Numerical methods for the inverse problem of density functional theory

DOE PAGES

Jensen, Daniel S.; Wasserman, Adam

2017-07-17

Here, the inverse problem of Kohn–Sham density functional theory (DFT) is often solved in an effort to benchmark and design approximate exchange-correlation potentials. The forward and inverse problems of DFT rely on the same equations but the numerical methods for solving each problem are substantially different. We examine both problems in this tutorial with a special emphasis on the algorithms and error analysis needed for solving the inverse problem. Two inversion methods based on partial differential equation constrained optimization and constrained variational ideas are introduced. We compare and contrast several different inversion methods applied to one-dimensional finite and periodic modelmore » systems.« less

Numerical methods for the inverse problem of density functional theory

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

Jensen, Daniel S.; Wasserman, Adam

Here, the inverse problem of Kohn–Sham density functional theory (DFT) is often solved in an effort to benchmark and design approximate exchange-correlation potentials. The forward and inverse problems of DFT rely on the same equations but the numerical methods for solving each problem are substantially different. We examine both problems in this tutorial with a special emphasis on the algorithms and error analysis needed for solving the inverse problem. Two inversion methods based on partial differential equation constrained optimization and constrained variational ideas are introduced. We compare and contrast several different inversion methods applied to one-dimensional finite and periodic modelmore » systems.« less

Estimation of biological parameters of marine organisms using linear and nonlinear acoustic scattering model-based inversion methods.

PubMed

Chu, Dezhang; Lawson, Gareth L; Wiebe, Peter H

2016-05-01

The linear inversion commonly used in fisheries and zooplankton acoustics assumes a constant inversion kernel and ignores the uncertainties associated with the shape and behavior of the scattering targets, as well as other relevant animal parameters. Here, errors of the linear inversion due to uncertainty associated with the inversion kernel are quantified. A scattering model-based nonlinear inversion method is presented that takes into account the nonlinearity of the inverse problem and is able to estimate simultaneously animal abundance and the parameters associated with the scattering model inherent to the kernel. It uses sophisticated scattering models to estimate first, the abundance, and second, the relevant shape and behavioral parameters of the target organisms. Numerical simulations demonstrate that the abundance, size, and behavior (tilt angle) parameters of marine animals (fish or zooplankton) can be accurately inferred from the inversion by using multi-frequency acoustic data. The influence of the singularity and uncertainty in the inversion kernel on the inversion results can be mitigated by examining the singular values for linear inverse problems and employing a non-linear inversion involving a scattering model-based kernel.

2D joint inversion of CSAMT and magnetic data based on cross-gradient theory

NASA Astrophysics Data System (ADS)

Wang, Kun-Peng; Tan, Han-Dong; Wang, Tao

2017-06-01

A two-dimensional forward and backward algorithm for the controlled-source audio-frequency magnetotelluric (CSAMT) method is developed to invert data in the entire region (near, transition, and far) and deal with the effects of artificial sources. First, a regularization factor is introduced in the 2D magnetic inversion, and the magnetic susceptibility is updated in logarithmic form so that the inversion magnetic susceptibility is always positive. Second, the joint inversion of the CSAMT and magnetic methods is completed with the introduction of the cross gradient. By searching for the weight of the cross-gradient term in the objective function, the mutual influence between two different physical properties at different locations are avoided. Model tests show that the joint inversion based on cross-gradient theory offers better results than the single-method inversion. The 2D forward and inverse algorithm for CSAMT with source can effectively deal with artificial sources and ensures the reliability of the final joint inversion algorithm.

Inversion of Density Interfaces Using the Pseudo-Backpropagation Neural Network Method

NASA Astrophysics Data System (ADS)

Chen, Xiaohong; Du, Yukun; Liu, Zhan; Zhao, Wenju; Chen, Xiaocheng

2018-05-01

This paper presents a new pseudo-backpropagation (BP) neural network method that can invert multi-density interfaces at one time. The new method is based on the conventional forward modeling and inverse modeling theories in addition to conventional pseudo-BP neural network arithmetic. A 3D inversion model for gravity anomalies of multi-density interfaces using the pseudo-BP neural network method is constructed after analyzing the structure and function of the artificial neural network. The corresponding iterative inverse formula of the space field is presented at the same time. Based on trials of gravity anomalies and density noise, the influence of the two kinds of noise on the inverse result is discussed and the scale of noise requested for the stability of the arithmetic is analyzed. The effects of the initial model on the reduction of the ambiguity of the result and improvement of the precision of inversion are discussed. The correctness and validity of the method were verified by the 3D model of the three interfaces. 3D inversion was performed on the observed gravity anomaly data of the Okinawa trough using the program presented herein. The Tertiary basement and Moho depth were obtained from the inversion results, which also testify the adaptability of the method. This study has made a useful attempt for the inversion of gravity density interfaces.

The whole space three-dimensional magnetotelluric inversion algorithm with static shift correction

NASA Astrophysics Data System (ADS)

Zhang, K.

2016-12-01

Base on the previous studies on the static shift correction and 3D inversion algorithms, we improve the NLCG 3D inversion method and propose a new static shift correction method which work in the inversion. The static shift correction method is based on the 3D theory and real data. The static shift can be detected by the quantitative analysis of apparent parameters (apparent resistivity and impedance phase) of MT in high frequency range, and completed correction with inversion. The method is an automatic processing technology of computer with 0 cost, and avoids the additional field work and indoor processing with good results.The 3D inversion algorithm is improved (Zhang et al., 2013) base on the NLCG method of Newman & Alumbaugh (2000) and Rodi & Mackie (2001). For the algorithm, we added the parallel structure, improved the computational efficiency, reduced the memory of computer and added the topographic and marine factors. So the 3D inversion could work in general PC with high efficiency and accuracy. And all the MT data of surface stations, seabed stations and underground stations can be used in the inversion algorithm. The verification and application example of 3D inversion algorithm is shown in Figure 1. From the comparison of figure 1, the inversion model can reflect all the abnormal bodies and terrain clearly regardless of what type of data (impedance/tipper/impedance and tipper). And the resolution of the bodies' boundary can be improved by using tipper data. The algorithm is very effective for terrain inversion. So it is very useful for the study of continental shelf with continuous exploration of land, marine and underground.The three-dimensional electrical model of the ore zone reflects the basic information of stratum, rock and structure. Although it cannot indicate the ore body position directly, the important clues are provided for prospecting work by the delineation of diorite pluton uplift range. The test results show that, the high quality of the data processing and efficient inversion method for electromagnetic method is an important guarantee for porphyry ore.

Reader reaction to "a robust method for estimating optimal treatment regimes" by Zhang et al. (2012).

PubMed

Taylor, Jeremy M G; Cheng, Wenting; Foster, Jared C

2015-03-01

A recent article (Zhang et al., 2012, Biometrics 168, 1010-1018) compares regression based and inverse probability based methods of estimating an optimal treatment regime and shows for a small number of covariates that inverse probability weighted methods are more robust to model misspecification than regression methods. We demonstrate that using models that fit the data better reduces the concern about non-robustness for the regression methods. We extend the simulation study of Zhang et al. (2012, Biometrics 168, 1010-1018), also considering the situation of a larger number of covariates, and show that incorporating random forests into both regression and inverse probability weighted based methods improves their properties. © 2014, The International Biometric Society.

Perturbational and nonperturbational inversion of Rayleigh-wave velocities

USGS Publications Warehouse

Haney, Matt; Tsai, Victor C.

2017-01-01

The inversion of Rayleigh-wave dispersion curves is a classic geophysical inverse problem. We have developed a set of MATLAB codes that performs forward modeling and inversion of Rayleigh-wave phase or group velocity measurements. We describe two different methods of inversion: a perturbational method based on finite elements and a nonperturbational method based on the recently developed Dix-type relation for Rayleigh waves. In practice, the nonperturbational method can be used to provide a good starting model that can be iteratively improved with the perturbational method. Although the perturbational method is well-known, we solve the forward problem using an eigenvalue/eigenvector solver instead of the conventional approach of root finding. Features of the codes include the ability to handle any mix of phase or group velocity measurements, combinations of modes of any order, the presence of a surface water layer, computation of partial derivatives due to changes in material properties and layer boundaries, and the implementation of an automatic grid of layers that is optimally suited for the depth sensitivity of Rayleigh waves.

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

Time-domain full waveform inversion using instantaneous phase information with damping

NASA Astrophysics Data System (ADS)

Luo, Jingrui; Wu, Ru-Shan; Gao, Fuchun

2018-06-01

In time domain, the instantaneous phase can be obtained from the complex seismic trace using Hilbert transform. The instantaneous phase information has great potential in overcoming the local minima problem and improving the result of full waveform inversion. However, the phase wrapping problem, which comes from numerical calculation, prevents its application. In order to avoid the phase wrapping problem, we choose to use the exponential phase combined with the damping method, which gives instantaneous phase-based multi-stage inversion. We construct the objective functions based on the exponential instantaneous phase, and also derive the corresponding gradient operators. Conventional full waveform inversion and the instantaneous phase-based inversion are compared with numerical examples, which indicates that in the case without low frequency information in seismic data, our method is an effective and efficient approach for initial model construction for full waveform inversion.

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.

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.

A 3D generic inverse dynamic method using wrench notation and quaternion algebra.

PubMed

Dumas, R; Aissaoui, R; de Guise, J A

2004-06-01

In the literature, conventional 3D inverse dynamic models are limited in three aspects related to inverse dynamic notation, body segment parameters and kinematic formalism. First, conventional notation yields separate computations of the forces and moments with successive coordinate system transformations. Secondly, the way conventional body segment parameters are defined is based on the assumption that the inertia tensor is principal and the centre of mass is located between the proximal and distal ends. Thirdly, the conventional kinematic formalism uses Euler or Cardanic angles that are sequence-dependent and suffer from singularities. In order to overcome these limitations, this paper presents a new generic method for inverse dynamics. This generic method is based on wrench notation for inverse dynamics, a general definition of body segment parameters and quaternion algebra for the kinematic formalism.

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.

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.

A sparse reconstruction method for the estimation of multi-resolution emission fields via atmospheric inversion

DOE PAGES

Ray, J.; Lee, J.; Yadav, V.; ...

2015-04-29

Atmospheric inversions are frequently used to estimate fluxes of atmospheric greenhouse gases (e.g., biospheric CO 2 flux fields) at Earth's surface. These inversions typically assume that flux departures from a prior model are spatially smoothly varying, which are then modeled using a multi-variate Gaussian. When the field being estimated is spatially rough, multi-variate Gaussian models are difficult to construct and a wavelet-based field model may be more suitable. Unfortunately, such models are very high dimensional and are most conveniently used when the estimation method can simultaneously perform data-driven model simplification (removal of model parameters that cannot be reliably estimated) andmore » fitting. Such sparse reconstruction methods are typically not used in atmospheric inversions. In this work, we devise a sparse reconstruction method, and illustrate it in an idealized atmospheric inversion problem for the estimation of fossil fuel CO 2 (ffCO 2) emissions in the lower 48 states of the USA. Our new method is based on stagewise orthogonal matching pursuit (StOMP), a method used to reconstruct compressively sensed images. Our adaptations bestow three properties to the sparse reconstruction procedure which are useful in atmospheric inversions. We have modified StOMP to incorporate prior information on the emission field being estimated and to enforce non-negativity on the estimated field. Finally, though based on wavelets, our method allows for the estimation of fields in non-rectangular geometries, e.g., emission fields inside geographical and political boundaries. Our idealized inversions use a recently developed multi-resolution (i.e., wavelet-based) random field model developed for ffCO 2 emissions and synthetic observations of ffCO 2 concentrations from a limited set of measurement sites. We find that our method for limiting the estimated field within an irregularly shaped region is about a factor of 10 faster than conventional approaches. It also reduces the overall computational cost by a factor of 2. Further, the sparse reconstruction scheme imposes non-negativity without introducing strong nonlinearities, such as those introduced by employing log-transformed fields, and thus reaps the benefits of simplicity and computational speed that are characteristic of linear inverse problems.« less

A sparse reconstruction method for the estimation of multi-resolution emission fields via atmospheric inversion

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

Ray, J.; Lee, J.; Yadav, V.

Atmospheric inversions are frequently used to estimate fluxes of atmospheric greenhouse gases (e.g., biospheric CO 2 flux fields) at Earth's surface. These inversions typically assume that flux departures from a prior model are spatially smoothly varying, which are then modeled using a multi-variate Gaussian. When the field being estimated is spatially rough, multi-variate Gaussian models are difficult to construct and a wavelet-based field model may be more suitable. Unfortunately, such models are very high dimensional and are most conveniently used when the estimation method can simultaneously perform data-driven model simplification (removal of model parameters that cannot be reliably estimated) andmore » fitting. Such sparse reconstruction methods are typically not used in atmospheric inversions. In this work, we devise a sparse reconstruction method, and illustrate it in an idealized atmospheric inversion problem for the estimation of fossil fuel CO 2 (ffCO 2) emissions in the lower 48 states of the USA. Our new method is based on stagewise orthogonal matching pursuit (StOMP), a method used to reconstruct compressively sensed images. Our adaptations bestow three properties to the sparse reconstruction procedure which are useful in atmospheric inversions. We have modified StOMP to incorporate prior information on the emission field being estimated and to enforce non-negativity on the estimated field. Finally, though based on wavelets, our method allows for the estimation of fields in non-rectangular geometries, e.g., emission fields inside geographical and political boundaries. Our idealized inversions use a recently developed multi-resolution (i.e., wavelet-based) random field model developed for ffCO 2 emissions and synthetic observations of ffCO 2 concentrations from a limited set of measurement sites. We find that our method for limiting the estimated field within an irregularly shaped region is about a factor of 10 faster than conventional approaches. It also reduces the overall computational cost by a factor of 2. Further, the sparse reconstruction scheme imposes non-negativity without introducing strong nonlinearities, such as those introduced by employing log-transformed fields, and thus reaps the benefits of simplicity and computational speed that are characteristic of linear inverse problems.« less

Improved FFT-based numerical inversion of Laplace transforms via fast Hartley transform algorithm

NASA Technical Reports Server (NTRS)

Hwang, Chyi; Lu, Ming-Jeng; Shieh, Leang S.

1991-01-01

The disadvantages of numerical inversion of the Laplace transform via the conventional fast Fourier transform (FFT) are identified and an improved method is presented to remedy them. The improved method is based on introducing a new integration step length Delta(omega) = pi/mT for trapezoidal-rule approximation of the Bromwich integral, in which a new parameter, m, is introduced for controlling the accuracy of the numerical integration. Naturally, this method leads to multiple sets of complex FFT computations. A new inversion formula is derived such that N equally spaced samples of the inverse Laplace transform function can be obtained by (m/2) + 1 sets of N-point complex FFT computations or by m sets of real fast Hartley transform (FHT) computations.

Distorted Born iterative T-matrix method for inversion of CSEM data in anisotropic media

NASA Astrophysics Data System (ADS)

Jakobsen, Morten; Tveit, Svenn

2018-05-01

We present a direct iterative solutions to the nonlinear controlled-source electromagnetic (CSEM) inversion problem in the frequency domain, which is based on a volume integral equation formulation of the forward modelling problem in anisotropic conductive media. Our vectorial nonlinear inverse scattering approach effectively replaces an ill-posed nonlinear inverse problem with a series of linear ill-posed inverse problems, for which there already exist efficient (regularized) solution methods. The solution update the dyadic Green's function's from the source to the scattering-volume and from the scattering-volume to the receivers, after each iteration. The T-matrix approach of multiple scattering theory is used for efficient updating of all dyadic Green's functions after each linearized inversion step. This means that we have developed a T-matrix variant of the Distorted Born Iterative (DBI) method, which is often used in the acoustic and electromagnetic (medical) imaging communities as an alternative to contrast-source inversion. The main advantage of using the T-matrix approach in this context, is that it eliminates the need to perform a full forward simulation at each iteration of the DBI method, which is known to be consistent with the Gauss-Newton method. The T-matrix allows for a natural domain decomposition, since in the sense that a large model can be decomposed into an arbitrary number of domains that can be treated independently and in parallel. The T-matrix we use for efficient model updating is also independent of the source-receiver configuration, which could be an advantage when performing fast-repeat modelling and time-lapse inversion. The T-matrix is also compatible with the use of modern renormalization methods that can potentially help us to reduce the sensitivity of the CSEM inversion results on the starting model. To illustrate the performance and potential of our T-matrix variant of the DBI method for CSEM inversion, we performed a numerical experiments based on synthetic CSEM data associated with 2D VTI and 3D orthorombic model inversions. The results of our numerical experiment suggest that the DBIT method for inversion of CSEM data in anisotropic media is both accurate and efficient.

A new wavelet transform to sparsely represent cortical current densities for EEG/MEG inverse problems.

PubMed

Liao, Ke; Zhu, Min; Ding, Lei

2013-08-01

The present study investigated the use of transform sparseness of cortical current density on human brain surface to improve electroencephalography/magnetoencephalography (EEG/MEG) inverse solutions. Transform sparseness was assessed by evaluating compressibility of cortical current densities in transform domains. To do that, a structure compression method from computer graphics was first adopted to compress cortical surface structure, either regular or irregular, into hierarchical multi-resolution meshes. Then, a new face-based wavelet method based on generated multi-resolution meshes was proposed to compress current density functions defined on cortical surfaces. Twelve cortical surface models were built by three EEG/MEG softwares and their structural compressibility was evaluated and compared by the proposed method. Monte Carlo simulations were implemented to evaluate the performance of the proposed wavelet method in compressing various cortical current density distributions as compared to other two available vertex-based wavelet methods. The present results indicate that the face-based wavelet method can achieve higher transform sparseness than vertex-based wavelet methods. Furthermore, basis functions from the face-based wavelet method have lower coherence against typical EEG and MEG measurement systems than vertex-based wavelet methods. Both high transform sparseness and low coherent measurements suggest that the proposed face-based wavelet method can improve the performance of L1-norm regularized EEG/MEG inverse solutions, which was further demonstrated in simulations and experimental setups using MEG data. Thus, this new transform on complicated cortical structure is promising to significantly advance EEG/MEG inverse source imaging technologies. Copyright © 2013 Elsevier Ireland Ltd. All rights reserved.

Aerosol characteristics inversion based on the improved lidar ratio profile with the ground-based rotational Raman-Mie lidar

NASA Astrophysics Data System (ADS)

Ji, Hongzhu; Zhang, Yinchao; Chen, Siying; Chen, He; Guo, Pan

2018-06-01

An iterative method, based on a derived inverse relationship between atmospheric backscatter coefficient and aerosol lidar ratio, is proposed to invert the lidar ratio profile and aerosol extinction coefficient. The feasibility of this method is investigated theoretically and experimentally. Simulation results show the inversion accuracy of aerosol optical properties for iterative method can be improved in the near-surface aerosol layer and the optical thick layer. Experimentally, as a result of the reduced insufficiency error and incoherence error, the aerosol optical properties with higher accuracy can be obtained in the near-surface region and the region of numerical derivative distortion. In addition, the particle component can be distinguished roughly based on this improved lidar ratio profile.

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.

Wedge-shaped slice-selective adiabatic inversion pulse for controlling temporal width of bolus in pulsed arterial spin labeling

PubMed Central

Guo, Jia; Buxton, Richard B.; Wong, Eric C.

2015-01-01

Purpose In pulsed arterial spin labeling (PASL) methods, arterial blood is labeled via inverting a slab with uniform thickness, resulting in different temporal widths of boluses in vessels with different flow velocities. This limits the temporal resolution and signal-to-noise ratio (SNR) efficiency gains in PASL-based methods intended for high temporal resolution and SNR efficiency, such as Turbo-ASL and Turbo-QUASAR. Theory and Methods A novel wedge-shaped (WS) adiabatic inversion pulse is developed by adding in-plane gradient pulses to a slice-selective (SS) adiabatic inversion pulse to linearly modulate the inversion thicknesses at different locations while maintaining the adiabatic properties of the original pulse. A hyperbolic secant (HS) based WS inversion pulse was implemented. Its performance was tested in simulations, phantom and human experiments, and compared to an SS HS inversion pulse. Results Compared to the SS inversion pulse, the WS inversion pulse is capable of inducing different inversion thicknesses at different locations. It can be adjusted to generate a uniform temporal width of boluses in arteries at locations with different flow velocities. Conclusion The WS inversion pulse can be used to control the temporal widths of labeled boluses in PASL experiments. This should benefit PASL experiments by maximizing labeling duty cycle, and improving temporal resolution and SNR efficiency. PMID:26451521

A new approach to integrate GPU-based Monte Carlo simulation into inverse treatment plan optimization for proton therapy.

PubMed

Li, Yongbao; Tian, Zhen; Song, Ting; Wu, Zhaoxia; Liu, Yaqiang; Jiang, Steve; Jia, Xun

2017-01-07

Monte Carlo (MC)-based spot dose calculation is highly desired for inverse treatment planning in proton therapy because of its accuracy. Recent studies on biological optimization have also indicated the use of MC methods to compute relevant quantities of interest, e.g. linear energy transfer. Although GPU-based MC engines have been developed to address inverse optimization problems, their efficiency still needs to be improved. Also, the use of a large number of GPUs in MC calculation is not favorable for clinical applications. The previously proposed adaptive particle sampling (APS) method can improve the efficiency of MC-based inverse optimization by using the computationally expensive MC simulation more effectively. This method is more efficient than the conventional approach that performs spot dose calculation and optimization in two sequential steps. In this paper, we propose a computational library to perform MC-based spot dose calculation on GPU with the APS scheme. The implemented APS method performs a non-uniform sampling of the particles from pencil beam spots during the optimization process, favoring those from the high intensity spots. The library also conducts two computationally intensive matrix-vector operations frequently used when solving an optimization problem. This library design allows a streamlined integration of the MC-based spot dose calculation into an existing proton therapy inverse planning process. We tested the developed library in a typical inverse optimization system with four patient cases. The library achieved the targeted functions by supporting inverse planning in various proton therapy schemes, e.g. single field uniform dose, 3D intensity modulated proton therapy, and distal edge tracking. The efficiency was 41.6  ±  15.3% higher than the use of a GPU-based MC package in a conventional calculation scheme. The total computation time ranged between 2 and 50 min on a single GPU card depending on the problem size.

A new approach to integrate GPU-based Monte Carlo simulation into inverse treatment plan optimization for proton therapy

NASA Astrophysics Data System (ADS)

Li, Yongbao; Tian, Zhen; Song, Ting; Wu, Zhaoxia; Liu, Yaqiang; Jiang, Steve; Jia, Xun

2017-01-01

Monte Carlo (MC)-based spot dose calculation is highly desired for inverse treatment planning in proton therapy because of its accuracy. Recent studies on biological optimization have also indicated the use of MC methods to compute relevant quantities of interest, e.g. linear energy transfer. Although GPU-based MC engines have been developed to address inverse optimization problems, their efficiency still needs to be improved. Also, the use of a large number of GPUs in MC calculation is not favorable for clinical applications. The previously proposed adaptive particle sampling (APS) method can improve the efficiency of MC-based inverse optimization by using the computationally expensive MC simulation more effectively. This method is more efficient than the conventional approach that performs spot dose calculation and optimization in two sequential steps. In this paper, we propose a computational library to perform MC-based spot dose calculation on GPU with the APS scheme. The implemented APS method performs a non-uniform sampling of the particles from pencil beam spots during the optimization process, favoring those from the high intensity spots. The library also conducts two computationally intensive matrix-vector operations frequently used when solving an optimization problem. This library design allows a streamlined integration of the MC-based spot dose calculation into an existing proton therapy inverse planning process. We tested the developed library in a typical inverse optimization system with four patient cases. The library achieved the targeted functions by supporting inverse planning in various proton therapy schemes, e.g. single field uniform dose, 3D intensity modulated proton therapy, and distal edge tracking. The efficiency was 41.6  ±  15.3% higher than the use of a GPU-based MC package in a conventional calculation scheme. The total computation time ranged between 2 and 50 min on a single GPU card depending on the problem size.

A New Approach to Integrate GPU-based Monte Carlo Simulation into Inverse Treatment Plan Optimization for Proton Therapy

PubMed Central

Li, Yongbao; Tian, Zhen; Song, Ting; Wu, Zhaoxia; Liu, Yaqiang; Jiang, Steve; Jia, Xun

2016-01-01

Monte Carlo (MC)-based spot dose calculation is highly desired for inverse treatment planning in proton therapy because of its accuracy. Recent studies on biological optimization have also indicated the use of MC methods to compute relevant quantities of interest, e.g. linear energy transfer. Although GPU-based MC engines have been developed to address inverse optimization problems, their efficiency still needs to be improved. Also, the use of a large number of GPUs in MC calculation is not favorable for clinical applications. The previously proposed adaptive particle sampling (APS) method can improve the efficiency of MC-based inverse optimization by using the computationally expensive MC simulation more effectively. This method is more efficient than the conventional approach that performs spot dose calculation and optimization in two sequential steps. In this paper, we propose a computational library to perform MC-based spot dose calculation on GPU with the APS scheme. The implemented APS method performs a non-uniform sampling of the particles from pencil beam spots during the optimization process, favoring those from the high intensity spots. The library also conducts two computationally intensive matrix-vector operations frequently used when solving an optimization problem. This library design allows a streamlined integration of the MC-based spot dose calculation into an existing proton therapy inverse planning process. We tested the developed library in a typical inverse optimization system with four patient cases. The library achieved the targeted functions by supporting inverse planning in various proton therapy schemes, e.g. single field uniform dose, 3D intensity modulated proton therapy, and distal edge tracking. The efficiency was 41.6±15.3% higher than the use of a GPU-based MC package in a conventional calculation scheme. The total computation time ranged between 2 and 50 min on a single GPU card depending on the problem size. PMID:27991456

New Additions to the Toolkit for Forward/Inverse Problems in Electrocardiography within the SCIRun Problem Solving Environment.

PubMed

Coll-Font, Jaume; Burton, Brett M; Tate, Jess D; Erem, Burak; Swenson, Darrel J; Wang, Dafang; Brooks, Dana H; van Dam, Peter; Macleod, Rob S

2014-09-01

Cardiac electrical imaging often requires the examination of different forward and inverse problem formulations based on mathematical and numerical approximations of the underlying source and the intervening volume conductor that can generate the associated voltages on the surface of the body. If the goal is to recover the source on the heart from body surface potentials, the solution strategy must include numerical techniques that can incorporate appropriate constraints and recover useful solutions, even though the problem is badly posed. Creating complete software solutions to such problems is a daunting undertaking. In order to make such tools more accessible to a broad array of researchers, the Center for Integrative Biomedical Computing (CIBC) has made an ECG forward/inverse toolkit available within the open source SCIRun system. Here we report on three new methods added to the inverse suite of the toolkit. These new algorithms, namely a Total Variation method, a non-decreasing TMP inverse and a spline-based inverse, consist of two inverse methods that take advantage of the temporal structure of the heart potentials and one that leverages the spatial characteristics of the transmembrane potentials. These three methods further expand the possibilities of researchers in cardiology to explore and compare solutions to their particular imaging problem.

Spatially constrained Bayesian inversion of frequency- and time-domain electromagnetic data from the Tellus projects

NASA Astrophysics Data System (ADS)

Kiyan, Duygu; Rath, Volker; Delhaye, Robert

2017-04-01

The frequency- and time-domain airborne electromagnetic (AEM) data collected under the Tellus projects of the Geological Survey of Ireland (GSI) which represent a wealth of information on the multi-dimensional electrical structure of Ireland's near-surface. Our project, which was funded by GSI under the framework of their Short Call Research Programme, aims to develop and implement inverse techniques based on various Bayesian methods for these densely sampled data. We have developed a highly flexible toolbox using Python language for the one-dimensional inversion of AEM data along the flight lines. The computational core is based on an adapted frequency- and time-domain forward modelling core derived from the well-tested open-source code AirBeo, which was developed by the CSIRO (Australia) and the AMIRA consortium. Three different inversion methods have been implemented: (i) Tikhonov-type inversion including optimal regularisation methods (Aster el al., 2012; Zhdanov, 2015), (ii) Bayesian MAP inversion in parameter and data space (e.g. Tarantola, 2005), and (iii) Full Bayesian inversion with Markov Chain Monte Carlo (Sambridge and Mosegaard, 2002; Mosegaard and Sambridge, 2002), all including different forms of spatial constraints. The methods have been tested on synthetic and field data. This contribution will introduce the toolbox and present case studies on the AEM data from the Tellus projects.

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.

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

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.

A frozen Gaussian approximation-based multi-level particle swarm optimization for seismic inversion

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

Li, Jinglai, E-mail: jinglaili@sjtu.edu.cn; Lin, Guang, E-mail: lin491@purdue.edu; Computational Sciences and Mathematics Division, Pacific Northwest National Laboratory, Richland, WA 99352

2015-09-01

In this paper, we propose a frozen Gaussian approximation (FGA)-based multi-level particle swarm optimization (MLPSO) method for seismic inversion of high-frequency wave data. The method addresses two challenges in it: First, the optimization problem is highly non-convex, which makes hard for gradient-based methods to reach global minima. This is tackled by MLPSO which can escape from undesired local minima. Second, the character of high-frequency of seismic waves requires a large number of grid points in direct computational methods, and thus renders an extremely high computational demand on the simulation of each sample in MLPSO. We overcome this difficulty by threemore » steps: First, we use FGA to compute high-frequency wave propagation based on asymptotic analysis on phase plane; Then we design a constrained full waveform inversion problem to prevent the optimization search getting into regions of velocity where FGA is not accurate; Last, we solve the constrained optimization problem by MLPSO that employs FGA solvers with different fidelity. The performance of the proposed method is demonstrated by a two-dimensional full-waveform inversion example of the smoothed Marmousi model.« less

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.

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.

An Innovations-Based Noise Cancelling Technique on Inverse Kepstrum Whitening Filter and Adaptive FIR Filter in Beamforming Structure

PubMed Central

Jeong, Jinsoo

2011-01-01

This paper presents an acoustic noise cancelling technique using an inverse kepstrum system as an innovations-based whitening application for an adaptive finite impulse response (FIR) filter in beamforming structure. The inverse kepstrum method uses an innovations-whitened form from one acoustic path transfer function between a reference microphone sensor and a noise source so that the rear-end reference signal will then be a whitened sequence to a cascaded adaptive FIR filter in the beamforming structure. By using an inverse kepstrum filter as a whitening filter with the use of a delay filter, the cascaded adaptive FIR filter estimates only the numerator of the polynomial part from the ratio of overall combined transfer functions. The test results have shown that the adaptive FIR filter is more effective in beamforming structure than an adaptive noise cancelling (ANC) structure in terms of signal distortion in the desired signal and noise reduction in noise with nonminimum phase components. In addition, the inverse kepstrum method shows almost the same convergence level in estimate of noise statistics with the use of a smaller amount of adaptive FIR filter weights than the kepstrum method, hence it could provide better computational simplicity in processing. Furthermore, the rear-end inverse kepstrum method in beamforming structure has shown less signal distortion in the desired signal than the front-end kepstrum method and the front-end inverse kepstrum method in beamforming structure. PMID:22163987

Three-dimensional Gravity Inversion with a New Gradient Scheme on Unstructured Grids

NASA Astrophysics Data System (ADS)

Sun, S.; Yin, C.; Gao, X.; Liu, Y.; Zhang, B.

2017-12-01

Stabilized gradient-based methods have been proved to be efficient for inverse problems. Based on these methods, setting gradient close to zero can effectively minimize the objective function. Thus the gradient of objective function determines the inversion results. By analyzing the cause of poor resolution on depth in gradient-based gravity inversion methods, we find that imposing depth weighting functional in conventional gradient can improve the depth resolution to some extent. However, the improvement is affected by the regularization parameter and the effect of the regularization term becomes smaller with increasing depth (shown as Figure 1 (a)). In this paper, we propose a new gradient scheme for gravity inversion by introducing a weighted model vector. The new gradient can improve the depth resolution more efficiently, which is independent of the regularization parameter, and the effect of regularization term will not be weakened when depth increases. Besides, fuzzy c-means clustering method and smooth operator are both used as regularization terms to yield an internal consecutive inverse model with sharp boundaries (Sun and Li, 2015). We have tested our new gradient scheme with unstructured grids on synthetic data to illustrate the effectiveness of the algorithm. Gravity forward modeling with unstructured grids is based on the algorithm proposed by Okbe (1979). We use a linear conjugate gradient inversion scheme to solve the inversion problem. The numerical experiments show a great improvement in depth resolution compared with regular gradient scheme, and the inverse model is compact at all depths (shown as Figure 1 (b)). AcknowledgeThis research is supported by Key Program of National Natural Science Foundation of China (41530320), China Natural Science Foundation for Young Scientists (41404093), and Key National Research Project of China (2016YFC0303100, 2017YFC0601900). ReferencesSun J, Li Y. 2015. Multidomain petrophysically constrained inversion and geology differentiation using guided fuzzy c-means clustering. Geophysics, 80(4): ID1-ID18. Okabe M. 1979. Analytical expressions for gravity anomalies due to homogeneous polyhedral bodies and translations into magnetic anomalies. Geophysics, 44(4), 730-741.

Inversion of time-domain induced polarization data based on time-lapse concept

NASA Astrophysics Data System (ADS)

Kim, Bitnarae; Nam, Myung Jin; Kim, Hee Joon

2018-05-01

Induced polarization (IP) surveys, measuring overvoltage phenomena of the medium, are widely and increasingly performed not only for exploration of mineral resources but also for engineering applications. Among several IP survey methods such as time-domain, frequency-domain and spectral IP surveys, this study introduces a noble inversion method for time-domain IP data to recover the chargeability structure of target medium. The inversion method employs the concept of 4D inversion of time-lapse resistivity data sets, considering the fact that measured voltage in time-domain IP survey is distorted by IP effects to increase from the instantaneous voltage measured at the moment the source current injection starts. Even though the increase is saturated very fast, we can consider the saturated and instantaneous voltages as a time-lapse data set. The 4D inversion method is one of the most powerful method for inverting time-lapse resistivity data sets. Using the developed IP inversion algorithm, we invert not only synthetic but also field IP data to show the effectiveness of the proposed method by comparing the recovered chargeability models with those from linear inversion that was used for the inversion of the field data in a previous study. Numerical results confirm that the proposed inversion method generates reliable chargeability models even though the anomalous bodies have large IP effects.

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)].

Multiple estimation channel decoupling and optimization method based on inverse system

NASA Astrophysics Data System (ADS)

Wu, Peng; Mu, Rongjun; Zhang, Xin; Deng, Yanpeng

2018-03-01

This paper addressed the intelligent autonomous navigation request of intelligent deformation missile, based on the intelligent deformation missile dynamics and kinematics modeling, navigation subsystem solution method and error modeling, and then focuses on the corresponding data fusion and decision fusion technology, decouples the sensitive channel of the filter input through the inverse system of design dynamics to reduce the influence of sudden change of the measurement information on the filter input. Then carrying out a series of simulation experiments, which verified the feasibility of the inverse system decoupling algorithm effectiveness.

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.

The neural network approximation method for solving multidimensional nonlinear inverse problems of geophysics

NASA Astrophysics Data System (ADS)

Shimelevich, M. I.; Obornev, E. A.; Obornev, I. E.; Rodionov, E. A.

2017-07-01

The iterative approximation neural network method for solving conditionally well-posed nonlinear inverse problems of geophysics is presented. The method is based on the neural network approximation of the inverse operator. The inverse problem is solved in the class of grid (block) models of the medium on a regularized parameterization grid. The construction principle of this grid relies on using the calculated values of the continuity modulus of the inverse operator and its modifications determining the degree of ambiguity of the solutions. The method provides approximate solutions of inverse problems with the maximal degree of detail given the specified degree of ambiguity with the total number of the sought parameters n × 103 of the medium. The a priori and a posteriori estimates of the degree of ambiguity of the approximated solutions are calculated. The work of the method is illustrated by the example of the three-dimensional (3D) inversion of the synthesized 2D areal geoelectrical (audio magnetotelluric sounding, AMTS) data corresponding to the schematic model of a kimberlite pipe.

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.

Improved Genetic Algorithm Based on the Cooperation of Elite and Inverse-elite

NASA Astrophysics Data System (ADS)

Kanakubo, Masaaki; Hagiwara, Masafumi

In this paper, we propose an improved genetic algorithm based on the combination of Bee system and Inverse-elitism, both are effective strategies for the improvement of GA. In the Bee system, in the beginning, each chromosome tries to find good solution individually as global search. When some chromosome is regarded as superior one, the other chromosomes try to find solution around there. However, since chromosomes for global search are generated randomly, Bee system lacks global search ability. On the other hand, in the Inverse-elitism, an inverse-elite whose gene values are reversed from the corresponding elite is produced. This strategy greatly contributes to diversification of chromosomes, but it lacks local search ability. In the proposed method, the Inverse-elitism with Pseudo-simplex method is employed for global search of Bee system in order to strengthen global search ability. In addition, it also has strong local search ability. The proposed method has synergistic effects of the three strategies. We confirmed validity and superior performance of the proposed method by computer simulations.

Characterization of six human disease-associated inversion polymorphisms.

PubMed

Antonacci, Francesca; Kidd, Jeffrey M; Marques-Bonet, Tomas; Ventura, Mario; Siswara, Priscillia; Jiang, Zhaoshi; Eichler, Evan E

2009-07-15

The human genome is a highly dynamic structure that shows a wide range of genetic polymorphic variation. Unlike other types of structural variation, little is known about inversion variants within normal individuals because such events are typically balanced and are difficult to detect and analyze by standard molecular approaches. Using sequence-based, cytogenetic and genotyping approaches, we characterized six large inversion polymorphisms that map to regions associated with genomic disorders with complex segmental duplications mapping at the breakpoints. We developed a metaphase FISH-based assay to genotype inversions and analyzed the chromosomes of 27 individuals from three HapMap populations. In this subset, we find that these inversions are less frequent or absent in Asians when compared with European and Yoruban populations. Analyzing multiple individuals from outgroup species of great apes, we show that most of these large inversion polymorphisms are specific to the human lineage with two exceptions, 17q21.31 and 8p23 inversions, which are found to be similarly polymorphic in other great ape species and where the inverted allele represents the ancestral state. Investigating linkage disequilibrium relationships with genotyped SNPs, we provide evidence that most of these inversions appear to have arisen on at least two different haplotype backgrounds. In these cases, discovery and genotyping methods based on SNPs may be confounded and molecular cytogenetics remains the only method to genotype these inversions.

a method of gravity and seismic sequential inversion and its GPU implementation

NASA Astrophysics Data System (ADS)

Liu, G.; Meng, X.

2011-12-01

In this abstract, we introduce a gravity and seismic sequential inversion method to invert for density and velocity together. For the gravity inversion, we use an iterative method based on correlation imaging algorithm; for the seismic inversion, we use the full waveform inversion. The link between the density and velocity is an empirical formula called Gardner equation, for large volumes of data, we use the GPU to accelerate the computation. For the gravity inversion method , we introduce a method based on correlation imaging algorithm,it is also a interative method, first we calculate the correlation imaging of the observed gravity anomaly, it is some value between -1 and +1, then we multiply this value with a little density ,this value become the initial density model. We get a forward reuslt with this initial model and also calculate the correaltion imaging of the misfit of observed data and the forward data, also multiply the correaltion imaging result a little density and add it to the initial model, then do the same procedure above , at last ,we can get a inversion density model. For the seismic inveron method ,we use a mothod base on the linearity of acoustic wave equation written in the frequency domain,with a intial velociy model, we can get a good velocity result. In the sequential inversion of gravity and seismic , we need a link formula to convert between density and velocity ,in our method , we use the Gardner equation. Driven by the insatiable market demand for real time, high-definition 3D images, the programmable NVIDIA Graphic Processing Unit (GPU) as co-processor of CPU has been developed for high performance computing. Compute Unified Device Architecture (CUDA) is a parallel programming model and software environment provided by NVIDIA designed to overcome the challenge of using traditional general purpose GPU while maintaining a low learn curve for programmers familiar with standard programming languages such as C. In our inversion processing, we use the GPU to accelerate our gravity and seismic inversion. Taking the gravity inversion as an example, its kernels are gravity forward simulation and correlation imaging, after the parallelization in GPU, in 3D case,the inversion module, the original five CPU loops are reduced to three,the forward module the original five CPU loops are reduced to two. Acknowledgments We acknowledge the financial support of Sinoprobe project (201011039 and 201011049-03), the Fundamental Research Funds for the Central Universities (2010ZY26 and 2011PY0183), the National Natural Science Foundation of China (41074095) and the Open Project of State Key Laboratory of Geological Processes and Mineral Resources (GPMR0945).

Hybrid Weighted Minimum Norm Method A new method based LORETA to solve EEG inverse problem.

PubMed

Song, C; Zhuang, T; Wu, Q

2005-01-01

This Paper brings forward a new method to solve EEG inverse problem. Based on following physiological characteristic of neural electrical activity source: first, the neighboring neurons are prone to active synchronously; second, the distribution of source space is sparse; third, the active intensity of the sources are high centralized, we take these prior knowledge as prerequisite condition to develop the inverse solution of EEG, and not assume other characteristic of inverse solution to realize the most commonly 3D EEG reconstruction map. The proposed algorithm takes advantage of LORETA's low resolution method which emphasizes particularly on 'localization' and FOCUSS's high resolution method which emphasizes particularly on 'separability'. The method is still under the frame of the weighted minimum norm method. The keystone is to construct a weighted matrix which takes reference from the existing smoothness operator, competition mechanism and study algorithm. The basic processing is to obtain an initial solution's estimation firstly, then construct a new estimation using the initial solution's information, repeat this process until the solutions under last two estimate processing is keeping unchanged.

Analytical and numerical analysis of inverse optimization problems: conditions of uniqueness and computational methods

PubMed Central

Zatsiorsky, Vladimir M.

2011-01-01

One of the key problems of motor control is the redundancy problem, in particular how the central nervous system (CNS) chooses an action out of infinitely many possible. A promising way to address this question is to assume that the choice is made based on optimization of a certain cost function. A number of cost functions have been proposed in the literature to explain performance in different motor tasks: from force sharing in grasping to path planning in walking. However, the problem of uniqueness of the cost function(s) was not addressed until recently. In this article, we analyze two methods of finding additive cost functions in inverse optimization problems with linear constraints, so-called linear-additive inverse optimization problems. These methods are based on the Uniqueness Theorem for inverse optimization problems that we proved recently (Terekhov et al., J Math Biol 61(3):423–453, 2010). Using synthetic data, we show that both methods allow for determining the cost function. We analyze the influence of noise on the both methods. Finally, we show how a violation of the conditions of the Uniqueness Theorem may lead to incorrect solutions of the inverse optimization problem. PMID:21311907

A Comparison between Model Base Hardconstrain, Bandlimited, and Sparse-Spike Seismic Inversion: New Insights for CBM Reservoir Modelling on Muara Enim Formation, South Sumatra

NASA Astrophysics Data System (ADS)

Mohamad Noor, Faris; Adipta, Agra

2018-03-01

Coal Bed Methane (CBM) as a newly developed resource in Indonesia is one of the alternatives to relieve Indonesia’s dependencies on conventional energies. Coal resource of Muara Enim Formation is known as one of the prolific reservoirs in South Sumatra Basin. Seismic inversion and well analysis are done to determine the coal seam characteristics of Muara Enim Formation. This research uses three inversion methods, which are: model base hard- constrain, bandlimited, and sparse-spike inversion. Each type of seismic inversion has its own advantages to display the coal seam and its characteristic. Interpretation result from the analysis data shows that the Muara Enim coal seam has 20 (API) gamma ray value, 1 (gr/cc) – 1.4 (gr/cc) from density log, and low AI cutoff value range between 5000-6400 (m/s)*(g/cc). The distribution of coal seam is laterally thinning northwest to southeast. Coal seam is seen biasedly on model base hard constraint inversion and discontinued on band-limited inversion which isn’t similar to the geological model. The appropriate AI inversion is sparse spike inversion which has 0.884757 value from cross plot inversion as the best correlation value among the chosen inversion methods. Sparse Spike inversion its self-has high amplitude as a proper tool to identify coal seam continuity which commonly appears as a thin layer. Cross-sectional sparse spike inversion shows that there are possible new boreholes in CDP 3662-3722, CDP 3586-3622, and CDP 4004-4148 which is seen in seismic data as a thick coal seam.

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.

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.

Magnetotelluric inversion via reverse time migration algorithm of seismic data

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

Ha, Taeyoung; Shin, Changsoo

2007-07-01

We propose a new algorithm for two-dimensional magnetotelluric (MT) inversion. Our algorithm is an MT inversion based on the steepest descent method, borrowed from the backpropagation technique of seismic inversion or reverse time migration, introduced in the middle 1980s by Lailly and Tarantola. The steepest descent direction can be calculated efficiently by using the symmetry of numerical Green's function derived from a mixed finite element method proposed by Nedelec for Maxwell's equation, without calculating the Jacobian matrix explicitly. We construct three different objective functions by taking the logarithm of the complex apparent resistivity as introduced in the recent waveform inversionmore » algorithm by Shin and Min. These objective functions can be naturally separated into amplitude inversion, phase inversion and simultaneous inversion. We demonstrate our algorithm by showing three inversion results for synthetic data.« less

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.

Prestack density inversion using the Fatti equation constrained by the P- and S-wave impedance and density

NASA Astrophysics Data System (ADS)

Liang, Li-Feng; Zhang, Hong-Bing; Dan, Zhi-Wei; Xu, Zi-Qiang; Liu, Xiu-Juan; Cao, Cheng-Hao

2017-03-01

Simultaneous prestack inversion is based on the modified Fatti equation and uses the ratio of the P- and S-wave velocity as constraints. We use the relation of P-wave impedance and density (PID) and S-wave impedance and density (SID) to replace the constant Vp/Vs constraint, and we propose the improved constrained Fatti equation to overcome the effect of P-wave impedance on density. We compare the sensitivity of both methods using numerical simulations and conclude that the density inversion sensitivity improves when using the proposed method. In addition, the random conjugate-gradient method is used in the inversion because it is fast and produces global solutions. The use of synthetic and field data suggests that the proposed inversion method is effective in conventional and nonconventional lithologies.

Joint Inversion of Body-Wave Arrival Times and Surface-Wave Dispersion Data in the Wavelet Domain Constrained by Sparsity Regularization

NASA Astrophysics Data System (ADS)

Zhang, H.; Fang, H.; Yao, H.; Maceira, M.; van der Hilst, R. D.

2014-12-01

Recently, Zhang et al. (2014, Pure and Appiled Geophysics) have developed a joint inversion code incorporating body-wave arrival times and surface-wave dispersion data. The joint inversion code was based on the regional-scale version of the double-difference tomography algorithm tomoDD. The surface-wave inversion part uses the propagator matrix solver in the algorithm DISPER80 (Saito, 1988) for forward calculation of dispersion curves from layered velocity models and the related sensitivities. The application of the joint inversion code to the SAFOD site in central California shows that the fault structure is better imaged in the new model, which is able to fit both the body-wave and surface-wave observations adequately. Here we present a new joint inversion method that solves the model in the wavelet domain constrained by sparsity regularization. Compared to the previous method, it has the following advantages: (1) The method is both data- and model-adaptive. For the velocity model, it can be represented by different wavelet coefficients at different scales, which are generally sparse. By constraining the model wavelet coefficients to be sparse, the inversion in the wavelet domain can inherently adapt to the data distribution so that the model has higher spatial resolution in the good data coverage zone. Fang and Zhang (2014, Geophysical Journal International) have showed the superior performance of the wavelet-based double-difference seismic tomography method compared to the conventional method. (2) For the surface wave inversion, the joint inversion code takes advantage of the recent development of direct inversion of surface wave dispersion data for 3-D variations of shear wave velocity without the intermediate step of phase or group velocity maps (Fang et al., 2014, Geophysical Journal International). A fast marching method is used to compute, at each period, surface wave traveltimes and ray paths between sources and receivers. We will test the new joint inversion code at the SAFOD site to compare its performance over the previous code. We will also select another fault zone such as the San Jacinto Fault Zone to better image its structure.

Refractive index inversion based on Mueller matrix method

NASA Astrophysics Data System (ADS)

Fan, Huaxi; Wu, Wenyuan; Huang, Yanhua; Li, Zhaozhao

2016-03-01

Based on Stokes vector and Jones vector, the correlation between Mueller matrix elements and refractive index was studied with the result simplified, and through Mueller matrix way, the expression of refractive index inversion was deduced. The Mueller matrix elements, under different incident angle, are simulated through the expression of specular reflection so as to analyze the influence of the angle of incidence and refractive index on it, which is verified through the measure of the Mueller matrix elements of polished metal surface. Research shows that, under the condition of specular reflection, the result of Mueller matrix inversion is consistent with the experiment and can be used as an index of refraction of inversion method, and it provides a new way for target detection and recognition technology.

Frnakenstein: multiple target inverse RNA folding.

PubMed

Lyngsø, Rune B; Anderson, James W J; Sizikova, Elena; Badugu, Amarendra; Hyland, Tomas; Hein, Jotun

2012-10-09

RNA secondary structure prediction, or folding, is a classic problem in bioinformatics: given a sequence of nucleotides, the aim is to predict the base pairs formed in its three dimensional conformation. The inverse problem of designing a sequence folding into a particular target structure has only more recently received notable interest. With a growing appreciation and understanding of the functional and structural properties of RNA motifs, and a growing interest in utilising biomolecules in nano-scale designs, the interest in the inverse RNA folding problem is bound to increase. However, whereas the RNA folding problem from an algorithmic viewpoint has an elegant and efficient solution, the inverse RNA folding problem appears to be hard. In this paper we present a genetic algorithm approach to solve the inverse folding problem. The main aims of the development was to address the hitherto mostly ignored extension of solving the inverse folding problem, the multi-target inverse folding problem, while simultaneously designing a method with superior performance when measured on the quality of designed sequences. The genetic algorithm has been implemented as a Python program called Frnakenstein. It was benchmarked against four existing methods and several data sets totalling 769 real and predicted single structure targets, and on 292 two structure targets. It performed as well as or better at finding sequences which folded in silico into the target structure than all existing methods, without the heavy bias towards CG base pairs that was observed for all other top performing methods. On the two structure targets it also performed well, generating a perfect design for about 80% of the targets. Our method illustrates that successful designs for the inverse RNA folding problem does not necessarily have to rely on heavy biases in base pair and unpaired base distributions. The design problem seems to become more difficult on larger structures when the target structures are real structures, while no deterioration was observed for predicted structures. Design for two structure targets is considerably more difficult, but far from impossible, demonstrating the feasibility of automated design of artificial riboswitches. The Python implementation is available at http://www.stats.ox.ac.uk/research/genome/software/frnakenstein.

Frnakenstein: multiple target inverse RNA folding

PubMed Central

2012-01-01

Background RNA secondary structure prediction, or folding, is a classic problem in bioinformatics: given a sequence of nucleotides, the aim is to predict the base pairs formed in its three dimensional conformation. The inverse problem of designing a sequence folding into a particular target structure has only more recently received notable interest. With a growing appreciation and understanding of the functional and structural properties of RNA motifs, and a growing interest in utilising biomolecules in nano-scale designs, the interest in the inverse RNA folding problem is bound to increase. However, whereas the RNA folding problem from an algorithmic viewpoint has an elegant and efficient solution, the inverse RNA folding problem appears to be hard. Results In this paper we present a genetic algorithm approach to solve the inverse folding problem. The main aims of the development was to address the hitherto mostly ignored extension of solving the inverse folding problem, the multi-target inverse folding problem, while simultaneously designing a method with superior performance when measured on the quality of designed sequences. The genetic algorithm has been implemented as a Python program called Frnakenstein. It was benchmarked against four existing methods and several data sets totalling 769 real and predicted single structure targets, and on 292 two structure targets. It performed as well as or better at finding sequences which folded in silico into the target structure than all existing methods, without the heavy bias towards CG base pairs that was observed for all other top performing methods. On the two structure targets it also performed well, generating a perfect design for about 80% of the targets. Conclusions Our method illustrates that successful designs for the inverse RNA folding problem does not necessarily have to rely on heavy biases in base pair and unpaired base distributions. The design problem seems to become more difficult on larger structures when the target structures are real structures, while no deterioration was observed for predicted structures. Design for two structure targets is considerably more difficult, but far from impossible, demonstrating the feasibility of automated design of artificial riboswitches. The Python implementation is available at http://www.stats.ox.ac.uk/research/genome/software/frnakenstein. PMID:23043260

A Hybrid Seismic Inversion Method for V P/V S Ratio and Its Application to Gas Identification

NASA Astrophysics Data System (ADS)

Guo, Qiang; Zhang, Hongbing; Han, Feilong; Xiao, Wei; Shang, Zuoping

2018-03-01

The ratio of compressional wave velocity to shear wave velocity (V P/V S ratio) has established itself as one of the most important parameters in identifying gas reservoirs. However, considering that seismic inversion process is highly non-linear and geological conditions encountered may be complex, a direct estimation of V P/V S ratio from pre-stack seismic data remains a challenging task. In this paper, we propose a hybrid seismic inversion method to estimate V P/V S ratio directly. In this method, post- and pre-stack inversions are combined in which the pre-stack inversion for V P/V S ratio is driven by the post-stack inversion results (i.e., V P and density). In particular, the V P/V S ratio is considered as a model parameter and is directly inverted from the pre-stack inversion based on the exact Zoeppritz equation. Moreover, anisotropic Markov random field is employed in order to regularise the inversion process as well as taking care of geological structures (boundaries) information. Aided by the proposed hybrid inversion strategy, the directional weighting coefficients incorporated in the anisotropic Markov random field neighbourhoods are quantitatively calculated by the anisotropic diffusion method. The synthetic test demonstrates the effectiveness of the proposed inversion method. In particular, given low quality of the pre-stack data and high heterogeneity of the target layers in the field data, the proposed inversion method reveals the detailed model of V P/V S ratio that can successfully identify the gas-bearing zones.

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.

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.

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.

Mineral inversion for element capture spectroscopy logging based on optimization theory

NASA Astrophysics Data System (ADS)

Zhao, Jianpeng; Chen, Hui; Yin, Lu; Li, Ning

2017-12-01

Understanding the mineralogical composition of a formation is an essential key step in the petrophysical evaluation of petroleum reservoirs. Geochemical logging tools can provide quantitative measurements of a wide range of elements. In this paper, element capture spectroscopy (ECS) was taken as an example and an optimization method was adopted to solve the mineral inversion problem for ECS. This method used the converting relationship between elements and minerals as response equations and took into account the statistical uncertainty of the element measurements and established an optimization function for ECS. Objective function value and reconstructed elemental logs were used to check the robustness and reliability of the inversion method. Finally, the inversion mineral results had a good agreement with x-ray diffraction laboratory data. The accurate conversion of elemental dry weights to mineral dry weights formed the foundation for the subsequent applications based on ECS.

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.

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.

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

2D magnetotelluric inversion using reflection seismic images as constraints and application in the COSC project

NASA Astrophysics Data System (ADS)

Kalscheuer, Thomas; Yan, Ping; Hedin, Peter; Garcia Juanatey, Maria d. l. A.

2017-04-01

We introduce a new constrained 2D magnetotelluric (MT) inversion scheme, in which the local weights of the regularization operator with smoothness constraints are based directly on the envelope attribute of a reflection seismic image. The weights resemble those of a previously published seismic modification of the minimum gradient support method introducing a global stabilization parameter. We measure the directional gradients of the seismic envelope to modify the horizontal and vertical smoothness constraints separately. An appropriate choice of the new stabilization parameter is based on a simple trial-and-error procedure. Our proposed constrained inversion scheme was easily implemented in an existing Gauss-Newton inversion package. From a theoretical perspective, we compare our new constrained inversion to similar constrained inversion methods, which are based on image theory and seismic attributes. Successful application of the proposed inversion scheme to the MT field data of the Collisional Orogeny in the Scandinavian Caledonides (COSC) project using constraints from the envelope attribute of the COSC reflection seismic profile (CSP) helped to reduce the uncertainty of the interpretation of the main décollement. Thus, the new model gave support to the proposed location of a future borehole COSC-2 which is supposed to penetrate the main décollement and the underlying Precambrian basement.

Finite-fault source inversion using adjoint methods in 3D heterogeneous media

NASA Astrophysics Data System (ADS)

Somala, Surendra Nadh; Ampuero, Jean-Paul; Lapusta, Nadia

2018-04-01

Accounting for lateral heterogeneities in the 3D velocity structure of the crust is known to improve earthquake source inversion, compared to results based on 1D velocity models which are routinely assumed to derive finite-fault slip models. The conventional approach to include known 3D heterogeneity in source inversion involves pre-computing 3D Green's functions, which requires a number of 3D wave propagation simulations proportional to the number of stations or to the number of fault cells. The computational cost of such an approach is prohibitive for the dense datasets that could be provided by future earthquake observation systems. Here, we propose an adjoint-based optimization technique to invert for the spatio-temporal evolution of slip velocity. The approach does not require pre-computed Green's functions. The adjoint method provides the gradient of the cost function, which is used to improve the model iteratively employing an iterative gradient-based minimization method. The adjoint approach is shown to be computationally more efficient than the conventional approach based on pre-computed Green's functions in a broad range of situations. We consider data up to 1 Hz from a Haskell source scenario (a steady pulse-like rupture) on a vertical strike-slip fault embedded in an elastic 3D heterogeneous velocity model. The velocity model comprises a uniform background and a 3D stochastic perturbation with the von Karman correlation function. Source inversions based on the 3D velocity model are performed for two different station configurations, a dense and a sparse network with 1 km and 20 km station spacing, respectively. These reference inversions show that our inversion scheme adequately retrieves the rise time when the velocity model is exactly known, and illustrates how dense coverage improves the inference of peak slip velocities. We investigate the effects of uncertainties in the velocity model by performing source inversions based on an incorrect, homogeneous velocity model. We find that, for velocity uncertainties that have standard deviation and correlation length typical of available 3D crustal models, the inverted sources can be severely contaminated by spurious features even if the station density is high. When data from thousand or more receivers is used in source inversions in 3D heterogeneous media, the computational cost of the method proposed in this work is at least two orders of magnitude lower than source inversion based on pre-computed Green's functions.

Finite-fault source inversion using adjoint methods in 3-D heterogeneous media

NASA Astrophysics Data System (ADS)

Somala, Surendra Nadh; Ampuero, Jean-Paul; Lapusta, Nadia

2018-07-01

Accounting for lateral heterogeneities in the 3-D velocity structure of the crust is known to improve earthquake source inversion, compared to results based on 1-D velocity models which are routinely assumed to derive finite-fault slip models. The conventional approach to include known 3-D heterogeneity in source inversion involves pre-computing 3-D Green's functions, which requires a number of 3-D wave propagation simulations proportional to the number of stations or to the number of fault cells. The computational cost of such an approach is prohibitive for the dense data sets that could be provided by future earthquake observation systems. Here, we propose an adjoint-based optimization technique to invert for the spatio-temporal evolution of slip velocity. The approach does not require pre-computed Green's functions. The adjoint method provides the gradient of the cost function, which is used to improve the model iteratively employing an iterative gradient-based minimization method. The adjoint approach is shown to be computationally more efficient than the conventional approach based on pre-computed Green's functions in a broad range of situations. We consider data up to 1 Hz from a Haskell source scenario (a steady pulse-like rupture) on a vertical strike-slip fault embedded in an elastic 3-D heterogeneous velocity model. The velocity model comprises a uniform background and a 3-D stochastic perturbation with the von Karman correlation function. Source inversions based on the 3-D velocity model are performed for two different station configurations, a dense and a sparse network with 1 and 20 km station spacing, respectively. These reference inversions show that our inversion scheme adequately retrieves the rise time when the velocity model is exactly known, and illustrates how dense coverage improves the inference of peak-slip velocities. We investigate the effects of uncertainties in the velocity model by performing source inversions based on an incorrect, homogeneous velocity model. We find that, for velocity uncertainties that have standard deviation and correlation length typical of available 3-D crustal models, the inverted sources can be severely contaminated by spurious features even if the station density is high. When data from thousand or more receivers is used in source inversions in 3-D heterogeneous media, the computational cost of the method proposed in this work is at least two orders of magnitude lower than source inversion based on pre-computed Green's functions.

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.

The New Method of Tsunami Source Reconstruction With r-Solution Inversion Method

NASA Astrophysics Data System (ADS)

Voronina, T. A.; Romanenko, A. A.

2016-12-01

Application of the r-solution method to reconstructing the initial tsunami waveform is discussed. This methodology is based on the inversion of remote measurements of water-level data. The wave propagation is considered within the scope of a linear shallow-water theory. The ill-posed inverse problem in question is regularized by means of a least square inversion using the truncated Singular Value Decomposition method. As a result of the numerical process, an r-solution is obtained. The method proposed allows one to control the instability of a numerical solution and to obtain an acceptable result in spite of ill posedness of the problem. Implementation of this methodology to reconstructing of the initial waveform to 2013 Solomon Islands tsunami validates the theoretical conclusion for synthetic data and a model tsunami source: the inversion result strongly depends on data noisiness, the azimuthal and temporal coverage of recording stations with respect to the source area. Furthermore, it is possible to make a preliminary selection of the most informative set of the available recording stations used in the inversion process.

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.

Three-dimensional full waveform inversion of short-period teleseismic wavefields based upon the SEM-DSM hybrid method

NASA Astrophysics Data System (ADS)

Monteiller, Vadim; Chevrot, Sébastien; Komatitsch, Dimitri; Wang, Yi

2015-08-01

We present a method for high-resolution imaging of lithospheric structures based on full waveform inversion of teleseismic waveforms. We model the propagation of seismic waves using our recently developed direct solution method/spectral-element method hybrid technique, which allows us to simulate the propagation of short-period teleseismic waves through a regional 3-D model. We implement an iterative quasi-Newton method based upon the L-BFGS algorithm, where the gradient of the misfit function is computed using the adjoint-state method. Compared to gradient or conjugate-gradient methods, the L-BFGS algorithm has a much faster convergence rate. We illustrate the potential of this method on a synthetic test case that consists of a crustal model with a crustal discontinuity at 25 km depth and a sharp Moho jump. This model contains short- and long-wavelength heterogeneities along the lateral and vertical directions. The iterative inversion starts from a smooth 1-D model derived from the IASP91 reference Earth model. We invert both radial and vertical component waveforms, starting from long-period signals filtered at 10 s and gradually decreasing the cut-off period down to 1.25 s. This multiscale algorithm quickly converges towards a model that is very close to the true model, in contrast to inversions involving short-period waveforms only, which always get trapped into a local minimum of the cost function.

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.

A multi-frequency iterative imaging method for discontinuous inverse medium problem

NASA Astrophysics Data System (ADS)

Zhang, Lei; Feng, Lixin

2018-06-01

The inverse medium problem with discontinuous refractive index is a kind of challenging inverse problem. We employ the primal dual theory and fast solution of integral equations, and propose a new iterative imaging method. The selection criteria of regularization parameter is given by the method of generalized cross-validation. Based on multi-frequency measurements of the scattered field, a recursive linearization algorithm has been presented with respect to the frequency from low to high. We also discuss the initial guess selection strategy by semi-analytical approaches. Numerical experiments are presented to show the effectiveness of the proposed method.

Reflection full-waveform inversion using a modified phase misfit function

NASA Astrophysics Data System (ADS)

Cui, Chao; Huang, Jian-Ping; Li, Zhen-Chun; Liao, Wen-Yuan; Guan, Zhe

2017-09-01

Reflection full-waveform inversion (RFWI) updates the low- and highwavenumber components, and yields more accurate initial models compared with conventional full-waveform inversion (FWI). However, there is strong nonlinearity in conventional RFWI because of the lack of low-frequency data and the complexity of the amplitude. The separation of phase and amplitude information makes RFWI more linear. Traditional phase-calculation methods face severe phase wrapping. To solve this problem, we propose a modified phase-calculation method that uses the phase-envelope data to obtain the pseudo phase information. Then, we establish a pseudophase-information-based objective function for RFWI, with the corresponding source and gradient terms. Numerical tests verify that the proposed calculation method using the phase-envelope data guarantees the stability and accuracy of the phase information and the convergence of the objective function. The application on a portion of the Sigsbee2A model and comparison with inversion results of the improved RFWI and conventional FWI methods verify that the pseudophase-based RFWI produces a highly accurate and efficient velocity model. Moreover, the proposed method is robust to noise and high frequency.

A Synthetic Study on the Resolution of 2D Elastic Full Waveform Inversion

NASA Astrophysics Data System (ADS)

Cui, C.; Wang, Y.

2017-12-01

Gradient based full waveform inversion is an effective method in seismic study, it makes full use of the information given by seismic records and is capable of providing a more accurate model of the interior of the earth at a relatively low computational cost. However, the strong non-linearity of the problem brings about many difficulties in the assessment of its resolution. Synthetic inversions are therefore helpful before an inversion based on real data is made. Checker-board test is a commonly used method, but it is not always reliable due to the significant difference between a checker-board and the true model. Our study aims to provide a basic understanding of the resolution of 2D elastic inversion by examining three main factors that affect the inversion result respectively: 1. The structural characteristic of the model; 2. The level of similarity between the initial model and the true model; 3. The spacial distribution of sources and receivers. We performed about 150 synthetic inversions to demonstrate how each factor contributes to quality of the result, and compared the inversion results with those achieved by checker-board tests. The study can be a useful reference to assess the resolution of an inversion in addition to regular checker-board tests, or to determine whether the seismic data of a specific region is sufficient for a successful inversion.

Stochastic seismic inversion based on an improved local gradual deformation method

NASA Astrophysics Data System (ADS)

Yang, Xiuwei; Zhu, Peimin

2017-12-01

A new stochastic seismic inversion method based on the local gradual deformation method is proposed, which can incorporate seismic data, well data, geology and their spatial correlations into the inversion process. Geological information, such as sedimentary facies and structures, could provide significant a priori information to constrain an inversion and arrive at reasonable solutions. The local a priori conditional cumulative distributions at each node of model to be inverted are first established by indicator cokriging, which integrates well data as hard data and geological information as soft data. Probability field simulation is used to simulate different realizations consistent with the spatial correlations and local conditional cumulative distributions. The corresponding probability field is generated by the fast Fourier transform moving average method. Then, optimization is performed to match the seismic data via an improved local gradual deformation method. Two improved strategies are proposed to be suitable for seismic inversion. The first strategy is that we select and update local areas of bad fitting between synthetic seismic data and real seismic data. The second one is that we divide each seismic trace into several parts and obtain the optimal parameters for each part individually. The applications to a synthetic example and a real case study demonstrate that our approach can effectively find fine-scale acoustic impedance models and provide uncertainty estimations.

Final Technical Report for "Applied Mathematics Research: Simulation Based Optimization and Application to Electromagnetic Inverse Problems"

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

Haber, Eldad

2014-03-17

The focus of research was: Developing adaptive mesh for the solution of Maxwell's equations; Developing a parallel framework for time dependent inverse Maxwell's equations; Developing multilevel methods for optimization problems with inequality constraints; A new inversion code for inverse Maxwell's equations in the 0th frequency (DC resistivity); A new inversion code for inverse Maxwell's equations in low frequency regime. Although the research concentrated on electromagnetic forward and in- verse problems the results of the research was applied to the problem of image registration.

Developing a Method for Resolving NOx Emission Inventory Biases Using Discrete Kalman Filter Inversion, Direct Sensitivities, and Satellite-Based Columns

EPA Science Inventory

An inverse method was developed to integrate satellite observations of atmospheric pollutant column concentrations and direct sensitivities predicted by a regional air quality model in order to discern biases in the emissions of the pollutant precursors.

3-D Magnetotelluric Forward Modeling And Inversion Incorporating Topography By Using Vector Finite-Element Method Combined With Divergence Corrections Based On The Magnetic Field (VFEH++)

NASA Astrophysics Data System (ADS)

Shi, X.; Utada, H.; Jiaying, W.

2009-12-01

The vector finite-element method combined with divergence corrections based on the magnetic field H, referred to as VFEH++ method, is developed to simulate the magnetotelluric (MT) responses of 3-D conductivity models. The advantages of the new VFEH++ method are the use of edge-elements to eliminate the vector parasites and the divergence corrections to explicitly guarantee the divergence-free conditions in the whole modeling domain. 3-D MT topographic responses are modeling using the new VFEH++ method, and are compared with those calculated by other numerical methods. The results show that MT responses can be modeled highly accurate using the VFEH+ +method. The VFEH++ algorithm is also employed for the 3-D MT data inversion incorporating topography. The 3-D MT inverse problem is formulated as a minimization problem of the regularized misfit function. In order to avoid the huge memory requirement and very long time for computing the Jacobian sensitivity matrix for Gauss-Newton method, we employ the conjugate gradient (CG) approach to solve the inversion equation. In each iteration of CG algorithm, the cost computation is the product of the Jacobian sensitivity matrix with a model vector x or its transpose with a data vector y, which can be transformed into two pseudo-forwarding modeling. This avoids the full explicitly Jacobian matrix calculation and storage which leads to considerable savings in the memory required by the inversion program in PC computer. The performance of CG algorithm will be illustrated by several typical 3-D models with horizontal earth surface and topographic surfaces. The results show that the VFEH++ and CG algorithms can be effectively employed to 3-D MT field data inversion.

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.

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.

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.

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.

Numerical solution of 2D-vector tomography problem using the method of approximate inverse

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

Svetov, Ivan; Maltseva, Svetlana; Polyakova, Anna

2016-08-10

We propose a numerical solution of reconstruction problem of a two-dimensional vector field in a unit disk from the known values of the longitudinal and transverse ray transforms. The algorithm is based on the method of approximate inverse. Numerical simulations confirm that the proposed method yields good results of reconstruction of vector fields.

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.

Large-scale inverse model analyses employing fast randomized data reduction

NASA Astrophysics Data System (ADS)

Lin, Youzuo; Le, Ellen B.; O'Malley, Daniel; Vesselinov, Velimir V.; Bui-Thanh, Tan

2017-08-01

When the number of observations is large, it is computationally challenging to apply classical inverse modeling techniques. We have developed a new computationally efficient technique for solving inverse problems with a large number of observations (e.g., on the order of 107 or greater). Our method, which we call the randomized geostatistical approach (RGA), is built upon the principal component geostatistical approach (PCGA). We employ a data reduction technique combined with the PCGA to improve the computational efficiency and reduce the memory usage. Specifically, we employ a randomized numerical linear algebra technique based on a so-called "sketching" matrix to effectively reduce the dimension of the observations without losing the information content needed for the inverse analysis. In this way, the computational and memory costs for RGA scale with the information content rather than the size of the calibration data. Our algorithm is coded in Julia and implemented in the MADS open-source high-performance computational framework (http://mads.lanl.gov). We apply our new inverse modeling method to invert for a synthetic transmissivity field. Compared to a standard geostatistical approach (GA), our method is more efficient when the number of observations is large. Most importantly, our method is capable of solving larger inverse problems than the standard GA and PCGA approaches. Therefore, our new model inversion method is a powerful tool for solving large-scale inverse problems. The method can be applied in any field and is not limited to hydrogeological applications such as the characterization of aquifer heterogeneity.

Nested Global Inversion for the Carbon Flux Distribution in Canada and USA from 1994 to 2003

NASA Astrophysics Data System (ADS)

Chen, J. M.; Deng, F.; Ishizawa, M.; Ju, W.; Mo, G.; Chan, D.; Higuchi, K.; Maksyutov, S.

2007-12-01

Based on TransCom inverse modeling for 22 global regions, we developed a nested global inversion system for estimating carbon fluxes of 30 regions in North America (2 of the 22 regions are divided into 30). Irregular boundaries of these 30 regions are delineated based on ecosystem types and provincial/state borders. Synthesis Bayesian inversion is conducted in monthly steps using CO2 concentration measurements at 88 coastal and continental stations of the globe for the 1994-2003 period (NOAA GlobalView database). Responses of these stations to carbon fluxes from the 50 regions are simulated using the transport model of National Institute for Environmental Studies of Japan and reanalysis wind fields of the National Centers for Environmental Prediction (NCEP). Terrestrial carbon flux fields modeled using BEPS and Biome-BGC driven by NCEP reanalysis meteorological data are used as two different a priori to constrain the inversion. The inversion (top- down) results are compared with remote sensing-based ecosystem modeling (bottom-up) results in Canada's forests and wetlands. There is a broad consistency in the spatial pattern of the carbon source and sink distributions obtained using these two independent methods. Both sets of results also indicate that Canada's forests and wetlands are carbon sinks in 1994-2003, but the top-down method produces consistently larger sinks than the bottom-up results. Reasons for this discrepancy may lie in both methods, and several issues are identified for further investigation.

Integrating conventional and inverse representation for face recognition.

PubMed

Xu, Yong; Li, Xuelong; Yang, Jian; Lai, Zhihui; Zhang, David

2014-10-01

Representation-based classification methods are all constructed on the basis of the conventional representation, which first expresses the test sample as a linear combination of the training samples and then exploits the deviation between the test sample and the expression result of every class to perform classification. However, this deviation does not always well reflect the difference between the test sample and each class. With this paper, we propose a novel representation-based classification method for face recognition. This method integrates conventional and the inverse representation-based classification for better recognizing the face. It first produces conventional representation of the test sample, i.e., uses a linear combination of the training samples to represent the test sample. Then it obtains the inverse representation, i.e., provides an approximation representation of each training sample of a subject by exploiting the test sample and training samples of the other subjects. Finally, the proposed method exploits the conventional and inverse representation to generate two kinds of scores of the test sample with respect to each class and combines them to recognize the face. The paper shows the theoretical foundation and rationale of the proposed method. Moreover, this paper for the first time shows that a basic nature of the human face, i.e., the symmetry of the face can be exploited to generate new training and test samples. As these new samples really reflect some possible appearance of the face, the use of them will enable us to obtain higher accuracy. The experiments show that the proposed conventional and inverse representation-based linear regression classification (CIRLRC), an improvement to linear regression classification (LRC), can obtain very high accuracy and greatly outperforms the naive LRC and other state-of-the-art conventional representation based face recognition methods. The accuracy of CIRLRC can be 10% greater than that of LRC.

Bayesian Inversion of 2D Models from Airborne Transient EM Data

NASA Astrophysics Data System (ADS)

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

2016-12-01

The inherent non-uniqueness in most geophysical inverse problems leads to an infinite number of Earth models that fit observed data to within an adequate tolerance. To resolve this ambiguity, traditional inversion methods based on optimization techniques such as the Gauss-Newton and conjugate gradient methods rely on an additional regularization constraint on the properties that an acceptable model can possess, such as having minimal roughness. While allowing such an inversion scheme to converge on a solution, regularization makes it difficult to estimate the uncertainty associated with the model parameters. This is because regularization biases the inversion process toward certain models that satisfy the regularization constraint and away from others that don't, even when both may suitably fit the data. By contrast, a Bayesian inversion framework aims to produce not a single `most acceptable' model but an estimate of the posterior likelihood of the model parameters, given the observed data. In this work, we develop a 2D Bayesian framework for the inversion of transient electromagnetic (TEM) data. Our method relies on a reversible-jump Markov Chain Monte Carlo (RJ-MCMC) Bayesian inverse method with parallel tempering. Previous gradient-based inversion work in this area used a spatially constrained scheme wherein individual (1D) soundings were inverted together and non-uniqueness was tackled by using lateral and vertical smoothness constraints. By contrast, our work uses a 2D model space of Voronoi cells whose parameterization (including number of cells) is fully data-driven. To make the problem work practically, we approximate the forward solution for each TEM sounding using a local 1D approximation where the model is obtained from the 2D model by retrieving a vertical profile through the Voronoi cells. The implicit parsimony of the Bayesian inversion process leads to the simplest models that adequately explain the data, obviating the need for explicit smoothness constraints. In addition, credible intervals in model space are directly obtained, resolving some of the uncertainty introduced by regularization. An example application shows how the method can be used to quantify the uncertainty in airborne EM soundings for imaging subglacial brine channels and groundwater systems.

Forward modeling and inversion of tensor CSAMT in 3D anisotropic media

NASA Astrophysics Data System (ADS)

Wang, Tao; Wang, Kun-Peng; Tan, Han-Dong

2017-12-01

Tensor controlled-source audio-frequency magnetotellurics (CSAMT) can yield information about electric and magnetic fields owing to its multi-transmitter configuration compared with the common scalar CSAMT. The most current theories, numerical simulations, and inversion of tensor CSAMT are based on far-field measurements and the assumption that underground media have isotropic resistivity. We adopt a three-dimensional (3D) staggered-grid finite difference numerical simulation method to analyze the resistivity in axial anisotropic and isotropic media. We further adopt the limited-memory Broyden-Fletcher-Goldfarb-Shanno (LBFGS) method to perform 3D tensor CSAMT axial anisotropic inversion. The inversion results suggest that when the underground structure is anisotropic, the isotropic inversion will introduce errors to the interpretation.

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.

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.

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.

Comparison result of inversion of gravity data of a fault by particle swarm optimization and Levenberg-Marquardt methods.

PubMed

Toushmalani, Reza

2013-01-01

The purpose of this study was to compare the performance of two methods for gravity inversion of a fault. First method [Particle swarm optimization (PSO)] is a heuristic global optimization method and also an optimization algorithm, which is based on swarm intelligence. It comes from the research on the bird and fish flock movement behavior. Second method [The Levenberg-Marquardt algorithm (LM)] is an approximation to the Newton method used also for training ANNs. In this paper first we discussed the gravity field of a fault, then describes the algorithms of PSO and LM And presents application of Levenberg-Marquardt algorithm, and a particle swarm algorithm in solving inverse problem of a fault. Most importantly the parameters for the algorithms are given for the individual tests. Inverse solution reveals that fault model parameters are agree quite well with the known results. A more agreement has been found between the predicted model anomaly and the observed gravity anomaly in PSO method rather than LM method.

A robust method of computing finite difference coefficients based on Vandermonde matrix

NASA Astrophysics Data System (ADS)

Zhang, Yijie; Gao, Jinghuai; Peng, Jigen; Han, Weimin

2018-05-01

When the finite difference (FD) method is employed to simulate the wave propagation, high-order FD method is preferred in order to achieve better accuracy. However, if the order of FD scheme is high enough, the coefficient matrix of the formula for calculating finite difference coefficients is close to be singular. In this case, when the FD coefficients are computed by matrix inverse operator of MATLAB, inaccuracy can be produced. In order to overcome this problem, we have suggested an algorithm based on Vandermonde matrix in this paper. After specified mathematical transformation, the coefficient matrix is transformed into a Vandermonde matrix. Then the FD coefficients of high-order FD method can be computed by the algorithm of Vandermonde matrix, which prevents the inverse of the singular matrix. The dispersion analysis and numerical results of a homogeneous elastic model and a geophysical model of oil and gas reservoir demonstrate that the algorithm based on Vandermonde matrix has better accuracy compared with matrix inverse operator of MATLAB.

Control Theory based Shape Design for the Incompressible Navier-Stokes Equations

NASA Astrophysics Data System (ADS)

Cowles, G.; Martinelli, L.

2003-12-01

A design method for shape optimization in incompressible turbulent viscous flow has been developed and validated for inverse design. The gradient information is determined using a control theory based algorithm. With such an approach, the cost of computing the gradient is negligible. An additional adjoint system must be solved which requires the cost of a single steady state flow solution. Thus, this method has an enormous advantage over traditional finite-difference based algorithms. The method of artificial compressibility is utilized to solve both the flow and adjoint systems. An algebraic turbulence model is used to compute the eddy viscosity. The method is validated using several inverse wing design test cases. In each case, the program must modify the shape of the initial wing such that its pressure distribution matches that of the target wing. Results are shown for the inversion of both finite thickness wings as well as zero thickness wings which can be considered a model of yacht sails.

2D Unstructured Grid Based Constrained Inversion of Magnetic Data Using Fuzzy C Means Clustering and Lithology Classification

NASA Astrophysics Data System (ADS)

Kumar, V.; Singh, A.; Sharma, S. P.

2016-12-01

Regular grid discretization is often utilized to define complex geological models. However, this subdivision strategy performs at lower precision to represent the topographical observation surface. We have developed a new 2D unstructured grid based inversion for magnetic data for models including topography. It will consolidate prior parametric information into a deterministic inversion system to enhance the boundary between the different lithology based on recovered magnetic susceptibility distribution from the inversion. The presented susceptibility model will satisfy both the observed magnetic data and parametric information and therefore can represent the earth better than geophysical inversion models that only honor the observed magnetic data. Geophysical inversion and lithology classification are generally treated as two autonomous methodologies and connected in a serial way. The presented inversion strategy integrates these two parts into a unified scheme. To reduce the storage space and computation time, the conjugate gradient method is used. It results in feasible and practical imaging inversion of magnetic data to deal with large number of triangular grids. The efficacy of the presented inversion is demonstrated using two synthetic examples and one field data example.

Space structures insulating material's thermophysical and radiation properties estimation

NASA Astrophysics Data System (ADS)

Nenarokomov, A. V.; Alifanov, O. M.; Titov, D. M.

2007-11-01

In many practical situations in aerospace technology it is impossible to measure directly such properties of analyzed materials (for example, composites) as thermal and radiation characteristics. The only way that can often be used to overcome these difficulties is indirect measurements. This type of measurement is usually formulated as the solution of inverse heat transfer problems. Such problems are ill-posed in mathematical sense and their main feature shows itself in the solution instabilities. That is why special regularizing methods are needed to solve them. The experimental methods of identification of the mathematical models of heat transfer based on solving the inverse problems are one of the modern effective solving manners. The objective of this paper is to estimate thermal and radiation properties of advanced materials using the approach based on inverse methods.

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.

Hybrid Adaptive Flight Control with Model Inversion Adaptation

NASA Technical Reports Server (NTRS)

Nguyen, Nhan

2011-01-01

This study investigates a hybrid adaptive flight control method as a design possibility for a flight control system that can enable an effective adaptation strategy to deal with off-nominal flight conditions. The hybrid adaptive control blends both direct and indirect adaptive control in a model inversion flight control architecture. The blending of both direct and indirect adaptive control provides a much more flexible and effective adaptive flight control architecture than that with either direct or indirect adaptive control alone. The indirect adaptive control is used to update the model inversion controller by an on-line parameter estimation of uncertain plant dynamics based on two methods. The first parameter estimation method is an indirect adaptive law based on the Lyapunov theory, and the second method is a recursive least-squares indirect adaptive law. The model inversion controller is therefore made to adapt to changes in the plant dynamics due to uncertainty. As a result, the modeling error is reduced that directly leads to a decrease in the tracking error. In conjunction with the indirect adaptive control that updates the model inversion controller, a direct adaptive control is implemented as an augmented command to further reduce any residual tracking error that is not entirely eliminated by the indirect adaptive control.

Adaptive eigenspace method for inverse scattering problems in the frequency domain

NASA Astrophysics Data System (ADS)

Grote, Marcus J.; Kray, Marie; Nahum, Uri

2017-02-01

A nonlinear optimization method is proposed for the solution of inverse scattering problems in the frequency domain, when the scattered field is governed by the Helmholtz equation. The time-harmonic inverse medium problem is formulated as a PDE-constrained optimization problem and solved by an inexact truncated Newton-type iteration. Instead of a grid-based discrete representation, the unknown wave speed is projected to a particular finite-dimensional basis of eigenfunctions, which is iteratively adapted during the optimization. Truncating the adaptive eigenspace (AE) basis at a (small and slowly increasing) finite number of eigenfunctions effectively introduces regularization into the inversion and thus avoids the need for standard Tikhonov-type regularization. Both analytical and numerical evidence underpins the accuracy of the AE representation. Numerical experiments demonstrate the efficiency and robustness to missing or noisy data of the resulting adaptive eigenspace inversion method.

A multiwave range test for obstacle reconstructions with unknown physical properties

NASA Astrophysics Data System (ADS)

Potthast, Roland; Schulz, Jochen

2007-08-01

We develop a new multiwave version of the range test for shape reconstruction in inverse scattering theory. The range test [R. Potthast, et al., A `range test' for determining scatterers with unknown physical properties, Inverse Problems 19(3) (2003) 533-547] has originally been proposed to obtain knowledge about an unknown scatterer when the far field pattern for only one plane wave is given. Here, we extend the method to the case of multiple waves and show that the full shape of the unknown scatterer can be reconstructed. We further will clarify the relation between the range test methods, the potential method [A. Kirsch, R. Kress, On an integral equation of the first kind in inverse acoustic scattering, in: Inverse Problems (Oberwolfach, 1986), Internationale Schriftenreihe zur Numerischen Mathematik, vol. 77, Birkhauser, Basel, 1986, pp. 93-102] and the singular sources method [R. Potthast, Point sources and multipoles in inverse scattering theory, Habilitation Thesis, Gottingen, 1999]. In particular, we propose a new version of the Kirsch-Kress method using the range test and a new approach to the singular sources method based on the range test and potential method. Numerical examples of reconstructions for all four methods are provided.

An Improved 3D Joint Inversion Method of Potential Field Data Using Cross-Gradient Constraint and LSQR Method

NASA Astrophysics Data System (ADS)

Joulidehsar, Farshad; Moradzadeh, Ali; Doulati Ardejani, Faramarz

2018-06-01

The joint interpretation of two sets of geophysical data related to the same source is an appropriate method for decreasing non-uniqueness of the resulting models during inversion process. Among the available methods, a method based on using cross-gradient constraint combines two datasets is an efficient approach. This method, however, is time-consuming for 3D inversion and cannot provide an exact assessment of situation and extension of anomaly of interest. In this paper, the first attempt is to speed up the required calculation by substituting singular value decomposition by least-squares QR method to solve the large-scale kernel matrix of 3D inversion, more rapidly. Furthermore, to improve the accuracy of resulting models, a combination of depth-weighing matrix and compacted constraint, as automatic selection covariance of initial parameters, is used in the proposed inversion algorithm. This algorithm was developed in Matlab environment and first implemented on synthetic data. The 3D joint inversion of synthetic gravity and magnetic data shows a noticeable improvement in the results and increases the efficiency of algorithm for large-scale problems. Additionally, a real gravity and magnetic dataset of Jalalabad mine, in southeast of Iran was tested. The obtained results by the improved joint 3D inversion of cross-gradient along with compacted constraint showed a mineralised zone in depth interval of about 110-300 m which is in good agreement with the available drilling data. This is also a further confirmation on the accuracy and progress of the improved inversion algorithm.

Full waveform inversion in the frequency domain using classified time-domain residual wavefields

NASA Astrophysics Data System (ADS)

Son, Woohyun; Koo, Nam-Hyung; Kim, Byoung-Yeop; Lee, Ho-Young; Joo, Yonghwan

2017-04-01

We perform the acoustic full waveform inversion in the frequency domain using residual wavefields that have been separated in the time domain. We sort the residual wavefields in the time domain according to the order of absolute amplitudes. Then, the residual wavefields are separated into several groups in the time domain. To analyze the characteristics of the residual wavefields, we compare the residual wavefields of conventional method with those of our residual separation method. From the residual analysis, the amplitude spectrum obtained from the trace before separation appears to have little energy at the lower frequency bands. However, the amplitude spectrum obtained from our strategy is regularized by the separation process, which means that the low-frequency components are emphasized. Therefore, our method helps to emphasize low-frequency components of residual wavefields. Then, we generate the frequency-domain residual wavefields by taking the Fourier transform of the separated time-domain residual wavefields. With these wavefields, we perform the gradient-based full waveform inversion in the frequency domain using back-propagation technique. Through a comparison of gradient directions, we confirm that our separation method can better describe the sub-salt image than the conventional approach. The proposed method is tested on the SEG/EAGE salt-dome model. The inversion results show that our algorithm is better than the conventional gradient based waveform inversion in the frequency domain, especially for deeper parts of the velocity model.

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.

A machine learning approach as a surrogate of finite element analysis-based inverse method to estimate the zero-pressure geometry of human thoracic aorta.

PubMed

Liang, Liang; Liu, Minliang; Martin, Caitlin; Sun, Wei

2018-05-09

Advances in structural finite element analysis (FEA) and medical imaging have made it possible to investigate the in vivo biomechanics of human organs such as blood vessels, for which organ geometries at the zero-pressure level need to be recovered. Although FEA-based inverse methods are available for zero-pressure geometry estimation, these methods typically require iterative computation, which are time-consuming and may be not suitable for time-sensitive clinical applications. In this study, by using machine learning (ML) techniques, we developed an ML model to estimate the zero-pressure geometry of human thoracic aorta given 2 pressurized geometries of the same patient at 2 different blood pressure levels. For the ML model development, a FEA-based method was used to generate a dataset of aorta geometries of 3125 virtual patients. The ML model, which was trained and tested on the dataset, is capable of recovering zero-pressure geometries consistent with those generated by the FEA-based method. Thus, this study demonstrates the feasibility and great potential of using ML techniques as a fast surrogate of FEA-based inverse methods to recover zero-pressure geometries of human organs. Copyright © 2018 John Wiley & Sons, Ltd.

Sparse Matrix Motivated Reconstruction of Far-Field Radiation Patterns

DTIC Science & Technology

2015-03-01

method for base - station antenna radiation patterns. IEEE Antennas Propagation Magazine. 2001;43(2):132. 4. Vasiliadis TG, Dimitriou D, Sergiadis JD...algorithm based on sparse representations of radiation patterns using the inverse Discrete Fourier Transform (DFT) and the inverse Discrete Cosine...patterns using a Model- Based Parameter Estimation (MBPE) technique that reduces the computational time required to model radiation patterns. Another

Sparsity-based acoustic inversion in cross-sectional multiscale optoacoustic imaging

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

Han, Yiyong; Tzoumas, Stratis; Nunes, Antonio

2015-09-15

Purpose: With recent advancement in hardware of optoacoustic imaging systems, highly detailed cross-sectional images may be acquired at a single laser shot, thus eliminating motion artifacts. Nonetheless, other sources of artifacts remain due to signal distortion or out-of-plane signals. The purpose of image reconstruction algorithms is to obtain the most accurate images from noisy, distorted projection data. Methods: In this paper, the authors use the model-based approach for acoustic inversion, combined with a sparsity-based inversion procedure. Specifically, a cost function is used that includes the L1 norm of the image in sparse representation and a total variation (TV) term. Themore » optimization problem is solved by a numerically efficient implementation of a nonlinear gradient descent algorithm. TV–L1 model-based inversion is tested in the cross section geometry for numerically generated data as well as for in vivo experimental data from an adult mouse. Results: In all cases, model-based TV–L1 inversion showed a better performance over the conventional Tikhonov regularization, TV inversion, and L1 inversion. In the numerical examples, the images reconstructed with TV–L1 inversion were quantitatively more similar to the originating images. In the experimental examples, TV–L1 inversion yielded sharper images and weaker streak artifact. Conclusions: The results herein show that TV–L1 inversion is capable of improving the quality of highly detailed, multiscale optoacoustic images obtained in vivo using cross-sectional imaging systems. As a result of its high fidelity, model-based TV–L1 inversion may be considered as the new standard for image reconstruction in cross-sectional imaging.« less

Feasibility of waveform inversion of Rayleigh waves for shallow shear-wave velocity using a genetic algorithm

USGS Publications Warehouse

Zeng, C.; Xia, J.; Miller, R.D.; Tsoflias, G.P.

2011-01-01

Conventional surface wave inversion for shallow shear (S)-wave velocity relies on the generation of dispersion curves of Rayleigh waves. This constrains the method to only laterally homogeneous (or very smooth laterally heterogeneous) earth models. Waveform inversion directly fits waveforms on seismograms, hence, does not have such a limitation. Waveforms of Rayleigh waves are highly related to S-wave velocities. By inverting the waveforms of Rayleigh waves on a near-surface seismogram, shallow S-wave velocities can be estimated for earth models with strong lateral heterogeneity. We employ genetic algorithm (GA) to perform waveform inversion of Rayleigh waves for S-wave velocities. The forward problem is solved by finite-difference modeling in the time domain. The model space is updated by generating offspring models using GA. Final solutions can be found through an iterative waveform-fitting scheme. Inversions based on synthetic records show that the S-wave velocities can be recovered successfully with errors no more than 10% for several typical near-surface earth models. For layered earth models, the proposed method can generate one-dimensional S-wave velocity profiles without the knowledge of initial models. For earth models containing lateral heterogeneity in which case conventional dispersion-curve-based inversion methods are challenging, it is feasible to produce high-resolution S-wave velocity sections by GA waveform inversion with appropriate priori information. The synthetic tests indicate that the GA waveform inversion of Rayleigh waves has the great potential for shallow S-wave velocity imaging with the existence of strong lateral heterogeneity. ?? 2011 Elsevier B.V.

The adaptive parallel UKF inversion method for the shape of space objects based on the ground-based photometric data

NASA Astrophysics Data System (ADS)

Du, Xiaoping; Wang, Yang; Liu, Hao

2018-04-01

The space object in highly elliptical orbit is always presented as an image point on the ground-based imaging equipment so that it is difficult to resolve and identify the shape and attitude directly. In this paper a novel algorithm is presented for the estimation of spacecraft shape. The apparent magnitude model suitable for the inversion of object information such as shape and attitude is established based on the analysis of photometric characteristics. A parallel adaptive shape inversion algorithm based on UKF was designed after the achievement of dynamic equation of the nonlinear, Gaussian system involved with the influence of various dragging forces. The result of a simulation study demonstrate the viability and robustness of the new filter and its fast convergence rate. It realizes the inversion of combination shape with high accuracy, especially for the bus of cube and cylinder. Even though with sparse photometric data, it still can maintain a higher success rate of inversion.

Approximation of the ruin probability using the scaled Laplace transform inversion

PubMed Central

Mnatsakanov, Robert M.; Sarkisian, Khachatur; Hakobyan, Artak

2015-01-01

The problem of recovering the ruin probability in the classical risk model based on the scaled Laplace transform inversion is studied. It is shown how to overcome the problem of evaluating the ruin probability at large values of an initial surplus process. Comparisons of proposed approximations with the ones based on the Laplace transform inversions using a fixed Talbot algorithm as well as on the ones using the Trefethen–Weideman–Schmelzer and maximum entropy methods are presented via a simulation study. PMID:26752796

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.

Secondary Structure Predictions for Long RNA Sequences Based on Inversion Excursions and MapReduce.

PubMed

Yehdego, Daniel T; Zhang, Boyu; Kodimala, Vikram K R; Johnson, Kyle L; Taufer, Michela; Leung, Ming-Ying

2013-05-01

Secondary structures of ribonucleic acid (RNA) molecules play important roles in many biological processes including gene expression and regulation. Experimental observations and computing limitations suggest that we can approach the secondary structure prediction problem for long RNA sequences by segmenting them into shorter chunks, predicting the secondary structures of each chunk individually using existing prediction programs, and then assembling the results to give the structure of the original sequence. The selection of cutting points is a crucial component of the segmenting step. Noting that stem-loops and pseudoknots always contain an inversion, i.e., a stretch of nucleotides followed closely by its inverse complementary sequence, we developed two cutting methods for segmenting long RNA sequences based on inversion excursions: the centered and optimized method. Each step of searching for inversions, chunking, and predictions can be performed in parallel. In this paper we use a MapReduce framework, i.e., Hadoop, to extensively explore meaningful inversion stem lengths and gap sizes for the segmentation and identify correlations between chunking methods and prediction accuracy. We show that for a set of long RNA sequences in the RFAM database, whose secondary structures are known to contain pseudoknots, our approach predicts secondary structures more accurately than methods that do not segment the sequence, when the latter predictions are possible computationally. We also show that, as sequences exceed certain lengths, some programs cannot computationally predict pseudoknots while our chunking methods can. Overall, our predicted structures still retain the accuracy level of the original prediction programs when compared with known experimental secondary structure.

High effective inverse dynamics modelling for dual-arm robot

NASA Astrophysics Data System (ADS)

Shen, Haoyu; Liu, Yanli; Wu, Hongtao

2018-05-01

To deal with the problem of inverse dynamics modelling for dual arm robot, a recursive inverse dynamics modelling method based on decoupled natural orthogonal complement is presented. In this model, the concepts and methods of Decoupled Natural Orthogonal Complement matrices are used to eliminate the constraint forces in the Newton-Euler kinematic equations, and the screws is used to express the kinematic and dynamics variables. On this basis, the paper has developed a special simulation program with symbol software of Mathematica and conducted a simulation research on the a dual-arm robot. Simulation results show that the proposed method based on decoupled natural orthogonal complement can save an enormous amount of CPU time that was spent in computing compared with the recursive Newton-Euler kinematic equations and the results is correct and reasonable, which can verify the reliability and efficiency of the method.

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.

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.

A new segmentation strategy for processing magnetic anomaly detection data of shallow depth ferromagnetic pipeline

NASA Astrophysics Data System (ADS)

Feng, Shuo; Liu, Dejun; Cheng, Xing; Fang, Huafeng; Li, Caifang

2017-04-01

Magnetic anomalies produced by underground ferromagnetic pipelines because of the polarization of earth's magnetic field are used to obtain the information on the location, buried depth and other parameters of pipelines. In order to achieve a fast inversion and interpretation of measured data, it is necessary to develop a fast and stable forward method. Magnetic dipole reconstruction (MDR), as a kind of integration numerical method, is well suited for simulating a thin pipeline anomaly. In MDR the pipeline model must be cut into small magnetic dipoles through different segmentation methods. The segmentation method has an impact on the stability and speed of forward calculation. Rapid and accurate simulation of deep-buried pipelines has been achieved by exciting segmentation method. However, in practical measurement, the depth of underground pipe is uncertain. When it comes to the shallow-buried pipeline, the present segmentation may generate significant errors. This paper aims at solving this problem in three stages. First, the cause of inaccuracy is analyzed by simulation experiment. Secondly, new variable interval section segmentation is proposed based on the existing segmentation. It can help MDR method to obtain simulation results in a fast way under the premise of ensuring the accuracy of different depth models. Finally, the measured data is inversed based on new segmentation method. The result proves that the inversion based on the new segmentation can achieve fast and accurate inversion of depth parameters of underground pipes without being limited by pipeline depth.

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.

Stochastic inversion of cross-borehole radar data from metalliferous vein detection

NASA Astrophysics Data System (ADS)

Zeng, Zhaofa; Huai, Nan; Li, Jing; Zhao, Xueyu; Liu, Cai; Hu, Yingsa; Zhang, Ling; Hu, Zuzhi; Yang, Hui

2017-12-01

In the exploration and evaluation of the metalliferous veins with a cross-borehole radar system, traditional linear inversion methods (least squares inversion, LSQR) only get indirect parameters (permittivity, resistivity, or velocity) to estimate the target structure. They cannot accurately reflect the geological parameters of the metalliferous veins’ media properties. In order to get the intrinsic geological parameters and internal distribution, in this paper, we build a metalliferous veins model based on the stochastic effective medium theory, and carry out stochastic inversion and parameter estimation based on the Monte Carlo sampling algorithm. Compared with conventional LSQR, the stochastic inversion can get higher resolution inversion permittivity and velocity of the target body. We can estimate more accurately the distribution characteristics of abnormality and target internal parameters. It provides a new research idea to evaluate the properties of complex target media.

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.

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.

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.

NLSE: Parameter-Based Inversion Algorithm

NASA Astrophysics Data System (ADS)

Sabbagh, Harold A.; Murphy, R. Kim; Sabbagh, Elias H.; Aldrin, John C.; Knopp, Jeremy S.

Chapter 11 introduced us to the notion of an inverse problem and gave us some examples of the value of this idea to the solution of realistic industrial problems. The basic inversion algorithm described in Chap. 11 was based upon the Gauss-Newton theory of nonlinear least-squares estimation and is called NLSE in this book. In this chapter we will develop the mathematical background of this theory more fully, because this algorithm will be the foundation of inverse methods and their applications during the remainder of this book. We hope, thereby, to introduce the reader to the application of sophisticated mathematical concepts to engineering practice without introducing excessive mathematical sophistication.

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.

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.

Simultaneous Gaussian and exponential inversion for improved analysis of shales by NMR relaxometry

USGS Publications Warehouse

Washburn, Kathryn E.; Anderssen, Endre; Vogt, Sarah J.; Seymour, Joseph D.; Birdwell, Justin E.; Kirkland, Catherine M.; Codd, Sarah L.

2014-01-01

Nuclear magnetic resonance (NMR) relaxometry is commonly used to provide lithology-independent porosity and pore-size estimates for petroleum resource evaluation based on fluid-phase signals. However in shales, substantial hydrogen content is associated with solid and fluid signals and both may be detected. Depending on the motional regime, the signal from the solids may be best described using either exponential or Gaussian decay functions. When the inverse Laplace transform, the standard method for analysis of NMR relaxometry results, is applied to data containing Gaussian decays, this can lead to physically unrealistic responses such as signal or porosity overcall and relaxation times that are too short to be determined using the applied instrument settings. We apply a new simultaneous Gaussian-Exponential (SGE) inversion method to simulated data and measured results obtained on a variety of oil shale samples. The SGE inversion produces more physically realistic results than the inverse Laplace transform and displays more consistent relaxation behavior at high magnetic field strengths. Residuals for the SGE inversion are consistently lower than for the inverse Laplace method and signal overcall at short T2 times is mitigated. Beyond geological samples, the method can also be applied in other fields where the sample relaxation consists of both Gaussian and exponential decays, for example in material, medical and food sciences.

Neural-Based Compensation of Nonlinearities in an Airplane Longitudinal Model with Dynamic-Inversion Control

PubMed Central

Li, YuHui; Jin, FeiTeng

2017-01-01

The inversion design approach is a very useful tool for the complex multiple-input-multiple-output nonlinear systems to implement the decoupling control goal, such as the airplane model and spacecraft model. In this work, the flight control law is proposed using the neural-based inversion design method associated with the nonlinear compensation for a general longitudinal model of the airplane. First, the nonlinear mathematic model is converted to the equivalent linear model based on the feedback linearization theory. Then, the flight control law integrated with this inversion model is developed to stabilize the nonlinear system and relieve the coupling effect. Afterwards, the inversion control combined with the neural network and nonlinear portion is presented to improve the transient performance and attenuate the uncertain effects on both external disturbances and model errors. Finally, the simulation results demonstrate the effectiveness of this controller. PMID:29410680

Two-dimensional probabilistic inversion of plane-wave electromagnetic data: methodology, model constraints and joint inversion with electrical resistivity data

NASA Astrophysics Data System (ADS)

Rosas-Carbajal, Marina; Linde, Niklas; Kalscheuer, Thomas; Vrugt, Jasper A.

2014-03-01

Probabilistic inversion methods based on Markov chain Monte Carlo (MCMC) simulation are well suited to quantify parameter and model uncertainty of nonlinear inverse problems. Yet, application of such methods to CPU-intensive forward models can be a daunting task, particularly if the parameter space is high dimensional. Here, we present a 2-D pixel-based MCMC inversion of plane-wave electromagnetic (EM) data. Using synthetic data, we investigate how model parameter uncertainty depends on model structure constraints using different norms of the likelihood function and the model constraints, and study the added benefits of joint inversion of EM and electrical resistivity tomography (ERT) data. Our results demonstrate that model structure constraints are necessary to stabilize the MCMC inversion results of a highly discretized model. These constraints decrease model parameter uncertainty and facilitate model interpretation. A drawback is that these constraints may lead to posterior distributions that do not fully include the true underlying model, because some of its features exhibit a low sensitivity to the EM data, and hence are difficult to resolve. This problem can be partly mitigated if the plane-wave EM data is augmented with ERT observations. The hierarchical Bayesian inverse formulation introduced and used herein is able to successfully recover the probabilistic properties of the measurement data errors and a model regularization weight. Application of the proposed inversion methodology to field data from an aquifer demonstrates that the posterior mean model realization is very similar to that derived from a deterministic inversion with similar model constraints.

High resolution tsunami inversion for 2010 Chile earthquake

NASA Astrophysics Data System (ADS)

Wu, T.-R.; Ho, T.-C.

2011-12-01

We investigate the feasibility of inverting high-resolution vertical seafloor displacement from tsunami waveforms. An inversion method named "SUTIM" (small unit tsunami inversion method) is developed to meet this goal. In addition to utilizing the conventional least-square inversion, this paper also enhances the inversion resolution by Grid-Shifting method. A smooth constraint is adopted to gain stability. After a series of validation and performance tests, SUTIM is used to study the 2010 Chile earthquake. Based upon data quality and azimuthal distribution, we select tsunami waveforms from 6 GLOSS stations and 1 DART buoy record. In total, 157 sub-faults are utilized for the high-resolution inversion. The resolution reaches 10 sub-faults per wavelength. The result is compared with the distribution of the aftershocks and waveforms at each gauge location with very good agreement. The inversion result shows that the source profile features a non-uniform distribution of the seafloor displacement. The highly elevated vertical seafloor is mainly concentrated in two areas: one is located in the northern part of the epicentre, between 34° S and 36° S; the other is in the southern part, between 37° S and 38° S.

Multidimensional NMR inversion without Kronecker products: Multilinear inversion

NASA Astrophysics Data System (ADS)

Medellín, David; Ravi, Vivek R.; Torres-Verdín, Carlos

2016-08-01

Multidimensional NMR inversion using Kronecker products poses several challenges. First, kernel compression is only possible when the kernel matrices are separable, and in recent years, there has been an increasing interest in NMR sequences with non-separable kernels. Second, in three or more dimensions, the singular value decomposition is not unique; therefore kernel compression is not well-defined for higher dimensions. Without kernel compression, the Kronecker product yields matrices that require large amounts of memory, making the inversion intractable for personal computers. Finally, incorporating arbitrary regularization terms is not possible using the Lawson-Hanson (LH) or the Butler-Reeds-Dawson (BRD) algorithms. We develop a minimization-based inversion method that circumvents the above problems by using multilinear forms to perform multidimensional NMR inversion without using kernel compression or Kronecker products. The new method is memory efficient, requiring less than 0.1% of the memory required by the LH or BRD methods. It can also be extended to arbitrary dimensions and adapted to include non-separable kernels, linear constraints, and arbitrary regularization terms. Additionally, it is easy to implement because only a cost function and its first derivative are required to perform the inversion.

Design for a Crane Metallic Structure Based on Imperialist Competitive Algorithm and Inverse Reliability Strategy

NASA Astrophysics Data System (ADS)

Fan, Xiao-Ning; Zhi, Bo

2017-07-01

Uncertainties in parameters such as materials, loading, and geometry are inevitable in designing metallic structures for cranes. When considering these uncertainty factors, reliability-based design optimization (RBDO) offers a more reasonable design approach. However, existing RBDO methods for crane metallic structures are prone to low convergence speed and high computational cost. A unilevel RBDO method, combining a discrete imperialist competitive algorithm with an inverse reliability strategy based on the performance measure approach, is developed. Application of the imperialist competitive algorithm at the optimization level significantly improves the convergence speed of this RBDO method. At the reliability analysis level, the inverse reliability strategy is used to determine the feasibility of each probabilistic constraint at each design point by calculating its α-percentile performance, thereby avoiding convergence failure, calculation error, and disproportionate computational effort encountered using conventional moment and simulation methods. Application of the RBDO method to an actual crane structure shows that the developed RBDO realizes a design with the best tradeoff between economy and safety together with about one-third of the convergence speed and the computational cost of the existing method. This paper provides a scientific and effective design approach for the design of metallic structures of cranes.

Approximate non-linear multiparameter inversion for multicomponent single and double P-wave scattering in isotropic elastic media

NASA Astrophysics Data System (ADS)

Ouyang, Wei; Mao, Weijian

2018-03-01

An asymptotic quadratic true-amplitude inversion method for isotropic elastic P waves is proposed to invert medium parameters. The multicomponent P-wave scattered wavefield is computed based on a forward relationship using second-order Born approximation and corresponding high-frequency ray theoretical methods. Within the local double scattering mechanism, the P-wave transmission factors are elaborately calculated, which results in the radiation pattern for P-waves scattering being a quadratic combination of the density and Lamé's moduli perturbation parameters. We further express the elastic P-wave scattered wavefield in a form of generalized Radon transform (GRT). After introducing classical backprojection operators, we obtain an approximate solution of the inverse problem by solving a quadratic non-linear system. Numerical tests with synthetic data computed by finite-differences scheme demonstrate that our quadratic inversion can accurately invert perturbation parameters for strong perturbations, compared with the P-wave single-scattering linear inversion method. Although our inversion strategy here is only syncretized with P-wave scattering, it can be extended to invert multicomponent elastic data containing both P-wave and S-wave information.

Approximate nonlinear multiparameter inversion for multicomponent single and double P-wave scattering in isotropic elastic media

NASA Astrophysics Data System (ADS)

Ouyang, Wei; Mao, Weijian

2018-07-01

An asymptotic quadratic true-amplitude inversion method for isotropic elastic P waves is proposed to invert medium parameters. The multicomponent P-wave scattered wavefield is computed based on a forward relationship using second-order Born approximation and corresponding high-frequency ray theoretical methods. Within the local double scattering mechanism, the P-wave transmission factors are elaborately calculated, which results in the radiation pattern for P-wave scattering being a quadratic combination of the density and Lamé's moduli perturbation parameters. We further express the elastic P-wave scattered wavefield in a form of generalized Radon transform. After introducing classical backprojection operators, we obtain an approximate solution of the inverse problem by solving a quadratic nonlinear system. Numerical tests with synthetic data computed by finite-differences scheme demonstrate that our quadratic inversion can accurately invert perturbation parameters for strong perturbations, compared with the P-wave single-scattering linear inversion method. Although our inversion strategy here is only syncretized with P-wave scattering, it can be extended to invert multicomponent elastic data containing both P- and S-wave information.

Calculation of the transitions in the amine inversion vibration of some local anesthetics

NASA Astrophysics Data System (ADS)

Alcolea Palafox, M.

1988-05-01

In the para-amino group of the local anesthetics benzocaine, procaine and procaine hydrochloride, the potential function of inversion, the barrier height V̂ i and the optimum ω o inversion angle have been determinated. Two methods are shown for calculating transitions based on the two frequencies of inversion which easily can be detected in the infrared absorption and Raman spectra in solid compounds. Also the frequencies associated with tra nsitions are able to be obtained.

A gEUD-based inverse planning technique for HDR prostate brachytherapy: Feasibility study

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

Giantsoudi, D.; Department of Radiation Oncology, Francis H. Burr Proton Therapy Center, Boston, Massachusetts 02114; Baltas, D.

2013-04-15

Purpose: The purpose of this work was to study the feasibility of a new inverse planning technique based on the generalized equivalent uniform dose for image-guided high dose rate (HDR) prostate cancer brachytherapy in comparison to conventional dose-volume based optimization. Methods: The quality of 12 clinical HDR brachytherapy implants for prostate utilizing HIPO (Hybrid Inverse Planning Optimization) is compared with alternative plans, which were produced through inverse planning using the generalized equivalent uniform dose (gEUD). All the common dose-volume indices for the prostate and the organs at risk were considered together with radiobiological measures. The clinical effectiveness of the differentmore » dose distributions was investigated by comparing dose volume histogram and gEUD evaluators. Results: Our results demonstrate the feasibility of gEUD-based inverse planning in HDR brachytherapy implants for prostate. A statistically significant decrease in D{sub 10} or/and final gEUD values for the organs at risk (urethra, bladder, and rectum) was found while improving dose homogeneity or dose conformity of the target volume. Conclusions: Following the promising results of gEUD-based optimization in intensity modulated radiation therapy treatment optimization, as reported in the literature, the implementation of a similar model in HDR brachytherapy treatment plan optimization is suggested by this study. The potential of improved sparing of organs at risk was shown for various gEUD-based optimization parameter protocols, which indicates the ability of this method to adapt to the user's preferences.« less

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.

Joint three-dimensional inversion of coupled groundwater flow and heat transfer based on automatic differentiation: sensitivity calculation, verification, and synthetic examples

NASA Astrophysics Data System (ADS)

Rath, V.; Wolf, A.; Bücker, H. M.

2006-10-01

Inverse methods are useful tools not only for deriving estimates of unknown parameters of the subsurface, but also for appraisal of the thus obtained models. While not being neither the most general nor the most efficient methods, Bayesian inversion based on the calculation of the Jacobian of a given forward model can be used to evaluate many quantities useful in this process. The calculation of the Jacobian, however, is computationally expensive and, if done by divided differences, prone to truncation error. Here, automatic differentiation can be used to produce derivative code by source transformation of an existing forward model. We describe this process for a coupled fluid flow and heat transport finite difference code, which is used in a Bayesian inverse scheme to estimate thermal and hydraulic properties and boundary conditions form measured hydraulic potentials and temperatures. The resulting derivative code was validated by comparison to simple analytical solutions and divided differences. Synthetic examples from different flow regimes demonstrate the use of the inverse scheme, and its behaviour in different configurations.

Forward and Inverse Modeling of Self-potential. A Tomography of Groundwater Flow and Comparison Between Deterministic and Stochastic Inversion Methods

NASA Astrophysics Data System (ADS)

Quintero-Chavarria, E.; Ochoa Gutierrez, L. H.

2016-12-01

Applications of the Self-potential Method in the fields of Hydrogeology and Environmental Sciences have had significant developments during the last two decades with a strong use on groundwater flows identification. Although only few authors deal with the forward problem's solution -especially in geophysics literature- different inversion procedures are currently being developed but in most cases they are compared with unconventional groundwater velocity fields and restricted to structured meshes. This research solves the forward problem based on the finite element method using the St. Venant's Principle to transform a point dipole, which is the field generated by a single vector, into a distribution of electrical monopoles. Then, two simple aquifer models were generated with specific boundary conditions and head potentials, velocity fields and electric potentials in the medium were computed. With the model's surface electric potential, the inverse problem is solved to retrieve the source of electric potential (vector field associated to groundwater flow) using deterministic and stochastic approaches. The first approach was carried out by implementing a Tikhonov regularization with a stabilized operator adapted to the finite element mesh while for the second a hierarchical Bayesian model based on Markov chain Monte Carlo (McMC) and Markov Random Fields (MRF) was constructed. For all implemented methods, the result between the direct and inverse models was contrasted in two ways: 1) shape and distribution of the vector field, and 2) magnitude's histogram. Finally, it was concluded that inversion procedures are improved when the velocity field's behavior is considered, thus, the deterministic method is more suitable for unconfined aquifers than confined ones. McMC has restricted applications and requires a lot of information (particularly in potentials fields) while MRF has a remarkable response especially when dealing with confined aquifers.

The Association Between Fog and Temperature Inversions from Ground and Radiosonde Observations in East Greenland

NASA Astrophysics Data System (ADS)

Gilson, G.; Jiskoot, H.

2016-12-01

Many Arctic glaciers terminate along coasts where temperature inversions and sea fog are frequent during summer. Both can influence glacier ablation, but the effects of fog may be complex. To understand fog's physical and radiative properties and its association to temperature inversions it is important to determine accurate Arctic coastal fog climatologies In previous research we determined that fog in East Greenland peaks in the melt season and can be spatially extensive over glacierized terrain. In this study we aim to understand which environmental factors influence fog occurrence in East Greenland; understand the association between fog and temperature inversions; and quantify fog height. We analyzed fog observations and other weather data from coastal synoptic weather stations, and extracted temperature inversions from the Integrated Global Radiosonde Archive radiosonde profiles. Fog height was calculated from radiosonde profiles, based on a method developed for radiation fog which we expanded to include advection and steam fog. Our results show that Arctic coastal fog requires sea ice breakup and a sea breeze with wind speed between 1-4 m/s. Fog is mostly advective, occurring under stable synoptic conditions characterized by deep and strong low-level temperature inversions. Steam fog may occur 5-30% of the time. Fog can occur under near-surface subsidence, with a subsaturated inversion base, or a saturated inversion base. We classified five types of fog based on their vertical sounding characteristics: only at the surface, below an inversion, capped by an inversion, inside a surface-based inversion, or inside a low-level inversion. Fog is commonly 100-400 m thick, often reaching the top of the boundary layer. Fog height is greater at northern stations, where daily fog duration is longer and relative humidity lower. Our results will be included in glacier energy-balance models to account for the influence of fog and temperature inversions on glacier melt.

Eruption mass estimation using infrasound waveform inversion and ash and gas measurements: Evaluation at Sakurajima Volcano, Japan [Comparison of eruption masses at Sakurajima Volcano, Japan calculated by infrasound waveform inversion and ground-based sampling

DOE PAGES

Fee, David; Izbekov, Pavel; Kim, Keehoon; ...

2017-10-09

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 appliedmore » to the inversion technique. Furthermore 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.« less

Eruption mass estimation using infrasound waveform inversion and ash and gas measurements: Evaluation at Sakurajima Volcano, Japan [Comparison of eruption masses at Sakurajima Volcano, Japan calculated by infrasound waveform inversion and ground-based sampling

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

Fee, David; Izbekov, Pavel; Kim, Keehoon

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 appliedmore » to the inversion technique. Furthermore 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.« less

Research on inverse, hybrid and optimization problems in engineering sciences with emphasis on turbomachine aerodynamics: Review of Chinese advances

NASA Technical Reports Server (NTRS)

Liu, Gao-Lian

1991-01-01

Advances in inverse design and optimization theory in engineering fields in China are presented. Two original approaches, the image-space approach and the variational approach, are discussed in terms of turbomachine aerodynamic inverse design. Other areas of research in turbomachine aerodynamic inverse design include the improved mean-streamline (stream surface) method and optimization theory based on optimal control. Among the additional engineering fields discussed are the following: the inverse problem of heat conduction, free-surface flow, variational cogeneration of optimal grid and flow field, and optimal meshing theory of gears.

Technical Note: Approximate Bayesian parameterization of a process-based tropical forest model

NASA Astrophysics Data System (ADS)

Hartig, F.; Dislich, C.; Wiegand, T.; Huth, A.

2014-02-01

Inverse parameter estimation of process-based models is a long-standing problem in many scientific disciplines. A key question for inverse parameter estimation is how to define the metric that quantifies how well model predictions fit to the data. This metric can be expressed by general cost or objective functions, but statistical inversion methods require a particular metric, the probability of observing the data given the model parameters, known as the likelihood. For technical and computational reasons, likelihoods for process-based stochastic models are usually based on general assumptions about variability in the observed data, and not on the stochasticity generated by the model. Only in recent years have new methods become available that allow the generation of likelihoods directly from stochastic simulations. Previous applications of these approximate Bayesian methods have concentrated on relatively simple models. Here, we report on the application of a simulation-based likelihood approximation for FORMIND, a parameter-rich individual-based model of tropical forest dynamics. We show that approximate Bayesian inference, based on a parametric likelihood approximation placed in a conventional Markov chain Monte Carlo (MCMC) sampler, performs well in retrieving known parameter values from virtual inventory data generated by the forest model. We analyze the results of the parameter estimation, examine its sensitivity to the choice and aggregation of model outputs and observed data (summary statistics), and demonstrate the application of this method by fitting the FORMIND model to field data from an Ecuadorian tropical forest. Finally, we discuss how this approach differs from approximate Bayesian computation (ABC), another method commonly used to generate simulation-based likelihood approximations. Our results demonstrate that simulation-based inference, which offers considerable conceptual advantages over more traditional methods for inverse parameter estimation, can be successfully applied to process-based models of high complexity. The methodology is particularly suitable for heterogeneous and complex data structures and can easily be adjusted to other model types, including most stochastic population and individual-based models. Our study therefore provides a blueprint for a fairly general approach to parameter estimation of stochastic process-based models.

Research on Inversion Models for Forest Height Estimation Using Polarimetric SAR Interferometry

NASA Astrophysics Data System (ADS)

Zhang, L.; Duan, B.; Zou, B.

2017-09-01

The forest height is an important forest resource information parameter and usually used in biomass estimation. Forest height extraction with PolInSAR is a hot research field of imaging SAR remote sensing. SAR interferometry is a well-established SAR technique to estimate the vertical location of the effective scattering center in each resolution cell through the phase difference in images acquired from spatially separated antennas. The manipulation of PolInSAR has applications ranging from climate monitoring to disaster detection especially when used in forest area, is of particular interest because it is quite sensitive to the location and vertical distribution of vegetation structure components. However, some of the existing methods can't estimate forest height accurately. Here we introduce several available inversion models and compare the precision of some classical inversion approaches using simulated data. By comparing the advantages and disadvantages of these inversion methods, researchers can find better solutions conveniently based on these inversion methods.

A sparse reconstruction method for the estimation of multiresolution emission fields via atmospheric inversion

DOE PAGES

Ray, J.; Lee, J.; Yadav, V.; ...

2014-08-20

We present a sparse reconstruction scheme that can also be used to ensure non-negativity when fitting wavelet-based random field models to limited observations in non-rectangular geometries. The method is relevant when multiresolution fields are estimated using linear inverse problems. Examples include the estimation of emission fields for many anthropogenic pollutants using atmospheric inversion or hydraulic conductivity in aquifers from flow measurements. The scheme is based on three new developments. Firstly, we extend an existing sparse reconstruction method, Stagewise Orthogonal Matching Pursuit (StOMP), to incorporate prior information on the target field. Secondly, we develop an iterative method that uses StOMP tomore » impose non-negativity on the estimated field. Finally, we devise a method, based on compressive sensing, to limit the estimated field within an irregularly shaped domain. We demonstrate the method on the estimation of fossil-fuel CO 2 (ffCO 2) emissions in the lower 48 states of the US. The application uses a recently developed multiresolution random field model and synthetic observations of ffCO 2 concentrations from a limited set of measurement sites. We find that our method for limiting the estimated field within an irregularly shaped region is about a factor of 10 faster than conventional approaches. It also reduces the overall computational cost by a factor of two. Further, the sparse reconstruction scheme imposes non-negativity without introducing strong nonlinearities, such as those introduced by employing log-transformed fields, and thus reaps the benefits of simplicity and computational speed that are characteristic of linear inverse problems.« less

Inverse problems and optimal experiment design in unsteady heat transfer processes identification

NASA Technical Reports Server (NTRS)

Artyukhin, Eugene A.

1991-01-01

Experimental-computational methods for estimating characteristics of unsteady heat transfer processes are analyzed. The methods are based on the principles of distributed parameter system identification. The theoretical basis of such methods is the numerical solution of nonlinear ill-posed inverse heat transfer problems and optimal experiment design problems. Numerical techniques for solving problems are briefly reviewed. The results of the practical application of identification methods are demonstrated when estimating effective thermophysical characteristics of composite materials and thermal contact resistance in two-layer systems.

Kinematics of an in-parallel actuated manipulator based on the Stewart platform mechanism

NASA Technical Reports Server (NTRS)

Williams, Robert L., II

1992-01-01

This paper presents kinematic equations and solutions for an in-parallel actuated robotic mechanism based on Stewart's platform. These equations are required for inverse position and resolved rate (inverse velocity) platform control. NASA LaRC has a Vehicle Emulator System (VES) platform designed by MIT which is based on Stewart's platform. The inverse position solution is straight-forward and computationally inexpensive. Given the desired position and orientation of the moving platform with respect to the base, the lengths of the prismatic leg actuators are calculated. The forward position solution is more complicated and theoretically has 16 solutions. The position and orientation of the moving platform with respect to the base is calculated given the leg actuator lengths. Two methods are pursued in this paper to solve this problem. The resolved rate (inverse velocity) solution is derived. Given the desired Cartesian velocity of the end-effector, the required leg actuator rates are calculated. The Newton-Raphson Jacobian matrix resulting from the second forward position kinematics solution is a modified inverse Jacobian matrix. Examples and simulations are given for the VES.

Whole head quantitative susceptibility mapping using a least-norm direct dipole inversion method.

PubMed

Sun, Hongfu; Ma, Yuhan; MacDonald, M Ethan; Pike, G Bruce

2018-06-15

A new dipole field inversion method for whole head quantitative susceptibility mapping (QSM) is proposed. Instead of performing background field removal and local field inversion sequentially, the proposed method performs dipole field inversion directly on the total field map in a single step. To aid this under-determined and ill-posed inversion process and obtain robust QSM images, Tikhonov regularization is implemented to seek the local susceptibility solution with the least-norm (LN) using the L-curve criterion. The proposed LN-QSM does not require brain edge erosion, thereby preserving the cerebral cortex in the final images. This should improve its applicability for QSM-based cortical grey matter measurement, functional imaging and venography of full brain. Furthermore, LN-QSM also enables susceptibility mapping of the entire head without the need for brain extraction, which makes QSM reconstruction more automated and less dependent on intermediate pre-processing methods and their associated parameters. It is shown that the proposed LN-QSM method reduced errors in a numerical phantom simulation, improved accuracy in a gadolinium phantom experiment, and suppressed artefacts in nine subjects, as compared to two-step and other single-step QSM methods. Measurements of deep grey matter and skull susceptibilities from LN-QSM are consistent with established reconstruction methods. Copyright © 2018 Elsevier Inc. All rights reserved.

Application of Sub-Bottom Profiler to Study Riverbed Structure and Sediment Density

NASA Astrophysics Data System (ADS)

Rui, Wang; Changzheng, Li; Xiaofei, Yan

2018-03-01

In this pater, we present a study on the riverbed structure and sediment density in-situ test by using sub-bottom profiler. Compared with traditional direct observation methods, the sub-bottom profiler method based on sonar technology is non-contact, low-disturbance and high-efficient. We finish the investigation of several sections in Sanmenxia and Xiaolangdi reservoirs, which located on the main channel of lower reaches of Yellow River. Collected data show a detailed layered structure of the riverbed sediment which believed caused by sedimentary processes in different periods. Further more, we analyse the reflection coefficient of water-sediment interface and inverse the sediment density data from the raw wave record. The inversion method is based on the effective density fluid model and Kozeny-Carman formula. The comparison of the inversion results and sample tests shows that the in-situ test is reliable and useable.

Adaptive multi-step Full Waveform Inversion based on Waveform Mode Decomposition

NASA Astrophysics Data System (ADS)

Hu, Yong; Han, Liguo; Xu, Zhuo; Zhang, Fengjiao; Zeng, Jingwen

2017-04-01

Full Waveform Inversion (FWI) can be used to build high resolution velocity models, but there are still many challenges in seismic field data processing. The most difficult problem is about how to recover long-wavelength components of subsurface velocity models when seismic data is lacking of low frequency information and without long-offsets. To solve this problem, we propose to use Waveform Mode Decomposition (WMD) method to reconstruct low frequency information for FWI to obtain a smooth model, so that the initial model dependence of FWI can be reduced. In this paper, we use adjoint-state method to calculate the gradient for Waveform Mode Decomposition Full Waveform Inversion (WMDFWI). Through the illustrative numerical examples, we proved that the low frequency which is reconstructed by WMD method is very reliable. WMDFWI in combination with the adaptive multi-step inversion strategy can obtain more faithful and accurate final inversion results. Numerical examples show that even if the initial velocity model is far from the true model and lacking of low frequency information, we still can obtain good inversion results with WMD method. From numerical examples of anti-noise test, we see that the adaptive multi-step inversion strategy for WMDFWI has strong ability to resist Gaussian noise. WMD method is promising to be able to implement for the land seismic FWI, because it can reconstruct the low frequency information, lower the dominant frequency in the adjoint source, and has a strong ability to resist noise.

Frequency-domain elastic full waveform inversion using encoded simultaneous sources

NASA Astrophysics Data System (ADS)

Jeong, W.; Son, W.; Pyun, S.; Min, D.

2011-12-01

Currently, numerous studies have endeavored to develop robust full waveform inversion and migration algorithms. These processes require enormous computational costs, because of the number of sources in the survey. To avoid this problem, the phase encoding technique for prestack migration was proposed by Romero (2000) and Krebs et al. (2009) proposed the encoded simultaneous-source inversion technique in the time domain. On the other hand, Ben-Hadj-Ali et al. (2011) demonstrated the robustness of the frequency-domain full waveform inversion with simultaneous sources for noisy data changing the source assembling. Although several studies on simultaneous-source inversion tried to estimate P- wave velocity based on the acoustic wave equation, seismic migration and waveform inversion based on the elastic wave equations are required to obtain more reliable subsurface information. In this study, we propose a 2-D frequency-domain elastic full waveform inversion technique using phase encoding methods. In our algorithm, the random phase encoding method is employed to calculate the gradients of the elastic parameters, source signature estimation and the diagonal entries of approximate Hessian matrix. The crosstalk for the estimated source signature and the diagonal entries of approximate Hessian matrix are suppressed with iteration as for the gradients. Our 2-D frequency-domain elastic waveform inversion algorithm is composed using the back-propagation technique and the conjugate-gradient method. Source signature is estimated using the full Newton method. We compare the simultaneous-source inversion with the conventional waveform inversion for synthetic data sets of the Marmousi-2 model. The inverted results obtained by simultaneous sources are comparable to those obtained by individual sources, and source signature is successfully estimated in simultaneous source technique. Comparing the inverted results using the pseudo Hessian matrix with previous inversion results provided by the approximate Hessian matrix, it is noted that the latter are better than the former for deeper parts of the model. This work was financially supported by the Brain Korea 21 project of Energy System Engineering, by the Basic Science Research Program through the National Research Foundation of Korea (NRF) funded by the Ministry of Education, Science and Technology (2010-0006155), by the Energy Efficiency & Resources of the Korea Institute of Energy Technology Evaluation and Planning (KETEP) grant funded by the Korea government Ministry of Knowledge Economy (No. 2010T100200133).

Using sequential self-calibration method to identify conductivity distribution: Conditioning on tracer test data

USGS Publications Warehouse

Hu, B.X.; He, C.

2008-01-01

An iterative inverse method, the sequential self-calibration method, is developed for mapping spatial distribution of a hydraulic conductivity field by conditioning on nonreactive tracer breakthrough curves. A streamline-based, semi-analytical simulator is adopted to simulate solute transport in a heterogeneous aquifer. The simulation is used as the forward modeling step. In this study, the hydraulic conductivity is assumed to be a deterministic or random variable. Within the framework of the streamline-based simulator, the efficient semi-analytical method is used to calculate sensitivity coefficients of the solute concentration with respect to the hydraulic conductivity variation. The calculated sensitivities account for spatial correlations between the solute concentration and parameters. The performance of the inverse method is assessed by two synthetic tracer tests conducted in an aquifer with a distinct spatial pattern of heterogeneity. The study results indicate that the developed iterative inverse method is able to identify and reproduce the large-scale heterogeneity pattern of the aquifer given appropriate observation wells in these synthetic cases. ?? International Association for Mathematical Geology 2008.

Low frequency full waveform seismic inversion within a tree based Bayesian framework

NASA Astrophysics Data System (ADS)

Ray, Anandaroop; Kaplan, Sam; Washbourne, John; Albertin, Uwe

2018-01-01

Limited illumination, insufficient offset, noisy data and poor starting models can pose challenges for seismic full waveform inversion. We present an application of a tree based Bayesian inversion scheme which attempts to mitigate these problems by accounting for data uncertainty while using a mildly informative prior about subsurface structure. We sample the resulting posterior model distribution of compressional velocity using a trans-dimensional (trans-D) or Reversible Jump Markov chain Monte Carlo method in the wavelet transform domain of velocity. This allows us to attain rapid convergence to a stationary distribution of posterior models while requiring a limited number of wavelet coefficients to define a sampled model. Two synthetic, low frequency, noisy data examples are provided. The first example is a simple reflection + transmission inverse problem, and the second uses a scaled version of the Marmousi velocity model, dominated by reflections. Both examples are initially started from a semi-infinite half-space with incorrect background velocity. We find that the trans-D tree based approach together with parallel tempering for navigating rugged likelihood (i.e. misfit) topography provides a promising, easily generalized method for solving large-scale geophysical inverse problems which are difficult to optimize, but where the true model contains a hierarchy of features at multiple scales.

Patient-specific Monte Carlo-based dose-kernel approach for inverse planning in afterloading brachytherapy.

PubMed

D'Amours, Michel; Pouliot, Jean; Dagnault, Anne; Verhaegen, Frank; Beaulieu, Luc

2011-12-01

Brachytherapy planning software relies on the Task Group report 43 dosimetry formalism. This formalism, based on a water approximation, neglects various heterogeneous materials present during treatment. Various studies have suggested that these heterogeneities should be taken into account to improve the treatment quality. The present study sought to demonstrate the feasibility of incorporating Monte Carlo (MC) dosimetry within an inverse planning algorithm to improve the dose conformity and increase the treatment quality. The method was based on precalculated dose kernels in full patient geometries, representing the dose distribution of a brachytherapy source at a single dwell position using MC simulations and the Geant4 toolkit. These dose kernels are used by the inverse planning by simulated annealing tool to produce a fast MC-based plan. A test was performed for an interstitial brachytherapy breast treatment using two different high-dose-rate brachytherapy sources: the microSelectron iridium-192 source and the electronic brachytherapy source Axxent operating at 50 kVp. A research version of the inverse planning by simulated annealing algorithm was combined with MC to provide a method to fully account for the heterogeneities in dose optimization, using the MC method. The effect of the water approximation was found to depend on photon energy, with greater dose attenuation for the lower energies of the Axxent source compared with iridium-192. For the latter, an underdosage of 5.1% for the dose received by 90% of the clinical target volume was found. A new method to optimize afterloading brachytherapy plans that uses MC dosimetric information was developed. Including computed tomography-based information in MC dosimetry in the inverse planning process was shown to take into account the full range of scatter and heterogeneity conditions. This led to significant dose differences compared with the Task Group report 43 approach for the Axxent source. Copyright © 2011 Elsevier Inc. All rights reserved.

A model-assisted radio occultation data inversion method based on data ingestion into NeQuick

NASA Astrophysics Data System (ADS)

Shaikh, M. M.; Nava, B.; Kashcheyev, A.

2017-01-01

Inverse Abel transform is the most common method to invert radio occultation (RO) data in the ionosphere and it is based on the assumption of the spherical symmetry for the electron density distribution in the vicinity of an occultation event. It is understood that this 'spherical symmetry hypothesis' could fail, above all, in the presence of strong horizontal electron density gradients. As a consequence, in some cases wrong electron density profiles could be obtained. In this work, in order to incorporate the knowledge of horizontal gradients, we have suggested an inversion technique based on the adaption of the empirical ionospheric model, NeQuick2, to RO-derived TEC. The method relies on the minimization of a cost function involving experimental and model-derived TEC data to determine NeQuick2 input parameters (effective local ionization parameters) at specific locations and times. These parameters are then used to obtain the electron density profile along the tangent point (TP) positions associated with the relevant RO event using NeQuick2. The main focus of our research has been laid on the mitigation of spherical symmetry effects from RO data inversion without using external data such as data from global ionospheric maps (GIM). By using RO data from Constellation Observing System for Meteorology Ionosphere and Climate (FORMOSAT-3/COSMIC) mission and manually scaled peak density data from a network of ionosondes along Asian and American longitudinal sectors, we have obtained a global improvement of 5% with 7% in Asian longitudinal sector (considering the data used in this work), in the retrieval of peak electron density (NmF2) with model-assisted inversion as compared to the Abel inversion. Mean errors of NmF2 in Asian longitudinal sector are calculated to be much higher compared to American sector.

Forward and inverse models of electromagnetic scattering from layered media with rough interfaces

NASA Astrophysics Data System (ADS)

Tabatabaeenejad, Seyed Alireza

This work addresses the problem of electromagnetic scattering from layered dielectric structures with rough boundaries and the associated inverse problem of retrieving the subsurface parameters of the structure using the scattered field. To this end, a forward scattering model based on the Small Perturbation Method (SPM) is developed to calculate the first-order spectral-domain bistatic scattering coefficients of a two-layer rough surface structure. SPM requires the boundaries to be slightly rough compared to the wavelength, but to understand the range of applicability of this method in scattering from two-layer rough surfaces, its region of validity is investigated by comparing its output with that of a first principle solver that does not impose roughness restrictions. The Method of Moments (MoM) is used for this purpose. Finally, for retrieval of the model parameters of the layered structure using scattered field, an inversion scheme based on the Simulated Annealing method is investigated and a strategy is proposed to address convergence to local minimum.

Chemically Patterned Inverse Opal Created by a Selective Photolysis Modification Process.

PubMed

Tian, Tian; Gao, Ning; Gu, Chen; Li, Jian; Wang, Hui; Lan, Yue; Yin, Xianpeng; Li, Guangtao

2015-09-02

Anisotropic photonic crystal materials have long been pursued for their broad applications. A novel method for creating chemically patterned inverse opals is proposed here. The patterning technique is based on selective photolysis of a photolabile polymer together with postmodification on released amine groups. The patterning method allows regioselective modification within an inverse opal structure, taking advantage of selective chemical reaction. Moreover, combined with the unique signal self-reporting feature of the photonic crystal, the fabricated structure is capable of various applications, including gradient photonic bandgap and dynamic chemical patterns. The proposed method provides the ability to extend the structural and chemical complexity of the photonic crystal, as well as its potential applications.

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.

Shape-based ultrasound tomography using a Born model with application to high intensity focused ultrasound therapy.

PubMed

Ulker Karbeyaz, Başak; Miller, Eric L; Cleveland, Robin O

2008-05-01

A shaped-based ultrasound tomography method is proposed to reconstruct ellipsoidal objects using a linearized scattering model. The method is motivated by the desire to detect the presence of lesions created by high intensity focused ultrasound (HIFU) in applications of cancer therapy. The computational size and limited view nature of the relevant three-dimensional inverse problem renders impractical the use of traditional pixel-based reconstruction methods. However, by employing a shape-based parametrization it is only necessary to estimate a small number of unknowns describing the geometry of the lesion, in this paper assumed to be ellipsoidal. The details of the shape-based nonlinear inversion method are provided. Results obtained from a commercial ultrasound scanner and a tissue phantom containing a HIFU-like lesion demonstrate the feasibility of the approach where a 20 mm x 5 mm x 6 mm ellipsoidal inclusion was detected with an accuracy of around 5%.

3D near-to-surface conductivity reconstruction by inversion of VETEM data using the distorted Born iterative method

USGS Publications Warehouse

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

2004-01-01

Three-dimensional (3D) subsurface imaging by using inversion of data obtained from the very early time electromagnetic system (VETEM) was discussed. The study was carried out by using the distorted Born iterative method to match the internal nonlinear property of the 3D inversion problem. The forward solver was based on the total-current formulation bi-conjugate gradient-fast Fourier transform (BCCG-FFT). It was found that the selection of regularization parameter follow a heuristic rule as used in the Levenberg-Marquardt algorithm so that the iteration is stable.

Gravity inversion of a fault by Particle swarm optimization (PSO).

PubMed

Toushmalani, Reza

2013-01-01

Particle swarm optimization is a heuristic global optimization method and also an optimization algorithm, which is based on swarm intelligence. It comes from the research on the bird and fish flock movement behavior. In this paper we introduce and use this method in gravity inverse problem. We discuss the solution for the inverse problem of determining the shape of a fault whose gravity anomaly is known. Application of the proposed algorithm to this problem has proven its capability to deal with difficult optimization problems. The technique proved to work efficiently when tested to a number of models.

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.

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.

Unmanned Systems: A Lab Based Robotic Arm for Grasping Phase II

DTIC Science & Technology

2016-12-01

Leap Motion Controller, inverse kinematics, DH parameters. 15. NUMBER OF PAGES 89 16. PRICE CODE 17. SECURITY CLASSIFICATION OF REPORT...robotic actuator. Inverse kinematics and Denavit-Hartenberg (DH) parameters will be briefly explained. A. POSITION ANALYSIS According to [3] and... inverse kinematic” method and allows us to calculate the actuator’s position in order to move the robot’s end effector to a specific point in space

Solving geosteering inverse problems by stochastic Hybrid Monte Carlo method

DOE PAGES

Shen, Qiuyang; Wu, Xuqing; Chen, Jiefu; ...

2017-11-20

The inverse problems arise in almost all fields of science where the real-world parameters are extracted from a set of measured data. The geosteering inversion plays an essential role in the accurate prediction of oncoming strata as well as a reliable guidance to adjust the borehole position on the fly to reach one or more geological targets. This mathematical treatment is not easy to solve, which requires finding an optimum solution among a large solution space, especially when the problem is non-linear and non-convex. Nowadays, a new generation of logging-while-drilling (LWD) tools has emerged on the market. The so-called azimuthalmore » resistivity LWD tools have azimuthal sensitivity and a large depth of investigation. Hence, the associated inverse problems become much more difficult since the earth model to be inverted will have more detailed structures. The conventional deterministic methods are incapable to solve such a complicated inverse problem, where they suffer from the local minimum trap. Alternatively, stochastic optimizations are in general better at finding global optimal solutions and handling uncertainty quantification. In this article, we investigate the Hybrid Monte Carlo (HMC) based statistical inversion approach and suggest that HMC based inference is more efficient in dealing with the increased complexity and uncertainty faced by the geosteering problems.« less

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.

A Gauss-Newton full-waveform inversion in PML-truncated domains using scalar probing waves

NASA Astrophysics Data System (ADS)

Pakravan, Alireza; Kang, Jun Won; Newtson, Craig M.

2017-12-01

This study considers the characterization of subsurface shear wave velocity profiles in semi-infinite media using scalar waves. Using surficial responses caused by probing waves, a reconstruction of the material profile is sought using a Gauss-Newton full-waveform inversion method in a two-dimensional domain truncated by perfectly matched layer (PML) wave-absorbing boundaries. The PML is introduced to limit the semi-infinite extent of the half-space and to prevent reflections from the truncated boundaries. A hybrid unsplit-field PML is formulated in the inversion framework to enable more efficient wave simulations than with a fully mixed PML. The full-waveform inversion method is based on a constrained optimization framework that is implemented using Karush-Kuhn-Tucker (KKT) optimality conditions to minimize the objective functional augmented by PML-endowed wave equations via Lagrange multipliers. The KKT conditions consist of state, adjoint, and control problems, and are solved iteratively to update the shear wave velocity profile of the PML-truncated domain. Numerical examples show that the developed Gauss-Newton inversion method is accurate enough and more efficient than another inversion method. The algorithm's performance is demonstrated by the numerical examples including the case of noisy measurement responses and the case of reduced number of sources and receivers.

Identification procedure for epistemic uncertainties using inverse fuzzy arithmetic

NASA Astrophysics Data System (ADS)

Haag, T.; Herrmann, J.; Hanss, M.

2010-10-01

For the mathematical representation of systems with epistemic uncertainties, arising, for example, from simplifications in the modeling procedure, models with fuzzy-valued parameters prove to be a suitable and promising approach. In practice, however, the determination of these parameters turns out to be a non-trivial problem. The identification procedure to appropriately update these parameters on the basis of a reference output (measurement or output of an advanced model) requires the solution of an inverse problem. Against this background, an inverse method for the computation of the fuzzy-valued parameters of a model with epistemic uncertainties is presented. This method stands out due to the fact that it only uses feedforward simulations of the model, based on the transformation method of fuzzy arithmetic, along with the reference output. An inversion of the system equations is not necessary. The advancement of the method presented in this paper consists of the identification of multiple input parameters based on a single reference output or measurement. An optimization is used to solve the resulting underdetermined problems by minimizing the uncertainty of the identified parameters. Regions where the identification procedure is reliable are determined by the computation of a feasibility criterion which is also based on the output data of the transformation method only. For a frequency response function of a mechanical system, this criterion allows a restriction of the identification process to some special range of frequency where its solution can be guaranteed. Finally, the practicability of the method is demonstrated by covering the measured output of a fluid-filled piping system by the corresponding uncertain FE model in a conservative way.

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.

Spectroscopic ellipsometry data inversion using constrained splines and application to characterization of ZnO with various morphologies

NASA Astrophysics Data System (ADS)

Gilliot, Mickaël; Hadjadj, Aomar; Stchakovsky, Michel

2017-11-01

An original method of ellipsometric data inversion is proposed based on the use of constrained splines. The imaginary part of the dielectric function is represented by a series of splines, constructed with particular constraints on slopes at the node boundaries to avoid well-know oscillations of natural splines. The nodes are used as fit parameters. The real part is calculated using Kramers-Kronig relations. The inversion can be performed in successive inversion steps with increasing resolution. This method is used to characterize thin zinc oxide layers obtained by a sol-gel and spin-coating process, with a particular recipe yielding very thin layers presenting nano-porosity. Such layers have particular optical properties correlated with thickness, morphological and structural properties. The use of the constrained spline method is particularly efficient for such materials which may not be easily represented by standard dielectric function models.

Modulating light propagation in ZnO-Cu₂O-inverse opal solar cells for enhanced photocurrents.

PubMed

Yantara, Natalia; Pham, Thi Thu Trang; Boix, Pablo P; Mathews, Nripan

2015-09-07

The advantages of employing an interconnected periodic ZnO morphology, i.e. an inverse opal structure, in electrodeposited ZnO/Cu2O devices are presented. The solar cells are fabricated using low cost solution based methods such as spin coating and electrodeposition. The impact of inverse opal geometry, mainly the diameter and thickness, is scrutinized. By employing 3 layers of an inverse opal structure with a 300 nm pore diameter, higher short circuit photocurrents (∼84% improvement) are observed; however the open circuit voltages decrease with increasing interfacial area. Optical simulation using a finite difference time domain method shows that the inverse opal structure modulates light propagation within the devices such that more photons are absorbed close to the ZnO/Cu2O junction. This increases the collection probability resulting in improved short circuit currents.

Cross hole GPR traveltime inversion using a fast and accurate neural network as a forward model

NASA Astrophysics Data System (ADS)

Mejer Hansen, Thomas

2017-04-01

Probabilistic formulated inverse problems can be solved using Monte Carlo based sampling methods. In principle both advanced prior information, such as based on geostatistics, and complex non-linear forward physical models can be considered. However, in practice these methods can 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 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 travel time inversion of cross hole ground-penetrating radar (GPR) data. An accurate forward model, based on 2D full-waveform modeling followed by automatic travel time picking, is replaced by a fast neural network. This provides a sampling algorithm three orders of magnitude faster than using the full forward model, and considerably faster, and more accurate, than commonly used approximate forward models. The methodology has the potential to dramatically change the complexity of the types of inverse problems that can be solved using non-linear Monte Carlo sampling techniques.

Parallelized Bayesian inversion for three-dimensional dental X-ray imaging.

PubMed

Kolehmainen, Ville; Vanne, Antti; Siltanen, Samuli; Järvenpää, Seppo; Kaipio, Jari P; Lassas, Matti; Kalke, Martti

2006-02-01

Diagnostic and operational tasks based on dental radiology often require three-dimensional (3-D) information that is not available in a single X-ray projection image. Comprehensive 3-D information about tissues can be obtained by computerized tomography (CT) imaging. However, in dental imaging a conventional CT scan may not be available or practical because of high radiation dose, low-resolution or the cost of the CT scanner equipment. In this paper, we consider a novel type of 3-D imaging modality for dental radiology. We consider situations in which projection images of the teeth are taken from a few sparsely distributed projection directions using the dentist's regular (digital) X-ray equipment and the 3-D X-ray attenuation function is reconstructed. A complication in these experiments is that the reconstruction of the 3-D structure based on a few projection images becomes an ill-posed inverse problem. Bayesian inversion is a well suited framework for reconstruction from such incomplete data. In Bayesian inversion, the ill-posed reconstruction problem is formulated in a well-posed probabilistic form in which a priori information is used to compensate for the incomplete information of the projection data. In this paper we propose a Bayesian method for 3-D reconstruction in dental radiology. The method is partially based on Kolehmainen et al. 2003. The prior model for dental structures consist of a weighted l1 and total variation (TV)-prior together with the positivity prior. The inverse problem is stated as finding the maximum a posteriori (MAP) estimate. To make the 3-D reconstruction computationally feasible, a parallelized version of an optimization algorithm is implemented for a Beowulf cluster computer. The method is tested with projection data from dental specimens and patient data. Tomosynthetic reconstructions are given as reference for the proposed method.

Interpretation of Trace Gas Data Using Inverse Methods and Global Chemical Transport Models

NASA Technical Reports Server (NTRS)

Prinn, Ronald G.

1997-01-01

This is a theoretical research project aimed at: (1) development, testing, and refining of inverse methods for determining regional and global transient source and sink strengths for long lived gases important in ozone depletion and climate forcing, (2) utilization of inverse methods to determine these source/sink strengths which use the NCAR/Boulder CCM2-T42 3-D model and a global 3-D Model for Atmospheric Transport and Chemistry (MATCH) which is based on analyzed observed wind fields (developed in collaboration by MIT and NCAR/Boulder), (3) determination of global (and perhaps regional) average hydroxyl radical concentrations using inverse methods with multiple titrating gases, and, (4) computation of the lifetimes and spatially resolved destruction rates of trace gases using 3-D models. Important goals include determination of regional source strengths of methane, nitrous oxide, and other climatically and chemically important biogenic trace gases and also of halocarbons restricted by the Montreal Protocol and its follow-on agreements and hydrohalocarbons used as alternatives to the restricted halocarbons.

Black hole algorithm for determining model parameter in self-potential data

NASA Astrophysics Data System (ADS)

Sungkono; Warnana, Dwa Desa

2018-01-01

Analysis of self-potential (SP) data is increasingly popular in geophysical method due to its relevance in many cases. However, the inversion of SP data is often highly nonlinear. Consequently, local search algorithms commonly based on gradient approaches have often failed to find the global optimum solution in nonlinear problems. Black hole algorithm (BHA) was proposed as a solution to such problems. As the name suggests, the algorithm was constructed based on the black hole phenomena. This paper investigates the application of BHA to solve inversions of field and synthetic self-potential (SP) data. The inversion results show that BHA accurately determines model parameters and model uncertainty. This indicates that BHA is highly potential as an innovative approach for SP data inversion.

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.

A method for the quantification of biased signalling at constitutively active receptors.

PubMed

Hall, David A; Giraldo, Jesús

2018-06-01

Biased agonism, the ability of an agonist to differentially activate one of several signal transduction pathways when acting at a given receptor, is an increasingly recognized phenomenon at many receptors. The Black and Leff operational model lacks a way to describe constitutive receptor activity and hence inverse agonism. Thus, it is impossible to analyse the biased signalling of inverse agonists using this model. In this theoretical work, we develop and illustrate methods for the analysis of biased inverse agonism. Methods were derived for quantifying biased signalling in systems that demonstrate constitutive activity using the modified operational model proposed by Slack and Hall. The methods were illustrated using Monte Carlo simulations. The Monte Carlo simulations demonstrated that, with an appropriate experimental design, the model parameters are 'identifiable'. The method is consistent with methods based on the measurement of intrinsic relative activity (RA i ) (ΔΔlogR or ΔΔlog(τ/K a )) proposed by Ehlert and Kenakin and their co-workers but has some advantages. In particular, it allows the quantification of ligand bias independently of 'system bias' removing the requirement to normalize to a standard ligand. In systems with constitutive activity, the Slack and Hall model provides methods for quantifying the absolute bias of agonists and inverse agonists. This provides an alternative to methods based on RA i and is complementary to the ΔΔlog(τ/K a ) method of Kenakin et al. in systems where use of that method is inappropriate due to the presence of constitutive activity. © 2018 The British Pharmacological Society.

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

Qualitative and quantitative comparison of geostatistical techniques of porosity prediction from the seismic and logging data: a case study from the Blackfoot Field, Alberta, Canada

NASA Astrophysics Data System (ADS)

Maurya, S. P.; Singh, K. H.; Singh, N. P.

2018-05-01

In present study, three recently developed geostatistical methods, single attribute analysis, multi-attribute analysis and probabilistic neural network algorithm have been used to predict porosity in inter well region for Blackfoot field, Alberta, Canada, an offshore oil field. These techniques make use of seismic attributes, generated by model based inversion and colored inversion techniques. The principle objective of the study is to find the suitable combination of seismic inversion and geostatistical techniques to predict porosity and identification of prospective zones in 3D seismic volume. The porosity estimated from these geostatistical approaches is corroborated with the well log porosity. The results suggest that all the three implemented geostatistical methods are efficient and reliable to predict the porosity but the multi-attribute and probabilistic neural network analysis provide more accurate and high resolution porosity sections. A low impedance (6000-8000 m/s g/cc) and high porosity (> 15%) zone is interpreted from inverted impedance and porosity sections respectively between 1060 and 1075 ms time interval and is characterized as reservoir. The qualitative and quantitative results demonstrate that of all the employed geostatistical methods, the probabilistic neural network along with model based inversion is the most efficient method for predicting porosity in inter well region.

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.

Fourier analysis and signal processing by use of the Moebius inversion formula

NASA Technical Reports Server (NTRS)

Reed, Irving S.; Yu, Xiaoli; Shih, Ming-Tang; Tufts, Donald W.; Truong, T. K.

1990-01-01

A novel Fourier technique for digital signal processing is developed. This approach to Fourier analysis is based on the number-theoretic method of the Moebius inversion of series. The Fourier transform method developed is shown also to yield the convolution of two signals. A computer simulation shows that this method for finding Fourier coefficients is quite suitable for digital signal processing. It competes with the classical FFT (fast Fourier transform) approach in terms of accuracy, complexity, and speed.

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.

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.

ℓ1-Regularized full-waveform inversion with prior model information based on orthant-wise limited memory quasi-Newton method

NASA Astrophysics Data System (ADS)

Dai, Meng-Xue; Chen, Jing-Bo; Cao, Jian

2017-07-01

Full-waveform inversion (FWI) is an ill-posed optimization problem which is sensitive to noise and initial model. To alleviate the ill-posedness of the problem, regularization techniques are usually adopted. The ℓ1-norm penalty is a robust regularization method that preserves contrasts and edges. The Orthant-Wise Limited-Memory Quasi-Newton (OWL-QN) method extends the widely-used limited-memory Broyden-Fletcher-Goldfarb-Shanno (L-BFGS) method to the ℓ1-regularized optimization problems and inherits the efficiency of L-BFGS. To take advantage of the ℓ1-regularized method and the prior model information obtained from sonic logs and geological information, we implement OWL-QN algorithm in ℓ1-regularized FWI with prior model information in this paper. Numerical experiments show that this method not only improve the inversion results but also has a strong anti-noise ability.

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.

Query-based learning for aerospace applications.

PubMed

Saad, E W; Choi, J J; Vian, J L; Wunsch, D C Ii

2003-01-01

Models of real-world applications often include a large number of parameters with a wide dynamic range, which contributes to the difficulties of neural network training. Creating the training data set for such applications becomes costly, if not impossible. In order to overcome the challenge, one can employ an active learning technique known as query-based learning (QBL) to add performance-critical data to the training set during the learning phase, thereby efficiently improving the overall learning/generalization. The performance-critical data can be obtained using an inverse mapping called network inversion (discrete network inversion and continuous network inversion) followed by oracle query. This paper investigates the use of both inversion techniques for QBL learning, and introduces an original heuristic to select the inversion target values for continuous network inversion method. Efficiency and generalization was further enhanced by employing node decoupled extended Kalman filter (NDEKF) training and a causality index (CI) as a means to reduce the input search dimensionality. The benefits of the overall QBL approach are experimentally demonstrated in two aerospace applications: a classification problem with large input space and a control distribution problem.

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.

Recursive Factorization of the Inverse Overlap Matrix in Linear-Scaling Quantum Molecular Dynamics Simulations.

PubMed

Negre, Christian F A; Mniszewski, Susan M; Cawkwell, Marc J; Bock, Nicolas; Wall, Michael E; Niklasson, Anders M N

2016-07-12

We present a reduced complexity algorithm to compute the inverse overlap factors required to solve the generalized eigenvalue problem in a quantum-based molecular dynamics (MD) simulation. Our method is based on the recursive, iterative refinement of an initial guess of Z (inverse square root of the overlap matrix S). The initial guess of Z is obtained beforehand by using either an approximate divide-and-conquer technique or dynamical methods, propagated within an extended Lagrangian dynamics from previous MD time steps. With this formulation, we achieve long-term stability and energy conservation even under the incomplete, approximate, iterative refinement of Z. Linear-scaling performance is obtained using numerically thresholded sparse matrix algebra based on the ELLPACK-R sparse matrix data format, which also enables efficient shared-memory parallelization. As we show in this article using self-consistent density-functional-based tight-binding MD, our approach is faster than conventional methods based on the diagonalization of overlap matrix S for systems as small as a few hundred atoms, substantially accelerating quantum-based simulations even for molecular structures of intermediate size. For a 4158-atom water-solvated polyalanine system, we find an average speedup factor of 122 for the computation of Z in each MD step.

MCMC genome rearrangement.

PubMed

Miklós, István

2003-10-01

As more and more genomes have been sequenced, genomic data is rapidly accumulating. Genome-wide mutations are believed more neutral than local mutations such as substitutions, insertions and deletions, therefore phylogenetic investigations based on inversions, transpositions and inverted transpositions are less biased by the hypothesis on neutral evolution. Although efficient algorithms exist for obtaining the inversion distance of two signed permutations, there is no reliable algorithm when both inversions and transpositions are considered. Moreover, different type of mutations happen with different rates, and it is not clear how to weight them in a distance based approach. We introduce a Markov Chain Monte Carlo method to genome rearrangement based on a stochastic model of evolution, which can estimate the number of different evolutionary events needed to sort a signed permutation. The performance of the method was tested on simulated data, and the estimated numbers of different types of mutations were reliable. Human and Drosophila mitochondrial data were also analysed with the new method. The mixing time of the Markov Chain is short both in terms of CPU times and number of proposals. The source code in C is available on request from the author.

Constructing inverse probability weights for continuous exposures: a comparison of methods.

PubMed

Naimi, Ashley I; Moodie, Erica E M; Auger, Nathalie; Kaufman, Jay S

2014-03-01

Inverse probability-weighted marginal structural models with binary exposures are common in epidemiology. Constructing inverse probability weights for a continuous exposure can be complicated by the presence of outliers, and the need to identify a parametric form for the exposure and account for nonconstant exposure variance. We explored the performance of various methods to construct inverse probability weights for continuous exposures using Monte Carlo simulation. We generated two continuous exposures and binary outcomes using data sampled from a large empirical cohort. The first exposure followed a normal distribution with homoscedastic variance. The second exposure followed a contaminated Poisson distribution, with heteroscedastic variance equal to the conditional mean. We assessed six methods to construct inverse probability weights using: a normal distribution, a normal distribution with heteroscedastic variance, a truncated normal distribution with heteroscedastic variance, a gamma distribution, a t distribution (1, 3, and 5 degrees of freedom), and a quantile binning approach (based on 10, 15, and 20 exposure categories). We estimated the marginal odds ratio for a single-unit increase in each simulated exposure in a regression model weighted by the inverse probability weights constructed using each approach, and then computed the bias and mean squared error for each method. For the homoscedastic exposure, the standard normal, gamma, and quantile binning approaches performed best. For the heteroscedastic exposure, the quantile binning, gamma, and heteroscedastic normal approaches performed best. Our results suggest that the quantile binning approach is a simple and versatile way to construct inverse probability weights for continuous exposures.

Full waveform inversion using a decomposed single frequency component from a spectrogram

NASA Astrophysics Data System (ADS)

Ha, Jiho; Kim, Seongpil; Koo, Namhyung; Kim, Young-Ju; Woo, Nam-Sub; Han, Sang-Mok; Chung, Wookeen; Shin, Sungryul; Shin, Changsoo; Lee, Jaejoon

2018-06-01

Although many full waveform inversion methods have been developed to construct velocity models of subsurface, various approaches have been presented to obtain an inversion result with long-wavelength features even though seismic data lacking low-frequency components were used. In this study, a new full waveform inversion algorithm was proposed to recover a long-wavelength velocity model that reflects the inherent characteristics of each frequency component of seismic data using a single-frequency component decomposed from the spectrogram. We utilized the wavelet transform method to obtain the spectrogram, and the decomposed signal from the spectrogram was used as transformed data. The Gauss-Newton method with the diagonal elements of an approximate Hessian matrix was used to update the model parameters at each iteration. Based on the results of time-frequency analysis in the spectrogram, numerical tests with some decomposed frequency components were performed using a modified SEG/EAGE salt dome (A-A‧) line to demonstrate the feasibility of the proposed inversion algorithm. This demonstrated that a reasonable inverted velocity model with long-wavelength structures can be obtained using a single frequency component. It was also confirmed that when strong noise occurs in part of the frequency band, it is feasible to obtain a long-wavelength velocity model from the noise data with a frequency component that is less affected by the noise. Finally, it was confirmed that the results obtained from the spectrogram inversion can be used as an initial velocity model in conventional inversion methods.

3D magnetotelluric inversion system with static shift correction and theoretical assessment in oil and gas exploration

NASA Astrophysics Data System (ADS)

Dong, H.; Kun, Z.; Zhang, L.

2015-12-01

This magnetotelluric (MT) system contains static shift correction and 3D inversion. The correction method is based on the data study on 3D forward modeling and field test. The static shift can be detected by the quantitative analysis of apparent parameters (apparent resistivity and impedance phase) of MT in high frequency range, and completed correction with inversion. The method is an automatic processing technology of computer with zero-cost, and avoids the additional field work and indoor processing with good results shown in Figure 1a-e. Figure 1a shows a normal model (I) without any local heterogeneity. Figure 1b shows a static-shifted model (II) with two local heterogeneous bodies (10 and 1000 ohm.m). Figure 1c is the inversion result (A) for the synthetic data generated from model I. Figure 1d is the inversion result (B) for the static-shifted data generated from model II. Figure 1e is the inversion result (C) for the static-shifted data from model II, but with static shift correction. The results show that the correction method is useful. The 3D inversion algorithm is improved base on the NLCG method of Newman & Alumbaugh (2000) and Rodi & Mackie (2001). For the algorithm, we added the frequency based parallel structure, improved the computational efficiency, reduced the memory of computer, added the topographic and marine factors, and added the constraints of geology and geophysics. So the 3D inversion could even work in PAD with high efficiency and accuracy. The application example of theoretical assessment in oil and gas exploration is shown in Figure 1f-i. The synthetic geophysical model consists of five layers (from top to downwards): shale, limestone, gas, oil, groundwater and limestone overlying a basement rock. Figure 1f-g show the 3D model and central profile. Figure 1h shows the centrel section of 3D inversion, the resultsd show a high degree of reduction in difference on the synthetic model. Figure 1i shows the seismic waveform reflects the interfaces of every layer overall, but the relative positions of the interface of the two-way travel time vary, and the interface between limestone and oil at the sides of the section is not reflected. So 3-D MT can make up for the deficiency of the seismic results such as the fake sync-phase axis and multiple waves.

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.

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.

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.

Fast Geostatistical Inversion using Randomized Matrix Decompositions and Sketchings for Heterogeneous Aquifer Characterization

NASA Astrophysics Data System (ADS)

O'Malley, D.; Le, E. B.; Vesselinov, V. V.

2015-12-01

We present a fast, scalable, and highly-implementable stochastic inverse method for characterization of aquifer heterogeneity. The method utilizes recent advances in randomized matrix algebra and exploits the structure of the Quasi-Linear Geostatistical Approach (QLGA), without requiring a structured grid like Fast-Fourier Transform (FFT) methods. The QLGA framework is a more stable version of Gauss-Newton iterates for a large number of unknown model parameters, but provides unbiased estimates. The methods are matrix-free and do not require derivatives or adjoints, and are thus ideal for complex models and black-box implementation. We also incorporate randomized least-square solvers and data-reduction methods, which speed up computation and simulate missing data points. The new inverse methodology 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. Inversion results based on series of synthetic problems with steady-state and transient calibration data are presented.

Infrasound Waveform Inversion and Mass Flux Validation from Sakurajima Volcano, Japan

NASA Astrophysics Data System (ADS)

Fee, D.; Kim, K.; Yokoo, A.; Izbekov, P. E.; Lopez, T. M.; Prata, F.; Ahonen, P.; Kazahaya, R.; Nakamichi, H.; Iguchi, M.

2015-12-01

Recent advances in numerical wave propagation modeling and station coverage have permitted robust inversion of infrasound data from volcanic explosions. Complex topography and crater morphology have been shown to substantially affect the infrasound waveform, suggesting that homogeneous acoustic propagation assumptions are invalid. Infrasound waveform inversion provides an exciting tool to accurately characterize emission volume and mass flux from both volcanic and non-volcanic explosions. Mass flux, arguably the most sought-after parameter from a volcanic eruption, can be determined from the volume flux using infrasound waveform inversion if the volcanic flow is well-characterized. Thus far, infrasound-based volume and mass flux estimates have yet to be validated. In February 2015 we deployed six infrasound stations around the explosive Sakurajima Volcano, Japan for 8 days. Here we present our full waveform inversion method and volume and mass flux estimates of numerous high amplitude explosions using a high resolution DEM and 3-D Finite Difference Time Domain modeling. Application of this technique to volcanic eruptions may produce realistic estimates of mass flux and plume height necessary for volcanic hazard mitigation. Several ground-based instruments and methods are used to independently determine the volume, composition, and mass flux of individual volcanic explosions. Specifically, we use ground-based ash sampling, multispectral infrared imagery, UV spectrometry, and multigas data to estimate the plume composition and flux. Unique tiltmeter data from underground tunnels at Sakurajima also provides a way to estimate the volume and mass of each explosion. In this presentation we compare the volume and mass flux estimates derived from the different methods and discuss sources of error and future improvements.

Technical Note: Approximate Bayesian parameterization of a complex tropical forest model

NASA Astrophysics Data System (ADS)

Hartig, F.; Dislich, C.; Wiegand, T.; Huth, A.

2013-08-01

Inverse parameter estimation of process-based models is a long-standing problem in ecology and evolution. A key problem of inverse parameter estimation is to define a metric that quantifies how well model predictions fit to the data. Such a metric can be expressed by general cost or objective functions, but statistical inversion approaches are based on a particular metric, the probability of observing the data given the model, known as the likelihood. Deriving likelihoods for dynamic models requires making assumptions about the probability for observations to deviate from mean model predictions. For technical reasons, these assumptions are usually derived without explicit consideration of the processes in the simulation. Only in recent years have new methods become available that allow generating likelihoods directly from stochastic simulations. Previous applications of these approximate Bayesian methods have concentrated on relatively simple models. Here, we report on the application of a simulation-based likelihood approximation for FORMIND, a parameter-rich individual-based model of tropical forest dynamics. We show that approximate Bayesian inference, based on a parametric likelihood approximation placed in a conventional MCMC, performs well in retrieving known parameter values from virtual field data generated by the forest model. We analyze the results of the parameter estimation, examine the sensitivity towards the choice and aggregation of model outputs and observed data (summary statistics), and show results from using this method to fit the FORMIND model to field data from an Ecuadorian tropical forest. Finally, we discuss differences of this approach to Approximate Bayesian Computing (ABC), another commonly used method to generate simulation-based likelihood approximations. Our results demonstrate that simulation-based inference, which offers considerable conceptual advantages over more traditional methods for inverse parameter estimation, can successfully be applied to process-based models of high complexity. The methodology is particularly suited to heterogeneous and complex data structures and can easily be adjusted to other model types, including most stochastic population and individual-based models. Our study therefore provides a blueprint for a fairly general approach to parameter estimation of stochastic process-based models in ecology and evolution.

An Inverse Modeling Plugin for HydroDesktop using the Method of Anchored Distributions (MAD)

NASA Astrophysics Data System (ADS)

Ames, D. P.; Osorio, C.; Over, M. W.; Rubin, Y.

2011-12-01

The CUAHSI Hydrologic Information System (HIS) software stack is based on an open and extensible architecture that facilitates the addition of new functions and capabilities at both the server side (using HydroServer) and the client side (using HydroDesktop). The HydroDesktop client plugin architecture is used here to expose a new scripting based plugin that makes use of the R statistics software as a means for conducting inverse modeling using the Method of Anchored Distributions (MAD). MAD is a Bayesian inversion technique for conditioning computational model parameters on relevant field observations yielding probabilistic distributions of the model parameters, related to the spatial random variable of interest, by assimilating multi-type and multi-scale data. The implementation of a desktop software tool for using the MAD technique is expected to significantly lower the barrier to use of inverse modeling in education, research, and resource management. The HydroDesktop MAD plugin is being developed following a community-based, open-source approach that will help both its adoption and long term sustainability as a user tool. This presentation will briefly introduce MAD, HydroDesktop, and the MAD plugin and software development effort.

An ionospheric occultation inversion technique based on epoch difference

NASA Astrophysics Data System (ADS)

Lin, Jian; Xiong, Jing; Zhu, Fuying; Yang, Jian; Qiao, Xuejun

2013-09-01

Of the ionospheric radio occultation (IRO) electron density profile (EDP) retrievals, the Abel based calibrated TEC inversion (CTI) is the most widely used technique. In order to eliminate the contribution from the altitude above the RO satellite, it is necessary to utilize the calibrated TEC to retrieve the EDP, which introduces the error due to the coplanar assumption. In this paper, a new technique based on the epoch difference inversion (EDI) is firstly proposed to eliminate this error. The comparisons between CTI and EDI have been done, taking advantage of the simulated and real COSMIC data. The following conclusions can be drawn: the EDI technique can successfully retrieve the EDPs without non-occultation side measurements and shows better performance than the CTI method, especially for lower orbit mission; no matter which technique is used, the inversion results at the higher altitudes are better than those at the lower altitudes, which could be explained theoretically.

Solving of the coefficient inverse problems for a nonlinear singularly perturbed reaction-diffusion-advection equation with the final time data

NASA Astrophysics Data System (ADS)

Lukyanenko, D. V.; Shishlenin, M. A.; Volkov, V. T.

2018-01-01

We propose the numerical method for solving coefficient inverse problem for a nonlinear singularly perturbed reaction-diffusion-advection equation with the final time observation data based on the asymptotic analysis and the gradient method. Asymptotic analysis allows us to extract a priory information about interior layer (moving front), which appears in the direct problem, and boundary layers, which appear in the conjugate problem. We describe and implement the method of constructing a dynamically adapted mesh based on this a priory information. The dynamically adapted mesh significantly reduces the complexity of the numerical calculations and improve the numerical stability in comparison with the usual approaches. Numerical example shows the effectiveness of the proposed method.

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.

Resolution enhancement of robust Bayesian pre-stack inversion in the frequency domain

NASA Astrophysics Data System (ADS)

Yin, Xingyao; Li, Kun; Zong, Zhaoyun

2016-10-01

AVO/AVA (amplitude variation with an offset or angle) inversion is one of the most practical and useful approaches to estimating model parameters. So far, publications on AVO inversion in the Fourier domain have been quite limited in view of its poor stability and sensitivity to noise compared with time-domain inversion. For the resolution and stability of AVO inversion in the Fourier domain, a novel robust Bayesian pre-stack AVO inversion based on the mixed domain formulation of stationary convolution is proposed which could solve the instability and achieve superior resolution. The Fourier operator will be integrated into the objective equation and it avoids the Fourier inverse transform in our inversion process. Furthermore, the background constraints of model parameters are taken into consideration to improve the stability and reliability of inversion which could compensate for the low-frequency components of seismic signals. Besides, the different frequency components of seismic signals can realize decoupling automatically. This will help us to solve the inverse problem by means of multi-component successive iterations and the convergence precision of the inverse problem could be improved. So, superior resolution compared with the conventional time-domain pre-stack inversion could be achieved easily. Synthetic tests illustrate that the proposed method could achieve high-resolution results with a high degree of agreement with the theoretical model and verify the quality of anti-noise. Finally, applications on a field data case demonstrate that the proposed method could obtain stable inversion results of elastic parameters from pre-stack seismic data in conformity with the real logging data.

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.

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.

Joint inversion for transponder localization and sound-speed profile temporal variation in high-precision acoustic surveys.

PubMed

Li, Zhao; Dosso, Stan E; Sun, Dajun

2016-07-01

This letter develops a Bayesian inversion for localizing underwater acoustic transponders using a surface ship which compensates for sound-speed profile (SSP) temporal variation during the survey. The method is based on dividing observed acoustic travel-time data into time segments and including depth-independent SSP variations for each segment as additional unknown parameters to approximate the SSP temporal variation. SSP variations are estimated jointly with transponder locations, rather than calculated separately as in existing two-step inversions. Simulation and sea-trial results show this localization/SSP joint inversion performs better than two-step inversion in terms of localization accuracy, agreement with measured SSP variations, and computational efficiency.

Simultaneous estimation of aquifer thickness, conductivity, and BC using borehole and hydrodynamic data with geostatistical inverse direct method

NASA Astrophysics Data System (ADS)

Gao, F.; Zhang, Y.

2017-12-01

A new inverse method is developed to simultaneously estimate aquifer thickness and boundary conditions using borehole and hydrodynamic measurements from a homogeneous confined aquifer under steady-state ambient flow. This method extends a previous groundwater inversion technique which had assumed known aquifer geometry and thickness. In this research, thickness inversion was successfully demonstrated when hydrodynamic data were supplemented with measured thicknesses from boreholes. Based on a set of hybrid formulations which describe approximate solutions to the groundwater flow equation, the new inversion technique can incorporate noisy observed data (i.e., thicknesses, hydraulic heads, Darcy fluxes or flow rates) at measurement locations as a set of conditioning constraints. Given sufficient quantity and quality of the measurements, the inverse method yields a single well-posed system of equations that can be solved efficiently with nonlinear optimization. The method is successfully tested on two-dimensional synthetic aquifer problems with regular geometries. The solution is stable when measurement errors are increased, with error magnitude reaching up to +/- 10% of the range of the respective measurement. When error-free observed data are used to condition the inversion, the estimated thickness is within a +/- 5% error envelope surrounding the true value; when data contain increasing errors, the estimated thickness become less accurate, as expected. Different combinations of measurement types are then investigated to evaluate data worth. Thickness can be inverted with the combination of observed heads and at least one of the other types of observations such as thickness, Darcy fluxes, or flow rates. Data requirement of the new inversion method is thus not much different from that of interpreting classic well tests. Future work will improve upon this research by developing an estimation strategy for heterogeneous aquifers while drawdown data from hydraulic tests will also be incorporated as conditioning measurements.

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.

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

Geometric shapes inversion method of space targets by ISAR image segmentation

NASA Astrophysics Data System (ADS)

Huo, Chao-ying; Xing, Xiao-yu; Yin, Hong-cheng; Li, Chen-guang; Zeng, Xiang-yun; Xu, Gao-gui

2017-11-01

The geometric shape of target is an effective characteristic in the process of space targets recognition. This paper proposed a method of shape inversion of space target based on components segmentation from ISAR image. The Radon transformation, Hough transformation, K-means clustering, triangulation will be introduced into ISAR image processing. Firstly, we use Radon transformation and edge detection to extract space target's main body spindle and solar panel spindle from ISAR image. Then the targets' main body, solar panel, rectangular and circular antenna are segmented from ISAR image based on image detection theory. Finally, the sizes of every structural component are computed. The effectiveness of this method is verified using typical targets' simulation data.

Intelligent inversion method for pre-stack seismic big data based on MapReduce

NASA Astrophysics Data System (ADS)

Yan, Xuesong; Zhu, Zhixin; Wu, Qinghua

2018-01-01

Seismic exploration is a method of oil exploration that uses seismic information; that is, according to the inversion of seismic information, the useful information of the reservoir parameters can be obtained to carry out exploration effectively. Pre-stack data are characterised by a large amount of data, abundant information, and so on, and according to its inversion, the abundant information of the reservoir parameters can be obtained. Owing to the large amount of pre-stack seismic data, existing single-machine environments have not been able to meet the computational needs of the huge amount of data; thus, the development of a method with a high efficiency and the speed to solve the inversion problem of pre-stack seismic data is urgently needed. The optimisation of the elastic parameters by using a genetic algorithm easily falls into a local optimum, which results in a non-obvious inversion effect, especially for the optimisation effect of the density. Therefore, an intelligent optimisation algorithm is proposed in this paper and used for the elastic parameter inversion of pre-stack seismic data. This algorithm improves the population initialisation strategy by using the Gardner formula and the genetic operation of the algorithm, and the improved algorithm obtains better inversion results when carrying out a model test with logging data. All of the elastic parameters obtained by inversion and the logging curve of theoretical model are fitted well, which effectively improves the inversion precision of the density. This algorithm was implemented with a MapReduce model to solve the seismic big data inversion problem. The experimental results show that the parallel model can effectively reduce the running time of the algorithm.

Fast, Nonlinear, Fully Probabilistic Inversion of Large Geophysical Problems

NASA Astrophysics Data System (ADS)

Curtis, A.; Shahraeeni, M.; Trampert, J.; Meier, U.; Cho, G.

2010-12-01

Almost all Geophysical inverse problems are in reality nonlinear. Fully nonlinear inversion including non-approximated physics, and solving for probability distribution functions (pdf’s) that describe the solution uncertainty, generally requires sampling-based Monte-Carlo style methods that are computationally intractable in most large problems. In order to solve such problems, physical relationships are usually linearized leading to efficiently-solved, (possibly iterated) linear inverse problems. However, it is well known that linearization can lead to erroneous solutions, and in particular to overly optimistic uncertainty estimates. What is needed across many Geophysical disciplines is a method to invert large inverse problems (or potentially tens of thousands of small inverse problems) fully probabilistically and without linearization. This talk shows how very large nonlinear inverse problems can be solved fully probabilistically and incorporating any available prior information using mixture density networks (driven by neural network banks), provided the problem can be decomposed into many small inverse problems. In this talk I will explain the methodology, compare multi-dimensional pdf inversion results to full Monte Carlo solutions, and illustrate the method with two applications: first, inverting surface wave group and phase velocities for a fully-probabilistic global tomography model of the Earth’s crust and mantle, and second inverting industrial 3D seismic data for petrophysical properties throughout and around a subsurface hydrocarbon reservoir. The latter problem is typically decomposed into 104 to 105 individual inverse problems, each solved fully probabilistically and without linearization. The results in both cases are sufficiently close to the Monte Carlo solution to exhibit realistic uncertainty, multimodality and bias. This provides far greater confidence in the results, and in decisions made on their basis.

A MATLAB implementation of the minimum relative entropy method for linear inverse problems

NASA Astrophysics Data System (ADS)

Neupauer, Roseanna M.; Borchers, Brian

2001-08-01

The minimum relative entropy (MRE) method can be used to solve linear inverse problems of the form Gm= d, where m is a vector of unknown model parameters and d is a vector of measured data. The MRE method treats the elements of m as random variables, and obtains a multivariate probability density function for m. The probability density function is constrained by prior information about the upper and lower bounds of m, a prior expected value of m, and the measured data. The solution of the inverse problem is the expected value of m, based on the derived probability density function. We present a MATLAB implementation of the MRE method. Several numerical issues arise in the implementation of the MRE method and are discussed here. We present the source history reconstruction problem from groundwater hydrology as an example of the MRE implementation.

Towards adjoint-based inversion of time-dependent mantle convection with nonlinear viscosity

NASA Astrophysics Data System (ADS)

Li, Dunzhu; Gurnis, Michael; Stadler, Georg

2017-04-01

We develop and study an adjoint-based inversion method for the simultaneous recovery of initial temperature conditions and viscosity parameters in time-dependent mantle convection from the current mantle temperature and historic plate motion. Based on a realistic rheological model with temperature-dependent and strain-rate-dependent viscosity, we formulate the inversion as a PDE-constrained optimization problem. The objective functional includes the misfit of surface velocity (plate motion) history, the misfit of the current mantle temperature, and a regularization for the uncertain initial condition. The gradient of this functional with respect to the initial temperature and the uncertain viscosity parameters is computed by solving the adjoint of the mantle convection equations. This gradient is used in a pre-conditioned quasi-Newton minimization algorithm. We study the prospects and limitations of the inversion, as well as the computational performance of the method using two synthetic problems, a sinking cylinder and a realistic subduction model. The subduction model is characterized by the migration of a ridge toward a trench whereby both plate motions and subduction evolve. The results demonstrate: (1) for known viscosity parameters, the initial temperature can be well recovered, as in previous initial condition-only inversions where the effective viscosity was given; (2) for known initial temperature, viscosity parameters can be recovered accurately, despite the existence of trade-offs due to ill-conditioning; (3) for the joint inversion of initial condition and viscosity parameters, initial condition and effective viscosity can be reasonably recovered, but the high dimension of the parameter space and the resulting ill-posedness may limit recovery of viscosity parameters.

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.

Ice Cores Dating With a New Inverse Method Taking Account of the Flow Modeling Errors

NASA Astrophysics Data System (ADS)

Lemieux-Dudon, B.; Parrenin, F.; Blayo, E.

2007-12-01

Deep ice cores extracted from Antarctica or Greenland recorded a wide range of past climatic events. In order to contribute to the Quaternary climate system understanding, the calculation of an accurate depth-age relationship is a crucial point. Up to now ice chronologies for deep ice cores estimated with inverse approaches are based on quite simplified ice-flow models that fail to reproduce flow irregularities and consequently to respect all available set of age markers. We describe in this paper, a new inverse method that takes into account the model uncertainty in order to circumvent the restrictions linked to the use of simplified flow models. This method uses first guesses on two flow physical entities, the ice thinning function and the accumulation rate and then identifies correction functions on both flow entities. We highlight two major benefits brought by this new method: first of all the ability to respect large set of observations and as a consequence, the feasibility to estimate a synchronized common ice chronology for several cores at the same time. This inverse approach relies on a bayesian framework. To respect the positive constraint on the searched correction functions, we assume lognormal probability distribution on one hand for the background errors, but also for one particular set of the observation errors. We test this new inversion method on three cores simultaneously (the two EPICA cores : DC and DML and the Vostok core) and we assimilate more than 150 observations (e.g.: age markers, stratigraphic links,...). We analyze the sensitivity of the solution with respect to the background information, especially the prior error covariance matrix. The confidence intervals based on the posterior covariance matrix calculation, are estimated on the correction functions and for the first time on the overall output chronologies.

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.

Remote sensing of suspended sediment water research: principles, methods, and progress

NASA Astrophysics Data System (ADS)

Shen, Ping; Zhang, Jing

2011-12-01

In this paper, we reviewed the principle, data, methods and steps in suspended sediment research by using remote sensing, summed up some representative models and methods, and analyzes the deficiencies of existing methods. Combined with the recent progress of remote sensing theory and application in water suspended sediment research, we introduced in some data processing methods such as atmospheric correction method, adjacent effect correction, and some intelligence algorithms such as neural networks, genetic algorithms, support vector machines into the suspended sediment inversion research, combined with other geographic information, based on Bayesian theory, we improved the suspended sediment inversion precision, and aim to give references to the related researchers.

Enhanced image fusion using directional contrast rules in fuzzy transform domain.

PubMed

Nandal, Amita; Rosales, Hamurabi Gamboa

2016-01-01

In this paper a novel image fusion algorithm based on directional contrast in fuzzy transform (FTR) domain is proposed. Input images to be fused are first divided into several non-overlapping blocks. The components of these sub-blocks are fused using directional contrast based fuzzy fusion rule in FTR domain. The fused sub-blocks are then transformed into original size blocks using inverse-FTR. Further, these inverse transformed blocks are fused according to select maximum based fusion rule for reconstructing the final fused image. The proposed fusion algorithm is both visually and quantitatively compared with other standard and recent fusion algorithms. Experimental results demonstrate that the proposed method generates better results than the other methods.

Retrieving rupture history using waveform inversions in time sequence

NASA Astrophysics Data System (ADS)

Yi, L.; Xu, C.; Zhang, X.

2017-12-01

The rupture history of large earthquakes is generally regenerated using the waveform inversion through utilizing seismological waveform records. In the waveform inversion, based on the superposition principle, the rupture process is linearly parameterized. After discretizing the fault plane into sub-faults, the local source time function of each sub-fault is usually parameterized using the multi-time window method, e.g., mutual overlapped triangular functions. Then the forward waveform of each sub-fault is synthesized through convoluting the source time function with its Green function. According to the superposition principle, these forward waveforms generated from the fault plane are summarized in the recorded waveforms after aligning the arrival times. Then the slip history is retrieved using the waveform inversion method after the superposing of all forward waveforms for each correspond seismological waveform records. Apart from the isolation of these forward waveforms generated from each sub-fault, we also realize that these waveforms are gradually and sequentially superimposed in the recorded waveforms. Thus we proposed a idea that the rupture model is possibly detachable in sequent rupture times. According to the constrained waveform length method emphasized in our previous work, the length of inverted waveforms used in the waveform inversion is objectively constrained by the rupture velocity and rise time. And one essential prior condition is the predetermined fault plane that limits the duration of rupture time, which means the waveform inversion is restricted in a pre-set rupture duration time. Therefore, we proposed a strategy to inverse the rupture process sequentially using the progressively shift rupture times as the rupture front expanding in the fault plane. And we have designed a simulation inversion to test the feasibility of the method. Our test result shows the prospect of this idea that requiring furthermore investigation.

A comparative study of surface waves inversion techniques at strong motion recording sites in Greece

USGS Publications Warehouse

Panagiotis C. Pelekis,; Savvaidis, Alexandros; Kayen, Robert E.; Vlachakis, Vasileios S.; Athanasopoulos, George A.

2015-01-01

Surface wave method was used for the estimation of Vs vs depth profile at 10 strong motion stations in Greece. The dispersion data were obtained by SASW method, utilizing a pair of electromechanical harmonic-wave source (shakers) or a random source (drop weight). In this study, three inversion techniques were used a) a recently proposed Simplified Inversion Method (SIM), b) an inversion technique based on a neighborhood algorithm (NA) which allows the incorporation of a priori information regarding the subsurface structure parameters, and c) Occam's inversion algorithm. For each site constant value of Poisson's ratio was assumed (ν=0.4) since the objective of the current study is the comparison of the three inversion schemes regardless the uncertainties resulting due to the lack of geotechnical data. A penalty function was introduced to quantify the deviations of the derived Vs profiles. The Vs models are compared as of Vs(z), Vs30 and EC8 soil category, in order to show the insignificance of the existing variations. The comparison results showed that the average variation of SIM profiles is 9% and 4.9% comparing with NA and Occam's profiles respectively whilst the average difference of Vs30 values obtained from SIM is 7.4% and 5.0% compared with NA and Occam's.

Abel inversion using fast Fourier transforms.

PubMed

Kalal, M; Nugent, K A

1988-05-15

A fast Fourier transform based Abel inversion technique is proposed. The method is faster than previously used techniques, potentially very accurate (even for a relatively small number of points), and capable of handling large data sets. The technique is discussed in the context of its use with 2-D digital interferogram analysis algorithms. Several examples are given.

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.

Model-based elastography: a survey of approaches to the inverse elasticity problem

PubMed Central

Doyley, M M

2012-01-01

Elastography is emerging as an imaging modality that can distinguish normal versus diseased tissues via their biomechanical properties. This article reviews current approaches to elastography in three areas — quasi-static, harmonic, and transient — and describes inversion schemes for each elastographic imaging approach. Approaches include: first-order approximation methods; direct and iterative inversion schemes for linear elastic; isotropic materials; and advanced reconstruction methods for recovering parameters that characterize complex mechanical behavior. The paper’s objective is to document efforts to develop elastography within the framework of solving an inverse problem, so that elastography may provide reliable estimates of shear modulus and other mechanical parameters. We discuss issues that must be addressed if model-based elastography is to become the prevailing approach to quasi-static, harmonic, and transient elastography: (1) developing practical techniques to transform the ill-posed problem with a well-posed one; (2) devising better forward models to capture the transient behavior of soft tissue; and (3) developing better test procedures to evaluate the performance of modulus elastograms. PMID:22222839

System parameter identification from projection of inverse analysis

NASA Astrophysics Data System (ADS)

Liu, K.; Law, S. S.; Zhu, X. Q.

2017-05-01

The output of a system due to a change of its parameters is often approximated with the sensitivity matrix from the first order Taylor series. The system output can be measured in practice, but the perturbation in the system parameters is usually not available. Inverse sensitivity analysis can be adopted to estimate the unknown system parameter perturbation from the difference between the observation output data and corresponding analytical output data calculated from the original system model. The inverse sensitivity analysis is re-visited in this paper with improvements based on the Principal Component Analysis on the analytical data calculated from the known system model. The identification equation is projected into a subspace of principal components of the system output, and the sensitivity of the inverse analysis is improved with an iterative model updating procedure. The proposed method is numerical validated with a planar truss structure and dynamic experiments with a seven-storey planar steel frame. Results show that it is robust to measurement noise, and the location and extent of stiffness perturbation can be identified with better accuracy compared with the conventional response sensitivity-based method.

Analysis of Tube Hydroforming by means of an Inverse Approach

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

Nguyen, Ba Nghiep; Johnson, Kenneth I.; Khaleel, Mohammad A.

2003-05-01

This paper presents a computational tool for the analysis of freely hydroformed tubes by means of an inverse approach. The formulation of the inverse method developed by Guo et al. is adopted and extended to the tube hydrofoming problems in which the initial geometry is a round tube submitted to hydraulic pressure and axial feed at the tube ends (end-feed). A simple criterion based on a forming limit diagram is used to predict the necking regions in the deformed workpiece. Although the developed computational tool is a stand-alone code, it has been linked to the Marc finite element code formore » meshing and visualization of results. The application of the inverse approach to tube hydroforming is illustrated through the analyses of the aluminum alloy AA6061-T4 seamless tubes under free hydroforming conditions. The results obtained are in good agreement with those issued from a direct incremental approach. However, the computational time in the inverse procedure is much less than that in the incremental method.« less

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.

A complete analytical solution for the inverse instantaneous kinematics of a spherical-revolute-spherical (7R) redundant manipulator

NASA Technical Reports Server (NTRS)

Podhorodeski, R. P.; Fenton, R. G.; Goldenberg, A. A.

1989-01-01

Using a method based upon resolving joint velocities using reciprocal screw quantities, compact analytical expressions are generated for the inverse solution of the joint rates of a seven revolute (spherical-revolute-spherical) manipulator. The method uses a sequential decomposition of screw coordinates to identify reciprocal screw quantities used in the resolution of a particular joint rate solution, and also to identify a Jacobian null-space basis used for the direct solution of optimal joint rates. The results of the screw decomposition are used to study special configurations of the manipulator, generating expressions for the inverse velocity solution for all non-singular configurations of the manipulator, and identifying singular configurations and their characteristics. Two functions are therefore served: a new general method for the solution of the inverse velocity problem is presented; and complete analytical expressions are derived for the resolution of the joint rates of a seven degree of freedom manipulator useful for telerobotic and industrial robotic application.

HT2DINV: A 2D forward and inverse code for steady-state and transient hydraulic tomography problems

NASA Astrophysics Data System (ADS)

Soueid Ahmed, A.; Jardani, A.; Revil, A.; Dupont, J. P.

2015-12-01

Hydraulic tomography is a technique used to characterize the spatial heterogeneities of storativity and transmissivity fields. The responses of an aquifer to a source of hydraulic stimulations are used to recover the features of the estimated fields using inverse techniques. We developed a 2D free source Matlab package for performing hydraulic tomography analysis in steady state and transient regimes. The package uses the finite elements method to solve the ground water flow equation for simple or complex geometries accounting for the anisotropy of the material properties. The inverse problem is based on implementing the geostatistical quasi-linear approach of Kitanidis combined with the adjoint-state method to compute the required sensitivity matrices. For undetermined inverse problems, the adjoint-state method provides a faster and more accurate approach for the evaluation of sensitivity matrices compared with the finite differences method. Our methodology is organized in a way that permits the end-user to activate parallel computing in order to reduce the computational burden. Three case studies are investigated demonstrating the robustness and efficiency of our approach for inverting hydraulic parameters.

Study on Material Parameters Identification of Brain Tissue Considering Uncertainty of Friction Coefficient

NASA Astrophysics Data System (ADS)

Guan, Fengjiao; Zhang, Guanjun; Liu, Jie; Wang, Shujing; Luo, Xu; Zhu, Feng

2017-10-01

Accurate material parameters are critical to construct the high biofidelity finite element (FE) models. However, it is hard to obtain the brain tissue parameters accurately because of the effects of irregular geometry and uncertain boundary conditions. Considering the complexity of material test and the uncertainty of friction coefficient, a computational inverse method for viscoelastic material parameters identification of brain tissue is presented based on the interval analysis method. Firstly, the intervals are used to quantify the friction coefficient in the boundary condition. And then the inverse problem of material parameters identification under uncertain friction coefficient is transformed into two types of deterministic inverse problem. Finally the intelligent optimization algorithm is used to solve the two types of deterministic inverse problems quickly and accurately, and the range of material parameters can be easily acquired with no need of a variety of samples. The efficiency and convergence of this method are demonstrated by the material parameters identification of thalamus. The proposed method provides a potential effective tool for building high biofidelity human finite element model in the study of traffic accident injury.

Studies of Trace Gas Chemical Cycles Using Inverse Methods and Global Chemical Transport Models

NASA Technical Reports Server (NTRS)

Prinn, Ronald G.

2003-01-01

We report progress in the first year, and summarize proposed work for the second year of the three-year dynamical-chemical modeling project devoted to: (a) development, testing, and refining of inverse methods for determining regional and global transient source and sink strengths for long lived gases important in ozone depletion and climate forcing, (b) utilization of inverse methods to determine these source/sink strengths using either MATCH (Model for Atmospheric Transport and Chemistry) which is based on analyzed observed wind fields or back-trajectories computed from these wind fields, (c) determination of global (and perhaps regional) average hydroxyl radical concentrations using inverse methods with multiple titrating gases, and (d) computation of the lifetimes and spatially resolved destruction rates of trace gases using 3D models. Important goals include determination of regional source strengths of methane, nitrous oxide, methyl bromide, and other climatically and chemically important biogenic/anthropogenic trace gases and also of halocarbons restricted by the Montreal protocol and its follow-on agreements and hydrohalocarbons now used as alternatives to the restricted halocarbons.

A hydraulic tomography approach coupling travel time inversion with steady shape analysis based on aquifer analogue study in coarsely clastic fluvial glacial deposit

NASA Astrophysics Data System (ADS)

Hu, R.; Brauchler, R.; Herold, M.; Bayer, P.; Sauter, M.

2009-04-01

Rarely is it possible to draw a significant conclusion about the geometry and the properties of geological structures of the underground using the information which is typically obtained from boreholes, since soil exploration is only representative of the position where the soil sample is taken from. Conventional aquifer investigation methods like pumping tests can provide hydraulic properties of a larger area; however, they lead to integral information. This information is insufficient to develop groundwater models, especially contaminant transport models, which require information about the spatial distribution of the hydraulic properties of the subsurface. Hydraulic tomography is an innovative method which has the potential to spatially resolve three dimensional structures of natural aquifer bodies. The method employs hydraulic short term tests performed between two or more wells, whereby the pumped intervals (sources) and the observation points (receivers) are separated by double packer systems. In order to optimize the computationally intensive tomographic inversion of transient hydraulic data we have decided to couple two inversion approaches (a) hydraulic travel time inversion and (b) steady shape inversion. (a) Hydraulic travel time inversion is based on the solution of the travel time integral, which describes the relationship between travel time of maximum signal variation of a transient hydraulic signal and the diffusivity between source and receiver. The travel time inversion is computationally extremely effective and robust, however, it is limited to the determination of diffusivity. In order to overcome this shortcoming we use the estimated diffusivity distribution as starting model for the steady shape inversion with the goal to separate the estimated diffusivity distribution into its components, hydraulic conductivity and specific storage. (b) The steady shape inversion utilizes the fact that at steady shape conditions, drawdown varies with time but the hydraulic gradient does not. By this trick, transient data can be analyzed with the computational efficiency of a steady state model, which proceeds hundreds of times faster than transient models. Finally, a specific storage distribution can be calculated from the diffusivity and hydraulic conductivity reconstructions derived from travel time and steady shape inversion. The groundwork of this study is the aquifer-analogue study from BAYER (1999), in which six parallel profiles of a natural sedimentary body with a size of 16m x 10m x 7m were mapped in high resolution with respect to structural and hydraulic parameters. Based on these results and using geostatistical interpolation methods, MAJI (2005) designed a three dimensional hydraulic model with a resolution of 5cm x 5cm x 5cm. This hydraulic model was used to simulate a large number of short term pumping tests in a tomographical array. The high resolution parameter reconstructions gained from the inversion of simulated pumping test data demonstrate that the proposed inversion scheme allows reconstructing the individual architectural elements and their hydraulic properties with a higher resolution compared to conventional hydraulic and geological investigation methods. Bayer P (1999) Aquifer-Analog-Studium in grobklastischen braided river Ablagerungen: Sedimentäre/hydrogeologische Wandkartierung und Kalibrierung von Georadarmessungen, Diplomkartierung am Lehrstuhl für Angewandte Geologie, Universität Tübingen, 25 pp. Maji, R. (2005) Conditional Stochastic Modelling of DNAPL Migration and Dissolution in a High-resolution Aquifer Analog, Ph.D. thesis at the University of Waterloo, 187 pp.

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.

Model based Inverse Methods for Sizing Cracks of Varying Shape and Location in Bolt hole Eddy Current (BHEC) Inspections (Postprint)

DTIC Science & Technology

2016-02-10

using bolt hole eddy current (BHEC) techniques. Data was acquired for a wide range of crack sizes and shapes, including mid- bore , corner and through...to select the most appropriate VIC-3D surrogate model for subsequent crack sizing inversion step. Inversion results for select mid- bore , through and...the flaw. 15. SUBJECT TERMS Bolt hole eddy current (BHEC); mid- bore , corner and through-thickness crack types; VIC-3D generated surrogate models

Inverse problems in the design, modeling and testing of engineering systems

NASA Technical Reports Server (NTRS)

Alifanov, Oleg M.

1991-01-01

Formulations, classification, areas of application, and approaches to solving different inverse problems are considered for the design of structures, modeling, and experimental data processing. Problems in the practical implementation of theoretical-experimental methods based on solving inverse problems are analyzed in order to identify mathematical models of physical processes, aid in input data preparation for design parameter optimization, help in design parameter optimization itself, and to model experiments, large-scale tests, and real tests of engineering systems.

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

Improving resolution of crosswell seismic section based on time-frequency analysis

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

Luo, H.; Li, Y.

1994-12-31

According to signal theory, to improve resolution of seismic section is to extend high-frequency band of seismic signal. In cross-well section, sonic log can be regarded as a reliable source providing high-frequency information to the trace near the borehole. In such case, what to do is to introduce this high-frequency information into the whole section. However, neither traditional deconvolution algorithms nor some new inversion methods such as BCI (Broad Constraint Inversion) are satisfied because of high-frequency noise and nonuniqueness of inversion results respectively. To overcome their disadvantages, this paper presents a new algorithm based on Time-Frequency Analysis (TFA) technology whichmore » has been increasingly received much attention as an useful signal analysis too. Practical applications show that the new method is a stable scheme to improve resolution of cross-well seismic section greatly without decreasing Signal to Noise Ratio (SNR).« less

Novel Scalable 3-D MT Inverse Solver

NASA Astrophysics Data System (ADS)

Kuvshinov, A. V.; Kruglyakov, M.; Geraskin, A.

2016-12-01

We present a new, robust and fast, three-dimensional (3-D) magnetotelluric (MT) inverse solver. As a forward modelling engine a highly-scalable solver extrEMe [1] is used. The (regularized) inversion is based on an iterative gradient-type optimization (quasi-Newton method) and exploits adjoint sources approach for fast calculation of the gradient of the misfit. The inverse solver is able to deal with highly detailed and contrasting models, allows for working (separately or jointly) with any type of MT (single-site and/or inter-site) responses, and supports massive parallelization. Different parallelization strategies implemented in the code allow for optimal usage of available computational resources for a given problem set up. To parameterize an inverse domain a mask approach is implemented, which means that one can merge any subset of forward modelling cells in order to account for (usually) irregular distribution of observation sites. We report results of 3-D numerical experiments aimed at analysing the robustness, performance and scalability of the code. In particular, our computational experiments carried out at different platforms ranging from modern laptops to high-performance clusters demonstrate practically linear scalability of the code up to thousands of nodes. 1. Kruglyakov, M., A. Geraskin, A. Kuvshinov, 2016. Novel accurate and scalable 3-D MT forward solver based on a contracting integral equation method, Computers and Geosciences, in press.

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.).

An ambiguity of information content and error in an ill-posed satellite inversion

NASA Astrophysics Data System (ADS)

Koner, Prabhat

According to Rodgers (2000, stochastic approach), the averaging kernel (AK) is the representational matrix to understand the information content in a scholastic inversion. On the other hand, in deterministic approach this is referred to as model resolution matrix (MRM, Menke 1989). The analysis of AK/MRM can only give some understanding of how much regularization is imposed on the inverse problem. The trace of the AK/MRM matrix, which is the so-called degree of freedom from signal (DFS; stochastic) or degree of freedom in retrieval (DFR; deterministic). There are no physical/mathematical explanations in the literature: why the trace of the matrix is a valid form to calculate this quantity? We will present an ambiguity between information and error using a real life problem of SST retrieval from GOES13. The stochastic information content calculation is based on the linear assumption. The validity of such mathematics in satellite inversion will be questioned because it is based on the nonlinear radiative transfer and ill-conditioned inverse problems. References: Menke, W., 1989: Geophysical data analysis: discrete inverse theory. San Diego academic press. Rodgers, C.D., 2000: Inverse methods for atmospheric soundings: theory and practice. Singapore :World Scientific.

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.

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.

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.

Large-Scale Optimization for Bayesian Inference in Complex Systems

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

Willcox, Karen; Marzouk, Youssef

2013-11-12

The SAGUARO (Scalable Algorithms for Groundwater Uncertainty Analysis and Robust Optimization) Project focused on the development of scalable numerical algorithms for large-scale Bayesian inversion in complex systems that capitalize on advances in large-scale simulation-based optimization and inversion methods. The project was a collaborative effort among MIT, the University of Texas at Austin, Georgia Institute of Technology, and Sandia National Laboratories. The research was directed in three complementary areas: efficient approximations of the Hessian operator, reductions in complexity of forward simulations via stochastic spectral approximations and model reduction, and employing large-scale optimization concepts to accelerate sampling. The MIT--Sandia component of themore » SAGUARO Project addressed the intractability of conventional sampling methods for large-scale statistical inverse problems by devising reduced-order models that are faithful to the full-order model over a wide range of parameter values; sampling then employs the reduced model rather than the full model, resulting in very large computational savings. Results indicate little effect on the computed posterior distribution. On the other hand, in the Texas--Georgia Tech component of the project, we retain the full-order model, but exploit inverse problem structure (adjoint-based gradients and partial Hessian information of the parameter-to-observation map) to implicitly extract lower dimensional information on the posterior distribution; this greatly speeds up sampling methods, so that fewer sampling points are needed. We can think of these two approaches as ``reduce then sample'' and ``sample then reduce.'' In fact, these two approaches are complementary, and can be used in conjunction with each other. Moreover, they both exploit deterministic inverse problem structure, in the form of adjoint-based gradient and Hessian information of the underlying parameter-to-observation map, to achieve their speedups.« less

Final Report: Large-Scale Optimization for Bayesian Inference in Complex Systems

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

Ghattas, Omar

2013-10-15

The SAGUARO (Scalable Algorithms for Groundwater Uncertainty Analysis and Robust Optimiza- tion) Project focuses on the development of scalable numerical algorithms for large-scale Bayesian inversion in complex systems that capitalize on advances in large-scale simulation-based optimiza- tion and inversion methods. Our research is directed in three complementary areas: efficient approximations of the Hessian operator, reductions in complexity of forward simulations via stochastic spectral approximations and model reduction, and employing large-scale optimization concepts to accelerate sampling. Our efforts are integrated in the context of a challenging testbed problem that considers subsurface reacting flow and transport. The MIT component of the SAGUAROmore » Project addresses the intractability of conventional sampling methods for large-scale statistical inverse problems by devising reduced-order models that are faithful to the full-order model over a wide range of parameter values; sampling then employs the reduced model rather than the full model, resulting in very large computational savings. Results indicate little effect on the computed posterior distribution. On the other hand, in the Texas-Georgia Tech component of the project, we retain the full-order model, but exploit inverse problem structure (adjoint-based gradients and partial Hessian information of the parameter-to- observation map) to implicitly extract lower dimensional information on the posterior distribution; this greatly speeds up sampling methods, so that fewer sampling points are needed. We can think of these two approaches as "reduce then sample" and "sample then reduce." In fact, these two approaches are complementary, and can be used in conjunction with each other. Moreover, they both exploit deterministic inverse problem structure, in the form of adjoint-based gradient and Hessian information of the underlying parameter-to-observation map, to achieve their speedups.« less

Object-based inversion of crosswell radar tomography data to monitor vegetable oil injection experiments

USGS Publications Warehouse

Lane, John W.; Day-Lewis, Frederick D.; Versteeg, Roelof J.; Casey, Clifton C.

2004-01-01

Crosswell radar methods can be used to dynamically image ground-water flow and mass transport associated with tracer tests, hydraulic tests, and natural physical processes, for improved characterization of preferential flow paths and complex aquifer heterogeneity. Unfortunately, because the raypath coverage of the interwell region is limited by the borehole geometry, the tomographic inverse problem is typically underdetermined, and tomograms may contain artifacts such as spurious blurring or streaking that confuse interpretation.We implement object-based inversion (using a constrained, non-linear, least-squares algorithm) to improve results from pixel-based inversion approaches that utilize regularization criteria, such as damping or smoothness. Our approach requires pre- and post-injection travel-time data. Parameterization of the image plane comprises a small number of objects rather than a large number of pixels, resulting in an overdetermined problem that reduces the need for prior information. The nature and geometry of the objects are based on hydrologic insight into aquifer characteristics, the nature of the experiment, and the planned use of the geophysical results.The object-based inversion is demonstrated using synthetic and crosswell radar field data acquired during vegetable-oil injection experiments at a site in Fridley, Minnesota. The region where oil has displaced ground water is discretized as a stack of rectangles of variable horizontal extents. The inversion provides the geometry of the affected region and an estimate of the radar slowness change for each rectangle. Applying petrophysical models to these results and porosity from neutron logs, we estimate the vegetable-oil emulsion saturation in various layers.Using synthetic- and field-data examples, object-based inversion is shown to be an effective strategy for inverting crosswell radar tomography data acquired to monitor the emplacement of vegetable-oil emulsions. A principal advantage of object-based inversion is that it yields images that hydrologists and engineers can easily interpret and use for model calibration.

A Geophysical Inversion Model Enhancement Technique Based on the Blind Deconvolution

NASA Astrophysics Data System (ADS)

Zuo, B.; Hu, X.; Li, H.

2011-12-01

A model-enhancement technique is proposed to enhance the geophysical inversion model edges and details without introducing any additional information. Firstly, the theoretic correctness of the proposed geophysical inversion model-enhancement technique is discussed. An inversion MRM (model resolution matrix) convolution approximating PSF (Point Spread Function) method is designed to demonstrate the correctness of the deconvolution model enhancement method. Then, a total-variation regularization blind deconvolution geophysical inversion model-enhancement algorithm is proposed. In previous research, Oldenburg et al. demonstrate the connection between the PSF and the geophysical inverse solution. Alumbaugh et al. propose that more information could be provided by the PSF if we return to the idea of it behaving as an averaging or low pass filter. We consider the PSF as a low pass filter to enhance the inversion model basis on the theory of the PSF convolution approximation. Both the 1D linear and the 2D magnetotelluric inversion examples are used to analyze the validity of the theory and the algorithm. To prove the proposed PSF convolution approximation theory, the 1D linear inversion problem is considered. It shows the ratio of convolution approximation error is only 0.15%. The 2D synthetic model enhancement experiment is presented. After the deconvolution enhancement, the edges of the conductive prism and the resistive host become sharper, and the enhancement result is closer to the actual model than the original inversion model according the numerical statistic analysis. Moreover, the artifacts in the inversion model are suppressed. The overall precision of model increases 75%. All of the experiments show that the structure details and the numerical precision of inversion model are significantly improved, especially in the anomalous region. The correlation coefficient between the enhanced inversion model and the actual model are shown in Fig. 1. The figure illustrates that more information and details structure of the actual model are enhanced through the proposed enhancement algorithm. Using the proposed enhancement method can help us gain a clearer insight into the results of the inversions and help make better informed decisions.

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.

Training-Image Based Geostatistical Inversion Using a Spatial Generative Adversarial Neural Network

NASA Astrophysics Data System (ADS)

Laloy, Eric; Hérault, Romain; Jacques, Diederik; Linde, Niklas

2018-01-01

Probabilistic inversion within a multiple-point statistics framework is often computationally prohibitive for high-dimensional problems. To partly address this, we introduce and evaluate a new training-image based inversion approach for complex geologic media. Our approach relies on a deep neural network of the generative adversarial network (GAN) type. After training using a training image (TI), our proposed spatial GAN (SGAN) can quickly generate 2-D and 3-D unconditional realizations. A key characteristic of our SGAN is that it defines a (very) low-dimensional parameterization, thereby allowing for efficient probabilistic inversion using state-of-the-art Markov chain Monte Carlo (MCMC) methods. In addition, available direct conditioning data can be incorporated within the inversion. Several 2-D and 3-D categorical TIs are first used to analyze the performance of our SGAN for unconditional geostatistical simulation. Training our deep network can take several hours. After training, realizations containing a few millions of pixels/voxels can be produced in a matter of seconds. This makes it especially useful for simulating many thousands of realizations (e.g., for MCMC inversion) as the relative cost of the training per realization diminishes with the considered number of realizations. Synthetic inversion case studies involving 2-D steady state flow and 3-D transient hydraulic tomography with and without direct conditioning data are used to illustrate the effectiveness of our proposed SGAN-based inversion. For the 2-D case, the inversion rapidly explores the posterior model distribution. For the 3-D case, the inversion recovers model realizations that fit the data close to the target level and visually resemble the true model well.

Identification of source velocities on 3D structures in non-anechoic environments: Theoretical background and experimental validation of the inverse patch transfer functions method

NASA Astrophysics Data System (ADS)

Aucejo, M.; Totaro, N.; Guyader, J.-L.

2010-08-01

In noise control, identification of the source velocity field remains a major problem open to investigation. Consequently, methods such as nearfield acoustical holography (NAH), principal source projection, the inverse frequency response function and hybrid NAH have been developed. However, these methods require free field conditions that are often difficult to achieve in practice. This article presents an alternative method known as inverse patch transfer functions, designed to identify source velocities and developed in the framework of the European SILENCE project. This method is based on the definition of a virtual cavity, the double measurement of the pressure and particle velocity fields on the aperture surfaces of this volume, divided into elementary areas called patches and the inversion of impedances matrices, numerically computed from a modal basis obtained by FEM. Theoretically, the method is applicable to sources with complex 3D geometries and measurements can be carried out in a non-anechoic environment even in the presence of other stationary sources outside the virtual cavity. In the present paper, the theoretical background of the iPTF method is described and the results (numerical and experimental) for a source with simple geometry (two baffled pistons driven in antiphase) are presented and discussed.

2-D inversion of VES data in Saqqara archaeological area, Egypt

NASA Astrophysics Data System (ADS)

El-Qady, Gad; Sakamoto, Chika; Ushijima, Keisuke

1999-10-01

The interpretation of actual geophysical field data still has a problem for obtaining a unique solution. In order to investigate the groundwater potentials in Saqqara archaeological area, vertical electrical soundings with Schlumberger array have been carried out. In the interpretation of VES data, 1D resistivity inversion has been performed based on a horizontally layered earth model by El-Qady (1995). However, some results of 1D inversion are not fully satisfied for actual 3D structures such as archaeological tombs. Therefore, we have carried out 2D inversion based on ABIC least squares method for Schlumberger VES data obtained in Saqqara area. Although the results of 2D cross sections were correlated with the previous interpretation, the 2D inversion still shows a rough spatial resistivity distribution, which is the abrupt change in resistivity between two neighboring blocks of the computed region. It is concluded that 3D interpretation is recommended for visualizing ground water distribution with depth in the Saqqara area.

Symbolic inversion of control relationships in model-based expert systems

NASA Technical Reports Server (NTRS)

Thomas, Stan

1988-01-01

Symbolic inversion is examined from several perspectives. First, a number of symbolic algebra and mathematical tool packages were studied in order to evaluate their capabilities and methods, specifically with respect to symbolic inversion. Second, the KATE system (without hardware interface) was ported to a Zenith Z-248 microcomputer running Golden Common Lisp. The interesting thing about the port is that it allows the user to have measurements vary and components fail in a non-deterministic manner based upon random value from probability distributions. Third, INVERT was studied as currently implemented in KATE, its operation documented, some of its weaknesses identified, and corrections made to it. The corrections and enhancements are primarily in the way that logical conditions involving AND's and OR's and inequalities are processed. In addition, the capability to handle equalities was also added. Suggestions were also made regarding the handling of ranges in INVERT. Last, other approaches to the inversion process were studied and recommendations were made as to how future versions of KATE should perform symbolic inversion.

Numerical Aspects of Cone Beam Contour Reconstruction

NASA Astrophysics Data System (ADS)

Louis, Alfred K.

2017-12-01

We describe a method for directly calculating the contours of a function from cone beam data. The algorithm is based on a new inversion formula for the gradient of a function presented in Louis (Inverse Probl 32(11):115005, 2016. http://stacks.iop.org/0266-5611/32/i=11/a=115005). The Radon transform of the gradient is found by using a Grangeat type of formula, reducing the inversion problem to the inversion of the Radon transform. In that way the influence of the scanning curve, vital for all exact inversion formulas for complete data, is avoided Numerical results are presented for the circular scanning geometry which neither fulfills the Tuy-Kirillov condition nor the much weaker condition given by the author in Louis (Inverse Probl 32(11):115005, 2016. http://stacks.iop.org/0266-5611/32/i=11/a=115005).

A PC-based inverse design method for radial and mixed flow turbomachinery

NASA Technical Reports Server (NTRS)

Skoe, Ivar Helge

1991-01-01

An Inverse Design Method suitable for radial and mixed flow turbomachinery is presented. The codes are based on the streamline curvature concept; therefore, it is applicable for current personal computers from the 286/287 range. In addition to the imposed aerodynamic constraints, mechanical constraints are imposed during the design process to ensure that the resulting geometry satisfies production consideration and that structural considerations are taken into account. By the use of Bezier Curves in the geometric modeling, the same subroutine is used to prepare input for both aero and structural files since it is important to ensure that the geometric data is identical to both structural analysis and production. To illustrate the method, a mixed flow turbine design is shown.

Non-Random Inversion Landscapes in Prokaryotic Genomes Are Shaped by Heterogeneous Selection Pressures

PubMed Central

Repar, Jelena; Warnecke, Tobias

2017-01-01

Abstract Inversions are a major contributor to structural genome evolution in prokaryotes. Here, using a novel alignment-based method, we systematically compare 1,651 bacterial and 98 archaeal genomes to show that inversion landscapes are frequently biased toward (symmetric) inversions around the origin–terminus axis. However, symmetric inversion bias is not a universal feature of prokaryotic genome evolution but varies considerably across clades. At the extremes, inversion landscapes in Bacillus–Clostridium and Actinobacteria are dominated by symmetric inversions, while there is little or no systematic bias favoring symmetric rearrangements in archaea with a single origin of replication. Within clades, we find strong but clade-specific relationships between symmetric inversion bias and different features of adaptive genome architecture, including the distance of essential genes to the origin of replication and the preferential localization of genes on the leading strand. We suggest that heterogeneous selection pressures have converged to produce similar patterns of structural genome evolution across prokaryotes. PMID:28407093

Calibrating the Spatiotemporal Root Density Distribution for Macroscopic Water Uptake Models Using Tikhonov Regularization

NASA Astrophysics Data System (ADS)

Li, N.; Yue, X. Y.

2018-03-01

Macroscopic root water uptake models proportional to a root density distribution function (RDDF) are most commonly used to model water uptake by plants. As the water uptake is difficult and labor intensive to measure, these models are often calibrated by inverse modeling. Most previous inversion studies assume RDDF to be constant with depth and time or dependent on only depth for simplification. However, under field conditions, this function varies with type of soil and root growth and thus changes with both depth and time. This study proposes an inverse method to calibrate both spatially and temporally varying RDDF in unsaturated water flow modeling. To overcome the difficulty imposed by the ill-posedness, the calibration is formulated as an optimization problem in the framework of the Tikhonov regularization theory, adding additional constraint to the objective function. Then the formulated nonlinear optimization problem is numerically solved with an efficient algorithm on the basis of the finite element method. The advantage of our method is that the inverse problem is translated into a Tikhonov regularization functional minimization problem and then solved based on the variational construction, which circumvents the computational complexity in calculating the sensitivity matrix involved in many derivative-based parameter estimation approaches (e.g., Levenberg-Marquardt optimization). Moreover, the proposed method features optimization of RDDF without any prior form, which is applicable to a more general root water uptake model. Numerical examples are performed to illustrate the applicability and effectiveness of the proposed method. Finally, discussions on the stability and extension of this method are presented.

The Foundation GPS Water Vapor Inversion and its Application Research

NASA Astrophysics Data System (ADS)

Liu, R.; Lee, T.; Lv, H.; Fan, C.; Liu, Q.

2018-04-01

Using GPS technology to retrieve atmospheric water vapor is a new water vapor detection method, which can effectively compensate for the shortcomings of conventional water vapor detection methods, to provide high-precision, large-capacity, near real-time water vapor information. In-depth study of ground-based GPS detection of atmospheric water vapor technology aims to further improve the accuracy and practicability of GPS inversion of water vapor and to explore its ability to detect atmospheric water vapor information to better serve the meteorological services. In this paper, the influence of the setting parameters of initial station coordinates, satellite ephemeris and solution observation on the total delay accuracy of the tropospheric zenith is discussed based on the observed data. In this paper, the observations obtained from the observation network consisting of 8 IGS stations in China in June 2013 are used to inverse the water vapor data of the 8 stations. The data of Wuhan station is further selected and compared with the data of Nanhu Sounding Station in Wuhan The error between the two data was between -6mm-6mm, and the trend of the two was almost the same, the correlation reached 95.8 %. The experimental results also verify the reliability of ground-based GPS inversion of water vapor technology.

A fast reconstruction algorithm for fluorescence optical diffusion tomography based on preiteration.

PubMed

Song, Xiaolei; Xiong, Xiaoyun; Bai, Jing

2007-01-01

Fluorescence optical diffusion tomography in the near-infrared (NIR) bandwidth is considered to be one of the most promising ways for noninvasive molecular-based imaging. Many reconstructive approaches to it utilize iterative methods for data inversion. However, they are time-consuming and they are far from meeting the real-time imaging demands. In this work, a fast preiteration algorithm based on the generalized inverse matrix is proposed. This method needs only one step of matrix-vector multiplication online, by pushing the iteration process to be executed offline. In the preiteration process, the second-order iterative format is employed to exponentially accelerate the convergence. Simulations based on an analytical diffusion model show that the distribution of fluorescent yield can be well estimated by this algorithm and the reconstructed speed is remarkably increased.

A sequential coalescent algorithm for chromosomal inversions

PubMed Central

Peischl, S; Koch, E; Guerrero, R F; Kirkpatrick, M

2013-01-01

Chromosomal inversions are common in natural populations and are believed to be involved in many important evolutionary phenomena, including speciation, the evolution of sex chromosomes and local adaptation. While recent advances in sequencing and genotyping methods are leading to rapidly increasing amounts of genome-wide sequence data that reveal interesting patterns of genetic variation within inverted regions, efficient simulation methods to study these patterns are largely missing. In this work, we extend the sequential Markovian coalescent, an approximation to the coalescent with recombination, to include the effects of polymorphic inversions on patterns of recombination. Results show that our algorithm is fast, memory-efficient and accurate, making it feasible to simulate large inversions in large populations for the first time. The SMC algorithm enables studies of patterns of genetic variation (for example, linkage disequilibria) and tests of hypotheses (using simulation-based approaches) that were previously intractable. PMID:23632894

Comparing mass balance and adjoint methods for inverse modeling of nitrogen dioxide columns for global nitrogen oxide emissions

NASA Astrophysics Data System (ADS)

Cooper, Matthew; Martin, Randall V.; Padmanabhan, Akhila; Henze, Daven K.

2017-04-01

Satellite observations offer information applicable to top-down constraints on emission inventories through inverse modeling. Here we compare two methods of inverse modeling for emissions of nitrogen oxides (NOx) from nitrogen dioxide (NO2) columns using the GEOS-Chem chemical transport model and its adjoint. We treat the adjoint-based 4D-Var modeling approach for estimating top-down emissions as a benchmark against which to evaluate variations on the mass balance method. We use synthetic NO2 columns generated from known NOx emissions to serve as "truth." We find that error in mass balance inversions can be reduced by up to a factor of 2 with an iterative process that uses finite difference calculations of the local sensitivity of NO2 columns to a change in emissions. In a simplified experiment to recover local emission perturbations, horizontal smearing effects due to NOx transport are better resolved by the adjoint approach than by mass balance. For more complex emission changes, or at finer resolution, the iterative finite difference mass balance and adjoint methods produce similar global top-down inventories when inverting hourly synthetic observations, both reducing the a priori error by factors of 3-4. Inversions of simulated satellite observations from low Earth and geostationary orbits also indicate that both the mass balance and adjoint inversions produce similar results, reducing a priori error by a factor of 3. As the iterative finite difference mass balance method provides similar accuracy as the adjoint method, it offers the prospect of accurately estimating top-down NOx emissions using models that do not have an adjoint.

Mathematics of Computed Tomography

NASA Astrophysics Data System (ADS)

Hawkins, William Grant

A review of the applications of the Radon transform is presented, with emphasis on emission computed tomography and transmission computed tomography. The theory of the 2D and 3D Radon transforms, and the effects of attenuation for emission computed tomography are presented. The algebraic iterative methods, their importance and limitations are reviewed. Analytic solutions of the 2D problem the convolution and frequency filtering methods based on linear shift invariant theory, and the solution of the circular harmonic decomposition by integral transform theory--are reviewed. The relation between the invisible kernels, the inverse circular harmonic transform, and the consistency conditions are demonstrated. The discussion and review are extended to the 3D problem-convolution, frequency filtering, spherical harmonic transform solutions, and consistency conditions. The Cormack algorithm based on reconstruction with Zernike polynomials is reviewed. An analogous algorithm and set of reconstruction polynomials is developed for the spherical harmonic transform. The relations between the consistency conditions, boundary conditions and orthogonal basis functions for the 2D projection harmonics are delineated and extended to the 3D case. The equivalence of the inverse circular harmonic transform, the inverse Radon transform, and the inverse Cormack transform is presented. The use of the number of nodes of a projection harmonic as a filter is discussed. Numerical methods for the efficient implementation of angular harmonic algorithms based on orthogonal functions and stable recursion are presented. The derivation of a lower bound for the signal-to-noise ratio of the Cormack algorithm is derived.

Simplified, inverse, ejector design tool

NASA Technical Reports Server (NTRS)

Dechant, Lawrence J.

1993-01-01

A simple lumped parameter based inverse design tool has been developed which provides flow path geometry and entrainment estimates subject to operational, acoustic, and design constraints. These constraints are manifested through specification of primary mass flow rate or ejector thrust, fully-mixed exit velocity, and static pressure matching. Fundamentally, integral forms of the conservation equations coupled with the specified design constraints are combined to yield an easily invertible linear system in terms of the flow path cross-sectional areas. Entrainment is computed by back substitution. Initial comparison with experimental and analogous one-dimensional methods show good agreement. Thus, this simple inverse design code provides an analytically based, preliminary design tool with direct application to High Speed Civil Transport (HSCT) design studies.

3-D minimum-structure inversion of magnetotelluric data using the finite-element method and tetrahedral grids

NASA Astrophysics Data System (ADS)

Jahandari, H.; Farquharson, C. G.

2017-11-01

Unstructured grids enable representing arbitrary structures more accurately and with fewer cells compared to regular structured grids. These grids also allow more efficient refinements compared to rectilinear meshes. In this study, tetrahedral grids are used for the inversion of magnetotelluric (MT) data, which allows for the direct inclusion of topography in the model, for constraining an inversion using a wireframe-based geological model and for local refinement at the observation stations. A minimum-structure method with an iterative model-space Gauss-Newton algorithm for optimization is used. An iterative solver is employed for solving the normal system of equations at each Gauss-Newton step and the sensitivity matrix-vector products that are required by this solver are calculated using pseudo-forward problems. This method alleviates the need to explicitly form the Hessian or Jacobian matrices which significantly reduces the required computation memory. Forward problems are formulated using an edge-based finite-element approach and a sparse direct solver is used for the solutions. This solver allows saving and re-using the factorization of matrices for similar pseudo-forward problems within a Gauss-Newton iteration which greatly minimizes the computation time. Two examples are presented to show the capability of the algorithm: the first example uses a benchmark model while the second example represents a realistic geological setting with topography and a sulphide deposit. The data that are inverted are the full-tensor impedance and the magnetic transfer function vector. The inversions sufficiently recovered the models and reproduced the data, which shows the effectiveness of unstructured grids for complex and realistic MT inversion scenarios. The first example is also used to demonstrate the computational efficiency of the presented model-space method by comparison with its data-space counterpart.

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

Moving from pixel to object scale when inverting radiative transfer models for quantitative estimation of biophysical variables in vegetation (Invited)

NASA Astrophysics Data System (ADS)

Atzberger, C.

2013-12-01

The robust and accurate retrieval of vegetation biophysical variables using RTM is seriously hampered by the ill-posedness of the inverse problem. The contribution presents our object-based inversion approach and evaluate it against measured data. The proposed method takes advantage of the fact that nearby pixels are generally more similar than those at a larger distance. For example, within a given vegetation patch, nearby pixels often share similar leaf angular distributions. This leads to spectral co-variations in the n-dimensional spectral features space, which can be used for regularization purposes. Using a set of leaf area index (LAI) measurements (n=26) acquired over alfalfa, sugar beet and garlic crops of the Barrax test site (Spain), it is demonstrated that the proposed regularization using neighbourhood information yields more accurate results compared to the traditional pixel-based inversion. Principle of the ill-posed inverse problem and the proposed solution illustrated in the red-nIR feature space using (PROSAIL). [A] spectral trajectory ('soil trajectory') obtained for one leaf angle (ALA) and one soil brightness (αsoil), when LAI varies between 0 and 10, [B] 'soil trajectories' for 5 soil brightness values and three leaf angles, [C] ill-posed inverse problem: different combinations of ALA × αsoil yield an identical crossing point, [D] object-based RTM inversion; only one 'soil trajectory' fits all nine pixelswithin a gliding (3×3) window. The black dots (plus the rectangle=central pixel) represent the hypothetical position of nine pixels within a 3×3 (gliding) window. Assuming that over short distances (× 1 pixel) variations in soil brightness can be neglected, the proposed object-based inversion searches for one common set of ALA × αsoil so that the resulting 'soil trajectory' best fits the nine measured pixels. Ground measured vs. retrieved LAI values for three crops. Left: proposed object-based approach. Right: pixel-based inversion

Acoustic and elastic waveform inversion best practices

NASA Astrophysics Data System (ADS)

Modrak, Ryan T.

Reaching the global minimum of a waveform misfit function requires careful choices about the nonlinear optimization, preconditioning and regularization methods underlying an inversion. Because waveform inversion problems are susceptible to erratic convergence, one or two test cases are not enough to reliably inform such decisions. We identify best practices instead using two global, one regional and four near-surface acoustic test problems. To obtain meaningful quantitative comparisons, we carry out hundreds acoustic inversions, varying one aspect of the implementation at a time. Comparing nonlinear optimization algorithms, we find that L-BFGS provides computational savings over nonlinear conjugate gradient methods in a wide variety of test cases. Comparing preconditioners, we show that a new diagonal scaling derived from the adjoint of the forward operator provides better performance than two conventional preconditioning schemes. Comparing regularization strategies, we find that projection, convolution, Tikhonov regularization, and total variation regularization are effective in different contexts. Besides these issues, reliability and efficiency in waveform inversion depend on close numerical attention and care. Implementation details have a strong effect on computational cost, regardless of the chosen material parameterization or nonlinear optimization algorithm. Building on the acoustic inversion results, we carry out elastic experiments with four test problems, three objective functions, and four material parameterizations. The choice of parameterization for isotropic elastic media is found to be more complicated than previous studies suggests, with "wavespeed-like'' parameters performing well with phase-based objective functions and Lame parameters performing well with amplitude-based objective functions. Reliability and efficiency can be even harder to achieve in transversely isotropic elastic inversions because rotation angle parameters describing fast-axis direction are difficult to recover. Using Voigt or Chen-Tromp parameters avoids the need to include rotation angles explicitly and provides an effective strategy for anisotropic inversion. The need for flexible and portable workflow management tools for seismic inversion also poses a major challenge. In a final chapter, the software used to the carry out the above experiments is described and instructions for reproducing experimental results are given.

Morphology-Controlled Synthesis of Organometal Halide Perovskite Inverse Opals.

PubMed

Chen, Kun; Tüysüz, Harun

2015-11-09

The booming development of organometal halide perovskites in recent years has prompted the exploration of morphology-control strategies to improve their performance in photovoltaic, photonic, and optoelectronic applications. However, the preparation of organometal halide perovskites with high hierarchical architecture is still highly challenging and a general morphology-control method for various organometal halide perovskites has not been achieved. A mild and scalable method to prepare organometal halide perovskites in inverse opal morphology is presented that uses a polystyrene-based artificial opal as hard template. Our method is flexible and compatible with different halides and organic ammonium compositions. Thus, the perovskite inverse opal maintains the advantage of straightforward structure and band gap engineering. Furthermore, optoelectronic investigations reveal that morphology exerted influence on the conducting nature of organometal halide perovskites. © 2015 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Parallel solution of the symmetric tridiagonal eigenproblem. Research report

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

Jessup, E.R.

1989-10-01

This thesis discusses methods for computing all eigenvalues and eigenvectors of a symmetric tridiagonal matrix on a distributed-memory Multiple Instruction, Multiple Data multiprocessor. Only those techniques having the potential for both high numerical accuracy and significant large-grained parallelism are investigated. These include the QL method or Cuppen's divide and conquer method based on rank-one updating to compute both eigenvalues and eigenvectors, bisection to determine eigenvalues and inverse iteration to compute eigenvectors. To begin, the methods are compared with respect to computation time, communication time, parallel speed up, and accuracy. Experiments on an IPSC hypercube multiprocessor reveal that Cuppen's method ismore » the most accurate approach, but bisection with inverse iteration is the fastest and most parallel. Because the accuracy of the latter combination is determined by the quality of the computed eigenvectors, the factors influencing the accuracy of inverse iteration are examined. This includes, in part, statistical analysis of the effect of a starting vector with random components. These results are used to develop an implementation of inverse iteration producing eigenvectors with lower residual error and better orthogonality than those generated by the EISPACK routine TINVIT. This thesis concludes with adaptions of methods for the symmetric tridiagonal eigenproblem to the related problem of computing the singular value decomposition (SVD) of a bidiagonal matrix.« less

Parallel solution of the symmetric tridiagonal eigenproblem

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

Jessup, E.R.

1989-01-01

This thesis discusses methods for computing all eigenvalues and eigenvectors of a symmetric tridiagonal matrix on a distributed memory MIMD multiprocessor. Only those techniques having the potential for both high numerical accuracy and significant large-grained parallelism are investigated. These include the QL method or Cuppen's divide and conquer method based on rank-one updating to compute both eigenvalues and eigenvectors, bisection to determine eigenvalues, and inverse iteration to compute eigenvectors. To begin, the methods are compared with respect to computation time, communication time, parallel speedup, and accuracy. Experiments on an iPSC hyper-cube multiprocessor reveal that Cuppen's method is the most accuratemore » approach, but bisection with inverse iteration is the fastest and most parallel. Because the accuracy of the latter combination is determined by the quality of the computed eigenvectors, the factors influencing the accuracy of inverse iteration are examined. This includes, in part, statistical analysis of the effects of a starting vector with random components. These results are used to develop an implementation of inverse iteration producing eigenvectors with lower residual error and better orthogonality than those generated by the EISPACK routine TINVIT. This thesis concludes with adaptations of methods for the symmetric tridiagonal eigenproblem to the related problem of computing the singular value decomposition (SVD) of a bidiagonal matrix.« less

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.

Porosity Estimation By Artificial Neural Networks Inversion . Application to Algerian South Field

NASA Astrophysics Data System (ADS)

Eladj, Said; Aliouane, Leila; Ouadfeul, Sid-Ali

2017-04-01

One of the main geophysicist's current challenge is the discovery and the study of stratigraphic traps, this last is a difficult task and requires a very fine analysis of the seismic data. The seismic data inversion allows obtaining lithological and stratigraphic information for the reservoir characterization . However, when solving the inverse problem we encounter difficult problems such as: Non-existence and non-uniqueness of the solution add to this the instability of the processing algorithm. Therefore, uncertainties in the data and the non-linearity of the relationship between the data and the parameters must be taken seriously. In this case, the artificial intelligence techniques such as Artificial Neural Networks(ANN) is used to resolve this ambiguity, this can be done by integrating different physical properties data which requires a supervised learning methods. In this work, we invert the acoustic impedance 3D seismic cube using the colored inversion method, then, the introduction of the acoustic impedance volume resulting from the first step as an input of based model inversion method allows to calculate the Porosity volume using the Multilayer Perceptron Artificial Neural Network. Application to an Algerian South hydrocarbon field clearly demonstrate the power of the proposed processing technique to predict the porosity for seismic data, obtained results can be used for reserves estimation, permeability prediction, recovery factor and reservoir monitoring. Keywords: Artificial Neural Networks, inversion, non-uniqueness , nonlinear, 3D porosity volume, reservoir characterization .

Strategies for efficient resolution analysis in full-waveform inversion

NASA Astrophysics Data System (ADS)

Fichtner, A.; van Leeuwen, T.; Trampert, J.

2016-12-01

Full-waveform inversion is developing into a standard method in the seismological toolbox. It combines numerical wave propagation for heterogeneous media with adjoint techniques in order to improve tomographic resolution. However, resolution becomes increasingly difficult to quantify because of the enormous computational requirements. Here we present two families of methods that can be used for efficient resolution analysis in full-waveform inversion. They are based on the targeted extraction of resolution proxies from the Hessian matrix, which is too large to store and to compute explicitly. Fourier methods rest on the application of the Hessian to Earth models with harmonic oscillations. This yields the Fourier spectrum of the Hessian for few selected wave numbers, from which we can extract properties of the tomographic point-spread function for any point in space. Random probing methods use uncorrelated, random test models instead of harmonic oscillations. Auto-correlating the Hessian-model applications for sufficiently many test models also characterises the point-spread function. Both Fourier and random probing methods provide a rich collection of resolution proxies. These include position- and direction-dependent resolution lengths, and the volume of point-spread functions as indicator of amplitude recovery and inter-parameter trade-offs. The computational requirements of these methods are equivalent to approximately 7 conjugate-gradient iterations in full-waveform inversion. This is significantly less than the optimisation itself, which may require tens to hundreds of iterations to reach convergence. In addition to the theoretical foundations of the Fourier and random probing methods, we show various illustrative examples from real-data full-waveform inversion for crustal and mantle structure.

Probabilistic 3-D time-lapse inversion of magnetotelluric data: application to an enhanced geothermal system

NASA Astrophysics Data System (ADS)

Rosas-Carbajal, M.; Linde, N.; Peacock, J.; Zyserman, F. I.; Kalscheuer, T.; Thiel, S.

2015-12-01

Surface-based monitoring of mass transfer caused by injections and extractions in deep boreholes is crucial to maximize oil, gas and geothermal production. Inductive electromagnetic methods, such as magnetotellurics, are appealing for these applications due to their large penetration depths and sensitivity to changes in fluid conductivity and fracture connectivity. In this work, we propose a 3-D Markov chain Monte Carlo inversion of time-lapse magnetotelluric data to image mass transfer following a saline fluid injection. The inversion estimates the posterior probability density function of the resulting plume, and thereby quantifies model uncertainty. To decrease computation times, we base the parametrization on a reduced Legendre moment decomposition of the plume. A synthetic test shows that our methodology is effective when the electrical resistivity structure prior to the injection is well known. The centre of mass and spread of the plume are well retrieved. We then apply our inversion strategy to an injection experiment in an enhanced geothermal system at Paralana, South Australia, and compare it to a 3-D deterministic time-lapse inversion. The latter retrieves resistivity changes that are more shallow than the actual injection interval, whereas the probabilistic inversion retrieves plumes that are located at the correct depths and oriented in a preferential north-south direction. To explain the time-lapse data, the inversion requires unrealistically large resistivity changes with respect to the base model. We suggest that this is partly explained by unaccounted subsurface heterogeneities in the base model from which time-lapse changes are inferred.

Probabilistic 3-D time-lapse inversion of magnetotelluric data: Application to an enhanced geothermal system

USGS Publications Warehouse

Rosas-Carbajal, Marina; Linde, Nicolas; Peacock, Jared R.; Zyserman, F. I.; Kalscheuer, Thomas; Thiel, Stephan

2015-01-01

Surface-based monitoring of mass transfer caused by injections and extractions in deep boreholes is crucial to maximize oil, gas and geothermal production. Inductive electromagnetic methods, such as magnetotellurics, are appealing for these applications due to their large penetration depths and sensitivity to changes in fluid conductivity and fracture connectivity. In this work, we propose a 3-D Markov chain Monte Carlo inversion of time-lapse magnetotelluric data to image mass transfer following a saline fluid injection. The inversion estimates the posterior probability density function of the resulting plume, and thereby quantifies model uncertainty. To decrease computation times, we base the parametrization on a reduced Legendre moment decomposition of the plume. A synthetic test shows that our methodology is effective when the electrical resistivity structure prior to the injection is well known. The centre of mass and spread of the plume are well retrieved.We then apply our inversion strategy to an injection experiment in an enhanced geothermal system at Paralana, South Australia, and compare it to a 3-D deterministic time-lapse inversion. The latter retrieves resistivity changes that are more shallow than the actual injection interval, whereas the probabilistic inversion retrieves plumes that are located at the correct depths and oriented in a preferential north-south direction. To explain the time-lapse data, the inversion requires unrealistically large resistivity changes with respect to the base model. We suggest that this is partly explained by unaccounted subsurface heterogeneities in the base model from which time-lapse changes are inferred.

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.

SaaS Platform for Time Series Data Handling

NASA Astrophysics Data System (ADS)

Oplachko, Ekaterina; Rykunov, Stanislav; Ustinin, Mikhail

2018-02-01

The paper is devoted to the description of MathBrain, a cloud-based resource, which works as a "Software as a Service" model. It is designed to maximize the efficiency of the current technology and to provide a tool for time series data handling. The resource provides access to the following analysis methods: direct and inverse Fourier transforms, Principal component analysis and Independent component analysis decompositions, quantitative analysis, magnetoencephalography inverse problem solution in a single dipole model based on multichannel spectral data.

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.

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.

Inverse optimal design of input-to-state stabilisation for affine nonlinear systems with input delays

NASA Astrophysics Data System (ADS)

Cai, Xiushan; Meng, Lingxin; Zhang, Wei; Liu, Leipo

2018-03-01

We establish robustness of the predictor feedback control law to perturbations appearing at the system input for affine nonlinear systems with time-varying input delay and additive disturbances. Furthermore, it is shown that it is inverse optimal with respect to a differential game problem. All of the stability and inverse optimality proofs are based on the infinite-dimensional backstepping transformation and an appropriate Lyapunov functional. A single-link manipulator subject to input delays and disturbances is given to illustrate the validity of the proposed method.

Direct Iterative Nonlinear Inversion by Multi-frequency T-matrix Completion

NASA Astrophysics Data System (ADS)

Jakobsen, M.; Wu, R. S.

2016-12-01

Researchers in the mathematical physics community have recently proposed a conceptually new method for solving nonlinear inverse scattering problems (like FWI) which is inspired by the theory of nonlocality of physical interactions. The conceptually new method, which may be referred to as the T-matrix completion method, is very interesting since it is not based on linearization at any stage. Also, there are no gradient vectors or (inverse) Hessian matrices to calculate. However, the convergence radius of this promising T-matrix completion method is seriously restricted by it's use of single-frequency scattering data only. In this study, we have developed a modified version of the T-matrix completion method which we believe is more suitable for applications to nonlinear inverse scattering problems in (exploration) seismology, because it makes use of multi-frequency data. Essentially, we have simplified the single-frequency T-matrix completion method of Levinson and Markel and combined it with the standard sequential frequency inversion (multi-scale regularization) method. For each frequency, we first estimate the experimental T-matrix by using the Moore-Penrose pseudo inverse concept. Then this experimental T-matrix is used to initiate an iterative procedure for successive estimation of the scattering potential and the T-matrix using the Lippmann-Schwinger for the nonlinear relation between these two quantities. The main physical requirements in the basic iterative cycle is that the T-matrix should be data-compatible and the scattering potential operator should be dominantly local; although a non-local scattering potential operator is allowed in the intermediate iterations. In our simplified T-matrix completion strategy, we ensure that the T-matrix updates are always data compatible simply by adding a suitable correction term in the real space coordinate representation. The use of singular-value decomposition representations are not required in our formulation since we have developed an efficient domain decomposition method. The results of several numerical experiments for the SEG/EAGE salt model illustrate the importance of using multi-frequency data when performing frequency domain full waveform inversion in strongly scattering media via the new concept of T-matrix completion.

Determination of the aerosol size distribution by analytic inversion of the extinction spectrum in the complex anomalous diffraction approximation.

PubMed

Franssens, G; De Maziére, M; Fonteyn, D

2000-08-20

A new derivation is presented for the analytical inversion of aerosol spectral extinction data to size distributions. It is based on the complex analytic extension of the anomalous diffraction approximation (ADA). We derive inverse formulas that are applicable to homogeneous nonabsorbing and absorbing spherical particles. Our method simplifies, generalizes, and unifies a number of results obtained previously in the literature. In particular, we clarify the connection between the ADA transform and the Fourier and Laplace transforms. Also, the effect of the particle refractive-index dispersion on the inversion is examined. It is shown that, when Lorentz's model is used for this dispersion, the continuous ADA inverse transform is mathematically well posed, whereas with a constant refractive index it is ill posed. Further, a condition is given, in terms of Lorentz parameters, for which the continuous inverse operator does not amplify the error.

Sequential Geoacoustic Filtering and Geoacoustic Inversion

DTIC Science & Technology

2015-09-30

and online algorithms. We show here that CS obtains higher resolution than MVDR, even in scenarios, which favor classical high-resolution methods...windows actually performs better than conventional beamforming and MVDR/ MUSIC (see Figs. 1-2). Compressive geoacoustic inversion Geoacoustic...histograms based on 100 Monte Carlo simulations, and c)(CS, exhaustive-search, CBF, MVDR, and MUSIC performance versus SNR. The true source positions

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.

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.

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

[Research on the method of interference correction for nondispersive infrared multi-component gas analysis].

PubMed

Sun, You-Wen; Liu, Wen-Qing; Wang, Shi-Mei; Huang, Shu-Hua; Yu, Xiao-Man

2011-10-01

A method of interference correction for nondispersive infrared multi-component gas analysis was described. According to the successive integral gas absorption models and methods, the influence of temperature and air pressure on the integral line strengths and linetype was considered, and based on Lorentz detuning linetypes, the absorption cross sections and response coefficients of H2O, CO2, CO, and NO on each filter channel were obtained. The four dimension linear regression equations for interference correction were established by response coefficients, the absorption cross interference was corrected by solving the multi-dimensional linear regression equations, and after interference correction, the pure absorbance signal on each filter channel was only controlled by the corresponding target gas concentration. When the sample cell was filled with gas mixture with a certain concentration proportion of CO, NO and CO2, the pure absorbance after interference correction was used for concentration inversion, the inversion concentration error for CO2 is 2.0%, the inversion concentration error for CO is 1.6%, and the inversion concentration error for NO is 1.7%. Both the theory and experiment prove that the interference correction method proposed for NDIR multi-component gas analysis is feasible.

Movement decoupling control for two-axis fast steering mirror

NASA Astrophysics Data System (ADS)

Wang, Rui; Qiao, Yongming; Lv, Tao

2017-02-01

Based on flexure hinge and piezoelectric actuator of two-axis fast steering mirror is a complex system with time varying, uncertain and strong coupling. It is extremely difficult to achieve high precision decoupling control with the traditional PID control method. The feedback error learning method was established an inverse hysteresis model which was based inner product dynamic neural network nonlinear and no-smooth for piezo-ceramic. In order to improve the actuator high precision, a method was proposed, which was based piezo-ceramic inverse model of two dynamic neural network adaptive control. The experiment result indicated that, compared with two neural network adaptive movement decoupling control algorithm, static relative error is reduced from 4.44% to 0.30% and coupling degree is reduced from 12.71% to 0.60%, while dynamic relative error is reduced from 13.92% to 2.85% and coupling degree is reduced from 2.63% to 1.17%.

Inverse metal-assisted chemical etching produces smooth high aspect ratio InP nanostructures.

PubMed

Kim, Seung Hyun; Mohseni, Parsian K; Song, Yi; Ishihara, Tatsumi; Li, Xiuling

2015-01-14

Creating high aspect ratio (AR) nanostructures by top-down fabrication without surface damage remains challenging for III-V semiconductors. Here, we demonstrate uniform, array-based InP nanostructures with lateral dimensions as small as sub-20 nm and AR > 35 using inverse metal-assisted chemical etching (I-MacEtch) in hydrogen peroxide (H2O2) and sulfuric acid (H2SO4), a purely solution-based yet anisotropic etching method. The mechanism of I-MacEtch, in contrast to regular MacEtch, is explored through surface characterization. Unique to I-MacEtch, the sidewall etching profile is remarkably smooth, independent of metal pattern edge roughness. The capability of this simple method to create various InP nanostructures, including high AR fins, can potentially enable the aggressive scaling of InP based transistors and optoelectronic devices with better performance and at lower cost than conventional etching methods.

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

Recursive Factorization of the Inverse Overlap Matrix in Linear Scaling Quantum Molecular Dynamics Simulations

DOE PAGES

Negre, Christian F. A; Mniszewski, Susan M.; Cawkwell, Marc Jon; ...

2016-06-06

We present a reduced complexity algorithm to compute the inverse overlap factors required to solve the generalized eigenvalue problem in a quantum-based molecular dynamics (MD) simulation. Our method is based on the recursive iterative re nement of an initial guess Z of the inverse overlap matrix S. The initial guess of Z is obtained beforehand either by using an approximate divide and conquer technique or dynamically, propagated within an extended Lagrangian dynamics from previous MD time steps. With this formulation, we achieve long-term stability and energy conservation even under incomplete approximate iterative re nement of Z. Linear scaling performance ismore » obtained using numerically thresholded sparse matrix algebra based on the ELLPACK-R sparse matrix data format, which also enables e cient shared memory parallelization. As we show in this article using selfconsistent density functional based tight-binding MD, our approach is faster than conventional methods based on the direct diagonalization of the overlap matrix S for systems as small as a few hundred atoms, substantially accelerating quantum-based simulations even for molecular structures of intermediate size. For a 4,158 atom water-solvated polyalanine system we nd an average speedup factor of 122 for the computation of Z in each MD step.« less

Rayleigh wave nonlinear inversion based on the Firefly algorithm

NASA Astrophysics Data System (ADS)

Zhou, Teng-Fei; Peng, Geng-Xin; Hu, Tian-Yue; Duan, Wen-Sheng; Yao, Feng-Chang; Liu, Yi-Mou

2014-06-01

Rayleigh waves have high amplitude, low frequency, and low velocity, which are treated as strong noise to be attenuated in reflected seismic surveys. This study addresses how to identify useful shear wave velocity profile and stratigraphic information from Rayleigh waves. We choose the Firefly algorithm for inversion of surface waves. The Firefly algorithm, a new type of particle swarm optimization, has the advantages of being robust, highly effective, and allows global searching. This algorithm is feasible and has advantages for use in Rayleigh wave inversion with both synthetic models and field data. The results show that the Firefly algorithm, which is a robust and practical method, can achieve nonlinear inversion of surface waves with high resolution.

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.

Easy way to determine quantitative spatial resolution distribution for a general inverse problem

NASA Astrophysics Data System (ADS)

An, M.; Feng, M.

2013-12-01

The spatial resolution computation of a solution was nontrivial and more difficult than solving an inverse problem. Most geophysical studies, except for tomographic studies, almost uniformly neglect the calculation of a practical spatial resolution. In seismic tomography studies, a qualitative resolution length can be indicatively given via visual inspection of the restoration of a synthetic structure (e.g., checkerboard tests). An effective strategy for obtaining quantitative resolution length is to calculate Backus-Gilbert resolution kernels (also referred to as a resolution matrix) by matrix operation. However, not all resolution matrices can provide resolution length information, and the computation of resolution matrix is often a difficult problem for very large inverse problems. A new class of resolution matrices, called the statistical resolution matrices (An, 2012, GJI), can be directly determined via a simple one-parameter nonlinear inversion performed based on limited pairs of random synthetic models and their inverse solutions. The total procedure were restricted to forward/inversion processes used in the real inverse problem and were independent of the degree of inverse skill used in the solution inversion. Spatial resolution lengths can be directly given during the inversion. Tests on 1D/2D/3D model inversion demonstrated that this simple method can be at least valid for a general linear inverse problem.

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.

Variational Bayesian Inversion of Quasi-Localized Seismic Attributes for the Spatial Distribution of Geological Facies

NASA Astrophysics Data System (ADS)

Nawaz, Muhammad Atif; Curtis, Andrew

2018-04-01

We introduce a new Bayesian inversion method that estimates the spatial distribution of geological facies from attributes of seismic data, by showing how the usual probabilistic inverse problem can be solved using an optimization framework still providing full probabilistic results. Our mathematical model consists of seismic attributes as observed data, which are assumed to have been generated by the geological facies. The method infers the post-inversion (posterior) probability density of the facies plus some other unknown model parameters, from the seismic attributes and geological prior information. Most previous research in this domain is based on the localized likelihoods assumption, whereby the seismic attributes at a location are assumed to depend on the facies only at that location. Such an assumption is unrealistic because of imperfect seismic data acquisition and processing, and fundamental limitations of seismic imaging methods. In this paper, we relax this assumption: we allow probabilistic dependence between seismic attributes at a location and the facies in any neighbourhood of that location through a spatial filter. We term such likelihoods quasi-localized.

Multiband infrared inversion for low-concentration methane monitoring in a confined dust-polluted atmosphere.

PubMed

Wang, Wenzheng; Wang, Yanming; Song, Wujun; Li, Xueqin

2017-03-20

A multiband infrared diagnostic (MBID) method for methane emission monitoring in limited underground environments was presented considering the strong optical background of gas/solid attenuation. Based on spatial distribution of aerosols and complex refractive index of dust particles, forward calculations were carried out with/without methane to obtain the spectral transmittance through the participating atmosphere in a mine roadway. Considering the concurrent attenuation and absorption behavior of dust and gases, four infrared wavebands were selected to retrieve the methane concentration combined with a stochastic particle swarm optimization (SPSO) algorithm. Inversion results prove that the presented MBID method is robust and effective in identifying methane at concentrations of 0.1% or even lower with inversed relative error within 10%. Further analyses illustrate that the four selected wavebands are indispensable, and the MBID method is still valid with transmission signal disturbance in a conventional dust-polluted atmosphere under mechanized mining condition. However, the effective detection distance should be limited within 50 m to ensure inversed relative error less than 5% at 1% methane concentration.

Comparison of Inversion (“flipping”) Rates Among Different Port Designs: A Single-Center Experience

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

Etezadi, Vahid, E-mail: vahid.etezadi@umm.edu; Trerotola, Scott O., E-mail: streroto@uphs.upenn.edu

PurposeTo compare incidence of port inversion among different types of implantable venous access devices.Materials and Methods Records of patients who underwent imaging-guided subcutaneous port placement without port fixation between July 2001 and April 2015 were reviewed with use of a quality assurance database. 1930 patients with complete follow-up (death or explant) were included in the study. Collected data included date and indication for port placement, port type, venous access site, immediate and long-term complications, indication for removal, and total number of catheter days. BMI of patients with inverted ports was also calculated.Results Port inversion within the pocket was observed inmore » 18 patients (0.9%) including 7/82 (9%) of Dignity ports, 4/126 (3%) of Vaxcel plastic arm ports, 3/142 (2%) of Smartports, 2/100 (2%) of Powerports, 1/14 (7%) of Vaccess ports, and 1/1421 (0.07%) of Vortex LP ports. Among these designs, the inversion rate was significantly lower in Vortex LP ports (0.1%) (P < 0.05). There was a trend toward higher inversion rate of Dignity ports, which have a rectangular design with a relatively narrow base. Mean dwell in inverted ports was 114 days (7–580).Conclusion The incidence of port inversion without suture fixation of the port base to the pocket is extremely low. The present study shows differences in inversion incidence based on port design.Level of Evidence: Case Series, Level IV.« less

Use of the ventricular propagated excitation model in the magnetocardiographic inverse problem for reconstruction of electrophysiological properties.

PubMed

Ohyu, Shigeharu; Okamoto, Yoshiwo; Kuriki, Shinya

2002-06-01

A novel magnetocardiographic inverse method for reconstructing the action potential amplitude (APA) and the activation time (AT) on the ventricular myocardium is proposed. This method is based on the propagated excitation model, in which the excitation is propagated through the ventricle with nonuniform height of action potential. Assumption of stepwise waveform on the transmembrane potential was introduced in the model. Spatial gradient of transmembrane potential, which is defined by APA and AT distributed in the ventricular wall, is used for the computation of a current source distribution. Based on this source model, the distributions of APA and AT are inversely reconstructed from the QRS interval of magnetocardiogram (MCG) utilizing a maximum a posteriori approach. The proposed reconstruction method was tested through computer simulations. Stability of the methods with respect to measurement noise was demonstrated. When reference APA was provided as a uniform distribution, root-mean-square errors of estimated APA were below 10 mV for MCG signal-to-noise ratios greater than, or equal to, 20 dB. Low-amplitude regions located at several sites in reference APA distributions were correctly reproduced in reconstructed APA distributions. The goal of our study is to develop a method for detecting myocardial ischemia through the depression of reconstructed APA distributions.

Look-up-table approach for leaf area index retrieval from remotely sensed data based on scale information

NASA Astrophysics Data System (ADS)

Zhu, Xiaohua; Li, Chuanrong; Tang, Lingli

2018-03-01

Leaf area index (LAI) is a key structural characteristic of vegetation and plays a significant role in global change research. Several methods and remotely sensed data have been evaluated for LAI estimation. This study aimed to evaluate the suitability of the look-up-table (LUT) approach for crop LAI retrieval from Satellite Pour l'Observation de la Terre (SPOT)-5 data and establish an LUT approach for LAI inversion based on scale information. The LAI inversion result was validated by in situ LAI measurements, indicating that the LUT generated based on the PROSAIL (PROSPECT+SAIL: properties spectra + scattering by arbitrarily inclined leaves) model was suitable for crop LAI estimation, with a root mean square error (RMSE) of ˜0.31m2 / m2 and determination coefficient (R2) of 0.65. The scale effect of crop LAI was analyzed based on Taylor expansion theory, indicating that when the SPOT data aggregated by 200 × 200 pixel, the relative error is significant with 13.7%. Finally, an LUT method integrated with scale information was proposed in this article, improving the inversion accuracy with RMSE of 0.20 m2 / m2 and R2 of 0.83.

Improving Simulations of Precipitation Phase and Snowpack at a Site Subject to Cold Air Intrusions: Snoqualmie Pass, WA

NASA Astrophysics Data System (ADS)

Wayand, N. E.; Stimberis, J.; Zagrodnik, J.; Mass, C.; Lundquist, J. D.

2016-12-01

Low-level cold air from eastern Washington state often flows westward through mountain passes in the Washington Cascades, creating localized inversions and locally reducing climatological temperatures. The persistence of this inversion during a frontal passage can result in complex patterns of snow and rain that are difficult to predict. Yet, these predictions are critical to support highway avalanche control, ski resort operations, and modeling of headwater snowpack storage. In this study we used observations of precipitation phase from a disdrometer and snow depth sensors across Snoqualmie Pass, WA, to evaluate surface-air-temperature-based and mesoscale-model-based predictions of precipitation phase during the anomalously warm 2014-2015 winter. The skill of surface-based methods was greatly improved by using air temperature from a nearby higher-elevation station, which was less impacted by low-level inversions. Alternatively, we found a hybrid method that combines surface-based predictions with output from the Weather Research and Forecasting mesoscale model to have improved skill over both parent models. These results suggest that prediction of precipitation phase in mountain passes can be improved by incorporating observations or models from above the surface layer.

Experimental validation of an OSEM-type iterative reconstruction algorithm for inverse geometry computed tomography

NASA Astrophysics Data System (ADS)

David, Sabrina; Burion, Steve; Tepe, Alan; Wilfley, Brian; Menig, Daniel; Funk, Tobias

2012-03-01

Iterative reconstruction methods have emerged as a promising avenue to reduce dose in CT imaging. Another, perhaps less well-known, advance has been the development of inverse geometry CT (IGCT) imaging systems, which can significantly reduce the radiation dose delivered to a patient during a CT scan compared to conventional CT systems. Here we show that IGCT data can be reconstructed using iterative methods, thereby combining two novel methods for CT dose reduction. A prototype IGCT scanner was developed using a scanning beam digital X-ray system - an inverse geometry fluoroscopy system with a 9,000 focal spot x-ray source and small photon counting detector. 90 fluoroscopic projections or "superviews" spanning an angle of 360 degrees were acquired of an anthropomorphic phantom mimicking a 1 year-old boy. The superviews were reconstructed with a custom iterative reconstruction algorithm, based on the maximum-likelihood algorithm for transmission tomography (ML-TR). The normalization term was calculated based on flat-field data acquired without a phantom. 15 subsets were used, and a total of 10 complete iterations were performed. Initial reconstructed images showed faithful reconstruction of anatomical details. Good edge resolution and good contrast-to-noise properties were observed. Overall, ML-TR reconstruction of IGCT data collected by a bench-top prototype was shown to be viable, which may be an important milestone in the further development of inverse geometry CT.

Lebedev acceleration and comparison of different photometric models in the inversion of lightcurves for asteroids

NASA Astrophysics Data System (ADS)

Lu, Xiao-Ping; Huang, Xiang-Jie; Ip, Wing-Huen; Hsia, Chi-Hao

2018-04-01

In the lightcurve inversion process where asteroid's physical parameters such as rotational period, pole orientation and overall shape are searched, the numerical calculations of the synthetic photometric brightness based on different shape models are frequently implemented. Lebedev quadrature is an efficient method to numerically calculate the surface integral on the unit sphere. By transforming the surface integral on the Cellinoid shape model to that on the unit sphere, the lightcurve inversion process based on the Cellinoid shape model can be remarkably accelerated. Furthermore, Matlab codes of the lightcurve inversion process based on the Cellinoid shape model are available on Github for free downloading. The photometric models, i.e., the scattering laws, also play an important role in the lightcurve inversion process, although the shape variations of asteroids dominate the morphologies of the lightcurves. Derived from the radiative transfer theory, the Hapke model can describe the light reflectance behaviors from the viewpoint of physics, while there are also many empirical models in numerical applications. Numerical simulations are implemented for the comparison of the Hapke model with the other three numerical models, including the Lommel-Seeliger, Minnaert, and Kaasalainen models. The results show that the numerical models with simple function expressions can fit well with the synthetic lightcurves generated based on the Hapke model; this good fit implies that they can be adopted in the lightcurve inversion process for asteroids to improve the numerical efficiency and derive similar results to those of the Hapke model.

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

Improving waveform inversion using modified interferometric imaging condition

NASA Astrophysics Data System (ADS)

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

2017-12-01

Similar to the reverse-time migration, full waveform inversion in the time domain is a memory-intensive processing method. The computational storage size for waveform inversion mainly depends on the model size and time recording length. In general, 3D and 4D data volumes need to be saved for 2D and 3D waveform inversion gradient calculations, respectively. Even the boundary region wavefield-saving strategy creates a huge storage demand. Using the last two slices of the wavefield to reconstruct wavefields at other moments through the random boundary, avoids the need to store a large number of wavefields; however, traditional random boundary method is less effective at low frequencies. In this study, we follow a new random boundary designed to regenerate random velocity anomalies in the boundary region for each shot of each iteration. The results obtained using the random boundary condition in less illuminated areas are more seriously affected by random scattering than other areas due to the lack of coverage. In this paper, we have replaced direct correlation for computing the waveform inversion gradient by modified interferometric imaging, which enhances the continuity of the imaging path and reduces noise interference. The new imaging condition is a weighted average of extended imaging gathers can be directly used in the gradient computation. In this process, we have not changed the objective function, and the role of the imaging condition is similar to regularization. The window size for the modified interferometric imaging condition-based waveform inversion plays an important role in this process. The numerical examples show that the proposed method significantly enhances waveform inversion performance.

Improving waveform inversion using modified interferometric imaging condition

NASA Astrophysics Data System (ADS)

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

2018-02-01

Similar to the reverse-time migration, full waveform inversion in the time domain is a memory-intensive processing method. The computational storage size for waveform inversion mainly depends on the model size and time recording length. In general, 3D and 4D data volumes need to be saved for 2D and 3D waveform inversion gradient calculations, respectively. Even the boundary region wavefield-saving strategy creates a huge storage demand. Using the last two slices of the wavefield to reconstruct wavefields at other moments through the random boundary, avoids the need to store a large number of wavefields; however, traditional random boundary method is less effective at low frequencies. In this study, we follow a new random boundary designed to regenerate random velocity anomalies in the boundary region for each shot of each iteration. The results obtained using the random boundary condition in less illuminated areas are more seriously affected by random scattering than other areas due to the lack of coverage. In this paper, we have replaced direct correlation for computing the waveform inversion gradient by modified interferometric imaging, which enhances the continuity of the imaging path and reduces noise interference. The new imaging condition is a weighted average of extended imaging gathers can be directly used in the gradient computation. In this process, we have not changed the objective function, and the role of the imaging condition is similar to regularization. The window size for the modified interferometric imaging condition-based waveform inversion plays an important role in this process. The numerical examples show that the proposed method significantly enhances waveform inversion performance.

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.

Limited-memory BFGS based least-squares pre-stack Kirchhoff depth migration

NASA Astrophysics Data System (ADS)

Wu, Shaojiang; Wang, Yibo; Zheng, Yikang; Chang, Xu

2015-08-01

Least-squares migration (LSM) is a linearized inversion technique for subsurface reflectivity estimation. Compared to conventional migration algorithms, it can improve spatial resolution significantly with a few iterative calculations. There are three key steps in LSM, (1) calculate data residuals between observed data and demigrated data using the inverted reflectivity model; (2) migrate data residuals to form reflectivity gradient and (3) update reflectivity model using optimization methods. In order to obtain an accurate and high-resolution inversion result, the good estimation of inverse Hessian matrix plays a crucial role. However, due to the large size of Hessian matrix, the inverse matrix calculation is always a tough task. The limited-memory BFGS (L-BFGS) method can evaluate the Hessian matrix indirectly using a limited amount of computer memory which only maintains a history of the past m gradients (often m < 10). We combine the L-BFGS method with least-squares pre-stack Kirchhoff depth migration. Then, we validate the introduced approach by the 2-D Marmousi synthetic data set and a 2-D marine data set. The results show that the introduced method can effectively obtain reflectivity model and has a faster convergence rate with two comparison gradient methods. It might be significant for general complex subsurface imaging.

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.

An introduction of Markov chain Monte Carlo method to geochemical inverse problems: Reading melting parameters from REE abundances in abyssal peridotites

NASA Astrophysics Data System (ADS)

Liu, Boda; Liang, Yan

2017-04-01

Markov chain Monte Carlo (MCMC) simulation is a powerful statistical method in solving inverse problems that arise from a wide range of applications. In Earth sciences applications of MCMC simulations are primarily in the field of geophysics. The purpose of this study is to introduce MCMC methods to geochemical inverse problems related to trace element fractionation during mantle melting. MCMC methods have several advantages over least squares methods in deciphering melting processes from trace element abundances in basalts and mantle rocks. Here we use an MCMC method to invert for extent of melting, fraction of melt present during melting, and extent of chemical disequilibrium between the melt and residual solid from REE abundances in clinopyroxene in abyssal peridotites from Mid-Atlantic Ridge, Central Indian Ridge, Southwest Indian Ridge, Lena Trough, and American-Antarctic Ridge. We consider two melting models: one with exact analytical solution and the other without. We solve the latter numerically in a chain of melting models according to the Metropolis-Hastings algorithm. The probability distribution of inverted melting parameters depends on assumptions of the physical model, knowledge of mantle source composition, and constraints from the REE data. Results from MCMC inversion are consistent with and provide more reliable uncertainty estimates than results based on nonlinear least squares inversion. We show that chemical disequilibrium is likely to play an important role in fractionating LREE in residual peridotites during partial melting beneath mid-ocean ridge spreading centers. MCMC simulation is well suited for more complicated but physically more realistic melting problems that do not have analytical solutions.

Monte Carlo Approach for Estimating Density and Atomic Number From Dual-Energy Computed Tomography Images of Carbonate Rocks

NASA Astrophysics Data System (ADS)

Victor, Rodolfo A.; Prodanović, Maša.; Torres-Verdín, Carlos

2017-12-01

We develop a new Monte Carlo-based inversion method for estimating electron density and effective atomic number from 3-D dual-energy computed tomography (CT) core scans. The method accounts for uncertainties in X-ray attenuation coefficients resulting from the polychromatic nature of X-ray beam sources of medical and industrial scanners, in addition to delivering uncertainty estimates of inversion products. Estimation of electron density and effective atomic number from CT core scans enables direct deterministic or statistical correlations with salient rock properties for improved petrophysical evaluation; this condition is specifically important in media such as vuggy carbonates where CT resolution better captures core heterogeneity that dominates fluid flow properties. Verification tests of the inversion method performed on a set of highly heterogeneous carbonate cores yield very good agreement with in situ borehole measurements of density and photoelectric factor.

New insights into old methods for identifying causal rare variants.

PubMed

Wang, Haitian; Huang, Chien-Hsun; Lo, Shaw-Hwa; Zheng, Tian; Hu, Inchi

2011-11-29

The advance of high-throughput next-generation sequencing technology makes possible the analysis of rare variants. However, the investigation of rare variants in unrelated-individuals data sets faces the challenge of low power, and most methods circumvent the difficulty by using various collapsing procedures based on genes, pathways, or gene clusters. We suggest a new way to identify causal rare variants using the F-statistic and sliced inverse regression. The procedure is tested on the data set provided by the Genetic Analysis Workshop 17 (GAW17). After preliminary data reduction, we ranked markers according to their F-statistic values. Top-ranked markers were then subjected to sliced inverse regression, and those with higher absolute coefficients in the most significant sliced inverse regression direction were selected. The procedure yields good false discovery rates for the GAW17 data and thus is a promising method for future study on rare variants.

An inverse method for the aerodynamic design of three-dimensional aircraft engine nacelles

NASA Technical Reports Server (NTRS)

Bell, R. A.; Cedar, R. D.

1991-01-01

A fast, efficient and user friendly inverse design system for 3-D nacelles was developed. The system is a product of a 2-D inverse design method originally developed at NASA-Langley and the CFL3D analysis code which was also developed at NASA-Langley and modified for nacelle analysis. The design system uses a predictor/corrector design approach in which an analysis code is used to calculate the flow field for an initial geometry, the geometry is then modified based on the difference between the calculated and target pressures. A detailed discussion of the design method, the process of linking it to the modified CFL3D solver and its extension to 3-D is presented. This is followed by a number of examples of the use of the design system for the design of both axisymmetric and 3-D nacelles.

Structural Damage Detection Using Changes in Natural Frequencies: Theory and Applications

NASA Astrophysics Data System (ADS)

He, K.; Zhu, W. D.

2011-07-01

A vibration-based method that uses changes in natural frequencies of a structure to detect damage has advantages over conventional nondestructive tests in detecting various types of damage, including loosening of bolted joints, using minimum measurement data. Two major challenges associated with applications of the vibration-based damage detection method to engineering structures are addressed: accurate modeling of structures and the development of a robust inverse algorithm to detect damage, which are defined as the forward and inverse problems, respectively. To resolve the forward problem, new physics-based finite element modeling techniques are developed for fillets in thin-walled beams and for bolted joints, so that complex structures can be accurately modeled with a reasonable model size. To resolve the inverse problem, a logistical function transformation is introduced to convert the constrained optimization problem to an unconstrained one, and a robust iterative algorithm using a trust-region method, called the Levenberg-Marquardt method, is developed to accurately detect the locations and extent of damage. The new methodology can ensure global convergence of the iterative algorithm in solving under-determined system equations and deal with damage detection problems with relatively large modeling error and measurement noise. The vibration-based damage detection method is applied to various structures including lightning masts, a space frame structure and one of its components, and a pipeline. The exact locations and extent of damage can be detected in the numerical simulation where there is no modeling error and measurement noise. The locations and extent of damage can be successfully detected in experimental damage detection.

Subspace-based optimization method for inverse scattering problems with an inhomogeneous background medium

NASA Astrophysics Data System (ADS)

Chen, Xudong

2010-07-01

This paper proposes a version of the subspace-based optimization method to solve the inverse scattering problem with an inhomogeneous background medium where the known inhomogeneities are bounded in a finite domain. Although the background Green's function at each discrete point in the computational domain is not directly available in an inhomogeneous background scenario, the paper uses the finite element method to simultaneously obtain the Green's function at all discrete points. The essence of the subspace-based optimization method is that part of the contrast source is determined from the spectrum analysis without using any optimization, whereas the orthogonally complementary part is determined by solving a lower dimension optimization problem. This feature significantly speeds up the convergence of the algorithm and at the same time makes it robust against noise. Numerical simulations illustrate the efficacy of the proposed algorithm. The algorithm presented in this paper finds wide applications in nondestructive evaluation, such as through-wall imaging.

A developed nearly analytic discrete method for forward modeling in the frequency domain

NASA Astrophysics Data System (ADS)

Liu, Shaolin; Lang, Chao; Yang, Hui; Wang, Wenshuai

2018-02-01

High-efficiency forward modeling methods play a fundamental role in full waveform inversion (FWI). In this paper, the developed nearly analytic discrete (DNAD) method is proposed to accelerate frequency-domain forward modeling processes. We first derive the discretization of frequency-domain wave equations via numerical schemes based on the nearly analytic discrete (NAD) method to obtain a linear system. The coefficients of numerical stencils are optimized to make the linear system easier to solve and to minimize computing time. Wavefield simulation and numerical dispersion analysis are performed to compare the numerical behavior of DNAD method with that of the conventional NAD method. The results demonstrate the superiority of our proposed method. Finally, the DNAD method is implemented in frequency-domain FWI, and high-resolution inverse results are obtained.

Magnetic resonance separation imaging using a divided inversion recovery technique (DIRT).

PubMed

Goldfarb, James W

2010-04-01

The divided inversion recovery technique is an MRI separation method based on tissue T(1) relaxation differences. When tissue T(1) relaxation times are longer than the time between inversion pulses in a segmented inversion recovery pulse sequence, longitudinal magnetization does not pass through the null point. Prior to additional inversion pulses, longitudinal magnetization may have an opposite polarity. Spatial displacement of tissues in inversion recovery balanced steady-state free-precession imaging has been shown to be due to this magnetization phase change resulting from incomplete magnetization recovery. In this paper, it is shown how this phase change can be used to provide image separation. A pulse sequence parameter, the time between inversion pulses (T180), can be adjusted to provide water-fat or fluid separation. Example water-fat and fluid separation images of the head, heart, and abdomen are presented. The water-fat separation performance was investigated by comparing image intensities in short-axis divided inversion recovery technique images of the heart. Fat, blood, and fluid signal was suppressed to the background noise level. Additionally, the separation performance was not affected by main magnetic field inhomogeneities.

Non-Random Inversion Landscapes in Prokaryotic Genomes Are Shaped by Heterogeneous Selection Pressures.

PubMed

Repar, Jelena; Warnecke, Tobias

2017-08-01

Inversions are a major contributor to structural genome evolution in prokaryotes. Here, using a novel alignment-based method, we systematically compare 1,651 bacterial and 98 archaeal genomes to show that inversion landscapes are frequently biased toward (symmetric) inversions around the origin-terminus axis. However, symmetric inversion bias is not a universal feature of prokaryotic genome evolution but varies considerably across clades. At the extremes, inversion landscapes in Bacillus-Clostridium and Actinobacteria are dominated by symmetric inversions, while there is little or no systematic bias favoring symmetric rearrangements in archaea with a single origin of replication. Within clades, we find strong but clade-specific relationships between symmetric inversion bias and different features of adaptive genome architecture, including the distance of essential genes to the origin of replication and the preferential localization of genes on the leading strand. We suggest that heterogeneous selection pressures have converged to produce similar patterns of structural genome evolution across prokaryotes. © The Author 2017. Published by Oxford University Press on behalf of the Society for Molecular Biology and Evolution.

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

Solving Large-Scale Inverse Magnetostatic Problems using the Adjoint Method

PubMed Central

Bruckner, Florian; Abert, Claas; Wautischer, Gregor; Huber, Christian; Vogler, Christoph; Hinze, Michael; Suess, Dieter

2017-01-01

An efficient algorithm for the reconstruction of the magnetization state within magnetic components is presented. The occurring inverse magnetostatic problem is solved by means of an adjoint approach, based on the Fredkin-Koehler method for the solution of the forward problem. Due to the use of hybrid FEM-BEM coupling combined with matrix compression techniques the resulting algorithm is well suited for large-scale problems. Furthermore the reconstruction of the magnetization state within a permanent magnet as well as an optimal design application are demonstrated. PMID:28098851

Numerical solution of inverse scattering for near-field optics.

PubMed

Bao, Gang; Li, Peijun

2007-06-01

A novel regularized recursive linearization method is developed for a two-dimensional inverse medium scattering problem that arises in near-field optics, which reconstructs the scatterer of an inhomogeneous medium located on a substrate from data accessible through photon scanning tunneling microscopy experiments. Based on multiple frequency scattering data, the method starts from the Born approximation corresponding to weak scattering at a low frequency, and each update is obtained by continuation on the wavenumber from solutions of one forward problem and one adjoint problem of the Helmholtz equation.

Estimation of surface area concentration of workplace incidental nanoparticles based on number and mass concentrations

NASA Astrophysics Data System (ADS)

Park, J. Y.; Ramachandran, G.; Raynor, P. C.; Kim, S. W.

2011-10-01

Surface area was estimated by three different methods using number and/or mass concentrations obtained from either two or three instruments that are commonly used in the field. The estimated surface area concentrations were compared with reference surface area concentrations (SAREF) calculated from the particle size distributions obtained from a scanning mobility particle sizer and an optical particle counter (OPC). The first estimation method (SAPSD) used particle size distribution measured by a condensation particle counter (CPC) and an OPC. The second method (SAINV1) used an inversion routine based on PM1.0, PM2.5, and number concentrations to reconstruct assumed lognormal size distributions by minimizing the difference between measurements and calculated values. The third method (SAINV2) utilized a simpler inversion method that used PM1.0 and number concentrations to construct a lognormal size distribution with an assumed value of geometric standard deviation. All estimated surface area concentrations were calculated from the reconstructed size distributions. These methods were evaluated using particle measurements obtained in a restaurant, an aluminum die-casting factory, and a diesel engine laboratory. SAPSD was 0.7-1.8 times higher and SAINV1 and SAINV2 were 2.2-8 times higher than SAREF in the restaurant and diesel engine laboratory. In the die casting facility, all estimated surface area concentrations were lower than SAREF. However, the estimated surface area concentration using all three methods had qualitatively similar exposure trends and rankings to those using SAREF within a workplace. This study suggests that surface area concentration estimation based on particle size distribution (SAPSD) is a more accurate and convenient method to estimate surface area concentrations than estimation methods using inversion routines and may be feasible to use for classifying exposure groups and identifying exposure trends.

Obtaining source current density related to irregularly structured electromagnetic target field inside human body using hybrid inverse/FDTD method.

PubMed

Han, Jijun; Yang, Deqiang; Sun, Houjun; Xin, Sherman Xuegang

2017-01-01

Inverse method is inherently suitable for calculating the distribution of source current density related with an irregularly structured electromagnetic target field. However, the present form of inverse method cannot calculate complex field-tissue interactions. A novel hybrid inverse/finite-difference time domain (FDTD) method that can calculate the complex field-tissue interactions for the inverse design of source current density related with an irregularly structured electromagnetic target field is proposed. A Huygens' equivalent surface is established as a bridge to combine the inverse and FDTD method. Distribution of the radiofrequency (RF) magnetic field on the Huygens' equivalent surface is obtained using the FDTD method by considering the complex field-tissue interactions within the human body model. The obtained magnetic field distributed on the Huygens' equivalent surface is regarded as the next target. The current density on the designated source surface is derived using the inverse method. The homogeneity of target magnetic field and specific energy absorption rate are calculated to verify the proposed method.

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.

Efficient Terahertz Wide-Angle NUFFT-Based Inverse Synthetic Aperture Imaging Considering Spherical Wavefront.

PubMed

Gao, Jingkun; Deng, Bin; Qin, Yuliang; Wang, Hongqiang; Li, Xiang

2016-12-14

An efficient wide-angle inverse synthetic aperture imaging method considering the spherical wavefront effects and suitable for the terahertz band is presented. Firstly, the echo signal model under spherical wave assumption is established, and the detailed wavefront curvature compensation method accelerated by 1D fast Fourier transform (FFT) is discussed. Then, to speed up the reconstruction procedure, the fast Gaussian gridding (FGG)-based nonuniform FFT (NUFFT) is employed to focus the image. Finally, proof-of-principle experiments are carried out and the results are compared with the ones obtained by the convolution back-projection (CBP) algorithm. The results demonstrate the effectiveness and the efficiency of the presented method. This imaging method can be directly used in the field of nondestructive detection and can also be used to provide a solution for the calculation of the far-field RCSs (Radar Cross Section) of targets in the terahertz regime.

A Monte Carlo simulation based inverse propagation method for stochastic model updating

NASA Astrophysics Data System (ADS)

Bao, Nuo; Wang, Chunjie

2015-08-01

This paper presents an efficient stochastic model updating method based on statistical theory. Significant parameters have been selected implementing the F-test evaluation and design of experiments, and then the incomplete fourth-order polynomial response surface model (RSM) has been developed. Exploiting of the RSM combined with Monte Carlo simulation (MCS), reduces the calculation amount and the rapid random sampling becomes possible. The inverse uncertainty propagation is given by the equally weighted sum of mean and covariance matrix objective functions. The mean and covariance of parameters are estimated synchronously by minimizing the weighted objective function through hybrid of particle-swarm and Nelder-Mead simplex optimization method, thus the better correlation between simulation and test is achieved. Numerical examples of a three degree-of-freedom mass-spring system under different conditions and GARTEUR assembly structure validated the feasibility and effectiveness of the proposed method.

Distributed Cooperative Optimal Control for Multiagent Systems on Directed Graphs: An Inverse Optimal Approach.

PubMed

Zhang, Huaguang; Feng, Tao; Yang, Guang-Hong; Liang, Hongjing

2015-07-01

In this paper, the inverse optimal approach is employed to design distributed consensus protocols that guarantee consensus and global optimality with respect to some quadratic performance indexes for identical linear systems on a directed graph. The inverse optimal theory is developed by introducing the notion of partial stability. As a result, the necessary and sufficient conditions for inverse optimality are proposed. By means of the developed inverse optimal theory, the necessary and sufficient conditions are established for globally optimal cooperative control problems on directed graphs. Basic optimal cooperative design procedures are given based on asymptotic properties of the resulting optimal distributed consensus protocols, and the multiagent systems can reach desired consensus performance (convergence rate and damping rate) asymptotically. Finally, two examples are given to illustrate the effectiveness of the proposed methods.

Probing numerical Laplace inversion methods for two and three-site molecular exchange between interconnected pore structures.

PubMed

Silletta, Emilia V; Franzoni, María B; Monti, Gustavo A; Acosta, Rodolfo H

2018-01-01

Two-dimension (2D) Nuclear Magnetic Resonance relaxometry experiments are a powerful tool extensively used to probe the interaction among different pore structures, mostly in inorganic systems. The analysis of the collected experimental data generally consists of a 2D numerical inversion of time-domain data where T 2 -T 2 maps are generated. Through the years, different algorithms for the numerical inversion have been proposed. In this paper, two different algorithms for numerical inversion are tested and compared under different conditions of exchange dynamics; the method based on Butler-Reeds-Dawson (BRD) algorithm and the fast-iterative shrinkage-thresholding algorithm (FISTA) method. By constructing a theoretical model, the algorithms were tested for a two- and three-site porous media, varying the exchange rates parameters, the pore sizes and the signal to noise ratio. In order to test the methods under realistic experimental conditions, a challenging organic system was chosen. The molecular exchange rates of water confined in hierarchical porous polymeric networks were obtained, for a two- and three-site porous media. Data processed with the BRD method was found to be accurate only under certain conditions of the exchange parameters, while data processed with the FISTA method is precise for all the studied parameters, except when SNR conditions are extreme. Copyright © 2017 Elsevier Inc. All rights reserved.

Subglottal Impedance-Based Inverse Filtering of Voiced Sounds Using Neck Surface Acceleration

PubMed Central

Zañartu, Matías; Ho, Julio C.; Mehta, Daryush D.; Hillman, Robert E.; Wodicka, George R.

2014-01-01

A model-based inverse filtering scheme is proposed for an accurate, non-invasive estimation of the aerodynamic source of voiced sounds at the glottis. The approach, referred to as subglottal impedance-based inverse filtering (IBIF), takes as input the signal from a lightweight accelerometer placed on the skin over the extrathoracic trachea and yields estimates of glottal airflow and its time derivative, offering important advantages over traditional methods that deal with the supraglottal vocal tract. The proposed scheme is based on mechano-acoustic impedance representations from a physiologically-based transmission line model and a lumped skin surface representation. A subject-specific calibration protocol is used to account for individual adjustments of subglottal impedance parameters and mechanical properties of the skin. Preliminary results for sustained vowels with various voice qualities show that the subglottal IBIF scheme yields comparable estimates with respect to current aerodynamics-based methods of clinical vocal assessment. A mean absolute error of less than 10% was observed for two glottal airflow measures –maximum flow declination rate and amplitude of the modulation component– that have been associated with the pathophysiology of some common voice disorders caused by faulty and/or abusive patterns of vocal behavior (i.e., vocal hyperfunction). The proposed method further advances the ambulatory assessment of vocal function based on the neck acceleration signal, that previously have been limited to the estimation of phonation duration, loudness, and pitch. Subglottal IBIF is also suitable for other ambulatory applications in speech communication, in which further evaluation is underway. PMID:25400531

Inverts permittivity and conductivity with structural constraint in GPR FWI based on truncated Newton method

NASA Astrophysics Data System (ADS)

Ren, Qianci

2018-04-01

Full waveform inversion (FWI) of ground penetrating radar (GPR) is a promising technique to quantitatively evaluate the permittivity and conductivity of near subsurface. However, these two parameters are simultaneously inverted in the GPR FWI, increasing the difficulty to obtain accurate inversion results for both parameters. In this study, I present a structural constrained GPR FWI procedure to jointly invert the two parameters, aiming to force a structural relationship between permittivity and conductivity in the process of model reconstruction. The structural constraint is enforced by a cross-gradient function. In this procedure, the permittivity and conductivity models are inverted alternately at each iteration and updated with hierarchical frequency components in the frequency domain. The joint inverse problem is solved by the truncated Newton method which considering the effect of Hessian operator and using the approximated solution of Newton equation to be the perturbation model in the updating process. The joint inversion procedure is tested by three synthetic examples. The results show that jointly inverting permittivity and conductivity in GPR FWI effectively increases the structural similarities between the two parameters, corrects the structures of parameter models, and significantly improves the accuracy of conductivity model, resulting in a better inversion result than the individual inversion.

Improved resistivity imaging of groundwater solute plumes using POD-based inversion

NASA Astrophysics Data System (ADS)

Oware, E. K.; Moysey, S. M.; Khan, T.

2012-12-01

We propose a new approach for enforcing physics-based regularization in electrical resistivity imaging (ERI) problems. The approach utilizes a basis-constrained inversion where an optimal set of basis vectors is extracted from training data by Proper Orthogonal Decomposition (POD). The key aspect of the approach is that Monte Carlo simulation of flow and transport is used to generate a training dataset, thereby intrinsically capturing the physics of the underlying flow and transport models in a non-parametric form. POD allows for these training data to be projected onto a subspace of the original domain, resulting in the extraction of a basis for the inversion that captures characteristics of the groundwater flow and transport system, while simultaneously allowing for dimensionality reduction of the original problem in the projected space We use two different synthetic transport scenarios in heterogeneous media to illustrate how the POD-based inversion compares with standard Tikhonov and coupled inversion. The first scenario had a single source zone leading to a unimodal solute plume (synthetic #1), whereas, the second scenario had two source zones that produced a bimodal plume (synthetic #2). For both coupled inversion and the POD approach, the conceptual flow and transport model used considered only a single source zone for both scenarios. Results were compared based on multiple metrics (concentration root-mean square error (RMSE), peak concentration, and total solute mass). In addition, results for POD inversion based on 3 different data densities (120, 300, and 560 data points) and varying number of selected basis images (100, 300, and 500) were compared. For synthetic #1, we found that all three methods provided qualitatively reasonable reproduction of the true plume. Quantitatively, the POD inversion performed best overall for each metric considered. Moreover, since synthetic #1 was consistent with the conceptual transport model, a small number of basis vectors (100) contained enough a priori information to constrain the inversion. Increasing the amount of data or number of selected basis images did not translate into significant improvement in imaging results. For synthetic #2, the RMSE and error in total mass were lowest for the POD inversion. However, the peak concentration was significantly overestimated by the POD approach. Regardless, the POD-based inversion was the only technique that could capture the bimodality of the plume in the reconstructed image, thus providing critical information that could be used to reconceptualize the transport problem. We also found that, in the case of synthetic #2, increasing the number of resistivity measurements and the number of selected basis vectors allowed for significant improvements in the reconstructed images.

Simultaneous Retrieval of Aerosol and Surface Optical Properties from Combined Airborne- and Ground-Based Direct and Diffuse Radiometric Measurements

NASA Technical Reports Server (NTRS)

Gatebe, C. K.; Dubovik, O.; King, M. D.; Sinyuk, A.

2010-01-01

This paper presents a new method for simultaneously retrieving aerosol and surface reflectance properties from combined airborne and ground-based direct and diffuse radiometric measurements. The method is based on the standard Aerosol Robotic Network (AERONET) method for retrieving aerosol size distribution, complex index of refraction, and single scattering albedo, but modified to retrieve aerosol properties in two layers, below and above the aircraft, and parameters on surface optical properties from combined datasets (Cloud Absorption Radiometer (CAR) and AERONET data). A key advantage of this method is the inversion of all available spectral and angular data at the same time, while accounting for the influence of noise in the inversion procedure using statistical optimization. The wide spectral (0.34-2.30 m) and angular range (180 ) of the CAR instrument, combined with observations from an AERONET sunphotometer, provide sufficient measurement constraints for characterizing aerosol and surface properties with minimal assumptions. The robustness of the method was tested on observations made during four different field campaigns: (a) the Southern African Regional Science Initiative 2000 over Mongu, Zambia, (b) the Intercontinental Transport Experiment-Phase B over Mexico City, Mexico (c) Cloud and Land Surface Interaction Campaign over the Atmospheric Radiation Measurement (ARM) Central Facility, Oklahoma, USA, and (d) the Arctic Research of the Composition of the Troposphere from Aircraft and Satellites (ARCTAS) over Elson Lagoon in Barrow, Alaska, USA. The four areas are dominated by different surface characteristics and aerosol types, and therefore provide good test cases for the new inversion method.

Synchronization of spin-transfer torque oscillators by spin pumping, inverse spin Hall, and spin Hall effects

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

Elyasi, Mehrdad; Bhatia, Charanjit S.; Yang, Hyunsoo, E-mail: eleyang@nus.edu.sg

2015-02-14

We have proposed a method to synchronize multiple spin-transfer torque oscillators based on spin pumping, inverse spin Hall, and spin Hall effects. The proposed oscillator system consists of a series of nano-magnets in junction with a normal metal with high spin-orbit coupling, and an accumulative feedback loop. We conduct simulations to demonstrate the effect of modulated charge currents in the normal metal due to spin pumping from each nano-magnet. We show that the interplay between the spin Hall effect and inverse spin Hall effect results in synchronization of the nano-magnets.

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.

An iterative solver for the 3D Helmholtz equation

NASA Astrophysics Data System (ADS)

Belonosov, Mikhail; Dmitriev, Maxim; Kostin, Victor; Neklyudov, Dmitry; Tcheverda, Vladimir

2017-09-01

We develop a frequency-domain iterative solver for numerical simulation of acoustic waves in 3D heterogeneous media. It is based on the application of a unique preconditioner to the Helmholtz equation that ensures convergence for Krylov subspace iteration methods. Effective inversion of the preconditioner involves the Fast Fourier Transform (FFT) and numerical solution of a series of boundary value problems for ordinary differential equations. Matrix-by-vector multiplication for iterative inversion of the preconditioned matrix involves inversion of the preconditioner and pointwise multiplication of grid functions. Our solver has been verified by benchmarking against exact solutions and a time-domain solver.

Importance of a 3D forward modeling tool for surface wave analysis methods

NASA Astrophysics Data System (ADS)

Pageot, Damien; Le Feuvre, Mathieu; Donatienne, Leparoux; Philippe, Côte; Yann, Capdeville

2016-04-01

Since a few years, seismic surface waves analysis methods (SWM) have been widely developed and tested in the context of subsurface characterization and have demonstrated their effectiveness for sounding and monitoring purposes, e.g., high-resolution tomography of the principal geological units of California or real time monitoring of the Piton de la Fournaise volcano. Historically, these methods are mostly developed under the assumption of semi-infinite 1D layered medium without topography. The forward modeling is generally based on Thomson-Haskell matrix based modeling algorithm and the inversion is driven by Monte-Carlo sampling. Given their efficiency, SWM have been transfered to several scale of which civil engineering structures in order to, e.g., determine the so-called V s30 parameter or assess other critical constructional parameters in pavement engineering. However, at this scale, many structures may often exhibit 3D surface variations which drastically limit the efficiency of SWM application. Indeed, even in the case of an homogeneous structure, 3D geometry can bias the dispersion diagram of Rayleigh waves up to obtain discontinuous phase velocity curves which drastically impact the 1D mean velocity model obtained from dispersion inversion. Taking advantages of high-performance computing center accessibility and wave propagation modeling algorithm development, it is now possible to consider the use of a 3D elastic forward modeling algorithm instead of Thomson-Haskell method in the SWM inversion process. We use a parallelized 3D elastic modeling code based on the spectral element method which allows to obtain accurate synthetic data with very low numerical dispersion and a reasonable numerical cost. In this study, we choose dike embankments as an illustrative example. We first show that their longitudinal geometry may have a significant effect on dispersion diagrams of Rayleigh waves. Then, we demonstrate the necessity of 3D elastic modeling as a forward problem for the inversion of dispersion curves.

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.

An adjoint-based simultaneous estimation method of the asthenosphere's viscosity and afterslip using a fast and scalable finite-element adjoint solver

NASA Astrophysics Data System (ADS)

Agata, Ryoichiro; Ichimura, Tsuyoshi; Hori, Takane; Hirahara, Kazuro; Hashimoto, Chihiro; Hori, Muneo

2018-04-01

The simultaneous estimation of the asthenosphere's viscosity and coseismic slip/afterslip is expected to improve largely the consistency of the estimation results to observation data of crustal deformation collected in widely spread observation points, compared to estimations of slips only. Such an estimate can be formulated as a non-linear inverse problem of material properties of viscosity and input force that is equivalent to fault slips based on large-scale finite-element (FE) modeling of crustal deformation, in which the degree of freedom is in the order of 109. We formulated and developed a computationally efficient adjoint-based estimation method for this inverse problem, together with a fast and scalable FE solver for the associated forward and adjoint problems. In a numerical experiment that imitates the 2011 Tohoku-Oki earthquake, the advantage of the proposed method is confirmed by comparing the estimated results with those obtained using simplified estimation methods. The computational cost required for the optimization shows that the proposed method enabled the targeted estimation to be completed with moderate amount of computational resources.

Bio-Optics Based Sensation Imaging for Breast Tumor Detection Using Tissue Characterization

PubMed Central

Lee, Jong-Ha; Kim, Yoon Nyun; Park, Hee-Jun

2015-01-01

The tissue inclusion parameter estimation method is proposed to measure the stiffness as well as geometric parameters. The estimation is performed based on the tactile data obtained at the surface of the tissue using an optical tactile sensation imaging system (TSIS). A forward algorithm is designed to comprehensively predict the tactile data based on the mechanical properties of tissue inclusion using finite element modeling (FEM). This forward information is used to develop an inversion algorithm that will be used to extract the size, depth, and Young's modulus of a tissue inclusion from the tactile data. We utilize the artificial neural network (ANN) for the inversion algorithm. The proposed estimation method was validated by a realistic tissue phantom with stiff inclusions. The experimental results showed that the proposed estimation method can measure the size, depth, and Young's modulus of a tissue inclusion with 0.58%, 3.82%, and 2.51% relative errors, respectively. The obtained results prove that the proposed method has potential to become a useful screening and diagnostic method for breast cancer. PMID:25785306

Towards adjoint-based inversion for rheological parameters in nonlinear viscous mantle flow

NASA Astrophysics Data System (ADS)

Worthen, Jennifer; Stadler, Georg; Petra, Noemi; Gurnis, Michael; Ghattas, Omar

2014-09-01

We address the problem of inferring mantle rheological parameter fields from surface velocity observations and instantaneous nonlinear mantle flow models. We formulate this inverse problem as an infinite-dimensional nonlinear least squares optimization problem governed by nonlinear Stokes equations. We provide expressions for the gradient of the cost functional of this optimization problem with respect to two spatially-varying rheological parameter fields: the viscosity prefactor and the exponent of the second invariant of the strain rate tensor. Adjoint (linearized) Stokes equations, which are characterized by a 4th order anisotropic viscosity tensor, facilitates efficient computation of the gradient. A quasi-Newton method for the solution of this optimization problem is presented, which requires the repeated solution of both nonlinear forward Stokes and linearized adjoint Stokes equations. For the solution of the nonlinear Stokes equations, we find that Newton’s method is significantly more efficient than a Picard fixed point method. Spectral analysis of the inverse operator given by the Hessian of the optimization problem reveals that the numerical eigenvalues collapse rapidly to zero, suggesting a high degree of ill-posedness of the inverse problem. To overcome this ill-posedness, we employ Tikhonov regularization (favoring smooth parameter fields) or total variation (TV) regularization (favoring piecewise-smooth parameter fields). Solution of two- and three-dimensional finite element-based model inverse problems show that a constant parameter in the constitutive law can be recovered well from surface velocity observations. Inverting for a spatially-varying parameter field leads to its reasonable recovery, in particular close to the surface. When inferring two spatially varying parameter fields, only an effective viscosity field and the total viscous dissipation are recoverable. Finally, a model of a subducting plate shows that a localized weak zone at the plate boundary can be partially recovered, especially with TV regularization.

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

Confidence intervals for single-case effect size measures based on randomization test inversion.

PubMed

Michiels, Bart; Heyvaert, Mieke; Meulders, Ann; Onghena, Patrick

2017-02-01

In the current paper, we present a method to construct nonparametric confidence intervals (CIs) for single-case effect size measures in the context of various single-case designs. We use the relationship between a two-sided statistical hypothesis test at significance level α and a 100 (1 - α) % two-sided CI to construct CIs for any effect size measure θ that contain all point null hypothesis θ values that cannot be rejected by the hypothesis test at significance level α. This method of hypothesis test inversion (HTI) can be employed using a randomization test as the statistical hypothesis test in order to construct a nonparametric CI for θ. We will refer to this procedure as randomization test inversion (RTI). We illustrate RTI in a situation in which θ is the unstandardized and the standardized difference in means between two treatments in a completely randomized single-case design. Additionally, we demonstrate how RTI can be extended to other types of single-case designs. Finally, we discuss a few challenges for RTI as well as possibilities when using the method with other effect size measures, such as rank-based nonoverlap indices. Supplementary to this paper, we provide easy-to-use R code, which allows the user to construct nonparametric CIs according to the proposed method.

SORTAN: a Unix program for calculation and graphical presentation of fault slip as induced by stresses

NASA Astrophysics Data System (ADS)

Pascal, Christophe

2004-04-01

Stress inversion programs are nowadays frequently used in tectonic analysis. The purpose of this family of programs is to reconstruct the stress tensor characteristics from fault slip data acquired in the field or derived from earthquake focal mechanisms (i.e. inverse methods). Until now, little attention has been paid to direct methods (i.e. to determine fault slip directions from an inferred stress tensor). During the 1990s, the fast increase in resolution in 3D seismic reflection techniques made it possible to determine the geometry of subsurface faults with a satisfactory accuracy but not to determine precisely their kinematics. This recent improvement allows the use of direct methods. A computer program, namely SORTAN, is introduced. The program is highly portable on Unix platforms, straightforward to install and user-friendly. The computation is based on classical stress-fault slip relationships and allows for fast treatment of a set of faults and graphical presentation of the results (i.e. slip directions). In addition, the SORTAN program permits one to test the sensitivity of the results to input uncertainties. It is a complementary tool to classical stress inversion methods and can be used to check the mechanical consistency and the limits of structural interpretations based upon 3D seismic reflection surveys.

Computational inverse methods of heat source in fatigue damage problems

NASA Astrophysics Data System (ADS)

Chen, Aizhou; Li, Yuan; Yan, Bo

2018-04-01

Fatigue dissipation energy is the research focus in field of fatigue damage at present. It is a new idea to solve the problem of calculating fatigue dissipation energy by introducing inverse method of heat source into parameter identification of fatigue dissipation energy model. This paper introduces the research advances on computational inverse method of heat source and regularization technique to solve inverse problem, as well as the existing heat source solution method in fatigue process, prospects inverse method of heat source applying in fatigue damage field, lays the foundation for further improving the effectiveness of fatigue dissipation energy rapid prediction.

Discrete Inverse and State Estimation Problems

NASA Astrophysics Data System (ADS)

Wunsch, Carl

2006-06-01

The problems of making inferences about the natural world from noisy observations and imperfect theories occur in almost all scientific disciplines. This book addresses these problems using examples taken from geophysical fluid dynamics. It focuses on discrete formulations, both static and time-varying, known variously as inverse, state estimation or data assimilation problems. Starting with fundamental algebraic and statistical ideas, the book guides the reader through a range of inference tools including the singular value decomposition, Gauss-Markov and minimum variance estimates, Kalman filters and related smoothers, and adjoint (Lagrange multiplier) methods. The final chapters discuss a variety of practical applications to geophysical flow problems. Discrete Inverse and State Estimation Problems is an ideal introduction to the topic for graduate students and researchers in oceanography, meteorology, climate dynamics, and geophysical fluid dynamics. It is also accessible to a wider scientific audience; the only prerequisite is an understanding of linear algebra. Provides a comprehensive introduction to discrete methods of inference from incomplete information Based upon 25 years of practical experience using real data and models Develops sequential and whole-domain analysis methods from simple least-squares Contains many examples and problems, and web-based support through MIT opencourseware

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).

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.

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.

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.

Elastic Cherenkov effects in transversely isotropic soft materials-II: Ex vivo and in vivo experiments

NASA Astrophysics Data System (ADS)

Li, Guo-Yang; He, Qiong; Qian, Lin-Xue; Geng, Huiying; Liu, Yanlin; Yang, Xue-Yi; Luo, Jianwen; Cao, Yanping

2016-09-01

In part I of this study, we investigated the elastic Cherenkov effect (ECE) in an incompressible transversely isotropic (TI) soft solid using a combined theoretical and computational approach, based on which an inverse method has been proposed to measure both the anisotropic and hyperelastic parameters of TI soft tissues. In this part, experiments were carried out to validate the inverse method and demonstrate its usefulness in practical measurements. We first performed ex vivo experiments on bovine skeletal muscles. Not only the shear moduli along and perpendicular to the direction of muscle fibers but also the elastic modulus EL and hyperelastic parameter c2 were determined. We next carried out tensile tests to determine EL, which was compared with the value obtained using the shear wave elastography method. Furthermore, we conducted in vivo experiments on the biceps brachii and gastrocnemius muscles of ten healthy volunteers. To the best of our knowledge, this study represents the first attempt to determine EL of human muscles using the dynamic elastography method and inverse analysis. The significance of our method and its potential for clinical use are discussed.

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.

Geoelectrical characterization by joint inversion of VES/TEM in Paraná basin, Brazil

NASA Astrophysics Data System (ADS)

Bortolozo, C. A.; Couto, M. A.; Almeida, E. R.; Porsani, J. L.; Santos, F. M.

2012-12-01

For many years electrical (DC) and transient electromagnetic (TEM) soundings have been used in a great number of environmental, hydrological and mining exploration studies. The data of both methods are interpreted usually by individual 1D models resulting in many cases in ambiguous models. This can be explained by how the two different methodologies sample the subsurface. The vertical electrical sounding (VES) is good on marking very resistive structures, while the transient electromagnetic sounding (TEM) is very sensitive to map conductive structures. Another characteristic is that VES is more sensitive to shallow structures, while TEM soundings can reach deeper structures. A Matlab program for joint inversion of VES and TEM soundings, by using CRS algorithm was developed aiming explore the best of the both methods. Initially, the algorithm was tested with synthetic data and after it was used to invert experimental data from Paraná sedimentary basin. We present the results of a re-interpretation of 46 VES/TEM soundings data set acquired in Bebedouro region in São Paulo State - Brazil. The previous interpretation was based in geoelectrical models obtained by single inversion of the VES and TEM soundings. In this work we present the results with single inversion of VES and TEM sounding inverted by the Curupira Program and a new interpretation based in the joint inversion of both methodologies. The goal is increase the accuracy in determining the underground structures. As a result a new geoelectrical model of the region is obtained.

Comparing Balance and Inverse Methods on Learning Conceptual and Procedural Knowledge in Equation Solving: A Cognitive Load Perspective

ERIC Educational Resources Information Center

Ngu, Bing Hiong; Phan, Huy Phuong

2016-01-01

We examined the use of balance and inverse methods in equation solving. The main difference between the balance and inverse methods lies in the operational line (e.g. +2 on both sides vs -2 becomes +2). Differential element interactivity favours the inverse method because the interaction between elements occurs on both sides of the equation for…

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.

Geophysical approaches to inverse problems: A methodological comparison. Part 1: A Posteriori approach

NASA Technical Reports Server (NTRS)

Seidman, T. I.; Munteanu, M. J.

1979-01-01

The relationships of a variety of general computational methods (and variances) for treating illposed problems such as geophysical inverse problems are considered. Differences in approach and interpretation based on varying assumptions as to, e.g., the nature of measurement uncertainties are discussed along with the factors to be considered in selecting an approach. The reliability of the results of such computation is addressed.

Viscoelastic property identification from waveform reconstruction

NASA Astrophysics Data System (ADS)

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

2002-05-01

An inverse method is proposed for the determination of the viscoelastic properties of material plates from the plane-wave transmitted acoustic field. Innovations lie in a two-step inversion scheme based on the well-known maximum-likelihood principle with an analytic signal formulation. In addition, establishing the analytical formulations of the plate transmission coefficient we implement an efficient and slightly noise-sensitive process suited to both very thin plates and strongly dispersive media.

A Sparsity-based Framework for Resolution Enhancement in Optical Fault Analysis of Integrated Circuits

DTIC Science & Technology

2015-01-01

for IC fault detection . This section provides background information on inversion methods. Conventional inversion techniques and their shortcomings are...physical techniques, electron beam imaging/analysis, ion beam techniques, scanning probe techniques. Electrical tests are used to detect faults in 13 an...hand, there is also the second harmonic technique through which duty cycle degradation faults are detected by collecting the magnitude and the phase of

Interpretation of deep directional resistivity measurements acquired in high-angle and horizontal wells using 3-D inversion

NASA Astrophysics Data System (ADS)

Puzyrev, Vladimir; Torres-Verdín, Carlos; Calo, Victor

2018-05-01

The interpretation of resistivity measurements acquired in high-angle and horizontal wells is a critical technical problem in formation evaluation. We develop an efficient parallel 3-D inversion method to estimate the spatial distribution of electrical resistivity in the neighbourhood of a well from deep directional electromagnetic induction measurements. The methodology places no restriction on the spatial distribution of the electrical resistivity around arbitrary well trajectories. The fast forward modelling of triaxial induction measurements performed with multiple transmitter-receiver configurations employs a parallel direct solver. The inversion uses a pre-conditioned gradient-based method whose accuracy is improved using the Wolfe conditions to estimate optimal step lengths at each iteration. The large transmitter-receiver offsets, used in the latest generation of commercial directional resistivity tools, improve the depth of investigation to over 30 m from the wellbore. Several challenging synthetic examples confirm the feasibility of the full 3-D inversion-based interpretations for these distances, hence enabling the integration of resistivity measurements with seismic amplitude data to improve the forecast of the petrophysical and fluid properties. Employing parallel direct solvers for the triaxial induction problems allows for large reductions in computational effort, thereby opening the possibility to invert multiposition 3-D data in practical CPU times.

Nonlinear Rayleigh wave inversion based on the shuffled frog-leaping algorithm

NASA Astrophysics Data System (ADS)

Sun, Cheng-Yu; Wang, Yan-Yan; Wu, Dun-Shi; Qin, Xiao-Jun

2017-12-01

At present, near-surface shear wave velocities are mainly calculated through Rayleigh wave dispersion-curve inversions in engineering surface investigations, but the required calculations pose a highly nonlinear global optimization problem. In order to alleviate the risk of falling into a local optimal solution, this paper introduces a new global optimization method, the shuffle frog-leaping algorithm (SFLA), into the Rayleigh wave dispersion-curve inversion process. SFLA is a swarm-intelligence-based algorithm that simulates a group of frogs searching for food. It uses a few parameters, achieves rapid convergence, and is capability of effective global searching. In order to test the reliability and calculation performance of SFLA, noise-free and noisy synthetic datasets were inverted. We conducted a comparative analysis with other established algorithms using the noise-free dataset, and then tested the ability of SFLA to cope with data noise. Finally, we inverted a real-world example to examine the applicability of SFLA. Results from both synthetic and field data demonstrated the effectiveness of SFLA in the interpretation of Rayleigh wave dispersion curves. We found that SFLA is superior to the established methods in terms of both reliability and computational efficiency, so it offers great potential to improve our ability to solve geophysical inversion problems.

The inverse problem of acoustic wave scattering by an air-saturated poroelastic cylinder.

PubMed

Ogam, Erick; Fellah, Z E A; Baki, Paul

2013-03-01

The efficient use of plastic foams in a diverse range of structural applications like in noise reduction, cushioning, and sleeping mattresses requires detailed characterization of their permeability and deformation (load-bearing) behavior. The elastic moduli and airflow resistance properties of foams are often measured using two separate techniques, one employing mechanical vibration methods and the other, flow rates of fluids based on fluid mechanics technology, respectively. A multi-parameter inverse acoustic scattering problem to recover airflow resistivity (AR) and mechanical properties of an air-saturated foam cylinder is solved. A wave-fluid saturated poroelastic structure interaction model based on the modified Biot theory and plane-wave decomposition using orthogonal cylindrical functions is employed to solve the inverse problem. The solutions to the inverse problem are obtained by constructing the objective functional given by the total square of the difference between predictions from the model and scattered acoustic field data acquired in an anechoic chamber. The value of the recovered AR is in good agreement with that of a slab sample cut from the cylinder and characterized using a method employing low frequency transmitted and reflected acoustic waves in a long waveguide developed by Fellah et al. [Rev. Sci. Instrum. 78(11), 114902 (2007)].

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.

Statistical methods for incomplete data: Some results on model misspecification.

PubMed

McIsaac, Michael; Cook, R J

2017-02-01

Inverse probability weighted estimating equations and multiple imputation are two of the most studied frameworks for dealing with incomplete data in clinical and epidemiological research. We examine the limiting behaviour of estimators arising from inverse probability weighted estimating equations, augmented inverse probability weighted estimating equations and multiple imputation when the requisite auxiliary models are misspecified. We compute limiting values for settings involving binary responses and covariates and illustrate the effects of model misspecification using simulations based on data from a breast cancer clinical trial. We demonstrate that, even when both auxiliary models are misspecified, the asymptotic biases of double-robust augmented inverse probability weighted estimators are often smaller than the asymptotic biases of estimators arising from complete-case analyses, inverse probability weighting or multiple imputation. We further demonstrate that use of inverse probability weighting or multiple imputation with slightly misspecified auxiliary models can actually result in greater asymptotic bias than the use of naïve, complete case analyses. These asymptotic results are shown to be consistent with empirical results from simulation studies.

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.

Objectified quantification of uncertainties in Bayesian atmospheric inversions

NASA Astrophysics Data System (ADS)

Berchet, A.; Pison, I.; Chevallier, F.; Bousquet, P.; Bonne, J.-L.; Paris, J.-D.

2015-05-01

Classical Bayesian atmospheric inversions process atmospheric observations and prior emissions, the two being connected by an observation operator picturing mainly the atmospheric transport. These inversions rely on prescribed errors in the observations, the prior emissions and the observation operator. When data pieces are sparse, inversion results are very sensitive to the prescribed error distributions, which are not accurately known. The classical Bayesian framework experiences difficulties in quantifying the impact of mis-specified error distributions on the optimized fluxes. In order to cope with this issue, we rely on recent research results to enhance the classical Bayesian inversion framework through a marginalization on a large set of plausible errors that can be prescribed in the system. The marginalization consists in computing inversions for all possible error distributions weighted by the probability of occurrence of the error distributions. The posterior distribution of the fluxes calculated by the marginalization is not explicitly describable. As a consequence, we carry out a Monte Carlo sampling based on an approximation of the probability of occurrence of the error distributions. This approximation is deduced from the well-tested method of the maximum likelihood estimation. Thus, the marginalized inversion relies on an automatic objectified diagnosis of the error statistics, without any prior knowledge about the matrices. It robustly accounts for the uncertainties on the error distributions, contrary to what is classically done with frozen expert-knowledge error statistics. Some expert knowledge is still used in the method for the choice of an emission aggregation pattern and of a sampling protocol in order to reduce the computation cost. The relevance and the robustness of the method is tested on a case study: the inversion of methane surface fluxes at the mesoscale with virtual observations on a realistic network in Eurasia. Observing system simulation experiments are carried out with different transport patterns, flux distributions and total prior amounts of emitted methane. The method proves to consistently reproduce the known "truth" in most cases, with satisfactory tolerance intervals. Additionally, the method explicitly provides influence scores and posterior correlation matrices. An in-depth interpretation of the inversion results is then possible. The more objective quantification of the influence of the observations on the fluxes proposed here allows us to evaluate the impact of the observation network on the characterization of the surface fluxes. The explicit correlations between emission aggregates reveal the mis-separated regions, hence the typical temporal and spatial scales the inversion can analyse. These scales are consistent with the chosen aggregation patterns.

Assessing performance of flaw characterization methods through uncertainty propagation

NASA Astrophysics Data System (ADS)

Miorelli, R.; Le Bourdais, F.; Artusi, X.

2018-04-01

In this work, we assess the inversion performance in terms of crack characterization and localization based on synthetic signals associated to ultrasonic and eddy current physics. More precisely, two different standard iterative inversion algorithms are used to minimize the discrepancy between measurements (i.e., the tested data) and simulations. Furthermore, in order to speed up the computational time and get rid of the computational burden often associated to iterative inversion algorithms, we replace the standard forward solver by a suitable metamodel fit on a database built offline. In a second step, we assess the inversion performance by adding uncertainties on a subset of the database parameters and then, through the metamodel, we propagate these uncertainties within the inversion procedure. The fast propagation of uncertainties enables efficiently evaluating the impact due to the lack of knowledge on some parameters employed to describe the inspection scenarios, which is a situation commonly encountered in the industrial NDE context.

Determining which phenotypes underlie a pleiotropic signal

PubMed Central

Majumdar, Arunabha; Haldar, Tanushree; Witte, John S.

2016-01-01

Discovering pleiotropic loci is important to understand the biological basis of seemingly distinct phenotypes. Most methods for assessing pleiotropy only test for the overall association between genetic variants and multiple phenotypes. To determine which specific traits are pleiotropic, we evaluate via simulation and application three different strategies. The first is model selection techniques based on the inverse regression of genotype on phenotypes. The second is a subset-based meta-analysis ASSET [Bhattacharjee et al., 2012], which provides an optimal subset of non-null traits. And the third is a modified Benjamini-Hochberg (B-H) procedure of controlling the expected false discovery rate [Benjamini and Hochberg, 1995] in the framework of phenome-wide association study. From our simulations we see that an inverse regression based approach MultiPhen [O’Reilly et al., 2012] is more powerful than ASSET for detecting overall pleiotropic association, except for when all the phenotypes are associated and have genetic effects in the same direction. For determining which specific traits are pleiotropic, the modified B-H procedure performs consistently better than the other two methods. The inverse regression based selection methods perform competitively with the modified B-H procedure only when the phenotypes are weakly correlated. The efficiency of ASSET is observed to lie below and in between the efficiency of the other two methods when the traits are weakly and strongly correlated, respectively. In our application to a large GWAS, we find that the modified B-H procedure also performs well, indicating that this may be an optimal approach for determining the traits underlying a pleiotropic signal. PMID:27238845

Seismic tomography of the southern California crust based on spectral-element and adjoint methods

NASA Astrophysics Data System (ADS)

Tape, Carl; Liu, Qinya; Maggi, Alessia; Tromp, Jeroen

2010-01-01

We iteratively improve a 3-D tomographic model of the southern California crust using numerical simulations of seismic wave propagation based on a spectral-element method (SEM) in combination with an adjoint method. The initial 3-D model is provided by the Southern California Earthquake Center. The data set comprises three-component seismic waveforms (i.e. both body and surface waves), filtered over the period range 2-30 s, from 143 local earthquakes recorded by a network of 203 stations. Time windows for measurements are automatically selected by the FLEXWIN algorithm. The misfit function in the tomographic inversion is based on frequency-dependent multitaper traveltime differences. The gradient of the misfit function and related finite-frequency sensitivity kernels for each earthquake are computed using an adjoint technique. The kernels are combined using a source subspace projection method to compute a model update at each iteration of a gradient-based minimization algorithm. The inversion involved 16 iterations, which required 6800 wavefield simulations. The new crustal model, m16, is described in terms of independent shear (VS) and bulk-sound (VB) wave speed variations. It exhibits strong heterogeneity, including local changes of +/-30 per cent with respect to the initial 3-D model. The model reveals several features that relate to geological observations, such as sedimentary basins, exhumed batholiths, and contrasting lithologies across faults. The quality of the new model is validated by quantifying waveform misfits of full-length seismograms from 91 earthquakes that were not used in the tomographic inversion. The new model provides more accurate synthetic seismograms that will benefit seismic hazard assessment.

Applied Mathematics in EM Studies with Special Emphasis on an Uncertainty Quantification and 3-D Integral Equation Modelling

NASA Astrophysics Data System (ADS)

Pankratov, Oleg; Kuvshinov, Alexey

2016-01-01

Despite impressive progress in the development and application of electromagnetic (EM) deterministic inverse schemes to map the 3-D distribution of electrical conductivity within the Earth, there is one question which remains poorly addressed—uncertainty quantification of the recovered conductivity models. Apparently, only an inversion based on a statistical approach provides a systematic framework to quantify such uncertainties. The Metropolis-Hastings (M-H) algorithm is the most popular technique for sampling the posterior probability distribution that describes the solution of the statistical inverse problem. However, all statistical inverse schemes require an enormous amount of forward simulations and thus appear to be extremely demanding computationally, if not prohibitive, if a 3-D set up is invoked. This urges development of fast and scalable 3-D modelling codes which can run large-scale 3-D models of practical interest for fractions of a second on high-performance multi-core platforms. But, even with these codes, the challenge for M-H methods is to construct proposal functions that simultaneously provide a good approximation of the target density function while being inexpensive to be sampled. In this paper we address both of these issues. First we introduce a variant of the M-H method which uses information about the local gradient and Hessian of the penalty function. This, in particular, allows us to exploit adjoint-based machinery that has been instrumental for the fast solution of deterministic inverse problems. We explain why this modification of M-H significantly accelerates sampling of the posterior probability distribution. In addition we show how Hessian handling (inverse, square root) can be made practicable by a low-rank approximation using the Lanczos algorithm. Ultimately we discuss uncertainty analysis based on stochastic inversion results. In addition, we demonstrate how this analysis can be performed within a deterministic approach. In the second part, we summarize modern trends in the development of efficient 3-D EM forward modelling schemes with special emphasis on recent advances in the integral equation approach.

Estimating uncertainty of Full Waveform Inversion with Ensemble-based methods

NASA Astrophysics Data System (ADS)

Thurin, J.; Brossier, R.; Métivier, L.

2017-12-01

Uncertainty estimation is one key feature of tomographic applications for robust interpretation. However, this information is often missing in the frame of large scale linearized inversions, and only the results at convergence are shown, despite the ill-posed nature of the problem. This issue is common in the Full Waveform Inversion community.While few methodologies have already been proposed in the literature, standard FWI workflows do not include any systematic uncertainty quantifications methods yet, but often try to assess the result's quality through cross-comparison with other results from seismic or comparison with other geophysical data. With the development of large seismic networks/surveys, the increase in computational power and the more and more systematic application of FWI, it is crucial to tackle this problem and to propose robust and affordable workflows, in order to address the uncertainty quantification problem faced for near surface targets, crustal exploration, as well as regional and global scales.In this work (Thurin et al., 2017a,b), we propose an approach which takes advantage of the Ensemble Transform Kalman Filter (ETKF) proposed by Bishop et al., (2001), in order to estimate a low-rank approximation of the posterior covariance matrix of the FWI problem, allowing us to evaluate some uncertainty information of the solution. Instead of solving the FWI problem through a Bayesian inversion with the ETKF, we chose to combine a conventional FWI, based on local optimization, and the ETKF strategies. This scheme allows combining the efficiency of local optimization for solving large scale inverse problems and make the sampling of the local solution space possible thanks to its embarrassingly parallel property. References:Bishop, C. H., Etherton, B. J. and Majumdar, S. J., 2001. Adaptive sampling with the ensemble transform Kalman filter. Part I: Theoretical aspects. Monthly weather review, 129(3), 420-436.Thurin, J., Brossier, R. and Métivier, L. 2017,a.: Ensemble-Based Uncertainty Estimation in Full Waveform Inversion. 79th EAGE Conference and Exhibition 2017, (12 - 15 June, 2017)Thurin, J., Brossier, R. and Métivier, L. 2017,b.: An Ensemble-Transform Kalman Filter - Full Waveform Inversion scheme for Uncertainty estimation; SEG Technical Program Expanded Abstracts 2012

Utility of inverse probability weighting in molecular pathological epidemiology.

PubMed

Liu, Li; Nevo, Daniel; Nishihara, Reiko; Cao, Yin; Song, Mingyang; Twombly, Tyler S; Chan, Andrew T; Giovannucci, Edward L; VanderWeele, Tyler J; Wang, Molin; Ogino, Shuji

2018-04-01

As one of causal inference methodologies, the inverse probability weighting (IPW) method has been utilized to address confounding and account for missing data when subjects with missing data cannot be included in a primary analysis. The transdisciplinary field of molecular pathological epidemiology (MPE) integrates molecular pathological and epidemiological methods, and takes advantages of improved understanding of pathogenesis to generate stronger biological evidence of causality and optimize strategies for precision medicine and prevention. Disease subtyping based on biomarker analysis of biospecimens is essential in MPE research. However, there are nearly always cases that lack subtype information due to the unavailability or insufficiency of biospecimens. To address this missing subtype data issue, we incorporated inverse probability weights into Cox proportional cause-specific hazards regression. The weight was inverse of the probability of biomarker data availability estimated based on a model for biomarker data availability status. The strategy was illustrated in two example studies; each assessed alcohol intake or family history of colorectal cancer in relation to the risk of developing colorectal carcinoma subtypes classified by tumor microsatellite instability (MSI) status, using a prospective cohort study, the Nurses' Health Study. Logistic regression was used to estimate the probability of MSI data availability for each cancer case with covariates of clinical features and family history of colorectal cancer. This application of IPW can reduce selection bias caused by nonrandom variation in biospecimen data availability. The integration of causal inference methods into the MPE approach will likely have substantial potentials to advance the field of epidemiology.

Noise models for low counting rate coherent diffraction imaging.

PubMed

Godard, Pierre; Allain, Marc; Chamard, Virginie; Rodenburg, John

2012-11-05

Coherent diffraction imaging (CDI) is a lens-less microscopy method that extracts the complex-valued exit field from intensity measurements alone. It is of particular importance for microscopy imaging with diffraction set-ups where high quality lenses are not available. The inversion scheme allowing the phase retrieval is based on the use of an iterative algorithm. In this work, we address the question of the choice of the iterative process in the case of data corrupted by photon or electron shot noise. Several noise models are presented and further used within two inversion strategies, the ordered subset and the scaled gradient. Based on analytical and numerical analysis together with Monte-Carlo studies, we show that any physical interpretations drawn from a CDI iterative technique require a detailed understanding of the relationship between the noise model and the used inversion method. We observe that iterative algorithms often assume implicitly a noise model. For low counting rates, each noise model behaves differently. Moreover, the used optimization strategy introduces its own artefacts. Based on this analysis, we develop a hybrid strategy which works efficiently in the absence of an informed initial guess. Our work emphasises issues which should be considered carefully when inverting experimental data.

Model based approach to UXO imaging using the time domain electromagnetic method

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

Lavely, E.M.

1999-04-01

Time domain electromagnetic (TDEM) sensors have emerged as a field-worthy technology for UXO detection in a variety of geological and environmental settings. This success has been achieved with commercial equipment that was not optimized for UXO detection and discrimination. The TDEM response displays a rich spatial and temporal behavior which is not currently utilized. Therefore, in this paper the author describes a research program for enhancing the effectiveness of the TDEM method for UXO detection and imaging. Fundamental research is required in at least three major areas: (a) model based imaging capability i.e. the forward and inverse problem, (b) detectormore » modeling and instrument design, and (c) target recognition and discrimination algorithms. These research problems are coupled and demand a unified treatment. For example: (1) the inverse solution depends on solution of the forward problem and knowledge of the instrument response; (2) instrument design with improved diagnostic power requires forward and inverse modeling capability; and (3) improved target recognition algorithms (such as neural nets) must be trained with data collected from the new instrument and with synthetic data computed using the forward model. Further, the design of the appropriate input and output layers of the net will be informed by the results of the forward and inverse modeling. A more fully developed model of the TDEM response would enable the joint inversion of data collected from multiple sensors (e.g., TDEM sensors and magnetometers). Finally, the author suggests that a complementary approach to joint inversions is the statistical recombination of data using principal component analysis. The decomposition into principal components is useful since the first principal component contains those features that are most strongly correlated from image to image.« less

Dynamic Shape Reconstruction of Three-Dimensional Frame Structures Using the Inverse Finite Element Method

NASA Technical Reports Server (NTRS)

Gherlone, Marco; Cerracchio, Priscilla; Mattone, Massimiliano; Di Sciuva, Marco; Tessler, Alexander

2011-01-01

A robust and efficient computational method for reconstructing the three-dimensional displacement field of truss, beam, and frame structures, using measured surface-strain data, is presented. Known as shape sensing , this inverse problem has important implications for real-time actuation and control of smart structures, and for monitoring of structural integrity. The present formulation, based on the inverse Finite Element Method (iFEM), uses a least-squares variational principle involving strain measures of Timoshenko theory for stretching, torsion, bending, and transverse shear. Two inverse-frame finite elements are derived using interdependent interpolations whose interior degrees-of-freedom are condensed out at the element level. In addition, relationships between the order of kinematic-element interpolations and the number of required strain gauges are established. As an example problem, a thin-walled, circular cross-section cantilevered beam subjected to harmonic excitations in the presence of structural damping is modeled using iFEM; where, to simulate strain-gauge values and to provide reference displacements, a high-fidelity MSC/NASTRAN shell finite element model is used. Examples of low and high-frequency dynamic motion are analyzed and the solution accuracy examined with respect to various levels of discretization and the number of strain gauges.

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

Improved L-BFGS diagonal preconditioners for a large-scale 4D-Var inversion system: application to CO2 flux constraints and analysis error calculation

NASA Astrophysics Data System (ADS)

Bousserez, Nicolas; Henze, Daven; Bowman, Kevin; Liu, Junjie; Jones, Dylan; Keller, Martin; Deng, Feng

2013-04-01

This work presents improved analysis error estimates for 4D-Var systems. From operational NWP models to top-down constraints on trace gas emissions, many of today's data assimilation and inversion systems in atmospheric science rely on variational approaches. This success is due to both the mathematical clarity of these formulations and the availability of computationally efficient minimization algorithms. However, unlike Kalman Filter-based algorithms, these methods do not provide an estimate of the analysis or forecast error covariance matrices, these error statistics being propagated only implicitly by the system. From both a practical (cycling assimilation) and scientific perspective, assessing uncertainties in the solution of the variational problem is critical. For large-scale linear systems, deterministic or randomization approaches can be considered based on the equivalence between the inverse Hessian of the cost function and the covariance matrix of analysis error. For perfectly quadratic systems, like incremental 4D-Var, Lanczos/Conjugate-Gradient algorithms have proven to be most efficient in generating low-rank approximations of the Hessian matrix during the minimization. For weakly non-linear systems though, the Limited-memory Broyden-Fletcher-Goldfarb-Shanno (L-BFGS), a quasi-Newton descent algorithm, is usually considered the best method for the minimization. Suitable for large-scale optimization, this method allows one to generate an approximation to the inverse Hessian using the latest m vector/gradient pairs generated during the minimization, m depending upon the available core memory. At each iteration, an initial low-rank approximation to the inverse Hessian has to be provided, which is called preconditioning. The ability of the preconditioner to retain useful information from previous iterations largely determines the efficiency of the algorithm. Here we assess the performance of different preconditioners to estimate the inverse Hessian of a large-scale 4D-Var system. The impact of using the diagonal preconditioners proposed by Gilbert and Le Maréchal (1989) instead of the usual Oren-Spedicato scalar will be first presented. We will also introduce new hybrid methods that combine randomization estimates of the analysis error variance with L-BFGS diagonal updates to improve the inverse Hessian approximation. Results from these new algorithms will be evaluated against standard large ensemble Monte-Carlo simulations. The methods explored here are applied to the problem of inferring global atmospheric CO2 fluxes using remote sensing observations, and are intended to be integrated with the future NASA Carbon Monitoring System.

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.

A comparison between Gauss-Newton and Markov chain Monte Carlo basedmethods for inverting spectral induced polarization data for Cole-Coleparameters

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

Chen, Jinsong; Kemna, Andreas; Hubbard, Susan S.

2008-05-15

We develop a Bayesian model to invert spectral induced polarization (SIP) data for Cole-Cole parameters using Markov chain Monte Carlo (MCMC) sampling methods. We compare the performance of the MCMC based stochastic method with an iterative Gauss-Newton based deterministic method for Cole-Cole parameter estimation through inversion of synthetic and laboratory SIP data. The Gauss-Newton based method can provide an optimal solution for given objective functions under constraints, but the obtained optimal solution generally depends on the choice of initial values and the estimated uncertainty information is often inaccurate or insufficient. In contrast, the MCMC based inversion method provides extensive globalmore » information on unknown parameters, such as the marginal probability distribution functions, from which we can obtain better estimates and tighter uncertainty bounds of the parameters than with the deterministic method. Additionally, the results obtained with the MCMC method are independent of the choice of initial values. Because the MCMC based method does not explicitly offer single optimal solution for given objective functions, the deterministic and stochastic methods can complement each other. For example, the stochastic method can first be used to obtain the means of the unknown parameters by starting from an arbitrary set of initial values and the deterministic method can then be initiated using the means as starting values to obtain the optimal estimates of the Cole-Cole parameters.« less

Application of Adaptive Autopilot Designs for an Unmanned Aerial Vehicle

NASA Technical Reports Server (NTRS)

Shin, Yoonghyun; Calise, Anthony J.; Motter, Mark A.

2005-01-01

This paper summarizes the application of two adaptive approaches to autopilot design, and presents an evaluation and comparison of the two approaches in simulation for an unmanned aerial vehicle. One approach employs two-stage dynamic inversion and the other employs feedback dynamic inversions based on a command augmentation system. Both are augmented with neural network based adaptive elements. The approaches permit adaptation to both parametric uncertainty and unmodeled dynamics, and incorporate a method that permits adaptation during periods of control saturation. Simulation results for an FQM-117B radio controlled miniature aerial vehicle are presented to illustrate the performance of the neural network based adaptation.

Full-waveform inversion of GPR data for civil engineering applications

NASA Astrophysics Data System (ADS)

van der Kruk, Jan; Kalogeropoulos, Alexis; Hugenschmidt, Johannes; Klotzsche, Anja; Busch, Sebastian; Vereecken, Harry

2014-05-01

Conventional GPR ray-based techniques are often limited in their capability to image complex structures due to the pertaining approximations. Due to the increased computational power, it is becoming more easy to use modeling and inversion tools that explicitly take into account the detailed electromagnetic wave propagation characteristics. In this way, new civil engineering application avenues are opening up that enable an improved high resolution imaging of quantitative medium properties. In this contribution, we show recent developments that enable the full-waveform inversion of off-ground, on-ground and crosshole GPR data. For a successful inversion, a proper start model must be used that generates synthetic data that overlaps the measured data with at least half a wavelength. In addition, the GPR system must be calibrated such that an effective wavelet is obtained that encompasses the complexity of the GPR source and receiver antennas. Simple geometries such as horizontal layers can be described with a limited number of model parameters, which enable the use of a combined global and local search using the Simplex search algorithm. This approach has been implemented for the full-waveform inversion of off-ground and on-ground GPR data measured over horizontally layered media. In this way, an accurate 3D frequency domain forward model of Maxwell's equation can be used where the integral representation of the electric field is numerically evaluated. The full-waveform inversion (FWI) for a large number of unknowns uses gradient-based optimization methods where a 3D to 2D conversion is used to apply this method to experimental data. Off-ground GPR data, measured over homogeneous concrete specimens, were inverted using the full-waveform inversion. In contrast to traditional ray-based techniques we were able to obtain quantitative values for the permittivity and conductivity and in this way distinguish between moisture and chloride effects. For increasing chloride content increasing frequency-dependent conductivity values were obtained. The off-ground full-waveform inversion was extended to invert for positive and negative gradients in conductivity and the conductivity gradient direction could be correctly identified. Experimental specimen containing gradients were generated by exposing a concrete slab to controlled wetting-drying cycles using a saline solution. Full-waveform inversion of the measured data correctly identified the conductivity gradient direction which was confirmed by destructive analysis. On-ground CMP GPR data measured over a concrete layer overlying a metal plate show interfering multiple reflections, which indicates that the structure acts as a waveguide. Calculation of the phase-velocity spectrum shows the presence of several higher order modes. Whereas the dispersion inversion returns the thickness and layer height, the full-waveform inversion was also able to estimate quantitative conductivity values. This abstract is a contribution to COST Action TU1208

Inversion methods for interpretation of asteroid lightcurves

NASA Technical Reports Server (NTRS)

Kaasalainen, Mikko; Lamberg, L.; Lumme, K.

1992-01-01

We have developed methods of inversion that can be used in the determination of the three-dimensional shape or the albedo distribution of the surface of a body from disk-integrated photometry, assuming the shape to be strictly convex. In addition to the theory of inversion methods, we have studied the practical aspects of the inversion problem and applied our methods to lightcurve data of 39 Laetitia and 16 Psyche.

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

Preparation of Co-Zn ferrite nano-based materials and their enhanced magnetic performance via inverse miniemulsion method

NASA Astrophysics Data System (ADS)

Ji, Juejin; Zhang, Zhenqian; Fang, Bijun; Ding, Jianning

2017-11-01

The well dispersed CZF/PAM nanoparticles were prepared by the inverse miniemulsion method, which present high calcining and sintering activity for preparing Co0.875Zn0.125Fe2O4 (CZF) films, powders and ceramics at rather low temperatures. The prepared CZF/PAM inverse miniemulsion exhibits excellent film-formation performance, which is feasible for coating CZF films. XRD and FT-IR measurements confirmed that phase pure spinel structure and well crystalline CZF powders can be prepared calcined at the least temperature of 400 °C. The 450 °C-calcined CZF powders exhibit nearly spherical shape grains with average particle size 20-30 nm accompanied by apparent conglomeration. Improved external magnetic performance and electrical properties are obtained in the synthesized CZF powders and ceramics, which provide versatile promising applications.

On the Duality of Forward and Inverse Light Transport.

PubMed

Chandraker, Manmohan; Bai, Jiamin; Ng, Tian-Tsong; Ramamoorthi, Ravi

2011-10-01

Inverse light transport seeks to undo global illumination effects, such as interreflections, that pervade images of most scenes. This paper presents the theoretical and computational foundations for inverse light transport as a dual of forward rendering. Mathematically, this duality is established through the existence of underlying Neumann series expansions. Physically, it can be shown that each term of our inverse series cancels an interreflection bounce, just as the forward series adds them. While the convergence properties of the forward series are well known, we show that the oscillatory convergence of the inverse series leads to more interesting conditions on material reflectance. Conceptually, the inverse problem requires the inversion of a large light transport matrix, which is impractical for realistic resolutions using standard techniques. A natural consequence of our theoretical framework is a suite of fast computational algorithms for light transport inversion--analogous to finite element radiosity, Monte Carlo and wavelet-based methods in forward rendering--that rely at most on matrix-vector multiplications. We demonstrate two practical applications, namely, separation of individual bounces of the light transport and fast projector radiometric compensation, to display images free of global illumination artifacts in real-world environments.

Parallel three-dimensional magnetotelluric inversion using adaptive finite-element method. Part I: theory and synthetic study

NASA Astrophysics Data System (ADS)

Grayver, Alexander V.

2015-07-01

This paper presents a distributed magnetotelluric inversion scheme based on adaptive finite-element method (FEM). The key novel aspect of the introduced algorithm is the use of automatic mesh refinement techniques for both forward and inverse modelling. These techniques alleviate tedious and subjective procedure of choosing a suitable model parametrization. To avoid overparametrization, meshes for forward and inverse problems were decoupled. For calculation of accurate electromagnetic (EM) responses, automatic mesh refinement algorithm based on a goal-oriented error estimator has been adopted. For further efficiency gain, EM fields for each frequency were calculated using independent meshes in order to account for substantially different spatial behaviour of the fields over a wide range of frequencies. An automatic approach for efficient initial mesh design in inverse problems based on linearized model resolution matrix was developed. To make this algorithm suitable for large-scale problems, it was proposed to use a low-rank approximation of the linearized model resolution matrix. In order to fill a gap between initial and true model complexities and resolve emerging 3-D structures better, an algorithm for adaptive inverse mesh refinement was derived. Within this algorithm, spatial variations of the imaged parameter are calculated and mesh is refined in the neighborhoods of points with the largest variations. A series of numerical tests were performed to demonstrate the utility of the presented algorithms. Adaptive mesh refinement based on the model resolution estimates provides an efficient tool to derive initial meshes which account for arbitrary survey layouts, data types, frequency content and measurement uncertainties. Furthermore, the algorithm is capable to deliver meshes suitable to resolve features on multiple scales while keeping number of unknowns low. However, such meshes exhibit dependency on an initial model guess. Additionally, it is demonstrated that the adaptive mesh refinement can be particularly efficient in resolving complex shapes. The implemented inversion scheme was able to resolve a hemisphere object with sufficient resolution starting from a coarse discretization and refining mesh adaptively in a fully automatic process. The code is able to harness the computational power of modern distributed platforms and is shown to work with models consisting of millions of degrees of freedom. Significant computational savings were achieved by using locally refined decoupled meshes.

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.

Part-to-itself model inversion in process compensated resonance testing

NASA Astrophysics Data System (ADS)

Mayes, Alexander; Jauriqui, Leanne; Biedermann, Eric; Heffernan, Julieanne; Livings, Richard; Aldrin, John C.; Goodlet, Brent; Mazdiyasni, Siamack

2018-04-01

Process Compensated Resonance Testing (PCRT) is a non-destructive evaluation (NDE) method involving the collection and analysis of a part's resonance spectrum to characterize its material or damage state. Prior work used the finite element method (FEM) to develop forward modeling and model inversion techniques. In many cases, the inversion problem can become confounded by multiple parameters having similar effects on a part's resonance frequencies. To reduce the influence of confounding parameters and isolate the change in a part (e.g., creep), a part-to-itself (PTI) approach can be taken. A PTI approach involves inverting only the change in resonance frequencies from the before and after states of a part. This approach reduces the possible inversion parameters to only those that change in response to in-service loads and damage mechanisms. To evaluate the effectiveness of using a PTI inversion approach, creep strain and material properties were estimated in virtual and real samples using FEM inversion. Virtual and real dog bone samples composed of nickel-based superalloy Mar-M-247 were examined. Virtual samples were modeled with typically observed variations in material properties and dimensions. Creep modeling was verified with the collected resonance spectra from an incrementally crept physical sample. All samples were inverted against a model space that allowed for change in the creep damage state and the material properties but was blind to initial part dimensions. Results quantified the capabilities of PTI inversion in evaluating creep strain and material properties, as well as its sensitivity to confounding initial dimensions.

Integrated Chassis Control of Active Front Steering and Yaw Stability Control Based on Improved Inverse Nyquist Array Method

PubMed Central

2014-01-01

An integrated chassis control (ICC) system with active front steering (AFS) and yaw stability control (YSC) is introduced in this paper. The proposed ICC algorithm uses the improved Inverse Nyquist Array (INA) method based on a 2-degree-of-freedom (DOF) planar vehicle reference model to decouple the plant dynamics under different frequency bands, and the change of velocity and cornering stiffness were considered to calculate the analytical solution in the precompensator design so that the INA based algorithm runs well and fast on the nonlinear vehicle system. The stability of the system is guaranteed by dynamic compensator together with a proposed PI feedback controller. After the response analysis of the system on frequency domain and time domain, simulations under step steering maneuver were carried out using a 2-DOF vehicle model and a 14-DOF vehicle model by Matlab/Simulink. The results show that the system is decoupled and the vehicle handling and stability performance are significantly improved by the proposed method. PMID:24782676

Integrated chassis control of active front steering and yaw stability control based on improved inverse nyquist array method.

PubMed

Zhu, Bing; Chen, Yizhou; Zhao, Jian

2014-01-01

An integrated chassis control (ICC) system with active front steering (AFS) and yaw stability control (YSC) is introduced in this paper. The proposed ICC algorithm uses the improved Inverse Nyquist Array (INA) method based on a 2-degree-of-freedom (DOF) planar vehicle reference model to decouple the plant dynamics under different frequency bands, and the change of velocity and cornering stiffness were considered to calculate the analytical solution in the precompensator design so that the INA based algorithm runs well and fast on the nonlinear vehicle system. The stability of the system is guaranteed by dynamic compensator together with a proposed PI feedback controller. After the response analysis of the system on frequency domain and time domain, simulations under step steering maneuver were carried out using a 2-DOF vehicle model and a 14-DOF vehicle model by Matlab/Simulink. The results show that the system is decoupled and the vehicle handling and stability performance are significantly improved by the proposed method.

Evaluation of structural and thermophysical effects on the measurement accuracy of deep body thermometers based on dual-heat-flux method.

PubMed

Huang, Ming; Tamura, Toshiyo; Chen, Wenxi; Kanaya, Shigehiko

2015-01-01

To help pave a path toward the practical use of continuous unconstrained noninvasive deep body temperature measurement, this study aims to evaluate the structural and thermophysical effects on measurement accuracy for the dual-heat-flux method (DHFM). By considering the thermometer's height, radius, conductivity, density and specific heat as variables affecting the accuracy of DHFM measurement, we investigated the relationship between those variables and accuracy using 3-D models based on finite element method. The results of our simulation study show that accuracy is proportional to the radius but inversely proportional to the thickness of the thermometer when the radius is less than 30.0mm, and is also inversely proportional to the heat conductivity of the heat insulator inside the thermometer. The insights from this study would help to build a guideline for design, fabrication and optimization of DHFM-based thermometers, as well as their practical use. Copyright © 2014 Elsevier Ltd. All rights reserved.

A direct application of the non-linear inverse transformation flight control system design on a STOVL aircraft

NASA Technical Reports Server (NTRS)

Chung, W. W.; Mcneill, W. E.; Stortz, M. W.

1993-01-01

The nonlinear inverse transformation flight control system design method is applied to the Lockheed Ft. Worth Company's E-7D short takeoff and vertical land (STOVL) supersonic fighter/attack aircraft design with a modified General Electric F110 engine which has augmented propulsive lift capability. The system is fully augmented to provide flight path control and velocity control, and rate command attitude hold for angular axes during the transition and hover operations. In cruise mode, the flight control system is configured to provide direct thrust command, rate command attitude hold for pitch and roll axes, and sideslip command with turn coordination. A control selector based on the nonlinear inverse transformation method is designed specifically to be compatible with the propulsion system's physical configuration which has a two dimensional convergent-divergent aft nozzle, a vectorable ventral nozzle, and a thrust augmented ejector. The nonlinear inverse transformation is used to determine the propulsive forces and nozzle deflections, which in combination with the aerodynamic forces and moments (including propulsive induced contributions), and gravitational force, are required to achieve the longitudinal and vertical acceleration commands. The longitudinal control axes are fully decoupled within the propulsion system's performance envelope. A piloted motion-base flight simulation was conducted on the Vertical Motion Simulator (VMS) at NASA Ames Research Center to examine the handling qualities of this design. Based on results of the simulation, refinements to the control system have been made and will also be covered in the report.

Convergence analysis of surrogate-based methods for Bayesian inverse problems

NASA Astrophysics Data System (ADS)

Yan, Liang; Zhang, Yuan-Xiang

2017-12-01

The major challenges in the Bayesian inverse problems arise from the need for repeated evaluations of the forward model, as required by Markov chain Monte Carlo (MCMC) methods for posterior sampling. Many attempts at accelerating Bayesian inference have relied on surrogates for the forward model, typically constructed through repeated forward simulations that are performed in an offline phase. Although such approaches can be quite effective at reducing computation cost, there has been little analysis of the approximation on posterior inference. In this work, we prove error bounds on the Kullback-Leibler (KL) distance between the true posterior distribution and the approximation based on surrogate models. Our rigorous error analysis show that if the forward model approximation converges at certain rate in the prior-weighted L 2 norm, then the posterior distribution generated by the approximation converges to the true posterior at least two times faster in the KL sense. The error bound on the Hellinger distance is also provided. To provide concrete examples focusing on the use of the surrogate model based methods, we present an efficient technique for constructing stochastic surrogate models to accelerate the Bayesian inference approach. The Christoffel least squares algorithms, based on generalized polynomial chaos, are used to construct a polynomial approximation of the forward solution over the support of the prior distribution. The numerical strategy and the predicted convergence rates are then demonstrated on the nonlinear inverse problems, involving the inference of parameters appearing in partial differential equations.

A simple calculation method for determination of equivalent square field.

PubMed

Shafiei, Seyed Ali; Hasanzadeh, Hadi; Shafiei, Seyed Ahmad

2012-04-01

Determination of the equivalent square fields for rectangular and shielded fields is of great importance in radiotherapy centers and treatment planning software. This is accomplished using standard tables and empirical formulas. The goal of this paper is to present a formula based on analysis of scatter reduction due to inverse square law to obtain equivalent field. Tables are published by different agencies such as ICRU (International Commission on Radiation Units and measurements), which are based on experimental data; but there exist mathematical formulas that yield the equivalent square field of an irregular rectangular field which are used extensively in computation techniques for dose determination. These processes lead to some complicated and time-consuming formulas for which the current study was designed. In this work, considering the portion of scattered radiation in absorbed dose at a point of measurement, a numerical formula was obtained based on which a simple formula was developed to calculate equivalent square field. Using polar coordinate and inverse square law will lead to a simple formula for calculation of equivalent field. The presented method is an analytical approach based on which one can estimate the equivalent square field of a rectangular field and may be used for a shielded field or an off-axis point. Besides, one can calculate equivalent field of rectangular field with the concept of decreased scatter radiation with inverse square law with a good approximation. This method may be useful in computing Percentage Depth Dose and Tissue-Phantom Ratio which are extensively used in treatment planning.

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.

Robust inverse-consistent affine CT-MR registration in MRI-assisted and MRI-alone prostate radiation therapy.

PubMed

Rivest-Hénault, David; Dowson, Nicholas; Greer, Peter B; Fripp, Jurgen; Dowling, Jason A

2015-07-01

CT-MR registration is a critical component of many radiation oncology protocols. In prostate external beam radiation therapy, it allows the propagation of MR-derived contours to reference CT images at the planning stage, and it enables dose mapping during dosimetry studies. The use of carefully registered CT-MR atlases allows the estimation of patient specific electron density maps from MRI scans, enabling MRI-alone radiation therapy planning and treatment adaptation. In all cases, the precision and accuracy achieved by registration influences the quality of the entire process. Most current registration algorithms do not robustly generalize and lack inverse-consistency, increasing the risk of human error and acting as a source of bias in studies where information is propagated in a particular direction, e.g. CT to MR or vice versa. In MRI-based treatment planning where both CT and MR scans serve as spatial references, inverse-consistency is critical, if under-acknowledged. A robust, inverse-consistent, rigid/affine registration algorithm that is well suited to CT-MR alignment in prostate radiation therapy is presented. The presented method is based on a robust block-matching optimization process that utilises a half-way space definition to maintain inverse-consistency. Inverse-consistency substantially reduces the influence of the order of input images, simplifying analysis, and increasing robustness. An open source implementation is available online at http://aehrc.github.io/Mirorr/. Experimental results on a challenging 35 CT-MR pelvis dataset demonstrate that the proposed method is more accurate than other popular registration packages and is at least as accurate as the state of the art, while being more robust and having an order of magnitude higher inverse-consistency than competing approaches. The presented results demonstrate that the proposed registration algorithm is readily applicable to prostate radiation therapy planning. Copyright © 2015. Published by Elsevier B.V.

Investigation of noise properties in grating-based x-ray phase tomography with reverse projection method

NASA Astrophysics Data System (ADS)

Bao, Yuan; Wang, Yan; Gao, Kun; Wang, Zhi-Li; Zhu, Pei-Ping; Wu, Zi-Yu

2015-10-01

The relationship between noise variance and spatial resolution in grating-based x-ray phase computed tomography (PCT) imaging is investigated with reverse projection extraction method, and the noise variances of the reconstructed absorption coefficient and refractive index decrement are compared. For the differential phase contrast method, the noise variance in the differential projection images follows the same inverse-square law with spatial resolution as in conventional absorption-based x-ray imaging projections. However, both theoretical analysis and simulations demonstrate that in PCT the noise variance of the reconstructed refractive index decrement scales with spatial resolution follows an inverse linear relationship at fixed slice thickness, while the noise variance of the reconstructed absorption coefficient conforms with the inverse cubic law. The results indicate that, for the same noise variance level, PCT imaging may enable higher spatial resolution than conventional absorption computed tomography (ACT), while ACT benefits more from degraded spatial resolution. This could be a useful guidance in imaging the inner structure of the sample in higher spatial resolution. Project supported by the National Basic Research Program of China (Grant No. 2012CB825800), the Science Fund for Creative Research Groups, the Knowledge Innovation Program of the Chinese Academy of Sciences (Grant Nos. KJCX2-YW-N42 and Y4545320Y2), the National Natural Science Foundation of China (Grant Nos. 11475170, 11205157, 11305173, 11205189, 11375225, 11321503, 11179004, and U1332109).

A fast iterative convolution weighting approach for gridding-based direct Fourier three-dimensional reconstruction with correction for the contrast transfer function.

PubMed

Abrishami, V; Bilbao-Castro, J R; Vargas, J; Marabini, R; Carazo, J M; Sorzano, C O S

2015-10-01

We describe a fast and accurate method for the reconstruction of macromolecular complexes from a set of projections. Direct Fourier inversion (in which the Fourier Slice Theorem plays a central role) is a solution for dealing with this inverse problem. Unfortunately, the set of projections provides a non-equidistantly sampled version of the macromolecule Fourier transform in the single particle field (and, therefore, a direct Fourier inversion) may not be an optimal solution. In this paper, we introduce a gridding-based direct Fourier method for the three-dimensional reconstruction approach that uses a weighting technique to compute a uniform sampled Fourier transform. Moreover, the contrast transfer function of the microscope, which is a limiting factor in pursuing a high resolution reconstruction, is corrected by the algorithm. Parallelization of this algorithm, both on threads and on multiple CPU's, makes the process of three-dimensional reconstruction even faster. The experimental results show that our proposed gridding-based direct Fourier reconstruction is slightly more accurate than similar existing methods and presents a lower computational complexity both in terms of time and memory, thereby allowing its use on larger volumes. The algorithm is fully implemented in the open-source Xmipp package and is downloadable from http://xmipp.cnb.csic.es. Copyright © 2015 Elsevier B.V. All rights reserved.

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.

Economic Data and Models in a Greenhouse Gas Monitoring System (Invited)

NASA Astrophysics Data System (ADS)

Reilly, J. M.

2010-12-01

Under the Framework Convention for Climate Change a system of inventory reporting of greenhouse gas emissions has been developed (UNFCCC, 2010). The system is based on a bottom-up approach that identifies activities associated with emissions (e.g. coal burning, rice production), develops coefficients associated with each unit of the activity (ton of coal, hectare of rice), and then based on the level of the activity (total tons, hectares) arrives through multiplication at an estimate of annual emissions at a country level. Tier 1, 2, and 3 approaches vary in the level of detail taken into account in making estimates, in large part attempting to take account of variation in emissions coefficients based on experimental measurements that may not be representative of the countries actual activities (differences among rice fields, livestock, etc). Top-down approaches use direct measurements of concentrations of GHGs in the atmosphere and inverse methods and assimilated weather data to estimate emissions sources (e.g. Prinn, 2000). The statistical approaches used rely on known relationships, measurements, and estimates of error to reconcile different measurements to improve the estimate of interest—i.e. emissions. While inverse methods have typically relied on measurement of concentrations, economic data and relationships such as those used in bottom-up reporting could also be brought into the inverse calculations to reconcile estimates of anthropogenic emissions in national reports with those of natural emissions , of non-reporting countries, and of concentrations. For example, per unit emissions from coal, oil, or gas combustion are well constrained, and estimates of tons know reasonably well but with some uncertainty. Inverse methods may improve estimates of tons of fuel combusted but because they are relatively well known that information is likely to tightly constrain fossil emissions and thus improve the estimate of emissions from land use change which are more poorly known. If inverse methods are to be used for treaty verification, it would seem particularly important to incorporate economic data because so far treaties have covered emissions from "anthropogenic" emissions and there may not be a distinct physical signature to identify concentration changes related to legally defined anthropogenic sources from natural sources (e.g. emissions or uptake on managed forest land from a natural change in uptake of carbon on land or nitrous oxide emissions related to land management (inorganic or organic fertilizers) from N2O from natural cycles. There are many issues that would need to be resolved to effectively utilize economic activity data in inverse calculations. In particular, economic activity data often lacks spatial and temporal resolution as it is reported for political units (e.g. at the national level) and often only annually. However, given the potential gain these data could contribute to top down estimates it is worth further investigating their incorporation, and it may give impetus to efforts to create economic data sets with greater spatial and temporal resolution. Prinn, R.G., 2000: Measurement Equation for Trace Chemicals in Fluids and Solution of its Inverse, in Inverse Methods in Global Biogeochemical Cycles, Geophysical Monograph 114, American Geophysical Union. UNFCCC, 2010, National Reports at http://unfccc.int/national_reports/items/1408.php

Location identification for indoor instantaneous point contaminant source by probability-based inverse Computational Fluid Dynamics modeling.

PubMed

Liu, X; Zhai, Z

2008-02-01

Indoor pollutions jeopardize human health and welfare and may even cause serious morbidity and mortality under extreme conditions. To effectively control and improve indoor environment quality requires immediate interpretation of pollutant sensor readings and accurate identification of indoor pollution history and source characteristics (e.g. source location and release time). This procedure is complicated by non-uniform and dynamic contaminant indoor dispersion behaviors as well as diverse sensor network distributions. This paper introduces a probability concept based inverse modeling method that is able to identify the source location for an instantaneous point source placed in an enclosed environment with known source release time. The study presents the mathematical models that address three different sensing scenarios: sensors without concentration readings, sensors with spatial concentration readings, and sensors with temporal concentration readings. The paper demonstrates the inverse modeling method and algorithm with two case studies: air pollution in an office space and in an aircraft cabin. The predictions were successfully verified against the forward simulation settings, indicating good capability of the method in finding indoor pollutant sources. The research lays a solid ground for further study of the method for more complicated indoor contamination problems. The method developed can help track indoor contaminant source location with limited sensor outputs. This will ensure an effective and prompt execution of building control strategies and thus achieve a healthy and safe indoor environment. The method can also assist the design of optimal sensor networks.

Acceleration for 2D time-domain elastic full waveform inversion using a single GPU card

NASA Astrophysics Data System (ADS)

Jiang, Jinpeng; Zhu, Peimin

2018-05-01

Full waveform inversion (FWI) is a challenging procedure due to the high computational cost related to the modeling, especially for the elastic case. The graphics processing unit (GPU) has become a popular device for the high-performance computing (HPC). To reduce the long computation time, we design and implement the GPU-based 2D elastic FWI (EFWI) in time domain using a single GPU card. We parallelize the forward modeling and gradient calculations using the CUDA programming language. To overcome the limitation of relatively small global memory on GPU, the boundary saving strategy is exploited to reconstruct the forward wavefield. Moreover, the L-BFGS optimization method used in the inversion increases the convergence of the misfit function. A multiscale inversion strategy is performed in the workflow to obtain the accurate inversion results. In our tests, the GPU-based implementations using a single GPU device achieve >15 times speedup in forward modeling, and about 12 times speedup in gradient calculation, compared with the eight-core CPU implementations optimized by OpenMP. The test results from the GPU implementations are verified to have enough accuracy by comparing the results obtained from the CPU implementations.

Spatiotemporal Interpolation for Environmental Modelling

PubMed Central

Susanto, Ferry; de Souza, Paulo; He, Jing

2016-01-01

A variation of the reduction-based approach to spatiotemporal interpolation (STI), in which time is treated independently from the spatial dimensions, is proposed in this paper. We reviewed and compared three widely-used spatial interpolation techniques: ordinary kriging, inverse distance weighting and the triangular irregular network. We also proposed a new distribution-based distance weighting (DDW) spatial interpolation method. In this study, we utilised one year of Tasmania’s South Esk Hydrology model developed by CSIRO. Root mean squared error statistical methods were performed for performance evaluations. Our results show that the proposed reduction approach is superior to the extension approach to STI. However, the proposed DDW provides little benefit compared to the conventional inverse distance weighting (IDW) method. We suggest that the improved IDW technique, with the reduction approach used for the temporal dimension, is the optimal combination for large-scale spatiotemporal interpolation within environmental modelling applications. PMID:27509497

Fast tomographic methods for the tokamak ISTTOK

NASA Astrophysics Data System (ADS)

Carvalho, P. J.; Thomsen, H.; Gori, S.; Toussaint, U. v.; Weller, A.; Coelho, R.; Neto, A.; Pereira, T.; Silva, C.; Fernandes, H.

2008-04-01

The achievement of long duration, alternating current discharges on the tokamak IST-TOK requires a real-time plasma position control system. The plasma position determination based on magnetic probes system has been found to be inadequate during the current inversion due to the reduced plasma current. A tomography diagnostic has been therefore installed to supply the required feedback to the control system. Several tomographic methods are available for soft X-ray or bolo-metric tomography, among which the Cormack and Neural networks methods stand out due to their inherent speed of up to 1000 reconstructions per second, with currently available technology. This paper discusses the application of these algorithms on fusion devices while comparing performance and reliability of the results. It has been found that although the Cormack based inversion proved to be faster, the neural networks reconstruction has fewer artifacts and is more accurate.

Estimation of slip distribution using an inverse method based on spectral decomposition of Green's function utilizing Global Positioning System (GPS) data

NASA Astrophysics Data System (ADS)

Jin, Honglin; Kato, Teruyuki; Hori, Muneo

2007-07-01

An inverse method based on the spectral decomposition of the Green's function was employed for estimating a slip distribution. We conducted numerical simulations along the Philippine Sea plate (PH) boundary in southwest Japan using this method to examine how to determine the essential parameters which are the number of deformation function modes and their coefficients. Japanese GPS Earth Observation Network (GEONET) Global Positioning System (GPS) data were used for three years covering 1997-1999 to estimate interseismic back slip distribution in this region. The estimated maximum back slip rate is about 7 cm/yr, which is consistent with the Philippine Sea plate convergence rate. Areas of strong coupling are confined between depths of 10 and 30 km and three areas of strong coupling were delineated. These results are consistent with other studies that have estimated locations of coupling distribution.

Remote Sensing Image Fusion Method Based on Nonsubsampled Shearlet Transform and Sparse Representation

NASA Astrophysics Data System (ADS)

Moonon, Altan-Ulzii; Hu, Jianwen; Li, Shutao

2015-12-01

The remote sensing image fusion is an important preprocessing technique in remote sensing image processing. In this paper, a remote sensing image fusion method based on the nonsubsampled shearlet transform (NSST) with sparse representation (SR) is proposed. Firstly, the low resolution multispectral (MS) image is upsampled and color space is transformed from Red-Green-Blue (RGB) to Intensity-Hue-Saturation (IHS). Then, the high resolution panchromatic (PAN) image and intensity component of MS image are decomposed by NSST to high and low frequency coefficients. The low frequency coefficients of PAN and the intensity component are fused by the SR with the learned dictionary. The high frequency coefficients of intensity component and PAN image are fused by local energy based fusion rule. Finally, the fused result is obtained by performing inverse NSST and inverse IHS transform. The experimental results on IKONOS and QuickBird satellites demonstrate that the proposed method provides better spectral quality and superior spatial information in the fused image than other remote sensing image fusion methods both in visual effect and object evaluation.

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.

[Global Atmospheric Chemistry/Transport Modeling and Data-Analysis

NASA Technical Reports Server (NTRS)

Prinn, Ronald G.

1999-01-01

This grant supported a global atmospheric chemistry/transport modeling and data- analysis project devoted to: (a) development, testing, and refining of inverse methods for determining regional and global transient source and sink strengths for trace gases; (b) utilization of these inverse methods which use either the Model for Atmospheric Chemistry and Transport (MATCH) which is based on analyzed observed winds or back- trajectories calculated from these same winds for determining regional and global source and sink strengths for long-lived trace gases important in ozone depletion and the greenhouse effect; (c) determination of global (and perhaps regional) average hydroxyl radical concentrations using inverse methods with multiple "titrating" gases; and (d) computation of the lifetimes and spatially resolved destruction rates of trace gases using 3D models. Important ultimate goals included determination of regional source strengths of important biogenic/anthropogenic trace gases and also of halocarbons restricted by the Montreal Protocol and its follow-on agreements, and hydrohalocarbons now used as alternatives to the above restricted halocarbons.

Local T1-T2 distribution measurements in porous media

NASA Astrophysics Data System (ADS)

Vashaee, S.; Li, M.; Newling, B.; MacMillan, B.; Marica, F.; Kwak, H. T.; Gao, J.; Al-harbi, A. M.; Balcom, B. J.

2018-02-01

A novel slice-selective T1-T2 measurement is proposed to measure spatially resolved T1-T2 distributions. An adiabatic inversion pulse is employed for slice-selection. The slice-selective pulse is able to select a quasi-rectangular slice, on the order of 1 mm, at an arbitrary position within the sample. The method does not employ conventional selective excitation in which selective excitation is often accomplished by rotation of the longitudinal magnetization in the slice of interest into the transverse plane, but rather a subtraction based on CPMG data acquired with and without adiabatic inversion slice selection. T1 weighting is introduced during recovery from the inversion associated with slice selection. The local T1-T2 distributions measured are of similar quality to bulk T1-T2 measurements. The new method can be employed to characterize oil-water mixtures and other fluids in porous media. The method is beneficial when a coarse spatial distribution of the components is of interest.

Inverse estimation of the elastic and anelastic properties of the porous frame of anisotropic open-cell foams.

PubMed

Cuenca, Jacques; Göransson, Peter

2012-08-01

This paper presents a method for simultaneously identifying both the elastic and anelastic properties of the porous frame of anisotropic open-cell foams. The approach is based on an inverse estimation procedure of the complex stiffness matrix of the frame by performing a model fit of a set of transfer functions of a sample of material subjected to compression excitation in vacuo. The material elastic properties are assumed to have orthotropic symmetry and the anelastic properties are described using a fractional-derivative model within the framework of an augmented Hooke's law. The inverse estimation problem is formulated as a numerical optimization procedure and solved using the globally convergent method of moving asymptotes. To show the feasibility of the approach a numerically generated target material is used here as a benchmark. It is shown that the method provides the full frequency-dependent orthotropic complex stiffness matrix within a reasonable degree of accuracy.

Prediction of sedimentary facies of x-oilfield in northwest of China by geostatistical inversion

NASA Astrophysics Data System (ADS)

Lei, Zhao; Ling, Ke; Tingting, He

2017-03-01

In the early stage of oilfield development, there are only a few wells and well spacing can reach several kilometers. for the alluvial fans and other heterogeneous reservoirs, information from wells alone is not sufficient to derive detailed reservoir information. In this paper, the method of calculating sand thickness through geostatistics inversion is studied, and quantitative relationships between each sedimentary micro-facies are analyzed by combining with single well sedimentary facies. Further, the sedimentary facies plane distribution based on seismic inversion is obtained by combining with sedimentary model, providing the geological basis for the next exploration and deployment.

GUEST EDITORS' INTRODUCTION: Testing inversion algorithms against experimental data: inhomogeneous targets

NASA Astrophysics Data System (ADS)

Belkebir, Kamal; Saillard, Marc

2005-12-01

This special section deals with the reconstruction of scattering objects from experimental data. A few years ago, inspired by the Ipswich database [1 4], we started to build an experimental database in order to validate and test inversion algorithms against experimental data. In the special section entitled 'Testing inversion algorithms against experimental data' [5], preliminary results were reported through 11 contributions from several research teams. (The experimental data are free for scientific use and can be downloaded from the web site.) The success of this previous section has encouraged us to go further and to design new challenges for the inverse scattering community. Taking into account the remarks formulated by several colleagues, the new data sets deal with inhomogeneous cylindrical targets and transverse electric (TE) polarized incident fields have also been used. Among the four inhomogeneous targets, three are purely dielectric, while the last one is a `hybrid' target mixing dielectric and metallic cylinders. Data have been collected in the anechoic chamber of the Centre Commun de Ressources Micro-ondes in Marseille. The experimental setup as well as the layout of the files containing the measurements are presented in the contribution by J-M Geffrin, P Sabouroux and C Eyraud. The antennas did not change from the ones used previously [5], namely wide-band horn antennas. However, improvements have been achieved by refining the mechanical positioning devices. In order to enlarge the scope of applications, both TE and transverse magnetic (TM) polarizations have been carried out for all targets. Special care has been taken not to move the target under test when switching from TE to TM measurements, ensuring that TE and TM data are available for the same configuration. All data correspond to electric field measurements. In TE polarization the measured component is orthogonal to the axis of invariance. Contributions A Abubakar, P M van den Berg and T M Habashy, Application of the multiplicative regularized contrast source inversion method TM- and TE-polarized experimental Fresnel data, present results of profile inversions obtained using the contrast source inversion (CSI) method, in which a multiplicative regularization is plugged in. The authors successfully inverted both TM- and TE-polarized fields. Note that this paper is one of only two contributions which address the inversion of TE-polarized data. A Baussard, Inversion of multi-frequency experimental data using an adaptive multiscale approach, reports results of reconstructions using the modified gradient method (MGM). It suggests that a coarse-to-fine iterative strategy based on spline pyramids. In this iterative technique, the number of degrees of freedom is reduced, which improves robustness. The introduction, during the iterative process, of finer scales inside areas of interest leads to an accurate representation of the object under test. The efficiency of this technique is shown via comparisons between the results obtained with the standard MGM and those from an adaptive approach. L Crocco, M D'Urso and T Isernia, Testing the contrast source extended Born inversion method against real data: the case of TM data, assume that the main contribution in the domain integral formulation comes from the singularity of Green's function, even though the media involved are lossless. A Fourier Bessel analysis of the incident and scattered measured fields is used to derive a model of the incident field and an estimate of the location and size of the target. The iterative procedure lies on a conjugate gradient method associated with Tikhonov regularization, and the multi-frequency data are dealt with using a frequency-hopping approach. In many cases, it is difficult to reconstruct accurately both real and imaginary parts of the permittivity if no prior information is included. M Donelli, D Franceschini, A Massa, M Pastorino and A Zanetti, Multi-resolution iterative inversion of real inhomogeneous targets, adopt a multi-resolution strategy, which, at each step, adaptive discretization of the integral equation is performed over an irregular mesh, with a coarser grid outside the regions of interest and tighter sampling where better resolution is required. Here, this procedure is achieved while keeping the number of unknowns constant. The way such a strategy could be combined with multi-frequency data, edge preserving regularization, or any technique also devoted to improve resolution, remains to be studied. As done by some other contributors, the model of incident field is chosen to fit the Fourier Bessel expansion of the measured one. A Dubois, K Belkebir and M Saillard, Retrieval of inhomogeneous targets from experimental frequency diversity data, present results of the reconstruction of targets using three different non-regularized techniques. It is suggested to minimize a frequency weighted cost function rather than a standard one. The different approaches are compared and discussed. C Estatico, G Bozza, A Massa, M Pastorino and A Randazzo, A two-step iterative inexact-Newton method for electromagnetic imaging of dielectric structures from real data, use a two nested iterative methods scheme, based on the second-order Born approximation, which is nonlinear in terms of contrast but does not involve the total field. At each step of the outer iteration, the problem is linearized and solved iteratively using the Landweber method. Better reconstructions than with the Born approximation are obtained at low numerical cost. O Feron, B Duchêne and A Mohammad-Djafari, Microwave imaging of inhomogeneous objects made of a finite number of dielectric and conductive materials from experimental data, adopt a Bayesian framework based on a hidden Markov model, built to take into account, as prior knowledge, that the target is composed of a finite number of homogeneous regions. It has been applied to diffraction tomography and to a rigorous formulation of the inverse problem. The latter can be viewed as a Bayesian adaptation of the contrast source method such that prior information about the contrast can be introduced in the prior law distribution, and it results in estimating the posterior mean instead of minimizing a cost functional. The accuracy of the result is thus closely linked to the prior knowledge of the contrast, making this approach well suited for non-destructive testing. J-M Geffrin, P Sabouroux and C Eyraud, Free space experimental scattering database continuation: experimental set-up and measurement precision, describe the experimental set-up used to carry out the data for the inversions. They report the modifications of the experimental system used previously in order to improve the precision of the measurements. Reliability of data is demonstrated through comparisons between measurements and computed scattered field with both fundamental polarizations. In addition, the reader interested in using the database will find the relevant information needed to perform inversions as well as the description of the targets under test. A Litman, Reconstruction by level sets of n-ary scattering obstacles, presents the reconstruction of targets using a level sets representation. It is assumed that the constitutive materials of the obstacles under test are known and the shape is retrieved. Two approaches are reported. In the first one the obstacles of different constitutive materials are represented in a single level set, while in the second approach several level sets are combined. The approaches are applied to the experimental data and compared. U Shahid, M Testorf and M A Fiddy, Minimum-phase-based inverse scattering algorithm applied to Institut Fresnel data, suggest a way of extending the use of minimum phase functions to 2D problems. In the kind of inverse problems we are concerned with, it consists of separating the contributions from the field and from the contrast in the so-called contrast source term, through homomorphic filtering. Images of the targets are obtained by combination with diffraction tomography. Both pre-processing and imaging are thus based on the use of Fourier transforms, making the algorithm very fast compared to classical iterative approaches. It is also pointed out that the design of appropriate filters remains an open topic. C Yu, L-P Song and Q H Liu, Inversion of multi-frequency experimental data for imaging complex objects by a DTA CSI method, use the contrast source inversion (CSI) method for the reconstruction of the targets, in which the initial guess is a solution deduced from another iterative technique based on the diagonal tensor approximation (DTA). In so doing, the authors combine the fast convergence of the DTA method for generating an accurate initial estimate for the CSI method. Note that this paper is one of only two contributions which address the inversion of TE-polarized data. Conclusion In this special section various inverse scattering techniques were used to successfully reconstruct inhomogeneous targets from multi-frequency multi-static measurements. This shows that the database is reliable and can be useful for researchers wanting to test and validate inversion algorithms. From the database, it is also possible to extract subsets to study particular inverse problems, for instance from phaseless data or from `aspect-limited' configurations. Our future efforts will be directed towards extending the database in order to explore inversions from transient fields and the full three-dimensional problem. Acknowledgments The authors would like to thank the Inverse Problems board for opening the journal to us, and offer profound thanks to Elaine Longden-Chapman and Kate Hooper for their help in organizing this special section.

Modeling the 16 September 2015 Chile tsunami source with the inversion of deep-ocean tsunami records by means of the r - solution method

NASA Astrophysics Data System (ADS)

Voronina, Tatyana; Romanenko, Alexey; Loskutov, Artem

2017-04-01

The key point in the state-of-the-art in the tsunami forecasting is constructing a reliable tsunami source. In this study, we present an application of the original numerical inversion technique to modeling the tsunami sources of the 16 September 2015 Chile tsunami. The problem of recovering a tsunami source from remote measurements of the incoming wave in the deep-water tsunameters is considered as an inverse problem of mathematical physics in the class of ill-posed problems. This approach is based on the least squares and the truncated singular value decomposition techniques. The tsunami wave propagation is considered within the scope of the linear shallow-water theory. As in inverse seismic problem, the numerical solutions obtained by mathematical methods become unstable due to the presence of noise in real data. A method of r-solutions makes it possible to avoid instability in the solution to the ill-posed problem under study. This method seems to be attractive from the computational point of view since the main efforts are required only once for calculating the matrix whose columns consist of computed waveforms for each harmonic as a source (an unknown tsunami source is represented as a part of a spatial harmonics series in the source area). Furthermore, analyzing the singular spectra of the matrix obtained in the course of numerical calculations one can estimate the future inversion by a certain observational system that will allow offering a more effective disposition for the tsunameters with the help of precomputations. In other words, the results obtained allow finding a way to improve the inversion by selecting the most informative set of available recording stations. The case study of the 6 February 2013 Solomon Islands tsunami highlights a critical role of arranging deep-water tsunameters for obtaining the inversion results. Implementation of the proposed methodology to the 16 September 2015 Chile tsunami has successfully produced tsunami source model. The function recovered by the method proposed can find practical applications both as an initial condition for various optimization approaches and for computer calculation of the tsunami wave propagation.

Pulse-Inversion Subharmonic Ultrafast Active Cavitation Imaging in Tissue Using Fast Eigenspace-Based Adaptive Beamforming and Cavitation Deconvolution.

PubMed

Bai, Chen; Xu, Shanshan; Duan, Junbo; Jing, Bowen; Yang, Miao; Wan, Mingxi

2017-08-01

Pulse-inversion subharmonic (PISH) imaging can display information relating to pure cavitation bubbles while excluding that of tissue. Although plane-wave-based ultrafast active cavitation imaging (UACI) can monitor the transient activities of cavitation bubbles, its resolution and cavitation-to-tissue ratio (CTR) are barely satisfactory but can be significantly improved by introducing eigenspace-based (ESB) adaptive beamforming. PISH and UACI are a natural combination for imaging of pure cavitation activity in tissue; however, it raises two problems: 1) the ESB beamforming is hard to implement in real time due to the enormous amount of computation associated with the covariance matrix inversion and eigendecomposition and 2) the narrowband characteristic of the subharmonic filter will incur a drastic degradation in resolution. Thus, in order to jointly address these two problems, we propose a new PISH-UACI method using novel fast ESB (F-ESB) beamforming and cavitation deconvolution for nonlinear signals. This method greatly reduces the computational complexity by using F-ESB beamforming through dimensionality reduction based on principal component analysis, while maintaining the high quality of ESB beamforming. The degraded resolution is recovered using cavitation deconvolution through a modified convolution model and compressive deconvolution. Both simulations and in vitro experiments were performed to verify the effectiveness of the proposed method. Compared with the ESB-based PISH-UACI, the entire computation of our proposed approach was reduced by 99%, while the axial resolution gain and CTR were increased by 3 times and 2 dB, respectively, confirming that satisfactory performance can be obtained for monitoring pure cavitation bubbles in tissue erosion.

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.

An unusual haplotype structure on human chromosome 8p23 derived from the inversion polymorphism.

PubMed

Deng, Libin; Zhang, Yuezheng; Kang, Jian; Liu, Tao; Zhao, Hongbin; Gao, Yang; Li, Chaohua; Pan, Hao; Tang, Xiaoli; Wang, Dunmei; Niu, Tianhua; Yang, Huanming; Zeng, Changqing

2008-10-01

Chromosomal inversion is an important type of genomic variations involved in both evolution and disease pathogenesis. Here, we describe the refined genetic structure of a 3.8-Mb inversion polymorphism at chromosome 8p23. Using HapMap data of 1,073 SNPs generated from 209 unrelated samples from CEPH-Utah residents with ancestry from northern and western Europe (CEU); Yoruba in Ibadan, Nigeria (YRI); and Asian (ASN) samples, which were comprised of Han Chinese from Beijing, China (CHB) and Japanese from Tokyo, Japan (JPT)-we successfully deduced the inversion orientations of all their 418 haplotypes. In particular, distinct haplotype subgroups were identified based on principal component analysis (PCA). Such genetic substructures were consistent with clustering patterns based on neighbor-joining tree reconstruction, which revealed a total of four haplotype clades across all samples. Metaphase fluorescence in situ hybridization (FISH) in a subset of 10 HapMap samples verified their inversion orientations predicted by PCA or phylogenetic tree reconstruction. Positioning of the outgroup haplotype within one of YRI clades suggested that Human NCBI Build 36-inverted order is most likely the ancestral orientation. Furthermore, the population differentiation test and the relative extended haplotype homozygosity (REHH) analysis in this region discovered multiple selection signals, also in a population-specific manner. A positive selection signal was detected at XKR6 in the ASN population. These results revealed the correlation of inversion polymorphisms to population-specific genetic structures, and various selection patterns as possible mechanisms for the maintenance of a large chromosomal rearrangement at 8p23 region during evolution. In addition, our study also showed that haplotype-based clustering methods, such as PCA, can be applied in scanning for cryptic inversion polymorphisms at a genome-wide scale.

Development of FWIGPR, an open-source package for full-waveform inversion of common-offset GPR data

NASA Astrophysics Data System (ADS)

Jazayeri, S.; Kruse, S.

2017-12-01

We introduce a package for full-waveform inversion (FWI) of Ground Penetrating Radar (GPR) data based on a combination of open-source programs. The FWI requires a good starting model, based on direct knowledge of field conditions or on traditional ray-based inversion methods. With a good starting model, the FWI can improve resolution of selected subsurface features. The package will be made available for general use in educational and research activities. The FWIGPR package consists of four main components: 3D to 2D data conversion, source wavelet estimation, forward modeling, and inversion. (These four components additionally require the development, by the user, of a good starting model.) A major challenge with GPR data is the unknown form of the waveform emitted by the transmitter held close to the ground surface. We apply a blind deconvolution method to estimate the source wavelet, based on a sparsity assumption about the reflectivity series of the subsurface model (Gholami and Sacchi 2012). The estimated wavelet is deconvolved from the data and the sparsest reflectivity series with fewest reflectors. The gprMax code (www.gprmax.com) is used as the forward modeling tool and the PEST parameter estimation package (www.pesthomepage.com) for the inversion. To reduce computation time, the field data are converted to an effective 2D equivalent, and the gprMax code can be run in 2D mode. In the first step, the user must create a good starting model of the data, presumably using ray-based methods. This estimated model will be introduced to the FWI process as an initial model. Next, the 3D data is converted to 2D, then the user estimates the source wavelet that best fits the observed data by sparsity assumption of the earth's response. Last, PEST runs gprMax with the initial model and calculates the misfit between the synthetic and observed data, and using an iterative algorithm calling gprMax several times ineach iteration, finds successive models that better fit the data. To gauge whether the iterative process has arrived at a local or global minima, the process can be repeated with a range of starting models. Tests have shown that this package can successfully improve estimates of selected subsurface model parameters for simple synthetic and real data. Ongoing research will focus on FWI of more complex scenarios.

On the value of incorporating spatial statistics in large-scale geophysical inversions: the SABRe case

NASA Astrophysics Data System (ADS)

Kokkinaki, A.; Sleep, B. E.; Chambers, J. E.; Cirpka, O. A.; Nowak, W.

2010-12-01

Electrical Resistance Tomography (ERT) is a popular method for investigating subsurface heterogeneity. The method relies on measuring electrical potential differences and obtaining, through inverse modeling, the underlying electrical conductivity field, which can be related to hydraulic conductivities. The quality of site characterization strongly depends on the utilized inversion technique. Standard ERT inversion methods, though highly computationally efficient, do not consider spatial correlation of soil properties; as a result, they often underestimate the spatial variability observed in earth materials, thereby producing unrealistic subsurface models. Also, these methods do not quantify the uncertainty of the estimated properties, thus limiting their use in subsequent investigations. Geostatistical inverse methods can be used to overcome both these limitations; however, they are computationally expensive, which has hindered their wide use in practice. In this work, we compare a standard Gauss-Newton smoothness constrained least squares inversion method against the quasi-linear geostatistical approach using the three-dimensional ERT dataset of the SABRe (Source Area Bioremediation) project. The two methods are evaluated for their ability to: a) produce physically realistic electrical conductivity fields that agree with the wide range of data available for the SABRe site while being computationally efficient, and b) provide information on the spatial statistics of other parameters of interest, such as hydraulic conductivity. To explore the trade-off between inversion quality and computational efficiency, we also employ a 2.5-D forward model with corrections for boundary conditions and source singularities. The 2.5-D model accelerates the 3-D geostatistical inversion method. New adjoint equations are developed for the 2.5-D forward model for the efficient calculation of sensitivities. Our work shows that spatial statistics can be incorporated in large-scale ERT inversions to improve the inversion results without making them computationally prohibitive.

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.

Content based image retrieval for matching images of improvised explosive devices in which snake initialization is viewed as an inverse problem

NASA Astrophysics Data System (ADS)

Acton, Scott T.; Gilliam, Andrew D.; Li, Bing; Rossi, Adam

2008-02-01

Improvised explosive devices (IEDs) are common and lethal instruments of terrorism, and linking a terrorist entity to a specific device remains a difficult task. In the effort to identify persons associated with a given IED, we have implemented a specialized content based image retrieval system to search and classify IED imagery. The system makes two contributions to the art. First, we introduce a shape-based matching technique exploiting shape, color, and texture (wavelet) information, based on novel vector field convolution active contours and a novel active contour initialization method which treats coarse segmentation as an inverse problem. Second, we introduce a unique graph theoretic approach to match annotated printed circuit board images for which no schematic or connectivity information is available. The shape-based image retrieval method, in conjunction with the graph theoretic tool, provides an efficacious system for matching IED images. For circuit imagery, the basic retrieval mechanism has a precision of 82.1% and the graph based method has a precision of 98.1%. As of the fall of 2007, the working system has processed over 400,000 case images.

Inverse scattering method and soliton double solution family for the general symplectic gravity model

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

Gao Yajun

A previously established Hauser-Ernst-type extended double-complex linear system is slightly modified and used to develop an inverse scattering method for the stationary axisymmetric general symplectic gravity model. The reduction procedures in this inverse scattering method are found to be fairly simple, which makes the inverse scattering method applied fine and effective. As an application, a concrete family of soliton double solutions for the considered theory is obtained.

High-resolution inverse synthetic aperture radar imaging for large rotation angle targets based on segmented processing algorithm

NASA Astrophysics Data System (ADS)

Chen, Hao; Zhang, Xinggan; Bai, Yechao; Tang, Lan

2017-01-01

In inverse synthetic aperture radar (ISAR) imaging, the migration through resolution cells (MTRCs) will occur when the rotation angle of the moving target is large, thereby degrading image resolution. To solve this problem, an ISAR imaging method based on segmented preprocessing is proposed. In this method, the echoes of large rotating target are divided into several small segments, and every segment can generate a low-resolution image without MTRCs. Then, each low-resolution image is rotated back to the original position. After image registration and phase compensation, a high-resolution image can be obtained. Simulation and real experiments show that the proposed algorithm can deal with the radar system with different range and cross-range resolutions and significantly compensate the MTRCs.

Mixed linear-non-linear inversion of crustal deformation data: Bayesian inference of model, weighting and regularization parameters

NASA Astrophysics Data System (ADS)

Fukuda, Jun'ichi; Johnson, Kaj M.

2010-06-01

We present a unified theoretical framework and solution method for probabilistic, Bayesian inversions of crustal deformation data. The inversions involve multiple data sets with unknown relative weights, model parameters that are related linearly or non-linearly through theoretic models to observations, prior information on model parameters and regularization priors to stabilize underdetermined problems. To efficiently handle non-linear inversions in which some of the model parameters are linearly related to the observations, this method combines both analytical least-squares solutions and a Monte Carlo sampling technique. In this method, model parameters that are linearly and non-linearly related to observations, relative weights of multiple data sets and relative weights of prior information and regularization priors are determined in a unified Bayesian framework. In this paper, we define the mixed linear-non-linear inverse problem, outline the theoretical basis for the method, provide a step-by-step algorithm for the inversion, validate the inversion method using synthetic data and apply the method to two real data sets. We apply the method to inversions of multiple geodetic data sets with unknown relative data weights for interseismic fault slip and locking depth. We also apply the method to the problem of estimating the spatial distribution of coseismic slip on faults with unknown fault geometry, relative data weights and smoothing regularization weight.

Investigation of error sources in regional inverse estimates of greenhouse gas emissions in Canada

NASA Astrophysics Data System (ADS)

Chan, E.; Chan, D.; Ishizawa, M.; Vogel, F.; Brioude, J.; Delcloo, A.; Wu, Y.; Jin, B.

2015-08-01

Inversion models can use atmospheric concentration measurements to estimate surface fluxes. This study is an evaluation of the errors in a regional flux inversion model for different provinces of Canada, Alberta (AB), Saskatchewan (SK) and Ontario (ON). Using CarbonTracker model results as the target, the synthetic data experiment analyses examined the impacts of the errors from the Bayesian optimisation method, prior flux distribution and the atmospheric transport model, as well as their interactions. The scaling factors for different sub-regions were estimated by the Markov chain Monte Carlo (MCMC) simulation and cost function minimization (CFM) methods. The CFM method results are sensitive to the relative size of the assumed model-observation mismatch and prior flux error variances. Experiment results show that the estimation error increases with the number of sub-regions using the CFM method. For the region definitions that lead to realistic flux estimates, the numbers of sub-regions for the western region of AB/SK combined and the eastern region of ON are 11 and 4 respectively. The corresponding annual flux estimation errors for the western and eastern regions using the MCMC (CFM) method are -7 and -3 % (0 and 8 %) respectively, when there is only prior flux error. The estimation errors increase to 36 and 94 % (40 and 232 %) resulting from transport model error alone. When prior and transport model errors co-exist in the inversions, the estimation errors become 5 and 85 % (29 and 201 %). This result indicates that estimation errors are dominated by the transport model error and can in fact cancel each other and propagate to the flux estimates non-linearly. In addition, it is possible for the posterior flux estimates having larger differences than the prior compared to the target fluxes, and the posterior uncertainty estimates could be unrealistically small that do not cover the target. The systematic evaluation of the different components of the inversion model can help in the understanding of the posterior estimates and percentage errors. Stable and realistic sub-regional and monthly flux estimates for western region of AB/SK can be obtained, but not for the eastern region of ON. This indicates that it is likely a real observation-based inversion for the annual provincial emissions will work for the western region whereas; improvements are needed with the current inversion setup before real inversion is performed for the eastern region.

Efficient moving target analysis for inverse synthetic aperture radar images via joint speeded-up robust features and regular moment

NASA Astrophysics Data System (ADS)

Yang, Hongxin; Su, Fulin

2018-01-01

We propose a moving target analysis algorithm using speeded-up robust features (SURF) and regular moment in inverse synthetic aperture radar (ISAR) image sequences. In our study, we first extract interest points from ISAR image sequences by SURF. Different from traditional feature point extraction methods, SURF-based feature points are invariant to scattering intensity, target rotation, and image size. Then, we employ a bilateral feature registering model to match these feature points. The feature registering scheme can not only search the isotropic feature points to link the image sequences but also reduce the error matching pairs. After that, the target centroid is detected by regular moment. Consequently, a cost function based on correlation coefficient is adopted to analyze the motion information. Experimental results based on simulated and real data validate the effectiveness and practicability of the proposed method.

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.

Unsupervised malaria parasite detection based on phase spectrum.

PubMed

Fang, Yuming; Xiong, Wei; Lin, Weisi; Chen, Zhenzhong

2011-01-01

In this paper, we propose a novel method for malaria parasite detection based on phase spectrum. The method first obtains the amplitude spectrum and phase spectrum for blood smear images through Quaternion Fourier Transform (QFT). Then it gets the reconstructed image based on Inverse Quaternion Fourier transform (IQFT) on a constant amplitude spectrum and the original phase spectrum. The malaria parasite areas can be detected easily from the reconstructed blood smear images. Extensive experiments have demonstrated the effectiveness of this novel method.

EDITORIAL: Introduction to the special issue on electromagnetic inverse problems: emerging methods and novel applications Introduction to the special issue on electromagnetic inverse problems: emerging methods and novel applications

NASA Astrophysics Data System (ADS)

Dorn, O.; Lesselier, D.

2010-07-01

Inverse problems in electromagnetics have a long history and have stimulated exciting research over many decades. New applications and solution methods are still emerging, providing a rich source of challenging topics for further investigation. The purpose of this special issue is to combine descriptions of several such developments that are expected to have the potential to fundamentally fuel new research, and to provide an overview of novel methods and applications for electromagnetic inverse problems. There have been several special sections published in Inverse Problems over the last decade addressing fully, or partly, electromagnetic inverse problems. Examples are: Electromagnetic imaging and inversion of the Earth's subsurface (Guest Editors: D Lesselier and T Habashy) October 2000 Testing inversion algorithms against experimental data (Guest Editors: K Belkebir and M Saillard) December 2001 Electromagnetic and ultrasonic nondestructive evaluation (Guest Editors: D Lesselier and J Bowler) December 2002 Electromagnetic characterization of buried obstacles (Guest Editors: D Lesselier and W C Chew) December 2004 Testing inversion algorithms against experimental data: inhomogeneous targets (Guest Editors: K Belkebir and M Saillard) December 2005 Testing inversion algorithms against experimental data: 3D targets (Guest Editors: A Litman and L Crocco) February 2009 In a certain sense, the current issue can be understood as a continuation of this series of special sections on electromagnetic inverse problems. On the other hand, its focus is intended to be more general than previous ones. Instead of trying to cover a well-defined, somewhat specialized research topic as completely as possible, this issue aims to show the broad range of techniques and applications that are relevant to electromagnetic imaging nowadays, which may serve as a source of inspiration and encouragement for all those entering this active and rapidly developing research area. Also, the construction of this special issue is likely to have been different from preceding ones. In addition to the invitations sent to specific research groups involved in electromagnetic inverse problems, the Guest Editors also solicited recommendations, from a large number of experts, of potential authors who were thereupon encouraged to contribute. Moreover, an open call for contributions was published on the homepage of Inverse Problems in order to attract as wide a scope of contributions as possible. This special issue's attempt at generality might also define its limitations: by no means could this collection of papers be exhaustive or complete, and as Guest Editors we are well aware that many exciting topics and potential contributions will be missing. This, however, also determines its very special flavor: besides addressing electromagnetic inverse problems in a broad sense, there were only a few restrictions on the contributions considered for this section. One requirement was plausible evidence of either novelty or the emergent nature of the technique or application described, judged mainly by the referees, and in some cases by the Guest Editors. The technical quality of the contributions always remained a stringent condition of acceptance, final adjudication (possibly questionable either way, not always positive) being made in most cases once a thorough revision process had been carried out. Therefore, we hope that the final result presented here constitutes an interesting collection of novel ideas and applications, properly refereed and edited, which will find its own readership and which can stimulate significant new research in the topics represented. Overall, as Guest Editors, we feel quite fortunate to have obtained such a strong response to the call for this issue and to have a really wide-ranging collection of high-quality contributions which, indeed, can be read from the first to the last page with sustained enthusiasm. A large number of applications and techniques is represented, overall via 16 contributions with 45 authors in total. This shows, in our opinion, that electromagnetic imaging and inversion remain amongst the most challenging and active research areas in applied inverse problems today. Below, we give a brief overview of the contributions included in this issue, ordered alphabetically by the surname of the leading author. 1. The complexity of handling potential randomness of the source in an inverse scattering problem is not minor, and the literature is far from being replete in this configuration. The contribution by G Bao, S N Chow, P Li and H Zhou, `Numerical solution of an inverse medium scattering problem with a stochastic source', exemplifies how to hybridize Wiener chaos expansion with a recursive linearization method in order to solve the stochastic problem as a set of decoupled deterministic ones. 2. In cases where the forward problem is expensive to evaluate, database methods might become a reliable method of choice, while enabling one to deliver more information on the inversion itself. The contribution by S Bilicz, M Lambert and Sz Gyimóthy, `Kriging-based generation of optimal databases as forward and inverse surrogate models', describes such a technique which uses kriging for constructing an efficient database with the goal of achieving an equidistant distribution of points in the measurement space. 3. Anisotropy remains a considerable challenge in electromagnetic imaging, which is tackled in the contribution by F Cakoni, D Colton, P Monk and J Sun, `The inverse electromagnetic scattering problem for anisotropic media', via the fact that transmission eigenvalues can be retrieved from a far-field scattering pattern, yielding, in particular, lower and upper bounds of the index of refraction of the unknown (dielectric anisotropic) scatterer. 4. So-called subspace optimization methods (SOM) have attracted a lot of interest recently in many fields. The contribution by X Chen, `Subspace-based optimization method for inverse scattering problems with an inhomogeneous background medium', illustrates how to address a realistic situation in which the medium containing the unknown obstacles is not homogeneous, via blending a properly developed SOM with a finite-element approach to the required Green's functions. 5. H Egger, M Hanke, C Schneider, J Schöberl and S Zaglmayr, in their contribution `Adjoint-based sampling methods for electromagnetic scattering', show how to efficiently develop sampling methods without explicit knowledge of the dyadic Green's function once an adjoint problem has been solved at much lower computational cost. This is demonstrated by examples in demanding propagative and diffusive situations. 6. Passive sensor arrays can be employed to image reflectors from ambient noise via proper migration of cross-correlation matrices into their embedding medium. This is investigated, and resolution, in particular, is considered in detail, as a function of the characteristics of the sensor array and those of the noise, in the contribution by J Garnier and G Papanicolaou, `Resolution analysis for imaging with noise'. 7. A direct reconstruction technique based on the conformal mapping theorem is proposed and investigated in depth in the contribution by H Haddar and R Kress, `Conformal mapping and impedance tomography'. This paper expands on previous work, with inclusions in homogeneous media, convergence results, and numerical illustrations. 8. The contribution by T Hohage and S Langer, `Acceleration techniques for regularized Newton methods applied to electromagnetic inverse medium scattering problems', focuses on a spectral preconditioner intended to accelerate regularized Newton methods as employed for the retrieval of a local inhomogeneity in a three-dimensional vector electromagnetic case, while also illustrating the implementation of a Lepskiĭ-type stopping rule outsmarting a traditional discrepancy principle. 9. Geophysical applications are a rich source of practically relevant inverse problems. The contribution by M Li, A Abubakar and T Habashy, `Application of a two-and-a-half dimensional model-based algorithm to crosswell electromagnetic data inversion', deals with a model-based inversion technique for electromagnetic imaging which addresses novel challenges such as multi-physics inversion, and incorporation of prior knowledge, such as in hydrocarbon recovery. 10. Non-stationary inverse problems, considered as a special class of Bayesian inverse problems, are framed via an orthogonal decomposition representation in the contribution by A Lipponen, A Seppänen and J P Kaipio, `Reduced order estimation of nonstationary flows with electrical impedance tomography'. The goal is to simultaneously estimate, from electrical impedance tomography data, certain characteristics of the Navier--Stokes fluid flow model together with time-varying concentration distribution. 11. Non-iterative imaging methods of thin, penetrable cracks, based on asymptotic expansion of the scattering amplitude and analysis of the multi-static response matrix, are discussed in the contribution by W-K Park, `On the imaging of thin dielectric inclusions buried within a half-space', completing, for a shallow burial case at multiple frequencies, the direct imaging of small obstacles (here, along their transverse dimension), MUSIC and non-MUSIC type indicator functions being used for that purpose. 12. The contribution by R Potthast, `A study on orthogonality sampling' envisages quick localization and shaping of obstacles from (portions of) far-field scattering patterns collected at one or more time-harmonic frequencies, via the simple calculation (and summation) of scalar products between those patterns and a test function. This is numerically exemplified for Neumann/Dirichlet boundary conditions and homogeneous/heterogeneous embedding media. 13. The contribution by J D Shea, P Kosmas, B D Van Veen and S C Hagness, `Contrast-enhanced microwave imaging of breast tumors: a computational study using 3D realistic numerical phantoms', aims at microwave medical imaging, namely the early detection of breast cancer. The use of contrast enhancing agents is discussed in detail and a number of reconstructions in three-dimensional geometry of realistic numerical breast phantoms are presented. 14. The contribution by D A Subbarayappa and V Isakov, `Increasing stability of the continuation for the Maxwell system', discusses enhanced log-type stability results for continuation of solutions of the time-harmonic Maxwell system, adding a fresh chapter to the interesting story of the study of the Cauchy problem for PDE. 15. In their contribution, `Recent developments of a monotonicity imaging method for magnetic induction tomography in the small skin-depth regime', A Tamburrino, S Ventre and G Rubinacci extend the recently developed monotonicity method toward the application of magnetic induction tomography in order to map surface-breaking defects affecting a damaged metal component. 16. The contribution by F Viani, P Rocca, M Benedetti, G Oliveri and A Massa, `Electromagnetic passive localization and tracking of moving targets in a WSN-infrastructured environment', contributes to what could still be seen as a niche problem, yet both useful in terms of applications, e.g., security, and challenging in terms of methodologies and experiments, in particular, in view of the complexity of environments in which this endeavor is to take place and the variability of the wireless sensor networks employed. To conclude, we would like to thank the able and tireless work of Kate Watt and Zoë Crossman, as past and present Publishers of the Journal, on what was definitely a long and exciting journey (sometimes a little discouraging when reports were not arriving, or authors were late, or Guest Editors overwhelmed) that started from a thorough discussion at the `Manchester workshop on electromagnetic inverse problems' held mid-June 2009, between Kate Watt and the Guest Editors. We gratefully acknowledge the fact that W W Symes gave us his full backing to carry out this special issue and that A K Louis completed it successfully. Last, but not least, the staff of Inverse Problems should be thanked, since they work together to make it a premier journal.

Analyzing the performance of PROSPECT model inversion based on different spectral information for leaf biochemical properties retrieval

NASA Astrophysics Data System (ADS)

Sun, Jia; Shi, Shuo; Yang, Jian; Du, Lin; Gong, Wei; Chen, Biwu; Song, Shalei

2018-01-01

Leaf biochemical constituents provide useful information about major ecological processes. As a fast and nondestructive method, remote sensing techniques are critical to reflect leaf biochemistry via models. PROSPECT model has been widely applied in retrieving leaf traits by providing hemispherical reflectance and transmittance. However, the process of measuring both reflectance and transmittance can be time-consuming and laborious. Contrary to use reflectance spectrum alone in PROSPECT model inversion, which has been adopted by many researchers, this study proposes to use transmission spectrum alone, with the increasing availability of the latter through various remote sensing techniques. Then we analyzed the performance of PROSPECT model inversion with (1) only transmission spectrum, (2) only reflectance and (3) both reflectance and transmittance, using synthetic datasets (with varying levels of random noise and systematic noise) and two experimental datasets (LOPEX and ANGERS). The results show that (1) PROSPECT-5 model inversion based solely on transmission spectrum is viable with results generally better than that based solely on reflectance spectrum; (2) leaf dry matter can be better estimated using only transmittance or reflectance than with both reflectance and transmittance spectra.

Three-Dimensional Inverse Transport Solver Based on Compressive Sensing Technique

NASA Astrophysics Data System (ADS)

Cheng, Yuxiong; Wu, Hongchun; Cao, Liangzhi; Zheng, Youqi

2013-09-01

According to the direct exposure measurements from flash radiographic image, a compressive sensing-based method for three-dimensional inverse transport problem is presented. The linear absorption coefficients and interface locations of objects are reconstructed directly at the same time. It is always very expensive to obtain enough measurements. With limited measurements, compressive sensing sparse reconstruction technique orthogonal matching pursuit is applied to obtain the sparse coefficients by solving an optimization problem. A three-dimensional inverse transport solver is developed based on a compressive sensing-based technique. There are three features in this solver: (1) AutoCAD is employed as a geometry preprocessor due to its powerful capacity in graphic. (2) The forward projection matrix rather than Gauss matrix is constructed by the visualization tool generator. (3) Fourier transform and Daubechies wavelet transform are adopted to convert an underdetermined system to a well-posed system in the algorithm. Simulations are performed and numerical results in pseudo-sine absorption problem, two-cube problem and two-cylinder problem when using compressive sensing-based solver agree well with the reference value.

Comparing Performance of Methods to Deal with Differential Attrition in Lottery Based Evaluations

ERIC Educational Resources Information Center

Zamarro, Gema; Anderson, Kaitlin; Steele, Jennifer; Miller, Trey

2016-01-01

The purpose of this study is to study the performance of different methods (inverse probability weighting and estimation of informative bounds) to control for differential attrition by comparing the results of different methods using two datasets: an original dataset from Portland Public Schools (PPS) subject to high rates of differential…

Two-dimensional frequency-domain acoustic full-waveform inversion with rugged topography

NASA Astrophysics Data System (ADS)

Zhang, Qian-Jiang; Dai, Shi-Kun; Chen, Long-Wei; Li, Kun; Zhao, Dong-Dong; Huang, Xing-Xing

2015-09-01

We studied finite-element-method-based two-dimensional frequency-domain acoustic FWI under rugged topography conditions. The exponential attenuation boundary condition suitable for rugged topography is proposed to solve the cutoff boundary problem as well as to consider the requirement of using the same subdivision grid in joint multifrequency inversion. The proposed method introduces the attenuation factor, and by adjusting it, acoustic waves are sufficiently attenuated in the attenuation layer to minimize the cutoff boundary effect. Based on the law of exponential attenuation, expressions for computing the attenuation factor and the thickness of attenuation layers are derived for different frequencies. In multifrequency-domain FWI, the conjugate gradient method is used to solve equations in the Gauss-Newton algorithm and thus minimize the computation cost in calculating the Hessian matrix. In addition, the effect of initial model selection and frequency combination on FWI is analyzed. Examples using numerical simulations and FWI calculations are used to verify the efficiency of the proposed method.

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.

Cooperative inversion of magnetotelluric and seismic data sets

NASA Astrophysics Data System (ADS)

Markovic, M.; Santos, F.

2012-04-01

Cooperative inversion of magnetotelluric and seismic data sets Milenko Markovic,Fernando Monteiro Santos IDL, Faculdade de Ciências da Universidade de Lisboa 1749-016 Lisboa Inversion of single geophysical data has well-known limitations due to the non-linearity of the fields and non-uniqueness of the model. There is growing need, both in academy and industry to use two or more different data sets and thus obtain subsurface property distribution. In our case ,we are dealing with magnetotelluric and seismic data sets. In our approach,we are developing algorithm based on fuzzy-c means clustering technique, for pattern recognition of geophysical data. Separate inversion is performed on every step, information exchanged for model integration. Interrelationships between parameters from different models is not required in analytical form. We are investigating how different number of clusters, affects zonation and spatial distribution of parameters. In our study optimization in fuzzy c-means clustering (for magnetotelluric and seismic data) is compared for two cases, firstly alternating optimization and then hybrid method (alternating optimization+ Quasi-Newton method). Acknowledgment: This work is supported by FCT Portugal

Efficient Stochastic Inversion Using Adjoint Models and Kernel-PCA

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

Thimmisetty, Charanraj A.; Zhao, Wenju; Chen, Xiao

2017-10-18

Performing stochastic inversion on a computationally expensive forward simulation model with a high-dimensional uncertain parameter space (e.g. a spatial random field) is computationally prohibitive even when gradient information can be computed efficiently. Moreover, the ‘nonlinear’ mapping from parameters to observables generally gives rise to non-Gaussian posteriors even with Gaussian priors, thus hampering the use of efficient inversion algorithms designed for models with Gaussian assumptions. In this paper, we propose a novel Bayesian stochastic inversion methodology, which is characterized by a tight coupling between the gradient-based Langevin Markov Chain Monte Carlo (LMCMC) method and a kernel principal component analysis (KPCA). Thismore » approach addresses the ‘curse-of-dimensionality’ via KPCA to identify a low-dimensional feature space within the high-dimensional and nonlinearly correlated parameter space. In addition, non-Gaussian posterior distributions are estimated via an efficient LMCMC method on the projected low-dimensional feature space. We will demonstrate this computational framework by integrating and adapting our recent data-driven statistics-on-manifolds constructions and reduction-through-projection techniques to a linear elasticity model.« less

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.

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.

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.

Determination of elastic moduli from measured acoustic velocities.

PubMed

Brown, J Michael

2018-06-01

Methods are evaluated in solution of the inverse problem associated with determination of elastic moduli for crystals of arbitrary symmetry from elastic wave velocities measured in many crystallographic directions. A package of MATLAB functions provides a robust and flexible environment for analysis of ultrasonic, Brillouin, or Impulsive Stimulated Light Scattering datasets. Three inverse algorithms are considered: the gradient-based methods of Levenberg-Marquardt and Backus-Gilbert, and a non-gradient-based (Nelder-Mead) simplex approach. Several data types are considered: body wave velocities alone, surface wave velocities plus a side constraint on X-ray-diffraction-based axes compressibilities, or joint body and surface wave velocities. The numerical algorithms are validated through comparisons with prior published results and through analysis of synthetic datasets. Although all approaches succeed in finding low-misfit solutions, the Levenberg-Marquardt method consistently demonstrates effectiveness and computational efficiency. However, linearized gradient-based methods, when applied to a strongly non-linear problem, may not adequately converge to the global minimum. The simplex method, while slower, is less susceptible to being trapped in local misfit minima. A "multi-start" strategy (initiate searches from more than one initial guess) provides better assurance that global minima have been located. Numerical estimates of parameter uncertainties based on Monte Carlo simulations are compared to formal uncertainties based on covariance calculations. Copyright © 2018 Elsevier B.V. All rights reserved.

Adjoint tomography of Europe

NASA Astrophysics Data System (ADS)

Zhu, H.; Bozdag, E.; Peter, D. B.; Tromp, J.

2010-12-01

We use spectral-element and adjoint methods to image crustal and upper mantle heterogeneity in Europe. The study area involves the convergent boundaries of the Eurasian, African and Arabian plates and the divergent boundary between the Eurasian and North American plates, making the tectonic structure of this region complex. Our goal is to iteratively fit observed seismograms and improve crustal and upper mantle images by taking advantage of 3D forward and inverse modeling techniques. We use data from 200 earthquakes with magnitudes between 5 and 6 recorded by 262 stations provided by ORFEUS. Crustal model Crust2.0 combined with mantle model S362ANI comprise the initial 3D model. Before the iterative adjoint inversion, we determine earthquake source parameters in the initial 3D model by using 3D Green functions and their Fréchet derivatives with respect to the source parameters (i.e., centroid moment tensor and location). The updated catalog is used in the subsequent structural inversion. Since we concentrate on upper mantle structures which involve anisotropy, transversely isotropic (frequency-dependent) traveltime sensitivity kernels are used in the iterative inversion. Taking advantage of the adjoint method, we use as many measurements as can obtain based on comparisons between observed and synthetic seismograms. FLEXWIN (Maggi et al., 2009) is used to automatically select measurement windows which are analyzed based on a multitaper technique. The bandpass ranges from 15 second to 150 second. Long-period surface waves and short-period body waves are combined in source relocations and structural inversions. A statistical assessments of traveltime anomalies and logarithmic waveform differences is used to characterize the inverted sources and structure.

Comparative evolution of the inverse problems (Introduction to an interdisciplinary study of the inverse problems)

NASA Technical Reports Server (NTRS)

Sabatier, P. C.

1972-01-01

The progressive realization of the consequences of nonuniqueness imply an evolution of both the methods and the centers of interest in inverse problems. This evolution is schematically described together with the various mathematical methods used. A comparative description is given of inverse methods in scientific research, with examples taken from mathematics, quantum and classical physics, seismology, transport theory, radiative transfer, electromagnetic scattering, electrocardiology, etc. It is hoped that this paper will pave the way for an interdisciplinary study of inverse problems.

Ultrasound viscoelasticity assessment using an adaptive torsional shear wave propagation method

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

Ouared, Abderrahmane; Kazemirad, Siavash; Montagnon, Emmanuel

2016-04-15

Purpose: Different approaches have been used in dynamic elastography to assess mechanical properties of biological tissues. Most techniques are based on a simple inversion based on the measurement of the shear wave speed to assess elasticity, whereas some recent strategies use more elaborated analytical or finite element method (FEM) models. In this study, a new method is proposed for the quantification of both shear storage and loss moduli of confined lesions, in the context of breast imaging, using adaptive torsional shear waves (ATSWs) generated remotely with radiation pressure. Methods: A FEM model was developed to solve the inverse wave propagationmore » problem and obtain viscoelastic properties of interrogated media. The inverse problem was formulated and solved in the frequency domain and its robustness to noise and geometric constraints was evaluated. The proposed model was validated in vitro with two independent rheology methods on several homogeneous and heterogeneous breast tissue-mimicking phantoms over a broad range of frequencies (up to 400 Hz). Results: Viscoelastic properties matched benchmark rheology methods with discrepancies of 8%–38% for the shear modulus G′ and 9%–67% for the loss modulus G″. The robustness study indicated good estimations of storage and loss moduli (maximum mean errors of 19% on G′ and 32% on G″) for signal-to-noise ratios between 19.5 and 8.5 dB. Larger errors were noticed in the case of biases in lesion dimension and position. Conclusions: The ATSW method revealed that it is possible to estimate the viscoelasticity of biological tissues with torsional shear waves when small biases in lesion geometry exist.« less

Forward and inverse solutions for three-element Risley prism beam scanners.

PubMed

Li, Anhu; Liu, Xingsheng; Sun, Wansong

2017-04-03

Scan blind zone and control singularity are two adverse issues for the beam scanning performance in double-prism Risley systems. In this paper, a theoretical model which introduces a third prism is developed. The critical condition for a fully eliminated scan blind zone is determined through a geometric derivation, providing several useful formulae for three-Risley-prism system design. Moreover, inverse solutions for a three-prism system are established, based on the damped least-squares iterative refinement by a forward ray tracing method. It is shown that the efficiency of this iterative calculation of the inverse solutions can be greatly enhanced by a numerical differentiation method. In order to overcome the control singularity problem, the motion law of any one prism in a three-prism system needs to be conditioned, resulting in continuous and steady motion profiles for the other two prisms.

Stretch or contraction induced inversion of rectification in diblock molecular junctions

NASA Astrophysics Data System (ADS)

Zhang, Guang-Ping; Hu, Gui-Chao; Song, Yang; Xie, Zhen; Wang, Chuan-Kui

2013-09-01

Based on ab initio theory and nonequilibrium Green's function method, the effect of stretch or contraction on the rectification in diblock co-oligomer molecular diodes is investigated theoretically. Interestingly, an inversion of rectifying direction induced by stretching or contracting the molecular junctions, which is closely related to the number of the pyrimidinyl-phenyl units, is proposed. The analysis of the molecular projected self-consistent Hamiltonian and the evolution of the frontier molecular orbitals as well as transmission coefficients under external biases gives an inside view of the observed results. It reveals that the asymmetric molecular level shift and asymmetric evolution of orbital wave functions under biases are competitive mechanisms for rectification. The stretching or contracting induced inversion of the rectification is due to the conversion of the dominant mechanism. This work suggests a feasible technique to manipulate the rectification performance in molecular diodes by use of the mechanically controllable method.

Study of multilayer thermal insulation by inverse problems method

NASA Astrophysics Data System (ADS)

Alifanov, O. M.; Nenarokomov, A. V.; Gonzalez, V. M.

2009-11-01

The purpose of this paper is to introduce a new method in the research of radiative and thermal properties of materials with further applications in the design of thermal control systems (TCS) of spacecrafts. In this paper the radiative and thermal properties (emissivity and thermal conductance) of a multilayered thermal-insulating blanket (MLI), which is a screen-vacuum thermal insulation as a part of the TCS for perspective spacecrafts, are estimated. Properties of the materials under study are determined in the result of temperature and heat flux measurement data processing based on the solution of the inverse heat transfer problem (IHTP) technique. Given are physical and mathematical models of heat transfer processes in a specimen of the multilayered thermal-insulating blanket located in the experimental facility. A mathematical formulation of the inverse heat conduction problem is presented as well. The practical approves were made for specimen of the real MLI.

Calculation of susceptibility through multiple orientation sampling (COSMOS): a method for conditioning the inverse problem from measured magnetic field map to susceptibility source image in MRI.

PubMed

Liu, Tian; Spincemaille, Pascal; de Rochefort, Ludovic; Kressler, Bryan; Wang, Yi

2009-01-01

Magnetic susceptibility differs among tissues based on their contents of iron, calcium, contrast agent, and other molecular compositions. Susceptibility modifies the magnetic field detected in the MR signal phase. The determination of an arbitrary susceptibility distribution from the induced field shifts is a challenging, ill-posed inverse problem. A method called "calculation of susceptibility through multiple orientation sampling" (COSMOS) is proposed to stabilize this inverse problem. The field created by the susceptibility distribution is sampled at multiple orientations with respect to the polarization field, B(0), and the susceptibility map is reconstructed by weighted linear least squares to account for field noise and the signal void region. Numerical simulations and phantom and in vitro imaging validations demonstrated that COSMOS is a stable and precise approach to quantify a susceptibility distribution using MRI.

Inverse kinematic-based robot control

NASA Technical Reports Server (NTRS)

Wolovich, W. A.; Flueckiger, K. F.

1987-01-01

A fundamental problem which must be resolved in virtually all non-trivial robotic operations is the well-known inverse kinematic question. More specifically, most of the tasks which robots are called upon to perform are specified in Cartesian (x,y,z) space, such as simple tracking along one or more straight line paths or following a specified surfacer with compliant force sensors and/or visual feedback. In all cases, control is actually implemented through coordinated motion of the various links which comprise the manipulator; i.e., in link space. As a consequence, the control computer of every sophisticated anthropomorphic robot must contain provisions for solving the inverse kinematic problem which, in the case of simple, non-redundant position control, involves the determination of the first three link angles, theta sub 1, theta sub 2, and theta sub 3, which produce a desired wrist origin position P sub xw, P sub yw, and P sub zw at the end of link 3 relative to some fixed base frame. Researchers outline a new inverse kinematic solution and demonstrate its potential via some recent computer simulations. They also compare it to current inverse kinematic methods and outline some of the remaining problems which will be addressed in order to render it fully operational. Also discussed are a number of practical consequences of this technique beyond its obvious use in solving the inverse kinematic question.

Inverse axial mounting stiffness design for lithographic projection lenses.

PubMed

Wen-quan, Yuan; Hong-bo, Shang; Wei, Zhang

2014-09-01

In order to balance axial mounting stiffness of lithographic projection lenses and the image quality under dynamic working conditions, an easy inverse axial mounting stiffness design method is developed in this article. Imaging quality deterioration at the wafer under different axial vibration levels is analyzed. The desired image quality can be determined according to practical requirements, and axial vibrational tolerance of each lens is solved with the damped least-squares method. Based on adaptive interval adjustment, a binary search algorithm, and the finite element method, the axial mounting stiffness of each lens can be traveled in a large interval, and converges to a moderate numerical solution which makes the axial vibrational amplitude of the lens converge to its axial vibrational tolerance. Model simulation is carried out to validate the effectiveness of the method.

Study on validation method for femur finite element model under multiple loading conditions

NASA Astrophysics Data System (ADS)

Guan, Fengjiao; Zhang, Guanjun; Liu, Jie; Wang, Shujing; Luo, Xu

2018-03-01

Acquisition of accurate and reliable constitutive parameters related to bio-tissue materials was beneficial to improve biological fidelity of a Finite Element (FE) model and predict impact damages more effectively. In this paper, a femur FE model was established under multiple loading conditions with diverse impact positions. Then, based on sequential response surface method and genetic algorithms, the material parameters identification was transformed to a multi-response optimization problem. Finally, the simulation results successfully coincided with force-displacement curves obtained by numerous experiments. Thus, computational accuracy and efficiency of the entire inverse calculation process were enhanced. This method was able to effectively reduce the computation time in the inverse process of material parameters. Meanwhile, the material parameters obtained by the proposed method achieved higher accuracy.

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.

Neural network approach for the calculation of potential coefficients in quantum mechanics

NASA Astrophysics Data System (ADS)

Ossandón, Sebastián; Reyes, Camilo; Cumsille, Patricio; Reyes, Carlos M.

2017-05-01

A numerical method based on artificial neural networks is used to solve the inverse Schrödinger equation for a multi-parameter class of potentials. First, the finite element method was used to solve repeatedly the direct problem for different parametrizations of the chosen potential function. Then, using the attainable eigenvalues as a training set of the direct radial basis neural network a map of new eigenvalues was obtained. This relationship was later inverted and refined by training an inverse radial basis neural network, allowing the calculation of the unknown parameters and therefore estimating the potential function. Three numerical examples are presented in order to prove the effectiveness of the method. The results show that the method proposed has the advantage to use less computational resources without a significant accuracy loss.

Studying the Transient Thermal Contact Conductance Between the Exhaust Valve and Its Seat Using the Inverse Method

NASA Astrophysics Data System (ADS)

Nezhad, Mohsen Motahari; Shojaeefard, Mohammad Hassan; Shahraki, Saeid

2016-02-01

In this study, the experiments aimed at analyzing thermally the exhaust valve in an air-cooled internal combustion engine and estimating the thermal contact conductance in fixed and periodic contacts. Due to the nature of internal combustion engines, the duration of contact between the valve and its seat is too short, and much time is needed to reach the quasi-steady state in the periodic contact between the exhaust valve and its seat. Using the methods of linear extrapolation and the inverse solution, the surface contact temperatures and the fixed and periodic thermal contact conductance were calculated. The results of linear extrapolation and inverse methods have similar trends, and based on the error analysis, they are accurate enough to estimate the thermal contact conductance. Moreover, due to the error analysis, a linear extrapolation method using inverse ratio is preferred. The effects of pressure, contact frequency, heat flux, and cooling air speed on thermal contact conductance have been investigated. The results show that by increasing the contact pressure the thermal contact conductance increases substantially. In addition, by increasing the engine speed the thermal contact conductance decreases. On the other hand, by boosting the air speed the thermal contact conductance increases, and by raising the heat flux the thermal contact conductance reduces. The average calculated error equals to 12.9 %.

A forward model and conjugate gradient inversion technique for low-frequency ultrasonic imaging.

PubMed

van Dongen, Koen W A; Wright, William M D

2006-10-01

Emerging methods of hyperthermia cancer treatment require noninvasive temperature monitoring, and ultrasonic techniques show promise in this regard. Various tomographic algorithms are available that reconstruct sound speed or contrast profiles, which can be related to temperature distribution. The requirement of a high enough frequency for adequate spatial resolution and a low enough frequency for adequate tissue penetration is a difficult compromise. In this study, the feasibility of using low frequency ultrasound for imaging and temperature monitoring was investigated. The transient probing wave field had a bandwidth spanning the frequency range 2.5-320.5 kHz. The results from a forward model which computed the propagation and scattering of low-frequency acoustic pressure and velocity wave fields were used to compare three imaging methods formulated within the Born approximation, representing two main types of reconstruction. The first uses Fourier techniques to reconstruct sound-speed profiles from projection or Radon data based on optical ray theory, seen as an asymptotical limit for comparison. The second uses backpropagation and conjugate gradient inversion methods based on acoustical wave theory. The results show that the accuracy in localization was 2.5 mm or better when using low frequencies and the conjugate gradient inversion scheme, which could be used for temperature monitoring.

Inversion of Surface-wave Dispersion Curves due to Low-velocity-layer Models

NASA Astrophysics Data System (ADS)

Shen, C.; Xia, J.; Mi, B.

2016-12-01

A successful inversion relies on exact forward modeling methods. It is a key step to accurately calculate multi-mode dispersion curves of a given model in high-frequency surface-wave (Rayleigh wave and Love wave) methods. For normal models (shear (S)-wave velocity increasing with depth), their theoretical dispersion curves completely match the dispersion spectrum that is generated based on wave equation. For models containing a low-velocity-layer, however, phase velocities calculated by existing forward-modeling algorithms (e.g. Thomson-Haskell algorithm, Knopoff algorithm, fast vector-transfer algorithm and so on) fail to be consistent with the dispersion spectrum at a high frequency range. They will approach a value that close to the surface-wave velocity of the low-velocity-layer under the surface layer, rather than that of the surface layer when their corresponding wavelengths are short enough. This phenomenon conflicts with the characteristics of surface waves, which results in an erroneous inverted model. By comparing the theoretical dispersion curves with simulated dispersion energy, we proposed a direct and essential solution to accurately compute surface-wave phase velocities due to low-velocity-layer models. Based on the proposed forward modeling technique, we can achieve correct inversion for these types of models. Several synthetic data proved the effectiveness of our method.

Three-dimensional mapping of the local interstellar medium with composite data

NASA Astrophysics Data System (ADS)

Capitanio, L.; Lallement, R.; Vergely, J. L.; Elyajouri, M.; Monreal-Ibero, A.

2017-10-01

Context. Three-dimensional maps of the Galactic interstellar medium are general astrophysical tools. Reddening maps may be based on the inversion of color excess measurements for individual target stars or on statistical methods using stellar surveys. Three-dimensional maps based on diffuse interstellar bands (DIBs) have also been produced. All methods benefit from the advent of massive surveys and may benefit from Gaia data. Aims: All of the various methods and databases have their own advantages and limitations. Here we present a first attempt to combine different datasets and methods to improve the local maps. Methods: We first updated our previous local dust maps based on a regularized Bayesian inversion of individual color excess data by replacing Hipparcos or photometric distances with Gaia Data Release 1 values when available. Secondly, we complemented this database with a series of ≃5000 color excess values estimated from the strength of the λ15273 DIB toward stars possessing a Gaia parallax. The DIB strengths were extracted from SDSS/APOGEE spectra. Third, we computed a low-resolution map based on a grid of Pan-STARRS reddening measurements by means of a new hierarchical technique and used this map as the prior distribution during the inversion of the two other datasets. Results: The use of Gaia parallaxes introduces significant changes in some areas and globally increases the compactness of the structures. Additional DIB-based data make it possible to assign distances to clouds located behind closer opaque structures and do not introduce contradictory information for the close structures. A more realistic prior distribution instead of a plane-parallel homogeneous distribution helps better define the structures. We validated the results through comparisons with other maps and with soft X-ray data. Conclusions: Our study demonstrates that the combination of various tracers is a potential tool for more accurate maps. An online tool makes it possible to retrieve maps and reddening estimations. Our online tool is available at http://stilism.obspm.fr

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.

A Study on Multi-Swing Stability Analysis of Power System using Damping Rate Inversion

NASA Astrophysics Data System (ADS)

Tsuji, Takao; Morii, Yuki; Oyama, Tsutomu; Hashiguchi, Takuhei; Goda, Tadahiro; Nomiyama, Fumitoshi; Kosugi, Narifumi

In recent years, much attention is paid to the nonlinear analysis method in the field of stability analysis of power systems. Especially for the multi-swing stability analysis, the unstable limit cycle has an important meaning as a stability margin. It is required to develop a high speed calculation method of stability boundary regarding multi-swing stability because the real-time calculation of ATC is necessary to realize the flexible wheeling trades. Therefore, the authors have developed a new method which can calculate the unstable limit cycle based on damping rate inversion method. Using the unstable limit cycle, it is possible to predict the multi-swing stability at the time when the fault transmission line is reclosed. The proposed method is tested in Lorenz equation, single-machine infinite-bus system model and IEEJ WEST10 system model.

Kinematic inversion of the 2008 Mw7 Iwate-Miyagi (Japan) earthquake by two independent methods: Sensitivity and resolution analysis

NASA Astrophysics Data System (ADS)

Gallovic, Frantisek; Cirella, Antonella; Plicka, Vladimir; Piatanesi, Alessio

2013-04-01

On 14 June 2008, UTC 23:43, the border of Iwate and Miyagi prefectures was hit by an Mw7 reverse-fault type crustal earthquake. The event is known to have the largest ground acceleration observed to date (~4g), which was recorded at station IWTH25. We analyze observed strong motion data with the objective to image the event rupture process and the associated uncertainties. Two different slip inversion approaches are used, the difference between the two methods being only in the parameterization of the source model. To minimize mismodeling of the propagation effects we use crustal model obtained by full waveform inversion of aftershock records in the frequency range between 0.05-0.3 Hz. In the first method, based on linear formulation, the parameters are represented by samples of slip velocity functions along the (finely discretized) fault in a time window spanning the whole rupture duration. Such a source description is very general with no prior constraint on the nucleation point, rupture velocity, shape of the velocity function. Thus the inversion could resolve very general (unexpected) features of the rupture evolution, such as multiple rupturing, rupture-propagation reversals, etc. On the other hand, due to the relatively large number of model parameters, the inversion result is highly non-unique, with possibility of obtaining a biased solution. The second method is a non-linear global inversion technique, where each point on the fault can slip only once, following a prescribed functional form of the source time function. We invert simultaneously for peak slip velocity, slip angle, rise time and rupture time by allowing a given range of variability for each kinematic model parameter. For this reason, unlike to the linear inversion approach, the rupture process needs a smaller number of parameters to be retrieved, and is more constrained with a proper control on the allowed range of parameter values. In order to test the resolution and reliability of the retrieved models, we present a thorough analysis of the performance of the two inversion approaches. In fact, depending on the inversion strategy and the intrinsic 'non-uniqueness' of the inverse problem, the final slip maps and distribution of rupture onset times are generally different, sometimes even incompatible with each other. Great emphasis is devoted to the uncertainty estimate of both techniques. Thus we do not compare only the best fitting models, but their 'compatibility' in terms of the uncertainty limits.

3D electromagnetic modelling of a TTI medium and TTI effects in inversion

NASA Astrophysics Data System (ADS)

Jaysaval, Piyoosh; Shantsev, Daniil; de la Kethulle de Ryhove, Sébastien

2016-04-01

We present a numerical algorithm for 3D electromagnetic (EM) forward modelling in conducting media with general electric anisotropy. The algorithm is based on the finite-difference discretization of frequency-domain Maxwell's equations on a Lebedev grid, in which all components of the electric field are collocated but half a spatial step staggered with respect to the magnetic field components, which also are collocated. This leads to a system of linear equations that is solved using a stabilized biconjugate gradient method with a multigrid preconditioner. We validate the accuracy of the numerical results for layered and 3D tilted transverse isotropic (TTI) earth models representing typical scenarios used in the marine controlled-source EM method. It is then demonstrated that not taking into account the full anisotropy of the conductivity tensor can lead to misleading inversion results. For simulation data corresponding to a 3D model with a TTI anticlinal structure, a standard vertical transverse isotropic inversion is not able to image a resistor, while for a 3D model with a TTI synclinal structure the inversion produces a false resistive anomaly. If inversion uses the proposed forward solver that can handle TTI anisotropy, it produces resistivity images consistent with the true models.

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.

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.

The Computation of Global Viscoelastic Co- and Post-seismic Displacement in a Realistic Earth Model by Straightforward Numerical Inverse Laplace Integration

NASA Astrophysics Data System (ADS)

Tang, H.; Sun, W.

2016-12-01

The theoretical computation of dislocation theory in a given earth model is necessary in the explanation of observations of the co- and post-seismic deformation of earthquakes. For this purpose, computation theories based on layered or pure half space [Okada, 1985; Okubo, 1992; Wang et al., 2006] and on spherically symmetric earth [Piersanti et al., 1995; Pollitz, 1997; Sabadini & Vermeersen, 1997; Wang, 1999] have been proposed. It is indicated that the compressibility, curvature and the continuous variation of the radial structure of Earth should be simultaneously taken into account for modern high precision displacement-based observations like GPS. Therefore, Tanaka et al. [2006; 2007] computed global displacement and gravity variation by combining the reciprocity theorem (RPT) [Okubo, 1993] and numerical inverse Laplace integration (NIL) instead of the normal mode method [Peltier, 1974]. Without using RPT, we follow the straightforward numerical integration of co-seismic deformation given by Sun et al. [1996] to present a straightforward numerical inverse Laplace integration method (SNIL). This method is used to compute the co- and post-seismic displacement of point dislocations buried in a spherically symmetric, self-gravitating viscoelastic and multilayered earth model and is easy to extended to the application of geoid and gravity. Comparing with pre-existing method, this method is relatively more straightforward and time-saving, mainly because we sum associated Legendre polynomials and dislocation love numbers before using Riemann-Merlin formula to implement SNIL.

A model reduction approach to numerical inversion for a parabolic partial differential equation

NASA Astrophysics Data System (ADS)

Borcea, Liliana; Druskin, Vladimir; Mamonov, Alexander V.; Zaslavsky, Mikhail

2014-12-01

We propose a novel numerical inversion algorithm for the coefficients of parabolic partial differential equations, based on model reduction. The study is motivated by the application of controlled source electromagnetic exploration, where the unknown is the subsurface electrical resistivity and the data are time resolved surface measurements of the magnetic field. The algorithm presented in this paper considers inversion in one and two dimensions. The reduced model is obtained with rational interpolation in the frequency (Laplace) domain and a rational Krylov subspace projection method. It amounts to a nonlinear mapping from the function space of the unknown resistivity to the small dimensional space of the parameters of the reduced model. We use this mapping as a nonlinear preconditioner for the Gauss-Newton iterative solution of the inverse problem. The advantage of the inversion algorithm is twofold. First, the nonlinear preconditioner resolves most of the nonlinearity of the problem. Thus the iterations are less likely to get stuck in local minima and the convergence is fast. Second, the inversion is computationally efficient because it avoids repeated accurate simulations of the time-domain response. We study the stability of the inversion algorithm for various rational Krylov subspaces, and assess its performance with numerical experiments.

Simulation studies of phase inversion in agitated vessels using a Monte Carlo technique.

PubMed

Yeo, Leslie Y; Matar, Omar K; Perez de Ortiz, E Susana; Hewitt, Geoffrey F

2002-04-15

A speculative study on the conditions under which phase inversion occurs in agitated liquid-liquid dispersions is conducted using a Monte Carlo technique. The simulation is based on a stochastic model, which accounts for fundamental physical processes such as drop deformation, breakup, and coalescence, and utilizes the minimization of interfacial energy as a criterion for phase inversion. Profiles of the interfacial energy indicate that a steady-state equilibrium is reached after a sufficiently large number of random moves and that predictions are insensitive to initial drop conditions. The calculated phase inversion holdup is observed to increase with increasing density and viscosity ratio, and to decrease with increasing agitation speed for a fixed viscosity ratio. It is also observed that, for a fixed viscosity ratio, the phase inversion holdup remains constant for large enough agitation speeds. The proposed model is therefore capable of achieving reasonable qualitative agreement with general experimental trends and of reproducing key features observed experimentally. The results of this investigation indicate that this simple stochastic method could be the basis upon which more advanced models for predicting phase inversion behavior can be developed.

Following the footprints of polymorphic inversions on SNP data: from detection to association tests

PubMed Central

Cáceres, Alejandro; González, Juan R.

2015-01-01

Inversion polymorphisms have important phenotypic and evolutionary consequences in humans. Two different methodologies have been used to infer inversions from SNP dense data, enabling the use of large cohorts for their study. One approach relies on the differences in linkage disequilibrium across breakpoints; the other one captures the internal haplotype groups that tag the inversion status of chromosomes. In this article, we assessed the convergence of the two methods in the detection of 20 human inversions that have been reported in the literature. The methods converged in four inversions including inv-8p23, for which we studied its association with low-BMI in American children. Using a novel haplotype tagging method with control on inversion ancestry, we computed the frequency of inv-8p23 in two American cohorts and observed inversion haplotype admixture. Accounting for haplotype ancestry, we found that the European inverted allele in children carries a recessive risk of underweight, validated in an independent Spanish cohort (combined: OR= 2.00, P = 0.001). While the footprints of inversions on SNP data are complex, we show that systematic analyses, such as convergence of different methods and controlling for ancestry, can reveal the contribution of inversions to the ancestral composition of populations and to the heritability of human disease. PMID:25672393

Nonlinear inversion of resistivity sounding data for 1-D earth models using the Neighbourhood Algorithm

NASA Astrophysics Data System (ADS)

Ojo, A. O.; Xie, Jun; Olorunfemi, M. O.

2018-01-01

To reduce ambiguity related to nonlinearities in the resistivity model-data relationships, an efficient direct-search scheme employing the Neighbourhood Algorithm (NA) was implemented to solve the 1-D resistivity problem. In addition to finding a range of best-fit models which are more likely to be global minimums, this method investigates the entire multi-dimensional model space and provides additional information about the posterior model covariance matrix, marginal probability density function and an ensemble of acceptable models. This provides new insights into how well the model parameters are constrained and make assessing trade-offs between them possible, thus avoiding some common interpretation pitfalls. The efficacy of the newly developed program is tested by inverting both synthetic (noisy and noise-free) data and field data from other authors employing different inversion methods so as to provide a good base for comparative performance. In all cases, the inverted model parameters were in good agreement with the true and recovered model parameters from other methods and remarkably correlate with the available borehole litho-log and known geology for the field dataset. The NA method has proven to be useful whilst a good starting model is not available and the reduced number of unknowns in the 1-D resistivity inverse problem makes it an attractive alternative to the linearized methods. Hence, it is concluded that the newly developed program offers an excellent complementary tool for the global inversion of the layered resistivity structure.

Approximation of reliability of direct genomic breeding values

USDA-ARS?s Scientific Manuscript database

Two methods to efficiently approximate theoretical genomic reliabilities are presented. The first method is based on the direct inverse of the left hand side (LHS) of mixed model equations. It uses the genomic relationship matrix for a small subset of individuals with the highest genomic relationshi...

Methods to approximate reliabilities in single-step genomic evaluation

USDA-ARS?s Scientific Manuscript database

Reliability of predictions from single-step genomic BLUP (ssGBLUP) can be calculated by inversion, but that is not feasible for large data sets. Two methods of approximating reliability were developed based on decomposition of a function of reliability into contributions from records, pedigrees, and...

Inverse scattering approach to improving pattern recognition

NASA Astrophysics Data System (ADS)

Chapline, George; Fu, Chi-Yung

2005-05-01

The Helmholtz machine provides what may be the best existing model for how the mammalian brain recognizes patterns. Based on the observation that the "wake-sleep" algorithm for training a Helmholtz machine is similar to the problem of finding the potential for a multi-channel Schrodinger equation, we propose that the construction of a Schrodinger potential using inverse scattering methods can serve as a model for how the mammalian brain learns to extract essential information from sensory data. In particular, inverse scattering theory provides a conceptual framework for imagining how one might use EEG and MEG observations of brain-waves together with sensory feedback to improve human learning and pattern recognition. Longer term, implementation of inverse scattering algorithms on a digital or optical computer could be a step towards mimicking the seamless information fusion of the mammalian brain.

Harmonic generation with a dual frequency pulse.

PubMed

Keravnou, Christina P; Averkiou, Michalakis A

2014-05-01

Nonlinear imaging was implemented in commercial ultrasound systems over the last 15 years offering major advantages in many clinical applications. In this work, pulsing schemes coupled with a dual frequency pulse are presented. The pulsing schemes considered were pulse inversion, power modulation, and power modulated pulse inversion. The pulse contains a fundamental frequency f and a specified amount of its second harmonic 2f. The advantages and limitations of this method were evaluated with both acoustic measurements of harmonic generation and theoretical simulations based on the KZK equation. The use of two frequencies in a pulse results in the generation of the sum and difference frequency components in addition to the other harmonic components. While with single frequency pulses, only power modulation and power modulated pulse inversion contained odd harmonic components, with the dual frequency pulse, pulse inversion now also contains odd harmonic components.

Inverse Scattering Approach to Improving Pattern Recognition

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

Chapline, G; Fu, C

2005-02-15

The Helmholtz machine provides what may be the best existing model for how the mammalian brain recognizes patterns. Based on the observation that the ''wake-sleep'' algorithm for training a Helmholtz machine is similar to the problem of finding the potential for a multi-channel Schrodinger equation, we propose that the construction of a Schrodinger potential using inverse scattering methods can serve as a model for how the mammalian brain learns to extract essential information from sensory data. In particular, inverse scattering theory provides a conceptual framework for imagining how one might use EEG and MEG observations of brain-waves together with sensorymore » feedback to improve human learning and pattern recognition. Longer term, implementation of inverse scattering algorithms on a digital or optical computer could be a step towards mimicking the seamless information fusion of the mammalian brain.« less

Inverse Diffusion Curves Using Shape Optimization.

PubMed

Zhao, Shuang; Durand, Fredo; Zheng, Changxi

2018-07-01

The inverse diffusion curve problem focuses on automatic creation of diffusion curve images that resemble user provided color fields. This problem is challenging since the 1D curves have a nonlinear and global impact on resulting color fields via a partial differential equation (PDE). We introduce a new approach complementary to previous methods by optimizing curve geometry. In particular, we propose a novel iterative algorithm based on the theory of shape derivatives. The resulting diffusion curves are clean and well-shaped, and the final image closely approximates the input. Our method provides a user-controlled parameter to regularize curve complexity, and generalizes to handle input color fields represented in a variety of formats.

Inverse Tone Mapping Based upon Retina Response

PubMed Central

Huo, Yongqing; Yang, Fan; Brost, Vincent

2014-01-01

The development of high dynamic range (HDR) display arouses the research of inverse tone mapping methods, which expand dynamic range of the low dynamic range (LDR) image to match that of HDR monitor. This paper proposed a novel physiological approach, which could avoid artifacts occurred in most existing algorithms. Inspired by the property of the human visual system (HVS), this dynamic range expansion scheme performs with a low computational complexity and a limited number of parameters and obtains high-quality HDR results. Comparisons with three recent algorithms in the literature also show that the proposed method reveals more important image details and produces less contrast loss and distortion. PMID:24744678

Laterally constrained inversion for CSAMT data interpretation

NASA Astrophysics Data System (ADS)

Wang, Ruo; Yin, Changchun; Wang, Miaoyue; Di, Qingyun

2015-10-01

Laterally constrained inversion (LCI) has been successfully applied to the inversion of dc resistivity, TEM and airborne EM data. However, it hasn't been yet applied to the interpretation of controlled-source audio-frequency magnetotelluric (CSAMT) data. In this paper, we apply the LCI method for CSAMT data inversion by preconditioning the Jacobian matrix. We apply a weighting matrix to Jacobian to balance the sensitivity of model parameters, so that the resolution with respect to different model parameters becomes more uniform. Numerical experiments confirm that this can improve the convergence of the inversion. We first invert a synthetic dataset with and without noise to investigate the effect of LCI applications to CSAMT data, for the noise free data, the results show that the LCI method can recover the true model better compared to the traditional single-station inversion; and for the noisy data, the true model is recovered even with a noise level of 8%, indicating that LCI inversions are to some extent noise insensitive. Then, we re-invert two CSAMT datasets collected respectively in a watershed and a coal mine area in Northern China and compare our results with those from previous inversions. The comparison with the previous inversion in a coal mine shows that LCI method delivers smoother layer interfaces that well correlate to seismic data, while comparison with a global searching algorithm of simulated annealing (SA) in a watershed shows that though both methods deliver very similar good results, however, LCI algorithm presented in this paper runs much faster. The inversion results for the coal mine CSAMT survey show that a conductive water-bearing zone that was not revealed by the previous inversions has been identified by the LCI. This further demonstrates that the method presented in this paper works for CSAMT data inversion.

Directional Slack-Based Measure for the Inverse Data Envelopment Analysis

PubMed Central

Abu Bakar, Mohd Rizam; Lee, Lai Soon; Jaafar, Azmi B.; Heydar, Maryam

2014-01-01

A novel technique has been introduced in this research which lends its basis to the Directional Slack-Based Measure for the inverse Data Envelopment Analysis. In practice, the current research endeavors to elucidate the inverse directional slack-based measure model within a new production possibility set. On one occasion, there is a modification imposed on the output (input) quantities of an efficient decision making unit. In detail, the efficient decision making unit in this method was omitted from the present production possibility set but substituted by the considered efficient decision making unit while its input and output quantities were subsequently modified. The efficiency score of the entire DMUs will be retained in this approach. Also, there would be an improvement in the efficiency score. The proposed approach was investigated in this study with reference to a resource allocation problem. It is possible to simultaneously consider any upsurges (declines) of certain outputs associated with the efficient decision making unit. The significance of the represented model is accentuated by presenting numerical examples. PMID:24883350