A frequency domain radar interferometric imaging (FII) technique based on high-resolution methods

NASA Astrophysics Data System (ADS)

Luce, H.; Yamamoto, M.; Fukao, S.; Helal, D.; Crochet, M.

2001-01-01

In the present work, we propose a frequency-domain interferometric imaging (FII) technique for a better knowledge of the vertical distribution of the atmospheric scatterers detected by MST radars. This is an extension of the dual frequency-domain interferometry (FDI) technique to multiple frequencies. Its objective is to reduce the ambiguity (resulting from the use of only two adjacent frequencies), inherent with the FDI technique. Different methods, commonly used in antenna array processing, are first described within the context of application to the FII technique. These methods are the Fourier-based imaging, the Capon's and the singular value decomposition method used with the MUSIC algorithm. Some preliminary simulations and tests performed on data collected with the middle and upper atmosphere (MU) radar (Shigaraki, Japan) are also presented. This work is a first step in the developments of the FII technique which seems to be very promising.

Scalable parallel elastic-plastic finite element analysis using a quasi-Newton method with a balancing domain decomposition preconditioner

NASA Astrophysics Data System (ADS)

Yusa, Yasunori; Okada, Hiroshi; Yamada, Tomonori; Yoshimura, Shinobu

2018-04-01

A domain decomposition method for large-scale elastic-plastic problems is proposed. The proposed method is based on a quasi-Newton method in conjunction with a balancing domain decomposition preconditioner. The use of a quasi-Newton method overcomes two problems associated with the conventional domain decomposition method based on the Newton-Raphson method: (1) avoidance of a double-loop iteration algorithm, which generally has large computational complexity, and (2) consideration of the local concentration of nonlinear deformation, which is observed in elastic-plastic problems with stress concentration. Moreover, the application of a balancing domain decomposition preconditioner ensures scalability. Using the conventional and proposed domain decomposition methods, several numerical tests, including weak scaling tests, were performed. The convergence performance of the proposed method is comparable to that of the conventional method. In particular, in elastic-plastic analysis, the proposed method exhibits better convergence performance than the conventional method.

Parallel Domain Decomposition Formulation and Software for Large-Scale Sparse Symmetrical/Unsymmetrical Aeroacoustic Applications

NASA Technical Reports Server (NTRS)

Nguyen, D. T.; Watson, Willie R. (Technical Monitor)

2005-01-01

The overall objectives of this research work are to formulate and validate efficient parallel algorithms, and to efficiently design/implement computer software for solving large-scale acoustic problems, arised from the unified frameworks of the finite element procedures. The adopted parallel Finite Element (FE) Domain Decomposition (DD) procedures should fully take advantages of multiple processing capabilities offered by most modern high performance computing platforms for efficient parallel computation. To achieve this objective. the formulation needs to integrate efficient sparse (and dense) assembly techniques, hybrid (or mixed) direct and iterative equation solvers, proper pre-conditioned strategies, unrolling strategies, and effective processors' communicating schemes. Finally, the numerical performance of the developed parallel finite element procedures will be evaluated by solving series of structural, and acoustic (symmetrical and un-symmetrical) problems (in different computing platforms). Comparisons with existing "commercialized" and/or "public domain" software are also included, whenever possible.

Domain decomposition: A bridge between nature and parallel computers

NASA Technical Reports Server (NTRS)

Keyes, David E.

1992-01-01

Domain decomposition is an intuitive organizing principle for a partial differential equation (PDE) computation, both physically and architecturally. However, its significance extends beyond the readily apparent issues of geometry and discretization, on one hand, and of modular software and distributed hardware, on the other. Engineering and computer science aspects are bridged by an old but recently enriched mathematical theory that offers the subject not only unity, but also tools for analysis and generalization. Domain decomposition induces function-space and operator decompositions with valuable properties. Function-space bases and operator splittings that are not derived from domain decompositions generally lack one or more of these properties. The evolution of domain decomposition methods for elliptically dominated problems has linked two major algorithmic developments of the last 15 years: multilevel and Krylov methods. Domain decomposition methods may be considered descendants of both classes with an inheritance from each: they are nearly optimal and at the same time efficiently parallelizable. Many computationally driven application areas are ripe for these developments. A progression is made from a mathematically informal motivation for domain decomposition methods to a specific focus on fluid dynamics applications. To be introductory rather than comprehensive, simple examples are provided while convergence proofs and algorithmic details are left to the original references; however, an attempt is made to convey their most salient features, especially where this leads to algorithmic insight.

A Domain Decomposition Parallelization of the Fast Marching Method

NASA Technical Reports Server (NTRS)

Herrmann, M.

2003-01-01

In this paper, the first domain decomposition parallelization of the Fast Marching Method for level sets has been presented. Parallel speedup has been demonstrated in both the optimal and non-optimal domain decomposition case. The parallel performance of the proposed method is strongly dependent on load balancing separately the number of nodes on each side of the interface. A load imbalance of nodes on either side of the domain leads to an increase in communication and rollback operations. Furthermore, the amount of inter-domain communication can be reduced by aligning the inter-domain boundaries with the interface normal vectors. In the case of optimal load balancing and aligned inter-domain boundaries, the proposed parallel FMM algorithm is highly efficient, reaching efficiency factors of up to 0.98. Future work will focus on the extension of the proposed parallel algorithm to higher order accuracy. Also, to further enhance parallel performance, the coupling of the domain decomposition parallelization to the G(sub 0)-based parallelization will be investigated.

Approximation, abstraction and decomposition in search and optimization

NASA Technical Reports Server (NTRS)

Ellman, Thomas

1992-01-01

In this paper, I discuss four different areas of my research. One portion of my research has focused on automatic synthesis of search control heuristics for constraint satisfaction problems (CSPs). I have developed techniques for automatically synthesizing two types of heuristics for CSPs: Filtering functions are used to remove portions of a search space from consideration. Another portion of my research is focused on automatic synthesis of hierarchic algorithms for solving constraint satisfaction problems (CSPs). I have developed a technique for constructing hierarchic problem solvers based on numeric interval algebra. Another portion of my research is focused on automatic decomposition of design optimization problems. We are using the design of racing yacht hulls as a testbed domain for this research. Decomposition is especially important in the design of complex physical shapes such as yacht hulls. Another portion of my research is focused on intelligent model selection in design optimization. The model selection problem results from the difficulty of using exact models to analyze the performance of candidate designs.

Vectorial finite elements for solving the radiative transfer equation

NASA Astrophysics Data System (ADS)

Badri, M. A.; Jolivet, P.; Rousseau, B.; Le Corre, S.; Digonnet, H.; Favennec, Y.

2018-06-01

The discrete ordinate method coupled with the finite element method is often used for the spatio-angular discretization of the radiative transfer equation. In this paper we attempt to improve upon such a discretization technique. Instead of using standard finite elements, we reformulate the radiative transfer equation using vectorial finite elements. In comparison to standard finite elements, this reformulation yields faster timings for the linear system assemblies, as well as for the solution phase when using scattering media. The proposed vectorial finite element discretization for solving the radiative transfer equation is cross-validated against a benchmark problem available in literature. In addition, we have used the method of manufactured solutions to verify the order of accuracy for our discretization technique within different absorbing, scattering, and emitting media. For solving large problems of radiation on parallel computers, the vectorial finite element method is parallelized using domain decomposition. The proposed domain decomposition method scales on large number of processes, and its performance is unaffected by the changes in optical thickness of the medium. Our parallel solver is used to solve a large scale radiative transfer problem of the Kelvin-cell radiation.

Asymmetric optical image encryption using Kolmogorov phase screens and equal modulus decomposition

NASA Astrophysics Data System (ADS)

Kumar, Ravi; Bhaduri, Basanta; Quan, Chenggen

2017-11-01

An asymmetric technique for optical image encryption is proposed using Kolmogorov phase screens (KPSs) and equal modulus decomposition (EMD). The KPSs are generated using the power spectral density of Kolmogorov turbulence. The input image is first randomized and then Fresnel propagated with distance d. Further, the output in the Fresnel domain is modulated with a random phase mask, and the gyrator transform (GT) of the modulated image is obtained with an angle α. The EMD is operated on the GT spectrum to get the complex images, Z1 and Z2. Among these, Z2 is reserved as a private key for decryption and Z1 is propagated through a medium consisting of four KPSs, located at specified distances, to get the final encrypted image. The proposed technique provides a large set of security keys and is robust against various potential attacks. Numerical simulation results validate the effectiveness and security of the proposed technique.

A New Domain Decomposition Approach for the Gust Response Problem

NASA Technical Reports Server (NTRS)

Scott, James R.; Atassi, Hafiz M.; Susan-Resiga, Romeo F.

2002-01-01

A domain decomposition method is developed for solving the aerodynamic/aeroacoustic problem of an airfoil in a vortical gust. The computational domain is divided into inner and outer regions wherein the governing equations are cast in different forms suitable for accurate computations in each region. Boundary conditions which ensure continuity of pressure and velocity are imposed along the interface separating the two regions. A numerical study is presented for reduced frequencies ranging from 0.1 to 3.0. It is seen that the domain decomposition approach in providing robust and grid independent solutions.

Domain Decomposition: A Bridge between Nature and Parallel Computers

DTIC Science & Technology

1992-09-01

B., "Domain Decomposition Algorithms for Indefinite Elliptic Problems," S"IAM Journal of S; cientific and Statistical (’omputing, Vol. 13, 1992, pp...AD-A256 575 NASA Contractor Report 189709 ICASE Report No. 92-44 ICASE DOMAIN DECOMPOSITION: A BRIDGE BETWEEN NATURE AND PARALLEL COMPUTERS DTIC dE...effectively implemented on dis- tributed memory multiprocessors. In 1990 (as reported in Ref. 38 using the tile algo- rithm), a 103,201-unknown 2D elliptic

Optimal domain decomposition strategies

NASA Technical Reports Server (NTRS)

Yoon, Yonghyun; Soni, Bharat K.

1995-01-01

The primary interest of the authors is in the area of grid generation, in particular, optimal domain decomposition about realistic configurations. A grid generation procedure with optimal blocking strategies has been developed to generate multi-block grids for a circular-to-rectangular transition duct. The focus of this study is the domain decomposition which optimizes solution algorithm/block compatibility based on geometrical complexities as well as the physical characteristics of flow field. The progress realized in this study is summarized in this paper.

Spectral element method for elastic and acoustic waves in frequency domain

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

Shi, Linlin; Zhou, Yuanguo; Wang, Jia-Min

Numerical techniques in time domain are widespread in seismic and acoustic modeling. In some applications, however, frequency-domain techniques can be advantageous over the time-domain approach when narrow band results are desired, especially if multiple sources can be handled more conveniently in the frequency domain. Moreover, the medium attenuation effects can be more accurately and conveniently modeled in the frequency domain. In this paper, we present a spectral-element method (SEM) in frequency domain to simulate elastic and acoustic waves in anisotropic, heterogeneous, and lossy media. The SEM is based upon the finite-element framework and has exponential convergence because of the usemore » of GLL basis functions. The anisotropic perfectly matched layer is employed to truncate the boundary for unbounded problems. Compared with the conventional finite-element method, the number of unknowns in the SEM is significantly reduced, and higher order accuracy is obtained due to its spectral accuracy. To account for the acoustic-solid interaction, the domain decomposition method (DDM) based upon the discontinuous Galerkin spectral-element method is proposed. Numerical experiments show the proposed method can be an efficient alternative for accurate calculation of elastic and acoustic waves in frequency domain.« less

A partitioned model order reduction approach to rationalise computational expenses in nonlinear fracture mechanics

PubMed Central

Kerfriden, P.; Goury, O.; Rabczuk, T.; Bordas, S.P.A.

2013-01-01

We propose in this paper a reduced order modelling technique based on domain partitioning for parametric problems of fracture. We show that coupling domain decomposition and projection-based model order reduction permits to focus the numerical effort where it is most needed: around the zones where damage propagates. No a priori knowledge of the damage pattern is required, the extraction of the corresponding spatial regions being based solely on algebra. The efficiency of the proposed approach is demonstrated numerically with an example relevant to engineering fracture. PMID:23750055

Image splitting and remapping method for radiological image compression

NASA Astrophysics Data System (ADS)

Lo, Shih-Chung B.; Shen, Ellen L.; Mun, Seong K.

1990-07-01

A new decomposition method using image splitting and gray-level remapping has been proposed for image compression, particularly for images with high contrast resolution. The effects of this method are especially evident in our radiological image compression study. In our experiments, we tested the impact of this decomposition method on image compression by employing it with two coding techniques on a set of clinically used CT images and several laser film digitized chest radiographs. One of the compression techniques used was full-frame bit-allocation in the discrete cosine transform domain, which has been proven to be an effective technique for radiological image compression. The other compression technique used was vector quantization with pruned tree-structured encoding, which through recent research has also been found to produce a low mean-square-error and a high compression ratio. The parameters we used in this study were mean-square-error and the bit rate required for the compressed file. In addition to these parameters, the difference between the original and reconstructed images will be presented so that the specific artifacts generated by both techniques can be discerned by visual perception.

Numerical simulation for solution of space-time fractional telegraphs equations with local fractional derivatives via HAFSTM

NASA Astrophysics Data System (ADS)

Pandey, Rishi Kumar; Mishra, Hradyesh Kumar

2017-11-01

In this paper, the semi-analytic numerical technique for the solution of time-space fractional telegraph equation is applied. This numerical technique is based on coupling of the homotopy analysis method and sumudu transform. It shows the clear advantage with mess methods like finite difference method and also with polynomial methods similar to perturbation and Adomian decomposition methods. It is easily transform the complex fractional order derivatives in simple time domain and interpret the results in same meaning.

Local energy decomposition analysis of hydrogen-bonded dimers within a domain-based pair natural orbital coupled cluster study.

PubMed

Altun, Ahmet; Neese, Frank; Bistoni, Giovanni

2018-01-01

The local energy decomposition (LED) analysis allows for a decomposition of the accurate domain-based local pair natural orbital CCSD(T) [DLPNO-CCSD(T)] energy into physically meaningful contributions including geometric and electronic preparation, electrostatic interaction, interfragment exchange, dynamic charge polarization, and London dispersion terms. Herein, this technique is employed in the study of hydrogen-bonding interactions in a series of conformers of water and hydrogen fluoride dimers. Initially, DLPNO-CCSD(T) dissociation energies for the most stable conformers are computed and compared with available experimental data. Afterwards, the decay of the LED terms with the intermolecular distance ( r ) is discussed and results are compared with the ones obtained from the popular symmetry adapted perturbation theory (SAPT). It is found that, as expected, electrostatic contributions slowly decay for increasing r and dominate the interaction energies in the long range. London dispersion contributions decay as expected, as r -6 . They significantly affect the depths of the potential wells. The interfragment exchange provides a further stabilizing contribution that decays exponentially with the intermolecular distance. This information is used to rationalize the trend of stability of various conformers of the water and hydrogen fluoride dimers.

A Fast Solver for Implicit Integration of the Vlasov--Poisson System in the Eulerian Framework

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

Garrett, C. Kristopher; Hauck, Cory D.

In this paper, we present a domain decomposition algorithm to accelerate the solution of Eulerian-type discretizations of the linear, steady-state Vlasov equation. The steady-state solver then forms a key component in the implementation of fully implicit or nearly fully implicit temporal integrators for the nonlinear Vlasov--Poisson system. The solver relies on a particular decomposition of phase space that enables the use of sweeping techniques commonly used in radiation transport applications. The original linear system for the phase space unknowns is then replaced by a smaller linear system involving only unknowns on the boundary between subdomains, which can then be solvedmore » efficiently with Krylov methods such as GMRES. Steady-state solves are combined to form an implicit Runge--Kutta time integrator, and the Vlasov equation is coupled self-consistently to the Poisson equation via a linearized procedure or a nonlinear fixed-point method for the electric field. Finally, numerical results for standard test problems demonstrate the efficiency of the domain decomposition approach when compared to the direct application of an iterative solver to the original linear system.« less

A Fast Solver for Implicit Integration of the Vlasov--Poisson System in the Eulerian Framework

DOE PAGES

Garrett, C. Kristopher; Hauck, Cory D.

2018-04-05

In this paper, we present a domain decomposition algorithm to accelerate the solution of Eulerian-type discretizations of the linear, steady-state Vlasov equation. The steady-state solver then forms a key component in the implementation of fully implicit or nearly fully implicit temporal integrators for the nonlinear Vlasov--Poisson system. The solver relies on a particular decomposition of phase space that enables the use of sweeping techniques commonly used in radiation transport applications. The original linear system for the phase space unknowns is then replaced by a smaller linear system involving only unknowns on the boundary between subdomains, which can then be solvedmore » efficiently with Krylov methods such as GMRES. Steady-state solves are combined to form an implicit Runge--Kutta time integrator, and the Vlasov equation is coupled self-consistently to the Poisson equation via a linearized procedure or a nonlinear fixed-point method for the electric field. Finally, numerical results for standard test problems demonstrate the efficiency of the domain decomposition approach when compared to the direct application of an iterative solver to the original linear system.« less

Balancing Conflicting Requirements for Grid and Particle Decomposition in Continuum-Lagrangian Solvers

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

Sitaraman, Hariswaran; Grout, Ray

2015-10-30

The load balancing strategies for hybrid solvers that involve grid based partial differential equation solution coupled with particle tracking are presented in this paper. A typical Message Passing Interface (MPI) based parallelization of grid based solves are done using a spatial domain decomposition while particle tracking is primarily done using either of the two techniques. One of the techniques is to distribute the particles to MPI ranks to whose grid they belong to while the other is to share the particles equally among all ranks, irrespective of their spatial location. The former technique provides spatial locality for field interpolation butmore » cannot assure load balance in terms of number of particles, which is achieved by the latter. The two techniques are compared for a case of particle tracking in a homogeneous isotropic turbulence box as well as a turbulent jet case. We performed a strong scaling study for more than 32,000 cores, which results in particle densities representative of anticipated exascale machines. The use of alternative implementations of MPI collectives and efficient load equalization strategies are studied to reduce data communication overheads.« less

Truncated feature representation for automatic target detection using transformed data-based decomposition

NASA Astrophysics Data System (ADS)

Riasati, Vahid R.

2016-05-01

In this work, the data covariance matrix is diagonalized to provide an orthogonal bases set using the eigen vectors of the data. The eigen-vector decomposition of the data is transformed and filtered in the transform domain to truncate the data for robust features related to a specified set of targets. These truncated eigen features are then combined and reconstructed to utilize in a composite filter and consequently utilized for the automatic target detection of the same class of targets. The results associated with the testing of the current technique are evaluated using the peak-correlation and peak-correlation energy metrics and are presented in this work. The inverse transformed eigen-bases of the current technique may be thought of as an injected sparsity to minimize data in representing the skeletal data structure information associated with the set of targets under consideration.

Matching multiple rigid domain decompositions of proteins

PubMed Central

Flynn, Emily; Streinu, Ileana

2017-01-01

We describe efficient methods for consistently coloring and visualizing collections of rigid cluster decompositions obtained from variations of a protein structure, and lay the foundation for more complex setups that may involve different computational and experimental methods. The focus here is on three biological applications: the conceptually simpler problems of visualizing results of dilution and mutation analyses, and the more complex task of matching decompositions of multiple NMR models of the same protein. Implemented into the KINARI web server application, the improved visualization techniques give useful information about protein folding cores, help examining the effect of mutations on protein flexibility and function, and provide insights into the structural motions of PDB proteins solved with solution NMR. These tools have been developed with the goal of improving and validating rigidity analysis as a credible coarse-grained model capturing essential information about a protein’s slow motions near the native state. PMID:28141528

Domain decomposition for a mixed finite element method in three dimensions

USGS Publications Warehouse

Cai, Z.; Parashkevov, R.R.; Russell, T.F.; Wilson, J.D.; Ye, X.

2003-01-01

We consider the solution of the discrete linear system resulting from a mixed finite element discretization applied to a second-order elliptic boundary value problem in three dimensions. Based on a decomposition of the velocity space, these equations can be reduced to a discrete elliptic problem by eliminating the pressure through the use of substructures of the domain. The practicality of the reduction relies on a local basis, presented here, for the divergence-free subspace of the velocity space. We consider additive and multiplicative domain decomposition methods for solving the reduced elliptic problem, and their uniform convergence is established.

Modern gyrokinetic particle-in-cell simulation of fusion plasmas on top supercomputers

DOE PAGES

Wang, Bei; Ethier, Stephane; Tang, William; ...

2017-06-29

The Gyrokinetic Toroidal Code at Princeton (GTC-P) is a highly scalable and portable particle-in-cell (PIC) code. It solves the 5D Vlasov-Poisson equation featuring efficient utilization of modern parallel computer architectures at the petascale and beyond. Motivated by the goal of developing a modern code capable of dealing with the physics challenge of increasing problem size with sufficient resolution, new thread-level optimizations have been introduced as well as a key additional domain decomposition. GTC-P's multiple levels of parallelism, including inter-node 2D domain decomposition and particle decomposition, as well as intra-node shared memory partition and vectorization have enabled pushing the scalability ofmore » the PIC method to extreme computational scales. In this paper, we describe the methods developed to build a highly parallelized PIC code across a broad range of supercomputer designs. This particularly includes implementations on heterogeneous systems using NVIDIA GPU accelerators and Intel Xeon Phi (MIC) co-processors and performance comparisons with state-of-the-art homogeneous HPC systems such as Blue Gene/Q. New discovery science capabilities in the magnetic fusion energy application domain are enabled, including investigations of Ion-Temperature-Gradient (ITG) driven turbulence simulations with unprecedented spatial resolution and long temporal duration. Performance studies with realistic fusion experimental parameters are carried out on multiple supercomputing systems spanning a wide range of cache capacities, cache-sharing configurations, memory bandwidth, interconnects and network topologies. These performance comparisons using a realistic discovery-science-capable domain application code provide valuable insights on optimization techniques across one of the broadest sets of current high-end computing platforms worldwide.« less

Modern gyrokinetic particle-in-cell simulation of fusion plasmas on top supercomputers

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

Wang, Bei; Ethier, Stephane; Tang, William

The Gyrokinetic Toroidal Code at Princeton (GTC-P) is a highly scalable and portable particle-in-cell (PIC) code. It solves the 5D Vlasov-Poisson equation featuring efficient utilization of modern parallel computer architectures at the petascale and beyond. Motivated by the goal of developing a modern code capable of dealing with the physics challenge of increasing problem size with sufficient resolution, new thread-level optimizations have been introduced as well as a key additional domain decomposition. GTC-P's multiple levels of parallelism, including inter-node 2D domain decomposition and particle decomposition, as well as intra-node shared memory partition and vectorization have enabled pushing the scalability ofmore » the PIC method to extreme computational scales. In this paper, we describe the methods developed to build a highly parallelized PIC code across a broad range of supercomputer designs. This particularly includes implementations on heterogeneous systems using NVIDIA GPU accelerators and Intel Xeon Phi (MIC) co-processors and performance comparisons with state-of-the-art homogeneous HPC systems such as Blue Gene/Q. New discovery science capabilities in the magnetic fusion energy application domain are enabled, including investigations of Ion-Temperature-Gradient (ITG) driven turbulence simulations with unprecedented spatial resolution and long temporal duration. Performance studies with realistic fusion experimental parameters are carried out on multiple supercomputing systems spanning a wide range of cache capacities, cache-sharing configurations, memory bandwidth, interconnects and network topologies. These performance comparisons using a realistic discovery-science-capable domain application code provide valuable insights on optimization techniques across one of the broadest sets of current high-end computing platforms worldwide.« less

Parallelization of PANDA discrete ordinates code using spatial decomposition

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

Humbert, P.

2006-07-01

We present the parallel method, based on spatial domain decomposition, implemented in the 2D and 3D versions of the discrete Ordinates code PANDA. The spatial mesh is orthogonal and the spatial domain decomposition is Cartesian. For 3D problems a 3D Cartesian domain topology is created and the parallel method is based on a domain diagonal plane ordered sweep algorithm. The parallel efficiency of the method is improved by directions and octants pipelining. The implementation of the algorithm is straightforward using MPI blocking point to point communications. The efficiency of the method is illustrated by an application to the 3D-Ext C5G7more » benchmark of the OECD/NEA. (authors)« less

Modal identification of structures by a novel approach based on FDD-wavelet method

NASA Astrophysics Data System (ADS)

Tarinejad, Reza; Damadipour, Majid

2014-02-01

An important application of system identification in structural dynamics is the determination of natural frequencies, mode shapes and damping ratios during operation which can then be used for calibrating numerical models. In this paper, the combination of two advanced methods of Operational Modal Analysis (OMA) called Frequency Domain Decomposition (FDD) and Continuous Wavelet Transform (CWT) based on novel cyclic averaging of correlation functions (CACF) technique are used for identification of dynamic properties. By using this technique, the autocorrelation of averaged correlation functions is used instead of original signals. Integration of FDD and CWT methods is used to overcome their deficiency and take advantage of the unique capabilities of these methods. The FDD method is able to accurately estimate the natural frequencies and mode shapes of structures in the frequency domain. On the other hand, the CWT method is in the time-frequency domain for decomposition of a signal at different frequencies and determines the damping coefficients. In this paper, a new formulation applied to the wavelet transform of the averaged correlation function of an ambient response is proposed. This application causes to accurate estimation of damping ratios from weak (noise) or strong (earthquake) vibrations and long or short duration record. For this purpose, the modified Morlet wavelet having two free parameters is used. The optimum values of these two parameters are obtained by employing a technique which minimizes the entropy of the wavelet coefficients matrix. The capabilities of the novel FDD-Wavelet method in the system identification of various dynamic systems with regular or irregular distribution of mass and stiffness are illustrated. This combined approach is superior to classic methods and yields results that agree well with the exact solutions of the numerical models.

Modal analysis of 2-D sedimentary basin from frequency domain decomposition of ambient vibration array recordings

NASA Astrophysics Data System (ADS)

Poggi, Valerio; Ermert, Laura; Burjanek, Jan; Michel, Clotaire; Fäh, Donat

2015-01-01

Frequency domain decomposition (FDD) is a well-established spectral technique used in civil engineering to analyse and monitor the modal response of buildings and structures. The method is based on singular value decomposition of the cross-power spectral density matrix from simultaneous array recordings of ambient vibrations. This method is advantageous to retrieve not only the resonance frequencies of the investigated structure, but also the corresponding modal shapes without the need for an absolute reference. This is an important piece of information, which can be used to validate the consistency of numerical models and analytical solutions. We apply this approach using advanced signal processing to evaluate the resonance characteristics of 2-D Alpine sedimentary valleys. In this study, we present the results obtained at Martigny, in the Rhône valley (Switzerland). For the analysis, we use 2 hr of ambient vibration recordings from a linear seismic array deployed perpendicularly to the valley axis. Only the horizontal-axial direction (SH) of the ground motion is considered. Using the FDD method, six separate resonant frequencies are retrieved together with their corresponding modal shapes. We compare the mode shapes with results from classical standard spectral ratios and numerical simulations of ambient vibration recordings.

Wavelet domain textual coding of Ottoman script images

NASA Astrophysics Data System (ADS)

Gerek, Oemer N.; Cetin, Enis A.; Tewfik, Ahmed H.

1996-02-01

Image coding using wavelet transform, DCT, and similar transform techniques is well established. On the other hand, these coding methods neither take into account the special characteristics of the images in a database nor are they suitable for fast database search. In this paper, the digital archiving of Ottoman printings is considered. Ottoman documents are printed in Arabic letters. Witten et al. describes a scheme based on finding the characters in binary document images and encoding the positions of the repeated characters This method efficiently compresses document images and is suitable for database research, but it cannot be applied to Ottoman or Arabic documents as the concept of character is different in Ottoman or Arabic. Typically, one has to deal with compound structures consisting of a group of letters. Therefore, the matching criterion will be according to those compound structures. Furthermore, the text images are gray tone or color images for Ottoman scripts for the reasons that are described in the paper. In our method the compound structure matching is carried out in wavelet domain which reduces the search space and increases the compression ratio. In addition to the wavelet transformation which corresponds to the linear subband decomposition, we also used nonlinear subband decomposition. The filters in the nonlinear subband decomposition have the property of preserving edges in the low resolution subband image.

A new adaptive algorithm for automated feature extraction in exponentially damped signals for health monitoring of smart structures

NASA Astrophysics Data System (ADS)

Qarib, Hossein; Adeli, Hojjat

2015-12-01

In this paper authors introduce a new adaptive signal processing technique for feature extraction and parameter estimation in noisy exponentially damped signals. The iterative 3-stage method is based on the adroit integration of the strengths of parametric and nonparametric methods such as multiple signal categorization, matrix pencil, and empirical mode decomposition algorithms. The first stage is a new adaptive filtration or noise removal scheme. The second stage is a hybrid parametric-nonparametric signal parameter estimation technique based on an output-only system identification technique. The third stage is optimization of estimated parameters using a combination of the primal-dual path-following interior point algorithm and genetic algorithm. The methodology is evaluated using a synthetic signal and a signal obtained experimentally from transverse vibrations of a steel cantilever beam. The method is successful in estimating the frequencies accurately. Further, it estimates the damping exponents. The proposed adaptive filtration method does not include any frequency domain manipulation. Consequently, the time domain signal is not affected as a result of frequency domain and inverse transformations.

Wavelet-domain de-noising of OCT images of human brain malignant glioma

NASA Astrophysics Data System (ADS)

Dolganova, I. N.; Aleksandrova, P. V.; Beshplav, S.-I. T.; Chernomyrdin, N. V.; Dubyanskaya, E. N.; Goryaynov, S. A.; Kurlov, V. N.; Reshetov, I. V.; Potapov, A. A.; Tuchin, V. V.; Zaytsev, K. I.

2018-04-01

We have proposed a wavelet-domain de-noising technique for imaging of human brain malignant glioma by optical coherence tomography (OCT). It implies OCT image decomposition using the direct fast wavelet transform, thresholding of the obtained wavelet spectrum and further inverse fast wavelet transform for image reconstruction. By selecting both wavelet basis and thresholding procedure, we have found an optimal wavelet filter, which application improves differentiation of the considered brain tissue classes - i.e. malignant glioma and normal/intact tissue. Namely, it allows reducing the scattering noise in the OCT images and retaining signal decrement for each tissue class. Therefore, the observed results reveals the wavelet-domain de-noising as a prospective tool for improved characterization of biological tissue using the OCT.

A Spectral Element Ocean Model on the Cray T3D: the interannual variability of the Mediterranean Sea general circulation

NASA Astrophysics Data System (ADS)

Molcard, A. J.; Pinardi, N.; Ansaloni, R.

A new numerical model, SEOM (Spectral Element Ocean Model, (Iskandarani et al, 1994)), has been implemented in the Mediterranean Sea. Spectral element methods combine the geometric flexibility of finite element techniques with the rapid convergence rate of spectral schemes. The current version solves the shallow water equations with a fifth (or sixth) order accuracy spectral scheme and about 50.000 nodes. The domain decomposition philosophy makes it possible to exploit the power of parallel machines. The original MIMD master/slave version of SEOM, written in F90 and PVM, has been ported to the Cray T3D. When critical for performance, Cray specific high-performance one-sided communication routines (SHMEM) have been adopted to fully exploit the Cray T3D interprocessor network. Tests performed with highly unstructured and irregular grid, on up to 128 processors, show an almost linear scalability even with unoptimized domain decomposition techniques. Results from various case studies on the Mediterranean Sea are shown, involving realistic coastline geometry, and monthly mean 1000mb winds from the ECMWF's atmospheric model operational analysis from the period January 1987 to December 1994. The simulation results show that variability in the wind forcing considerably affect the circulation dynamics of the Mediterranean Sea.

System identification of timber masonry walls using shaking table test

NASA Astrophysics Data System (ADS)

Roy, Timir B.; Guerreiro, Luis; Bagchi, Ashutosh

2017-04-01

Dynamic study is important in order to design, repair and rehabilitation of structures. It has played an important role in the behavior characterization of structures; such as: bridges, dams, high rise buildings etc. There had been substantial development in this area over the last few decades, especially in the field of dynamic identification techniques of structural systems. Frequency Domain Decomposition (FDD) and Time Domain Decomposition are most commonly used methods to identify modal parameters; such as: natural frequency, modal damping and mode shape. The focus of the present research is to study the dynamic characteristics of typical timber masonry walls commonly used in Portugal. For that purpose, a multi-storey structural prototype of such wall has been tested on a seismic shake table at the National Laboratory for Civil Engineering, Portugal (LNEC). Signal processing has been performed of the output response, which is collected from the shaking table experiment of the prototype using accelerometers. In the present work signal processing of the output response, based on the input response has been done in two ways: FDD and Stochastic Subspace Identification (SSI). In order to estimate the values of the modal parameters, algorithms for FDD are formulated and parametric functions for the SSI are computed. Finally, estimated values from both the methods are compared to measure the accuracy of both the techniques.

Using domain decomposition in the multigrid NAS parallel benchmark on the Fujitsu VPP500

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

Wang, J.C.H.; Lung, H.; Katsumata, Y.

1995-12-01

In this paper, we demonstrate how domain decomposition can be applied to the multigrid algorithm to convert the code for MPP architectures. We also discuss the performance and scalability of this implementation on the new product line of Fujitsu`s vector parallel computer, VPP500. This computer has Fujitsu`s well-known vector processor as the PE each rated at 1.6 C FLOPS. The high speed crossbar network rated at 800 MB/s provides the inter-PE communication. The results show that the physical domain decomposition is the best way to solve MG problems on VPP500.

A multilevel preconditioner for domain decomposition boundary systems

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

Bramble, J.H.; Pasciak, J.E.; Xu, Jinchao.

1991-12-11

In this note, we consider multilevel preconditioning of the reduced boundary systems which arise in non-overlapping domain decomposition methods. It will be shown that the resulting preconditioned systems have condition numbers which be bounded in the case of multilevel spaces on the whole domain and grow at most proportional to the number of levels in the case of multilevel boundary spaces without multilevel extensions into the interior.

3-D modeling of ductile tearing using finite elements: Computational aspects and techniques

NASA Astrophysics Data System (ADS)

Gullerud, Arne Stewart

This research focuses on the development and application of computational tools to perform large-scale, 3-D modeling of ductile tearing in engineering components under quasi-static to mild loading rates. Two standard models for ductile tearing---the computational cell methodology and crack growth controlled by the crack tip opening angle (CTOA)---are described and their 3-D implementations are explored. For the computational cell methodology, quantification of the effects of several numerical issues---computational load step size, procedures for force release after cell deletion, and the porosity for cell deletion---enables construction of computational algorithms to remove the dependence of predicted crack growth on these issues. This work also describes two extensions of the CTOA approach into 3-D: a general 3-D method and a constant front technique. Analyses compare the characteristics of the extensions, and a validation study explores the ability of the constant front extension to predict crack growth in thin aluminum test specimens over a range of specimen geometries, absolutes sizes, and levels of out-of-plane constraint. To provide a computational framework suitable for the solution of these problems, this work also describes the parallel implementation of a nonlinear, implicit finite element code. The implementation employs an explicit message-passing approach using the MPI standard to maintain portability, a domain decomposition of element data to provide parallel execution, and a master-worker organization of the computational processes to enhance future extensibility. A linear preconditioned conjugate gradient (LPCG) solver serves as the core of the solution process. The parallel LPCG solver utilizes an element-by-element (EBE) structure of the computations to permit a dual-level decomposition of the element data: domain decomposition of the mesh provides efficient coarse-grain parallel execution, while decomposition of the domains into blocks of similar elements (same type, constitutive model, etc.) provides fine-grain parallel computation on each processor. A major focus of the LPCG solver is a new implementation of the Hughes-Winget element-by-element (HW) preconditioner. The implementation employs a weighted dependency graph combined with a new coloring algorithm to provide load-balanced scheduling for the preconditioner and overlapped communication/computation. This approach enables efficient parallel application of the HW preconditioner for arbitrary unstructured meshes.

Application of higher-order cepstral techniques in problems of fetal heart signal extraction

NASA Astrophysics Data System (ADS)

Sabry-Rizk, Madiha; Zgallai, Walid; Hardiman, P.; O'Riordan, J.

1996-10-01

Recently, cepstral analysis based on second order statistics and homomorphic filtering techniques have been used in the adaptive decomposition of overlapping, or otherwise, and noise contaminated ECG complexes of mothers and fetals obtained by a transabdominal surface electrodes connected to a monitoring instrument, an interface card, and a PC. Differential time delays of fetal heart beats measured from a reference point located on the mother complex after transformation to cepstra domains are first obtained and this is followed by fetal heart rate variability computations. Homomorphic filtering in the complex cepstral domain and the subuent transformation to the time domain results in fetal complex recovery. However, three problems have been identified with second-order based cepstral techniques that needed rectification in this paper. These are (1) errors resulting from the phase unwrapping algorithms and leading to fetal complex perturbation, (2) the unavoidable conversion of noise statistics from Gaussianess to non-Gaussianess due to the highly non-linear nature of homomorphic transform does warrant stringent noise cancellation routines, (3) due to the aforementioned problems in (1) and (2), it is difficult to adaptively optimize windows to include all individual fetal complexes in the time domain based on amplitude thresholding routines in the complex cepstral domain (i.e. the task of `zooming' in on weak fetal complexes requires more processing time). The use of third-order based high resolution differential cepstrum technique results in recovery of the delay of the order of 120 milliseconds.

Scalable and fast heterogeneous molecular simulation with predictive parallelization schemes

NASA Astrophysics Data System (ADS)

Guzman, Horacio V.; Junghans, Christoph; Kremer, Kurt; Stuehn, Torsten

2017-11-01

Multiscale and inhomogeneous molecular systems are challenging topics in the field of molecular simulation. In particular, modeling biological systems in the context of multiscale simulations and exploring material properties are driving a permanent development of new simulation methods and optimization algorithms. In computational terms, those methods require parallelization schemes that make a productive use of computational resources for each simulation and from its genesis. Here, we introduce the heterogeneous domain decomposition approach, which is a combination of an heterogeneity-sensitive spatial domain decomposition with an a priori rearrangement of subdomain walls. Within this approach, the theoretical modeling and scaling laws for the force computation time are proposed and studied as a function of the number of particles and the spatial resolution ratio. We also show the new approach capabilities, by comparing it to both static domain decomposition algorithms and dynamic load-balancing schemes. Specifically, two representative molecular systems have been simulated and compared to the heterogeneous domain decomposition proposed in this work. These two systems comprise an adaptive resolution simulation of a biomolecule solvated in water and a phase-separated binary Lennard-Jones fluid.

A Parallel Algorithm for Contact in a Finite Element Hydrocode

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

Pierce, Timothy G.

A parallel algorithm is developed for contact/impact of multiple three dimensional bodies undergoing large deformation. As time progresses the relative positions of contact between the multiple bodies changes as collision and sliding occurs. The parallel algorithm is capable of tracking these changes and enforcing an impenetrability constraint and momentum transfer across the surfaces in contact. Portions of the various surfaces of the bodies are assigned to the processors of a distributed-memory parallel machine in an arbitrary fashion, known as the primary decomposition. A secondary, dynamic decomposition is utilized to bring opposing sections of the contacting surfaces together on the samemore » processors, so that opposing forces may be balanced and the resultant deformation of the bodies calculated. The secondary decomposition is accomplished and updated using only local communication with a limited subset of neighbor processors. Each processor represents both a domain of the primary decomposition and a domain of the secondary, or contact, decomposition. Thus each processor has four sets of neighbor processors: (a) those processors which represent regions adjacent to it in the primary decomposition, (b) those processors which represent regions adjacent to it in the contact decomposition, (c) those processors which send it the data from which it constructs its contact domain, and (d) those processors to which it sends its primary domain data, from which they construct their contact domains. The latter three of these neighbor sets change dynamically as the simulation progresses. By constraining all communication to these sets of neighbors, all global communication, with its attendant nonscalable performance, is avoided. A set of tests are provided to measure the degree of scalability achieved by this algorithm on up to 1024 processors. Issues related to the operating system of the test platform which lead to some degradation of the results are analyzed. This algorithm has been implemented as the contact capability of the ALE3D multiphysics code, and is currently in production use.« less

Matrix decomposition graphics processing unit solver for Poisson image editing

NASA Astrophysics Data System (ADS)

Lei, Zhao; Wei, Li

2012-10-01

In recent years, gradient-domain methods have been widely discussed in the image processing field, including seamless cloning and image stitching. These algorithms are commonly carried out by solving a large sparse linear system: the Poisson equation. However, solving the Poisson equation is a computational and memory intensive task which makes it not suitable for real-time image editing. A new matrix decomposition graphics processing unit (GPU) solver (MDGS) is proposed to settle the problem. A matrix decomposition method is used to distribute the work among GPU threads, so that MDGS will take full advantage of the computing power of current GPUs. Additionally, MDGS is a hybrid solver (combines both the direct and iterative techniques) and has two-level architecture. These enable MDGS to generate identical solutions with those of the common Poisson methods and achieve high convergence rate in most cases. This approach is advantageous in terms of parallelizability, enabling real-time image processing, low memory-taken and extensive applications.

Statistical CT noise reduction with multiscale decomposition and penalized weighted least squares in the projection domain

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

Tang Shaojie; Tang Xiangyang; School of Automation, Xi'an University of Posts and Telecommunications, Xi'an, Shaanxi 710121

2012-09-15

Purposes: The suppression of noise in x-ray computed tomography (CT) imaging is of clinical relevance for diagnostic image quality and the potential for radiation dose saving. Toward this purpose, statistical noise reduction methods in either the image or projection domain have been proposed, which employ a multiscale decomposition to enhance the performance of noise suppression while maintaining image sharpness. Recognizing the advantages of noise suppression in the projection domain, the authors propose a projection domain multiscale penalized weighted least squares (PWLS) method, in which the angular sampling rate is explicitly taken into consideration to account for the possible variation ofmore » interview sampling rate in advanced clinical or preclinical applications. Methods: The projection domain multiscale PWLS method is derived by converting an isotropic diffusion partial differential equation in the image domain into the projection domain, wherein a multiscale decomposition is carried out. With adoption of the Markov random field or soft thresholding objective function, the projection domain multiscale PWLS method deals with noise at each scale. To compensate for the degradation in image sharpness caused by the projection domain multiscale PWLS method, an edge enhancement is carried out following the noise reduction. The performance of the proposed method is experimentally evaluated and verified using the projection data simulated by computer and acquired by a CT scanner. Results: The preliminary results show that the proposed projection domain multiscale PWLS method outperforms the projection domain single-scale PWLS method and the image domain multiscale anisotropic diffusion method in noise reduction. In addition, the proposed method can preserve image sharpness very well while the occurrence of 'salt-and-pepper' noise and mosaic artifacts can be avoided. Conclusions: Since the interview sampling rate is taken into account in the projection domain multiscale decomposition, the proposed method is anticipated to be useful in advanced clinical and preclinical applications where the interview sampling rate varies.« less

A Multigrid Approach to Embedded-Grid Solvers

DTIC Science & Technology

1992-08-01

previously as a Master’s Thesis at the University of Florida. Not edited by TESCO , Inc. 12a. DISTRIBUTION / AVAILABILITY STATEMENT 12b. DISTRIBUTION CODE...domain decomposition techniques in order to accurately model the aerodynamics of complex geometries 𔃾, 5, 11, 12, 13, 24’. Although these high...quantities subscripted by oc denote reference values in the undisturbed gas. Uv v, e e P - (10) Where • = (7b,/•)1/2, is the speed of sound in the

Dynamic load balancing algorithm for molecular dynamics based on Voronoi cells domain decompositions

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

Fattebert, J.-L.; Richards, D.F.; Glosli, J.N.

2012-12-01

We present a new algorithm for automatic parallel load balancing in classical molecular dynamics. It assumes a spatial domain decomposition of particles into Voronoi cells. It is a gradient method which attempts to minimize a cost function by displacing Voronoi sites associated with each processor/sub-domain along steepest descent directions. Excellent load balance has been obtained for quasi-2D and 3D practical applications, with up to 440·10 6 particles on 65,536 MPI tasks.

Mapping to Irregular Torus Topologies and Other Techniques for Petascale Biomolecular Simulation

PubMed Central

Phillips, James C.; Sun, Yanhua; Jain, Nikhil; Bohm, Eric J.; Kalé, Laxmikant V.

2014-01-01

Currently deployed petascale supercomputers typically use toroidal network topologies in three or more dimensions. While these networks perform well for topology-agnostic codes on a few thousand nodes, leadership machines with 20,000 nodes require topology awareness to avoid network contention for communication-intensive codes. Topology adaptation is complicated by irregular node allocation shapes and holes due to dedicated input/output nodes or hardware failure. In the context of the popular molecular dynamics program NAMD, we present methods for mapping a periodic 3-D grid of fixed-size spatial decomposition domains to 3-D Cray Gemini and 5-D IBM Blue Gene/Q toroidal networks to enable hundred-million atom full machine simulations, and to similarly partition node allocations into compact domains for smaller simulations using multiple-copy algorithms. Additional enabling techniques are discussed and performance is reported for NCSA Blue Waters, ORNL Titan, ANL Mira, TACC Stampede, and NERSC Edison. PMID:25594075

Scalable and fast heterogeneous molecular simulation with predictive parallelization schemes

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

Guzman, Horacio V.; Junghans, Christoph; Kremer, Kurt

Multiscale and inhomogeneous molecular systems are challenging topics in the field of molecular simulation. In particular, modeling biological systems in the context of multiscale simulations and exploring material properties are driving a permanent development of new simulation methods and optimization algorithms. In computational terms, those methods require parallelization schemes that make a productive use of computational resources for each simulation and from its genesis. Here, we introduce the heterogeneous domain decomposition approach, which is a combination of an heterogeneity-sensitive spatial domain decomposition with an a priori rearrangement of subdomain walls. Within this approach and paper, the theoretical modeling and scalingmore » laws for the force computation time are proposed and studied as a function of the number of particles and the spatial resolution ratio. We also show the new approach capabilities, by comparing it to both static domain decomposition algorithms and dynamic load-balancing schemes. Specifically, two representative molecular systems have been simulated and compared to the heterogeneous domain decomposition proposed in this work. Finally, these two systems comprise an adaptive resolution simulation of a biomolecule solvated in water and a phase-separated binary Lennard-Jones fluid.« less

Scalable and fast heterogeneous molecular simulation with predictive parallelization schemes

DOE PAGES

Guzman, Horacio V.; Junghans, Christoph; Kremer, Kurt; ...

2017-11-27

Multiscale and inhomogeneous molecular systems are challenging topics in the field of molecular simulation. In particular, modeling biological systems in the context of multiscale simulations and exploring material properties are driving a permanent development of new simulation methods and optimization algorithms. In computational terms, those methods require parallelization schemes that make a productive use of computational resources for each simulation and from its genesis. Here, we introduce the heterogeneous domain decomposition approach, which is a combination of an heterogeneity-sensitive spatial domain decomposition with an a priori rearrangement of subdomain walls. Within this approach and paper, the theoretical modeling and scalingmore » laws for the force computation time are proposed and studied as a function of the number of particles and the spatial resolution ratio. We also show the new approach capabilities, by comparing it to both static domain decomposition algorithms and dynamic load-balancing schemes. Specifically, two representative molecular systems have been simulated and compared to the heterogeneous domain decomposition proposed in this work. Finally, these two systems comprise an adaptive resolution simulation of a biomolecule solvated in water and a phase-separated binary Lennard-Jones fluid.« less

A Dual Super-Element Domain Decomposition Approach for Parallel Nonlinear Finite Element Analysis

NASA Astrophysics Data System (ADS)

Jokhio, G. A.; Izzuddin, B. A.

2015-05-01

This article presents a new domain decomposition method for nonlinear finite element analysis introducing the concept of dual partition super-elements. The method extends ideas from the displacement frame method and is ideally suited for parallel nonlinear static/dynamic analysis of structural systems. In the new method, domain decomposition is realized by replacing one or more subdomains in a "parent system," each with a placeholder super-element, where the subdomains are processed separately as "child partitions," each wrapped by a dual super-element along the partition boundary. The analysis of the overall system, including the satisfaction of equilibrium and compatibility at all partition boundaries, is realized through direct communication between all pairs of placeholder and dual super-elements. The proposed method has particular advantages for matrix solution methods based on the frontal scheme, and can be readily implemented for existing finite element analysis programs to achieve parallelization on distributed memory systems with minimal intervention, thus overcoming memory bottlenecks typically faced in the analysis of large-scale problems. Several examples are presented in this article which demonstrate the computational benefits of the proposed parallel domain decomposition approach and its applicability to the nonlinear structural analysis of realistic structural systems.

Low-rank matrix decomposition and spatio-temporal sparse recovery for STAP radar

DOE PAGES

Sen, Satyabrata

2015-08-04

We develop space-time adaptive processing (STAP) methods by leveraging the advantages of sparse signal processing techniques in order to detect a slowly-moving target. We observe that the inherent sparse characteristics of a STAP problem can be formulated as the low-rankness of clutter covariance matrix when compared to the total adaptive degrees-of-freedom, and also as the sparse interference spectrum on the spatio-temporal domain. By exploiting these sparse properties, we propose two approaches for estimating the interference covariance matrix. In the first approach, we consider a constrained matrix rank minimization problem (RMP) to decompose the sample covariance matrix into a low-rank positivemore » semidefinite and a diagonal matrix. The solution of RMP is obtained by applying the trace minimization technique and the singular value decomposition with matrix shrinkage operator. Our second approach deals with the atomic norm minimization problem to recover the clutter response-vector that has a sparse support on the spatio-temporal plane. We use convex relaxation based standard sparse-recovery techniques to find the solutions. With extensive numerical examples, we demonstrate the performances of proposed STAP approaches with respect to both the ideal and practical scenarios, involving Doppler-ambiguous clutter ridges, spatial and temporal decorrelation effects. As a result, the low-rank matrix decomposition based solution requires secondary measurements as many as twice the clutter rank to attain a near-ideal STAP performance; whereas the spatio-temporal sparsity based approach needs a considerably small number of secondary data.« less

Combining DCQGMP-Based Sparse Decomposition and MPDR Beamformer for Multi-Type Interferences Mitigation for GNSS Receivers.

PubMed

Guo, Qiang; Qi, Liangang

2017-04-10

In the coexistence of multiple types of interfering signals, the performance of interference suppression methods based on time and frequency domains is degraded seriously, and the technique using an antenna array requires a large enough size and huge hardware costs. To combat multi-type interferences better for GNSS receivers, this paper proposes a cascaded multi-type interferences mitigation method combining improved double chain quantum genetic matching pursuit (DCQGMP)-based sparse decomposition and an MPDR beamformer. The key idea behind the proposed method is that the multiple types of interfering signals can be excised by taking advantage of their sparse features in different domains. In the first stage, the single-tone (multi-tone) and linear chirp interfering signals are canceled by sparse decomposition according to their sparsity in the over-complete dictionary. In order to improve the timeliness of matching pursuit (MP)-based sparse decomposition, a DCQGMP is introduced by combining an improved double chain quantum genetic algorithm (DCQGA) and the MP algorithm, and the DCQGMP algorithm is extended to handle the multi-channel signals according to the correlation among the signals in different channels. In the second stage, the minimum power distortionless response (MPDR) beamformer is utilized to nullify the residuary interferences (e.g., wideband Gaussian noise interferences). Several simulation results show that the proposed method can not only improve the interference mitigation degree of freedom (DoF) of the array antenna, but also effectively deal with the interference arriving from the same direction with the GNSS signal, which can be sparse represented in the over-complete dictionary. Moreover, it does not bring serious distortions into the navigation signal.

Combining DCQGMP-Based Sparse Decomposition and MPDR Beamformer for Multi-Type Interferences Mitigation for GNSS Receivers

PubMed Central

Guo, Qiang; Qi, Liangang

2017-01-01

In the coexistence of multiple types of interfering signals, the performance of interference suppression methods based on time and frequency domains is degraded seriously, and the technique using an antenna array requires a large enough size and huge hardware costs. To combat multi-type interferences better for GNSS receivers, this paper proposes a cascaded multi-type interferences mitigation method combining improved double chain quantum genetic matching pursuit (DCQGMP)-based sparse decomposition and an MPDR beamformer. The key idea behind the proposed method is that the multiple types of interfering signals can be excised by taking advantage of their sparse features in different domains. In the first stage, the single-tone (multi-tone) and linear chirp interfering signals are canceled by sparse decomposition according to their sparsity in the over-complete dictionary. In order to improve the timeliness of matching pursuit (MP)-based sparse decomposition, a DCQGMP is introduced by combining an improved double chain quantum genetic algorithm (DCQGA) and the MP algorithm, and the DCQGMP algorithm is extended to handle the multi-channel signals according to the correlation among the signals in different channels. In the second stage, the minimum power distortionless response (MPDR) beamformer is utilized to nullify the residuary interferences (e.g., wideband Gaussian noise interferences). Several simulation results show that the proposed method can not only improve the interference mitigation degree of freedom (DoF) of the array antenna, but also effectively deal with the interference arriving from the same direction with the GNSS signal, which can be sparse represented in the over-complete dictionary. Moreover, it does not bring serious distortions into the navigation signal. PMID:28394290

Sandia Higher Order Elements (SHOE) v 0.5 alpha

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

2013-09-24

SHOE is research code for characterizing and visualizing higher-order finite elements; it contains a framework for defining classes of interpolation techniques and element shapes; methods for interpolating triangular, quadrilateral, tetrahedral, and hexahedral cells using Lagrange and Legendre polynomial bases of arbitrary order; methods to decompose each element into domains of constant gradient flow (using a polynomial solver to identify critical points); and an isocontouring technique that uses this decomposition to guarantee topological correctness. Please note that this is an alpha release of research software and that some time has passed since it was actively developed; build- and run-time issues likelymore » exist.« less

Impact of joint statistical dual-energy CT reconstruction of proton stopping power images: Comparison to image- and sinogram-domain material decomposition approaches.

PubMed

Zhang, Shuangyue; Han, Dong; Politte, David G; Williamson, Jeffrey F; O'Sullivan, Joseph A

2018-05-01

The purpose of this study was to assess the performance of a novel dual-energy CT (DECT) approach for proton stopping power ratio (SPR) mapping that integrates image reconstruction and material characterization using a joint statistical image reconstruction (JSIR) method based on a linear basis vector model (BVM). A systematic comparison between the JSIR-BVM method and previously described DECT image- and sinogram-domain decomposition approaches is also carried out on synthetic data. The JSIR-BVM method was implemented to estimate the electron densities and mean excitation energies (I-values) required by the Bethe equation for SPR mapping. In addition, image- and sinogram-domain DECT methods based on three available SPR models including BVM were implemented for comparison. The intrinsic SPR modeling accuracy of the three models was first validated. Synthetic DECT transmission sinograms of two 330 mm diameter phantoms each containing 17 soft and bony tissues (for a total of 34) of known composition were then generated with spectra of 90 and 140 kVp. The estimation accuracy of the reconstructed SPR images were evaluated for the seven investigated methods. The impact of phantom size and insert location on SPR estimation accuracy was also investigated. All three selected DECT-SPR models predict the SPR of all tissue types with less than 0.2% RMS errors under idealized conditions with no reconstruction uncertainties. When applied to synthetic sinograms, the JSIR-BVM method achieves the best performance with mean and RMS-average errors of less than 0.05% and 0.3%, respectively, for all noise levels, while the image- and sinogram-domain decomposition methods show increasing mean and RMS-average errors with increasing noise level. The JSIR-BVM method also reduces statistical SPR variation by sixfold compared to other methods. A 25% phantom diameter change causes up to 4% SPR differences for the image-domain decomposition approach, while the JSIR-BVM method and sinogram-domain decomposition methods are insensitive to size change. Among all the investigated methods, the JSIR-BVM method achieves the best performance for SPR estimation in our simulation phantom study. This novel method is robust with respect to sinogram noise and residual beam-hardening effects, yielding SPR estimation errors comparable to intrinsic BVM modeling error. In contrast, the achievable SPR estimation accuracy of the image- and sinogram-domain decomposition methods is dominated by the CT image intensity uncertainties introduced by the reconstruction and decomposition processes. © 2018 American Association of Physicists in Medicine.

Development Of Polarimetric Decomposition Techniques For Indian Forest Resource Assessment Using Radar Imaging Satellite (Risat-1) Images

NASA Astrophysics Data System (ADS)

Sridhar, J.

2015-12-01

The focus of this work is to examine polarimetric decomposition techniques primarily focussed on Pauli decomposition and Sphere Di-Plane Helix (SDH) decomposition for forest resource assessment. The data processing methods adopted are Pre-processing (Geometric correction and Radiometric calibration), Speckle Reduction, Image Decomposition and Image Classification. Initially to classify forest regions, unsupervised classification was applied to determine different unknown classes. It was observed K-means clustering method gave better results in comparison with ISO Data method.Using the algorithm developed for Radar Tools, the code for decomposition and classification techniques were applied in Interactive Data Language (IDL) and was applied to RISAT-1 image of Mysore-Mandya region of Karnataka, India. This region is chosen for studying forest vegetation and consists of agricultural lands, water and hilly regions. Polarimetric SAR data possess a high potential for classification of earth surface.After applying the decomposition techniques, classification was done by selecting region of interests andpost-classification the over-all accuracy was observed to be higher in the SDH decomposed image, as it operates on individual pixels on a coherent basis and utilises the complete intrinsic coherent nature of polarimetric SAR data. Thereby, making SDH decomposition particularly suited for analysis of high-resolution SAR data. The Pauli Decomposition represents all the polarimetric information in a single SAR image however interpretation of the resulting image is difficult. The SDH decomposition technique seems to produce better results and interpretation as compared to Pauli Decomposition however more quantification and further analysis are being done in this area of research. The comparison of Polarimetric decomposition techniques and evolutionary classification techniques will be the scope of this work.

MO-FG-204-03: Using Edge-Preserving Algorithm for Significantly Improved Image-Domain Material Decomposition in Dual Energy CT

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

Zhao, W; Niu, T; Xing, L

2015-06-15

Purpose: To significantly improve dual energy CT (DECT) imaging by establishing a new theoretical framework of image-domain material decomposition with incorporation of edge-preserving techniques. Methods: The proposed algorithm, HYPR-NLM, combines the edge-preserving non-local mean filter (NLM) with the HYPR-LR (Local HighlY constrained backPRojection Reconstruction) framework. Image denoising using HYPR-LR framework depends on the noise level of the composite image which is the average of the different energy images. For DECT, the composite image is the average of high- and low-energy images. To further reduce noise, one may want to increase the window size of the filter of the HYPR-LR, leadingmore » resolution degradation. By incorporating the NLM filtering and the HYPR-LR framework, HYPR-NLM reduces the boost material decomposition noise using energy information redundancies as well as the non-local mean. We demonstrate the noise reduction and resolution preservation of the algorithm with both iodine concentration numerical phantom and clinical patient data by comparing the HYPR-NLM algorithm to the direct matrix inversion, HYPR-LR and iterative image-domain material decomposition (Iter-DECT). Results: The results show iterative material decomposition method reduces noise to the lowest level and provides improved DECT images. HYPR-NLM significantly reduces noise while preserving the accuracy of quantitative measurement and resolution. For the iodine concentration numerical phantom, the averaged noise levels are about 2.0, 0.7, 0.2 and 0.4 for direct inversion, HYPR-LR, Iter- DECT and HYPR-NLM, respectively. For the patient data, the noise levels of the water images are about 0.36, 0.16, 0.12 and 0.13 for direct inversion, HYPR-LR, Iter-DECT and HYPR-NLM, respectively. Difference images of both HYPR-LR and Iter-DECT show edge effect, while no significant edge effect is shown for HYPR-NLM, suggesting spatial resolution is well preserved for HYPR-NLM. Conclusion: HYPR-NLM provides an effective way to reduce the generic magnified image noise of dual–energy material decomposition while preserving resolution. This work is supported in part by NIH grants 7R01HL111141 and 1R01-EB016777. This work is also supported by the Natural Science Foundation of China (NSFC Grant No. 81201091), Fundamental Research Funds for the Central Universities in China, and Fund Project for Excellent Abroad Scholar Personnel in Science and Technology.« less

Density-cluster NMA: A new protein decomposition technique for coarse-grained normal mode analysis.

PubMed

Demerdash, Omar N A; Mitchell, Julie C

2012-07-01

Normal mode analysis has emerged as a useful technique for investigating protein motions on long time scales. This is largely due to the advent of coarse-graining techniques, particularly Hooke's Law-based potentials and the rotational-translational blocking (RTB) method for reducing the size of the force-constant matrix, the Hessian. Here we present a new method for domain decomposition for use in RTB that is based on hierarchical clustering of atomic density gradients, which we call Density-Cluster RTB (DCRTB). The method reduces the number of degrees of freedom by 85-90% compared with the standard blocking approaches. We compared the normal modes from DCRTB against standard RTB using 1-4 residues in sequence in a single block, with good agreement between the two methods. We also show that Density-Cluster RTB and standard RTB perform well in capturing the experimentally determined direction of conformational change. Significantly, we report superior correlation of DCRTB with B-factors compared with 1-4 residue per block RTB. Finally, we show significant reduction in computational cost for Density-Cluster RTB that is nearly 100-fold for many examples. Copyright © 2012 Wiley Periodicals, Inc.

Parallel CE/SE Computations via Domain Decomposition

NASA Technical Reports Server (NTRS)

Himansu, Ananda; Jorgenson, Philip C. E.; Wang, Xiao-Yen; Chang, Sin-Chung

2000-01-01

This paper describes the parallelization strategy and achieved parallel efficiency of an explicit time-marching algorithm for solving conservation laws. The Space-Time Conservation Element and Solution Element (CE/SE) algorithm for solving the 2D and 3D Euler equations is parallelized with the aid of domain decomposition. The parallel efficiency of the resultant algorithm on a Silicon Graphics Origin 2000 parallel computer is checked.

Least squares parameter estimation methods for material decomposition with energy discriminating detectors

PubMed Central

Le, Huy Q.; Molloi, Sabee

2011-01-01

Purpose: Energy resolving detectors provide more than one spectral measurement in one image acquisition. The purpose of this study is to investigate, with simulation, the ability to decompose four materials using energy discriminating detectors and least squares minimization techniques. Methods: Three least squares parameter estimation decomposition techniques were investigated for four-material breast imaging tasks in the image domain. The first technique treats the voxel as if it consisted of fractions of all the materials. The second method assumes that a voxel primarily contains one material and divides the decomposition process into segmentation and quantification tasks. The third is similar to the second method but a calibration was used. The simulated computed tomography (CT) system consisted of an 80 kVp spectrum and a CdZnTe (CZT) detector that could resolve the x-ray spectrum into five energy bins. A postmortem breast specimen was imaged with flat panel CT to provide a model for the digital phantoms. Hydroxyapatite (HA) (50, 150, 250, 350, 450, and 550 mg∕ml) and iodine (4, 12, 20, 28, 36, and 44 mg∕ml) contrast elements were embedded into the glandular region of the phantoms. Calibration phantoms consisted of a 30∕70 glandular-to-adipose tissue ratio with embedded HA (100, 200, 300, 400, and 500 mg∕ml) and iodine (5, 15, 25, 35, and 45 mg∕ml). The x-ray transport process was simulated where the Beer–Lambert law, Poisson process, and CZT absorption efficiency were applied. Qualitative and quantitative evaluations of the decomposition techniques were performed and compared. The effect of breast size was also investigated. Results: The first technique decomposed iodine adequately but failed for other materials. The second method separated the materials but was unable to quantify the materials. With the addition of a calibration, the third technique provided good separation and quantification of hydroxyapatite, iodine, glandular, and adipose tissues. Quantification with this technique was accurate with errors of 9.83% and 6.61% for HA and iodine, respectively. Calibration at one point (one breast size) showed increased errors as the mismatch in breast diameters between calibration and measurement increased. A four-point calibration successfully decomposed breast diameter spanning the entire range from 8 to 20 cm. For a 14 cm breast, errors were reduced from 5.44% to 1.75% and from 6.17% to 3.27% with the multipoint calibration for HA and iodine, respectively. Conclusions: The results of the simulation study showed that a CT system based on CZT detectors in conjunction with least squares minimization technique can be used to decompose four materials. The calibrated least squares parameter estimation decomposition technique performed the best, separating and accurately quantifying the concentrations of hydroxyapatite and iodine. PMID:21361193

Domain decomposition by the advancing-partition method for parallel unstructured grid generation

NASA Technical Reports Server (NTRS)

Banihashemi, legal representative, Soheila (Inventor); Pirzadeh, Shahyar Z. (Inventor)

2012-01-01

In a method for domain decomposition for generating unstructured grids, a surface mesh is generated for a spatial domain. A location of a partition plane dividing the domain into two sections is determined. Triangular faces on the surface mesh that intersect the partition plane are identified. A partition grid of tetrahedral cells, dividing the domain into two sub-domains, is generated using a marching process in which a front comprises only faces of new cells which intersect the partition plane. The partition grid is generated until no active faces remain on the front. Triangular faces on each side of the partition plane are collected into two separate subsets. Each subset of triangular faces is renumbered locally and a local/global mapping is created for each sub-domain. A volume grid is generated for each sub-domain. The partition grid and volume grids are then merged using the local-global mapping.

Algebraic multigrid domain and range decomposition (AMG-DD / AMG-RD)*

DOE PAGES

Bank, R.; Falgout, R. D.; Jones, T.; ...

2015-10-29

In modern large-scale supercomputing applications, algebraic multigrid (AMG) is a leading choice for solving matrix equations. However, the high cost of communication relative to that of computation is a concern for the scalability of traditional implementations of AMG on emerging architectures. This paper introduces two new algebraic multilevel algorithms, algebraic multigrid domain decomposition (AMG-DD) and algebraic multigrid range decomposition (AMG-RD), that replace traditional AMG V-cycles with a fully overlapping domain decomposition approach. While the methods introduced here are similar in spirit to the geometric methods developed by Brandt and Diskin [Multigrid solvers on decomposed domains, in Domain Decomposition Methods inmore » Science and Engineering, Contemp. Math. 157, AMS, Providence, RI, 1994, pp. 135--155], Mitchell [Electron. Trans. Numer. Anal., 6 (1997), pp. 224--233], and Bank and Holst [SIAM J. Sci. Comput., 22 (2000), pp. 1411--1443], they differ primarily in that they are purely algebraic: AMG-RD and AMG-DD trade communication for computation by forming global composite “grids” based only on the matrix, not the geometry. (As is the usual AMG convention, “grids” here should be taken only in the algebraic sense, regardless of whether or not it corresponds to any geometry.) Another important distinguishing feature of AMG-RD and AMG-DD is their novel residual communication process that enables effective parallel computation on composite grids, avoiding the all-to-all communication costs of the geometric methods. The main purpose of this paper is to study the potential of these two algebraic methods as possible alternatives to existing AMG approaches for future parallel machines. As a result, this paper develops some theoretical properties of these methods and reports on serial numerical tests of their convergence properties over a spectrum of problem parameters.« less

Comparative study of the dynamics of lipid membrane phase decomposition in experiment and simulation.

PubMed

Burger, Stefan; Fraunholz, Thomas; Leirer, Christian; Hoppe, Ronald H W; Wixforth, Achim; Peter, Malte A; Franke, Thomas

2013-06-25

Phase decomposition in lipid membranes has been the subject of numerous investigations by both experiment and theoretical simulation, yet quantitative comparisons of the simulated data to the experimental results are rare. In this work, we present a novel way of comparing the temporal development of liquid-ordered domains obtained from numerically solving the Cahn-Hilliard equation and by inducing a phase transition in giant unilamellar vesicles (GUVs). Quantitative comparison is done by calculating the structure factor of the domain pattern. It turns out that the decomposition takes place in three distinct regimes in both experiment and simulation. These regimes are characterized by different rates of growth of the mean domain diameter, and there is quantitative agreement between experiment and simulation as to the duration of each regime and the absolute rate of growth in each regime.

Decomposition of Proteins into Dynamic Units from Atomic Cross-Correlation Functions.

PubMed

Calligari, Paolo; Gerolin, Marco; Abergel, Daniel; Polimeno, Antonino

2017-01-10

In this article, we present a clustering method of atoms in proteins based on the analysis of the correlation times of interatomic distance correlation functions computed from MD simulations. The goal is to provide a coarse-grained description of the protein in terms of fewer elements that can be treated as dynamically independent subunits. Importantly, this domain decomposition method does not take into account structural properties of the protein. Instead, the clustering of protein residues in terms of networks of dynamically correlated domains is defined on the basis of the effective correlation times of the pair distance correlation functions. For these properties, our method stands as a complementary analysis to the customary protein decomposition in terms of quasi-rigid, structure-based domains. Results obtained for a prototypal protein structure illustrate the approach proposed.

A novel fusion framework of visible light and infrared images based on singular value decomposition and adaptive DUAL-PCNN in NSST domain

NASA Astrophysics Data System (ADS)

Cheng, Boyang; Jin, Longxu; Li, Guoning

2018-06-01

Visible light and infrared images fusion has been a significant subject in imaging science. As a new contribution to this field, a novel fusion framework of visible light and infrared images based on adaptive dual-channel unit-linking pulse coupled neural networks with singular value decomposition (ADS-PCNN) in non-subsampled shearlet transform (NSST) domain is present in this paper. First, the source images are decomposed into multi-direction and multi-scale sub-images by NSST. Furthermore, an improved novel sum modified-Laplacian (INSML) of low-pass sub-image and an improved average gradient (IAVG) of high-pass sub-images are input to stimulate the ADS-PCNN, respectively. To address the large spectral difference between infrared and visible light and the occurrence of black artifacts in fused images, a local structure information operator (LSI), which comes from local area singular value decomposition in each source image, is regarded as the adaptive linking strength that enhances fusion accuracy. Compared with PCNN models in other studies, the proposed method simplifies certain peripheral parameters, and the time matrix is utilized to decide the iteration number adaptively. A series of images from diverse scenes are used for fusion experiments and the fusion results are evaluated subjectively and objectively. The results of the subjective and objective evaluation show that our algorithm exhibits superior fusion performance and is more effective than the existing typical fusion techniques.

Effect of aging temperature on phase decomposition and mechanical properties in cast duplex stainless steels

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

Mburu, Sarah; Kolli, R. Prakash; Perea, Daniel E.

The microstructure and mechanical properties in unaged and thermally aged (at 280 °C, 320 °C, 360 °C, and 400 °C to 4300 h) CF–3 and CF–8 cast duplex stainless steels (CDSS) are investigated. The unaged CF–8 steel has Cr-rich M 23C 6 carbides located at the δ–ferrite/γ–austenite heterophase interfaces that were not observed in the CF–3 steel and this corresponds to a difference in mechanical properties. Both unaged steels exhibit incipient spinodal decomposition into Fe-rich α–domains and Cr-rich α’–domains. During aging, spinodal decomposition progresses and the mean wavelength (MW) and mean amplitude (MA) of the compositional fluctuations increase as amore » function of aging temperature. Additionally, G–phase precipitates form between the spinodal decomposition domains in CF–3 at 360 °C and 400 °C and in CF–8 at 400 °C. Finally, the microstructural evolution is correlated to changes in mechanical properties.« less

Effect of aging temperature on phase decomposition and mechanical properties in cast duplex stainless steels

DOE PAGES

Mburu, Sarah; Kolli, R. Prakash; Perea, Daniel E.; ...

2017-03-06

The microstructure and mechanical properties in unaged and thermally aged (at 280 °C, 320 °C, 360 °C, and 400 °C to 4300 h) CF–3 and CF–8 cast duplex stainless steels (CDSS) are investigated. The unaged CF–8 steel has Cr-rich M 23C 6 carbides located at the δ–ferrite/γ–austenite heterophase interfaces that were not observed in the CF–3 steel and this corresponds to a difference in mechanical properties. Both unaged steels exhibit incipient spinodal decomposition into Fe-rich α–domains and Cr-rich α’–domains. During aging, spinodal decomposition progresses and the mean wavelength (MW) and mean amplitude (MA) of the compositional fluctuations increase as amore » function of aging temperature. Additionally, G–phase precipitates form between the spinodal decomposition domains in CF–3 at 360 °C and 400 °C and in CF–8 at 400 °C. Finally, the microstructural evolution is correlated to changes in mechanical properties.« less

Effect of aging temperature on phase decomposition and mechanical properties in cast duplex stainless steels

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

Mburu, Sarah; Kolli, R. Prakash; Perea, Daniel E.

The microstructure and mechanical properties in unaged and thermally aged (at 280 oC, 320 oC, 360 oC, and 400 oC to 4300 h) CF–3 and CF–8 cast duplex stainless steels (CDSS) are investigated. The unaged CF–8 steel has Cr-rich M23C6 carbides located at the δ–ferrite/γ– austenite heterophase interfaces that were not observed in the CF–3 steel and this corresponds to a difference in mechanical properties. Both unaged steels exhibit incipient spinodal decomposition into Fe-rich α–domains and Cr-rich α’–domains. During aging, spinodal decomposition progresses and the mean wavelength (MW) and mean amplitude (MA) of the compositional fluctuations increase as a functionmore » of aging temperature. Additionally, G–phase precipitates form between the spinodal decomposition domains in CF–3 at 360 oC and 400 oC and in CF–8 at 400 oC. The microstructural evolution is correlated to changes in mechanical properties.« less

GPR random noise reduction using BPD and EMD

NASA Astrophysics Data System (ADS)

Ostoori, Roya; Goudarzi, Alireza; Oskooi, Behrooz

2018-04-01

Ground-penetrating radar (GPR) exploration is a new high-frequency technology that explores near-surface objects and structures accurately. The high-frequency antenna of the GPR system makes it a high-resolution method compared to other geophysical methods. The frequency range of recorded GPR is so wide that random noise recording is inevitable due to acquisition. This kind of noise comes from unknown sources and its correlation to the adjacent traces is nearly zero. This characteristic of random noise along with the higher accuracy of GPR system makes denoising very important for interpretable results. The main objective of this paper is to reduce GPR random noise based on pursuing denoising using empirical mode decomposition. Our results showed that empirical mode decomposition in combination with basis pursuit denoising (BPD) provides satisfactory outputs due to the sifting process compared to the time-domain implementation of the BPD method on both synthetic and real examples. Our results demonstrate that because of the high computational costs, the BPD-empirical mode decomposition technique should only be used for heavily noisy signals.

Rapid Transient Pressure Field Computations in the Nearfield of Circular Transducers using Frequency Domain Time-Space Decomposition

PubMed Central

Alles, E. J.; Zhu, Y.; van Dongen, K. W. A.; McGough, R. J.

2013-01-01

The fast nearfield method, when combined with time-space decomposition, is a rapid and accurate approach for calculating transient nearfield pressures generated by ultrasound transducers. However, the standard time-space decomposition approach is only applicable to certain analytical representations of the temporal transducer surface velocity that, when applied to the fast nearfield method, are expressed as a finite sum of products of separate temporal and spatial terms. To extend time-space decomposition such that accelerated transient field simulations are enabled in the nearfield for an arbitrary transducer surface velocity, a new transient simulation method, frequency domain time-space decomposition (FDTSD), is derived. With this method, the temporal transducer surface velocity is transformed into the frequency domain, and then each complex-valued term is processed separately. Further improvements are achieved by spectral clipping, which reduces the number of terms and the computation time. Trade-offs between speed and accuracy are established for FDTSD calculations, and pressure fields obtained with the FDTSD method for a circular transducer are compared to those obtained with Field II and the impulse response method. The FDTSD approach, when combined with the fast nearfield method and spectral clipping, consistently achieves smaller errors in less time and requires less memory than Field II or the impulse response method. PMID:23160476

Active listening room compensation for massive multichannel sound reproduction systems using wave-domain adaptive filtering.

PubMed

Spors, Sascha; Buchner, Herbert; Rabenstein, Rudolf; Herbordt, Wolfgang

2007-07-01

The acoustic theory for multichannel sound reproduction systems usually assumes free-field conditions for the listening environment. However, their performance in real-world listening environments may be impaired by reflections at the walls. This impairment can be reduced by suitable compensation measures. For systems with many channels, active compensation is an option, since the compensating waves can be created by the reproduction loudspeakers. Due to the time-varying nature of room acoustics, the compensation signals have to be determined by an adaptive system. The problems associated with the successful operation of multichannel adaptive systems are addressed in this contribution. First, a method for decoupling the adaptation problem is introduced. It is based on a generalized singular value decomposition and is called eigenspace adaptive filtering. Unfortunately, it cannot be implemented in its pure form, since the continuous adaptation of the generalized singular value decomposition matrices to the variable room acoustics is numerically very demanding. However, a combination of this mathematical technique with the physical description of wave propagation yields a realizable multichannel adaptation method with good decoupling properties. It is called wave domain adaptive filtering and is discussed here in the context of wave field synthesis.

Frequency Domain Decomposition performed on the strain data obtained from the aluminium model of an offshore support structure

NASA Astrophysics Data System (ADS)

Mieloszyk, M.; Opoka, S.; Ostachowicz, W.

2015-07-01

This paper presents an application of Fibre Bragg Grating (FBG) sensors for Structural Health Monitoring (SHM) of offshore wind energy support structure model. The analysed structure is a tripod equipped with 16 FBG sensors. From a wide variety of Operational Modal Analysis (OMA) methods Frequency Domain Decomposition (FDD) technique is used in this paper under assumption that the input loading is similar to a white noise excitation. The FDD method can be applied using different sets of sensors, i.e. the one which contains all FBG sensors and the other set of sensors localised only on a particular tripod's leg. The cases considered during investigation were as follows: damaged and undamaged scenarios, different support conditions. The damage was simulated as an dismantled flange on an upper brace in one of the tripod legs. First the model was fixed to an antishaker table and investigated in the air under impulse excitations. Next the tripod was submerged into water basin in order to check the quality of the measurement set-up in different environmental condition. In this case the model was excited by regular waves.

A time-domain decomposition iterative method for the solution of distributed linear quadratic optimal control problems

NASA Astrophysics Data System (ADS)

Heinkenschloss, Matthias

2005-01-01

We study a class of time-domain decomposition-based methods for the numerical solution of large-scale linear quadratic optimal control problems. Our methods are based on a multiple shooting reformulation of the linear quadratic optimal control problem as a discrete-time optimal control (DTOC) problem. The optimality conditions for this DTOC problem lead to a linear block tridiagonal system. The diagonal blocks are invertible and are related to the original linear quadratic optimal control problem restricted to smaller time-subintervals. This motivates the application of block Gauss-Seidel (GS)-type methods for the solution of the block tridiagonal systems. Numerical experiments show that the spectral radii of the block GS iteration matrices are larger than one for typical applications, but that the eigenvalues of the iteration matrices decay to zero fast. Hence, while the GS method is not expected to convergence for typical applications, it can be effective as a preconditioner for Krylov-subspace methods. This is confirmed by our numerical tests.A byproduct of this research is the insight that certain instantaneous control techniques can be viewed as the application of one step of the forward block GS method applied to the DTOC optimality system.

JPEG2000-coded image error concealment exploiting convex sets projections.

PubMed

Atzori, Luigi; Ginesu, Giaime; Raccis, Alessio

2005-04-01

Transmission errors in JPEG2000 can be grouped into three main classes, depending on the affected area: LL, high frequencies at the lower decomposition levels, and high frequencies at the higher decomposition levels. The first type of errors are the most annoying but can be concealed exploiting the signal spatial correlation like in a number of techniques proposed in the past; the second are less annoying but more difficult to address; the latter are often imperceptible. In this paper, we address the problem of concealing the second class or errors when high bit-planes are damaged by proposing a new approach based on the theory of projections onto convex sets. Accordingly, the error effects are masked by iteratively applying two procedures: low-pass (LP) filtering in the spatial domain and restoration of the uncorrupted wavelet coefficients in the transform domain. It has been observed that a uniform LP filtering brought to some undesired side effects that negatively compensated the advantages. This problem has been overcome by applying an adaptive solution, which exploits an edge map to choose the optimal filter mask size. Simulation results demonstrated the efficiency of the proposed approach.

An asymptotic induced numerical method for the convection-diffusion-reaction equation

NASA Technical Reports Server (NTRS)

Scroggs, Jeffrey S.; Sorensen, Danny C.

1988-01-01

A parallel algorithm for the efficient solution of a time dependent reaction convection diffusion equation with small parameter on the diffusion term is presented. The method is based on a domain decomposition that is dictated by singular perturbation analysis. The analysis is used to determine regions where certain reduced equations may be solved in place of the full equation. Parallelism is evident at two levels. Domain decomposition provides parallelism at the highest level, and within each domain there is ample opportunity to exploit parallelism. Run time results demonstrate the viability of the method.

An operational modal analysis method in frequency and spatial domain

NASA Astrophysics Data System (ADS)

Wang, Tong; Zhang, Lingmi; Tamura, Yukio

2005-12-01

A frequency and spatial domain decomposition method (FSDD) for operational modal analysis (OMA) is presented in this paper, which is an extension of the complex mode indicator function (CMIF) method for experimental modal analysis (EMA). The theoretical background of the FSDD method is clarified. Singular value decomposition is adopted to separate the signal space from the noise space. Finally, an enhanced power spectrum density (PSD) is proposed to obtain more accurate modal parameters by curve fitting in the frequency domain. Moreover, a simulation case and an application case are used to validate this method.

Distributed-Memory Computing With the Langley Aerothermodynamic Upwind Relaxation Algorithm (LAURA)

NASA Technical Reports Server (NTRS)

Riley, Christopher J.; Cheatwood, F. McNeil

1997-01-01

The Langley Aerothermodynamic Upwind Relaxation Algorithm (LAURA), a Navier-Stokes solver, has been modified for use in a parallel, distributed-memory environment using the Message-Passing Interface (MPI) standard. A standard domain decomposition strategy is used in which the computational domain is divided into subdomains with each subdomain assigned to a processor. Performance is examined on dedicated parallel machines and a network of desktop workstations. The effect of domain decomposition and frequency of boundary updates on performance and convergence is also examined for several realistic configurations and conditions typical of large-scale computational fluid dynamic analysis.

Decomposition techniques

USGS Publications Warehouse

Chao, T.T.; Sanzolone, R.F.

1992-01-01

Sample decomposition is a fundamental and integral step in the procedure of geochemical analysis. It is often the limiting factor to sample throughput, especially with the recent application of the fast and modern multi-element measurement instrumentation. The complexity of geological materials makes it necessary to choose the sample decomposition technique that is compatible with the specific objective of the analysis. When selecting a decomposition technique, consideration should be given to the chemical and mineralogical characteristics of the sample, elements to be determined, precision and accuracy requirements, sample throughput, technical capability of personnel, and time constraints. This paper addresses these concerns and discusses the attributes and limitations of many techniques of sample decomposition along with examples of their application to geochemical analysis. The chemical properties of reagents as to their function as decomposition agents are also reviewed. The section on acid dissolution techniques addresses the various inorganic acids that are used individually or in combination in both open and closed systems. Fluxes used in sample fusion are discussed. The promising microwave-oven technology and the emerging field of automation are also examined. A section on applications highlights the use of decomposition techniques for the determination of Au, platinum group elements (PGEs), Hg, U, hydride-forming elements, rare earth elements (REEs), and multi-elements in geological materials. Partial dissolution techniques used for geochemical exploration which have been treated in detail elsewhere are not discussed here; nor are fire-assaying for noble metals and decomposition techniques for X-ray fluorescence or nuclear methods be discussed. ?? 1992.

Newton-Krylov-Schwarz: An implicit solver for CFD

NASA Technical Reports Server (NTRS)

Cai, Xiao-Chuan; Keyes, David E.; Venkatakrishnan, V.

1995-01-01

Newton-Krylov methods and Krylov-Schwarz (domain decomposition) methods have begun to become established in computational fluid dynamics (CFD) over the past decade. The former employ a Krylov method inside of Newton's method in a Jacobian-free manner, through directional differencing. The latter employ an overlapping Schwarz domain decomposition to derive a preconditioner for the Krylov accelerator that relies primarily on local information, for data-parallel concurrency. They may be composed as Newton-Krylov-Schwarz (NKS) methods, which seem particularly well suited for solving nonlinear elliptic systems in high-latency, distributed-memory environments. We give a brief description of this family of algorithms, with an emphasis on domain decomposition iterative aspects. We then describe numerical simulations with Newton-Krylov-Schwarz methods on aerodynamics applications emphasizing comparisons with a standard defect-correction approach, subdomain preconditioner consistency, subdomain preconditioner quality, and the effect of a coarse grid.

Mechanical and Assembly Units of Viral Capsids Identified via Quasi-Rigid Domain Decomposition

PubMed Central

Polles, Guido; Indelicato, Giuliana; Potestio, Raffaello; Cermelli, Paolo; Twarock, Reidun; Micheletti, Cristian

2013-01-01

Key steps in a viral life-cycle, such as self-assembly of a protective protein container or in some cases also subsequent maturation events, are governed by the interplay of physico-chemical mechanisms involving various spatial and temporal scales. These salient aspects of a viral life cycle are hence well described and rationalised from a mesoscopic perspective. Accordingly, various experimental and computational efforts have been directed towards identifying the fundamental building blocks that are instrumental for the mechanical response, or constitute the assembly units, of a few specific viral shells. Motivated by these earlier studies we introduce and apply a general and efficient computational scheme for identifying the stable domains of a given viral capsid. The method is based on elastic network models and quasi-rigid domain decomposition. It is first applied to a heterogeneous set of well-characterized viruses (CCMV, MS2, STNV, STMV) for which the known mechanical or assembly domains are correctly identified. The validated method is next applied to other viral particles such as L-A, Pariacoto and polyoma viruses, whose fundamental functional domains are still unknown or debated and for which we formulate verifiable predictions. The numerical code implementing the domain decomposition strategy is made freely available. PMID:24244139

The Multiscale Robin Coupled Method for flows in porous media

NASA Astrophysics Data System (ADS)

Guiraldello, Rafael T.; Ausas, Roberto F.; Sousa, Fabricio S.; Pereira, Felipe; Buscaglia, Gustavo C.

2018-02-01

A multiscale mixed method aiming at the accurate approximation of velocity and pressure fields in heterogeneous porous media is proposed. The procedure is based on a new domain decomposition method in which the local problems are subject to Robin boundary conditions. The domain decomposition procedure is defined in terms of two independent spaces on the skeleton of the decomposition, corresponding to interface pressures and fluxes, that can be chosen with great flexibility to accommodate local features of the underlying permeability fields. The well-posedness of the new domain decomposition procedure is established and its connection with the method of Douglas et al. (1993) [12], is identified, also allowing us to reinterpret the known procedure as an optimized Schwarz (or Two-Lagrange-Multiplier) method. The multiscale property of the new domain decomposition method is indicated, and its relation with the Multiscale Mortar Mixed Finite Element Method (MMMFEM) and the Multiscale Hybrid-Mixed (MHM) Finite Element Method is discussed. Numerical simulations are presented aiming at illustrating several features of the new method. Initially we illustrate the possibility of switching from MMMFEM to MHM by suitably varying the Robin condition parameter in the new multiscale method. Then we turn our attention to realistic flows in high-contrast, channelized porous formations. We show that for a range of values of the Robin condition parameter our method provides better approximations for pressure and velocity than those computed with either the MMMFEM and the MHM. This is an indication that our method has the potential to produce more accurate velocity fields in the presence of rough, realistic permeability fields of petroleum reservoirs.

Domain decomposition and matching for time-domain analysis of motions of ships advancing in head sea

NASA Astrophysics Data System (ADS)

Tang, Kai; Zhu, Ren-chuan; Miao, Guo-ping; Fan, Ju

2014-08-01

A domain decomposition and matching method in the time-domain is outlined for simulating the motions of ships advancing in waves. The flow field is decomposed into inner and outer domains by an imaginary control surface, and the Rankine source method is applied to the inner domain while the transient Green function method is used in the outer domain. Two initial boundary value problems are matched on the control surface. The corresponding numerical codes are developed, and the added masses, wave exciting forces and ship motions advancing in head sea for Series 60 ship and S175 containership, are presented and verified. A good agreement has been obtained when the numerical results are compared with the experimental data and other references. It shows that the present method is more efficient because of the panel discretization only in the inner domain during the numerical calculation, and good numerical stability is proved to avoid divergence problem regarding ships with flare.

Porting LAMMPS to GPUs.

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

Brown, William Michael; Plimpton, Steven James; Wang, Peng

2010-03-01

LAMMPS is a classical molecular dynamics code, and an acronym for Large-scale Atomic/Molecular Massively Parallel Simulator. LAMMPS has potentials for soft materials (biomolecules, polymers) and solid-state materials (metals, semiconductors) and coarse-grained or mesoscopic systems. It can be used to model atoms or, more generically, as a parallel particle simulator at the atomic, meso, or continuum scale. LAMMPS runs on single processors or in parallel using message-passing techniques and a spatial-decomposition of the simulation domain. The code is designed to be easy to modify or extend with new functionality.

Domain Decomposition with Local Mesh Refinement.

DTIC Science & Technology

1989-08-01

smoothi coefficients, or non-smooth solui ioni,. We eiriplov fromn 1 to 1024 tiles on problems containing irp to 161K (degrees of freedom. Though io... methodology survives such compromises and is even sequentially advantageous in many problems. The domain decomposition algorithms we employ (sertiun 3...iog( I + !J2 it - g i Ol Qunit squiare 1 he (,mai oive i> Hie outward normal. lfie sevoh iih exam pie, from [1. 27] has a smoothi solution, but rapidlY

Multi-Objectivising Combinatorial Optimisation Problems by Means of Elementary Landscape Decompositions.

PubMed

Ceberio, Josu; Calvo, Borja; Mendiburu, Alexander; Lozano, Jose A

2018-02-15

In the last decade, many works in combinatorial optimisation have shown that, due to the advances in multi-objective optimisation, the algorithms from this field could be used for solving single-objective problems as well. In this sense, a number of papers have proposed multi-objectivising single-objective problems in order to use multi-objective algorithms in their optimisation. In this article, we follow up this idea by presenting a methodology for multi-objectivising combinatorial optimisation problems based on elementary landscape decompositions of their objective function. Under this framework, each of the elementary landscapes obtained from the decomposition is considered as an independent objective function to optimise. In order to illustrate this general methodology, we consider four problems from different domains: the quadratic assignment problem and the linear ordering problem (permutation domain), the 0-1 unconstrained quadratic optimisation problem (binary domain), and the frequency assignment problem (integer domain). We implemented two widely known multi-objective algorithms, NSGA-II and SPEA2, and compared their performance with that of a single-objective GA. The experiments conducted on a large benchmark of instances of the four problems show that the multi-objective algorithms clearly outperform the single-objective approaches. Furthermore, a discussion on the results suggests that the multi-objective space generated by this decomposition enhances the exploration ability, thus permitting NSGA-II and SPEA2 to obtain better results in the majority of the tested instances.

Parallel deterministic transport sweeps of structured and unstructured meshes with overloaded mesh decompositions

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

Pautz, Shawn D.; Bailey, Teresa S.

Here, the efficiency of discrete ordinates transport sweeps depends on the scheduling algorithm, the domain decomposition, the problem to be solved, and the computational platform. Sweep scheduling algorithms may be categorized by their approach to several issues. In this paper we examine the strategy of domain overloading for mesh partitioning as one of the components of such algorithms. In particular, we extend the domain overloading strategy, previously defined and analyzed for structured meshes, to the general case of unstructured meshes. We also present computational results for both the structured and unstructured domain overloading cases. We find that an appropriate amountmore » of domain overloading can greatly improve the efficiency of parallel sweeps for both structured and unstructured partitionings of the test problems examined on up to 10 5 processor cores.« less

Parallel deterministic transport sweeps of structured and unstructured meshes with overloaded mesh decompositions

DOE PAGES

Pautz, Shawn D.; Bailey, Teresa S.

2016-11-29

Here, the efficiency of discrete ordinates transport sweeps depends on the scheduling algorithm, the domain decomposition, the problem to be solved, and the computational platform. Sweep scheduling algorithms may be categorized by their approach to several issues. In this paper we examine the strategy of domain overloading for mesh partitioning as one of the components of such algorithms. In particular, we extend the domain overloading strategy, previously defined and analyzed for structured meshes, to the general case of unstructured meshes. We also present computational results for both the structured and unstructured domain overloading cases. We find that an appropriate amountmore » of domain overloading can greatly improve the efficiency of parallel sweeps for both structured and unstructured partitionings of the test problems examined on up to 10 5 processor cores.« less

A comparative study on book shelf structure based on different domain modal analysis

NASA Astrophysics Data System (ADS)

Sabamehr, Ardalan; Roy, Timir Baran; Bagchi, Ashutosh

2017-04-01

Structural Health Monitoring (SHM) based on the vibration of structures has been very attractive topic for researchers in different fields such as: civil, aeronautical and mechanical engineering. The aim of this paper is to compare three most common modal identification techniques such as Frequency Domain Decomposition (FDD), Stochastic Subspace Identification (SSI) and Continuous Wavelet Transform (CWT) to find modal properties (such as natural frequency, mode shape and damping ratio) of three story book shelf steel structure which was built in Concordia University Lab. The modified Complex Morlet wavelet have been selected for wavelet in order to use asymptotic signal rather than real one with variable bandwidth and wavelet central frequency. So, CWT is able to detect instantaneous modulus and phase by use of local maxima ridge detection.

Discretization and Preconditioning Algorithms for the Euler and Navier-Stokes Equations on Unstructured Meshes

NASA Technical Reports Server (NTRS)

Barth, Timothy J.; Kutler, Paul (Technical Monitor)

1998-01-01

Several stabilized demoralization procedures for conservation law equations on triangulated domains will be considered. Specifically, numerical schemes based on upwind finite volume, fluctuation splitting, Galerkin least-squares, and space discontinuous Galerkin demoralization will be considered in detail. A standard energy analysis for several of these methods will be given via entropy symmetrization. Next, we will present some relatively new theoretical results concerning congruence relationships for left or right symmetrized equations. These results suggest new variants of existing FV, DG, GLS, and FS methods which are computationally more efficient while retaining the pleasant theoretical properties achieved by entropy symmetrization. In addition, the task of Jacobean linearization of these schemes for use in Newton's method is greatly simplified owing to exploitation of exact symmetries which exist in the system. The FV, FS and DG schemes also permit discrete maximum principle analysis and enforcement which greatly adds to the robustness of the methods. Discrete maximum principle theory will be presented for general finite volume approximations on unstructured meshes. Next, we consider embedding these nonlinear space discretizations into exact and inexact Newton solvers which are preconditioned using a nonoverlapping (Schur complement) domain decomposition technique. Elements of nonoverlapping domain decomposition for elliptic problems will be reviewed followed by the present extension to hyperbolic and elliptic-hyperbolic problems. Other issues of practical relevance such the meshing of geometries, code implementation, turbulence modeling, global convergence, etc, will. be addressed as needed.

Discretization and Preconditioning Algorithms for the Euler and Navier-Stokes Equations on Unstructured Meshes

NASA Technical Reports Server (NTRS)

Barth, Timothy; Chancellor, Marisa K. (Technical Monitor)

1997-01-01

Several stabilized discretization procedures for conservation law equations on triangulated domains will be considered. Specifically, numerical schemes based on upwind finite volume, fluctuation splitting, Galerkin least-squares, and space discontinuous Galerkin discretization will be considered in detail. A standard energy analysis for several of these methods will be given via entropy symmetrization. Next, we will present some relatively new theoretical results concerning congruence relationships for left or right symmetrized equations. These results suggest new variants of existing FV, DG, GLS and FS methods which are computationally more efficient while retaining the pleasant theoretical properties achieved by entropy symmetrization. In addition, the task of Jacobian linearization of these schemes for use in Newton's method is greatly simplified owing to exploitation of exact symmetries which exist in the system. These variants have been implemented in the "ELF" library for which example calculations will be shown. The FV, FS and DG schemes also permit discrete maximum principle analysis and enforcement which greatly adds to the robustness of the methods. Some prevalent limiting strategies will be reviewed. Next, we consider embedding these nonlinear space discretizations into exact and inexact Newton solvers which are preconditioned using a nonoverlapping (Schur complement) domain decomposition technique. Elements of nonoverlapping domain decomposition for elliptic problems will be reviewed followed by the present extension to hyperbolic and elliptic-hyperbolic problems. Other issues of practical relevance such the meshing of geometries, code implementation, turbulence modeling, global convergence, etc. will be addressed as needed.

Conceptual design optimization study

NASA Technical Reports Server (NTRS)

Hollowell, S. J.; Beeman, E. R., II; Hiyama, R. M.

1990-01-01

The feasibility of applying multilevel functional decomposition and optimization techniques to conceptual design of advanced fighter aircraft was investigated. Applying the functional decomposition techniques to the conceptual design phase appears to be feasible. The initial implementation of the modified design process will optimize wing design variables. A hybrid approach, combining functional decomposition techniques for generation of aerodynamic and mass properties linear sensitivity derivatives with existing techniques for sizing mission performance and optimization, is proposed.

Computation of forces arising from the polarizable continuum model within the domain-decomposition paradigm

NASA Astrophysics Data System (ADS)

Gatto, Paolo; Lipparini, Filippo; Stamm, Benjamin

2017-12-01

The domain-decomposition (dd) paradigm, originally introduced for the conductor-like screening model, has been recently extended to the dielectric Polarizable Continuum Model (PCM), resulting in the ddPCM method. We present here a complete derivation of the analytical derivatives of the ddPCM energy with respect to the positions of the solute's atoms and discuss their efficient implementation. As it is the case for the energy, we observe a quadratic scaling, which is discussed and demonstrated with numerical tests.

Tensorial extensions of independent component analysis for multisubject FMRI analysis.

PubMed

Beckmann, C F; Smith, S M

2005-03-01

We discuss model-free analysis of multisubject or multisession FMRI data by extending the single-session probabilistic independent component analysis model (PICA; Beckmann and Smith, 2004. IEEE Trans. on Medical Imaging, 23 (2) 137-152) to higher dimensions. This results in a three-way decomposition that represents the different signals and artefacts present in the data in terms of their temporal, spatial, and subject-dependent variations. The technique is derived from and compared with parallel factor analysis (PARAFAC; Harshman and Lundy, 1984. In Research methods for multimode data analysis, chapter 5, pages 122-215. Praeger, New York). Using simulated data as well as data from multisession and multisubject FMRI studies we demonstrate that the tensor PICA approach is able to efficiently and accurately extract signals of interest in the spatial, temporal, and subject/session domain. The final decompositions improve upon PARAFAC results in terms of greater accuracy, reduced interference between the different estimated sources (reduced cross-talk), robustness (against deviations of the data from modeling assumptions and against overfitting), and computational speed. On real FMRI 'activation' data, the tensor PICA approach is able to extract plausible activation maps, time courses, and session/subject modes as well as provide a rich description of additional processes of interest such as image artefacts or secondary activation patterns. The resulting data decomposition gives simple and useful representations of multisubject/multisession FMRI data that can aid the interpretation and optimization of group FMRI studies beyond what can be achieved using model-based analysis techniques.

Performance evaluation of canny edge detection on a tiled multicore architecture

NASA Astrophysics Data System (ADS)

Brethorst, Andrew Z.; Desai, Nehal; Enright, Douglas P.; Scrofano, Ronald

2011-01-01

In the last few years, a variety of multicore architectures have been used to parallelize image processing applications. In this paper, we focus on assessing the parallel speed-ups of different Canny edge detection parallelization strategies on the Tile64, a tiled multicore architecture developed by the Tilera Corporation. Included in these strategies are different ways Canny edge detection can be parallelized, as well as differences in data management. The two parallelization strategies examined were loop-level parallelism and domain decomposition. Loop-level parallelism is achieved through the use of OpenMP,1 and it is capable of parallelization across the range of values over which a loop iterates. Domain decomposition is the process of breaking down an image into subimages, where each subimage is processed independently, in parallel. The results of the two strategies show that for the same number of threads, programmer implemented, domain decomposition exhibits higher speed-ups than the compiler managed, loop-level parallelism implemented with OpenMP.

A Framework for Parallel Unstructured Grid Generation for Complex Aerodynamic Simulations

NASA Technical Reports Server (NTRS)

Zagaris, George; Pirzadeh, Shahyar Z.; Chrisochoides, Nikos

2009-01-01

A framework for parallel unstructured grid generation targeting both shared memory multi-processors and distributed memory architectures is presented. The two fundamental building-blocks of the framework consist of: (1) the Advancing-Partition (AP) method used for domain decomposition and (2) the Advancing Front (AF) method used for mesh generation. Starting from the surface mesh of the computational domain, the AP method is applied recursively to generate a set of sub-domains. Next, the sub-domains are meshed in parallel using the AF method. The recursive nature of domain decomposition naturally maps to a divide-and-conquer algorithm which exhibits inherent parallelism. For the parallel implementation, the Master/Worker pattern is employed to dynamically balance the varying workloads of each task on the set of available CPUs. Performance results by this approach are presented and discussed in detail as well as future work and improvements.

A refined Frequency Domain Decomposition tool for structural modal monitoring in earthquake engineering

NASA Astrophysics Data System (ADS)

Pioldi, Fabio; Rizzi, Egidio

2017-07-01

Output-only structural identification is developed by a refined Frequency Domain Decomposition ( rFDD) approach, towards assessing current modal properties of heavy-damped buildings (in terms of identification challenge), under strong ground motions. Structural responses from earthquake excitations are taken as input signals for the identification algorithm. A new dedicated computational procedure, based on coupled Chebyshev Type II bandpass filters, is outlined for the effective estimation of natural frequencies, mode shapes and modal damping ratios. The identification technique is also coupled with a Gabor Wavelet Transform, resulting in an effective and self-contained time-frequency analysis framework. Simulated response signals generated by shear-type frames (with variable structural features) are used as a necessary validation condition. In this context use is made of a complete set of seismic records taken from the FEMA P695 database, i.e. all 44 "Far-Field" (22 NS, 22 WE) earthquake signals. The modal estimates are statistically compared to their target values, proving the accuracy of the developed algorithm in providing prompt and accurate estimates of all current strong ground motion modal parameters. At this stage, such analysis tool may be employed for convenient application in the realm of Earthquake Engineering, towards potential Structural Health Monitoring and damage detection purposes.

Underdetermined blind separation of three-way fluorescence spectra of PAHs in water

NASA Astrophysics Data System (ADS)

Yang, Ruifang; Zhao, Nanjing; Xiao, Xue; Zhu, Wei; Chen, Yunan; Yin, Gaofang; Liu, Jianguo; Liu, Wenqing

2018-06-01

In this work, underdetermined blind decomposition method is developed to recognize individual components from the three-way fluorescent spectra of their mixtures by using sparse component analysis (SCA). The mixing matrix is estimated from the mixtures using fuzzy data clustering algorithm together with the scatters corresponding to local energy maximum value in the time-frequency domain, and the spectra of object components are recovered by pseudo inverse technique. As an example, using this method three and four pure components spectra can be blindly extracted from two samples of their mixture, with similarities between resolved and reference spectra all above 0.80. This work opens a new and effective path to realize monitoring PAHs in water by three-way fluorescence spectroscopy technique.

Parallel implementation of the particle simulation method with dynamic load balancing: Toward realistic geodynamical simulation

NASA Astrophysics Data System (ADS)

Furuichi, M.; Nishiura, D.

2015-12-01

Fully Lagrangian methods such as Smoothed Particle Hydrodynamics (SPH) and Discrete Element Method (DEM) have been widely used to solve the continuum and particles motions in the computational geodynamics field. These mesh-free methods are suitable for the problems with the complex geometry and boundary. In addition, their Lagrangian nature allows non-diffusive advection useful for tracking history dependent properties (e.g. rheology) of the material. These potential advantages over the mesh-based methods offer effective numerical applications to the geophysical flow and tectonic processes, which are for example, tsunami with free surface and floating body, magma intrusion with fracture of rock, and shear zone pattern generation of granular deformation. In order to investigate such geodynamical problems with the particle based methods, over millions to billion particles are required for the realistic simulation. Parallel computing is therefore important for handling such huge computational cost. An efficient parallel implementation of SPH and DEM methods is however known to be difficult especially for the distributed-memory architecture. Lagrangian methods inherently show workload imbalance problem for parallelization with the fixed domain in space, because particles move around and workloads change during the simulation. Therefore dynamic load balance is key technique to perform the large scale SPH and DEM simulation. In this work, we present the parallel implementation technique of SPH and DEM method utilizing dynamic load balancing algorithms toward the high resolution simulation over large domain using the massively parallel super computer system. Our method utilizes the imbalances of the executed time of each MPI process as the nonlinear term of parallel domain decomposition and minimizes them with the Newton like iteration method. In order to perform flexible domain decomposition in space, the slice-grid algorithm is used. Numerical tests show that our approach is suitable for solving the particles with different calculation costs (e.g. boundary particles) as well as the heterogeneous computer architecture. We analyze the parallel efficiency and scalability on the super computer systems (K-computer, Earth simulator 3, etc.).

Vision-based system identification technique for building structures using a motion capture system

NASA Astrophysics Data System (ADS)

Oh, Byung Kwan; Hwang, Jin Woo; Kim, Yousok; Cho, Tongjun; Park, Hyo Seon

2015-11-01

This paper presents a new vision-based system identification (SI) technique for building structures by using a motion capture system (MCS). The MCS with outstanding capabilities for dynamic response measurements can provide gage-free measurements of vibrations through the convenient installation of multiple markers. In this technique, from the dynamic displacement responses measured by MCS, the dynamic characteristics (natural frequency, mode shape, and damping ratio) of building structures are extracted after the processes of converting the displacement from MCS to acceleration and conducting SI by frequency domain decomposition. A free vibration experiment on a three-story shear frame was conducted to validate the proposed technique. The SI results from the conventional accelerometer-based method were compared with those from the proposed technique and showed good agreement, which confirms the validity and applicability of the proposed vision-based SI technique for building structures. Furthermore, SI directly employing MCS measured displacements to FDD was performed and showed identical results to those of conventional SI method.

Deep data analysis via physically constrained linear unmixing: universal framework, domain examples, and a community-wide platform.

PubMed

Kannan, R; Ievlev, A V; Laanait, N; Ziatdinov, M A; Vasudevan, R K; Jesse, S; Kalinin, S V

2018-01-01

Many spectral responses in materials science, physics, and chemistry experiments can be characterized as resulting from the superposition of a number of more basic individual spectra. In this context, unmixing is defined as the problem of determining the individual spectra, given measurements of multiple spectra that are spatially resolved across samples, as well as the determination of the corresponding abundance maps indicating the local weighting of each individual spectrum. Matrix factorization is a popular linear unmixing technique that considers that the mixture model between the individual spectra and the spatial maps is linear. Here, we present a tutorial paper targeted at domain scientists to introduce linear unmixing techniques, to facilitate greater understanding of spectroscopic imaging data. We detail a matrix factorization framework that can incorporate different domain information through various parameters of the matrix factorization method. We demonstrate many domain-specific examples to explain the expressivity of the matrix factorization framework and show how the appropriate use of domain-specific constraints such as non-negativity and sum-to-one abundance result in physically meaningful spectral decompositions that are more readily interpretable. Our aim is not only to explain the off-the-shelf available tools, but to add additional constraints when ready-made algorithms are unavailable for the task. All examples use the scalable open source implementation from https://github.com/ramkikannan/nmflibrary that can run from small laptops to supercomputers, creating a user-wide platform for rapid dissemination and adoption across scientific disciplines.

Scalable domain decomposition solvers for stochastic PDEs in high performance computing

DOE PAGES

Desai, Ajit; Khalil, Mohammad; Pettit, Chris; ...

2017-09-21

Stochastic spectral finite element models of practical engineering systems may involve solutions of linear systems or linearized systems for non-linear problems with billions of unknowns. For stochastic modeling, it is therefore essential to design robust, parallel and scalable algorithms that can efficiently utilize high-performance computing to tackle such large-scale systems. Domain decomposition based iterative solvers can handle such systems. And though these algorithms exhibit excellent scalabilities, significant algorithmic and implementational challenges exist to extend them to solve extreme-scale stochastic systems using emerging computing platforms. Intrusive polynomial chaos expansion based domain decomposition algorithms are extended here to concurrently handle high resolutionmore » in both spatial and stochastic domains using an in-house implementation. Sparse iterative solvers with efficient preconditioners are employed to solve the resulting global and subdomain level local systems through multi-level iterative solvers. We also use parallel sparse matrix–vector operations to reduce the floating-point operations and memory requirements. Numerical and parallel scalabilities of these algorithms are presented for the diffusion equation having spatially varying diffusion coefficient modeled by a non-Gaussian stochastic process. Scalability of the solvers with respect to the number of random variables is also investigated.« less

Scalable domain decomposition solvers for stochastic PDEs in high performance computing

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

Desai, Ajit; Khalil, Mohammad; Pettit, Chris

Stochastic spectral finite element models of practical engineering systems may involve solutions of linear systems or linearized systems for non-linear problems with billions of unknowns. For stochastic modeling, it is therefore essential to design robust, parallel and scalable algorithms that can efficiently utilize high-performance computing to tackle such large-scale systems. Domain decomposition based iterative solvers can handle such systems. And though these algorithms exhibit excellent scalabilities, significant algorithmic and implementational challenges exist to extend them to solve extreme-scale stochastic systems using emerging computing platforms. Intrusive polynomial chaos expansion based domain decomposition algorithms are extended here to concurrently handle high resolutionmore » in both spatial and stochastic domains using an in-house implementation. Sparse iterative solvers with efficient preconditioners are employed to solve the resulting global and subdomain level local systems through multi-level iterative solvers. We also use parallel sparse matrix–vector operations to reduce the floating-point operations and memory requirements. Numerical and parallel scalabilities of these algorithms are presented for the diffusion equation having spatially varying diffusion coefficient modeled by a non-Gaussian stochastic process. Scalability of the solvers with respect to the number of random variables is also investigated.« less

Coherency strain engineered decomposition of unstable multilayer alloys for improved thermal stability

NASA Astrophysics Data System (ADS)

Forsén, R.; Ghafoor, N.; Odén, M.

2013-12-01

A concept to improve hardness and thermal stability of unstable multilayer alloys is presented based on control of the coherency strain such that the driving force for decomposition is favorably altered. Cathodic arc evaporated cubic TiCrAlN/Ti1-xCrxN multilayer coatings are used as demonstrators. Upon annealing, the coatings undergo spinodal decomposition into nanometer-sized coherent Ti- and Al-rich cubic domains which is affected by the coherency strain. In addition, the growth of the domains is restricted by the surrounding TiCrN layer compared to a non-layered TiCrAlN coating which together results in an improved thermal stability of the cubic structure. A significant hardness increase is seen during decomposition for the case with high coherency strain while a low coherency strain results in a hardness decrease for high annealing temperatures. The metal diffusion paths during the domain coarsening are affected by strain which in turn is controlled by the Cr-content (x) in the Ti1-xCrxN layers. For x = 0 the diffusion occurs both parallel and perpendicular to the growth direction but for x > =0.9 the diffusion occurs predominantly parallel to the growth direction. Altogether this study shows a structural tool to alter and fine-tune high temperature properties of multicomponent materials.

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

Le, Huy Q.; Molloi, Sabee

Purpose: Energy resolving detectors provide more than one spectral measurement in one image acquisition. The purpose of this study is to investigate, with simulation, the ability to decompose four materials using energy discriminating detectors and least squares minimization techniques. Methods: Three least squares parameter estimation decomposition techniques were investigated for four-material breast imaging tasks in the image domain. The first technique treats the voxel as if it consisted of fractions of all the materials. The second method assumes that a voxel primarily contains one material and divides the decomposition process into segmentation and quantification tasks. The third is similar tomore » the second method but a calibration was used. The simulated computed tomography (CT) system consisted of an 80 kVp spectrum and a CdZnTe (CZT) detector that could resolve the x-ray spectrum into five energy bins. A postmortem breast specimen was imaged with flat panel CT to provide a model for the digital phantoms. Hydroxyapatite (HA) (50, 150, 250, 350, 450, and 550 mg/ml) and iodine (4, 12, 20, 28, 36, and 44 mg/ml) contrast elements were embedded into the glandular region of the phantoms. Calibration phantoms consisted of a 30/70 glandular-to-adipose tissue ratio with embedded HA (100, 200, 300, 400, and 500 mg/ml) and iodine (5, 15, 25, 35, and 45 mg/ml). The x-ray transport process was simulated where the Beer-Lambert law, Poisson process, and CZT absorption efficiency were applied. Qualitative and quantitative evaluations of the decomposition techniques were performed and compared. The effect of breast size was also investigated. Results: The first technique decomposed iodine adequately but failed for other materials. The second method separated the materials but was unable to quantify the materials. With the addition of a calibration, the third technique provided good separation and quantification of hydroxyapatite, iodine, glandular, and adipose tissues. Quantification with this technique was accurate with errors of 9.83% and 6.61% for HA and iodine, respectively. Calibration at one point (one breast size) showed increased errors as the mismatch in breast diameters between calibration and measurement increased. A four-point calibration successfully decomposed breast diameter spanning the entire range from 8 to 20 cm. For a 14 cm breast, errors were reduced from 5.44% to 1.75% and from 6.17% to 3.27% with the multipoint calibration for HA and iodine, respectively. Conclusions: The results of the simulation study showed that a CT system based on CZT detectors in conjunction with least squares minimization technique can be used to decompose four materials. The calibrated least squares parameter estimation decomposition technique performed the best, separating and accurately quantifying the concentrations of hydroxyapatite and iodine.« less

A New Coarsening Operator for the Optimal Preconditioning of the Dual and Primal Domain Decomposition Methods: Application to Problems with Severe Coefficient Jumps

NASA Technical Reports Server (NTRS)

Farhat, Charbel; Rixen, Daniel

1996-01-01

We present an optimal preconditioning algorithm that is equally applicable to the dual (FETI) and primal (Balancing) Schur complement domain decomposition methods, and which successfully addresses the problems of subdomain heterogeneities including the effects of large jumps of coefficients. The proposed preconditioner is derived from energy principles and embeds a new coarsening operator that propagates the error globally and accelerates convergence. The resulting iterative solver is illustrated with the solution of highly heterogeneous elasticity problems.

Multiscale Simulations of Magnetic Island Coalescence

NASA Technical Reports Server (NTRS)

Dorelli, John C.

2010-01-01

We describe a new interactive parallel Adaptive Mesh Refinement (AMR) framework written in the Python programming language. This new framework, PyAMR, hides the details of parallel AMR data structures and algorithms (e.g., domain decomposition, grid partition, and inter-process communication), allowing the user to focus on the development of algorithms for advancing the solution of a systems of partial differential equations on a single uniform mesh. We demonstrate the use of PyAMR by simulating the pairwise coalescence of magnetic islands using the resistive Hall MHD equations. Techniques for coupling different physics models on different levels of the AMR grid hierarchy are discussed.

A numerical code for the simulation of non-equilibrium chemically reacting flows on hybrid CPU-GPU clusters

NASA Astrophysics Data System (ADS)

Kudryavtsev, Alexey N.; Kashkovsky, Alexander V.; Borisov, Semyon P.; Shershnev, Anton A.

2017-10-01

In the present work a computer code RCFS for numerical simulation of chemically reacting compressible flows on hybrid CPU/GPU supercomputers is developed. It solves 3D unsteady Euler equations for multispecies chemically reacting flows in general curvilinear coordinates using shock-capturing TVD schemes. Time advancement is carried out using the explicit Runge-Kutta TVD schemes. Program implementation uses CUDA application programming interface to perform GPU computations. Data between GPUs is distributed via domain decomposition technique. The developed code is verified on the number of test cases including supersonic flow over a cylinder.

Evaluating the performance of distributed approaches for modal identification

NASA Astrophysics Data System (ADS)

Krishnan, Sriram S.; Sun, Zhuoxiong; Irfanoglu, Ayhan; Dyke, Shirley J.; Yan, Guirong

2011-04-01

In this paper two modal identification approaches appropriate for use in a distributed computing environment are applied to a full-scale, complex structure. The natural excitation technique (NExT) is used in conjunction with a condensed eigensystem realization algorithm (ERA), and the frequency domain decomposition with peak-picking (FDD-PP) are both applied to sensor data acquired from a 57.5-ft, 10 bay highway sign truss structure. Monte-Carlo simulations are performed on a numerical example to investigate the statistical properties and sensitivity to noise of the two distributed algorithms. Experimental results are provided and discussed.

Iterative refinement of implicit boundary models for improved geological feature reproduction

NASA Astrophysics Data System (ADS)

Martin, Ryan; Boisvert, Jeff B.

2017-12-01

Geological domains contain non-stationary features that cannot be described by a single direction of continuity. Non-stationary estimation frameworks generate more realistic curvilinear interpretations of subsurface geometries. A radial basis function (RBF) based implicit modeling framework using domain decomposition is developed that permits introduction of locally varying orientations and magnitudes of anisotropy for boundary models to better account for the local variability of complex geological deposits. The interpolation framework is paired with a method to automatically infer the locally predominant orientations, which results in a rapid and robust iterative non-stationary boundary modeling technique that can refine locally anisotropic geological shapes automatically from the sample data. The method also permits quantification of the volumetric uncertainty associated with the boundary modeling. The methodology is demonstrated on a porphyry dataset and shows improved local geological features.

Multi-Group Maximum Entropy Model for Translational Non-Equilibrium

NASA Technical Reports Server (NTRS)

Jayaraman, Vegnesh; Liu, Yen; Panesi, Marco

2017-01-01

The aim of the current work is to describe a new model for flows in translational non- equilibrium. Starting from the statistical description of a gas proposed by Boltzmann, the model relies on a domain decomposition technique in velocity space. Using the maximum entropy principle, the logarithm of the distribution function in each velocity sub-domain (group) is expressed with a power series in molecular velocity. New governing equations are obtained using the method of weighted residuals by taking the velocity moments of the Boltzmann equation. The model is applied to a spatially homogeneous Boltzmann equation with a Bhatnagar-Gross-Krook1(BGK) model collision operator and the relaxation of an initial non-equilibrium distribution to a Maxwellian is studied using the model. In addition, numerical results obtained using the model for a 1D shock tube problem are also reported.

Domain decomposition method for the Baltic Sea based on theory of adjoint equation and inverse problem.

NASA Astrophysics Data System (ADS)

Lezina, Natalya; Agoshkov, Valery

2017-04-01

Domain decomposition method (DDM) allows one to present a domain with complex geometry as a set of essentially simpler subdomains. This method is particularly applied for the hydrodynamics of oceans and seas. In each subdomain the system of thermo-hydrodynamic equations in the Boussinesq and hydrostatic approximations is solved. The problem of obtaining solution in the whole domain is that it is necessary to combine solutions in subdomains. For this purposes iterative algorithm is created and numerical experiments are conducted to investigate an effectiveness of developed algorithm using DDM. For symmetric operators in DDM, Poincare-Steklov's operators [1] are used, but for the problems of the hydrodynamics, it is not suitable. In this case for the problem, adjoint equation method [2] and inverse problem theory are used. In addition, it is possible to create algorithms for the parallel calculations using DDM on multiprocessor computer system. DDM for the model of the Baltic Sea dynamics is numerically studied. The results of numerical experiments using DDM are compared with the solution of the system of hydrodynamic equations in the whole domain. The work was supported by the Russian Science Foundation (project 14-11-00609, the formulation of the iterative process and numerical experiments). [1] V.I. Agoshkov, Domain Decompositions Methods in the Mathematical Physics Problem // Numerical processes and systems, No 8, Moscow, 1991 (in Russian). [2] V.I. Agoshkov, Optimal Control Approaches and Adjoint Equations in the Mathematical Physics Problem, Institute of Numerical Mathematics, RAS, Moscow, 2003 (in Russian).

Fast modal decomposition for optical fibers using digital holography.

PubMed

Lyu, Meng; Lin, Zhiquan; Li, Guowei; Situ, Guohai

2017-07-26

Eigenmode decomposition of the light field at the output end of optical fibers can provide fundamental insights into the nature of electromagnetic-wave propagation through the fibers. Here we present a fast and complete modal decomposition technique for step-index optical fibers. The proposed technique employs digital holography to measure the light field at the output end of the multimode optical fiber, and utilizes the modal orthonormal property of the basis modes to calculate the modal coefficients of each mode. Optical experiments were carried out to demonstrate the proposed decomposition technique, showing that this approach is fast, accurate and cost-effective.

How to Compute the Partial Fraction Decomposition without Really Trying

ERIC Educational Resources Information Center

Brazier, Richard; Boman, Eugene

2007-01-01

For various reasons there has been a recent trend in college and high school calculus courses to de-emphasize teaching the Partial Fraction Decomposition (PFD) as an integration technique. This is regrettable because the Partial Fraction Decomposition is considerably more than an integration technique. It is, in fact, a general purpose tool which…

Analysis and Prediction of Sea Ice Evolution using Koopman Mode Decomposition Techniques

DTIC Science & Technology

2018-04-30

Title: Analysis and Prediction of Sea Ice Evolution using Koopman Mode Decomposition Techniques Subject: Monthly Progress Report Period of...Resources: N/A TOTAL: $18,687 2 TECHNICAL STATUS REPORT Abstract The program goal is analysis of sea ice dynamical behavior using Koopman Mode Decompo...sition (KMD) techniques. The work in the program’s first month consisted of improvements to data processing code, inclusion of additional arctic sea ice

Using Multiple Grids To Compute Flows

NASA Technical Reports Server (NTRS)

Rai, Man Mohan

1991-01-01

Paper discusses decomposition of global grids into multiple patched and/or overlaid local grids in computations of fluid flow. Such "domain decomposition" particularly useful in computation of flows about complicated bodies moving relative to each other; for example, flows associated with rotors and stators in turbomachinery and rotors and fuselages in helicopters.

Empirical projection-based basis-component decomposition method

NASA Astrophysics Data System (ADS)

Brendel, Bernhard; Roessl, Ewald; Schlomka, Jens-Peter; Proksa, Roland

2009-02-01

Advances in the development of semiconductor based, photon-counting x-ray detectors stimulate research in the domain of energy-resolving pre-clinical and clinical computed tomography (CT). For counting detectors acquiring x-ray attenuation in at least three different energy windows, an extended basis component decomposition can be performed in which in addition to the conventional approach of Alvarez and Macovski a third basis component is introduced, e.g., a gadolinium based CT contrast material. After the decomposition of the measured projection data into the basis component projections, conventional filtered-backprojection reconstruction is performed to obtain the basis-component images. In recent work, this basis component decomposition was obtained by maximizing the likelihood-function of the measurements. This procedure is time consuming and often unstable for excessively noisy data or low intrinsic energy resolution of the detector. Therefore, alternative procedures are of interest. Here, we introduce a generalization of the idea of empirical dual-energy processing published by Stenner et al. to multi-energy, photon-counting CT raw data. Instead of working in the image-domain, we use prior spectral knowledge about the acquisition system (tube spectra, bin sensitivities) to parameterize the line-integrals of the basis component decomposition directly in the projection domain. We compare this empirical approach with the maximum-likelihood (ML) approach considering image noise and image bias (artifacts) and see that only moderate noise increase is to be expected for small bias in the empirical approach. Given the drastic reduction of pre-processing time, the empirical approach is considered a viable alternative to the ML approach.

Interdependence between Greece and other European stock markets: A comparison of wavelet and VMD copula, and the portfolio implications

NASA Astrophysics Data System (ADS)

Shahzad, Syed Jawad Hussain; Kumar, Ronald Ravinesh; Ali, Sajid; Ameer, Saba

2016-09-01

The interdependence of Greece and other European stock markets and the subsequent portfolio implications are examined in wavelet and variational mode decomposition domain. In applying the decomposition techniques, we analyze the structural properties of data and distinguish between short and long term dynamics of stock market returns. First, the GARCH-type models are fitted to obtain the standardized residuals. Next, different copula functions are evaluated, and based on the conventional information criteria and time varying parameter, Joe-Clayton copula is chosen to model the tail dependence between the stock markets. The short-run lower tail dependence time paths show a sudden increase in comovement during the global financial crises. The results of the long-run dependence suggest that European stock markets have higher interdependence with Greece stock market. Individual country's Value at Risk (VaR) separates the countries into two distinct groups. Finally, the two-asset portfolio VaR measures provide potential markets for Greece stock market investment diversification.

Newmark-Beta-FDTD method for super-resolution analysis of time reversal waves

NASA Astrophysics Data System (ADS)

Shi, Sheng-Bing; Shao, Wei; Ma, Jing; Jin, Congjun; Wang, Xiao-Hua

2017-09-01

In this work, a new unconditionally stable finite-difference time-domain (FDTD) method with the split-field perfectly matched layer (PML) is proposed for the analysis of time reversal (TR) waves. The proposed method is very suitable for multiscale problems involving microstructures. The spatial and temporal derivatives in this method are discretized by the central difference technique and Newmark-Beta algorithm, respectively, and the derivation results in the calculation of a banded-sparse matrix equation. Since the coefficient matrix keeps unchanged during the whole simulation process, the lower-upper (LU) decomposition of the matrix needs to be performed only once at the beginning of the calculation. Moreover, the reverse Cuthill-Mckee (RCM) technique, an effective preprocessing technique in bandwidth compression of sparse matrices, is used to improve computational efficiency. The super-resolution focusing of TR wave propagation in two- and three-dimensional spaces is included to validate the accuracy and efficiency of the proposed method.

Trend extraction using empirical mode decomposition and statistical empirical mode decomposition: Case study: Kuala Lumpur stock market

NASA Astrophysics Data System (ADS)

Jaber, Abobaker M.

2014-12-01

Two nonparametric methods for prediction and modeling of financial time series signals are proposed. The proposed techniques are designed to handle non-stationary and non-linearity behave and to extract meaningful signals for reliable prediction. Due to Fourier Transform (FT), the methods select significant decomposed signals that will be employed for signal prediction. The proposed techniques developed by coupling Holt-winter method with Empirical Mode Decomposition (EMD) and it is Extending the scope of empirical mode decomposition by smoothing (SEMD). To show performance of proposed techniques, we analyze daily closed price of Kuala Lumpur stock market index.

Underdetermined blind separation of three-way fluorescence spectra of PAHs in water.

PubMed

Yang, Ruifang; Zhao, Nanjing; Xiao, Xue; Zhu, Wei; Chen, Yunan; Yin, Gaofang; Liu, Jianguo; Liu, Wenqing

2018-06-15

In this work, underdetermined blind decomposition method is developed to recognize individual components from the three-way fluorescent spectra of their mixtures by using sparse component analysis (SCA). The mixing matrix is estimated from the mixtures using fuzzy data clustering algorithm together with the scatters corresponding to local energy maximum value in the time-frequency domain, and the spectra of object components are recovered by pseudo inverse technique. As an example, using this method three and four pure components spectra can be blindly extracted from two samples of their mixture, with similarities between resolved and reference spectra all above 0.80. This work opens a new and effective path to realize monitoring PAHs in water by three-way fluorescence spectroscopy technique. Copyright © 2018 Elsevier B.V. All rights reserved.

Signal processing method and system for noise removal and signal extraction

DOEpatents

Fu, Chi Yung; Petrich, Loren

2009-04-14

A signal processing method and system combining smooth level wavelet pre-processing together with artificial neural networks all in the wavelet domain for signal denoising and extraction. Upon receiving a signal corrupted with noise, an n-level decomposition of the signal is performed using a discrete wavelet transform to produce a smooth component and a rough component for each decomposition level. The n.sup.th level smooth component is then inputted into a corresponding neural network pre-trained to filter out noise in that component by pattern recognition in the wavelet domain. Additional rough components, beginning at the highest level, may also be retained and inputted into corresponding neural networks pre-trained to filter out noise in those components also by pattern recognition in the wavelet domain. In any case, an inverse discrete wavelet transform is performed on the combined output from all the neural networks to recover a clean signal back in the time domain.

Wavelet-bounded empirical mode decomposition for measured time series analysis

NASA Astrophysics Data System (ADS)

Moore, Keegan J.; Kurt, Mehmet; Eriten, Melih; McFarland, D. Michael; Bergman, Lawrence A.; Vakakis, Alexander F.

2018-01-01

Empirical mode decomposition (EMD) is a powerful technique for separating the transient responses of nonlinear and nonstationary systems into finite sets of nearly orthogonal components, called intrinsic mode functions (IMFs), which represent the dynamics on different characteristic time scales. However, a deficiency of EMD is the mixing of two or more components in a single IMF, which can drastically affect the physical meaning of the empirical decomposition results. In this paper, we present a new approached based on EMD, designated as wavelet-bounded empirical mode decomposition (WBEMD), which is a closed-loop, optimization-based solution to the problem of mode mixing. The optimization routine relies on maximizing the isolation of an IMF around a characteristic frequency. This isolation is measured by fitting a bounding function around the IMF in the frequency domain and computing the area under this function. It follows that a large (small) area corresponds to a poorly (well) separated IMF. An optimization routine is developed based on this result with the objective of minimizing the bounding-function area and with the masking signal parameters serving as free parameters, such that a well-separated IMF is extracted. As examples of application of WBEMD we apply the proposed method, first to a stationary, two-component signal, and then to the numerically simulated response of a cantilever beam with an essentially nonlinear end attachment. We find that WBEMD vastly improves upon EMD and that the extracted sets of IMFs provide insight into the underlying physics of the response of each system.

Simultaneous F 0-F 1 modifications of Arabic for the improvement of natural-sounding

NASA Astrophysics Data System (ADS)

Ykhlef, F.; Bensebti, M.

2013-03-01

Pitch (F 0) modification is one of the most important problems in the area of speech synthesis. Several techniques have been developed in the literature to achieve this goal. The main restrictions of these techniques are in the modification range and the synthesised speech quality, intelligibility and naturalness. The control of formants in a spoken language can significantly improve the naturalness of the synthesised speech. This improvement is mainly dependent on the control of the first formant (F 1). Inspired by this observation, this article proposes a new approach that modifies both F 0 and F 1 of Arabic voiced sounds in order to improve the naturalness of the pitch shifted speech. The developed strategy takes a parallel processing approach, in which the analysis segments are decomposed into sub-bands in the wavelet domain, modified in the desired sub-band by using a resampling technique and reconstructed without affecting the remained sub-bands. Pitch marking and voicing detection are performed in the frequency decomposition step based on the comparison of the multi-level approximation and detail signals. The performance of the proposed technique is evaluated by listening tests and compared to the pitch synchronous overlap and add (PSOLA) technique in the third approximation level. Experimental results have shown that the manipulation in the wavelet domain of F 0 in conjunction with F 1 guarantees natural-sounding of the synthesised speech compared to the classical pitch modification technique. This improvement was appropriate for high pitch modifications.

Parallel computing of a climate model on the dawn 1000 by domain decomposition method

NASA Astrophysics Data System (ADS)

Bi, Xunqiang

1997-12-01

In this paper the parallel computing of a grid-point nine-level atmospheric general circulation model on the Dawn 1000 is introduced. The model was developed by the Institute of Atmospheric Physics (IAP), Chinese Academy of Sciences (CAS). The Dawn 1000 is a MIMD massive parallel computer made by National Research Center for Intelligent Computer (NCIC), CAS. A two-dimensional domain decomposition method is adopted to perform the parallel computing. The potential ways to increase the speed-up ratio and exploit more resources of future massively parallel supercomputation are also discussed.

New evidence favoring multilevel decomposition and optimization

NASA Technical Reports Server (NTRS)

Padula, Sharon L.; Polignone, Debra A.

1990-01-01

The issue of the utility of multilevel decomposition and optimization remains controversial. To date, only the structural optimization community has actively developed and promoted multilevel optimization techniques. However, even this community acknowledges that multilevel optimization is ideally suited for a rather limited set of problems. It is warned that decomposition typically requires eliminating local variables by using global variables and that this in turn causes ill-conditioning of the multilevel optimization by adding equality constraints. The purpose is to suggest a new multilevel optimization technique. This technique uses behavior variables, in addition to design variables and constraints, to decompose the problem. The new technique removes the need for equality constraints, simplifies the decomposition of the design problem, simplifies the programming task, and improves the convergence speed of multilevel optimization compared to conventional optimization.

Extended FDD-WT method based on correcting the errors due to non-synchronous sensing of sensors

NASA Astrophysics Data System (ADS)

Tarinejad, Reza; Damadipour, Majid

2016-05-01

In this research, a combinational non-parametric method called frequency domain decomposition-wavelet transform (FDD-WT) that was recently presented by the authors, is extended for correction of the errors resulting from asynchronous sensing of sensors, in order to extend the application of the algorithm for different kinds of structures, especially for huge structures. Therefore, the analysis process is based on time-frequency domain decomposition and is performed with emphasis on correcting time delays between sensors. Time delay estimation (TDE) methods are investigated for their efficiency and accuracy for noisy environmental records and the Phase Transform - β (PHAT-β) technique was selected as an appropriate method to modify the operation of traditional FDD-WT in order to achieve the exact results. In this paper, a theoretical example (3DOF system) has been provided in order to indicate the non-synchronous sensing effects of the sensors on the modal parameters; moreover, the Pacoima dam subjected to 13 Jan 2001 earthquake excitation was selected as a case study. The modal parameters of the dam obtained from the extended FDD-WT method were compared with the output of the classical signal processing method, which is referred to as 4-Spectral method, as well as other literatures relating to the dynamic characteristics of Pacoima dam. The results comparison indicates that values are correct and reliable.

A Novel Multilevel-SVD Method to Improve Multistep Ahead Forecasting in Traffic Accidents Domain.

PubMed

Barba, Lida; Rodríguez, Nibaldo

2017-01-01

Here is proposed a novel method for decomposing a nonstationary time series in components of low and high frequency. The method is based on Multilevel Singular Value Decomposition (MSVD) of a Hankel matrix. The decomposition is used to improve the forecasting accuracy of Multiple Input Multiple Output (MIMO) linear and nonlinear models. Three time series coming from traffic accidents domain are used. They represent the number of persons with injuries in traffic accidents of Santiago, Chile. The data were continuously collected by the Chilean Police and were weekly sampled from 2000:1 to 2014:12. The performance of MSVD is compared with the decomposition in components of low and high frequency of a commonly accepted method based on Stationary Wavelet Transform (SWT). SWT in conjunction with the Autoregressive model (SWT + MIMO-AR) and SWT in conjunction with an Autoregressive Neural Network (SWT + MIMO-ANN) were evaluated. The empirical results have shown that the best accuracy was achieved by the forecasting model based on the proposed decomposition method MSVD, in comparison with the forecasting models based on SWT.

A Novel Multilevel-SVD Method to Improve Multistep Ahead Forecasting in Traffic Accidents Domain

PubMed Central

Rodríguez, Nibaldo

2017-01-01

Here is proposed a novel method for decomposing a nonstationary time series in components of low and high frequency. The method is based on Multilevel Singular Value Decomposition (MSVD) of a Hankel matrix. The decomposition is used to improve the forecasting accuracy of Multiple Input Multiple Output (MIMO) linear and nonlinear models. Three time series coming from traffic accidents domain are used. They represent the number of persons with injuries in traffic accidents of Santiago, Chile. The data were continuously collected by the Chilean Police and were weekly sampled from 2000:1 to 2014:12. The performance of MSVD is compared with the decomposition in components of low and high frequency of a commonly accepted method based on Stationary Wavelet Transform (SWT). SWT in conjunction with the Autoregressive model (SWT + MIMO-AR) and SWT in conjunction with an Autoregressive Neural Network (SWT + MIMO-ANN) were evaluated. The empirical results have shown that the best accuracy was achieved by the forecasting model based on the proposed decomposition method MSVD, in comparison with the forecasting models based on SWT. PMID:28261267

An exploration of function analysis and function allocation in the commercial flight domain

NASA Technical Reports Server (NTRS)

Mcguire, James C.; Zich, John A.; Goins, Richard T.; Erickson, Jeffery B.; Dwyer, John P.; Cody, William J.; Rouse, William B.

1991-01-01

The applicability is explored of functional analysis methods to support cockpit design. Specifically, alternative techniques are studied for ensuring an effective division of responsibility between the flight crew and automation. A functional decomposition is performed of the commercial flight domain to provide the information necessary to support allocation decisions and demonstrate methodology for allocating functions to flight crew or to automation. The function analysis employed 'bottom up' and 'top down' analyses and demonstrated the comparability of identified functions, using the 'lift off' segment of the 'take off' phase as a test case. The normal flight mission and selected contingencies were addressed. Two alternative methods for using the functional description in the allocation of functions between man and machine were investigated. The two methods were compared in order to ascertain their relative strengths and weaknesses. Finally, conclusions were drawn regarding the practical utility of function analysis methods.

Hydrogen assisted growth of high quality epitaxial graphene on the C-face of 4H-SiC

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

Cai, Tuocheng; Jia, Zhenzhao; Yan, Baoming

2015-01-05

We demonstrate hydrogen assisted growth of high quality epitaxial graphene on the C-face of 4H-SiC. Compared with the conventional thermal decomposition technique, the size of the growth domain by this method is substantially increased and the thickness variation is reduced. Based on the morphology of epitaxial graphene, the role of hydrogen is revealed. It is found that hydrogen acts as a carbon etchant. It suppresses the defect formation and nucleation of graphene. It also improves the kinetics of carbon atoms via hydrocarbon species. These effects lead to increase of the domain size and the structure quality. The consequent capping effectmore » results in smooth surface morphology and suppression of multilayer growth. Our method provides a viable route to fine tune the growth kinetics of epitaxial graphene on SiC.« less

Using dynamic mode decomposition for real-time background/foreground separation in video

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

Kutz, Jose Nathan; Grosek, Jacob; Brunton, Steven

The technique of dynamic mode decomposition (DMD) is disclosed herein for the purpose of robustly separating video frames into background (low-rank) and foreground (sparse) components in real-time. Foreground/background separation is achieved at the computational cost of just one singular value decomposition (SVD) and one linear equation solve, thus producing results orders of magnitude faster than robust principal component analysis (RPCA). Additional techniques, including techniques for analyzing the video for multi-resolution time-scale components, and techniques for reusing computations to allow processing of streaming video in real time, are also described herein.

A parallel domain decomposition-based implicit method for the Cahn–Hilliard–Cook phase-field equation in 3D

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

Zheng, Xiang; Yang, Chao; State Key Laboratory of Computer Science, Chinese Academy of Sciences, Beijing 100190

2015-03-15

We present a numerical algorithm for simulating the spinodal decomposition described by the three dimensional Cahn–Hilliard–Cook (CHC) equation, which is a fourth-order stochastic partial differential equation with a noise term. The equation is discretized in space and time based on a fully implicit, cell-centered finite difference scheme, with an adaptive time-stepping strategy designed to accelerate the progress to equilibrium. At each time step, a parallel Newton–Krylov–Schwarz algorithm is used to solve the nonlinear system. We discuss various numerical and computational challenges associated with the method. The numerical scheme is validated by a comparison with an explicit scheme of high accuracymore » (and unreasonably high cost). We present steady state solutions of the CHC equation in two and three dimensions. The effect of the thermal fluctuation on the spinodal decomposition process is studied. We show that the existence of the thermal fluctuation accelerates the spinodal decomposition process and that the final steady morphology is sensitive to the stochastic noise. We also show the evolution of the energies and statistical moments. In terms of the parallel performance, it is found that the implicit domain decomposition approach scales well on supercomputers with a large number of processors.« less

Reduced-order model for underwater target identification using proper orthogonal decomposition

NASA Astrophysics Data System (ADS)

Ramesh, Sai Sudha; Lim, Kian Meng

2017-03-01

Research on underwater acoustics has seen major development over the past decade due to its widespread applications in domains such as underwater communication/navigation (SONAR), seismic exploration and oceanography. In particular, acoustic signatures from partially or fully buried targets can be used in the identification of buried mines for mine counter measures (MCM). Although there exist several techniques to identify target properties based on SONAR images and acoustic signatures, these methods first employ a feature extraction method to represent the dominant characteristics of a data set, followed by the use of an appropriate classifier based on neural networks or the relevance vector machine. The aim of the present study is to demonstrate the applications of proper orthogonal decomposition (POD) technique in capturing dominant features of a set of scattered pressure signals, and subsequent use of the POD modes and coefficients in the identification of partially buried underwater target parameters such as its location, size and material density. Several numerical examples are presented to demonstrate the performance of the system identification method based on POD. Although the present study is based on 2D acoustic model, the method can be easily extended to 3D models and thereby enables cost-effective representations of large-scale data.

Matrix-Inversion-Free Compressed Sensing With Variable Orthogonal Multi-Matching Pursuit Based on Prior Information for ECG Signals.

PubMed

Cheng, Yih-Chun; Tsai, Pei-Yun; Huang, Ming-Hao

2016-05-19

Low-complexity compressed sensing (CS) techniques for monitoring electrocardiogram (ECG) signals in wireless body sensor network (WBSN) are presented. The prior probability of ECG sparsity in the wavelet domain is first exploited. Then, variable orthogonal multi-matching pursuit (vOMMP) algorithm that consists of two phases is proposed. In the first phase, orthogonal matching pursuit (OMP) algorithm is adopted to effectively augment the support set with reliable indices and in the second phase, the orthogonal multi-matching pursuit (OMMP) is employed to rescue the missing indices. The reconstruction performance is thus enhanced with the prior information and the vOMMP algorithm. Furthermore, the computation-intensive pseudo-inverse operation is simplified by the matrix-inversion-free (MIF) technique based on QR decomposition. The vOMMP-MIF CS decoder is then implemented in 90 nm CMOS technology. The QR decomposition is accomplished by two systolic arrays working in parallel. The implementation supports three settings for obtaining 40, 44, and 48 coefficients in the sparse vector. From the measurement result, the power consumption is 11.7 mW at 0.9 V and 12 MHz. Compared to prior chip implementations, our design shows good hardware efficiency and is suitable for low-energy applications.

Origin of the Chemical and Kinetic Stability of Graphene Oxide

PubMed Central

Zhou, Si; Bongiorno, Angelo

2013-01-01

At moderate temperatures (≤ 70°C), thermal reduction of graphene oxide is inefficient and after its synthesis the material enters in a metastable state. Here, first-principles and statistical calculations are used to investigate both the low-temperature processes leading to decomposition of graphene oxide and the role of ageing on the structure and stability of this material. Our study shows that the key factor underlying the stability of graphene oxide is the tendency of the oxygen functionalities to agglomerate and form highly oxidized domains surrounded by areas of pristine graphene. Within the agglomerates of functional groups, the primary decomposition reactions are hindered by both geometrical and energetic factors. The number of reacting sites is reduced by the occurrence of local order in the oxidized domains, and due to the close packing of the oxygen functionalities, the decomposition reactions become – on average – endothermic by more than 0.6 eV. PMID:23963517

Origin of the chemical and kinetic stability of graphene oxide.

PubMed

Zhou, Si; Bongiorno, Angelo

2013-01-01

At moderate temperatures (≤ 70°C), thermal reduction of graphene oxide is inefficient and after its synthesis the material enters in a metastable state. Here, first-principles and statistical calculations are used to investigate both the low-temperature processes leading to decomposition of graphene oxide and the role of ageing on the structure and stability of this material. Our study shows that the key factor underlying the stability of graphene oxide is the tendency of the oxygen functionalities to agglomerate and form highly oxidized domains surrounded by areas of pristine graphene. Within the agglomerates of functional groups, the primary decomposition reactions are hindered by both geometrical and energetic factors. The number of reacting sites is reduced by the occurrence of local order in the oxidized domains, and due to the close packing of the oxygen functionalities, the decomposition reactions become - on average - endothermic by more than 0.6 eV.

Survey of the status of finite element methods for partial differential equations

NASA Technical Reports Server (NTRS)

Temam, Roger

1986-01-01

The finite element methods (FEM) have proved to be a powerful technique for the solution of boundary value problems associated with partial differential equations of either elliptic, parabolic, or hyperbolic type. They also have a good potential for utilization on parallel computers particularly in relation to the concept of domain decomposition. This report is intended as an introduction to the FEM for the nonspecialist. It contains a survey which is totally nonexhaustive, and it also contains as an illustration, a report on some new results concerning two specific applications, namely a free boundary fluid-structure interaction problem and the Euler equations for inviscid flows.

Removing volatile organic compounds in cooking fume by nano-sized TiO2 photocatalytic reaction combined with ozone oxidation technique.

PubMed

Li, Yu-Hua; Cheng, Su-Wen; Yuan, Chung-Shin; Lai, Tzu-Fan; Hung, Chung-Hsuang

2018-06-05

Chinese cooking fume is one of the sources of volatile organic compounds (VOCs) in the air. An innovative control technology combining photocatalytic degradation and ozone oxidation (UV/TiO 2 +O 3 ) was developed to decompose VOCs in the cooking fume. Fiberglass filter (FGF) coated with TiO 2 was prepared by an impregnation procedure. A continuous-flow reaction system was self-designed by combining photocatalysis with advanced ozone oxidation technique. By passing the simulated cooking fume through the FGF, the VOC decomposition efficiency in the cooking fume could be increased by about 10%. The decomposition efficiency of VOCs in the cooking fume increased and then decreased with the inlet VOC concentration. A maximum VOC decomposition efficiency of 64% was obtained at 100 ppm. Similar trend was observed for reaction temperature with the VOC decomposition efficiencies ranging from 64 to 68%. Moreover, inlet ozone concentration had a positive effect on the decomposition of VOCs in the cooking fume for inlet ozone≤1000 ppm and leveled off for inlet ozone>1000 ppm. 34% of VOC decomposition efficiency was achieved solely by ozone oxidation with or without near-UV irradiation. A maximum of 75% and 94% VOC decomposition efficiency could be achieved by O 3 +UV/TiO 2 and UV/TiO 2 +O 3 techniques, respectively. The maximum decomposition efficiencies of VOCs decreased to 79% for using UV/TiO 2 +O 3 technique with adding water in the oil fume. Comparing the chromatographical species of VOCs in the oil fume before and after the decomposition of VOCs by using UV/TiO 2 +O 3 technique, we found that both TVOC and VOC species in the oil fume were effectively decomposed. Copyright © 2018 Elsevier Ltd. All rights reserved.

Characterization of cancer and normal tissue fluorescence through wavelet transform and singular value decomposition

NASA Astrophysics Data System (ADS)

Gharekhan, Anita H.; Biswal, Nrusingh C.; Gupta, Sharad; Pradhan, Asima; Sureshkumar, M. B.; Panigrahi, Prasanta K.

2008-02-01

The statistical and characteristic features of the polarized fluorescence spectra from cancer, normal and benign human breast tissues are studied through wavelet transform and singular value decomposition. The discrete wavelets enabled one to isolate high and low frequency spectral fluctuations, which revealed substantial randomization in the cancerous tissues, not present in the normal cases. In particular, the fluctuations fitted well with a Gaussian distribution for the cancerous tissues in the perpendicular component. One finds non-Gaussian behavior for normal and benign tissues' spectral variations. The study of the difference of intensities in parallel and perpendicular channels, which is free from the diffusive component, revealed weak fluorescence activity in the 630nm domain, for the cancerous tissues. This may be ascribable to porphyrin emission. The role of both scatterers and fluorophores in the observed minor intensity peak for the cancer case is experimentally confirmed through tissue-phantom experiments. Continuous Morlet wavelet also highlighted this domain for the cancerous tissue fluorescence spectra. Correlation in the spectral fluctuation is further studied in different tissue types through singular value decomposition. Apart from identifying different domains of spectral activity for diseased and non-diseased tissues, we found random matrix support for the spectral fluctuations. The small eigenvalues of the perpendicular polarized fluorescence spectra of cancerous tissues fitted remarkably well with random matrix prediction for Gaussian random variables, confirming our observations about spectral fluctuations in the wavelet domain.

A non-invasive implementation of a mixed domain decomposition method for frictional contact problems

NASA Astrophysics Data System (ADS)

Oumaziz, Paul; Gosselet, Pierre; Boucard, Pierre-Alain; Guinard, Stéphane

2017-11-01

A non-invasive implementation of the Latin domain decomposition method for frictional contact problems is described. The formulation implies to deal with mixed (Robin) conditions on the faces of the subdomains, which is not a classical feature of commercial software. Therefore we propose a new implementation of the linear stage of the Latin method with a non-local search direction built as the stiffness of a layer of elements on the interfaces. This choice enables us to implement the method within the open source software Code_Aster, and to derive 2D and 3D examples with similar performance as the standard Latin method.

Domain Decomposition Algorithms for First-Order System Least Squares Methods

NASA Technical Reports Server (NTRS)

Pavarino, Luca F.

1996-01-01

Least squares methods based on first-order systems have been recently proposed and analyzed for second-order elliptic equations and systems. They produce symmetric and positive definite discrete systems by using standard finite element spaces, which are not required to satisfy the inf-sup condition. In this paper, several domain decomposition algorithms for these first-order least squares methods are studied. Some representative overlapping and substructuring algorithms are considered in their additive and multiplicative variants. The theoretical and numerical results obtained show that the classical convergence bounds (on the iteration operator) for standard Galerkin discretizations are also valid for least squares methods.

Through-wall image enhancement using fuzzy and QR decomposition.

PubMed

Riaz, Muhammad Mohsin; Ghafoor, Abdul

2014-01-01

QR decomposition and fuzzy logic based scheme is proposed for through-wall image enhancement. QR decomposition is less complex compared to singular value decomposition. Fuzzy inference engine assigns weights to different overlapping subspaces. Quantitative measures and visual inspection are used to analyze existing and proposed techniques.

Convergence issues in domain decomposition parallel computation of hovering rotor

NASA Astrophysics Data System (ADS)

Xiao, Zhongyun; Liu, Gang; Mou, Bin; Jiang, Xiong

2018-05-01

Implicit LU-SGS time integration algorithm has been widely used in parallel computation in spite of its lack of information from adjacent domains. When applied to parallel computation of hovering rotor flows in a rotating frame, it brings about convergence issues. To remedy the problem, three LU factorization-based implicit schemes (consisting of LU-SGS, DP-LUR and HLU-SGS) are investigated comparatively. A test case of pure grid rotation is designed to verify these algorithms, which show that LU-SGS algorithm introduces errors on boundary cells. When partition boundaries are circumferential, errors arise in proportion to grid speed, accumulating along with the rotation, and leading to computational failure in the end. Meanwhile, DP-LUR and HLU-SGS methods show good convergence owing to boundary treatment which are desirable in domain decomposition parallel computations.

An MPI + $X$ implementation of contact global search using Kokkos

DOE PAGES

Hansen, Glen A.; Xavier, Patrick G.; Mish, Sam P.; ...

2015-10-05

This paper describes an approach that seeks to parallelize the spatial search associated with computational contact mechanics. In contact mechanics, the purpose of the spatial search is to find “nearest neighbors,” which is the prelude to an imprinting search that resolves the interactions between the external surfaces of contacting bodies. In particular, we are interested in the contact global search portion of the spatial search associated with this operation on domain-decomposition-based meshes. Specifically, we describe an implementation that combines standard domain-decomposition-based MPI-parallel spatial search with thread-level parallelism (MPI-X) available on advanced computer architectures (those with GPU coprocessors). Our goal ismore » to demonstrate the efficacy of the MPI-X paradigm in the overall contact search. Standard MPI-parallel implementations typically use a domain decomposition of the external surfaces of bodies within the domain in an attempt to efficiently distribute computational work. This decomposition may or may not be the same as the volume decomposition associated with the host physics. The parallel contact global search phase is then employed to find and distribute surface entities (nodes and faces) that are needed to compute contact constraints between entities owned by different MPI ranks without further inter-rank communication. Key steps of the contact global search include computing bounding boxes, building surface entity (node and face) search trees and finding and distributing entities required to complete on-rank (local) spatial searches. To enable source-code portability and performance across a variety of different computer architectures, we implemented the algorithm using the Kokkos hardware abstraction library. While we targeted development towards machines with a GPU accelerator per MPI rank, we also report performance results for OpenMP with a conventional multi-core compute node per rank. Results here demonstrate a 47 % decrease in the time spent within the global search algorithm, comparing the reference ACME algorithm with the GPU implementation, on an 18M face problem using four MPI ranks. As a result, while further work remains to maximize performance on the GPU, this result illustrates the potential of the proposed implementation.« less

A knowledge-based tool for multilevel decomposition of a complex design problem

NASA Technical Reports Server (NTRS)

Rogers, James L.

1989-01-01

Although much work has been done in applying artificial intelligence (AI) tools and techniques to problems in different engineering disciplines, only recently has the application of these tools begun to spread to the decomposition of complex design problems. A new tool based on AI techniques has been developed to implement a decomposition scheme suitable for multilevel optimization and display of data in an N x N matrix format.

A Joint Time-Frequency and Matrix Decomposition Feature Extraction Methodology for Pathological Voice Classification

NASA Astrophysics Data System (ADS)

Ghoraani, Behnaz; Krishnan, Sridhar

2009-12-01

The number of people affected by speech problems is increasing as the modern world places increasing demands on the human voice via mobile telephones, voice recognition software, and interpersonal verbal communications. In this paper, we propose a novel methodology for automatic pattern classification of pathological voices. The main contribution of this paper is extraction of meaningful and unique features using Adaptive time-frequency distribution (TFD) and nonnegative matrix factorization (NMF). We construct Adaptive TFD as an effective signal analysis domain to dynamically track the nonstationarity in the speech and utilize NMF as a matrix decomposition (MD) technique to quantify the constructed TFD. The proposed method extracts meaningful and unique features from the joint TFD of the speech, and automatically identifies and measures the abnormality of the signal. Depending on the abnormality measure of each signal, we classify the signal into normal or pathological. The proposed method is applied on the Massachusetts Eye and Ear Infirmary (MEEI) voice disorders database which consists of 161 pathological and 51 normal speakers, and an overall classification accuracy of 98.6% was achieved.

The implementation of an aeronautical CFD flow code onto distributed memory parallel systems

NASA Astrophysics Data System (ADS)

Ierotheou, C. S.; Forsey, C. R.; Leatham, M.

2000-04-01

The parallelization of an industrially important in-house computational fluid dynamics (CFD) code for calculating the airflow over complex aircraft configurations using the Euler or Navier-Stokes equations is presented. The code discussed is the flow solver module of the SAUNA CFD suite. This suite uses a novel grid system that may include block-structured hexahedral or pyramidal grids, unstructured tetrahedral grids or a hybrid combination of both. To assist in the rapid convergence to a solution, a number of convergence acceleration techniques are employed including implicit residual smoothing and a multigrid full approximation storage scheme (FAS). Key features of the parallelization approach are the use of domain decomposition and encapsulated message passing to enable the execution in parallel using a single programme multiple data (SPMD) paradigm. In the case where a hybrid grid is used, a unified grid partitioning scheme is employed to define the decomposition of the mesh. The parallel code has been tested using both structured and hybrid grids on a number of different distributed memory parallel systems and is now routinely used to perform industrial scale aeronautical simulations. Copyright

Full waveform time domain solutions for source and induced magnetotelluric and controlled-source electromagnetic fields using quasi-equivalent time domain decomposition and GPU parallelization

NASA Astrophysics Data System (ADS)

Imamura, N.; Schultz, A.

2015-12-01

Recently, a full waveform time domain solution has been developed for the magnetotelluric (MT) and controlled-source electromagnetic (CSEM) methods. The ultimate goal of this approach is to obtain a computationally tractable direct waveform joint inversion for source fields and earth conductivity structure in three and four dimensions. This is desirable on several grounds, including the improved spatial resolving power expected from use of a multitude of source illuminations of non-zero wavenumber, the ability to operate in areas of high levels of source signal spatial complexity and non-stationarity, etc. This goal would not be obtainable if one were to adopt the finite difference time-domain (FDTD) approach for the forward problem. This is particularly true for the case of MT surveys, since an enormous number of degrees of freedom are required to represent the observed MT waveforms across the large frequency bandwidth. It means that for FDTD simulation, the smallest time steps should be finer than that required to represent the highest frequency, while the number of time steps should also cover the lowest frequency. This leads to a linear system that is computationally burdensome to solve. We have implemented our code that addresses this situation through the use of a fictitious wave domain method and GPUs to speed up the computation time. We also substantially reduce the size of the linear systems by applying concepts from successive cascade decimation, through quasi-equivalent time domain decomposition. By combining these refinements, we have made good progress toward implementing the core of a full waveform joint source field/earth conductivity inverse modeling method. From results, we found the use of previous generation of CPU/GPU speeds computations by an order of magnitude over a parallel CPU only approach. In part, this arises from the use of the quasi-equivalent time domain decomposition, which shrinks the size of the linear system dramatically.

Efficient calculation of full waveform time domain inversion for electromagnetic problem using fictitious wave domain method and cascade decimation decomposition

NASA Astrophysics Data System (ADS)

Imamura, N.; Schultz, A.

2016-12-01

Recently, a full waveform time domain inverse solution has been developed for the magnetotelluric (MT) and controlled-source electromagnetic (CSEM) methods. The ultimate goal of this approach is to obtain a computationally tractable direct waveform joint inversion to solve simultaneously for source fields and earth conductivity structure in three and four dimensions. This is desirable on several grounds, including the improved spatial resolving power expected from use of a multitude of source illuminations, the ability to operate in areas of high levels of source signal spatial complexity, and non-stationarity. This goal would not be obtainable if one were to adopt the pure time domain solution for the inverse problem. This is particularly true for the case of MT surveys, since an enormous number of degrees of freedom are required to represent the observed MT waveforms across a large frequency bandwidth. This means that for the forward simulation, the smallest time steps should be finer than that required to represent the highest frequency, while the number of time steps should also cover the lowest frequency. This leads to a sensitivity matrix that is computationally burdensome to solve a model update. We have implemented a code that addresses this situation through the use of cascade decimation decomposition to reduce the size of the sensitivity matrix substantially, through quasi-equivalent time domain decomposition. We also use a fictitious wave domain method to speed up computation time of the forward simulation in the time domain. By combining these refinements, we have developed a full waveform joint source field/earth conductivity inverse modeling method. We found that cascade decimation speeds computations of the sensitivity matrices dramatically, keeping the solution close to that of the undecimated case. For example, for a model discretized into 2.6x105 cells, we obtain model updates in less than 1 hour on a 4U rack-mounted workgroup Linux server, which is a practical computational time for the inverse problem.

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

Niu, T; Dong, X; Petrongolo, M

Purpose: Dual energy CT (DECT) imaging plays an important role in advanced imaging applications due to its material decomposition capability. Direct decomposition via matrix inversion suffers from significant degradation of image signal-to-noise ratios, which reduces clinical value. Existing de-noising algorithms achieve suboptimal performance since they suppress image noise either before or after the decomposition and do not fully explore the noise statistical properties of the decomposition process. We propose an iterative image-domain decomposition method for noise suppression in DECT, using the full variance-covariance matrix of the decomposed images. Methods: The proposed algorithm is formulated in the form of least-square estimationmore » with smoothness regularization. It includes the inverse of the estimated variance-covariance matrix of the decomposed images as the penalty weight in the least-square term. Performance is evaluated using an evaluation phantom (Catphan 600) and an anthropomorphic head phantom. Results are compared to those generated using direct matrix inversion with no noise suppression, a de-noising method applied on the decomposed images, and an existing algorithm with similar formulation but with an edge-preserving regularization term. Results: On the Catphan phantom, our method retains the same spatial resolution as the CT images before decomposition while reducing the noise standard deviation of decomposed images by over 98%. The other methods either degrade spatial resolution or achieve less low-contrast detectability. Also, our method yields lower electron density measurement error than direct matrix inversion and reduces error variation by over 97%. On the head phantom, it reduces the noise standard deviation of decomposed images by over 97% without blurring the sinus structures. Conclusion: We propose an iterative image-domain decomposition method for DECT. The method combines noise suppression and material decomposition into an iterative process and achieves both goals simultaneously. The proposed algorithm shows superior performance on noise suppression with high image spatial resolution and low-contrast detectability. This work is supported by a Varian MRA grant.« less

Pseudospectral reverse time migration based on wavefield decomposition

NASA Astrophysics Data System (ADS)

Du, Zengli; Liu, Jianjun; Xu, Feng; Li, Yongzhang

2017-05-01

The accuracy of seismic numerical simulations and the effectiveness of imaging conditions are important in reverse time migration studies. Using the pseudospectral method, the precision of the calculated spatial derivative of the seismic wavefield can be improved, increasing the vertical resolution of images. Low-frequency background noise, generated by the zero-lag cross-correlation of mismatched forward-propagated and backward-propagated wavefields at the impedance interfaces, can be eliminated effectively by using the imaging condition based on the wavefield decomposition technique. The computation complexity can be reduced when imaging is performed in the frequency domain. Since the Fourier transformation in the z-axis may be derived directly as one of the intermediate results of the spatial derivative calculation, the computation load of the wavefield decomposition can be reduced, improving the computation efficiency of imaging. Comparison of the results for a pulse response in a constant-velocity medium indicates that, compared with the finite difference method, the peak frequency of the Ricker wavelet can be increased by 10-15 Hz for avoiding spatial numerical dispersion, when the second-order spatial derivative of the seismic wavefield is obtained using the pseudospectral method. The results for the SEG/EAGE and Sigsbee2b models show that the signal-to-noise ratio of the profile and the imaging quality of the boundaries of the salt dome migrated using the pseudospectral method are better than those obtained using the finite difference method.

Constraint-based integration of planning and scheduling for space-based observatory management

NASA Technical Reports Server (NTRS)

Muscettola, Nicola; Smith, Steven F.

1994-01-01

Progress toward the development of effective, practical solutions to space-based observatory scheduling problems within the HSTS scheduling framework is reported. HSTS was developed and originally applied in the context of the Hubble Space Telescope (HST) short-term observation scheduling problem. The work was motivated by the limitations of the current solution and, more generally, by the insufficiency of classical planning and scheduling approaches in this problem context. HSTS has subsequently been used to develop improved heuristic solution techniques in related scheduling domains and is currently being applied to develop a scheduling tool for the upcoming Submillimeter Wave Astronomy Satellite (SWAS) mission. The salient architectural characteristics of HSTS and their relationship to previous scheduling and AI planning research are summarized. Then, some key problem decomposition techniques underlying the integrated planning and scheduling approach to the HST problem are described; research results indicate that these techniques provide leverage in solving space-based observatory scheduling problems. Finally, more recently developed constraint-posting scheduling procedures and the current SWAS application focus are summarized.

Endothermic decompositions of inorganic monocrystalline thin plates. II. Displacement rate modulation of the reaction front

NASA Astrophysics Data System (ADS)

Bertrand, G.; Comperat, M.; Lallemant, M.

1980-09-01

Copper sulfate pentahydrate dehydration into trihydrate was investigated using monocrystalline platelets with (110) crystallographic orientation. Temperature and pressure conditions were selected so as to obtain elliptical trihydrate domains. The study deals with the evolution, vs time, of elliptical domain dimensions and the evolution, vs water vapor pressure, of the {D}/{d} ratio of ellipse axes and on the other hand of the interface displacement rate along a given direction. The phenomena observed are not basically different from those yielded by the overall kinetic study of the solid sample. Their magnitude, however, is modulated depending on displacement direction. The results are analyzed within the scope of our study of endothermic decomposition of solids.

Domain decomposition methods in computational fluid dynamics

NASA Technical Reports Server (NTRS)

Gropp, William D.; Keyes, David E.

1991-01-01

The divide-and-conquer paradigm of iterative domain decomposition, or substructuring, has become a practical tool in computational fluid dynamic applications because of its flexibility in accommodating adaptive refinement through locally uniform (or quasi-uniform) grids, its ability to exploit multiple discretizations of the operator equations, and the modular pathway it provides towards parallelism. These features are illustrated on the classic model problem of flow over a backstep using Newton's method as the nonlinear iteration. Multiple discretizations (second-order in the operator and first-order in the preconditioner) and locally uniform mesh refinement pay dividends separately, and they can be combined synergistically. Sample performance results are included from an Intel iPSC/860 hypercube implementation.

Domain decomposition methods for nonconforming finite element spaces of Lagrange-type

NASA Technical Reports Server (NTRS)

Cowsar, Lawrence C.

1993-01-01

In this article, we consider the application of three popular domain decomposition methods to Lagrange-type nonconforming finite element discretizations of scalar, self-adjoint, second order elliptic equations. The additive Schwarz method of Dryja and Widlund, the vertex space method of Smith, and the balancing method of Mandel applied to nonconforming elements are shown to converge at a rate no worse than their applications to the standard conforming piecewise linear Galerkin discretization. Essentially, the theory for the nonconforming elements is inherited from the existing theory for the conforming elements with only modest modification by constructing an isomorphism between the nonconforming finite element space and a space of continuous piecewise linear functions.

Galerkin-collocation domain decomposition method for arbitrary binary black holes

NASA Astrophysics Data System (ADS)

Barreto, W.; Clemente, P. C. M.; de Oliveira, H. P.; Rodriguez-Mueller, B.

2018-05-01

We present a new computational framework for the Galerkin-collocation method for double domain in the context of ADM 3 +1 approach in numerical relativity. This work enables us to perform high resolution calculations for initial sets of two arbitrary black holes. We use the Bowen-York method for binary systems and the puncture method to solve the Hamiltonian constraint. The nonlinear numerical code solves the set of equations for the spectral modes using the standard Newton-Raphson method, LU decomposition and Gaussian quadratures. We show convergence of our code for the conformal factor and the ADM mass. Thus, we display features of the conformal factor for different masses, spins and linear momenta.

Segmented Domain Decomposition Multigrid For 3-D Turbomachinery Flows

NASA Technical Reports Server (NTRS)

Celestina, M. L.; Adamczyk, J. J.; Rubin, S. G.

2001-01-01

A Segmented Domain Decomposition Multigrid (SDDMG) procedure was developed for three-dimensional viscous flow problems as they apply to turbomachinery flows. The procedure divides the computational domain into a coarse mesh comprised of uniformly spaced cells. To resolve smaller length scales such as the viscous layer near a surface, segments of the coarse mesh are subdivided into a finer mesh. This is repeated until adequate resolution of the smallest relevant length scale is obtained. Multigrid is used to communicate information between the different grid levels. To test the procedure, simulation results will be presented for a compressor and turbine cascade. These simulations are intended to show the ability of the present method to generate grid independent solutions. Comparisons with data will also be presented. These comparisons will further demonstrate the usefulness of the present work for they allow an estimate of the accuracy of the flow modeling equations independent of error attributed to numerical discretization.

Nonconforming mortar element methods: Application to spectral discretizations

NASA Technical Reports Server (NTRS)

Maday, Yvon; Mavriplis, Cathy; Patera, Anthony

1988-01-01

Spectral element methods are p-type weighted residual techniques for partial differential equations that combine the generality of finite element methods with the accuracy of spectral methods. Presented here is a new nonconforming discretization which greatly improves the flexibility of the spectral element approach as regards automatic mesh generation and non-propagating local mesh refinement. The method is based on the introduction of an auxiliary mortar trace space, and constitutes a new approach to discretization-driven domain decomposition characterized by a clean decoupling of the local, structure-preserving residual evaluations and the transmission of boundary and continuity conditions. The flexibility of the mortar method is illustrated by several nonconforming adaptive Navier-Stokes calculations in complex geometry.

GROMACS: High performance molecular simulations through multi-level parallelism from laptops to supercomputers

DOE PAGES

Abraham, Mark James; Murtola, Teemu; Schulz, Roland; ...

2015-07-15

GROMACS is one of the most widely used open-source and free software codes in chemistry, used primarily for dynamical simulations of biomolecules. It provides a rich set of calculation types, preparation and analysis tools. Several advanced techniques for free-energy calculations are supported. In version 5, it reaches new performance heights, through several new and enhanced parallelization algorithms. This work on every level; SIMD registers inside cores, multithreading, heterogeneous CPU–GPU acceleration, state-of-the-art 3D domain decomposition, and ensemble-level parallelization through built-in replica exchange and the separate Copernicus framework. Finally, the latest best-in-class compressed trajectory storage format is supported.

GROMACS: High performance molecular simulations through multi-level parallelism from laptops to supercomputers

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

Abraham, Mark James; Murtola, Teemu; Schulz, Roland

GROMACS is one of the most widely used open-source and free software codes in chemistry, used primarily for dynamical simulations of biomolecules. It provides a rich set of calculation types, preparation and analysis tools. Several advanced techniques for free-energy calculations are supported. In version 5, it reaches new performance heights, through several new and enhanced parallelization algorithms. This work on every level; SIMD registers inside cores, multithreading, heterogeneous CPU–GPU acceleration, state-of-the-art 3D domain decomposition, and ensemble-level parallelization through built-in replica exchange and the separate Copernicus framework. Finally, the latest best-in-class compressed trajectory storage format is supported.

Breast density evaluation using spectral mammography, radiologist reader assessment and segmentation techniques: a retrospective study based on left and right breast comparison

PubMed Central

Molloi, Sabee; Ding, Huanjun; Feig, Stephen

2015-01-01

Purpose The purpose of this study was to compare the precision of mammographic breast density measurement using radiologist reader assessment, histogram threshold segmentation, fuzzy C-mean segmentation and spectral material decomposition. Materials and Methods Spectral mammography images from a total of 92 consecutive asymptomatic women (50–69 years old) who presented for annual screening mammography were retrospectively analyzed for this study. Breast density was estimated using 10 radiologist reader assessment, standard histogram thresholding, fuzzy C-mean algorithm and spectral material decomposition. The breast density correlation between left and right breasts was used to assess the precision of these techniques to measure breast composition relative to dual-energy material decomposition. Results In comparison to the other techniques, the results of breast density measurements using dual-energy material decomposition showed the highest correlation. The relative standard error of estimate for breast density measurements from left and right breasts using radiologist reader assessment, standard histogram thresholding, fuzzy C-mean algorithm and dual-energy material decomposition was calculated to be 1.95, 2.87, 2.07 and 1.00, respectively. Conclusion The results indicate that the precision of dual-energy material decomposition was approximately factor of two higher than the other techniques with regard to better correlation of breast density measurements from right and left breasts. PMID:26031229

Steganography based on pixel intensity value decomposition

NASA Astrophysics Data System (ADS)

Abdulla, Alan Anwar; Sellahewa, Harin; Jassim, Sabah A.

2014-05-01

This paper focuses on steganography based on pixel intensity value decomposition. A number of existing schemes such as binary, Fibonacci, Prime, Natural, Lucas, and Catalan-Fibonacci (CF) are evaluated in terms of payload capacity and stego quality. A new technique based on a specific representation is proposed to decompose pixel intensity values into 16 (virtual) bit-planes suitable for embedding purposes. The proposed decomposition has a desirable property whereby the sum of all bit-planes does not exceed the maximum pixel intensity value, i.e. 255. Experimental results demonstrate that the proposed technique offers an effective compromise between payload capacity and stego quality of existing embedding techniques based on pixel intensity value decomposition. Its capacity is equal to that of binary and Lucas, while it offers a higher capacity than Fibonacci, Prime, Natural, and CF when the secret bits are embedded in 1st Least Significant Bit (LSB). When the secret bits are embedded in higher bit-planes, i.e., 2nd LSB to 8th Most Significant Bit (MSB), the proposed scheme has more capacity than Natural numbers based embedding. However, from the 6th bit-plane onwards, the proposed scheme offers better stego quality. In general, the proposed decomposition scheme has less effect in terms of quality on pixel value when compared to most existing pixel intensity value decomposition techniques when embedding messages in higher bit-planes.

A new time-frequency method for identification and classification of ball bearing faults

NASA Astrophysics Data System (ADS)

Attoui, Issam; Fergani, Nadir; Boutasseta, Nadir; Oudjani, Brahim; Deliou, Adel

2017-06-01

In order to fault diagnosis of ball bearing that is one of the most critical components of rotating machinery, this paper presents a time-frequency procedure incorporating a new feature extraction step that combines the classical wavelet packet decomposition energy distribution technique and a new feature extraction technique based on the selection of the most impulsive frequency bands. In the proposed procedure, firstly, as a pre-processing step, the most impulsive frequency bands are selected at different bearing conditions using a combination between Fast-Fourier-Transform FFT and Short-Frequency Energy SFE algorithms. Secondly, once the most impulsive frequency bands are selected, the measured machinery vibration signals are decomposed into different frequency sub-bands by using discrete Wavelet Packet Decomposition WPD technique to maximize the detection of their frequency contents and subsequently the most useful sub-bands are represented in the time-frequency domain by using Short Time Fourier transform STFT algorithm for knowing exactly what the frequency components presented in those frequency sub-bands are. Once the proposed feature vector is obtained, three feature dimensionality reduction techniques are employed using Linear Discriminant Analysis LDA, a feedback wrapper method and Locality Sensitive Discriminant Analysis LSDA. Lastly, the Adaptive Neuro-Fuzzy Inference System ANFIS algorithm is used for instantaneous identification and classification of bearing faults. In order to evaluate the performances of the proposed method, different testing data set to the trained ANFIS model by using different conditions of healthy and faulty bearings under various load levels, fault severities and rotating speed. The conclusion resulting from this paper is highlighted by experimental results which prove that the proposed method can serve as an intelligent bearing fault diagnosis system.

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

Gamblin, T; de Supinski, B R; Schulz, M

Good load balance is crucial on very large parallel systems, but the most sophisticated algorithms introduce dynamic imbalances through adaptation in domain decomposition or use of adaptive solvers. To observe and diagnose imbalance, developers need system-wide, temporally-ordered measurements from full-scale runs. This potentially requires data collection from multiple code regions on all processors over the entire execution. Doing this instrumentation naively can, in combination with the application itself, exceed available I/O bandwidth and storage capacity, and can induce severe behavioral perturbations. We present and evaluate a novel technique for scalable, low-error load balance measurement. This uses a parallel wavelet transformmore » and other parallel encoding methods. We show that our technique collects and reconstructs system-wide measurements with low error. Compression time scales sublinearly with system size and data volume is several orders of magnitude smaller than the raw data. The overhead is low enough for online use in a production environment.« less

Simulation of hypersonic rarefied flows with the immersed-boundary method

NASA Astrophysics Data System (ADS)

Bruno, D.; De Palma, P.; de Tullio, M. D.

2011-05-01

This paper provides a validation of an immersed boundary method for computing hypersonic rarefied gas flows. The method is based on the solution of the Navier-Stokes equation and is validated versus numerical results obtained by the DSMC approach. The Navier-Stokes solver employs a flexible local grid refinement technique and is implemented on parallel machines using a domain-decomposition approach. Thanks to the efficient grid generation process, based on the ray-tracing technique, and the use of the METIS software, it is possible to obtain the partitioned grids to be assigned to each processor with a minimal effort by the user. This allows one to by-pass the expensive (in terms of time and human resources) classical generation process of a body fitted grid. First-order slip-velocity boundary conditions are employed and tested for taking into account rarefied gas effects.

Spatiotemporal Domain Decomposition for Massive Parallel Computation of Space-Time Kernel Density

NASA Astrophysics Data System (ADS)

Hohl, A.; Delmelle, E. M.; Tang, W.

2015-07-01

Accelerated processing capabilities are deemed critical when conducting analysis on spatiotemporal datasets of increasing size, diversity and availability. High-performance parallel computing offers the capacity to solve computationally demanding problems in a limited timeframe, but likewise poses the challenge of preventing processing inefficiency due to workload imbalance between computing resources. Therefore, when designing new algorithms capable of implementing parallel strategies, careful spatiotemporal domain decomposition is necessary to account for heterogeneity in the data. In this study, we perform octtree-based adaptive decomposition of the spatiotemporal domain for parallel computation of space-time kernel density. In order to avoid edge effects near subdomain boundaries, we establish spatiotemporal buffers to include adjacent data-points that are within the spatial and temporal kernel bandwidths. Then, we quantify computational intensity of each subdomain to balance workloads among processors. We illustrate the benefits of our methodology using a space-time epidemiological dataset of Dengue fever, an infectious vector-borne disease that poses a severe threat to communities in tropical climates. Our parallel implementation of kernel density reaches substantial speedup compared to sequential processing, and achieves high levels of workload balance among processors due to great accuracy in quantifying computational intensity. Our approach is portable of other space-time analytical tests.

A hybrid perturbation-Galerkin technique for partial differential equations

NASA Technical Reports Server (NTRS)

Geer, James F.; Anderson, Carl M.

1990-01-01

A two-step hybrid perturbation-Galerkin technique for improving the usefulness of perturbation solutions to partial differential equations which contain a parameter is presented and discussed. In the first step of the method, the leading terms in the asymptotic expansion(s) of the solution about one or more values of the perturbation parameter are obtained using standard perturbation methods. In the second step, the perturbation functions obtained in the first step are used as trial functions in a Bubnov-Galerkin approximation. This semi-analytical, semi-numerical hybrid technique appears to overcome some of the drawbacks of the perturbation and Galerkin methods when they are applied by themselves, while combining some of the good features of each. The technique is illustrated first by a simple example. It is then applied to the problem of determining the flow of a slightly compressible fluid past a circular cylinder and to the problem of determining the shape of a free surface due to a sink above the surface. Solutions obtained by the hybrid method are compared with other approximate solutions, and its possible application to certain problems associated with domain decomposition is discussed.

SVD compression for magnetic resonance fingerprinting in the time domain.

PubMed

McGivney, Debra F; Pierre, Eric; Ma, Dan; Jiang, Yun; Saybasili, Haris; Gulani, Vikas; Griswold, Mark A

2014-12-01

Magnetic resonance (MR) fingerprinting is a technique for acquiring and processing MR data that simultaneously provides quantitative maps of different tissue parameters through a pattern recognition algorithm. A predefined dictionary models the possible signal evolutions simulated using the Bloch equations with different combinations of various MR parameters and pattern recognition is completed by computing the inner product between the observed signal and each of the predicted signals within the dictionary. Though this matching algorithm has been shown to accurately predict the MR parameters of interest, one desires a more efficient method to obtain the quantitative images. We propose to compress the dictionary using the singular value decomposition, which will provide a low-rank approximation. By compressing the size of the dictionary in the time domain, we are able to speed up the pattern recognition algorithm, by a factor of between 3.4-4.8, without sacrificing the high signal-to-noise ratio of the original scheme presented previously.

Geometrical and topological issues in octree based automatic meshing

NASA Technical Reports Server (NTRS)

Saxena, Mukul; Perucchio, Renato

1987-01-01

Finite element meshes derived automatically from solid models through recursive spatial subdivision schemes (octrees) can be made to inherit the hierarchical structure and the spatial addressability intrinsic to the underlying grid. These two properties, together with the geometric regularity that can also be built into the mesh, make octree based meshes ideally suited for efficient analysis and self-adaptive remeshing and reanalysis. The element decomposition of the octal cells that intersect the boundary of the domain is discussed. The problem, central to octree based meshing, is solved by combining template mapping and element extraction into a procedure that utilizes both constructive solid geometry and boundary representation techniques. Boundary cells that are not intersected by the edge of the domain boundary are easily mapped to predefined element topology. Cells containing edges (and vertices) are first transformed into a planar polyhedron and then triangulated via element extractor. The modeling environments required for the derivation of planar polyhedra and for element extraction are analyzed.

Octree based automatic meshing from CSG models

NASA Technical Reports Server (NTRS)

Perucchio, Renato

1987-01-01

Finite element meshes derived automatically from solid models through recursive spatial subdivision schemes (octrees) can be made to inherit the hierarchical structure and the spatial addressability intrinsic to the underlying grid. These two properties, together with the geometric regularity that can also be built into the mesh, make octree based meshes ideally suited for efficient analysis and self-adaptive remeshing and reanalysis. The element decomposition of the octal cells that intersect the boundary of the domain is emphasized. The problem, central to octree based meshing, is solved by combining template mapping and element extraction into a procedure that utilizes both constructive solid geometry and boundary respresentation techniques. Boundary cells that are not intersected by the edge of the domain boundary are easily mapped to predefined element topology. Cells containing edges (and vertices) are first transformed into a planar polyhedron and then triangulated via element extractors. The modeling environments required for the derivation of planar polyhedra and for element extraction are analyzed.

SVD Compression for Magnetic Resonance Fingerprinting in the Time Domain

PubMed Central

McGivney, Debra F.; Pierre, Eric; Ma, Dan; Jiang, Yun; Saybasili, Haris; Gulani, Vikas; Griswold, Mark A.

2016-01-01

Magnetic resonance fingerprinting is a technique for acquiring and processing MR data that simultaneously provides quantitative maps of different tissue parameters through a pattern recognition algorithm. A predefined dictionary models the possible signal evolutions simulated using the Bloch equations with different combinations of various MR parameters and pattern recognition is completed by computing the inner product between the observed signal and each of the predicted signals within the dictionary. Though this matching algorithm has been shown to accurately predict the MR parameters of interest, one desires a more efficient method to obtain the quantitative images. We propose to compress the dictionary using the singular value decomposition (SVD), which will provide a low-rank approximation. By compressing the size of the dictionary in the time domain, we are able to speed up the pattern recognition algorithm, by a factor of between 3.4-4.8, without sacrificing the high signal-to-noise ratio of the original scheme presented previously. PMID:25029380

Domain decomposition methods for the parallel computation of reacting flows

NASA Technical Reports Server (NTRS)

Keyes, David E.

1988-01-01

Domain decomposition is a natural route to parallel computing for partial differential equation solvers. Subdomains of which the original domain of definition is comprised are assigned to independent processors at the price of periodic coordination between processors to compute global parameters and maintain the requisite degree of continuity of the solution at the subdomain interfaces. In the domain-decomposed solution of steady multidimensional systems of PDEs by finite difference methods using a pseudo-transient version of Newton iteration, the only portion of the computation which generally stands in the way of efficient parallelization is the solution of the large, sparse linear systems arising at each Newton step. For some Jacobian matrices drawn from an actual two-dimensional reacting flow problem, comparisons are made between relaxation-based linear solvers and also preconditioned iterative methods of Conjugate Gradient and Chebyshev type, focusing attention on both iteration count and global inner product count. The generalized minimum residual method with block-ILU preconditioning is judged the best serial method among those considered, and parallel numerical experiments on the Encore Multimax demonstrate for it approximately 10-fold speedup on 16 processors.

A spectral analysis of the domain decomposed Monte Carlo method for linear systems

DOE PAGES

Slattery, Stuart R.; Evans, Thomas M.; Wilson, Paul P. H.

2015-09-08

The domain decomposed behavior of the adjoint Neumann-Ulam Monte Carlo method for solving linear systems is analyzed using the spectral properties of the linear oper- ator. Relationships for the average length of the adjoint random walks, a measure of convergence speed and serial performance, are made with respect to the eigenvalues of the linear operator. In addition, relationships for the effective optical thickness of a domain in the decomposition are presented based on the spectral analysis and diffusion theory. Using the effective optical thickness, the Wigner rational approxi- mation and the mean chord approximation are applied to estimate the leakagemore » frac- tion of random walks from a domain in the decomposition as a measure of parallel performance and potential communication costs. The one-speed, two-dimensional neutron diffusion equation is used as a model problem in numerical experiments to test the models for symmetric operators with spectral qualities similar to light water reactor problems. We find, in general, the derived approximations show good agreement with random walk lengths and leakage fractions computed by the numerical experiments.« less

Application of Direct Parallel Methods to Reconstruction and Forecasting Problems

NASA Astrophysics Data System (ADS)

Song, Changgeun

Many important physical processes in nature are represented by partial differential equations. Numerical weather prediction in particular, requires vast computational resources. We investigate the significance of parallel processing technology to the real world problem of atmospheric prediction. In this paper we consider the classic problem of decomposing the observed wind field into the irrotational and nondivergent components. Recognizing the fact that on a limited domain this problem has a non-unique solution, Lynch (1989) described eight different ways to accomplish the decomposition. One set of elliptic equations is associated with the decomposition--this determines the initial nondivergent state for the forecast model. It is shown that the entire decomposition problem can be solved in a fraction of a second using multi-vector processor such as ALLIANT FX/8. Secondly, the barotropic model is used to track hurricanes. Also, one set of elliptic equations is solved to recover the streamfunction from the forecasted vorticity. A 72 h prediction of Elena is made while it is in the Gulf of Mexico. During this time the hurricane executes a dramatic re-curvature that is captured by the model. Furthermore, an improvement in the track prediction results when a simple assimilation strategy is used. This technique makes use of the wind fields in the 24 h period immediately preceding the initial time for the prediction. In this particular application, solutions to systems of elliptic equations are the center of the computational mechanics. We demonstrate that direct, parallel methods based on accelerated block cyclic reduction (BCR) significantly reduce the computational time required to solve the elliptic equations germane to the decomposition, the forecast and adjoint assimilation.

a Non-Overlapping Discretization Method for Partial Differential Equations

NASA Astrophysics Data System (ADS)

Rosas-Medina, A.; Herrera, I.

2013-05-01

Mathematical models of many systems of interest, including very important continuous systems of Engineering and Science, lead to a great variety of partial differential equations whose solution methods are based on the computational processing of large-scale algebraic systems. Furthermore, the incredible expansion experienced by the existing computational hardware and software has made amenable to effective treatment problems of an ever increasing diversity and complexity, posed by engineering and scientific applications. The emergence of parallel computing prompted on the part of the computational-modeling community a continued and systematic effort with the purpose of harnessing it for the endeavor of solving boundary-value problems (BVPs) of partial differential equations. Very early after such an effort began, it was recognized that domain decomposition methods (DDM) were the most effective technique for applying parallel computing to the solution of partial differential equations, since such an approach drastically simplifies the coordination of the many processors that carry out the different tasks and also reduces very much the requirements of information-transmission between them. Ideally, DDMs intend producing algorithms that fulfill the DDM-paradigm; i.e., such that "the global solution is obtained by solving local problems defined separately in each subdomain of the coarse-mesh -or domain-decomposition-". Stated in a simplistic manner, the basic idea is that, when the DDM-paradigm is satisfied, full parallelization can be achieved by assigning each subdomain to a different processor. When intensive DDM research began much attention was given to overlapping DDMs, but soon after attention shifted to non-overlapping DDMs. This evolution seems natural when the DDM-paradigm is taken into account: it is easier to uncouple the local problems when the subdomains are separated. However, an important limitation of non-overlapping domain decompositions, as that concept is usually understood today, is that interface nodes are shared by two or more subdomains of the coarse-mesh and, therefore, even non-overlapping DDMs are actually overlapping when seen from the perspective of the nodes used in the discretization. In this talk we present and discuss a discretization method in which the nodes used are non-overlapping, in the sense that each one of them belongs to one and only one subdomain of the coarse-mesh.

Preprocessed cumulative reconstructor with domain decomposition: a fast wavefront reconstruction method for pyramid wavefront sensor.

PubMed

Shatokhina, Iuliia; Obereder, Andreas; Rosensteiner, Matthias; Ramlau, Ronny

2013-04-20

We present a fast method for the wavefront reconstruction from pyramid wavefront sensor (P-WFS) measurements. The method is based on an analytical relation between pyramid and Shack-Hartmann sensor (SH-WFS) data. The algorithm consists of two steps--a transformation of the P-WFS data to SH data, followed by the application of cumulative reconstructor with domain decomposition, a wavefront reconstructor from SH-WFS measurements. The closed loop simulations confirm that our method provides the same quality as the standard matrix vector multiplication method. A complexity analysis as well as speed tests confirm that the method is very fast. Thus, the method can be used on extremely large telescopes, e.g., for eXtreme adaptive optics systems.

Object detection with a multistatic array using singular value decomposition

DOEpatents

Hallquist, Aaron T.; Chambers, David H.

2014-07-01

A method and system for detecting the presence of subsurface objects within a medium is provided. In some embodiments, the detection system operates in a multistatic mode to collect radar return signals generated by an array of transceiver antenna pairs that is positioned across a surface and that travels down the surface. The detection system converts the return signals from a time domain to a frequency domain, resulting in frequency return signals. The detection system then performs a singular value decomposition for each frequency to identify singular values for each frequency. The detection system then detects the presence of a subsurface object based on a comparison of the identified singular values to expected singular values when no subsurface object is present.

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

Meng, F.; Banks, J. W.; Henshaw, W. D.

We describe a new partitioned approach for solving conjugate heat transfer (CHT) problems where the governing temperature equations in different material domains are time-stepped in a implicit manner, but where the interface coupling is explicit. The new approach, called the CHAMP scheme (Conjugate Heat transfer Advanced Multi-domain Partitioned), is based on a discretization of the interface coupling conditions using a generalized Robin (mixed) condition. The weights in the Robin condition are determined from the optimization of a condition derived from a local stability analysis of the coupling scheme. The interface treatment combines ideas from optimized-Schwarz methods for domain-decomposition problems togethermore » with the interface jump conditions and additional compatibility jump conditions derived from the governing equations. For many problems (i.e. for a wide range of material properties, grid-spacings and time-steps) the CHAMP algorithm is stable and second-order accurate using no sub-time-step iterations (i.e. a single implicit solve of the temperature equation in each domain). In extreme cases (e.g. very fine grids with very large time-steps) it may be necessary to perform one or more sub-iterations. Each sub-iteration generally increases the range of stability substantially and thus one sub-iteration is likely sufficient for the vast majority of practical problems. The CHAMP algorithm is developed first for a model problem and analyzed using normal-mode the- ory. The theory provides a mechanism for choosing optimal parameters in the mixed interface condition. A comparison is made to the classical Dirichlet-Neumann (DN) method and, where applicable, to the optimized- Schwarz (OS) domain-decomposition method. For problems with different thermal conductivities and dif- fusivities, the CHAMP algorithm outperforms the DN scheme. For domain-decomposition problems with uniform conductivities and diffusivities, the CHAMP algorithm performs better than the typical OS scheme with one grid-cell overlap. Lastly, the CHAMP scheme is also developed for general curvilinear grids and CHT ex- amples are presented using composite overset grids that confirm the theory and demonstrate the effectiveness of the approach.« less

Iterative load-balancing method with multigrid level relaxation for particle simulation with short-range interactions

NASA Astrophysics Data System (ADS)

Furuichi, Mikito; Nishiura, Daisuke

2017-10-01

We developed dynamic load-balancing algorithms for Particle Simulation Methods (PSM) involving short-range interactions, such as Smoothed Particle Hydrodynamics (SPH), Moving Particle Semi-implicit method (MPS), and Discrete Element method (DEM). These are needed to handle billions of particles modeled in large distributed-memory computer systems. Our method utilizes flexible orthogonal domain decomposition, allowing the sub-domain boundaries in the column to be different for each row. The imbalances in the execution time between parallel logical processes are treated as a nonlinear residual. Load-balancing is achieved by minimizing the residual within the framework of an iterative nonlinear solver, combined with a multigrid technique in the local smoother. Our iterative method is suitable for adjusting the sub-domain frequently by monitoring the performance of each computational process because it is computationally cheaper in terms of communication and memory costs than non-iterative methods. Numerical tests demonstrated the ability of our approach to handle workload imbalances arising from a non-uniform particle distribution, differences in particle types, or heterogeneous computer architecture which was difficult with previously proposed methods. We analyzed the parallel efficiency and scalability of our method using Earth simulator and K-computer supercomputer systems.

Iterative image-domain decomposition for dual-energy CT

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

Niu, Tianye; Dong, Xue; Petrongolo, Michael

2014-04-15

Purpose: Dual energy CT (DECT) imaging plays an important role in advanced imaging applications due to its capability of material decomposition. Direct decomposition via matrix inversion suffers from significant degradation of image signal-to-noise ratios, which reduces clinical values of DECT. Existing denoising algorithms achieve suboptimal performance since they suppress image noise either before or after the decomposition and do not fully explore the noise statistical properties of the decomposition process. In this work, the authors propose an iterative image-domain decomposition method for noise suppression in DECT, using the full variance-covariance matrix of the decomposed images. Methods: The proposed algorithm ismore » formulated in the form of least-square estimation with smoothness regularization. Based on the design principles of a best linear unbiased estimator, the authors include the inverse of the estimated variance-covariance matrix of the decomposed images as the penalty weight in the least-square term. The regularization term enforces the image smoothness by calculating the square sum of neighboring pixel value differences. To retain the boundary sharpness of the decomposed images, the authors detect the edges in the CT images before decomposition. These edge pixels have small weights in the calculation of the regularization term. Distinct from the existing denoising algorithms applied on the images before or after decomposition, the method has an iterative process for noise suppression, with decomposition performed in each iteration. The authors implement the proposed algorithm using a standard conjugate gradient algorithm. The method performance is evaluated using an evaluation phantom (Catphan©600) and an anthropomorphic head phantom. The results are compared with those generated using direct matrix inversion with no noise suppression, a denoising method applied on the decomposed images, and an existing algorithm with similar formulation as the proposed method but with an edge-preserving regularization term. Results: On the Catphan phantom, the method maintains the same spatial resolution on the decomposed images as that of the CT images before decomposition (8 pairs/cm) while significantly reducing their noise standard deviation. Compared to that obtained by the direct matrix inversion, the noise standard deviation in the images decomposed by the proposed algorithm is reduced by over 98%. Without considering the noise correlation properties in the formulation, the denoising scheme degrades the spatial resolution to 6 pairs/cm for the same level of noise suppression. Compared to the edge-preserving algorithm, the method achieves better low-contrast detectability. A quantitative study is performed on the contrast-rod slice of Catphan phantom. The proposed method achieves lower electron density measurement error as compared to that by the direct matrix inversion, and significantly reduces the error variation by over 97%. On the head phantom, the method reduces the noise standard deviation of decomposed images by over 97% without blurring the sinus structures. Conclusions: The authors propose an iterative image-domain decomposition method for DECT. The method combines noise suppression and material decomposition into an iterative process and achieves both goals simultaneously. By exploring the full variance-covariance properties of the decomposed images and utilizing the edge predetection, the proposed algorithm shows superior performance on noise suppression with high image spatial resolution and low-contrast detectability.« less

Combined iterative reconstruction and image-domain decomposition for dual energy CT using total-variation regularization

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

Dong, Xue; Niu, Tianye; Zhu, Lei, E-mail: leizhu@gatech.edu

2014-05-15

Purpose: Dual-energy CT (DECT) is being increasingly used for its capability of material decomposition and energy-selective imaging. A generic problem of DECT, however, is that the decomposition process is unstable in the sense that the relative magnitude of decomposed signals is reduced due to signal cancellation while the image noise is accumulating from the two CT images of independent scans. Direct image decomposition, therefore, leads to severe degradation of signal-to-noise ratio on the resultant images. Existing noise suppression techniques are typically implemented in DECT with the procedures of reconstruction and decomposition performed independently, which do not explore the statistical propertiesmore » of decomposed images during the reconstruction for noise reduction. In this work, the authors propose an iterative approach that combines the reconstruction and the signal decomposition procedures to minimize the DECT image noise without noticeable loss of resolution. Methods: The proposed algorithm is formulated as an optimization problem, which balances the data fidelity and total variation of decomposed images in one framework, and the decomposition step is carried out iteratively together with reconstruction. The noise in the CT images from the proposed algorithm becomes well correlated even though the noise of the raw projections is independent on the two CT scans. Due to this feature, the proposed algorithm avoids noise accumulation during the decomposition process. The authors evaluate the method performance on noise suppression and spatial resolution using phantom studies and compare the algorithm with conventional denoising approaches as well as combined iterative reconstruction methods with different forms of regularization. Results: On the Catphan©600 phantom, the proposed method outperforms the existing denoising methods on preserving spatial resolution at the same level of noise suppression, i.e., a reduction of noise standard deviation by one order of magnitude. This improvement is mainly attributed to the high noise correlation in the CT images reconstructed by the proposed algorithm. Iterative reconstruction using different regularization, including quadratic orq-generalized Gaussian Markov random field regularization, achieves similar noise suppression from high noise correlation. However, the proposed TV regularization obtains a better edge preserving performance. Studies of electron density measurement also show that our method reduces the average estimation error from 9.5% to 7.1%. On the anthropomorphic head phantom, the proposed method suppresses the noise standard deviation of the decomposed images by a factor of ∼14 without blurring the fine structures in the sinus area. Conclusions: The authors propose a practical method for DECT imaging reconstruction, which combines the image reconstruction and material decomposition into one optimization framework. Compared to the existing approaches, our method achieves a superior performance on DECT imaging with respect to decomposition accuracy, noise reduction, and spatial resolution.« less

Edge compression techniques for visualization of dense directed graphs.

PubMed

Dwyer, Tim; Henry Riche, Nathalie; Marriott, Kim; Mears, Christopher

2013-12-01

We explore the effectiveness of visualizing dense directed graphs by replacing individual edges with edges connected to 'modules'-or groups of nodes-such that the new edges imply aggregate connectivity. We only consider techniques that offer a lossless compression: that is, where the entire graph can still be read from the compressed version. The techniques considered are: a simple grouping of nodes with identical neighbor sets; Modular Decomposition which permits internal structure in modules and allows them to be nested; and Power Graph Analysis which further allows edges to cross module boundaries. These techniques all have the same goal--to compress the set of edges that need to be rendered to fully convey connectivity--but each successive relaxation of the module definition permits fewer edges to be drawn in the rendered graph. Each successive technique also, we hypothesize, requires a higher degree of mental effort to interpret. We test this hypothetical trade-off with two studies involving human participants. For Power Graph Analysis we propose a novel optimal technique based on constraint programming. This enables us to explore the parameter space for the technique more precisely than could be achieved with a heuristic. Although applicable to many domains, we are motivated by--and discuss in particular--the application to software dependency analysis.

TEMPORAL SIGNATURES OF AIR QUALITY OBSERVATIONS AND MODEL OUTPUTS: DO TIME SERIES DECOMPOSITION METHODS CAPTURE RELEVANT TIME SCALES?

EPA Science Inventory

Time series decomposition methods were applied to meteorological and air quality data and their numerical model estimates. Decomposition techniques express a time series as the sum of a small number of independent modes which hypothetically represent identifiable forcings, thereb...

Unmitigated numerical solution to the diffraction term in the parabolic nonlinear ultrasound wave equation.

PubMed

Hasani, Mojtaba H; Gharibzadeh, Shahriar; Farjami, Yaghoub; Tavakkoli, Jahan

2013-09-01

Various numerical algorithms have been developed to solve the Khokhlov-Kuznetsov-Zabolotskaya (KZK) parabolic nonlinear wave equation. In this work, a generalized time-domain numerical algorithm is proposed to solve the diffraction term of the KZK equation. This algorithm solves the transverse Laplacian operator of the KZK equation in three-dimensional (3D) Cartesian coordinates using a finite-difference method based on the five-point implicit backward finite difference and the five-point Crank-Nicolson finite difference discretization techniques. This leads to a more uniform discretization of the Laplacian operator which in turn results in fewer calculation gridding nodes without compromising accuracy in the diffraction term. In addition, a new empirical algorithm based on the LU decomposition technique is proposed to solve the system of linear equations obtained from this discretization. The proposed empirical algorithm improves the calculation speed and memory usage, while the order of computational complexity remains linear in calculation of the diffraction term in the KZK equation. For evaluating the accuracy of the proposed algorithm, two previously published algorithms are used as comparison references: the conventional 2D Texas code and its generalization for 3D geometries. The results show that the accuracy/efficiency performance of the proposed algorithm is comparable with the established time-domain methods.

A novel method of identifying motor primitives using wavelet decomposition*

PubMed Central

Popov, Anton; Olesh, Erienne V.; Yakovenko, Sergiy; Gritsenko, Valeriya

2018-01-01

This study reports a new technique for extracting muscle synergies using continuous wavelet transform. The method allows to quantify coincident activation of muscle groups caused by the physiological processes of fixed duration, thus enabling the extraction of wavelet modules of arbitrary groups of muscles. Hierarchical clustering and identification of the repeating wavelet modules across subjects and across movements, was used to identify consistent muscle synergies. Results indicate that the most frequently repeated wavelet modules comprised combinations of two muscles that are not traditional agonists and span different joints. We have also found that these wavelet modules were flexibly combined across different movement directions in a pattern resembling directional tuning. This method is extendable to multiple frequency domains and signal modalities.

Development of a large scale Chimera grid system for the Space Shuttle Launch Vehicle

NASA Technical Reports Server (NTRS)

Pearce, Daniel G.; Stanley, Scott A.; Martin, Fred W., Jr.; Gomez, Ray J.; Le Beau, Gerald J.; Buning, Pieter G.; Chan, William M.; Chiu, Ing-Tsau; Wulf, Armin; Akdag, Vedat

1993-01-01

The application of CFD techniques to large problems has dictated the need for large team efforts. This paper offers an opportunity to examine the motivations, goals, needs, problems, as well as the methods, tools, and constraints that defined NASA's development of a 111 grid/16 million point grid system model for the Space Shuttle Launch Vehicle. The Chimera approach used for domain decomposition encouraged separation of the complex geometry into several major components each of which was modeled by an autonomous team. ICEM-CFD, a CAD based grid generation package, simplified the geometry and grid topology definition by provoding mature CAD tools and patch independent meshing. The resulting grid system has, on average, a four inch resolution along the surface.

Information criteria for quantifying loss of reversibility in parallelized KMC

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

Gourgoulias, Konstantinos, E-mail: gourgoul@math.umass.edu; Katsoulakis, Markos A., E-mail: markos@math.umass.edu; Rey-Bellet, Luc, E-mail: luc@math.umass.edu

Parallel Kinetic Monte Carlo (KMC) is a potent tool to simulate stochastic particle systems efficiently. However, despite literature on quantifying domain decomposition errors of the particle system for this class of algorithms in the short and in the long time regime, no study yet explores and quantifies the loss of time-reversibility in Parallel KMC. Inspired by concepts from non-equilibrium statistical mechanics, we propose the entropy production per unit time, or entropy production rate, given in terms of an observable and a corresponding estimator, as a metric that quantifies the loss of reversibility. Typically, this is a quantity that cannot bemore » computed explicitly for Parallel KMC, which is why we develop a posteriori estimators that have good scaling properties with respect to the size of the system. Through these estimators, we can connect the different parameters of the scheme, such as the communication time step of the parallelization, the choice of the domain decomposition, and the computational schedule, with its performance in controlling the loss of reversibility. From this point of view, the entropy production rate can be seen both as an information criterion to compare the reversibility of different parallel schemes and as a tool to diagnose reversibility issues with a particular scheme. As a demonstration, we use Sandia Lab's SPPARKS software to compare different parallelization schemes and different domain (lattice) decompositions.« less

Information criteria for quantifying loss of reversibility in parallelized KMC

NASA Astrophysics Data System (ADS)

Gourgoulias, Konstantinos; Katsoulakis, Markos A.; Rey-Bellet, Luc

2017-01-01

Parallel Kinetic Monte Carlo (KMC) is a potent tool to simulate stochastic particle systems efficiently. However, despite literature on quantifying domain decomposition errors of the particle system for this class of algorithms in the short and in the long time regime, no study yet explores and quantifies the loss of time-reversibility in Parallel KMC. Inspired by concepts from non-equilibrium statistical mechanics, we propose the entropy production per unit time, or entropy production rate, given in terms of an observable and a corresponding estimator, as a metric that quantifies the loss of reversibility. Typically, this is a quantity that cannot be computed explicitly for Parallel KMC, which is why we develop a posteriori estimators that have good scaling properties with respect to the size of the system. Through these estimators, we can connect the different parameters of the scheme, such as the communication time step of the parallelization, the choice of the domain decomposition, and the computational schedule, with its performance in controlling the loss of reversibility. From this point of view, the entropy production rate can be seen both as an information criterion to compare the reversibility of different parallel schemes and as a tool to diagnose reversibility issues with a particular scheme. As a demonstration, we use Sandia Lab's SPPARKS software to compare different parallelization schemes and different domain (lattice) decompositions.

Decomposition of Multi-player Games

NASA Astrophysics Data System (ADS)

Zhao, Dengji; Schiffel, Stephan; Thielscher, Michael

Research in General Game Playing aims at building systems that learn to play unknown games without human intervention. We contribute to this endeavour by generalising the established technique of decomposition from AI Planning to multi-player games. To this end, we present a method for the automatic decomposition of previously unknown games into independent subgames, and we show how a general game player can exploit a successful decomposition for game tree search.

Phase segregation in multiphase turbulent channel flow

NASA Astrophysics Data System (ADS)

Bianco, Federico; Soldati, Alfredo

2014-11-01

The phase segregation of a rapidly quenched mixture (namely spinodal decomposition) is numerically investigated. A phase field approach is considered. Direct numerical simulation of the coupled Navier-Stokes and Cahn-Hilliard equations is performed with spectral accuracy and focus has been put on domain growth scaling laws, in a wide range of regimes. The numerical method has been first validated against well known results of literature, then spinodal decomposition in a turbulent bounded flow (channel flow) has been considered. As for homogeneous isotropic case, turbulent fluctuations suppress the segregation process when surface tension at the interfaces is relatively low (namely low Weber number regimes). For these regimes, segregated domains size reaches a statistically steady state due to mixing and break-up phenomena. In contrast with homogenous and isotropic turbulence, the presence of mean shear, leads to a typical domain size that show a wall-distance dependence. Finally, preliminary results on the effects to the drag forces at the wall, due to phase segregation, have been discussed. Regione FVG, program PAR-FSC.

MARS-MD: rejection based image domain material decomposition

NASA Astrophysics Data System (ADS)

Bateman, C. J.; Knight, D.; Brandwacht, B.; McMahon, J.; Healy, J.; Panta, R.; Aamir, R.; Rajendran, K.; Moghiseh, M.; Ramyar, M.; Rundle, D.; Bennett, J.; de Ruiter, N.; Smithies, D.; Bell, S. T.; Doesburg, R.; Chernoglazov, A.; Mandalika, V. B. H.; Walsh, M.; Shamshad, M.; Anjomrouz, M.; Atharifard, A.; Vanden Broeke, L.; Bheesette, S.; Kirkbride, T.; Anderson, N. G.; Gieseg, S. P.; Woodfield, T.; Renaud, P. F.; Butler, A. P. H.; Butler, P. H.

2018-05-01

This paper outlines image domain material decomposition algorithms that have been routinely used in MARS spectral CT systems. These algorithms (known collectively as MARS-MD) are based on a pragmatic heuristic for solving the under-determined problem where there are more materials than energy bins. This heuristic contains three parts: (1) splitting the problem into a number of possible sub-problems, each containing fewer materials; (2) solving each sub-problem; and (3) applying rejection criteria to eliminate all but one sub-problem's solution. An advantage of this process is that different constraints can be applied to each sub-problem if necessary. In addition, the result of this process is that solutions will be sparse in the material domain, which reduces crossover of signal between material images. Two algorithms based on this process are presented: the Segmentation variant, which uses segmented material classes to define each sub-problem; and the Angular Rejection variant, which defines the rejection criteria using the angle between reconstructed attenuation vectors.

Multiscale infrared and visible image fusion using gradient domain guided image filtering

NASA Astrophysics Data System (ADS)

Zhu, Jin; Jin, Weiqi; Li, Li; Han, Zhenghao; Wang, Xia

2018-03-01

For better surveillance with infrared and visible imaging, a novel hybrid multiscale decomposition fusion method using gradient domain guided image filtering (HMSD-GDGF) is proposed in this study. In this method, hybrid multiscale decomposition with guided image filtering and gradient domain guided image filtering of source images are first applied before the weight maps of each scale are obtained using a saliency detection technology and filtering means with three different fusion rules at different scales. The three types of fusion rules are for small-scale detail level, large-scale detail level, and base level. Finally, the target becomes more salient and can be more easily detected in the fusion result, with the detail information of the scene being fully displayed. After analyzing the experimental comparisons with state-of-the-art fusion methods, the HMSD-GDGF method has obvious advantages in fidelity of salient information (including structural similarity, brightness, and contrast), preservation of edge features, and human visual perception. Therefore, visual effects can be improved by using the proposed HMSD-GDGF method.

Assessment of a new method for the analysis of decomposition gases of polymers by a combining thermogravimetric solid-phase extraction and thermal desorption gas chromatography mass spectrometry.

PubMed

Duemichen, E; Braun, U; Senz, R; Fabian, G; Sturm, H

2014-08-08

For analysis of the gaseous thermal decomposition products of polymers, the common techniques are thermogravimetry, combined with Fourier transformed infrared spectroscopy (TGA-FTIR) and mass spectrometry (TGA-MS). These methods offer a simple approach to the decomposition mechanism, especially for small decomposition molecules. Complex spectra of gaseous mixtures are very often hard to identify because of overlapping signals. In this paper a new method is described to adsorb the decomposition products during controlled conditions in TGA on solid-phase extraction (SPE) material: twisters. Subsequently the twisters were analysed with thermal desorption gas chromatography mass spectrometry (TDS-GC-MS), which allows the decomposition products to be separated and identified using an MS library. The thermoplastics polyamide 66 (PA 66) and polybutylene terephthalate (PBT) were used as example polymers. The influence of the sample mass and of the purge gas flow during the decomposition process was investigated in TGA. The advantages and limitations of the method were presented in comparison to the common analysis techniques, TGA-FTIR and TGA-MS. Copyright © 2014 Elsevier B.V. All rights reserved.

F4 , E6 and G2 exceptional gauge groups in the vacuum domain structure model

NASA Astrophysics Data System (ADS)

Shahlaei, Amir; Rafibakhsh, Shahnoosh

2018-03-01

Using a vacuum domain structure model, we calculate trivial static potentials in various representations of F4 , E6, and G2 exceptional groups by means of the unit center element. Due to the absence of the nontrivial center elements, the potential of every representation is screened at far distances. However, the linear part is observed at intermediate quark separations and is investigated by the decomposition of the exceptional group to its maximal subgroups. Comparing the group factor of the supergroup with the corresponding one obtained from the nontrivial center elements of S U (3 ) subgroup shows that S U (3 ) is not the direct cause of temporary confinement in any of the exceptional groups. However, the trivial potential obtained from the group decomposition into the S U (3 ) subgroup is the same as the potential of the supergroup itself. In addition, any regular or singular decomposition into the S U (2 ) subgroup that produces the Cartan generator with the same elements as h1, in any exceptional group, leads to the linear intermediate potential of the exceptional gauge groups. The other S U (2 ) decompositions with the Cartan generator different from h1 are still able to describe the linear potential if the number of S U (2 ) nontrivial center elements that emerge in the decompositions is the same. As a result, it is the center vortices quantized in terms of nontrivial center elements of the S U (2 ) subgroup that give rise to the intermediate confinement in the static potentials.

Fast non-overlapping Schwarz domain decomposition methods for solving the neutron diffusion equation

NASA Astrophysics Data System (ADS)

Jamelot, Erell; Ciarlet, Patrick

2013-05-01

Studying numerically the steady state of a nuclear core reactor is expensive, in terms of memory storage and computational time. In order to address both requirements, one can use a domain decomposition method, implemented on a parallel computer. We present here such a method for the mixed neutron diffusion equations, discretized with Raviart-Thomas-Nédélec finite elements. This method is based on the Schwarz iterative algorithm with Robin interface conditions to handle communications. We analyse this method from the continuous point of view to the discrete point of view, and we give some numerical results in a realistic highly heterogeneous 3D configuration. Computations are carried out with the MINOS solver of the APOLLO3® neutronics code. APOLLO3 is a registered trademark in France.

Low-Rank Correction Methods for Algebraic Domain Decomposition Preconditioners

DOE PAGES

Li, Ruipeng; Saad, Yousef

2017-08-01

This study presents a parallel preconditioning method for distributed sparse linear systems, based on an approximate inverse of the original matrix, that adopts a general framework of distributed sparse matrices and exploits domain decomposition (DD) and low-rank corrections. The DD approach decouples the matrix and, once inverted, a low-rank approximation is applied by exploiting the Sherman--Morrison--Woodbury formula, which yields two variants of the preconditioning methods. The low-rank expansion is computed by the Lanczos procedure with reorthogonalizations. Numerical experiments indicate that, when combined with Krylov subspace accelerators, this preconditioner can be efficient and robust for solving symmetric sparse linear systems. Comparisonsmore » with pARMS, a DD-based parallel incomplete LU (ILU) preconditioning method, are presented for solving Poisson's equation and linear elasticity problems.« less

A domain decomposition approach to implementing fault slip in finite-element models of quasi-static and dynamic crustal deformation

USGS Publications Warehouse

Aagaard, Brad T.; Knepley, M.G.; Williams, C.A.

2013-01-01

We employ a domain decomposition approach with Lagrange multipliers to implement fault slip in a finite-element code, PyLith, for use in both quasi-static and dynamic crustal deformation applications. This integrated approach to solving both quasi-static and dynamic simulations leverages common finite-element data structures and implementations of various boundary conditions, discretization schemes, and bulk and fault rheologies. We have developed a custom preconditioner for the Lagrange multiplier portion of the system of equations that provides excellent scalability with problem size compared to conventional additive Schwarz methods. We demonstrate application of this approach using benchmarks for both quasi-static viscoelastic deformation and dynamic spontaneous rupture propagation that verify the numerical implementation in PyLith.

Low-Rank Correction Methods for Algebraic Domain Decomposition Preconditioners

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

Li, Ruipeng; Saad, Yousef

This study presents a parallel preconditioning method for distributed sparse linear systems, based on an approximate inverse of the original matrix, that adopts a general framework of distributed sparse matrices and exploits domain decomposition (DD) and low-rank corrections. The DD approach decouples the matrix and, once inverted, a low-rank approximation is applied by exploiting the Sherman--Morrison--Woodbury formula, which yields two variants of the preconditioning methods. The low-rank expansion is computed by the Lanczos procedure with reorthogonalizations. Numerical experiments indicate that, when combined with Krylov subspace accelerators, this preconditioner can be efficient and robust for solving symmetric sparse linear systems. Comparisonsmore » with pARMS, a DD-based parallel incomplete LU (ILU) preconditioning method, are presented for solving Poisson's equation and linear elasticity problems.« less

Regularization of nonlinear decomposition of spectral x-ray projection images.

PubMed

Ducros, Nicolas; Abascal, Juan Felipe Perez-Juste; Sixou, Bruno; Rit, Simon; Peyrin, Françoise

2017-09-01

Exploiting the x-ray measurements obtained in different energy bins, spectral computed tomography (CT) has the ability to recover the 3-D description of a patient in a material basis. This may be achieved solving two subproblems, namely the material decomposition and the tomographic reconstruction problems. In this work, we address the material decomposition of spectral x-ray projection images, which is a nonlinear ill-posed problem. Our main contribution is to introduce a material-dependent spatial regularization in the projection domain. The decomposition problem is solved iteratively using a Gauss-Newton algorithm that can benefit from fast linear solvers. A Matlab implementation is available online. The proposed regularized weighted least squares Gauss-Newton algorithm (RWLS-GN) is validated on numerical simulations of a thorax phantom made of up to five materials (soft tissue, bone, lung, adipose tissue, and gadolinium), which is scanned with a 120 kV source and imaged by a 4-bin photon counting detector. To evaluate the method performance of our algorithm, different scenarios are created by varying the number of incident photons, the concentration of the marker and the configuration of the phantom. The RWLS-GN method is compared to the reference maximum likelihood Nelder-Mead algorithm (ML-NM). The convergence of the proposed method and its dependence on the regularization parameter are also studied. We show that material decomposition is feasible with the proposed method and that it converges in few iterations. Material decomposition with ML-NM was very sensitive to noise, leading to decomposed images highly affected by noise, and artifacts even for the best case scenario. The proposed method was less sensitive to noise and improved contrast-to-noise ratio of the gadolinium image. Results were superior to those provided by ML-NM in terms of image quality and decomposition was 70 times faster. For the assessed experiments, material decomposition was possible with the proposed method when the number of incident photons was equal or larger than 10 5 and when the marker concentration was equal or larger than 0.03 g·cm -3 . The proposed method efficiently solves the nonlinear decomposition problem for spectral CT, which opens up new possibilities such as material-specific regularization in the projection domain and a parallelization framework, in which projections are solved in parallel. © 2017 American Association of Physicists in Medicine.

Decomposition of Metrosideros polymorpha leaf litter along elevational gradients in Hawaii

Treesearch

Paul G. Scowcroft; Douglas R. Turner; Peter M. Vitousek

2000-01-01

We examined interactions between temperature, soil development, and decomposition on three elevational gradients, the upper and lower ends of each being situated on a common lava flow or ash deposit. We used the reciprocal transplant technique to estimate decomposition rates of Metrosideros polymorpha leaf litter during a three-year period at warm...

Mechanism of thermal decomposition of K2FeO4 and BaFeO4: A review

NASA Astrophysics Data System (ADS)

Sharma, Virender K.; Machala, Libor

2016-12-01

This paper presents thermal decomposition of potassium ferrate(VI) (K2FeO4) and barium ferrate(VI) (BaFeO4) in air and nitrogen atmosphere. Mössbauer spectroscopy and nuclear forward scattering (NFS) synchrotron radiation approaches are reviewed to advance understanding of electron-transfer processes involved in reduction of ferrate(VI) to Fe(III) phases. Direct evidences of Fe V and Fe IV as intermediate iron species using the applied techniques are given. Thermal decomposition of K2FeO4 involved Fe V, Fe IV, and K3FeO3 as intermediate species while BaFeO3 (i.e. Fe IV) was the only intermediate species during the decomposition of BaFeO4. Nature of ferrite species, formed as final Fe(III) species, of thermal decomposition of K2FeO4 and BaFeO4 under different conditions are evaluated. Steps of the mechanisms of thermal decomposition of ferrate(VI), which reasonably explained experimental observations of applied approaches in conjunction with thermal and surface techniques, are summarized.

A New Homotopy Perturbation Scheme for Solving Singular Boundary Value Problems Arising in Various Physical Models

NASA Astrophysics Data System (ADS)

Roul, Pradip; Warbhe, Ujwal

2017-08-01

The classical homotopy perturbation method proposed by J. H. He, Comput. Methods Appl. Mech. Eng. 178, 257 (1999) is useful for obtaining the approximate solutions for a wide class of nonlinear problems in terms of series with easily calculable components. However, in some cases, it has been found that this method results in slowly convergent series. To overcome the shortcoming, we present a new reliable algorithm called the domain decomposition homotopy perturbation method (DDHPM) to solve a class of singular two-point boundary value problems with Neumann and Robin-type boundary conditions arising in various physical models. Five numerical examples are presented to demonstrate the accuracy and applicability of our method, including thermal explosion, oxygen-diffusion in a spherical cell and heat conduction through a solid with heat generation. A comparison is made between the proposed technique and other existing seminumerical or numerical techniques. Numerical results reveal that only two or three iterations lead to high accuracy of the solution and this newly improved technique introduces a powerful improvement for solving nonlinear singular boundary value problems (SBVPs).

Parallel SOR methods with a parabolic-diffusion acceleration technique for solving an unstructured-grid Poisson equation on 3D arbitrary geometries

NASA Astrophysics Data System (ADS)

Zapata, M. A. Uh; Van Bang, D. Pham; Nguyen, K. D.

2016-05-01

This paper presents a parallel algorithm for the finite-volume discretisation of the Poisson equation on three-dimensional arbitrary geometries. The proposed method is formulated by using a 2D horizontal block domain decomposition and interprocessor data communication techniques with message passing interface. The horizontal unstructured-grid cells are reordered according to the neighbouring relations and decomposed into blocks using a load-balanced distribution to give all processors an equal amount of elements. In this algorithm, two parallel successive over-relaxation methods are presented: a multi-colour ordering technique for unstructured grids based on distributed memory and a block method using reordering index following similar ideas of the partitioning for structured grids. In all cases, the parallel algorithms are implemented with a combination of an acceleration iterative solver. This solver is based on a parabolic-diffusion equation introduced to obtain faster solutions of the linear systems arising from the discretisation. Numerical results are given to evaluate the performances of the methods showing speedups better than linear.

Wavelet bases on the L-shaped domain

NASA Astrophysics Data System (ADS)

Jouini, Abdellatif; Lemarié-Rieusset, Pierre Gilles

2013-07-01

We present in this paper two elementary constructions of multiresolution analyses on the L-shaped domain D. In the first one, we shall describe a direct method to define an orthonormal multiresolution analysis. In the second one, we use the decomposition method for constructing a biorthogonal multiresolution analysis. These analyses are adapted for the study of the Sobolev spaces Hs(D)(s∈N).

Adaptive Fourier decomposition based R-peak detection for noisy ECG Signals.

PubMed

Ze Wang; Chi Man Wong; Feng Wan

2017-07-01

An adaptive Fourier decomposition (AFD) based R-peak detection method is proposed for noisy ECG signals. Although lots of QRS detection methods have been proposed in literature, most detection methods require high signal quality. The proposed method extracts the R waves from the energy domain using the AFD and determines the R-peak locations based on the key decomposition parameters, achieving the denoising and the R-peak detection at the same time. Validated by clinical ECG signals in the MIT-BIH Arrhythmia Database, the proposed method shows better performance than the Pan-Tompkin (PT) algorithm in both situations of a native PT and the PT with a denoising process.

A Linked-Cell Domain Decomposition Method for Molecular Dynamics Simulation on a Scalable Multiprocessor

DOE PAGES

Yang, L. H.; Brooks III, E. D.; Belak, J.

1992-01-01

A molecular dynamics algorithm for performing large-scale simulations using the Parallel C Preprocessor (PCP) programming paradigm on the BBN TC2000, a massively parallel computer, is discussed. The algorithm uses a linked-cell data structure to obtain the near neighbors of each atom as time evoles. Each processor is assigned to a geometric domain containing many subcells and the storage for that domain is private to the processor. Within this scheme, the interdomain (i.e., interprocessor) communication is minimized.

A leakage-free resonance sparse decomposition technique for bearing fault detection in gearboxes

NASA Astrophysics Data System (ADS)

Osman, Shazali; Wang, Wilson

2018-03-01

Most of rotating machinery deficiencies are related to defects in rolling element bearings. Reliable bearing fault detection still remains a challenging task, especially for bearings in gearboxes as bearing-defect-related features are nonstationary and modulated by gear mesh vibration. A new leakage-free resonance sparse decomposition (LRSD) technique is proposed in this paper for early bearing fault detection of gearboxes. In the proposed LRSD technique, a leakage-free filter is suggested to remove strong gear mesh and shaft running signatures. A kurtosis and cosine distance measure is suggested to select appropriate redundancy r and quality factor Q. The signal residual is processed by signal sparse decomposition for highpass and lowpass resonance analysis to extract representative features for bearing fault detection. The effectiveness of the proposed technique is verified by a succession of experimental tests corresponding to different gearbox and bearing conditions.

Terascale Optimal PDE Simulations (TOPS) Center

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

Professor Olof B. Widlund

2007-07-09

Our work has focused on the development and analysis of domain decomposition algorithms for a variety of problems arising in continuum mechanics modeling. In particular, we have extended and analyzed FETI-DP and BDDC algorithms; these iterative solvers were first introduced and studied by Charbel Farhat and his collaborators, see [11, 45, 12], and by Clark Dohrmann of SANDIA, Albuquerque, see [43, 2, 1], respectively. These two closely related families of methods are of particular interest since they are used more extensively than other iterative substructuring methods to solve very large and difficult problems. Thus, the FETI algorithms are part ofmore » the SALINAS system developed by the SANDIA National Laboratories for very large scale computations, and as already noted, BDDC was first developed by a SANDIA scientist, Dr. Clark Dohrmann. The FETI algorithms are also making inroads in commercial engineering software systems. We also note that the analysis of these algorithms poses very real mathematical challenges. The success in developing this theory has, in several instances, led to significant improvements in the performance of these algorithms. A very desirable feature of these iterative substructuring and other domain decomposition algorithms is that they respect the memory hierarchy of modern parallel and distributed computing systems, which is essential for approaching peak floating point performance. The development of improved methods, together with more powerful computer systems, is making it possible to carry out simulations in three dimensions, with quite high resolution, relatively easily. This work is supported by high quality software systems, such as Argonne's PETSc library, which facilitates code development as well as the access to a variety of parallel and distributed computer systems. The success in finding scalable and robust domain decomposition algorithms for very large number of processors and very large finite element problems is, e.g., illustrated in [24, 25, 26]. This work is based on [29, 31]. Our work over these five and half years has, in our opinion, helped advance the knowledge of domain decomposition methods significantly. We see these methods as providing valuable alternatives to other iterative methods, in particular, those based on multi-grid. In our opinion, our accomplishments also match the goals of the TOPS project quite closely.« less

Predicting domain-domain interaction based on domain profiles with feature selection and support vector machines

PubMed Central

2010-01-01

Background Protein-protein interaction (PPI) plays essential roles in cellular functions. The cost, time and other limitations associated with the current experimental methods have motivated the development of computational methods for predicting PPIs. As protein interactions generally occur via domains instead of the whole molecules, predicting domain-domain interaction (DDI) is an important step toward PPI prediction. Computational methods developed so far have utilized information from various sources at different levels, from primary sequences, to molecular structures, to evolutionary profiles. Results In this paper, we propose a computational method to predict DDI using support vector machines (SVMs), based on domains represented as interaction profile hidden Markov models (ipHMM) where interacting residues in domains are explicitly modeled according to the three dimensional structural information available at the Protein Data Bank (PDB). Features about the domains are extracted first as the Fisher scores derived from the ipHMM and then selected using singular value decomposition (SVD). Domain pairs are represented by concatenating their selected feature vectors, and classified by a support vector machine trained on these feature vectors. The method is tested by leave-one-out cross validation experiments with a set of interacting protein pairs adopted from the 3DID database. The prediction accuracy has shown significant improvement as compared to InterPreTS (Interaction Prediction through Tertiary Structure), an existing method for PPI prediction that also uses the sequences and complexes of known 3D structure. Conclusions We show that domain-domain interaction prediction can be significantly enhanced by exploiting information inherent in the domain profiles via feature selection based on Fisher scores, singular value decomposition and supervised learning based on support vector machines. Datasets and source code are freely available on the web at http://liao.cis.udel.edu/pub/svdsvm. Implemented in Matlab and supported on Linux and MS Windows. PMID:21034480

Reassessment of the NH4 NO3 thermal decomposition technique for calibration of the N2 O isotopic composition.

PubMed

Mohn, Joachim; Gutjahr, Wilhelm; Toyoda, Sakae; Harris, Eliza; Ibraim, Erkan; Geilmann, Heike; Schleppi, Patrick; Kuhn, Thomas; Lehmann, Moritz F; Decock, Charlotte; Werner, Roland A; Yoshida, Naohiro; Brand, Willi A

2016-09-08

In the last few years, the study of N 2 O site-specific nitrogen isotope composition has been established as a powerful technique to disentangle N 2 O emission pathways. This trend has been accelerated by significant analytical progress in the field of isotope-ratio mass-spectrometry (IRMS) and more recently quantum cascade laser absorption spectroscopy (QCLAS). Methods The ammonium nitrate (NH 4 NO 3 ) decomposition technique provides a strategy to scale the 15 N site-specific (SP ≡ δ 15 N α - δ 15 N β ) and bulk (δ 15 N bulk  = (δ 15 N α  + δ 15 N β )/2) isotopic composition of N 2 O against the international standard for the 15 N/ 14 N isotope ratio (AIR-N 2 ). Within the current project 15 N fractionation effects during thermal decomposition of NH 4 NO 3 on the N 2 O site preference were studied using static and dynamic decomposition techniques. The validity of the NH 4 NO 3 decomposition technique to link NH 4 + and NO 3 - moiety-specific δ 15 N analysis by IRMS to the site-specific nitrogen isotopic composition of N 2 O was confirmed. However, the accuracy of this approach for the calibration of δ 15 N α and δ 15 N β values was found to be limited by non-quantitative NH 4 NO 3 decomposition in combination with substantially different isotope enrichment factors for the conversion of the NO 3 - or NH 4 + nitrogen atom into the α or β position of the N 2 O molecule. The study reveals that the completeness and reproducibility of the NH 4 NO 3 decomposition reaction currently confine the anchoring of N 2 O site-specific isotopic composition to the international isotope ratio scale AIR-N 2 . The authors suggest establishing a set of N 2 O isotope reference materials with appropriate site-specific isotopic composition, as community standards, to improve inter-laboratory compatibility. This article is protected by copyright. All rights reserved.

Application of decomposition techniques to the preliminary design of a transport aircraft

NASA Technical Reports Server (NTRS)

Rogan, J. E.; Mcelveen, R. P.; Kolb, M. A.

1986-01-01

A multifaceted decomposition of a nonlinear constrained optimization problem describing the preliminary design process for a transport aircraft has been made. Flight dynamics, flexible aircraft loads and deformations, and preliminary structural design subproblems appear prominently in the decomposition. The use of design process decomposition for scheduling design projects, a new system integration approach to configuration control, and the application of object-centered programming to a new generation of design tools are discussed.

Development of Novel Decontamination and Inerting Techniques for Explosives Contaminated Facilities. Phase 1. Identification and Evaluation of Novel Decontamination Concepts. Volume 1

DTIC Science & Technology

1983-07-01

the decomposition reaction (Leider, 1981; Kageyama, 1973; Wolfrom, 1956), 2) Hydrolysis of linkages between glucose units (Urbanski, 1964), 3... dehydration ), 2) Acceleration period (to 50 percent decomposition ), 3) First order reaction rate period. The products of thermal decomposition of...simple mechanism to clean an entire building at once. o Depending on the contaminant, thermal decomposition and or hydrolysis may occur. o May be

Introducing the Improved Heaviside Approach to Partial Fraction Decomposition to Undergraduate Students: Results and Implications from a Pilot Study

ERIC Educational Resources Information Center

Man, Yiu-Kwong

2012-01-01

Partial fraction decomposition is a useful technique often taught at senior secondary or undergraduate levels to handle integrations, inverse Laplace transforms or linear ordinary differential equations, etc. In recent years, an improved Heaviside's approach to partial fraction decomposition was introduced and developed by the author. An important…

Proceedings for the ICASE Workshop on Heterogeneous Boundary Conditions

NASA Technical Reports Server (NTRS)

Perkins, A. Louise; Scroggs, Jeffrey S.

1991-01-01

Domain Decomposition is a complex problem with many interesting aspects. The choice of decomposition can be made based on many different criteria, and the choice of interface of internal boundary conditions are numerous. The various regions under study may have different dynamical balances, indicating that different physical processes are dominating the flow in these regions. This conference was called in recognition of the need to more clearly define the nature of these complex problems. This proceedings is a collection of the presentations and the discussion groups.

Domain decomposition algorithms and computation fluid dynamics

NASA Technical Reports Server (NTRS)

Chan, Tony F.

1988-01-01

In the past several years, domain decomposition was a very popular topic, partly motivated by the potential of parallelization. While a large body of theory and algorithms were developed for model elliptic problems, they are only recently starting to be tested on realistic applications. The application of some of these methods to two model problems in computational fluid dynamics are investigated. Some examples are two dimensional convection-diffusion problems and the incompressible driven cavity flow problem. The construction and analysis of efficient preconditioners for the interface operator to be used in the iterative solution of the interface solution is described. For the convection-diffusion problems, the effect of the convection term and its discretization on the performance of some of the preconditioners is discussed. For the driven cavity problem, the effectiveness of a class of boundary probe preconditioners is discussed.

Final Report, DE-FG01-06ER25718 Domain Decomposition and Parallel Computing

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

Widlund, Olof B.

2015-06-09

The goal of this project is to develop and improve domain decomposition algorithms for a variety of partial differential equations such as those of linear elasticity and electro-magnetics.These iterative methods are designed for massively parallel computing systems and allow the fast solution of the very large systems of algebraic equations that arise in large scale and complicated simulations. A special emphasis is placed on problems arising from Maxwell's equation. The approximate solvers, the preconditioners, are combined with the conjugate gradient method and must always include a solver of a coarse model in order to have a performance which is independentmore » of the number of processors used in the computer simulation. A recent development allows for an adaptive construction of this coarse component of the preconditioner.« less

Adaptive multigrid domain decomposition solutions for viscous interacting flows

NASA Technical Reports Server (NTRS)

Rubin, Stanley G.; Srinivasan, Kumar

1992-01-01

Several viscous incompressible flows with strong pressure interaction and/or axial flow reversal are considered with an adaptive multigrid domain decomposition procedure. Specific examples include the triple deck structure surrounding the trailing edge of a flat plate, the flow recirculation in a trough geometry, and the flow in a rearward facing step channel. For the latter case, there are multiple recirculation zones, of different character, for laminar and turbulent flow conditions. A pressure-based form of flux-vector splitting is applied to the Navier-Stokes equations, which are represented by an implicit lowest-order reduced Navier-Stokes (RNS) system and a purely diffusive, higher-order, deferred-corrector. A trapezoidal or box-like form of discretization insures that all mass conservation properties are satisfied at interfacial and outflow boundaries, even for this primitive-variable, non-staggered grid computation.

Three geographic decomposition approaches in transportation network analysis

DOT National Transportation Integrated Search

1980-03-01

This document describes the results of research into the application of geographic decomposition techniques to practical transportation network problems. Three approaches are described for the solution of the traffic assignment problem. One approach ...

Application of Decomposition to Transportation Network Analysis

DOT National Transportation Integrated Search

1976-10-01

This document reports preliminary results of five potential applications of the decomposition techniques from mathematical programming to transportation network problems. The five application areas are (1) the traffic assignment problem with fixed de...

Transportation Network Analysis and Decomposition Methods

DOT National Transportation Integrated Search

1978-03-01

The report outlines research in transportation network analysis using decomposition techniques as a basis for problem solutions. Two transportation network problems were considered in detail: a freight network flow problem and a scheduling problem fo...

A stable and accurate partitioned algorithm for conjugate heat transfer

NASA Astrophysics Data System (ADS)

Meng, F.; Banks, J. W.; Henshaw, W. D.; Schwendeman, D. W.

2017-09-01

We describe a new partitioned approach for solving conjugate heat transfer (CHT) problems where the governing temperature equations in different material domains are time-stepped in an implicit manner, but where the interface coupling is explicit. The new approach, called the CHAMP scheme (Conjugate Heat transfer Advanced Multi-domain Partitioned), is based on a discretization of the interface coupling conditions using a generalized Robin (mixed) condition. The weights in the Robin condition are determined from the optimization of a condition derived from a local stability analysis of the coupling scheme. The interface treatment combines ideas from optimized-Schwarz methods for domain-decomposition problems together with the interface jump conditions and additional compatibility jump conditions derived from the governing equations. For many problems (i.e. for a wide range of material properties, grid-spacings and time-steps) the CHAMP algorithm is stable and second-order accurate using no sub-time-step iterations (i.e. a single implicit solve of the temperature equation in each domain). In extreme cases (e.g. very fine grids with very large time-steps) it may be necessary to perform one or more sub-iterations. Each sub-iteration generally increases the range of stability substantially and thus one sub-iteration is likely sufficient for the vast majority of practical problems. The CHAMP algorithm is developed first for a model problem and analyzed using normal-mode theory. The theory provides a mechanism for choosing optimal parameters in the mixed interface condition. A comparison is made to the classical Dirichlet-Neumann (DN) method and, where applicable, to the optimized-Schwarz (OS) domain-decomposition method. For problems with different thermal conductivities and diffusivities, the CHAMP algorithm outperforms the DN scheme. For domain-decomposition problems with uniform conductivities and diffusivities, the CHAMP algorithm performs better than the typical OS scheme with one grid-cell overlap. The CHAMP scheme is also developed for general curvilinear grids and CHT examples are presented using composite overset grids that confirm the theory and demonstrate the effectiveness of the approach.

A stable and accurate partitioned algorithm for conjugate heat transfer

DOE PAGES

Meng, F.; Banks, J. W.; Henshaw, W. D.; ...

2017-04-25

We describe a new partitioned approach for solving conjugate heat transfer (CHT) problems where the governing temperature equations in different material domains are time-stepped in a implicit manner, but where the interface coupling is explicit. The new approach, called the CHAMP scheme (Conjugate Heat transfer Advanced Multi-domain Partitioned), is based on a discretization of the interface coupling conditions using a generalized Robin (mixed) condition. The weights in the Robin condition are determined from the optimization of a condition derived from a local stability analysis of the coupling scheme. The interface treatment combines ideas from optimized-Schwarz methods for domain-decomposition problems togethermore » with the interface jump conditions and additional compatibility jump conditions derived from the governing equations. For many problems (i.e. for a wide range of material properties, grid-spacings and time-steps) the CHAMP algorithm is stable and second-order accurate using no sub-time-step iterations (i.e. a single implicit solve of the temperature equation in each domain). In extreme cases (e.g. very fine grids with very large time-steps) it may be necessary to perform one or more sub-iterations. Each sub-iteration generally increases the range of stability substantially and thus one sub-iteration is likely sufficient for the vast majority of practical problems. The CHAMP algorithm is developed first for a model problem and analyzed using normal-mode the- ory. The theory provides a mechanism for choosing optimal parameters in the mixed interface condition. A comparison is made to the classical Dirichlet-Neumann (DN) method and, where applicable, to the optimized- Schwarz (OS) domain-decomposition method. For problems with different thermal conductivities and dif- fusivities, the CHAMP algorithm outperforms the DN scheme. For domain-decomposition problems with uniform conductivities and diffusivities, the CHAMP algorithm performs better than the typical OS scheme with one grid-cell overlap. Lastly, the CHAMP scheme is also developed for general curvilinear grids and CHT ex- amples are presented using composite overset grids that confirm the theory and demonstrate the effectiveness of the approach.« less

Application of decomposition techniques to the preliminary design of a transport aircraft

NASA Technical Reports Server (NTRS)

Rogan, J. E.; Kolb, M. A.

1987-01-01

A nonlinear constrained optimization problem describing the preliminary design process for a transport aircraft has been formulated. A multifaceted decomposition of the optimization problem has been made. Flight dynamics, flexible aircraft loads and deformations, and preliminary structural design subproblems appear prominently in the decomposition. The use of design process decomposition for scheduling design projects, a new system integration approach to configuration control, and the application of object-centered programming to a new generation of design tools are discussed.

Parallel Monte Carlo transport modeling in the context of a time-dependent, three-dimensional multi-physics code

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

Procassini, R.J.

1997-12-31

The fine-scale, multi-space resolution that is envisioned for accurate simulations of complex weapons systems in three spatial dimensions implies flop-rate and memory-storage requirements that will only be obtained in the near future through the use of parallel computational techniques. Since the Monte Carlo transport models in these simulations usually stress both of these computational resources, they are prime candidates for parallelization. The MONACO Monte Carlo transport package, which is currently under development at LLNL, will utilize two types of parallelism within the context of a multi-physics design code: decomposition of the spatial domain across processors (spatial parallelism) and distribution ofmore » particles in a given spatial subdomain across additional processors (particle parallelism). This implementation of the package will utilize explicit data communication between domains (message passing). Such a parallel implementation of a Monte Carlo transport model will result in non-deterministic communication patterns. The communication of particles between subdomains during a Monte Carlo time step may require a significant level of effort to achieve a high parallel efficiency.« less

A spatial domain decomposition approach to distributed H ∞ observer design of a linear unstable parabolic distributed parameter system with spatially discrete sensors

NASA Astrophysics Data System (ADS)

Wang, Jun-Wei; Liu, Ya-Qiang; Hu, Yan-Yan; Sun, Chang-Yin

2017-12-01

This paper discusses the design problem of distributed H∞ Luenberger-type partial differential equation (PDE) observer for state estimation of a linear unstable parabolic distributed parameter system (DPS) with external disturbance and measurement disturbance. Both pointwise measurement in space and local piecewise uniform measurement in space are considered; that is, sensors are only active at some specified points or applied at part thereof of the spatial domain. The spatial domain is decomposed into multiple subdomains according to the location of the sensors such that only one sensor is located at each subdomain. By using Lyapunov technique, Wirtinger's inequality at each subdomain, and integration by parts, a Lyapunov-based design of Luenberger-type PDE observer is developed such that the resulting estimation error system is exponentially stable with an H∞ performance constraint, and presented in terms of standard linear matrix inequalities (LMIs). For the case of local piecewise uniform measurement in space, the first mean value theorem for integrals is utilised in the observer design development. Moreover, the problem of optimal H∞ observer design is also addressed in the sense of minimising the attenuation level. Numerical simulation results are presented to show the satisfactory performance of the proposed design method.

On the decomposition of synchronous state mechines using sequence invariant state machines

NASA Technical Reports Server (NTRS)

Hebbalalu, K.; Whitaker, S.; Cameron, K.

1992-01-01

This paper presents a few techniques for the decomposition of Synchronous State Machines of medium to large sizes into smaller component machines. The methods are based on the nature of the transitions and sequences of states in the machine and on the number and variety of inputs to the machine. The results of the decomposition, and of using the Sequence Invariant State Machine (SISM) Design Technique for generating the component machines, include great ease and quickness in the design and implementation processes. Furthermore, there is increased flexibility in making modifications to the original design leading to negligible re-design time.

Pursuing reliable thermal analysis techniques for energetic materials: decomposition kinetics and thermal stability of dihydroxylammonium 5,5'-bistetrazole-1,1'-diolate (TKX-50).

PubMed

Muravyev, Nikita V; Monogarov, Konstantin A; Asachenko, Andrey F; Nechaev, Mikhail S; Ananyev, Ivan V; Fomenkov, Igor V; Kiselev, Vitaly G; Pivkina, Alla N

2016-12-21

Thermal decomposition of a novel promising high-performance explosive dihydroxylammonium 5,5'-bistetrazole-1,1'-diolate (TKX-50) was studied using a number of thermal analysis techniques (thermogravimetry, differential scanning calorimetry, and accelerating rate calorimetry, ARC). To obtain more comprehensive insight into the kinetics and mechanism of TKX-50 decomposition, a variety of complementary thermoanalytical experiments were performed under various conditions. Non-isothermal and isothermal kinetics were obtained at both atmospheric and low (up to 0.3 Torr) pressures. The gas products of thermolysis were detected in situ using IR spectroscopy, and the structure of solid-state decomposition products was determined by X-ray diffraction and scanning electron microscopy. Diammonium 5,5'-bistetrazole-1,1'-diolate (ABTOX) was directly identified to be the most important intermediate of the decomposition process. The important role of bistetrazole diol (BTO) in the mechanism of TKX-50 decomposition was also rationalized by thermolysis experiments with mixtures of TKX-50 and BTO. Several widely used thermoanalytical data processing techniques (Kissinger, isoconversional, formal kinetic approaches, etc.) were independently benchmarked against the ARC data, which are more germane to the real storage and application conditions of energetic materials. Our study revealed that none of the Arrhenius parameters reported before can properly describe the complex two-stage decomposition process of TKX-50. In contrast, we showed the superior performance of the isoconversional methods combined with isothermal measurements, which yielded the most reliable kinetic parameters of TKX-50 thermolysis. In contrast with the existing reports, the thermal stability of TKX-50 was determined in the ARC experiments to be lower than that of hexogen, but close to that of hexanitrohexaazaisowurtzitane (CL-20).

Introducing Network Analysis into Science Education: Methodological Research Examining Secondary School Students' Understanding of "Decomposition"

ERIC Educational Resources Information Center

Schizas, Dimitrios; Katrana, Evagelia; Stamou, George

2013-01-01

In the present study we used the technique of word association tests to assess students' cognitive structures during the learning period. In particular, we tried to investigate what students living near a protected area in Greece (Dadia forest) knew about the phenomenon of decomposition. Decomposition was chosen as a stimulus word because it…

DOMAIN DECOMPOSITION METHOD APPLIED TO A FLOW PROBLEM Norberto C. Vera Guzmán Institute of Geophysics, UNAM

NASA Astrophysics Data System (ADS)

Vera, N. C.; GMMC

2013-05-01

In this paper we present the results of macrohybrid mixed Darcian flow in porous media in a general three-dimensional domain. The global problem is solved as a set of local subproblems which are posed using a domain decomposition method. Unknown fields of local problems, velocity and pressure are approximated using mixed finite elements. For this application, a general three-dimensional domain is considered which is discretized using tetrahedra. The discrete domain is decomposed into subdomains and reformulated the original problem as a set of subproblems, communicated through their interfaces. To solve this set of subproblems, we use finite element mixed and parallel computing. The parallelization of a problem using this methodology can, in principle, to fully exploit a computer equipment and also provides results in less time, two very important elements in modeling. Referencias G.Alduncin and N.Vera-Guzmán Parallel proximal-point algorithms for mixed _nite element models of _ow in the subsurface, Commun. Numer. Meth. Engng 2004; 20:83-104 (DOI: 10.1002/cnm.647) Z. Chen, G.Huan and Y. Ma Computational Methods for Multiphase Flows in Porous Media, SIAM, Society for Industrial and Applied Mathematics, Philadelphia, 2006. A. Quarteroni and A. Valli, Numerical Approximation of Partial Differential Equations, Springer-Verlag, Berlin, 1994. Brezzi F, Fortin M. Mixed and Hybrid Finite Element Methods. Springer: New York, 1991.

Mode Decomposition Methods for Soil Moisture Prediction

NASA Astrophysics Data System (ADS)

Jana, R. B.; Efendiev, Y. R.; Mohanty, B.

2014-12-01

Lack of reliable, well-distributed, long-term datasets for model validation is a bottle-neck for most exercises in soil moisture analysis and prediction. Understanding what factors drive soil hydrological processes at different scales and their variability is very critical to further our ability to model the various components of the hydrologic cycle more accurately. For this, a comprehensive dataset with measurements across scales is very necessary. Intensive fine-resolution sampling of soil moisture over extended periods of time is financially and logistically prohibitive. Installation of a few long term monitoring stations is also expensive, and needs to be situated at critical locations. The concept of Time Stable Locations has been in use for some time now to find locations that reflect the mean values for the soil moisture across the watershed under all wetness conditions. However, the soil moisture variability across the watershed is lost when measuring at only time stable locations. We present here a study using techniques such as Dynamic Mode Decomposition (DMD) and Discrete Empirical Interpolation Method (DEIM) that extends the concept of time stable locations to arrive at locations that provide not simply the average soil moisture values for the watershed, but also those that can help re-capture the dynamics across all locations in the watershed. As with the time stability, the initial analysis is dependent on an intensive sampling history. The DMD/DEIM method is an application of model reduction techniques for non-linearly related measurements. Using this technique, we are able to determine the number of sampling points that would be required for a given accuracy of prediction across the watershed, and the location of those points. Locations with higher energetics in the basis domain are chosen first. We present case studies across watersheds in the US and India. The technique can be applied to other hydro-climates easily.

Efficient morse decompositions of vector fields.

PubMed

Chen, Guoning; Mischaikow, Konstantin; Laramee, Robert S; Zhang, Eugene

2008-01-01

Existing topology-based vector field analysis techniques rely on the ability to extract the individual trajectories such as fixed points, periodic orbits, and separatrices that are sensitive to noise and errors introduced by simulation and interpolation. This can make such vector field analysis unsuitable for rigorous interpretations. We advocate the use of Morse decompositions, which are robust with respect to perturbations, to encode the topological structures of a vector field in the form of a directed graph, called a Morse connection graph (MCG). While an MCG exists for every vector field, it need not be unique. Previous techniques for computing MCG's, while fast, are overly conservative and usually results in MCG's that are too coarse to be useful for the applications. To address this issue, we present a new technique for performing Morse decomposition based on the concept of tau-maps, which typically provides finer MCG's than existing techniques. Furthermore, the choice of tau provides a natural tradeoff between the fineness of the MCG's and the computational costs. We provide efficient implementations of Morse decomposition based on tau-maps, which include the use of forward and backward mapping techniques and an adaptive approach in constructing better approximations of the images of the triangles in the meshes used for simulation.. Furthermore, we propose the use of spatial tau-maps in addition to the original temporal tau-maps. These techniques provide additional trade-offs between the quality of the MCGs and the speed of computation. We demonstrate the utility of our technique with various examples in the plane and on surfaces including engine simulation data sets.

DVS-SOFTWARE: An Effective Tool for Applying Highly Parallelized Hardware To Computational Geophysics

NASA Astrophysics Data System (ADS)

Herrera, I.; Herrera, G. S.

2015-12-01

Most geophysical systems are macroscopic physical systems. The behavior prediction of such systems is carried out by means of computational models whose basic models are partial differential equations (PDEs) [1]. Due to the enormous size of the discretized version of such PDEs it is necessary to apply highly parallelized super-computers. For them, at present, the most efficient software is based on non-overlapping domain decomposition methods (DDM). However, a limiting feature of the present state-of-the-art techniques is due to the kind of discretizations used in them. Recently, I. Herrera and co-workers using 'non-overlapping discretizations' have produced the DVS-Software which overcomes this limitation [2]. The DVS-software can be applied to a great variety of geophysical problems and achieves very high parallel efficiencies (90%, or so [3]). It is therefore very suitable for effectively applying the most advanced parallel supercomputers available at present. In a parallel talk, in this AGU Fall Meeting, Graciela Herrera Z. will present how this software is being applied to advance MOD-FLOW. Key Words: Parallel Software for Geophysics, High Performance Computing, HPC, Parallel Computing, Domain Decomposition Methods (DDM)REFERENCES [1]. Herrera Ismael and George F. Pinder, Mathematical Modelling in Science and Engineering: An axiomatic approach", John Wiley, 243p., 2012. [2]. Herrera, I., de la Cruz L.M. and Rosas-Medina A. "Non Overlapping Discretization Methods for Partial, Differential Equations". NUMER METH PART D E, 30: 1427-1454, 2014, DOI 10.1002/num 21852. (Open source) [3]. Herrera, I., & Contreras Iván "An Innovative Tool for Effectively Applying Highly Parallelized Software To Problems of Elasticity". Geofísica Internacional, 2015 (In press)

Progressive Precision Surface Design

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

Duchaineau, M; Joy, KJ

2002-01-11

We introduce a novel wavelet decomposition algorithm that makes a number of powerful new surface design operations practical. Wavelets, and hierarchical representations generally, have held promise to facilitate a variety of design tasks in a unified way by approximating results very precisely, thus avoiding a proliferation of undergirding mathematical representations. However, traditional wavelet decomposition is defined from fine to coarse resolution, thus limiting its efficiency for highly precise surface manipulation when attempting to create new non-local editing methods. Our key contribution is the progressive wavelet decomposition algorithm, a general-purpose coarse-to-fine method for hierarchical fitting, based in this paper on anmore » underlying multiresolution representation called dyadic splines. The algorithm requests input via a generic interval query mechanism, allowing a wide variety of non-local operations to be quickly implemented. The algorithm performs work proportionate to the tiny compressed output size, rather than to some arbitrarily high resolution that would otherwise be required, thus increasing performance by several orders of magnitude. We describe several design operations that are made tractable because of the progressive decomposition. Free-form pasting is a generalization of the traditional control-mesh edit, but for which the shape of the change is completely general and where the shape can be placed using a free-form deformation within the surface domain. Smoothing and roughening operations are enhanced so that an arbitrary loop in the domain specifies the area of effect. Finally, the sculpting effect of moving a tool shape along a path is simulated.« less

Spatial, temporal, and hybrid decompositions for large-scale vehicle routing with time windows

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

Bent, Russell W

This paper studies the use of decomposition techniques to quickly find high-quality solutions to large-scale vehicle routing problems with time windows. It considers an adaptive decomposition scheme which iteratively decouples a routing problem based on the current solution. Earlier work considered vehicle-based decompositions that partitions the vehicles across the subproblems. The subproblems can then be optimized independently and merged easily. This paper argues that vehicle-based decompositions, although very effective on various problem classes also have limitations. In particular, they do not accommodate temporal decompositions and may produce spatial decompositions that are not focused enough. This paper then proposes customer-based decompositionsmore » which generalize vehicle-based decouplings and allows for focused spatial and temporal decompositions. Experimental results on class R2 of the extended Solomon benchmarks demonstrates the benefits of the customer-based adaptive decomposition scheme and its spatial, temporal, and hybrid instantiations. In particular, they show that customer-based decompositions bring significant benefits over large neighborhood search in contrast to vehicle-based decompositions.« less

A general framework of noise suppression in material decomposition for dual-energy CT

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

Petrongolo, Michael; Dong, Xue; Zhu, Lei, E-mail: leizhu@gatech.edu

Purpose: As a general problem of dual-energy CT (DECT), noise amplification in material decomposition severely reduces the signal-to-noise ratio on the decomposed images compared to that on the original CT images. In this work, the authors propose a general framework of noise suppression in material decomposition for DECT. The method is based on an iterative algorithm recently developed in their group for image-domain decomposition of DECT, with an extension to include nonlinear decomposition models. The generalized framework of iterative DECT decomposition enables beam-hardening correction with simultaneous noise suppression, which improves the clinical benefits of DECT. Methods: The authors propose tomore » suppress noise on the decomposed images of DECT using convex optimization, which is formulated in the form of least-squares estimation with smoothness regularization. Based on the design principles of a best linear unbiased estimator, the authors include the inverse of the estimated variance–covariance matrix of the decomposed images as the penalty weight in the least-squares term. Analytical formulas are derived to compute the variance–covariance matrix for decomposed images with general-form numerical or analytical decomposition. As a demonstration, the authors implement the proposed algorithm on phantom data using an empirical polynomial function of decomposition measured on a calibration scan. The polynomial coefficients are determined from the projection data acquired on a wedge phantom, and the signal decomposition is performed in the projection domain. Results: On the Catphan{sup ®}600 phantom, the proposed noise suppression method reduces the average noise standard deviation of basis material images by one to two orders of magnitude, with a superior performance on spatial resolution as shown in comparisons of line-pair images and modulation transfer function measurements. On the synthesized monoenergetic CT images, the noise standard deviation is reduced by a factor of 2–3. By using nonlinear decomposition on projections, the authors’ method effectively suppresses the streaking artifacts of beam hardening and obtains more uniform images than their previous approach based on a linear model. Similar performance of noise suppression is observed in the results of an anthropomorphic head phantom and a pediatric chest phantom generated by the proposed method. With beam-hardening correction enabled by their approach, the image spatial nonuniformity on the head phantom is reduced from around 10% on the original CT images to 4.9% on the synthesized monoenergetic CT image. On the pediatric chest phantom, their method suppresses image noise standard deviation by a factor of around 7.5, and compared with linear decomposition, it reduces the estimation error of electron densities from 33.3% to 8.6%. Conclusions: The authors propose a general framework of noise suppression in material decomposition for DECT. Phantom studies have shown the proposed method improves the image uniformity and the accuracy of electron density measurements by effective beam-hardening correction and reduces noise level without noticeable resolution loss.« less

How localized is ``local?'' Efficiency vs. accuracy of O(N) domain decomposition in local orbital based all-electron electronic structure theory

NASA Astrophysics Data System (ADS)

Havu, Vile; Blum, Volker; Scheffler, Matthias

2007-03-01

Numeric atom-centered local orbitals (NAO) are efficient basis sets for all-electron electronic structure theory. The locality of NAO's can be exploited to render (in principle) all operations of the self-consistency cycle O(N). This is straightforward for 3D integrals using domain decomposition into spatially close subsets of integration points, enabling critical computational savings that are effective from ˜tens of atoms (no significant overhead for smaller systems) and make large systems (100s of atoms) computationally feasible. Using a new all-electron NAO-based code,^1 we investigate the quantitative impact of exploiting this locality on two distinct classes of systems: Large light-element molecules [Alanine-based polypeptide chains (Ala)n], and compact transition metal clusters. Strict NAO locality is achieved by imposing a cutoff potential with an onset radius rc, and exploited by appropriately shaped integration domains (subsets of integration points). Conventional tight rc<= 3å have no measurable accuracy impact in (Ala)n, but introduce inaccuracies of 20-30 meV/atom in Cun. The domain shape impacts the computational effort by only 10-20 % for reasonable rc. ^1 V. Blum, R. Gehrke, P. Havu, V. Havu, M. Scheffler, The FHI Ab Initio Molecular Simulations (aims) Project, Fritz-Haber-Institut, Berlin (2006).

Self-force via m-mode regularization and 2+1D evolution. II. Scalar-field implementation on Kerr spacetime

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

Dolan, Sam R.; Barack, Leor; Wardell, Barry

2011-10-15

This is the second in a series of papers aimed at developing a practical time-domain method for self-force calculations in Kerr spacetime. The key elements of the method are (i) removal of a singular part of the perturbation field with a suitable analytic 'puncture' based on the Detweiler-Whiting decomposition, (ii) decomposition of the perturbation equations in azimuthal (m-)modes, taking advantage of the axial symmetry of the Kerr background, (iii) numerical evolution of the individual m-modes in 2+1 dimensions with a finite-difference scheme, and (iv) reconstruction of the physical self-force from the mode sum. Here we report an implementation of themore » method to compute the scalar-field self-force along circular equatorial geodesic orbits around a Kerr black hole. This constitutes a first time-domain computation of the self-force in Kerr geometry. Our time-domain code reproduces the results of a recent frequency-domain calculation by Warburton and Barack, but has the added advantage of being readily adaptable to include the backreaction from the self-force in a self-consistent manner. In a forthcoming paper--the third in the series--we apply our method to the gravitational self-force (in the Lorenz gauge).« less

Characteristic-eddy decomposition of turbulence in a channel

NASA Technical Reports Server (NTRS)

Moin, Parviz; Moser, Robert D.

1989-01-01

Lumley's proper orthogonal decomposition technique is applied to the turbulent flow in a channel. Coherent structures are extracted by decomposing the velocity field into characteristic eddies with random coefficients. A generalization of the shot-noise expansion is used to determine the characteristic eddies in homogeneous spatial directions. Three different techniques are used to determine the phases of the Fourier coefficients in the expansion: (1) one based on the bispectrum, (2) a spatial compactness requirement, and (3) a functional continuity argument. Similar results are found from each of these techniques.

Characteristic eddy decomposition of turbulence in a channel

NASA Technical Reports Server (NTRS)

Moin, Parviz; Moser, Robert D.

1991-01-01

The proper orthogonal decomposition technique (Lumley's decomposition) is applied to the turbulent flow in a channel to extract coherent structures by decomposing the velocity field into characteristic eddies with random coefficients. In the homogeneous spatial directions, a generaliztion of the shot-noise expansion is used to determine the characteristic eddies. In this expansion, the Fourier coefficients of the characteristic eddy cannot be obtained from the second-order statistics. Three different techniques are used to determine the phases of these coefficients. They are based on: (1) the bispectrum, (2) a spatial compactness requirement, and (3) a functional continuity argument. Results from these three techniques are found to be similar in most respects. The implications of these techniques and the shot-noise expansion are discussed. The dominant eddy is found to contribute as much as 76 percent to the turbulent kinetic energy. In both 2D and 3D, the characteristic eddies consist of an ejection region straddled by streamwise vortices that leave the wall in the very short streamwise distance of about 100 wall units.

A compositional approach to building applications in a computational environment

NASA Astrophysics Data System (ADS)

Roslovtsev, V. V.; Shumsky, L. D.; Wolfengagen, V. E.

2014-04-01

The paper presents an approach to creating an applicative computational environment to feature computational processes and data decomposition, and a compositional approach to application building. The approach in question is based on the notion of combinator - both in systems with variable binding (such as λ-calculi) and those allowing programming without variables (combinatory logic style). We present a computation decomposition technique based on objects' structural decomposition, with the focus on computation decomposition. The computational environment's architecture is based on a network with nodes playing several roles simultaneously.

An Optimal Strategy for Accurate Bulge-to-disk Decomposition of Disk Galaxies

NASA Astrophysics Data System (ADS)

Gao, Hua; Ho, Luis C.

2017-08-01

The development of two-dimensional (2D) bulge-to-disk decomposition techniques has shown their advantages over traditional one-dimensional (1D) techniques, especially for galaxies with non-axisymmetric features. However, the full potential of 2D techniques has yet to be fully exploited. Secondary morphological features in nearby disk galaxies, such as bars, lenses, rings, disk breaks, and spiral arms, are seldom accounted for in 2D image decompositions, even though some image-fitting codes, such as GALFIT, are capable of handling them. We present detailed, 2D multi-model and multi-component decomposition of high-quality R-band images of a representative sample of nearby disk galaxies selected from the Carnegie-Irvine Galaxy Survey, using the latest version of GALFIT. The sample consists of five barred and five unbarred galaxies, spanning Hubble types from S0 to Sc. Traditional 1D decomposition is also presented for comparison. In detailed case studies of the 10 galaxies, we successfully model the secondary morphological features. Through a comparison of best-fit parameters obtained from different input surface brightness models, we identify morphological features that significantly impact bulge measurements. We show that nuclear and inner lenses/rings and disk breaks must be properly taken into account to obtain accurate bulge parameters, whereas outer lenses/rings and spiral arms have a negligible effect. We provide an optimal strategy to measure bulge parameters of typical disk galaxies, as well as prescriptions to estimate realistic uncertainties of them, which will benefit subsequent decomposition of a larger galaxy sample.

An Optimal Strategy for Accurate Bulge-to-disk Decomposition of Disk Galaxies

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

Gao Hua; Ho, Luis C.

The development of two-dimensional (2D) bulge-to-disk decomposition techniques has shown their advantages over traditional one-dimensional (1D) techniques, especially for galaxies with non-axisymmetric features. However, the full potential of 2D techniques has yet to be fully exploited. Secondary morphological features in nearby disk galaxies, such as bars, lenses, rings, disk breaks, and spiral arms, are seldom accounted for in 2D image decompositions, even though some image-fitting codes, such as GALFIT, are capable of handling them. We present detailed, 2D multi-model and multi-component decomposition of high-quality R -band images of a representative sample of nearby disk galaxies selected from the Carnegie-Irvine Galaxymore » Survey, using the latest version of GALFIT. The sample consists of five barred and five unbarred galaxies, spanning Hubble types from S0 to Sc. Traditional 1D decomposition is also presented for comparison. In detailed case studies of the 10 galaxies, we successfully model the secondary morphological features. Through a comparison of best-fit parameters obtained from different input surface brightness models, we identify morphological features that significantly impact bulge measurements. We show that nuclear and inner lenses/rings and disk breaks must be properly taken into account to obtain accurate bulge parameters, whereas outer lenses/rings and spiral arms have a negligible effect. We provide an optimal strategy to measure bulge parameters of typical disk galaxies, as well as prescriptions to estimate realistic uncertainties of them, which will benefit subsequent decomposition of a larger galaxy sample.« less

Multitrace/singletrace formulations and Domain Decomposition Methods for the solution of Helmholtz transmission problems for bounded composite scatterers

NASA Astrophysics Data System (ADS)

Jerez-Hanckes, Carlos; Pérez-Arancibia, Carlos; Turc, Catalin

2017-12-01

We present Nyström discretizations of multitrace/singletrace formulations and non-overlapping Domain Decomposition Methods (DDM) for the solution of Helmholtz transmission problems for bounded composite scatterers with piecewise constant material properties. We investigate the performance of DDM with both classical Robin and optimized transmission boundary conditions. The optimized transmission boundary conditions incorporate square root Fourier multiplier approximations of Dirichlet to Neumann operators. While the multitrace/singletrace formulations as well as the DDM that use classical Robin transmission conditions are not particularly well suited for Krylov subspace iterative solutions of high-contrast high-frequency Helmholtz transmission problems, we provide ample numerical evidence that DDM with optimized transmission conditions constitute efficient computational alternatives for these type of applications. In the case of large numbers of subdomains with different material properties, we show that the associated DDM linear system can be efficiently solved via hierarchical Schur complements elimination.

Basis adaptation and domain decomposition for steady partial differential equations with random coefficients

DOE PAGES

Tipireddy, R.; Stinis, P.; Tartakovsky, A. M.

2017-09-04

In this paper, we present a novel approach for solving steady-state stochastic partial differential equations (PDEs) with high-dimensional random parameter space. The proposed approach combines spatial domain decomposition with basis adaptation for each subdomain. The basis adaptation is used to address the curse of dimensionality by constructing an accurate low-dimensional representation of the stochastic PDE solution (probability density function and/or its leading statistical moments) in each subdomain. Restricting the basis adaptation to a specific subdomain affords finding a locally accurate solution. Then, the solutions from all of the subdomains are stitched together to provide a global solution. We support ourmore » construction with numerical experiments for a steady-state diffusion equation with a random spatially dependent coefficient. Lastly, our results show that highly accurate global solutions can be obtained with significantly reduced computational costs.« less

A resilient domain decomposition polynomial chaos solver for uncertain elliptic PDEs

NASA Astrophysics Data System (ADS)

Mycek, Paul; Contreras, Andres; Le Maître, Olivier; Sargsyan, Khachik; Rizzi, Francesco; Morris, Karla; Safta, Cosmin; Debusschere, Bert; Knio, Omar

2017-07-01

A resilient method is developed for the solution of uncertain elliptic PDEs on extreme scale platforms. The method is based on a hybrid domain decomposition, polynomial chaos (PC) framework that is designed to address soft faults. Specifically, parallel and independent solves of multiple deterministic local problems are used to define PC representations of local Dirichlet boundary-to-boundary maps that are used to reconstruct the global solution. A LAD-lasso type regression is developed for this purpose. The performance of the resulting algorithm is tested on an elliptic equation with an uncertain diffusivity field. Different test cases are considered in order to analyze the impacts of correlation structure of the uncertain diffusivity field, the stochastic resolution, as well as the probability of soft faults. In particular, the computations demonstrate that, provided sufficiently many samples are generated, the method effectively overcomes the occurrence of soft faults.

Basis adaptation and domain decomposition for steady-state partial differential equations with random coefficients

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

Tipireddy, R.; Stinis, P.; Tartakovsky, A. M.

We present a novel approach for solving steady-state stochastic partial differential equations (PDEs) with high-dimensional random parameter space. The proposed approach combines spatial domain decomposition with basis adaptation for each subdomain. The basis adaptation is used to address the curse of dimensionality by constructing an accurate low-dimensional representation of the stochastic PDE solution (probability density function and/or its leading statistical moments) in each subdomain. Restricting the basis adaptation to a specific subdomain affords finding a locally accurate solution. Then, the solutions from all of the subdomains are stitched together to provide a global solution. We support our construction with numericalmore » experiments for a steady-state diffusion equation with a random spatially dependent coefficient. Our results show that highly accurate global solutions can be obtained with significantly reduced computational costs.« less

A time domain frequency-selective multivariate Granger causality approach.

PubMed

Leistritz, Lutz; Witte, Herbert

2016-08-01

The investigation of effective connectivity is one of the major topics in computational neuroscience to understand the interaction between spatially distributed neuronal units of the brain. Thus, a wide variety of methods has been developed during the last decades to investigate functional and effective connectivity in multivariate systems. Their spectrum ranges from model-based to model-free approaches with a clear separation into time and frequency range methods. We present in this simulation study a novel time domain approach based on Granger's principle of predictability, which allows frequency-selective considerations of directed interactions. It is based on a comparison of prediction errors of multivariate autoregressive models fitted to systematically modified time series. These modifications are based on signal decompositions, which enable a targeted cancellation of specific signal components with specific spectral properties. Depending on the embedded signal decomposition method, a frequency-selective or data-driven signal-adaptive Granger Causality Index may be derived.

A 3D staggered-grid finite difference scheme for poroelastic wave equation

NASA Astrophysics Data System (ADS)

Zhang, Yijie; Gao, Jinghuai

2014-10-01

Three dimensional numerical modeling has been a viable tool for understanding wave propagation in real media. The poroelastic media can better describe the phenomena of hydrocarbon reservoirs than acoustic and elastic media. However, the numerical modeling in 3D poroelastic media demands significantly more computational capacity, including both computational time and memory. In this paper, we present a 3D poroelastic staggered-grid finite difference (SFD) scheme. During the procedure, parallel computing is implemented to reduce the computational time. Parallelization is based on domain decomposition, and communication between processors is performed using message passing interface (MPI). Parallel analysis shows that the parallelized SFD scheme significantly improves the simulation efficiency and 3D decomposition in domain is the most efficient. We also analyze the numerical dispersion and stability condition of the 3D poroelastic SFD method. Numerical results show that the 3D numerical simulation can provide a real description of wave propagation.

Coupling lattice Boltzmann and continuum equations for flow and reactive transport in porous media.

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

Coon, Ethan; Porter, Mark L.; Kang, Qinjun

2012-06-18

In spatially and temporally localized instances, capturing sub-reservoir scale information is necessary. Capturing sub-reservoir scale information everywhere is neither necessary, nor computationally possible. The lattice Boltzmann Method for solving pore-scale systems. At the pore-scale, LBM provides an extremely scalable, efficient way of solving Navier-Stokes equations on complex geometries. Coupling pore-scale and continuum scale systems via domain decomposition. By leveraging the interpolations implied by pore-scale and continuum scale discretizations, overlapping Schwartz domain decomposition is used to ensure continuity of pressure and flux. This approach is demonstrated on a fractured medium, in which Navier-Stokes equations are solved within the fracture while Darcy'smore » equation is solved away from the fracture Coupling reactive transport to pore-scale flow simulators allows hybrid approaches to be extended to solve multi-scale reactive transport.« less

A statistical forecast model using the time-scale decomposition technique to predict rainfall during flood period over the middle and lower reaches of the Yangtze River Valley

NASA Astrophysics Data System (ADS)

Hu, Yijia; Zhong, Zhong; Zhu, Yimin; Ha, Yao

2018-04-01

In this paper, a statistical forecast model using the time-scale decomposition method is established to do the seasonal prediction of the rainfall during flood period (FPR) over the middle and lower reaches of the Yangtze River Valley (MLYRV). This method decomposites the rainfall over the MLYRV into three time-scale components, namely, the interannual component with the period less than 8 years, the interdecadal component with the period from 8 to 30 years, and the interdecadal component with the period larger than 30 years. Then, the predictors are selected for the three time-scale components of FPR through the correlation analysis. At last, a statistical forecast model is established using the multiple linear regression technique to predict the three time-scale components of the FPR, respectively. The results show that this forecast model can capture the interannual and interdecadal variation of FPR. The hindcast of FPR during 14 years from 2001 to 2014 shows that the FPR can be predicted successfully in 11 out of the 14 years. This forecast model performs better than the model using traditional scheme without time-scale decomposition. Therefore, the statistical forecast model using the time-scale decomposition technique has good skills and application value in the operational prediction of FPR over the MLYRV.

Identification of particle-laden flow features from wavelet decomposition

NASA Astrophysics Data System (ADS)

Jackson, A.; Turnbull, B.

2017-12-01

A wavelet decomposition based technique is applied to air pressure data obtained from laboratory-scale powder snow avalanches. This technique is shown to be a powerful tool for identifying both repeatable and chaotic features at any frequency within the signal. Additionally, this technique is demonstrated to be a robust method for the removal of noise from the signal as well as being capable of removing other contaminants from the signal. Whilst powder snow avalanches are the focus of the experiments analysed here, the features identified can provide insight to other particle-laden gravity currents and the technique described is applicable to a wide variety of experimental signals.

High and low frequency unfolded partial least squares regression based on empirical mode decomposition for quantitative analysis of fuel oil samples.

PubMed

Bian, Xihui; Li, Shujuan; Lin, Ligang; Tan, Xiaoyao; Fan, Qingjie; Li, Ming

2016-06-21

Accurate prediction of the model is fundamental to the successful analysis of complex samples. To utilize abundant information embedded over frequency and time domains, a novel regression model is presented for quantitative analysis of hydrocarbon contents in the fuel oil samples. The proposed method named as high and low frequency unfolded PLSR (HLUPLSR), which integrates empirical mode decomposition (EMD) and unfolded strategy with partial least squares regression (PLSR). In the proposed method, the original signals are firstly decomposed into a finite number of intrinsic mode functions (IMFs) and a residue by EMD. Secondly, the former high frequency IMFs are summed as a high frequency matrix and the latter IMFs and residue are summed as a low frequency matrix. Finally, the two matrices are unfolded to an extended matrix in variable dimension, and then the PLSR model is built between the extended matrix and the target values. Coupled with Ultraviolet (UV) spectroscopy, HLUPLSR has been applied to determine hydrocarbon contents of light gas oil and diesel fuels samples. Comparing with single PLSR and other signal processing techniques, the proposed method shows superiority in prediction ability and better model interpretation. Therefore, HLUPLSR method provides a promising tool for quantitative analysis of complex samples. Copyright © 2016 Elsevier B.V. All rights reserved.

Techniques for Reaeration of Hydropower Releases.

DTIC Science & Technology

1983-02-01

peak production from air induction through the baffle ring. The other aeration technique at Norris required modifications to the vacuum-breaker system...of Gas Tracers for Reaeration," Jour. Environ. Div., Proc. Amer. Soc. Civil Engr., 104, 215, April. Rathbun, R. E., 1979, "Estimating the Gas and Dye ...or dissolved in the water, and--last but not least--by the decomposition of bottom mud and by oxidation of the decomposition products stirred up out

Tomographic reconstruction of tokamak plasma light emission using wavelet-vaguelette decomposition

NASA Astrophysics Data System (ADS)

Schneider, Kai; Nguyen van Yen, Romain; Fedorczak, Nicolas; Brochard, Frederic; Bonhomme, Gerard; Farge, Marie; Monier-Garbet, Pascale

2012-10-01

Images acquired by cameras installed in tokamaks are difficult to interpret because the three-dimensional structure of the plasma is flattened in a non-trivial way. Nevertheless, taking advantage of the slow variation of the fluctuations along magnetic field lines, the optical transformation may be approximated by a generalized Abel transform, for which we proposed in Nguyen van yen et al., Nucl. Fus., 52 (2012) 013005, an inversion technique based on the wavelet-vaguelette decomposition. After validation of the new method using an academic test case and numerical data obtained with the Tokam 2D code, we present an application to an experimental movie obtained in the tokamak Tore Supra. A comparison with a classical regularization technique for ill-posed inverse problems, the singular value decomposition, allows us to assess the efficiency. The superiority of the wavelet-vaguelette technique is reflected in preserving local features, such as blobs and fronts, in the denoised emissivity map.

Tomographic reconstruction of tokamak plasma light emission from single image using wavelet-vaguelette decomposition

NASA Astrophysics Data System (ADS)

Nguyen van yen, R.; Fedorczak, N.; Brochard, F.; Bonhomme, G.; Schneider, K.; Farge, M.; Monier-Garbet, P.

2012-01-01

Images acquired by cameras installed in tokamaks are difficult to interpret because the three-dimensional structure of the plasma is flattened in a non-trivial way. Nevertheless, taking advantage of the slow variation of the fluctuations along magnetic field lines, the optical transformation may be approximated by a generalized Abel transform, for which we propose an inversion technique based on the wavelet-vaguelette decomposition. After validation of the new method using an academic test case and numerical data obtained with the Tokam 2D code, we present an application to an experimental movie obtained in the tokamak Tore Supra. A comparison with a classical regularization technique for ill-posed inverse problems, the singular value decomposition, allows us to assess the efficiency. The superiority of the wavelet-vaguelette technique is reflected in preserving local features, such as blobs and fronts, in the denoised emissivity map.

Kinematics of reflections in subsurface offset and angle-domain image gathers

NASA Astrophysics Data System (ADS)

Dafni, Raanan; Symes, William W.

2018-05-01

Seismic migration in the angle-domain generates multiple images of the earth's interior in which reflection takes place at different scattering-angles. Mechanically, the angle-dependent reflection is restricted to happen instantaneously and at a fixed point in space: Incident wave hits a discontinuity in the subsurface media and instantly generates a scattered wave at the same common point of interaction. Alternatively, the angle-domain image may be associated with space-shift (regarded as subsurface offset) extended migration that artificially splits the reflection geometry. Meaning that, incident and scattered waves interact at some offset distance. The geometric differences between the two approaches amount to a contradictory angle-domain behaviour, and unlike kinematic description. We present a phase space depiction of migration methods extended by the peculiar subsurface offset split and stress its profound dissimilarity. In spite of being in radical contradiction with the general physics, the subsurface offset reveals a link to some valuable angle-domain quantities, via post-migration transformations. The angle quantities are indicated by the direction normal to the subsurface offset extended image. They specifically define the local dip and scattering angles if the velocity at the split reflection coordinates is the same for incident and scattered wave pairs. Otherwise, the reflector normal is not a bisector of the opening angle, but of the corresponding slowness vectors. This evidence, together with the distinguished geometry configuration, fundamentally differentiates the angle-domain decomposition based on the subsurface offset split from the conventional decomposition at a common reflection point. An asymptotic simulation of angle-domain moveout curves in layered media exposes the notion of split versus common reflection point geometry. Traveltime inversion methods that involve the subsurface offset extended migration must accommodate the split geometry in the inversion scheme for a robust and successful convergence at the optimal velocity model.

Analysis of Self-Excited Combustion Instabilities Using Decomposition Techniques

DTIC Science & Technology

2016-07-05

are evaluated for the study of self-excited longitudinal combustion instabilities in laboratory-scaled single-element gas turbine and rocket...Air Force Base, California 93524 DOI: 10.2514/1.J054557 Proper orthogonal decomposition and dynamic mode decomposition are evaluated for the study of...instabilities. In addition, we also evaluate the capabilities of the methods to deal with data sets of different spatial extents and temporal resolution

RIO: a new computational framework for accurate initial data of binary black holes

NASA Astrophysics Data System (ADS)

Barreto, W.; Clemente, P. C. M.; de Oliveira, H. P.; Rodriguez-Mueller, B.

2018-06-01

We present a computational framework ( Rio) in the ADM 3+1 approach for numerical relativity. This work enables us to carry out high resolution calculations for initial data of two arbitrary black holes. We use the transverse conformal treatment, the Bowen-York and the puncture methods. For the numerical solution of the Hamiltonian constraint we use the domain decomposition and the spectral decomposition of Galerkin-Collocation. The nonlinear numerical code solves the set of equations for the spectral modes using the standard Newton-Raphson method, LU decomposition and Gaussian quadratures. We show the convergence of the Rio code. This code allows for easy deployment of large calculations. We show how the spin of one of the black holes is manifest in the conformal factor.

Understanding neurodynamical systems via Fuzzy Symbolic Dynamics.

PubMed

Dobosz, Krzysztof; Duch, Włodzisław

2010-05-01

Neurodynamical systems are characterized by a large number of signal streams, measuring activity of individual neurons, local field potentials, aggregated electrical (EEG) or magnetic potentials (MEG), oxygen use (fMRI) or activity of simulated neurons. Various basis set decomposition techniques are used to analyze such signals, trying to discover components that carry meaningful information, but these techniques tell us little about the global activity of the whole system. A novel technique called Fuzzy Symbolic Dynamics (FSD) is introduced to help in understanding of the multidimensional dynamical system's behavior. It is based on a fuzzy partitioning of the signal space that defines a non-linear mapping of the system's trajectory to the low-dimensional space of membership function activations. This allows for visualization of the trajectory showing various aspects of observed signals that may be difficult to discover looking at individual components, or to notice otherwise. FSD mapping can be applied to raw signals, transformed signals (for example, ICA components), or to signals defined in the time-frequency domain. To illustrate the method two FSD visualizations are presented: a model system with artificial radial oscillatory sources, and the output layer (50 neurons) of Respiratory Rhythm Generator (RRG) composed of 300 spiking neurons. 2009 Elsevier Ltd. All rights reserved.

Nonlinear QR code based optical image encryption using spiral phase transform, equal modulus decomposition and singular value decomposition

NASA Astrophysics Data System (ADS)

Kumar, Ravi; Bhaduri, Basanta; Nishchal, Naveen K.

2018-01-01

In this study, we propose a quick response (QR) code based nonlinear optical image encryption technique using spiral phase transform (SPT), equal modulus decomposition (EMD) and singular value decomposition (SVD). First, the primary image is converted into a QR code and then multiplied with a spiral phase mask (SPM). Next, the product is spiral phase transformed with particular spiral phase function, and further, the EMD is performed on the output of SPT, which results into two complex images, Z 1 and Z 2. Among these, Z 1 is further Fresnel propagated with distance d, and Z 2 is reserved as a decryption key. Afterwards, SVD is performed on Fresnel propagated output to get three decomposed matrices i.e. one diagonal matrix and two unitary matrices. The two unitary matrices are modulated with two different SPMs and then, the inverse SVD is performed using the diagonal matrix and modulated unitary matrices to get the final encrypted image. Numerical simulation results confirm the validity and effectiveness of the proposed technique. The proposed technique is robust against noise attack, specific attack, and brutal force attack. Simulation results are presented in support of the proposed idea.

Method of assessing the state of a rolling bearing based on the relative compensation distance of multiple-domain features and locally linear embedding

NASA Astrophysics Data System (ADS)

Kang, Shouqiang; Ma, Danyang; Wang, Yujing; Lan, Chaofeng; Chen, Qingguo; Mikulovich, V. I.

2017-03-01

To effectively assess different fault locations and different degrees of performance degradation of a rolling bearing with a unified assessment index, a novel state assessment method based on the relative compensation distance of multiple-domain features and locally linear embedding is proposed. First, for a single-sample signal, time-domain and frequency-domain indexes can be calculated for the original vibration signal and each sensitive intrinsic mode function obtained by improved ensemble empirical mode decomposition, and the singular values of the sensitive intrinsic mode function matrix can be extracted by singular value decomposition to construct a high-dimensional hybrid-domain feature vector. Second, a feature matrix can be constructed by arranging each feature vector of multiple samples, the dimensions of each row vector of the feature matrix can be reduced by the locally linear embedding algorithm, and the compensation distance of each fault state of the rolling bearing can be calculated using the support vector machine. Finally, the relative distance between different fault locations and different degrees of performance degradation and the normal-state optimal classification surface can be compensated, and on the basis of the proposed relative compensation distance, the assessment model can be constructed and an assessment curve drawn. Experimental results show that the proposed method can effectively assess different fault locations and different degrees of performance degradation of the rolling bearing under certain conditions.

Application of Conjugate Gradient methods to tidal simulation

USGS Publications Warehouse

Barragy, E.; Carey, G.F.; Walters, R.A.

1993-01-01

A harmonic decomposition technique is applied to the shallow water equations to yield a complex, nonsymmetric, nonlinear, Helmholtz type problem for the sea surface and an accompanying complex, nonlinear diagonal problem for the velocities. The equation for the sea surface is linearized using successive approximation and then discretized with linear, triangular finite elements. The study focuses on applying iterative methods to solve the resulting complex linear systems. The comparative evaluation includes both standard iterative methods for the real subsystems and complex versions of the well known Bi-Conjugate Gradient and Bi-Conjugate Gradient Squared methods. Several Incomplete LU type preconditioners are discussed, and the effects of node ordering, rejection strategy, domain geometry and Coriolis parameter (affecting asymmetry) are investigated. Implementation details for the complex case are discussed. Performance studies are presented and comparisons made with a frontal solver. ?? 1993.

A comparison of reduced-order modelling techniques for application in hyperthermia control and estimation.

PubMed

Bailey, E A; Dutton, A W; Mattingly, M; Devasia, S; Roemer, R B

1998-01-01

Reduced-order modelling techniques can make important contributions in the control and state estimation of large systems. In hyperthermia, reduced-order modelling can provide a useful tool by which a large thermal model can be reduced to the most significant subset of its full-order modes, making real-time control and estimation possible. Two such reduction methods, one based on modal decomposition and the other on balanced realization, are compared in the context of simulated hyperthermia heat transfer problems. The results show that the modal decomposition reduction method has three significant advantages over that of balanced realization. First, modal decomposition reduced models result in less error, when compared to the full-order model, than balanced realization reduced models of similar order in problems with low or moderate advective heat transfer. Second, because the balanced realization based methods require a priori knowledge of the sensor and actuator placements, the reduced-order model is not robust to changes in sensor or actuator locations, a limitation not present in modal decomposition. Third, the modal decomposition transformation is less demanding computationally. On the other hand, in thermal problems dominated by advective heat transfer, numerical instabilities make modal decomposition based reduction problematic. Modal decomposition methods are therefore recommended for reduction of models in which advection is not dominant and research continues into methods to render balanced realization based reduction more suitable for real-time clinical hyperthermia control and estimation.

The use of the modified Cholesky decomposition in divergence and classification calculations

NASA Technical Reports Server (NTRS)

Vanroony, D. L.; Lynn, M. S.; Snyder, C. H.

1973-01-01

The use of the Cholesky decomposition technique is analyzed as applied to the feature selection and classification algorithms used in the analysis of remote sensing data (e.g. as in LARSYS). This technique is approximately 30% faster in classification and a factor of 2-3 faster in divergence, as compared with LARSYS. Also numerical stability and accuracy are slightly improved. Other methods necessary to deal with numerical stablity problems are briefly discussed.

The use of the modified Cholesky decomposition in divergence and classification calculations

NASA Technical Reports Server (NTRS)

Van Rooy, D. L.; Lynn, M. S.; Snyder, C. H.

1973-01-01

This report analyzes the use of the modified Cholesky decomposition technique as applied to the feature selection and classification algorithms used in the analysis of remote sensing data (e.g., as in LARSYS). This technique is approximately 30% faster in classification and a factor of 2-3 faster in divergence, as compared with LARSYS. Also numerical stability and accuracy are slightly improved. Other methods necessary to deal with numerical stability problems are briefly discussed.

Temperature sensitivity of soil organic carbon decomposition increased with mean carbon residence time: Field incubation and data assimilation.

PubMed

Zhou, Xuhui; Xu, Xia; Zhou, Guiyao; Luo, Yiqi

2018-02-01

Temperature sensitivity of soil organic carbon (SOC) decomposition is one of the major uncertainties in predicting climate-carbon (C) cycle feedback. Results from previous studies are highly contradictory with old soil C decomposition being more, similarly, or less sensitive to temperature than decomposition of young fractions. The contradictory results are partly from difficulties in distinguishing old from young SOC and their changes over time in the experiments with or without isotopic techniques. In this study, we have conducted a long-term field incubation experiment with deep soil collars (0-70 cm in depth, 10 cm in diameter of PVC tubes) for excluding root C input to examine apparent temperature sensitivity of SOC decomposition under ambient and warming treatments from 2002 to 2008. The data from the experiment were infused into a multi-pool soil C model to estimate intrinsic temperature sensitivity of SOC decomposition and C residence times of three SOC fractions (i.e., active, slow, and passive) using a data assimilation (DA) technique. As active SOC with the short C residence time was progressively depleted in the deep soil collars under both ambient and warming treatments, the residences times of the whole SOC became longer over time. Concomitantly, the estimated apparent and intrinsic temperature sensitivity of SOC decomposition also became gradually higher over time as more than 50% of active SOC was depleted. Thus, the temperature sensitivity of soil C decomposition in deep soil collars was positively correlated with the mean C residence times. However, the regression slope of the temperature sensitivity against the residence time was lower under the warming treatment than under ambient temperature, indicating that other processes also regulated temperature sensitivity of SOC decomposition. These results indicate that old SOC decomposition is more sensitive to temperature than young components, making the old C more vulnerable to future warmer climate. © 2017 John Wiley & Sons Ltd.

Using the Binary Phase-Field Crystal Model to Describe Non-Classical Nucleation Pathways in Gold Nanoparticles

NASA Astrophysics Data System (ADS)

Smith, Nathan; Provatas, Nikolas

Recent experimental work has shown that gold nanoparticles can precipitate from an aqueous solution through a non-classical, multi-step nucleation process. This multi-step process begins with spinodal decomposition into solute-rich and solute-poor liquid domains followed by nucleation from within the solute-rich domains. We present a binary phase-field crystal theory that shows the same phenomology and examine various cross-over regimes in the growth and coarsening of liquid and solid domains. We'd like to the thank Canada Research Chairs (CRC) program for funding this work.

Insight into the novel inhibition mechanism of apigenin to Pneumolysin by molecular modeling

NASA Astrophysics Data System (ADS)

Niu, Xiaodi; Yang, Yanan; Song, Meng; Wang, Guizhen; Sun, Lin; Gao, Yawen; Wang, Hongsu

2017-11-01

In this study, the mechanism of apigenin inhibition was explored using molecular modelling, binding energy calculation, and mutagenesis assays. Energy decomposition analysis indicated that apigenin binds in the gap between domains 3 and 4 of PLY. Using principal component analysis, we found that binding of apigenin to PLY weakens the motion of domains 3 and 4. Consequently, these domains cannot complete the transition from monomer to oligomer, thereby blocking oligomerisation of PLY and counteracting its haemolytic activity. This inhibitory mechanism was confirmed by haemolysis assays, and these findings will promote the future development of an antimicrobial agent.

Wake acoustic analysis and image decomposition via beamforming of microphone signal projections on wavelet subspaces

DOT National Transportation Integrated Search

2006-05-08

This paper describes the integration of wavelet analysis and time-domain beamforming : of microphone array output signals for analyzing the acoustic emissions from airplane : generated wake vortices. This integrated process provides visual and quanti...

Output-only modal dynamic identification of frames by a refined FDD algorithm at seismic input and high damping

NASA Astrophysics Data System (ADS)

Pioldi, Fabio; Ferrari, Rosalba; Rizzi, Egidio

2016-02-01

The present paper deals with the seismic modal dynamic identification of frame structures by a refined Frequency Domain Decomposition (rFDD) algorithm, autonomously formulated and implemented within MATLAB. First, the output-only identification technique is outlined analytically and then employed to characterize all modal properties. Synthetic response signals generated prior to the dynamic identification are adopted as input channels, in view of assessing a necessary condition for the procedure's efficiency. Initially, the algorithm is verified on canonical input from random excitation. Then, modal identification has been attempted successfully at given seismic input, taken as base excitation, including both strong motion data and single and multiple input ground motions. Rather than different attempts investigating the role of seismic response signals in the Time Domain, this paper considers the identification analysis in the Frequency Domain. Results turn-out very much consistent with the target values, with quite limited errors in the modal estimates, including for the damping ratios, ranging from values in the order of 1% to 10%. Either seismic excitation and high values of damping, resulting critical also in case of well-spaced modes, shall not fulfill traditional FFD assumptions: this shows the consistency of the developed algorithm. Through original strategies and arrangements, the paper shows that a comprehensive rFDD modal dynamic identification of frames at seismic input is feasible, also at concomitant high damping.

A general CFD framework for fault-resilient simulations based on multi-resolution information fusion

NASA Astrophysics Data System (ADS)

Lee, Seungjoon; Kevrekidis, Ioannis G.; Karniadakis, George Em

2017-10-01

We develop a general CFD framework for multi-resolution simulations to target multiscale problems but also resilience in exascale simulations, where faulty processors may lead to gappy, in space-time, simulated fields. We combine approximation theory and domain decomposition together with statistical learning techniques, e.g. coKriging, to estimate boundary conditions and minimize communications by performing independent parallel runs. To demonstrate this new simulation approach, we consider two benchmark problems. First, we solve the heat equation (a) on a small number of spatial "patches" distributed across the domain, simulated by finite differences at fine resolution and (b) on the entire domain simulated at very low resolution, thus fusing multi-resolution models to obtain the final answer. Second, we simulate the flow in a lid-driven cavity in an analogous fashion, by fusing finite difference solutions obtained with fine and low resolution assuming gappy data sets. We investigate the influence of various parameters for this framework, including the correlation kernel, the size of a buffer employed in estimating boundary conditions, the coarseness of the resolution of auxiliary data, and the communication frequency across different patches in fusing the information at different resolution levels. In addition to its robustness and resilience, the new framework can be employed to generalize previous multiscale approaches involving heterogeneous discretizations or even fundamentally different flow descriptions, e.g. in continuum-atomistic simulations.

INDDGO: Integrated Network Decomposition & Dynamic programming for Graph Optimization

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

Groer, Christopher S; Sullivan, Blair D; Weerapurage, Dinesh P

2012-10-01

It is well-known that dynamic programming algorithms can utilize tree decompositions to provide a way to solve some \\emph{NP}-hard problems on graphs where the complexity is polynomial in the number of nodes and edges in the graph, but exponential in the width of the underlying tree decomposition. However, there has been relatively little computational work done to determine the practical utility of such dynamic programming algorithms. We have developed software to construct tree decompositions using various heuristics and have created a fast, memory-efficient dynamic programming implementation for solving maximum weighted independent set. We describe our software and the algorithms wemore » have implemented, focusing on memory saving techniques for the dynamic programming. We compare the running time and memory usage of our implementation with other techniques for solving maximum weighted independent set, including a commercial integer programming solver and a semi-definite programming solver. Our results indicate that it is possible to solve some instances where the underlying decomposition has width much larger than suggested by the literature. For certain types of problems, our dynamic programming code runs several times faster than these other methods.« less

Solventless synthesis, morphology, structure and magnetic properties of iron oxide nanoparticles

NASA Astrophysics Data System (ADS)

Das, Bratati; Kusz, Joachim; Reddy, V. Raghavendra; Zubko, Maciej; Bhattacharjee, Ashis

2017-12-01

In this study we report the solventless synthesis of iron oxide through thermal decomposition of acetyl ferrocene as well as its mixtures with maliec anhydride and characterization of the synthesized product by various comprehensive physical techniques. Morphology, size and structure of the reaction products were investigated by scanning electron microscopy, transmission electron microscopy and X-ray powder diffraction technique, respectively. Physical characterization techniques like FT-IR spectroscopy, dc magnetization study as well as 57Fe Mössbauer spectroscopy were employed to characterize the magnetic property of the product. The results observed from these studies unequivocally established that the synthesized materials are hematite. Thermal decomposition has been studied with the help of thermogravimetry. Reaction pathway for synthesis of hematite has been proposed. It is noted that maliec anhydride in the solid reaction environment as well as the gaseous reaction atmosphere strongly affect the reaction yield as well as the particle size. In general, a method of preparing hematite nanoparticles through solventless thermal decomposition technique using organometallic compounds and the possible use of reaction promoter have been discussed in detail.

Nanorods, nanospheres, nanocubes: Synthesis, characterization and catalytic activity of nanoferrites of Mn, Co, Ni, Part-89

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

Singh, Supriya; Srivastava, Pratibha; Singh, Gurdip, E-mail: gsingh4us@yahoo.com

2013-02-15

Graphical abstract: Prepared nanoferrites were characterized by FE-SEM and bright field TEM micrographs. The catalytic effect of these nanoferrites was evaluated on the thermal decomposition of ammonium perchlorate using TG and TG–DSC techniques. The kinetics of thermal decomposition of AP was evaluated using isothermal TG data by model fitting as well as isoconversional method. Display Omitted Highlights: ► Synthesis of ferrite nanostructures (∼20.0 nm) by wet-chemical method under different synthetic conditions. ► Characterization using XRD, FE-SEM, EDS, TEM, HRTEM and SAED pattern. ► Catalytic activity of ferrite nanostructures on AP thermal decomposition by thermal techniques. ► Burning rate measurements ofmore » CSPs with ferrite nanostructures. ► Kinetics of thermal decomposition of AP + nanoferrites. -- Abstract: In this paper, the nanoferrites of Mn, Co and Ni were synthesized by wet chemical method and characterized by X-ray diffraction (XRD), field emission scanning electron microscopy (FE-SEM), energy dispersive, X-ray spectra (EDS), transmission electron microscopy (TEM) and high resolution transmission electron microscopy (HR-TEM). It is catalytic activity were investigated on the thermal decomposition of ammonium perchlorate (AP) and composite solid propellants (CSPs) using thermogravimetry (TG), TG coupled with differential scanning calorimetry (TG–DSC) and ignition delay measurements. Kinetics of thermal decomposition of AP + nanoferrites have also been investigated using isoconversional and model fitting approaches which have been applied to data for isothermal TG decomposition. The burning rate of CSPs was considerably enhanced by these nanoferrites. Addition of nanoferrites to AP led to shifting of the high temperature decomposition peak toward lower temperature. All these studies reveal that ferrite nanorods show the best catalytic activity superior to that of nanospheres and nanocubes.« less

Reducing Projection Calculation in Quantum Teleportation by Virtue of the IWOP Technique and Schmidt Decomposition of |η〉 State

NASA Astrophysics Data System (ADS)

Fan, Hong-Yi; Fan, Yue

2002-01-01

By virtue of the technique of integration within an ordered product of operators and the Schmidt decomposition of the entangled state |η〉, we reduce the general projection calculation in the theory of quantum teleportation to a as simple as possible form and present a general formalism for teleportating quantum states of continuous variable. The project supported by National Natural Science Foundation of China and Educational Ministry Foundation of China

Advances in the Application of High-order Techniques in Simulation of Multi-disciplinary Phenomena

NASA Astrophysics Data System (ADS)

Gaitonde, D. V.; Visbal, M. R.

2003-03-01

This paper describes the development of a comprehensive high-fidelity algorithmic framework to simulate the three-dimensional fields associated with multi-disciplinary physics. A wide range of phenomena is considered, from aero-acoustics and turbulence to electromagnetics, non-linear fluid-structure interactions, and magnetogasdynamics. The scheme depends primarily on "spectral-like," up to sixth-order accurate compact-differencing and up to tenth-order filtering techniques. The tightly coupled procedure suppresses numerical instabilities commonly encountered with high-order methods on non-uniform meshes, near computational boundaries or in the simulation of nonlinear dynamics. Particular emphasis is placed on developing the proper metric evaluation procedures for three-dimensional moving and curvilinear meshes so that the advantages of higher-order schemes are retained in practical calculations. A domain-decomposition strategy based on finite-sized overlap regions and interface boundary treatments enables the development of highly scalable solvers. The utility of the method to simulate problems governed by widely disparate governing equations is demonstrated with several examples encompassing vortex dynamics, wave scattering, electro-fluid plasma interactions, and panel flutter.

Properties of NiO thin films deposited by intermittent spray pyrolysis process

NASA Astrophysics Data System (ADS)

Reguig, B. A.; Khelil, A.; Cattin, L.; Morsli, M.; Bernède, J. C.

2007-02-01

NiO thin films have been grown on glass substrates by intermittent spray pyrolysis deposition of NiCl 2·6H 2O diluted in distilled water, using a simple "perfume atomizer". The effect of the solution molarity on their properties was studied and compared to those of NiO thin films deposited with a classical spray system. It is shown that NiO thin films crystallized in the NiO structure are achieved after deposition. Whatever the precursor molarity, the grain size is around 25-30 nm. The crystallites are preferentially oriented along the (1 1 1) direction. All the films are p-type. However, the thickness and the conductivity of the NiO films depend on the precursor contraction. By comparison with the properties of films deposited by classical spray technique, it is shown that the critical precursor concentration, which induces strong thin films properties perturbations, is higher when a perfume atomizer is used. This broader stability domain can be attributed to better chlorides decomposition during the rest time used in the perfume atomizer technique.

High performance computation of radiative transfer equation using the finite element method

NASA Astrophysics Data System (ADS)

Badri, M. A.; Jolivet, P.; Rousseau, B.; Favennec, Y.

2018-05-01

This article deals with an efficient strategy for numerically simulating radiative transfer phenomena using distributed computing. The finite element method alongside the discrete ordinate method is used for spatio-angular discretization of the monochromatic steady-state radiative transfer equation in an anisotropically scattering media. Two very different methods of parallelization, angular and spatial decomposition methods, are presented. To do so, the finite element method is used in a vectorial way. A detailed comparison of scalability, performance, and efficiency on thousands of processors is established for two- and three-dimensional heterogeneous test cases. Timings show that both algorithms scale well when using proper preconditioners. It is also observed that our angular decomposition scheme outperforms our domain decomposition method. Overall, we perform numerical simulations at scales that were previously unattainable by standard radiative transfer equation solvers.

Domain Hierarchy and closed Loops (DHcL): a server for exploring hierarchy of protein domain structure

PubMed Central

Koczyk, Grzegorz; Berezovsky, Igor N.

2008-01-01

Domain hierarchy and closed loops (DHcL) (http://sitron.bccs.uib.no/dhcl/) is a web server that delineates energy hierarchy of protein domain structure and detects domains at different levels of this hierarchy. The server also identifies closed loops and van der Waals locks, which constitute a structural basis for the protein domain hierarchy. The DHcL can be a useful tool for an express analysis of protein structures and their alternative domain decompositions. The user submits a PDB identifier(s) or uploads a 3D protein structure in a PDB format. The results of the analysis are the location of domains at different levels of hierarchy, closed loops, van der Waals locks and their interactive visualization. The server maintains a regularly updated database of domains, closed loop and van der Waals locks for all X-ray structures in PDB. DHcL server is available at: http://sitron.bccs.uib.no/dhcl. PMID:18502776

Physico-Geometrical Kinetics of Solid-State Reactions in an Undergraduate Thermal Analysis Laboratory

ERIC Educational Resources Information Center

Koga, Nobuyoshi; Goshi, Yuri; Yoshikawa, Masahiro; Tatsuoka, Tomoyuki

2014-01-01

An undergraduate kinetic experiment of the thermal decomposition of solids by microscopic observation and thermal analysis was developed by investigating a suitable reaction, applicable techniques of thermal analysis and microscopic observation, and a reliable kinetic calculation method. The thermal decomposition of sodium hydrogen carbonate is…

Non-invasive quantitative pulmonary V/Q imaging using Fourier decomposition MRI at 1.5T.

PubMed

Kjørstad, Åsmund; Corteville, Dominique M R; Henzler, Thomas; Schmid-Bindert, Gerald; Zöllner, Frank G; Schad, Lothar R

2015-12-01

Techniques for quantitative pulmonary perfusion and ventilation using the Fourier Decomposition method were recently demonstrated. We combine these two techniques and show that ventilation-perfusion (V/Q) imaging is possible using only a single MR acquisition of less than thirty seconds. The Fourier Decomposition method is used in combination with two quantification techniques, which extract baselines from within the images themselves and thus allows quantification. For the perfusion, a region assumed to consist of 100% blood is utilized, while for the ventilation the zero-frequency component is used. V/Q-imaging is then done by dividing the quantified ventilation map with the quantified perfusion map. The techniques were used on ten healthy volunteers and fifteen patients diagnosed with lung cancer. A mean V/Q-ratio of 1.15 ± 0.22 was found for the healthy volunteers and a mean V/Q-ratio of 1.93 ± 0.83 for the non-afflicted lung in the patients. Mean V/Q-ratio in the afflicted (tumor-bearing) lung was found to be 1.61 ± 1.06. Functional defects were clearly visible in many of the patient images, but 5 of 15 patient images had to be excluded due to artifacts or low SNR, indicating a lack of robustness. Non-invasive, quantitative V/Q-imaging is possible using Fourier Decomposition MRI. The method requires only a single acquisition of less than 30 seconds, but robustness in patients remains an issue. Copyright © 2015. Published by Elsevier GmbH.

Learning inverse kinematics: reduced sampling through decomposition into virtual robots.

PubMed

de Angulo, Vicente Ruiz; Torras, Carme

2008-12-01

We propose a technique to speedup the learning of the inverse kinematics of a robot manipulator by decomposing it into two or more virtual robot arms. Unlike previous decomposition approaches, this one does not place any requirement on the robot architecture, and thus, it is completely general. Parametrized self-organizing maps are particularly adequate for this type of learning, and permit comparing results directly obtained and through the decomposition. Experimentation shows that time reductions of up to two orders of magnitude are easily attained.

Efficient Delaunay Tessellation through K-D Tree Decomposition

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

Morozov, Dmitriy; Peterka, Tom

Delaunay tessellations are fundamental data structures in computational geometry. They are important in data analysis, where they can represent the geometry of a point set or approximate its density. The algorithms for computing these tessellations at scale perform poorly when the input data is unbalanced. We investigate the use of k-d trees to evenly distribute points among processes and compare two strategies for picking split points between domain regions. Because resulting point distributions no longer satisfy the assumptions of existing parallel Delaunay algorithms, we develop a new parallel algorithm that adapts to its input and prove its correctness. We evaluatemore » the new algorithm using two late-stage cosmology datasets. The new running times are up to 50 times faster using k-d tree compared with regular grid decomposition. Moreover, in the unbalanced data sets, decomposing the domain into a k-d tree is up to five times faster than decomposing it into a regular grid.« less

Frozen Gaussian approximation based domain decomposition methods for the linear Schrödinger equation beyond the semi-classical regime

NASA Astrophysics Data System (ADS)

Lorin, E.; Yang, X.; Antoine, X.

2016-06-01

The paper is devoted to develop efficient domain decomposition methods for the linear Schrödinger equation beyond the semiclassical regime, which does not carry a small enough rescaled Planck constant for asymptotic methods (e.g. geometric optics) to produce a good accuracy, but which is too computationally expensive if direct methods (e.g. finite difference) are applied. This belongs to the category of computing middle-frequency wave propagation, where neither asymptotic nor direct methods can be directly used with both efficiency and accuracy. Motivated by recent works of the authors on absorbing boundary conditions (Antoine et al. (2014) [13] and Yang and Zhang (2014) [43]), we introduce Semiclassical Schwarz Waveform Relaxation methods (SSWR), which are seamless integrations of semiclassical approximation to Schwarz Waveform Relaxation methods. Two versions are proposed respectively based on Herman-Kluk propagation and geometric optics, and we prove the convergence and provide numerical evidence of efficiency and accuracy of these methods.

Scalable Parallel Computation for Extended MHD Modeling of Fusion Plasmas

NASA Astrophysics Data System (ADS)

Glasser, Alan H.

2008-11-01

Parallel solution of a linear system is scalable if simultaneously doubling the number of dependent variables and the number of processors results in little or no increase in the computation time to solution. Two approaches have this property for parabolic systems: multigrid and domain decomposition. Since extended MHD is primarily a hyperbolic rather than a parabolic system, additional steps must be taken to parabolize the linear system to be solved by such a method. Such physics-based preconditioning (PBP) methods have been pioneered by Chac'on, using finite volumes for spatial discretization, multigrid for solution of the preconditioning equations, and matrix-free Newton-Krylov methods for the accurate solution of the full nonlinear preconditioned equations. The work described here is an extension of these methods using high-order spectral element methods and FETI-DP domain decomposition. Application of PBP to a flux-source representation of the physics equations is discussed. The resulting scalability will be demonstrated for simple wave and for ideal and Hall MHD waves.

A partitioning strategy for nonuniform problems on multiprocessors

NASA Technical Reports Server (NTRS)

Berger, M. J.; Bokhari, S.

1985-01-01

The partitioning of a problem on a domain with unequal work estimates in different subddomains is considered in a way that balances the work load across multiple processors. Such a problem arises for example in solving partial differential equations using an adaptive method that places extra grid points in certain subregions of the domain. A binary decomposition of the domain is used to partition it into rectangles requiring equal computational effort. The communication costs of mapping this partitioning onto different microprocessors: a mesh-connected array, a tree machine and a hypercube is then studied. The communication cost expressions can be used to determine the optimal depth of the above partitioning.

Remote-sensing image encryption in hybrid domains

NASA Astrophysics Data System (ADS)

Zhang, Xiaoqiang; Zhu, Guiliang; Ma, Shilong

2012-04-01

Remote-sensing technology plays an important role in military and industrial fields. Remote-sensing image is the main means of acquiring information from satellites, which always contain some confidential information. To securely transmit and store remote-sensing images, we propose a new image encryption algorithm in hybrid domains. This algorithm makes full use of the advantages of image encryption in both spatial domain and transform domain. First, the low-pass subband coefficients of image DWT (discrete wavelet transform) decomposition are sorted by a PWLCM system in transform domain. Second, the image after IDWT (inverse discrete wavelet transform) reconstruction is diffused with 2D (two-dimensional) Logistic map and XOR operation in spatial domain. The experiment results and algorithm analyses show that the new algorithm possesses a large key space and can resist brute-force, statistical and differential attacks. Meanwhile, the proposed algorithm has the desirable encryption efficiency to satisfy requirements in practice.

Emotion Recognition from EEG Signals Using Multidimensional Information in EMD Domain.

PubMed

Zhuang, Ning; Zeng, Ying; Tong, Li; Zhang, Chi; Zhang, Hanming; Yan, Bin

2017-01-01

This paper introduces a method for feature extraction and emotion recognition based on empirical mode decomposition (EMD). By using EMD, EEG signals are decomposed into Intrinsic Mode Functions (IMFs) automatically. Multidimensional information of IMF is utilized as features, the first difference of time series, the first difference of phase, and the normalized energy. The performance of the proposed method is verified on a publicly available emotional database. The results show that the three features are effective for emotion recognition. The role of each IMF is inquired and we find that high frequency component IMF1 has significant effect on different emotional states detection. The informative electrodes based on EMD strategy are analyzed. In addition, the classification accuracy of the proposed method is compared with several classical techniques, including fractal dimension (FD), sample entropy, differential entropy, and discrete wavelet transform (DWT). Experiment results on DEAP datasets demonstrate that our method can improve emotion recognition performance.

The effect of inlet swirl on the dynamics of long annular seals in centrifugal pumps

NASA Technical Reports Server (NTRS)

Ismail, M.; Brown, R. D.; France, D.

1994-01-01

This paper describes additional results from a continuing research program which aims to identify the dynamics of long annular seals in centrifugal pumps. A seal test rig designed at Heriot-Watt University and commissioned at Weir Pumps Research Laboratory in Alloa permits the identification of mass, stiffness, and damping coefficients using a least-squares technique based on the singular value decomposition method. The analysis is carried out in the time domain using a multi-fiequency forcing function. The experimental method relies on the forced excitation of a flexibly supported stator by two hydraulic shakers. Running through the stator embodying two symmetrical balance drum seals is a rigid rotor supported in rolling element bearings. The only physical connection between shaft and stator is the pair of annular gaps filled with pressurized water discharged axially. The experimental coefficients obtained from the tests are compared with theoretical values.

Understanding a reference-free impedance method using collocated piezoelectric transducers

NASA Astrophysics Data System (ADS)

Kim, Eun Jin; Kim, Min Koo; Sohn, Hoon; Park, Hyun Woo

2010-03-01

A new concept of a reference-free impedance method, which does not require direct comparison with a baseline impedance signal, is proposed for damage detection in a plate-like structure. A single pair of piezoelectric (PZT) wafers collocated on both surfaces of a plate are utilized for extracting electro-mechanical signatures (EMS) associated with mode conversion due to damage. A numerical simulation is conducted to investigate the EMS of collocated PZT wafers in the frequency domain at the presence of damage through spectral element analysis. Then, the EMS due to mode conversion induced by damage are extracted using the signal decomposition technique based on the polarization characteristics of the collocated PZT wafers. The effects of the size and the location of damage on the decomposed EMS are investigated as well. Finally, the applicability of the decomposed EMS to the reference-free damage diagnosis is discussed.

Topology-generating interfacial pattern formation during liquid metal dealloying

DOE PAGES

Geslin, Pierre -Antoine; McCue, Ian; Gaskey, Bernard; ...

2015-11-19

Liquid metal dealloying has emerged as a novel technique to produce topologically complex nanoporous and nanocomposite structures with ultra-high interfacial area and other unique properties relevant for diverse material applications. This process is empirically known to require the selective dissolution of one element of a multicomponent solid alloy into a liquid metal to obtain desirable structures. However, how structures form is not known. Here we demonstrate, using mesoscale phase-field modelling and experiments, that nano/microstructural pattern formation during dealloying results from the interplay of (i) interfacial spinodal decomposition, forming compositional domain structures enriched in the immiscible element, and (ii) diffusion-coupled growthmore » of the enriched solid phase and the liquid phase into the alloy. We highlight how those two basic mechanisms interact to yield a rich variety of topologically disconnected and connected structures. Furthermore, we deduce scaling laws governing microstructural length scales and dealloying kinetics.« less

International Space Station Future Correlation Analysis Improvements

NASA Technical Reports Server (NTRS)

Laible, Michael R.; Pinnamaneni, Murthy; Sugavanam, Sujatha; Grygier, Michael

2018-01-01

Ongoing modal analyses and model correlation are performed on different configurations of the International Space Station (ISS). These analyses utilize on-orbit dynamic measurements collected using four main ISS instrumentation systems: External Wireless Instrumentation System (EWIS), Internal Wireless Instrumentation System (IWIS), Space Acceleration Measurement System (SAMS), and Structural Dynamic Measurement System (SDMS). Remote Sensor Units (RSUs) are network relay stations that acquire flight data from sensors. Measured data is stored in the Remote Sensor Unit (RSU) until it receives a command to download data via RF to the Network Control Unit (NCU). Since each RSU has its own clock, it is necessary to synchronize measurements before analysis. Imprecise synchronization impacts analysis results. A study was performed to evaluate three different synchronization techniques: (i) measurements visually aligned to analytical time-response data using model comparison, (ii) Frequency Domain Decomposition (FDD), and (iii) lag from cross-correlation to align measurements. This paper presents the results of this study.

Topology-generating interfacial pattern formation during liquid metal dealloying.

PubMed

Geslin, Pierre-Antoine; McCue, Ian; Gaskey, Bernard; Erlebacher, Jonah; Karma, Alain

2015-11-19

Liquid metal dealloying has emerged as a novel technique to produce topologically complex nanoporous and nanocomposite structures with ultra-high interfacial area and other unique properties relevant for diverse material applications. This process is empirically known to require the selective dissolution of one element of a multicomponent solid alloy into a liquid metal to obtain desirable structures. However, how structures form is not known. Here we demonstrate, using mesoscale phase-field modelling and experiments, that nano/microstructural pattern formation during dealloying results from the interplay of (i) interfacial spinodal decomposition, forming compositional domain structures enriched in the immiscible element, and (ii) diffusion-coupled growth of the enriched solid phase and the liquid phase into the alloy. We highlight how those two basic mechanisms interact to yield a rich variety of topologically disconnected and connected structures. Moreover, we deduce scaling laws governing microstructural length scales and dealloying kinetics.

FEAST fundamental framework for electronic structure calculations: Reformulation and solution of the muffin-tin problem

NASA Astrophysics Data System (ADS)

Levin, Alan R.; Zhang, Deyin; Polizzi, Eric

2012-11-01

In a recent article Polizzi (2009) [15], the FEAST algorithm has been presented as a general purpose eigenvalue solver which is ideally suited for addressing the numerical challenges in electronic structure calculations. Here, FEAST is presented beyond the “black-box” solver as a fundamental modeling framework which can naturally address the original numerical complexity of the electronic structure problem as formulated by Slater in 1937 [3]. The non-linear eigenvalue problem arising from the muffin-tin decomposition of the real-space domain is first derived and then reformulated to be solved exactly within the FEAST framework. This new framework is presented as a fundamental and practical solution for performing both accurate and scalable electronic structure calculations, bypassing the various issues of using traditional approaches such as linearization and pseudopotential techniques. A finite element implementation of this FEAST framework along with simulation results for various molecular systems is also presented and discussed.

Discrete sensitivity derivatives of the Navier-Stokes equations with a parallel Krylov solver

NASA Technical Reports Server (NTRS)

Ajmani, Kumud; Taylor, Arthur C., III

1994-01-01

This paper solves an 'incremental' form of the sensitivity equations derived by differentiating the discretized thin-layer Navier Stokes equations with respect to certain design variables of interest. The equations are solved with a parallel, preconditioned Generalized Minimal RESidual (GMRES) solver on a distributed-memory architecture. The 'serial' sensitivity analysis code is parallelized by using the Single Program Multiple Data (SPMD) programming model, domain decomposition techniques, and message-passing tools. Sensitivity derivatives are computed for low and high Reynolds number flows over a NACA 1406 airfoil on a 32-processor Intel Hypercube, and found to be identical to those computed on a single-processor Cray Y-MP. It is estimated that the parallel sensitivity analysis code has to be run on 40-50 processors of the Intel Hypercube in order to match the single-processor processing time of a Cray Y-MP.

High-performance parallel analysis of coupled problems for aircraft propulsion

NASA Technical Reports Server (NTRS)

Felippa, C. A.; Farhat, C.; Lanteri, S.; Maman, N.; Piperno, S.; Gumaste, U.

1994-01-01

This research program deals with the application of high-performance computing methods for the analysis of complete jet engines. We have entitled this program by applying the two dimensional parallel aeroelastic codes to the interior gas flow problem of a bypass jet engine. The fluid mesh generation, domain decomposition, and solution capabilities were successfully tested. We then focused attention on methodology for the partitioned analysis of the interaction of the gas flow with a flexible structure and with the fluid mesh motion that results from these structural displacements. This is treated by a new arbitrary Lagrangian-Eulerian (ALE) technique that models the fluid mesh motion as that of a fictitious mass-spring network. New partitioned analysis procedures to treat this coupled three-component problem are developed. These procedures involved delayed corrections and subcycling. Preliminary results on the stability, accuracy, and MPP computational efficiency are reported.

An expert support system for breast cancer diagnosis using color wavelet features.

PubMed

Issac Niwas, S; Palanisamy, P; Chibbar, Rajni; Zhang, W J

2012-10-01

Breast cancer diagnosis can be done through the pathologic assessments of breast tissue samples such as core needle biopsy technique. The result of analysis on this sample by pathologist is crucial for breast cancer patient. In this paper, nucleus of tissue samples are investigated after decomposition by means of the Log-Gabor wavelet on HSV color domain and an algorithm is developed to compute the color wavelet features. These features are used for breast cancer diagnosis using Support Vector Machine (SVM) classifier algorithm. The ability of properly trained SVM is to correctly classify patterns and make them particularly suitable for use in an expert system that aids in the diagnosis of cancer tissue samples. The results are compared with other multivariate classifiers such as Naïves Bayes classifier and Artificial Neural Network. The overall accuracy of the proposed method using SVM classifier will be further useful for automation in cancer diagnosis.

A novel hybrid model for air quality index forecasting based on two-phase decomposition technique and modified extreme learning machine.

PubMed

Wang, Deyun; Wei, Shuai; Luo, Hongyuan; Yue, Chenqiang; Grunder, Olivier

2017-02-15

The randomness, non-stationarity and irregularity of air quality index (AQI) series bring the difficulty of AQI forecasting. To enhance forecast accuracy, a novel hybrid forecasting model combining two-phase decomposition technique and extreme learning machine (ELM) optimized by differential evolution (DE) algorithm is developed for AQI forecasting in this paper. In phase I, the complementary ensemble empirical mode decomposition (CEEMD) is utilized to decompose the AQI series into a set of intrinsic mode functions (IMFs) with different frequencies; in phase II, in order to further handle the high frequency IMFs which will increase the forecast difficulty, variational mode decomposition (VMD) is employed to decompose the high frequency IMFs into a number of variational modes (VMs). Then, the ELM model optimized by DE algorithm is applied to forecast all the IMFs and VMs. Finally, the forecast value of each high frequency IMF is obtained through adding up the forecast results of all corresponding VMs, and the forecast series of AQI is obtained by aggregating the forecast results of all IMFs. To verify and validate the proposed model, two daily AQI series from July 1, 2014 to June 30, 2016 collected from Beijing and Shanghai located in China are taken as the test cases to conduct the empirical study. The experimental results show that the proposed hybrid model based on two-phase decomposition technique is remarkably superior to all other considered models for its higher forecast accuracy. Copyright © 2016 Elsevier B.V. All rights reserved.

Spectral-decomposition techniques for the identification of periodic and anomalous phenomena in radon time-series.

NASA Astrophysics Data System (ADS)

Crockett, R. G. M.; Perrier, F.; Richon, P.

2009-04-01

Building on independent investigations by research groups at both IPGP, France, and the University of Northampton, UK, hourly-sampled radon time-series of durations exceeding one year have been investigated for periodic and anomalous phenomena using a variety of established and novel techniques. These time-series have been recorded in locations having no routine human behaviour and thus are effectively free of significant anthropogenic influences. With regard to periodic components, the long durations of these time-series allow, in principle, very high frequency resolutions for established spectral-measurement techniques such as Fourier and maximum-entropy. However, as has been widely observed, the stochastic nature of radon emissions from rocks and soils, coupled with sensitivity to a wide variety influences such as temperature, wind-speed and soil moisture-content has made interpretation of the results obtained by such techniques very difficult, with uncertain results, in many cases. We here report developments in the investigation of radon-time series for periodic and anomalous phenomena using spectral-decomposition techniques. These techniques, in variously separating ‘high', ‘middle' and ‘low' frequency components, effectively ‘de-noise' the data by allowing components of interest to be isolated from others which (might) serve to obscure weaker information-containing components. Once isolated, these components can be investigated using a variety of techniques. Whilst this is very much work in early stages of development, spectral decomposition methods have been used successfully to indicate the presence of diurnal and sub-diurnal cycles in radon concentration which we provisionally attribute to tidal influences. Also, these methods have been used to enhance the identification of short-duration anomalies, attributable to a variety of causes including, for example, earthquakes and rapid large-magnitude changes in weather conditions. Keywords: radon; earthquakes; tidal-influences; anomalies; time series; spectral-decomposition.

Non-equilibrium theory of arrested spinodal decomposition

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

Olais-Govea, José Manuel; López-Flores, Leticia; Medina-Noyola, Magdaleno

The non-equilibrium self-consistent generalized Langevin equation theory of irreversible relaxation [P. E. Ramŕez-González and M. Medina-Noyola, Phys. Rev. E 82, 061503 (2010); 82, 061504 (2010)] is applied to the description of the non-equilibrium processes involved in the spinodal decomposition of suddenly and deeply quenched simple liquids. For model liquids with hard-sphere plus attractive (Yukawa or square well) pair potential, the theory predicts that the spinodal curve, besides being the threshold of the thermodynamic stability of homogeneous states, is also the borderline between the regions of ergodic and non-ergodic homogeneous states. It also predicts that the high-density liquid-glass transition line, whosemore » high-temperature limit corresponds to the well-known hard-sphere glass transition, at lower temperature intersects the spinodal curve and continues inside the spinodal region as a glass-glass transition line. Within the region bounded from below by this low-temperature glass-glass transition and from above by the spinodal dynamic arrest line, we can recognize two distinct domains with qualitatively different temperature dependence of various physical properties. We interpret these two domains as corresponding to full gas-liquid phase separation conditions and to the formation of physical gels by arrested spinodal decomposition. The resulting theoretical scenario is consistent with the corresponding experimental observations in a specific colloidal model system.« less

Uncertainty propagation in orbital mechanics via tensor decomposition

NASA Astrophysics Data System (ADS)

Sun, Yifei; Kumar, Mrinal

2016-03-01

Uncertainty forecasting in orbital mechanics is an essential but difficult task, primarily because the underlying Fokker-Planck equation (FPE) is defined on a relatively high dimensional (6-D) state-space and is driven by the nonlinear perturbed Keplerian dynamics. In addition, an enormously large solution domain is required for numerical solution of this FPE (e.g. encompassing the entire orbit in the x-y-z subspace), of which the state probability density function (pdf) occupies a tiny fraction at any given time. This coupling of large size, high dimensionality and nonlinearity makes for a formidable computational task, and has caused the FPE for orbital uncertainty propagation to remain an unsolved problem. To the best of the authors' knowledge, this paper presents the first successful direct solution of the FPE for perturbed Keplerian mechanics. To tackle the dimensionality issue, the time-varying state pdf is approximated in the CANDECOMP/PARAFAC decomposition tensor form where all the six spatial dimensions as well as the time dimension are separated from one other. The pdf approximation for all times is obtained simultaneously via the alternating least squares algorithm. Chebyshev spectral differentiation is employed for discretization on account of its spectral ("super-fast") convergence rate. To facilitate the tensor decomposition and control the solution domain size, system dynamics is expressed using spherical coordinates in a noninertial reference frame. Numerical results obtained on a regular personal computer are compared with Monte Carlo simulations.

Solid/FEM integration at SNLA

NASA Technical Reports Server (NTRS)

Chavez, Patrick F.

1987-01-01

The effort at Sandia National Labs. on the methodologies and techniques being used to generate strict hexahedral finite element meshes from a solid model is described. The functionality of the modeler is used to decompose the solid into a set of nonintersecting meshable finite element primitives. The description of the decomposition is exported, via a Boundary Representative format, to the meshing program which uses the information for complete finite element model specification. Particular features of the program are discussed in some detail along with future plans for development which includes automation of the decomposition using artificial intelligence techniques.

Application of empirical mode decomposition with local linear quantile regression in financial time series forecasting.

PubMed

Jaber, Abobaker M; Ismail, Mohd Tahir; Altaher, Alsaidi M

2014-01-01

This paper mainly forecasts the daily closing price of stock markets. We propose a two-stage technique that combines the empirical mode decomposition (EMD) with nonparametric methods of local linear quantile (LLQ). We use the proposed technique, EMD-LLQ, to forecast two stock index time series. Detailed experiments are implemented for the proposed method, in which EMD-LPQ, EMD, and Holt-Winter methods are compared. The proposed EMD-LPQ model is determined to be superior to the EMD and Holt-Winter methods in predicting the stock closing prices.

Fast Sampling Gas Chromatography (GC) System for Speciation in a Shock Tube

DTIC Science & Technology

2016-10-31

capture similar ethylene decomposition rates for temperature-dependent shock experiments. (a) Papers published in peer-reviewed journals (N/A for none...3 GC Sampling System Validation Experiments ............................................................................... 5 Ethylene ...results for cold shock experiments, and both techniques capture similar ethylene decomposition rates for temperature-dependent shock experiments. Problem

Photoacoustic tomography from weak and noisy signals by using a pulse decomposition algorithm in the time-domain.

PubMed

Liu, Liangbing; Tao, Chao; Liu, XiaoJun; Deng, Mingxi; Wang, Senhua; Liu, Jun

2015-10-19

Photoacoustic tomography is a promising and rapidly developed methodology of biomedical imaging. It confronts an increasing urgent problem to reconstruct the image from weak and noisy photoacoustic signals, owing to its high benefit in extending the imaging depth and decreasing the dose of laser exposure. Based on the time-domain characteristics of photoacoustic signals, a pulse decomposition algorithm is proposed to reconstruct a photoacoustic image from signals with low signal-to-noise ratio. In this method, a photoacoustic signal is decomposed as the weighted summation of a set of pulses in the time-domain. Images are reconstructed from the weight factors, which are directly related to the optical absorption coefficient. Both simulation and experiment are conducted to test the performance of the method. Numerical simulations show that when the signal-to-noise ratio is -4 dB, the proposed method decreases the reconstruction error to about 17%, in comparison with the conventional back-projection method. Moreover, it can produce acceptable images even when the signal-to-noise ratio is decreased to -10 dB. Experiments show that, when the laser influence level is low, the proposed method achieves a relatively clean image of a hair phantom with some well preserved pattern details. The proposed method demonstrates imaging potential of photoacoustic tomography in expanding applications.

Chemical stability of molten 2,4,6-trinitrotoluene at high pressure

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

Dattelbaum, Dana M., E-mail: danadat@lanl.gov; Chellappa, Raja S.; Bowden, Patrick R.

2014-01-13

2,4,6-trinitrotoluene (TNT) is a molecular explosive that exhibits chemical stability in the molten phase at ambient pressure. A combination of visual, spectroscopic, and structural (x-ray diffraction) methods coupled to high pressure, resistively heated diamond anvil cells was used to determine the melt and decomposition boundaries to >15 GPa. The chemical stability of molten TNT was found to be limited, existing in a small domain of pressure-temperature conditions below 2 GPa. Decomposition dominates the phase diagram at high temperatures beyond 6 GPa. From the calculated bulk temperature rise, we conclude that it is unlikely that TNT melts on its principal Hugoniot.

Efficient implementation of a 3-dimensional ADI method on the iPSC/860

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

Van der Wijngaart, R.F.

1993-12-31

A comparison is made between several domain decomposition strategies for the solution of three-dimensional partial differential equations on a MIMD distributed memory parallel computer. The grids used are structured, and the numerical algorithm is ADI. Important implementation issues regarding load balancing, storage requirements, network latency, and overlap of computations and communications are discussed. Results of the solution of the three-dimensional heat equation on the Intel iPSC/860 are presented for the three most viable methods. It is found that the Bruno-Cappello decomposition delivers optimal computational speed through an almost complete elimination of processor idle time, while providing good memory efficiency.

Analysis of Coherent Phonon Signals by Sparsity-promoting Dynamic Mode Decomposition

NASA Astrophysics Data System (ADS)

Murata, Shin; Aihara, Shingo; Tokuda, Satoru; Iwamitsu, Kazunori; Mizoguchi, Kohji; Akai, Ichiro; Okada, Masato

2018-05-01

We propose a method to decompose normal modes in a coherent phonon (CP) signal by sparsity-promoting dynamic mode decomposition. While the CP signals can be modeled as the sum of finite number of damped oscillators, the conventional method such as Fourier transform adopts continuous bases in a frequency domain. Thus, the uncertainty of frequency appears and it is difficult to estimate the initial phase. Moreover, measurement artifacts are imposed on the CP signal and deforms the Fourier spectrum. In contrast, the proposed method can separate the signal from the artifact precisely and can successfully estimate physical properties of the normal modes.

Comparison of Techniques for Sampling Adult Necrophilous Insects From Pig Carcasses.

PubMed

Cruise, Angela; Hatano, Eduardo; Watson, David W; Schal, Coby

2018-02-06

Studies of the pre-colonization interval and mechanisms driving necrophilous insect ecological succession depend on effective sampling of adult insects and knowledge of their diel and successional activity patterns. The number of insects trapped, their diversity, and diel periodicity were compared with four sampling methods on neonate pigs. Sampling method, time of day and decomposition age of the pigs significantly affected the number of insects sampled from pigs. We also found significant interactions of sampling method and decomposition day, time of sampling and decomposition day. No single method was superior to the other methods during all three decomposition days. Sampling times after noon yielded the largest samples during the first 2 d of decomposition. On day 3 of decomposition however, all sampling times were equally effective. Therefore, to maximize insect collections from neonate pigs, the method used to sample must vary by decomposition day. The suction trap collected the most species-rich samples, but sticky trap samples were the most diverse, when both species richness and evenness were factored into a Shannon diversity index. Repeated sampling during the noon to 18:00 hours period was most effective to obtain the maximum diversity of trapped insects. The integration of multiple sampling techniques would most effectively sample the necrophilous insect community. However, because all four tested methods were deficient at sampling beetle species, future work should focus on optimizing the most promising methods, alone or in combinations, and incorporate hand-collections of beetles. © The Author(s) 2018. Published by Oxford University Press on behalf of Entomological Society of America. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

Plant Species Rather Than Climate Greatly Alters the Temporal Pattern of Litter Chemical Composition During Long-Term Decomposition

NASA Astrophysics Data System (ADS)

Li, Yongfu; Chen, Na; Harmon, Mark E.; Li, Yuan; Cao, Xiaoyan; Chappell, Mark A.; Mao, Jingdong

2015-10-01

A feedback between decomposition and litter chemical composition occurs with decomposition altering composition that in turn influences the decomposition rate. Elucidating the temporal pattern of chemical composition is vital to understand this feedback, but the effects of plant species and climate on chemical changes remain poorly understood, especially over multiple years. In a 10-year decomposition experiment with litter of four species (Acer saccharum, Drypetes glauca, Pinus resinosa, and Thuja plicata) from four sites that range from the arctic to tropics, we determined the abundance of 11 litter chemical constituents that were grouped into waxes, carbohydrates, lignin/tannins, and proteins/peptides using advanced 13C solid-state NMR techniques. Decomposition generally led to an enrichment of waxes and a depletion of carbohydrates, whereas the changes of other chemical constituents were inconsistent. Inconsistent convergence in chemical compositions during decomposition was observed among different litter species across a range of site conditions, whereas one litter species converged under different climate conditions. Our data clearly demonstrate that plant species rather than climate greatly alters the temporal pattern of litter chemical composition, suggesting the decomposition-chemistry feedback varies among different plant species.

Plant Species Rather Than Climate Greatly Alters the Temporal Pattern of Litter Chemical Composition During Long-Term Decomposition

PubMed Central

Li, Yongfu; Chen, Na; Harmon, Mark E.; Li, Yuan; Cao, Xiaoyan; Chappell, Mark A.; Mao, Jingdong

2015-01-01

A feedback between decomposition and litter chemical composition occurs with decomposition altering composition that in turn influences the decomposition rate. Elucidating the temporal pattern of chemical composition is vital to understand this feedback, but the effects of plant species and climate on chemical changes remain poorly understood, especially over multiple years. In a 10-year decomposition experiment with litter of four species (Acer saccharum, Drypetes glauca, Pinus resinosa, and Thuja plicata) from four sites that range from the arctic to tropics, we determined the abundance of 11 litter chemical constituents that were grouped into waxes, carbohydrates, lignin/tannins, and proteins/peptides using advanced 13C solid-state NMR techniques. Decomposition generally led to an enrichment of waxes and a depletion of carbohydrates, whereas the changes of other chemical constituents were inconsistent. Inconsistent convergence in chemical compositions during decomposition was observed among different litter species across a range of site conditions, whereas one litter species converged under different climate conditions. Our data clearly demonstrate that plant species rather than climate greatly alters the temporal pattern of litter chemical composition, suggesting the decomposition-chemistry feedback varies among different plant species. PMID:26515033

Cerebrospinal fluid PCR analysis and biochemistry in bodies with severe decomposition.

PubMed

Palmiere, Cristian; Vanhaebost, Jessica; Ventura, Francesco; Bonsignore, Alessandro; Bonetti, Luca Reggiani

2015-02-01

The aim of this study was to assess whether Neisseria meningitidis, Listeria monocytogenes, Streptococcus pneumoniae and Haemophilus influenzae can be identified using the polymerase chain reaction technique in the cerebrospinal fluid of severely decomposed bodies with known, noninfectious causes of death or whether postmortem changes can lead to false positive results and thus erroneous diagnostic information. Biochemical investigations, postmortem bacteriology and real-time polymerase chain reaction analysis in cerebrospinal fluid were performed in a series of medico-legal autopsies that included noninfectious causes of death with decomposition, bacterial meningitis without decomposition, bacterial meningitis with decomposition, low respiratory tract infections with decomposition and abdominal infections with decomposition. In noninfectious causes of death with decomposition, postmortem investigations failed to reveal results consistent with generalized inflammation or bacterial infections at the time of death. Real-time polymerase chain reaction analysis in cerebrospinal fluid did not identify the studied bacteria in any of these cases. The results of this study highlight the usefulness of molecular approaches in bacteriology as well as the use of alternative biological samples in postmortem biochemistry in order to obtain suitable information even in corpses with severe decompositional changes. Copyright © 2014 Elsevier Ltd and Faculty of Forensic and Legal Medicine. All rights reserved.

Search for memory effects in methane hydrate: structure of water before hydrate formation and after hydrate decomposition.

PubMed

Buchanan, Piers; Soper, Alan K; Thompson, Helen; Westacott, Robin E; Creek, Jefferson L; Hobson, Greg; Koh, Carolyn A

2005-10-22

Neutron diffraction with HD isotope substitution has been used to study the formation and decomposition of the methane clathrate hydrate. Using this atomistic technique coupled with simultaneous gas consumption measurements, we have successfully tracked the formation of the sI methane hydrate from a water/gas mixture and then the subsequent decomposition of the hydrate from initiation to completion. These studies demonstrate that the application of neutron diffraction with simultaneous gas consumption measurements provides a powerful method for studying the clathrate hydrate crystal growth and decomposition. We have also used neutron diffraction to examine the water structure before the hydrate growth and after the hydrate decomposition. From the neutron-scattering curves and the empirical potential structure refinement analysis of the data, we find that there is no significant difference between the structure of water before the hydrate formation and the structure of water after the hydrate decomposition. Nor is there any significant change to the methane hydration shell. These results are discussed in the context of widely held views on the existence of memory effects after the hydrate decomposition.

Composite solvers for linear saddle point problems arising from the incompressible Stokes equations with highly heterogeneous viscosity structure

NASA Astrophysics Data System (ADS)

Sanan, P.; Schnepp, S. M.; May, D.; Schenk, O.

2014-12-01

Geophysical applications require efficient forward models for non-linear Stokes flow on high resolution spatio-temporal domains. The bottleneck in applying the forward model is solving the linearized, discretized Stokes problem which takes the form of a large, indefinite (saddle point) linear system. Due to the heterogeniety of the effective viscosity in the elliptic operator, devising effective preconditioners for saddle point problems has proven challenging and highly problem-dependent. Nevertheless, at least three approaches show promise for preconditioning these difficult systems in an algorithmically scalable way using multigrid and/or domain decomposition techniques. The first is to work with a hierarchy of coarser or smaller saddle point problems. The second is to use the Schur complement method to decouple and sequentially solve for the pressure and velocity. The third is to use the Schur decomposition to devise preconditioners for the full operator. These involve sub-solves resembling inexact versions of the sequential solve. The choice of approach and sub-methods depends crucially on the motivating physics, the discretization, and available computational resources. Here we examine the performance trade-offs for preconditioning strategies applied to idealized models of mantle convection and lithospheric dynamics, characterized by large viscosity gradients. Due to the arbitrary topological structure of the viscosity field in geodynamical simulations, we utilize low order, inf-sup stable mixed finite element spatial discretizations which are suitable when sharp viscosity variations occur in element interiors. Particular attention is paid to possibilities within the decoupled and approximate Schur complement factorization-based monolithic approaches to leverage recently-developed flexible, communication-avoiding, and communication-hiding Krylov subspace methods in combination with `heavy' smoothers, which require solutions of large per-node sub-problems, well-suited to solution on hybrid computational clusters. To manage the combinatorial explosion of solver options (which include hybridizations of all the approaches mentioned above), we leverage the modularity of the PETSc library.

Decomposition of aquatic plants in lakes

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

Godshalk, G.L.

1977-01-01

This study was carried out to systematically determine the effects of temperature and oxygen concentration, two environmental parameters crucial to lake metabolism in general, on decomposition of five species of aquatic vascular plants of three growth forms in a Michigan lake. Samples of dried plant material were decomposed in flasks in the laboratory under three different oxygen regimes, aerobic-to-anaerobic, strict anaerobic, and aerated, each at 10/sup 0/C and 25/sup 0/C. In addition, in situ decomposition of the same species was monitored using the litter bag technique under four conditions.

Forecasting hotspots in East Kutai, Kutai Kartanegara, and West Kutai as early warning information

NASA Astrophysics Data System (ADS)

Wahyuningsih, S.; Goejantoro, R.; Rizki, N. A.

2018-04-01

The aims of this research are to model hotspots and forecast hotspot 2017 in East Kutai, Kutai Kartanegara and West Kutai. The methods which used in this research were Holt exponential smoothing, Holt’s additive dump trend method, Holt-Winters’ additive method, additive decomposition method, multiplicative decomposition method, Loess decomposition method and Box-Jenkins method. For smoothing techniques, additive decomposition is better than Holt’s exponential smoothing. The hotspots model using Box-Jenkins method were Autoregressive Moving Average ARIMA(1,1,0), ARIMA(0,2,1), and ARIMA(0,1,0). Comparing the results from all methods which were used in this research, and based on Root of Mean Squared Error (RMSE), show that Loess decomposition method is the best times series model, because it has the least RMSE. Thus the Loess decomposition model used to forecast the number of hotspot. The forecasting result indicatethat hotspots pattern tend to increase at the end of 2017 in Kutai Kartanegara and West Kutai, but stationary in East Kutai.

Mössbauer study of the thermal decomposition of alkali tris(oxalato)ferrates(III)

NASA Astrophysics Data System (ADS)

Brar, A. S.; Randhawa, B. S.

1985-07-01

The thermal decomposition of alkali (Li,Na,K,Cs,NH 4) tris(oxalato)ferrates(III) has been studied at different temperatures up to 700°C using Mössbauer, infrared spectroscopy, and thermogravimetric techniques. The formation of different intermediates has been observed during thermal decomposition. The decomposition in these complexes starts at different temperatures, i.e., at 200°C in the case of lithium, cesium, and ammonium ferrate(III), 250°C in the case of sodium, and 270°C in the case of potassium tris(oxalato)ferrate(III). The intermediates, i.e., Fe 11C 2O 4, K 6Fe 112(ox) 5. and Cs 2Fe 11 (ox) 2(H 2O) 2, are formed during thermal decomposition of lithium, potassium, and cesium tris(oxalato)ferrates(III), respectively. In the case of sodium and ammonium tris(oxalato)ferrates(III), the decomposition occurs without reduction to the iron(II) state and leads directly to α-Fe 2O 3.

Parallelisation study of a three-dimensional environmental flow model

NASA Astrophysics Data System (ADS)

O'Donncha, Fearghal; Ragnoli, Emanuele; Suits, Frank

2014-03-01

There are many simulation codes in the geosciences that are serial and cannot take advantage of the parallel computational resources commonly available today. One model important for our work in coastal ocean current modelling is EFDC, a Fortran 77 code configured for optimal deployment on vector computers. In order to take advantage of our cache-based, blade computing system we restructured EFDC from serial to parallel, thereby allowing us to run existing models more quickly, and to simulate larger and more detailed models that were previously impractical. Since the source code for EFDC is extensive and involves detailed computation, it is important to do such a port in a manner that limits changes to the files, while achieving the desired speedup. We describe a parallelisation strategy involving surgical changes to the source files to minimise error-prone alteration of the underlying computations, while allowing load-balanced domain decomposition for efficient execution on a commodity cluster. The use of conjugate gradient posed particular challenges due to implicit non-local communication posing a hindrance to standard domain partitioning schemes; a number of techniques are discussed to address this in a feasible, computationally efficient manner. The parallel implementation demonstrates good scalability in combination with a novel domain partitioning scheme that specifically handles mixed water/land regions commonly found in coastal simulations. The approach presented here represents a practical methodology to rejuvenate legacy code on a commodity blade cluster with reasonable effort; our solution has direct application to other similar codes in the geosciences.

Optimal mapping of irregular finite element domains to parallel processors

NASA Technical Reports Server (NTRS)

Flower, J.; Otto, S.; Salama, M.

1987-01-01

Mapping the solution domain of n-finite elements into N-subdomains that may be processed in parallel by N-processors is an optimal one if the subdomain decomposition results in a well-balanced workload distribution among the processors. The problem is discussed in the context of irregular finite element domains as an important aspect of the efficient utilization of the capabilities of emerging multiprocessor computers. Finding the optimal mapping is an intractable combinatorial optimization problem, for which a satisfactory approximate solution is obtained here by analogy to a method used in statistical mechanics for simulating the annealing process in solids. The simulated annealing analogy and algorithm are described, and numerical results are given for mapping an irregular two-dimensional finite element domain containing a singularity onto the Hypercube computer.

Performance of Scattering Matrix Decomposition and Color Spaces for Synthetic Aperture Radar Imagery

DTIC Science & Technology

2010-03-01

Color Spaces and Synthetic Aperture Radar (SAR) Multicolor Imaging. 15 2.3.1 Colorimetry . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 16 2.3.2...III. Decomposition Techniques on SAR Polarimetry and Colorimetry applied to SAR Imagery...space polarimetric SAR systems. Colorimetry is also introduced in this chapter, presenting the fundamentals of the RGB and CMY color spaces, defined for

Influence of Temperature and Catalyst on the Decomposition of Potassium Chlorate in a Simple DTA-Apparatus.

ERIC Educational Resources Information Center

Wiederholt, Erwin

1983-01-01

DTA is a technique in which the temperature difference between sample/reference is measured as a function of temperature, while both are subject to a controlled temperature program. Use of a simple DTA-apparatus in demonstrating catalytic effects of manganese dioxide and aluminum oxide on decomposition temperature of potassium chlorate is…

Using Learning Decomposition and Bootstrapping with Randomization to Compare the Impact of Different Educational Interventions on Learning

ERIC Educational Resources Information Center

Feng, Mingyu; Beck, Joseph E.; Heffernan, Neil T.

2009-01-01

A basic question of instructional interventions is how effective it is in promoting student learning. This paper presents a study to determine the relative efficacy of different instructional strategies by applying an educational data mining technique, learning decomposition. We use logistic regression to determine how much learning is caused by…

Anodic electrochemical performances of MgCo{sub 2}O{sub 4} synthesized by oxalate decomposition method and electrospinning technique for Li-ion battery application

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

Darbar, Devendrasinh; Department of Mechanical Engineering, National University of Singapore, 117576; Department of Physics, National University of Singapore, 117542

2016-01-15

Highlights: • MgCo{sub 2}O{sub 4} was prepared by oxalate decomposition method and electrospinning technique. • Electrospun MgCo{sub 2}O{sub 4} shows the reversible capacity of 795 and 227 mAh g{sup −1} oxalate decomposition MgCo{sub 2}O{sub 4} after 50 cycle. • Electrospun MgCo{sub 2}O{sub 4} show good cycling stability and electrochemical performance. - Abstract: Magnesium cobalt oxide, MgCo{sub 2}O{sub 4} was synthesized by oxalate decomposition method and electrospinning technique. The electrochemical performances, structures, phase formation and morphology of MgCo{sub 2}O{sub 4} synthesized by both the methods are compared. Scanning electron microscope (SEM) studies show spherical and fiber type morphology, respectively for themore » oxalate decomposition and electrospinning method. The electrospun nanofibers of MgCo{sub 2}O{sub 4} calcined at 650 °C, showed a very good reversible capacity of 795 mAh g{sup −1} after 50 cycles when compared to bulk material capacity of 227 mAh g{sup −1} at current rate of 60 mA g{sup −1}. MgCo{sub 2}O{sub 4} nanofiber showed a reversible capacity of 411 mAh g{sup −1} (at cycle) at current density of 240 mA g{sup −1}. Improved performance was due to improved conductivity of MgO, which may act as buffer layer leading to improved cycling stability. The cyclic voltammetry studies at scan rate of 0.058 mV/s show main cathodic at around 1.0 V and anodic peaks at 2.1 V vs. Li.« less

Influence of Heat Treatments on Microstructure and Magnetic Domains in Duplex Stainless Steel S31803

NASA Astrophysics Data System (ADS)

Dille, Jean; Pacheco, Clara Johanna; Camerini, Cesar Giron; Malet, Loic Charles; Nysten, Bernard; Pereira, Gabriela Ribeiro; De Almeida, Luiz Henrique; Alcoforado Rebello, João Marcos

2018-06-01

The influence of heat treatments on microstructure and magnetic domains in duplex stainless steel S31803 is studied using an innovative structural characterization protocol. Electron backscatter diffraction (EBSD) maps as well as magnetic force microscopy (MFM) images acquired on the same region of the sample, before and after heat treatment, are compared. The influence of heat treatments on the phase volumetric fractions is studied, and several structural modifications after heat treatment are highlighted. Three different mechanisms for the decomposition of ferrite into sigma phase and secondary austenite are observed during annealing at 800 °C. MFM analysis reveals that a variety of magnetic domain patterns can exist in one ferrite grain.

Tissue artifact removal from respiratory signals based on empirical mode decomposition.

PubMed

Liu, Shaopeng; Gao, Robert X; John, Dinesh; Staudenmayer, John; Freedson, Patty

2013-05-01

On-line measurement of respiration plays an important role in monitoring human physical activities. Such measurement commonly employs sensing belts secured around the rib cage and abdomen of the test object. Affected by the movement of body tissues, respiratory signals typically have a low signal-to-noise ratio. Removing tissue artifacts therefore is critical to ensuring effective respiration analysis. This paper presents a signal decomposition technique for tissue artifact removal from respiratory signals, based on the empirical mode decomposition (EMD). An algorithm based on the mutual information and power criteria was devised to automatically select appropriate intrinsic mode functions for tissue artifact removal and respiratory signal reconstruction. Performance of the EMD-algorithm was evaluated through simulations and real-life experiments (N = 105). Comparison with low-pass filtering that has been conventionally applied confirmed the effectiveness of the technique in tissue artifacts removal.

An Integrated Centroid Finding and Particle Overlap Decomposition Algorithm for Stereo Imaging Velocimetry

NASA Technical Reports Server (NTRS)

McDowell, Mark

2004-01-01

An integrated algorithm for decomposing overlapping particle images (multi-particle objects) along with determining each object s constituent particle centroid(s) has been developed using image analysis techniques. The centroid finding algorithm uses a modified eight-direction search method for finding the perimeter of any enclosed object. The centroid is calculated using the intensity-weighted center of mass of the object. The overlap decomposition algorithm further analyzes the object data and breaks it down into its constituent particle centroid(s). This is accomplished with an artificial neural network, feature based technique and provides an efficient way of decomposing overlapping particles. Combining the centroid finding and overlap decomposition routines into a single algorithm allows us to accurately predict the error associated with finding the centroid(s) of particles in our experiments. This algorithm has been tested using real, simulated, and synthetic data and the results are presented and discussed.

Confinement in F4 Exceptional Gauge Group Using Domain Structures

NASA Astrophysics Data System (ADS)

Rafibakhsh, Shahnoosh; Shahlaei, Amir

2017-03-01

We calculate the potential between static quarks in the fundamental representation of the F4 exceptional gauge group using domain structures of the thick center vortex model. As non-trivial center elements are absent, the asymptotic string tension is lost while an intermediate linear potential is observed. SU(2) is a subgroup of F4. Investigating the decomposition of the 26 dimensional representation of F4 to the SU(2) representations, might explain what accounts for the intermediate linear potential, in the exceptional groups with no center element.

Optimal cost design of water distribution networks using a decomposition approach

NASA Astrophysics Data System (ADS)

Lee, Ho Min; Yoo, Do Guen; Sadollah, Ali; Kim, Joong Hoon

2016-12-01

Water distribution network decomposition, which is an engineering approach, is adopted to increase the efficiency of obtaining the optimal cost design of a water distribution network using an optimization algorithm. This study applied the source tracing tool in EPANET, which is a hydraulic and water quality analysis model, to the decomposition of a network to improve the efficiency of the optimal design process. The proposed approach was tested by carrying out the optimal cost design of two water distribution networks, and the results were compared with other optimal cost designs derived from previously proposed optimization algorithms. The proposed decomposition approach using the source tracing technique enables the efficient decomposition of an actual large-scale network, and the results can be combined with the optimal cost design process using an optimization algorithm. This proves that the final design in this study is better than those obtained with other previously proposed optimization algorithms.

Parallel processing for pitch splitting decomposition

NASA Astrophysics Data System (ADS)

Barnes, Levi; Li, Yong; Wadkins, David; Biederman, Steve; Miloslavsky, Alex; Cork, Chris

2009-10-01

Decomposition of an input pattern in preparation for a double patterning process is an inherently global problem in which the influence of a local decomposition decision can be felt across an entire pattern. In spite of this, a large portion of the work can be massively distributed. Here, we discuss the advantages of geometric distribution for polygon operations with limited range of influence. Further, we have found that even the naturally global "coloring" step can, in large part, be handled in a geometrically local manner. In some practical cases, up to 70% of the work can be distributed geometrically. We also describe the methods for partitioning the problem into local pieces and present scaling data up to 100 CPUs. These techniques reduce DPT decomposition runtime by orders of magnitude.

Understanding paper degradation: identification of products of cellulosic paper decomposition at the wet-dry "tideline" interface using GC-MS.

PubMed

Sladkevich, Sergey; Dupont, Anne-Laurence; Sablier, Michel; Seghouane, Dalila; Cole, Richard B

2016-11-01

Cellulose paper degradation products forming in the "tideline" area at the wet-dry interface of pure cellulose paper were analyzed using gas chromatography-electron ionization-mass spectrometry (GC-EI-MS) and high-resolution electrospray ionization-mass spectrometry (ESI-MS, LTQ Orbitrap) techniques. Different extraction protocols were employed in order to solubilize the products of oxidative cellulose decomposition, i.e., a direct solvent extraction or a more laborious chromophore release and identification (CRI) technique aiming to reveal products responsible for paper discoloration in the tideline area. Several groups of low molecular weight compounds were identified, suggesting a complex pathway of cellulose decomposition in the tidelines formed at the cellulose-water-oxygen interface. Our findings, namely the appearance of a wide range of linear saturated carboxylic acids (from formic to nonanoic), support the oxidative autocatalytic mechanism of decomposition. In addition, the identification of several furanic compounds (which can be, in part, responsible for paper discoloration) plus anhydro carbohydrate derivatives sheds more light on the pathways of cellulose decomposition. Most notably, the mechanisms of tideline formation in the presence of molecular oxygen appear surprisingly similar to pathways of pyrolytic cellulose degradation. More complex chromophore compounds were not detected in this study, thereby revealing a difference between this short-term tideline experiment and longer-term cellulose aging.

Application of vacuum stability test to determine thermal decomposition kinetics of nitramines bonded by polyurethane matrix

NASA Astrophysics Data System (ADS)

Elbeih, Ahmed; Abd-Elghany, Mohamed; Elshenawy, Tamer

2017-03-01

Vacuum stability test (VST) is mainly used to study compatibility and stability of energetic materials. In this work, VST has been investigated to study thermal decomposition kinetics of four cyclic nitramines, 1,3,5-trinitro-1,3,5-triazinane (RDX) and 1,3,5,7-tetranitro-1,3,5,7-tetrazocane (HMX), cis-1,3,4,6-tetranitrooctahydroimidazo-[4,5-d]imidazole (BCHMX), 2,4,6,8,10,12-hexanitro-2,4,6,8,10,12-hexaazaisowurtzitane (ε-HNIW, CL-20), bonded by polyurethane matrix based on hydroxyl terminated polybutadiene (HTPB). Model fitting and model free (isoconversional) methods have been applied to determine the decomposition kinetics from VST results. For comparison, the decomposition kinetics were determined isothermally by ignition delay technique and non-isothermally by Advanced Kinetics and Technology Solution (AKTS) software. The activation energies for thermolysis obtained by isoconversional method based on VST technique of RDX/HTPB, HMX/HTPB, BCHMX/HTPB and CL20/HTPB were 157.1, 203.1, 190.0 and 176.8 kJ mol-1 respectively. Model fitting method proved that the mechanism of thermal decomposition of BCHMX/HTPB is controlled by the nucleation model while all the other studied PBXs are controlled by the diffusion models. A linear relationship between the ignition temperatures and the activation energies was observed. BCHMX/HTPB is interesting new PBX in the research stage.

Comparison and Computational Performance of Tsunami-HySEA and MOST Models for the LANTEX 2013 scenario

NASA Astrophysics Data System (ADS)

González-Vida, Jose M.; Macías, Jorge; Mercado, Aurelio; Ortega, Sergio; Castro, Manuel J.

2017-04-01

Tsunami-HySEA model is used to simulate the Caribbean LANTEX 2013 scenario (LANTEX is the acronym for Large AtlaNtic Tsunami EXercise, which is carried out annually). The numerical simulation of the propagation and inundation phases, is performed with both models but using different mesh resolutions and nested meshes. Some comparisons with the MOST tsunami model available at the University of Puerto Rico (UPR) are made. Both models compare well for propagating tsunami waves in open sea, producing very similar results. In near-shore shallow waters, Tsunami-HySEA should be compared with the inundation version of MOST, since the propagation version of MOST is limited to deeper waters. Regarding the inundation phase, a 1 arc-sec (approximately 30 m) resolution mesh covering all of Puerto Rico, is used, and a three-level nested meshes technique implemented. In the inundation phase, larger differences between model results are observed. Nevertheless, the most striking difference resides in computational time; Tsunami-HySEA is coded using the advantages of GPU architecture, and can produce a 4 h simulation in a 60 arcsec resolution grid for the whole Caribbean Sea in less than 4 min with a single general-purpose GPU and as fast as 11 s with 32 general-purpose GPUs. In the inundation stage with nested meshes, approximately 8 hours of wall clock time is needed for a 2-h simulation in a single GPU (versus more than 2 days for the MOST inundation, running three different parts of the island—West, Center, East—at the same time due to memory limitations in MOST). When domain decomposition techniques are finally implemented by breaking up the computational domain into sub-domains and assigning a GPU to each sub-domain (multi-GPU Tsunami-HySEA version), we show that the wall clock time significantly decreases, allowing high-resolution inundation modelling in very short computational times, reducing, for example, if eight GPUs are used, the wall clock time to around 1 hour. Besides, these computational times are obtained using general-purpose GPU hardware.

Intelligent transportation systems data compression using wavelet decomposition technique.

DOT National Transportation Integrated Search

2009-12-01

Intelligent Transportation Systems (ITS) generates massive amounts of traffic data, which posts : challenges for data storage, transmission and retrieval. Data compression and reconstruction technique plays an : important role in ITS data procession....

Coarse-to-fine markerless gait analysis based on PCA and Gauss-Laguerre decomposition

NASA Astrophysics Data System (ADS)

Goffredo, Michela; Schmid, Maurizio; Conforto, Silvia; Carli, Marco; Neri, Alessandro; D'Alessio, Tommaso

2005-04-01

Human movement analysis is generally performed through the utilization of marker-based systems, which allow reconstructing, with high levels of accuracy, the trajectories of markers allocated on specific points of the human body. Marker based systems, however, show some drawbacks that can be overcome by the use of video systems applying markerless techniques. In this paper, a specifically designed computer vision technique for the detection and tracking of relevant body points is presented. It is based on the Gauss-Laguerre Decomposition, and a Principal Component Analysis Technique (PCA) is used to circumscribe the region of interest. Results obtained on both synthetic and experimental tests provide significant reduction of the computational costs, with no significant reduction of the tracking accuracy.

A taxonomy and comparison of parallel block multi-level preconditioners for the incompressible Navier-Stokes equations.

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

Shadid, John Nicolas; Elman, Howard; Shuttleworth, Robert R.

2007-04-01

In recent years, considerable effort has been placed on developing efficient and robust solution algorithms for the incompressible Navier-Stokes equations based on preconditioned Krylov methods. These include physics-based methods, such as SIMPLE, and purely algebraic preconditioners based on the approximation of the Schur complement. All these techniques can be represented as approximate block factorization (ABF) type preconditioners. The goal is to decompose the application of the preconditioner into simplified sub-systems in which scalable multi-level type solvers can be applied. In this paper we develop a taxonomy of these ideas based on an adaptation of a generalized approximate factorization of themore » Navier-Stokes system first presented in [25]. This taxonomy illuminates the similarities and differences among these preconditioners and the central role played by efficient approximation of certain Schur complement operators. We then present a parallel computational study that examines the performance of these methods and compares them to an additive Schwarz domain decomposition (DD) algorithm. Results are presented for two and three-dimensional steady state problems for enclosed domains and inflow/outflow systems on both structured and unstructured meshes. The numerical experiments are performed using MPSalsa, a stabilized finite element code.« less

Gradient-based multiresolution image fusion.

PubMed

Petrović, Valdimir S; Xydeas, Costas S

2004-02-01

A novel approach to multiresolution signal-level image fusion is presented for accurately transferring visual information from any number of input image signals, into a single fused image without loss of information or the introduction of distortion. The proposed system uses a "fuse-then-decompose" technique realized through a novel, fusion/decomposition system architecture. In particular, information fusion is performed on a multiresolution gradient map representation domain of image signal information. At each resolution, input images are represented as gradient maps and combined to produce new, fused gradient maps. Fused gradient map signals are processed, using gradient filters derived from high-pass quadrature mirror filters to yield a fused multiresolution pyramid representation. The fused output image is obtained by applying, on the fused pyramid, a reconstruction process that is analogous to that of conventional discrete wavelet transform. This new gradient fusion significantly reduces the amount of distortion artefacts and the loss of contrast information usually observed in fused images obtained from conventional multiresolution fusion schemes. This is because fusion in the gradient map domain significantly improves the reliability of the feature selection and information fusion processes. Fusion performance is evaluated through informal visual inspection and subjective psychometric preference tests, as well as objective fusion performance measurements. Results clearly demonstrate the superiority of this new approach when compared to conventional fusion systems.

Discussion summary: Fictitious domain methods

NASA Technical Reports Server (NTRS)

Glowinski, Rowland; Rodrigue, Garry

1991-01-01

Fictitious Domain methods are constructed in the following manner: Suppose a partial differential equation is to be solved on an open bounded set, Omega, in 2-D or 3-D. Let R be a rectangle domain containing the closure of Omega. The partial differential equation is first solved on R. Using the solution on R, the solution of the equation on Omega is then recovered by some procedure. The advantage of the fictitious domain method is that in many cases the solution of a partial differential equation on a rectangular region is easier to compute than on a nonrectangular region. Fictitious domain methods for solving elliptic PDEs on general regions are also very efficient when used on a parallel computer. The reason is that one can use the many domain decomposition methods that are available for solving the PDE on the fictitious rectangular region. The discussion on fictitious domain methods began with a talk by R. Glowinski in which he gave some examples of a variational approach to ficititious domain methods for solving the Helmholtz and Navier-Stokes equations.

Sizes of lipid domains: What do we know from artificial lipid membranes? What are the possible shared features with membrane rafts in cells?

PubMed

Rosetti, Carla M; Mangiarotti, Agustín; Wilke, Natalia

2017-05-01

In model lipid membranes with phase coexistence, domain sizes distribute in a very wide range, from the nanometer (reported in vesicles and supported films) to the micrometer (observed in many model membranes). Domain growth by coalescence and Ostwald ripening is slow (minutes to hours), the domain size being correlated with the size of the capture region. Domain sizes thus strongly depend on the number of domains which, in the case of a nucleation process, depends on the oversaturation of the system, on line tension and on the perturbation rate in relation to the membrane dynamics. Here, an overview is given of the factors that affect nucleation or spinodal decomposition and domain growth, and their influence on the distribution of domain sizes in different model membranes is discussed. The parameters analyzed respond to very general physical rules, and we therefore propose a similar behavior for the rafts in the plasma membrane of cells, but with obstructed mobility and with a continuously changing environment. Copyright © 2017 Elsevier B.V. All rights reserved.

Refinement and application of acoustic impulse technique to study nozzle transmission characteristics

NASA Technical Reports Server (NTRS)

Salikuddin, M.; Brown, W. H.; Ramakrishnan, R.; Tanna, H. K.

1983-01-01

An improved acoustic impulse technique was developed and was used to study the transmission characteristics of duct/nozzle systems. To accomplish the above objective, various problems associated with the existing spark-discharge impulse technique were first studied. These included (1) the nonlinear behavior of high intensity pulses, (2) the contamination of the signal with flow noise, (3) low signal-to-noise ratio at high exhaust velocities, and (4) the inability to control or shape the signal generated by the source, specially when multiple spark points were used as the source. The first step to resolve these problems was the replacement of the spark-discharge source with electroacoustic driver(s). These included (1) synthesizing on acoustic impulse with acoustic driver(s) to control and shape the output signal, (2) time domain signal averaging to remove flow noise from the contaminated signal, (3) signal editing to remove unwanted portions of the time history, (4) spectral averaging, and (5) numerical smoothing. The acoustic power measurement technique was improved by taking multiple induct measurements and by a modal decomposition process to account for the contribution of higher order modes in the power computation. The improved acoustic impulse technique was then validated by comparing the results derived by an impedance tube method. The mechanism of acoustic power loss, that occurs when sound is transmitted through nozzle terminations, was investigated. Finally, the refined impulse technique was applied to obtain more accurate results for the acoustic transmission characteristics of a conical nozzle and a multi-lobe multi-tube supressor nozzle.

A physics-motivated Centroidal Voronoi Particle domain decomposition method

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

Fu, Lin, E-mail: lin.fu@tum.de; Hu, Xiangyu Y., E-mail: xiangyu.hu@tum.de; Adams, Nikolaus A., E-mail: nikolaus.adams@tum.de

2017-04-15

In this paper, we propose a novel domain decomposition method for large-scale simulations in continuum mechanics by merging the concepts of Centroidal Voronoi Tessellation (CVT) and Voronoi Particle dynamics (VP). The CVT is introduced to achieve a high-level compactness of the partitioning subdomains by the Lloyd algorithm which monotonically decreases the CVT energy. The number of computational elements between neighboring partitioning subdomains, which scales the communication effort for parallel simulations, is optimized implicitly as the generated partitioning subdomains are convex and simply connected with small aspect-ratios. Moreover, Voronoi Particle dynamics employing physical analogy with a tailored equation of state ismore » developed, which relaxes the particle system towards the target partition with good load balance. Since the equilibrium is computed by an iterative approach, the partitioning subdomains exhibit locality and the incremental property. Numerical experiments reveal that the proposed Centroidal Voronoi Particle (CVP) based algorithm produces high-quality partitioning with high efficiency, independently of computational-element types. Thus it can be used for a wide range of applications in computational science and engineering.« less

On the Hodge-type decomposition and cohomology groups of k-Cauchy-Fueter complexes over domains in the quaternionic space

NASA Astrophysics Data System (ADS)

Chang, Der-Chen; Markina, Irina; Wang, Wei

2016-09-01

The k-Cauchy-Fueter operator D0(k) on one dimensional quaternionic space H is the Euclidean version of spin k / 2 massless field operator on the Minkowski space in physics. The k-Cauchy-Fueter equation for k ≥ 2 is overdetermined and its compatibility condition is given by the k-Cauchy-Fueter complex. In quaternionic analysis, these complexes play the role of Dolbeault complex in several complex variables. We prove that a natural boundary value problem associated to this complex is regular. Then by using the theory of regular boundary value problems, we show the Hodge-type orthogonal decomposition, and the fact that the non-homogeneous k-Cauchy-Fueter equation D0(k) u = f on a smooth domain Ω in H is solvable if and only if f satisfies the compatibility condition and is orthogonal to the set ℋ(k)1 (Ω) of Hodge-type elements. This set is isomorphic to the first cohomology group of the k-Cauchy-Fueter complex over Ω, which is finite dimensional, while the second cohomology group is always trivial.

Parallel Finite Element Domain Decomposition for Structural/Acoustic Analysis

NASA Technical Reports Server (NTRS)

Nguyen, Duc T.; Tungkahotara, Siroj; Watson, Willie R.; Rajan, Subramaniam D.

2005-01-01

A domain decomposition (DD) formulation for solving sparse linear systems of equations resulting from finite element analysis is presented. The formulation incorporates mixed direct and iterative equation solving strategics and other novel algorithmic ideas that are optimized to take advantage of sparsity and exploit modern computer architecture, such as memory and parallel computing. The most time consuming part of the formulation is identified and the critical roles of direct sparse and iterative solvers within the framework of the formulation are discussed. Experiments on several computer platforms using several complex test matrices are conducted using software based on the formulation. Small-scale structural examples are used to validate thc steps in the formulation and large-scale (l,000,000+ unknowns) duct acoustic examples are used to evaluate the ORIGIN 2000 processors, and a duster of 6 PCs (running under the Windows environment). Statistics show that the formulation is efficient in both sequential and parallel computing environmental and that the formulation is significantly faster and consumes less memory than that based on one of the best available commercialized parallel sparse solvers.

A physics-motivated Centroidal Voronoi Particle domain decomposition method

NASA Astrophysics Data System (ADS)

Fu, Lin; Hu, Xiangyu Y.; Adams, Nikolaus A.

2017-04-01

In this paper, we propose a novel domain decomposition method for large-scale simulations in continuum mechanics by merging the concepts of Centroidal Voronoi Tessellation (CVT) and Voronoi Particle dynamics (VP). The CVT is introduced to achieve a high-level compactness of the partitioning subdomains by the Lloyd algorithm which monotonically decreases the CVT energy. The number of computational elements between neighboring partitioning subdomains, which scales the communication effort for parallel simulations, is optimized implicitly as the generated partitioning subdomains are convex and simply connected with small aspect-ratios. Moreover, Voronoi Particle dynamics employing physical analogy with a tailored equation of state is developed, which relaxes the particle system towards the target partition with good load balance. Since the equilibrium is computed by an iterative approach, the partitioning subdomains exhibit locality and the incremental property. Numerical experiments reveal that the proposed Centroidal Voronoi Particle (CVP) based algorithm produces high-quality partitioning with high efficiency, independently of computational-element types. Thus it can be used for a wide range of applications in computational science and engineering.

High Frequency Electromechanical Imaging of Ferroelectrics in a Liquid Environment

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

Jesse, Stephen; Chu, Ying-Hao; Kalinin, Sergei V

The coupling between electrical and mechanical phenomena is a ubiquitous feature of many information and energy storage materials and devices. In addition to involvement in performance and degradation mechanisms, electromechanical effects underpin a broad spectrum of nanoscale imaging and spectroscopies including piezoresponse force and electrochemical strain microscopies. Traditionally, these studies are conducted under ambient conditions. However, applications related to imaging energy storage and electrophysiological phenomena require operation in a liquid phase and therefore the development of electromechanical probing techniques suitable to liquid environments. Due to the relative high conductivity of most liquids and liquid decomposition at low voltages, the transfermore » of characterization techniques from ambient to liquid is not straightforward. Here we present a detailed study of ferroelectric domain imaging and manipulation in thin film BiFeO{sub 3} using piezoresponse force microscopy in liquid environments as model systems for electromechanical phenomena in general. We explore the use of contact resonance enhancement and the application of multifrequency excitation and detection principles to overcome the experimental problems introduced by a liquid environment. Understanding electromechanical sample characterization in liquid is a key aspect not only for ferroelectric oxides but also for biological and electrochemical sample systems.« less

Decentralized system identification using stochastic subspace identification on wireless smart sensor networks

NASA Astrophysics Data System (ADS)

Sim, Sung-Han; Spencer, Billie F., Jr.; Park, Jongwoong; Jung, Hyungjo

2012-04-01

Wireless Smart Sensor Networks (WSSNs) facilitates a new paradigm to structural identification and monitoring for civil infrastructure. Conventional monitoring systems based on wired sensors and centralized data acquisition and processing have been considered to be challenging and costly due to cabling and expensive equipment and maintenance costs. WSSNs have emerged as a technology that can overcome such difficulties, making deployment of a dense array of sensors on large civil structures both feasible and economical. However, as opposed to wired sensor networks in which centralized data acquisition and processing is common practice, WSSNs require decentralized computing algorithms to reduce data transmission due to the limitation associated with wireless communication. Thus, several system identification methods have been implemented to process sensor data and extract essential information, including Natural Excitation Technique with Eigensystem Realization Algorithm, Frequency Domain Decomposition (FDD), and Random Decrement Technique (RDT); however, Stochastic Subspace Identification (SSI) has not been fully utilized in WSSNs, while SSI has the strong potential to enhance the system identification. This study presents a decentralized system identification using SSI in WSSNs. The approach is implemented on MEMSIC's Imote2 sensor platform and experimentally verified using a 5-story shear building model.

Towards reduced order modelling for predicting the dynamics of coherent vorticity structures within wind turbine wakes

NASA Astrophysics Data System (ADS)

Debnath, M.; Santoni, C.; Leonardi, S.; Iungo, G. V.

2017-03-01

The dynamics of the velocity field resulting from the interaction between the atmospheric boundary layer and a wind turbine array can affect significantly the performance of a wind power plant and the durability of wind turbines. In this work, dynamics in wind turbine wakes and instabilities of helicoidal tip vortices are detected and characterized through modal decomposition techniques. The dataset under examination consists of snapshots of the velocity field obtained from large-eddy simulations (LES) of an isolated wind turbine, for which aerodynamic forcing exerted by the turbine blades on the atmospheric boundary layer is mimicked through the actuator line model. Particular attention is paid to the interaction between the downstream evolution of the helicoidal tip vortices and the alternate vortex shedding from the turbine tower. The LES dataset is interrogated through different modal decomposition techniques, such as proper orthogonal decomposition and dynamic mode decomposition. The dominant wake dynamics are selected for the formulation of a reduced order model, which consists in a linear time-marching algorithm where temporal evolution of flow dynamics is obtained from the previous temporal realization multiplied by a time-invariant operator. This article is part of the themed issue 'Wind energy in complex terrains'.

Pressure-induced metallization of condensed phase β-HMX under shock loadings via molecular dynamics simulations in conjunction with multi-scale shock technique.

PubMed

Ge, Ni-Na; Wei, Yong-Kai; Zhao, Feng; Chen, Xiang-Rong; Ji, Guang-Fu

2014-07-01

The electronic structure and initial decomposition in high explosive HMX under conditions of shock loading are examined. The simulation is performed using quantum molecular dynamics in conjunction with multi-scale shock technique (MSST). A self-consistent charge density-functional tight-binding (SCC-DFTB) method is adapted. The results show that the N-N-C angle has a drastic change under shock wave compression along lattice vector b at shock velocity 11 km/s, which is the main reason that leads to an insulator-to-metal transition for the HMX system. The metallization pressure (about 130 GPa) of condensed-phase HMX is predicted firstly. We also detect the formation of several key products of condensed-phase HMX decomposition, such as NO2, NO, N2, N2O, H2O, CO, and CO2, and all of them have been observed in previous experimental studies. Moreover, the initial decomposition products include H2 due to the C-H bond breaking as a primary reaction pathway at extreme condition, which presents a new insight into the initial decomposition mechanism of HMX under shock loading at the atomistic level.

Signal enhancement based on complex curvelet transform and complementary ensemble empirical mode decomposition

NASA Astrophysics Data System (ADS)

Dong, Lieqian; Wang, Deying; Zhang, Yimeng; Zhou, Datong

2017-09-01

Signal enhancement is a necessary step in seismic data processing. In this paper we utilize the complementary ensemble empirical mode decomposition (CEEMD) and complex curvelet transform (CCT) methods to separate signal from random noise further to improve the signal to noise (S/N) ratio. Firstly, the original data with noise is decomposed into a series of intrinsic mode function (IMF) profiles with the aid of CEEMD. Then the IMFs with noise are transformed into CCT domain. By choosing different thresholds which are based on the noise level difference of each IMF profile, the noise in original data can be suppressed. Finally, we illustrate the effectiveness of the approach by simulated and field datasets.

Thermal and Chemical Characterization of Non-Metallic Materials Using Coupled Thermogravimetric Analysis and Infrared Spectroscopy

NASA Technical Reports Server (NTRS)

Huff, Timothy L.

2002-01-01

Thermogravimetric analysis (TGA) is widely employed in the thermal characterization of non-metallic materials, yielding valuable information on decomposition characteristics of a sample over a wide temperature range. However, a potential wealth of chemical information is lost during the process, with the evolving gases generated during thermal decomposition escaping through the exhaust line. Fourier Transform-Infrared spectroscopy (FT-IR) is a powerful analytical technique for determining many chemical constituents while in any material state, in this application, the gas phase. By linking these two techniques, evolving gases generated during the TGA process are directed into an appropriately equipped infrared spectrometer for chemical speciation. Consequently, both thermal decomposition and chemical characterization of a material may be obtained in a single sample run. In practice, a heated transfer line is employed to connect the two instruments while a purge gas stream directs the evolving gases into the FT-IR. The purge gas can be either high purity air or an inert gas such as nitrogen to allow oxidative and pyrolytic processes to be examined, respectively. The FT-IR data is collected realtime, allowing continuous monitoring of chemical compositional changes over the course of thermal decomposition. Using this coupled technique, an array of diverse materials has been examined, including composites, plastics, rubber, fiberglass epoxy resins, polycarbonates, silicones, lubricants and fluorocarbon materials. The benefit of combining these two methodologies is of particular importance in the aerospace community, where newly developing materials have little available data with which to refer. By providing both thermal and chemical data simultaneously, a more definitive and comprehensive characterization of the material is possible. Additionally, this procedure has been found to be a viable screening technique for certain materials, with the generated data useful in the selection of other appropriate analytical procedures for further material characterization.

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.

Crystal structures of carbonates up to Mbar pressures determined by single crystal synchrotron radiation diffraction

NASA Astrophysics Data System (ADS)

Merlini, M.

2013-12-01

The recent improvements at synchrotron beamlines, currently allow single crystal diffraction experiments at extreme pressures and temperatures [1,2] on very small single crystal domains. We successfully applied such technique to determine the crystal structure adopted by carbonates at mantle pressures. The knowledge of carbon-bearing phases is in fact fundamental for any quantitative modelling of global carbon cycle. The major technical difficulty arises after first order transitions or decomposition reactions, since original crystal (apx. 10x10x5 μm3) is transformed in much smaller crystalline domains often with random orientation. The use of 3D reciprocal space visualization software and the improved resolution of new generation flat panel detectors, however, allow both identification and integration of each single crystal domain, with suitable accuracy for ab-initio structure solution, performed with direct and charge-flipping methods and successive structure refinements. The results obtained on carbonates, indicate two major crystal-chemistry trends established at high pressures. The CO32- units, planar and parallel in ambient pressure calcite and dolomite structures, becomes non parallel in calcite- and dolomite-II and III phases, allowing more flexibility in the structures with possibility to accommodate strain arising from different cation sizes (Ca and Mg in particular). Dolomite-III is therefore also observed to be thermodynamically stable at lower mantle pressures and temperatures, differently from dolomite, which undergoes decomposition into pure end-members in upper mantle. At higher pressure, towards Mbar (lowermost mantle and D'' region) in agreement with theoretical calculations [3,4] and other experimental results [5], carbon coordination transform into 4-fold CO4 units, with different polymerisation in the structure depending on carbonate composition. The second important crystal chemistry feature detected is related to Fe2+ in Fe-bearing magnesite, which spontaneously oxidises at HP/HT, forming Fe3+ carbonates, Fe3+ oxides and reduced carbon (diamonds). Single crystal diffraction approach allowed full structure determination of these phases, yielding to the discovery of few unpredicted structures, such as Mg2Fe2C4O13 and Fe13O19, which can be well reproduced in different experiments. Mg2Fe2C4O13 carbonate present truncated chain C4O13 groups, and Fe13O19 oxide, whose stoichiometry is intermediate between magnetite and hematite, is a one-layer structure, with features encountered in superconducting materials. The results fully support the ideas of unexpected complexities in the mineralogy of the lowermost mantle, and single crystal technique, once properly optimized in ad-hoc synchrotron beamlines, is fundamental for extracting accurate structural information, otherwise rarely accessible with other experimental techniques. References: [1] Merlini M., Hanfland M. (2013). Single crystal diffraction at Mbar conditions by synchrotron radiation. High Pressure Research, in press. [2] Dubrovinsky et al., (2010). High Pressure Research, 30, 620-633. [3] Arapan et al. (1997). Phys. Rev. Lett., 98, 268501. [4] Oganov et al. (2008) EPSL, 273, 38-47. [5] Boulard et al. (2011) PNAS, 108, 5184-5187.

The Distributed Diagonal Force Decomposition Method for Parallelizing Molecular Dynamics Simulations

PubMed Central

Boršnik, Urban; Miller, Benjamin T.; Brooks, Bernard R.; Janežič, Dušanka

2011-01-01

Parallelization is an effective way to reduce the computational time needed for molecular dynamics simulations. We describe a new parallelization method, the distributed-diagonal force decomposition method, with which we extend and improve the existing force decomposition methods. Our new method requires less data communication during molecular dynamics simulations than replicated data and current force decomposition methods, increasing the parallel efficiency. It also dynamically load-balances the processors' computational load throughout the simulation. The method is readily implemented in existing molecular dynamics codes and it has been incorporated into the CHARMM program, allowing its immediate use in conjunction with the many molecular dynamics simulation techniques that are already present in the program. We also present the design of the Force Decomposition Machine, a cluster of personal computers and networks that is tailored to running molecular dynamics simulations using the distributed diagonal force decomposition method. The design is expandable and provides various degrees of fault resilience. This approach is easily adaptable to computers with Graphics Processing Units because it is independent of the processor type being used. PMID:21793007

Sparse decomposition of seismic data and migration using Gaussian beams with nonzero initial curvature

NASA Astrophysics Data System (ADS)

Liu, Peng; Wang, Yanfei

2018-04-01

We study problems associated with seismic data decomposition and migration imaging. We first represent the seismic data utilizing Gaussian beam basis functions, which have nonzero curvature, and then consider the sparse decomposition technique. The sparse decomposition problem is an l0-norm constrained minimization problem. In solving the l0-norm minimization, a polynomial Radon transform is performed to achieve sparsity, and a fast gradient descent method is used to calculate the waveform functions. The waveform functions can subsequently be used for sparse Gaussian beam migration. Compared with traditional sparse Gaussian beam methods, the seismic data can be properly reconstructed employing fewer Gaussian beams with nonzero initial curvature. The migration approach described in this paper is more efficient than the traditional sparse Gaussian beam migration.

Statistical image-domain multimaterial decomposition for dual-energy CT.

PubMed

Xue, Yi; Ruan, Ruoshui; Hu, Xiuhua; Kuang, Yu; Wang, Jing; Long, Yong; Niu, Tianye

2017-03-01

Dual-energy CT (DECT) enhances tissue characterization because of its basis material decomposition capability. In addition to conventional two-material decomposition from DECT measurements, multimaterial decomposition (MMD) is required in many clinical applications. To solve the ill-posed problem of reconstructing multi-material images from dual-energy measurements, additional constraints are incorporated into the formulation, including volume and mass conservation and the assumptions that there are at most three materials in each pixel and various material types among pixels. The recently proposed flexible image-domain MMD method decomposes pixels sequentially into multiple basis materials using a direct inversion scheme which leads to magnified noise in the material images. In this paper, we propose a statistical image-domain MMD method for DECT to suppress the noise. The proposed method applies penalized weighted least-square (PWLS) reconstruction with a negative log-likelihood term and edge-preserving regularization for each material. The statistical weight is determined by a data-based method accounting for the noise variance of high- and low-energy CT images. We apply the optimization transfer principles to design a serial of pixel-wise separable quadratic surrogates (PWSQS) functions which monotonically decrease the cost function. The separability in each pixel enables the simultaneous update of all pixels. The proposed method is evaluated on a digital phantom, Catphan©600 phantom and three patients (pelvis, head, and thigh). We also implement the direct inversion and low-pass filtration methods for a comparison purpose. Compared with the direct inversion method, the proposed method reduces noise standard deviation (STD) in soft tissue by 95.35% in the digital phantom study, by 88.01% in the Catphan©600 phantom study, by 92.45% in the pelvis patient study, by 60.21% in the head patient study, and by 81.22% in the thigh patient study, respectively. The overall volume fraction accuracy is improved by around 6.85%. Compared with the low-pass filtration method, the root-mean-square percentage error (RMSE(%)) of electron densities in the Catphan©600 phantom is decreased by 20.89%. As modulation transfer function (MTF) magnitude decreased to 50%, the proposed method increases the spatial resolution by an overall factor of 1.64 on the digital phantom, and 2.16 on the Catphan©600 phantom. The overall volume fraction accuracy is increased by 6.15%. We proposed a statistical image-domain MMD method using DECT measurements. The method successfully suppresses the magnified noise while faithfully retaining the quantification accuracy and anatomical structure in the decomposed material images. The proposed method is practical and promising for advanced clinical applications using DECT imaging. © 2017 American Association of Physicists in Medicine.

Numerical simulations of incompressible laminar flows using viscous-inviscid interaction procedures

NASA Astrophysics Data System (ADS)

Shatalov, Alexander V.

The present method is based on Helmholtz velocity decomposition where velocity is written as a sum of irrotational (gradient of a potential) and rotational (correction due to vorticity) components. Substitution of the velocity decomposition into the continuity equation yields an equation for the potential, while substitution into the momentum equations yields equations for the velocity corrections. A continuation approach is used to relate the pressure to the gradient of the potential through a modified Bernoulli's law, which allows the elimination of the pressure variable from the momentum equations. The present work considers steady and unsteady two-dimensional incompressible flows over an infinite cylinder and NACA 0012 airfoil shape. The numerical results are compared against standard methods (stream function-vorticity and SMAC methods) and data available in literature. The results demonstrate that the proposed formulation leads to a good approximation with some possible benefits compared to the available formulations. The method is not restricted to two-dimensional flows and can be used for viscous-inviscid domain decomposition calculations.

Scenario-based modeling for multiple allocation hub location problem under disruption risk: multiple cuts Benders decomposition approach

NASA Astrophysics Data System (ADS)

Yahyaei, Mohsen; Bashiri, Mahdi

2017-12-01

The hub location problem arises in a variety of domains such as transportation and telecommunication systems. In many real-world situations, hub facilities are subject to disruption. This paper deals with the multiple allocation hub location problem in the presence of facilities failure. To model the problem, a two-stage stochastic formulation is developed. In the proposed model, the number of scenarios grows exponentially with the number of facilities. To alleviate this issue, two approaches are applied simultaneously. The first approach is to apply sample average approximation to approximate the two stochastic problem via sampling. Then, by applying the multiple cuts Benders decomposition approach, computational performance is enhanced. Numerical studies show the effective performance of the SAA in terms of optimality gap for small problem instances with numerous scenarios. Moreover, performance of multi-cut Benders decomposition is assessed through comparison with the classic version and the computational results reveal the superiority of the multi-cut approach regarding the computational time and number of iterations.

Development of Fast Algorithms Using Recursion, Nesting and Iterations for Computational Electromagnetics

NASA Technical Reports Server (NTRS)

Chew, W. C.; Song, J. M.; Lu, C. C.; Weedon, W. H.

1995-01-01

In the first phase of our work, we have concentrated on laying the foundation to develop fast algorithms, including the use of recursive structure like the recursive aggregate interaction matrix algorithm (RAIMA), the nested equivalence principle algorithm (NEPAL), the ray-propagation fast multipole algorithm (RPFMA), and the multi-level fast multipole algorithm (MLFMA). We have also investigated the use of curvilinear patches to build a basic method of moments code where these acceleration techniques can be used later. In the second phase, which is mainly reported on here, we have concentrated on implementing three-dimensional NEPAL on a massively parallel machine, the Connection Machine CM-5, and have been able to obtain some 3D scattering results. In order to understand the parallelization of codes on the Connection Machine, we have also studied the parallelization of 3D finite-difference time-domain (FDTD) code with PML material absorbing boundary condition (ABC). We found that simple algorithms like the FDTD with material ABC can be parallelized very well allowing us to solve within a minute a problem of over a million nodes. In addition, we have studied the use of the fast multipole method and the ray-propagation fast multipole algorithm to expedite matrix-vector multiplication in a conjugate-gradient solution to integral equations of scattering. We find that these methods are faster than LU decomposition for one incident angle, but are slower than LU decomposition when many incident angles are needed as in the monostatic RCS calculations.

Fast divide-and-conquer algorithm for evaluating polarization in classical force fields

NASA Astrophysics Data System (ADS)

Nocito, Dominique; Beran, Gregory J. O.

2017-03-01

Evaluation of the self-consistent polarization energy forms a major computational bottleneck in polarizable force fields. In large systems, the linear polarization equations are typically solved iteratively with techniques based on Jacobi iterations (JI) or preconditioned conjugate gradients (PCG). Two new variants of JI are proposed here that exploit domain decomposition to accelerate the convergence of the induced dipoles. The first, divide-and-conquer JI (DC-JI), is a block Jacobi algorithm which solves the polarization equations within non-overlapping sub-clusters of atoms directly via Cholesky decomposition, and iterates to capture interactions between sub-clusters. The second, fuzzy DC-JI, achieves further acceleration by employing overlapping blocks. Fuzzy DC-JI is analogous to an additive Schwarz method, but with distance-based weighting when averaging the fuzzy dipoles from different blocks. Key to the success of these algorithms is the use of K-means clustering to identify natural atomic sub-clusters automatically for both algorithms and to determine the appropriate weights in fuzzy DC-JI. The algorithm employs knowledge of the 3-D spatial interactions to group important elements in the 2-D polarization matrix. When coupled with direct inversion in the iterative subspace (DIIS) extrapolation, fuzzy DC-JI/DIIS in particular converges in a comparable number of iterations as PCG, but with lower computational cost per iteration. In the end, the new algorithms demonstrated here accelerate the evaluation of the polarization energy by 2-3 fold compared to existing implementations of PCG or JI/DIIS.

Enhancement of lung sounds based on empirical mode decomposition and Fourier transform algorithm.

PubMed

Mondal, Ashok; Banerjee, Poulami; Somkuwar, Ajay

2017-02-01

There is always heart sound (HS) signal interfering during the recording of lung sound (LS) signals. This obscures the features of LS signals and creates confusion on pathological states, if any, of the lungs. In this work, a new method is proposed for reduction of heart sound interference which is based on empirical mode decomposition (EMD) technique and prediction algorithm. In this approach, first the mixed signal is split into several components in terms of intrinsic mode functions (IMFs). Thereafter, HS-included segments are localized and removed from them. The missing values of the gap thus produced, is predicted by a new Fast Fourier Transform (FFT) based prediction algorithm and the time domain LS signal is reconstructed by taking an inverse FFT of the estimated missing values. The experiments have been conducted on simulated and recorded HS corrupted LS signals at three different flow rates and various SNR levels. The performance of the proposed method is evaluated by qualitative and quantitative analysis of the results. It is found that the proposed method is superior to the baseline method in terms of quantitative and qualitative measurement. The developed method gives better results compared to baseline method for different SNR levels. Our method gives cross correlation index (CCI) of 0.9488, signal to deviation ratio (SDR) of 9.8262, and normalized maximum amplitude error (NMAE) of 26.94 for 0 dB SNR value. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

Problem decomposition by mutual information and force-based clustering

NASA Astrophysics Data System (ADS)

Otero, Richard Edward

The scale of engineering problems has sharply increased over the last twenty years. Larger coupled systems, increasing complexity, and limited resources create a need for methods that automatically decompose problems into manageable sub-problems by discovering and leveraging problem structure. The ability to learn the coupling (inter-dependence) structure and reorganize the original problem could lead to large reductions in the time to analyze complex problems. Such decomposition methods could also provide engineering insight on the fundamental physics driving problem solution. This work forwards the current state of the art in engineering decomposition through the application of techniques originally developed within computer science and information theory. The work describes the current state of automatic problem decomposition in engineering and utilizes several promising ideas to advance the state of the practice. Mutual information is a novel metric for data dependence and works on both continuous and discrete data. Mutual information can measure both the linear and non-linear dependence between variables without the limitations of linear dependence measured through covariance. Mutual information is also able to handle data that does not have derivative information, unlike other metrics that require it. The value of mutual information to engineering design work is demonstrated on a planetary entry problem. This study utilizes a novel tool developed in this work for planetary entry system synthesis. A graphical method, force-based clustering, is used to discover related sub-graph structure as a function of problem structure and links ranked by their mutual information. This method does not require the stochastic use of neural networks and could be used with any link ranking method currently utilized in the field. Application of this method is demonstrated on a large, coupled low-thrust trajectory problem. Mutual information also serves as the basis for an alternative global optimizer, called MIMIC, which is unrelated to Genetic Algorithms. Advancement to the current practice demonstrates the use of MIMIC as a global method that explicitly models problem structure with mutual information, providing an alternate method for globally searching multi-modal domains. By leveraging discovered problem inter- dependencies, MIMIC may be appropriate for highly coupled problems or those with large function evaluation cost. This work introduces a useful addition to the MIMIC algorithm that enables its use on continuous input variables. By leveraging automatic decision tree generation methods from Machine Learning and a set of randomly generated test problems, decision trees for which method to apply are also created, quantifying decomposition performance over a large region of the design space.

Acceleration of aircraft-level Traffic Flow Management

NASA Astrophysics Data System (ADS)

Rios, Joseph Lucio

This dissertation describes novel approaches to solving large-scale, high fidelity, aircraft-level Traffic Flow Management scheduling problems. Depending on the methods employed, solving these problems to optimality can take longer than the length of the planning horizon in question. Research in this domain typically focuses on the quality of the modeling used to describe the problem and the benefits achieved from the optimized solution, often treating computational aspects as secondary or tertiary. The work presented here takes the complementary view and considers the computational aspect as the primary concern. To this end, a previously published model for solving this Traffic Flow Management scheduling problem is used as starting point for this study. The model proposed by Bertsimas and Stock-Patterson is a binary integer program taking into account all major resource capacities and the trajectories of each flight to decide which flights should be held in which resource for what amount of time in order to satisfy all capacity requirements. For large instances, the solve time using state-of-the-art solvers is prohibitive for use within a potential decision support tool. With this dissertation, however, it will be shown that solving can be achieved in reasonable time for instances of real-world size. Five other techniques developed and tested for this dissertation will be described in detail. These are heuristic methods that provide good results. Performance is measured in terms of runtime and "optimality gap." We then describe the most successful method presented in this dissertation: Dantzig-Wolfe Decomposition. Results indicate that a parallel implementation of Dantzig-Wolfe Decomposition optimally solves the original problem in much reduced time and with better integrality and smaller optimality gap than any of the heuristic methods or state-of-the-art, commercial solvers. The solution quality improves in every measureable way as the number of subproblems solved in parallel increases. A maximal decomposition provides the best results of any method tested. The convergence qualities of Dantzig-Wolfe Decomposition have been criticized in the past, so we examine what makes the Bertsimas-Stock Patterson model so amenable to use of this method. These mathematical qualities of the model are generalized to provide guidance on other problems that may benefit from massively parallel Dantzig-Wolfe Decomposition. This result, together with the development of the software, and the experimental results indicating the feasibility of real-time, nationwide Traffic Flow Management scheduling represent the major contributions of this dissertation.

A Signal Processing Approach with a Smooth Empirical Mode Decomposition to Reveal Hidden Trace of Corrosion in Highly Contaminated Guided Wave Signals for Concrete-Covered Pipes

PubMed Central

Rostami, Javad; Chen, Jingming; Tse, Peter W.

2017-01-01

Ultrasonic guided waves have been extensively applied for non-destructive testing of plate-like structures particularly pipes in past two decades. In this regard, if a structure has a simple geometry, obtained guided waves’ signals are easy to explain. However, any small degree of complexity in the geometry such as contacting with other materials may cause an extra amount of complication in the interpretation of guided wave signals. The problem deepens if defects have irregular shapes such as natural corrosion. Signal processing techniques that have been proposed for guided wave signals’ analysis are generally good for simple signals obtained in a highly controlled experimental environment. In fact, guided wave signals in a real situation such as the existence of natural corrosion in wall-covered pipes are much more complicated. Considering pipes in residential buildings that pass through concrete walls, in this paper we introduced Smooth Empirical Mode Decomposition (SEMD) to efficiently separate overlapped guided waves. As empirical mode decomposition (EMD) which is a good candidate for analyzing non-stationary signals, suffers from some shortcomings, wavelet transform was adopted in the sifting stage of EMD to improve its outcome in SEMD. However, selection of mother wavelet that suits best for our purpose plays an important role. Since in guided wave inspection, the incident waves are well known and are usually tone-burst signals, we tailored a complex tone-burst signal to be used as our mother wavelet. In the sifting stage of EMD, wavelet de-noising was applied to eliminate unwanted frequency components from each IMF. SEMD greatly enhances the performance of EMD in guided wave analysis for highly contaminated signals. In our experiment on concrete covered pipes with natural corrosion, this method not only separates the concrete wall indication clearly in time domain signal, a natural corrosion with complex geometry that was hidden and located inside the concrete section was successfully exposed. PMID:28178220

A Signal Processing Approach with a Smooth Empirical Mode Decomposition to Reveal Hidden Trace of Corrosion in Highly Contaminated Guided Wave Signals for Concrete-Covered Pipes.

PubMed

Rostami, Javad; Chen, Jingming; Tse, Peter W

2017-02-07

Ultrasonic guided waves have been extensively applied for non-destructive testing of plate-like structures particularly pipes in past two decades. In this regard, if a structure has a simple geometry, obtained guided waves' signals are easy to explain. However, any small degree of complexity in the geometry such as contacting with other materials may cause an extra amount of complication in the interpretation of guided wave signals. The problem deepens if defects have irregular shapes such as natural corrosion. Signal processing techniques that have been proposed for guided wave signals' analysis are generally good for simple signals obtained in a highly controlled experimental environment. In fact, guided wave signals in a real situation such as the existence of natural corrosion in wall-covered pipes are much more complicated. Considering pipes in residential buildings that pass through concrete walls, in this paper we introduced Smooth Empirical Mode Decomposition (SEMD) to efficiently separate overlapped guided waves. As empirical mode decomposition (EMD) which is a good candidate for analyzing non-stationary signals, suffers from some shortcomings, wavelet transform was adopted in the sifting stage of EMD to improve its outcome in SEMD. However, selection of mother wavelet that suits best for our purpose plays an important role. Since in guided wave inspection, the incident waves are well known and are usually tone-burst signals, we tailored a complex tone-burst signal to be used as our mother wavelet. In the sifting stage of EMD, wavelet de-noising was applied to eliminate unwanted frequency components from each IMF. SEMD greatly enhances the performance of EMD in guided wave analysis for highly contaminated signals. In our experiment on concrete covered pipes with natural corrosion, this method not only separates the concrete wall indication clearly in time domain signal, a natural corrosion with complex geometry that was hidden and located inside the concrete section was successfully exposed.

Enhancing our View of the Reservoir: New Insights into Deepwater Gulf of Mexico fields using Frequency Decomposition

NASA Astrophysics Data System (ADS)

Murat, M.

2017-12-01

Color-blended frequency decomposition is a seismic attribute that can be used to educe or draw out and visualize geomorphological features enabling a better understanding of reservoir architecture and connectivity for both exploration and field development planning. Color-blended frequency decomposition was applied to seismic data in several areas of interest in the Deepwater Gulf of Mexico. The objective was stratigraphic characterization to better define reservoir extent, highlight depositional features, identify thicker reservoir zones and examine potential connectivity issues due to stratigraphic variability. Frequency decomposition is a technique to analyze changes in seismic frequency caused by changes in the reservoir thickness, lithology and fluid content. This technique decomposes or separates the seismic frequency spectra into discrete bands of frequency limited seismic data using digital filters. The workflow consists of frequency (spectral) decomposition, RGB color blending of three frequency slices, and horizon or stratal slicing of the color blended frequency data for interpretation. Patterns were visualized and identified in the data that were not obvious on standard stacked seismic sections. These seismic patterns were interpreted and compared to known geomorphological patterns and their environment of deposition. From this we inferred the distribution of potential reservoir sand versus non-reservoir shale and even finer scale details such as the overall direction of the sediment transport and relative thickness. In exploratory areas, stratigraphic characterization from spectral decomposition is used for prospect risking and well planning. Where well control exists, we can validate the seismic observations and our interpretation and use the stratigraphic/geomorphological information to better inform decisions on the need for and placement of development wells.

Real-time simulation of biological soft tissues: a PGD approach.

PubMed

Niroomandi, S; González, D; Alfaro, I; Bordeu, F; Leygue, A; Cueto, E; Chinesta, F

2013-05-01

We introduce here a novel approach for the numerical simulation of nonlinear, hyperelastic soft tissues at kilohertz feedback rates necessary for haptic rendering. This approach is based upon the use of proper generalized decomposition techniques, a generalization of PODs. Proper generalized decomposition techniques can be considered as a means of a priori model order reduction and provides a physics-based meta-model without the need for prior computer experiments. The suggested strategy is thus composed of an offline phase, in which a general meta-model is computed, and an online evaluation phase in which the results are obtained at real time. Results are provided that show the potential of the proposed technique, together with some benchmark test that shows the accuracy of the method. Copyright © 2013 John Wiley & Sons, Ltd.

Decomposition of the Inequality of Income Distribution by Income Types—Application for Romania

NASA Astrophysics Data System (ADS)

Andrei, Tudorel; Oancea, Bogdan; Richmond, Peter; Dhesi, Gurjeet; Herteliu, Claudiu

2017-09-01

This paper identifies the salient factors that characterize the inequality income distribution for Romania. Data analysis is rigorously carried out using sophisticated techniques borrowed from classical statistics (Theil). Decomposition of the inequalities measured by the Theil index is also performed. This study relies on an exhaustive (11.1 million records for 2014) data-set for total personal gross income of Romanian citizens.

MAUD: An Interactive Computer Program for the Structuring, Decomposition, and Recomposition of Preferences between Multiattributed Alternatives. Final Report. Technical Report 543.

ERIC Educational Resources Information Center

Humphreys, Patrick; Wisudha, Ayleen

As a demonstration of the application of heuristic devices to decision-theoretical techniques, an interactive computer program known as MAUD (Multiattribute Utility Decomposition) has been designed to support decision or choice problems that can be decomposed into component factors, or to act as a tool for investigating the microstructure of a…

A technique for plasma velocity-space cross-correlation

NASA Astrophysics Data System (ADS)

Mattingly, Sean; Skiff, Fred

2018-05-01

An advance in experimental plasma diagnostics is presented and used to make the first measurement of a plasma velocity-space cross-correlation matrix. The velocity space correlation function can detect collective fluctuations of plasmas through a localized measurement. An empirical decomposition, singular value decomposition, is applied to this Hermitian matrix in order to obtain the plasma fluctuation eigenmode structure on the ion distribution function. A basic theory is introduced and compared to the modes obtained by the experiment. A full characterization of these modes is left for future work, but an outline of this endeavor is provided. Finally, the requirements for this experimental technique in other plasma regimes are discussed.

Study of thermal decomposition mechanisms and low-level detection of explosives using pulsed photoacoustic technique

NASA Astrophysics Data System (ADS)

Yehya, F.; Chaudhary, A. K.; Srinivas, D.; Muralidharan, K.

2015-11-01

We report a novel time-resolved photoacoustic-based technique for studying the thermal decomposition mechanisms of some secondary explosives such as RDX (hexahydro-1,3,5-trinitro-1,3,5-triazine), picric acid, 4,6-dinitro-5-(4-nitro-1 H-imidazol-1-yl)-1 H-benzo[ d] [1-3] triazole, and 5-chloro-1-(4-nitrophenyl)-1 H-tetrazole. A comparison of the thermal decomposition mechanisms of these secondary explosives was made by detecting NO2 molecules released under controlled pyrolysis between 25 and 350 °C. The results show excellent agreement with the thermogravimetric and differential thermal analysis (TGA-DTA) results. A specially designed PA cell made of stainless steel was filled with explosive vapor and pumped using second harmonic, i.e., λ = 532 nm, pulses of duration 7 ns at a 10 Hz repetition rate, obtained using a Q-switched Nd:YAG laser. The use of a combination of PA and TGA-DTA techniques enables the study of NO2 generation, and this method can be used to scale the performance of these explosives as rocket fuels. The minimum detection limits of the four explosives were 38 ppmv to 69 ppbv, depending on their respective vapor pressures.

On the use of the singular value decomposition for text retrieval

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

Husbands, P.; Simon, H.D.; Ding, C.

2000-12-04

The use of the Singular Value Decomposition (SVD) has been proposed for text retrieval in several recent works. This technique uses the SVD to project very high dimensional document and query vectors into a low dimensional space. In this new space it is hoped that the underlying structure of the collection is revealed thus enhancing retrieval performance. Theoretical results have provided some evidence for this claim and to some extent experiments have confirmed this. However, these studies have mostly used small test collections and simplified document models. In this work we investigate the use of the SVD on large documentmore » collections. We show that, if interpreted as a mechanism for representing the terms of the collection, this technique alone is insufficient for dealing with the variability in term occurrence. Section 2 introduces the text retrieval concepts necessary for our work. A short description of our experimental architecture is presented in Section 3. Section 4 describes how term occurrence variability affects the SVD and then shows how the decomposition influences retrieval performance. A possible way of improving SVD-based techniques is presented in Section 5 and concluded in Section 6.« less

Identification of channel geometries applying seismic attributes and spectral decomposition techniques, Temsah Field, Offshore East Nile Delta, Egypt

NASA Astrophysics Data System (ADS)

Othman, Adel A. A.; Fathy, M.; Negm, Adel

2018-06-01

The Temsah field is located in eastern part of the Nile delta to seaward. The main reservoirs of the area are Middle Pliocene mainly consist from siliciclastic which associated with a close deep marine environment. The Distribution pattern of the reservoir facies is limited scale indicating fast lateral and vertical changes which are not easy to resolve by applying of conventional seismic attribute. The target of the present study is to create geophysical workflows to a better image of the channel sand distribution in the study area. We apply both Average Absolute Amplitude and Energy attribute which are indicated on the distribution of the sand bodies in the study area but filled to fully described the channel geometry. So another tool, which offers more detailed geometry description is needed. The spectral decomposition analysis method is an alternative technique focused on processing Discrete Fourier Transform which can provide better results. Spectral decomposition have been done over the upper channel shows that the frequency in the eastern part of the channel is the same frequency in places where the wells are drilled, which confirm the connection of both the eastern and western parts of the upper channel. Results suggest that application of the spectral decomposition method leads to reliable inferences. Hence, using the spectral decomposition method alone or along with other attributes has a positive impact on reserves growth and increased production where the reserve in the study area increases to 75bcf.

Study of the Gray Scale, Polychromatic, Distortion Invariant Neural Networks Using the Ipa Model.

NASA Astrophysics Data System (ADS)

Uang, Chii-Maw

Research in the optical neural network field is primarily motivated by the fact that humans recognize objects better than the conventional digital computers and the massively parallel inherent nature of optics. This research represents a continuous effort during the past several years in the exploitation of using neurocomputing for pattern recognition. Based on the interpattern association (IPA) model and Hamming net model, many new systems and applications are introduced. A gray level discrete associative memory that is based on object decomposition/composition is proposed for recognizing gray-level patterns. This technique extends the processing ability from the binary mode to gray-level mode, and thus the information capacity is increased. Two polychromatic optical neural networks using color liquid crystal television (LCTV) panels for color pattern recognition are introduced. By introducing a color encoding technique in conjunction with the interpattern associative algorithm, a color associative memory was realized. Based on the color decomposition and composition technique, a color exemplar-based Hamming net was built for color image classification. A shift-invariant neural network is presented through use of the translation invariant property of the modulus of the Fourier transformation and the hetero-associative interpattern association (IPA) memory. To extract the main features, a quadrantal sampling method is used to sampled data and then replace the training patterns. Using the concept of hetero-associative memory to recall the distorted object. A shift and rotation invariant neural network using an interpattern hetero-association (IHA) model is presented. To preserve the shift and rotation invariant properties, a set of binarized-encoded circular harmonic expansion (CHE) functions at the Fourier domain is used as the training set. We use the shift and symmetric properties of the modulus of the Fourier spectrum to avoid the problem of centering the CHE functions. Almost all neural networks have the positive and negative weights, which increases the difficulty of optical implementation. A method to construct a unipolar IPA IWM is discussed. By searching the redundant interconnection links, an effective way that removes all negative links is discussed.

Mode decomposition and Lagrangian structures of the flow dynamics in orbitally shaken bioreactors

NASA Astrophysics Data System (ADS)

Weheliye, Weheliye Hashi; Cagney, Neil; Rodriguez, Gregorio; Micheletti, Martina; Ducci, Andrea

2018-03-01

In this study, two mode decomposition techniques were applied and compared to assess the flow dynamics in an orbital shaken bioreactor (OSB) of cylindrical geometry and flat bottom: proper orthogonal decomposition and dynamic mode decomposition. Particle Image Velocimetry (PIV) experiments were carried out for different operating conditions including fluid height, h, and shaker rotational speed, N. A detailed flow analysis is provided for conditions when the fluid and vessel motions are in-phase (Fr = 0.23) and out-of-phase (Fr = 0.47). PIV measurements in vertical and horizontal planes were combined to reconstruct low order models of the full 3D flow and to determine its Finite-Time Lyapunov Exponent (FTLE) within OSBs. The combined results from the mode decomposition and the FTLE fields provide a useful insight into the flow dynamics and Lagrangian coherent structures in OSBs and offer a valuable tool to optimise bioprocess design in terms of mixing and cell suspension.

Augmenting the decomposition of EMG signals using supervised feature extraction techniques.

PubMed

Parsaei, Hossein; Gangeh, Mehrdad J; Stashuk, Daniel W; Kamel, Mohamed S

2012-01-01

Electromyographic (EMG) signal decomposition is the process of resolving an EMG signal into its constituent motor unit potential trains (MUPTs). In this work, the possibility of improving the decomposing results using two supervised feature extraction methods, i.e., Fisher discriminant analysis (FDA) and supervised principal component analysis (SPCA), is explored. Using the MUP labels provided by a decomposition-based quantitative EMG system as a training data for FDA and SPCA, the MUPs are transformed into a new feature space such that the MUPs of a single MU become as close as possible to each other while those created by different MUs become as far as possible. The MUPs are then reclassified using a certainty-based classification algorithm. Evaluation results using 10 simulated EMG signals comprised of 3-11 MUPTs demonstrate that FDA and SPCA on average improve the decomposition accuracy by 6%. The improvement for the most difficult-to-decompose signal is about 12%, which shows the proposed approach is most beneficial in the decomposition of more complex signals.

X-Ray Thomson Scattering Without the Chihara Decomposition

NASA Astrophysics Data System (ADS)

Magyar, Rudolph; Baczewski, Andrew; Shulenburger, Luke; Hansen, Stephanie B.; Desjarlais, Michael P.; Sandia National Laboratories Collaboration

X-Ray Thomson Scattering is an important experimental technique used in dynamic compression experiments to measure the properties of warm dense matter. The fundamental property probed in these experiments is the electronic dynamic structure factor that is typically modeled using an empirical three-term decomposition (Chihara, J. Phys. F, 1987). One of the crucial assumptions of this decomposition is that the system's electrons can be either classified as bound to ions or free. This decomposition may not be accurate for materials in the warm dense regime. We present unambiguous first principles calculations of the dynamic structure factor independent of the Chihara decomposition that can be used to benchmark these assumptions. Results are generated using a finite-temperature real-time time-dependent density functional theory applied for the first time in these conditions. 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-AC04-94AL85000.

A fast new algorithm for a robot neurocontroller using inverse QR decomposition

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

Morris, A.S.; Khemaissia, S.

2000-01-01

A new adaptive neural network controller for robots is presented. The controller is based on direct adaptive techniques. Unlike many neural network controllers in the literature, inverse dynamical model evaluation is not required. A numerically robust, computationally efficient processing scheme for neutral network weight estimation is described, namely, the inverse QR decomposition (INVQR). The inverse QR decomposition and a weighted recursive least-squares (WRLS) method for neural network weight estimation is derived using Cholesky factorization of the data matrix. The algorithm that performs the efficient INVQR of the underlying space-time data matrix may be implemented in parallel on a triangular array.more » Furthermore, its systolic architecture is well suited for VLSI implementation. Another important benefit is well suited for VLSI implementation. Another important benefit of the INVQR decomposition is that it solves directly for the time-recursive least-squares filter vector, while avoiding the sequential back-substitution step required by the QR decomposition approaches.« less

The response of the HMX-based material PBXN-9 to thermal insults: thermal decomposition kinetics and morphological changes

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

Glascoe, E A; Hsu, P C; Springer, H K

PBXN-9, an HMX-formulation, is thermally damaged and thermally decomposed in order to determine the morphological changes and decomposition kinetics that occur in the material after mild to moderate heating. The material and its constituents were decomposed using standard thermal analysis techniques (DSC and TGA) and the decomposition kinetics are reported using different kinetic models. Pressed parts and prill were thermally damaged, i.e. heated to temperatures that resulted in material changes but did not result in significant decomposition or explosion, and analyzed. In general, the thermally damaged samples showed a significant increase in porosity and decrease in density and a smallmore » amount of weight loss. These PBXN-9 samples appear to sustain more thermal damage than similar HMX-Viton A formulations and the most likely reasons are the decomposition/evaporation of a volatile plasticizer and a polymorphic transition of the HMX from {beta} to {delta} phase.« less

Concurrent Probabilistic Simulation of High Temperature Composite Structural Response

NASA Technical Reports Server (NTRS)

Abdi, Frank

1996-01-01

A computational structural/material analysis and design tool which would meet industry's future demand for expedience and reduced cost is presented. This unique software 'GENOA' is dedicated to parallel and high speed analysis to perform probabilistic evaluation of high temperature composite response of aerospace systems. The development is based on detailed integration and modification of diverse fields of specialized analysis techniques and mathematical models to combine their latest innovative capabilities into a commercially viable software package. The technique is specifically designed to exploit the availability of processors to perform computationally intense probabilistic analysis assessing uncertainties in structural reliability analysis and composite micromechanics. The primary objectives which were achieved in performing the development were: (1) Utilization of the power of parallel processing and static/dynamic load balancing optimization to make the complex simulation of structure, material and processing of high temperature composite affordable; (2) Computational integration and synchronization of probabilistic mathematics, structural/material mechanics and parallel computing; (3) Implementation of an innovative multi-level domain decomposition technique to identify the inherent parallelism, and increasing convergence rates through high- and low-level processor assignment; (4) Creating the framework for Portable Paralleled architecture for the machine independent Multi Instruction Multi Data, (MIMD), Single Instruction Multi Data (SIMD), hybrid and distributed workstation type of computers; and (5) Market evaluation. The results of Phase-2 effort provides a good basis for continuation and warrants Phase-3 government, and industry partnership.

Enhanced decomposition of stable soil organic carbon and microbial catabolic potentials by long-term field warming

DOE PAGES

Feng, Wenting; Liang, Junyi; Hale, Lauren E.; ...

2017-06-09

Quantifying soil organic carbon (SOC) decomposition under warming is critical to predict carbon–climate feedbacks. According to the substrate regulating principle, SOC decomposition would decrease as labile SOC declines under field warming, but observations of SOC decomposition under warming do not always support this prediction. This discrepancy could result from varying changes in SOC components and soil microbial communities under warming. This study aimed to determine the decomposition of SOC components with different turnover times after subjected to long-term field warming and/or root exclusion to limit C input, and to test whether SOC decomposition is driven by substrate lability under warming.more » Taking advantage of a 12-year field warming experiment in a prairie, we assessed the decomposition of SOC components by incubating soils from control and warmed plots, with and without root exclusion for 3 years. We assayed SOC decomposition from these incubations by combining inverse modeling and microbial functional genes during decomposition with a metagenomic technique (GeoChip). The decomposition of SOC components with turnover times of years and decades, which contributed to 95% of total cumulative CO 2 respiration, was greater in soils from warmed plots. But the decomposition of labile SOC was similar in warmed plots compared to the control. The diversity of C-degradation microbial genes generally declined with time during the incubation in all treatments, suggesting shifts of microbial functional groups as substrate composition was changing. Compared to the control, soils from warmed plots showed significant increase in the signal intensities of microbial genes involved in degrading complex organic compounds, implying enhanced potential abilities of microbial catabolism. These are likely responsible for accelerated decomposition of SOC components with slow turnover rates. Overall, the shifted microbial community induced by long-term warming accelerates the decomposition of SOC components with slow turnover rates and thus amplify the positive feedback to climate change.« less

Enhanced decomposition of stable soil organic carbon and microbial catabolic potentials by long-term field warming

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

Feng, Wenting; Liang, Junyi; Hale, Lauren E.

Quantifying soil organic carbon (SOC) decomposition under warming is critical to predict carbon–climate feedbacks. According to the substrate regulating principle, SOC decomposition would decrease as labile SOC declines under field warming, but observations of SOC decomposition under warming do not always support this prediction. This discrepancy could result from varying changes in SOC components and soil microbial communities under warming. This study aimed to determine the decomposition of SOC components with different turnover times after subjected to long-term field warming and/or root exclusion to limit C input, and to test whether SOC decomposition is driven by substrate lability under warming.more » Taking advantage of a 12-year field warming experiment in a prairie, we assessed the decomposition of SOC components by incubating soils from control and warmed plots, with and without root exclusion for 3 years. We assayed SOC decomposition from these incubations by combining inverse modeling and microbial functional genes during decomposition with a metagenomic technique (GeoChip). The decomposition of SOC components with turnover times of years and decades, which contributed to 95% of total cumulative CO 2 respiration, was greater in soils from warmed plots. But the decomposition of labile SOC was similar in warmed plots compared to the control. The diversity of C-degradation microbial genes generally declined with time during the incubation in all treatments, suggesting shifts of microbial functional groups as substrate composition was changing. Compared to the control, soils from warmed plots showed significant increase in the signal intensities of microbial genes involved in degrading complex organic compounds, implying enhanced potential abilities of microbial catabolism. These are likely responsible for accelerated decomposition of SOC components with slow turnover rates. Overall, the shifted microbial community induced by long-term warming accelerates the decomposition of SOC components with slow turnover rates and thus amplify the positive feedback to climate change.« less

Enhanced decomposition of stable soil organic carbon and microbial catabolic potentials by long-term field warming.

PubMed

Feng, Wenting; Liang, Junyi; Hale, Lauren E; Jung, Chang Gyo; Chen, Ji; Zhou, Jizhong; Xu, Minggang; Yuan, Mengting; Wu, Liyou; Bracho, Rosvel; Pegoraro, Elaine; Schuur, Edward A G; Luo, Yiqi

2017-11-01

Quantifying soil organic carbon (SOC) decomposition under warming is critical to predict carbon-climate feedbacks. According to the substrate regulating principle, SOC decomposition would decrease as labile SOC declines under field warming, but observations of SOC decomposition under warming do not always support this prediction. This discrepancy could result from varying changes in SOC components and soil microbial communities under warming. This study aimed to determine the decomposition of SOC components with different turnover times after subjected to long-term field warming and/or root exclusion to limit C input, and to test whether SOC decomposition is driven by substrate lability under warming. Taking advantage of a 12-year field warming experiment in a prairie, we assessed the decomposition of SOC components by incubating soils from control and warmed plots, with and without root exclusion for 3 years. We assayed SOC decomposition from these incubations by combining inverse modeling and microbial functional genes during decomposition with a metagenomic technique (GeoChip). The decomposition of SOC components with turnover times of years and decades, which contributed to 95% of total cumulative CO 2 respiration, was greater in soils from warmed plots. But the decomposition of labile SOC was similar in warmed plots compared to the control. The diversity of C-degradation microbial genes generally declined with time during the incubation in all treatments, suggesting shifts of microbial functional groups as substrate composition was changing. Compared to the control, soils from warmed plots showed significant increase in the signal intensities of microbial genes involved in degrading complex organic compounds, implying enhanced potential abilities of microbial catabolism. These are likely responsible for accelerated decomposition of SOC components with slow turnover rates. Overall, the shifted microbial community induced by long-term warming accelerates the decomposition of SOC components with slow turnover rates and thus amplify the positive feedback to climate change. © 2017 John Wiley & Sons Ltd.

Wind Farm Flow Modeling using an Input-Output Reduced-Order Model

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

Annoni, Jennifer; Gebraad, Pieter; Seiler, Peter

Wind turbines in a wind farm operate individually to maximize their own power regardless of the impact of aerodynamic interactions on neighboring turbines. There is the potential to increase power and reduce overall structural loads by properly coordinating turbines. To perform control design and analysis, a model needs to be of low computational cost, but retains the necessary dynamics seen in high-fidelity models. The objective of this work is to obtain a reduced-order model that represents the full-order flow computed using a high-fidelity model. A variety of methods, including proper orthogonal decomposition and dynamic mode decomposition, can be used tomore » extract the dominant flow structures and obtain a reduced-order model. In this paper, we combine proper orthogonal decomposition with a system identification technique to produce an input-output reduced-order model. This technique is used to construct a reduced-order model of the flow within a two-turbine array computed using a large-eddy simulation.« less

Preparation and catalytic activities of LaFeO3 and Fe2O3 for HMX thermal decomposition.

PubMed

Wei, Zhi-Xian; Xu, Yan-Qing; Liu, Hai-Yan; Hu, Chang-Wen

2009-06-15

Perovskite-type LaFeO(3) and alpha-Fe(2)O(3) with high specific surface areas were directly prepared with appropriate stearic acid-nitrates ratios by a novel stearic acid solution combustion method. The obtained powders were characterized by XRD, FT-IR and XPS techniques. The catalytic activities of perovskite-type LaFeO(3) and alpha-Fe(2)O(3) for the thermal decomposition of octahydro-1,3,5,7-tetranitro-1,3,5,7-tetrazocine (HMX) were investigated by TG and TG-EGA techniques. The experimental results show that the catalytic activity of perovskite-type LaFeO(3) was much higher than that of alpha-Fe(2)O(3) because of higher concentration of surface-adsorbed oxygen (O(ad)) and hydroxyl of LaFeO(3). The study points out a potential way to develop new and more active perovskite-type catalysts for the HMX thermal decomposition.

Separable decompositions of bipartite mixed states

NASA Astrophysics Data System (ADS)

Li, Jun-Li; Qiao, Cong-Feng

2018-04-01

We present a practical scheme for the decomposition of a bipartite mixed state into a sum of direct products of local density matrices, using the technique developed in Li and Qiao (Sci. Rep. 8:1442, 2018). In the scheme, the correlation matrix which characterizes the bipartite entanglement is first decomposed into two matrices composed of the Bloch vectors of local states. Then, we show that the symmetries of Bloch vectors are consistent with that of the correlation matrix, and the magnitudes of the local Bloch vectors are lower bounded by the correlation matrix. Concrete examples for the separable decompositions of bipartite mixed states are presented for illustration.

Software-engineering challenges of building and deploying reusable problem solvers.

PubMed

O'Connor, Martin J; Nyulas, Csongor; Tu, Samson; Buckeridge, David L; Okhmatovskaia, Anna; Musen, Mark A

2009-11-01

Problem solving methods (PSMs) are software components that represent and encode reusable algorithms. They can be combined with representations of domain knowledge to produce intelligent application systems. A goal of research on PSMs is to provide principled methods and tools for composing and reusing algorithms in knowledge-based systems. The ultimate objective is to produce libraries of methods that can be easily adapted for use in these systems. Despite the intuitive appeal of PSMs as conceptual building blocks, in practice, these goals are largely unmet. There are no widely available tools for building applications using PSMs and no public libraries of PSMs available for reuse. This paper analyzes some of the reasons for the lack of widespread adoptions of PSM techniques and illustrate our analysis by describing our experiences developing a complex, high-throughput software system based on PSM principles. We conclude that many fundamental principles in PSM research are useful for building knowledge-based systems. In particular, the task-method decomposition process, which provides a means for structuring knowledge-based tasks, is a powerful abstraction for building systems of analytic methods. However, despite the power of PSMs in the conceptual modeling of knowledge-based systems, software engineering challenges have been seriously underestimated. The complexity of integrating control knowledge modeled by developers using PSMs with the domain knowledge that they model using ontologies creates a barrier to widespread use of PSM-based systems. Nevertheless, the surge of recent interest in ontologies has led to the production of comprehensive domain ontologies and of robust ontology-authoring tools. These developments present new opportunities to leverage the PSM approach.

Software-engineering challenges of building and deploying reusable problem solvers

PubMed Central

O’CONNOR, MARTIN J.; NYULAS, CSONGOR; TU, SAMSON; BUCKERIDGE, DAVID L.; OKHMATOVSKAIA, ANNA; MUSEN, MARK A.

2012-01-01

Problem solving methods (PSMs) are software components that represent and encode reusable algorithms. They can be combined with representations of domain knowledge to produce intelligent application systems. A goal of research on PSMs is to provide principled methods and tools for composing and reusing algorithms in knowledge-based systems. The ultimate objective is to produce libraries of methods that can be easily adapted for use in these systems. Despite the intuitive appeal of PSMs as conceptual building blocks, in practice, these goals are largely unmet. There are no widely available tools for building applications using PSMs and no public libraries of PSMs available for reuse. This paper analyzes some of the reasons for the lack of widespread adoptions of PSM techniques and illustrate our analysis by describing our experiences developing a complex, high-throughput software system based on PSM principles. We conclude that many fundamental principles in PSM research are useful for building knowledge-based systems. In particular, the task–method decomposition process, which provides a means for structuring knowledge-based tasks, is a powerful abstraction for building systems of analytic methods. However, despite the power of PSMs in the conceptual modeling of knowledge-based systems, software engineering challenges have been seriously underestimated. The complexity of integrating control knowledge modeled by developers using PSMs with the domain knowledge that they model using ontologies creates a barrier to widespread use of PSM-based systems. Nevertheless, the surge of recent interest in ontologies has led to the production of comprehensive domain ontologies and of robust ontology-authoring tools. These developments present new opportunities to leverage the PSM approach. PMID:23565031

A Screen Space GPGPU Surface LIC Algorithm for Distributed Memory Data Parallel Sort Last Rendering Infrastructures

NASA Astrophysics Data System (ADS)

Loring, B.; Karimabadi, H.; Rortershteyn, V.

2015-10-01

The surface line integral convolution(LIC) visualization technique produces dense visualization of vector fields on arbitrary surfaces. We present a screen space surface LIC algorithm for use in distributed memory data parallel sort last rendering infrastructures. The motivations for our work are to support analysis of datasets that are too large to fit in the main memory of a single computer and compatibility with prevalent parallel scientific visualization tools such as ParaView and VisIt. By working in screen space using OpenGL we can leverage the computational power of GPUs when they are available and run without them when they are not. We address efficiency and performance issues that arise from the transformation of data from physical to screen space by selecting an alternate screen space domain decomposition. We analyze the algorithm's scaling behavior with and without GPUs on two high performance computing systems using data from turbulent plasma simulations.

Second International Workshop on Software Engineering and Code Design in Parallel Meteorological and Oceanographic Applications

NASA Technical Reports Server (NTRS)

OKeefe, Matthew (Editor); Kerr, Christopher L. (Editor)

1998-01-01

This report contains the abstracts and technical papers from the Second International Workshop on Software Engineering and Code Design in Parallel Meteorological and Oceanographic Applications, held June 15-18, 1998, in Scottsdale, Arizona. The purpose of the workshop is to bring together software developers in meteorology and oceanography to discuss software engineering and code design issues for parallel architectures, including Massively Parallel Processors (MPP's), Parallel Vector Processors (PVP's), Symmetric Multi-Processors (SMP's), Distributed Shared Memory (DSM) multi-processors, and clusters. Issues to be discussed include: (1) code architectures for current parallel models, including basic data structures, storage allocation, variable naming conventions, coding rules and styles, i/o and pre/post-processing of data; (2) designing modular code; (3) load balancing and domain decomposition; (4) techniques that exploit parallelism efficiently yet hide the machine-related details from the programmer; (5) tools for making the programmer more productive; and (6) the proliferation of programming models (F--, OpenMP, MPI, and HPF).

A mixed parallel strategy for the solution of coupled multi-scale problems at finite strains

NASA Astrophysics Data System (ADS)

Lopes, I. A. Rodrigues; Pires, F. M. Andrade; Reis, F. J. P.

2018-02-01

A mixed parallel strategy for the solution of homogenization-based multi-scale constitutive problems undergoing finite strains is proposed. The approach aims to reduce the computational time and memory requirements of non-linear coupled simulations that use finite element discretization at both scales (FE^2). In the first level of the algorithm, a non-conforming domain decomposition technique, based on the FETI method combined with a mortar discretization at the interface of macroscopic subdomains, is employed. A master-slave scheme, which distributes tasks by macroscopic element and adopts dynamic scheduling, is then used for each macroscopic subdomain composing the second level of the algorithm. This strategy allows the parallelization of FE^2 simulations in computers with either shared memory or distributed memory architectures. The proposed strategy preserves the quadratic rates of asymptotic convergence that characterize the Newton-Raphson scheme. Several examples are presented to demonstrate the robustness and efficiency of the proposed parallel strategy.

Combining dictionary techniques with extensible markup language (XML)--requirements to a new approach towards flexible and standardized documentation.

PubMed Central

Altmann, U.; Tafazzoli, A. G.; Noelle, G.; Huybrechts, T.; Schweiger, R.; Wächter, W.; Dudeck, J. W.

1999-01-01

In oncology various international and national standards exist for the documentation of different aspects of a disease. Since elements of these standards are repeated in different contexts, a common data dictionary could support consistent representation in any context. For the construction of such a dictionary existing documents have to be worked up in a complex procedure, that considers aspects of hierarchical decomposition of documents and of domain control as well as aspects of user presentation and models of the underlying model of patient data. In contrast to other thesauri, text chunks like definitions or explanations are very important and have to be preserved, since oncologic documentation often means coding and classification on an aggregate level and the safe use of coding systems is an important precondition for comparability of data. This paper discusses the potentials of the use of XML in combination with a dictionary for the promotion and development of standard conformable applications for tumor documentation. PMID:10566311

A Screen Space GPGPU Surface LIC Algorithm for Distributed Memory Data Parallel Sort Last Rendering Infrastructures

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

Loring, Burlen; Karimabadi, Homa; Rortershteyn, Vadim

2014-07-01

The surface line integral convolution(LIC) visualization technique produces dense visualization of vector fields on arbitrary surfaces. We present a screen space surface LIC algorithm for use in distributed memory data parallel sort last rendering infrastructures. The motivations for our work are to support analysis of datasets that are too large to fit in the main memory of a single computer and compatibility with prevalent parallel scientific visualization tools such as ParaView and VisIt. By working in screen space using OpenGL we can leverage the computational power of GPUs when they are available and run without them when they are not.more » We address efficiency and performance issues that arise from the transformation of data from physical to screen space by selecting an alternate screen space domain decomposition. We analyze the algorithm's scaling behavior with and without GPUs on two high performance computing systems using data from turbulent plasma simulations.« less

A cut-cell immersed boundary technique for fire dynamics simulation

NASA Astrophysics Data System (ADS)

Vanella, Marcos; McDermott, Randall; Forney, Glenn

2015-11-01

Fire simulation around complex geometry is gaining increasing attention in performance based design of fire protection systems, fire-structure interaction and pollutant transport in complex terrains, among others. This presentation will focus on our present effort in improving the capability of FDS (Fire Dynamics Simulator, developed at the Fire Research Division, NIST. https://github.com/firemodels/fds-smv) to represent fire scenarios around complex bodies. Velocities in the vicinity of the bodies are reconstructed using a classical immersed boundary scheme (Fadlun and co-workers, J. Comput. Phys., 161:35-60, 2000). Also, a conservative treatment of scalar transport equations (i.e. for chemical species) will be presented. In our method, discrete conservation and no penetration of species across solid boundaries are enforced using a cut-cell finite volume scheme. The small cell problem inherent to the method is tackled using explicit-implicit domain decomposition for scalar, within the FDS time integration scheme. Some details on the derivation, implementation and numerical tests of this numerical scheme will be discussed.

Layout compliance for triple patterning lithography: an iterative approach

NASA Astrophysics Data System (ADS)

Yu, Bei; Garreton, Gilda; Pan, David Z.

2014-10-01

As the semiconductor process further scales down, the industry encounters many lithography-related issues. In the 14nm logic node and beyond, triple patterning lithography (TPL) is one of the most promising techniques for Metal1 layer and possibly Via0 layer. As one of the most challenging problems in TPL, recently layout decomposition efforts have received more attention from both industry and academia. Ideally the decomposer should point out locations in the layout that are not triple patterning decomposable and therefore manual intervention by designers is required. A traditional decomposition flow would be an iterative process, where each iteration consists of an automatic layout decomposition step and manual layout modification task. However, due to the NP-hardness of triple patterning layout decomposition, automatic full chip level layout decomposition requires long computational time and therefore design closure issues continue to linger around in the traditional flow. Challenged by this issue, we present a novel incremental layout decomposition framework to facilitate accelerated iterative decomposition. In the first iteration, our decomposer not only points out all conflicts, but also provides the suggestions to fix them. After the layout modification, instead of solving the full chip problem from scratch, our decomposer can provide a quick solution for a selected portion of layout. We believe this framework is efficient, in terms of performance and designer friendly.

Analytical electron microscope study of eight ataxites

NASA Technical Reports Server (NTRS)

Novotny, P. M.; Goldstein, J. I.; Williams, D. B.

1982-01-01

Optical and electron optical (SEM, TEM, AEM) techniques were employed to investigate the fine structure of eight ataxite-iron meteorites. Structural studies indicated that the ataxites can be divided into two groups: a Widmanstaetten decomposition group and a martensite decomposition group. The Widmanstaetten decomposition group has a Type I plessite microstructure and the central taenite regions contain highly dislocated lath martensite. The steep M shaped Ni gradients in the taenite are consistent with the fast cooling rates, of not less than 500 C/my, observed for this group. The martensite decomposition group has a Type III plessite microstructure and contains all the chemical group IVB ataxites. The maximum taenite Ni contents vary from 47.5 to 52.7 wt % and are consistent with slow cooling to low temperatures of not greater than 350 C at cooling rates of not greater than 25 C/my.

Endothermic decompositions of inorganic monocrystalline thin plates. I. Shape of polycrystalline product domains versus constraints and time

NASA Astrophysics Data System (ADS)

Bertrand, G.; Comperat, M.; Lallemant, M.; Watelle, G.

1980-03-01

Copper sulfate pentahydrate dehydration into trihydrate was investigated using monocrystalline platelets with varying crystallographic orientations. The morphological and kinetic features of the trihydrate domains were examined. Different shapes were observed: polygons (parallelograms, hexagons) and ellipses; their conditions of occurrence are reported in the (P, T) diagram. At first (for about 2 min), the ratio of the long to the short axes of elliptical domains changes with time; these subsequently develop homothetically and the rate ratio is then only pressure dependent. Temperature influence is inferred from that of pressure. Polygonal shapes are time dependent and result in ellipses. So far, no model can be put forward. Yet, qualitatively, the polygonal shape of a domain may be explained by the prevalence of the crystal arrangement and the elliptical shape by that of the solid tensorial properties. The influence of those factors might be modulated versus pressure, temperature, interface extent, and, thus, time.

A multi-domain spectral method for time-fractional differential equations

NASA Astrophysics Data System (ADS)

Chen, Feng; Xu, Qinwu; Hesthaven, Jan S.

2015-07-01

This paper proposes an approach for high-order time integration within a multi-domain setting for time-fractional differential equations. Since the kernel is singular or nearly singular, two main difficulties arise after the domain decomposition: how to properly account for the history/memory part and how to perform the integration accurately. To address these issues, we propose a novel hybrid approach for the numerical integration based on the combination of three-term-recurrence relations of Jacobi polynomials and high-order Gauss quadrature. The different approximations used in the hybrid approach are justified theoretically and through numerical examples. Based on this, we propose a new multi-domain spectral method for high-order accurate time integrations and study its stability properties by identifying the method as a generalized linear method. Numerical experiments confirm hp-convergence for both time-fractional differential equations and time-fractional partial differential equations.

Jammed Limit of Bijel Structure Formation

DOE PAGES

Welch, P. M.; Lee, M. N.; Parra-Vasquez, A. N. G.; ...

2017-11-02

Over the past decade, methods to control microstructure in heterogeneous mixtures by arresting spinodal decomposition via the addition of colloidal particles have led to an entirely new class of bicontinuous materials known as bijels. We present a new model for the development of these materials that yields to both numerical and analytical evaluation. This model reveals that a single dimensionless parameter that captures both chemical and environmental variables dictates the dynamics and ultimate structure formed in bijels. We also demonstrate that this parameter must fall within a fixed range in order for jamming to occur during spinodal decomposition, as wellmore » as show that known experimental trends for the characteristic domain sizes and time scales for formation are recovered by this model.« less

Towards reduced order modelling for predicting the dynamics of coherent vorticity structures within wind turbine wakes.

PubMed

Debnath, M; Santoni, C; Leonardi, S; Iungo, G V

2017-04-13

The dynamics of the velocity field resulting from the interaction between the atmospheric boundary layer and a wind turbine array can affect significantly the performance of a wind power plant and the durability of wind turbines. In this work, dynamics in wind turbine wakes and instabilities of helicoidal tip vortices are detected and characterized through modal decomposition techniques. The dataset under examination consists of snapshots of the velocity field obtained from large-eddy simulations (LES) of an isolated wind turbine, for which aerodynamic forcing exerted by the turbine blades on the atmospheric boundary layer is mimicked through the actuator line model. Particular attention is paid to the interaction between the downstream evolution of the helicoidal tip vortices and the alternate vortex shedding from the turbine tower. The LES dataset is interrogated through different modal decomposition techniques, such as proper orthogonal decomposition and dynamic mode decomposition. The dominant wake dynamics are selected for the formulation of a reduced order model, which consists in a linear time-marching algorithm where temporal evolution of flow dynamics is obtained from the previous temporal realization multiplied by a time-invariant operator.This article is part of the themed issue 'Wind energy in complex terrains'. © 2017 The Author(s).

GENESIS: a hybrid-parallel and multi-scale molecular dynamics simulator with enhanced sampling algorithms for biomolecular and cellular simulations.

PubMed

Jung, Jaewoon; Mori, Takaharu; Kobayashi, Chigusa; Matsunaga, Yasuhiro; Yoda, Takao; Feig, Michael; Sugita, Yuji

2015-07-01

GENESIS (Generalized-Ensemble Simulation System) is a new software package for molecular dynamics (MD) simulations of macromolecules. It has two MD simulators, called ATDYN and SPDYN. ATDYN is parallelized based on an atomic decomposition algorithm for the simulations of all-atom force-field models as well as coarse-grained Go-like models. SPDYN is highly parallelized based on a domain decomposition scheme, allowing large-scale MD simulations on supercomputers. Hybrid schemes combining OpenMP and MPI are used in both simulators to target modern multicore computer architectures. Key advantages of GENESIS are (1) the highly parallel performance of SPDYN for very large biological systems consisting of more than one million atoms and (2) the availability of various REMD algorithms (T-REMD, REUS, multi-dimensional REMD for both all-atom and Go-like models under the NVT, NPT, NPAT, and NPγT ensembles). The former is achieved by a combination of the midpoint cell method and the efficient three-dimensional Fast Fourier Transform algorithm, where the domain decomposition space is shared in real-space and reciprocal-space calculations. Other features in SPDYN, such as avoiding concurrent memory access, reducing communication times, and usage of parallel input/output files, also contribute to the performance. We show the REMD simulation results of a mixed (POPC/DMPC) lipid bilayer as a real application using GENESIS. GENESIS is released as free software under the GPLv2 licence and can be easily modified for the development of new algorithms and molecular models. WIREs Comput Mol Sci 2015, 5:310-323. doi: 10.1002/wcms.1220.

Electrocardiogram signal denoising based on empirical mode decomposition technique: an overview

NASA Astrophysics Data System (ADS)

Han, G.; Lin, B.; Xu, Z.

2017-03-01

Electrocardiogram (ECG) signal is nonlinear and non-stationary weak signal which reflects whether the heart is functioning normally or abnormally. ECG signal is susceptible to various kinds of noises such as high/low frequency noises, powerline interference and baseline wander. Hence, the removal of noises from ECG signal becomes a vital link in the ECG signal processing and plays a significant role in the detection and diagnosis of heart diseases. The review will describe the recent developments of ECG signal denoising based on Empirical Mode Decomposition (EMD) technique including high frequency noise removal, powerline interference separation, baseline wander correction, the combining of EMD and Other Methods, EEMD technique. EMD technique is a quite potential and prospective but not perfect method in the application of processing nonlinear and non-stationary signal like ECG signal. The EMD combined with other algorithms is a good solution to improve the performance of noise cancellation. The pros and cons of EMD technique in ECG signal denoising are discussed in detail. Finally, the future work and challenges in ECG signal denoising based on EMD technique are clarified.

Cellulose and hemicellulose decomposition by forest soil bacteria proceeds by the action of structurally variable enzymatic systems

PubMed Central

López-Mondéjar, Rubén; Zühlke, Daniela; Becher, Dörte; Riedel, Katharina; Baldrian, Petr

2016-01-01

Evidence shows that bacteria contribute actively to the decomposition of cellulose and hemicellulose in forest soil; however, their role in this process is still unclear. Here we performed the screening and identification of bacteria showing potential cellulolytic activity from litter and organic soil of a temperate oak forest. The genomes of three cellulolytic isolates previously described as abundant in this ecosystem were sequenced and their proteomes were characterized during the growth on plant biomass and on microcrystalline cellulose. Pedobacter and Mucilaginibacter showed complex enzymatic systems containing highly diverse carbohydrate-active enzymes for the degradation of cellulose and hemicellulose, which were functionally redundant for endoglucanases, β-glucosidases, endoxylanases, β-xylosidases, mannosidases and carbohydrate-binding modules. Luteibacter did not express any glycosyl hydrolases traditionally recognized as cellulases. Instead, cellulose decomposition was likely performed by an expressed GH23 family protein containing a cellulose-binding domain. Interestingly, the presence of plant lignocellulose as well as crystalline cellulose both trigger the production of a wide set of hydrolytic proteins including cellulases, hemicellulases and other glycosyl hydrolases. Our findings highlight the extensive and unexplored structural diversity of enzymatic systems in cellulolytic soil bacteria and indicate the roles of multiple abundant bacterial taxa in the decomposition of cellulose and other plant polysaccharides. PMID:27125755

High performance Python for direct numerical simulations of turbulent flows

NASA Astrophysics Data System (ADS)

Mortensen, Mikael; Langtangen, Hans Petter

2016-06-01

Direct Numerical Simulations (DNS) of the Navier Stokes equations is an invaluable research tool in fluid dynamics. Still, there are few publicly available research codes and, due to the heavy number crunching implied, available codes are usually written in low-level languages such as C/C++ or Fortran. In this paper we describe a pure scientific Python pseudo-spectral DNS code that nearly matches the performance of C++ for thousands of processors and billions of unknowns. We also describe a version optimized through Cython, that is found to match the speed of C++. The solvers are written from scratch in Python, both the mesh, the MPI domain decomposition, and the temporal integrators. The solvers have been verified and benchmarked on the Shaheen supercomputer at the KAUST supercomputing laboratory, and we are able to show very good scaling up to several thousand cores. A very important part of the implementation is the mesh decomposition (we implement both slab and pencil decompositions) and 3D parallel Fast Fourier Transforms (FFT). The mesh decomposition and FFT routines have been implemented in Python using serial FFT routines (either NumPy, pyFFTW or any other serial FFT module), NumPy array manipulations and with MPI communications handled by MPI for Python (mpi4py). We show how we are able to execute a 3D parallel FFT in Python for a slab mesh decomposition using 4 lines of compact Python code, for which the parallel performance on Shaheen is found to be slightly better than similar routines provided through the FFTW library. For a pencil mesh decomposition 7 lines of code is required to execute a transform.

Wood decomposition as influenced by invertebrates.

PubMed

Ulyshen, Michael D

2016-02-01

The diversity and habitat requirements of invertebrates associated with dead wood have been the subjects of hundreds of studies in recent years but we still know very little about the ecological or economic importance of these organisms. The purpose of this review is to examine whether, how and to what extent invertebrates affect wood decomposition in terrestrial ecosystems. Three broad conclusions can be reached from the available literature. First, wood decomposition is largely driven by microbial activity but invertebrates also play a significant role in both temperate and tropical environments. Primary mechanisms include enzymatic digestion (involving both endogenous enzymes and those produced by endo- and ectosymbionts), substrate alteration (tunnelling and fragmentation), biotic interactions and nitrogen fertilization (i.e. promoting nitrogen fixation by endosymbiotic and free-living bacteria). Second, the effects of individual invertebrate taxa or functional groups can be accelerative or inhibitory but the cumulative effect of the entire community is generally to accelerate wood decomposition, at least during the early stages of the process (most studies are limited to the first 2-3 years). Although methodological differences and design limitations preclude meta-analysis, studies aimed at quantifying the contributions of invertebrates to wood decomposition commonly attribute 10-20% of wood loss to these organisms. Finally, some taxa appear to be particularly influential with respect to promoting wood decomposition. These include large wood-boring beetles (Coleoptera) and termites (Termitoidae), especially fungus-farming macrotermitines. The presence or absence of these species may be more consequential than species richness and the influence of invertebrates is likely to vary biogeographically. Published 2014. This article is a U.S. Government work and is in the public domain in the USA.

Characterization of domain-peptide interaction interface: a case study on the amphiphysin-1 SH3 domain.

PubMed

Hou, Tingjun; Zhang, Wei; Case, David A; Wang, Wei

2008-02-29

Many important protein-protein interactions are mediated by peptide recognition modular domains, such as the Src homology 3 (SH3), SH2, PDZ, and WW domains. Characterizing the interaction interface of domain-peptide complexes and predicting binding specificity for modular domains are critical for deciphering protein-protein interaction networks. Here, we propose the use of an energetic decomposition analysis to characterize domain-peptide interactions and the molecular interaction energy components (MIECs), including van der Waals, electrostatic, and desolvation energy between residue pairs on the binding interface. We show a proof-of-concept study on the amphiphysin-1 SH3 domain interacting with its peptide ligands. The structures of the human amphiphysin-1 SH3 domain complexed with 884 peptides were first modeled using virtual mutagenesis and optimized by molecular mechanics (MM) minimization. Next, the MIECs between domain and peptide residues were computed using the MM/generalized Born decomposition analysis. We conducted two types of statistical analyses on the MIECs to demonstrate their usefulness for predicting binding affinities of peptides and for classifying peptides into binder and non-binder categories. First, combining partial least squares analysis and genetic algorithm, we fitted linear regression models between the MIECs and the peptide binding affinities on the training data set. These models were then used to predict binding affinities for peptides in the test data set; the predicted values have a correlation coefficient of 0.81 and an unsigned mean error of 0.39 compared with the experimentally measured ones. The partial least squares-genetic algorithm analysis on the MIECs revealed the critical interactions for the binding specificity of the amphiphysin-1 SH3 domain. Next, a support vector machine (SVM) was employed to build classification models based on the MIECs of peptides in the training set. A rigorous training-validation procedure was used to assess the performances of different kernel functions in SVM and different combinations of the MIECs. The best SVM classifier gave satisfactory predictions for the test set, indicated by average prediction accuracy rates of 78% and 91% for the binding and non-binding peptides, respectively. We also showed that the performance of our approach on both binding affinity prediction and binder/non-binder classification was superior to the performances of the conventional MM/Poisson-Boltzmann solvent-accessible surface area and MM/generalized Born solvent-accessible surface area calculations. Our study demonstrates that the analysis of the MIECs between peptides and the SH3 domain can successfully characterize the binding interface, and it provides a framework to derive integrated prediction models for different domain-peptide systems.

[Litter decomposition and nutrient release in Acacia mangium plantations established on degraded soils of Colombia].

PubMed

Castellanos-Barliza, Jeiner; León Peláez, Juan Diego

2011-03-01

Several factors control the decomposition in terrestrial ecosystems such as humidity, temperature, quality of litter and microbial activity. We investigated the effects of rainfall and soil plowing prior to the establishment of Acacia mangium plantations, using the litterbag technique, during a six month period, in forests plantations in Bajo Cauca region, Colombia. The annual decomposition constants (k) of simple exponential model, oscillated between 1.24 and 1.80, meanwhile k1 y k2 decomposition constants of double exponential model were 0.88-1.81 and 0.58-7.01. At the end of the study, the mean residual dry matter (RDM) was 47% of the initial value for the three sites. We found a slow N, Ca and Mg release pattern from the A. mangium leaf litter, meanwhile, phosphorus (P) showed a dominant immobilization phase, suggesting its low availability in soils. Chemical leaf litter quality parameters (e.g. N and P concentrations, C/N, N/P ratios and phenols content) showed an important influence on decomposition rates. The results of this study indicated that rainfall plays an important role on the decomposition process, but not soil plowing.

Selective growth of Pb islands on graphene/SiC buffer layers

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

Liu, X. T.; Miao, Y. P.; Ma, D. Y.

2015-02-14

Graphene is fabricated by thermal decomposition of silicon carbide (SiC) and Pb islands are deposited by Pb flux in molecular beam epitaxy chamber. It is found that graphene domains and SiC buffer layer coexist. Selective growth of Pb islands on SiC buffer layer rather than on graphene domains is observed. It can be ascribed to the higher adsorption energy of Pb atoms on the 6√(3) reconstruction of SiC. However, once Pb islands nucleate on graphene domains, they will grow very large owing to the lower diffusion barrier of Pb atoms on graphene. The results are consistent with first-principle calculations. Sincemore » Pb atoms on graphene are nearly free-standing, Pb islands grow in even-number mode.« less

Nested ocean models: Work in progress

NASA Technical Reports Server (NTRS)

Perkins, A. Louise

1991-01-01

The ongoing work of combining three existing software programs into a nested grid oceanography model is detailed. The HYPER domain decomposition program, the SPEM ocean modeling program, and a quasi-geostrophic model written in England are being combined into a general ocean modeling facility. This facility will be used to test the viability and the capability of two-way nested grids in the North Atlantic.

Box schemes and their implementation on the iPSC/860

NASA Technical Reports Server (NTRS)

Chattot, J. J.; Merriam, M. L.

1991-01-01

Research on algoriths for efficiently solving fluid flow problems on massively parallel computers is continued in the present paper. Attention is given to the implementation of a box scheme on the iPSC/860, a massively parallel computer with a peak speed of 10 Gflops and a memory of 128 Mwords. A domain decomposition approach to parallelism is used.

Enhanced visualization of abnormalities in digital-mammographic images

NASA Astrophysics Data System (ADS)

Young, Susan S.; Moore, William E.

2002-05-01

This paper describes two new presentation methods that are intended to improve the ability of radiologists to visualize abnormalities in mammograms by enhancing the appearance of the breast parenchyma pattern relative to the fatty-tissue surroundings. The first method, referred to as mountain- view, is obtained via multiscale edge decomposition through filter banks. The image is displayed in a multiscale edge domain that causes the image to have a topographic-like appearance. The second method displays the image in the intensity domain and is referred to as contrast-enhancement presentation. The input image is first passed through a decomposition filter bank to produce a filtered output (Id). The image at the lowest resolution is processed using a LUT (look-up table) to produce a tone scaled image (I'). The LUT is designed to optimally map the code value range corresponding to the parenchyma pattern in the mammographic image into the dynamic range of the output medium. The algorithm uses a contrast weight control mechanism to produce the desired weight factors to enhance the edge information corresponding to the parenchyma pattern. The output image is formed using a reconstruction filter bank through I' and enhanced Id.

Automatic partitioning of unstructured meshes for the parallel solution of problems in computational mechanics

NASA Technical Reports Server (NTRS)

Farhat, Charbel; Lesoinne, Michel

1993-01-01

Most of the recently proposed computational methods for solving partial differential equations on multiprocessor architectures stem from the 'divide and conquer' paradigm and involve some form of domain decomposition. For those methods which also require grids of points or patches of elements, it is often necessary to explicitly partition the underlying mesh, especially when working with local memory parallel processors. In this paper, a family of cost-effective algorithms for the automatic partitioning of arbitrary two- and three-dimensional finite element and finite difference meshes is presented and discussed in view of a domain decomposed solution procedure and parallel processing. The influence of the algorithmic aspects of a solution method (implicit/explicit computations), and the architectural specifics of a multiprocessor (SIMD/MIMD, startup/transmission time), on the design of a mesh partitioning algorithm are discussed. The impact of the partitioning strategy on load balancing, operation count, operator conditioning, rate of convergence and processor mapping is also addressed. Finally, the proposed mesh decomposition algorithms are demonstrated with realistic examples of finite element, finite volume, and finite difference meshes associated with the parallel solution of solid and fluid mechanics problems on the iPSC/2 and iPSC/860 multiprocessors.

On some Aitken-like acceleration of the Schwarz method

NASA Astrophysics Data System (ADS)

Garbey, M.; Tromeur-Dervout, D.

2002-12-01

In this paper we present a family of domain decomposition based on Aitken-like acceleration of the Schwarz method seen as an iterative procedure with a linear rate of convergence. We first present the so-called Aitken-Schwarz procedure for linear differential operators. The solver can be a direct solver when applied to the Helmholtz problem with five-point finite difference scheme on regular grids. We then introduce the Steffensen-Schwarz variant which is an iterative domain decomposition solver that can be applied to linear and nonlinear problems. We show that these solvers have reasonable numerical efficiency compared to classical fast solvers for the Poisson problem or multigrids for more general linear and nonlinear elliptic problems. However, the salient feature of our method is that our algorithm has high tolerance to slow network in the context of distributed parallel computing and is attractive, generally speaking, to use with computer architecture for which performance is limited by the memory bandwidth rather than the flop performance of the CPU. This is nowadays the case for most parallel. computer using the RISC processor architecture. We will illustrate this highly desirable property of our algorithm with large-scale computing experiments.

A tightly-coupled domain-decomposition approach for highly nonlinear stochastic multiphysics systems

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

Taverniers, Søren; Tartakovsky, Daniel M., E-mail: dmt@ucsd.edu

2017-02-01

Multiphysics simulations often involve nonlinear components that are driven by internally generated or externally imposed random fluctuations. When used with a domain-decomposition (DD) algorithm, such components have to be coupled in a way that both accurately propagates the noise between the subdomains and lends itself to a stable and cost-effective temporal integration. We develop a conservative DD approach in which tight coupling is obtained by using a Jacobian-free Newton–Krylov (JfNK) method with a generalized minimum residual iterative linear solver. This strategy is tested on a coupled nonlinear diffusion system forced by a truncated Gaussian noise at the boundary. Enforcement ofmore » path-wise continuity of the state variable and its flux, as opposed to continuity in the mean, at interfaces between subdomains enables the DD algorithm to correctly propagate boundary fluctuations throughout the computational domain. Reliance on a single Newton iteration (explicit coupling), rather than on the fully converged JfNK (implicit) coupling, may increase the solution error by an order of magnitude. Increase in communication frequency between the DD components reduces the explicit coupling's error, but makes it less efficient than the implicit coupling at comparable error levels for all noise strengths considered. Finally, the DD algorithm with the implicit JfNK coupling resolves temporally-correlated fluctuations of the boundary noise when the correlation time of the latter exceeds some multiple of an appropriately defined characteristic diffusion time.« less

Airbreathing Propulsion System Analysis Using Multithreaded Parallel Processing

NASA Technical Reports Server (NTRS)

Schunk, Richard Gregory; Chung, T. J.; Rodriguez, Pete (Technical Monitor)

2000-01-01

In this paper, parallel processing is used to analyze the mixing, and combustion behavior of hypersonic flow. Preliminary work for a sonic transverse hydrogen jet injected from a slot into a Mach 4 airstream in a two-dimensional duct combustor has been completed [Moon and Chung, 1996]. Our aim is to extend this work to three-dimensional domain using multithreaded domain decomposition parallel processing based on the flowfield-dependent variation theory. Numerical simulations of chemically reacting flows are difficult because of the strong interactions between the turbulent hydrodynamic and chemical processes. The algorithm must provide an accurate representation of the flowfield, since unphysical flowfield calculations will lead to the faulty loss or creation of species mass fraction, or even premature ignition, which in turn alters the flowfield information. Another difficulty arises from the disparity in time scales between the flowfield and chemical reactions, which may require the use of finite rate chemistry. The situations are more complex when there is a disparity in length scales involved in turbulence. In order to cope with these complicated physical phenomena, it is our plan to utilize the flowfield-dependent variation theory mentioned above, facilitated by large eddy simulation. Undoubtedly, the proposed computation requires the most sophisticated computational strategies. The multithreaded domain decomposition parallel processing will be necessary in order to reduce both computational time and storage. Without special treatments involved in computer engineering, our attempt to analyze the airbreathing combustion appears to be difficult, if not impossible.

Effects of calibration methods on quantitative material decomposition in photon-counting spectral computed tomography using a maximum a posteriori estimator.

PubMed

Curtis, Tyler E; Roeder, Ryan K

2017-10-01

Advances in photon-counting detectors have enabled quantitative material decomposition using multi-energy or spectral computed tomography (CT). Supervised methods for material decomposition utilize an estimated attenuation for each material of interest at each photon energy level, which must be calibrated based upon calculated or measured values for known compositions. Measurements using a calibration phantom can advantageously account for system-specific noise, but the effect of calibration methods on the material basis matrix and subsequent quantitative material decomposition has not been experimentally investigated. Therefore, the objective of this study was to investigate the influence of the range and number of contrast agent concentrations within a modular calibration phantom on the accuracy of quantitative material decomposition in the image domain. Gadolinium was chosen as a model contrast agent in imaging phantoms, which also contained bone tissue and water as negative controls. The maximum gadolinium concentration (30, 60, and 90 mM) and total number of concentrations (2, 4, and 7) were independently varied to systematically investigate effects of the material basis matrix and scaling factor calibration on the quantitative (root mean squared error, RMSE) and spatial (sensitivity and specificity) accuracy of material decomposition. Images of calibration and sample phantoms were acquired using a commercially available photon-counting spectral micro-CT system with five energy bins selected to normalize photon counts and leverage the contrast agent k-edge. Material decomposition of gadolinium, calcium, and water was performed for each calibration method using a maximum a posteriori estimator. Both the quantitative and spatial accuracy of material decomposition were most improved by using an increased maximum gadolinium concentration (range) in the basis matrix calibration; the effects of using a greater number of concentrations were relatively small in magnitude by comparison. The material basis matrix calibration was more sensitive to changes in the calibration methods than the scaling factor calibration. The material basis matrix calibration significantly influenced both the quantitative and spatial accuracy of material decomposition, while the scaling factor calibration influenced quantitative but not spatial accuracy. Importantly, the median RMSE of material decomposition was as low as ~1.5 mM (~0.24 mg/mL gadolinium), which was similar in magnitude to that measured by optical spectroscopy on the same samples. The accuracy of quantitative material decomposition in photon-counting spectral CT was significantly influenced by calibration methods which must therefore be carefully considered for the intended diagnostic imaging application. © 2017 American Association of Physicists in Medicine.

Investigation of automated task learning, decomposition and scheduling

NASA Technical Reports Server (NTRS)

Livingston, David L.; Serpen, Gursel; Masti, Chandrashekar L.

1990-01-01

The details and results of research conducted in the application of neural networks to task planning and decomposition are presented. Task planning and decomposition are operations that humans perform in a reasonably efficient manner. Without the use of good heuristics and usually much human interaction, automatic planners and decomposers generally do not perform well due to the intractable nature of the problems under consideration. The human-like performance of neural networks has shown promise for generating acceptable solutions to intractable problems such as planning and decomposition. This was the primary reasoning behind attempting the study. The basis for the work is the use of state machines to model tasks. State machine models provide a useful means for examining the structure of tasks since many formal techniques have been developed for their analysis and synthesis. It is the approach to integrate the strong algebraic foundations of state machines with the heretofore trial-and-error approach to neural network synthesis.

Novel techniques for data decomposition and load balancing for parallel processing of vision systems: Implementation and evaluation using a motion estimation system

NASA Technical Reports Server (NTRS)

Choudhary, Alok Nidhi; Leung, Mun K.; Huang, Thomas S.; Patel, Janak H.

1989-01-01

Computer vision systems employ a sequence of vision algorithms in which the output of an algorithm is the input of the next algorithm in the sequence. Algorithms that constitute such systems exhibit vastly different computational characteristics, and therefore, require different data decomposition techniques and efficient load balancing techniques for parallel implementation. However, since the input data for a task is produced as the output data of the previous task, this information can be exploited to perform knowledge based data decomposition and load balancing. Presented here are algorithms for a motion estimation system. The motion estimation is based on the point correspondence between the involved images which are a sequence of stereo image pairs. Researchers propose algorithms to obtain point correspondences by matching feature points among stereo image pairs at any two consecutive time instants. Furthermore, the proposed algorithms employ non-iterative procedures, which results in saving considerable amounts of computation time. The system consists of the following steps: (1) extraction of features; (2) stereo match of images in one time instant; (3) time match of images from consecutive time instants; (4) stereo match to compute final unambiguous points; and (5) computation of motion parameters.

Whole-annulus aeroelasticity analysis of a 17-bladerow WRF compressor using an unstructured Navier Stokes solver

NASA Astrophysics Data System (ADS)

Wu, X.; Vahdati, M.; Sayma, A.; Imregun, M.

2005-03-01

This paper describes a large-scale aeroelasticity computation for an aero-engine core compressor. The computational domain includes all 17 bladerows, resulting in a mesh with over 68 million points. The Favre-averaged Navier Stokes equations are used to represent the flow in a non-linear time-accurate fashion on unstructured meshes of mixed elements. The structural model of the first two rotor bladerows is based on a standard finite element representation. The fluid mesh is moved at each time step according to the structural motion so that changes in blade aerodynamic damping and flow unsteadiness can be accommodated automatically. An efficient domain decomposition technique, where special care was taken to balance the memory requirement across processors, was developed as part of the work. The calculation was conducted in parallel mode on 128 CPUs of an SGI Origin 3000. Ten vibration cycles were obtained using over 2.2 CPU years, though the elapsed time was a week only. Steady-state flow measurements and predictions were found to be in good agreement. A comparison of the averaged unsteady flow and the steady-state flow revealed some discrepancies. It was concluded that, in due course, the methodology would be adopted by industry to perform routine numerical simulations of the unsteady flow through entire compressor assemblies with vibrating blades not only to minimise engine and rig tests but also to improve performance predictions.

Robust/optimal temperature profile control of a high-speed aerospace vehicle using neural networks.

PubMed

Yadav, Vivek; Padhi, Radhakant; Balakrishnan, S N

2007-07-01

An approximate dynamic programming (ADP)-based suboptimal neurocontroller to obtain desired temperature for a high-speed aerospace vehicle is synthesized in this paper. A 1-D distributed parameter model of a fin is developed from basic thermal physics principles. "Snapshot" solutions of the dynamics are generated with a simple dynamic inversion-based feedback controller. Empirical basis functions are designed using the "proper orthogonal decomposition" (POD) technique and the snapshot solutions. A low-order nonlinear lumped parameter system to characterize the infinite dimensional system is obtained by carrying out a Galerkin projection. An ADP-based neurocontroller with a dual heuristic programming (DHP) formulation is obtained with a single-network-adaptive-critic (SNAC) controller for this approximate nonlinear model. Actual control in the original domain is calculated with the same POD basis functions through a reverse mapping. Further contribution of this paper includes development of an online robust neurocontroller to account for unmodeled dynamics and parametric uncertainties inherent in such a complex dynamic system. A neural network (NN) weight update rule that guarantees boundedness of the weights and relaxes the need for persistence of excitation (PE) condition is presented. Simulation studies show that in a fairly extensive but compact domain, any desired temperature profile can be achieved starting from any initial temperature profile. Therefore, the ADP and NN-based controllers appear to have the potential to become controller synthesis tools for nonlinear distributed parameter systems.

A Decomposition Method for Security Constrained Economic Dispatch of a Three-Layer Power System

NASA Astrophysics Data System (ADS)

Yang, Junfeng; Luo, Zhiqiang; Dong, Cheng; Lai, Xiaowen; Wang, Yang

2018-01-01

This paper proposes a new decomposition method for the security-constrained economic dispatch in a three-layer large-scale power system. The decomposition is realized using two main techniques. The first is to use Ward equivalencing-based network reduction to reduce the number of variables and constraints in the high-layer model without sacrificing accuracy. The second is to develop a price response function to exchange signal information between neighboring layers, which significantly improves the information exchange efficiency of each iteration and results in less iterations and less computational time. The case studies based on the duplicated RTS-79 system demonstrate the effectiveness and robustness of the proposed method.

Solid-state reaction kinetics of neodymium doped magnesium hydrogen phosphate system

NASA Astrophysics Data System (ADS)

Gupta, Rashmi; Slathia, Goldy; Bamzai, K. K.

2018-05-01

Neodymium doped magnesium hydrogen phosphate (NdMHP) crystals were grown by using gel encapsulation technique. Structural characterization of the grown crystals has been carried out by single crystal X-ray diffraction (XRD) and it revealed that NdMHP crystals crystallize in orthorhombic crystal system with space group Pbca. Kinetics of the decomposition of the grown crystals has been studied by non-isothermal analysis. The estimation of decomposition temperatures and weight loss has been made from the thermogravimetric/differential thermo analytical (TG/DTA) in conjuncture with DSC studies. The various steps involved in the thermal decomposition of the material have been analysed using Horowitz-Metzger, Coats-Redfern and Piloyan-Novikova equations for evaluating various kinetic parameters.

A hybrid Dantzig-Wolfe, Benders decomposition and column generation procedure for multiple diet production planning under uncertainties

NASA Astrophysics Data System (ADS)

Udomsungworagul, A.; Charnsethikul, P.

2018-03-01

This article introduces methodology to solve large scale two-phase linear programming with a case of multiple time period animal diet problems under both nutrients in raw materials and finished product demand uncertainties. Assumption of allowing to manufacture multiple product formulas in the same time period and assumption of allowing to hold raw materials and finished products inventory have been added. Dantzig-Wolfe decompositions, Benders decomposition and Column generations technique has been combined and applied to solve the problem. The proposed procedure was programmed using VBA and Solver tool in Microsoft Excel. A case study was used and tested in term of efficiency and effectiveness trade-offs.

Theory and experimental evidence of phonon domains and their roles in pre-martensitic phenomena

NASA Astrophysics Data System (ADS)

Jin, Yongmei M.; Wang, Yu U.; Ren, Yang

2015-12-01

Pre-martensitic phenomena, also called martensite precursor effects, have been known for decades while yet remain outstanding issues. This paper addresses pre-martensitic phenomena from new theoretical and experimental perspectives. A statistical mechanics-based Grüneisen-type phonon theory is developed. On the basis of deformation-dependent incompletely softened low-energy phonons, the theory predicts a lattice instability and pre-martensitic transition into elastic-phonon domains via 'phonon spinodal decomposition.' The phase transition lifts phonon degeneracy in cubic crystal and has a nature of phonon pseudo-Jahn-Teller lattice instability. The theory and notion of phonon domains consistently explain the ubiquitous pre-martensitic anomalies as natural consequences of incomplete phonon softening. The phonon domains are characterised by broken dynamic symmetry of lattice vibrations and deform through internal phonon relaxation in response to stress (a particular case of Le Chatelier's principle), leading to previously unexplored new domain phenomenon. Experimental evidence of phonon domains is obtained by in situ three-dimensional phonon diffuse scattering and Bragg reflection using high-energy synchrotron X-ray single-crystal diffraction, which observes exotic domain phenomenon fundamentally different from usual ferroelastic domain switching phenomenon. In light of the theory and experimental evidence of phonon domains and their roles in pre-martensitic phenomena, currently existing alternative opinions on martensitic precursor phenomena are revisited.

An investigation into scalability and compliance for triple patterning with stitches for metal 1 at the 14nm node

NASA Astrophysics Data System (ADS)

Cork, Christopher; Miloslavsky, Alexander; Friedberg, Paul; Luk-Pat, Gerry

2013-04-01

Lithographers had hoped that single patterning would be enabled at the 20nm node by way of EUV lithography. However, due to delays in EUV readiness, double patterning with 193i lithography is currently relied upon for volume production for the 20nm node's metal 1 layer. At the 14nm and likely at the 10nm node, LE-LE-LE triple patterning technology (TPT) is one of the favored options [1,2] for patterning local interconnect and Metal 1 layers. While previous research has focused on TPT for contact mask, metal layers offer new challenges and opportunities, in particular the ability to decompose design polygons across more than one mask. The extra flexibility offered by the third mask and ability to leverage polygon stitching both serve to improve compliance. However, ensuring TPT compliance - the task of finding a 3-color mask decomposition for a design - is still a difficult task. Moreover, scalability concerns multiply the difficulty of triple patterning decomposition which is an NP-complete problem. Indeed previous work shows that network sizes above a few thousand nodes or polygons start to take significantly longer times to compute [3], making full chip decomposition for arbitrary layouts impractical. In practice Metal 1 layouts can be considered as two separate problem domains, namely: decomposition of standard cells and decomposition of IP blocks. Standard cells typically include only a few 10's of polygons and should be amenable to fast decomposition. Successive design iterations should resolve compliance issues and improve packing density. Density improvements are multiplied repeatedly as standard cells are placed multiple times. IP blocks, on the other hand, may involve very large networks. This paper evaluates multiple approaches to triple patterning decomposition for the Metal 1 layer. The benefits of polygon stitching, in particular, the ability to resolve commonly encountered non-compliant layout configurations and improve packing density, are weighed against the increased difficulty in finding an optimized, legal decomposition and coping with the increased scalability challenges.

Thermal and Chemical Characterization of Non-metallic Materials Using Coupled Thermogravimetric Analysis and Infrared Spectroscopy

NASA Technical Reports Server (NTRS)

Huff, Timothy L.; Griffin, Dennis E. (Technical Monitor)

2001-01-01

Thermogravimetric analysis (TGA) is widely employed in the thermal characterization of non-metallic materials, yielding valuable information on decomposition characteristics of a sample over a wide temperature range. However, a potential wealth of chemical information is lost during the process, with the evolving gases generated during thermal decomposition escaping through the exhaust line. Fourier Transform-Infrared spectroscopy (FT-IR) is a powerful analytical technique for determining many chemical constituents while in any material state, in this application, the gas phase. By linking these two techniques, evolving gases generated during the TGA process are directed into an appropriately equipped infrared spectrometer for chemical speciation. Consequently, both thermal decomposition and chemical characterization of a material may be obtained in a single sample run. In practice, a heated transfer line is employed to connect the two instruments while a purge gas stream directs the evolving gases into the FT-IR, The purge gas can be either high purity air or an inert gas such as nitrogen to allow oxidative and pyrolytic processes to be examined, respectively. The FT-IR data is collected real-time, allowing continuous monitoring of chemical compositional changes over the course of thermal decomposition. Using this coupled technique, an array of diverse materials has been examined, including composites, plastics, rubber, fiberglass epoxy resins, polycarbonates, silicones, lubricants and fluorocarbon materials. The benefit of combining these two methodologies is of particular importance in the aerospace community, where newly developing materials have little available data with which to refer. By providing both thermal and chemical data simultaneously, a more definitive and comprehensive characterization of the material is possible. Additionally, this procedure has been found to be a viable screening technique for certain materials, with the generated data useful in the selection of other appropriate analytical procedures for further material characterization.

Modeling software systems by domains

NASA Technical Reports Server (NTRS)

Dippolito, Richard; Lee, Kenneth

1992-01-01

The Software Architectures Engineering (SAE) Project at the Software Engineering Institute (SEI) has developed engineering modeling techniques that both reduce the complexity of software for domain-specific computer systems and result in systems that are easier to build and maintain. These techniques allow maximum freedom for system developers to apply their domain expertise to software. We have applied these techniques to several types of applications, including training simulators operating in real time, engineering simulators operating in non-real time, and real-time embedded computer systems. Our modeling techniques result in software that mirrors both the complexity of the application and the domain knowledge requirements. We submit that the proper measure of software complexity reflects neither the number of software component units nor the code count, but the locus of and amount of domain knowledge. As a result of using these techniques, domain knowledge is isolated by fields of engineering expertise and removed from the concern of the software engineer. In this paper, we will describe kinds of domain expertise, describe engineering by domains, and provide relevant examples of software developed for simulator applications using the techniques.

Non-Cooperative Target Recognition by Means of Singular Value Decomposition Applied to Radar High Resolution Range Profiles †

PubMed Central

López-Rodríguez, Patricia; Escot-Bocanegra, David; Fernández-Recio, Raúl; Bravo, Ignacio

2015-01-01

Radar high resolution range profiles are widely used among the target recognition community for the detection and identification of flying targets. In this paper, singular value decomposition is applied to extract the relevant information and to model each aircraft as a subspace. The identification algorithm is based on angle between subspaces and takes place in a transformed domain. In order to have a wide database of radar signatures and evaluate the performance, simulated range profiles are used as the recognition database while the test samples comprise data of actual range profiles collected in a measurement campaign. Thanks to the modeling of aircraft as subspaces only the valuable information of each target is used in the recognition process. Thus, one of the main advantages of using singular value decomposition, is that it helps to overcome the notable dissimilarities found in the shape and signal-to-noise ratio between actual and simulated profiles due to their difference in nature. Despite these differences, the recognition rates obtained with the algorithm are quite promising. PMID:25551484

Dynamic mode decomposition for plasma diagnostics and validation.

PubMed

Taylor, Roy; Kutz, J Nathan; Morgan, Kyle; Nelson, Brian A

2018-05-01

We demonstrate the application of the Dynamic Mode Decomposition (DMD) for the diagnostic analysis of the nonlinear dynamics of a magnetized plasma in resistive magnetohydrodynamics. The DMD method is an ideal spatio-temporal matrix decomposition that correlates spatial features of computational or experimental data while simultaneously associating the spatial activity with periodic temporal behavior. DMD can produce low-rank, reduced order surrogate models that can be used to reconstruct the state of the system with high fidelity. This allows for a reduction in the computational cost and, at the same time, accurate approximations of the problem, even if the data are sparsely sampled. We demonstrate the use of the method on both numerical and experimental data, showing that it is a successful mathematical architecture for characterizing the helicity injected torus with steady inductive (HIT-SI) magnetohydrodynamics. Importantly, the DMD produces interpretable, dominant mode structures, including a stationary mode consistent with our understanding of a HIT-SI spheromak accompanied by a pair of injector-driven modes. In combination, the 3-mode DMD model produces excellent dynamic reconstructions across the domain of analyzed data.

Dynamic mode decomposition for plasma diagnostics and validation

NASA Astrophysics Data System (ADS)

Taylor, Roy; Kutz, J. Nathan; Morgan, Kyle; Nelson, Brian A.

2018-05-01

We demonstrate the application of the Dynamic Mode Decomposition (DMD) for the diagnostic analysis of the nonlinear dynamics of a magnetized plasma in resistive magnetohydrodynamics. The DMD method is an ideal spatio-temporal matrix decomposition that correlates spatial features of computational or experimental data while simultaneously associating the spatial activity with periodic temporal behavior. DMD can produce low-rank, reduced order surrogate models that can be used to reconstruct the state of the system with high fidelity. This allows for a reduction in the computational cost and, at the same time, accurate approximations of the problem, even if the data are sparsely sampled. We demonstrate the use of the method on both numerical and experimental data, showing that it is a successful mathematical architecture for characterizing the helicity injected torus with steady inductive (HIT-SI) magnetohydrodynamics. Importantly, the DMD produces interpretable, dominant mode structures, including a stationary mode consistent with our understanding of a HIT-SI spheromak accompanied by a pair of injector-driven modes. In combination, the 3-mode DMD model produces excellent dynamic reconstructions across the domain of analyzed data.

Analysis of a parallelized nonlinear elliptic boundary value problem solver with application to reacting flows

NASA Technical Reports Server (NTRS)

Keyes, David E.; Smooke, Mitchell D.

1987-01-01

A parallelized finite difference code based on the Newton method for systems of nonlinear elliptic boundary value problems in two dimensions is analyzed in terms of computational complexity and parallel efficiency. An approximate cost function depending on 15 dimensionless parameters is derived for algorithms based on stripwise and boxwise decompositions of the domain and a one-to-one assignment of the strip or box subdomains to processors. The sensitivity of the cost functions to the parameters is explored in regions of parameter space corresponding to model small-order systems with inexpensive function evaluations and also a coupled system of nineteen equations with very expensive function evaluations. The algorithm was implemented on the Intel Hypercube, and some experimental results for the model problems with stripwise decompositions are presented and compared with the theory. In the context of computational combustion problems, multiprocessors of either message-passing or shared-memory type may be employed with stripwise decompositions to realize speedup of O(n), where n is mesh resolution in one direction, for reasonable n.

Singular value decomposition: a diagnostic tool for ill-posed inverse problems in optical computed tomography

NASA Astrophysics Data System (ADS)

Lanen, Theo A.; Watt, David W.

1995-10-01

Singular value decomposition has served as a diagnostic tool in optical computed tomography by using its capability to provide insight into the condition of ill-posed inverse problems. Various tomographic geometries are compared to one another through the singular value spectrum of their weight matrices. The number of significant singular values in the singular value spectrum of a weight matrix is a quantitative measure of the condition of the system of linear equations defined by a tomographic geometery. The analysis involves variation of the following five parameters, characterizing a tomographic geometry: 1) the spatial resolution of the reconstruction domain, 2) the number of views, 3) the number of projection rays per view, 4) the total observation angle spanned by the views, and 5) the selected basis function. Five local basis functions are considered: the square pulse, the triangle, the cubic B-spline, the Hanning window, and the Gaussian distribution. Also items like the presence of noise in the views, the coding accuracy of the weight matrix, as well as the accuracy of the accuracy of the singular value decomposition procedure itself are assessed.

Radiation noise of the bearing applied to the ceramic motorized spindle based on the sub-source decomposition method

NASA Astrophysics Data System (ADS)

Bai, X. T.; Wu, Y. H.; Zhang, K.; Chen, C. Z.; Yan, H. P.

2017-12-01

This paper mainly focuses on the calculation and analysis on the radiation noise of the angular contact ball bearing applied to the ceramic motorized spindle. The dynamic model containing the main working conditions and structural parameters is established based on dynamic theory of rolling bearing. The sub-source decomposition method is introduced in for the calculation of the radiation noise of the bearing, and a comparative experiment is adopted to check the precision of the method. Then the comparison between the contribution of different components is carried out in frequency domain based on the sub-source decomposition method. The spectrum of radiation noise of different components under various rotation speeds are used as the basis of assessing the contribution of different eigenfrequencies on the radiation noise of the components, and the proportion of friction noise and impact noise is evaluated as well. The results of the research provide the theoretical basis for the calculation of bearing noise, and offers reference to the impact of different components on the radiation noise of the bearing under different rotation speed.

Pilot study assessing differentiation of steatosis hepatis, hepatic iron overload, and combined disease using two-point dixon MRI at 3 T: in vitro and in vivo results of a 2D decomposition technique.

PubMed

Boll, Daniel T; Marin, Daniele; Redmon, Grace M; Zink, Stephen I; Merkle, Elmar M

2010-04-01

The purpose of our study was to evaluate whether two-point Dixon MRI using a 2D decomposition technique facilitates metabolite differentiation between lipids and iron in standardized in vitro liver phantoms with in vivo patient validation and allows semiquantitative in vitro assessment of metabolites associated with steatosis, iron overload, and combined disease. The acrylamide-based phantoms were made to reproduce the T1- and T2-weighted MRI appearances of physiologic hepatic parenchyma and hepatic steatosis-iron overload by the admixture of triglycerides and ferumoxides. Combined disease was simulated using joint admixtures of triglycerides and ferumoxides at various concentrations. For phantom validation, 30 patients were included, of whom 10 had steatosis, 10 had iron overload, and 10 had no liver disease. For MRI an in-phase/opposed-phase T1-weighted sequence with TR/TE(opposed-phase)/TE(in-phase) of 4.19/1.25/2.46 was used. Fat/water series were obtained by Dixon-based algorithms. In-phase and opposed-phase and fat/water ratios were calculated. Statistical cluster analysis assessed ratio pairs of physiologic liver, steatosis, iron overload, and combined disease in 2D metabolite discrimination plots. Statistical assessment proved that metabolite decomposition in phantoms simulating steatosis (1.77|0.22; in-phase/opposed-phase|fat/water ratios), iron overload (0.75|0.21), and healthy control subjects (1.09|0.05) formed three clusters with distinct ratio pairs. Patient validation for hepatic steatosis (3.29|0.51), iron overload (0.56|0.41), and normal control subjects (0.99|0.05) confirmed this clustering (p < 0.001). One-dimensional analysis assessing in vitro combined disease only with in-phase/opposed-phase ratios would have failed to characterize metabolites. The 2D analysis plotting in-phase/opposed-phase and fat/water ratios (2.16|0.59) provided accurate semiquantitative metabolite decomposition (p < 0.001). MR Dixon imaging facilitates metabolite decomposition of intrahepatic lipids and iron using in vitro phantoms with in vivo patient validation. The proposed decomposition technique identified distinct in-phase/opposed-phase and fat/water ratios for in vitro steatosis, iron overload, and combined disease.

Development of a novel hydroxyl ammonium nitrate based liquid propellant for air-independent propulsion

NASA Astrophysics Data System (ADS)

Fontaine, Joseph Henry

The focus of this dissertation is the development of an Unmanned Undersea Vehicle (UUV) liquid propellant employing Hydroxyl Ammonium Nitrate (HAN) as the oxidizer. Hydroxyl Ammonium Nitrate is a highly acidic aqueous based liquid oxidizer. Therefore, in order to achieve efficient combustion of a propellant using this oxidizer, the fuel must be highly water soluble and compatible with the oxidizer to prevent a premature ignition prior to being heated within the combustion chamber. An extensive search of the fuel to be used with this oxidizer was conducted. Propylene glycol was chosen as the fuel for this propellant, and the propellant given the name RF-402. The propellant development process will first evaluate the propellants thermal stability and kinetic parameters using a Differential Scanning Calorimeter (DSC). The purpose of the thermal stability analysis is to determine the temperature at which the propellant decomposition begins for the future safe handling of the propellant and the optimization of the combustion chamber. Additionally, the thermogram results will provide information regarding any undesirable endotherms prior to the decomposition and whether or not the decomposition process is a multi-step process. The Arrhenius type kinetic parameters will be determined using the ASTM method for thermally unstable materials. The activation energy and pre-exponential factor of the propellant will be determined by evaluating the decomposition peak temperature over a temperature scan rate ranging from 1°C per minute to 10°C per minute. The kinetic parameters of the propellant will be compared to those of 81 wt% HAN to determine if the HAN decomposition is controlling the overall decomposition of the propellant RF-402. The lifetime of individual droplets will be analyzed using both experimental and theoretical techniques. The theoretical technique will involve modeling the lifetime of an individual droplet in a combustion chamber like operating environment. The experimental technique will consist of subjecting droplets suspended from a fine gauge thermocouple to an instantaneous hot gas source and recording its temperature response while imaging it using a high power video microscope to determine the physical response of the droplet. This analysis will be the foundation for all future efforts in developing a propulsion system employing the use of RF-402.

Subband directional vector quantization in radiological image compression

NASA Astrophysics Data System (ADS)

Akrout, Nabil M.; Diab, Chaouki; Prost, Remy; Goutte, Robert; Amiel, Michel

1992-05-01

The aim of this paper is to propose a new scheme for image compression. The method is very efficient for images which have directional edges such as the tree-like structure of the coronary vessels in digital angiograms. This method involves two steps. First, the original image is decomposed at different resolution levels using a pyramidal subband decomposition scheme. For decomposition/reconstruction of the image, free of aliasing and boundary errors, we use an ideal band-pass filter bank implemented in the Discrete Cosine Transform domain (DCT). Second, the high-frequency subbands are vector quantized using a multiresolution codebook with vertical and horizontal codewords which take into account the edge orientation of each subband. The proposed method reduces the blocking effect encountered at low bit rates in conventional vector quantization.

Formation of metastable phases by spinodal decomposition

PubMed Central

Alert, Ricard; Tierno, Pietro; Casademunt, Jaume

2016-01-01

Metastable phases may be spontaneously formed from other metastable phases through nucleation. Here we demonstrate the spontaneous formation of a metastable phase from an unstable equilibrium by spinodal decomposition, which leads to a transient coexistence of stable and metastable phases. This phenomenon is generic within the recently introduced scenario of the landscape-inversion phase transitions, which we experimentally realize as a structural transition in a colloidal crystal. This transition exhibits a rich repertoire of new phase-ordering phenomena, including the coexistence of two equilibrium phases connected by two physically different interfaces. In addition, this scenario enables the control of sizes and lifetimes of metastable domains. Our findings open a new setting that broadens the fundamental understanding of phase-ordering kinetics, and yield new prospects of applications in materials science. PMID:27713406

Singular-value decomposition of a tomosynthesis system

PubMed Central

Burvall, Anna; Barrett, Harrison H.; Myers, Kyle J.; Dainty, Christopher

2010-01-01

Tomosynthesis is an emerging technique with potential to replace mammography, since it gives 3D information at a relatively small increase in dose and cost. We present an analytical singular-value decomposition of a tomosynthesis system, which provides the measurement component of any given object. The method is demonstrated on an example object. The measurement component can be used as a reconstruction of the object, and can also be utilized in future observer studies of tomosynthesis image quality. PMID:20940966

Ultrasonic technique for imaging tissue vibrations: preliminary results.

PubMed

Sikdar, Siddhartha; Beach, Kirk W; Vaezy, Shahram; Kim, Yongmin

2005-02-01

We propose an ultrasound (US)-based technique for imaging vibrations in the blood vessel walls and surrounding tissue caused by eddies produced during flow through narrowed or punctured arteries. Our approach is to utilize the clutter signal, normally suppressed in conventional color flow imaging, to detect and characterize local tissue vibrations. We demonstrate the feasibility of visualizing the origin and extent of vibrations relative to the underlying anatomy and blood flow in real-time and their quantitative assessment, including measurements of the amplitude, frequency and spatial distribution. We present two signal-processing algorithms, one based on phase decomposition and the other based on spectral estimation using eigen decomposition for isolating vibrations from clutter, blood flow and noise using an ensemble of US echoes. In simulation studies, the computationally efficient phase-decomposition method achieved 96% sensitivity and 98% specificity for vibration detection and was robust to broadband vibrations. Somewhat higher sensitivity (98%) and specificity (99%) could be achieved using the more computationally intensive eigen decomposition-based algorithm. Vibration amplitudes as low as 1 mum were measured accurately in phantom experiments. Real-time tissue vibration imaging at typical color-flow frame rates was implemented on a software-programmable US system. Vibrations were studied in vivo in a stenosed femoral bypass vein graft in a human subject and in a punctured femoral artery and incised spleen in an animal model.

Coherent vorticity extraction in resistive drift-wave turbulence: Comparison of orthogonal wavelets versus proper orthogonal decomposition

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

Futatani, S.; Bos, W.J.T.; Del-Castillo-Negrete, Diego B

2011-01-01

We assess two techniques for extracting coherent vortices out of turbulent flows: the wavelet based Coherent Vorticity Extraction (CVE) and the Proper Orthogonal Decomposition (POD). The former decomposes the flow field into an orthogonal wavelet representation and subsequent thresholding of the coefficients allows one to split the flow into organized coherent vortices with non-Gaussian statistics and an incoherent random part which is structureless. POD is based on the singular value decomposition and decomposes the flow into basis functions which are optimal with respect to the retained energy for the ensemble average. Both techniques are applied to direct numerical simulation datamore » of two-dimensional drift-wave turbulence governed by Hasegawa Wakatani equation, considering two limit cases: the quasi-hydrodynamic and the quasi-adiabatic regimes. The results are compared in terms of compression rate, retained energy, retained enstrophy and retained radial flux, together with the enstrophy spectrum and higher order statistics. (c) 2010 Published by Elsevier Masson SAS on behalf of Academie des sciences.« less

DeMAID/GA an Enhanced Design Manager's Aid for Intelligent Decomposition

NASA Technical Reports Server (NTRS)

Rogers, J. L.

1996-01-01

Many companies are looking for new tools and techniques to aid a design manager in making decisions that can reduce the time and cost of a design cycle. One tool is the Design Manager's Aid for Intelligent Decomposition (DeMAID). Since the initial public release of DeMAID in 1989, much research has been done in the areas of decomposition, concurrent engineering, parallel processing, and process management; many new tools and techniques have emerged. Based on these recent research and development efforts, numerous enhancements have been added to DeMAID to further aid the design manager in saving both cost and time in a design cycle. The key enhancement, a genetic algorithm (GA), will be available in the next public release called DeMAID/GA. The GA sequences the design processes to minimize the cost and time in converging a solution. The major enhancements in the upgrade of DeMAID to DeMAID/GA are discussed in this paper. A sample conceptual design project is used to show how these enhancements can be applied to improve the design cycle.

Decomposition Odour Profiling in the Air and Soil Surrounding Vertebrate Carrion

PubMed Central

2014-01-01

Chemical profiling of decomposition odour is conducted in the environmental sciences to detect malodourous target sources in air, water or soil. More recently decomposition odour profiling has been employed in the forensic sciences to generate a profile of the volatile organic compounds (VOCs) produced by decomposed remains. The chemical profile of decomposition odour is still being debated with variations in the VOC profile attributed to the sample collection technique, method of chemical analysis, and environment in which decomposition occurred. To date, little consideration has been given to the partitioning of odour between different matrices and the impact this has on developing an accurate VOC profile. The purpose of this research was to investigate the decomposition odour profile surrounding vertebrate carrion to determine how VOCs partition between soil and air. Four pig carcasses (Sus scrofa domesticus L.) were placed on a soil surface to decompose naturally and their odour profile monitored over a period of two months. Corresponding control sites were also monitored to determine the VOC profile of the surrounding environment. Samples were collected from the soil below and the air (headspace) above the decomposed remains using sorbent tubes and analysed using gas chromatography-mass spectrometry. A total of 249 compounds were identified but only 58 compounds were common to both air and soil samples. This study has demonstrated that soil and air samples produce distinct subsets of VOCs that contribute to the overall decomposition odour. Sample collection from only one matrix will reduce the likelihood of detecting the complete spectrum of VOCs, which further confounds the issue of determining a complete and accurate decomposition odour profile. Confirmation of this profile will enhance the performance of cadaver-detection dogs that are tasked with detecting decomposition odour in both soil and air to locate victim remains. PMID:24740412

Decomposition odour profiling in the air and soil surrounding vertebrate carrion.

PubMed

Forbes, Shari L; Perrault, Katelynn A

2014-01-01

Chemical profiling of decomposition odour is conducted in the environmental sciences to detect malodourous target sources in air, water or soil. More recently decomposition odour profiling has been employed in the forensic sciences to generate a profile of the volatile organic compounds (VOCs) produced by decomposed remains. The chemical profile of decomposition odour is still being debated with variations in the VOC profile attributed to the sample collection technique, method of chemical analysis, and environment in which decomposition occurred. To date, little consideration has been given to the partitioning of odour between different matrices and the impact this has on developing an accurate VOC profile. The purpose of this research was to investigate the decomposition odour profile surrounding vertebrate carrion to determine how VOCs partition between soil and air. Four pig carcasses (Sus scrofa domesticus L.) were placed on a soil surface to decompose naturally and their odour profile monitored over a period of two months. Corresponding control sites were also monitored to determine the VOC profile of the surrounding environment. Samples were collected from the soil below and the air (headspace) above the decomposed remains using sorbent tubes and analysed using gas chromatography-mass spectrometry. A total of 249 compounds were identified but only 58 compounds were common to both air and soil samples. This study has demonstrated that soil and air samples produce distinct subsets of VOCs that contribute to the overall decomposition odour. Sample collection from only one matrix will reduce the likelihood of detecting the complete spectrum of VOCs, which further confounds the issue of determining a complete and accurate decomposition odour profile. Confirmation of this profile will enhance the performance of cadaver-detection dogs that are tasked with detecting decomposition odour in both soil and air to locate victim remains.

Two-level Schwartz methods for nonconforming finite elements and discontinuous coefficients

NASA Technical Reports Server (NTRS)

Sarkis, Marcus

1993-01-01

Two-level domain decomposition methods are developed for a simple nonconforming approximation of second order elliptic problems. A bound is established for the condition number of these iterative methods, which grows only logarithmically with the number of degrees of freedom in each subregion. This bound holds for two and three dimensions and is independent of jumps in the value of the coefficients.

Domain decomposition preconditioners for the spectral collocation method

NASA Technical Reports Server (NTRS)

Quarteroni, Alfio; Sacchilandriani, Giovanni

1988-01-01

Several block iteration preconditioners are proposed and analyzed for the solution of elliptic problems by spectral collocation methods in a region partitioned into several rectangles. It is shown that convergence is achieved with a rate which does not depend on the polynomial degree of the spectral solution. The iterative methods here presented can be effectively implemented on multiprocessor systems due to their high degree of parallelism.

Dynamics of phase separation of binary fluids

NASA Technical Reports Server (NTRS)

Ma, Wen-Jong; Maritan, Amos; Banavar, Jayanth R.; Koplik, Joel

1992-01-01

The results of molecular-dynamics studies of surface-tension-dominated spinodal decomposition of initially well-mixed binary fluids in the absence and presence of gravity are presented. The growth exponent for the domain size and the decay exponent of the potential energy of interaction between the two species with time are found to be 0.6 +/- 0.1, inconsistent with scaling arguments based on dimensional analysis.

A numerical scheme based on radial basis function finite difference (RBF-FD) technique for solving the high-dimensional nonlinear Schrödinger equations using an explicit time discretization: Runge-Kutta method

NASA Astrophysics Data System (ADS)

Dehghan, Mehdi; Mohammadi, Vahid

2017-08-01

In this research, we investigate the numerical solution of nonlinear Schrödinger equations in two and three dimensions. The numerical meshless method which will be used here is RBF-FD technique. The main advantage of this method is the approximation of the required derivatives based on finite difference technique at each local-support domain as Ωi. At each Ωi, we require to solve a small linear system of algebraic equations with a conditionally positive definite matrix of order 1 (interpolation matrix). This scheme is efficient and its computational cost is same as the moving least squares (MLS) approximation. A challengeable issue is choosing suitable shape parameter for interpolation matrix in this way. In order to overcome this matter, an algorithm which was established by Sarra (2012), will be applied. This algorithm computes the condition number of the local interpolation matrix using the singular value decomposition (SVD) for obtaining the smallest and largest singular values of that matrix. Moreover, an explicit method based on Runge-Kutta formula of fourth-order accuracy will be applied for approximating the time variable. It also decreases the computational costs at each time step since we will not solve a nonlinear system. On the other hand, to compare RBF-FD method with another meshless technique, the moving kriging least squares (MKLS) approximation is considered for the studied model. Our results demonstrate the ability of the present approach for solving the applicable model which is investigated in the current research work.

Prediction of Microstructure in HAZ of Welds

NASA Astrophysics Data System (ADS)

Khurana, S. P.; Yancey, R.; Jung, G.

2004-06-01

A modeling technique for predicting microstructure in the heat-affected zone (HAZ) of the hypoeutectoid steels is presented. This technique aims at predicting the phase fractions of ferrite, pearlite, bainite and martensite present in the HAZ after the cool down of a weld. The austenite formation kinetics and austenite decomposition kinetics are calculated using the transient temperature profile. The thermal profile in the weld and the HAZ is calculated by finite-element analysis (FEA). Two kinds of austenite decomposition models are included. The final phase fractions are predicted with the help of a continuous cooling transformation (CCT) diagram of the material. In the calculation of phase fractions either the experimental CCT diagram or the mathematically calculated CCT diagram can be used.

GENESIS: a hybrid-parallel and multi-scale molecular dynamics simulator with enhanced sampling algorithms for biomolecular and cellular simulations

PubMed Central

Jung, Jaewoon; Mori, Takaharu; Kobayashi, Chigusa; Matsunaga, Yasuhiro; Yoda, Takao; Feig, Michael; Sugita, Yuji

2015-01-01

GENESIS (Generalized-Ensemble Simulation System) is a new software package for molecular dynamics (MD) simulations of macromolecules. It has two MD simulators, called ATDYN and SPDYN. ATDYN is parallelized based on an atomic decomposition algorithm for the simulations of all-atom force-field models as well as coarse-grained Go-like models. SPDYN is highly parallelized based on a domain decomposition scheme, allowing large-scale MD simulations on supercomputers. Hybrid schemes combining OpenMP and MPI are used in both simulators to target modern multicore computer architectures. Key advantages of GENESIS are (1) the highly parallel performance of SPDYN for very large biological systems consisting of more than one million atoms and (2) the availability of various REMD algorithms (T-REMD, REUS, multi-dimensional REMD for both all-atom and Go-like models under the NVT, NPT, NPAT, and NPγT ensembles). The former is achieved by a combination of the midpoint cell method and the efficient three-dimensional Fast Fourier Transform algorithm, where the domain decomposition space is shared in real-space and reciprocal-space calculations. Other features in SPDYN, such as avoiding concurrent memory access, reducing communication times, and usage of parallel input/output files, also contribute to the performance. We show the REMD simulation results of a mixed (POPC/DMPC) lipid bilayer as a real application using GENESIS. GENESIS is released as free software under the GPLv2 licence and can be easily modified for the development of new algorithms and molecular models. WIREs Comput Mol Sci 2015, 5:310–323. doi: 10.1002/wcms.1220 PMID:26753008

Hierarchical fractional-step approximations and parallel kinetic Monte Carlo algorithms

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

Arampatzis, Giorgos, E-mail: garab@math.uoc.gr; Katsoulakis, Markos A., E-mail: markos@math.umass.edu; Plechac, Petr, E-mail: plechac@math.udel.edu

2012-10-01

We present a mathematical framework for constructing and analyzing parallel algorithms for lattice kinetic Monte Carlo (KMC) simulations. The resulting algorithms have the capacity to simulate a wide range of spatio-temporal scales in spatially distributed, non-equilibrium physiochemical processes with complex chemistry and transport micro-mechanisms. Rather than focusing on constructing exactly the stochastic trajectories, our approach relies on approximating the evolution of observables, such as density, coverage, correlations and so on. More specifically, we develop a spatial domain decomposition of the Markov operator (generator) that describes the evolution of all observables according to the kinetic Monte Carlo algorithm. This domain decompositionmore » corresponds to a decomposition of the Markov generator into a hierarchy of operators and can be tailored to specific hierarchical parallel architectures such as multi-core processors or clusters of Graphical Processing Units (GPUs). Based on this operator decomposition, we formulate parallel Fractional step kinetic Monte Carlo algorithms by employing the Trotter Theorem and its randomized variants; these schemes, (a) are partially asynchronous on each fractional step time-window, and (b) are characterized by their communication schedule between processors. The proposed mathematical framework allows us to rigorously justify the numerical and statistical consistency of the proposed algorithms, showing the convergence of our approximating schemes to the original serial KMC. The approach also provides a systematic evaluation of different processor communicating schedules. We carry out a detailed benchmarking of the parallel KMC schemes using available exact solutions, for example, in Ising-type systems and we demonstrate the capabilities of the method to simulate complex spatially distributed reactions at very large scales on GPUs. Finally, we discuss work load balancing between processors and propose a re-balancing scheme based on probabilistic mass transport methods.« less

Interest rate next-day variation prediction based on hybrid feedforward neural network, particle swarm optimization, and multiresolution techniques

NASA Astrophysics Data System (ADS)

Lahmiri, Salim

2016-02-01

Multiresolution analysis techniques including continuous wavelet transform, empirical mode decomposition, and variational mode decomposition are tested in the context of interest rate next-day variation prediction. In particular, multiresolution analysis techniques are used to decompose interest rate actual variation and feedforward neural network for training and prediction. Particle swarm optimization technique is adopted to optimize its initial weights. For comparison purpose, autoregressive moving average model, random walk process and the naive model are used as main reference models. In order to show the feasibility of the presented hybrid models that combine multiresolution analysis techniques and feedforward neural network optimized by particle swarm optimization, we used a set of six illustrative interest rates; including Moody's seasoned Aaa corporate bond yield, Moody's seasoned Baa corporate bond yield, 3-Month, 6-Month and 1-Year treasury bills, and effective federal fund rate. The forecasting results show that all multiresolution-based prediction systems outperform the conventional reference models on the criteria of mean absolute error, mean absolute deviation, and root mean-squared error. Therefore, it is advantageous to adopt hybrid multiresolution techniques and soft computing models to forecast interest rate daily variations as they provide good forecasting performance.

A practical material decomposition method for x-ray dual spectral computed tomography.

PubMed

Hu, Jingjing; Zhao, Xing

2016-03-17

X-ray dual spectral CT (DSCT) scans the measured object with two different x-ray spectra, and the acquired rawdata can be used to perform the material decomposition of the object. Direct calibration methods allow a faster material decomposition for DSCT and can be separated in two groups: image-based and rawdata-based. The image-based method is an approximative method, and beam hardening artifacts remain in the resulting material-selective images. The rawdata-based method generally obtains better image quality than the image-based method, but this method requires geometrically consistent rawdata. However, today's clinical dual energy CT scanners usually measure different rays for different energy spectra and acquire geometrically inconsistent rawdata sets, and thus cannot meet the requirement. This paper proposes a practical material decomposition method to perform rawdata-based material decomposition in the case of inconsistent measurement. This method first yields the desired consistent rawdata sets from the measured inconsistent rawdata sets, and then employs rawdata-based technique to perform material decomposition and reconstruct material-selective images. The proposed method was evaluated by use of simulated FORBILD thorax phantom rawdata and dental CT rawdata, and simulation results indicate that this method can produce highly quantitative DSCT images in the case of inconsistent DSCT measurements.

Dual domain watermarking for authentication and compression of cultural heritage images.

PubMed

Zhao, Yang; Campisi, Patrizio; Kundur, Deepa

2004-03-01

This paper proposes an approach for the combined image authentication and compression of color images by making use of a digital watermarking and data hiding framework. The digital watermark is comprised of two components: a soft-authenticator watermark for authentication and tamper assessment of the given image, and a chrominance watermark employed to improve the efficiency of compression. The multipurpose watermark is designed by exploiting the orthogonality of various domains used for authentication, color decomposition and watermark insertion. The approach is implemented as a DCT-DWT dual domain algorithm and is applied for the protection and compression of cultural heritage imagery. Analysis is provided to characterize the behavior of the scheme under ideal conditions. Simulations and comparisons of the proposed approach with state-of-the-art existing work demonstrate the potential of the overall scheme.

A Nested Modeling Scheme for High-resolution Simulation of the Aquitard Compaction in a Regional Groundwater Extraction Field

NASA Astrophysics Data System (ADS)

Aichi, M.; Tokunaga, T.

2006-12-01

In the fields that experienced both significant drawdown/land subsidence and the recovery of groundwater potential, temporal change of the effective stress in the clayey layers is not simple. Conducting consolidation tests of core samples is a straightforward approach to know the pre-consolidation stress. However, especially in the urban area, the cost of boring and the limitation of sites for boring make it difficult to carry out enough number of tests. Numerical simulation to reproduce stress history can contribute to selecting boring sites and to complement the results of the laboratory tests. To trace the effective stress profile in the clayey layers by numerical simulation, discretization in the clayey layers should be fine. At the same time, the size of the modeled domain should be large enough to calculate the effect of regional groundwater extraction. Here, we developed a new scheme to reduce memory consumption based on domain decomposition technique. A finite element model of coupled groundwater flow and land subsidence is used for the local model, and a finite difference groundwater flow model is used for the regional model. The local model is discretized to fine mesh in the clayey layers to reproduce the temporal change of pore pressure in the layers while the regional model is discretized to relatively coarse mesh to reproduce the effect of the regional groundwater extraction on the groundwater flow. We have tested this scheme by comparing the results obtained from this scheme with those from the finely gridded model for the entire calculation domain. The difference between the results of these models was small enough and our new scheme can be used for the practical problem.

Conformational dynamics of bacterial trigger factor in apo and ribosome-bound states.

PubMed

Can, Mehmet Tarik; Kurkcuoglu, Zeynep; Ezeroglu, Gokce; Uyar, Arzu; Kurkcuoglu, Ozge; Doruker, Pemra

2017-01-01

The chaperone trigger factor (TF) binds to the ribosome exit tunnel and helps cotranslational folding of nascent chains (NC) in bacterial cells and chloroplasts. In this study, we aim to investigate the functional dynamics of fully-atomistic apo TF and its complex with 50S. As TF accomodates a high percentage of charged residues on its surface, the effect of ionic strength on TF dynamics is assessed here by performing five independent molecular dynamics (MD) simulations (total of 1.3 micro-second duration) at 29 mM and 150 mM ionic strengths. At both concentrations, TF exhibits high inter- and intra-domain flexibility related to its binding (BD), core (CD), and head (HD) domains. Even though large oscillations in gyration radius exist during each run, we do not detect the so-called 'fully collapsed' state with both HD and BD collapsed upon the core. In fact, the extended conformers with relatively open HD and BD are highly populated at the physiological concentration of 150 mM. More importantly, extended TF snapshots stand out in terms of favorable docking onto the 50S subunit. Elastic network modeling (ENM) indicates significant changes in TF's functional dynamics and domain decomposition depending on its conformation and positioning on the 50S. The most dominant slow motions are the lateral sweeping and vertical opening/closing of HD relative to 50S. Finally, our ENM-based efficient technique -ClustENM- is used to sample atomistic conformers starting with an extended TF-50S complex. Specifically, BD and CD motions are restricted near the tunnel exit, while HD is highly mobile. The atomistic conformers generated without an NC are in agreement with the cryo-EM maps available for TF-ribosome-NC complex.

Improved medical image fusion based on cascaded PCA and shift invariant wavelet transforms.

PubMed

Reena Benjamin, J; Jayasree, T

2018-02-01

In the medical field, radiologists need more informative and high-quality medical images to diagnose diseases. Image fusion plays a vital role in the field of biomedical image analysis. It aims to integrate the complementary information from multimodal images, producing a new composite image which is expected to be more informative for visual perception than any of the individual input images. The main objective of this paper is to improve the information, to preserve the edges and to enhance the quality of the fused image using cascaded principal component analysis (PCA) and shift invariant wavelet transforms. A novel image fusion technique based on cascaded PCA and shift invariant wavelet transforms is proposed in this paper. PCA in spatial domain extracts relevant information from the large dataset based on eigenvalue decomposition, and the wavelet transform operating in the complex domain with shift invariant properties brings out more directional and phase details of the image. The significance of maximum fusion rule applied in dual-tree complex wavelet transform domain enhances the average information and morphological details. The input images of the human brain of two different modalities (MRI and CT) are collected from whole brain atlas data distributed by Harvard University. Both MRI and CT images are fused using cascaded PCA and shift invariant wavelet transform method. The proposed method is evaluated based on three main key factors, namely structure preservation, edge preservation, contrast preservation. The experimental results and comparison with other existing fusion methods show the superior performance of the proposed image fusion framework in terms of visual and quantitative evaluations. In this paper, a complex wavelet-based image fusion has been discussed. The experimental results demonstrate that the proposed method enhances the directional features as well as fine edge details. Also, it reduces the redundant details, artifacts, distortions.

Comparison of hybrid spectral-decomposition artificial neural network models for understanding climatic forcing of groundwater levels

NASA Astrophysics Data System (ADS)

Abrokwah, K.; O'Reilly, A. M.

2017-12-01

Groundwater is an important resource that is extracted every day because of its invaluable use for domestic, industrial and agricultural purposes. The need for sustaining groundwater resources is clearly indicated by declining water levels and has led to modeling and forecasting accurate groundwater levels. In this study, spectral decomposition of climatic forcing time series was used to develop hybrid wavelet analysis (WA) and moving window average (MWA) artificial neural network (ANN) models. These techniques are explored by modeling historical groundwater levels in order to provide understanding of potential causes of the observed groundwater-level fluctuations. Selection of the appropriate decomposition level for WA and window size for MWA helps in understanding the important time scales of climatic forcing, such as rainfall, that influence water levels. Discrete wavelet transform (DWT) is used to decompose the input time-series data into various levels of approximate and details wavelet coefficients, whilst MWA acts as a low-pass signal-filtering technique for removing high-frequency signals from the input data. The variables used to develop and validate the models were daily average rainfall measurements from five National Atmospheric and Oceanic Administration (NOAA) weather stations and daily water-level measurements from two wells recorded from 1978 to 2008 in central Florida, USA. Using different decomposition levels and different window sizes, several WA-ANN and MWA-ANN models for simulating the water levels were created and their relative performances compared against each other. The WA-ANN models performed better than the corresponding MWA-ANN models; also higher decomposition levels of the input signal by the DWT gave the best results. The results obtained show the applicability and feasibility of hybrid WA-ANN and MWA-ANN models for simulating daily water levels using only climatic forcing time series as model inputs.

New monitoring by thermogravimetry for radiation degradation of EVA

NASA Astrophysics Data System (ADS)

Boguski, J.; Przybytniak, G.; Łyczko, K.

2014-07-01

The radiation ageing of ethylene vinyl-acetate copolymer (EVA) as the jacket of cable applied in nuclear power plant was carried out by gamma rays irradiation, and the degradation was monitored by a thermo-gravimetric analysis (TGA). The EVA decomposition rate in air by the isothermal at 400 °C decreased with increase of dose and also with decrease of the dose rate. The behavior of EVA jacket of cable indicated that the decomposition rate at 400 °C was reduced with increase of oxidation. The elongation at break by tensile test for the radiation aged EVA was closely related to the decomposition rate at 400 °C; therefore, the TGA might be applied for a diagnostic technique of the cable degradation.

Implementation of ADI: Schemes on MIMD parallel computers

NASA Technical Reports Server (NTRS)

Vanderwijngaart, Rob F.

1993-01-01

In order to simulate the effects of the impingement of hot exhaust jets of High Performance Aircraft on landing surfaces a multi-disciplinary computation coupling flow dynamics to heat conduction in the runway needs to be carried out. Such simulations, which are essentially unsteady, require very large computational power in order to be completed within a reasonable time frame of the order of an hour. Such power can be furnished by the latest generation of massively parallel computers. These remove the bottleneck of ever more congested data paths to one or a few highly specialized central processing units (CPU's) by having many off-the-shelf CPU's work independently on their own data, and exchange information only when needed. During the past year the first phase of this project was completed, in which the optimal strategy for mapping an ADI-algorithm for the three dimensional unsteady heat equation to a MIMD parallel computer was identified. This was done by implementing and comparing three different domain decomposition techniques that define the tasks for the CPU's in the parallel machine. These implementations were done for a Cartesian grid and Dirichlet boundary conditions. The most promising technique was then used to implement the heat equation solver on a general curvilinear grid with a suite of nontrivial boundary conditions. Finally, this technique was also used to implement the Scalar Penta-diagonal (SP) benchmark, which was taken from the NAS Parallel Benchmarks report. All implementations were done in the programming language C on the Intel iPSC/860 computer.

Process modelling for materials preparation experiments

NASA Technical Reports Server (NTRS)

Rosenberger, Franz; Alexander, J. Iwan D.

1994-01-01

The main goals of the research under this grant consist of the development of mathematical tools and measurement techniques for transport properties necessary for high fidelity modelling of crystal growth from the melt and solution. Of the tasks described in detail in the original proposal, two remain to be worked on: development of a spectral code for moving boundary problems, and development of an expedient diffusivity measurement technique for concentrated and supersaturated solutions. We have focused on developing a code to solve for interface shape, heat and species transport during directional solidification. The work involved the computation of heat, mass and momentum transfer during Bridgman-Stockbarger solidification of compound semiconductors. Domain decomposition techniques and preconditioning methods were used in conjunction with Chebyshev spectral methods to accelerate convergence while retaining the high-order spectral accuracy. During the report period we have further improved our experimental setup. These improvements include: temperature control of the measurement cell to 0.1 C between 10 and 60 C; enclosure of the optical measurement path outside the ZYGO interferometer in a metal housing that is temperature controlled to the same temperature setting as the measurement cell; simultaneous dispensing and partial removal of the lower concentration (lighter) solution above the higher concentration (heavier) solution through independently motor-driven syringes; three-fold increase in data resolution by orientation of the interferometer with respect to diffusion direction; and increase of the optical path length in the solution cell to 12 mm.

Scalable Domain Decomposed Monte Carlo Particle Transport

NASA Astrophysics Data System (ADS)

O'Brien, Matthew Joseph

In this dissertation, we present the parallel algorithms necessary to run domain decomposed Monte Carlo particle transport on large numbers of processors (millions of processors). Previous algorithms were not scalable, and the parallel overhead became more computationally costly than the numerical simulation. The main algorithms we consider are: • Domain decomposition of constructive solid geometry: enables extremely large calculations in which the background geometry is too large to fit in the memory of a single computational node. • Load Balancing: keeps the workload per processor as even as possible so the calculation runs efficiently. • Global Particle Find: if particles are on the wrong processor, globally resolve their locations to the correct processor based on particle coordinate and background domain. • Visualizing constructive solid geometry, sourcing particles, deciding that particle streaming communication is completed and spatial redecomposition. These algorithms are some of the most important parallel algorithms required for domain decomposed Monte Carlo particle transport. We demonstrate that our previous algorithms were not scalable, prove that our new algorithms are scalable, and run some of the algorithms up to 2 million MPI processes on the Sequoia supercomputer.

Electrochemical Protection of Thin Film Electrodes in Solid State Nanopores

PubMed Central

Harrer, Stefan; Waggoner, Philip S.; Luan, Binquan; Afzali-Ardakani, Ali; Goldfarb, Dario L.; Peng, Hongbo; Martyna, Glenn; Rossnagel, Stephen M.; Stolovitzky, Gustavo A.

2011-01-01

We have eliminated electrochemical surface oxidation and reduction as well as water decomposition inside sub-5-nm wide nanopores in conducting TiN membranes using a surface passivation technique. Nanopore ionic conductances, and therefore pore diameters, were unchanged in passivated pores after applying potentials of ±4.5 V for as long as 24 h. Water decomposition was eliminated by using aqueous 90% glycerol solvent. The use of a protective self-assembled monolayer of hexadecylphosphonic acid was also investigated. PMID:21597142

SOI layout decomposition for double patterning lithography on high-performance computer platforms

NASA Astrophysics Data System (ADS)

Verstov, Vladimir; Zinchenko, Lyudmila; Makarchuk, Vladimir

2014-12-01

In the paper silicon on insulator layout decomposition algorithms for the double patterning lithography on high performance computing platforms are discussed. Our approach is based on the use of a contradiction graph and a modified concurrent breadth-first search algorithm. We evaluate our technique on 45 nm Nangate Open Cell Library including non-Manhattan geometry. Experimental results show that our soft computing algorithms decompose layout successfully and a minimal distance between polygons in layout is increased.

Koopman Mode Decomposition Methods in Dynamic Stall: Reduced Order Modeling and Control

DTIC Science & Technology

2015-11-10

the flow phenomena by separating them into individual modes. The technique of Proper Orthogonal Decomposition (POD), see [ Holmes : 1998] is a popular...sampled values h(k), k = 0,…,2M-1, of the exponential sum 1. Solve the following linear system where 2. Compute all zeros zj  D, j = 1,…,M...of the Prony polynomial i.e., calculate all eigenvalues of the associated companion matrix and form fj = log zj for j = 1,…,M, where log is the

[Progress in Raman spectroscopic measurement of methane hydrate].

PubMed

Xu, Feng; Zhu, Li-hua; Wu, Qiang; Xu, Long-jun

2009-09-01

Complex thermodynamics and kinetics problems are involved in the methane hydrate formation and decomposition, and these problems are crucial to understanding the mechanisms of hydrate formation and hydrate decomposition. However, it was difficult to accurately obtain such information due to the difficulty of measurement since methane hydrate is only stable under low temperature and high pressure condition, and until recent years, methane hydrate has been measured in situ using Raman spectroscopy. Raman spectroscopy, a non-destructive and non-invasive technique, is used to study vibrational modes of molecules. Studies of methane hydrate using Raman spectroscopy have been developed over the last decade. The Raman spectra of CH4 in vapor phase and in hydrate phase are presented in this paper. The progress in the research on methane hydrate formation thermodynamics, formation kinetics, decomposition kinetics and decomposition mechanism based on Raman spectroscopic measurements in the laboratory and deep sea are reviewed. Formation thermodynamic studies, including in situ observation of formation condition of methane hydrate, analysis of structure, and determination of hydrate cage occupancy and hydration numbers by using Raman spectroscopy, are emphasized. In the aspect of formation kinetics, research on variation in hydrate cage amount and methane concentration in water during the growth of hydrate using Raman spectroscopy is also introduced. For the methane hydrate decomposition, the investigation associated with decomposition mechanism, the mutative law of cage occupancy ratio and the formulation of decomposition rate in porous media are described. The important aspects for future hydrate research based on Raman spectroscopy are discussed.

EEMD-Based Steady-State Indexes and Their Applications to Condition Monitoring and Fault Diagnosis of Railway Axle Bearings

PubMed Central

Fan, Wei; Tsui, Kwok-Leung; Lin, Jianhui

2018-01-01

Railway axle bearings are one of the most important components used in vehicles and their failures probably result in unexpected accidents and economic losses. To realize a condition monitoring and fault diagnosis scheme of railway axle bearings, three dimensionless steadiness indexes in a time domain, a frequency domain, and a shape domain are respectively proposed to measure the steady states of bearing vibration signals. Firstly, vibration data collected from some designed experiments are pre-processed by using ensemble empirical mode decomposition (EEMD). Then, the coefficient of variation is introduced to construct two steady-state indexes from pre-processed vibration data in a time domain and a frequency domain, respectively. A shape function is used to construct a steady-state index in a shape domain. At last, to distinguish normal and abnormal bearing health states, some guideline thresholds are proposed. Further, to identify axle bearings with outer race defects, a pin roller defect, a cage defect, and coupling defects, the boundaries of all steadiness indexes are experimentally established. Experimental results showed that the proposed condition monitoring and fault diagnosis scheme is effective in identifying different bearing health conditions. PMID:29495446

On domain modelling of the service system with its application to enterprise information systems

NASA Astrophysics Data System (ADS)

Wang, J. W.; Wang, H. F.; Ding, J. L.; Furuta, K.; Kanno, T.; Ip, W. H.; Zhang, W. J.

2016-01-01

Information systems are a kind of service systems and they are throughout every element of a modern industrial and business system, much like blood in our body. Types of information systems are heterogeneous because of extreme uncertainty in changes in modern industrial and business systems. To effectively manage information systems, modelling of the work domain (or domain) of information systems is necessary. In this paper, a domain modelling framework for the service system is proposed and its application to the enterprise information system is outlined. The framework is defined based on application of a general domain modelling tool called function-context-behaviour-principle-state-structure (FCBPSS). The FCBPSS is based on a set of core concepts, namely: function, context, behaviour, principle, state and structure and system decomposition. Different from many other applications of FCBPSS in systems engineering, the FCBPSS is applied to both infrastructure and substance systems, which is novel and effective to modelling of service systems including enterprise information systems. It is to be noted that domain modelling of systems (e.g. enterprise information systems) is a key to integration of heterogeneous systems and to coping with unanticipated situations facing to systems.

A comparative quantitative analysis of the IDEAL (iterative decomposition of water and fat with echo asymmetry and least-squares estimation) and the CHESS (chemical shift selection suppression) techniques in 3.0 T L-spine MRI

NASA Astrophysics Data System (ADS)

Kim, Eng-Chan; Cho, Jae-Hwan; Kim, Min-Hye; Kim, Ki-Hong; Choi, Cheon-Woong; Seok, Jong-min; Na, Kil-Ju; Han, Man-Seok

2013-03-01

This study was conducted on 20 patients who had undergone pedicle screw fixation between March and December 2010 to quantitatively compare a conventional fat suppression technique, CHESS (chemical shift selection suppression), and a new technique, IDEAL (iterative decomposition of water and fat with echo asymmetry and least squares estimation). The general efficacy and usefulness of the IDEAL technique was also evaluated. Fat-suppressed transverse-relaxation-weighed images and longitudinal-relaxation-weighted images were obtained before and after contrast injection by using these two techniques with a 1.5T MR (magnetic resonance) scanner. The obtained images were analyzed for image distortion, susceptibility artifacts and homogenous fat removal in the target region. The results showed that the image distortion due to the susceptibility artifacts caused by implanted metal was lower in the images obtained using the IDEAL technique compared to those obtained using the CHESS technique. The results of a qualitative analysis also showed that compared to the CHESS technique, fewer susceptibility artifacts and more homogenous fat removal were found in the images obtained using the IDEAL technique in a comparative image evaluation of the axial plane images before and after contrast injection. In summary, compared to the CHESS technique, the IDEAL technique showed a lower occurrence of susceptibility artifacts caused by metal and lower image distortion. In addition, more homogenous fat removal was shown in the IDEAL technique.

Efficient computation of turbulent flow in ribbed passages using a non-overlapping near-wall domain decomposition method

NASA Astrophysics Data System (ADS)

Jones, Adam; Utyuzhnikov, Sergey

2017-08-01

Turbulent flow in a ribbed channel is studied using an efficient near-wall domain decomposition (NDD) method. The NDD approach is formulated by splitting the computational domain into an inner and outer region, with an interface boundary between the two. The computational mesh covers the outer region, and the flow in this region is solved using the open-source CFD code Code_Saturne with special boundary conditions on the interface boundary, called interface boundary conditions (IBCs). The IBCs are of Robin type and incorporate the effect of the inner region on the flow in the outer region. IBCs are formulated in terms of the distance from the interface boundary to the wall in the inner region. It is demonstrated that up to 90% of the region between the ribs in the ribbed passage can be removed from the computational mesh with an error on the friction factor within 2.5%. In addition, computations with NDD are faster than computations based on low Reynolds number (LRN) models by a factor of five. Different rib heights can be studied with the same mesh in the outer region without affecting the accuracy of the friction factor. This is tested with six different rib heights in an example of a design optimisation study. It is found that the friction factors computed with NDD are almost identical to the fully-resolved results. When used for inverse problems, NDD is considerably more efficient than LRN computations because only one computation needs to be performed and only one mesh needs to be generated.

A spectral X-ray CT simulation study for quantitative determination of iron

NASA Astrophysics Data System (ADS)

Su, Ting; Kaftandjian, Valérie; Duvauchelle, Philippe; Zhu, Yuemin

2018-06-01

Iron is an essential element in the human body and disorders in iron such as iron deficiency or overload can cause serious diseases. This paper aims to explore the ability of spectral X-ray CT to quantitatively separate iron from calcium and potassium and to investigate the influence of different acquisition parameters on material decomposition performance. We simulated spectral X-ray CT imaging of a PMMA phantom filled with iron, calcium, and potassium solutions at various concentrations (15-200 mg/cc). Different acquisition parameters were considered, such as the number of energy bins (6, 10, 15, 20, 30, 60) and exposure factor per projection (0.025, 0.1, 1, 10, 100 mA s). Based on the simulation data, we investigated the performance of two regularized material decomposition approaches: projection domain method and image domain method. It was found that the former method discriminated iron from calcium, potassium and water in all cases and tended to benefit from lower number of energy bins for lower exposure factor acquisition. The latter method succeeded in iron determination only when the number of energy bins equals 60, and in this case, the contrast-to-noise ratios of the decomposed iron images are higher than those obtained using the projection domain method. The results demonstrate that both methods are able to discriminate and quantify iron from calcium, potassium and water under certain conditions. Their performances vary with the acquisition parameters of spectral CT. One can use one method or the other to benefit better performance according to the data available.

A novel spatial-temporal detection method of dim infrared moving small target

NASA Astrophysics Data System (ADS)

Chen, Zhong; Deng, Tao; Gao, Lei; Zhou, Heng; Luo, Song

2014-09-01

Moving small target detection under complex background in infrared image sequence is one of the major challenges of modern military in Early Warning Systems (EWS) and the use of Long-Range Strike (LRS). However, because of the low SNR and undulating background, the infrared moving small target detection is a difficult problem in a long time. To solve this problem, a novel spatial-temporal detection method based on bi-dimensional empirical mode decomposition (EMD) and time-domain difference is proposed in this paper. This method is downright self-data decomposition and do not rely on any transition kernel function, so it has a strong adaptive capacity. Firstly, we generalized the 1D EMD algorithm to the 2D case. In this process, the project has solved serial issues in 2D EMD, such as large amount of data operations, define and identify extrema in 2D case, and two-dimensional signal boundary corrosion. The EMD algorithm studied in this project can be well adapted to the automatic detection of small targets under low SNR and complex background. Secondly, considering the characteristics of moving target, we proposed an improved filtering method based on three-frame difference on basis of the original difference filtering in time-domain, which greatly improves the ability of anti-jamming algorithm. Finally, we proposed a new time-space fusion method based on a combined processing of 2D EMD and improved time-domain differential filtering. And, experimental results show that this method works well in infrared small moving target detection under low SNR and complex background.

Improving the Design of Laboratory Worksheets.

ERIC Educational Resources Information Center

McDowell, E. T.; Wadding, R. E. L.

1985-01-01

Describes a technique to improve the adaptation, development, and utilization of laboratory worksheets. Two sample worksheets (on decomposition of ethanol and on solubility of potassium chloride) are included. (JN)

OMA analysis of a launcher under operational conditions with time-varying properties

NASA Astrophysics Data System (ADS)

Eugeni, M.; Coppotelli, G.; Mastroddi, F.; Gaudenzi, P.; Muller, S.; Troclet, B.

2018-05-01

The objective of this paper is the investigation of the capability of operational modal analysis approaches to deal with time-varying system in the low-frequency domain. Specifically, the problem of the identification of the dynamic properties of a launch vehicle, working under actual operative conditions, is studied. Two OMA methods are considered: the frequency-domain decomposition and the Hilbert transform method. It is demonstrated that both OMA approaches allow the time-tracking of modal parameters, namely, natural frequencies, damping ratios, and mode shapes, from the response accelerations only recorded during actual flight tests of a launcher characterized by a large mass variation due to fuel burning typical of the first phase of the flight.

Supercomputer simulations of structure formation in the Universe

NASA Astrophysics Data System (ADS)

Ishiyama, Tomoaki

2017-06-01

We describe the implementation and performance results of our massively parallel MPI†/OpenMP‡ hybrid TreePM code for large-scale cosmological N-body simulations. For domain decomposition, a recursive multi-section algorithm is used and the size of domains are automatically set so that the total calculation time is the same for all processes. We developed a highly-tuned gravity kernel for short-range forces, and a novel communication algorithm for long-range forces. For two trillion particles benchmark simulation, the average performance on the fullsystem of K computer (82,944 nodes, the total number of core is 663,552) is 5.8 Pflops, which corresponds to 55% of the peak speed.

Spatially coupled catalytic ignition of CO oxidation on Pt: mesoscopic versus nano-scale

PubMed Central

Spiel, C.; Vogel, D.; Schlögl, R.; Rupprechter, G.; Suchorski, Y.

2015-01-01

Spatial coupling during catalytic ignition of CO oxidation on μm-sized Pt(hkl) domains of a polycrystalline Pt foil has been studied in situ by PEEM (photoemission electron microscopy) in the 10−5 mbar pressure range. The same reaction has been examined under similar conditions by FIM (field ion microscopy) on nm-sized Pt(hkl) facets of a Pt nanotip. Proper orthogonal decomposition (POD) of the digitized FIM images has been employed to analyze spatiotemporal dynamics of catalytic ignition. The results show the essential role of the sample size and of the morphology of the domain (facet) boundary in the spatial coupling in CO oxidation. PMID:26021411

Convolution of large 3D images on GPU and its decomposition

NASA Astrophysics Data System (ADS)

Karas, Pavel; Svoboda, David

2011-12-01

In this article, we propose a method for computing convolution of large 3D images. The convolution is performed in a frequency domain using a convolution theorem. The algorithm is accelerated on a graphic card by means of the CUDA parallel computing model. Convolution is decomposed in a frequency domain using the decimation in frequency algorithm. We pay attention to keeping our approach efficient in terms of both time and memory consumption and also in terms of memory transfers between CPU and GPU which have a significant inuence on overall computational time. We also study the implementation on multiple GPUs and compare the results between the multi-GPU and multi-CPU implementations.

Symposium on Parallel Computational Methods for Large-scale Structural Analysis and Design, 2nd, Norfolk, VA, US

NASA Technical Reports Server (NTRS)

Storaasli, Olaf O. (Editor); Housner, Jerrold M. (Editor)

1993-01-01

Computing speed is leaping forward by several orders of magnitude each decade. Engineers and scientists gathered at a NASA Langley symposium to discuss these exciting trends as they apply to parallel computational methods for large-scale structural analysis and design. Among the topics discussed were: large-scale static analysis; dynamic, transient, and thermal analysis; domain decomposition (substructuring); and nonlinear and numerical methods.

Scalable High-order Methods for Multi-Scale Problems: Analysis, Algorithms and Application

DTIC Science & Technology

2016-02-26

Karniadakis, “Resilient algorithms for reconstructing and simulating gappy flow fields in CFD ”, Fluid Dynamic Research, vol. 47, 051402, 2015. 2. Y. Yu, H...simulation, domain decomposition, CFD , gappy data, estimation theory, and gap-tooth algorithm. 16. SECURITY CLASSIFICATION OF: 17. LIMITATION OF...objective of this project was to develop a general CFD framework for multifidelity simula- tions to target multiscale problems but also resilience in

Computational mechanics analysis tools for parallel-vector supercomputers

NASA Technical Reports Server (NTRS)

Storaasli, Olaf O.; Nguyen, Duc T.; Baddourah, Majdi; Qin, Jiangning

1993-01-01

Computational algorithms for structural analysis on parallel-vector supercomputers are reviewed. These parallel algorithms, developed by the authors, are for the assembly of structural equations, 'out-of-core' strategies for linear equation solution, massively distributed-memory equation solution, unsymmetric equation solution, general eigensolution, geometrically nonlinear finite element analysis, design sensitivity analysis for structural dynamics, optimization search analysis and domain decomposition. The source code for many of these algorithms is available.

Methodology for fault detection in induction motors via sound and vibration signals

NASA Astrophysics Data System (ADS)

Delgado-Arredondo, Paulo Antonio; Morinigo-Sotelo, Daniel; Osornio-Rios, Roque Alfredo; Avina-Cervantes, Juan Gabriel; Rostro-Gonzalez, Horacio; Romero-Troncoso, Rene de Jesus

2017-01-01

Nowadays, timely maintenance of electric motors is vital to keep up the complex processes of industrial production. There are currently a variety of methodologies for fault diagnosis. Usually, the diagnosis is performed by analyzing current signals at a steady-state motor operation or during a start-up transient. This method is known as motor current signature analysis, which identifies frequencies associated with faults in the frequency domain or by the time-frequency decomposition of the current signals. Fault identification may also be possible by analyzing acoustic sound and vibration signals, which is useful because sometimes this information is the only available. The contribution of this work is a methodology for detecting faults in induction motors in steady-state operation based on the analysis of acoustic sound and vibration signals. This proposed approach uses the Complete Ensemble Empirical Mode Decomposition for decomposing the signal into several intrinsic mode functions. Subsequently, the frequency marginal of the Gabor representation is calculated to obtain the spectral content of the IMF in the frequency domain. This proposal provides good fault detectability results compared to other published works in addition to the identification of more frequencies associated with the faults. The faults diagnosed in this work are two broken rotor bars, mechanical unbalance and bearing defects.

Membrane covered duct lining for high-frequency noise attenuation: prediction using a Chebyshev collocation method.

PubMed

Huang, Lixi

2008-11-01

A spectral method of Chebyshev collocation with domain decomposition is introduced for linear interaction between sound and structure in a duct lined with flexible walls backed by cavities with or without a porous material. The spectral convergence is validated by a one-dimensional problem with a closed-form analytical solution, and is then extended to the two-dimensional configuration and compared favorably against a previous method based on the Fourier-Galerkin procedure and a finite element modeling. The nonlocal, exact Dirichlet-to-Neumann boundary condition is embedded in the domain decomposition scheme without imposing extra computational burden. The scheme is applied to the problem of high-frequency sound absorption by duct lining, which is normally ineffective when the wavelength is comparable with or shorter than the duct height. When a tensioned membrane covers the lining, however, it scatters the incident plane wave into higher-order modes, which then penetrate the duct lining more easily and get dissipated. For the frequency range of f=0.3-3 studied here, f=0.5 being the first cut-on frequency of the central duct, the membrane cover is found to offer an additional 0.9 dB attenuation per unit axial distance equal to half of the duct height.

Accelerating large-scale simulation of seismic wave propagation by multi-GPUs and three-dimensional domain decomposition

NASA Astrophysics Data System (ADS)

Okamoto, Taro; Takenaka, Hiroshi; Nakamura, Takeshi; Aoki, Takayuki

2010-12-01

We adopted the GPU (graphics processing unit) to accelerate the large-scale finite-difference simulation of seismic wave propagation. The simulation can benefit from the high-memory bandwidth of GPU because it is a "memory intensive" problem. In a single-GPU case we achieved a performance of about 56 GFlops, which was about 45-fold faster than that achieved by a single core of the host central processing unit (CPU). We confirmed that the optimized use of fast shared memory and registers were essential for performance. In the multi-GPU case with three-dimensional domain decomposition, the non-contiguous memory alignment in the ghost zones was found to impose quite long time in data transfer between GPU and the host node. This problem was solved by using contiguous memory buffers for ghost zones. We achieved a performance of about 2.2 TFlops by using 120 GPUs and 330 GB of total memory: nearly (or more than) 2200 cores of host CPUs would be required to achieve the same performance. The weak scaling was nearly proportional to the number of GPUs. We therefore conclude that GPU computing for large-scale simulation of seismic wave propagation is a promising approach as a faster simulation is possible with reduced computational resources compared to CPUs.

Influence of gamma-irradiation on the non-isothermal decomposition of calcium-gadolinium oxalate

NASA Astrophysics Data System (ADS)

Moharana, S. C.; Praharaj, J.; Bhatta, D.

Thermal decomposition of co-precipitated unirradiated and irradiated Ca-Gd oxalate has been studied by adopting differential thermal analysis (DTA) and thermogravimetric (TG) techniques. The reaction occurs through two stages corresponding to the decomposition of gadolinium oxalate (Gd-Ox) followed by that of calcium oxalate (Ca-Ox). The kinetic parameters for both the stages are calculated by using solid state reaction models and Coats-Redfern's equation. The co-precipitation as well as irradiation alter the DTA peak temperatures and the kinetic parameters of Ca-Ox. The decomposition of Gd-Ox follows the two dimensional Contracting area (R-2) mechanism, while that of Ca-Ox follows the Avrami-Erofeev (A(2)) mechanism (n =2), which are also exhibited by the co-precipitated and irradiated samples. Co-precipitation decreases the energy of activation and the pre-exponential factor of the individual components but the reverse phenomenon takes place upon irradiation of the co-precipitate. The mechanisms underlying the phenomena are explored.

Multivariate Curve Resolution Applied to Infrared Reflection Measurements of Soil Contaminated with an Organophosphorus Analyte

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

Gallagher, Neal B.; Blake, Thomas A.; Gassman, Paul L.

2006-07-01

Multivariate curve resolution (MCR) is a powerful technique for extracting chemical information from measured spectra on complex mixtures. The difficulty with applying MCR to soil reflectance measurements is that light scattering artifacts can contribute much more variance to the measurements than the analyte(s) of interest. Two methods were integrated into a MCR decomposition to account for light scattering effects. Firstly, an extended mixture model using pure analyte spectra augmented with scattering ‘spectra’ was used for the measured spectra. And secondly, second derivative preprocessed spectra, which have higher selectivity than the unprocessed spectra, were included in a second block as amore » part of the decomposition. The conventional alternating least squares (ALS) algorithm was modified to simultaneously decompose the measured and second derivative spectra in a two-block decomposition. Equality constraints were also included to incorporate information about sampling conditions. The result was an MCR decomposition that provided interpretable spectra from soil reflectance measurements.« less

Simulation of municipal solid waste degradation in aerobic and anaerobic bioreactor landfills.

PubMed

Patil, Bhagwan Shamrao; C, Agnes Anto; Singh, Devendra Narain

2017-03-01

Municipal solid waste generation is huge in growing cities of developing nations such as India, owing to the rapid industrial and population growth. In addition to various methods for treatment and disposal of municipal solid waste (landfills, composting, bio-methanation, incineration and pyrolysis), aerobic/anaerobic bioreactor landfills are gaining popularity for economical and effective disposal of municipal solid waste. However, efficiency of municipal solid waste bioreactor landfills primarily depends on the municipal solid waste decomposition rate, which can be accelerated through monitoring moisture content and temperature by using the frequency domain reflectometry probe and thermocouples, respectively. The present study demonstrates that these landfill physical properties of the heterogeneous municipal solid waste mass can be monitored using these instruments, which facilitates proper scheduling of the leachate recirculation for accelerating the decomposition rate of municipal solid waste.

FDTD modelling of induced polarization phenomena in transient electromagnetics

NASA Astrophysics Data System (ADS)

Commer, Michael; Petrov, Peter V.; Newman, Gregory A.

2017-04-01

The finite-difference time-domain scheme is augmented in order to treat the modelling of transient electromagnetic signals containing induced polarization effects from 3-D distributions of polarizable media. Compared to the non-dispersive problem, the discrete dispersive Maxwell system contains costly convolution operators. Key components to our solution for highly digitized model meshes are Debye decomposition and composite memory variables. We revert to the popular Cole-Cole model of dispersion to describe the frequency-dependent behaviour of electrical conductivity. Its inversely Laplace-transformed Debye decomposition results in a series of time convolutions between electric field and exponential decay functions, with the latter reflecting each Debye constituents' individual relaxation time. These function types in the discrete-time convolution allow for their substitution by memory variables, annihilating the otherwise prohibitive computing demands. Numerical examples demonstrate the efficiency and practicality of our algorithm.