minimizing the square misfit under the assumption of a uniform slip on a rectangular fault, and then apply the usual linear inversion technique to estimate a slip distribution on the determined fault. It is not guaranteed, however, that the fault determined under the assumption of a uniform slip gives the best fault geometry for a spatially variable slip distribution. In addition, in obtaining a uniform slip fault model, we have to simultaneously determine the values of the nine mutually dependent parameters, which is a highly non-linear, complicated process. Although the inverse problem is non-linear for cases with unknown fault geometries, the non-linearity of the problems is actually weak, when we can assume the fault surface to be flat. In particular, when a clear fault trace is observed on the EarthOs surface after an earthquake, we can precisely estimate the strike and the location of the fault. In this case only the dip angle has large ambiguity. In geodetic data inversion we usually need to introduce smoothness constraints in order to compromise reciprocal requirements for model resolution and estimation errors in a natural way. Strictly speaking, the inverse problem with smoothness constraints is also non-linear, even if the fault geometry is known. The non-linearity has been dissolved by introducing AkaikeOs Bayesian Information Criterion (ABIC), with which the optimal value of the relative weight of observed data to smoothness constraints is objectively determined. In this study, using ABIC in determining the optimal dip angle, we dissolved the non-linearity of the inverse problem. We applied the method to the InSAR data of the 1995 Dinar, Turkey earthquake and obtained a much shallower dip angle than before.

Tsunami Waves Joint Inversion Using Tsunami Inundation, Tsunami Deposits Distribution and Marine-Terrestrial Sediment Signal in Tsunami Deposit

NASA Astrophysics Data System (ADS)

Tang, H.; WANG, J.

2017-12-01

Population living close to coastlines is increasing, which creates higher risks due to coastal hazards, such as the tsunami. However, the generation of a tsunami is not fully understood yet, especially for paleo-tsunami. Tsunami deposits are one of the concrete evidence in the geological record which we can apply for studying paleo-tsunami. The understanding of tsunami deposits has significantly improved over the last decades. There are many inversion models (e.g. TsuSedMod, TSUFLIND, and TSUFLIND-EnKF) to study the overland-flow characteristics based on tsunami deposits. However, none of them tries to reconstruct offshore tsunami wave characteristics (wave form, wave height, and length) based on tsunami deposits. Here we present a state-of-the-art inverse approach to reconstruct offshore tsunami wave based on the tsunami inundation data, the spatial distribution of tsunami deposits and Marine-terrestrial sediment signal in the tsunami deposits. Ensemble Kalman Filter (EnKF) Method is used for assimilating both sediment transport simulations and the field observation data. While more computationally expensive, the EnKF approach potentially provides more accurate reconstructions for tsunami waveform. In addition to the improvement of inversion results, the ensemble-based method can also quantify the uncertainties of the results. Meanwhile, joint inversion improves the resolution of tsunami waves compared with inversions using any single data type. The method will be tested by field survey data and gauge data from the 2011 Tohoku tsunami on Sendai plain area.

Relevance of detail in basal topography for basal slipperiness inversions: a case study on Pine Island Glacier, Antarctica

NASA Astrophysics Data System (ADS)

Kyrke-Smith, Teresa M.; Gudmundsson, G. Hilmar; Farrell, Patrick E.

2018-04-01

Given high-resolution satellite-derived surface elevation and velocity data, ice-sheet models generally estimate mechanical basal boundary conditions using surface-to-bed inversion methods. In this work, we address the sensitivity of results from inversion methods to the accuracy of the bed elevation data on Pine Island Glacier. We show that misfit between observations and model output is reduced when high-resolution bed topography is used in the inverse model. By looking at results with a range of detail included in the bed elevation, we consider the separation of basal drag due to the bed topography (form drag) and that due to inherent bed properties (skin drag). The mean value of basal shear stress is reduced when more detailed topography is included in the model. This suggests that without a fully resolved bed a significant amount of the basal shear stress recovered from inversion methods may be due to the unresolved bed topography. However, the spatial structure of the retrieved fields is robust as the bed accuracy is varied; the fields are instead sensitive to the degree of regularisation applied to the inversion. While the implications for the future temporal evolution of PIG are not quantified here directly, our work raises the possibility that skin drag may be overestimated in the current generation of numerical ice-sheet models of this area. These shortcomings could be overcome by inverting simultaneously for both bed topography and basal slipperiness.

CSAMT Data Processing with Source Effect and Static Corrections, Application of Occam's Inversion, and Its Application in Geothermal System

NASA Astrophysics Data System (ADS)

Hamdi, H.; Qausar, A. M.; Srigutomo, W.

2016-08-01

Controlled source audio-frequency magnetotellurics (CSAMT) is a frequency-domain electromagnetic sounding technique which uses a fixed grounded dipole as an artificial signal source. Measurement of CSAMT with finite distance between transmitter and receiver caused a complex wave. The shifted of the electric field due to the static effect caused elevated resistivity curve up or down and affects the result of measurement. The objective of this study was to obtain data that have been corrected for source and static effects as to have the same characteristic as MT data which are assumed to exhibit plane wave properties. Corrected CSAMT data were inverted to reveal subsurface resistivity model. Source effect correction method was applied to eliminate the effect of the signal source and static effect was corrected by using spatial filtering technique. Inversion method that used in this study is the Occam's 2D Inversion. The results of inversion produces smooth models with a small misfit value, it means the model can describe subsurface conditions well. Based on the result of inversion was predicted measurement area is rock that has high permeability values with rich hot fluid.

Source mechanism analysis of central Aceh earthquake July 2, 2013 Mw 6.2 using moment tensor inversion with BMKG waveform data

DOE Office of Scientific and Technical Information (OSTI.GOV)

Prasetyo, Retno Agung, E-mail: prasetyo.agung@bmkg.go.id; Heryandoko, Nova; Afnimar

The source mechanism of earthquake on July 2, 2013 was investigated by using moment tensor inversion. The result also compared by the field observation. Five waveform data of BMKG’s seismic network used to estimate the mechanism of earthquake, namely ; KCSI, MLSI, LASI, TPTI and SNSI. Main shock data taken during 200 seconds and filtered by using Butterworth band pass method from 0.03 to 0.05 Hz of frequency. Moment tensor inversion method is applied based on the point source assumption. Furthermore, the Green function calculated using the extended reflectivity method which modified by Kohketsu. The inversion result showed a strike-slipmore » faulting, where the nodal plane strike/dip/rake (124/80.6/152.8) and minimum variance value 0.3285 at a depth of 6 km (centroid). It categorized as a shallow earthquake. Field observation indicated that the building orientated to the east. It can be related to the southwest of dip direction which has 152 degrees of slip. As conclusion, the Pressure (P) and Tension (T) axis described dominant compression is happen from the south which is caused by pressure of the Indo-Australian plate.« less

Crustal velocity structure of central Gansu Province from regional seismic waveform inversion using firework algorithm

NASA Astrophysics Data System (ADS)

Chen, Yanyang; Wang, Yanbin; Zhang, Yuansheng

2017-04-01

The firework algorithm (FWA) is a novel swarm intelligence-based method recently proposed for the optimization of multi-parameter, nonlinear functions. Numerical waveform inversion experiments using a synthetic model show that the FWA performs well in both solution quality and efficiency. We apply the FWA in this study to crustal velocity structure inversion using regional seismic waveform data of central Gansu on the northeastern margin of the Qinghai-Tibet plateau. Seismograms recorded from the moment magnitude ( M W) 5.4 Minxian earthquake enable obtaining an average crustal velocity model for this region. We initially carried out a series of FWA robustness tests in regional waveform inversion at the same earthquake and station positions across the study region, inverting two velocity structure models, with and without a low-velocity crustal layer; the accuracy of our average inversion results and their standard deviations reveal the advantages of the FWA for the inversion of regional seismic waveforms. We applied the FWA across our study area using three component waveform data recorded by nine broadband permanent seismic stations with epicentral distances ranging between 146 and 437 km. These inversion results show that the average thickness of the crust in this region is 46.75 km, while thicknesses of the sedimentary layer, and the upper, middle, and lower crust are 3.15, 15.69, 13.08, and 14.83 km, respectively. Results also show that the P-wave velocities of these layers and the upper mantle are 4.47, 6.07, 6.12, 6.87, and 8.18 km/s, respectively.

Waveform inversion of acoustic waves for explosion yield estimation

DOE PAGES

Kim, K.; Rodgers, A. J.

2016-07-08

We present a new waveform inversion technique to estimate the energy of near-surface explosions using atmospheric acoustic waves. Conventional methods often employ air blast models based on a homogeneous atmosphere, where the acoustic wave propagation effects (e.g., refraction and diffraction) are not taken into account, and therefore, their accuracy decreases with increasing source-receiver distance. In this study, three-dimensional acoustic simulations are performed with a finite difference method in realistic atmospheres and topography, and the modeled acoustic Green's functions are incorporated into the waveform inversion for the acoustic source time functions. The strength of the acoustic source is related to explosionmore » yield based on a standard air blast model. The technique was applied to local explosions (<10 km) and provided reasonable yield estimates (<~30% error) in the presence of realistic topography and atmospheric structure. In conclusion, the presented method can be extended to explosions recorded at far distance provided proper meteorological specifications.« less

Waveform inversion of acoustic waves for explosion yield estimation

DOE Office of Scientific and Technical Information (OSTI.GOV)

Kim, K.; Rodgers, A. J.

We present a new waveform inversion technique to estimate the energy of near-surface explosions using atmospheric acoustic waves. Conventional methods often employ air blast models based on a homogeneous atmosphere, where the acoustic wave propagation effects (e.g., refraction and diffraction) are not taken into account, and therefore, their accuracy decreases with increasing source-receiver distance. In this study, three-dimensional acoustic simulations are performed with a finite difference method in realistic atmospheres and topography, and the modeled acoustic Green's functions are incorporated into the waveform inversion for the acoustic source time functions. The strength of the acoustic source is related to explosionmore » yield based on a standard air blast model. The technique was applied to local explosions (<10 km) and provided reasonable yield estimates (<~30% error) in the presence of realistic topography and atmospheric structure. In conclusion, the presented method can be extended to explosions recorded at far distance provided proper meteorological specifications.« less

The conformal transformation of an airfoil into a straight line and its application to the inverse problem of airfoil theory

NASA Technical Reports Server (NTRS)

Mutterperl, William

1944-01-01

A method of conformal transformation is developed that maps an airfoil into a straight line, the line being chosen as the extended chord line of the airfoil. The mapping is accomplished by operating directly with the airfoil ordinates. The absence of any preliminary transformation is found to shorten the work substantially over that of previous methods. Use is made of the superposition of solutions to obtain a rigorous counterpart of the approximate methods of thin-airfoils theory. The method is applied to the solution of the direct and inverse problems for arbitrary airfoils and pressure distributions. Numerical examples are given. Applications to more general types of regions, in particular to biplanes and to cascades of airfoils, are indicated. (author)

Mass, heat and nutrient fluxes in the Atlantic Ocean determined by inverse methods. Ph.D. Thesis

NASA Technical Reports Server (NTRS)

Rintoul, Stephen Rich

1988-01-01

Inverse methods are applied to historical hydrographic data to address two aspects of the general circulation of the Atlantic Ocean. The method allows conservation statements for mass and other properties, along with a variety of other constraints, to be combined in a dynamically consistent way to estimate the absolute velocity field and associated property transports. The method was first used to examine the exchange of mass and heat between the South Atlantic and the neighboring ocean basins. The second problem addressed concerns the circulation and property fluxes across the 24 and 36 deg N in the subtropical North Atlantic. Conservation statements are considered for the nutrients as well as mass, and the nutrients are found to contribute significant information independent of temperature and salinity.

Exact exchange-correlation potentials of singlet two-electron systems

NASA Astrophysics Data System (ADS)

Ryabinkin, Ilya G.; Ospadov, Egor; Staroverov, Viktor N.

2017-10-01

We suggest a non-iterative analytic method for constructing the exchange-correlation potential, v XC ( r ) , of any singlet ground-state two-electron system. The method is based on a convenient formula for v XC ( r ) in terms of quantities determined only by the system's electronic wave function, exact or approximate, and is essentially different from the Kohn-Sham inversion technique. When applied to Gaussian-basis-set wave functions, the method yields finite-basis-set approximations to the corresponding basis-set-limit v XC ( r ) , whereas the Kohn-Sham inversion produces physically inappropriate (oscillatory and divergent) potentials. The effectiveness of the procedure is demonstrated by computing accurate exchange-correlation potentials of several two-electron systems (helium isoelectronic series, H2, H3 + ) using common ab initio methods and Gaussian basis sets.

Inverting ion images without Abel inversion: maximum entropy reconstruction of velocity maps.

PubMed

Dick, Bernhard

2014-01-14

A new method for the reconstruction of velocity maps from ion images is presented, which is based on the maximum entropy concept. In contrast to other methods used for Abel inversion the new method never applies an inversion or smoothing to the data. Instead, it iteratively finds the map which is the most likely cause for the observed data, using the correct likelihood criterion for data sampled from a Poissonian distribution. The entropy criterion minimizes the information content in this map, which hence contains no information for which there is no evidence in the data. Two implementations are proposed, and their performance is demonstrated with simulated and experimental data: Maximum Entropy Velocity Image Reconstruction (MEVIR) obtains a two-dimensional slice through the velocity distribution and can be compared directly to Abel inversion. Maximum Entropy Velocity Legendre Reconstruction (MEVELER) finds one-dimensional distribution functions Q(l)(v) in an expansion of the velocity distribution in Legendre polynomials P((cos θ) for the angular dependence. Both MEVIR and MEVELER can be used for the analysis of ion images with intensities as low as 0.01 counts per pixel, with MEVELER performing significantly better than MEVIR for images with low intensity. Both methods perform better than pBASEX, in particular for images with less than one average count per pixel.

Combination of photogrammetric and geoelectric methods to assess 3d structures associated to natural hazards

NASA Astrophysics Data System (ADS)

Fargier, Yannick; Dore, Ludovic; Antoine, Raphael; Palma Lopes, Sérgio; Fauchard, Cyrille

2016-04-01

The extraction of subsurface materials is a key element for the economy of a nation. However, natural degradation of underground quarries is a major issue from an economic and public safety point of view. Consequently, the quarries stakeholders require relevant tools to define hazards associated to these structures. Safety assessment methods of underground quarries are recent and mainly based on rock physical properties. This kind of method leads to a certain homogeneity assumption of pillar internal properties that can cause an underestimation of the risk. Electrical Resistivity Imaging (ERI) is a widely used method that possesses two advantages to overcome this limitation. The first is to provide a qualitative understanding for the detection and monitoring of anomalies in the pillar body (e.g. faults). The second is to provide a quantitative description of the electrical resistivity distribution inside the pillar. This quantitative description can be interpreted with constitutive laws to help decision support (water content decreases the mechanical resistance of a chalk). However, conventional 2D and 3D Imaging techniques are usually applied to flat surface surveys or to surfaces with moderate topography. A 3D inversion of more complex media (case of the pillar) requires a full consideration of the geometry that was never taken into account before. The Photogrammetric technique presents a cost effective solution to obtain an accurate description of the external geometry of a complex media. However, this method has never been fully coupled with a geophysical method to enhance/improve the inversion process. Consequently we developed a complete procedure showing that photogrammetric and ERI tools can be efficiently combined to assess a complex 3D structure. This procedure includes in a first part a photogrammetric survey, a processing stage with an open source software and a post-processing stage finalizing a 3D surface model. The second part necessitates the production of a complete 3D mesh of the previous surface model to operate some forward modelization of the geo-electrical problem. To solve the inverse problem and obtain a 3D resistivity distribution we use a double grid method associated with a regularized Gauss-Newton inversion scheme. We applied this procedure to a synthetic case to demonstrate the impact of the geometry on the inversion result. This study shows that geometrical information in between electrodes are necessary to reconstruct finely the "true model". Finally, we apply the methodology to a real underground quarry pillar, implying one photogrammetric survey and three ERI surveys. The results show that the procedure can greatly improve the reconstruction and avoid some artifacts due to strong geometry variations.

Geological modeling and infiltration pattern of a karstic system based upon crossed geophysical methods and image-guided inversion

NASA Astrophysics Data System (ADS)

Duran, Lea; Jardani, Abderrahim; Fournier, Matthieu; Massei, Nicolas

2015-04-01

Karstic aquifers represent an important part of the water resources worldwide. Though they have been widely studied on many aspects, their geological and hydrogeological modeling is still complex. Geophysical methods can provide useful subsurface information for the characterization and mapping of karstic systems, especially when not accessible by speleology. The site investigated in this study is a sinkhole-spring system, with small diameter conduits that run within a chalk aquifer (Norville, in Upper Normandy, France). This site was investigated using several geophysical methods: electrical tomography, self-potential, mise-à-la-masse methods, and electromagnetic method (EM34). Coupling those results with boreholes data, a 3D geological model of the hydrogeological basin was established, including tectonic features as well as infiltration structures (sinkhole, covered dolines). The direction of the karstic conduits near the main sinkhole could be established, and the major fault was shown to be a hydraulic barrier. Also the average concentration of dolines on the basin could be estimated, as well as their depth. At last, several hypotheses could be made concerning the location of the main conduit network between the sinkhole and the spring, using previous hydrodynamic study of the site along with geophysical data. In order to validate the 3D geological model, an image-guided inversion of the apparent resistivity data was used. With this approach it is possible to use geological cross sections to constrain the inversion of apparent resistivity data, preserving both discontinuities and coherences in the inversion of the resistivity data. This method was used on the major fault, enabling to choose one geological interpretation over another (fault block structure near the fault, rather than important folding). The constrained inversion was also applied on covered dolines, to validate the interpretation of their shape and depth. Key words: Magnetic and electrical methods, karstic system modeling; image-guided inversion

Decomposed direct matrix inversion for fast non-cartesian SENSE reconstructions.

PubMed

Qian, Yongxian; Zhang, Zhenghui; Wang, Yi; Boada, Fernando E

2006-08-01

A new k-space direct matrix inversion (DMI) method is proposed here to accelerate non-Cartesian SENSE reconstructions. In this method a global k-space matrix equation is established on basic MRI principles, and the inverse of the global encoding matrix is found from a set of local matrix equations by taking advantage of the small extension of k-space coil maps. The DMI algorithm's efficiency is achieved by reloading the precalculated global inverse when the coil maps and trajectories remain unchanged, such as in dynamic studies. Phantom and human subject experiments were performed on a 1.5T scanner with a standard four-channel phased-array cardiac coil. Interleaved spiral trajectories were used to collect fully sampled and undersampled 3D raw data. The equivalence of the global k-space matrix equation to its image-space version, was verified via conjugate gradient (CG) iterative algorithms on a 2x undersampled phantom and numerical-model data sets. When applied to the 2x undersampled phantom and human-subject raw data, the decomposed DMI method produced images with small errors (< or = 3.9%) relative to the reference images obtained from the fully-sampled data, at a rate of 2 s per slice (excluding 4 min for precalculating the global inverse at an image size of 256 x 256). The DMI method may be useful for noise evaluations in parallel coil designs, dynamic MRI, and 3D sodium MRI with fixed coils and trajectories. Copyright 2006 Wiley-Liss, Inc.

Inverse transport calculations in optical imaging with subspace optimization algorithms

DOE Office of Scientific and Technical Information (OSTI.GOV)

Ding, Tian, E-mail: tding@math.utexas.edu; Ren, Kui, E-mail: ren@math.utexas.edu

2014-09-15

Inverse boundary value problems for the radiative transport equation play an important role in optics-based medical imaging techniques such as diffuse optical tomography (DOT) and fluorescence optical tomography (FOT). Despite the rapid progress in the mathematical theory and numerical computation of these inverse problems in recent years, developing robust and efficient reconstruction algorithms remains a challenging task and an active research topic. We propose here a robust reconstruction method that is based on subspace minimization techniques. The method splits the unknown transport solution (or a functional of it) into low-frequency and high-frequency components, and uses singular value decomposition to analyticallymore » recover part of low-frequency information. Minimization is then applied to recover part of the high-frequency components of the unknowns. We present some numerical simulations with synthetic data to demonstrate the performance of the proposed algorithm.« less

Three-dimensional geostatistical inversion of flowmeter and pumping test data.

PubMed

Li, Wei; Englert, Andreas; Cirpka, Olaf A; Vereecken, Harry

2008-01-01

We jointly invert field data of flowmeter and multiple pumping tests in fully screened wells to estimate hydraulic conductivity using a geostatistical method. We use the steady-state drawdowns of pumping tests and the discharge profiles of flowmeter tests as our data in the inference. The discharge profiles need not be converted to absolute hydraulic conductivities. Consequently, we do not need measurements of depth-averaged hydraulic conductivity at well locations. The flowmeter profiles contain information about relative vertical distributions of hydraulic conductivity, while drawdown measurements of pumping tests provide information about horizontal fluctuation of the depth-averaged hydraulic conductivity. We apply the method to data obtained at the Krauthausen test site of the Forschungszentrum Jülich, Germany. The resulting estimate of our joint three-dimensional (3D) geostatistical inversion shows an improved 3D structure in comparison to the inversion of pumping test data only.

On uncertainty quantification in hydrogeology and hydrogeophysics

NASA Astrophysics Data System (ADS)

Linde, Niklas; Ginsbourger, David; Irving, James; Nobile, Fabio; Doucet, Arnaud

2017-12-01

Recent advances in sensor technologies, field methodologies, numerical modeling, and inversion approaches have contributed to unprecedented imaging of hydrogeological properties and detailed predictions at multiple temporal and spatial scales. Nevertheless, imaging results and predictions will always remain imprecise, which calls for appropriate uncertainty quantification (UQ). In this paper, we outline selected methodological developments together with pioneering UQ applications in hydrogeology and hydrogeophysics. The applied mathematics and statistics literature is not easy to penetrate and this review aims at helping hydrogeologists and hydrogeophysicists to identify suitable approaches for UQ that can be applied and further developed to their specific needs. To bypass the tremendous computational costs associated with forward UQ based on full-physics simulations, we discuss proxy-modeling strategies and multi-resolution (Multi-level Monte Carlo) methods. We consider Bayesian inversion for non-linear and non-Gaussian state-space problems and discuss how Sequential Monte Carlo may become a practical alternative. We also describe strategies to account for forward modeling errors in Bayesian inversion. Finally, we consider hydrogeophysical inversion, where petrophysical uncertainty is often ignored leading to overconfident parameter estimation. The high parameter and data dimensions encountered in hydrogeological and geophysical problems make UQ a complicated and important challenge that has only been partially addressed to date.

Comparison of methods applied in photoinduced transient spectroscopy to determining the defect center parameters: The correlation procedure and the signal analysis based on inverse Laplace transformation

NASA Astrophysics Data System (ADS)

Suproniuk, M.; Pawłowski, M.; Wierzbowski, M.; Majda-Zdancewicz, E.; Pawłowski, Ma.

2018-04-01

The procedure for determination of trap parameters by photo-induced transient spectroscopy is based on the Arrhenius plot that illustrates a thermal dependence of the emission rate. In this paper, we show that the Arrhenius plot obtained by the correlation method is shifted toward lower temperatures as compared to the one obtained with the inverse Laplace transformation. This shift is caused by the model adequacy error of the correlation method and introduces errors to a calculation procedure of defect center parameters. The effect is exemplified by comparing the results of the determination of trap parameters with both methods based on photocurrent transients for defect centers observed in tin-doped neutron-irradiated silicon crystals and in gallium arsenide grown with the Vertical Gradient Freeze method.

A novel post-processing scheme for two-dimensional electrical impedance tomography based on artificial neural networks

PubMed Central

2017-01-01

Objective Electrical Impedance Tomography (EIT) is a powerful non-invasive technique for imaging applications. The goal is to estimate the electrical properties of living tissues by measuring the potential at the boundary of the domain. Being safe with respect to patient health, non-invasive, and having no known hazards, EIT is an attractive and promising technology. However, it suffers from a particular technical difficulty, which consists of solving a nonlinear inverse problem in real time. Several nonlinear approaches have been proposed as a replacement for the linear solver, but in practice very few are capable of stable, high-quality, and real-time EIT imaging because of their very low robustness to errors and inaccurate modeling, or because they require considerable computational effort. Methods In this paper, a post-processing technique based on an artificial neural network (ANN) is proposed to obtain a nonlinear solution to the inverse problem, starting from a linear solution. While common reconstruction methods based on ANNs estimate the solution directly from the measured data, the method proposed here enhances the solution obtained from a linear solver. Conclusion Applying a linear reconstruction algorithm before applying an ANN reduces the effects of noise and modeling errors. Hence, this approach significantly reduces the error associated with solving 2D inverse problems using machine-learning-based algorithms. Significance This work presents radical enhancements in the stability of nonlinear methods for biomedical EIT applications. PMID:29206856

Refining mortality estimates in shark demographic analyses: a Bayesian inverse matrix approach.

PubMed

Smart, Jonathan J; Punt, André E; White, William T; Simpfendorfer, Colin A

2018-01-18

Leslie matrix models are an important analysis tool in conservation biology that are applied to a diversity of taxa. The standard approach estimates the finite rate of population growth (λ) from a set of vital rates. In some instances, an estimate of λ is available, but the vital rates are poorly understood and can be solved for using an inverse matrix approach. However, these approaches are rarely attempted due to prerequisites of information on the structure of age or stage classes. This study addressed this issue by using a combination of Monte Carlo simulations and the sample-importance-resampling (SIR) algorithm to solve the inverse matrix problem without data on population structure. This approach was applied to the grey reef shark (Carcharhinus amblyrhynchos) from the Great Barrier Reef (GBR) in Australia to determine the demography of this population. Additionally, these outputs were applied to another heavily fished population from Papua New Guinea (PNG) that requires estimates of λ for fisheries management. The SIR analysis determined that natural mortality (M) and total mortality (Z) based on indirect methods have previously been overestimated for C. amblyrhynchos, leading to an underestimated λ. The updated Z distributions determined using SIR provided λ estimates that matched an empirical λ for the GBR population and corrected obvious error in the demographic parameters for the PNG population. This approach provides opportunity for the inverse matrix approach to be applied more broadly to situations where information on population structure is lacking. © 2018 by the Ecological Society of America.

Time-domain wavefield reconstruction inversion

NASA Astrophysics Data System (ADS)

Li, Zhen-Chun; Lin, Yu-Zhao; Zhang, Kai; Li, Yuan-Yuan; Yu, Zhen-Nan

2017-12-01

Wavefield reconstruction inversion (WRI) is an improved full waveform inversion theory that has been proposed in recent years. WRI method expands the searching space by introducing the wave equation into the objective function and reconstructing the wavefield to update model parameters, thereby improving the computing efficiency and mitigating the influence of the local minimum. However, frequency-domain WRI is difficult to apply to real seismic data because of the high computational memory demand and requirement of time-frequency transformation with additional computational costs. In this paper, wavefield reconstruction inversion theory is extended into the time domain, the augmented wave equation of WRI is derived in the time domain, and the model gradient is modified according to the numerical test with anomalies. The examples of synthetic data illustrate the accuracy of time-domain WRI and the low dependency of WRI on low-frequency information.

Inversion of chlorophyll contents by use of hyperspectral CHRIS data based on radiative transfer model

NASA Astrophysics Data System (ADS)

Wang, M. C.; Niu, X. F.; Chen, S. B.; Guo, P. J.; Yang, Q.; Wang, Z. J.

2014-03-01

Chlorophyll content, the most important pigment related to photosynthesis, is the key parameter for vegetation growth. The continuous spectrum characteristics of ground objects can be captured through hyperspectral remotely sensed data. In this study, based on the coniferous forest radiative transfer model, chlorophyll contents were inverted by use of hyperspectral CHRIS data in the coniferous forest coverage of Changbai Mountain Area. In addition, the sensitivity of LIBERTY model was analyzed. The experimental results validated that the reflectance simulation of different chlorophyll contents was coincided with that of the field measurement, and hyperspectral vegetation indices applied to the quantitative inversion of chlorophyll contents was feasible and accurate. This study presents a reasonable method of chlorophyll inversion for the coniferous forest, promotes the inversion precision, is of significance in coniferous forest monitoring.

A stochastic approach for model reduction and memory function design in hydrogeophysical inversion

NASA Astrophysics Data System (ADS)

Hou, Z.; Kellogg, A.; Terry, N.

2009-12-01

Geophysical (e.g., seismic, electromagnetic, radar) techniques and statistical methods are essential for research related to subsurface characterization, including monitoring subsurface flow and transport processes, oil/gas reservoir identification, etc. For deep subsurface characterization such as reservoir petroleum exploration, seismic methods have been widely used. Recently, electromagnetic (EM) methods have drawn great attention in the area of reservoir characterization. However, considering the enormous computational demand corresponding to seismic and EM forward modeling, it is usually a big problem to have too many unknown parameters in the modeling domain. For shallow subsurface applications, the characterization can be very complicated considering the complexity and nonlinearity of flow and transport processes in the unsaturated zone. It is warranted to reduce the dimension of parameter space to a reasonable level. Another common concern is how to make the best use of time-lapse data with spatial-temporal correlations. This is even more critical when we try to monitor subsurface processes using geophysical data collected at different times. The normal practice is to get the inverse images individually. These images are not necessarily continuous or even reasonably related, because of the non-uniqueness of hydrogeophysical inversion. We propose to use a stochastic framework by integrating minimum-relative-entropy concept, quasi Monto Carlo sampling techniques, and statistical tests. The approach allows efficient and sufficient exploration of all possibilities of model parameters and evaluation of their significances to geophysical responses. The analyses enable us to reduce the parameter space significantly. The approach can be combined with Bayesian updating, allowing us to treat the updated ‘posterior’ pdf as a memory function, which stores all the information up to date about the distributions of soil/field attributes/properties, then consider the memory function as a new prior and generate samples from it for further updating when more geophysical data is available. We applied this approach for deep oil reservoir characterization and for shallow subsurface flow monitoring. The model reduction approach reliably helps reduce the joint seismic/EM/radar inversion computational time to reasonable levels. Continuous inversion images are obtained using time-lapse data with the “memory function” applied in the Bayesian inversion.

Bayesian prestack seismic inversion with a self-adaptive Huber-Markov random-field edge protection scheme

NASA Astrophysics Data System (ADS)

Tian, Yu-Kun; Zhou, Hui; Chen, Han-Ming; Zou, Ya-Ming; Guan, Shou-Jun

2013-12-01

Seismic inversion is a highly ill-posed problem, due to many factors such as the limited seismic frequency bandwidth and inappropriate forward modeling. To obtain a unique solution, some smoothing constraints, e.g., the Tikhonov regularization are usually applied. The Tikhonov method can maintain a global smooth solution, but cause a fuzzy structure edge. In this paper we use Huber-Markov random-field edge protection method in the procedure of inverting three parameters, P-velocity, S-velocity and density. The method can avoid blurring the structure edge and resist noise. For the parameter to be inverted, the Huber-Markov random-field constructs a neighborhood system, which further acts as the vertical and lateral constraints. We use a quadratic Huber edge penalty function within the layer to suppress noise and a linear one on the edges to avoid a fuzzy result. The effectiveness of our method is proved by inverting the synthetic data without and with noises. The relationship between the adopted constraints and the inversion results is analyzed as well.

Silk fibroin scaffolds with inverse opal structure for bone tissue engineering.

PubMed

Sommer, Marianne R; Vetsch, Jolanda R; Leemann, Jessica; Müller, Ralph; Studart, André R; Hofmann, Sandra

2017-10-01

How scaffold porosity, pore diameter and geometry influence cellular behavior is-although heavily researched - merely understood, especially in 3D. This is mainly caused by a lack of suitable, reproducible scaffold fabrication methods, with processes such as gas foaming, lyophilization or particulate leaching still being the standard. Here we propose a method to generate highly porous silk fibroin scaffolds with monodisperse spherical pores, namely inverse opals, and study their effect on cell behavior. These silk fibroin inverse opal scaffolds were compared to salt-leached silk fibroin scaffolds in terms of human mesenchymal stem cell response upon osteogenic differentiation signals. While cell number remained similar on both scaffold types, extracellular matrix mineralization nearly doubled on the newly developed scaffolds, suggesting a positive effect on cell differentiation. By using the very same material with comparable average pore diameters, this increase in mineral content can be attributed to either the differences in pore diameter distribution or the pore geometry. Although the exact mechanisms leading to enhanced mineralization in inverse opals are not yet fully understood, our results indicate that control over pore geometry alone can have a major impact on the bioactivity of a scaffold toward stem cell differentiation into bone tissue. © 2016 The Authors Journal of Biomedical Materials Research Part B: Applied Biomaterials Published by Wiley Periodicals, Inc. J Biomed Mater Res Part B: Appl Biomater, 105B: 2074-2084, 2017. © 2016 The Authors Journal of Biomedical Materials Research Part B: Applied Biomaterials Published by Wiley Periodicals, Inc.

WE-D-204-02: Novel Method for Correcting Degradation of Sharpness of Liquid-Crystal Display Based On Modulation Transfer Function

DOE Office of Scientific and Technical Information (OSTI.GOV)

Tokurei, S; Department of Radiology, Yamaguchi University Hospital, Ube, Yamaguchi; Morishita, J

2015-06-15

Purpose: To develop a method for improving sharpness of images reproduced on liquid-crystal displays (LCDs) by compensating for the degradation of modulation transfer function (MTF) of the LCD. Methods: The inherent MTF of a color LCD (display MTF) was measured using a commercially available color digital camera. The frequency responses necessary to compensate for the resolution property of the LCD were calculated from the inverses of the display MTFs in both the horizontal and vertical directions. In addition, the inverses of the display MTFs were combined with the response of the human eye. The finite impulse response (FIR) filters weremore » computed by taking the inverse Fourier transform of the frequency responses, and the effects of the FIR filtering on both the resolution and noise properties of the displayed images were verified by measuring the MTF and Wiener spectrum (WS), respectively. The FIR filtering was then applied to the representation of digital bone and chest radiographs. Results: The FIR filtering improved the MTF values by up to almost 1.0 or greater over the frequency range of interest, while it minimally increased the WS values. Combining the inverses of the display MTFs with the response of the human eye led to further refinement of the MTF. Our method was successfully and beneficially applied to the image interpretation of bone radiographs. The resolution enhancement of chest radiographs, which include larger scattered radiation than bone radiographs, was easily perceived by incorporating the response of the human eye. In addition, no artifacts were observed on the processed images. Conclusion: Our proposed method to compensate for the degradation of the resolution properties of LCDs has the potential to improve the observer performance of radiologists when reading digital radiographs. This work was supported in part by grant from EIZO Corporation.« less

Inversion method applied to the rotation curves of galaxies

NASA Astrophysics Data System (ADS)

Márquez-Caicedo, L. A.; Lora-Clavijo, F. D.; Sanabria-Gómez, J. D.

2017-07-01

We used simulated annealing, Montecarlo and genetic algorithm methods for matching both numerical data of density and velocity profiles in some low surface brigthness galaxies with theoretical models of Boehmer-Harko, Navarro-Frenk-White and Pseudo Isothermal Profiles for galaxies with dark matter halos. We found that Navarro-Frenk-White model does not fit at all in contrast with the other two models which fit very well. Inversion methods have been widely used in various branches of science including astrophysics (Charbonneau 1995, ApJS, 101, 309). In this work we have used three different parametric inversion methods (MonteCarlo, Genetic Algorithm and Simmulated Annealing) in order to determine the best fit of the observed data of the density and velocity profiles of a set of low surface brigthness galaxies (De Block et al. 2001, ApJ, 122, 2396) with three models of galaxies containing dark mattter. The parameters adjusted by the inversion methods were the central density and a characteristic distance in the Boehmer-Harko BH (Boehmer & Harko 2007, JCAP, 6, 25), Navarro-Frenk-White NFW (Navarro et al. 2007, ApJ, 490, 493) and Pseudo Isothermal Profile PI (Robles & Matos 2012, MNRAS, 422, 282). The results obtained showed that the BH and PI Profile dark matter galaxies fit very well for both the density and the velocity profiles, in contrast the NFW model did not make good adjustments to the profiles in any analized galaxy.

Full-Field Reconstruction of Structural Deformations and Loads from Measured Strain Data on a Wing Using the Inverse Finite Element Method

NASA Technical Reports Server (NTRS)

Miller, Eric J.; Manalo, Russel; Tessler, Alexander

2016-01-01

A study was undertaken to investigate the measurement of wing deformation and internal loads using measured strain data. Future aerospace vehicle research depends on the ability to accurately measure the deformation and internal loads during ground testing and in flight. The approach uses the inverse Finite Element Method (iFEM). The iFEM is a robust, computationally efficient method that is well suited for real-time measurement of real-time structural deformation and loads. The method has been validated in previous work, but has yet to be applied to a large-scale test article. This work is in preparation for an upcoming loads test of a half-span test wing in the Flight Loads Laboratory at the National Aeronautics and Space Administration Armstrong Flight Research Center (Edwards, California). The method has been implemented into an efficient MATLAB® (The MathWorks, Inc., Natick, Massachusetts) code for testing different sensor configurations. This report discusses formulation and implementation along with the preliminary results from a representative aerospace structure. The end goal is to investigate the modeling and sensor placement approach so that the best practices can be applied to future aerospace projects.

Multiple grid arrangement improves ligand docking with unknown binding sites: Application to the inverse docking problem.

PubMed

Ban, Tomohiro; Ohue, Masahito; Akiyama, Yutaka

2018-04-01

The identification of comprehensive drug-target interactions is important in drug discovery. Although numerous computational methods have been developed over the years, a gold standard technique has not been established. Computational ligand docking and structure-based drug design allow researchers to predict the binding affinity between a compound and a target protein, and thus, they are often used to virtually screen compound libraries. In addition, docking techniques have also been applied to the virtual screening of target proteins (inverse docking) to predict target proteins of a drug candidate. Nevertheless, a more accurate docking method is currently required. In this study, we proposed a method in which a predicted ligand-binding site is covered by multiple grids, termed multiple grid arrangement. Notably, multiple grid arrangement facilitates the conformational search for a grid-based ligand docking software and can be applied to the state-of-the-art commercial docking software Glide (Schrödinger, LLC). We validated the proposed method by re-docking with the Astex diverse benchmark dataset and blind binding site situations, which improved the correct prediction rate of the top scoring docking pose from 27.1% to 34.1%; however, only a slight improvement in target prediction accuracy was observed with inverse docking scenarios. These findings highlight the limitations and challenges of current scoring functions and the need for more accurate docking methods. The proposed multiple grid arrangement method was implemented in Glide by modifying a cross-docking script for Glide, xglide.py. The script of our method is freely available online at http://www.bi.cs.titech.ac.jp/mga_glide/. Copyright © 2018 The Authors. Published by Elsevier Ltd.. All rights reserved.

On computational experiments in some inverse problems of heat and mass transfer

NASA Astrophysics Data System (ADS)

Bilchenko, G. G.; Bilchenko, N. G.

2016-11-01

The results of mathematical modeling of effective heat and mass transfer on hypersonic aircraft permeable surfaces are considered. The physic-chemical processes (the dissociation and the ionization) in laminar boundary layer of compressible gas are appreciated. Some algorithms of control restoration are suggested for the interpolation and approximation statements of heat and mass transfer inverse problems. The differences between the methods applied for the problem solutions search for these statements are discussed. Both the algorithms are realized as programs. Many computational experiments were accomplished with the use of these programs. The parameters of boundary layer obtained by means of the A.A.Dorodnicyn's generalized integral relations method from solving the direct problems have been used to obtain the inverse problems solutions. Two types of blowing laws restoration for the inverse problem in interpolation statement are presented as the examples. The influence of the temperature factor on the blowing restoration is investigated. The different character of sensitivity of controllable parameters (the local heat flow and local tangent friction) respectively to step (discrete) changing of control (the blowing) and the switching point position is studied.

An improved pulse sequence and inversion algorithm of T2 spectrum

NASA Astrophysics Data System (ADS)

Ge, Xinmin; Chen, Hua; Fan, Yiren; Liu, Juntao; Cai, Jianchao; Liu, Jianyu

2017-03-01

The nuclear magnetic resonance transversal relaxation time is widely applied in geological prospecting, both in laboratory and downhole environments. However, current methods used for data acquisition and inversion should be reformed to characterize geological samples with complicated relaxation components and pore size distributions, such as samples of tight oil, gas shale, and carbonate. We present an improved pulse sequence to collect transversal relaxation signals based on the CPMG (Carr, Purcell, Meiboom, and Gill) pulse sequence. The echo spacing is not constant but varies in different windows, depending on prior knowledge or customer requirements. We use the entropy based truncated singular value decomposition (TSVD) to compress the ill-posed matrix and discard small singular values which cause the inversion instability. A hybrid algorithm combining the iterative TSVD and a simultaneous iterative reconstruction technique is implemented to reach the global convergence and stability of the inversion. Numerical simulations indicate that the improved pulse sequence leads to the same result as CPMG, but with lower echo numbers and computational time. The proposed method is a promising technique for geophysical prospecting and other related fields in future.

Multi-GPU parallel algorithm design and analysis for improved inversion of probability tomography with gravity gradiometry data

NASA Astrophysics Data System (ADS)

Hou, Zhenlong; Huang, Danian

2017-09-01

In this paper, we make a study on the inversion of probability tomography (IPT) with gravity gradiometry data at first. The space resolution of the results is improved by multi-tensor joint inversion, depth weighting matrix and the other methods. Aiming at solving the problems brought by the big data in the exploration, we present the parallel algorithm and the performance analysis combining Compute Unified Device Architecture (CUDA) with Open Multi-Processing (OpenMP) based on Graphics Processing Unit (GPU) accelerating. In the test of the synthetic model and real data from Vinton Dome, we get the improved results. It is also proved that the improved inversion algorithm is effective and feasible. The performance of parallel algorithm we designed is better than the other ones with CUDA. The maximum speedup could be more than 200. In the performance analysis, multi-GPU speedup and multi-GPU efficiency are applied to analyze the scalability of the multi-GPU programs. The designed parallel algorithm is demonstrated to be able to process larger scale of data and the new analysis method is practical.

Waveform inversion for 3-D earth structure using the Direct Solution Method implemented on vector-parallel supercomputer

NASA Astrophysics Data System (ADS)

Hara, Tatsuhiko

2004-08-01

We implement the Direct Solution Method (DSM) on a vector-parallel supercomputer and show that it is possible to significantly improve its computational efficiency through parallel computing. We apply the parallel DSM calculation to waveform inversion of long period (250-500 s) surface wave data for three-dimensional (3-D) S-wave velocity structure in the upper and uppermost lower mantle. We use a spherical harmonic expansion to represent lateral variation with the maximum angular degree 16. We find significant low velocities under south Pacific hot spots in the transition zone. This is consistent with other seismological studies conducted in the Superplume project, which suggests deep roots of these hot spots. We also perform simultaneous waveform inversion for 3-D S-wave velocity and Q structure. Since resolution for Q is not good, we develop a new technique in which power spectra are used as data for inversion. We find good correlation between long wavelength patterns of Vs and Q in the transition zone such as high Vs and high Q under the western Pacific.

Modeling and inversion Matlab algorithms for resistivity, induced polarization and seismic data

NASA Astrophysics Data System (ADS)

Karaoulis, M.; Revil, A.; Minsley, B. J.; Werkema, D. D.

2011-12-01

M. Karaoulis (1), D.D. Werkema (3), A. Revil (1,2), A., B. Minsley (4), (1) Colorado School of Mines, Dept. of Geophysics, Golden, CO, USA. (2) ISTerre, CNRS, UMR 5559, Université de Savoie, Equipe Volcan, Le Bourget du Lac, France. (3) U.S. EPA, ORD, NERL, ESD, CMB, Las Vegas, Nevada, USA . (4) USGS, Federal Center, Lakewood, 10, 80225-0046, CO. Abstract We propose 2D and 3D forward modeling and inversion package for DC resistivity, time domain induced polarization (IP), frequency-domain IP, and seismic refraction data. For the resistivity and IP case, discretization is based on rectangular cells, where each cell has as unknown resistivity in the case of DC modelling, resistivity and chargeability in the time domain IP modelling, and complex resistivity in the spectral IP modelling. The governing partial-differential equations are solved with the finite element method, which can be applied to both real and complex variables that are solved for. For the seismic case, forward modeling is based on solving the eikonal equation using a second-order fast marching method. The wavepaths are materialized by Fresnel volumes rather than by conventional rays. This approach accounts for complicated velocity models and is advantageous because it considers frequency effects on the velocity resolution. The inversion can accommodate data at a single time step, or as a time-lapse dataset if the geophysical data are gathered for monitoring purposes. The aim of time-lapse inversion is to find the change in the velocities or resistivities of each model cell as a function of time. Different time-lapse algorithms can be applied such as independent inversion, difference inversion, 4D inversion, and 4D active time constraint inversion. The forward algorithms are benchmarked against analytical solutions and inversion results are compared with existing ones. The algorithms are packaged as Matlab codes with a simple Graphical User Interface. Although the code is parallelized for multi-core cpus, it is not as fast as machine code. In the case of large datasets, someone should consider transferring parts of the code to C or Fortran through mex files. This code is available through EPA's website on the following link http://www.epa.gov/esd/cmb/GeophysicsWebsite/index.html Although this work was reviewed by EPA and approved for publication, it may not necessarily reflect official Agency policy.

Wavelength modulation spectroscopy--digital detection of gas absorption harmonics based on Fourier analysis.

PubMed

Mei, Liang; Svanberg, Sune

2015-03-20

This work presents a detailed study of the theoretical aspects of the Fourier analysis method, which has been utilized for gas absorption harmonic detection in wavelength modulation spectroscopy (WMS). The lock-in detection of the harmonic signal is accomplished by studying the phase term of the inverse Fourier transform of the Fourier spectrum that corresponds to the harmonic signal. The mathematics and the corresponding simulation results are given for each procedure when applying the Fourier analysis method. The present work provides a detailed view of the WMS technique when applying the Fourier analysis method.

Contribution of 3D inversion of Electrical Resistivity Tomography data applied to volcanic structures

NASA Astrophysics Data System (ADS)

Portal, Angélie; Fargier, Yannick; Lénat, Jean-François; Labazuy, Philippe

2016-04-01

The electrical resistivity tomography (ERT) method, initially developed for environmental and engineering exploration, is now commonly used for geological structures imaging. Such structures can present complex characteristics that conventional 2D inversion processes cannot perfectly integrate. Here we present a new 3D inversion algorithm named EResI, firstly developed for levee investigation, and presently applied to the study of a complex lava dome (the Puy de Dôme volcano, France). EResI algorithm is based on a conventional regularized Gauss-Newton inversion scheme and a 3D non-structured discretization of the model (double grid method based on tetrahedrons). This discretization allows to accurately model the topography of investigated structure (without a mesh deformation procedure) and also permits a precise location of the electrodes. Moreover, we demonstrate that a complete 3D unstructured discretization limits the number of inversion cells and is better adapted to the resolution capacity of tomography than a structured discretization. This study shows that a 3D inversion with a non-structured parametrization has some advantages compared to classical 2D inversions. The first advantage comes from the fact that a 2D inversion leads to artefacts due to 3D effects (3D topography, 3D internal resistivity). The second advantage comes from the fact that the capacity to experimentally align electrodes along an axis (for 2D surveys) depends on the constrains on the field (topography...). In this case, a 2D assumption induced by 2.5D inversion software prevents its capacity to model electrodes outside this axis leading to artefacts in the inversion result. The last limitation comes from the use of mesh deformation techniques used to accurately model the topography in 2D softwares. This technique used for structured discretization (Res2dinv) is prohibed for strong topography (>60 %) and leads to a small computational errors. A wide geophysical survey was carried out on the Puy de Dôme volcano resulting in 12 ERT profiles with approximatively 800 electrodes. We performed two processing stages by inverting independently each profiles in 2D (RES2DINV software) and the complete data set in 3D (EResI). The comparison of the 3D inversion results with those obtained through a conventional 2D inversion process underlined that EResI allows to accurately take into account the random electrodes positioning and reduce out-line artefacts into the inversion models due to positioning errors out of the profile axis. This comparison also highlighted the advantages to integrate several ERT lines to compute the 3D models of complex volcanic structures. Finally, the resulting 3D model allows a better interpretation of the Puy de Dome Volcano.

The inverse problem of refraction travel times, part II: Quantifying refraction nonuniqueness using a three-layer model

USGS Publications Warehouse

Ivanov, J.; Miller, R.D.; Xia, J.; Steeples, D.

2005-01-01

This paper is the second of a set of two papers in which we study the inverse refraction problem. The first paper, "Types of Geophysical Nonuniqueness through Minimization," studies and classifies the types of nonuniqueness that exist when solving inverse problems depending on the participation of a priori information required to obtain reliable solutions of inverse geophysical problems. In view of the classification developed, in this paper we study the type of nonuniqueness associated with the inverse refraction problem. An approach for obtaining a realistic solution to the inverse refraction problem is offered in a third paper that is in preparation. The nonuniqueness of the inverse refraction problem is examined by using a simple three-layer model. Like many other inverse geophysical problems, the inverse refraction problem does not have a unique solution. Conventionally, nonuniqueness is considered to be a result of insufficient data and/or error in the data, for any fixed number of model parameters. This study illustrates that even for overdetermined and error free data, nonlinear inverse refraction problems exhibit exact-data nonuniqueness, which further complicates the problem of nonuniqueness. By evaluating the nonuniqueness of the inverse refraction problem, this paper targets the improvement of refraction inversion algorithms, and as a result, the achievement of more realistic solutions. The nonuniqueness of the inverse refraction problem is examined initially by using a simple three-layer model. The observations and conclusions of the three-layer model nonuniqueness study are used to evaluate the nonuniqueness of more complicated n-layer models and multi-parameter cell models such as in refraction tomography. For any fixed number of model parameters, the inverse refraction problem exhibits continuous ranges of exact-data nonuniqueness. Such an unfavorable type of nonuniqueness can be uniquely solved only by providing abundant a priori information. Insufficient a priori information during the inversion is the reason why refraction methods often may not produce desired results or even fail. This work also demonstrates that the application of the smoothing constraints, typical when solving ill-posed inverse problems, has a dual and contradictory role when applied to the ill-posed inverse problem of refraction travel times. This observation indicates that smoothing constraints may play such a two-fold role when applied to other inverse problems. Other factors that contribute to inverse-refraction-problem nonuniqueness are also considered, including indeterminacy, statistical data-error distribution, numerical error and instability, finite data, and model parameters. ?? Birkha??user Verlag, Basel, 2005.

Electrical Resistivity Tomography using a finite element based BFGS algorithm with algebraic multigrid preconditioning

NASA Astrophysics Data System (ADS)

Codd, A. L.; Gross, L.

2018-03-01

We present a new inversion method for Electrical Resistivity Tomography which, in contrast to established approaches, minimizes the cost function prior to finite element discretization for the unknown electric conductivity and electric potential. Minimization is performed with the Broyden-Fletcher-Goldfarb-Shanno method (BFGS) in an appropriate function space. BFGS is self-preconditioning and avoids construction of the dense Hessian which is the major obstacle to solving large 3-D problems using parallel computers. In addition to the forward problem predicting the measurement from the injected current, the so-called adjoint problem also needs to be solved. For this problem a virtual current is injected through the measurement electrodes and an adjoint electric potential is obtained. The magnitude of the injected virtual current is equal to the misfit at the measurement electrodes. This new approach has the advantage that the solution process of the optimization problem remains independent to the meshes used for discretization and allows for mesh adaptation during inversion. Computation time is reduced by using superposition of pole loads for the forward and adjoint problems. A smoothed aggregation algebraic multigrid (AMG) preconditioned conjugate gradient is applied to construct the potentials for a given electric conductivity estimate and for constructing a first level BFGS preconditioner. Through the additional reuse of AMG operators and coarse grid solvers inversion time for large 3-D problems can be reduced further. We apply our new inversion method to synthetic survey data created by the resistivity profile representing the characteristics of subsurface fluid injection. We further test it on data obtained from a 2-D surface electrode survey on Heron Island, a small tropical island off the east coast of central Queensland, Australia.

Required Accuracy of Structural Constraints in the Inversion of Electrical Resistivity Data for Improved Water Content Estimation

NASA Astrophysics Data System (ADS)

Heinze, T.; Budler, J.; Weigand, M.; Kemna, A.

2017-12-01

Water content distribution in the ground is essential for hazard analysis during monitoring of landslide prone hills. Geophysical methods like electrical resistivity tomography (ERT) can be utilized to determine the spatial distribution of water content using established soil physical relationships between bulk electrical resistivity and water content. However, often more dominant electrical contrasts due to lithological structures outplay these hydraulic signatures and blur the results in the inversion process. Additionally, the inversion of ERT data requires further constraints. In the standard Occam inversion method, a smoothness constraint is used, assuming that soil properties change softly in space. While this applies in many scenarios, sharp lithological layers with strongly divergent hydrological parameters, as often found in landslide prone hillslopes, are typically badly resolved by standard ERT. We use a structurally constrained ERT inversion approach for improving water content estimation in landslide prone hills by including a-priori information about lithological layers. The smoothness constraint is reduced along layer boundaries identified using seismic data. This approach significantly improves water content estimations, because in landslide prone hills often a layer of rather high hydraulic conductivity is followed by a hydraulic barrier like clay-rich soil, causing higher pore pressures. One saturated layer and one almost drained layer typically result also in a sharp contrast in electrical resistivity, assuming that surface conductivity of the soil does not change in similar order. Using synthetic data, we study the influence of uncertainties in the a-priori information on the inverted resistivity and estimated water content distribution. We find a similar behavior over a broad range of models and depths. Based on our simulation results, we provide best-practice recommendations for field applications and suggest important tests to obtain reliable, reproducible and trustworthy results. We finally apply our findings to field data, compare conventional and improved analysis results, and discuss limitations of the structurally-constrained inversion approach.

Computing the Sensitivity Kernels for 2.5-D Seismic Waveform Inversion in Heterogeneous, Anisotropic Media

NASA Astrophysics Data System (ADS)

Zhou, Bing; Greenhalgh, S. A.

2011-10-01

2.5-D modeling and inversion techniques are much closer to reality than the simple and traditional 2-D seismic wave modeling and inversion. The sensitivity kernels required in full waveform seismic tomographic inversion are the Fréchet derivatives of the displacement vector with respect to the independent anisotropic model parameters of the subsurface. They give the sensitivity of the seismograms to changes in the model parameters. This paper applies two methods, called `the perturbation method' and `the matrix method', to derive the sensitivity kernels for 2.5-D seismic waveform inversion. We show that the two methods yield the same explicit expressions for the Fréchet derivatives using a constant-block model parameterization, and are available for both the line-source (2-D) and the point-source (2.5-D) cases. The method involves two Green's function vectors and their gradients, as well as the derivatives of the elastic modulus tensor with respect to the independent model parameters. The two Green's function vectors are the responses of the displacement vector to the two directed unit vectors located at the source and geophone positions, respectively; they can be generally obtained by numerical methods. The gradients of the Green's function vectors may be approximated in the same manner as the differential computations in the forward modeling. The derivatives of the elastic modulus tensor with respect to the independent model parameters can be obtained analytically, dependent on the class of medium anisotropy. Explicit expressions are given for two special cases—isotropic and tilted transversely isotropic (TTI) media. Numerical examples are given for the latter case, which involves five independent elastic moduli (or Thomsen parameters) plus one angle defining the symmetry axis.

Inverse Modeling of Texas NOx Emissions Using Space-Based and Ground-Based NO2 Observations

NASA Technical Reports Server (NTRS)

Tang, Wei; Cohan, D.; Lamsal, L. N.; Xiao, X.; Zhou, W.

2013-01-01

Inverse modeling of nitrogen oxide (NOx) emissions using satellite-based NO2 observations has become more prevalent in recent years, but has rarely been applied to regulatory modeling at regional scales. In this study, OMI satellite observations of NO2 column densities are used to conduct inverse modeling of NOx emission inventories for two Texas State Implementation Plan (SIP) modeling episodes. Addition of lightning, aircraft, and soil NOx emissions to the regulatory inventory narrowed but did not close the gap between modeled and satellite observed NO2 over rural regions. Satellitebased top-down emission inventories are created with the regional Comprehensive Air Quality Model with extensions (CAMx) using two techniques: the direct scaling method and discrete Kalman filter (DKF) with Decoupled Direct Method (DDM) sensitivity analysis. The simulations with satellite-inverted inventories are compared to the modeling results using the a priori inventory as well as an inventory created by a ground-level NO2 based DKF inversion. The DKF inversions yield conflicting results: the satellite based inversion scales up the a priori NOx emissions in most regions by factors of 1.02 to 1.84, leading to 3-55% increase in modeled NO2 column densities and 1-7 ppb increase in ground 8 h ozone concentrations, while the ground-based inversion indicates the a priori NOx emissions should be scaled by factors of 0.34 to 0.57 in each region. However, none of the inversions improve the model performance in simulating aircraft-observed NO2 or ground-level ozone (O3) concentrations.

Inverse modeling of Texas NOx emissions using space-based and ground-based NO2 observations

NASA Astrophysics Data System (ADS)

Tang, W.; Cohan, D. S.; Lamsal, L. N.; Xiao, X.; Zhou, W.

2013-11-01

Inverse modeling of nitrogen oxide (NOx) emissions using satellite-based NO2 observations has become more prevalent in recent years, but has rarely been applied to regulatory modeling at regional scales. In this study, OMI satellite observations of NO2 column densities are used to conduct inverse modeling of NOx emission inventories for two Texas State Implementation Plan (SIP) modeling episodes. Addition of lightning, aircraft, and soil NOx emissions to the regulatory inventory narrowed but did not close the gap between modeled and satellite-observed NO2 over rural regions. Satellite-based top-down emission inventories are created with the regional Comprehensive Air Quality Model with extensions (CAMx) using two techniques: the direct scaling method and discrete Kalman filter (DKF) with decoupled direct method (DDM) sensitivity analysis. The simulations with satellite-inverted inventories are compared to the modeling results using the a priori inventory as well as an inventory created by a ground-level NO2-based DKF inversion. The DKF inversions yield conflicting results: the satellite-based inversion scales up the a priori NOx emissions in most regions by factors of 1.02 to 1.84, leading to 3-55% increase in modeled NO2 column densities and 1-7 ppb increase in ground 8 h ozone concentrations, while the ground-based inversion indicates the a priori NOx emissions should be scaled by factors of 0.34 to 0.57 in each region. However, none of the inversions improve the model performance in simulating aircraft-observed NO2 or ground-level ozone (O3) concentrations.

Inverse modeling of Texas NOx emissions using space-based and ground-based NO2 observations

NASA Astrophysics Data System (ADS)

Tang, W.; Cohan, D.; Lamsal, L. N.; Xiao, X.; Zhou, W.

2013-07-01

Inverse modeling of nitrogen oxide (NOx) emissions using satellite-based NO2 observations has become more prevalent in recent years, but has rarely been applied to regulatory modeling at regional scales. In this study, OMI satellite observations of NO2 column densities are used to conduct inverse modeling of NOx emission inventories for two Texas State Implementation Plan (SIP) modeling episodes. Addition of lightning, aircraft, and soil NOx emissions to the regulatory inventory narrowed but did not close the gap between modeled and satellite observed NO2 over rural regions. Satellite-based top-down emission inventories are created with the regional Comprehensive Air Quality Model with extensions (CAMx) using two techniques: the direct scaling method and discrete Kalman filter (DKF) with Decoupled Direct Method (DDM) sensitivity analysis. The simulations with satellite-inverted inventories are compared to the modeling results using the a priori inventory as well as an inventory created by a ground-level NO2 based DKF inversion. The DKF inversions yield conflicting results: the satellite-based inversion scales up the a priori NOx emissions in most regions by factors of 1.02 to 1.84, leading to 3-55% increase in modeled NO2 column densities and 1-7 ppb increase in ground 8 h ozone concentrations, while the ground-based inversion indicates the a priori NOx emissions should be scaled by factors of 0.34 to 0.57 in each region. However, none of the inversions improve the model performance in simulating aircraft-observed NO2 or ground-level ozone (O3) concentrations.

Methodes entropiques appliquees au probleme inverse en magnetoencephalographie

NASA Astrophysics Data System (ADS)

Lapalme, Ervig

2005-07-01

This thesis is devoted to biomagnetic source localization using magnetoencephalography. This problem is known to have an infinite number of solutions. So methods are required to take into account anatomical and functional information on the solution. The work presented in this thesis uses the maximum entropy on the mean method to constrain the solution. This method originates from statistical mechanics and information theory. This thesis is divided into two main parts containing three chapters each. The first part reviews the magnetoencephalographic inverse problem: the theory needed to understand its context and the hypotheses for simplifying the problem. In the last chapter of this first part, the maximum entropy on the mean method is presented: its origins are explained and also how it is applied to our problem. The second part is the original work of this thesis presenting three articles; one of them already published and two others submitted for publication. In the first article, a biomagnetic source model is developed and applied in a theoretical con text but still demonstrating the efficiency of the method. In the second article, we go one step further towards a realistic modelization of the cerebral activation. The main priors are estimated using the magnetoencephalographic data. This method proved to be very efficient in realistic simulations. In the third article, the previous method is extended to deal with time signals thus exploiting the excellent time resolution offered by magnetoencephalography. Compared with our previous work, the temporal method is applied to real magnetoencephalographic data coming from a somatotopy experience and results agree with previous physiological knowledge about this kind of cognitive process.

Fast method to compute scattering by a buried object under a randomly rough surface: PILE combined with FB-SA.

PubMed

Bourlier, Christophe; Kubické, Gildas; Déchamps, Nicolas

2008-04-01

A fast, exact numerical method based on the method of moments (MM) is developed to calculate the scattering from an object below a randomly rough surface. Déchamps et al. [J. Opt. Soc. Am. A23, 359 (2006)] have recently developed the PILE (propagation-inside-layer expansion) method for a stack of two one-dimensional rough interfaces separating homogeneous media. From the inversion of the impedance matrix by block (in which two impedance matrices of each interface and two coupling matrices are involved), this method allows one to calculate separately and exactly the multiple-scattering contributions inside the layer in which the inverses of the impedance matrices of each interface are involved. Our purpose here is to apply this method for an object below a rough surface. In addition, to invert a matrix of large size, the forward-backward spectral acceleration (FB-SA) approach of complexity O(N) (N is the number of unknowns on the interface) proposed by Chou and Johnson [Radio Sci.33, 1277 (1998)] is applied. The new method, PILE combined with FB-SA, is tested on perfectly conducting circular and elliptic cylinders located below a dielectric rough interface obeying a Gaussian process with Gaussian and exponential height autocorrelation functions.

An adaptive coupling strategy for joint inversions that use petrophysical information as constraints

NASA Astrophysics Data System (ADS)

Heincke, Björn; Jegen, Marion; Moorkamp, Max; Hobbs, Richard W.; Chen, Jin

2017-01-01

Joint inversion strategies for geophysical data have become increasingly popular as they allow for the efficient combination of complementary information from different data sets. The algorithm used for the joint inversion needs to be flexible in its description of the subsurface so as to be able to handle the diverse nature of the data. Hence, joint inversion schemes are needed that 1) adequately balance data from the different methods, 2) have stable convergence behavior, 3) consider the different resolution power of the methods used and 4) link the parameter models in a way that they are suited for a wide range of applications. Here, we combine active source seismic P-wave tomography, gravity and magnetotelluric (MT) data in a petrophysical joint inversion that accounts for these issues. Data from the different methods are inverted separately but are linked through constraints accounting for parameter relationships. An advantage of performing the inversions separately is that no relative weighting between the data sets is required. To avoid perturbing the convergence behavior of the inversions by the coupling, the strengths of the constraints are readjusted at each iteration. The criterion we use to control the adaption of the coupling strengths is based on variations in the objective functions of the individual inversions from one to the next iteration. Adaption of the coupling strengths makes the joint inversion scheme also applicable to subsurface conditions, where assumed relationships are not valid everywhere, because the individual inversions decouple if it is not possible to reach adequately low data misfits for the made assumptions. In addition, the coupling constraints depend on the relative resolutions of the methods, which leads to an improved convergence behavior of the joint inversion. Another benefit of the proposed scheme is that structural information can easily be incorporated in the petrophysical joint inversion (no additional terms are added in the objective functions) by using mutually controlled structural weights for the smoothing constraints. We test our scheme using data generated from a synthetic 2-D sub-basalt model. We observe that the adaption of the coupling strengths makes the convergence of the inversions very robust (data misfits of all methods are close to the target misfits) and that final results are always close to the true models independent of the parameter choices. Finally, the scheme is applied on real data sets from the Faroe-Shetland Basin to image a basaltic sequence and underlying structures. The presence of a borehole and a 3-D reflection seismic survey in this region allows direct comparison and, hence, evaluate the quality of the joint inversion results. The results from joint inversion are more consistent with results from other studies than the ones from the corresponding individual inversions and the shape of the basaltic sequence is better resolved. However, due to the limited resolution of the individual methods used it was not possible to resolve structures underneath the basalt in detail, indicating that additional geophysical information (e.g. CSEM, reflection onsets) needs to be included.

A genetic meta-algorithm-assisted inversion approach: hydrogeological study for the determination of volumetric rock properties and matrix and fluid parameters in unsaturated formations

NASA Astrophysics Data System (ADS)

Szabó, Norbert Péter

2018-03-01

An evolutionary inversion approach is suggested for the interpretation of nuclear and resistivity logs measured by direct-push tools in shallow unsaturated sediments. The efficiency of formation evaluation is improved by estimating simultaneously (1) the petrophysical properties that vary rapidly along a drill hole with depth and (2) the zone parameters that can be treated as constant, in one inversion procedure. In the workflow, the fractional volumes of water, air, matrix and clay are estimated in adjacent depths by linearized inversion, whereas the clay and matrix properties are updated using a float-encoded genetic meta-algorithm. The proposed inversion method provides an objective estimate of the zone parameters that appear in the tool response equations applied to solve the forward problem, which can significantly increase the reliability of the petrophysical model as opposed to setting these parameters arbitrarily. The global optimization meta-algorithm not only assures the best fit between the measured and calculated data but also gives a reliable solution, practically independent of the initial model, as laboratory data are unnecessary in the inversion procedure. The feasibility test uses engineering geophysical sounding logs observed in an unsaturated loessy-sandy formation in Hungary. The multi-borehole extension of the inversion technique is developed to determine the petrophysical properties and their estimation errors along a profile of drill holes. The genetic meta-algorithmic inversion method is recommended for hydrogeophysical logging applications of various kinds to automatically extract the volumetric ratios of rock and fluid constituents as well as the most important zone parameters in a reliable inversion procedure.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Kitanidis, Peter

As large-scale, commercial storage projects become operational, the problem of utilizing information from diverse sources becomes more critically important. In this project, we developed, tested, and applied an advanced joint data inversion system for CO 2 storage modeling with large data sets for use in site characterization and real-time monitoring. Emphasis was on the development of advanced and efficient computational algorithms for joint inversion of hydro-geophysical data, coupled with state-of-the-art forward process simulations. The developed system consists of (1) inversion tools using characterization data, such as 3D seismic survey (amplitude images), borehole log and core data, as well as hydraulic,more » tracer and thermal tests before CO 2 injection, (2) joint inversion tools for updating the geologic model with the distribution of rock properties, thus reducing uncertainty, using hydro-geophysical monitoring data, and (3) highly efficient algorithms for directly solving the dense or sparse linear algebra systems derived from the joint inversion. The system combines methods from stochastic analysis, fast linear algebra, and high performance computing. The developed joint inversion tools have been tested through synthetic CO 2 storage examples.« less

Bayesian inversion of refraction seismic traveltime data

NASA Astrophysics Data System (ADS)

Ryberg, T.; Haberland, Ch

2018-03-01

We apply a Bayesian Markov chain Monte Carlo (McMC) formalism to the inversion of refraction seismic, traveltime data sets to derive 2-D velocity models below linear arrays (i.e. profiles) of sources and seismic receivers. Typical refraction data sets, especially when using the far-offset observations, are known as having experimental geometries which are very poor, highly ill-posed and far from being ideal. As a consequence, the structural resolution quickly degrades with depth. Conventional inversion techniques, based on regularization, potentially suffer from the choice of appropriate inversion parameters (i.e. number and distribution of cells, starting velocity models, damping and smoothing constraints, data noise level, etc.) and only local model space exploration. McMC techniques are used for exhaustive sampling of the model space without the need of prior knowledge (or assumptions) of inversion parameters, resulting in a large number of models fitting the observations. Statistical analysis of these models allows to derive an average (reference) solution and its standard deviation, thus providing uncertainty estimates of the inversion result. The highly non-linear character of the inversion problem, mainly caused by the experiment geometry, does not allow to derive a reference solution and error map by a simply averaging procedure. We present a modified averaging technique, which excludes parts of the prior distribution in the posterior values due to poor ray coverage, thus providing reliable estimates of inversion model properties even in those parts of the models. The model is discretized by a set of Voronoi polygons (with constant slowness cells) or a triangulated mesh (with interpolation within the triangles). Forward traveltime calculations are performed by a fast, finite-difference-based eikonal solver. The method is applied to a data set from a refraction seismic survey from Northern Namibia and compared to conventional tomography. An inversion test for a synthetic data set from a known model is also presented.

Iterative Inverse Modeling for Reconciliation of Emission Inventories during the 2006 TexAQS Intensive Field Campaign

NASA Astrophysics Data System (ADS)

Xiao, X.; Cohan, D. S.

2009-12-01

Substantial uncertainties in current emission inventories have been detected by the Texas Air Quality Study 2006 (TexAQS 2006) intensive field program. These emission uncertainties have caused large inaccuracies in model simulations of air quality and its responses to management strategies. To improve the quantitative understanding of the temporal, spatial, and categorized distributions of primary pollutant emissions by utilizing the corresponding measurements collected during TexAQS 2006, we implemented both the recursive Kalman filter and a batch matrix inversion 4-D data assimilation (FDDA) method in an iterative inverse modeling framework of the CMAQ-DDM model. Equipped with the decoupled direct method, CMAQ-DDM enables simultaneous calculation of the sensitivity coefficients of pollutant concentrations to emissions to be used in the inversions. Primary pollutant concentrations measured by the multiple platforms (TCEQ ground-based, NOAA WP-3D aircraft and Ronald H. Brown vessel, and UH Moody Tower) during TexAQS 2006 have been integrated for the use in the inverse modeling. Firstly pseudo-data analyses have been conducted to assess the two methods, taking a coarse spatial resolution emission inventory as a case. Model base case concentrations of isoprene and ozone at arbitrarily selected ground grid cells were perturbed to generate pseudo measurements with different assumed Gaussian uncertainties expressed by 1-sigma standard deviations. Single-species inversions have been conducted with both methods for isoprene and NOx surface emissions from eight states in the Southeastern United States by using the pseudo measurements of isoprene and ozone, respectively. Utilization of ozone pseudo data to invert for NOx emissions serves only for the purpose of method assessment. Both the Kalman filter and FDDA methods show good performance in tuning arbitrarily shifted a priori emissions to the base case “true” values within 3-4 iterations even for the nonlinear responses of ozone to NOx emissions. While the Kalman filter has better performance under the situation of very large observational uncertainties, the batch matrix FDDA method is better suited for incorporating temporally and spatially irregular data such as those measured by NOAA aircraft and ship. After validating the methods with the pseudo data, the inverse technique is applied to improve emission estimates of NOx from different source sectors and regions in the Houston metropolitan area by using NOx measurements during TexAQS 2006. EPA NEI2005-based and Texas-specified Emission Inventories for 2006 are used as the a priori emission estimates before optimization. The inversion results will be presented and discussed. Future work will conduct inverse modeling for additional species, and then perform a multi-species inversion for emissions consistency and reconciliation with secondary pollutants such as ozone.

Toward 2D and 3D imaging of magnetic nanoparticles using EPR measurements.

PubMed

Coene, A; Crevecoeur, G; Leliaert, J; Dupré, L

2015-09-01

Magnetic nanoparticles (MNPs) are an important asset in many biomedical applications. An effective working of these applications requires an accurate knowledge of the spatial MNP distribution. A promising, noninvasive, and sensitive technique to visualize MNP distributions in vivo is electron paramagnetic resonance (EPR). Currently only 1D MNP distributions can be reconstructed. In this paper, the authors propose extending 1D EPR toward 2D and 3D using computer simulations to allow accurate imaging of MNP distributions. To find the MNP distribution belonging to EPR measurements, an inverse problem needs to be solved. The solution of this inverse problem highly depends on the stability of the inverse problem. The authors adapt 1D EPR imaging to realize the imaging of multidimensional MNP distributions. Furthermore, the authors introduce partial volume excitation in which only parts of the volume are imaged to increase stability of the inverse solution and to speed up the measurements. The authors simulate EPR measurements of different 2D and 3D MNP distributions and solve the inverse problem. The stability is evaluated by calculating the condition measure and by comparing the actual MNP distribution to the reconstructed MNP distribution. Based on these simulations, the authors define requirements for the EPR system to cope with the added dimensions. Moreover, the authors investigate how EPR measurements should be conducted to improve the stability of the associated inverse problem and to increase reconstruction quality. The approach used in 1D EPR can only be employed for the reconstruction of small volumes in 2D and 3D EPRs due to numerical instability of the inverse solution. The authors performed EPR measurements of increasing cylindrical volumes and evaluated the condition measure. This showed that a reduction of the inherent symmetry in the EPR methodology is necessary. By reducing the symmetry of the EPR setup, quantitative images of larger volumes can be obtained. The authors found that, by selectively exciting parts of the volume, the authors could increase the reconstruction quality even further while reducing the amount of measurements. Additionally, the inverse solution of this activation method degrades slower for increasing volumes. Finally, the methodology was applied to noisy EPR measurements: using the reduced EPR setup's symmetry and the partial activation method, an increase in reconstruction quality of ≈ 80% can be seen with a speedup of the measurements with 10%. Applying the aforementioned requirements to the EPR setup and stabilizing the EPR measurements showed a tremendous increase in noise robustness, thereby making EPR a valuable method for quantitative imaging of multidimensional MNP distributions.

Seismic velocity structure and microearthquake source properties at The Geysers, California, geothermal area

DOE Office of Scientific and Technical Information (OSTI.GOV)

O'Connell, D.R.

1986-12-01

The method of progressive hypocenter-velocity inversion has been extended to incorporate S-wave arrival time data and to estimate S-wave velocities in addition to P-wave velocities. S-wave data to progressive inversion does not completely eliminate hypocenter-velocity tradeoffs, but they are substantially reduced. Results of a P and S-wave progressive hypocenter-velocity inversion at The Geysers show that the top of the steam reservoir is clearly defined by a large decrease of V/sub p//V/sub s/ at the condensation zone-production zone contact. The depth interval of maximum steam production coincides with minimum observed V/sub p//V/sub s/, and V/sub p//V/sub s/ increses below the shallowmore » primary production zone suggesting that reservoir rock becomes more fluid saturated. The moment tensor inversion method was applied to three microearthquakes at The Geysers. Estimated principal stress orientations were comparable to those estimated using P-wave firstmotions as constraints. Well constrained principal stress orientations were obtained for one event for which the 17 P-first motions could not distinguish between normal-slip and strike-slip mechanisms. The moment tensor estimates of principal stress orientations were obtained using far fewer stations than required for first-motion focal mechanism solutions. The three focal mechanisms obtained here support the hypothesis that focal mechanisms are a function of depth at The Geysers. Progressive inversion as developed here and the moment tensor inversion method provide a complete approach for determining earthquake locations, P and S-wave velocity structure, and earthquake source mechanisms.« less

Inverse spin Hall effect in a closed loop circuit

DOE Office of Scientific and Technical Information (OSTI.GOV)

Omori, Y.; Auvray, F.; Wakamura, T.

We present measurements of inverse spin Hall effects (ISHEs), in which the conversion of a spin current into a charge current via the ISHE is detected not as a voltage in a standard open circuit but directly as the charge current generated in a closed loop. The method is applied to the ISHEs of Bi-doped Cu and Pt. The derived expression of ISHE for the loop structure can relate the charge current flowing into the loop to the spin Hall angle of the SHE material and the resistance of the loop.

Geoid Recovery using Geophysical Inverse Theory Applied to Satellite to Satellite Tracking Data

NASA Technical Reports Server (NTRS)

Gaposchkin, E. M.; Frey, H. (Technical Monitor)

2000-01-01

This report describes a new method for determination of the geopotential. The analysis is aimed at the GRACE mission. This Satellite-to-Satellite Tracking (SST) mission is viewed as a mapping mission The result will be maps of the geoid. The elements of potential theory, celestial mechanics, and Geophysical Inverse Theory are integrated into a computation architecture, and the results of several simulations presented Centimeter accuracy geoids with 50 to 100 km resolution can be recovered with a 30 to 60 day mission.

Research in Image Understanding as Applied to 3-D Microwave Tomographic Imaging with Near Optical Resolution.

DTIC Science & Technology

1987-03-01

Oct. 1985. 28. D.L. Jaggard, K. Schultz, Y. Kim and P. Frangos , "Inverse Scattering for Dielectric Media", Annual OSA Meeting, Wash. D.C., Oct. 1985...T.H. Chu - Graduate Student (50%) C.Y. Ho - Graduate Student (50%) Y. Kim - Graduate Student (50%) K S. Lee - Graduate Student (50%) P. Frangos ...1982. 3. P. Frangos (Ph.D.) - "One-Dimensional Inverse Scattering: Exact Methods and Applications". 4. C.L. Werner (Ph.D.) - ŗ-D Imaging of Coherent and

Movement Characteristics Analysis and Dynamic Simulation of Collaborative Measuring Robot

NASA Astrophysics Data System (ADS)

guoqing, MA; li, LIU; zhenglin, YU; guohua, CAO; yanbin, ZHENG

2017-03-01

Human-machine collaboration is becoming increasingly more necessary, and so collaborative robot applications are also in high demand. We selected a UR10 robot as our research subject for this study. First, we applied D-H coordinate transformation of the robot to establish a link system, and we then used inverse transformation to solve the robot’s inverse kinematics and find all the joints. Use Lagrange method to analysis UR robot dynamics; use ADAMS multibody dynamics simulation software to dynamic simulation; verifying the correctness of the derived kinetic models.

An Alternative Method of Computing Altitude Adjustment Corrected Geomagnetic Coordinates as Applied to IGRF Epoch 2005

DTIC Science & Technology

2007-07-20

science.msfc.nasa.gov/ss/pad/ sppb /workshoV7/&eoma&ne/Reo cgn/geo c&m.for. See also the GEOPACK library at http:/nssdcftp.gsfc.na-a.gov/models...calculations, fed into the inverse computation, should reproduce the original coordinate grid. This test of the consistency of the direct and inverse...algorithm. A test of this type was performed for a uniform grid, for line traces from 7200 km to the ground, and for 800 km to the ground. The maximum

A fast marching algorithm for the factored eikonal equation

DOE Office of Scientific and Technical Information (OSTI.GOV)

Treister, Eran, E-mail: erantreister@gmail.com; Haber, Eldad, E-mail: haber@math.ubc.ca; Department of Mathematics, The University of British Columbia, Vancouver, BC

The eikonal equation is instrumental in many applications in several fields ranging from computer vision to geoscience. This equation can be efficiently solved using the iterative Fast Sweeping (FS) methods and the direct Fast Marching (FM) methods. However, when used for a point source, the original eikonal equation is known to yield inaccurate numerical solutions, because of a singularity at the source. In this case, the factored eikonal equation is often preferred, and is known to yield a more accurate numerical solution. One application that requires the solution of the eikonal equation for point sources is travel time tomography. Thismore » inverse problem may be formulated using the eikonal equation as a forward problem. While this problem has been solved using FS in the past, the more recent choice for applying it involves FM methods because of the efficiency in which sensitivities can be obtained using them. However, while several FS methods are available for solving the factored equation, the FM method is available only for the original eikonal equation. In this paper we develop a Fast Marching algorithm for the factored eikonal equation, using both first and second order finite-difference schemes. Our algorithm follows the same lines as the original FM algorithm and requires the same computational effort. In addition, we show how to obtain sensitivities using this FM method and apply travel time tomography, formulated as an inverse factored eikonal equation. Numerical results in two and three dimensions show that our algorithm solves the factored eikonal equation efficiently, and demonstrate the achieved accuracy for computing the travel time. We also demonstrate a recovery of a 2D and 3D heterogeneous medium by travel time tomography using the eikonal equation for forward modeling and inversion by Gauss–Newton.« less

Refraction traveltime tomography based on damped wave equation for irregular topographic model

NASA Astrophysics Data System (ADS)

Park, Yunhui; Pyun, Sukjoon

2018-03-01

Land seismic data generally have time-static issues due to irregular topography and weathered layers at shallow depths. Unless the time static is handled appropriately, interpretation of the subsurface structures can be easily distorted. Therefore, static corrections are commonly applied to land seismic data. The near-surface velocity, which is required for static corrections, can be inferred from first-arrival traveltime tomography, which must consider the irregular topography, as the land seismic data are generally obtained in irregular topography. This paper proposes a refraction traveltime tomography technique that is applicable to an irregular topographic model. This technique uses unstructured meshes to express an irregular topography, and traveltimes calculated from the frequency-domain damped wavefields using the finite element method. The diagonal elements of the approximate Hessian matrix were adopted for preconditioning, and the principle of reciprocity was introduced to efficiently calculate the Fréchet derivative. We also included regularization to resolve the ill-posed inverse problem, and used the nonlinear conjugate gradient method to solve the inverse problem. As the damped wavefields were used, there were no issues associated with artificial reflections caused by unstructured meshes. In addition, the shadow zone problem could be circumvented because this method is based on the exact wave equation, which does not require a high-frequency assumption. Furthermore, the proposed method was both robust to an initial velocity model and efficient compared to full wavefield inversions. Through synthetic and field data examples, our method was shown to successfully reconstruct shallow velocity structures. To verify our method, static corrections were roughly applied to the field data using the estimated near-surface velocity. By comparing common shot gathers and stack sections with and without static corrections, we confirmed that the proposed tomography algorithm can be used to correct the statics of land seismic data.

The inverse electroencephalography pipeline

NASA Astrophysics Data System (ADS)

Weinstein, David Michael

The inverse electroencephalography (EEG) problem is defined as determining which regions of the brain are active based on remote measurements recorded with scalp EEG electrodes. An accurate solution to this problem would benefit both fundamental neuroscience research and clinical neuroscience applications. However, constructing accurate patient-specific inverse EEG solutions requires complex modeling, simulation, and visualization algorithms, and to date only a few systems have been developed that provide such capabilities. In this dissertation, a computational system for generating and investigating patient-specific inverse EEG solutions is introduced, and the requirements for each stage of this Inverse EEG Pipeline are defined and discussed. While the requirements of many of the stages are satisfied with existing algorithms, others have motivated research into novel modeling and simulation methods. The principal technical results of this work include novel surface-based volume modeling techniques, an efficient construction for the EEG lead field, and the Open Source release of the Inverse EEG Pipeline software for use by the bioelectric field research community. In this work, the Inverse EEG Pipeline is applied to three research problems in neurology: comparing focal and distributed source imaging algorithms; separating measurements into independent activation components for multifocal epilepsy; and localizing the cortical activity that produces the P300 effect in schizophrenia.

Stress regimes in the northwest of Iran from stress inversion of earthquake focal mechanisms

NASA Astrophysics Data System (ADS)

Afra, Mahsa; Moradi, Ali; Pakzad, Mehrdad

2017-11-01

Northwestern Iran is one of the seismically active regions with a high seismic risk in the world. This area is a part of the complex tectonic system due to the interaction between Arabia, Anatolia and Eurasia. The purpose of this study is to deduce the stress regimes in the northwestern Iran and surrounding regions from stress inversion of earthquake focal mechanisms. We compile 92 focal mechanisms data from the Global CMT catalogue and other sources and also determine the focal mechanisms of 14 earthquakes applying the moment tensor inversion. We divide the studied region into 9 zones using similarity of the horizontal GPS velocities and existing focal mechanisms. We implement two stress inversion methods, Multiple Inverse Method and Iterative Joint Inversion Method, which provide comparable results in terms of orientations of maximum horizontal stress axes SHmax. The similar results of the two methods should make us more confident about the interpretations. We consider zones of exclusion surrounding all the earthquakes according to independent focal mechanisms hypothesis. The hypothesis says that the inversion should involve events that are far enough from each other in order that any previous event doesn't affect the stress field near the earthquake under consideration. Accordingly we deal with the matter by considering zones of exclusion around all the events. The result of exclusion is only significant for eastern Anatolia. The stress regime in this region changes from oblique to strike slip faulting because of the exclusion. In eastern Anatolia, the direction of maximum horizontal stress is nearly north-south. The direction alters to east-west in Talesh region. Errors of σ1 are lower in all zones comparing with errors of σ2 and σ3 and there is a trade-off between data resolution and covariance of the model. The results substantiate the strike-slip and thrust faulting stress regimes in the northwest of Iran.

Data matching for free-surface multiple attenuation by multidimensional deconvolution

NASA Astrophysics Data System (ADS)

van der Neut, Joost; Frijlink, Martijn; van Borselen, Roald

2012-09-01

A common strategy for surface-related multiple elimination of seismic data is to predict multiples by a convolutional model and subtract these adaptively from the input gathers. Problems can be posed by interfering multiples and primaries. Removing multiples by multidimensional deconvolution (MDD) (inversion) does not suffer from these problems. However, this approach requires data to be consistent, which is often not the case, especially not at interpolated near-offsets. A novel method is proposed to improve data consistency prior to inversion. This is done by backpropagating first-order multiples with a time-gated reference primary event and matching these with early primaries in the input gather. After data matching, multiple elimination by MDD can be applied with a deterministic inversion scheme.

Improving the accurate assessment of a layered shear-wave velocity model using joint inversion of the effective Rayleigh wave and Love wave dispersion curves

NASA Astrophysics Data System (ADS)

Yin, X.; Xia, J.; Xu, H.

2016-12-01

Rayleigh and Love waves are two types of surface waves that travel along a free surface.Based on the assumption of horizontal layered homogenous media, Rayleigh-wave phase velocity can be defined as a function of frequency and four groups of earth parameters: P-wave velocity, SV-wave velocity, density and thickness of each layer. Unlike Rayleigh waves, Love-wave phase velocities of a layered homogenous earth model could be calculated using frequency and three groups of earth properties: SH-wave velocity, density, and thickness of each layer. Because the dispersion of Love waves is independent of P-wave velocities, Love-wave dispersion curves are much simpler than Rayleigh wave. The research of joint inversion methods of Rayleigh and Love dispersion curves is necessary. (1) This dissertation adopts the combinations of theoretical analysis and practical applications. In both lateral homogenous media and radial anisotropic media, joint inversion approaches of Rayleigh and Love waves are proposed to improve the accuracy of S-wave velocities.A 10% random white noise and a 20% random white noise are added to the synthetic dispersion curves to check out anti-noise ability of the proposed joint inversion method.Considering the influences of the anomalous layer, Rayleigh and Love waves are insensitive to those layers beneath the high-velocity layer or low-velocity layer and the high-velocity layer itself. Low sensitivities will give rise to high degree of uncertainties of the inverted S-wave velocities of these layers. Considering that sensitivity peaks of Rayleigh and Love waves separate at different frequency ranges, the theoretical analyses have demonstrated that joint inversion of these two types of waves would probably ameliorate the inverted model.The lack of surface-wave (Rayleigh or Love waves) dispersion data may lead to inaccuracy S-wave velocities through the single inversion of Rayleigh or Love waves, so this dissertation presents the joint inversion method of Rayleigh and Love waves which will improve the accuracy of S-wave velocities. Finally, a real-world example is applied to verify the accuracy and stability of the proposed joint inversion method. Keywords: Rayleigh wave; Love wave; Sensitivity analysis; Joint inversion method.

Estimating soil hydraulic parameters from transient flow experiments in a centrifuge using parameter optimization technique

USGS Publications Warehouse

Šimůnek, Jirka; Nimmo, John R.

2005-01-01

A modified version of the Hydrus software package that can directly or inversely simulate water flow in a transient centrifugal field is presented. The inverse solver for parameter estimation of the soil hydraulic parameters is then applied to multirotation transient flow experiments in a centrifuge. Using time‐variable water contents measured at a sequence of several rotation speeds, soil hydraulic properties were successfully estimated by numerical inversion of transient experiments. The inverse method was then evaluated by comparing estimated soil hydraulic properties with those determined independently using an equilibrium analysis. The optimized soil hydraulic properties compared well with those determined using equilibrium analysis and steady state experiment. Multirotation experiments in a centrifuge not only offer significant time savings by accelerating time but also provide significantly more information for the parameter estimation procedure compared to multistep outflow experiments in a gravitational field.

PREFACE: The Second International Conference on Inverse Problems: Recent Theoretical Developments and Numerical Approaches

NASA Astrophysics Data System (ADS)

Cheng, Jin; Hon, Yiu-Chung; Seo, Jin Keun; Yamamoto, Masahiro

2005-01-01

The Second International Conference on Inverse Problems: Recent Theoretical Developments and Numerical Approaches was held at Fudan University, Shanghai from 16-21 June 2004. The first conference in this series was held at the City University of Hong Kong in January 2002 and it was agreed to hold the conference once every two years in a Pan-Pacific Asian country. The next conference is scheduled to be held at Hokkaido University, Sapporo, Japan in July 2006. The purpose of this series of biennial conferences is to establish and develop constant international collaboration, especially among the Pan-Pacific Asian countries. In recent decades, interest in inverse problems has been flourishing all over the globe because of both the theoretical interest and practical requirements. In particular, in Asian countries, one is witnessing remarkable new trends of research in inverse problems as well as the participation of many young talents. Considering these trends, the second conference was organized with the chairperson Professor Li Tat-tsien (Fudan University), in order to provide forums for developing research cooperation and to promote activities in the field of inverse problems. Because solutions to inverse problems are needed in various applied fields, we entertained a total of 92 participants at the second conference and arranged various talks which ranged from mathematical analyses to solutions of concrete inverse problems in the real world. This volume contains 18 selected papers, all of which have undergone peer review. The 18 papers are classified as follows: Surveys: four papers give reviews of specific inverse problems. Theoretical aspects: six papers investigate the uniqueness, stability, and reconstruction schemes. Numerical methods: four papers devise new numerical methods and their applications to inverse problems. Solutions to applied inverse problems: four papers discuss concrete inverse problems such as scattering problems and inverse problems in atmospheric sciences and oceanography. Last but not least is our gratitude. As editors we would like to express our sincere thanks to all the plenary and invited speakers, the members of the International Scientific Committee and the Advisory Board for the success of the conference, which has given rise to this present volume of selected papers. We would also like to thank Mr Wang Yanbo, Miss Wan Xiqiong and the graduate students at Fudan University for their effective work to make this conference a success. The conference was financially supported by the NFS of China, the Mathematical Center of Ministry of Education of China, E-Institutes of Shanghai Municipal Education Commission (No E03004) and Fudan University, Grant 15340027 from the Japan Society for the Promotion of Science, and Grant 15654015 from the Ministry of Education, Cultures, Sports and Technology.

Neural Network Assisted Inverse Dynamic Guidance for Terminally Constrained Entry Flight

PubMed Central

Chen, Wanchun

2014-01-01

This paper presents a neural network assisted entry guidance law that is designed by applying Bézier approximation. It is shown that a fully constrained approximation of a reference trajectory can be made by using the Bézier curve. Applying this approximation, an inverse dynamic system for an entry flight is solved to generate guidance command. The guidance solution thus gotten ensures terminal constraints for position, flight path, and azimuth angle. In order to ensure terminal velocity constraint, a prediction of the terminal velocity is required, based on which, the approximated Bézier curve is adjusted. An artificial neural network is used for this prediction of the terminal velocity. The method enables faster implementation in achieving fully constrained entry flight. Results from simulations indicate improved performance of the neural network assisted method. The scheme is expected to have prospect for further research on automated onboard control of terminal velocity for both reentry and terminal guidance laws. PMID:24723821

Numerical methods for industrial vertical Bridgman growth of (Cd,Zn)Te

NASA Astrophysics Data System (ADS)

Lin, K.; Boschert, S.; Dold, P.; Benz, K. W.; Kriessl, O.; Schmidt, A.; Siebert, K. G.; Dziuk, G.

2002-04-01

This paper presents efficient numerical methods—the "inverse modeling" method and the adaptive finite element method—for optimizing the heat transport as well as for investigating the heat and mass transport under the influence of convection during crystal growth, especially near the liquid/solid interface. These methods have been applied to industrial Bridgman-furnaces for the growth of 65-75 mm diameter (Cd,Zn)Te crystals.

Hansen solubility parameters for polyethylene glycols by inverse gas chromatography.

PubMed

Adamska, Katarzyna; Voelkel, Adam

2006-11-03

Inverse gas chromatography (IGC) has been applied to determine solubility parameter and its components for nonionic surfactants--polyethylene glycols (PEG) of different molecular weight. Flory-Huggins interaction parameter (chi) and solubility parameter (delta(2)) were calculated according to DiPaola-Baranyi and Guillet method from experimentally collected retention data for the series of carefully selected test solutes. The Hansen's three-dimensional solubility parameters concept was applied to determine components (delta(d), delta(p), delta(h)) of corrected solubility parameter (delta(T)). The molecular weight and temperature of measurement influence the solubility parameter data, estimated from the slope, intercept and total solubility parameter. The solubility parameters calculated from the intercept are lower than those calculated from the slope. Temperature and structural dependences of the entopic factor (chi(S)) are presented and discussed.

Variational approach to direct and inverse problems of atmospheric pollution studies

NASA Astrophysics Data System (ADS)

Penenko, Vladimir; Tsvetova, Elena; Penenko, Alexey

2016-04-01

We present the development of a variational approach for solving interrelated problems of atmospheric hydrodynamics and chemistry concerning air pollution transport and transformations. The proposed approach allows us to carry out complex studies of different-scale physical and chemical processes using the methods of direct and inverse modeling [1-3]. We formulate the problems of risk/vulnerability and uncertainty assessment, sensitivity studies, variational data assimilation procedures [4], etc. A computational technology of constructing consistent mathematical models and methods of their numerical implementation is based on the variational principle in the weak constraint formulation specifically designed to account for uncertainties in models and observations. Algorithms for direct and inverse modeling are designed with the use of global and local adjoint problems. Implementing the idea of adjoint integrating factors provides unconditionally monotone and stable discrete-analytic approximations for convection-diffusion-reaction problems [5,6]. The general framework is applied to the direct and inverse problems for the models of transport and transformation of pollutants in Siberian and Arctic regions. The work has been partially supported by the RFBR grant 14-01-00125 and RAS Presidium Program I.33P. References: 1. V. Penenko, A.Baklanov, E. Tsvetova and A. Mahura . Direct and inverse problems in a variational concept of environmental modeling //Pure and Applied Geoph.(2012) v.169: 447-465. 2. V. V. Penenko, E. A. Tsvetova, and A. V. Penenko Development of variational approach for direct and inverse problems of atmospheric hydrodynamics and chemistry, Izvestiya, Atmospheric and Oceanic Physics, 2015, Vol. 51, No. 3, p. 311-319, DOI: 10.1134/S0001433815030093. 3. V.V. Penenko, E.A. Tsvetova, A.V. Penenko. Methods based on the joint use of models and observational data in the framework of variational approach to forecasting weather and atmospheric composition quality// Russian meteorology and hydrology, V. 40, Issue: 6, Pages: 365-373, DOI: 10.3103/S1068373915060023. 4. A.V. Penenko and V.V. Penenko. Direct data assimilation method for convection-diffusion models based on splitting scheme. Computational technologies, 19(4):69-83, 2014. 5. V.V. Penenko, E.A. Tsvetova, A.V. Penenko Variational approach and Euler's integrating factors for environmental studies// Computers and Mathematics with Applications, 2014, V.67, Issue 12, Pages 2240-2256, DOI:10.1016/j.camwa.2014.04.004 6. V.V. Penenko, E.A. Tsvetova. Variational methods of constructing monotone approximations for atmospheric chemistry models // Numerical analysis and applications, 2013, V. 6, Issue 3, pp 210-220, DOI 10.1134/S199542391303004X

Hamiltonian Monte Carlo Inversion of Seismic Sources in Complex Media

NASA Astrophysics Data System (ADS)

Fichtner, A.; Simutė, S.

2017-12-01

We present a probabilistic seismic source inversion method that properly accounts for 3D heterogeneous Earth structure and provides full uncertainty information on the timing, location and mechanism of the event. Our method rests on two essential elements: (1) reciprocity and spectral-element simulations in complex media, and (2) Hamiltonian Monte Carlo sampling that requires only a small amount of test models. Using spectral-element simulations of 3D, visco-elastic, anisotropic wave propagation, we precompute a data base of the strain tensor in time and space by placing sources at the positions of receivers. Exploiting reciprocity, this receiver-side strain data base can be used to promptly compute synthetic seismograms at the receiver locations for any hypothetical source within the volume of interest. The rapid solution of the forward problem enables a Bayesian solution of the inverse problem. For this, we developed a variant of Hamiltonian Monte Carlo (HMC) sampling. Taking advantage of easily computable derivatives, HMC converges to the posterior probability density with orders of magnitude less samples than derivative-free Monte Carlo methods. (Exact numbers depend on observational errors and the quality of the prior). We apply our method to the Japanese Islands region where we previously constrained 3D structure of the crust and upper mantle using full-waveform inversion with a minimum period of around 15 s.

Joint inversion of lake-floor electrical resistivity tomography and boat-towed radio-magnetotelluric data illustrated on synthetic data and an application from the Äspö Hard Rock Laboratory site, Sweden

NASA Astrophysics Data System (ADS)

Wang, Shunguo; Kalscheuer, Thomas; Bastani, Mehrdad; Malehmir, Alireza; Pedersen, Laust B.; Dahlin, Torleif; Meqbel, Naser

2018-04-01

The electrical resistivity tomography (ERT) method provides moderately good constraints for both conductive and resistive structures, while the radio-magnetotelluric (RMT) method is well suited to constrain conductive structures. Additionally, RMT and ERT data may have different target coverage and are differently affected by various types of noise. Hence, joint inversion of RMT and ERT data sets may provide a better constrained model as compared to individual inversions. In this study, joint inversion of boat-towed RMT and lake-floor ERT data has for the first time been formulated and implemented. The implementation was tested on both synthetic and field data sets incorporating RMT transverse electrical mode and ERT data. Results from synthetic data demonstrate that the joint inversion yields models with better resolution compared with individual inversions. A case study from an area adjacent to the Äspö Hard Rock Laboratory (HRL) in southeastern Sweden was used to demonstrate the implementation of the method. A 790-m-long profile comprising lake-floor ERT and boat-towed RMT data combined with partial land data was used for this purpose. Joint inversions with and without weighting (applied to different data sets, vertical and horizontal model smoothness) as well as constrained joint inversions incorporating bathymetry data and water resistivity measurements were performed. The resulting models delineate subsurface structures such as a major northeasterly directed fracture system, which is observed in the HRL facility underground and confirmed by boreholes. A previously uncertain weakness zone, likely a fracture system in the northern part of the profile, is inferred in this study. The fractures are highly saturated with saline water, which make them good targets of resistivity-based geophysical methods. Nevertheless, conductive sediments overlain by the lake water add further difficulty to resolve these deep fracture zones. Therefore, the joint inversion of RMT and ERT data particularly helps to improve the resolution of the resistivity models in areas where the profile traverses shallow water and land sections. Our modification of the joint inversion of RMT and ERT data improves the study of geological units underneath shallow water bodies where underground infrastructures are planned. Thus, it allows better planning and mitigating the risks and costs associated with conductive weakness zones.

Constraining mass anomalies in the interior of spherical bodies using Trans-dimensional Bayesian Hierarchical inference.

NASA Astrophysics Data System (ADS)

Izquierdo, K.; Lekic, V.; Montesi, L.

2017-12-01

Gravity inversions are especially important for planetary applications since measurements of the variations in gravitational acceleration are often the only constraint available to map out lateral density variations in the interiors of planets and other Solar system objects. Currently, global gravity data is available for the terrestrial planets and the Moon. Although several methods for inverting these data have been developed and applied, the non-uniqueness of global density models that fit the data has not yet been fully characterized. We make use of Bayesian inference and a Reversible Jump Markov Chain Monte Carlo (RJMCMC) approach to develop a Trans-dimensional Hierarchical Bayesian (THB) inversion algorithm that yields a large sample of models that fit a gravity field. From this group of models, we can determine the most likely value of parameters of a global density model and a measure of the non-uniqueness of each parameter when the number of anomalies describing the gravity field is not fixed a priori. We explore the use of a parallel tempering algorithm and fast multipole method to reduce the number of iterations and computing time needed. We applied this method to a synthetic gravity field of the Moon and a long wavelength synthetic model of density anomalies in the Earth's lower mantle. We obtained a good match between the given gravity field and the gravity field produced by the most likely model in each inversion. The number of anomalies of the models showed parsimony of the algorithm, the value of the noise variance of the input data was retrieved, and the non-uniqueness of the models was quantified. Our results show that the ability to constrain the latitude and longitude of density anomalies, which is excellent at shallow locations (<200 km), decreases with increasing depth. With higher computational resources, this THB method for gravity inversion could give new information about the overall density distribution of celestial bodies even when there is no other geophysical data available.

Efficient Inversion of Mult-frequency and Multi-Source Electromagnetic Data

DOE Office of Scientific and Technical Information (OSTI.GOV)

Gary D. Egbert

2007-03-22

The project covered by this report focused on development of efficient but robust non-linear inversion algorithms for electromagnetic induction data, in particular for data collected with multiple receivers, and multiple transmitters, a situation extremely common in eophysical EM subsurface imaging methods. A key observation is that for such multi-transmitter problems each step in commonly used linearized iterative limited memory search schemes such as conjugate gradients (CG) requires solution of forward and adjoint EM problems for each of the N frequencies or sources, essentially generating data sensitivities for an N dimensional data-subspace. These multiple sensitivities allow a good approximation to themore » full Jacobian of the data mapping to be built up in many fewer search steps than would be required by application of textbook optimization methods, which take no account of the multiplicity of forward problems that must be solved for each search step. We have applied this idea to a develop a hybrid inversion scheme that combines features of the iterative limited memory type methods with a Newton-type approach using a partial calculation of the Jacobian. Initial tests on 2D problems show that the new approach produces results essentially identical to a Newton type Occam minimum structure inversion, while running more rapidly than an iterative (fixed regularization parameter) CG style inversion. Memory requirements, while greater than for something like CG, are modest enough that even in 3D the scheme should allow 3D inverse problems to be solved on a common desktop PC, at least for modest (~ 100 sites, 15-20 frequencies) data sets. A secondary focus of the research has been development of a modular system for EM inversion, using an object oriented approach. This system has proven useful for more rapid prototyping of inversion algorithms, in particular allowing initial development and testing to be conducted with two-dimensional example problems, before approaching more computationally cumbersome three-dimensional problems.« less

Final Project Report: Imaging Fault Zones Using a Novel Elastic Reverse-Time Migration Imaging Technique

DOE Office of Scientific and Technical Information (OSTI.GOV)

Huang, Lianjie; Chen, Ting; Tan, Sirui

Imaging fault zones and fractures is crucial for geothermal operators, providing important information for reservoir evaluation and management strategies. However, there are no existing techniques available for directly and clearly imaging fault zones, particularly for steeply dipping faults and fracture zones. In this project, we developed novel acoustic- and elastic-waveform inversion methods for high-resolution velocity model building. In addition, we developed acoustic and elastic reverse-time migration methods for high-resolution subsurface imaging of complex subsurface structures and steeply-dipping fault/fracture zones. We first evaluated and verified the improved capabilities of our newly developed seismic inversion and migration imaging methods using synthetic seismicmore » data. Our numerical tests verified that our new methods directly image subsurface fracture/fault zones using surface seismic reflection data. We then applied our novel seismic inversion and migration imaging methods to a field 3D surface seismic dataset acquired at the Soda Lake geothermal field using Vibroseis sources. Our migration images of the Soda Lake geothermal field obtained using our seismic inversion and migration imaging algorithms revealed several possible fault/fracture zones. AltaRock Energy, Inc. is working with Cyrq Energy, Inc. to refine the geologic interpretation at the Soda Lake geothermal field. Trenton Cladouhos, Senior Vice President R&D of AltaRock, was very interested in our imaging results of 3D surface seismic data from the Soda Lake geothermal field. He planed to perform detailed interpretation of our images in collaboration with James Faulds and Holly McLachlan of University of Nevada at Reno. Using our high-resolution seismic inversion and migration imaging results can help determine the optimal locations to drill wells for geothermal energy production and reduce the risk of geothermal exploration.« less

Huge Inverse Magnetization Generated by Faraday Induction in Nano-Sized Au@Ni Core@Shell Nanoparticles.

PubMed

Kuo, Chen-Chen; Li, Chi-Yen; Lee, Chi-Hung; Li, Hsiao-Chi; Li, Wen-Hsien

2015-08-25

We report on the design and observation of huge inverse magnetizations pointing in the direction opposite to the applied magnetic field, induced in nano-sized amorphous Ni shells deposited on crystalline Au nanoparticles by turning the applied magnetic field off. The magnitude of the induced inverse magnetization is very sensitive to the field reduction rate as well as to the thermal and field processes before turning the magnetic field off, and can be as high as 54% of the magnetization prior to cutting off the applied magnetic field. Memory effect of the induced inverse magnetization is clearly revealed in the relaxation measurements. The relaxation of the inverse magnetization can be described by an exponential decay profile, with a critical exponent that can be effectively tuned by the wait time right after reaching the designated temperature and before the applied magnetic field is turned off. The key to these effects is to have the induced eddy current running beneath the amorphous Ni shells through Faraday induction.

Integrating Electromagnetic Data with Other Geophysical Observations for Enhanced Imaging of the Earth: A Tutorial and Review

NASA Astrophysics Data System (ADS)

Moorkamp, Max

2017-09-01

In this review, I discuss the basic principles of joint inversion and constrained inversion approaches and show a few instructive examples of applications of these approaches in the literature. Starting with some basic definitions of the terms joint inversion and constrained inversion, I use a simple three-layered model as a tutorial example that demonstrates the general properties of joint inversion with different coupling methods. In particular, I investigate to which extent combining different geophysical methods can restrict the set of acceptable models and under which circumstances the results can be biased. Some ideas on how to identify such biased results and how negative results can be interpreted conclude the tutorial part. The case studies in the second part have been selected to highlight specific issues such as choosing an appropriate parameter relationship to couple seismic and electromagnetic data and demonstrate the most commonly used approaches, e.g., the cross-gradient constraint and direct parameter coupling. Throughout the discussion, I try to identify topics for future work. Overall, it appears that integrating electromagnetic data with other observations has reached a level of maturity and is starting to move away from fundamental proof-of-concept studies to answering questions about the structure of the subsurface. With a wide selection of coupling methods suited to different geological scenarios, integrated approaches can be applied on all scales and have the potential to deliver new answers to important geological questions.

Data-driven methods towards learning the highly nonlinear inverse kinematics of tendon-driven surgical manipulators.

PubMed

Xu, Wenjun; Chen, Jie; Lau, Henry Y K; Ren, Hongliang

2017-09-01

Accurate motion control of flexible surgical manipulators is crucial in tissue manipulation tasks. The tendon-driven serpentine manipulator (TSM) is one of the most widely adopted flexible mechanisms in minimally invasive surgery because of its enhanced maneuverability in torturous environments. TSM, however, exhibits high nonlinearities and conventional analytical kinematics model is insufficient to achieve high accuracy. To account for the system nonlinearities, we applied a data driven approach to encode the system inverse kinematics. Three regression methods: extreme learning machine (ELM), Gaussian mixture regression (GMR) and K-nearest neighbors regression (KNNR) were implemented to learn a nonlinear mapping from the robot 3D position states to the control inputs. The performance of the three algorithms was evaluated both in simulation and physical trajectory tracking experiments. KNNR performed the best in the tracking experiments, with the lowest RMSE of 2.1275 mm. The proposed inverse kinematics learning methods provide an alternative and efficient way to accurately model the tendon driven flexible manipulator. Copyright © 2016 John Wiley & Sons, Ltd.

Projected regression method for solving Fredholm integral equations arising in the analytic continuation problem of quantum physics

NASA Astrophysics Data System (ADS)

Arsenault, Louis-François; Neuberg, Richard; Hannah, Lauren A.; Millis, Andrew J.

2017-11-01

We present a supervised machine learning approach to the inversion of Fredholm integrals of the first kind as they arise, for example, in the analytic continuation problem of quantum many-body physics. The approach provides a natural regularization for the ill-conditioned inverse of the Fredholm kernel, as well as an efficient and stable treatment of constraints. The key observation is that the stability of the forward problem permits the construction of a large database of outputs for physically meaningful inputs. Applying machine learning to this database generates a regression function of controlled complexity, which returns approximate solutions for previously unseen inputs; the approximate solutions are then projected onto the subspace of functions satisfying relevant constraints. Under standard error metrics the method performs as well or better than the Maximum Entropy method for low input noise and is substantially more robust to increased input noise. We suggest that the methodology will be similarly effective for other problems involving a formally ill-conditioned inversion of an integral operator, provided that the forward problem can be efficiently solved.

A harmonic analysis approach to joint inversion of P-receiver functions and wave dispersion data in high dense seismic profiles

NASA Astrophysics Data System (ADS)

Molina-Aguilera, A.; Mancilla, F. D. L.; Julià, J.; Morales, J.

2017-12-01

Joint inversion techniques of P-receiver functions and wave dispersion data implicitly assume an isotropic radial stratified earth. The conventional approach invert stacked radial component receiver functions from different back-azimuths to obtain a laterally homogeneous single-velocity model. However, in the presence of strong lateral heterogeneities as anisotropic layers and/or dipping interfaces, receiver functions are considerably perturbed and both the radial and transverse components exhibit back azimuthal dependences. Harmonic analysis methods exploit these azimuthal periodicities to separate the effects due to the isotropic flat-layered structure from those effects caused by lateral heterogeneities. We implement a harmonic analysis method based on radial and transverse receiver functions components and carry out a synthetic study to illuminate the capabilities of the method in isolating the isotropic flat-layered part of receiver functions and constrain the geometry and strength of lateral heterogeneities. The independent of the baz P receiver function are jointly inverted with phase and group dispersion curves using a linearized inversion procedure. We apply this approach to high dense seismic profiles ( 2 km inter-station distance, see figure) located in the central Betics (western Mediterranean region), a region which has experienced complex geodynamic processes and exhibit strong variations in Moho topography. The technique presented here is robust and can be applied systematically to construct a 3-D model of the crust and uppermost mantle across large networks.

Bayesian inversion of marine CSEM data from the Scarborough gas field using a transdimensional 2-D parametrization

NASA Astrophysics Data System (ADS)

Ray, Anandaroop; Key, Kerry; Bodin, Thomas; Myer, David; Constable, Steven

2014-12-01

We apply a reversible-jump Markov chain Monte Carlo method to sample the Bayesian posterior model probability density function of 2-D seafloor resistivity as constrained by marine controlled source electromagnetic data. This density function of earth models conveys information on which parts of the model space are illuminated by the data. Whereas conventional gradient-based inversion approaches require subjective regularization choices to stabilize this highly non-linear and non-unique inverse problem and provide only a single solution with no model uncertainty information, the method we use entirely avoids model regularization. The result of our approach is an ensemble of models that can be visualized and queried to provide meaningful information about the sensitivity of the data to the subsurface, and the level of resolution of model parameters. We represent models in 2-D using a Voronoi cell parametrization. To make the 2-D problem practical, we use a source-receiver common midpoint approximation with 1-D forward modelling. Our algorithm is transdimensional and self-parametrizing where the number of resistivity cells within a 2-D depth section is variable, as are their positions and geometries. Two synthetic studies demonstrate the algorithm's use in the appraisal of a thin, segmented, resistive reservoir which makes for a challenging exploration target. As a demonstration example, we apply our method to survey data collected over the Scarborough gas field on the Northwest Australian shelf.

Adjoint-Based Sensitivity Kernels for Glacial Isostatic Adjustment in a Laterally Varying Earth

NASA Astrophysics Data System (ADS)

Crawford, O.; Al-Attar, D.; Tromp, J.; Mitrovica, J. X.; Austermann, J.; Lau, H. C. P.

2017-12-01

We consider a new approach to both the forward and inverse problems in glacial isostatic adjustment. We present a method for forward modelling GIA in compressible and laterally heterogeneous earth models with a variety of linear and non-linear rheologies. Instead of using the so-called sea level equation, which must be solved iteratively, the forward theory we present consists of a number of coupled evolution equations that can be straightforwardly numerically integrated. We also apply the adjoint method to the inverse problem in order to calculate the derivatives of measurements of GIA with respect to the viscosity structure of the Earth. Such derivatives quantify the sensitivity of the measurements to the model. The adjoint method enables efficient calculation of continuous and laterally varying derivatives, allowing us to calculate the sensitivity of measurements of glacial isostatic adjustment to the Earth's three-dimensional viscosity structure. The derivatives have a number of applications within the inverse method. Firstly, they can be used within a gradient-based optimisation method to find a model which minimises some data misfit function. The derivatives can also be used to quantify the uncertainty in such a model and hence to provide understanding of which parts of the model are well constrained. Finally, they enable construction of measurements which provide sensitivity to a particular part of the model space. We illustrate both the forward and inverse aspects with numerical examples in a spherically symmetric earth model.

Identifying Flow Networks in a Karstified Aquifer by Application of the Cellular Automata-Based Deterministic Inversion Method (Lez Aquifer, France)

NASA Astrophysics Data System (ADS)

Fischer, P.; Jardani, A.; Wang, X.; Jourde, H.; Lecoq, N.

2017-12-01

The distributed modeling of flow paths within karstic and fractured fields remains a complex task because of the high dependence of the hydraulic responses to the relative locations between observational boreholes and interconnected fractures and karstic conduits that control the main flow of the hydrosystem. The inverse problem in a distributed model is one alternative approach to interpret the hydraulic test data by mapping the karstic networks and fractured areas. In this work, we developed a Bayesian inversion approach, the Cellular Automata-based Deterministic Inversion (CADI) algorithm to infer the spatial distribution of hydraulic properties in a structurally constrained model. This method distributes hydraulic properties along linear structures (i.e., flow conduits) and iteratively modifies the structural geometry of this conduit network to progressively match the observed hydraulic data to the modeled ones. As a result, this method produces a conductivity model that is composed of a discrete conduit network embedded in the background matrix, capable of producing the same flow behavior as the investigated hydrologic system. The method is applied to invert a set of multiborehole hydraulic tests collected from a hydraulic tomography experiment conducted at the Terrieu field site in the Lez aquifer, Southern France. The emergent model shows a high consistency to field observation of hydraulic connections between boreholes. Furthermore, it provides a geologically realistic pattern of flow conduits. This method is therefore of considerable value toward an enhanced distributed modeling of the fractured and karstified aquifers.

PREFACE: First International Congress of the International Association of Inverse Problems (IPIA): Applied Inverse Problems 2007: Theoretical and Computational Aspects

NASA Astrophysics Data System (ADS)

Uhlmann, Gunther

2008-07-01

This volume represents the proceedings of the fourth Applied Inverse Problems (AIP) international conference and the first congress of the Inverse Problems International Association (IPIA) which was held in Vancouver, Canada, June 25 29, 2007. The organizing committee was formed by Uri Ascher, University of British Columbia, Richard Froese, University of British Columbia, Gary Margrave, University of Calgary, and Gunther Uhlmann, University of Washington, chair. The conference was part of the activities of the Pacific Institute of Mathematical Sciences (PIMS) Collaborative Research Group on inverse problems (http://www.pims.math.ca/scientific/collaborative-research-groups/past-crgs). This event was also supported by grants from NSF and MITACS. Inverse Problems (IP) are problems where causes for a desired or an observed effect are to be determined. They lie at the heart of scientific inquiry and technological development. The enormous increase in computing power and the development of powerful algorithms have made it possible to apply the techniques of IP to real-world problems of growing complexity. Applications include a number of medical as well as other imaging techniques, location of oil and mineral deposits in the earth's substructure, creation of astrophysical images from telescope data, finding cracks and interfaces within materials, shape optimization, model identification in growth processes and, more recently, modelling in the life sciences. The series of Applied Inverse Problems (AIP) Conferences aims to provide a primary international forum for academic and industrial researchers working on all aspects of inverse problems, such as mathematical modelling, functional analytic methods, computational approaches, numerical algorithms etc. The steering committee of the AIP conferences consists of Heinz Engl (Johannes Kepler Universität, Austria), Joyce McLaughlin (RPI, USA), William Rundell (Texas A&M, USA), Erkki Somersalo (Helsinki University of Technology, Finland), Masahiro Yamamoto (University of Tokyo, Japan), Gunther Uhlmann (University of Washington) and Jun Zou (Chinese University of Hong Kong). IPIA is a recently formed organization that intends to promote the field of inverse problem at all levels. See http://www.inverse-problems.net/. IPIA awarded the first Calderón prize at the opening of the conference to Matti Lassas (see first article in the Proceedings). There was also a general meeting of IPIA during the workshop. This was probably the largest conference ever on IP with 350 registered participants. The program consisted of 18 invited speakers and the Calderón Prize Lecture given by Matti Lassas. Another integral part of the program was the more than 60 mini-symposia that covered a broad spectrum of the theory and applications of inverse problems, focusing on recent developments in medical imaging, seismic exploration, remote sensing, industrial applications, numerical and regularization methods in inverse problems. Another important related topic was image processing in particular the advances which have allowed for significant enhancement of widely used imaging techniques. For more details on the program see the web page: http://www.pims.math.ca/science/2007/07aip. These proceedings reflect the broad spectrum of topics covered in AIP 2007. The conference and these proceedings would not have happened without the contributions of many people. I thank all my fellow organizers, the invited speakers, the speakers and organizers of mini-symposia for making this an exciting and vibrant event. I also thank PIMS, NSF and MITACS for their generous financial support. I take this opportunity to thank the PIMS staff, particularly Ken Leung, for making the local arrangements. Also thanks are due to Stephen McDowall for his help in preparing the schedule of the conference and Xiaosheng Li for the help in preparing these proceedings. I also would like to thank the contributors of this volume and the referees. Finally, many thanks are due to Graham Douglas and Elaine Longden-Chapman for suggesting publication in Journal of Physics: Conference Series.

Approximate solutions of acoustic 3D integral equation and their application to seismic modeling and full-waveform inversion

NASA Astrophysics Data System (ADS)

Malovichko, M.; Khokhlov, N.; Yavich, N.; Zhdanov, M.

2017-10-01

Over the recent decades, a number of fast approximate solutions of Lippmann-Schwinger equation, which are more accurate than classic Born and Rytov approximations, were proposed in the field of electromagnetic modeling. Those developments could be naturally extended to acoustic and elastic fields; however, until recently, they were almost unknown in seismology. This paper presents several solutions of this kind applied to acoustic modeling for both lossy and lossless media. We evaluated the numerical merits of those methods and provide an estimation of their numerical complexity. In our numerical realization we use the matrix-free implementation of the corresponding integral operator. We study the accuracy of those approximate solutions and demonstrate, that the quasi-analytical approximation is more accurate, than the Born approximation. Further, we apply the quasi-analytical approximation to the solution of the inverse problem. It is demonstrated that, this approach improves the estimation of the data gradient, comparing to the Born approximation. The developed inversion algorithm is based on the conjugate-gradient type optimization. Numerical model study demonstrates that the quasi-analytical solution significantly reduces computation time of the seismic full-waveform inversion. We also show how the quasi-analytical approximation can be extended to the case of elastic wavefield.

Teleseismic tomography for imaging Earth's upper mantle

NASA Astrophysics Data System (ADS)

Aktas, Kadircan

Teleseismic tomography is an important imaging tool in earthquake seismology, used to characterize lithospheric structure beneath a region of interest. In this study I investigate three different tomographic techniques applied to real and synthetic teleseismic data, with the aim of imaging the velocity structure of the upper mantle. First, by applying well established traveltime tomographic techniques to teleseismic data from southern Ontario, I obtained high-resolution images of the upper mantle beneath the lower Great Lakes. Two salient features of the 3D models are: (1) a patchy, NNW-trending low-velocity region, and (2) a linear, NE-striking high-velocity anomaly. I interpret the high-velocity anomaly as a possible relict slab associated with ca. 1.25 Ga subduction, whereas the low-velocity anomaly is interpreted as a zone of alteration and metasomatism associated with the ascent of magmas that produced the Late Cretaceous Monteregian plutons. The next part of the thesis is concerned with adaptation of existing full-waveform tomographic techniques for application to teleseismic body-wave observations. The method used here is intended to be complementary to traveltime tomography, and to take advantage of efficient frequency-domain methodologies that have been developed for inverting large controlled-source datasets. Existing full-waveform acoustic modelling and inversion codes have been modified to handle plane waves impinging from the base of the lithospheric model at a known incidence angle. A processing protocol has been developed to prepare teleseismic observations for the inversion algorithm. To assess the validity of the acoustic approximation, the processing procedure and modelling-inversion algorithm were tested using synthetic seismograms computed using an elastic Kirchhoff integral method. These tests were performed to evaluate the ability of the frequency-domain full-waveform inversion algorithm to recover topographic variations of the Moho under a variety of realistic scenarios. Results show that frequency-domain full-waveform tomography is generally successful in recovering both sharp and discontinuous features. Thirdly, I developed a new method for creating an initial background velocity model for the inversion algorithm, which is sufficiently close to the true model so that convergence is likely to be achieved. I adapted a method named Deformable Layer Tomography (DLT), which adjusts interfaces between layers rather than velocities within cells. I applied this method to a simple model comprising a single uniform crustal layer and a constant-velocity mantle, separated by an irregular Moho interface. A series of tests was performed to evaluate the sensitivity of the DLT algorithm; the results show that my algorithm produces useful results within a realistic range of incident-wave obliquity, incidence angle and signal-to-noise level. Keywords. Teleseismic tomography, full waveform tomography, deformable layer tomography, lower Great Lakes, crust and upper mantle.

Error decomposition and estimation of inherent optical properties.

PubMed

Salama, Mhd Suhyb; Stein, Alfred

2009-09-10

We describe a methodology to quantify and separate the errors of inherent optical properties (IOPs) derived from ocean-color model inversion. Their total error is decomposed into three different sources, namely, model approximations and inversion, sensor noise, and atmospheric correction. Prior information on plausible ranges of observation, sensor noise, and inversion goodness-of-fit are employed to derive the posterior probability distribution of the IOPs. The relative contribution of each error component to the total error budget of the IOPs, all being of stochastic nature, is then quantified. The method is validated with the International Ocean Colour Coordinating Group (IOCCG) data set and the NASA bio-Optical Marine Algorithm Data set (NOMAD). The derived errors are close to the known values with correlation coefficients of 60-90% and 67-90% for IOCCG and NOMAD data sets, respectively. Model-induced errors inherent to the derived IOPs are between 10% and 57% of the total error, whereas atmospheric-induced errors are in general above 43% and up to 90% for both data sets. The proposed method is applied to synthesized and in situ measured populations of IOPs. The mean relative errors of the derived values are between 2% and 20%. A specific error table to the Medium Resolution Imaging Spectrometer (MERIS) sensor is constructed. It serves as a benchmark to evaluate the performance of the atmospheric correction method and to compute atmospheric-induced errors. Our method has a better performance and is more appropriate to estimate actual errors of ocean-color derived products than the previously suggested methods. Moreover, it is generic and can be applied to quantify the error of any derived biogeophysical parameter regardless of the used derivation.

Neural network modeling and prediction of resistivity structures using VES Schlumberger data over a geothermal area

NASA Astrophysics Data System (ADS)

Singh, Upendra K.; Tiwari, R. K.; Singh, S. B.

2013-03-01

This paper presents the effects of several parameters on the artificial neural networks (ANN) inversion of vertical electrical sounding (VES) data. Sensitivity of ANN parameters was examined on the performance of adaptive backpropagation (ABP) and Levenberg-Marquardt algorithms (LMA) to test the robustness to noisy synthetic as well as field geophysical data and resolving capability of these methods for predicting the subsurface resistivity layers. We trained, tested and validated ANN using the synthetic VES data as input to the networks and layer parameters of the models as network output. ANN learning parameters are varied and corresponding observations are recorded. The sensitivity analysis of synthetic data and real model demonstrate that ANN algorithms applied in VES data inversion should be considered well not only in terms of accuracy but also in terms of high computational efforts. Also the analysis suggests that ANN model with its various controlling parameters are largely data dependent and hence no unique architecture can be designed for VES data analysis. ANN based methods are also applied to the actual VES field data obtained from the tectonically vital geothermal areas of Jammu and Kashmir, India. Analysis suggests that both the ABP and LMA are suitable methods for 1-D VES modeling. But the LMA method provides greater degree of robustness than the ABP in case of 2-D VES modeling. Comparison of the inversion results with known lithology correlates well and also reveals the additional significant feature of reconsolidated breccia of about 7.0 m thickness beneath the overburden in some cases like at sounding point RDC-5. We may therefore conclude that ANN based methods are significantly faster and efficient for detection of complex layered resistivity structures with a relatively greater degree of precision and resolution.

An efficient implementation of a high-order filter for a cubed-sphere spectral element model

NASA Astrophysics Data System (ADS)

Kang, Hyun-Gyu; Cheong, Hyeong-Bin

2017-03-01

A parallel-scalable, isotropic, scale-selective spatial filter was developed for the cubed-sphere spectral element model on the sphere. The filter equation is a high-order elliptic (Helmholtz) equation based on the spherical Laplacian operator, which is transformed into cubed-sphere local coordinates. The Laplacian operator is discretized on the computational domain, i.e., on each cell, by the spectral element method with Gauss-Lobatto Lagrange interpolating polynomials (GLLIPs) as the orthogonal basis functions. On the global domain, the discrete filter equation yielded a linear system represented by a highly sparse matrix. The density of this matrix increases quadratically (linearly) with the order of GLLIP (order of the filter), and the linear system is solved in only O (Ng) operations, where Ng is the total number of grid points. The solution, obtained by a row reduction method, demonstrated the typical accuracy and convergence rate of the cubed-sphere spectral element method. To achieve computational efficiency on parallel computers, the linear system was treated by an inverse matrix method (a sparse matrix-vector multiplication). The density of the inverse matrix was lowered to only a few times of the original sparse matrix without degrading the accuracy of the solution. For better computational efficiency, a local-domain high-order filter was introduced: The filter equation is applied to multiple cells, and then the central cell was only used to reconstruct the filtered field. The parallel efficiency of applying the inverse matrix method to the global- and local-domain filter was evaluated by the scalability on a distributed-memory parallel computer. The scale-selective performance of the filter was demonstrated on Earth topography. The usefulness of the filter as a hyper-viscosity for the vorticity equation was also demonstrated.

Partial F-tests with multiply imputed data in the linear regression framework via coefficient of determination.

PubMed

Chaurasia, Ashok; Harel, Ofer

2015-02-10

Tests for regression coefficients such as global, local, and partial F-tests are common in applied research. In the framework of multiple imputation, there are several papers addressing tests for regression coefficients. However, for simultaneous hypothesis testing, the existing methods are computationally intensive because they involve calculation with vectors and (inversion of) matrices. In this paper, we propose a simple method based on the scalar entity, coefficient of determination, to perform (global, local, and partial) F-tests with multiply imputed data. The proposed method is evaluated using simulated data and applied to suicide prevention data. Copyright © 2014 John Wiley & Sons, Ltd.

Correcting Classifiers for Sample Selection Bias in Two-Phase Case-Control Studies

PubMed Central

Theis, Fabian J.

2017-01-01

Epidemiological studies often utilize stratified data in which rare outcomes or exposures are artificially enriched. This design can increase precision in association tests but distorts predictions when applying classifiers on nonstratified data. Several methods correct for this so-called sample selection bias, but their performance remains unclear especially for machine learning classifiers. With an emphasis on two-phase case-control studies, we aim to assess which corrections to perform in which setting and to obtain methods suitable for machine learning techniques, especially the random forest. We propose two new resampling-based methods to resemble the original data and covariance structure: stochastic inverse-probability oversampling and parametric inverse-probability bagging. We compare all techniques for the random forest and other classifiers, both theoretically and on simulated and real data. Empirical results show that the random forest profits from only the parametric inverse-probability bagging proposed by us. For other classifiers, correction is mostly advantageous, and methods perform uniformly. We discuss consequences of inappropriate distribution assumptions and reason for different behaviors between the random forest and other classifiers. In conclusion, we provide guidance for choosing correction methods when training classifiers on biased samples. For random forests, our method outperforms state-of-the-art procedures if distribution assumptions are roughly fulfilled. We provide our implementation in the R package sambia. PMID:29312464

Imaging the Earth's anisotropic structure with Bayesian Inversion of fundamental and higher mode surface-wave dispersion data

NASA Astrophysics Data System (ADS)

Ravenna, Matteo; Lebedev, Sergei; Celli, Nicolas

2017-04-01

We develop a Markov Chain Monte Carlo inversion of fundamental and higher mode phase-velocity curves for radially and azimuthally anisotropic structure of the crust and upper mantle. In the inversions of Rayleigh- and Love-wave dispersion curves for radially anisotropic structure, we obtain probabilistic 1D radially anisotropic shear-velocity profiles of the isotropic average Vs and anisotropy (or Vsv and Vsh) as functions of depth. In the inversions for azimuthal anisotropy, Rayleigh-wave dispersion curves at different azimuths are inverted for the vertically polarized shear-velocity structure (Vsv) and the 2-phi component of azimuthal anisotropy. The strength and originality of the method is in its fully non-linear approach. Each model realization is computed using exact forward calculations. The uncertainty of the models is a part of the output. In the inversions for azimuthal anisotropy, in particular, the computation of the forward problem is performed separately at different azimuths, with no linear approximations on the relation of the Earth's elastic parameters to surface wave phase velocities. The computations are performed in parallel in order reduce the computing time. We compare inversions of the fundamental mode phase-velocity curves alone with inversions that also include overtones. The addition of higher modes enhances the resolving power of the anisotropic structure of the deep upper mantle. We apply the inversion method to phase-velocity curves in a few regions, including the Hangai dome region in Mongolia. Our models provide constraints on the Moho depth, the Lithosphere-Asthenosphere Boundary, and the alignment of the anisotropic fabric and the direction of current and past flow, from the crust down to the deep asthenosphere.

Time-lapse ERT interpretation methodology for leachate injection monitoring based on multiple inversions and a clustering strategy (MICS)

NASA Astrophysics Data System (ADS)

Audebert, M.; Clément, R.; Touze-Foltz, N.; Günther, T.; Moreau, S.; Duquennoi, C.

2014-12-01

Leachate recirculation is a key process in municipal waste landfills functioning as bioreactors. To quantify the water content and to assess the leachate injection system, in-situ methods are required to obtain spatially distributed information, usually electrical resistivity tomography (ERT). This geophysical method is based on the inversion process, which presents two major problems in terms of delimiting the infiltration area. First, it is difficult for ERT users to choose an appropriate inversion parameter set. Indeed, it might not be sufficient to interpret only the optimum model (i.e. the model with the chosen regularisation strength) because it is not necessarily the model which best represents the physical process studied. Second, it is difficult to delineate the infiltration front based on resistivity models because of the smoothness of the inversion results. This paper proposes a new methodology called MICS (multiple inversions and clustering strategy), which allows ERT users to improve the delimitation of the infiltration area in leachate injection monitoring. The MICS methodology is based on (i) a multiple inversion step by varying the inversion parameter values to take a wide range of resistivity models into account and (ii) a clustering strategy to improve the delineation of the infiltration front. In this paper, MICS was assessed on two types of data. First, a numerical assessment allows us to optimise and test MICS for different infiltration area sizes, contrasts and shapes. Second, MICS was applied to a field data set gathered during leachate recirculation on a bioreactor.

Fetal head detection and measurement in ultrasound images by a direct inverse randomized Hough transform

NASA Astrophysics Data System (ADS)

Lu, Wei; Tan, Jinglu; Floyd, Randall C.

2005-04-01

Object detection in ultrasound fetal images is a challenging task for the relatively low resolution and low signal-to-noise ratio. A direct inverse randomized Hough transform (DIRHT) is developed for filtering and detecting incomplete curves in images with strong noise. The DIRHT combines the advantages of both the inverse and the randomized Hough transforms. In the reverse image, curves are highlighted while a large number of unrelated pixels are removed, demonstrating a "curve-pass filtering" effect. Curves are detected by iteratively applying the DIRHT to the filtered image. The DIRHT was applied to head detection and measurement of the biparietal diameter (BPD) and head circumference (HC). No user input or geometric properties of the head were required for the detection. The detection and measurement took 2 seconds for each image on a PC. The inter-run variations and the differences between the automatic measurements and sonographers" manual measurements were small compared with published inter-observer variations. The results demonstrated that the automatic measurements were consistent and accurate. This method provides a valuable tool for fetal examinations.

Solution of Inverse Kinematics for 6R Robot Manipulators With Offset Wrist Based on Geometric Algebra.

PubMed

Fu, Zhongtao; Yang, Wenyu; Yang, Zhen

2013-08-01

In this paper, we present an efficient method based on geometric algebra for computing the solutions to the inverse kinematics problem (IKP) of the 6R robot manipulators with offset wrist. Due to the fact that there exist some difficulties to solve the inverse kinematics problem when the kinematics equations are complex, highly nonlinear, coupled and multiple solutions in terms of these robot manipulators stated mathematically, we apply the theory of Geometric Algebra to the kinematic modeling of 6R robot manipulators simply and generate closed-form kinematics equations, reformulate the problem as a generalized eigenvalue problem with symbolic elimination technique, and then yield 16 solutions. Finally, a spray painting robot, which conforms to the type of robot manipulators, is used as an example of implementation for the effectiveness and real-time of this method. The experimental results show that this method has a large advantage over the classical methods on geometric intuition, computation and real-time, and can be directly extended to all serial robot manipulators and completely automatized, which provides a new tool on the analysis and application of general robot manipulators.

Using Landslide Failure Forecast Models in Near Real Time: the Mt. de La Saxe case-study

NASA Astrophysics Data System (ADS)

Manconi, Andrea; Giordan, Daniele

2014-05-01

Forecasting the occurrence of landslide phenomena in space and time is a major scientific challenge. The approaches used to forecast landslides mainly depend on the spatial scale analyzed (regional vs. local), the temporal range of forecast (long- vs. short-term), as well as the triggering factor and the landslide typology considered. By focusing on short-term forecast methods for large, deep seated slope instabilities, the potential time of failure (ToF) can be estimated by studying the evolution of the landslide deformation over time (i.e., strain rate) provided that, under constant stress conditions, landslide materials follow creep mechanism before reaching rupture. In the last decades, different procedures have been proposed to estimate ToF by considering simplified empirical and/or graphical methods applied to time series of deformation data. Fukuzono, 1985 proposed a failure forecast method based on the experience performed during large scale laboratory experiments, which were aimed at observing the kinematic evolution of a landslide induced by rain. This approach, known also as the inverse-velocity method, considers the evolution over time of the inverse value of the surface velocity (v) as an indicator of the ToF, by assuming that failure approaches while 1/v tends to zero. Here we present an innovative method to aimed at achieving failure forecast of landslide phenomena by considering near-real-time monitoring data. Starting from the inverse velocity theory, we analyze landslide surface displacements on different temporal windows, and then apply straightforward statistical methods to obtain confidence intervals on the time of failure. Our results can be relevant to support the management of early warning systems during landslide emergency conditions, also when the predefined displacement and/or velocity thresholds are exceeded. In addition, our statistical approach for the definition of confidence interval and forecast reliability can be applied also to different failure forecast methods. We applied for the first time the herein presented approach in near real time during the emergency scenario relevant to the reactivation of the La Saxe rockslide, a large mass wasting menacing the population of Courmayeur, northern Italy, and the important European route E25. We show how the application of simplified but robust forecast models can be a convenient method to manage and support early warning systems during critical situations. References: Fukuzono T. (1985), A New Method for Predicting the Failure Time of a Slope, Proc. IVth International Conference and Field Workshop on Landslides, Tokyo.

Evaluation of Süleymanköy (Diyarbakir, Eastern Turkey) and Seferihisar (Izmir, Western Turkey) Self Potential Anomalies with Multilayer Perceptron Neural Networks

NASA Astrophysics Data System (ADS)

Kaftan, Ilknur; Sindirgi, Petek

2013-04-01

Self-potential (SP) is one of the oldest geophysical methods that provides important information about near-surface structures. Several methods have been developed to interpret SP data using simple geometries. This study investigated inverse solution of a buried, polarized sphere-shaped self-potential (SP ) anomaly via Multilayer Perceptron Neural Networks ( MLPNN ). The polarization angle ( α ) and depth to the centre of sphere ( h )were estimated. The MLPNN is applied to synthetic and field SP data. In order to see the capability of the method in detecting the number of sources, MLPNN was applied to different spherical models at different depths and locations.. Additionally, the performance of MLPNN was tested by adding random noise to the same synthetic test data. The sphere model successfully obtained similar parameters under different S/N ratios. Then, MLPNN method was applied to two field examples. The first one is the cross section taken from the SP anomaly map of the Ergani-Süleymanköy (Turkey) copper mine. MLPNN was also applied to SP data from Seferihisar Izmir (Western Turkey) geothermal field. The MLPNN results showed good agreement with the original synthetic data set. The effect of The technique gave satisfactory results following the addition of 5% and 10% Gaussian noise levels. The MLPNN results were compared to other SP interpretation techniques, such as Normalized Full Gradient (NFG), inverse solution and nomogram methods. All of the techniques showed strong similarity. Consequently, the synthetic and field applications of this study show that MLPNN provides reliable evaluation of the self potential data modelled by the sphere model.

An inverse method to estimate the flow through a levee breach

NASA Astrophysics Data System (ADS)

D'Oria, Marco; Mignosa, Paolo; Tanda, Maria Giovanna

2015-08-01

We propose a procedure to estimate the flow through a levee breach based on water levels recorded in river stations downstream and/or upstream of the failure site. The inverse problem is solved using a Bayesian approach and requires the execution of several forward unsteady flow simulations. For this purpose, we have used the well-known 1-D HEC-RAS model, but any unsteady flow model could be adopted in the same way. The procedure has been tested using four synthetic examples. Levee breaches with different characteristics (free flow, flow with tailwater effects, etc.) have been simulated to collect the synthetic level data used at a later stage in the inverse procedure. The method was able to accurately reproduce the flow through the breach in all cases. The practicability of the procedure was then confirmed applying it to the inundation of the Polesine Region (Northern Italy) which occurred in 1951 and was caused by three contiguous and almost simultaneous breaches on the left embankment of the Po River.

Joint inversion of time-lapse VSP data for monitoring CO2 injection at the Farnsworth EOR field in Texas

NASA Astrophysics Data System (ADS)

Zhang, M.; Gao, K.; Balch, R. S.; Huang, L.

2016-12-01

During the Development Phase (Phase III) of the U.S. Southwest Regional Partnership on Carbon Sequestration (SWP), time-lapse 3D vertical seismic profiling (VSP) data were acquired to monitor CO2 injection/migration at the Farnsworth Enhanced Oil Recovery (EOR) field, in partnership with the industrial partner Chaparral Energy. The project is to inject a million tons of carbon dioxide into the target formation, the deep oil-bearing Morrow Formation in the Farnsworth Unit EOR field. Quantitative time-lapse seismic monitoring has the potential to track CO2 movement in geologic carbon storage sites. Los Alamos National Laboratory (LANL) has recently developed new full-waveform inversion methods to jointly invert time-lapse seismic data for changes in elastic and anisotropic parameters in target monitoring regions such as a CO2 reservoir. We apply our new joint inversion methods to time-lapse VSP data acquired at the Farnsworth EOR filed, and present some preliminary results showing geophysical properties changes in the reservoir.

Localization of incipient tip vortex cavitation using ray based matched field inversion method

NASA Astrophysics Data System (ADS)

Kim, Dongho; Seong, Woojae; Choo, Youngmin; Lee, Jeunghoon

2015-10-01

Cavitation of marine propeller is one of the main contributing factors of broadband radiated ship noise. In this research, an algorithm for the source localization of incipient vortex cavitation is suggested. Incipient cavitation is modeled as monopole type source and matched-field inversion method is applied to find the source position by comparing the spatial correlation between measured and replicated pressure fields at the receiver array. The accuracy of source localization is improved by broadband matched-field inversion technique that enhances correlation by incoherently averaging correlations of individual frequencies. Suggested localization algorithm is verified through known virtual source and model test conducted in Samsung ship model basin cavitation tunnel. It is found that suggested localization algorithm enables efficient localization of incipient tip vortex cavitation using a few pressure data measured on the outer hull above the propeller and practically applicable to the typically performed model scale experiment in a cavitation tunnel at the early design stage.

INFO-RNA--a fast approach to inverse RNA folding.

PubMed

Busch, Anke; Backofen, Rolf

2006-08-01

The structure of RNA molecules is often crucial for their function. Therefore, secondary structure prediction has gained much interest. Here, we consider the inverse RNA folding problem, which means designing RNA sequences that fold into a given structure. We introduce a new algorithm for the inverse folding problem (INFO-RNA) that consists of two parts; a dynamic programming method for good initial sequences and a following improved stochastic local search that uses an effective neighbor selection method. During the initialization, we design a sequence that among all sequences adopts the given structure with the lowest possible energy. For the selection of neighbors during the search, we use a kind of look-ahead of one selection step applying an additional energy-based criterion. Afterwards, the pre-ordered neighbors are tested using the actual optimization criterion of minimizing the structure distance between the target structure and the mfe structure of the considered neighbor. We compared our algorithm to RNAinverse and RNA-SSD for artificial and biological test sets. Using INFO-RNA, we performed better than RNAinverse and in most cases, we gained better results than RNA-SSD, the probably best inverse RNA folding tool on the market. www.bioinf.uni-freiburg.de?Subpages/software.html.

Joint Inversion of Gravity and Gravity Tensor Data Using the Structural Index as Weighting Function Rate Decay

NASA Astrophysics Data System (ADS)

Ialongo, S.; Cella, F.; Fedi, M.; Florio, G.

2011-12-01

Most geophysical inversion problems are characterized by a number of data considerably higher than the number of the unknown parameters. This corresponds to solve highly underdetermined systems. To get a unique solution, a priori information must be therefore introduced. We here analyze the inversion of the gravity gradient tensor (GGT). Previous approaches to invert jointly or independently more gradient components are by Li (2001) proposing an algorithm using a depth weighting function and Zhdanov et alii (2004), providing a well focused inversion of gradient data. Both the methods give a much-improved solution compared with the minimum length solution, which is invariably shallow and not representative of the true source distribution. For very undetermined problems, this feature is due to the role of the depth weighting matrices used by both the methods. Recently, Cella and Fedi (2011) showed however that for magnetic and gravity data the depth weighting function has to be defined carefully, under a preliminary application of Euler Deconvolution or Depth from Extreme Point methods, yielding the appropriate structural index and then using it as the rate decay of the weighting function. We therefore propose to extend this last approach to invert jointly or independently the GGT tensor using the structural index as weighting function rate decay. In case of a joint inversion, gravity data can be added as well. This multicomponent case is also relevant because the simultaneous use of several components and gravity increase the number of data and reduce the algebraic ambiguity compared to the inversion of a single component. The reduction of such ambiguity was shown in Fedi et al, (2005) decisive to get an improved depth resolution in inverse problems, independently from any form of depth weighting function. The method is demonstrated to synthetic cases and applied to real cases, such as the Vredefort impact area (South Africa), characterized by a complex density distribution, well defining a central uplift area, ring structures and low density sediments. REFERENCES Cella F., and Fedi M., 2011, Inversion of potential field data using the structural index as weighting function rate decay, Geophysical Prospecting, doi: 10.1111/j.1365-2478.2011.00974.x Fedi M., Hansen P. C., and Paoletti V., 2005 Analysis of depth resolution in potential-field inversion. Geophysics, 70, NO. 6 Li, Y., 2001, 3-D inversion of gravity gradiometry data: 71st Annual Meeting, SEG, Expanded Abstracts, 1470-1473. Zhdanov, M. S., Ellis, R. G., and Mukherjee, S., 2004, Regularized focusing inversion of 3-D gravity tensor data: Geophysics, 69, 925-937.

Earthquake source tensor inversion with the gCAP method and 3D Green's functions

NASA Astrophysics Data System (ADS)

Zheng, J.; Ben-Zion, Y.; Zhu, L.; Ross, Z.

2013-12-01

We develop and apply a method to invert earthquake seismograms for source properties using a general tensor representation and 3D Green's functions. The method employs (i) a general representation of earthquake potency/moment tensors with double couple (DC), compensated linear vector dipole (CLVD), and isotropic (ISO) components, and (ii) a corresponding generalized CAP (gCap) scheme where the continuous wave trains are broken into Pnl and surface waves (Zhu & Ben-Zion, 2013). For comparison, we also use the waveform inversion method of Zheng & Chen (2012) and Ammon et al. (1998). Sets of 3D Green's functions are calculated on a grid of 1 km3 using the 3-D community velocity model CVM-4 (Kohler et al. 2003). A bootstrap technique is adopted to establish robustness of the inversion results using the gCap method (Ross & Ben-Zion, 2013). Synthetic tests with 1-D and 3-D waveform calculations show that the source tensor inversion procedure is reasonably reliable and robust. As initial application, the method is used to investigate source properties of the March 11, 2013, Mw=4.7 earthquake on the San Jacinto fault using recordings of ~45 stations up to ~0.2Hz. Both the best fitting and most probable solutions include ISO component of ~1% and CLVD component of ~0%. The obtained ISO component, while small, is found to be a non-negligible positive value that can have significant implications for the physics of the failure process. Work on using higher frequency data for this and other earthquakes is in progress.

Determination of the Geometric Form of a Plane of a Tectonic Gap as the Inverse III-posed Problem of Mathematical Physics

NASA Astrophysics Data System (ADS)

Sirota, Dmitry; Ivanov, Vadim

2017-11-01

Any mining operations influence stability of natural and technogenic massifs are the reason of emergence of the sources of differences of mechanical tension. These sources generate a quasistationary electric field with a Newtonian potential. The paper reviews the method of determining the shape and size of a flat source field with this kind of potential. This common problem meets in many fields of mining: geological exploration mineral resources, ore deposits, control of mining by underground method, determining coal self-heating source, localization of the rock crack's sources and other applied problems of practical physics. This problems are ill-posed and inverse and solved by converting to Fredholm-Uryson integral equation of the first kind. This equation will be solved by A.N. Tikhonov regularization method.

Electromagnetic holographic sensitivity field of two-phase flow in horizontal wells

NASA Astrophysics Data System (ADS)

Zhang, Kuo; Wu, Xi-Ling; Yan, Jing-Fu; Cai, Jia-Tie

2017-03-01

Electromagnetic holographic data are characterized by two modes, suggesting that image reconstruction requires a dual-mode sensitivity field as well. We analyze an electromagnetic holographic field based on tomography theory and Radon inverse transform to derive the expression of the electromagnetic holographic sensitivity field (EMHSF). Then, we apply the EMHSF calculated by using finite-element methods to flow simulations and holographic imaging. The results suggest that the EMHSF based on the partial derivative of radius of the complex electric potential φ is closely linked to the Radon inverse transform and encompasses the sensitivities of the amplitude and phase data. The flow images obtained with inversion using EMHSF better agree with the actual flow patterns. The EMHSF overcomes the limitations of traditional single-mode sensitivity fields.

Determination of hot carrier energy distributions from inversion of ultrafast pump-probe reflectivity measurements.

PubMed

Heilpern, Tal; Manjare, Manoj; Govorov, Alexander O; Wiederrecht, Gary P; Gray, Stephen K; Harutyunyan, Hayk

2018-05-10

Developing a fundamental understanding of ultrafast non-thermal processes in metallic nanosystems will lead to applications in photodetection, photochemistry and photonic circuitry. Typically, non-thermal and thermal carrier populations in plasmonic systems are inferred either by making assumptions about the functional form of the initial energy distribution or using indirect sensors like localized plasmon frequency shifts. Here we directly determine non-thermal and thermal distributions and dynamics in thin films by applying a double inversion procedure to optical pump-probe data that relates the reflectivity changes around Fermi energy to the changes in the dielectric function and in the single-electron energy band occupancies. When applied to normal incidence measurements our method uncovers the ultrafast excitation of a non-Fermi-Dirac distribution and its subsequent thermalization dynamics. Furthermore, when applied to the Kretschmann configuration, we show that the excitation of propagating plasmons leads to a broader energy distribution of electrons due to the enhanced Landau damping.

A systematic linear space approach to solving partially described inverse eigenvalue problems

NASA Astrophysics Data System (ADS)

Hu, Sau-Lon James; Li, Haujun

2008-06-01

Most applications of the inverse eigenvalue problem (IEP), which concerns the reconstruction of a matrix from prescribed spectral data, are associated with special classes of structured matrices. Solving the IEP requires one to satisfy both the spectral constraint and the structural constraint. If the spectral constraint consists of only one or few prescribed eigenpairs, this kind of inverse problem has been referred to as the partially described inverse eigenvalue problem (PDIEP). This paper develops an efficient, general and systematic approach to solve the PDIEP. Basically, the approach, applicable to various structured matrices, converts the PDIEP into an ordinary inverse problem that is formulated as a set of simultaneous linear equations. While solving simultaneous linear equations for model parameters, the singular value decomposition method is applied. Because of the conversion to an ordinary inverse problem, other constraints associated with the model parameters can be easily incorporated into the solution procedure. The detailed derivation and numerical examples to implement the newly developed approach to symmetric Toeplitz and quadratic pencil (including mass, damping and stiffness matrices of a linear dynamic system) PDIEPs are presented. Excellent numerical results for both kinds of problem are achieved under the situations that have either unique or infinitely many solutions.

Automated rapid finite fault inversion for megathrust earthquakes: Application to the Maule (2010), Iquique (2014) and Illapel (2015) great earthquakes

NASA Astrophysics Data System (ADS)

Benavente, Roberto; Cummins, Phil; Dettmer, Jan

2016-04-01

Rapid estimation of the spatial and temporal rupture characteristics of large megathrust earthquakes by finite fault inversion is important for disaster mitigation. For example, estimates of the spatio-temporal evolution of rupture can be used to evaluate population exposure to tsunami waves and ground shaking soon after the event by providing more accurate predictions than possible with point source approximations. In addition, rapid inversion results can reveal seismic source complexity to guide additional, more detailed subsequent studies. This work develops a method to rapidly estimate the slip distribution of megathrust events while reducing subjective parameter choices by automation. The method is simple yet robust and we show that it provides excellent preliminary rupture models as soon as 30 minutes for three great earthquakes in the South-American subduction zone. This may slightly change for other regions depending on seismic station coverage but method can be applied to any subduction region. The inversion is based on W-phase data since it is rapidly and widely available and of low amplitude which avoids clipping at close stations for large events. In addition, prior knowledge of the slab geometry (e.g. SLAB 1.0) is applied and rapid W-phase point source information (time delay and centroid location) is used to constrain the fault geometry and extent. Since the linearization by multiple time window (MTW) parametrization requires regularization, objective smoothing is achieved by the discrepancy principle in two fully automated steps. First, the residuals are estimated assuming unknown noise levels, and second, seeking a subsequent solution which fits the data to noise level. The MTW scheme is applied with positivity constraints and a solution is obtained by an efficient non-negative least squares solver. Systematic application of the algorithm to the Maule (2010), Iquique (2014) and Illapel (2015) events illustrates that rapid finite fault inversion with teleseismic data is feasible and provides meaningful results. The results for the three events show excellent data fits and are consistent with other solutions showing most of the slip occurring close to the trench for the Maule an Illapel events and some deeper slip for the Iquique event. Importantly, the Illapel source model predicts tsunami waveforms of close agreement with observed waveforms. Finally, we develop a new Bayesian approach to approximate uncertainties as part of the rapid inversion scheme with positivity constraints. Uncertainties are estimated by approximating the posterior distribution as a multivariate log-normal distribution. While solving for the posterior adds some additional computational cost, we illustrate that uncertainty estimation is important for meaningful interpretation of finite fault models.

Visco-elastic controlled-source full waveform inversion without surface waves

NASA Astrophysics Data System (ADS)

Paschke, Marco; Krause, Martin; Bleibinhaus, Florian

2016-04-01

We developed a frequency-domain visco-elastic full waveform inversion for onshore seismic experiments with topography. The forward modeling is based on a finite-difference time-domain algorithm by Robertsson that uses the image-method to ensure a stress-free condition at the surface. The time-domain data is Fourier-transformed at every point in the model space during the forward modeling for a given set of frequencies. The motivation for this approach is the reduced amount of memory when computing kernels, and the straightforward implementation of the multiscale approach. For the inversion, we calculate the Frechet derivative matrix explicitly, and we implement a Levenberg-Marquardt scheme that allows for computing the resolution matrix. To reduce the size of the Frechet derivative matrix, and to stabilize the inversion, an adapted inverse mesh is used. The node spacing is controlled by the velocity distribution and the chosen frequencies. To focus the inversion on body waves (P, P-coda, and S) we mute the surface waves from the data. Consistent spatiotemporal weighting factors are applied to the wavefields during the Fourier transform to obtain the corresponding kernels. We test our code with a synthetic study using the Marmousi model with arbitrary topography. This study also demonstrates the importance of topography and muting surface waves in controlled-source full waveform inversion.

Application of 2-D travel-time inversion of seismic refraction data to the mid-continent rift beneath Lake Superior

USGS Publications Warehouse

Lutter, William J.; Tréhu, Anne M.; Nowack, Robert L.

1993-01-01

The inversion technique of Nowack and Lutter (1988a) and Lutter et al. (1990) has been applied to first arrival seismic refraction data collected along Line A of the 1986 Lake Superior GLIMPCE experiment, permitting comparison of the inversion image with an independently derived forward model (Trehu et al., 1991; Shay and Trehu, in press). For this study, the inversion method was expanded to allow variable grid spacing for the bicubic spline parameterization of velocity. The variable grid spacing improved model delineation and data fit by permitting model parameters to be clustered at features of interest. Over 800 first-arrival travel-times were fit with a final RMS error of 0.045 s. The inversion model images a low velocity central graben and smaller flanking half-grabens of the Midcontinent Rift, and higher velocity regions (+0.5 to +0.75 km/s) associated with the Isle Royale and Keweenaw faults, which bound the central graben. Although the forward modeling interpretation gives finer details associated with the near surface expression of the two faults because of the inclusion of secondary reflections and refractions that were not included in the inversion, the inversion model reproduces the primary features of the forward model.

Method of imaging the electrical conductivity distribution of a subsurface

DOEpatents

Johnson, Timothy C.

2017-09-26

A method of imaging electrical conductivity distribution of a subsurface containing metallic structures with known locations and dimensions is disclosed. Current is injected into the subsurface to measure electrical potentials using multiple sets of electrodes, thus generating electrical resistivity tomography measurements. A numeric code is applied to simulate the measured potentials in the presence of the metallic structures. An inversion code is applied that utilizes the electrical resistivity tomography measurements and the simulated measured potentials to image the subsurface electrical conductivity distribution and remove effects of the subsurface metallic structures with known locations and dimensions.

Prediction-Correction Algorithms for Time-Varying Constrained Optimization

DOE PAGES

Simonetto, Andrea; Dall'Anese, Emiliano

2017-07-26

This article develops online algorithms to track solutions of time-varying constrained optimization problems. Particularly, resembling workhorse Kalman filtering-based approaches for dynamical systems, the proposed methods involve prediction-correction steps to provably track the trajectory of the optimal solutions of time-varying convex problems. The merits of existing prediction-correction methods have been shown for unconstrained problems and for setups where computing the inverse of the Hessian of the cost function is computationally affordable. This paper addresses the limitations of existing methods by tackling constrained problems and by designing first-order prediction steps that rely on the Hessian of the cost function (and do notmore » require the computation of its inverse). In addition, the proposed methods are shown to improve the convergence speed of existing prediction-correction methods when applied to unconstrained problems. Numerical simulations corroborate the analytical results and showcase performance and benefits of the proposed algorithms. A realistic application of the proposed method to real-time control of energy resources is presented.« less

DOE Office of Scientific and Technical Information (OSTI.GOV)

Simonetto, Andrea; Dall'Anese, Emiliano

This article develops online algorithms to track solutions of time-varying constrained optimization problems. Particularly, resembling workhorse Kalman filtering-based approaches for dynamical systems, the proposed methods involve prediction-correction steps to provably track the trajectory of the optimal solutions of time-varying convex problems. The merits of existing prediction-correction methods have been shown for unconstrained problems and for setups where computing the inverse of the Hessian of the cost function is computationally affordable. This paper addresses the limitations of existing methods by tackling constrained problems and by designing first-order prediction steps that rely on the Hessian of the cost function (and do notmore » require the computation of its inverse). In addition, the proposed methods are shown to improve the convergence speed of existing prediction-correction methods when applied to unconstrained problems. Numerical simulations corroborate the analytical results and showcase performance and benefits of the proposed algorithms. A realistic application of the proposed method to real-time control of energy resources is presented.« less

Escript: Open Source Environment For Solving Large-Scale Geophysical Joint Inversion Problems in Python

NASA Astrophysics Data System (ADS)

Gross, Lutz; Altinay, Cihan; Fenwick, Joel; Smith, Troy

2014-05-01

The program package escript has been designed for solving mathematical modeling problems using python, see Gross et al. (2013). Its development and maintenance has been funded by the Australian Commonwealth to provide open source software infrastructure for the Australian Earth Science community (recent funding by the Australian Geophysical Observing System EIF (AGOS) and the AuScope Collaborative Research Infrastructure Scheme (CRIS)). The key concepts of escript are based on the terminology of spatial functions and partial differential equations (PDEs) - an approach providing abstraction from the underlying spatial discretization method (i.e. the finite element method (FEM)). This feature presents a programming environment to the user which is easy to use even for complex models. Due to the fact that implementations are independent from data structures simulations are easily portable across desktop computers and scalable compute clusters without modifications to the program code. escript has been successfully applied in a variety of applications including modeling mantel convection, melting processes, volcanic flow, earthquakes, faulting, multi-phase flow, block caving and mineralization (see Poulet et al. 2013). The recent escript release (see Gross et al. (2013)) provides an open framework for solving joint inversion problems for geophysical data sets (potential field, seismic and electro-magnetic). The strategy bases on the idea to formulate the inversion problem as an optimization problem with PDE constraints where the cost function is defined by the data defect and the regularization term for the rock properties, see Gross & Kemp (2013). This approach of first-optimize-then-discretize avoids the assemblage of the - in general- dense sensitivity matrix as used in conventional approaches where discrete programming techniques are applied to the discretized problem (first-discretize-then-optimize). In this paper we will discuss the mathematical framework for inversion and appropriate solution schemes in escript. We will also give a brief introduction into escript's open framework for defining and solving geophysical inversion problems. Finally we will show some benchmark results to demonstrate the computational scalability of the inversion method across a large number of cores and compute nodes in a parallel computing environment. References: - L. Gross et al. (2013): Escript Solving Partial Differential Equations in Python Version 3.4, The University of Queensland, https://launchpad.net/escript-finley - L. Gross and C. Kemp (2013) Large Scale Joint Inversion of Geophysical Data using the Finite Element Method in escript. ASEG Extended Abstracts 2013, http://dx.doi.org/10.1071/ASEG2013ab306 - T. Poulet, L. Gross, D. Georgiev, J. Cleverley (2012): escript-RT: Reactive transport simulation in Python using escript, Computers & Geosciences, Volume 45, 168-176. http://dx.doi.org/10.1016/j.cageo.2011.11.005.

Geophysical characterization of peatlands using crosshole GPR full-waveform inversion: Case study from a bog in northwestern Germany

NASA Astrophysics Data System (ADS)

Schmäck, J.; Klotzsche, A.; Van Der Kruk, J.; Vereecken, H.; Bechtold, M.

2017-12-01

The characterization of peatlands is of particular interest, since areas with peat soils represent global hotspots for the exchange of greenhouse gases. Their effect on global warming depends on several parameters, like mean annual water level and land use. Models of greenhouse gas emissions and carbon accumulation in peatlands can be improved by including small-scale soil properties that e.g. act as gas traps and periodically release gases to the atmosphere during ebullition events. Ground penetrating radar (GPR) is well suited to non- or minimal invasively characterize and improve our understanding of dynamic processes that take place in the critical zone. It uses high frequency electromagnetic waves to image and characterize the dielectric permittivity and electrical conductivity of the critical zone, which can be related to hydrogeological properties like porosity, soil water content, salinity and clay content. In the last decade, the full-waveform inversion of crosshole GPR data has proved to be a powerful tool to improve the image resolution compared to standard ray-based methods. This approach was successfully applied to several different aquifers and was able to provide decimeter-scale resolution images including small-scale high contrast layers that can be related to zones of high porosity, zones of preferential flow or clay lenses. The comparison to independently measured e.g. logging data proved the reliability of the method. Here, for the first time crosshole GPR full-waveform inversion is used to image three peatland plots with different land use that are part of the "Ahlen-Falkenberger Moor peat bog complex" in northwestern Germany. The full-waveform inversion of the acquired data returned higher resolution images than standard ray-based GPR methods, and, is able to improve our understanding of subsurface structures. The comparison of the different plots is expected to provide new insights into gas content and gas trapping structures across different land uses. Additionally, season-related changes of peatland soil properties are investigated. The crosshole GPR full-waveform inversion was successfully applied to several datasets and the results show the utility and credibility of GPR FWI to analyze peatland properties.

A musculoskeletal shoulder model based on pseudo-inverse and null-space optimization.

PubMed

Terrier, Alexandre; Aeberhard, Martin; Michellod, Yvan; Mullhaupt, Philippe; Gillet, Denis; Farron, Alain; Pioletti, Dominique P

2010-11-01

The goal of the present work was assess the feasibility of using a pseudo-inverse and null-space optimization approach in the modeling of the shoulder biomechanics. The method was applied to a simplified musculoskeletal shoulder model. The mechanical system consisted in the arm, and the external forces were the arm weight, 6 scapulo-humeral muscles and the reaction at the glenohumeral joint, which was considered as a spherical joint. The muscle wrapping was considered around the humeral head assumed spherical. The dynamical equations were solved in a Lagrangian approach. The mathematical redundancy of the mechanical system was solved in two steps: a pseudo-inverse optimization to minimize the square of the muscle stress and a null-space optimization to restrict the muscle force to physiological limits. Several movements were simulated. The mathematical and numerical aspects of the constrained redundancy problem were efficiently solved by the proposed method. The prediction of muscle moment arms was consistent with cadaveric measurements and the joint reaction force was consistent with in vivo measurements. This preliminary work demonstrated that the developed algorithm has a great potential for more complex musculoskeletal modeling of the shoulder joint. In particular it could be further applied to a non-spherical joint model, allowing for the natural translation of the humeral head in the glenoid fossa. Copyright © 2010 IPEM. Published by Elsevier Ltd. All rights reserved.

Passive acoustic measurement of bedload grain size distribution using self-generated noise

NASA Astrophysics Data System (ADS)

Petrut, Teodor; Geay, Thomas; Gervaise, Cédric; Belleudy, Philippe; Zanker, Sebastien

2018-01-01

Monitoring sediment transport processes in rivers is of particular interest to engineers and scientists to assess the stability of rivers and hydraulic structures. Various methods for sediment transport process description were proposed using conventional or surrogate measurement techniques. This paper addresses the topic of the passive acoustic monitoring of bedload transport in rivers and especially the estimation of the bedload grain size distribution from self-generated noise. It discusses the feasibility of linking the acoustic signal spectrum shape to bedload grain sizes involved in elastic impacts with the river bed treated as a massive slab. Bedload grain size distribution is estimated by a regularized algebraic inversion scheme fed with the power spectrum density of river noise estimated from one hydrophone. The inversion methodology relies upon a physical model that predicts the acoustic field generated by the collision between rigid bodies. Here we proposed an analytic model of the acoustic energy spectrum generated by the impacts between a sphere and a slab. The proposed model computes the power spectral density of bedload noise using a linear system of analytic energy spectra weighted by the grain size distribution. The algebraic system of equations is then solved by least square optimization and solution regularization methods. The result of inversion leads directly to the estimation of the bedload grain size distribution. The inversion method was applied to real acoustic data from passive acoustics experiments realized on the Isère River, in France. The inversion of in situ measured spectra reveals good estimations of grain size distribution, fairly close to what was estimated by physical sampling instruments. These results illustrate the potential of the hydrophone technique to be used as a standalone method that could ensure high spatial and temporal resolution measurements for sediment transport in rivers.

Ground-based microwave radiometric remote sensing of the tropical atmosphere

DOE Office of Scientific and Technical Information (OSTI.GOV)

Han, Yong.

1992-01-01

A partially developed 9-channel ground-based microwave radiometer for the Department of Meteorology at Penn State was completed and tested. Complementary units were added, corrections to both hardware and software were made, and system software was corrected and upgraded. Measurements from this radiometer were used to infer tropospheric temperature, water vapor and cloud liquid water. The various weighting functions at each of the 9 channels were calculated and analyzed to estimate the sensitivities of the brightness temperature to the desired atmospheric variables. The mathematical inversion problem, in a linear form, was viewed in terms of the theory of linear algebra. Severalmore » methods for solving the inversion problem were reviewed. Radiometric observations were conducted during the 1990 Tropical Cyclone Motion Experiment. The radiometer was installed on the island of Saipan in a tropical region. The radiometer was calibrated using tipping curve and radiosonde data as well as measurements of the radiation from a blackbody absorber. A linear statistical method was applied for the data inversion. The inversion coefficients in the equation were obtained using a large number of radiosonde profiles from Guam and a radiative transfer model. Retrievals were compared with those from local, Saipan, radiosonde measurements. Water vapor profiles, integrated water vapor, and integrated liquid water were retrieved successfully. For temperature profile retrievals, however, the radiometric measurements with experimental noises added no more profile information to the inversion than that they were determined mainly by the surface pressure measurements. A method was developed to derive the integrated water vapor and liquid water from combined radiometer and ceilometer measurements. Significant improvement on radiometric measurements of the integrated liquid water can be gained with this method.« less

Rapid identification of transience in streambed conductance by inversion of floodwave responses

NASA Astrophysics Data System (ADS)

Gianni, Guillaume; Richon, Julien; Perrochet, Pierre; Vogel, Alexandre; Brunner, Philip

2016-04-01

Streambed conductance controls the interaction between surface and groundwater. However, the streambed conductance is often subject to transience. Directly measuring hydraulic properties in a river yields only point values, is time-consuming and therefore not suited to detect transience of physical properties. Here, we present a method to continuously monitor transience in streambed conductance. Input data are time series of stream stage and near stream hydraulic head. The method is based on the inversion of floodwave responses. The analytical model consists of three parameters: x, the distance between streambank and an observation well, α, the aquifer diffusivity, and a the retardation coefficient that is inversely proportional to the streambed conductance. Estimation of a is carried out over successive time steps in order to identify transience in streambed conductance. The method is tested using synthetic data and is applied to field data from the Rhône River and its alluvial aquifer (Switzerland). The synthetic method demonstrated the robustness of the proposed methodology. Application of the method to the field data allowed identifying transience in streambed properties, following flood events in the Rhône. This method requires transience in the surface water, and the river should not change its width significantly with a rising water level. If these conditions are fulfilled, this method allows for a rapid and effective identification of transience in streambed conductance.

Marine magnetotelluric inversion with an unstructured tetrahedral mesh

NASA Astrophysics Data System (ADS)

Usui, Yoshiya; Kasaya, Takafumi; Ogawa, Yasuo; Iwamoto, Hisanori

2018-05-01

The finite element method using an unstructured tetrahedral mesh is one of the most effective methods for the three-dimensional modelling of marine magnetotelluric data which are strongly affected by bathymetry, because it enables us to incorporate both small-scale and regional-scale bathymetry into a computational mesh with a practical number of elements. The authors applied a three-dimensional inversion scheme using mesh of this type to marine magnetotelluric problems for the first time and verified its applicability. Forward calculations for two bathymetry models demonstrated that the results obtained with an unstructured tetrahedral mesh are close to the reference solutions. To evaluate the forward calculation results, we developed a general TM-mode analytical formulation for a two-dimensional sinusoidal topography. Moreover, synthetic inversion test results confirmed that a three-dimensional inversion scheme with an unstructured tetrahedral mesh enables us to recover subseafloor resistivity structure properly even for a model including a land-sea boundary as well as seafloor undulations. The verified inversion scheme was subsequently applied to a set of marine magnetotelluric data observed around the Iheya North Knoll, the middle Okinawa Trough. Three-dimensional modelling using a mesh with precise bathymetry demonstrated that the data observed around the Iheya North Knoll are strongly affected by bathymetry, especially by the sea-depth differences between the depression of the trough and the shallow East China Sea. The estimated resistivity structure under the knoll is characterized by a conductive surface layer underlain by a resistive layer. The conductive layer implies permeable pelagic/hemi-pelagic sediments, which are consistent with a previous seismological study. Furthermore, the conductive layer has a resistive part immediately below the knoll, which is regarded as the consolidated magma intrusion that formed the knoll. Furthermore, at depth of 10 km, we found that the resistor underneath the knoll extends to the southeast, implying that subseafloor resistivity under the Volcanic Arc Migration Phenomenon (VAMP) area is more resistive than the surroundings due to the presence of consolidated magma.

Time-Lapse Acoustic Impedance Inversion in CO2 Sequestration Study (Weyburn Field, Canada)

NASA Astrophysics Data System (ADS)

Wang, Y.; Morozov, I. B.

2016-12-01

Acoustic-impedance (AI) pseudo-logs are useful for characterising subtle variations of fluid content during seismic monitoring of reservoirs undergoing enhanced oil recovery and/or geologic CO2 sequestration. However, highly accurate AI images are required for time-lapse analysis, which may be difficult to achieve with conventional inversion approaches. In this study, two enhancements of time-lapse AI analysis are proposed. First, a well-known uncertainty of AI inversion is caused by the lack of low-frequency signal in reflection seismic data. To resolve this difficulty, we utilize an integrated AI inversion approach combining seismic data, acoustic well logs and seismic-processing velocities. The use of well logs helps stabilizing the recursive AI inverse, and seismic-processing velocities are used to complement the low-frequency information in seismic records. To derive the low-frequency AI from seismic-processing velocity data, an empirical relation is determined by using the available acoustic logs. This method is simple and does not require subjective choices of parameters and regularization schemes as in the more sophisticated joint inversion methods. The second improvement to accurate time-lapse AI imaging consists in time-variant calibration of reflectivity. Calibration corrections consist of time shifts, amplitude corrections, spectral shaping and phase rotations. Following the calibration, average and differential reflection amplitudes are calculated, from which the average and differential AI are obtained. The approaches are applied to a time-lapse 3-D 3-C dataset from Weyburn CO2 sequestration project in southern Saskatchewan, Canada. High quality time-lapse AI volumes are obtained. Comparisons with traditional recursive and colored AI inversions (obtained without using seismic-processing velocities) show that the new method gives a better representation of spatial AI variations. Although only early stages of monitoring seismic data are available, time-lapse AI variations mapped within and near the reservoir zone suggest correlations with CO2 injection. By extending this procedure to elastic impedances, additional constraints on the variations of physical properties within the reservoir can be obtained.

Calculation of earthquake rupture histories using a hybrid global search algorithm: Application to the 1992 Landers, California, earthquake

USGS Publications Warehouse

Hartzell, S.; Liu, P.

1996-01-01

A method is presented for the simultaneous calculation of slip amplitudes and rupture times for a finite fault using a hybrid global search algorithm. The method we use combines simulated annealing with the downhill simplex method to produce a more efficient search algorithm then either of the two constituent parts. This formulation has advantages over traditional iterative or linearized approaches to the problem because it is able to escape local minima in its search through model space for the global optimum. We apply this global search method to the calculation of the rupture history for the Landers, California, earthquake. The rupture is modeled using three separate finite-fault planes to represent the three main fault segments that failed during this earthquake. Both the slip amplitude and the time of slip are calculated for a grid work of subfaults. The data used consist of digital, teleseismic P and SH body waves. Long-period, broadband, and short-period records are utilized to obtain a wideband characterization of the source. The results of the global search inversion are compared with a more traditional linear-least-squares inversion for only slip amplitudes. We use a multi-time-window linear analysis to relax the constraints on rupture time and rise time in the least-squares inversion. Both inversions produce similar slip distributions, although the linear-least-squares solution has a 10% larger moment (7.3 ?? 1026 dyne-cm compared with 6.6 ?? 1026 dyne-cm). Both inversions fit the data equally well and point out the importance of (1) using a parameterization with sufficient spatial and temporal flexibility to encompass likely complexities in the rupture process, (2) including suitable physically based constraints on the inversion to reduce instabilities in the solution, and (3) focusing on those robust rupture characteristics that rise above the details of the parameterization and data set.

Bianisotropic metamaterial

DOEpatents

El-Kady, Ihab F.; Reinke, Charles M.

2017-07-18

The topology of the elements of a metamaterial can be engineered from its desired electromagnetic constitutive tensor using an inverse group theory method. Therefore, given a desired electromagnetic response and a generic metamaterial elemental design, group theory is applied to predict the various ways that the element can be arranged in three dimensions to produce the desired functionality. An optimizer can then be applied to an electromagnetic modeling tool to fine tune the values of the electromagnetic properties of the resulting metamaterial topology.

Improving water content estimation on landslide-prone hillslopes using structurally-constrained inversion of electrical resistivity data

NASA Astrophysics Data System (ADS)

Heinze, Thomas; Möhring, Simon; Budler, Jasmin; Weigand, Maximilian; Kemna, Andreas

2017-04-01

Rainfall-triggered landslides are a latent danger in almost any place of the world. Due to climate change heavy rainfalls might occur more often, increasing the risk of landslides. With pore pressure as mechanical trigger, knowledge of water content distribution in the ground is essential for hazard analysis during monitoring of potentially dangerous rainfall events. Geophysical methods like electrical resistivity tomography (ERT) can be utilized to determine the spatial distribution of water content using established soil physical relationships between bulk electrical resistivity and water content. However, often more dominant electrical contrasts due to lithological structures outplay these hydraulic signatures and blur the results in the inversion process. Additionally, the inversion of ERT data requires further constraints. In the standard Occam inversion method, a smoothness constraint is used, assuming that soil properties change softly in space. This applies in many scenarios, as for example during infiltration of water without a clear saturation front. Sharp lithological layers with strongly divergent hydrological parameters, as often found in landslide prone hillslopes, on the other hand, are typically badly resolved by standard ERT. We use a structurally constrained ERT inversion approach for improving water content estimation in landslide prone hills by including a-priori information about lithological layers. Here the standard smoothness constraint is reduced along layer boundaries identified using seismic data or other additional sources. This approach significantly improves water content estimations, because in landslide prone hills often a layer of rather high hydraulic conductivity is followed by a hydraulic barrier like clay-rich soil, causing higher pore pressures. One saturated layer and one almost drained layer typically result also in a sharp contrast in electrical resistivity, assuming that surface conductivity of the soil does not change in similar order. Using synthetic data, we study the influence of uncertainties in the a-priori information on the inverted resistivity and estimated water content distribution. Based on our simulation results, we provide best-practice recommendations for field applications and suggest important tests to obtain reliable, reproducible and trustworthy results. We finally apply our findings to field data, compare conventional and improved analysis results, and discuss limitations of the structurally-constrained inversion approach.

Regularized minimum I-divergence methods for the inverse blackbody radiation problem

NASA Astrophysics Data System (ADS)

Choi, Kerkil; Lanterman, Aaron D.; Shin, Jaemin

2006-08-01

This paper proposes iterative methods for estimating the area temperature distribution of a blackbody from its total radiated power spectrum measurements. This is called the inverse blackbody radiation problem. This problem is inherently ill-posed due to the characteristics of the kernel in the underlying integral equation given by Planck's law. The functions involved in the problem are all non-negative. Csiszár's I-divergence is an information-theoretic discrepancy measure between two non-negative functions. We derive iterative methods for minimizing Csiszár's I-divergence between the measured power spectrum and the power spectrum arising from the estimate according to the integral equation. Due to the ill-posedness of the problem, unconstrained algorithms often produce poor estimates, especially when the measurements are corrupted by noise. To alleviate this difficulty, we apply regularization methods to our algorithms. Penalties based on Shannon's entropy, the L1-norm and Good's roughness are chosen to suppress the undesirable artefacts. When a penalty is applied, the pertinent optimization that needs to be performed at each iteration is no longer trivial. In particular, Good's roughness causes couplings between estimate components. To handle this issue, we adapt Green's one-step-late method. This choice is based on the important fact that our minimum I-divergence algorithms can be interpreted as asymptotic forms of certain expectation-maximization algorithms. The effectiveness of our methods is illustrated via various numerical experiments.

Evaluation of Uncertainties in Measuring Particulate Matter Emission Factors from Atmospheric Fugitive Sources Using Optical Remote Sensing

NASA Astrophysics Data System (ADS)

Yuen, W.; Ma, Q.; Du, K.; Koloutsou-Vakakis, S.; Rood, M. J.

2015-12-01

Measurements of particulate matter (PM) emissions generated from fugitive sources are of interest in air pollution studies, since such emissions vary widely both spatially and temporally. This research focuses on determining the uncertainties in quantifying fugitive PM emission factors (EFs) generated from mobile vehicles using a vertical scanning micro-pulse lidar (MPL). The goal of this research is to identify the greatest sources of uncertainty of the applied lidar technique in determining fugitive PM EFs, and to recommend methods to reduce the uncertainties in this measurement. The MPL detects the PM plume generated by mobile fugitive sources that are carried downwind to the MPL's vertical scanning plane. Range-resolved MPL signals are measured, corrected, and converted to light extinction coefficients, through inversion of the lidar equation and calculation of the lidar ratio. In this research, both the near-end and far-end lidar equation inversion methods are considered. Range-resolved PM mass concentrations are then determined from the extinction coefficient measurements using the measured mass extinction efficiency (MEE) value, which is an intensive PM property. MEE is determined by collocated PM mass concentration and light extinction measurements, provided respectively by a DustTrak and an open-path laser transmissometer. These PM mass concentrations are then integrated with wind information, duration of plume event, and vehicle distance travelled to obtain fugitive PM EFs. To obtain the uncertainty of PM EFs, uncertainties in MPL signals, lidar ratio, MEE, and wind variation are considered. Error propagation method is applied to each of the above intermediate steps to aggregate uncertainty sources. Results include determination of uncertainties in each intermediate step, and comparison of uncertainties between the use of near-end and far-end lidar equation inversion methods.

Analysis of group-velocity dispersion of high-frequency Rayleigh waves for near-surface applications

USGS Publications Warehouse

Luo, Y.; Xia, J.; Xu, Y.; Zeng, C.

2011-01-01

The Multichannel Analysis of Surface Waves (MASW) method is an efficient tool to obtain the vertical shear (S)-wave velocity profile using the dispersive characteristic of Rayleigh waves. Most MASW researchers mainly apply Rayleigh-wave phase-velocity dispersion for S-wave velocity estimation with a few exceptions applying Rayleigh-wave group-velocity dispersion. Herein, we first compare sensitivities of fundamental surface-wave phase velocities with group velocities with three four-layer models including a low-velocity layer or a high-velocity layer. Then synthetic data are simulated by a finite difference method. Images of group-velocity dispersive energy of the synthetic data are generated using the Multiple Filter Analysis (MFA) method. Finally we invert a high-frequency surface-wave group-velocity dispersion curve of a real-world example. Results demonstrate that (1) the sensitivities of group velocities are higher than those of phase velocities and usable frequency ranges are wider than that of phase velocities, which is very helpful in improving inversion stability because for a stable inversion system, small changes in phase velocities do not result in a large fluctuation in inverted S-wave velocities; (2) group-velocity dispersive energy can be measured using single-trace data if Rayleigh-wave fundamental-mode energy is dominant, which suggests that the number of shots required in data acquisition can be dramatically reduced and the horizontal resolution can be greatly improved using analysis of group-velocity dispersion; and (3) the suspension logging results of the real-world example demonstrate that inversion of group velocities generated by the MFA method can successfully estimate near-surface S-wave velocities. ?? 2011 Elsevier B.V.

A new algorithm for three-dimensional joint inversion of body wave and surface wave data and its application to the Southern California plate boundary region

NASA Astrophysics Data System (ADS)

Fang, Hongjian; Zhang, Haijiang; Yao, Huajian; Allam, Amir; Zigone, Dimitri; Ben-Zion, Yehuda; Thurber, Clifford; van der Hilst, Robert D.

2016-05-01

We introduce a new algorithm for joint inversion of body wave and surface wave data to get better 3-D P wave (Vp) and S wave (Vs) velocity models by taking advantage of the complementary strengths of each data set. Our joint inversion algorithm uses a one-step inversion of surface wave traveltime measurements at different periods for 3-D Vs and Vp models without constructing the intermediate phase or group velocity maps. This allows a more straightforward modeling of surface wave traveltime data with the body wave arrival times. We take into consideration the sensitivity of surface wave data with respect to Vp in addition to its large sensitivity to Vs, which means both models are constrained by two different data types. The method is applied to determine 3-D crustal Vp and Vs models using body wave and Rayleigh wave data in the Southern California plate boundary region, which has previously been studied with both double-difference tomography method using body wave arrival times and ambient noise tomography method with Rayleigh and Love wave group velocity dispersion measurements. Our approach creates self-consistent and unique models with no prominent gaps, with Rayleigh wave data resolving shallow and large-scale features and body wave data constraining relatively deeper structures where their ray coverage is good. The velocity model from the joint inversion is consistent with local geological structures and produces better fits to observed seismic waveforms than the current Southern California Earthquake Center (SCEC) model.

Inversion of surface parameters using fast learning neural networks

NASA Technical Reports Server (NTRS)

Dawson, M. S.; Olvera, J.; Fung, A. K.; Manry, M. T.

1992-01-01

A neural network approach to the inversion of surface scattering parameters is presented. Simulated data sets based on a surface scattering model are used so that the data may be viewed as taken from a completely known randomly rough surface. The fast learning (FL) neural network and a multilayer perceptron (MLP) trained with backpropagation learning (BP network) are tested on the simulated backscattering data. The RMS error of training the FL network is found to be less than one half the error of the BP network while requiring one to two orders of magnitude less CPU time. When applied to inversion of parameters from a statistically rough surface, the FL method is successful at recovering the surface permittivity, the surface correlation length, and the RMS surface height in less time and with less error than the BP network. Further applications of the FL neural network to the inversion of parameters from backscatter measurements of an inhomogeneous layer above a half space are shown.

Round-off errors in cutting plane algorithms based on the revised simplex procedure

NASA Technical Reports Server (NTRS)

Moore, J. E.

1973-01-01

This report statistically analyzes computational round-off errors associated with the cutting plane approach to solving linear integer programming problems. Cutting plane methods require that the inverse of a sequence of matrices be computed. The problem basically reduces to one of minimizing round-off errors in the sequence of inverses. Two procedures for minimizing this problem are presented, and their influence on error accumulation is statistically analyzed. One procedure employs a very small tolerance factor to round computed values to zero. The other procedure is a numerical analysis technique for reinverting or improving the approximate inverse of a matrix. The results indicated that round-off accumulation can be effectively minimized by employing a tolerance factor which reflects the number of significant digits carried for each calculation and by applying the reinversion procedure once to each computed inverse. If 18 significant digits plus an exponent are carried for each variable during computations, then a tolerance value of 0.1 x 10 to the minus 12th power is reasonable.

The transient divided bar method for laboratory measurements of thermal properties

NASA Astrophysics Data System (ADS)

Bording, Thue S.; Nielsen, Søren B.; Balling, Niels

2016-12-01

Accurate information on thermal conductivity and thermal diffusivity of materials is of central importance in relation to geoscience and engineering problems involving the transfer of heat. Several methods, including the classical divided bar technique, are available for laboratory measurements of thermal conductivity, but much fewer for thermal diffusivity. We have generalized the divided bar technique to the transient case in which thermal conductivity, volumetric heat capacity and thereby also thermal diffusivity are measured simultaneously. As the density of samples is easily determined independently, specific heat capacity can also be determined. The finite element formulation provides a flexible forward solution for heat transfer across the bar, and thermal properties are estimated by inverse Monte Carlo modelling. This methodology enables a proper quantification of experimental uncertainties on measured thermal properties and information on their origin. The developed methodology was applied to various materials, including a standard ceramic material and different rock samples, and measuring results were compared with results applying traditional steady-state divided bar and an independent line-source method. All measurements show highly consistent results and with excellent reproducibility and high accuracy. For conductivity the obtained uncertainty is typically 1-3 per cent, and for diffusivity uncertainty may be reduced to about 3-5 per cent. The main uncertainty originates from the presence of thermal contact resistance associated with the internal interfaces in the bar. These are not resolved during inversion and it is imperative that they are minimized. The proposed procedure is simple and may quite easily be implemented to the many steady-state divided bar systems in operation. A thermally controlled bath, as applied here, may not be needed. Simpler systems, such as applying temperature-controlled water directly from a tap, may also be applied.

Determining Crust and Upper Mantle Structure by Bayesian Joint Inversion of Receiver Functions and Surface Wave Dispersion at a Single Station: Preparation for Data from the InSight Mission

NASA Astrophysics Data System (ADS)

Jia, M.; Panning, M. P.; Lekic, V.; Gao, C.

2017-12-01

The InSight (Interior Exploration using Seismic Investigations, Geodesy and Heat Transport) mission will deploy a geophysical station on Mars in 2018. Using seismology to explore the interior structure of the Mars is one of the main targets, and as part of the mission, we will use 3-component seismic data to constrain the crust and upper mantle structure including P and S wave velocities and densities underneath the station. We will apply a reversible jump Markov chain Monte Carlo algorithm in the transdimensional hierarchical Bayesian inversion framework, in which the number of parameters in the model space and the noise level of the observed data are also treated as unknowns in the inversion process. Bayesian based methods produce an ensemble of models which can be analyzed to quantify uncertainties and trade-offs of the model parameters. In order to get better resolution, we will simultaneously invert three different types of seismic data: receiver functions, surface wave dispersion (SWD), and ZH ratios. Because the InSight mission will only deliver a single seismic station to Mars, and both the source location and the interior structure will be unknown, we will jointly invert the ray parameter in our approach. In preparation for this work, we first verify our approach by using a set of synthetic data. We find that SWD can constrain the absolute value of velocities while receiver functions constrain the discontinuities. By joint inversion, the velocity structure in the crust and upper mantle is well recovered. Then, we apply our approach to real data from an earth-based seismic station BFO located in Black Forest Observatory in Germany, as already used in a demonstration study for single station location methods. From the comparison of the results, our hierarchical treatment shows its advantage over the conventional method in which the noise level of observed data is fixed as a prior.

A stochastic vortex structure method for interacting particles in turbulent shear flows

NASA Astrophysics Data System (ADS)

Dizaji, Farzad F.; Marshall, Jeffrey S.; Grant, John R.

2018-01-01

In a recent study, we have proposed a new synthetic turbulence method based on stochastic vortex structures (SVSs), and we have demonstrated that this method can accurately predict particle transport, collision, and agglomeration in homogeneous, isotropic turbulence in comparison to direct numerical simulation results. The current paper extends the SVS method to non-homogeneous, anisotropic turbulence. The key element of this extension is a new inversion procedure, by which the vortex initial orientation can be set so as to generate a prescribed Reynolds stress field. After validating this inversion procedure for simple problems, we apply the SVS method to the problem of interacting particle transport by a turbulent planar jet. Measures of the turbulent flow and of particle dispersion, clustering, and collision obtained by the new SVS simulations are shown to compare well with direct numerical simulation results. The influence of different numerical parameters, such as number of vortices and vortex lifetime, on the accuracy of the SVS predictions is also examined.

Application of genetic algorithms to focal mechanism determination

NASA Astrophysics Data System (ADS)

Kobayashi, Reiji; Nakanishi, Ichiro

1994-04-01

Genetic algorithms are a new class of methods for global optimization. They resemble Monte Carlo techniques, but search for solutions more efficiently than uniform Monte Carlo sampling. In the field of geophysics, genetic algorithms have recently been used to solve some non-linear inverse problems (e.g., earthquake location, waveform inversion, migration velocity estimation). We present an application of genetic algorithms to focal mechanism determination from first-motion polarities of P-waves and apply our method to two recent large events, the Kushiro-oki earthquake of January 15, 1993 and the SW Hokkaido (Japan Sea) earthquake of July 12, 1993. Initial solution and curvature information of the objective function that gradient methods need are not required in our approach. Moreover globally optimal solutions can be efficiently obtained. Calculation of polarities based on double-couple models is the most time-consuming part of the source mechanism determination. The amount of calculations required by the method designed in this study is much less than that of previous grid search methods.

Cybernetic group method of data handling (GMDH) statistical learning for hyperspectral remote sensing inverse problems in coastal ocean optics

NASA Astrophysics Data System (ADS)

Filippi, Anthony Matthew

For complex systems, sufficient a priori knowledge is often lacking about the mathematical or empirical relationship between cause and effect or between inputs and outputs of a given system. Automated machine learning may offer a useful solution in such cases. Coastal marine optical environments represent such a case, as the optical remote sensing inverse problem remains largely unsolved. A self-organizing, cybernetic mathematical modeling approach known as the group method of data handling (GMDH), a type of statistical learning network (SLN), was used to generate explicit spectral inversion models for optically shallow coastal waters. Optically shallow water light fields represent a particularly difficult challenge in oceanographic remote sensing. Several algorithm-input data treatment combinations were utilized in multiple experiments to automatically generate inverse solutions for various inherent optical property (IOP), bottom optical property (BOP), constituent concentration, and bottom depth estimations. The objective was to identify the optimal remote-sensing reflectance Rrs(lambda) inversion algorithm. The GMDH also has the potential of inductive discovery of physical hydro-optical laws. Simulated data were used to develop generalized, quasi-universal relationships. The Hydrolight numerical forward model, based on radiative transfer theory, was used to compute simulated above-water remote-sensing reflectance Rrs(lambda) psuedodata, matching the spectral channels and resolution of the experimental Naval Research Laboratory Ocean PHILLS (Portable Hyperspectral Imager for Low-Light Spectroscopy) sensor. The input-output pairs were for GMDH and artificial neural network (ANN) model development, the latter of which was used as a baseline, or control, algorithm. Both types of models were applied to in situ and aircraft data. Also, in situ spectroradiometer-derived Rrs(lambda) were used as input to an optimization-based inversion procedure. Target variables included bottom depth z b, chlorophyll a concentration [chl- a], spectral bottom irradiance reflectance Rb(lambda), and spectral total absorption a(lambda) and spectral total backscattering bb(lambda) coefficients. When applying the cybernetic and neural models to in situ HyperTSRB-derived Rrs, the difference in the means of the absolute error of the inversion estimates for zb was significant (alpha = 0.05). GMDH yielded significantly better zb than the ANN. The ANN model posted a mean absolute error (MAE) of 0.62214 m, compared with 0.55161 m for GMDH.

TOPEX/POSEIDON tides estimated using a global inverse model

NASA Technical Reports Server (NTRS)

Egbert, Gary D.; Bennett, Andrew F.; Foreman, Michael G. G.

1994-01-01

Altimetric data from the TOPEX/POSEIDON mission will be used for studies of global ocean circulation and marine geophysics. However, it is first necessary to remove the ocean tides, which are aliased in the raw data. The tides are constrained by the two distinct types of information: the hydrodynamic equations which the tidal fields of elevations and velocities must satisfy, and direct observational data from tide gauges and satellite altimetry. Here we develop and apply a generalized inverse method, which allows us to combine rationally all of this information into global tidal fields best fitting both the data and the dynamics, in a least squares sense. The resulting inverse solution is a sum of the direct solution to the astronomically forced Laplace tidal equations and a linear combination of the representers for the data functionals. The representer functions (one for each datum) are determined by the dynamical equations, and by our prior estimates of the statistics or errors in these equations. Our major task is a direct numerical calculation of these representers. This task is computationally intensive, but well suited to massively parallel processing. By calculating the representers we reduce the full (infinite dimensional) problem to a relatively low-dimensional problem at the outset, allowing full control over the conditioning and hence the stability of the inverse solution. With the representers calculated we can easily update our model as additional TOPEX/POSEIDON data become available. As an initial illustration we invert harmonic constants from a set of 80 open-ocean tide gauges. We then present a practical scheme for direct inversion of TOPEX/POSEIDON crossover data. We apply this method to 38 cycles of geophysical data records (GDR) data, computing preliminary global estimates of the four principal tidal constituents, M(sub 2), S(sub 2), K(sub 1) and O(sub 1). The inverse solution yields tidal fields which are simultaneously smoother, and in better agreement with altimetric and ground truth data, than previously proposed tidal models. Relative to the 'default' tidal corrections provided with the TOPEX/POSEIDON GDR, the inverse solution reduces crossover difference variances significantly (approximately 20-30%), even though only a small number of free parameters (approximately equal to 1000) are actually fit to the crossover data.

Waveform inversion in the frequency domain for the simultaneous determination of earthquake source mechanism and moment function

NASA Astrophysics Data System (ADS)

Nakano, M.; Kumagai, H.; Inoue, H.

2008-06-01

We propose a method of waveform inversion to rapidly and routinely estimate both the moment function and the centroid moment tensor (CMT) of an earthquake. In this method, waveform inversion is carried out in the frequency domain to obtain the moment function more rapidly than when solved in the time domain. We assume a pure double-couple source mechanism in order to stabilize the solution when using data from a small number of seismic stations. The fault and slip orientations are estimated by a grid search with respect to the strike, dip and rake angles. The moment function in the time domain is obtained from the inverse Fourier transform of the frequency components determined by the inversion. Since observed waveforms used for the inversion are limited in a particular frequency band, the estimated moment function is a bandpassed form. We develop a practical approach to estimate the deconvolved form of the moment function, from which we can reconstruct detailed rupture history and the seismic moment. The source location is determined by a spatial grid search using adaptive grid spacings, which are gradually decreased in each step of the search. We apply this method to two events that occurred in Indonesia by using data from a broad-band seismic network in Indonesia (JISNET): one northeast of Sulawesi (Mw = 7.5) on 2007 January 21, and the other south of Java (Mw = 7.5) on 2006 July 17. The source centroid locations and mechanisms we estimated for both events are consistent with those determined by the Global CMT Project and the National Earthquake Information Center of the U.S. Geological Survey. The estimated rupture duration of the Sulawesi event is 16 s, which is comparable to a typical duration for earthquakes of this magnitude, while that of the Java event is anomalously long (176 s), suggesting that this event was a tsunami earthquake. Our application demonstrates that this inversion method has great potential for rapid and routine estimations of both the CMT and the moment function, and may be useful for identification of tsunami earthquakes.

Bayesian ISOLA: new tool for automated centroid moment tensor inversion

NASA Astrophysics Data System (ADS)

Vackář, Jiří; Burjánek, Jan; Gallovič, František; Zahradník, Jiří; Clinton, John

2017-04-01

Focal mechanisms are important for understanding seismotectonics of a region, and they serve as a basic input for seismic hazard assessment. Usually, the point source approximation and the moment tensor (MT) are used. We have developed a new, fully automated tool for the centroid moment tensor (CMT) inversion in a Bayesian framework. It includes automated data retrieval, data selection where station components with various instrumental disturbances and high signal-to-noise are rejected, and full-waveform inversion in a space-time grid around a provided hypocenter. The method is innovative in the following aspects: (i) The CMT inversion is fully automated, no user interaction is required, although the details of the process can be visually inspected latter on many figures which are automatically plotted.(ii) The automated process includes detection of disturbances based on MouseTrap code, so disturbed recordings do not affect inversion.(iii) A data covariance matrix calculated from pre-event noise yields an automated weighting of the station recordings according to their noise levels and also serves as an automated frequency filter suppressing noisy frequencies.(iv) Bayesian approach is used, so not only the best solution is obtained, but also the posterior probability density function.(v) A space-time grid search effectively combined with the least-squares inversion of moment tensor components speeds up the inversion and allows to obtain more accurate results compared to stochastic methods. The method has been tested on synthetic and observed data. It has been tested by comparison with manually processed moment tensors of all events greater than M≥3 in the Swiss catalogue over 16 years using data available at the Swiss data center (http://arclink.ethz.ch). The quality of the results of the presented automated process is comparable with careful manual processing of data. The software package programmed in Python has been designed to be as versatile as possible in order to be applicable in various networks ranging from local to regional. The method can be applied either to the everyday network data flow, or to process large previously existing earthquake catalogues and data sets.

An Improvement to the Fourier Series Method for Inversion of Laplace Transforms Applied to Elastic and Viscoelastic Waves

DTIC Science & Technology

2007-01-01

Lawrence Livermore National Laboratory Report UCRL -MA-107254 Rev. 1. NO. OF COPIES ORGANIZATION 1 DEFENSE TECHNICAL (PDF INFORMATION CTR...AFB FL 32542 3 DARPA L CHRISTODOULOU W COBLENZ S WAX 3701 N FAIRFAX DR ARLINGTON VA 22203-1714 1 DIRECTOR US ARMY ARDEC

Estimating production and consumption of solid reactive Fe phases in marine sediments from concentration profiles

EPA Science Inventory

1D diffusion models may be used to estimate rates of production and consumption of dissolved metabolites in marine sediments, but are applied less often to the solid phase. Here we used a numerical inverse method to estimate solid phase Fe(III) and Fe(II) consumption and product...

Development of direct-inverse 3-D methods for applied transonic aerodynamic wing design and analysis

NASA Technical Reports Server (NTRS)

Carlson, Leland A.

1989-01-01

Progress in the direct-inverse wing design method in curvilinear coordinates has been made. This includes the remedying of a spanwise oscillation problem and the assessment of grid skewness, viscous interaction, and the initial airfoil section on the final design. It was found that, in response to the spanwise oscillation problem that designing at every other spanwise station produced the best results for the cases presented, a smoothly varying grid is especially needed for the accurate design at the wing tip, the boundary layer displacement thicknesses must be included in a successful wing design, the design of high and medium aspect ratio wings is possible with this code, and the final airfoil section designed is fairly independent of the initial section.

Electron energy and electron trajectories in an inverse free-electron laser accelerator based on a novel electrostatic wiggler

NASA Astrophysics Data System (ADS)

Nikrah, M.; Jafari, S.

2016-06-01

We expand here a theory of a high-gradient laser-excited electron accelerator based on an inverse free-electron laser (inverse-FEL), but with innovations in the structure and design. The electrostatic wiggler used in our scheme, namely termed the Paul wiggler, is generated by segmented cylindrical electrodes with applied oscillatory voltages {{V}\\text{osc}}(t) over {{90}\\circ} segments. The inverse-FEL interaction can be described by the equations that govern the electron motion in the combined fields of both the laser pulse and Paul wiggler field. A numerical study of electron energy and electron trajectories has been made using the fourth-order Runge-Kutta method. The results indicate that the electron attains a considerable energy at short distances in this device. It is found that if the electron has got sufficient suitable wiggler amplitude intensities, it can not only gain higher energy in longer distances, but also can retain it even after the passing of the laser pulse. In addition, the results reveal that the electron energy gains different peaks for different initial axial velocities, so that a suitable small initial axial velocity of e-beam produces substantially high energy gain. With regard to the transverse confinement of the electron beam in a Paul wiggler, there is no applied axial guide magnetic field in this device.

Three dimensional inversion of magnetic survey data collected over kimberlite pipes in presence of remanent magnetization

NASA Astrophysics Data System (ADS)

Zhao, Pengzhi

Magnetic method is a common geophysical technique used to explore kimberlites. The analysis and interpretation of measured magnetic data provides the information of magnetic and geometric properties of potential kimberlite pipes. A crucial parameter of kimberlite magnetic interpretation is the remanent magnetization that dominates the classification of kimberlite. However, the measured magnetic data is the total field affected by the remanent magnetization and the susceptibility. The presence of remanent magnetization can pose severe challenges to the quantitative interpretation of magnetic data by skewing or laterally shifting magnetic anomalies relative to the subsurface source (Haney and Li, 2002). Therefore, identification of remanence effects and determination of remanent magnetization are important in magnetic data interpretation. This project presents a new method to determine the magnetic and geometric properties of kimberlite pipes in the presence of strong remanent magnetization. This method consists of two steps. The first step is to estimate the total magnetization and geometric properties of magnetic anomaly. The second step is to separate the remanent magnetization from the total magnetization. In the first step, a joint parametric inversion of total-field magnetic data and its analytic signal (derived from the survey data by Fourier transform method) is used. The algorithm of the joint inversion is based on the Gauss-Newton method and it is more stable and more accurate than the separate inversion method. It has been tested with synthetic data and applied to interpret the field data from the Lac de Gras, North-West Territories of Canada. The results of the synthetic examples and the field data applications show that joint inversion can recovers the total magnetization and geometric properties of magnetic anomaly with a good data fit and stable convergence. In the second step, the remanent magnetization is separated from the total magnetization by using a determined susceptibility. The susceptibility value is estimated by using the frequency domain electromagnetic data. The inversion method is achieved by a code, named “EM1DFM”, developed by University of British Columbia was designed to construct one of four types of 1D model, using any type of geophysical frequency domain loop-loop data with one of four variations of the inversion algorithm. The results show that the susceptibility of magnetic body is recovered, even if the depth and thickness are not well estimated. This two-step process provides a new way to determine magnetic and geometric properties of kimberlite pipes in the presence of strong remanent magnetization. The joint inversion of the total-field magnetic data and its analytic signal obtains the total magnetization and geometric properties. The frequency domain EM method provides the susceptibility. As a result, the remanent magnetization can be separated from the total magnetization accurately.

Time-domain induced polarization - an analysis of Cole-Cole parameter resolution and correlation using Markov Chain Monte Carlo inversion

NASA Astrophysics Data System (ADS)

Madsen, Line Meldgaard; Fiandaca, Gianluca; Auken, Esben; Christiansen, Anders Vest

2017-12-01

The application of time-domain induced polarization (TDIP) is increasing with advances in acquisition techniques, data processing and spectral inversion schemes. An inversion of TDIP data for the spectral Cole-Cole parameters is a non-linear problem, but by applying a 1-D Markov Chain Monte Carlo (MCMC) inversion algorithm, a full non-linear uncertainty analysis of the parameters and the parameter correlations can be accessed. This is essential to understand to what degree the spectral Cole-Cole parameters can be resolved from TDIP data. MCMC inversions of synthetic TDIP data, which show bell-shaped probability distributions with a single maximum, show that the Cole-Cole parameters can be resolved from TDIP data if an acquisition range above two decades in time is applied. Linear correlations between the Cole-Cole parameters are observed and by decreasing the acquisitions ranges, the correlations increase and become non-linear. It is further investigated how waveform and parameter values influence the resolution of the Cole-Cole parameters. A limiting factor is the value of the frequency exponent, C. As C decreases, the resolution of all the Cole-Cole parameters decreases and the results become increasingly non-linear. While the values of the time constant, τ, must be in the acquisition range to resolve the parameters well, the choice between a 50 per cent and a 100 per cent duty cycle for the current injection does not have an influence on the parameter resolution. The limits of resolution and linearity are also studied in a comparison between the MCMC and a linearized gradient-based inversion approach. The two methods are consistent for resolved models, but the linearized approach tends to underestimate the uncertainties for poorly resolved parameters due to the corresponding non-linear features. Finally, an MCMC inversion of 1-D field data verifies that spectral Cole-Cole parameters can also be resolved from TD field measurements.

Possibilities of magnetotelluric methods in geophysical exploration for ore minerals

NASA Astrophysics Data System (ADS)

Varentsov M., Iv.; Kulikov, V. A.; Yakovlev, A. G.; Yakovlev, D. V.

2013-05-01

In the past decade, the applications of magnetotelluric method in the electric prospecting for ore bodies have been rapidly progressing. In the present work, we summarize the first results on this way. We discuss the specificity of the geoelectrical models in the problems of mining prospecting for ore bodies. The state-of-the-art capabilities of the method, which rely on the synchronous observation systems and the procedure of joint inversion of magnetotelluric and magnetovariational responses, are considered in the context of ore mineral exploration. The results of modeling a typical mining audio-magnetotelluric survey for ore minerals are presented. On the basis of these simulations and the data provided by in-situ soundings, the efficient approaches to the processing, analysis, and inversion of these data are discussed and illustrated. The future trends in magnetotellurics as applied to the mining prospecting are analyzed.

Full wave two-dimensional modeling of scattering and inverse scattering for layered rough surfaces with buried objects

NASA Astrophysics Data System (ADS)

Kuo, Chih-Hao

Efficient and accurate modeling of electromagnetic scattering from layered rough surfaces with buried objects finds applications ranging from detection of landmines to remote sensing of subsurface soil moisture. The formulation of a hybrid numerical/analytical solution to electromagnetic scattering from layered rough surfaces is first presented in this dissertation. The solution to scattering from each rough interface is sought independently based on the extended boundary condition method (EBCM), where the scattered fields of each rough interface are expressed as a summation of plane waves and then cast into reflection/transmission matrices. To account for interactions between multiple rough boundaries, the scattering matrix method (SMM) is applied to recursively cascade reflection and transmission matrices of each rough interface and obtain the composite reflection matrix from the overall scattering medium. The validation of this method against the Method of Moments (MoM) and Small Perturbation Method (SPM) is addressed and the numerical results which investigate the potential of low frequency radar systems in estimating deep soil moisture are presented. Computational efficiency of the proposed method is also discussed. In order to demonstrate the capability of this method in modeling coherent multiple scattering phenomena, the proposed method has been employed to analyze backscattering enhancement and satellite peaks due to surface plasmon waves from layered rough surfaces. Numerical results which show the appearance of enhanced backscattered peaks and satellite peaks are presented. Following the development of the EBCM/SMM technique, a technique which incorporates a buried object in layered rough surfaces by employing the T-matrix method and the cylindrical-to-spatial harmonics transformation is proposed. Validation and numerical results are provided. Finally, a multi-frequency polarimetric inversion algorithm for the retrieval of subsurface soil properties using VHF/UHF band radar measurements is devised. The top soil dielectric constant is first determined using an L-band inversion algorithm. For the retrieval of subsurface properties, a time-domain inversion technique is employed together with a parameter optimization for the pulse shape of time delay echoes from VHF/UHF band radar observations. Numerical studies to investigate the accuracy of the proposed inversion technique in presence of errors are addressed.

Validation of Spherically Symmetric Inversion by Use of a Tomographically Reconstructed Three-Dimensional Electron Density of the Solar Corona

NASA Technical Reports Server (NTRS)

Wang, Tongjiang; Davila, Joseph M.

2014-01-01

Determining the coronal electron density by the inversion of white-light polarized brightness (pB) measurements by coronagraphs is a classic problem in solar physics. An inversion technique based on the spherically symmetric geometry (spherically symmetric inversion, SSI) was developed in the 1950s and has been widely applied to interpret various observations. However, to date there is no study of the uncertainty estimation of this method. We here present the detailed assessment of this method using a three-dimensional (3D) electron density in the corona from 1.5 to 4 solar radius as a model, which is reconstructed by a tomography method from STEREO/COR1 observations during the solar minimum in February 2008 (Carrington Rotation, CR 2066).We first show in theory and observation that the spherically symmetric polynomial approximation (SSPA) method and the Van de Hulst inversion technique are equivalent. Then we assess the SSPA method using synthesized pB images from the 3D density model, and find that the SSPA density values are close to the model inputs for the streamer core near the plane of the sky (POS) with differences generally smaller than about a factor of two; the former has the lower peak but extends more in both longitudinal and latitudinal directions than the latter. We estimate that the SSPA method may resolve the coronal density structure near the POS with angular resolution in longitude of about 50 deg. Our results confirm the suggestion that the SSI method is applicable to the solar minimum streamer (belt), as stated in some previous studies. In addition, we demonstrate that the SSPA method can be used to reconstruct the 3D coronal density, roughly in agreement with the reconstruction by tomography for a period of low solar activity (CR 2066). We suggest that the SSI method is complementary to the 3D tomographic technique in some cases, given that the development of the latter is still an ongoing research effort.

An Inverse Problem for a Class of Conditional Probability Measure-Dependent Evolution Equations

PubMed Central

Mirzaev, Inom; Byrne, Erin C.; Bortz, David M.

2016-01-01

We investigate the inverse problem of identifying a conditional probability measure in measure-dependent evolution equations arising in size-structured population modeling. We formulate the inverse problem as a least squares problem for the probability measure estimation. Using the Prohorov metric framework, we prove existence and consistency of the least squares estimates and outline a discretization scheme for approximating a conditional probability measure. For this scheme, we prove general method stability. The work is motivated by Partial Differential Equation (PDE) models of flocculation for which the shape of the post-fragmentation conditional probability measure greatly impacts the solution dynamics. To illustrate our methodology, we apply the theory to a particular PDE model that arises in the study of population dynamics for flocculating bacterial aggregates in suspension, and provide numerical evidence for the utility of the approach. PMID:28316360

Magnetic topology of Co-based inverse opal-like structures

NASA Astrophysics Data System (ADS)

Grigoryeva, N. A.; Mistonov, A. A.; Napolskii, K. S.; Sapoletova, N. A.; Eliseev, A. A.; Bouwman, W.; Byelov, D. V.; Petukhov, A. V.; Chernyshov, D. Yu.; Eckerlebe, H.; Vasilieva, A. V.; Grigoriev, S. V.

2011-08-01

The magnetic and structural properties of a cobalt inverse opal-like crystal have been studied by a combination of complementary techniques ranging from polarized neutron scattering and superconducting quantum interference device (SQUID) magnetometry to x-ray diffraction. Microradian small-angle x-ray diffraction shows that the inverse opal-like structure (OLS) synthesized by the electrochemical method fully duplicates the three-dimensional net of voids of the template artificial opal. The inverse OLS has a face-centered cubic (fcc) structure with a lattice constant of 640±10 nm and with a clear tendency to a random hexagonal close-packed structure along the [111] axes. Wide-angle x-ray powder diffraction shows that the atomic cobalt structure is described by coexistence of 95% hexagonal close-packed and 5% fcc phases. The SQUID measurements demonstrate that the inverse OLS film possesses easy-plane magnetization geometry with a coercive field of 14.0 ± 0.5 mT at room temperature. The detailed picture of the transformation of the magnetic structure under an in-plane applied field was detected with the help of small-angle diffraction of polarized neutrons. In the demagnetized state the magnetic system consists of randomly oriented magnetic domains. A complex magnetic structure appears upon application of the magnetic field, with nonhomogeneous distribution of magnetization density within the unit element of the OLS. This distribution is determined by the combined effect of the easy-plane geometry of the film and the crystallographic geometry of the opal-like structure with respect to the applied field direction.

Iterative joint inversion of in-situ stress state along Simeulue-Nias Island

NASA Astrophysics Data System (ADS)

Agustina, Anisa; Sahara, David P.; Nugraha, Andri Dian

2017-07-01

In-situ stress inversion from focal mechanisms requires knowledge of which of the two nodal planes is the fault. This is challenging, in particular, because of the inherent ambiguity of focal mechanisms the fault and the auxiliary nodal plane could not be distinguished. A relatively new inversion technique for estimating both stress and fault plane is developed by Vavryĉuk in 2014. The fault orientations are determined by applying the fault instability constraint, and the stress is calculated in iterations. In this study, this method is applied to a high-density earthquake regions, Simeulue-Batu Island. This area is interesting to be investigated because of the occurrence of the two large earthquakes, i.e. Aceh 2004 and Nias 2005 earthquake. The inversion was done based on 343 focal mechanisms data with Magnitude ≥5.5 Mw between 25th Mei 1977- 25th August 2015 from Harvard and Global Centroid Moment Tensor (GCMT) catalog. The area is divided into some grids, in which the analysis of stress orientation variation and its shape ratio is done for each grid. Stress inversion results show that there are three segments along Simeulue-Batu Island based on the variation of orientation stress σ1. The stress characteristics of each segments are discussed, i.e. shape ratio, principal stress orientation and subduction angle. Interestingly, the highest value of shape ratio is 0.93 and its association with the large earthquake Aceh 2004. This suggest that the zonation obtained in this study could also be used as a proxy for the hazard map.

The cloud radiation impact from optics simulation and airborne observation

NASA Astrophysics Data System (ADS)

Melnikova, Irina; Kuznetsov, Anatoly; Gatebe, Charles

2017-02-01

The analytical approach of inverse asymptotic formulas of the radiative transfer theory is used for solving inverse problems of cloud optics. The method has advantages because it does not impose strict constraints, but it is tied to the desired solution. Observations are accomplished in extended stratus cloudiness, above a homogeneous ocean surface. Data from NASA`s Cloud Absorption Radiometer (CAR) during two airborne experiments (SAFARI-2000 and ARCTAS-2008) were analyzed. The analytical method of inverse asymptotic formulas was used to retrieve cloud optical parameters (optical thickness, single scattering albedo and asymmetry parameter of the phase function) and ground albedo in all 8 spectral channels independently. The method is free from a priori restrictions and there is no links to parameters, and it has been applied to data set of different origin and geometry of observations. Results obtained from different airborne, satellite and ground radiative experiments appeared consistence and showed common features of values of cloud parameters and its spectral dependence (Vasiluev, Melnikova, 2004; Gatebe et al., 2014). Optical parameters, retrieved here, are used for calculation of radiative divergence, reflected and transmitted irradiance and heating rates in cloudy atmosphere, that agree with previous observational data.

Accurate reconstruction of the thermal conductivity depth profile in case hardened steel

NASA Astrophysics Data System (ADS)

Celorrio, Ricardo; Apiñaniz, Estibaliz; Mendioroz, Arantza; Salazar, Agustín; Mandelis, Andreas

2010-04-01

The problem of retrieving a nonhomogeneous thermal conductivity profile from photothermal radiometry data is addressed from the perspective of a stabilized least square fitting algorithm. We have implemented an inversion method with several improvements: (a) a renormalization of the experimental data which removes not only the instrumental factor, but the constants affecting the amplitude and the phase as well, (b) the introduction of a frequency weighting factor in order to balance the contribution of high and low frequencies in the inversion algorithm, (c) the simultaneous fitting of amplitude and phase data, balanced according to their experimental noises, (d) a modified Tikhonov regularization procedure has been introduced to stabilize the inversion, and (e) the Morozov discrepancy principle has been used to stop the iterative process automatically, according to the experimental noise, to avoid "overfitting" of the experimental data. We have tested this improved method by fitting theoretical data generated from a known conductivity profile. Finally, we have applied our method to real data obtained in a hardened stainless steel plate. The reconstructed in-depth thermal conductivity profile exhibits low dispersion, even at the deepest locations, and is in good anticorrelation with the hardness indentation test.

3D Hydraulic tomography from joint inversion of the hydraulic heads and self-potential data. (Invited)

NASA Astrophysics Data System (ADS)

Jardani, A.; Soueid Ahmed, A.; Revil, A.; Dupont, J.

2013-12-01

Pumping tests are usually employed to predict the hydraulic conductivity filed from the inversion of the head measurements. Nevertheless, the inverse problem is strongly underdetermined and a reliable imaging requires a considerable number of wells. We propose to add more information to the inversion of the heads by adding (non-intrusive) streaming potentials (SP) data. The SP corresponds to perturbations in the local electrical field caused directly by the fow of the ground water. These SP are obtained with a set of the non-polarising electrodes installed at the ground surface. We developed a geostatistical method for the estimation of the hydraulic conductivity field from measurements of hydraulic heads and SP during pumping and injection experiments. We use the adjoint state method and a recent petrophysical formulation of the streaming potential problem in which the streaming coupling coefficient is derived from the hydraulic conductivity allowed reducing of the unknown parameters. The geostatistical inverse framework is applied to three synthetic case studies with different number of the wells and electrodes used to measure the hydraulic heads and the streaming potentials. To evaluate the benefits of the incorporating of the streaming potential to the hydraulic data, we compared the cases in which the data are coupled or not to map the hydraulic conductivity. The results of the inversion revealed that a dense distribution of electrodes can be used to infer the heterogeneities in the hydraulic conductivity field. Incorporating the streaming potential information to the hydraulic head data improves the estimate of hydraulic conductivity field especially when the number of piezometers is limited.

Super-resolution Doppler beam sharpening method using fast iterative adaptive approach-based spectral estimation

NASA Astrophysics Data System (ADS)

Mao, Deqing; Zhang, Yin; Zhang, Yongchao; Huang, Yulin; Yang, Jianyu

2018-01-01

Doppler beam sharpening (DBS) is a critical technology for airborne radar ground mapping in forward-squint region. In conventional DBS technology, the narrow-band Doppler filter groups formed by fast Fourier transform (FFT) method suffer from low spectral resolution and high side lobe levels. The iterative adaptive approach (IAA), based on the weighted least squares (WLS), is applied to the DBS imaging applications, forming narrower Doppler filter groups than the FFT with lower side lobe levels. Regrettably, the IAA is iterative, and requires matrix multiplication and inverse operation when forming the covariance matrix, its inverse and traversing the WLS estimate for each sampling point, resulting in a notably high computational complexity for cubic time. We propose a fast IAA (FIAA)-based super-resolution DBS imaging method, taking advantage of the rich matrix structures of the classical narrow-band filtering. First, we formulate the covariance matrix via the FFT instead of the conventional matrix multiplication operation, based on the typical Fourier structure of the steering matrix. Then, by exploiting the Gohberg-Semencul representation, the inverse of the Toeplitz covariance matrix is computed by the celebrated Levinson-Durbin (LD) and Toeplitz-vector algorithm. Finally, the FFT and fast Toeplitz-vector algorithm are further used to traverse the WLS estimates based on the data-dependent trigonometric polynomials. The method uses the Hermitian feature of the echo autocorrelation matrix R to achieve its fast solution and uses the Toeplitz structure of R to realize its fast inversion. The proposed method enjoys a lower computational complexity without performance loss compared with the conventional IAA-based super-resolution DBS imaging method. The results based on simulations and measured data verify the imaging performance and the operational efficiency.

Significance of the model considering mixed grain-size for inverse analysis of turbidites

NASA Astrophysics Data System (ADS)

Nakao, K.; Naruse, H.; Tokuhashi, S., Sr.

2016-12-01

A method for inverse analysis of turbidity currents is proposed for application to field observations. Estimation of initial condition of the catastrophic events from field observations has been important for sedimentological researches. For instance, there are various inverse analyses to estimate hydraulic conditions from topography observations of pyroclastic flows (Rossano et al., 1996), real-time monitored debris-flow events (Fraccarollo and Papa, 2000), tsunami deposits (Jaffe and Gelfenbaum, 2007) and ancient turbidites (Falcini et al., 2009). These inverse analyses need forward models and the most turbidity current models employ uniform grain-size particles. The turbidity currents, however, are the best characterized by variation of grain-size distribution. Though there are numerical models of mixed grain-sized particles, the models have difficulty in feasibility of application to natural examples because of calculating costs (Lesshaft et al., 2011). Here we expand the turbidity current model based on the non-steady 1D shallow-water equation at low calculation costs for mixed grain-size particles and applied the model to the inverse analysis. In this study, we compared two forward models considering uniform and mixed grain-size particles respectively. We adopted inverse analysis based on the Simplex method that optimizes the initial conditions (thickness, depth-averaged velocity and depth-averaged volumetric concentration of a turbidity current) with multi-point start and employed the result of the forward model [h: 2.0 m, U: 5.0 m/s, C: 0.01%] as reference data. The result shows that inverse analysis using the mixed grain-size model found the known initial condition of reference data even if the condition where the optimization started is deviated from the true solution, whereas the inverse analysis using the uniform grain-size model requires the condition in which the starting parameters for optimization must be in quite narrow range near the solution. The uniform grain-size model often reaches to local optimum condition that is significantly different from true solution. In conclusion, we propose a method of optimization based on the model considering mixed grain-size particles, and show its application to examples of turbidites in the Kiyosumi Formation, Boso Peninsula, Japan.

Localization of synchronous cortical neural sources.

PubMed

Zerouali, Younes; Herry, Christophe L; Jemel, Boutheina; Lina, Jean-Marc

2013-03-01

Neural synchronization is a key mechanism to a wide variety of brain functions, such as cognition, perception, or memory. High temporal resolution achieved by EEG recordings allows the study of the dynamical properties of synchronous patterns of activity at a very fine temporal scale but with very low spatial resolution. Spatial resolution can be improved by retrieving the neural sources of EEG signal, thus solving the so-called inverse problem. Although many methods have been proposed to solve the inverse problem and localize brain activity, few of them target the synchronous brain regions. In this paper, we propose a novel algorithm aimed at localizing specifically synchronous brain regions and reconstructing the time course of their activity. Using multivariate wavelet ridge analysis, we extract signals capturing the synchronous events buried in the EEG and then solve the inverse problem on these signals. Using simulated data, we compare results of source reconstruction accuracy achieved by our method to a standard source reconstruction approach. We show that the proposed method performs better across a wide range of noise levels and source configurations. In addition, we applied our method on real dataset and identified successfully cortical areas involved in the functional network underlying visual face perception. We conclude that the proposed approach allows an accurate localization of synchronous brain regions and a robust estimation of their activity.

Moment Tensor Analysis of Shallow Sources

NASA Astrophysics Data System (ADS)

Chiang, A.; Dreger, D. S.; Ford, S. R.; Walter, W. R.; Yoo, S. H.

2015-12-01

A potential issue for moment tensor inversion of shallow seismic sources is that some moment tensor components have vanishing amplitudes at the free surface, which can result in bias in the moment tensor solution. The effects of the free-surface on the stability of the moment tensor method becomes important as we continue to investigate and improve the capabilities of regional full moment tensor inversion for source-type identification and discrimination. It is important to understand these free surface effects on discriminating shallow explosive sources for nuclear monitoring purposes. It may also be important in natural systems that have shallow seismicity such as volcanoes and geothermal systems. In this study, we apply the moment tensor based discrimination method to the HUMMING ALBATROSS quarry blasts. These shallow chemical explosions at approximately 10 m depth and recorded up to several kilometers distance represent rather severe source-station geometry in terms of vanishing traction issues. We show that the method is capable of recovering a predominantly explosive source mechanism, and the combined waveform and first motion method enables the unique discrimination of these events. Recovering the correct yield using seismic moment estimates from moment tensor inversion remains challenging but we can begin to put error bounds on our moment estimates using the NSS technique.

Acoustic-articulatory mapping in vowels by locally weighted regression

PubMed Central

McGowan, Richard S.; Berger, Michael A.

2009-01-01

A method for mapping between simultaneously measured articulatory and acoustic data is proposed. The method uses principal components analysis on the articulatory and acoustic variables, and mapping between the domains by locally weighted linear regression, or loess [Cleveland, W. S. (1979). J. Am. Stat. Assoc. 74, 829–836]. The latter method permits local variation in the slopes of the linear regression, assuming that the function being approximated is smooth. The methodology is applied to vowels of four speakers in the Wisconsin X-ray Microbeam Speech Production Database, with formant analysis. Results are examined in terms of (1) examples of forward (articulation-to-acoustics) mappings and inverse mappings, (2) distributions of local slopes and constants, (3) examples of correlations among slopes and constants, (4) root-mean-square error, and (5) sensitivity of formant frequencies to articulatory change. It is shown that the results are qualitatively correct and that loess performs better than global regression. The forward mappings show different root-mean-square error properties than the inverse mappings indicating that this method is better suited for the forward mappings than the inverse mappings, at least for the data chosen for the current study. Some preliminary results on sensitivity of the first two formant frequencies to the two most important articulatory principal components are presented. PMID:19813812

Exploring chemical reaction mechanisms through harmonic Fourier beads path optimization.

PubMed

Khavrutskii, Ilja V; Smith, Jason B; Wallqvist, Anders

2013-10-28

Here, we apply the harmonic Fourier beads (HFB) path optimization method to study chemical reactions involving covalent bond breaking and forming on quantum mechanical (QM) and hybrid QM∕molecular mechanical (QM∕MM) potential energy surfaces. To improve efficiency of the path optimization on such computationally demanding potentials, we combined HFB with conjugate gradient (CG) optimization. The combined CG-HFB method was used to study two biologically relevant reactions, namely, L- to D-alanine amino acid inversion and alcohol acylation by amides. The optimized paths revealed several unexpected reaction steps in the gas phase. For example, on the B3LYP∕6-31G(d,p) potential, we found that alanine inversion proceeded via previously unknown intermediates, 2-iminopropane-1,1-diol and 3-amino-3-methyloxiran-2-ol. The CG-HFB method accurately located transition states, aiding in the interpretation of complex reaction mechanisms. Thus, on the B3LYP∕6-31G(d,p) potential, the gas phase activation barriers for the inversion and acylation reactions were 50.5 and 39.9 kcal∕mol, respectively. These barriers determine the spontaneous loss of amino acid chirality and cleavage of peptide bonds in proteins. We conclude that the combined CG-HFB method further advances QM and QM∕MM studies of reaction mechanisms.

The convolutional differentiator method for numerical modelling of acoustic and elastic wavefields

NASA Astrophysics Data System (ADS)

Zhang, Zhong-Jie; Teng, Ji-Wen; Yang, Ding-Hui

1996-02-01

Based on the techniques of forward and inverse Fourier transformation, the authors discussed the design scheme of ordinary differentiator used and applied in the simulation of acoustic and elastic wavefields in isotropic media respectively. To compress Gibbs effects by truncation effectively, Hanning window is introduced in. The model computation shows that, the convolutional differentiator method has the advantages of rapidity, low requirements of computer’s inner storage and high precision, which is a potential method of numerical simulation.

Numerical approach for ECT by using boundary element method with Laplace transform

DOE Office of Scientific and Technical Information (OSTI.GOV)

Enokizono, M.; Todaka, T.; Shibao, K.

1997-03-01

This paper presents an inverse analysis by using BEM with Laplace transform. The method is applied to a simple problem in the eddy current testing (ECT). Some crack shapes in a conductive specimen are estimated from distributions of the transient eddy current on its sensing surface and magnetic flux density in the liftoff space. Because the transient behavior includes information on various frequency components, the method is applicable to the shape estimation of a comparative small crack.

Kinematic source inversions of teleseismic data based on the QUESO library for uncertainty quantification and prediction

NASA Astrophysics Data System (ADS)

Zielke, O.; McDougall, D.; Mai, P. M.; Babuska, I.

2014-12-01

One fundamental aspect of seismic hazard mitigation is gaining a better understanding of the rupture process. Because direct observation of the relevant parameters and properties is not possible, other means such as kinematic source inversions are used instead. By constraining the spatial and temporal evolution of fault slip during an earthquake, those inversion approaches may enable valuable insights in the physics of the rupture process. However, due to the underdetermined nature of this inversion problem (i.e., inverting a kinematic source model for an extended fault based on seismic data), the provided solutions are generally non-unique. Here we present a statistical (Bayesian) inversion approach based on an open-source library for uncertainty quantification (UQ) called QUESO that was developed at ICES (UT Austin). The approach has advantages with respect to deterministic inversion approaches as it provides not only a single (non-unique) solution but also provides uncertainty bounds with it. Those uncertainty bounds help to qualitatively and quantitatively judge how well constrained an inversion solution is and how much rupture complexity the data reliably resolve. The presented inversion scheme uses only tele-seismically recorded body waves but future developments may lead us towards joint inversion schemes. After giving an insight in the inversion scheme ifself (based on delayed rejection adaptive metropolis, DRAM) we explore the method's resolution potential. For that, we synthetically generate tele-seismic data, add for example different levels of noise and/or change fault plane parameterization and then apply our inversion scheme in the attempt to extract the (known) kinematic rupture model. We conclude with exemplary inverting real tele-seismic data of a recent large earthquake and compare those results with deterministically derived kinematic source models provided by other research groups.

Semiautomatic and Automatic Cooperative Inversion of Seismic and Magnetotelluric Data

NASA Astrophysics Data System (ADS)

Le, Cuong V. A.; Harris, Brett D.; Pethick, Andrew M.; Takam Takougang, Eric M.; Howe, Brendan

2016-09-01

Natural source electromagnetic methods have the potential to recover rock property distributions from the surface to great depths. Unfortunately, results in complex 3D geo-electrical settings can be disappointing, especially where significant near-surface conductivity variations exist. In such settings, unconstrained inversion of magnetotelluric data is inexorably non-unique. We believe that: (1) correctly introduced information from seismic reflection can substantially improve MT inversion, (2) a cooperative inversion approach can be automated, and (3) massively parallel computing can make such a process viable. Nine inversion strategies including baseline unconstrained inversion and new automated/semiautomated cooperative inversion approaches are applied to industry-scale co-located 3D seismic and magnetotelluric data sets. These data sets were acquired in one of the Carlin gold deposit districts in north-central Nevada, USA. In our approach, seismic information feeds directly into the creation of sets of prior conductivity model and covariance coefficient distributions. We demonstrate how statistical analysis of the distribution of selected seismic attributes can be used to automatically extract subvolumes that form the framework for prior model 3D conductivity distribution. Our cooperative inversion strategies result in detailed subsurface conductivity distributions that are consistent with seismic, electrical logs and geochemical analysis of cores. Such 3D conductivity distributions would be expected to provide clues to 3D velocity structures that could feed back into full seismic inversion for an iterative practical and truly cooperative inversion process. We anticipate that, with the aid of parallel computing, cooperative inversion of seismic and magnetotelluric data can be fully automated, and we hold confidence that significant and practical advances in this direction have been accomplished.

Extraction of human gait signatures: an inverse kinematic approach using Groebner basis theory applied to gait cycle analysis

NASA Astrophysics Data System (ADS)

Barki, Anum; Kendricks, Kimberly; Tuttle, Ronald F.; Bunker, David J.; Borel, Christoph C.

2013-05-01

This research highlights the results obtained from applying the method of inverse kinematics, using Groebner basis theory, to the human gait cycle to extract and identify lower extremity gait signatures. The increased threat from suicide bombers and the force protection issues of today have motivated a team at Air Force Institute of Technology (AFIT) to research pattern recognition in the human gait cycle. The purpose of this research is to identify gait signatures of human subjects and distinguish between subjects carrying a load to those subjects without a load. These signatures were investigated via a model of the lower extremities based on motion capture observations, in particular, foot placement and the joint angles for subjects affected by carrying extra load on the body. The human gait cycle was captured and analyzed using a developed toolkit consisting of an inverse kinematic motion model of the lower extremity and a graphical user interface. Hip, knee, and ankle angles were analyzed to identify gait angle variance and range of motion. Female subjects exhibited the most knee angle variance and produced a proportional correlation between knee flexion and load carriage.

Estimation of Bridge Height over Water from Polarimetric SAR Image Data Using Mapping and Projection Algorithm and De-Orientation Theory

NASA Astrophysics Data System (ADS)

Wang, Haipeng; Xu, Feng; Jin, Ya-Qiu; Ouchi, Kazuo

An inversion method of bridge height over water by polarimetric synthetic aperture radar (SAR) is developed. A geometric ray description to illustrate scattering mechanism of a bridge over water surface is identified by polarimetric image analysis. Using the mapping and projecting algorithm, a polarimetric SAR image of a bridge model is first simulated and shows that scattering from a bridge over water can be identified by three strip lines corresponding to single-, double-, and triple-order scattering, respectively. A set of polarimetric parameters based on the de-orientation theory is applied to analysis of three types scattering, and the thinning-clustering algorithm and Hough transform are then employed to locate the image positions of these strip lines. These lines are used to invert the bridge height. Fully polarimetric image data of airborne Pi-SAR at X-band are applied to inversion of the height and width of the Naruto Bridge in Japan. Based on the same principle, this approach is also applicable to spaceborne ALOSPALSAR single-polarization data of the Eastern Ocean Bridge in China. The results show good feasibility to realize the bridge height inversion.

Genetic algorithms and their use in Geophysical Problems

DOE Office of Scientific and Technical Information (OSTI.GOV)

Parker, Paul B.

1999-04-01

Genetic algorithms (GAs), global optimization methods that mimic Darwinian evolution are well suited to the nonlinear inverse problems of geophysics. A standard genetic algorithm selects the best or ''fittest'' models from a ''population'' and then applies operators such as crossover and mutation in order to combine the most successful characteristics of each model and produce fitter models. More sophisticated operators have been developed, but the standard GA usually provides a robust and efficient search. Although the choice of parameter settings such as crossover and mutation rate may depend largely on the type of problem being solved, numerous results show thatmore » certain parameter settings produce optimal performance for a wide range of problems and difficulties. In particular, a low (about half of the inverse of the population size) mutation rate is crucial for optimal results, but the choice of crossover method and rate do not seem to affect performance appreciably. Optimal efficiency is usually achieved with smaller (< 50) populations. Lastly, tournament selection appears to be the best choice of selection methods due to its simplicity and its autoscaling properties. However, if a proportional selection method is used such as roulette wheel selection, fitness scaling is a necessity, and a high scaling factor (> 2.0) should be used for the best performance. Three case studies are presented in which genetic algorithms are used to invert for crustal parameters. The first is an inversion for basement depth at Yucca mountain using gravity data, the second an inversion for velocity structure in the crust of the south island of New Zealand using receiver functions derived from teleseismic events, and the third is a similar receiver function inversion for crustal velocities beneath the Mendocino Triple Junction region of Northern California. The inversions demonstrate that genetic algorithms are effective in solving problems with reasonably large numbers of free parameters and with computationally expensive objective function calculations. More sophisticated techniques are presented for special problems. Niching and island model algorithms are introduced as methods to find multiple, distinct solutions to the nonunique problems that are typically seen in geophysics. Finally, hybrid algorithms are investigated as a way to improve the efficiency of the standard genetic algorithm.« less

Genetic algorithms and their use in geophysical problems

NASA Astrophysics Data System (ADS)

Parker, Paul Bradley

Genetic algorithms (GAs), global optimization methods that mimic Darwinian evolution are well suited to the nonlinear inverse problems of geophysics. A standard genetic algorithm selects the best or "fittest" models from a "population" and then applies operators such as crossover and mutation in order to combine the most successful characteristics of each model and produce fitter models. More sophisticated operators have been developed, but the standard GA usually provides a robust and efficient search. Although the choice of parameter settings such as crossover and mutation rate may depend largely on the type of problem being solved, numerous results show that certain parameter settings produce optimal performance for a wide range of problems and difficulties. In particular, a low (about half of the inverse of the population size) mutation rate is crucial for optimal results, but the choice of crossover method and rate do not seem to affect performance appreciably. Also, optimal efficiency is usually achieved with smaller (<50) populations. Lastly, tournament selection appears to be the best choice of selection methods due to its simplicity and its autoscaling properties. However, if a proportional selection method is used such as roulette wheel selection, fitness scaling is a necessity, and a high scaling factor (>2.0) should be used for the best performance. Three case studies are presented in which genetic algorithms are used to invert for crustal parameters. The first is an inversion for basement depth at Yucca mountain using gravity data, the second an inversion for velocity structure in the crust of the south island of New Zealand using receiver functions derived from teleseismic events, and the third is a similar receiver function inversion for crustal velocities beneath the Mendocino Triple Junction region of Northern California. The inversions demonstrate that genetic algorithms are effective in solving problems with reasonably large numbers of free parameters and with computationally expensive objective function calculations. More sophisticated techniques are presented for special problems. Niching and island model algorithms are introduced as methods to find multiple, distinct solutions to the nonunique problems that are typically seen in geophysics. Finally, hybrid algorithms are investigated as a way to improve the efficiency of the standard genetic algorithm.

A comparison of different interpolation methods for wind data in Central Asia

NASA Astrophysics Data System (ADS)

Reinhardt, Katja; Samimi, Cyrus

2017-04-01

For the assessment of the global climate change and its consequences, the results of computer based climate models are of central importance. The quality of these results and the validity of the derived forecasts are strongly determined by the quality of the underlying climate data. However, in many parts of the world high resolution data are not available. This is particularly true for many regions in Central Asia, where the density of climatological stations has often to be described as thinned out. Due to this insufficient data base the use of statistical methods to improve the resolution of existing climate data is of crucial importance. Only this can provide a substantial data base for a well-founded analysis of past climate changes as well as for a reliable forecast of future climate developments for the particular region. The study presented here shows a comparison of different interpolation methods for the wind components u and v for a region in Central Asia with a pronounced topography. The aim of the study is to find out whether there is an optimal interpolation method which can equally be applied for all pressure levels or if different interpolation methods have to be applied for each pressure level. The European reanalysis data Era-Interim for the years 1989 - 2015 are used as input data for the pressure levels of 850 hPa, 500 hPa and 200 hPa. In order to improve the input data, two different interpolation procedures were applied: On the one hand pure interpolation methods were used, such as inverse distance weighting and ordinary kriging. On the other hand machine learning algorithms, generalized additive models and regression kriging were applied, considering additional influencing factors, e.g. geopotential and topography. As a result it can be concluded that regression kriging provides the best results for all pressure levels, followed by support vector machine, neural networks and ordinary kriging. Inverse distance weighting showed the worst results.

A pseudospectral Legendre method for hyperbolic equations with an improved stability condition

NASA Technical Reports Server (NTRS)

Tal-Ezer, Hillel

1986-01-01

A new pseudospectral method is introduced for solving hyperbolic partial differential equations. This method uses different grid points than previously used pseudospectral methods: in fact the grid points are related to the zeroes of the Legendre polynomials. The main advantage of this method is that the allowable time step is proportional to the inverse of the number of grid points 1/N rather than to 1/n(2) (as in the case of other pseudospectral methods applied to mixed initial boundary value problems). A highly accurate time discretization suitable for these spectral methods is discussed.

A pseudospectral Legendre method for hyperbolic equations with an improved stability condition

NASA Technical Reports Server (NTRS)

Tal-Ezer, H.

1984-01-01

A new pseudospectral method is introduced for solving hyperbolic partial differential equations. This method uses different grid points than previously used pseudospectral methods: in fact the grid are related to the zeroes of the Legendre polynomials. The main advantage of this method is that the allowable time step is proportional to the inverse of the number of grid points 1/N rather than to 1/n(2) (as in the case of other pseudospectral methods applied to mixed initial boundary value problems). A highly accurate time discretization suitable for these spectral methods is discussed.

2D joint inversion of dc and scalar audio-magnetotelluric data in the evaluation of low enthalpy geothermal fields

NASA Astrophysics Data System (ADS)

Monteiro Santos, Fernando A.; Afonso, António R. Andrade; Dupis, André

2007-03-01

Audio-magnetotelluric (AMT) and resistivity (dc) surveys are often used in environmental, hydrological and geothermal evaluation. The separate interpretation of those geophysical data sets assuming two-dimensional models frequently produces ambiguous results. The joint inversion of AMT and dc data is advocated by several authors as an efficient method for reducing the ambiguity inherent to each of those methods. This paper presents results obtained from the two-dimensional joint inversion of dipole-dipole and scalar AMT data acquired in a low enthalpy geothermal field situated in a graben. The joint inverted models show a better definition of shallow and deep structures. The results show that the extension of the benefits using joint inversion depends on the number and spacing of the AMT sites. The models obtained from experimental data display a low resistivity zone (<20 Ω m) in the central part of the graben that was correlated with the geothermal reservoir. The resistivity distribution models were used to estimate the distribution of the porosity in the geothermal reservoir applying two different approaches and considering the clay minerals effect. The results suggest that the maximum porosity of the reservoir is not uniform and might be in the range of 12% to 24%.

3D imaging of soil apparent electrical conductivity from VERIS data using a 1D spatially constrained inversion algorithm

NASA Astrophysics Data System (ADS)

Jesús Moral García, Francisco; Rebollo Castillo, Francisco Javier; Monteiro Santos, Fernando

2016-04-01

Maps of apparent electrical conductivity of the soil are commonly used in precision agriculture to indirectly characterize some important properties like salinity, water, and clay content. Traditionally, these studies are made through an empirical relationship between apparent electrical conductivity and properties measured in soil samples collected at a few locations in the experimental area and at a few selected depths. Recently, some authors have used not the apparent conductivity values but the soil bulk conductivity (in 2D or 3D) calculated from measured apparent electrical conductivity through the application of an inversion method. All the published works used data collected with electromagnetic (EM) instruments. We present a new software to invert the apparent electrical conductivity data collected with VERIS 3100 and 3150 (or the more recent version with three pairs of electrodes) using the 1D spatially constrained inversion method (1D SCI). The software allows the calculation of the distribution of the bulk electrical conductivity in the survey area till a depth of 1 m. The algorithm is applied to experimental data and correlations with clay and water content have been established using soil samples collected at some boreholes. Keywords: Digital soil mapping; inversion modelling; VERIS; soil apparent electrical conductivity.

Demonstration of improved seismic source inversion method of tele-seismic body wave

NASA Astrophysics Data System (ADS)

Yagi, Y.; Okuwaki, R.

2017-12-01

Seismic rupture inversion of tele-seismic body wave has been widely applied to studies of large earthquakes. In general, tele-seismic body wave contains information of overall rupture process of large earthquake, while the tele-seismic body wave is inappropriate for analyzing a detailed rupture process of M6 7 class earthquake. Recently, the quality and quantity of tele-seismic data and the inversion method has been greatly improved. Improved data and method enable us to study a detailed rupture process of M6 7 class earthquake even if we use only tele-seismic body wave. In this study, we demonstrate the ability of the improved data and method through analyses of the 2016 Rieti, Italy earthquake (Mw 6.2) and the 2016 Kumamoto, Japan earthquake (Mw 7.0) that have been well investigated by using the InSAR data set and the field observations. We assumed the rupture occurring on a single fault plane model inferred from the moment tensor solutions and the aftershock distribution. We constructed spatiotemporal discretized slip-rate functions with patches arranged as closely as possible. We performed inversions using several fault models and found that the spatiotemporal location of large slip-rate area was robust. In the 2016 Kumamoto, Japan earthquake, the slip-rate distribution shows that the rupture propagated to southwest during the first 5 s. At 5 s after the origin time, the main rupture started to propagate toward northeast. First episode and second episode correspond to rupture propagation along the Hinagu fault and the Futagawa fault, respectively. In the 2016 Rieti, Italy earthquake, the slip-rate distribution shows that the rupture propagated to up-dip direction during the first 2 s, and then rupture propagated toward northwest. From both analyses, we propose that the spatiotemporal slip-rate distribution estimated by improved inversion method of tele-seismic body wave has enough information to study a detailed rupture process of M6 7 class earthquake.

Convergence acceleration in scattering series and seismic waveform inversion using nonlinear Shanks transformation

NASA Astrophysics Data System (ADS)

Eftekhar, Roya; Hu, Hao; Zheng, Yingcai

2018-06-01

Iterative solution process is fundamental in seismic inversions, such as in full-waveform inversions and some inverse scattering methods. However, the convergence could be slow or even divergent depending on the initial model used in the iteration. We propose to apply Shanks transformation (ST for short) to accelerate the convergence of the iterative solution. ST is a local nonlinear transformation, which transforms a series locally into another series with an improved convergence property. ST works by separating the series into a smooth background trend called the secular term versus an oscillatory transient term. ST then accelerates the convergence of the secular term. Since the transformation is local, we do not need to know all the terms in the original series which is very important in the numerical implementation. The ST performance was tested numerically for both the forward Born series and the inverse scattering series (ISS). The ST has been shown to accelerate the convergence in several examples, including three examples of forward modeling using the Born series and two examples of velocity inversion based on a particular type of the ISS. We observe that ST is effective in accelerating the convergence and it can also achieve convergence even for a weakly divergent scattering series. As such, it provides a useful technique to invert for a large-contrast medium perturbation in seismic inversion.

3D joint inversion of gravity-gradient and borehole gravity data

NASA Astrophysics Data System (ADS)

Geng, Meixia; Yang, Qingjie; Huang, Danian

2017-12-01

Borehole gravity is increasingly used in mineral exploration due to the advent of slim-hole gravimeters. Given the full-tensor gradiometry data available nowadays, joint inversion of surface and borehole data is a logical next step. Here, we base our inversions on cokriging, which is a geostatistical method of estimation where the error variance is minimised by applying cross-correlation between several variables. In this study, the density estimates are derived using gravity-gradient data, borehole gravity and known densities along the borehole as a secondary variable and the density as the primary variable. Cokriging is non-iterative and therefore is computationally efficient. In addition, cokriging inversion provides estimates of the error variance for each model, which allows direct assessment of the inverse model. Examples are shown involving data from a single borehole, from multiple boreholes, and combinations of borehole gravity and gravity-gradient data. The results clearly show that the depth resolution of gravity-gradient inversion can be improved significantly by including borehole data in addition to gravity-gradient data. However, the resolution of borehole data falls off rapidly as the distance between the borehole and the feature of interest increases. In the case where the borehole is far away from the target of interest, the inverted result can be improved by incorporating gravity-gradient data, especially all five independent components for inversion.

Atmospheric inverse modeling via sparse reconstruction

NASA Astrophysics Data System (ADS)

Hase, Nils; Miller, Scot M.; Maaß, Peter; Notholt, Justus; Palm, Mathias; Warneke, Thorsten

2017-10-01

Many applications in atmospheric science involve ill-posed inverse problems. A crucial component of many inverse problems is the proper formulation of a priori knowledge about the unknown parameters. In most cases, this knowledge is expressed as a Gaussian prior. This formulation often performs well at capturing smoothed, large-scale processes but is often ill equipped to capture localized structures like large point sources or localized hot spots. Over the last decade, scientists from a diverse array of applied mathematics and engineering fields have developed sparse reconstruction techniques to identify localized structures. In this study, we present a new regularization approach for ill-posed inverse problems in atmospheric science. It is based on Tikhonov regularization with sparsity constraint and allows bounds on the parameters. We enforce sparsity using a dictionary representation system. We analyze its performance in an atmospheric inverse modeling scenario by estimating anthropogenic US methane (CH4) emissions from simulated atmospheric measurements. Different measures indicate that our sparse reconstruction approach is better able to capture large point sources or localized hot spots than other methods commonly used in atmospheric inversions. It captures the overall signal equally well but adds details on the grid scale. This feature can be of value for any inverse problem with point or spatially discrete sources. We show an example for source estimation of synthetic methane emissions from the Barnett shale formation.

LES on Plume Dispersion in the Convective Boundary Layer Capped by a Temperature Inversion

NASA Astrophysics Data System (ADS)

Nakayama, Hiromasa; Tamura, Tetsuro; Abe, Satoshi

Large-eddy simulation (LES) is applied to the problem of plume dispersion in the spatially-developing convective boundary layer (CBL) capped by a temperature inversion. In order to generate inflow turbulence with buoyant forcing, we first, simulate the neutral boundary layer flow (NBL) in the driver region using Lund's method. At the same time, the temperature profile possessing the inversion part is imposed at the entrance of the driver region and the temperature field is calculated as a passive scalar. Next, the buoyancy effect is introduced into the flow field in the main region. We evaluate the applicability of the LES model for atmospheric dispersion in the CBL flow and compare the characteristics of plume dispersion in the CBL flow with those in the neutral boundary layer. The Richardson number based on the temperature increment across the inversion obtained by the present LES model is 22.4 and the capping effect of the temperature inversion can be captured qualitatively in the upper portion of the CBL. Characteristics of flow and temperature fields in the main portion of CBL flow are similar to those of previous experiments[1],[2] and observations[3]. Concerning dispersion behavior, we also find that mean concentrations decrease immediately above the inversion height and the peak values of r.m.s concentrations are located near the inversion height at larger distances from the point source.

Guidance of Nonlinear Nonminimum-Phase Dynamic Systems

NASA Technical Reports Server (NTRS)

Devasia, Santosh

1996-01-01

The research work has advanced the inversion-based guidance theory for: systems with non-hyperbolic internal dynamics; systems with parameter jumps; and systems where a redesign of the output trajectory is desired. A technique to achieve output tracking for nonminimum phase linear systems with non-hyperbolic and near non-hyperbolic internal dynamics was developed. This approach integrated stable inversion techniques, that achieve exact-tracking, with approximation techniques, that modify the internal dynamics to achieve desirable performance. Such modification of the internal dynamics was used (a) to remove non-hyperbolicity which is an obstruction to applying stable inversion techniques and (b) to reduce large preactuation times needed to apply stable inversion for near non-hyperbolic cases. The method was applied to an example helicopter hover control problem with near non-hyperbolic internal dynamics for illustrating the trade-off between exact tracking and reduction of preactuation time. Future work will extend these results to guidance of nonlinear non-hyperbolic systems. The exact output tracking problem for systems with parameter jumps was considered. Necessary and sufficient conditions were derived for the elimination of switching-introduced output transient. While previous works had studied this problem by developing a regulator that maintains exact tracking through parameter jumps (switches), such techniques are, however, only applicable to minimum-phase systems. In contrast, our approach is also applicable to nonminimum-phase systems and leads to bounded but possibly non-causal solutions. In addition, for the case when the reference trajectories are generated by an exosystem, we developed an exact-tracking controller which could be written in a feedback form. As in standard regulator theory, we also obtained a linear map from the states of the exosystem to the desired system state, which was defined via a matrix differential equation.

Advantages of the full-waveform inversion: real data example from the Polish Basin

NASA Astrophysics Data System (ADS)

Malinowski, M.; Operto, S.

2006-12-01

Modern acquisition techniques allow us to gather high-density seismic data even in case of crustal-scale investigations. In combination with increasing availability of computational resources (eg. PC clusters), this allow us to image the Earth's structure on much finer scale than offered by ray-theory based methods (like travel time tomography) by applying the full waveform inversion/tomography method (FWT). Recently, the FWT method was for the first time successfully applied to the real wide-aperture data: 100-km long OBS profile (Operto et al. 2006) and a 15-km long land profile (Operto et al. 2004, Ravaut et al., 2004). We present the results of the application of the FWT method to the GRUNDY 2003 experiment data, which is standing in between the scale of the mentioned datasets. This project was targeted at recognition of the pre-Zechstein strata within the Polish Basin. For a successful investigations relatively low-frequencies and wide-apertures were used. In the 50 by 10 km rectangular area ca. 800 RefTek 125 "Texan" stations with 4.5 Hz geophones were deployed, forming high-density central line (receiver spacing 100 m) and additional 4 parallel profiles. Previously the data were modelled using conventional methods: CDP processing and traveltime tomography. In order to utilise secondary arrivals, we used the frequency-domain FWT method of Pratt et al. (1998). The wide-aperture content of our data leads to a redundant wavenumber coverage which can be partially removed without loss of information by limiting the inversion to few frequencies only. The inversion proceeds by stepping from low to high frequencies and uses the model inferred for one component as the starting one for the next frequency. Before full waveform inversion, the data were preprocessed by QC editing, spectral deconvolution (whitening), bandpass filtering and muting in narrow window around the first arrival. Traveltime tomogram was choosen as the starting model for 2D waveform inversion. The model size was 50x10 km with 25 m FD grid step. We have selected 10 frequencies from 4 to 13 Hz. For each frequency 10 iterations were computed (on a Linux cluster). There is a clear improvement in resolution of the obtained tomographic images by exploiting the full wavefield. The model allows to predict also fairly well the observed seismograms and is consistent with both the geological horizons projected from industrial reflection profiles as well as check-shot velocity log. Benefits of FWT in application to our data seems to be clear: in one step, without the need for performing the forward raytracing modelling, we gained both the quasi-structural image (perturbational model) and the detailed velocity model. In this way we fully exploited the broad range of recorded offsets and reflection angles from pre- to postcritical ones for a successful imaging beneath the Zechstein strata.

Review of inversion techniques using analysis of different tests

NASA Astrophysics Data System (ADS)

Smaglichenko, T. A.

2012-04-01

Tomographic techniques are tools, which estimate the Earth's deep interior by inverting seismic data. Reliability of visualization provides adequate understanding of geodynamic processes for prediction of natural hazard and protection of environment. This presentation focuses on two interrelated factors, which affect on the reliability namely: particularities of geophysical medium and strategy for choice of inversion method. Three main techniques are under review. First, the standard LSQR algorithm is derived directly by the Lanczos algebraic application. The Double Difference tomography widely incorporates this algorithm and its expansion. Next, the CSSA technique, or method of subtraction has been introduced into seismology by Nikolaev et al. in 1985. This method got farther development in 2003 (Smaglichenko et al.) as the coordinate method of possible directions, which has been already known in the theory of numerical methods. And finally, the new Differentiated Approach (DA) tomography that has been recently developed by the author for seismology and introduced into applied mathematics as the modification of Gaussian elimination. Different test models are presented by detecting various properties of the medium and having a value for the mining sector as well for prediction of seismic activity. They are: 1) checker-board resolution test; 2) the single anomalous block surrounded by an uniform zone; 3) the large-size structure; 4) the most complicated case, when the model consist of contrast layers and the observation response is equal zero value. The geometry of experiment for all models is given in the note of Leveque et al., 1993. It was assumed that errors in experimental data are in limits of pre-assigned accuracy. The testing showed that LSQR is effective, when the small-size structure (1) is retrieved, while CSSA works faster under reconstruction of the separated anomaly (2). The large-size structure (3) can be reconstructed applying DA, which uses both Lanczos's method and CSSA as composed parts of the inversion process. Difficulty of the model of contrast layers (4) can be overcome with a priori information that could allow the DA implementation. The testing leads us to the following conclusion. Careful analyze and weighted assumptions about characteristics of the being investigated medium should be done before start of data inversion. The choice of suitable technique will provide reliability of solution. Nevertheless, DA is preferred in the case of noisy and large data.

The Natural-CCD Algorithm, a Novel Method to Solve the Inverse Kinematics of Hyper-redundant and Soft Robots.

PubMed

Martín, Andrés; Barrientos, Antonio; Del Cerro, Jaime

2018-03-22

This article presents a new method to solve the inverse kinematics problem of hyper-redundant and soft manipulators. From an engineering perspective, this kind of robots are underdetermined systems. Therefore, they exhibit an infinite number of solutions for the inverse kinematics problem, and to choose the best one can be a great challenge. A new algorithm based on the cyclic coordinate descent (CCD) and named as natural-CCD is proposed to solve this issue. It takes its name as a result of generating very harmonious robot movements and trajectories that also appear in nature, such as the golden spiral. In addition, it has been applied to perform continuous trajectories, to develop whole-body movements, to analyze motion planning in complex environments, and to study fault tolerance, even for both prismatic and rotational joints. The proposed algorithm is very simple, precise, and computationally efficient. It works for robots either in two or three spatial dimensions and handles a large amount of degrees-of-freedom. Because of this, it is aimed to break down barriers between discrete hyper-redundant and continuum soft robots.

Learning the inverse kinetics of an octopus-like manipulator in three-dimensional space.

PubMed

Giorelli, M; Renda, F; Calisti, M; Arienti, A; Ferri, G; Laschi, C

2015-05-13

This work addresses the inverse kinematics problem of a bioinspired octopus-like manipulator moving in three-dimensional space. The bioinspired manipulator has a conical soft structure that confers the ability of twirling around objects as a real octopus arm does. Despite the simple design, the soft conical shape manipulator driven by cables is described by nonlinear differential equations, which are difficult to solve analytically. Since exact solutions of the equations are not available, the Jacobian matrix cannot be calculated analytically and the classical iterative methods cannot be used. To overcome the intrinsic problems of methods based on the Jacobian matrix, this paper proposes a neural network learning the inverse kinematics of a soft octopus-like manipulator driven by cables. After the learning phase, a feed-forward neural network is able to represent the relation between manipulator tip positions and forces applied to the cables. Experimental results show that a desired tip position can be achieved in a short time, since heavy computations are avoided, with a degree of accuracy of 8% relative average error with respect to the total arm length.

Geoid Recovery Using Geophysical Inverse Theory Applied to Satellite to Satellite Tracking Data

NASA Technical Reports Server (NTRS)

Gaposchkin, E. M.

2000-01-01

This report describes a new method for determination of the geopotential, or the equivalent geoid. It is based on Satellite-to-Satellite Tracking (SST) of two co-orbiting low earth satellites separated by a few hundred kilometers. The analysis is aimed at the GRACE Mission, though it is generally applicable to any SST data. It is proposed that the SST be viewed as a mapping mission. That is, the result will be maps of the geoid or gravity, as contrasted with determination of spherical harmonics or Fourier coefficients. A method has been developed, based on Geophysical Inverse Theory (GIT), that can provide maps at a prescribed (desired) resolution and the corresponding error map from the SST data. This computation can be done area by area avoiding simultaneous recovery of all the geopotential information. The necessary elements of potential theory, celestial mechanics, and Geophysical Inverse Theory are described, a computation architecture is described, and the results of several simulations presented. Centimeter accuracy geoids with 50 to 100 km resolution can be recovered with a 30 to 60 day mission.

Study on the determination and chiral inversion of R-salbutamol in human plasma and urine by liquid chromatography-tandem mass spectrometry.

PubMed

Zhou, Ting; Zeng, Jing; Liu, Shan; Zhao, Ting; Wu, Jie; Lai, Wenshi; He, Mingzhi; Xu, Beining; Qu, Shanshan; Xu, Ling; Tan, Wen

2015-10-01

The chiral inversion has been a concerned issue during the research and development of a chiral drug. In this study, a sensitive chiral liquid chromatography-tandem mass spectrometry (LC-MS/MS) method was developed for determination of salbutamol enantiomers in human plasma and urine. The chiral inversion mechanism of R-salbutamol was fully investigated for the first time by studying the effects of physicochemical factors, including pH, temperature and time. A fitted model to predict the chiral inversion ratio of R-salbutamol was proposed using a Box-Behnken design. All the samples were separated on an Astec Chirobiotic T column and detected by a tandem mass spectrometer in multiple reaction monitoring mode. Lower limit of quantification of 0.100ng/mL was achieved under the optimized conditions. The method was fully validated and successfully applied to the clinical pharmacokinetic study of R-salbutamol in healthy volunteers. Chiral inversion of R-salbutamol to S-salbutamol has been detected in urine samples. The results indicated that pH and temperature were two dominant factors that caused the chiral inversion of R-salbutamol, which should be taken into consideration during the analysis of chiral drugs. The chiral inversion of R-salbutamol determined in this study was confirmed resulted from the gastric acid in stomach rather than caused by the analysis conditions. Moreover, the calculated results of the fitted model matched very well with the enantioselective pharmacokinetic study of R-salbutamol, and the individual difference of the chiral inversion ratio of R-salbutamol was related to the individual gastric environment. On the basis of the results, this study provides important and concrete information not only for the chiral analysis but also for the metabolism research of chiral drugs. Copyright © 2015 Elsevier B.V. All rights reserved.

Location of Sinabung volcano magma chamber on 2013 using lavenberg-marquardt inversion scheme

NASA Astrophysics Data System (ADS)

Kumalasari, R.; Srigutomo, W.; Djamal, M.; Meilano, I.; Gunawan, H.

2018-05-01

Sinabung Volcano has been monitoring using GPS after his eruption on August 2010. We Applied Levenberg-Marquardt Inversion Scheme to GPS data on 2013 because deformation of Sinabung Volcano in this year show an inflation and deflation, first we applied Levenberg-Marquardt to velocity data on 23 January 2013 then we applied Levenberg-Marquardt Inversion Scheme to data on 31 December 2013. From our analysis we got the depth of the pressure source modeling results that indicate some possibilities that Sinabung has a deep magma chamber about 15km and also shallow magma chamber about 1km from the surface.

Removal of Stationary Sinusoidal Noise from Random Vibration Signals.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Johnson, Brian; Cap, Jerome S.

In random vibration environments, sinusoidal line noise may appear in the vibration signal and can affect analysis of the resulting data. We studied two methods which remove stationary sine tones from random noise: a matrix inversion algorithm and a chirp-z transform algorithm. In addition, we developed new methods to determine the frequency of the tonal noise. The results show that both of the removal methods can eliminate sine tones in prefabricated random vibration data when the sine-to-random ratio is at least 0.25. For smaller ratios down to 0.02 only the matrix inversion technique can remove the tones, but the metricsmore » to evaluate its effectiveness also degrade. We also found that using fast Fourier transforms best identified the tonal noise, and determined that band-pass-filtering the signals prior to the process improved sine removal. When applied to actual vibration test data, the methods were not as effective at removing harmonic tones, which we believe to be a result of mixed-phase sinusoidal noise.« less

Invisibility problem in acoustics, electromagnetism and heat transfer. Inverse design method

NASA Astrophysics Data System (ADS)

Alekseev, G.; Tokhtina, A.; Soboleva, O.

2017-10-01

Two approaches (direct design and inverse design methods) for solving problems of designing devices providing invisibility of material bodies of detection using different physical fields - electromagnetic, acoustic and static are discussed. The second method is applied for solving problems of designing cloaking devices for the 3D stationary thermal scattering model. Based on this method the design problems under study are reduced to respective control problems. The material parameters (radial and tangential heat conductivities) of the inhomogeneous anisotropic medium filling the thermal cloak and the density of auxiliary heat sources play the role of controls. A unique solvability of direct thermal scattering problem in the Sobolev space is proved and the new estimates of solutions are established. Using these results, the solvability of control problem is proved and the optimality system is derived. Based on analysis of optimality system, the stability estimates of optimal solutions are established and numerical algorithms for solving particular thermal cloaking problem are proposed.

Probabilistic inversion with graph cuts: Application to the Boise Hydrogeophysical Research Site

NASA Astrophysics Data System (ADS)

Pirot, Guillaume; Linde, Niklas; Mariethoz, Grégoire; Bradford, John H.

2017-02-01

Inversion methods that build on multiple-point statistics tools offer the possibility to obtain model realizations that are not only in agreement with field data, but also with conceptual geological models that are represented by training images. A recent inversion approach based on patch-based geostatistical resimulation using graph cuts outperforms state-of-the-art multiple-point statistics methods when applied to synthetic inversion examples featuring continuous and discontinuous property fields. Applications of multiple-point statistics tools to field data are challenging due to inevitable discrepancies between actual subsurface structure and the assumptions made in deriving the training image. We introduce several amendments to the original graph cut inversion algorithm and present a first-ever field application by addressing porosity estimation at the Boise Hydrogeophysical Research Site, Boise, Idaho. We consider both a classical multi-Gaussian and an outcrop-based prior model (training image) that are in agreement with available porosity data. When conditioning to available crosshole ground-penetrating radar data using Markov chain Monte Carlo, we find that the posterior realizations honor overall both the characteristics of the prior models and the geophysical data. The porosity field is inverted jointly with the measurement error and the petrophysical parameters that link dielectric permittivity to porosity. Even though the multi-Gaussian prior model leads to posterior realizations with higher likelihoods, the outcrop-based prior model shows better convergence. In addition, it offers geologically more realistic posterior realizations and it better preserves the full porosity range of the prior.

Mass change distribution inverted from space-borne gravimetric data using a Monte Carlo method

NASA Astrophysics Data System (ADS)

Zhou, X.; Sun, X.; Wu, Y.; Sun, W.

2017-12-01

Mass estimate plays a key role in using temporally satellite gravimetric data to quantify the terrestrial water storage change. GRACE (Gravity Recovery and Climate Experiment) only observes the low degree gravity field changes, which can be used to estimate the total surface density or equivalent water height (EWH) variation, with a limited spatial resolution of 300 km. There are several methods to estimate the mass variation in an arbitrary region, such as averaging kernel, forward modelling and mass concentration (mascon). Mascon method can isolate the local mass from the gravity change at a large scale through solving the observation equation (objective function) which represents the relationship between unknown masses and the measurements. To avoid the unreasonable local mass inverted from smoothed gravity change map, regularization has to be used in the inversion. We herein give a Markov chain Monte Carlo (MCMC) method to objectively determine the regularization parameter for the non-negative mass inversion problem. We first apply this approach to the mass inversion from synthetic data. Result show MCMC can effectively reproduce the local mass variation taking GRACE measurement error into consideration. We then use MCMC to estimate the ground water change rate of North China Plain from GRACE gravity change rate from 2003 to 2014 under a supposition of the continuous ground water loss in this region. Inversion result show that the ground water loss rate in North China Plain is 7.6±0.2Gt/yr during past 12 years which is coincident with that from previous researches.

Common Structure in Different Physical Properties: Electrical Conductivity and Surface Waves Phase Velocity

NASA Astrophysics Data System (ADS)

Mandolesi, E.; Jones, A. G.; Roux, E.; Lebedev, S.

2009-12-01

Recently different studies were undertaken on the correlation between diverse geophysical datasets. Magnetotelluric (MT) data are used to map the electrical conductivity structure behind the Earth, but one of the problems in MT method is the lack in resolution in mapping zones beneath a region of high conductivity. Joint inversion of different datasets in which a common structure is recognizable reduces non-uniqueness and may improve the quality of interpretation when different dataset are sensitive to different physical properties with an underlined common structure. A common structure is recognized if the change of physical properties occur at the same spatial locations. Common structure may be recognized in 1D inversion of seismic and MT datasets, and numerous authors show that also 2D common structure may drive to an improvement of inversion quality while dataset are jointly inverted. In this presentation a tool to constrain MT 2D inversion with phase velocity of surface wave seismic data (SW) is proposed and is being developed and tested on synthetic data. Results obtained suggest that a joint inversion scheme could be applied with success along a section profile for which data are compatible with a 2D MT model.

Comparison of gravimetric and mantle flow solutions for sub-lithopsheric stress modeling and their combination

NASA Astrophysics Data System (ADS)

Eshagh, Mehdi; Steinberger, Bernhard; Tenzer, Robert; Tassara, Andrés

2018-05-01

Based on Hager and O'Connell's solution to mantle flow equations, the stresses induced by mantle convection are determined using the density and viscosity structure in addition to topographic data and a plate velocity model. The solution to mantle flow equations requires the knowledge of mantle properties that are typically retrieved from seismic information. Large parts of the world are, however, not yet covered sufficiently by seismic surveys. An alternative method of modeling the stress field was introduced by Runcorn. He formulated a direct relation between the stress field and gravity data, while adopting several assumptions, particularly disregarding the toroidal mantle flow component and mantle viscosity variations. A possible way to overcome theoretical deficiencies of Runcorn's theory as well as some practical limitations of applying Hager and O'Connell's theory (in the absence of seismic data) is to combine these two methods. In this study, we apply a least-squares analysis to combine these two methods based on the gravity data inversion constraint on mantle flow equations. In particular, we use vertical gravity gradients from the Gravity field and steady state Ocean Circulation Explorer that are corrected for the gravitational contribution of crustal density heterogeneities prior to applying a localized gravity-gradient inversion. This gravitational contribution is estimated based on combining the Vening Meinesz-Moritz and flexural isostatic theories. Moreover, we treat the non-isostatic effect implicitly by applying a band-limited kernel of the integral equation during the inversion. In numerical studies of modeling, the stress field within the South American continental lithosphere we compare the results obtained after applying Runcorn and Hager and O'Connell's methods as well as their combination. The results show that, according to Hager and O'Connell's (mantle flow) solution, the maximum stress intensity is inferred under the northern Andes. Additional large stress anomalies are detected along the central and southern Andes, while stresses under most of old, stable cratonic formations are much less pronounced or absent. A prevailing stress-vector orientation realistically resembles a convergent mantle flow and downward currents under continental basins that separate Andean Orogeny from the Amazonian Shield and adjacent cratons. Runcorn's (gravimetric) solution, on the other hand, reflects a tectonic response of the lithosphere to mantle flow, with the maximum stress intensity detected along the subduction zone between the Nazca and Altiplano plates and along the convergent tectonic margin between the Altiplano and South American plates. The results also reveal a very close agreement between the results obtained from the combined and Hager and O'Connell's solutions.

On epicardial potential reconstruction using regularization schemes with the L1-norm data term.

PubMed

Shou, Guofa; Xia, Ling; Liu, Feng; Jiang, Mingfeng; Crozier, Stuart

2011-01-07

The electrocardiographic (ECG) inverse problem is ill-posed and usually solved by regularization schemes. These regularization methods, such as the Tikhonov method, are often based on the L2-norm data and constraint terms. However, L2-norm-based methods inherently provide smoothed inverse solutions that are sensitive to measurement errors, and also lack the capability of localizing and distinguishing multiple proximal cardiac electrical sources. This paper presents alternative regularization schemes employing the L1-norm data term for the reconstruction of epicardial potentials (EPs) from measured body surface potentials (BSPs). During numerical implementation, the iteratively reweighted norm algorithm was applied to solve the L1-norm-related schemes, and measurement noises were considered in the BSP data. The proposed L1-norm data term-based regularization schemes (with L1 and L2 penalty terms of the normal derivative constraint (labelled as L1TV and L1L2)) were compared with the L2-norm data terms (Tikhonov with zero-order and normal derivative constraints, labelled as ZOT and FOT, and the total variation method labelled as L2TV). The studies demonstrated that, with averaged measurement noise, the inverse solutions provided by the L1L2 and FOT algorithms have less relative error values. However, when larger noise occurred in some electrodes (for example, signal lost during measurement), the L1TV and L1L2 methods can obtain more accurate EPs in a robust manner. Therefore the L1-norm data term-based solutions are generally less perturbed by measurement noises, suggesting that the new regularization scheme is promising for providing practical ECG inverse solutions.

Fast nonlinear gravity inversion in spherical coordinates with application to the South American Moho

NASA Astrophysics Data System (ADS)

Uieda, Leonardo; Barbosa, Valéria C. F.

2017-01-01

Estimating the relief of the Moho from gravity data is a computationally intensive nonlinear inverse problem. What is more, the modelling must take the Earths curvature into account when the study area is of regional scale or greater. We present a regularized nonlinear gravity inversion method that has a low computational footprint and employs a spherical Earth approximation. To achieve this, we combine the highly efficient Bott's method with smoothness regularization and a discretization of the anomalous Moho into tesseroids (spherical prisms). The computational efficiency of our method is attained by harnessing the fact that all matrices involved are sparse. The inversion results are controlled by three hyperparameters: the regularization parameter, the anomalous Moho density-contrast, and the reference Moho depth. We estimate the regularization parameter using the method of hold-out cross-validation. Additionally, we estimate the density-contrast and the reference depth using knowledge of the Moho depth at certain points. We apply the proposed method to estimate the Moho depth for the South American continent using satellite gravity data and seismological data. The final Moho model is in accordance with previous gravity-derived models and seismological data. The misfit to the gravity and seismological data is worse in the Andes and best in oceanic areas, central Brazil and Patagonia, and along the Atlantic coast. Similarly to previous results, the model suggests a thinner crust of 30-35 km under the Andean foreland basins. Discrepancies with the seismological data are greatest in the Guyana Shield, the central Solimões and Amazonas Basins, the Paraná Basin, and the Borborema province. These differences suggest the existence of crustal or mantle density anomalies that were unaccounted for during gravity data processing.

Optimization of flow-sensitive alternating inversion recovery (FAIR) for perfusion functional MRI of rodent brain.

PubMed

Nasrallah, Fatima A; Lee, Eugene L Q; Chuang, Kai-Hsiang

2012-11-01

Arterial spin labeling (ASL) MRI provides a noninvasive method to image perfusion, and has been applied to map neural activation in the brain. Although pulsed labeling methods have been widely used in humans, continuous ASL with a dedicated neck labeling coil is still the preferred method in rodent brain functional MRI (fMRI) to maximize the sensitivity and allow multislice acquisition. However, the additional hardware is not readily available and hence its application is limited. In this study, flow-sensitive alternating inversion recovery (FAIR) pulsed ASL was optimized for fMRI of rat brain. A practical challenge of FAIR is the suboptimal global inversion by the transmit coil of limited dimensions, which results in low effective labeling. By using a large volume transmit coil and proper positioning to optimize the body coverage, the perfusion signal was increased by 38.3% compared with positioning the brain at the isocenter. An additional 53.3% gain in signal was achieved using optimized repetition and inversion times compared with a long TR. Under electrical stimulation to the forepaws, a perfusion activation signal change of 63.7 ± 6.3% can be reliably detected in the primary somatosensory cortices using single slice or multislice echo planar imaging at 9.4 T. This demonstrates the potential of using pulsed ASL for multislice perfusion fMRI in functional and pharmacological applications in rat brain. Copyright © 2012 John Wiley & Sons, Ltd.

Numerical simulations of induction and MWD logging tools and data inversion method with X-window interface on a UNIX workstation

NASA Astrophysics Data System (ADS)

Tian, Xiang-Dong

The purpose of this research is to simulate induction and measuring-while-drilling (MWD) logs. In simulation of logs, there are two tasks. The first task, the forward modeling procedure, is to compute the logs from known formation. The second task, the inversion procedure, is to determine the unknown properties of the formation from the measured field logs. In general, the inversion procedure requires the solution of a forward model. In this study, a stable numerical method to simulate induction and MWD logs is presented. The proposed algorithm is based on a horizontal eigenmode expansion method. Vertical propagation of modes is modeled by a three-layer module. The multilayer cases are treated as a cascade of these modules. The mode tracing algorithm possesses stable characteristics that are superior to other methods. This method is applied to simulate the logs in the formations with both vertical and horizontal layers, and also used to study the groove effects of the MWD tool. The results are very good. Two-dimensional inversion of induction logs is an nonlinear problem. Nonlinear functions of the apparent conductivity are expanded into a Taylor series. After truncating the high order terms in this Taylor series, the nonlinear functions are linearized. An iterative procedure is then devised to solve the inversion problem. In each iteration, the Jacobian matrix is calculated, and a small variation computed using the least-squares method is used to modify the background medium. Finally, the inverted medium is obtained. The horizontal eigenstate method is used to solve the forward problem. It is found that a good inverted formation can be obtained by using measurements. In order to help the user simulate the induction logs conveniently, a Wellog Simulator, based on the X-window system, is developed. The application software (FORTRAN codes) embedded in the Simulator is designed to simulate the responses of the induction tools in the layered formation with dipping beds. The graphic user-interface part of the Wellog Simulator is implemented with C and Motif. Through the user interface, the user can prepare the simulation data, select the tools, simulate the logs and plot the results.

Effective CO2 sequestration monitoring using joint inversion result of seismic and electromagnetic data

NASA Astrophysics Data System (ADS)

Noh, K.; Jeong, S.; Seol, S. J.; Byun, J.; Kwon, T.

2015-12-01

Man-made carbon dioxide (CO2) released into the atmosphere is a significant contributor to the greenhouse gas effect and related global warming. Sequestration of CO2 into saline aquifers has been proposed as one of the most practical options of all geological sequestration possibilities. During CO2 geological sequestration, monitoring is indispensable to delineate the change of CO2 saturation and migration of CO2 in the subsurface. Especially, monitoring of CO2 saturation in aquifers provides useful information for determining amount of injected CO2. Seismic inversion can provide the migration of CO2 plume with high resolution because velocity is reduced when CO2 replaces the pore fluid during CO2 injection. However, the estimation of CO2 saturation using the seismic method is difficult due to the lower sensitivity of the velocity to the saturation when the CO2 saturation up to 20%. On the other hand, marine controlled-source EM (mCSEM) inversion is sensitive to the resistivity changes resulting from variations in CO2 saturation, even though it has poor resolution than seismic method. In this study, we proposed an effective CO2 sequestration monitoring method using joint inversion of seismic and mCSEM data based on a cross-gradient constraint. The method was tested with realistic CO2 injection models in a deep brine aquifer beneath a shallow sea which is selected with consideration for the access convenience for the installation of source and receiver and an environmental safety. Resistivity images of CO2 plume by the proposed method for different CO2 injection stages have been significantly improved over those obtained from individual EM inversion. In addition, we could estimate a reliable CO2 saturation by rock physics model (RPM) using the P-wave velocity and the improved resistivity. The proposed method is a basis of three-dimensional estimation of reservoir parameters such as porosity and fluid saturation, and the method can be also applied for detecting a reservoir and calculating the accurate oil and gas reserves.

Technical Note: Atmospheric CO2 inversions on the mesoscale using data-driven prior uncertainties: methodology and system evaluation

NASA Astrophysics Data System (ADS)

Kountouris, Panagiotis; Gerbig, Christoph; Rödenbeck, Christian; Karstens, Ute; Koch, Thomas Frank; Heimann, Martin

2018-03-01

Atmospheric inversions are widely used in the optimization of surface carbon fluxes on a regional scale using information from atmospheric CO2 dry mole fractions. In many studies the prior flux uncertainty applied to the inversion schemes does not directly reflect the true flux uncertainties but is used to regularize the inverse problem. Here, we aim to implement an inversion scheme using the Jena inversion system and applying a prior flux error structure derived from a model-data residual analysis using high spatial and temporal resolution over a full year period in the European domain. We analyzed the performance of the inversion system with a synthetic experiment, in which the flux constraint is derived following the same residual analysis but applied to the model-model mismatch. The synthetic study showed a quite good agreement between posterior and true fluxes on European, country, annual and monthly scales. Posterior monthly and country-aggregated fluxes improved their correlation coefficient with the known truth by 7 % compared to the prior estimates when compared to the reference, with a mean correlation of 0.92. The ratio of the SD between the posterior and reference and between the prior and reference was also reduced by 33 % with a mean value of 1.15. We identified temporal and spatial scales on which the inversion system maximizes the derived information; monthly temporal scales at around 200 km spatial resolution seem to maximize the information gain.

Identifing Atmospheric Pollutant Sources Using Artificial Neural Networks

NASA Astrophysics Data System (ADS)

Paes, F. F.; Campos, H. F.; Luz, E. P.; Carvalho, A. R.

2008-05-01

The estimation of the area source pollutant strength is a relevant issue for atmospheric environment. This characterizes an inverse problem in the atmospheric pollution dispersion. In the inverse analysis, an area source domain is considered, where the strength of such area source term is assumed unknown. The inverse problem is solved by using a supervised artificial neural network: multi-layer perceptron. The conection weights of the neural network are computed from delta rule - learning process. The neural network inversion is compared with results from standard inverse analysis (regularized inverse solution). In the regularization method, the inverse problem is formulated as a non-linear optimization approach, whose the objective function is given by the square difference between the measured pollutant concentration and the mathematical models, associated with a regularization operator. In our numerical experiments, the forward problem is addressed by a source-receptor scheme, where a regressive Lagrangian model is applied to compute the transition matrix. The second order maximum entropy regularization is used, and the regularization parameter is calculated by the L-curve technique. The objective function is minimized employing a deterministic scheme (a quasi-Newton algorithm) [1] and a stochastic technique (PSO: particle swarm optimization) [2]. The inverse problem methodology is tested with synthetic observational data, from six measurement points in the physical domain. The best inverse solutions were obtained with neural networks. References: [1] D. R. Roberti, D. Anfossi, H. F. Campos Velho, G. A. Degrazia (2005): Estimating Emission Rate and Pollutant Source Location, Ciencia e Natura, p. 131-134. [2] E.F.P. da Luz, H.F. de Campos Velho, J.C. Becceneri, D.R. Roberti (2007): Estimating Atmospheric Area Source Strength Through Particle Swarm Optimization. Inverse Problems, Desing and Optimization Symposium IPDO-2007, April 16-18, Miami (FL), USA, vol 1, p. 354-359.

The Source Inversion Validation (SIV) Initiative: A Collaborative Study on Uncertainty Quantification in Earthquake Source Inversions

NASA Astrophysics Data System (ADS)

Mai, P. M.; Schorlemmer, D.; Page, M.

2012-04-01

Earthquake source inversions image the spatio-temporal rupture evolution on one or more fault planes using seismic and/or geodetic data. Such studies are critically important for earthquake seismology in general, and for advancing seismic hazard analysis in particular, as they reveal earthquake source complexity and help (i) to investigate earthquake mechanics; (ii) to develop spontaneous dynamic rupture models; (iii) to build models for generating rupture realizations for ground-motion simulations. In applications (i - iii), the underlying finite-fault source models are regarded as "data" (input information), but their uncertainties are essentially unknown. After all, source models are obtained from solving an inherently ill-posed inverse problem to which many a priori assumptions and uncertain observations are applied. The Source Inversion Validation (SIV) project is a collaborative effort to better understand the variability between rupture models for a single earthquake (as manifested in the finite-source rupture model database) and to develop robust uncertainty quantification for earthquake source inversions. The SIV project highlights the need to develop a long-standing and rigorous testing platform to examine the current state-of-the-art in earthquake source inversion, and to develop and test novel source inversion approaches. We will review the current status of the SIV project, and report the findings and conclusions of the recent workshops. We will briefly discuss several source-inversion methods, how they treat uncertainties in data, and assess the posterior model uncertainty. Case studies include initial forward-modeling tests on Green's function calculations, and inversion results for synthetic data from spontaneous dynamic crack-like strike-slip earthquake on steeply dipping fault, embedded in a layered crustal velocity-density structure.

Evaluation of Inversion Methods Applied to Ionospheric ro Observations

NASA Astrophysics Data System (ADS)

Rios Caceres, Arq. Estela Alejandra; Rios, Victor Hugo; Guyot, Elia

The new technique of radio-occultation can be used to study the Earth's ionosphere. The retrieval processes of ionospheric profiling from radio occultation observations usually assume spherical symmetry of electron density distribution at the locality of occultation and use the Abel integral transform to invert the measured total electron content (TEC) values. This pa-per presents a set of ionospheric profiles obtained from SAC-C satellite with the Abel inversion technique. The effects of the ionosphere on the GPS signal during occultation, such as bending and scintillation, are examined. Electron density profiles are obtained using the Abel inversion technique. Ionospheric radio occultations are validated using vertical profiles of electron con-centration from inverted ionograms , obtained from ionosonde sounding in the vicinity of the occultation. Results indicate that the Abel transform works well in the mid-latitudes during the daytime, but is less accurate during the night-time.

Control of a flexible bracing manipulator: Integration of current research work to realize the bracing manipulator

NASA Technical Reports Server (NTRS)

Kwon, Dong-Soo

1991-01-01

All research results about flexible manipulator control were integrated to show a control scenario of a bracing manipulator. First, dynamic analysis of a flexible manipulator was done for modeling. Second, from the dynamic model, the inverse dynamic equation was derived, and the time domain inverse dynamic method was proposed for the calculation of the feedforward torque and the desired flexible coordinate trajectories. Third, a tracking controller was designed by combining the inverse dynamic feedforward control with the joint feedback control. The control scheme was applied to the tip position control of a single link flexible manipulator for zero and non-zero initial condition cases. Finally, the contact control scheme was added to the position tracking control. A control scenario of a bracing manipulator is provided and evaluated through simulation and experiment on a single link flexible manipulator.

Individually Watermarked Information Distributed Scalable by Modified Transforms

DTIC Science & Technology

2009-10-01

inverse of the secret transform is needed. Each trusted recipient has a unique inverse transform that is similar to the inverse of the original...transform. The elements of this individual inverse transform are given by the individual descrambling key. After applying the individual inverse ... transform the retrieved image is embedded with a recipient individual watermark. Souce 1 I Decode IW1 Decode IW2 Decode ISC Scramb K Recipient 3

In vivo spatial frequency domain spectroscopy of two layer media

NASA Astrophysics Data System (ADS)

Yudovsky, Dmitry; Nguyen, John Quan M.; Durkin, Anthony J.

2012-10-01

Monitoring of tissue blood volume and local oxygen saturation can inform the assessment of tissue health, healing, and dysfunction. These quantities can be estimated from the contribution of oxyhemoglobin and deoxyhemoglobin to the absorption spectrum of the dermis. However, estimation of blood related absorption in skin can be confounded by the strong absorption of melanin in the epidermis and epidermal thickness and pigmentation varies with anatomic location, race, gender, and degree of disease progression. Therefore, a method is desired that decouples the effect of melanin absorption in the epidermis from blood absorption in the dermis for a large range of skin types and thicknesses. A previously developed inverse method based on a neural network forward model was applied to simulated spatial frequency domain reflectance of skin for multiple wavelengths in the near infrared. It is demonstrated that the optical thickness of the epidermis and absorption and reduced scattering coefficients of the dermis can be determined independently and with minimal coupling. Then, the same inverse method was applied to reflectance measurements from a tissue simulating phantom and in vivo human skin. Oxygen saturation and total hemoglobin concentrations were estimated from the volar forearms of weakly and strongly pigmented subjects using a standard homogeneous model and the present two layer model.

The use of forest stand age information in an atmospheric CO2 inversion applied to North America

Treesearch

F. Deng; J.M. Chen; Y. Pan; W. Peters; R. Birdsey; K. McCullough; J. Xiao

2013-01-01

Atmospheric inversions have become an important tool in quantifying carbon dioxide (CO2) sinks and sources at a variety of spatiotemporal scales, but associated large uncertainties restrain the inversion research community from reaching agreement on many important subjects. We enhanced an atmospheric inversion of the CO2...

Real Variable Inversion of Laplace Transforms: An Application in Plasma Physics.

ERIC Educational Resources Information Center

Bohn, C. L.; Flynn, R. W.

1978-01-01

Discusses the nature of Laplace transform techniques and explains an alternative to them: the Widder's real inversion. To illustrate the power of this new technique, it is applied to a difficult inversion: the problem of Landau damping. (GA)

DOE Office of Scientific and Technical Information (OSTI.GOV)

Niu, T; Dong, X; Petrongolo, M

Purpose: Dual energy CT (DECT) imaging plays an important role in advanced imaging applications due to its material decomposition capability. Direct decomposition via matrix inversion suffers from significant degradation of image signal-to-noise ratios, which reduces clinical value. Existing de-noising algorithms achieve suboptimal performance since they suppress image noise either before or after the decomposition and do not fully explore the noise statistical properties of the decomposition process. We propose an iterative image-domain decomposition method for noise suppression in DECT, using the full variance-covariance matrix of the decomposed images. Methods: The proposed algorithm is formulated in the form of least-square estimationmore » with smoothness regularization. It includes the inverse of the estimated variance-covariance matrix of the decomposed images as the penalty weight in the least-square term. Performance is evaluated using an evaluation phantom (Catphan 600) and an anthropomorphic head phantom. Results are compared to those generated using direct matrix inversion with no noise suppression, a de-noising method applied on the decomposed images, and an existing algorithm with similar formulation but with an edge-preserving regularization term. Results: On the Catphan phantom, our method retains the same spatial resolution as the CT images before decomposition while reducing the noise standard deviation of decomposed images by over 98%. The other methods either degrade spatial resolution or achieve less low-contrast detectability. Also, our method yields lower electron density measurement error than direct matrix inversion and reduces error variation by over 97%. On the head phantom, it reduces the noise standard deviation of decomposed images by over 97% without blurring the sinus structures. Conclusion: We propose an iterative image-domain decomposition method for DECT. The method combines noise suppression and material decomposition into an iterative process and achieves both goals simultaneously. The proposed algorithm shows superior performance on noise suppression with high image spatial resolution and low-contrast detectability. This work is supported by a Varian MRA grant.« less

Inverting Monotonic Nonlinearities by Entropy Maximization

PubMed Central

López-de-Ipiña Pena, Karmele; Caiafa, Cesar F.

2016-01-01

This paper proposes a new method for blind inversion of a monotonic nonlinear map applied to a sum of random variables. Such kinds of mixtures of random variables are found in source separation and Wiener system inversion problems, for example. The importance of our proposed method is based on the fact that it permits to decouple the estimation of the nonlinear part (nonlinear compensation) from the estimation of the linear one (source separation matrix or deconvolution filter), which can be solved by applying any convenient linear algorithm. Our new nonlinear compensation algorithm, the MaxEnt algorithm, generalizes the idea of Gaussianization of the observation by maximizing its entropy instead. We developed two versions of our algorithm based either in a polynomial or a neural network parameterization of the nonlinear function. We provide a sufficient condition on the nonlinear function and the probability distribution that gives a guarantee for the MaxEnt method to succeed compensating the distortion. Through an extensive set of simulations, MaxEnt is compared with existing algorithms for blind approximation of nonlinear maps. Experiments show that MaxEnt is able to successfully compensate monotonic distortions outperforming other methods in terms of the obtained Signal to Noise Ratio in many important cases, for example when the number of variables in a mixture is small. Besides its ability for compensating nonlinearities, MaxEnt is very robust, i.e. showing small variability in the results. PMID:27780261

Inverting Monotonic Nonlinearities by Entropy Maximization.

PubMed

Solé-Casals, Jordi; López-de-Ipiña Pena, Karmele; Caiafa, Cesar F

2016-01-01

This paper proposes a new method for blind inversion of a monotonic nonlinear map applied to a sum of random variables. Such kinds of mixtures of random variables are found in source separation and Wiener system inversion problems, for example. The importance of our proposed method is based on the fact that it permits to decouple the estimation of the nonlinear part (nonlinear compensation) from the estimation of the linear one (source separation matrix or deconvolution filter), which can be solved by applying any convenient linear algorithm. Our new nonlinear compensation algorithm, the MaxEnt algorithm, generalizes the idea of Gaussianization of the observation by maximizing its entropy instead. We developed two versions of our algorithm based either in a polynomial or a neural network parameterization of the nonlinear function. We provide a sufficient condition on the nonlinear function and the probability distribution that gives a guarantee for the MaxEnt method to succeed compensating the distortion. Through an extensive set of simulations, MaxEnt is compared with existing algorithms for blind approximation of nonlinear maps. Experiments show that MaxEnt is able to successfully compensate monotonic distortions outperforming other methods in terms of the obtained Signal to Noise Ratio in many important cases, for example when the number of variables in a mixture is small. Besides its ability for compensating nonlinearities, MaxEnt is very robust, i.e. showing small variability in the results.

Model-based assist feature insertion for sub-40nm memory device

NASA Astrophysics Data System (ADS)

Suh, Sungsoo; Lee, Suk-joo; Choi, Seong-woon; Lee, Sung-Woo; Park, Chan-hoon

2009-04-01

Many issues need to be resolved for a production-worthy model based assist feature insertion flow for single and double exposure patterning process to extend low k1 process at 193 nm immersion technology. Model based assist feature insertion is not trivial to implement either for single and double exposure patterning compared to rule based methods. As shown in Fig. 1, pixel based mask inversion technology in itself has difficulties in mask writing and inspection although it presents as one of key technology to extend single exposure for contact layer. Thus far, inversion technology is tried as a cooptimization of target mask to simultaneously generate optimized main and sub-resolution assists features for a desired process window. Alternatively, its technology can also be used to optimize for a target feature after an assist feature types are inserted in order to simplify the mask complexity. Simplification of inversion mask is one of major issue with applying inversion technology to device development even if a smaller mask feature can be fabricated since the mask writing time is also a major factor. As shown in Figure 2, mask writing time may be a limiting factor in determining whether or not an inversion solution is viable. It can be reasoned that increased number of shot counts relates to increase in margin for inversion methodology. On the other hand, there is a limit on how complex a mask can be in order to be production worthy. There is also source and mask co-optimization which influences the final mask patterns and assist feature sizes and positions for a given target. In this study, we will discuss assist feature insertion methods for sub 40-nm technology.

A Depolarisation Lidar Based Method for the Determination of Liquid-Cloud Microphysical Properties.

NASA Astrophysics Data System (ADS)

Donovan, D. P.; Klein Baltink, H.; Henzing, J. S.; De Roode, S. R.; Siebesma, P.

2014-12-01

The fact that polarisation lidars measure a multiple-scattering induced depolarisation signal in liquid clouds is well-known. The depolarisation signal depends on the lidar characteristics (e.g. wavelength and field-of-view) as well as the cloud properties (e.g. liquid water content (LWC) and cloud droplet number concentration (CDNC)). Previous efforts seeking to use depolarisation information in a quantitative manner to retrieve cloud properties have been undertaken with, arguably, limited practical success. In this work we present a retrieval procedure applicable to clouds with (quasi-)linear LWC profiles and (quasi-)constant CDNC in the cloud base region. Limiting the applicability of the procedure in this manner allows us to reduce the cloud variables to two parameters (namely liquid water content lapse-rate and the CDNC). This simplification, in turn, allows us to employ a robust optimal-estimation inversion using pre-computed look-up-tables produced using lidar Monte-Carlo multiple-scattering simulations. Here, we describe the theory behind the inversion procedure and apply it to simulated observations based on large-eddy simulation model output. The inversion procedure is then applied to actual depolarisation lidar data covering to a range of cases taken from the Cabauw measurement site in the central Netherlands. The lidar results were then used to predict the corresponding cloud-base region radar reflectivities. In non-drizzling condition, it was found that the lidar inversion results can be used to predict the observed radar reflectivities with an accuracy within the radar calibration uncertainty (2-3 dBZ). This result strongly supports the accuracy of the lidar inversion results. Results of a comparison between ground-based aerosol number concentration and lidar-derived CDNC are also presented. The results are seen to be consistent with previous studies based on aircraft-based in situ measurements.

The Thermodynamic Structure of Arctic Coastal Fog Occurring During the Melt Season over East Greenland

NASA Astrophysics Data System (ADS)

Gilson, Gaëlle F.; Jiskoot, Hester; Cassano, John J.; Gultepe, Ismail; James, Timothy D.

2018-05-01

An automated method to classify Arctic fog into distinct thermodynamic profiles using historic in-situ surface and upper-air observations is presented. This classification is applied to low-resolution Integrated Global Radiosonde Archive (IGRA) soundings and high-resolution Arctic Summer Cloud Ocean Study (ASCOS) soundings in low- and high-Arctic coastal and pack-ice environments. Results allow investigation of fog macrophysical properties and processes in coastal East Greenland during melt seasons 1980-2012. Integrated with fog observations from three synoptic weather stations, 422 IGRA soundings are classified into six fog thermodynamic types based on surface saturation ratio, type of temperature inversion, fog-top height relative to inversion-base height and stability using the virtual potential temperature gradient. Between 65-80% of fog observations occur with a low-level inversion, and statically neutral or unstable surface layers occur frequently. Thermodynamic classification is sensitive to the assigned dew-point depression threshold, but categorization is robust. Despite differences in the vertical resolution of radiosonde observations, IGRA and ASCOS soundings yield the same six fog classes, with fog-class distribution varying with latitude and environmental conditions. High-Arctic fog frequently resides within an elevated inversion layer, whereas low-Arctic fog is more often restricted to the mixed layer. Using supplementary time-lapse images, ASCOS microwave radiometer retrievals and airmass back-trajectories, we hypothesize that the thermodynamic classes represent different stages of advection fog formation, development, and dissipation, including stratus-base lowering and fog lifting. This automated extraction of thermodynamic boundary-layer and inversion structure can be applied to radiosonde observations worldwide to better evaluate fog conditions that affect transportation and lead to improvements in numerical models.

An Inverse Neural Controller Based on the Applicability Domain of RBF Network Models

PubMed Central

Alexandridis, Alex; Stogiannos, Marios; Papaioannou, Nikolaos; Zois, Elias; Sarimveis, Haralambos

2018-01-01

This paper presents a novel methodology of generic nature for controlling nonlinear systems, using inverse radial basis function neural network models, which may combine diverse data originating from various sources. The algorithm starts by applying the particle swarm optimization-based non-symmetric variant of the fuzzy means (PSO-NSFM) algorithm so that an approximation of the inverse system dynamics is obtained. PSO-NSFM offers models of high accuracy combined with small network structures. Next, the applicability domain concept is suitably tailored and embedded into the proposed control structure in order to ensure that extrapolation is avoided in the controller predictions. Finally, an error correction term, estimating the error produced by the unmodeled dynamics and/or unmeasured external disturbances, is included to the control scheme to increase robustness. The resulting controller guarantees bounded input-bounded state (BIBS) stability for the closed loop system when the open loop system is BIBS stable. The proposed methodology is evaluated on two different control problems, namely, the control of an experimental armature-controlled direct current (DC) motor and the stabilization of a highly nonlinear simulated inverted pendulum. For each one of these problems, appropriate case studies are tested, in which a conventional neural controller employing inverse models and a PID controller are also applied. The results reveal the ability of the proposed control scheme to handle and manipulate diverse data through a data fusion approach and illustrate the superiority of the method in terms of faster and less oscillatory responses. PMID:29361781

Nondestructive mechanical characterization of developing biological tissues using inflation testing.

PubMed

Oomen, P J A; van Kelle, M A J; Oomens, C W J; Bouten, C V C; Loerakker, S

2017-10-01

One of the hallmarks of biological soft tissues is their capacity to grow and remodel in response to changes in their environment. Although it is well-accepted that these processes occur at least partly to maintain a mechanical homeostasis, it remains unclear which mechanical constituent(s) determine(s) mechanical homeostasis. In the current study a nondestructive mechanical test and a two-step inverse analysis method were developed and validated to nondestructively estimate the mechanical properties of biological tissue during tissue culture. Nondestructive mechanical testing was achieved by performing an inflation test on tissues that were cultured inside a bioreactor, while the tissue displacement and thickness were nondestructively measured using ultrasound. The material parameters were estimated by an inverse finite element scheme, which was preceded by an analytical estimation step to rapidly obtain an initial estimate that already approximated the final solution. The efficiency and accuracy of the two-step inverse method was demonstrated on virtual experiments of several material types with known parameters. PDMS samples were used to demonstrate the method's feasibility, where it was shown that the proposed method yielded similar results to tensile testing. Finally, the method was applied to estimate the material properties of tissue-engineered constructs. Via this method, the evolution of mechanical properties during tissue growth and remodeling can now be monitored in a well-controlled system. The outcomes can be used to determine various mechanical constituents and to assess their contribution to mechanical homeostasis. Copyright © 2017 Elsevier Ltd. All rights reserved.

2.5D complex resistivity modeling and inversion using unstructured grids

NASA Astrophysics Data System (ADS)

Xu, Kaijun; Sun, Jie

2016-04-01

The characteristic of complex resistivity on rock and ore has been recognized by people for a long time. Generally we have used the Cole-Cole Model(CCM) to describe complex resistivity. It has been proved that the electrical anomaly of geologic body can be quantitative estimated by CCM parameters such as direct resistivity(ρ0), chargeability(m), time constant(τ) and frequency dependence(c). Thus it is very important to obtain the complex parameters of geologic body. It is difficult to approximate complex structures and terrain using traditional rectangular grid. In order to enhance the numerical accuracy and rationality of modeling and inversion, we use an adaptive finite-element algorithm for forward modeling of the frequency-domain 2.5D complex resistivity and implement the conjugate gradient algorithm in the inversion of 2.5D complex resistivity. An adaptive finite element method is applied for solving the 2.5D complex resistivity forward modeling of horizontal electric dipole source. First of all, the CCM is introduced into the Maxwell's equations to calculate the complex resistivity electromagnetic fields. Next, the pseudo delta function is used to distribute electric dipole source. Then the electromagnetic fields can be expressed in terms of the primary fields caused by layered structure and the secondary fields caused by inhomogeneities anomalous conductivity. At last, we calculated the electromagnetic fields response of complex geoelectric structures such as anticline, syncline, fault. The modeling results show that adaptive finite-element methods can automatically improve mesh generation and simulate complex geoelectric models using unstructured grids. The 2.5D complex resistivity invertion is implemented based the conjugate gradient algorithm.The conjugate gradient algorithm doesn't need to compute the sensitivity matrix but directly computes the sensitivity matrix or its transpose multiplying vector. In addition, the inversion target zones are segmented with fine grids and the background zones are segmented with big grid, the method can reduce the grid amounts of inversion, it is very helpful to improve the computational efficiency. The inversion results verify the validity and stability of conjugate gradient inversion algorithm. The results of theoretical calculation indicate that the modeling and inversion of 2.5D complex resistivity using unstructured grids are feasible. Using unstructured grids can improve the accuracy of modeling, but the large number of grids inversion is extremely time-consuming, so the parallel computation for the inversion is necessary. Acknowledgments: We thank to the support of the National Natural Science Foundation of China(41304094).

A New Self-Constrained Inversion Method of Potential Fields Based on Probability Tomography

NASA Astrophysics Data System (ADS)

Sun, S.; Chen, C.; WANG, H.; Wang, Q.

2014-12-01

The self-constrained inversion method of potential fields uses a priori information self-extracted from potential field data. Differing from external a priori information, the self-extracted information are generally parameters derived exclusively from the analysis of the gravity and magnetic data (Paoletti et al., 2013). Here we develop a new self-constrained inversion method based on probability tomography. Probability tomography doesn't need any priori information, as well as large inversion matrix operations. Moreover, its result can describe the sources, especially the distribution of which is complex and irregular, entirely and clearly. Therefore, we attempt to use the a priori information extracted from the probability tomography results to constrain the inversion for physical properties. The magnetic anomaly data was taken as an example in this work. The probability tomography result of magnetic total field anomaly(ΔΤ) shows a smoother distribution than the anomalous source and cannot display the source edges exactly. However, the gradients of ΔΤ are with higher resolution than ΔΤ in their own direction, and this characteristic is also presented in their probability tomography results. So we use some rules to combine the probability tomography results of ∂ΔΤ⁄∂x, ∂ΔΤ⁄∂y and ∂ΔΤ⁄∂z into a new result which is used for extracting a priori information, and then incorporate the information into the model objective function as spatial weighting functions to invert the final magnetic susceptibility. Some magnetic synthetic examples incorporated with and without a priori information extracted from the probability tomography results were made to do comparison, results of which show that the former are more concentrated and with higher resolution of the source body edges. This method is finally applied in an iron mine in China with field measured ΔΤ data and performs well. ReferencesPaoletti, V., Ialongo, S., Florio, G., Fedi, M. & Cella, F., 2013. Self-constrained inversion of potential fields, Geophys J Int.This research is supported by the Fundamental Research Funds for Institute for Geophysical and Geochemical Exploration, Chinese Academy of Geological Sciences (Grant Nos. WHS201210 and WHS201211).

Resolution analysis of marine seismic full waveform data by Bayesian inversion

NASA Astrophysics Data System (ADS)

Ray, A.; Sekar, A.; Hoversten, G. M.; Albertin, U.

2015-12-01

The Bayesian posterior density function (PDF) of earth models that fit full waveform seismic data convey information on the uncertainty with which the elastic model parameters are resolved. In this work, we apply the trans-dimensional reversible jump Markov Chain Monte Carlo method (RJ-MCMC) for the 1D inversion of noisy synthetic full-waveform seismic data in the frequency-wavenumber domain. While seismic full waveform inversion (FWI) is a powerful method for characterizing subsurface elastic parameters, the uncertainty in the inverted models has remained poorly known, if at all and is highly initial model dependent. The Bayesian method we use is trans-dimensional in that the number of model layers is not fixed, and flexible such that the layer boundaries are free to move around. The resulting parameterization does not require regularization to stabilize the inversion. Depth resolution is traded off with the number of layers, providing an estimate of uncertainty in elastic parameters (compressional and shear velocities Vp and Vs as well as density) with depth. We find that in the absence of additional constraints, Bayesian inversion can result in a wide range of posterior PDFs on Vp, Vs and density. These PDFs range from being clustered around the true model, to those that contain little resolution of any particular features other than those in the near surface, depending on the particular data and target geometry. We present results for a suite of different frequencies and offset ranges, examining the differences in the posterior model densities thus derived. Though these results are for a 1D earth, they are applicable to areas with simple, layered geology and provide valuable insight into the resolving capabilities of FWI, as well as highlight the challenges in solving a highly non-linear problem. The RJ-MCMC method also presents a tantalizing possibility for extension to 2D and 3D Bayesian inversion of full waveform seismic data in the future, as it objectively tackles the problem of model selection (i.e., the number of layers or cells for parameterization), which could ease the computational burden of evaluating forward models with many parameters.

Ground-Based Microwave Radiometric Remote Sensing of the Tropical Atmosphere

NASA Astrophysics Data System (ADS)

Han, Yong

A partially developed 9-channel ground-based microwave radiometer for the Department of Meteorology at Penn State was completed and tested. Complementary units were added, corrections to both hardware and software were made, and system software was corrected and upgraded. Measurements from this radiometer were used to infer tropospheric temperature, water vapor and cloud liquid water. The various weighting functions at each of the 9 channels were calculated and analyzed to estimate the sensitivities of the brightness temperatures to the desired atmospheric variables. The mathematical inversion problem, in a linear form, was viewed in terms of the theory of linear algebra. Several methods for solving the inversion problem were reviewed. Radiometric observations were conducted during the 1990 Tropical Cyclone Motion Experiment. The radiometer was installed on the island of Saipan in a tropical region. During this experiment, the radiometer was calibrated by using tipping curve and radiosonde data as well as measurements of the radiation from a blackbody absorber. A linear statistical method was first applied for the data inversion. The inversion coefficients in the equation were obtained using a large number of radiosonde profiles from Guam and a radiative transfer model. Retrievals were compared with those from local, Saipan, radiosonde measurements. Water vapor profiles, integrated water vapor, and integrated liquid water were retrieved successfully. For temperature profile retrievals, however, it was shown that the radiometric measurements with experimental noises added no more profile information to the inversion than that which was available from a climatological mean. Although successful retrievals of the geopotential heights were made, it was shown that they were determined mainly by the surface pressure measurements. The reasons why the radiometer did not contribute to the retrievals of temperature profiles and geopotential heights were discussed. A method was developed to derive the integrated water vapor and liquid water from combined radiometer and ceilometer measurements. Under certain assumptions, the cloud absorption coefficients and mean radiating temperature, used in the physical or statistical inversion equation, were determined from the measurements. It was shown that significant improvement on radiometric measurements of the integrated liquid water can be gained with this method.

Parameter identification for structural dynamics based on interval analysis algorithm

NASA Astrophysics Data System (ADS)

Yang, Chen; Lu, Zixing; Yang, Zhenyu; Liang, Ke

2018-04-01

A parameter identification method using interval analysis algorithm for structural dynamics is presented in this paper. The proposed uncertain identification method is investigated by using central difference method and ARMA system. With the help of the fixed memory least square method and matrix inverse lemma, a set-membership identification technology is applied to obtain the best estimation of the identified parameters in a tight and accurate region. To overcome the lack of insufficient statistical description of the uncertain parameters, this paper treats uncertainties as non-probabilistic intervals. As long as we know the bounds of uncertainties, this algorithm can obtain not only the center estimations of parameters, but also the bounds of errors. To improve the efficiency of the proposed method, a time-saving algorithm is presented by recursive formula. At last, to verify the accuracy of the proposed method, two numerical examples are applied and evaluated by three identification criteria respectively.

3D CSEM data inversion using Newton and Halley class methods

NASA Astrophysics Data System (ADS)

Amaya, M.; Hansen, K. R.; Morten, J. P.

2016-05-01

For the first time in 3D controlled source electromagnetic data inversion, we explore the use of the Newton and the Halley optimization methods, which may show their potential when the cost function has a complex topology. The inversion is formulated as a constrained nonlinear least-squares problem which is solved by iterative optimization. These methods require the derivatives up to second order of the residuals with respect to model parameters. We show how Green's functions determine the high-order derivatives, and develop a diagrammatical representation of the residual derivatives. The Green's functions are efficiently calculated on-the-fly, making use of a finite-difference frequency-domain forward modelling code based on a multi-frontal sparse direct solver. This allow us to build the second-order derivatives of the residuals keeping the memory cost in the same order as in a Gauss-Newton (GN) scheme. Model updates are computed with a trust-region based conjugate-gradient solver which does not require the computation of a stabilizer. We present inversion results for a synthetic survey and compare the GN, Newton, and super-Halley optimization schemes, and consider two different approaches to set the initial trust-region radius. Our analysis shows that the Newton and super-Halley schemes, using the same regularization configuration, add significant information to the inversion so that the convergence is reached by different paths. In our simple resistivity model examples, the convergence speed of the Newton and the super-Halley schemes are either similar or slightly superior with respect to the convergence speed of the GN scheme, close to the minimum of the cost function. Due to the current noise levels and other measurement inaccuracies in geophysical investigations, this advantageous behaviour is at present of low consequence, but may, with the further improvement of geophysical data acquisition, be an argument for more accurate higher-order methods like those applied in this paper.

Direct vibro-elastography FEM inversion in Cartesian and cylindrical coordinate systems without the local homogeneity assumption

NASA Astrophysics Data System (ADS)

Honarvar, M.; Lobo, J.; Mohareri, O.; Salcudean, S. E.; Rohling, R.

2015-05-01

To produce images of tissue elasticity, the vibro-elastography technique involves applying a steady-state multi-frequency vibration to tissue, estimating displacements from ultrasound echo data, and using the estimated displacements in an inverse elasticity problem with the shear modulus spatial distribution as the unknown. In order to fully solve the inverse problem, all three displacement components are required. However, using ultrasound, the axial component of the displacement is measured much more accurately than the other directions. Therefore, simplifying assumptions must be used in this case. Usually, the equations of motion are transformed into a Helmholtz equation by assuming tissue incompressibility and local homogeneity. The local homogeneity assumption causes significant imaging artifacts in areas of varying elasticity. In this paper, we remove the local homogeneity assumption. In particular we introduce a new finite element based direct inversion technique in which only the coupling terms in the equation of motion are ignored, so it can be used with only one component of the displacement. Both Cartesian and cylindrical coordinate systems are considered. The use of multi-frequency excitation also allows us to obtain multiple measurements and reduce artifacts in areas where the displacement of one frequency is close to zero. The proposed method was tested in simulations and experiments against a conventional approach in which the local homogeneity is used. The results show significant improvements in elasticity imaging with the new method compared to previous methods that assumes local homogeneity. For example in simulations, the contrast to noise ratio (CNR) for the region with spherical inclusion increases from an average value of 1.5-17 after using the proposed method instead of the local inversion with homogeneity assumption, and similarly in the prostate phantom experiment, the CNR improved from an average value of 1.6 to about 20.

PREFACE: Inverse Problems in Applied Sciences—towards breakthrough

NASA Astrophysics Data System (ADS)

Cheng, Jin; Iso, Yuusuke; Nakamura, Gen; Yamamoto, Masahiro

2007-06-01

These are the proceedings of the international conference `Inverse Problems in Applied Sciences—towards breakthrough' which was held at Hokkaido University, Sapporo, Japan on 3-7 July 2006 (http://coe.math.sci.hokudai.ac.jp/sympo/inverse/). There were 88 presentations and more than 100 participants, and we are proud to say that the conference was very successful. Nowadays, many new activities on inverse problems are flourishing at many centers of research around the world, and the conference has successfully gathered a world-wide variety of researchers. We believe that this volume contains not only main papers, but also conveys the general status of current research into inverse problems. This conference was the third biennial international conference on inverse problems, the core of which is the Pan-Pacific Asian area. The purpose of this series of conferences is to establish and develop constant international collaboration, especially among the Pan-Pacific Asian countries, and to lead the organization of activities concerning inverse problems centered in East Asia. The first conference was held at City University of Hong Kong in January 2002 and the second was held at Fudan University in June 2004. Following the preceding two successes, the third conference was organized in order to extend the scope of activities and build useful bridges to the next conference in Seoul in 2008. Therefore this third biennial conference was intended not only to establish collaboration and links between researchers in Asia and leading researchers worldwide in inverse problems but also to nurture interdisciplinary collaboration in theoretical fields such as mathematics, applied fields and evolving aspects of inverse problems. For these purposes, we organized tutorial lectures, serial lectures and a panel discussion as well as conference research presentations. This volume contains three lecture notes from the tutorial and serial lectures, and 22 papers. Especially at this flourishing time, it is necessary to carefully analyse the current status of inverse problems for further development. Thus we have opened with the panel discussion entitled `Future of Inverse Problems' with panelists: Professors J Cheng, H W Engl, V Isakov, R Kress, J-K Seo, G Uhlmann and the commentator: Elaine Longden-Chapman from IOP Publishing. The aims of the panel discussion were to examine the current research status from various viewpoints, to discuss how we can overcome any difficulties and how we can promote young researchers and open new possibilities for inverse problems such as industrial linkages. As one output, the panel discussion has triggered the organization of the Inverse Problems International Association (IPIA) which has led to its first international congress in the summer of 2007. Another remarkable outcome of the conference is, of course, the present volume: this is the very high quality online proceedings volume of Journal of Physics: Conference Series. Readers can see in these proceedings very well written tutorial lecture notes, and very high quality original research and review papers all of which show what was achieved by the time the conference was held. The electronic publication of the proceedings is a new way of publicizing the achievement of the conference. It has the advantage of wide circulation and cost reduction. We believe this is a most efficient method for our needs and purposes. We would like to take this opportunity to acknowledge all the people who helped to organize the conference. Guest Editors Jin Cheng, Fudan University, Shanghai, China Yuusuke Iso, Kyoto University, Kyoto, Japan Gen Nakamura, Hokkaido University, Sapporo, Japan Masahiro Yamamoto, University of Tokyo, Tokyo, Japan

Joint body and surface wave tomography applied to the Toba caldera complex (Indonesia)

NASA Astrophysics Data System (ADS)

Jaxybulatov, Kairly; Koulakov, Ivan; Shapiro, Nikolai

2016-04-01

We developed a new algorithm for a joint body and surface wave tomography. The algorithm is a modification of the existing LOTOS code (Koulakov, 2009) developed for local earthquake tomography. The input data for the new method are travel times of P and S waves and dispersion curves of Rayleigh and Love waves. The main idea is that the two data types have complementary sensitivities. The body-wave data have good resolution at depth, where we have enough crossing rays between sources and receivers, whereas the surface waves have very good near-surface resolution. The surface wave dispersion curves can be retrieved from the correlations of the ambient seismic noise and in this case the sampled path distribution does not depend on the earthquake sources. The contributions of the two data types to the inversion are controlled by the weighting of the respective equations. One of the clearest cases where such approach may be useful are volcanic systems in subduction zones with their complex magmatic feeding systems that have deep roots in the mantle and intermediate magma chambers in the crust. In these areas, the joint inversion of different types of data helps us to build a comprehensive understanding of the entire system. We apply our algorithm to data collected in the region surrounding the Toba caldera complex (north Sumatra, Indonesia) during two temporary seismic experiments (IRIS, PASSCAL, 1995, GFZ, LAKE TOBA, 2008). We invert 6644 P and 5240 S wave arrivals and ~500 group velocity dispersion curves of Rayleigh and Love waves. We present a series of synthetic tests and real data inversions which show that joint inversion approach gives more reliable results than the separate inversion of two data types. Koulakov, I., LOTOS code for local earthquake tomographic inversion. Benchmarks for testing tomographic algorithms, Bull. seism. Soc. Am., 99(1), 194-214, 2009, doi:10.1785/0120080013

Free energy profiles from single-molecule pulling experiments.

PubMed

Hummer, Gerhard; Szabo, Attila

2010-12-14

Nonequilibrium pulling experiments provide detailed information about the thermodynamic and kinetic properties of molecules. We show that unperturbed free energy profiles as a function of molecular extension can be obtained rigorously from such experiments without using work-weighted position histograms. An inverse Weierstrass transform is used to relate the system free energy obtained from the Jarzynski equality directly to the underlying molecular free energy surface. An accurate approximation for the free energy surface is obtained by using the method of steepest descent to evaluate the inverse transform. The formalism is applied to simulated data obtained from a kinetic model of RNA folding, in which the dynamics consists of jumping between linker-dominated folded and unfolded free energy surfaces.

Detection of pure inverse spin-Hall effect induced by spin pumping at various excitation

NASA Astrophysics Data System (ADS)

Inoue, H. Y.; Harii, K.; Ando, K.; Sasage, K.; Saitoh, E.

2007-10-01

Electric-field generation due to the inverse spin-Hall effect (ISHE) driven by spin pumping was detected and separated experimentally from the extrinsic magnetogalvanic effects in a Ni81Fe19/Pt film. By applying a sample-cavity configuration in which the extrinsic effects are suppressed, the spin pumping using ferromagnetic resonance gives rise to a symmetric spectral shape in the electromotive force spectrum, indicating that the motive force is due entirely to ISHE. This method allows the quantitative analysis of the ISHE and the spin-pumping effect. The microwave-power dependence of the ISHE amplitude is consistent with the prediction of a direct current-spin-pumping scenario.

In vivo lactate and beta-hydroxybutyrate editing using a pure-phase refocusing pulse train.

PubMed

Shen, J; Novotny, E J; Rothman, D L

1998-11-01

A refocusing pulse train consisting of a semiselective refocusing pulse and a selective inversion pulse to obtain a pure-phase refocusing at the frequency of maximal excitation of the semiselective refocusing pulse is proposed and applied to in vivo lactate and beta-hydroxybutyrate editing using difference spectroscopy. It is shown, using both rotation matrix theory and phantom experiments, that the soft inversion pulse has to be halved to flank the semiselective pulse to obtain perfect refocusing and cancellation of interfering resonances. The editing method is used to obtain lactate and beta-hydroxybutyrate spectra from the occipital cortex of juvenile epilepsy patients before and after ketogenic diet treatment.

Intrinsic nonlinearity and method of disturbed observations in inverse problems of celestial mechanics

NASA Astrophysics Data System (ADS)

Avdyushev, Victor A.

2017-12-01

Orbit determination from a small sample of observations over a very short observed orbital arc is a strongly nonlinear inverse problem. In such problems an evaluation of orbital uncertainty due to random observation errors is greatly complicated, since linear estimations conventionally used are no longer acceptable for describing the uncertainty even as a rough approximation. Nevertheless, if an inverse problem is weakly intrinsically nonlinear, then one can resort to the so-called method of disturbed observations (aka observational Monte Carlo). Previously, we showed that the weaker the intrinsic nonlinearity, the more efficient the method, i.e. the more accurate it enables one to simulate stochastically the orbital uncertainty, while it is strictly exact only when the problem is intrinsically linear. However, as we ascertained experimentally, its efficiency was found to be higher than that of other stochastic methods widely applied in practice. In the present paper we investigate the intrinsic nonlinearity in complicated inverse problems of Celestial Mechanics when orbits are determined from little informative samples of observations, which typically occurs for recently discovered asteroids. To inquire into the question, we introduce an index of intrinsic nonlinearity. In asteroid problems it evinces that the intrinsic nonlinearity can be strong enough to affect appreciably probabilistic estimates, especially at the very short observed orbital arcs that the asteroids travel on for about a hundredth of their orbital periods and less. As it is known from regression analysis, the source of intrinsic nonlinearity is the nonflatness of the estimation subspace specified by a dynamical model in the observation space. Our numerical results indicate that when determining asteroid orbits it is actually very slight. However, in the parametric space the effect of intrinsic nonlinearity is exaggerated mainly by the ill-conditioning of the inverse problem. Even so, as for the method of disturbed observations, we conclude that it practically should be still entirely acceptable to adequately describe the orbital uncertainty since, from a geometrical point of view, the efficiency of the method directly depends only on the nonflatness of the estimation subspace and it gets higher as the nonflatness decreases.

Multi-scale Slip Inversion Based on Simultaneous Spatial and Temporal Domain Wavelet Transform

NASA Astrophysics Data System (ADS)

Liu, W.; Yao, H.; Yang, H. Y.

2017-12-01

Finite fault inversion is a widely used method to study earthquake rupture processes. Some previous studies have proposed different methods to implement finite fault inversion, including time-domain, frequency-domain, and wavelet-domain methods. Many previous studies have found that different frequency bands show different characteristics of the seismic rupture (e.g., Wang and Mori, 2011; Yao et al., 2011, 2013; Uchide et al., 2013; Yin et al., 2017). Generally, lower frequency waveforms correspond to larger-scale rupture characteristics while higher frequency data are representative of smaller-scale ones. Therefore, multi-scale analysis can help us understand the earthquake rupture process thoroughly from larger scale to smaller scale. By the use of wavelet transform, the wavelet-domain methods can analyze both the time and frequency information of signals in different scales. Traditional wavelet-domain methods (e.g., Ji et al., 2002) implement finite fault inversion with both lower and higher frequency signals together to recover larger-scale and smaller-scale characteristics of the rupture process simultaneously. Here we propose an alternative strategy with a two-step procedure, i.e., firstly constraining the larger-scale characteristics with lower frequency signals, and then resolving the smaller-scale ones with higher frequency signals. We have designed some synthetic tests to testify our strategy and compare it with the traditional one. We also have applied our strategy to study the 2015 Gorkha Nepal earthquake using tele-seismic waveforms. Both the traditional method and our two-step strategy only analyze the data in different temporal scales (i.e., different frequency bands), while the spatial distribution of model parameters also shows multi-scale characteristics. A more sophisticated strategy is to transfer the slip model into different spatial scales, and then analyze the smooth slip distribution (larger scales) with lower frequency data firstly and more detailed slip distribution (smaller scales) with higher frequency data subsequently. We are now implementing the slip inversion using both spatial and temporal domain wavelets. This multi-scale analysis can help us better understand frequency-dependent rupture characteristics of large earthquakes.

Three-Dimensional Anisotropic Acoustic and Elastic Full-Waveform Seismic Inversion

NASA Astrophysics Data System (ADS)

Warner, M.; Morgan, J. V.

2013-12-01

Three-dimensional full-waveform inversion is a high-resolution, high-fidelity, quantitative, seismic imaging technique that has advanced rapidly within the oil and gas industry. The method involves the iterative improvement of a starting model using a series of local linearized updates to solve the full non-linear inversion problem. During the inversion, forward modeling employs the full two-way three-dimensional heterogeneous anisotropic acoustic or elastic wave equation to predict the observed raw field data, wiggle-for-wiggle, trace-by-trace. The method is computationally demanding; it is highly parallelized, and runs on large multi-core multi-node clusters. Here, we demonstrate what can be achieved by applying this newly practical technique to several high-density 3D seismic datasets that were acquired to image four contrasting sedimentary targets: a gas cloud above an oil reservoir, a radially faulted dome, buried fluvial channels, and collapse structures overlying an evaporate sequence. We show that the resulting anisotropic p-wave velocity models match in situ measurements in deep boreholes, reproduce detailed structure observed independently on high-resolution seismic reflection sections, accurately predict the raw seismic data, simplify and sharpen reverse-time-migrated reflection images of deeper horizons, and flatten Kirchhoff-migrated common-image gathers. We also show that full-elastic 3D full-waveform inversion of pure pressure data can generate a reasonable shear-wave velocity model for one of these datasets. For two of the four datasets, the inclusion of significant transversely isotropic anisotropy with a vertical axis of symmetry was necessary in order to fit the kinematics of the field data properly. For the faulted dome, the full-waveform-inversion p-wave velocity model recovers the detailed structure of every fault that can be seen on coincident seismic reflection data. Some of the individual faults represent high-velocity zones, some represent low-velocity zones, some have more-complex internal structure, and some are visible merely as offsets between two regions with contrasting velocity. Although this has not yet been demonstrated quantitatively for this dataset, it seems likely that at least some of this fine structure in the recovered velocity model is related to the detailed lithology, strain history and fluid properties within the individual faults. We have here applied this technique to seismic data that were acquired by the extractive industries, however this inversion scheme is immediately scalable and applicable to a much wider range of problems given sufficient quality and density of observed data. Potential targets range from shallow magma chambers beneath active volcanoes, through whole-crustal sections across plate boundaries, to regional and whole-Earth models.

Projected Regression Methods for Inverting Fredholm Integrals: Formalism and Application to Analytical Continuation

NASA Astrophysics Data System (ADS)

Arsenault, Louis-Francois; Neuberg, Richard; Hannah, Lauren A.; Millis, Andrew J.

We present a machine learning-based statistical regression approach to the inversion of Fredholm integrals of the first kind by studying an important example for the quantum materials community, the analytical continuation problem of quantum many-body physics. It involves reconstructing the frequency dependence of physical excitation spectra from data obtained at specific points in the complex frequency plane. The approach provides a natural regularization in cases where the inverse of the Fredholm kernel is ill-conditioned and yields robust error metrics. The stability of the forward problem permits the construction of a large database of input-output pairs. Machine learning methods applied to this database generate approximate solutions which are projected onto the subspace of functions satisfying relevant constraints. We show that for low input noise the method performs as well or better than Maximum Entropy (MaxEnt) under standard error metrics, and is substantially more robust to noise. We expect the methodology to be similarly effective for any problem involving a formally ill-conditioned inversion, provided that the forward problem can be efficiently solved. AJM was supported by the Office of Science of the U.S. Department of Energy under Subcontract No. 3F-3138 and LFA by the Columbia Univeristy IDS-ROADS project, UR009033-05 which also provided part support to RN and LH.

The Thin Oil Film Equation

NASA Technical Reports Server (NTRS)

Brown, James L.; Naughton, Jonathan W.

1999-01-01

A thin film of oil on a surface responds primarily to the wall shear stress generated on that surface by a three-dimensional flow. The oil film is also subject to wall pressure gradients, surface tension effects and gravity. The partial differential equation governing the oil film flow is shown to be related to Burgers' equation. Analytical and numerical methods for solving the thin oil film equation are presented. A direct numerical solver is developed where the wall shear stress variation on the surface is known and which solves for the oil film thickness spatial and time variation on the surface. An inverse numerical solver is also developed where the oil film thickness spatial variation over the surface at two discrete times is known and which solves for the wall shear stress variation over the test surface. A One-Time-Level inverse solver is also demonstrated. The inverse numerical solver provides a mathematically rigorous basis for an improved form of a wall shear stress instrument suitable for application to complex three-dimensional flows. To demonstrate the complexity of flows for which these oil film methods are now suitable, extensive examination is accomplished for these analytical and numerical methods as applied to a thin oil film in the vicinity of a three-dimensional saddle of separation.

A 2D forward and inverse code for streaming potential problems

NASA Astrophysics Data System (ADS)

Soueid Ahmed, A.; Jardani, A.; Revil, A.

2013-12-01

The self-potential method corresponds to the passive measurement of the electrical field in response to the occurrence of natural sources of current in the ground. One of these sources corresponds to the streaming current associated with the flow of the groundwater. We can therefore apply the self- potential method to recover non-intrusively some information regarding the groundwater flow. We first solve the forward problem starting with the solution of the groundwater flow problem, then computing the source current density, and finally solving a Poisson equation for the electrical potential. We use the finite-element method to solve the relevant partial differential equations. In order to reduce the number of (petrophysical) model parameters required to solve the forward problem, we introduced an effective charge density tensor of the pore water, which can be determined directly from the permeability tensor for neutral pore waters. The second aspect of our work concerns the inversion of the self-potential data using Tikhonov regularization with smoothness and weighting depth constraints. This approach accounts for the distribution of the electrical resistivity, which can be independently and approximately determined from electrical resistivity tomography. A numerical code, SP2DINV, has been implemented in Matlab to perform both the forward and inverse modeling. Three synthetic case studies are discussed.

A simulation based method to assess inversion algorithms for transverse relaxation data

NASA Astrophysics Data System (ADS)

Ghosh, Supriyo; Keener, Kevin M.; Pan, Yong

2008-04-01

NMR relaxometry is a very useful tool for understanding various chemical and physical phenomena in complex multiphase systems. A Carr-Purcell-Meiboom-Gill (CPMG) [P.T. Callaghan, Principles of Nuclear Magnetic Resonance Microscopy, Clarendon Press, Oxford, 1991] experiment is an easy and quick way to obtain transverse relaxation constant (T2) in low field. Most of the samples usually have a distribution of T2 values. Extraction of this distribution of T2s from the noisy decay data is essentially an ill-posed inverse problem. Various inversion approaches have been used to solve this problem, to date. A major issue in using an inversion algorithm is determining how accurate the computed distribution is. A systematic analysis of an inversion algorithm, UPEN [G.C. Borgia, R.J.S. Brown, P. Fantazzini, Uniform-penalty inversion of multiexponential decay data, Journal of Magnetic Resonance 132 (1998) 65-77; G.C. Borgia, R.J.S. Brown, P. Fantazzini, Uniform-penalty inversion of multiexponential decay data II. Data spacing, T2 data, systematic data errors, and diagnostics, Journal of Magnetic Resonance 147 (2000) 273-285] was performed by means of simulated CPMG data generation. Through our simulation technique and statistical analyses, the effects of various experimental parameters on the computed distribution were evaluated. We converged to the true distribution by matching up the inversion results from a series of true decay data and a noisy simulated data. In addition to simulation studies, the same approach was also applied on real experimental data to support the simulation results.

Evidence for large inversion polymorphisms in the human genome from HapMap data

PubMed Central

Bansal, Vikas; Bashir, Ali; Bafna, Vineet

2007-01-01

Knowledge about structural variation in the human genome has grown tremendously in the past few years. However, inversions represent a class of structural variation that remains difficult to detect. We present a statistical method to identify large inversion polymorphisms using unusual Linkage Disequilibrium (LD) patterns from high-density SNP data. The method is designed to detect chromosomal segments that are inverted (in a majority of the chromosomes) in a population with respect to the reference human genome sequence. We demonstrate the power of this method to detect such inversion polymorphisms through simulations done using the HapMap data. Application of this method to the data from the first phase of the International HapMap project resulted in 176 candidate inversions ranging from 200 kb to several megabases in length. Our predicted inversions include an 800-kb polymorphic inversion at 7p22, a 1.1-Mb inversion at 16p12, and a novel 1.2-Mb inversion on chromosome 10 that is supported by the presence of two discordant fosmids. Analysis of the genomic sequence around inversion breakpoints showed that 11 predicted inversions are flanked by pairs of highly homologous repeats in the inverted orientation. In addition, for three candidate inversions, the inverted orientation is represented in the Celera genome assembly. Although the power of our method to detect inversions is restricted because of inherently noisy LD patterns in population data, inversions predicted by our method represent strong candidates for experimental validation and analysis. PMID:17185644

Balancing aggregation and smoothing errors in inverse models

DOE PAGES

Turner, A. J.; Jacob, D. J.

2015-06-30

Inverse models use observations of a system (observation vector) to quantify the variables driving that system (state vector) by statistical optimization. When the observation vector is large, such as with satellite data, selecting a suitable dimension for the state vector is a challenge. A state vector that is too large cannot be effectively constrained by the observations, leading to smoothing error. However, reducing the dimension of the state vector leads to aggregation error as prior relationships between state vector elements are imposed rather than optimized. Here we present a method for quantifying aggregation and smoothing errors as a function ofmore » state vector dimension, so that a suitable dimension can be selected by minimizing the combined error. Reducing the state vector within the aggregation error constraints can have the added advantage of enabling analytical solution to the inverse problem with full error characterization. We compare three methods for reducing the dimension of the state vector from its native resolution: (1) merging adjacent elements (grid coarsening), (2) clustering with principal component analysis (PCA), and (3) applying a Gaussian mixture model (GMM) with Gaussian pdfs as state vector elements on which the native-resolution state vector elements are projected using radial basis functions (RBFs). The GMM method leads to somewhat lower aggregation error than the other methods, but more importantly it retains resolution of major local features in the state vector while smoothing weak and broad features.« less

Balancing aggregation and smoothing errors in inverse models

NASA Astrophysics Data System (ADS)

Turner, A. J.; Jacob, D. J.

2015-01-01

Inverse models use observations of a system (observation vector) to quantify the variables driving that system (state vector) by statistical optimization. When the observation vector is large, such as with satellite data, selecting a suitable dimension for the state vector is a challenge. A state vector that is too large cannot be effectively constrained by the observations, leading to smoothing error. However, reducing the dimension of the state vector leads to aggregation error as prior relationships between state vector elements are imposed rather than optimized. Here we present a method for quantifying aggregation and smoothing errors as a function of state vector dimension, so that a suitable dimension can be selected by minimizing the combined error. Reducing the state vector within the aggregation error constraints can have the added advantage of enabling analytical solution to the inverse problem with full error characterization. We compare three methods for reducing the dimension of the state vector from its native resolution: (1) merging adjacent elements (grid coarsening), (2) clustering with principal component analysis (PCA), and (3) applying a Gaussian mixture model (GMM) with Gaussian pdfs as state vector elements on which the native-resolution state vector elements are projected using radial basis functions (RBFs). The GMM method leads to somewhat lower aggregation error than the other methods, but more importantly it retains resolution of major local features in the state vector while smoothing weak and broad features.

Balancing aggregation and smoothing errors in inverse models

NASA Astrophysics Data System (ADS)

Turner, A. J.; Jacob, D. J.

2015-06-01

Inverse models use observations of a system (observation vector) to quantify the variables driving that system (state vector) by statistical optimization. When the observation vector is large, such as with satellite data, selecting a suitable dimension for the state vector is a challenge. A state vector that is too large cannot be effectively constrained by the observations, leading to smoothing error. However, reducing the dimension of the state vector leads to aggregation error as prior relationships between state vector elements are imposed rather than optimized. Here we present a method for quantifying aggregation and smoothing errors as a function of state vector dimension, so that a suitable dimension can be selected by minimizing the combined error. Reducing the state vector within the aggregation error constraints can have the added advantage of enabling analytical solution to the inverse problem with full error characterization. We compare three methods for reducing the dimension of the state vector from its native resolution: (1) merging adjacent elements (grid coarsening), (2) clustering with principal component analysis (PCA), and (3) applying a Gaussian mixture model (GMM) with Gaussian pdfs as state vector elements on which the native-resolution state vector elements are projected using radial basis functions (RBFs). The GMM method leads to somewhat lower aggregation error than the other methods, but more importantly it retains resolution of major local features in the state vector while smoothing weak and broad features.

Moment tensor analysis of very shallow sources

DOE PAGES

Chiang, Andrea; Dreger, Douglas S.; Ford, Sean R.; ...

2016-10-11

An issue for moment tensor (MT) inversion of shallow seismic sources is that some components of the Green’s functions have vanishing amplitudes at the free surface, which can result in bias in the MT solution. The effects of the free surface on the stability of the MT method become important as we continue to investigate and improve the capabilities of regional full MT inversion for source–type identification and discrimination. It is important to understand free–surface effects on discriminating shallow explosive sources for nuclear monitoring purposes. It may also be important in natural systems that have very shallow seismicity, such asmore » volcanic and geothermal systems. We examine the effects of the free surface on the MT via synthetic testing and apply the MT–based discrimination method to three quarry blasts from the HUMMING ALBATROSS experiment. These shallow chemical explosions at ~10 m depth and recorded up to several kilometers distance represent rather severe source–station geometry in terms of free–surface effects. We show that the method is capable of recovering a predominantly explosive source mechanism, and the combined waveform and first–motion method enables the unique discrimination of these events. Furthermore, recovering the design yield using seismic moment estimates from MT inversion remains challenging, but we can begin to put error bounds on our moment estimates using the network sensitivity solution technique.« less

Silk fibroin scaffolds with inverse opal structure for bone tissue engineering

PubMed Central

Sommer, Marianne R.; Vetsch, Jolanda R.; Leemann, Jessica; Müller, Ralph

2016-01-01

Abstract How scaffold porosity, pore diameter and geometry influence cellular behavior is‐although heavily researched ‐ merely understood, especially in 3D. This is mainly caused by a lack of suitable, reproducible scaffold fabrication methods, with processes such as gas foaming, lyophilization or particulate leaching still being the standard. Here we propose a method to generate highly porous silk fibroin scaffolds with monodisperse spherical pores, namely inverse opals, and study their effect on cell behavior. These silk fibroin inverse opal scaffolds were compared to salt‐leached silk fibroin scaffolds in terms of human mesenchymal stem cell response upon osteogenic differentiation signals. While cell number remained similar on both scaffold types, extracellular matrix mineralization nearly doubled on the newly developed scaffolds, suggesting a positive effect on cell differentiation. By using the very same material with comparable average pore diameters, this increase in mineral content can be attributed to either the differences in pore diameter distribution or the pore geometry. Although the exact mechanisms leading to enhanced mineralization in inverse opals are not yet fully understood, our results indicate that control over pore geometry alone can have a major impact on the bioactivity of a scaffold toward stem cell differentiation into bone tissue. © 2016 The Authors Journal of Biomedical Materials Research Part B: Applied Biomaterials Published by Wiley Periodicals, Inc. J Biomed Mater Res Part B: Appl Biomater, 105B: 2074–2084, 2017. PMID:27407014

Global Ocean Circulation in Thermohaline Coordinates and Small-scale and Mesoscale mixing: An Inverse Estimate.

NASA Astrophysics Data System (ADS)

Groeskamp, S.; Zika, J. D.; McDougall, T. J.; Sloyan, B.

2016-02-01

I will present results of a new inverse technique that infers small-scale turbulent diffusivities and mesoscale eddy diffusivities from an ocean climatology of Salinity (S) and Temperature (T) in combination with surface freshwater and heat fluxes.First, the ocean circulation is represented in (S,T) coordinates, by the diathermohaline streamfunction. Framing the ocean circulation in (S,T) coordinates, isolates the component of the circulation that is directly related to water-mass transformation.Because water-mass transformation is directly related to fluxes of salt and heat, this framework allows for the formulation of an inverse method in which the diathermohaline streamfunction is balanced with known air-sea forcing and unknown mixing. When applying this inverse method to observations, we obtain observationally based estimates for both the streamfunction and the mixing. The results reveal new information about the component of the global ocean circulation due to water-mass transformation and its relation to surface freshwater and heat fluxes and small-scale and mesoscale mixing. The results provide global constraints on spatially varying patterns of diffusivities, in order to obtain a realistic overturning circulation. We find that mesoscale isopycnal mixing is much smaller than expected. These results are important for our understanding of the relation between global ocean circulation and mixing and may lead to improved parameterisations in numerical ocean models.

Beam hardening correction for interior tomography based on exponential formed model and radon inversion transform

NASA Astrophysics Data System (ADS)

Chen, Siyu; Zhang, Hanming; Li, Lei; Xi, Xiaoqi; Han, Yu; Yan, Bin

2016-10-01

X-ray computed tomography (CT) has been extensively applied in industrial non-destructive testing (NDT). However, in practical applications, the X-ray beam polychromaticity often results in beam hardening problems for image reconstruction. The beam hardening artifacts, which manifested as cupping, streaks and flares, not only debase the image quality, but also disturb the subsequent analyses. Unfortunately, conventional CT scanning requires that the scanned object is completely covered by the field of view (FOV), the state-of-art beam hardening correction methods only consider the ideal scanning configuration, and often suffer problems for interior tomography due to the projection truncation. Aiming at this problem, this paper proposed a beam hardening correction method based on radon inversion transform for interior tomography. Experimental results show that, compared to the conventional correction algorithms, the proposed approach has achieved excellent performance in both beam hardening artifacts reduction and truncation artifacts suppression. Therefore, the presented method has vitally theoretic and practicable meaning in artifacts correction of industrial CT.

Mapping thunder sources by inverting acoustic and electromagnetic observations

NASA Astrophysics Data System (ADS)

Anderson, J. F.; Johnson, J. B.; Arechiga, R. O.; Thomas, R. J.

2014-12-01

We present a new method of locating current flow in lightning strikes by inversion of thunder recordings constrained by Lightning Mapping Array observations. First, radio frequency (RF) pulses are connected to reconstruct conductive channels created by leaders. Then, acoustic signals that would be produced by current flow through each channel are forward modeled. The recorded thunder is considered to consist of a weighted superposition of these acoustic signals. We calculate the posterior distribution of acoustic source energy for each channel with a Markov Chain Monte Carlo inversion that fits power envelopes of modeled and recorded thunder; these results show which parts of the flash carry current and produce thunder. We examine the effects of RF pulse location imprecision and atmospheric winds on quality of results and apply this method to several lightning flashes over the Magdalena Mountains in New Mexico, USA. This method will enable more detailed study of lightning phenomena by allowing researchers to map current flow in addition to leader propagation.

Characterizing crustal and uppermost mantle anisotropy with a depth-dependent tilted hexagonally symmetric elastic tensor: theory and examples

NASA Astrophysics Data System (ADS)

Feng, L.; Xie, J.; Ritzwoller, M. H.

2017-12-01

Two major types of surface wave anisotropy are commonly observed by seismologists but are only rarely interpreted jointly: apparent radial anisotropy, which is the difference in propagation speed between horizontally and vertically polarized waves inferred from Love and Rayleigh waves, and apparent azimuthal anisotropy, which is the directional dependence of surface wave speeds (usually Rayleigh waves). We describe a method of inversion that interprets simultaneous observations of radial and azimuthal anisotropy under the assumption of a hexagonally symmetric elastic tensor with a tilted symmetry axis defined by dip and strike angles. With a full-waveform numerical solver based on the spectral element method (SEM), we verify the validity of the forward theory used for the inversion. We also present two examples, in the US and Tibet, in which we have successfully applied the tomographic method to demonstrate that the two types of apparent anisotropy can be interpreted jointly as a tilted hexagonally symmetric medium.

Monotonicity based imaging method for time-domain eddy current problems

NASA Astrophysics Data System (ADS)

Su, Z.; Ventre, S.; Udpa, L.; Tamburrino, A.

2017-12-01

Eddy current imaging is an example of inverse problem in nondestructive evaluation for detecting anomalies in conducting materials. This paper introduces the concept of time constants and associated natural modes in eddy current imaging. The monotonicity of time constants is then described and applied to develop a non-iterative imaging method. The proposed imaging method has a low computational cost which makes it suitable for real-time operations. Full 3D numerical examples prove the effectiveness of the method in realistic scenarios. This paper is dedicated to Professor Guglielmo Rubinacci on the occasion of his 65th Birthday.

PCR-based karyotyping of Anopheles gambiae inversion 2Rj identifies the BAMAKO chromosomal form.

PubMed

Coulibaly, Mamadou B; Pombi, Marco; Caputo, Beniamino; Nwakanma, Davis; Jawara, Musa; Konate, Lassana; Dia, Ibrahima; Fofana, Abdrahamane; Kern, Marcia; Simard, Frédéric; Conway, David J; Petrarca, Vincenzo; della Torre, Alessandra; Traoré, Sékou; Besansky, Nora J

2007-10-01

The malaria vector Anopheles gambiae is polymorphic for chromosomal inversions on the right arm of chromosome 2 that segregate nonrandomly between assortatively mating populations in West Africa. One such inversion, 2Rj, is associated with the BAMAKO chromosomal form endemic to southern Mali and northern Guinea Conakry near the Niger River. Although it exploits a unique ecology and both molecular and chromosomal data suggest reduced gene flow between BAMAKO and other A. gambiae populations, no molecular markers exist to identify this form. To facilitate study of the BAMAKO form, a PCR assay for molecular karyotyping of 2Rj was developed based on sequences at the breakpoint junctions. The assay was extensively validated using more than 700 field specimens whose karyotypes were determined in parallel by cytogenetic and molecular methods. As inversion 2Rj also occurs in SAVANNA populations outside the geographic range of BAMAKO, samples were tested from Senegal, Cameroon and western Guinea Conakry as well as from Mali. In southern Mali, where 2Rj polymorphism in SAVANNA populations was very low and most of the 2Rj homozygotes were found in BAMAKO karyotypes, the molecular and cytogenetic methods were almost perfectly congruent. Elsewhere agreement between the methods was much poorer, as the molecular assay frequently misclassified 2Rj heterozygotes as 2R+j standard homozygotes. Molecular karyotyping of 2Rj is robust and accurate on 2R+j standard and 2Rj inverted homozygotes. Therefore, the proposed approach overcomes the lack of a rapid tool for identifying the BAMAKO form across developmental stages and sexes, and opens new perspectives for the study of BAMAKO ecology and behaviour. On the other hand, the method should not be applied for molecular karyotyping of j-carriers within the SAVANNA chromosomal form.

Basis set expansion for inverse problems in plasma diagnostic analysis

DOE Office of Scientific and Technical Information (OSTI.GOV)

Jones, B.; Ruiz, C. L.

A basis set expansion method [V. Dribinski, A. Ossadtchi, V. A. Mandelshtam, and H. Reisler, Rev. Sci. Instrum. 73, 2634 (2002)] is applied to recover physical information about plasma radiation sources from instrument data, which has been forward transformed due to the nature of the measurement technique. This method provides a general approach for inverse problems, and we discuss two specific examples relevant to diagnosing fast z pinches on the 20–25 MA Z machine [M. E. Savage, L. F. Bennett, D. E. Bliss, W. T. Clark, R. S. Coats, J. M. Elizondo, K. R. LeChien, H. C. Harjes, J. M.more » Lehr, J. E. Maenchen, D. H. McDaniel, M. F. Pasik, T. D. Pointon, A. C. Owen, D. B. Seidel, D. L. Smith, B. S. Stoltzfus, K. W. Struve, W. A. Stygar, L. K. Warne, J. R. Woodworth, C. W. Mendel, K. R. Prestwich, R. W. Shoup, D. L. Johnson, J. P. Corley, K. C. Hodge, T. C. Wagoner, and P. E. Wakeland, in Proceedings of the Pulsed Power Plasma Sciences Conference (IEEE, 2007), p. 979]. First, Abel inversion of time-gated, self-emission x-ray images from a wire array implosion is studied. Second, we present an approach for unfolding neutron time-of-flight measurements from a deuterium gas puff z pinch to recover information about emission time history and energy distribution. Through these examples, we discuss how noise in the measured data limits the practical resolution of the inversion, and how the method handles discontinuities in the source function and artifacts in the projected image. We add to the method a propagation of errors calculation for estimating uncertainties in the inverted solution.« less

An Inverse Method to Estimate the Root Water Uptake Source-Sink Term in Soil Water Transport Equation under the Effect of Superabsorbent Polymer

PubMed Central

Liao, Renkuan; Yang, Peiling; Wu, Wenyong; Ren, Shumei

2016-01-01

The widespread use of superabsorbent polymers (SAPs) in arid regions improves the efficiency of local land and water use. However, SAPs’ repeated absorption and release of water has periodic and unstable effects on both soil’s physical and chemical properties and on the growth of plant roots, which complicates modeling of water movement in SAP-treated soils. In this paper, we proposea model of soil water movement for SAP-treated soils. The residence time of SAP in the soil and the duration of the experiment were considered as the same parameter t. This simplifies previously proposed models in which the residence time of SAP in the soil and the experiment’s duration were considered as two independent parameters. Numerical testing was carried out on the inverse method of estimating the source/sink term of root water uptake in the model of soil water movement under the effect of SAP. The test results show that time interval, hydraulic parameters, test error, and instrument precision had a significant influence on the stability of the inverse method, while time step, layering of soil, and boundary conditions had relatively smaller effects. A comprehensive analysis of the method’s stability, calculation, and accuracy suggests that the proposed inverse method applies if the following conditions are satisfied: the time interval is between 5 d and 17 d; the time step is between 1000 and 10000; the test error is ≥ 0.9; the instrument precision is ≤ 0.03; and the rate of soil surface evaporation is ≤ 0.6 mm/d. PMID:27505000

Basis set expansion for inverse problems in plasma diagnostic analysis

NASA Astrophysics Data System (ADS)

Jones, B.; Ruiz, C. L.

2013-07-01

A basis set expansion method [V. Dribinski, A. Ossadtchi, V. A. Mandelshtam, and H. Reisler, Rev. Sci. Instrum. 73, 2634 (2002)], 10.1063/1.1482156 is applied to recover physical information about plasma radiation sources from instrument data, which has been forward transformed due to the nature of the measurement technique. This method provides a general approach for inverse problems, and we discuss two specific examples relevant to diagnosing fast z pinches on the 20-25 MA Z machine [M. E. Savage, L. F. Bennett, D. E. Bliss, W. T. Clark, R. S. Coats, J. M. Elizondo, K. R. LeChien, H. C. Harjes, J. M. Lehr, J. E. Maenchen, D. H. McDaniel, M. F. Pasik, T. D. Pointon, A. C. Owen, D. B. Seidel, D. L. Smith, B. S. Stoltzfus, K. W. Struve, W. A. Stygar, L. K. Warne, J. R. Woodworth, C. W. Mendel, K. R. Prestwich, R. W. Shoup, D. L. Johnson, J. P. Corley, K. C. Hodge, T. C. Wagoner, and P. E. Wakeland, in Proceedings of the Pulsed Power Plasma Sciences Conference (IEEE, 2007), p. 979]. First, Abel inversion of time-gated, self-emission x-ray images from a wire array implosion is studied. Second, we present an approach for unfolding neutron time-of-flight measurements from a deuterium gas puff z pinch to recover information about emission time history and energy distribution. Through these examples, we discuss how noise in the measured data limits the practical resolution of the inversion, and how the method handles discontinuities in the source function and artifacts in the projected image. We add to the method a propagation of errors calculation for estimating uncertainties in the inverted solution.

A parallel algorithm for 2D visco-acoustic frequency-domain full-waveform inversion: application to a dense OBS data set

NASA Astrophysics Data System (ADS)

Sourbier, F.; Operto, S.; Virieux, J.

2006-12-01

We present a distributed-memory parallel algorithm for 2D visco-acoustic full-waveform inversion of wide-angle seismic data. Our code is written in fortran90 and use MPI for parallelism. The algorithm was applied to real wide-angle data set recorded by 100 OBSs with a 1-km spacing in the eastern-Nankai trough (Japan) to image the deep structure of the subduction zone. Full-waveform inversion is applied sequentially to discrete frequencies by proceeding from the low to the high frequencies. The inverse problem is solved with a classic gradient method. Full-waveform modeling is performed with a frequency-domain finite-difference method. In the frequency-domain, solving the wave equation requires resolution of a large unsymmetric system of linear equations. We use the massively parallel direct solver MUMPS (http://www.enseeiht.fr/irit/apo/MUMPS) for distributed-memory computer to solve this system. The MUMPS solver is based on a multifrontal method for the parallel factorization. The MUMPS algorithm is subdivided in 3 main steps: a symbolic analysis step that performs re-ordering of the matrix coefficients to minimize the fill-in of the matrix during the subsequent factorization and an estimation of the assembly tree of the matrix. Second, the factorization is performed with dynamic scheduling to accomodate numerical pivoting and provides the LU factors distributed over all the processors. Third, the resolution is performed for multiple sources. To compute the gradient of the cost function, 2 simulations per shot are required (one to compute the forward wavefield and one to back-propagate residuals). The multi-source resolutions can be performed in parallel with MUMPS. In the end, each processor stores in core a sub-domain of all the solutions. These distributed solutions can be exploited to compute in parallel the gradient of the cost function. Since the gradient of the cost function is a weighted stack of the shot and residual solutions of MUMPS, each processor computes the corresponding sub-domain of the gradient. In the end, the gradient is centralized on the master processor using a collective communation. The gradient is scaled by the diagonal elements of the Hessian matrix. This scaling is computed only once per frequency before the first iteration of the inversion. Estimation of the diagonal terms of the Hessian requires performing one simulation per non redondant shot and receiver position. The same strategy that the one used for the gradient is used to compute the diagonal Hessian in parallel. This algorithm was applied to a dense wide-angle data set recorded by 100 OBSs in the eastern Nankai trough, offshore Japan. Thirteen frequencies ranging from 3 and 15 Hz were inverted. Tweny iterations per frequency were computed leading to 260 tomographic velocity models of increasing resolution. The velocity model dimensions are 105 km x 25 km corresponding to a finite-difference grid of 4201 x 1001 grid with a 25-m grid interval. The number of shot was 1005 and the number of inverted OBS gathers was 93. The inversion requires 20 days on 6 32-bits bi-processor nodes with 4 Gbytes of RAM memory per node when only the LU factorization is performed in parallel. Preliminary estimations of the time required to perform the inversion with the fully-parallelized code is 6 and 4 days using 20 and 50 processors respectively.

Variable-permittivity linear inverse problem for the H(sub z)-polarized case

NASA Technical Reports Server (NTRS)

Moghaddam, M.; Chew, W. C.

1993-01-01

The H(sub z)-polarized inverse problem has rarely been studied before due to the complicated way in which the unknown permittivity appears in the wave equation. This problem is equivalent to the acoustic inverse problem with variable density. We have recently reported the solution to the nonlinear variable-permittivity H(sub z)-polarized inverse problem using the Born iterative method. Here, the linear inverse problem is solved for permittivity (epsilon) and permeability (mu) using a different approach which is an extension of the basic ideas of diffraction tomography (DT). The key to solving this problem is to utilize frequency diversity to obtain the required independent measurements. The receivers are assumed to be in the far field of the object, and plane wave incidence is also assumed. It is assumed that the scatterer is weak, so that the Born approximation can be used to arrive at a relationship between the measured pressure field and two terms related to the spatial Fourier transform of the two unknowns, epsilon and mu. The term involving permeability corresponds to monopole scattering and that for permittivity to dipole scattering. Measurements at several frequencies are used and a least squares problem is solved to reconstruct epsilon and mu. It is observed that the low spatial frequencies in the spectra of epsilon and mu produce inaccuracies in the results. Hence, a regularization method is devised to remove this problem. Several results are shown. Low contrast objects for which the above analysis holds are used to show that good reconstructions are obtained for both permittivity and permeability after regularization is applied.

Delineation of a quick clay zone at Smørgrav, Norway, with electromagnetic methods under geotechnical constraints

NASA Astrophysics Data System (ADS)

Kalscheuer, Thomas; Bastani, Mehrdad; Donohue, Shane; Persson, Lena; Aspmo Pfaffhuber, Andreas; Reiser, Fabienne; Ren, Zhengyong

2013-05-01

In many coastal areas of North America and Scandinavia, post-glacial clay sediments have emerged above sea level due to iso-static uplift. These clays are often destabilised by fresh water leaching and transformed to so-called quick clays as at the investigated area at Smørgrav, Norway. Slight mechanical disturbances of these materials may trigger landslides. Since the leaching increases the electrical resistivity of quick clay as compared to normal marine clay, the application of electromagnetic (EM) methods is of particular interest in the study of quick clay structures. For the first time, single and joint inversions of direct-current resistivity (DCR), radiomagnetotelluric (RMT) and controlled-source audiomagnetotelluric (CSAMT) data were applied to delineate a zone of quick clay. The resulting 2-D models of electrical resistivity correlate excellently with previously published data from a ground conductivity metre and resistivity logs from two resistivity cone penetration tests (RCPT) into marine clay and quick clay. The RCPT log into the central part of the quick clay identifies the electrical resistivity of the quick clay structure to lie between 10 and 80 Ω m. In combination with the 2-D inversion models, it becomes possible to delineate the vertical and horizontal extent of the quick clay zone. As compared to the inversions of single data sets, the joint inversion model exhibits sharper resistivity contrasts and its resistivity values are more characteristic of the expected geology. In our preferred joint inversion model, there is a clear demarcation between dry soil, marine clay, quick clay and bedrock, which consists of alum shale and limestone.

Extracting grain-orientation-dependent data from in situ time-of-flight neutron diffraction. I. Inverse pole figures

DOE PAGES

Stoica, Grigoreta M.; Stoica, Alexandru Dan; An, Ke; ...

2014-11-28

The problem of calculating the inverse pole figure (IPF) is analyzed from the perspective of the application of time-of flight neutron diffraction toin situmonitoring of the thermomechanical behavior of engineering materials. On the basis of a quasi-Monte Carlo (QMC) method, a consistent set of grain orientations is generated and used to compute the weighting factors for IPF normalization. The weighting factors are instrument dependent and were calculated for the engineering materials diffractometer VULCAN (Spallation Neutron Source, Oak Ridge National Laboratory). The QMC method is applied to face-centered cubic structures and can be easily extended to other crystallographic symmetries. Examples includemore » 316LN stainless steelin situloaded in tension at room temperature and an Al–2%Mg alloy, substantially deformed by cold rolling and in situannealed up to 653 K.« less

Source localization in electromyography using the inverse potential problem

NASA Astrophysics Data System (ADS)

van den Doel, Kees; Ascher, Uri M.; Pai, Dinesh K.

2011-02-01

We describe an efficient method for reconstructing the activity in human muscles from an array of voltage sensors on the skin surface. MRI is used to obtain morphometric data which are segmented into muscle tissue, fat, bone and skin, from which a finite element model for volume conduction is constructed. The inverse problem of finding the current sources in the muscles is solved using a careful regularization technique which adds a priori information, yielding physically reasonable solutions from among those that satisfy the basic potential problem. Several regularization functionals are considered and numerical experiments on a 2D test model are performed to determine which performs best. The resulting scheme leads to numerical difficulties when applied to large-scale 3D problems. We clarify the nature of these difficulties and provide a method to overcome them, which is shown to perform well in the large-scale problem setting.

New Approaches to Minimum-Energy Design of Integer- and Fractional-Order Perfect Control Algorithms

NASA Astrophysics Data System (ADS)

Hunek, Wojciech P.; Wach, Łukasz

2017-10-01

In this paper the new methods concerning the energy-based minimization of the perfect control inputs is presented. For that reason the multivariable integer- and fractional-order models are applied which can be used for describing a various real world processes. Up to now, the classical approaches have been used in forms of minimum-norm/least squares inverses. Notwithstanding, the above-mentioned tool do not guarantee the optimal control corresponding to optimal input energy. Therefore the new class of inversebased methods has been introduced, in particular the new σ- and H-inverse of nonsquare parameter and polynomial matrices. Thus a proposed solution remarkably outperforms the typical ones in systems where the control runs can be understood in terms of different physical quantities, for example heat and mass transfer, electricity etc. A simulation study performed in Matlab/Simulink environment confirms the big potential of the new energy-based approaches.

Simultaneous stochastic inversion for geomagnetic main field and secular variation. II - 1820-1980

NASA Technical Reports Server (NTRS)

Bloxham, Jeremy; Jackson, Andrew

1989-01-01

With the aim of producing readable time-dependent maps of the geomagnetic field at the core-mantle boundary, the method of simultaneous stochastic inversion for the geomagnetic main field and secular variation, described by Bloxham (1987), was applied to survey data from the period 1820-1980 to yield two time-dependent geomagnetic-field models, one for the period 1900-1980 and the other for 1820-1900. Particular consideration was given to the effect of crustal fields on observations. It was found that the existing methods of accounting for these fields as sources of random noise are inadequate in two circumstances: (1) when sequences of measurements are made at one particular site, and (2) for measurements made at satellite altitude. The present model shows many of the features in the earth's magnetic field at the core-mantle boundary described by Bloxham and Gubbins (1985) and supports many of their earlier conclusions.

Inverse atmospheric radiative transfer problems - A nonlinear minimization search method of solution. [aerosol pollution monitoring

NASA Technical Reports Server (NTRS)

Fymat, A. L.

1976-01-01

The paper studies the inversion of the radiative transfer equation describing the interaction of electromagnetic radiation with atmospheric aerosols. The interaction can be considered as the propagation in the aerosol medium of two light beams: the direct beam in the line-of-sight attenuated by absorption and scattering, and the diffuse beam arising from scattering into the viewing direction, which propagates more or less in random fashion. The latter beam has single scattering and multiple scattering contributions. In the former case and for single scattering, the problem is reducible to first-kind Fredholm equations, while for multiple scattering it is necessary to invert partial integrodifferential equations. A nonlinear minimization search method, applicable to the solution of both types of problems has been developed, and is applied here to the problem of monitoring aerosol pollution, namely the complex refractive index and size distribution of aerosol particles.

Robust Inversion and Data Compression in Control Allocation

NASA Technical Reports Server (NTRS)

Hodel, A. Scottedward

2000-01-01

We present an off-line computational method for control allocation design. The control allocation function delta = F(z)tau = delta (sub 0) (z) mapping commanded body-frame torques to actuator commands is implicitly specified by trim condition delta (sub 0) (z) and by a robust pseudo-inverse problem double vertical line I - G(z) F(z) double vertical line less than epsilon (z) where G(z) is a system Jacobian evaluated at operating point z, z circumflex is an estimate of z, and epsilon (z) less than 1 is a specified error tolerance. The allocation function F(z) = sigma (sub i) psi (z) F (sub i) is computed using a heuristic technique for selecting wavelet basis functions psi and a constrained least-squares criterion for selecting the allocation matrices F (sub i). The method is applied to entry trajectory control allocation for a reusable launch vehicle (X-33).

Parallelized Three-Dimensional Resistivity Inversion Using Finite Elements And Adjoint State Methods

NASA Astrophysics Data System (ADS)

Schaa, Ralf; Gross, Lutz; Du Plessis, Jaco

2015-04-01

The resistivity method is one of the oldest geophysical exploration methods, which employs one pair of electrodes to inject current into the ground and one or more pairs of electrodes to measure the electrical potential difference. The potential difference is a non-linear function of the subsurface resistivity distribution described by an elliptic partial differential equation (PDE) of the Poisson type. Inversion of measured potentials solves for the subsurface resistivity represented by PDE coefficients. With increasing advances in multichannel resistivity acquisition systems (systems with more than 60 channels and full waveform recording are now emerging), inversion software require efficient storage and solver algorithms. We developed the finite element solver Escript, which provides a user-friendly programming environment in Python to solve large-scale PDE-based problems (see https://launchpad.net/escript-finley). Using finite elements, highly irregular shaped geology and topography can readily be taken into account. For the 3D resistivity problem, we have implemented the secondary potential approach, where the PDE is decomposed into a primary potential caused by the source current and the secondary potential caused by changes in subsurface resistivity. The primary potential is calculated analytically, and the boundary value problem for the secondary potential is solved using nodal finite elements. This approach removes the singularity caused by the source currents and provides more accurate 3D resistivity models. To solve the inversion problem we apply a 'first optimize then discretize' approach using the quasi-Newton scheme in form of the limited-memory Broyden-Fletcher-Goldfarb-Shanno (L-BFGS) method (see Gross & Kemp 2013). The evaluation of the cost function requires the solution of the secondary potential PDE for each source current and the solution of the corresponding adjoint-state PDE for the cost function gradients with respect to the subsurface resistivity. The Hessian of the regularization term is used as preconditioner which requires an additional PDE solution in each iteration step. As it turns out, the relevant PDEs are naturally formulated in the finite element framework. Using the domain decomposition method provided in Escript, the inversion scheme has been parallelized for distributed memory computers with multi-core shared memory nodes. We show numerical examples from simple layered models to complex 3D models and compare with the results from other methods. The inversion scheme is furthermore tested on a field data example to characterise localised freshwater discharge in a coastal environment.. References: L. Gross and C. Kemp (2013) Large Scale Joint Inversion of Geophysical Data using the Finite Element Method in escript. ASEG Extended Abstracts 2013, http://dx.doi.org/10.1071/ASEG2013ab306

The attitude inversion method of geostationary satellites based on unscented particle filter

NASA Astrophysics Data System (ADS)

Du, Xiaoping; Wang, Yang; Hu, Heng; Gou, Ruixin; Liu, Hao

2018-04-01

The attitude information of geostationary satellites is difficult to be obtained since they are presented in non-resolved images on the ground observation equipment in space object surveillance. In this paper, an attitude inversion method for geostationary satellite based on Unscented Particle Filter (UPF) and ground photometric data is presented. The inversion algorithm based on UPF is proposed aiming at the strong non-linear feature in the photometric data inversion for satellite attitude, which combines the advantage of Unscented Kalman Filter (UKF) and Particle Filter (PF). This update method improves the particle selection based on the idea of UKF to redesign the importance density function. Moreover, it uses the RMS-UKF to partially correct the prediction covariance matrix, which improves the applicability of the attitude inversion method in view of UKF and the particle degradation and dilution of the attitude inversion method based on PF. This paper describes the main principles and steps of algorithm in detail, correctness, accuracy, stability and applicability of the method are verified by simulation experiment and scaling experiment in the end. The results show that the proposed method can effectively solve the problem of particle degradation and depletion in the attitude inversion method on account of PF, and the problem that UKF is not suitable for the strong non-linear attitude inversion. However, the inversion accuracy is obviously superior to UKF and PF, in addition, in the case of the inversion with large attitude error that can inverse the attitude with small particles and high precision.

Inverse scattering theory: Inverse scattering series method for one dimensional non-compact support potential

DOE Office of Scientific and Technical Information (OSTI.GOV)

Yao, Jie, E-mail: yjie2@uh.edu; Lesage, Anne-Cécile; Hussain, Fazle

2014-12-15

The reversion of the Born-Neumann series of the Lippmann-Schwinger equation is one of the standard ways to solve the inverse acoustic scattering problem. One limitation of the current inversion methods based on the reversion of the Born-Neumann series is that the velocity potential should have compact support. However, this assumption cannot be satisfied in certain cases, especially in seismic inversion. Based on the idea of distorted wave scattering, we explore an inverse scattering method for velocity potentials without compact support. The strategy is to decompose the actual medium as a known single interface reference medium, which has the same asymptoticmore » form as the actual medium and a perturbative scattering potential with compact support. After introducing the method to calculate the Green’s function for the known reference potential, the inverse scattering series and Volterra inverse scattering series are derived for the perturbative potential. Analytical and numerical examples demonstrate the feasibility and effectiveness of this method. Besides, to ensure stability of the numerical computation, the Lanczos averaging method is employed as a filter to reduce the Gibbs oscillations for the truncated discrete inverse Fourier transform of each order. Our method provides a rigorous mathematical framework for inverse acoustic scattering with a non-compact support velocity potential.« less

Efficient computational methods for electromagnetic imaging with applications to 3D magnetotellurics

NASA Astrophysics Data System (ADS)

Kordy, Michal Adam

The motivation for this work is the forward and inverse problem for magnetotellurics, a frequency domain electromagnetic remote-sensing geophysical method used in mineral, geothermal, and groundwater exploration. The dissertation consists of four papers. In the first paper, we prove the existence and uniqueness of a representation of any vector field in H(curl) by a vector lying in H(curl) and H(div). It allows us to represent electric or magnetic fields by another vector field, for which nodal finite element approximation may be used in the case of non-constant electromagnetic properties. With this approach, the system matrix does not become ill-posed for low-frequency. In the second paper, we consider hexahedral finite element approximation of an electric field for the magnetotelluric forward problem. The near-null space of the system matrix for low frequencies makes the numerical solution unstable in the air. We show that the proper solution may obtained by applying a correction on the null space of the curl. It is done by solving a Poisson equation using discrete Helmholtz decomposition. We parallelize the forward code on multicore workstation with large RAM. In the next paper, we use the forward code in the inversion. Regularization of the inversion is done by using the second norm of the logarithm of conductivity. The data space Gauss-Newton approach allows for significant savings in memory and computational time. We show the efficiency of the method by considering a number of synthetic inversions and we apply it to real data collected in Cascade Mountains. The last paper considers a cross-frequency interpolation of the forward response as well as the Jacobian. We consider Pade approximation through model order reduction and rational Krylov subspace. The interpolating frequencies are chosen adaptively in order to minimize the maximum error of interpolation. Two error indicator functions are compared. We prove a theorem of almost always lucky failure in the case of the right hand analytically dependent on frequency. The operator's null space is treated by decomposing the solution into the part in the null space and orthogonal to it.