Preconditioned alternating direction method of multipliers for inverse problems with constraints

NASA Astrophysics Data System (ADS)

Jiao, Yuling; Jin, Qinian; Lu, Xiliang; Wang, Weijie

2017-02-01

We propose a preconditioned alternating direction method of multipliers (ADMM) to solve linear inverse problems in Hilbert spaces with constraints, where the feature of the sought solution under a linear transformation is captured by a possibly non-smooth convex function. During each iteration step, our method avoids solving large linear systems by choosing a suitable preconditioning operator. In case the data is given exactly, we prove the convergence of our preconditioned ADMM without assuming the existence of a Lagrange multiplier. In case the data is corrupted by noise, we propose a stopping rule using information on noise level and show that our preconditioned ADMM is a regularization method; we also propose a heuristic rule when the information on noise level is unavailable or unreliable and give its detailed analysis. Numerical examples are presented to test the performance of the proposed method.

A frequency dependent preconditioned wavelet method for atmospheric tomography

NASA Astrophysics Data System (ADS)

Yudytskiy, Mykhaylo; Helin, Tapio; Ramlau, Ronny

2013-12-01

Atmospheric tomography, i.e. the reconstruction of the turbulence in the atmosphere, is a main task for the adaptive optics systems of the next generation telescopes. For extremely large telescopes, such as the European Extremely Large Telescope, this problem becomes overly complex and an efficient algorithm is needed to reduce numerical costs. Recently, a conjugate gradient method based on wavelet parametrization of turbulence layers was introduced [5]. An iterative algorithm can only be numerically efficient when the number of iterations required for a sufficient reconstruction is low. A way to achieve this is to design an efficient preconditioner. In this paper we propose a new frequency-dependent preconditioner for the wavelet method. In the context of a multi conjugate adaptive optics (MCAO) system simulated on the official end-to-end simulation tool OCTOPUS of the European Southern Observatory we demonstrate robustness and speed of the preconditioned algorithm. We show that three iterations are sufficient for a good reconstruction.

Preconditioning the Helmholtz Equation for Rigid Ducts

NASA Technical Reports Server (NTRS)

Baumeister, Kenneth J.; Kreider, Kevin L.

1998-01-01

An innovative hyperbolic preconditioning technique is developed for the numerical solution of the Helmholtz equation which governs acoustic propagation in ducts. Two pseudo-time parameters are used to produce an explicit iterative finite difference scheme. This scheme eliminates the large matrix storage requirements normally associated with numerical solutions to the Helmholtz equation. The solution procedure is very fast when compared to other transient and steady methods. Optimization and an error analysis of the preconditioning factors are present. For validation, the method is applied to sound propagation in a 2D semi-infinite hard wall duct.

Comparing direct and iterative equation solvers in a large structural analysis software system

NASA Technical Reports Server (NTRS)

Poole, E. L.

1991-01-01

Two direct Choleski equation solvers and two iterative preconditioned conjugate gradient (PCG) equation solvers used in a large structural analysis software system are described. The two direct solvers are implementations of the Choleski method for variable-band matrix storage and sparse matrix storage. The two iterative PCG solvers include the Jacobi conjugate gradient method and an incomplete Choleski conjugate gradient method. The performance of the direct and iterative solvers is compared by solving several representative structural analysis problems. Some key factors affecting the performance of the iterative solvers relative to the direct solvers are identified.

Iterative methods for mixed finite element equations

NASA Technical Reports Server (NTRS)

Nakazawa, S.; Nagtegaal, J. C.; Zienkiewicz, O. C.

1985-01-01

Iterative strategies for the solution of indefinite system of equations arising from the mixed finite element method are investigated in this paper with application to linear and nonlinear problems in solid and structural mechanics. The augmented Hu-Washizu form is derived, which is then utilized to construct a family of iterative algorithms using the displacement method as the preconditioner. Two types of iterative algorithms are implemented. Those are: constant metric iterations which does not involve the update of preconditioner; variable metric iterations, in which the inverse of the preconditioning matrix is updated. A series of numerical experiments is conducted to evaluate the numerical performance with application to linear and nonlinear model problems.

Preconditioned conjugate gradient methods for the compressible Navier-Stokes equations

NASA Technical Reports Server (NTRS)

Venkatakrishnan, V.

1990-01-01

The compressible Navier-Stokes equations are solved for a variety of two-dimensional inviscid and viscous problems by preconditioned conjugate gradient-like algorithms. Roe's flux difference splitting technique is used to discretize the inviscid fluxes. The viscous terms are discretized by using central differences. An algebraic turbulence model is also incorporated. The system of linear equations which arises out of the linearization of a fully implicit scheme is solved iteratively by the well known methods of GMRES (Generalized Minimum Residual technique) and Chebyschev iteration. Incomplete LU factorization and block diagonal factorization are used as preconditioners. The resulting algorithm is competitive with the best current schemes, but has wide applications in parallel computing and unstructured mesh computations.

An accelerated lambda iteration method for multilevel radiative transfer. I - Non-overlapping lines with background continuum

NASA Technical Reports Server (NTRS)

Rybicki, G. B.; Hummer, D. G.

1991-01-01

A method is presented for solving multilevel transfer problems when nonoverlapping lines and background continuum are present and active continuum transfer is absent. An approximate lambda operator is employed to derive linear, 'preconditioned', statistical-equilibrium equations. A method is described for finding the diagonal elements of the 'true' numerical lambda operator, and therefore for obtaining the coefficients of the equations. Iterations of the preconditioned equations, in conjunction with the transfer equation's formal solution, are used to solve linear equations. Some multilevel problems are considered, including an eleven-level neutral helium atom. Diagonal and tridiagonal approximate lambda operators are utilized in the problems to examine the convergence properties of the method, and it is found to be effective for the line transfer problems.

Accelerating nuclear configuration interaction calculations through a preconditioned block iterative eigensolver

NASA Astrophysics Data System (ADS)

Shao, Meiyue; Aktulga, H. Metin; Yang, Chao; Ng, Esmond G.; Maris, Pieter; Vary, James P.

2018-01-01

We describe a number of recently developed techniques for improving the performance of large-scale nuclear configuration interaction calculations on high performance parallel computers. We show the benefit of using a preconditioned block iterative method to replace the Lanczos algorithm that has traditionally been used to perform this type of computation. The rapid convergence of the block iterative method is achieved by a proper choice of starting guesses of the eigenvectors and the construction of an effective preconditioner. These acceleration techniques take advantage of special structure of the nuclear configuration interaction problem which we discuss in detail. The use of a block method also allows us to improve the concurrency of the computation, and take advantage of the memory hierarchy of modern microprocessors to increase the arithmetic intensity of the computation relative to data movement. We also discuss the implementation details that are critical to achieving high performance on massively parallel multi-core supercomputers, and demonstrate that the new block iterative solver is two to three times faster than the Lanczos based algorithm for problems of moderate sizes on a Cray XC30 system.

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

Jing Yanfei, E-mail: yanfeijing@uestc.edu.c; Huang Tingzhu, E-mail: tzhuang@uestc.edu.c; Duan Yong, E-mail: duanyong@yahoo.c

This study is mainly focused on iterative solutions with simple diagonal preconditioning to two complex-valued nonsymmetric systems of linear equations arising from a computational chemistry model problem proposed by Sherry Li of NERSC. Numerical experiments show the feasibility of iterative methods to some extent when applied to the problems and reveal the competitiveness of our recently proposed Lanczos biconjugate A-orthonormalization methods to other classic and popular iterative methods. By the way, experiment results also indicate that application specific preconditioners may be mandatory and required for accelerating convergence.

Projection methods for line radiative transfer in spherical media.

NASA Astrophysics Data System (ADS)

Anusha, L. S.; Nagendra, K. N.

An efficient numerical method called the Preconditioned Bi-Conjugate Gradient (Pre-BiCG) method is presented for the solution of radiative transfer equation in spherical geometry. A variant of this method called Stabilized Preconditioned Bi-Conjugate Gradient (Pre-BiCG-STAB) is also presented. These methods are based on projections on the subspaces of the n dimensional Euclidean space mathbb {R}n called Krylov subspaces. The methods are shown to be faster in terms of convergence rate compared to the contemporary iterative methods such as Jacobi, Gauss-Seidel and Successive Over Relaxation (SOR).

Moving force identification based on modified preconditioned conjugate gradient method

NASA Astrophysics Data System (ADS)

Chen, Zhen; Chan, Tommy H. T.; Nguyen, Andy

2018-06-01

This paper develops a modified preconditioned conjugate gradient (M-PCG) method for moving force identification (MFI) by improving the conjugate gradient (CG) and preconditioned conjugate gradient (PCG) methods with a modified Gram-Schmidt algorithm. The method aims to obtain more accurate and more efficient identification results from the responses of bridge deck caused by vehicles passing by, which are known to be sensitive to ill-posed problems that exist in the inverse problem. A simply supported beam model with biaxial time-varying forces is used to generate numerical simulations with various analysis scenarios to assess the effectiveness of the method. Evaluation results show that regularization matrix L and number of iterations j are very important influence factors to identification accuracy and noise immunity of M-PCG. Compared with the conventional counterpart SVD embedded in the time domain method (TDM) and the standard form of CG, the M-PCG with proper regularization matrix has many advantages such as better adaptability and more robust to ill-posed problems. More importantly, it is shown that the average optimal numbers of iterations of M-PCG can be reduced by more than 70% compared with PCG and this apparently makes M-PCG a preferred choice for field MFI applications.

Generalized Preconditioned Locally Harmonic Residual Eigensolver (GPLHR) v0.1

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

VECHARYNSKI, EUGENE; YANG, CHAO

The software contains a MATLAB implementation of the Generalized Preconditioned Locally Harmonic Residual (GPLHR) method for solving standard and generalized non-Hermitian eigenproblems. The method is particularly useful for computing a subset of eigenvalues, and their eigen- or Schur vectors, closest to a given shift. The proposed method is based on block iterations and can take advantage of a preconditioner if it is available. It does not need to perform exact shift-and-invert transformation. Standard and generalized eigenproblems are handled in a unified framework.

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.

PRECONDITIONED CONJUGATE-GRADIENT 2 (PCG2), a computer program for solving ground-water flow equations

USGS Publications Warehouse

Hill, Mary C.

1990-01-01

This report documents PCG2 : a numerical code to be used with the U.S. Geological Survey modular three-dimensional, finite-difference, ground-water flow model . PCG2 uses the preconditioned conjugate-gradient method to solve the equations produced by the model for hydraulic head. Linear or nonlinear flow conditions may be simulated. PCG2 includes two reconditioning options : modified incomplete Cholesky preconditioning, which is efficient on scalar computers; and polynomial preconditioning, which requires less computer storage and, with modifications that depend on the computer used, is most efficient on vector computers . Convergence of the solver is determined using both head-change and residual criteria. Nonlinear problems are solved using Picard iterations. This documentation provides a description of the preconditioned conjugate gradient method and the two preconditioners, detailed instructions for linking PCG2 to the modular model, sample data inputs, a brief description of PCG2, and a FORTRAN listing.

Accelerating nuclear configuration interaction calculations through a preconditioned block iterative eigensolver

DOE PAGES

Shao, Meiyue; Aktulga, H.  Metin; Yang, Chao; ...

2017-09-14

In this paper, we describe a number of recently developed techniques for improving the performance of large-scale nuclear configuration interaction calculations on high performance parallel computers. We show the benefit of using a preconditioned block iterative method to replace the Lanczos algorithm that has traditionally been used to perform this type of computation. The rapid convergence of the block iterative method is achieved by a proper choice of starting guesses of the eigenvectors and the construction of an effective preconditioner. These acceleration techniques take advantage of special structure of the nuclear configuration interaction problem which we discuss in detail. Themore » use of a block method also allows us to improve the concurrency of the computation, and take advantage of the memory hierarchy of modern microprocessors to increase the arithmetic intensity of the computation relative to data movement. Finally, we also discuss the implementation details that are critical to achieving high performance on massively parallel multi-core supercomputers, and demonstrate that the new block iterative solver is two to three times faster than the Lanczos based algorithm for problems of moderate sizes on a Cray XC30 system.« less

Accelerating nuclear configuration interaction calculations through a preconditioned block iterative eigensolver

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

Shao, Meiyue; Aktulga, H.  Metin; Yang, Chao

In this paper, we describe a number of recently developed techniques for improving the performance of large-scale nuclear configuration interaction calculations on high performance parallel computers. We show the benefit of using a preconditioned block iterative method to replace the Lanczos algorithm that has traditionally been used to perform this type of computation. The rapid convergence of the block iterative method is achieved by a proper choice of starting guesses of the eigenvectors and the construction of an effective preconditioner. These acceleration techniques take advantage of special structure of the nuclear configuration interaction problem which we discuss in detail. Themore » use of a block method also allows us to improve the concurrency of the computation, and take advantage of the memory hierarchy of modern microprocessors to increase the arithmetic intensity of the computation relative to data movement. Finally, we also discuss the implementation details that are critical to achieving high performance on massively parallel multi-core supercomputers, and demonstrate that the new block iterative solver is two to three times faster than the Lanczos based algorithm for problems of moderate sizes on a Cray XC30 system.« less

Implementation of Preconditioned Dual-Time Procedures in OVERFLOW

NASA Technical Reports Server (NTRS)

Pandya, Shishir A.; Venkateswaran, Sankaran; Pulliam, Thomas H.; Kwak, Dochan (Technical Monitor)

2003-01-01

Preconditioning methods have become the method of choice for the solution of flowfields involving the simultaneous presence of low Mach and transonic regions. It is well known that these methods are important for insuring accurate numerical discretization as well as convergence efficiency over various operating conditions such as low Mach number, low Reynolds number and high Strouhal numbers. For unsteady problems, the preconditioning is introduced within a dual-time framework wherein the physical time-derivatives are used to march the unsteady equations and the preconditioned time-derivatives are used for purposes of numerical discretization and iterative solution. In this paper, we describe the implementation of the preconditioned dual-time methodology in the OVERFLOW code. To demonstrate the performance of the method, we employ both simple and practical unsteady flowfields, including vortex propagation in a low Mach number flow, flowfield of an impulsively started plate (Stokes' first problem) arid a cylindrical jet in a low Mach number crossflow with ground effect. All the results demonstrate that the preconditioning algorithm is responsible for improvements to both numerical accuracy and convergence efficiency and, thereby, enables low Mach number unsteady computations to be performed at a fraction of the cost of traditional time-marching methods.

Shape reanalysis and sensitivities utilizing preconditioned iterative boundary solvers

NASA Technical Reports Server (NTRS)

Guru Prasad, K.; Kane, J. H.

1992-01-01

The computational advantages associated with the utilization of preconditined iterative equation solvers are quantified for the reanalysis of perturbed shapes using continuum structural boundary element analysis (BEA). Both single- and multi-zone three-dimensional problems are examined. Significant reductions in computer time are obtained by making use of previously computed solution vectors and preconditioners in subsequent analyses. The effectiveness of this technique is demonstrated for the computation of shape response sensitivities required in shape optimization. Computer times and accuracies achieved using the preconditioned iterative solvers are compared with those obtained via direct solvers and implicit differentiation of the boundary integral equations. It is concluded that this approach employing preconditioned iterative equation solvers in reanalysis and sensitivity analysis can be competitive with if not superior to those involving direct solvers.

Preserving Symmetry in Preconditioned Krylov Subspace Methods

NASA Technical Reports Server (NTRS)

Chan, Tony F.; Chow, E.; Saad, Y.; Yeung, M. C.

1996-01-01

We consider the problem of solving a linear system Ax = b when A is nearly symmetric and when the system is preconditioned by a symmetric positive definite matrix M. In the symmetric case, one can recover symmetry by using M-inner products in the conjugate gradient (CG) algorithm. This idea can also be used in the nonsymmetric case, and near symmetry can be preserved similarly. Like CG, the new algorithms are mathematically equivalent to split preconditioning, but do not require M to be factored. Better robustness in a specific sense can also be observed. When combined with truncated versions of iterative methods, tests show that this is more effective than the common practice of forfeiting near-symmetry altogether.

Analysis of Monte Carlo accelerated iterative methods for sparse linear systems: Analysis of Monte Carlo accelerated iterative methods for sparse linear systems

DOE PAGES

Benzi, Michele; Evans, Thomas M.; Hamilton, Steven P.; ...

2017-03-05

Here, we consider hybrid deterministic-stochastic iterative algorithms for the solution of large, sparse linear systems. Starting from a convergent splitting of the coefficient matrix, we analyze various types of Monte Carlo acceleration schemes applied to the original preconditioned Richardson (stationary) iteration. We expect that these methods will have considerable potential for resiliency to faults when implemented on massively parallel machines. We also establish sufficient conditions for the convergence of the hybrid schemes, and we investigate different types of preconditioners including sparse approximate inverses. Numerical experiments on linear systems arising from the discretization of partial differential equations are presented.

AZTEC: A parallel iterative package for the solving linear systems

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

Hutchinson, S.A.; Shadid, J.N.; Tuminaro, R.S.

1996-12-31

We describe a parallel linear system package, AZTEC. The package incorporates a number of parallel iterative methods (e.g. GMRES, biCGSTAB, CGS, TFQMR) and preconditioners (e.g. Jacobi, Gauss-Seidel, polynomial, domain decomposition with LU or ILU within subdomains). Additionally, AZTEC allows for the reuse of previous preconditioning factorizations within Newton schemes for nonlinear methods. Currently, a number of different users are using this package to solve a variety of PDE applications.

Use of the preconditioned conjugate gradient algorithm as a generic solver for mixed-model equations in animal breeding applications.

PubMed

Tsuruta, S; Misztal, I; Strandén, I

2001-05-01

Utility of the preconditioned conjugate gradient algorithm with a diagonal preconditioner for solving mixed-model equations in animal breeding applications was evaluated with 16 test problems. The problems included single- and multiple-trait analyses, with data on beef, dairy, and swine ranging from small examples to national data sets. Multiple-trait models considered low and high genetic correlations. Convergence was based on relative differences between left- and right-hand sides. The ordering of equations was fixed effects followed by random effects, with no special ordering within random effects. The preconditioned conjugate gradient program implemented with double precision converged for all models. However, when implemented in single precision, the preconditioned conjugate gradient algorithm did not converge for seven large models. The preconditioned conjugate gradient and successive overrelaxation algorithms were subsequently compared for 13 of the test problems. The preconditioned conjugate gradient algorithm was easy to implement with the iteration on data for general models. However, successive overrelaxation requires specific programming for each set of models. On average, the preconditioned conjugate gradient algorithm converged in three times fewer rounds of iteration than successive overrelaxation. With straightforward implementations, programs using the preconditioned conjugate gradient algorithm may be two or more times faster than those using successive overrelaxation. However, programs using the preconditioned conjugate gradient algorithm would use more memory than would comparable implementations using successive overrelaxation. Extensive optimization of either algorithm can influence rankings. The preconditioned conjugate gradient implemented with iteration on data, a diagonal preconditioner, and in double precision may be the algorithm of choice for solving mixed-model equations when sufficient memory is available and ease of implementation is essential.

An Extension of the Krieger-Li-Iafrate Approximation to the Optimized-Effective-Potential Method

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

Wilson, B.G.

1999-11-11

The Krieger-Li-Iafrate approximation can be expressed as the zeroth order result of an unstable iterative method for solving the integral equation form of the optimized-effective-potential method. By pre-conditioning the iterate a first order correction can be obtained which recovers the bulk of quantal oscillations missing in the zeroth order approximation. A comparison of calculated total energies are given with Krieger-Li-Iafrate, Local Density Functional, and Hyper-Hartree-Fock results for non-relativistic atoms and ions.

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.

Preconditioned Mixed Spectral Element Methods for Elasticity and Stokes Problems

NASA Technical Reports Server (NTRS)

Pavarino, Luca F.

1996-01-01

Preconditioned iterative methods for the indefinite systems obtained by discretizing the linear elasticity and Stokes problems with mixed spectral elements in three dimensions are introduced and analyzed. The resulting stiffness matrices have the structure of saddle point problems with a penalty term, which is associated with the Poisson ratio for elasticity problems or with stabilization techniques for Stokes problems. The main results of this paper show that the convergence rate of the resulting algorithms is independent of the penalty parameter, the number of spectral elements Nu and mildly dependent on the spectral degree eta via the inf-sup constant. The preconditioners proposed for the whole indefinite system are block-diagonal and block-triangular. Numerical experiments presented in the final section show that these algorithms are a practical and efficient strategy for the iterative solution of the indefinite problems arising from mixed spectral element discretizations of elliptic systems.

Multilevel Iterative Methods in Nonlinear Computational Plasma Physics

NASA Astrophysics Data System (ADS)

Knoll, D. A.; Finn, J. M.

1997-11-01

Many applications in computational plasma physics involve the implicit numerical solution of coupled systems of nonlinear partial differential equations or integro-differential equations. Such problems arise in MHD, systems of Vlasov-Fokker-Planck equations, edge plasma fluid equations. We have been developing matrix-free Newton-Krylov algorithms for such problems and have applied these algorithms to the edge plasma fluid equations [1,2] and to the Vlasov-Fokker-Planck equation [3]. Recently we have found that with increasing grid refinement, the number of Krylov iterations required per Newton iteration has grown unmanageable [4]. This has led us to the study of multigrid methods as a means of preconditioning matrix-free Newton-Krylov methods. In this poster we will give details of the general multigrid preconditioned Newton-Krylov algorithm, as well as algorithm performance details on problems of interest in the areas of magnetohydrodynamics and edge plasma physics. Work supported by US DoE 1. Knoll and McHugh, J. Comput. Phys., 116, pg. 281 (1995) 2. Knoll and McHugh, Comput. Phys. Comm., 88, pg. 141 (1995) 3. Mousseau and Knoll, J. Comput. Phys. (1997) (to appear) 4. Knoll and McHugh, SIAM J. Sci. Comput. 19, (1998) (to appear)

An iterative solver for the 3D Helmholtz equation

NASA Astrophysics Data System (ADS)

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

2017-09-01

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

Conjugate-gradient preconditioning methods for shift-variant PET image reconstruction.

PubMed

Fessler, J A; Booth, S D

1999-01-01

Gradient-based iterative methods often converge slowly for tomographic image reconstruction and image restoration problems, but can be accelerated by suitable preconditioners. Diagonal preconditioners offer some improvement in convergence rate, but do not incorporate the structure of the Hessian matrices in imaging problems. Circulant preconditioners can provide remarkable acceleration for inverse problems that are approximately shift-invariant, i.e., for those with approximately block-Toeplitz or block-circulant Hessians. However, in applications with nonuniform noise variance, such as arises from Poisson statistics in emission tomography and in quantum-limited optical imaging, the Hessian of the weighted least-squares objective function is quite shift-variant, and circulant preconditioners perform poorly. Additional shift-variance is caused by edge-preserving regularization methods based on nonquadratic penalty functions. This paper describes new preconditioners that approximate more accurately the Hessian matrices of shift-variant imaging problems. Compared to diagonal or circulant preconditioning, the new preconditioners lead to significantly faster convergence rates for the unconstrained conjugate-gradient (CG) iteration. We also propose a new efficient method for the line-search step required by CG methods. Applications to positron emission tomography (PET) illustrate the method.

Multigrid preconditioned conjugate-gradient method for large-scale wave-front reconstruction.

PubMed

Gilles, Luc; Vogel, Curtis R; Ellerbroek, Brent L

2002-09-01

We introduce a multigrid preconditioned conjugate-gradient (MGCG) iterative scheme for computing open-loop wave-front reconstructors for extreme adaptive optics systems. We present numerical simulations for a 17-m class telescope with n = 48756 sensor measurement grid points within the aperture, which indicate that our MGCG method has a rapid convergence rate for a wide range of subaperture average slope measurement signal-to-noise ratios. The total computational cost is of order n log n. Hence our scheme provides for fast wave-front simulation and control in large-scale adaptive optics systems.

Multiple solution of linear algebraic systems by an iterative method with recomputed preconditioner in the analysis of microstrip structures

NASA Astrophysics Data System (ADS)

Ahunov, Roman R.; Kuksenko, Sergey P.; Gazizov, Talgat R.

2016-06-01

A multiple solution of linear algebraic systems with dense matrix by iterative methods is considered. To accelerate the process, the recomputing of the preconditioning matrix is used. A priory condition of the recomputing based on change of the arithmetic mean of the current solution time during the multiple solution is proposed. To confirm the effectiveness of the proposed approach, the numerical experiments using iterative methods BiCGStab and CGS for four different sets of matrices on two examples of microstrip structures are carried out. For solution of 100 linear systems the acceleration up to 1.6 times, compared to the approach without recomputing, is obtained.

An overview of NSPCG: A nonsymmetric preconditioned conjugate gradient package

NASA Astrophysics Data System (ADS)

Oppe, Thomas C.; Joubert, Wayne D.; Kincaid, David R.

1989-05-01

The most recent research-oriented software package developed as part of the ITPACK Project is called "NSPCG" since it contains many nonsymmetric preconditioned conjugate gradient procedures. It is designed to solve large sparse systems of linear algebraic equations by a variety of different iterative methods. One of the main purposes for the development of the package is to provide a common modular structure for research on iterative methods for nonsymmetric matrices. Another purpose for the development of the package is to investigate the suitability of several iterative methods for vector computers. Since the vectorizability of an iterative method depends greatly on the matrix structure, NSPCG allows great flexibility in the operator representation. The coefficient matrix can be passed in one of several different matrix data storage schemes. These sparse data formats allow matrices with a wide range of structures from highly structured ones such as those with all nonzeros along a relatively small number of diagonals to completely unstructured sparse matrices. Alternatively, the package allows the user to call the accelerators directly with user-supplied routines for performing certain matrix operations. In this case, one can use the data format from an application program and not be required to copy the matrix into one of the package formats. This is particularly advantageous when memory space is limited. Some of the basic preconditioners that are available are point methods such as Jacobi, Incomplete LU Decomposition and Symmetric Successive Overrelaxation as well as block and multicolor preconditioners. The user can select from a large collection of accelerators such as Conjugate Gradient (CG), Chebyshev (SI, for semi-iterative), Generalized Minimal Residual (GMRES), Biconjugate Gradient Squared (BCGS) and many others. The package is modular so that almost any accelerator can be used with almost any preconditioner.

The preconditioned Gauss-Seidel method faster than the SOR method

NASA Astrophysics Data System (ADS)

Niki, Hiroshi; Kohno, Toshiyuki; Morimoto, Munenori

2008-09-01

In recent years, a number of preconditioners have been applied to linear systems [A.D. Gunawardena, S.K. Jain, L. Snyder, Modified iterative methods for consistent linear systems, Linear Algebra Appl. 154-156 (1991) 123-143; T. Kohno, H. Kotakemori, H. Niki, M. Usui, Improving modified Gauss-Seidel method for Z-matrices, Linear Algebra Appl. 267 (1997) 113-123; H. Kotakemori, K. Harada, M. Morimoto, H. Niki, A comparison theorem for the iterative method with the preconditioner (I+Smax), J. Comput. Appl. Math. 145 (2002) 373-378; H. Kotakemori, H. Niki, N. Okamoto, Accelerated iteration method for Z-matrices, J. Comput. Appl. Math. 75 (1996) 87-97; M. Usui, H. Niki, T.Kohno, Adaptive Gauss-Seidel method for linear systems, Internat. J. Comput. Math. 51(1994)119-125 [10

Multigrid and Krylov Subspace Methods for the Discrete Stokes Equations

NASA Technical Reports Server (NTRS)

Elman, Howard C.

1996-01-01

Discretization of the Stokes equations produces a symmetric indefinite system of linear equations. For stable discretizations, a variety of numerical methods have been proposed that have rates of convergence independent of the mesh size used in the discretization. In this paper, we compare the performance of four such methods: variants of the Uzawa, preconditioned conjugate gradient, preconditioned conjugate residual, and multigrid methods, for solving several two-dimensional model problems. The results indicate that where it is applicable, multigrid with smoothing based on incomplete factorization is more efficient than the other methods, but typically by no more than a factor of two. The conjugate residual method has the advantage of being both independent of iteration parameters and widely applicable.

Preconditioned augmented Lagrangian formulation for nearly incompressible cardiac mechanics.

PubMed

Campos, Joventino Oliveira; Dos Santos, Rodrigo Weber; Sundnes, Joakim; Rocha, Bernardo Martins

2018-04-01

Computational modeling of the heart is a subject of substantial medical and scientific interest, which may contribute to increase the understanding of several phenomena associated with cardiac physiological and pathological states. Modeling the mechanics of the heart have led to considerable insights, but it still represents a complex and a demanding computational problem, especially in a strongly coupled electromechanical setting. Passive cardiac tissue is commonly modeled as hyperelastic and is characterized by quasi-incompressible, orthotropic, and nonlinear material behavior. These factors are known to be very challenging for the numerical solution of the model. The near-incompressibility is known to cause numerical issues such as the well-known locking phenomenon and ill-conditioning of the stiffness matrix. In this work, the augmented Lagrangian method is used to handle the nearly incompressible condition. This approach can potentially improve computational performance by reducing the condition number of the stiffness matrix and thereby improving the convergence of iterative solvers. We also improve the performance of iterative solvers by the use of an algebraic multigrid preconditioner. Numerical results of the augmented Lagrangian method combined with a preconditioned iterative solver for a cardiac mechanics benchmark suite are presented to show its improved performance. Copyright © 2017 John Wiley & Sons, Ltd.

A SEMI-LAGRANGIAN TWO-LEVEL PRECONDITIONED NEWTON-KRYLOV SOLVER FOR CONSTRAINED DIFFEOMORPHIC IMAGE REGISTRATION.

PubMed

Mang, Andreas; Biros, George

2017-01-01

We propose an efficient numerical algorithm for the solution of diffeomorphic image registration problems. We use a variational formulation constrained by a partial differential equation (PDE), where the constraints are a scalar transport equation. We use a pseudospectral discretization in space and second-order accurate semi-Lagrangian time stepping scheme for the transport equations. We solve for a stationary velocity field using a preconditioned, globalized, matrix-free Newton-Krylov scheme. We propose and test a two-level Hessian preconditioner. We consider two strategies for inverting the preconditioner on the coarse grid: a nested preconditioned conjugate gradient method (exact solve) and a nested Chebyshev iterative method (inexact solve) with a fixed number of iterations. We test the performance of our solver in different synthetic and real-world two-dimensional application scenarios. We study grid convergence and computational efficiency of our new scheme. We compare the performance of our solver against our initial implementation that uses the same spatial discretization but a standard, explicit, second-order Runge-Kutta scheme for the numerical time integration of the transport equations and a single-level preconditioner. Our improved scheme delivers significant speedups over our original implementation. As a highlight, we observe a 20 × speedup for a two dimensional, real world multi-subject medical image registration problem.

Robust parallel iterative solvers for linear and least-squares problems, Final Technical Report

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

Saad, Yousef

2014-01-16

The primary goal of this project is to study and develop robust iterative methods for solving linear systems of equations and least squares systems. The focus of the Minnesota team is on algorithms development, robustness issues, and on tests and validation of the methods on realistic problems. 1. The project begun with an investigation on how to practically update a preconditioner obtained from an ILU-type factorization, when the coefficient matrix changes. 2. We investigated strategies to improve robustness in parallel preconditioners in a specific case of a PDE with discontinuous coefficients. 3. We explored ways to adapt standard preconditioners formore » solving linear systems arising from the Helmholtz equation. These are often difficult linear systems to solve by iterative methods. 4. We have also worked on purely theoretical issues related to the analysis of Krylov subspace methods for linear systems. 5. We developed an effective strategy for performing ILU factorizations for the case when the matrix is highly indefinite. The strategy uses shifting in some optimal way. The method was extended to the solution of Helmholtz equations by using complex shifts, yielding very good results in many cases. 6. We addressed the difficult problem of preconditioning sparse systems of equations on GPUs. 7. A by-product of the above work is a software package consisting of an iterative solver library for GPUs based on CUDA. This was made publicly available. It was the first such library that offers complete iterative solvers for GPUs. 8. We considered another form of ILU which blends coarsening techniques from Multigrid with algebraic multilevel methods. 9. We have released a new version on our parallel solver - called pARMS [new version is version 3]. As part of this we have tested the code in complex settings - including the solution of Maxwell and Helmholtz equations and for a problem of crystal growth.10. As an application of polynomial preconditioning we considered the problem of evaluating f(A)v which arises in statistical sampling. 11. As an application to the methods we developed, we tackled the problem of computing the diagonal of the inverse of a matrix. This arises in statistical applications as well as in many applications in physics. We explored probing methods as well as domain-decomposition type methods. 12. A collaboration with researchers from Toulouse, France, considered the important problem of computing the Schur complement in a domain-decomposition approach. 13. We explored new ways of preconditioning linear systems, based on low-rank approximations.« less

Augmenting the one-shot framework by additional constraints

DOE PAGES

Bosse, Torsten

2016-05-12

The (multistep) one-shot method for design optimization problems has been successfully implemented for various applications. To this end, a slowly convergent primal fixed-point iteration of the state equation is augmented by an adjoint iteration and a corresponding preconditioned design update. In this paper we present a modification of the method that allows for additional equality constraints besides the usual state equation. Finally, a retardation analysis and the local convergence of the method in terms of necessary and sufficient conditions are given, which depend on key characteristics of the underlying problem and the quality of the utilized preconditioner.

Augmenting the one-shot framework by additional constraints

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

Bosse, Torsten

The (multistep) one-shot method for design optimization problems has been successfully implemented for various applications. To this end, a slowly convergent primal fixed-point iteration of the state equation is augmented by an adjoint iteration and a corresponding preconditioned design update. In this paper we present a modification of the method that allows for additional equality constraints besides the usual state equation. Finally, a retardation analysis and the local convergence of the method in terms of necessary and sufficient conditions are given, which depend on key characteristics of the underlying problem and the quality of the utilized preconditioner.

An Unsteady Preconditioning Scheme Based on Convective-Upwind Split-Pressure (CUSP) Artificial Dissipation

DTIC Science & Technology

2014-01-07

this can have a disastrous effect on convergence rate. Even if steady state is obtained for low Mach number flows (after many iterations ), the results...rally lead do a diagonally dominant left-hand-side matrix, which causes stability problems for implicit Gauss - Seidel schemes. For this reason, matrix... convergence at the stagnation point. The iterations for each airfoil is also reported in Fig. 2. Without preconditioning, dramatic efficiency problems are seen

A Robust Locally Preconditioned Semi-Coarsening Multigrid Algorithm for the 2-D Navier-Stokes Equations

NASA Technical Reports Server (NTRS)

Cain, Michael D.

1999-01-01

The goal of this thesis is to develop an efficient and robust locally preconditioned semi-coarsening multigrid algorithm for the two-dimensional Navier-Stokes equations. This thesis examines the performance of the multigrid algorithm with local preconditioning for an upwind-discretization of the Navier-Stokes equations. A block Jacobi iterative scheme is used because of its high frequency error mode damping ability. At low Mach numbers, the performance of a flux preconditioner is investigated. The flux preconditioner utilizes a new limiting technique based on local information that was developed by Siu. Full-coarsening and-semi-coarsening are examined as well as the multigrid V-cycle and full multigrid. The numerical tests were performed on a NACA 0012 airfoil at a range of Mach numbers. The tests show that semi-coarsening with flux preconditioning is the most efficient and robust combination of coarsening strategy, and iterative scheme - especially at low Mach numbers.

Algebraic multigrid preconditioning within parallel finite-element solvers for 3-D electromagnetic modelling problems in geophysics

NASA Astrophysics Data System (ADS)

Koldan, Jelena; Puzyrev, Vladimir; de la Puente, Josep; Houzeaux, Guillaume; Cela, José María

2014-06-01

We present an elaborate preconditioning scheme for Krylov subspace methods which has been developed to improve the performance and reduce the execution time of parallel node-based finite-element (FE) solvers for 3-D electromagnetic (EM) numerical modelling in exploration geophysics. This new preconditioner is based on algebraic multigrid (AMG) that uses different basic relaxation methods, such as Jacobi, symmetric successive over-relaxation (SSOR) and Gauss-Seidel, as smoothers and the wave front algorithm to create groups, which are used for a coarse-level generation. We have implemented and tested this new preconditioner within our parallel nodal FE solver for 3-D forward problems in EM induction geophysics. We have performed series of experiments for several models with different conductivity structures and characteristics to test the performance of our AMG preconditioning technique when combined with biconjugate gradient stabilized method. The results have shown that, the more challenging the problem is in terms of conductivity contrasts, ratio between the sizes of grid elements and/or frequency, the more benefit is obtained by using this preconditioner. Compared to other preconditioning schemes, such as diagonal, SSOR and truncated approximate inverse, the AMG preconditioner greatly improves the convergence of the iterative solver for all tested models. Also, when it comes to cases in which other preconditioners succeed to converge to a desired precision, AMG is able to considerably reduce the total execution time of the forward-problem code-up to an order of magnitude. Furthermore, the tests have confirmed that our AMG scheme ensures grid-independent rate of convergence, as well as improvement in convergence regardless of how big local mesh refinements are. In addition, AMG is designed to be a black-box preconditioner, which makes it easy to use and combine with different iterative methods. Finally, it has proved to be very practical and efficient in the parallel context.

Multilevel acceleration of scattering-source iterations with application to electron transport

DOE PAGES

Drumm, Clif; Fan, Wesley

2017-08-18

Acceleration/preconditioning strategies available in the SCEPTRE radiation transport code are described. A flexible transport synthetic acceleration (TSA) algorithm that uses a low-order discrete-ordinates (S N) or spherical-harmonics (P N) solve to accelerate convergence of a high-order S N source-iteration (SI) solve is described. Convergence of the low-order solves can be further accelerated by applying off-the-shelf incomplete-factorization or algebraic-multigrid methods. Also available is an algorithm that uses a generalized minimum residual (GMRES) iterative method rather than SI for convergence, using a parallel sweep-based solver to build up a Krylov subspace. TSA has been applied as a preconditioner to accelerate the convergencemore » of the GMRES iterations. The methods are applied to several problems involving electron transport and problems with artificial cross sections with large scattering ratios. These methods were compared and evaluated by considering material discontinuities and scattering anisotropy. Observed accelerations obtained are highly problem dependent, but speedup factors around 10 have been observed in typical applications.« less

ONRASIA Scientific Information Bulletin. Volume 8, Number 3, July- September 1993

DTIC Science & Technology

1993-09-01

the Ninth Symposium on Preconditioned Conjugate Dr. Steven F. Ashby Gradient Methods , which he organized. Computing Sciences Department Computing...ditioned Conjugate Gradient Methods , held at Keio chines and is currently a topic of considerable University (Yokohama). During this meeting, I interest...in the United States. In Japan, on the other discussed iterative methods for linear systems with hand, this technique does not appear to be too well

Low-memory iterative density fitting.

PubMed

Grajciar, Lukáš

2015-07-30

A new low-memory modification of the density fitting approximation based on a combination of a continuous fast multipole method (CFMM) and a preconditioned conjugate gradient solver is presented. Iterative conjugate gradient solver uses preconditioners formed from blocks of the Coulomb metric matrix that decrease the number of iterations needed for convergence by up to one order of magnitude. The matrix-vector products needed within the iterative algorithm are calculated using CFMM, which evaluates them with the linear scaling memory requirements only. Compared with the standard density fitting implementation, up to 15-fold reduction of the memory requirements is achieved for the most efficient preconditioner at a cost of only 25% increase in computational time. The potential of the method is demonstrated by performing density functional theory calculations for zeolite fragment with 2592 atoms and 121,248 auxiliary basis functions on a single 12-core CPU workstation. © 2015 Wiley Periodicals, Inc.

High-performance equation solvers and their impact on finite element analysis

NASA Technical Reports Server (NTRS)

Poole, Eugene L.; Knight, Norman F., Jr.; Davis, D. Dale, Jr.

1990-01-01

The role of equation solvers in modern structural analysis software is described. Direct and iterative equation solvers which exploit vectorization on modern high-performance computer systems are described and compared. The direct solvers are two Cholesky factorization methods. The first method utilizes a novel variable-band data storage format to achieve very high computation rates and the second method uses a sparse data storage format designed to reduce the number of operations. The iterative solvers are preconditioned conjugate gradient methods. Two different preconditioners are included; the first uses a diagonal matrix storage scheme to achieve high computation rates and the second requires a sparse data storage scheme and converges to the solution in fewer iterations that the first. The impact of using all of the equation solvers in a common structural analysis software system is demonstrated by solving several representative structural analysis problems.

High-performance equation solvers and their impact on finite element analysis

NASA Technical Reports Server (NTRS)

Poole, Eugene L.; Knight, Norman F., Jr.; Davis, D. D., Jr.

1992-01-01

The role of equation solvers in modern structural analysis software is described. Direct and iterative equation solvers which exploit vectorization on modern high-performance computer systems are described and compared. The direct solvers are two Cholesky factorization methods. The first method utilizes a novel variable-band data storage format to achieve very high computation rates and the second method uses a sparse data storage format designed to reduce the number od operations. The iterative solvers are preconditioned conjugate gradient methods. Two different preconditioners are included; the first uses a diagonal matrix storage scheme to achieve high computation rates and the second requires a sparse data storage scheme and converges to the solution in fewer iterations that the first. The impact of using all of the equation solvers in a common structural analysis software system is demonstrated by solving several representative structural analysis problems.

Fast Multilevel Solvers for a Class of Discrete Fourth Order Parabolic Problems

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

Zheng, Bin; Chen, Luoping; Hu, Xiaozhe

2016-03-05

In this paper, we study fast iterative solvers for the solution of fourth order parabolic equations discretized by mixed finite element methods. We propose to use consistent mass matrix in the discretization and use lumped mass matrix to construct efficient preconditioners. We provide eigenvalue analysis for the preconditioned system and estimate the convergence rate of the preconditioned GMRes method. Furthermore, we show that these preconditioners only need to be solved inexactly by optimal multigrid algorithms. Our numerical examples indicate that the proposed preconditioners are very efficient and robust with respect to both discretization parameters and diffusion coefficients. We also investigatemore » the performance of multigrid algorithms with either collective smoothers or distributive smoothers when solving the preconditioner systems.« less

Sensitivity calculations for iteratively solved problems

NASA Technical Reports Server (NTRS)

Haftka, R. T.

1985-01-01

The calculation of sensitivity derivatives of solutions of iteratively solved systems of algebraic equations is investigated. A modified finite difference procedure is presented which improves the accuracy of the calculated derivatives. The procedure is demonstrated for a simple algebraic example as well as an element-by-element preconditioned conjugate gradient iterative solution technique applied to truss examples.

Repeated Red-Black ordering

NASA Astrophysics Data System (ADS)

Ciarlet, P.

1994-09-01

Hereafter, we describe and analyze, from both a theoretical and a numerical point of view, an iterative method for efficiently solving symmetric elliptic problems with possibly discontinuous coefficients. In the following, we use the Preconditioned Conjugate Gradient method to solve the symmetric positive definite linear systems which arise from the finite element discretization of the problems. We focus our interest on sparse and efficient preconditioners. In order to define the preconditioners, we perform two steps: first we reorder the unknowns and then we carry out a (modified) incomplete factorization of the original matrix. We study numerically and theoretically two preconditioners, the second preconditioner corresponding to the one investigated by Brand and Heinemann [2]. We prove convergence results about the Poisson equation with either Dirichlet or periodic boundary conditions. For a meshsizeh, Brand proved that the condition number of the preconditioned system is bounded byO(h-1/2) for Dirichlet boundary conditions. By slightly modifying the preconditioning process, we prove that the condition number is bounded byO(h-1/3).

Two new modified Gauss-Seidel methods for linear system with M-matrices

NASA Astrophysics Data System (ADS)

Zheng, Bing; Miao, Shu-Xin

2009-12-01

In 2002, H. Kotakemori et al. proposed the modified Gauss-Seidel (MGS) method for solving the linear system with the preconditioner [H. Kotakemori, K. Harada, M. Morimoto, H. Niki, A comparison theorem for the iterative method with the preconditioner () J. Comput. Appl. Math. 145 (2002) 373-378]. Since this preconditioner is constructed by only the largest element on each row of the upper triangular part of the coefficient matrix, the preconditioning effect is not observed on the nth row. In the present paper, to deal with this drawback, we propose two new preconditioners. The convergence and comparison theorems of the modified Gauss-Seidel methods with these two preconditioners for solving the linear system are established. The convergence rates of the new proposed preconditioned methods are compared. In addition, numerical experiments are used to show the effectiveness of the new MGS methods.

Efficient spectral computation of the stationary states of rotating Bose-Einstein condensates by preconditioned nonlinear conjugate gradient methods

NASA Astrophysics Data System (ADS)

Antoine, Xavier; Levitt, Antoine; Tang, Qinglin

2017-08-01

We propose a preconditioned nonlinear conjugate gradient method coupled with a spectral spatial discretization scheme for computing the ground states (GS) of rotating Bose-Einstein condensates (BEC), modeled by the Gross-Pitaevskii Equation (GPE). We first start by reviewing the classical gradient flow (also known as imaginary time (IMT)) method which considers the problem from the PDE standpoint, leading to numerically solve a dissipative equation. Based on this IMT equation, we analyze the forward Euler (FE), Crank-Nicolson (CN) and the classical backward Euler (BE) schemes for linear problems and recognize classical power iterations, allowing us to derive convergence rates. By considering the alternative point of view of minimization problems, we propose the preconditioned steepest descent (PSD) and conjugate gradient (PCG) methods for the GS computation of the GPE. We investigate the choice of the preconditioner, which plays a key role in the acceleration of the convergence process. The performance of the new algorithms is tested in 1D, 2D and 3D. We conclude that the PCG method outperforms all the previous methods, most particularly for 2D and 3D fast rotating BECs, while being simple to implement.

Techniques and Software for Monolithic Preconditioning of Moderately-sized Geodynamic Stokes Flow Problems

NASA Astrophysics Data System (ADS)

Sanan, Patrick; May, Dave A.; Schenk, Olaf; Bollhöffer, Matthias

2017-04-01

Geodynamics simulations typically involve the repeated solution of saddle-point systems arising from the Stokes equations. These computations often dominate the time to solution. Direct solvers are known for their robustness and ``black box'' properties, yet exhibit superlinear memory requirements and time to solution. More complex multilevel-preconditioned iterative solvers have been very successful for large problems, yet their use can require more effort from the practitioner in terms of setting up a solver and choosing its parameters. We champion an intermediate approach, based on leveraging the power of modern incomplete factorization techniques for indefinite symmetric matrices. These provide an interesting alternative in situations in between the regimes where direct solvers are an obvious choice and those where complex, scalable, iterative solvers are an obvious choice. That is, much like their relatives for definite systems, ILU/ICC-preconditioned Krylov methods and ILU/ICC-smoothed multigrid methods, the approaches demonstrated here provide a useful addition to the solver toolkit. We present results with a simple, PETSc-based, open-source Q2-Q1 (Taylor-Hood) finite element discretization, in 2 and 3 dimensions, with the Stokes and Lamé (linear elasticity) saddle point systems. Attention is paid to cases in which full-operator incomplete factorization gives an improvement in time to solution over direct solution methods (which may not even be feasible due to memory limitations), without the complication of more complex (or at least, less-automatic) preconditioners or smoothers. As an important factor in the relevance of these tools is their availability in portable software, we also describe open-source PETSc interfaces to the factorization routines.

A conjugate gradient method for solving the non-LTE line radiation transfer problem

NASA Astrophysics Data System (ADS)

Paletou, F.; Anterrieu, E.

2009-12-01

This study concerns the fast and accurate solution of the line radiation transfer problem, under non-LTE conditions. We propose and evaluate an alternative iterative scheme to the classical ALI-Jacobi method, and to the more recently proposed Gauss-Seidel and successive over-relaxation (GS/SOR) schemes. Our study is indeed based on applying a preconditioned bi-conjugate gradient method (BiCG-P). Standard tests, in 1D plane parallel geometry and in the frame of the two-level atom model with monochromatic scattering are discussed. Rates of convergence between the previously mentioned iterative schemes are compared, as are their respective timing properties. The smoothing capability of the BiCG-P method is also demonstrated.

Preconditioned conjugate residual methods for the solution of spectral equations

NASA Technical Reports Server (NTRS)

Wong, Y. S.; Zang, T. A.; Hussaini, M. Y.

1986-01-01

Conjugate residual methods for the solution of spectral equations are described. An inexact finite-difference operator is introduced as a preconditioner in the iterative procedures. Application of these techniques is limited to problems for which the symmetric part of the coefficient matrix is positive definite. Although the spectral equation is a very ill-conditioned and full matrix problem, the computational effort of the present iterative methods for solving such a system is comparable to that for the sparse matrix equations obtained from the application of either finite-difference or finite-element methods to the same problems. Numerical experiments are shown for a self-adjoint elliptic partial differential equation with Dirichlet boundary conditions, and comparison with other solution procedures for spectral equations is presented.

On iterative processes in the Krylov-Sonneveld subspaces

NASA Astrophysics Data System (ADS)

Ilin, Valery P.

2016-10-01

The iterative Induced Dimension Reduction (IDR) methods are considered for solving large systems of linear algebraic equations (SLAEs) with nonsingular nonsymmetric matrices. These approaches are investigated by many authors and are charachterized sometimes as the alternative to the classical processes of Krylov type. The key moments of the IDR algorithms consist in the construction of the embedded Sonneveld subspaces, which have the decreasing dimensions and use the orthogonalization to some fixed subspace. Other independent approaches for research and optimization of the iterations are based on the augmented and modified Krylov subspaces by using the aggregation and deflation procedures with present various low rank approximations of the original matrices. The goal of this paper is to show, that IDR method in Sonneveld subspaces present an original interpretation of the modified algorithms in the Krylov subspaces. In particular, such description is given for the multi-preconditioned semi-conjugate direction methods which are actual for the parallel algebraic domain decomposition approaches.

A preconditioner for the finite element computation of incompressible, nonlinear elastic deformations

NASA Astrophysics Data System (ADS)

Whiteley, J. P.

2017-10-01

Large, incompressible elastic deformations are governed by a system of nonlinear partial differential equations. The finite element discretisation of these partial differential equations yields a system of nonlinear algebraic equations that are usually solved using Newton's method. On each iteration of Newton's method, a linear system must be solved. We exploit the structure of the Jacobian matrix to propose a preconditioner, comprising two steps. The first step is the solution of a relatively small, symmetric, positive definite linear system using the preconditioned conjugate gradient method. This is followed by a small number of multigrid V-cycles for a larger linear system. Through the use of exemplar elastic deformations, the preconditioner is demonstrated to facilitate the iterative solution of the linear systems arising. The number of GMRES iterations required has only a very weak dependence on the number of degrees of freedom of the linear systems.

Parallelization of the preconditioned IDR solver for modern multicore computer systems

NASA Astrophysics Data System (ADS)

Bessonov, O. A.; Fedoseyev, A. I.

2012-10-01

This paper present the analysis, parallelization and optimization approach for the large sparse matrix solver CNSPACK for modern multicore microprocessors. CNSPACK is an advanced solver successfully used for coupled solution of stiff problems arising in multiphysics applications such as CFD, semiconductor transport, kinetic and quantum problems. It employs iterative IDR algorithm with ILU preconditioning (user chosen ILU preconditioning order). CNSPACK has been successfully used during last decade for solving problems in several application areas, including fluid dynamics and semiconductor device simulation. However, there was a dramatic change in processor architectures and computer system organization in recent years. Due to this, performance criteria and methods have been revisited, together with involving the parallelization of the solver and preconditioner using Open MP environment. Results of the successful implementation for efficient parallelization are presented for the most advances computer system (Intel Core i7-9xx or two-processor Xeon 55xx/56xx).

Parallel iterative solution for h and p approximations of the shallow water equations

USGS Publications Warehouse

Barragy, E.J.; Walters, R.A.

1998-01-01

A p finite element scheme and parallel iterative solver are introduced for a modified form of the shallow water equations. The governing equations are the three-dimensional shallow water equations. After a harmonic decomposition in time and rearrangement, the resulting equations are a complex Helmholz problem for surface elevation, and a complex momentum equation for the horizontal velocity. Both equations are nonlinear and the resulting system is solved using the Picard iteration combined with a preconditioned biconjugate gradient (PBCG) method for the linearized subproblems. A subdomain-based parallel preconditioner is developed which uses incomplete LU factorization with thresholding (ILUT) methods within subdomains, overlapping ILUT factorizations for subdomain boundaries and under-relaxed iteration for the resulting block system. The method builds on techniques successfully applied to linear elements by introducing ordering and condensation techniques to handle uniform p refinement. The combined methods show good performance for a range of p (element order), h (element size), and N (number of processors). Performance and scalability results are presented for a field scale problem where up to 512 processors are used. ?? 1998 Elsevier Science Ltd. All rights reserved.

A Higher Order Iterative Method for Computing the Drazin Inverse

PubMed Central

Soleymani, F.; Stanimirović, Predrag S.

2013-01-01

A method with high convergence rate for finding approximate inverses of nonsingular matrices is suggested and established analytically. An extension of the introduced computational scheme to general square matrices is defined. The extended method could be used for finding the Drazin inverse. The application of the scheme on large sparse test matrices alongside the use in preconditioning of linear system of equations will be presented to clarify the contribution of the paper. PMID:24222747

Implicit solvers for unstructured meshes

NASA Technical Reports Server (NTRS)

Venkatakrishnan, V.; Mavriplis, Dimitri J.

1991-01-01

Implicit methods were developed and tested for unstructured mesh computations. The approximate system which arises from the Newton linearization of the nonlinear evolution operator is solved by using the preconditioned GMRES (Generalized Minimum Residual) technique. Three different preconditioners were studied, namely, the incomplete LU factorization (ILU), block diagonal factorization, and the symmetric successive over relaxation (SSOR). The preconditioners were optimized to have good vectorization properties. SSOR and ILU were also studied as iterative schemes. The various methods are compared over a wide range of problems. Ordering of the unknowns, which affects the convergence of these sparse matrix iterative methods, is also studied. Results are presented for inviscid and turbulent viscous calculations on single and multielement airfoil configurations using globally and adaptively generated meshes.

Applicability of Kerker preconditioning scheme to the self-consistent density functional theory calculations of inhomogeneous systems

NASA Astrophysics Data System (ADS)

Zhou, Yuzhi; Wang, Han; Liu, Yu; Gao, Xingyu; Song, Haifeng

2018-03-01

The Kerker preconditioner, based on the dielectric function of homogeneous electron gas, is designed to accelerate the self-consistent field (SCF) iteration in the density functional theory calculations. However, a question still remains regarding its applicability to the inhomogeneous systems. We develop a modified Kerker preconditioning scheme which captures the long-range screening behavior of inhomogeneous systems and thus improves the SCF convergence. The effectiveness and efficiency is shown by the tests on long-z slabs of metals, insulators, and metal-insulator contacts. For situations without a priori knowledge of the system, we design the a posteriori indicator to monitor if the preconditioner has suppressed charge sloshing during the iterations. Based on the a posteriori indicator, we demonstrate two schemes of the self-adaptive configuration for the SCF iteration.

Application of linear multifrequency-grey acceleration to preconditioned Krylov iterations for thermal radiation transport

DOE PAGES

Till, Andrew T.; Warsa, James S.; Morel, Jim E.

2018-06-15

The thermal radiative transfer (TRT) equations comprise a radiation equation coupled to the material internal energy equation. Linearization of these equations produces effective, thermally-redistributed scattering through absorption-reemission. In this paper, we investigate the effectiveness and efficiency of Linear-Multi-Frequency-Grey (LMFG) acceleration that has been reformulated for use as a preconditioner to Krylov iterative solution methods. We introduce two general frameworks, the scalar flux formulation (SFF) and the absorption rate formulation (ARF), and investigate their iterative properties in the absence and presence of true scattering. SFF has a group-dependent state size but may be formulated without inner iterations in the presence ofmore » scattering, while ARF has a group-independent state size but requires inner iterations when scattering is present. We compare and evaluate the computational cost and efficiency of LMFG applied to these two formulations using a direct solver for the preconditioners. Finally, this work is novel because the use of LMFG for the radiation transport equation, in conjunction with Krylov methods, involves special considerations not required for radiation diffusion.« less

LSRN: A PARALLEL ITERATIVE SOLVER FOR STRONGLY OVER- OR UNDERDETERMINED SYSTEMS*

PubMed Central

Meng, Xiangrui; Saunders, Michael A.; Mahoney, Michael W.

2014-01-01

We describe a parallel iterative least squares solver named LSRN that is based on random normal projection. LSRN computes the min-length solution to minx∈ℝn ‖Ax − b‖2, where A ∈ ℝm × n with m ≫ n or m ≪ n, and where A may be rank-deficient. Tikhonov regularization may also be included. Since A is involved only in matrix-matrix and matrix-vector multiplications, it can be a dense or sparse matrix or a linear operator, and LSRN automatically speeds up when A is sparse or a fast linear operator. The preconditioning phase consists of a random normal projection, which is embarrassingly parallel, and a singular value decomposition of size ⌈γ min(m, n)⌉ × min(m, n), where γ is moderately larger than 1, e.g., γ = 2. We prove that the preconditioned system is well-conditioned, with a strong concentration result on the extreme singular values, and hence that the number of iterations is fully predictable when we apply LSQR or the Chebyshev semi-iterative method. As we demonstrate, the Chebyshev method is particularly efficient for solving large problems on clusters with high communication cost. Numerical results show that on a shared-memory machine, LSRN is very competitive with LAPACK’s DGELSD and a fast randomized least squares solver called Blendenpik on large dense problems, and it outperforms the least squares solver from SuiteSparseQR on sparse problems without sparsity patterns that can be exploited to reduce fill-in. Further experiments show that LSRN scales well on an Amazon Elastic Compute Cloud cluster. PMID:25419094

Krylov subspace methods on supercomputers

NASA Technical Reports Server (NTRS)

Saad, Youcef

1988-01-01

A short survey of recent research on Krylov subspace methods with emphasis on implementation on vector and parallel computers is presented. Conjugate gradient methods have proven very useful on traditional scalar computers, and their popularity is likely to increase as three-dimensional models gain importance. A conservative approach to derive effective iterative techniques for supercomputers has been to find efficient parallel/vector implementations of the standard algorithms. The main source of difficulty in the incomplete factorization preconditionings is in the solution of the triangular systems at each step. A few approaches consisting of implementing efficient forward and backward triangular solutions are described in detail. Polynomial preconditioning as an alternative to standard incomplete factorization techniques is also discussed. Another efficient approach is to reorder the equations so as to improve the structure of the matrix to achieve better parallelism or vectorization. An overview of these and other ideas and their effectiveness or potential for different types of architectures is given.

Fourier analysis of finite element preconditioned collocation schemes

NASA Technical Reports Server (NTRS)

Deville, Michel O.; Mund, Ernest H.

1990-01-01

The spectrum of the iteration operator of some finite element preconditioned Fourier collocation schemes is investigated. The first part of the paper analyses one-dimensional elliptic and hyperbolic model problems and the advection-diffusion equation. Analytical expressions of the eigenvalues are obtained with use of symbolic computation. The second part of the paper considers the set of one-dimensional differential equations resulting from Fourier analysis (in the tranverse direction) of the 2-D Stokes problem. All results agree with previous conclusions on the numerical efficiency of finite element preconditioning schemes.

Direct reconstruction of cardiac PET kinetic parametric images using a preconditioned conjugate gradient approach

PubMed Central

Rakvongthai, Yothin; Ouyang, Jinsong; Guerin, Bastien; Li, Quanzheng; Alpert, Nathaniel M.; El Fakhri, Georges

2013-01-01

Purpose: Our research goal is to develop an algorithm to reconstruct cardiac positron emission tomography (PET) kinetic parametric images directly from sinograms and compare its performance with the conventional indirect approach. Methods: Time activity curves of a NCAT phantom were computed according to a one-tissue compartmental kinetic model with realistic kinetic parameters. The sinograms at each time frame were simulated using the activity distribution for the time frame. The authors reconstructed the parametric images directly from the sinograms by optimizing a cost function, which included the Poisson log-likelihood and a spatial regularization terms, using the preconditioned conjugate gradient (PCG) algorithm with the proposed preconditioner. The proposed preconditioner is a diagonal matrix whose diagonal entries are the ratio of the parameter and the sensitivity of the radioactivity associated with parameter. The authors compared the reconstructed parametric images using the direct approach with those reconstructed using the conventional indirect approach. Results: At the same bias, the direct approach yielded significant relative reduction in standard deviation by 12%–29% and 32%–70% for 50 × 106 and 10 × 106 detected coincidences counts, respectively. Also, the PCG method effectively reached a constant value after only 10 iterations (with numerical convergence achieved after 40–50 iterations), while more than 500 iterations were needed for CG. Conclusions: The authors have developed a novel approach based on the PCG algorithm to directly reconstruct cardiac PET parametric images from sinograms, and yield better estimation of kinetic parameters than the conventional indirect approach, i.e., curve fitting of reconstructed images. The PCG method increases the convergence rate of reconstruction significantly as compared to the conventional CG method. PMID:24089922

Exploiting Data Sparsity in Parallel Matrix Powers Computations

DTIC Science & Technology

2013-05-03

2013 Report Documentation Page Form ApprovedOMB No. 0704-0188 Public reporting burden for the collection of information is estimated to average 1 hour...matrices of the form A = D+USV H, where D is sparse and USV H has low rank but may be dense. Matrices of this form arise in many practical applications...methods numerical partial di erential equation solvers, and preconditioned iterative methods. If A has this form , our algorithm enables a communication

Efficient Iterative Methods Applied to the Solution of Transonic Flows

NASA Astrophysics Data System (ADS)

Wissink, Andrew M.; Lyrintzis, Anastasios S.; Chronopoulos, Anthony T.

1996-02-01

We investigate the use of an inexact Newton's method to solve the potential equations in the transonic regime. As a test case, we solve the two-dimensional steady transonic small disturbance equation. Approximate factorization/ADI techniques have traditionally been employed for implicit solutions of this nonlinear equation. Instead, we apply Newton's method using an exact analytical determination of the Jacobian with preconditioned conjugate gradient-like iterative solvers for solution of the linear systems in each Newton iteration. Two iterative solvers are tested; a block s-step version of the classical Orthomin(k) algorithm called orthogonal s-step Orthomin (OSOmin) and the well-known GMRES method. The preconditioner is a vectorizable and parallelizable version of incomplete LU (ILU) factorization. Efficiency of the Newton-Iterative method on vector and parallel computer architectures is the main issue addressed. In vectorized tests on a single processor of the Cray C-90, the performance of Newton-OSOmin is superior to Newton-GMRES and a more traditional monotone AF/ADI method (MAF) for a variety of transonic Mach numbers and mesh sizes. Newton-GMRES is superior to MAF for some cases. The parallel performance of the Newton method is also found to be very good on multiple processors of the Cray C-90 and on the massively parallel thinking machine CM-5, where very fast execution rates (up to 9 Gflops) are found for large problems.

Generalized conjugate-gradient methods for the Navier-Stokes equations

NASA Technical Reports Server (NTRS)

Ajmani, Kumud; Ng, Wing-Fai; Liou, Meng-Sing

1991-01-01

A generalized conjugate-gradient method is used to solve the two-dimensional, compressible Navier-Stokes equations of fluid flow. The equations are discretized with an implicit, upwind finite-volume formulation. Preconditioning techniques are incorporated into the new solver to accelerate convergence of the overall iterative method. The superiority of the new solver is demonstrated by comparisons with a conventional line Gauss-Siedel Relaxation solver. Computational test results for transonic flow (trailing edge flow in a transonic turbine cascade) and hypersonic flow (M = 6.0 shock-on-shock phenoena on a cylindrical leading edge) are presented. When applied to the transonic cascade case, the new solver is 4.4 times faster in terms of number of iterations and 3.1 times faster in terms of CPU time than the Relaxation solver. For the hypersonic shock case, the new solver is 3.0 times faster in terms of number of iterations and 2.2 times faster in terms of CPU time than the Relaxation solver.

PRIM: An Efficient Preconditioning Iterative Reweighted Least Squares Method for Parallel Brain MRI Reconstruction.

PubMed

Xu, Zheng; Wang, Sheng; Li, Yeqing; Zhu, Feiyun; Huang, Junzhou

2018-02-08

The most recent history of parallel Magnetic Resonance Imaging (pMRI) has in large part been devoted to finding ways to reduce acquisition time. While joint total variation (JTV) regularized model has been demonstrated as a powerful tool in increasing sampling speed for pMRI, however, the major bottleneck is the inefficiency of the optimization method. While all present state-of-the-art optimizations for the JTV model could only reach a sublinear convergence rate, in this paper, we squeeze the performance by proposing a linear-convergent optimization method for the JTV model. The proposed method is based on the Iterative Reweighted Least Squares algorithm. Due to the complexity of the tangled JTV objective, we design a novel preconditioner to further accelerate the proposed method. Extensive experiments demonstrate the superior performance of the proposed algorithm for pMRI regarding both accuracy and efficiency compared with state-of-the-art methods.

A note on the preconditioner Pm=(I+Sm)

NASA Astrophysics Data System (ADS)

Kohno, Toshiyuki; Niki, Hiroshi

2009-03-01

Kotakemori et al. [H. Kotakemori, K. Harada, M. Morimoto, H. Niki, A comparison theorem for the iterative method with the preconditioner (I+Smax), Journal of Computational and Applied Mathematics 145 (2002) 373-378] have reported that the convergence rate of the iterative method with a preconditioner Pm=(I+Sm) was superior to one of the modified Gauss-Seidel method under the condition. These authors derived a theorem comparing the Gauss-Seidel method with the proposed method. However, through application of a counter example, Wen Li [Wen Li, A note on the preconditioned GaussSeidel (GS) method for linear systems, Journal of Computational and Applied Mathematics 182 (2005) 81-91] pointed out that there exists a special matrix that does not satisfy this comparison theorem. In this note, we analyze the reason why such a to counter example may be produced, and propose a preconditioner to overcome this problem.

Efficient iterative method for solving the Dirac-Kohn-Sham density functional theory

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

Lin, Lin; Shao, Sihong; E, Weinan

2012-11-06

We present for the first time an efficient iterative method to directly solve the four-component Dirac-Kohn-Sham (DKS) density functional theory. Due to the existence of the negative energy continuum in the DKS operator, the existing iterative techniques for solving the Kohn-Sham systems cannot be efficiently applied to solve the DKS systems. The key component of our method is a novel filtering step (F) which acts as a preconditioner in the framework of the locally optimal block preconditioned conjugate gradient (LOBPCG) method. The resulting method, dubbed the LOBPCG-F method, is able to compute the desired eigenvalues and eigenvectors in the positive energy band without computing any state in the negative energy band. The LOBPCG-F method introduces mild extra cost compared to the standard LOBPCG method and can be easily implemented. We demonstrate our method in the pseudopotential framework with a planewave basis set which naturally satisfies the kinetic balance prescription. Numerical results for Ptmore » $$_{2}$$, Au$$_{2}$$, TlF, and Bi$$_{2}$$Se$$_{3}$$ indicate that the LOBPCG-F method is a robust and efficient method for investigating the relativistic effect in systems containing heavy elements.« less

Direct reconstruction of cardiac PET kinetic parametric images using a preconditioned conjugate gradient approach.

PubMed

Rakvongthai, Yothin; Ouyang, Jinsong; Guerin, Bastien; Li, Quanzheng; Alpert, Nathaniel M; El Fakhri, Georges

2013-10-01

Our research goal is to develop an algorithm to reconstruct cardiac positron emission tomography (PET) kinetic parametric images directly from sinograms and compare its performance with the conventional indirect approach. Time activity curves of a NCAT phantom were computed according to a one-tissue compartmental kinetic model with realistic kinetic parameters. The sinograms at each time frame were simulated using the activity distribution for the time frame. The authors reconstructed the parametric images directly from the sinograms by optimizing a cost function, which included the Poisson log-likelihood and a spatial regularization terms, using the preconditioned conjugate gradient (PCG) algorithm with the proposed preconditioner. The proposed preconditioner is a diagonal matrix whose diagonal entries are the ratio of the parameter and the sensitivity of the radioactivity associated with parameter. The authors compared the reconstructed parametric images using the direct approach with those reconstructed using the conventional indirect approach. At the same bias, the direct approach yielded significant relative reduction in standard deviation by 12%-29% and 32%-70% for 50 × 10(6) and 10 × 10(6) detected coincidences counts, respectively. Also, the PCG method effectively reached a constant value after only 10 iterations (with numerical convergence achieved after 40-50 iterations), while more than 500 iterations were needed for CG. The authors have developed a novel approach based on the PCG algorithm to directly reconstruct cardiac PET parametric images from sinograms, and yield better estimation of kinetic parameters than the conventional indirect approach, i.e., curve fitting of reconstructed images. The PCG method increases the convergence rate of reconstruction significantly as compared to the conventional CG method.

Interpreting the Coulomb-field approximation for generalized-Born electrostatics using boundary-integral equation theory.

PubMed

Bardhan, Jaydeep P

2008-10-14

The importance of molecular electrostatic interactions in aqueous solution has motivated extensive research into physical models and numerical methods for their estimation. The computational costs associated with simulations that include many explicit water molecules have driven the development of implicit-solvent models, with generalized-Born (GB) models among the most popular of these. In this paper, we analyze a boundary-integral equation interpretation for the Coulomb-field approximation (CFA), which plays a central role in most GB models. This interpretation offers new insights into the nature of the CFA, which traditionally has been assessed using only a single point charge in the solute. The boundary-integral interpretation of the CFA allows the use of multiple point charges, or even continuous charge distributions, leading naturally to methods that eliminate the interpolation inaccuracies associated with the Still equation. This approach, which we call boundary-integral-based electrostatic estimation by the CFA (BIBEE/CFA), is most accurate when the molecular charge distribution generates a smooth normal displacement field at the solute-solvent boundary, and CFA-based GB methods perform similarly. Conversely, both methods are least accurate for charge distributions that give rise to rapidly varying or highly localized normal displacement fields. Supporting this analysis are comparisons of the reaction-potential matrices calculated using GB methods and boundary-element-method (BEM) simulations. An approximation similar to BIBEE/CFA exhibits complementary behavior, with superior accuracy for charge distributions that generate rapidly varying normal fields and poorer accuracy for distributions that produce smooth fields. This approximation, BIBEE by preconditioning (BIBEE/P), essentially generates initial guesses for preconditioned Krylov-subspace iterative BEMs. Thus, iterative refinement of the BIBEE/P results recovers the BEM solution; excellent agreement is obtained in only a few iterations. The boundary-integral-equation framework may also provide a means to derive rigorous results explaining how the empirical correction terms in many modern GB models significantly improve accuracy despite their simple analytical forms.

Layer-oriented multigrid wavefront reconstruction algorithms for multi-conjugate adaptive optics

NASA Astrophysics Data System (ADS)

Gilles, Luc; Ellerbroek, Brent L.; Vogel, Curtis R.

2003-02-01

Multi-conjugate adaptive optics (MCAO) systems with 104-105 degrees of freedom have been proposed for future giant telescopes. Using standard matrix methods to compute, optimize, and implement wavefront control algorithms for these systems is impractical, since the number of calculations required to compute and apply the reconstruction matrix scales respectively with the cube and the square of the number of AO degrees of freedom. In this paper, we develop an iterative sparse matrix implementation of minimum variance wavefront reconstruction for telescope diameters up to 32m with more than 104 actuators. The basic approach is the preconditioned conjugate gradient method, using a multigrid preconditioner incorporating a layer-oriented (block) symmetric Gauss-Seidel iterative smoothing operator. We present open-loop numerical simulation results to illustrate algorithm convergence.

Efficient iterative methods applied to the solution of transonic flows

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

Wissink, A.M.; Lyrintzis, A.S.; Chronopoulos, A.T.

1996-02-01

We investigate the use of an inexact Newton`s method to solve the potential equations in the transonic regime. As a test case, we solve the two-dimensional steady transonic small disturbance equation. Approximate factorization/ADI techniques have traditionally been employed for implicit solutions of this nonlinear equation. Instead, we apply Newton`s method using an exact analytical determination of the Jacobian with preconditioned conjugate gradient-like iterative solvers for solution of the linear systems in each Newton iteration. Two iterative solvers are tested; a block s-step version of the classical Orthomin(k) algorithm called orthogonal s-step Orthomin (OSOmin) and the well-known GIVIRES method. The preconditionermore » is a vectorizable and parallelizable version of incomplete LU (ILU) factorization. Efficiency of the Newton-Iterative method on vector and parallel computer architectures is the main issue addressed. In vectorized tests on a single processor of the Cray C-90, the performance of Newton-OSOmin is superior to Newton-GMRES and a more traditional monotone AF/ADI method (MAF) for a variety of transonic Mach numbers and mesh sizes. Newton- GIVIRES is superior to MAF for some cases. The parallel performance of the Newton method is also found to be very good on multiple processors of the Cray C-90 and on the massively parallel thinking machine CM-5, where very fast execution rates (up to 9 Gflops) are found for large problems. 38 refs., 14 figs., 7 tabs.« less

An approximate block Newton method for coupled iterations of nonlinear solvers: Theory and conjugate heat transfer applications

NASA Astrophysics Data System (ADS)

Yeckel, Andrew; Lun, Lisa; Derby, Jeffrey J.

2009-12-01

A new, approximate block Newton (ABN) method is derived and tested for the coupled solution of nonlinear models, each of which is treated as a modular, black box. Such an approach is motivated by a desire to maintain software flexibility without sacrificing solution efficiency or robustness. Though block Newton methods of similar type have been proposed and studied, we present a unique derivation and use it to sort out some of the more confusing points in the literature. In particular, we show that our ABN method behaves like a Newton iteration preconditioned by an inexact Newton solver derived from subproblem Jacobians. The method is demonstrated on several conjugate heat transfer problems modeled after melt crystal growth processes. These problems are represented by partitioned spatial regions, each modeled by independent heat transfer codes and linked by temperature and flux matching conditions at the boundaries common to the partitions. Whereas a typical block Gauss-Seidel iteration fails about half the time for the model problem, quadratic convergence is achieved by the ABN method under all conditions studied here. Additional performance advantages over existing methods are demonstrated and discussed.

D4Z - a new renumbering for iterative solution of ground-water flow and solute- transport equations

USGS Publications Warehouse

Kipp, K.L.; Russell, T.F.; Otto, J.S.

1992-01-01

D4 zig-zag (D4Z) is a new renumbering scheme for producing a reduced matrix to be solved by an incomplete LU preconditioned, restarted conjugate-gradient iterative solver. By renumbering alternate diagonals in a zig-zag fashion, a very low sensitivity of convergence rate to renumbering direction is obtained. For two demonstration problems involving groundwater flow and solute transport, iteration counts are related to condition numbers and spectra of the reduced matrices.

A geometric multigrid preconditioning strategy for DPG system matrices

DOE PAGES

Roberts, Nathan V.; Chan, Jesse

2017-08-23

Here, the discontinuous Petrov–Galerkin (DPG) methodology of Demkowicz and Gopalakrishnan (2010, 2011) guarantees the optimality of the solution in an energy norm, and provides several features facilitating adaptive schemes. A key question that has not yet been answered in general – though there are some results for Poisson, e.g.– is how best to precondition the DPG system matrix, so that iterative solvers may be used to allow solution of large-scale problems.

Higher Order Time Integration Schemes for the Unsteady Navier-Stokes Equations on Unstructured Meshes

NASA Technical Reports Server (NTRS)

Jothiprasad, Giridhar; Mavriplis, Dimitri J.; Caughey, David A.; Bushnell, Dennis M. (Technical Monitor)

2002-01-01

The efficiency gains obtained using higher-order implicit Runge-Kutta schemes as compared with the second-order accurate backward difference schemes for the unsteady Navier-Stokes equations are investigated. Three different algorithms for solving the nonlinear system of equations arising at each timestep are presented. The first algorithm (NMG) is a pseudo-time-stepping scheme which employs a non-linear full approximation storage (FAS) agglomeration multigrid method to accelerate convergence. The other two algorithms are based on Inexact Newton's methods. The linear system arising at each Newton step is solved using iterative/Krylov techniques and left preconditioning is used to accelerate convergence of the linear solvers. One of the methods (LMG) uses Richardson's iterative scheme for solving the linear system at each Newton step while the other (PGMRES) uses the Generalized Minimal Residual method. Results demonstrating the relative superiority of these Newton's methods based schemes are presented. Efficiency gains as high as 10 are obtained by combining the higher-order time integration schemes with the more efficient nonlinear solvers.

GPU computing with Kaczmarz’s and other iterative algorithms for linear systems

PubMed Central

Elble, Joseph M.; Sahinidis, Nikolaos V.; Vouzis, Panagiotis

2009-01-01

The graphics processing unit (GPU) is used to solve large linear systems derived from partial differential equations. The differential equations studied are strongly convection-dominated, of various sizes, and common to many fields, including computational fluid dynamics, heat transfer, and structural mechanics. The paper presents comparisons between GPU and CPU implementations of several well-known iterative methods, including Kaczmarz’s, Cimmino’s, component averaging, conjugate gradient normal residual (CGNR), symmetric successive overrelaxation-preconditioned conjugate gradient, and conjugate-gradient-accelerated component-averaged row projections (CARP-CG). Computations are preformed with dense as well as general banded systems. The results demonstrate that our GPU implementation outperforms CPU implementations of these algorithms, as well as previously studied parallel implementations on Linux clusters and shared memory systems. While the CGNR method had begun to fall out of favor for solving such problems, for the problems studied in this paper, the CGNR method implemented on the GPU performed better than the other methods, including a cluster implementation of the CARP-CG method. PMID:20526446

Efficient preconditioning of the electronic structure problem in large scale ab initio molecular dynamics simulations

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

Schiffmann, Florian; VandeVondele, Joost, E-mail: Joost.VandeVondele@mat.ethz.ch

2015-06-28

We present an improved preconditioning scheme for electronic structure calculations based on the orbital transformation method. First, a preconditioner is developed which includes information from the full Kohn-Sham matrix but avoids computationally demanding diagonalisation steps in its construction. This reduces the computational cost of its construction, eliminating a bottleneck in large scale simulations, while maintaining rapid convergence. In addition, a modified form of Hotelling’s iterative inversion is introduced to replace the exact inversion of the preconditioner matrix. This method is highly effective during molecular dynamics (MD), as the solution obtained in earlier MD steps is a suitable initial guess. Filteringmore » small elements during sparse matrix multiplication leads to linear scaling inversion, while retaining robustness, already for relatively small systems. For system sizes ranging from a few hundred to a few thousand atoms, which are typical for many practical applications, the improvements to the algorithm lead to a 2-5 fold speedup per MD step.« less

Complex wet-environments in electronic-structure calculations

NASA Astrophysics Data System (ADS)

Fisicaro, Giuseppe; Genovese, Luigi; Andreussi, Oliviero; Marzari, Nicola; Goedecker, Stefan

The computational study of chemical reactions in complex, wet environments is critical for applications in many fields. It is often essential to study chemical reactions in the presence of an applied electrochemical potentials, including complex electrostatic screening coming from the solvent. In the present work we present a solver to handle both the Generalized Poisson and the Poisson-Boltzmann equation. A preconditioned conjugate gradient (PCG) method has been implemented for the Generalized Poisson and the linear regime of the Poisson-Boltzmann, allowing to solve iteratively the minimization problem with some ten iterations. On the other hand, a self-consistent procedure enables us to solve the Poisson-Boltzmann problem. The algorithms take advantage of a preconditioning procedure based on the BigDFT Poisson solver for the standard Poisson equation. They exhibit very high accuracy and parallel efficiency, and allow different boundary conditions, including surfaces. The solver has been integrated into the BigDFT and Quantum-ESPRESSO electronic-structure packages and it will be released as a independent program, suitable for integration in other codes. We present test calculations for large proteins to demonstrate efficiency and performances. This work was done within the PASC and NCCR MARVEL projects. Computer resources were provided by the Swiss National Supercomputing Centre (CSCS) under Project ID s499. LG acknowledges also support from the EXTMOS EU project.

Factorizing the factorization - a spectral-element solver for elliptic equations with linear operation count

NASA Astrophysics Data System (ADS)

Huismann, Immo; Stiller, Jörg; Fröhlich, Jochen

2017-10-01

The paper proposes a novel factorization technique for static condensation of a spectral-element discretization matrix that yields a linear operation count of just 13N multiplications for the residual evaluation, where N is the total number of unknowns. In comparison to previous work it saves a factor larger than 3 and outpaces unfactored variants for all polynomial degrees. Using the new technique as a building block for a preconditioned conjugate gradient method yields linear scaling of the runtime with N which is demonstrated for polynomial degrees from 2 to 32. This makes the spectral-element method cost effective even for low polynomial degrees. Moreover, the dependence of the iterative solution on the element aspect ratio is addressed, showing only a slight increase in the number of iterations for aspect ratios up to 128. Hence, the solver is very robust for practical applications.

A 3D finite-difference BiCG iterative solver with the Fourier-Jacobi preconditioner for the anisotropic EIT/EEG forward problem.

PubMed

Turovets, Sergei; Volkov, Vasily; Zherdetsky, Aleksej; Prakonina, Alena; Malony, Allen D

2014-01-01

The Electrical Impedance Tomography (EIT) and electroencephalography (EEG) forward problems in anisotropic inhomogeneous media like the human head belongs to the class of the three-dimensional boundary value problems for elliptic equations with mixed derivatives. We introduce and explore the performance of several new promising numerical techniques, which seem to be more suitable for solving these problems. The proposed numerical schemes combine the fictitious domain approach together with the finite-difference method and the optimally preconditioned Conjugate Gradient- (CG-) type iterative method for treatment of the discrete model. The numerical scheme includes the standard operations of summation and multiplication of sparse matrices and vector, as well as FFT, making it easy to implement and eligible for the effective parallel implementation. Some typical use cases for the EIT/EEG problems are considered demonstrating high efficiency of the proposed numerical technique.

Efficient geostatistical inversion of transient groundwater flow using preconditioned nonlinear conjugate gradients

NASA Astrophysics Data System (ADS)

Klein, Ole; Cirpka, Olaf A.; Bastian, Peter; Ippisch, Olaf

2017-04-01

In the geostatistical inverse problem of subsurface hydrology, continuous hydraulic parameter fields, in most cases hydraulic conductivity, are estimated from measurements of dependent variables, such as hydraulic heads, under the assumption that the parameter fields are autocorrelated random space functions. Upon discretization, the continuous fields become large parameter vectors with O (104 -107) elements. While cokriging-like inversion methods have been shown to be efficient for highly resolved parameter fields when the number of measurements is small, they require the calculation of the sensitivity of each measurement with respect to all parameters, which may become prohibitive with large sets of measured data such as those arising from transient groundwater flow. We present a Preconditioned Conjugate Gradient method for the geostatistical inverse problem, in which a single adjoint equation needs to be solved to obtain the gradient of the objective function. Using the autocovariance matrix of the parameters as preconditioning matrix, expensive multiplications with its inverse can be avoided, and the number of iterations is significantly reduced. We use a randomized spectral decomposition of the posterior covariance matrix of the parameters to perform a linearized uncertainty quantification of the parameter estimate. The feasibility of the method is tested by virtual examples of head observations in steady-state and transient groundwater flow. These synthetic tests demonstrate that transient data can reduce both parameter uncertainty and time spent conducting experiments, while the presented methods are able to handle the resulting large number of measurements.

A fast, preconditioned conjugate gradient Toeplitz solver

NASA Technical Reports Server (NTRS)

Pan, Victor; Schrieber, Robert

1989-01-01

A simple factorization is given of an arbitrary hermitian, positive definite matrix in which the factors are well-conditioned, hermitian, and positive definite. In fact, given knowledge of the extreme eigenvalues of the original matrix A, an optimal improvement can be achieved, making the condition numbers of each of the two factors equal to the square root of the condition number of A. This technique is to applied to the solution of hermitian, positive definite Toeplitz systems. Large linear systems with hermitian, positive definite Toeplitz matrices arise in some signal processing applications. A stable fast algorithm is given for solving these systems that is based on the preconditioned conjugate gradient method. The algorithm exploits Toeplitz structure to reduce the cost of an iteration to O(n log n) by applying the fast Fourier Transform to compute matrix-vector products. Matrix factorization is used as a preconditioner.

Comparison of SIRT and SQS for Regularized Weighted Least Squares Image Reconstruction

PubMed Central

Gregor, Jens; Fessler, Jeffrey A.

2015-01-01

Tomographic image reconstruction is often formulated as a regularized weighted least squares (RWLS) problem optimized by iterative algorithms that are either inherently algebraic or derived from a statistical point of view. This paper compares a modified version of SIRT (Simultaneous Iterative Reconstruction Technique), which is of the former type, with a version of SQS (Separable Quadratic Surrogates), which is of the latter type. We show that the two algorithms minimize the same criterion function using similar forms of preconditioned gradient descent. We present near-optimal relaxation for both based on eigenvalue bounds and include a heuristic extension for use with ordered subsets. We provide empirical evidence that SIRT and SQS converge at the same rate for all intents and purposes. For context, we compare their performance with an implementation of preconditioned conjugate gradient. The illustrative application is X-ray CT of luggage for aviation security. PMID:26478906

Efficient numerical calculation of MHD equilibria with magnetic islands, with particular application to saturated neoclassical tearing modes

NASA Astrophysics Data System (ADS)

Raburn, Daniel Louis

We have developed a preconditioned, globalized Jacobian-free Newton-Krylov (JFNK) solver for calculating equilibria with magnetic islands. The solver has been developed in conjunction with the Princeton Iterative Equilibrium Solver (PIES) and includes two notable enhancements over a traditional JFNK scheme: (1) globalization of the algorithm by a sophisticated backtracking scheme, which optimizes between the Newton and steepest-descent directions; and, (2) adaptive preconditioning, wherein information regarding the system Jacobian is reused between Newton iterations to form a preconditioner for our GMRES-like linear solver. We have developed a formulation for calculating saturated neoclassical tearing modes (NTMs) which accounts for the incomplete loss of a bootstrap current due to gradients of multiple physical quantities. We have applied the coupled PIES-JFNK solver to calculate saturated island widths on several shots from the Tokamak Fusion Test Reactor (TFTR) and have found reasonable agreement with experimental measurement.

Implicit solvers for unstructured meshes

NASA Technical Reports Server (NTRS)

Venkatakrishnan, V.; Mavriplis, Dimitri J.

1991-01-01

Implicit methods for unstructured mesh computations are developed and tested. The approximate system which arises from the Newton-linearization of the nonlinear evolution operator is solved by using the preconditioned generalized minimum residual technique. These different preconditioners are investigated: the incomplete LU factorization (ILU), block diagonal factorization, and the symmetric successive over-relaxation (SSOR). The preconditioners have been optimized to have good vectorization properties. The various methods are compared over a wide range of problems. Ordering of the unknowns, which affects the convergence of these sparse matrix iterative methods, is also investigated. Results are presented for inviscid and turbulent viscous calculations on single and multielement airfoil configurations using globally and adaptively generated meshes.

Solving coupled groundwater flow systems using a Jacobian Free Newton Krylov method

NASA Astrophysics Data System (ADS)

Mehl, S.

2012-12-01

Jacobian Free Newton Kyrlov (JFNK) methods can have several advantages for simulating coupled groundwater flow processes versus conventional methods. Conventional methods are defined here as those based on an iterative coupling (rather than a direct coupling) and/or that use Picard iteration rather than Newton iteration. In an iterative coupling, the systems are solved separately, coupling information is updated and exchanged between the systems, and the systems are re-solved, etc., until convergence is achieved. Trusted simulators, such as Modflow, are based on these conventional methods of coupling and work well in many cases. An advantage of the JFNK method is that it only requires calculation of the residual vector of the system of equations and thus can make use of existing simulators regardless of how the equations are formulated. This opens the possibility of coupling different process models via augmentation of a residual vector by each separate process, which often requires substantially fewer changes to the existing source code than if the processes were directly coupled. However, appropriate perturbation sizes need to be determined for accurate approximations of the Frechet derivative, which is not always straightforward. Furthermore, preconditioning is necessary for reasonable convergence of the linear solution required at each Kyrlov iteration. Existing preconditioners can be used and applied separately to each process which maximizes use of existing code and robust preconditioners. In this work, iteratively coupled parent-child local grid refinement models of groundwater flow and groundwater flow models with nonlinear exchanges to streams are used to demonstrate the utility of the JFNK approach for Modflow models. Use of incomplete Cholesky preconditioners with various levels of fill are examined on a suite of nonlinear and linear models to analyze the effect of the preconditioner. Comparisons of convergence and computer simulation time are made using conventional iteratively coupled methods and those based on Picard iteration to those formulated with JFNK to gain insights on the types of nonlinearities and system features that make one approach advantageous. Results indicate that nonlinearities associated with stream/aquifer exchanges are more problematic than those resulting from unconfined flow.

A new preconditioner update strategy for the solution of sequences of linear systems in structural mechanics: application to saddle point problems in elasticity

NASA Astrophysics Data System (ADS)

Mercier, Sylvain; Gratton, Serge; Tardieu, Nicolas; Vasseur, Xavier

2017-12-01

Many applications in structural mechanics require the numerical solution of sequences of linear systems typically issued from a finite element discretization of the governing equations on fine meshes. The method of Lagrange multipliers is often used to take into account mechanical constraints. The resulting matrices then exhibit a saddle point structure and the iterative solution of such preconditioned linear systems is considered as challenging. A popular strategy is then to combine preconditioning and deflation to yield an efficient method. We propose an alternative that is applicable to the general case and not only to matrices with a saddle point structure. In this approach, we consider to update an existing algebraic or application-based preconditioner, using specific available information exploiting the knowledge of an approximate invariant subspace or of matrix-vector products. The resulting preconditioner has the form of a limited memory quasi-Newton matrix and requires a small number of linearly independent vectors. Numerical experiments performed on three large-scale applications in elasticity highlight the relevance of the new approach. We show that the proposed method outperforms the deflation method when considering sequences of linear systems with varying matrices.

Iterative algorithms for large sparse linear systems on parallel computers

NASA Technical Reports Server (NTRS)

Adams, L. M.

1982-01-01

Algorithms for assembling in parallel the sparse system of linear equations that result from finite difference or finite element discretizations of elliptic partial differential equations, such as those that arise in structural engineering are developed. Parallel linear stationary iterative algorithms and parallel preconditioned conjugate gradient algorithms are developed for solving these systems. In addition, a model for comparing parallel algorithms on array architectures is developed and results of this model for the algorithms are given.

The Mixed Finite Element Multigrid Method for Stokes Equations

PubMed Central

Muzhinji, K.; Shateyi, S.; Motsa, S. S.

2015-01-01

The stable finite element discretization of the Stokes problem produces a symmetric indefinite system of linear algebraic equations. A variety of iterative solvers have been proposed for such systems in an attempt to construct efficient, fast, and robust solution techniques. This paper investigates one of such iterative solvers, the geometric multigrid solver, to find the approximate solution of the indefinite systems. The main ingredient of the multigrid method is the choice of an appropriate smoothing strategy. This study considers the application of different smoothers and compares their effects in the overall performance of the multigrid solver. We study the multigrid method with the following smoothers: distributed Gauss Seidel, inexact Uzawa, preconditioned MINRES, and Braess-Sarazin type smoothers. A comparative study of the smoothers shows that the Braess-Sarazin smoothers enhance good performance of the multigrid method. We study the problem in a two-dimensional domain using stable Hood-Taylor Q 2-Q 1 pair of finite rectangular elements. We also give the main theoretical convergence results. We present the numerical results to demonstrate the efficiency and robustness of the multigrid method and confirm the theoretical results. PMID:25945361

Solution of the within-group multidimensional discrete ordinates transport equations on massively parallel architectures

NASA Astrophysics Data System (ADS)

Zerr, Robert Joseph

2011-12-01

The integral transport matrix method (ITMM) has been used as the kernel of new parallel solution methods for the discrete ordinates approximation of the within-group neutron transport equation. The ITMM abandons the repetitive mesh sweeps of the traditional source iterations (SI) scheme in favor of constructing stored operators that account for the direct coupling factors among all the cells and between the cells and boundary surfaces. The main goals of this work were to develop the algorithms that construct these operators and employ them in the solution process, determine the most suitable way to parallelize the entire procedure, and evaluate the behavior and performance of the developed methods for increasing number of processes. This project compares the effectiveness of the ITMM with the SI scheme parallelized with the Koch-Baker-Alcouffe (KBA) method. The primary parallel solution method involves a decomposition of the domain into smaller spatial sub-domains, each with their own transport matrices, and coupled together via interface boundary angular fluxes. Each sub-domain has its own set of ITMM operators and represents an independent transport problem. Multiple iterative parallel solution methods have investigated, including parallel block Jacobi (PBJ), parallel red/black Gauss-Seidel (PGS), and parallel GMRES (PGMRES). The fastest observed parallel solution method, PGS, was used in a weak scaling comparison with the PARTISN code. Compared to the state-of-the-art SI-KBA with diffusion synthetic acceleration (DSA), this new method without acceleration/preconditioning is not competitive for any problem parameters considered. The best comparisons occur for problems that are difficult for SI DSA, namely highly scattering and optically thick. SI DSA execution time curves are generally steeper than the PGS ones. However, until further testing is performed it cannot be concluded that SI DSA does not outperform the ITMM with PGS even on several thousand or tens of thousands of processors. The PGS method does outperform SI DSA for the periodic heterogeneous layers (PHL) configuration problems. Although this demonstrates a relative strength/weakness between the two methods, the practicality of these problems is much less, further limiting instances where it would be beneficial to select ITMM over SI DSA. The results strongly indicate a need for a robust, stable, and efficient acceleration method (or preconditioner for PGMRES). The spatial multigrid (SMG) method is currently incomplete in that it does not work for all cases considered and does not effectively improve the convergence rate for all values of scattering ratio c or cell dimension h. Nevertheless, it does display the desired trend for highly scattering, optically thin problems. That is, it tends to lower the rate of growth of number of iterations with increasing number of processes, P, while not increasing the number of additional operations per iteration to the extent that the total execution time of the rapidly converging accelerated iterations exceeds that of the slower unaccelerated iterations. A predictive parallel performance model has been developed for the PBJ method. Timing tests were performed such that trend lines could be fitted to the data for the different components and used to estimate the execution times. Applied to the weak scaling results, the model notably underestimates construction time, but combined with a slight overestimation in iterative solution time, the model predicts total execution time very well for large P. It also does a decent job with the strong scaling results, closely predicting the construction time and time per iteration, especially as P increases. Although not shown to be competitive up to 1,024 processing elements with the current state of the art, the parallelized ITMM exhibits promising scaling trends. Ultimately, compared to the KBA method, the parallelized ITMM may be found to be a very attractive option for transport calculations spatially decomposed over several tens of thousands of processes. Acceleration/preconditioning of the parallelized ITMM once developed will improve the convergence rate and improve its competitiveness. (Abstract shortened by UMI.)

Distributed weighted least-squares estimation with fast convergence for large-scale systems.

PubMed

Marelli, Damián Edgardo; Fu, Minyue

2015-01-01

In this paper we study a distributed weighted least-squares estimation problem for a large-scale system consisting of a network of interconnected sub-systems. Each sub-system is concerned with a subset of the unknown parameters and has a measurement linear in the unknown parameters with additive noise. The distributed estimation task is for each sub-system to compute the globally optimal estimate of its own parameters using its own measurement and information shared with the network through neighborhood communication. We first provide a fully distributed iterative algorithm to asymptotically compute the global optimal estimate. The convergence rate of the algorithm will be maximized using a scaling parameter and a preconditioning method. This algorithm works for a general network. For a network without loops, we also provide a different iterative algorithm to compute the global optimal estimate which converges in a finite number of steps. We include numerical experiments to illustrate the performances of the proposed methods.

Distributed weighted least-squares estimation with fast convergence for large-scale systems☆

PubMed Central

Marelli, Damián Edgardo; Fu, Minyue

2015-01-01

In this paper we study a distributed weighted least-squares estimation problem for a large-scale system consisting of a network of interconnected sub-systems. Each sub-system is concerned with a subset of the unknown parameters and has a measurement linear in the unknown parameters with additive noise. The distributed estimation task is for each sub-system to compute the globally optimal estimate of its own parameters using its own measurement and information shared with the network through neighborhood communication. We first provide a fully distributed iterative algorithm to asymptotically compute the global optimal estimate. The convergence rate of the algorithm will be maximized using a scaling parameter and a preconditioning method. This algorithm works for a general network. For a network without loops, we also provide a different iterative algorithm to compute the global optimal estimate which converges in a finite number of steps. We include numerical experiments to illustrate the performances of the proposed methods. PMID:25641976

Preconditioned steepest descent methods for some nonlinear elliptic equations involving p-Laplacian terms

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

Feng, Wenqiang, E-mail: wfeng1@vols.utk.edu; Salgado, Abner J., E-mail: asalgad1@utk.edu; Wang, Cheng, E-mail: cwang1@umassd.edu

We describe and analyze preconditioned steepest descent (PSD) solvers for fourth and sixth-order nonlinear elliptic equations that include p-Laplacian terms on periodic domains in 2 and 3 dimensions. The highest and lowest order terms of the equations are constant-coefficient, positive linear operators, which suggests a natural preconditioning strategy. Such nonlinear elliptic equations often arise from time discretization of parabolic equations that model various biological and physical phenomena, in particular, liquid crystals, thin film epitaxial growth and phase transformations. The analyses of the schemes involve the characterization of the strictly convex energies associated with the equations. We first give a generalmore » framework for PSD in Hilbert spaces. Based on certain reasonable assumptions of the linear pre-conditioner, a geometric convergence rate is shown for the nonlinear PSD iteration. We then apply the general theory to the fourth and sixth-order problems of interest, making use of Sobolev embedding and regularity results to confirm the appropriateness of our pre-conditioners for the regularized p-Lapacian problems. Our results include a sharper theoretical convergence result for p-Laplacian systems compared to what may be found in existing works. We demonstrate rigorously how to apply the theory in the finite dimensional setting using finite difference discretization methods. Numerical simulations for some important physical application problems – including thin film epitaxy with slope selection and the square phase field crystal model – are carried out to verify the efficiency of the scheme.« less

Preconditioned steepest descent methods for some nonlinear elliptic equations involving p-Laplacian terms

NASA Astrophysics Data System (ADS)

Feng, Wenqiang; Salgado, Abner J.; Wang, Cheng; Wise, Steven M.

2017-04-01

We describe and analyze preconditioned steepest descent (PSD) solvers for fourth and sixth-order nonlinear elliptic equations that include p-Laplacian terms on periodic domains in 2 and 3 dimensions. The highest and lowest order terms of the equations are constant-coefficient, positive linear operators, which suggests a natural preconditioning strategy. Such nonlinear elliptic equations often arise from time discretization of parabolic equations that model various biological and physical phenomena, in particular, liquid crystals, thin film epitaxial growth and phase transformations. The analyses of the schemes involve the characterization of the strictly convex energies associated with the equations. We first give a general framework for PSD in Hilbert spaces. Based on certain reasonable assumptions of the linear pre-conditioner, a geometric convergence rate is shown for the nonlinear PSD iteration. We then apply the general theory to the fourth and sixth-order problems of interest, making use of Sobolev embedding and regularity results to confirm the appropriateness of our pre-conditioners for the regularized p-Lapacian problems. Our results include a sharper theoretical convergence result for p-Laplacian systems compared to what may be found in existing works. We demonstrate rigorously how to apply the theory in the finite dimensional setting using finite difference discretization methods. Numerical simulations for some important physical application problems - including thin film epitaxy with slope selection and the square phase field crystal model - are carried out to verify the efficiency of the scheme.

Construction, classification and parametrization of complex Hadamard matrices

NASA Astrophysics Data System (ADS)

Szöllősi, Ferenc

To improve the design of nuclear systems, high-fidelity neutron fluxes are required. Leadership-class machines provide platforms on which very large problems can be solved. Computing such fluxes efficiently requires numerical methods with good convergence properties and algorithms that can scale to hundreds of thousands of cores. Many 3-D deterministic transport codes are decomposable in space and angle only, limiting them to tens of thousands of cores. Most codes rely on methods such as Gauss Seidel for fixed source problems and power iteration for eigenvalue problems, which can be slow to converge for challenging problems like those with highly scattering materials or high dominance ratios. Three methods have been added to the 3-D SN transport code Denovo that are designed to improve convergence and enable the full use of cutting-edge computers. The first is a multigroup Krylov solver that converges more quickly than Gauss Seidel and parallelizes the code in energy such that Denovo can use hundreds of thousand of cores effectively. The second is Rayleigh quotient iteration (RQI), an old method applied in a new context. This eigenvalue solver finds the dominant eigenvalue in a mathematically optimal way and should converge in fewer iterations than power iteration. RQI creates energy-block-dense equations that the new Krylov solver treats efficiently. However, RQI can have convergence problems because it creates poorly conditioned systems. This can be overcome with preconditioning. The third method is a multigrid-in-energy preconditioner. The preconditioner takes advantage of the new energy decomposition because the grids are in energy rather than space or angle. The preconditioner greatly reduces iteration count for many problem types and scales well in energy. It also allows RQI to be successful for problems it could not solve otherwise. The methods added to Denovo accomplish the goals of this work. They converge in fewer iterations than traditional methods and enable the use of hundreds of thousands of cores. Each method can be used individually, with the multigroup Krylov solver and multigrid-in-energy preconditioner being particularly successful on their own. The largest benefit, though, comes from using these methods in concert.

PRIFIRA: General regularization using prior-conditioning for fast radio interferometric imaging†

NASA Astrophysics Data System (ADS)

Naghibzadeh, Shahrzad; van der Veen, Alle-Jan

2018-06-01

Image formation in radio astronomy is a large-scale inverse problem that is inherently ill-posed. We present a general algorithmic framework based on a Bayesian-inspired regularized maximum likelihood formulation of the radio astronomical imaging problem with a focus on diffuse emission recovery from limited noisy correlation data. The algorithm is dubbed PRIor-conditioned Fast Iterative Radio Astronomy (PRIFIRA) and is based on a direct embodiment of the regularization operator into the system by right preconditioning. The resulting system is then solved using an iterative method based on projections onto Krylov subspaces. We motivate the use of a beamformed image (which includes the classical "dirty image") as an efficient prior-conditioner. Iterative reweighting schemes generalize the algorithmic framework and can account for different regularization operators that encourage sparsity of the solution. The performance of the proposed method is evaluated based on simulated one- and two-dimensional array arrangements as well as actual data from the core stations of the Low Frequency Array radio telescope antenna configuration, and compared to state-of-the-art imaging techniques. We show the generality of the proposed method in terms of regularization schemes while maintaining a competitive reconstruction quality with the current reconstruction techniques. Furthermore, we show that exploiting Krylov subspace methods together with the proper noise-based stopping criteria results in a great improvement in imaging efficiency.

An assessment of coupling algorithms for nuclear reactor core physics simulations

DOE PAGES

Hamilton, Steven; Berrill, Mark; Clarno, Kevin; ...

2016-04-01

This paper evaluates the performance of multiphysics coupling algorithms applied to a light water nuclear reactor core simulation. The simulation couples the k-eigenvalue form of the neutron transport equation with heat conduction and subchannel flow equations. We compare Picard iteration (block Gauss–Seidel) to Anderson acceleration and multiple variants of preconditioned Jacobian-free Newton–Krylov (JFNK). The performance of the methods are evaluated over a range of energy group structures and core power levels. A novel physics-based approximation to a Jacobian-vector product has been developed to mitigate the impact of expensive on-line cross section processing steps. Furthermore, numerical simulations demonstrating the efficiency ofmore » JFNK and Anderson acceleration relative to standard Picard iteration are performed on a 3D model of a nuclear fuel assembly. Both criticality (k-eigenvalue) and critical boron search problems are considered.« less

An assessment of coupling algorithms for nuclear reactor core physics simulations

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

Hamilton, Steven; Berrill, Mark; Clarno, Kevin

This paper evaluates the performance of multiphysics coupling algorithms applied to a light water nuclear reactor core simulation. The simulation couples the k-eigenvalue form of the neutron transport equation with heat conduction and subchannel flow equations. We compare Picard iteration (block Gauss–Seidel) to Anderson acceleration and multiple variants of preconditioned Jacobian-free Newton–Krylov (JFNK). The performance of the methods are evaluated over a range of energy group structures and core power levels. A novel physics-based approximation to a Jacobian-vector product has been developed to mitigate the impact of expensive on-line cross section processing steps. Furthermore, numerical simulations demonstrating the efficiency ofmore » JFNK and Anderson acceleration relative to standard Picard iteration are performed on a 3D model of a nuclear fuel assembly. Both criticality (k-eigenvalue) and critical boron search problems are considered.« less

An assessment of coupling algorithms for nuclear reactor core physics simulations

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

Hamilton, Steven, E-mail: hamiltonsp@ornl.gov; Berrill, Mark, E-mail: berrillma@ornl.gov; Clarno, Kevin, E-mail: clarnokt@ornl.gov

This paper evaluates the performance of multiphysics coupling algorithms applied to a light water nuclear reactor core simulation. The simulation couples the k-eigenvalue form of the neutron transport equation with heat conduction and subchannel flow equations. We compare Picard iteration (block Gauss–Seidel) to Anderson acceleration and multiple variants of preconditioned Jacobian-free Newton–Krylov (JFNK). The performance of the methods are evaluated over a range of energy group structures and core power levels. A novel physics-based approximation to a Jacobian-vector product has been developed to mitigate the impact of expensive on-line cross section processing steps. Numerical simulations demonstrating the efficiency of JFNKmore » and Anderson acceleration relative to standard Picard iteration are performed on a 3D model of a nuclear fuel assembly. Both criticality (k-eigenvalue) and critical boron search problems are considered.« less

Acceleration of the direct reconstruction of linear parametric images using nested algorithms.

PubMed

Wang, Guobao; Qi, Jinyi

2010-03-07

Parametric imaging using dynamic positron emission tomography (PET) provides important information for biological research and clinical diagnosis. Indirect and direct methods have been developed for reconstructing linear parametric images from dynamic PET data. Indirect methods are relatively simple and easy to implement because the image reconstruction and kinetic modeling are performed in two separate steps. Direct methods estimate parametric images directly from raw PET data and are statistically more efficient. However, the convergence rate of direct algorithms can be slow due to the coupling between the reconstruction and kinetic modeling. Here we present two fast gradient-type algorithms for direct reconstruction of linear parametric images. The new algorithms decouple the reconstruction and linear parametric modeling at each iteration by employing the principle of optimization transfer. Convergence speed is accelerated by running more sub-iterations of linear parametric estimation because the computation cost of the linear parametric modeling is much less than that of the image reconstruction. Computer simulation studies demonstrated that the new algorithms converge much faster than the traditional expectation maximization (EM) and the preconditioned conjugate gradient algorithms for dynamic PET.

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

Lin, Paul T.; Shadid, John N.; Tsuji, Paul H.

Here, this study explores the performance and scaling of a GMRES Krylov method employed as a smoother for an algebraic multigrid (AMG) preconditioned Newton- Krylov solution approach applied to a fully-implicit variational multiscale (VMS) nite element (FE) resistive magnetohydrodynamics (MHD) formulation. In this context a Newton iteration is used for the nonlinear system and a Krylov (GMRES) method is employed for the linear subsystems. The efficiency of this approach is critically dependent on the scalability and performance of the AMG preconditioner for the linear solutions and the performance of the smoothers play a critical role. Krylov smoothers are considered inmore » an attempt to reduce the time and memory requirements of existing robust smoothers based on additive Schwarz domain decomposition (DD) with incomplete LU factorization solves on each subdomain. Three time dependent resistive MHD test cases are considered to evaluate the method. The results demonstrate that the GMRES smoother can be faster due to a decrease in the preconditioner setup time and a reduction in outer GMRESR solver iterations, and requires less memory (typically 35% less memory for global GMRES smoother) than the DD ILU smoother.« less

Three-dimensional unstructured grid Euler computations using a fully-implicit, upwind method

NASA Technical Reports Server (NTRS)

Whitaker, David L.

1993-01-01

A method has been developed to solve the Euler equations on a three-dimensional unstructured grid composed of tetrahedra. The method uses an upwind flow solver with a linearized, backward-Euler time integration scheme. Each time step results in a sparse linear system of equations which is solved by an iterative, sparse matrix solver. Local-time stepping, switched evolution relaxation (SER), preconditioning and reuse of the Jacobian are employed to accelerate the convergence rate. Implicit boundary conditions were found to be extremely important for fast convergence. Numerical experiments have shown that convergence rates comparable to that of a multigrid, central-difference scheme are achievable on the same mesh. Results are presented for several grids about an ONERA M6 wing.

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.

Efficient Parallel Formulations of Hierarchical Methods and Their Applications

NASA Astrophysics Data System (ADS)

Grama, Ananth Y.

1996-01-01

Hierarchical methods such as the Fast Multipole Method (FMM) and Barnes-Hut (BH) are used for rapid evaluation of potential (gravitational, electrostatic) fields in particle systems. They are also used for solving integral equations using boundary element methods. The linear systems arising from these methods are dense and are solved iteratively. Hierarchical methods reduce the complexity of the core matrix-vector product from O(n^2) to O(n log n) and the memory requirement from O(n^2) to O(n). We have developed highly scalable parallel formulations of a hybrid FMM/BH method that are capable of handling arbitrarily irregular distributions. We apply these formulations to astrophysical simulations of Plummer and Gaussian galaxies. We have used our parallel formulations to solve the integral form of the Laplace equation. We show that our parallel hierarchical mat-vecs yield high efficiency and overall performance even on relatively small problems. A problem containing approximately 200K nodes takes under a second to compute on 256 processors and yet yields over 85% efficiency. The efficiency and raw performance is expected to increase for bigger problems. For the 200K node problem, our code delivers about 5 GFLOPS of performance on a 256 processor T3D. This is impressive considering the fact that the problem has floating point divides and roots, and very little locality resulting in poor cache performance. A dense matrix-vector product of the same dimensions would require about 0.5 TeraBytes of memory and about 770 TeraFLOPS of computing speed. Clearly, if the loss in accuracy resulting from the use of hierarchical methods is acceptable, our code yields significant savings in time and memory. We also study the convergence of a GMRES solver built around this mat-vec. We accelerate the convergence of the solver using three preconditioning techniques: diagonal scaling, block-diagonal preconditioning, and inner-outer preconditioning. We study the performance and parallel efficiency of these preconditioned solvers. Using this solver, we solve dense linear systems with hundreds of thousands of unknowns. Solving a 105K unknown problem takes about 10 minutes on a 64 processor T3D. Until very recently, boundary element problems of this magnitude could not even be generated, let alone solved.

[Theory, method and application of method R on estimation of (co)variance components].

PubMed

Liu, Wen-Zhong

2004-07-01

Theory, method and application of Method R on estimation of (co)variance components were reviewed in order to make the method be reasonably used. Estimation requires R values,which are regressions of predicted random effects that are calculated using complete dataset on predicted random effects that are calculated using random subsets of the same data. By using multivariate iteration algorithm based on a transformation matrix,and combining with the preconditioned conjugate gradient to solve the mixed model equations, the computation efficiency of Method R is much improved. Method R is computationally inexpensive,and the sampling errors and approximate credible intervals of estimates can be obtained. Disadvantages of Method R include a larger sampling variance than other methods for the same data,and biased estimates in small datasets. As an alternative method, Method R can be used in larger datasets. It is necessary to study its theoretical properties and broaden its application range further.

Large scale Brownian dynamics of confined suspensions of rigid particles

NASA Astrophysics Data System (ADS)

Sprinkle, Brennan; Balboa Usabiaga, Florencio; Patankar, Neelesh A.; Donev, Aleksandar

2017-12-01

We introduce methods for large-scale Brownian Dynamics (BD) simulation of many rigid particles of arbitrary shape suspended in a fluctuating fluid. Our method adds Brownian motion to the rigid multiblob method [F. Balboa Usabiaga et al., Commun. Appl. Math. Comput. Sci. 11(2), 217-296 (2016)] at a cost comparable to the cost of deterministic simulations. We demonstrate that we can efficiently generate deterministic and random displacements for many particles using preconditioned Krylov iterative methods, if kernel methods to efficiently compute the action of the Rotne-Prager-Yamakawa (RPY) mobility matrix and its "square" root are available for the given boundary conditions. These kernel operations can be computed with near linear scaling for periodic domains using the positively split Ewald method. Here we study particles partially confined by gravity above a no-slip bottom wall using a graphical processing unit implementation of the mobility matrix-vector product, combined with a preconditioned Lanczos iteration for generating Brownian displacements. We address a major challenge in large-scale BD simulations, capturing the stochastic drift term that arises because of the configuration-dependent mobility. Unlike the widely used Fixman midpoint scheme, our methods utilize random finite differences and do not require the solution of resistance problems or the computation of the action of the inverse square root of the RPY mobility matrix. We construct two temporal schemes which are viable for large-scale simulations, an Euler-Maruyama traction scheme and a trapezoidal slip scheme, which minimize the number of mobility problems to be solved per time step while capturing the required stochastic drift terms. We validate and compare these schemes numerically by modeling suspensions of boomerang-shaped particles sedimented near a bottom wall. Using the trapezoidal scheme, we investigate the steady-state active motion in dense suspensions of confined microrollers, whose height above the wall is set by a combination of thermal noise and active flows. We find the existence of two populations of active particles, slower ones closer to the bottom and faster ones above them, and demonstrate that our method provides quantitative accuracy even with relatively coarse resolutions of the particle geometry.

Truncated Conjugate Gradient: An Optimal Strategy for the Analytical Evaluation of the Many-Body Polarization Energy and Forces in Molecular Simulations.

PubMed

Aviat, Félix; Levitt, Antoine; Stamm, Benjamin; Maday, Yvon; Ren, Pengyu; Ponder, Jay W; Lagardère, Louis; Piquemal, Jean-Philip

2017-01-10

We introduce a new class of methods, denoted as Truncated Conjugate Gradient(TCG), to solve the many-body polarization energy and its associated forces in molecular simulations (i.e. molecular dynamics (MD) and Monte Carlo). The method consists in a fixed number of Conjugate Gradient (CG) iterations. TCG approaches provide a scalable solution to the polarization problem at a user-chosen cost and a corresponding optimal accuracy. The optimality of the CG-method guarantees that the number of the required matrix-vector products are reduced to a minimum compared to other iterative methods. This family of methods is non-empirical, fully adaptive, and provides analytical gradients, avoiding therefore any energy drift in MD as compared to popular iterative solvers. Besides speed, one great advantage of this class of approximate methods is that their accuracy is systematically improvable. Indeed, as the CG-method is a Krylov subspace method, the associated error is monotonically reduced at each iteration. On top of that, two improvements can be proposed at virtually no cost: (i) the use of preconditioners can be employed, which leads to the Truncated Preconditioned Conjugate Gradient (TPCG); (ii) since the residual of the final step of the CG-method is available, one additional Picard fixed point iteration ("peek"), equivalent to one step of Jacobi Over Relaxation (JOR) with relaxation parameter ω, can be made at almost no cost. This method is denoted by TCG-n(ω). Black-box adaptive methods to find good choices of ω are provided and discussed. Results show that TPCG-3(ω) is converged to high accuracy (a few kcal/mol) for various types of systems including proteins and highly charged systems at the fixed cost of four matrix-vector products: three CG iterations plus the initial CG descent direction. Alternatively, T(P)CG-2(ω) provides robust results at a reduced cost (three matrix-vector products) and offers new perspectives for long polarizable MD as a production algorithm. The T(P)CG-1(ω) level provides less accurate solutions for inhomogeneous systems, but its applicability to well-conditioned problems such as water is remarkable, with only two matrix-vector product evaluations.

Truncated Conjugate Gradient: An Optimal Strategy for the Analytical Evaluation of the Many-Body Polarization Energy and Forces in Molecular Simulations

PubMed Central

2016-01-01

We introduce a new class of methods, denoted as Truncated Conjugate Gradient(TCG), to solve the many-body polarization energy and its associated forces in molecular simulations (i.e. molecular dynamics (MD) and Monte Carlo). The method consists in a fixed number of Conjugate Gradient (CG) iterations. TCG approaches provide a scalable solution to the polarization problem at a user-chosen cost and a corresponding optimal accuracy. The optimality of the CG-method guarantees that the number of the required matrix-vector products are reduced to a minimum compared to other iterative methods. This family of methods is non-empirical, fully adaptive, and provides analytical gradients, avoiding therefore any energy drift in MD as compared to popular iterative solvers. Besides speed, one great advantage of this class of approximate methods is that their accuracy is systematically improvable. Indeed, as the CG-method is a Krylov subspace method, the associated error is monotonically reduced at each iteration. On top of that, two improvements can be proposed at virtually no cost: (i) the use of preconditioners can be employed, which leads to the Truncated Preconditioned Conjugate Gradient (TPCG); (ii) since the residual of the final step of the CG-method is available, one additional Picard fixed point iteration (“peek”), equivalent to one step of Jacobi Over Relaxation (JOR) with relaxation parameter ω, can be made at almost no cost. This method is denoted by TCG-n(ω). Black-box adaptive methods to find good choices of ω are provided and discussed. Results show that TPCG-3(ω) is converged to high accuracy (a few kcal/mol) for various types of systems including proteins and highly charged systems at the fixed cost of four matrix-vector products: three CG iterations plus the initial CG descent direction. Alternatively, T(P)CG-2(ω) provides robust results at a reduced cost (three matrix-vector products) and offers new perspectives for long polarizable MD as a production algorithm. The T(P)CG-1(ω) level provides less accurate solutions for inhomogeneous systems, but its applicability to well-conditioned problems such as water is remarkable, with only two matrix-vector product evaluations. PMID:28068773

Efficient mixing scheme for self-consistent all-electron charge density

NASA Astrophysics Data System (ADS)

Shishidou, Tatsuya; Weinert, Michael

2015-03-01

In standard ab initio density-functional theory calculations, the charge density ρ is gradually updated using the ``input'' and ``output'' densities of the current and previous iteration steps. To accelerate the convergence, Pulay mixing has been widely used with great success. It expresses an ``optimal'' input density ρopt and its ``residual'' Ropt by a linear combination of the densities of the iteration sequences. In large-scale metallic systems, however, the long range nature of Coulomb interaction often causes the ``charge sloshing'' phenomenon and significantly impacts the convergence. Two treatments, represented in reciprocal space, are known to suppress the sloshing: (i) the inverse Kerker metric for Pulay optimization and (ii) Kerker-type preconditioning in mixing Ropt. In all-electron methods, where the charge density does not have a converging Fourier representation, treatments equivalent or similar to (i) and (ii) have not been described so far. In this work, we show that, by going through the calculation of Hartree potential, one can accomplish the procedures (i) and (ii) without entering the reciprocal space. Test calculations are done with a FLAPW method.

WARP3D-Release 10.8: Dynamic Nonlinear Analysis of Solids using a Preconditioned Conjugate Gradient Software Architecture

NASA Technical Reports Server (NTRS)

Koppenhoefer, Kyle C.; Gullerud, Arne S.; Ruggieri, Claudio; Dodds, Robert H., Jr.; Healy, Brian E.

1998-01-01

This report describes theoretical background material and commands necessary to use the WARP3D finite element code. WARP3D is under continuing development as a research code for the solution of very large-scale, 3-D solid models subjected to static and dynamic loads. Specific features in the code oriented toward the investigation of ductile fracture in metals include a robust finite strain formulation, a general J-integral computation facility (with inertia, face loading), an element extinction facility to model crack growth, nonlinear material models including viscoplastic effects, and the Gurson-Tver-gaard dilatant plasticity model for void growth. The nonlinear, dynamic equilibrium equations are solved using an incremental-iterative, implicit formulation with full Newton iterations to eliminate residual nodal forces. The history integration of the nonlinear equations of motion is accomplished with Newmarks Beta method. A central feature of WARP3D involves the use of a linear-preconditioned conjugate gradient (LPCG) solver implemented in an element-by-element format to replace a conventional direct linear equation solver. This software architecture dramatically reduces both the memory requirements and CPU time for very large, nonlinear solid models since formation of the assembled (dynamic) stiffness matrix is avoided. Analyses thus exhibit the numerical stability for large time (load) steps provided by the implicit formulation coupled with the low memory requirements characteristic of an explicit code. In addition to the much lower memory requirements of the LPCG solver, the CPU time required for solution of the linear equations during each Newton iteration is generally one-half or less of the CPU time required for a traditional direct solver. All other computational aspects of the code (element stiffnesses, element strains, stress updating, element internal forces) are implemented in the element-by- element, blocked architecture. This greatly improves vectorization of the code on uni-processor hardware and enables straightforward parallel-vector processing of element blocks on multi-processor hardware.

Accelerated fast iterative shrinkage thresholding algorithms for sparsity-regularized cone-beam CT image reconstruction

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

Xu, Qiaofeng; Sawatzky, Alex; Anastasio, Mark A., E-mail: anastasio@wustl.edu

Purpose: The development of iterative image reconstruction algorithms for cone-beam computed tomography (CBCT) remains an active and important research area. Even with hardware acceleration, the overwhelming majority of the available 3D iterative algorithms that implement nonsmooth regularizers remain computationally burdensome and have not been translated for routine use in time-sensitive applications such as image-guided radiation therapy (IGRT). In this work, two variants of the fast iterative shrinkage thresholding algorithm (FISTA) are proposed and investigated for accelerated iterative image reconstruction in CBCT. Methods: Algorithm acceleration was achieved by replacing the original gradient-descent step in the FISTAs by a subproblem that ismore » solved by use of the ordered subset simultaneous algebraic reconstruction technique (OS-SART). Due to the preconditioning matrix adopted in the OS-SART method, two new weighted proximal problems were introduced and corresponding fast gradient projection-type algorithms were developed for solving them. We also provided efficient numerical implementations of the proposed algorithms that exploit the massive data parallelism of multiple graphics processing units. Results: The improved rates of convergence of the proposed algorithms were quantified in computer-simulation studies and by use of clinical projection data corresponding to an IGRT study. The accelerated FISTAs were shown to possess dramatically improved convergence properties as compared to the standard FISTAs. For example, the number of iterations to achieve a specified reconstruction error could be reduced by an order of magnitude. Volumetric images reconstructed from clinical data were produced in under 4 min. Conclusions: The FISTA achieves a quadratic convergence rate and can therefore potentially reduce the number of iterations required to produce an image of a specified image quality as compared to first-order methods. We have proposed and investigated accelerated FISTAs for use with two nonsmooth penalty functions that will lead to further reductions in image reconstruction times while preserving image quality. Moreover, with the help of a mixed sparsity-regularization, better preservation of soft-tissue structures can be potentially obtained. The algorithms were systematically evaluated by use of computer-simulated and clinical data sets.« less

Accelerated fast iterative shrinkage thresholding algorithms for sparsity-regularized cone-beam CT image reconstruction

PubMed Central

Xu, Qiaofeng; Yang, Deshan; Tan, Jun; Sawatzky, Alex; Anastasio, Mark A.

2016-01-01

Purpose: The development of iterative image reconstruction algorithms for cone-beam computed tomography (CBCT) remains an active and important research area. Even with hardware acceleration, the overwhelming majority of the available 3D iterative algorithms that implement nonsmooth regularizers remain computationally burdensome and have not been translated for routine use in time-sensitive applications such as image-guided radiation therapy (IGRT). In this work, two variants of the fast iterative shrinkage thresholding algorithm (FISTA) are proposed and investigated for accelerated iterative image reconstruction in CBCT. Methods: Algorithm acceleration was achieved by replacing the original gradient-descent step in the FISTAs by a subproblem that is solved by use of the ordered subset simultaneous algebraic reconstruction technique (OS-SART). Due to the preconditioning matrix adopted in the OS-SART method, two new weighted proximal problems were introduced and corresponding fast gradient projection-type algorithms were developed for solving them. We also provided efficient numerical implementations of the proposed algorithms that exploit the massive data parallelism of multiple graphics processing units. Results: The improved rates of convergence of the proposed algorithms were quantified in computer-simulation studies and by use of clinical projection data corresponding to an IGRT study. The accelerated FISTAs were shown to possess dramatically improved convergence properties as compared to the standard FISTAs. For example, the number of iterations to achieve a specified reconstruction error could be reduced by an order of magnitude. Volumetric images reconstructed from clinical data were produced in under 4 min. Conclusions: The FISTA achieves a quadratic convergence rate and can therefore potentially reduce the number of iterations required to produce an image of a specified image quality as compared to first-order methods. We have proposed and investigated accelerated FISTAs for use with two nonsmooth penalty functions that will lead to further reductions in image reconstruction times while preserving image quality. Moreover, with the help of a mixed sparsity-regularization, better preservation of soft-tissue structures can be potentially obtained. The algorithms were systematically evaluated by use of computer-simulated and clinical data sets. PMID:27036582

ML 3.0 smoothed aggregation user's guide.

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

Sala, Marzio; Hu, Jonathan Joseph; Tuminaro, Raymond Stephen

2004-05-01

ML is a multigrid preconditioning package intended to solve linear systems of equations Az = b where A is a user supplied n x n sparse matrix, b is a user supplied vector of length n and x is a vector of length n to be computed. ML should be used on large sparse linear systems arising from partial differential equation (PDE) discretizations. While technically any linear system can be considered, ML should be used on linear systems that correspond to things that work well with multigrid methods (e.g. elliptic PDEs). ML can be used as a stand-alone package ormore » to generate preconditioners for a traditional iterative solver package (e.g. Krylov methods). We have supplied support for working with the AZTEC 2.1 and AZTECOO iterative package [15]. However, other solvers can be used by supplying a few functions. This document describes one specific algebraic multigrid approach: smoothed aggregation. This approach is used within several specialized multigrid methods: one for the eddy current formulation for Maxwell's equations, and a multilevel and domain decomposition method for symmetric and non-symmetric systems of equations (like elliptic equations, or compressible and incompressible fluid dynamics problems). Other methods exist within ML but are not described in this document. Examples are given illustrating the problem definition and exercising multigrid options.« less

ML 3.1 smoothed aggregation user's guide.

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

Sala, Marzio; Hu, Jonathan Joseph; Tuminaro, Raymond Stephen

2004-10-01

ML is a multigrid preconditioning package intended to solve linear systems of equations Ax = b where A is a user supplied n x n sparse matrix, b is a user supplied vector of length n and x is a vector of length n to be computed. ML should be used on large sparse linear systems arising from partial differential equation (PDE) discretizations. While technically any linear system can be considered, ML should be used on linear systems that correspond to things that work well with multigrid methods (e.g. elliptic PDEs). ML can be used as a stand-alone package ormore » to generate preconditioners for a traditional iterative solver package (e.g. Krylov methods). We have supplied support for working with the Aztec 2.1 and AztecOO iterative package [16]. However, other solvers can be used by supplying a few functions. This document describes one specific algebraic multigrid approach: smoothed aggregation. This approach is used within several specialized multigrid methods: one for the eddy current formulation for Maxwell's equations, and a multilevel and domain decomposition method for symmetric and nonsymmetric systems of equations (like elliptic equations, or compressible and incompressible fluid dynamics problems). Other methods exist within ML but are not described in this document. Examples are given illustrating the problem definition and exercising multigrid options.« less

A Chebyshev Collocation Method for Moving Boundaries, Heat Transfer, and Convection During Directional Solidification

NASA Technical Reports Server (NTRS)

Zhang, Yiqiang; Alexander, J. I. D.; Ouazzani, J.

1994-01-01

Free and moving boundary problems require the simultaneous solution of unknown field variables and the boundaries of the domains on which these variables are defined. There are many technologically important processes that lead to moving boundary problems associated with fluid surfaces and solid-fluid boundaries. These include crystal growth, metal alloy and glass solidification, melting and name propagation. The directional solidification of semi-conductor crystals by the Bridgman-Stockbarger method is a typical example of such a complex process. A numerical model of this growth method must solve the appropriate heat, mass and momentum transfer equations and determine the location of the melt-solid interface. In this work, a Chebyshev pseudospectra collocation method is adapted to the problem of directional solidification. Implementation involves a solution algorithm that combines domain decomposition, finite-difference preconditioned conjugate minimum residual method and a Picard type iterative scheme.

Reliability enhancement of Navier-Stokes codes through convergence acceleration

NASA Technical Reports Server (NTRS)

Merkle, Charles L.; Dulikravich, George S.

1995-01-01

Methods for enhancing the reliability of Navier-Stokes computer codes through improving convergence characteristics are presented. The improving of these characteristics decreases the likelihood of code unreliability and user interventions in a design environment. The problem referred to as a 'stiffness' in the governing equations for propulsion-related flowfields is investigated, particularly in regard to common sources of equation stiffness that lead to convergence degradation of CFD algorithms. Von Neumann stability theory is employed as a tool to study the convergence difficulties involved. Based on the stability results, improved algorithms are devised to ensure efficient convergence in different situations. A number of test cases are considered to confirm a correlation between stability theory and numerical convergence. The examples of turbulent and reacting flow are presented, and a generalized form of the preconditioning matrix is derived to handle these problems, i.e., the problems involving additional differential equations for describing the transport of turbulent kinetic energy, dissipation rate and chemical species. Algorithms for unsteady computations are considered. The extension of the preconditioning techniques and algorithms derived for Navier-Stokes computations to three-dimensional flow problems is discussed. New methods to accelerate the convergence of iterative schemes for the numerical integration of systems of partial differential equtions are developed, with a special emphasis on the acceleration of convergence on highly clustered grids.

Inelastic scattering with Chebyshev polynomials and preconditioned conjugate gradient minimization.

PubMed

Temel, Burcin; Mills, Greg; Metiu, Horia

2008-03-27

We describe and test an implementation, using a basis set of Chebyshev polynomials, of a variational method for solving scattering problems in quantum mechanics. This minimum error method (MEM) determines the wave function Psi by minimizing the least-squares error in the function (H Psi - E Psi), where E is the desired scattering energy. We compare the MEM to an alternative, the Kohn variational principle (KVP), by solving the Secrest-Johnson model of two-dimensional inelastic scattering, which has been studied previously using the KVP and for which other numerical solutions are available. We use a conjugate gradient (CG) method to minimize the error, and by preconditioning the CG search, we are able to greatly reduce the number of iterations necessary; the method is thus faster and more stable than a matrix inversion, as is required in the KVP. Also, we avoid errors due to scattering off of the boundaries, which presents substantial problems for other methods, by matching the wave function in the interaction region to the correct asymptotic states at the specified energy; the use of Chebyshev polynomials allows this boundary condition to be implemented accurately. The use of Chebyshev polynomials allows for a rapid and accurate evaluation of the kinetic energy. This basis set is as efficient as plane waves but does not impose an artificial periodicity on the system. There are problems in surface science and molecular electronics which cannot be solved if periodicity is imposed, and the Chebyshev basis set is a good alternative in such situations.

Improved quality and more attractive work by applying EBM in disability evaluations: a qualitative survey.

PubMed

Hoving, Jan L; Kok, Rob; Ketelaar, Sarah M; Smits, Paul B A; van Dijk, Frank J H; Verbeek, Jos H

2016-02-29

The uptake of evidence in practice by physicians, even if they are trained in the systematic method of evidence-based medicine (EBM), remains difficult to improve. The aim of this study was to explore perceptions and experiences of physicians doing disability evaluations regarding motivators and preconditions for the implementation of EBM in daily practice. This qualitative study was nested in a cluster randomized controlled trial (Trial registration NTR1767; 20-apr-2009) evaluating the effects of training in EBM. The 45 physicians that participated received a comprehensive 6-months training program in EBM of which the last course day included audio-recorded interviews in groups. During these interviews participating physicians discussed perceptions and experiences regarding EBM application in daily practice. In an iterative process we searched for common motivators or preconditions for the implementation of EBM. Three main concepts or themes emerged after analyzing the transcriptions of the discussions: 1) improved quality of physicians' actions, such as clients benefiting from the application of EBM; 2) improved work attractiveness of physicians; and 3) preconditions that have to be met in order to work in an evidence-based manner including professional competence, facilitating material conditions and organizational support and demands. Physicians trained in EBM are motivated to use EBM because they perceive it as a factor improving the quality of their work and making their work more attractive. In addition to personal investments and gains, organizational support should further facilitate the uptake of evidence in practice.

Multi-color incomplete Cholesky conjugate gradient methods for vector computers. Ph.D. Thesis

NASA Technical Reports Server (NTRS)

Poole, E. L.

1986-01-01

In this research, we are concerned with the solution on vector computers of linear systems of equations, Ax = b, where A is a larger, sparse symmetric positive definite matrix. We solve the system using an iterative method, the incomplete Cholesky conjugate gradient method (ICCG). We apply a multi-color strategy to obtain p-color matrices for which a block-oriented ICCG method is implemented on the CYBER 205. (A p-colored matrix is a matrix which can be partitioned into a pXp block matrix where the diagonal blocks are diagonal matrices). This algorithm, which is based on a no-fill strategy, achieves O(N/p) length vector operations in both the decomposition of A and in the forward and back solves necessary at each iteration of the method. We discuss the natural ordering of the unknowns as an ordering that minimizes the number of diagonals in the matrix and define multi-color orderings in terms of disjoint sets of the unknowns. We give necessary and sufficient conditions to determine which multi-color orderings of the unknowns correpond to p-color matrices. A performance model is given which is used both to predict execution time for ICCG methods and also to compare an ICCG method to conjugate gradient without preconditioning or another ICCG method. Results are given from runs on the CYBER 205 at NASA's Langley Research Center for four model problems.

Preconditioned MoM Solutions for Complex Planar Arrays

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

Fasenfest, B J; Jackson, D; Champagne, N

2004-01-23

The numerical analysis of large arrays is a complex problem. There are several techniques currently under development in this area. One such technique is the FAIM (Faster Adaptive Integral Method). This method uses a modification of the standard AIM approach which takes into account the reusability properties of matrices that arise from identical array elements. If the array consists of planar conducting bodies, the array elements are meshed using standard subdomain basis functions, such as the RWG basis. These bases are then projected onto a regular grid of interpolating polynomials. This grid can then be used in a 2D ormore » 3D FFT to accelerate the matrix-vector product used in an iterative solver. The method has been proven to greatly reduce solve time by speeding the matrix-vector product computation. The FAIM approach also reduces fill time and memory requirements, since only the near element interactions need to be calculated exactly. The present work extends FAIM by modifying it to allow for layered material Green's Functions and dielectrics. In addition, a preconditioner is implemented to greatly reduce the number of iterations required for a solution. The general scheme of the FAIM method is reported in; this contribution is limited to presenting new results.« less

Efficient Power Network Analysis with Modeling of Inductive Effects

NASA Astrophysics Data System (ADS)

Zeng, Shan; Yu, Wenjian; Hong, Xianlong; Cheng, Chung-Kuan

In this paper, an efficient method is proposed to accurately analyze large-scale power/ground (P/G) networks, where inductive parasitics are modeled with the partial reluctance. The method is based on frequency-domain circuit analysis and the technique of vector fitting [14], and obtains the time-domain voltage response at given P/G nodes. The frequency-domain circuit equation including partial reluctances is derived, and then solved with the GMRES algorithm with rescaling, preconditioning and recycling techniques. With the merit of sparsified reluctance matrix and iterative solving techniques for the frequency-domain circuit equations, the proposed method is able to handle large-scale P/G networks with complete inductive modeling. Numerical results show that the proposed method is orders of magnitude faster than HSPICE, several times faster than INDUCTWISE [4], and capable of handling the inductive P/G structures with more than 100, 000 wire segments.

Improved Conjugate Gradient Bundle Adjustment of Dunhuang Wall Painting Images

NASA Astrophysics Data System (ADS)

Hu, K.; Huang, X.; You, H.

2017-09-01

Bundle adjustment with additional parameters is identified as a critical step for precise orthoimage generation and 3D reconstruction of Dunhuang wall paintings. Due to the introduction of self-calibration parameters and quasi-planar constraints, the structure of coefficient matrix of the reduced normal equation is banded-bordered, making the solving process of bundle adjustment complex. In this paper, Conjugate Gradient Bundle Adjustment (CGBA) method is deduced by calculus of variations. A preconditioning method based on improved incomplete Cholesky factorization is adopt to reduce the condition number of coefficient matrix, as well as to accelerate the iteration rate of CGBA. Both theoretical analysis and experimental results comparison with conventional method indicate that, the proposed method can effectively conquer the ill-conditioned problem of normal equation and improve the calculation efficiency of bundle adjustment with additional parameters considerably, while maintaining the actual accuracy.

A Well-Tempered Hybrid Method for Solving Challenging Time-Dependent Density Functional Theory (TDDFT) Systems.

PubMed

Kasper, Joseph M; Williams-Young, David B; Vecharynski, Eugene; Yang, Chao; Li, Xiaosong

2018-04-10

The time-dependent Hartree-Fock (TDHF) and time-dependent density functional theory (TDDFT) equations allow one to probe electronic resonances of a system quickly and inexpensively. However, the iterative solution of the eigenvalue problem can be challenging or impossible to converge, using standard methods such as the Davidson algorithm for spectrally dense regions in the interior of the spectrum, as are common in X-ray absorption spectroscopy (XAS). More robust solvers, such as the generalized preconditioned locally harmonic residual (GPLHR) method, can alleviate this problem, but at the expense of higher average computational cost. A hybrid method is proposed which adapts to the problem in order to maximize computational performance while providing the superior convergence of GPLHR. In addition, a modification to the GPLHR algorithm is proposed to adaptively choose the shift parameter to enforce a convergence of states above a predefined energy threshold.

A projected preconditioned conjugate gradient algorithm for computing many extreme eigenpairs of a Hermitian matrix [A projected preconditioned conjugate gradient algorithm for computing a large eigenspace of a Hermitian matrix

DOE PAGES

Vecharynski, Eugene; Yang, Chao; Pask, John E.

2015-02-25

Here, we present an iterative algorithm for computing an invariant subspace associated with the algebraically smallest eigenvalues of a large sparse or structured Hermitian matrix A. We are interested in the case in which the dimension of the invariant subspace is large (e.g., over several hundreds or thousands) even though it may still be small relative to the dimension of A. These problems arise from, for example, density functional theory (DFT) based electronic structure calculations for complex materials. The key feature of our algorithm is that it performs fewer Rayleigh–Ritz calculations compared to existing algorithms such as the locally optimalmore » block preconditioned conjugate gradient or the Davidson algorithm. It is a block algorithm, and hence can take advantage of efficient BLAS3 operations and be implemented with multiple levels of concurrency. We discuss a number of practical issues that must be addressed in order to implement the algorithm efficiently on a high performance computer.« less

Accelerated fast iterative shrinkage thresholding algorithms for sparsity-regularized cone-beam CT image reconstruction.

PubMed

Xu, Qiaofeng; Yang, Deshan; Tan, Jun; Sawatzky, Alex; Anastasio, Mark A

2016-04-01

The development of iterative image reconstruction algorithms for cone-beam computed tomography (CBCT) remains an active and important research area. Even with hardware acceleration, the overwhelming majority of the available 3D iterative algorithms that implement nonsmooth regularizers remain computationally burdensome and have not been translated for routine use in time-sensitive applications such as image-guided radiation therapy (IGRT). In this work, two variants of the fast iterative shrinkage thresholding algorithm (FISTA) are proposed and investigated for accelerated iterative image reconstruction in CBCT. Algorithm acceleration was achieved by replacing the original gradient-descent step in the FISTAs by a subproblem that is solved by use of the ordered subset simultaneous algebraic reconstruction technique (OS-SART). Due to the preconditioning matrix adopted in the OS-SART method, two new weighted proximal problems were introduced and corresponding fast gradient projection-type algorithms were developed for solving them. We also provided efficient numerical implementations of the proposed algorithms that exploit the massive data parallelism of multiple graphics processing units. The improved rates of convergence of the proposed algorithms were quantified in computer-simulation studies and by use of clinical projection data corresponding to an IGRT study. The accelerated FISTAs were shown to possess dramatically improved convergence properties as compared to the standard FISTAs. For example, the number of iterations to achieve a specified reconstruction error could be reduced by an order of magnitude. Volumetric images reconstructed from clinical data were produced in under 4 min. The FISTA achieves a quadratic convergence rate and can therefore potentially reduce the number of iterations required to produce an image of a specified image quality as compared to first-order methods. We have proposed and investigated accelerated FISTAs for use with two nonsmooth penalty functions that will lead to further reductions in image reconstruction times while preserving image quality. Moreover, with the help of a mixed sparsity-regularization, better preservation of soft-tissue structures can be potentially obtained. The algorithms were systematically evaluated by use of computer-simulated and clinical data sets.

Advances in Global Adjoint Tomography - Data Assimilation and Inversion Strategy

NASA Astrophysics Data System (ADS)

Ruan, Y.; Lei, W.; Lefebvre, M. P.; Modrak, R. T.; Smith, J. A.; Bozdag, E.; Tromp, J.

2016-12-01

Seismic tomography provides the most direct way to understand Earth's interior by imaging elastic heterogeneity, anisotropy and anelasticity. Resolving thefine structure of these properties requires accurate simulations of seismic wave propagation in complex 3-D Earth models. On the supercomputer "Titan" at Oak Ridge National Laboratory, we are employing a spectral-element method (Komatitsch & Tromp 1999, 2002) in combination with an adjoint method (Tromp et al., 2005) to accurately calculate theoretical seismograms and Frechet derivatives. Using 253 carefully selected events, Bozdag et al. (2016) iteratively determined a transversely isotropic earth model (GLAD_M15) using 15 preconditioned conjugate-gradient iterations. To obtain higher resolution images of the mantle, we have expanded our database to more than 4,220 Mw5.0-7.0 events occurred between 1995 and 2014. Instead of using the entire database all at once, we choose to draw subsets of about 1,000 events from our database for each iteration to achieve a faster convergence rate with limited computing resources. To provide good coverage of deep structures, we selected approximately 700 deep and intermedia earthquakes and 300 shallow events to start a new iteration. We reinverted the CMT solutions of these events in the latest model, and recalculated synthetic seismograms. Using the synthetics as reference seismograms, we selected time windows that show good agreement with data and make measurements within the windows. From the measurements we further assess the overall quality of each event and station, and exclude bad measurements base upon certain criteria. So far, with very conservative criteria, we have assimilated more than 8.0 million windows from 1,000 earthquakes in three period bands for the new iteration. For subsequent iterations, we will change the period bands and window selecting criteria to include more window. In the inversion, dense array data (e.g., USArray) usually dominate model updates. In order to better handle this issue, we introduced weighting of stations and events based upon their relative distance and showed that the contribution from dense array is better balanced in the Frechet derivatives. We will present a summary of this form of data assimilation and preliminary results of the first few iterations.

On conjugate gradient type methods and polynomial preconditioners for a class of complex non-Hermitian matrices

NASA Technical Reports Server (NTRS)

Freund, Roland

1988-01-01

Conjugate gradient type methods are considered for the solution of large linear systems Ax = b with complex coefficient matrices of the type A = T + i(sigma)I where T is Hermitian and sigma, a real scalar. Three different conjugate gradient type approaches with iterates defined by a minimal residual property, a Galerkin type condition, and an Euclidian error minimization, respectively, are investigated. In particular, numerically stable implementations based on the ideas behind Paige and Saunder's SYMMLQ and MINRES for real symmetric matrices are proposed. Error bounds for all three methods are derived. It is shown how the special shift structure of A can be preserved by using polynomial preconditioning. Results on the optimal choice of the polynomial preconditioner are given. Also, some numerical experiments for matrices arising from finite difference approximations to the complex Helmholtz equation are reported.

Pseudo-compressibility methods for the incompressible flow equations

NASA Technical Reports Server (NTRS)

Turkel, Eli; Arnone, A.

1993-01-01

Preconditioning methods to accelerate convergence to a steady state for the incompressible fluid dynamics equations are considered. The analysis relies on the inviscid equations. The preconditioning consists of a matrix multiplying the time derivatives. Thus the steady state of the preconditioned system is the same as the steady state of the original system. The method is compared to other types of pseudo-compressibility. For finite difference methods preconditioning can change and improve the steady state solutions. An application to viscous flow around a cascade with a non-periodic mesh is presented.

A new extrapolation cascadic multigrid method for three dimensional elliptic boundary value problems

NASA Astrophysics Data System (ADS)

Pan, Kejia; He, Dongdong; Hu, Hongling; Ren, Zhengyong

2017-09-01

In this paper, we develop a new extrapolation cascadic multigrid method, which makes it possible to solve three dimensional elliptic boundary value problems with over 100 million unknowns on a desktop computer in half a minute. First, by combining Richardson extrapolation and quadratic finite element (FE) interpolation for the numerical solutions on two-level of grids (current and previous grids), we provide a quite good initial guess for the iterative solution on the next finer grid, which is a third-order approximation to the FE solution. And the resulting large linear system from the FE discretization is then solved by the Jacobi-preconditioned conjugate gradient (JCG) method with the obtained initial guess. Additionally, instead of performing a fixed number of iterations as used in existing cascadic multigrid methods, a relative residual tolerance is introduced in the JCG solver, which enables us to obtain conveniently the numerical solution with the desired accuracy. Moreover, a simple method based on the midpoint extrapolation formula is proposed to achieve higher-order accuracy on the finest grid cheaply and directly. Test results from four examples including two smooth problems with both constant and variable coefficients, an H3-regular problem as well as an anisotropic problem are reported to show that the proposed method has much better efficiency compared to the classical V-cycle and W-cycle multigrid methods. Finally, we present the reason why our method is highly efficient for solving these elliptic problems.

Krylov Deferred Correction Accelerated Method of Lines Transpose for Parabolic Problems

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

Jia, Jun; Jingfang, Huang

2008-01-01

In this paper, a new class of numerical methods for the accurate and efficient solutions of parabolic partial differential equations is presented. Unlike traditional method of lines (MoL), the new {\\bf \\it Krylov deferred correction (KDC) accelerated method of lines transpose (MoL^T)} first discretizes the temporal direction using Gaussian type nodes and spectral integration, and symbolically applies low-order time marching schemes to form a preconditioned elliptic system, which is then solved iteratively using Newton-Krylov techniques such as Newton-GMRES or Newton-BiCGStab method. Each function evaluation in the Newton-Krylov method is simply one low-order time-stepping approximation of the error by solving amore » decoupled system using available fast elliptic equation solvers. Preliminary numerical experiments show that the KDC accelerated MoL^T technique is unconditionally stable, can be spectrally accurate in both temporal and spatial directions, and allows optimal time-step sizes in long-time simulations.« less

Three-dimensional forward modeling and inversion of marine CSEM data in anisotropic conductivity structures

NASA Astrophysics Data System (ADS)

Han, B.; Li, Y.

2016-12-01

We present a three-dimensional (3D) forward and inverse modeling code for marine controlled-source electromagnetic (CSEM) surveys in anisotropic media. The forward solution is based on a primary/secondary field approach, in which secondary fields are solved using a staggered finite-volume (FV) method and primary fields are solved for 1D isotropic background models analytically. It is shown that it is rather straightforward to extend the isotopic 3D FV algorithm to a triaxial anisotropic one, while additional coefficients are required to account for full tensor conductivity. To solve the linear system resulting from FV discretization of Maxwell' s equations, both iterative Krylov solvers (e.g. BiCGSTAB) and direct solvers (e.g. MUMPS) have been implemented, makes the code flexible for different computing platforms and different problems. For iterative soloutions, the linear system in terms of electromagnetic potentials (A-Phi) is used to precondition the original linear system, transforming the discretized Curl-Curl equations to discretized Laplace-like equations, thus much more favorable numerical properties can be obtained. Numerical experiments suggest that this A-Phi preconditioner can dramatically improve the convergence rate of an iterative solver and high accuracy can be achieved without divergence correction even for low frequencies. To efficiently calculate the sensitivities, i.e. the derivatives of CSEM data with respect to tensor conductivity, the adjoint method is employed. For inverse modeling, triaxial anisotropy is taken into account. Since the number of model parameters to be resolved of triaxial anisotropic medias is twice or thrice that of isotropic medias, the data-space version of the Gauss-Newton (GN) minimization method is preferred due to its lower computational cost compared with the traditional model-space GN method. We demonstrate the effectiveness of the code with synthetic examples.

Preconditioning and the limit to the incompressible flow equations

NASA Technical Reports Server (NTRS)

Turkel, E.; Fiterman, A.; Vanleer, B.

1993-01-01

The use of preconditioning methods to accelerate the convergence to a steady state for both the incompressible and compressible fluid dynamic equations are considered. The relation between them for both the continuous problem and the finite difference approximation is also considered. The analysis relies on the inviscid equations. The preconditioning consists of a matrix multiplying the time derivatives. Hence, the steady state of the preconditioned system is the same as the steady state of the original system. For finite difference methods the preconditioning can change and improve the steady state solutions. An application to flow around an airfoil is presented.

Optimal preconditioning of lattice Boltzmann methods

NASA Astrophysics Data System (ADS)

Izquierdo, Salvador; Fueyo, Norberto

2009-09-01

A preconditioning technique to accelerate the simulation of steady-state problems using the single-relaxation-time (SRT) lattice Boltzmann (LB) method was first proposed by Guo et al. [Z. Guo, T. Zhao, Y. Shi, Preconditioned lattice-Boltzmann method for steady flows, Phys. Rev. E 70 (2004) 066706-1]. The key idea in this preconditioner is to modify the equilibrium distribution function in such a way that, by means of a Chapman-Enskog expansion, a time-derivative preconditioner of the Navier-Stokes (NS) equations is obtained. In the present contribution, the optimal values for the free parameter γ of this preconditioner are searched both numerically and theoretically; the later with the aid of linear-stability analysis and with the condition number of the system of NS equations. The influence of the collision operator, single- versus multiple-relaxation-times (MRT), is also studied. Three steady-state laminar test cases are used for validation, namely: the two-dimensional lid-driven cavity, a two-dimensional microchannel and the three-dimensional backward-facing step. Finally, guidelines are suggested for an a priori definition of optimal preconditioning parameters as a function of the Reynolds and Mach numbers. The new optimally preconditioned MRT method derived is shown to improve, simultaneously, the rate of convergence, the stability and the accuracy of the lattice Boltzmann simulations, when compared to the non-preconditioned methods and to the optimally preconditioned SRT one. Additionally, direct time-derivative preconditioning of the LB equation is also studied.

A survey of packages for large linear systems

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

Wu, Kesheng; Milne, Brent

2000-02-11

This paper evaluates portable software packages for the iterative solution of very large sparse linear systems on parallel architectures. While we cannot hope to tell individual users which package will best suit their needs, we do hope that our systematic evaluation provides essential unbiased information about the packages and the evaluation process may serve as an example on how to evaluate these packages. The information contained here include feature comparisons, usability evaluations and performance characterizations. This review is primarily focused on self-contained packages that can be easily integrated into an existing program and are capable of computing solutions to verymore » large sparse linear systems of equations. More specifically, it concentrates on portable parallel linear system solution packages that provide iterative solution schemes and related preconditioning schemes because iterative methods are more frequently used than competing schemes such as direct methods. The eight packages evaluated are: Aztec, BlockSolve,ISIS++, LINSOL, P-SPARSLIB, PARASOL, PETSc, and PINEAPL. Among the eight portable parallel iterative linear system solvers reviewed, we recommend PETSc and Aztec for most application programmers because they have well designed user interface, extensive documentation and very responsive user support. Both PETSc and Aztec are written in the C language and are callable from Fortran. For those users interested in using Fortran 90, PARASOL is a good alternative. ISIS++is a good alternative for those who prefer the C++ language. Both PARASOL and ISIS++ are relatively new and are continuously evolving. Thus their user interface may change. In general, those packages written in Fortran 77 are more cumbersome to use because the user may need to directly deal with a number of arrays of varying sizes. Languages like C++ and Fortran 90 offer more convenient data encapsulation mechanisms which make it easier to implement a clean and intuitive user interface. In addition to reviewing these portable parallel iterative solver packages, we also provide a more cursory assessment of a range of related packages, from specialized parallel preconditioners to direct methods for sparse linear systems.« less

Preconditioning strategies for nonlinear conjugate gradient methods, based on quasi-Newton updates

NASA Astrophysics Data System (ADS)

Andrea, Caliciotti; Giovanni, Fasano; Massimo, Roma

2016-10-01

This paper reports two proposals of possible preconditioners for the Nonlinear Conjugate Gradient (NCG) method, in large scale unconstrained optimization. On one hand, the common idea of our preconditioners is inspired to L-BFGS quasi-Newton updates, on the other hand we aim at explicitly approximating in some sense the inverse of the Hessian matrix. Since we deal with large scale optimization problems, we propose matrix-free approaches where the preconditioners are built using symmetric low-rank updating formulae. Our distinctive new contributions rely on using information on the objective function collected as by-product of the NCG, at previous iterations. Broadly speaking, our first approach exploits the secant equation, in order to impose interpolation conditions on the objective function. In the second proposal we adopt and ad hoc modified-secant approach, in order to possibly guarantee some additional theoretical properties.

Efficient block preconditioned eigensolvers for linear response time-dependent density functional theory

NASA Astrophysics Data System (ADS)

Vecharynski, Eugene; Brabec, Jiri; Shao, Meiyue; Govind, Niranjan; Yang, Chao

2017-12-01

We present two efficient iterative algorithms for solving the linear response eigenvalue problem arising from the time dependent density functional theory. Although the matrix to be diagonalized is nonsymmetric, it has a special structure that can be exploited to save both memory and floating point operations. In particular, the nonsymmetric eigenvalue problem can be transformed into an eigenvalue problem that involves the product of two matrices M and K. We show that, because MK is self-adjoint with respect to the inner product induced by the matrix K, this product eigenvalue problem can be solved efficiently by a modified Davidson algorithm and a modified locally optimal block preconditioned conjugate gradient (LOBPCG) algorithm that make use of the K-inner product. The solution of the product eigenvalue problem yields one component of the eigenvector associated with the original eigenvalue problem. We show that the other component of the eigenvector can be easily recovered in an inexpensive postprocessing procedure. As a result, the algorithms we present here become more efficient than existing methods that try to approximate both components of the eigenvectors simultaneously. In particular, our numerical experiments demonstrate that the new algorithms presented here consistently outperform the existing state-of-the-art Davidson type solvers by a factor of two in both solution time and storage.

Condition number estimation of preconditioned matrices.

PubMed

Kushida, Noriyuki

2015-01-01

The present paper introduces a condition number estimation method for preconditioned matrices. The newly developed method provides reasonable results, while the conventional method which is based on the Lanczos connection gives meaningless results. The Lanczos connection based method provides the condition numbers of coefficient matrices of systems of linear equations with information obtained through the preconditioned conjugate gradient method. Estimating the condition number of preconditioned matrices is sometimes important when describing the effectiveness of new preconditionerers or selecting adequate preconditioners. Operating a preconditioner on a coefficient matrix is the simplest method of estimation. However, this is not possible for large-scale computing, especially if computation is performed on distributed memory parallel computers. This is because, the preconditioned matrices become dense, even if the original matrices are sparse. Although the Lanczos connection method can be used to calculate the condition number of preconditioned matrices, it is not considered to be applicable to large-scale problems because of its weakness with respect to numerical errors. Therefore, we have developed a robust and parallelizable method based on Hager's method. The feasibility studies are curried out for the diagonal scaling preconditioner and the SSOR preconditioner with a diagonal matrix, a tri-daigonal matrix and Pei's matrix. As a result, the Lanczos connection method contains around 10% error in the results even with a simple problem. On the other hand, the new method contains negligible errors. In addition, the newly developed method returns reasonable solutions when the Lanczos connection method fails with Pei's matrix, and matrices generated with the finite element method.

High-order solution methods for grey discrete ordinates thermal radiative transfer

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

Maginot, Peter G., E-mail: maginot1@llnl.gov; Ragusa, Jean C., E-mail: jean.ragusa@tamu.edu; Morel, Jim E., E-mail: morel@tamu.edu

This work presents a solution methodology for solving the grey radiative transfer equations that is both spatially and temporally more accurate than the canonical radiative transfer solution technique of linear discontinuous finite element discretization in space with implicit Euler integration in time. We solve the grey radiative transfer equations by fully converging the nonlinear temperature dependence of the material specific heat, material opacities, and Planck function. The grey radiative transfer equations are discretized in space using arbitrary-order self-lumping discontinuous finite elements and integrated in time with arbitrary-order diagonally implicit Runge–Kutta time integration techniques. Iterative convergence of the radiation equation ismore » accelerated using a modified interior penalty diffusion operator to precondition the full discrete ordinates transport operator.« less

High-order solution methods for grey discrete ordinates thermal radiative transfer

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

Maginot, Peter G.; Ragusa, Jean C.; Morel, Jim E.

This paper presents a solution methodology for solving the grey radiative transfer equations that is both spatially and temporally more accurate than the canonical radiative transfer solution technique of linear discontinuous finite element discretization in space with implicit Euler integration in time. We solve the grey radiative transfer equations by fully converging the nonlinear temperature dependence of the material specific heat, material opacities, and Planck function. The grey radiative transfer equations are discretized in space using arbitrary-order self-lumping discontinuous finite elements and integrated in time with arbitrary-order diagonally implicit Runge–Kutta time integration techniques. Iterative convergence of the radiation equation ismore » accelerated using a modified interior penalty diffusion operator to precondition the full discrete ordinates transport operator.« less

High-order solution methods for grey discrete ordinates thermal radiative transfer

DOE PAGES

Maginot, Peter G.; Ragusa, Jean C.; Morel, Jim E.

2016-09-29

This paper presents a solution methodology for solving the grey radiative transfer equations that is both spatially and temporally more accurate than the canonical radiative transfer solution technique of linear discontinuous finite element discretization in space with implicit Euler integration in time. We solve the grey radiative transfer equations by fully converging the nonlinear temperature dependence of the material specific heat, material opacities, and Planck function. The grey radiative transfer equations are discretized in space using arbitrary-order self-lumping discontinuous finite elements and integrated in time with arbitrary-order diagonally implicit Runge–Kutta time integration techniques. Iterative convergence of the radiation equation ismore » accelerated using a modified interior penalty diffusion operator to precondition the full discrete ordinates transport operator.« less

A numerical solution for the diffusion equation in hydrogeologic systems

USGS Publications Warehouse

Ishii, A.L.; Healy, R.W.; Striegl, Robert G.

1989-01-01

The documentation of a computer code for the numerical solution of the linear diffusion equation in one or two dimensions in Cartesian or cylindrical coordinates is presented. Applications of the program include molecular diffusion, heat conduction, and fluid flow in confined systems. The flow media may be anisotropic and heterogeneous. The model is formulated by replacing the continuous linear diffusion equation by discrete finite-difference approximations at each node in a block-centered grid. The resulting matrix equation is solved by the method of preconditioned conjugate gradients. The conjugate gradient method does not require the estimation of iteration parameters and is guaranteed convergent in the absence of rounding error. The matrixes are preconditioned to decrease the steps to convergence. The model allows the specification of any number of boundary conditions for any number of stress periods, and the output of a summary table for selected nodes showing flux and the concentration of the flux quantity for each time step. The model is written in a modular format for ease of modification. The model was verified by comparison of numerical and analytical solutions for cases of molecular diffusion, two-dimensional heat transfer, and axisymmetric radial saturated fluid flow. Application of the model to a hypothetical two-dimensional field situation of gas diffusion in the unsaturated zone is demonstrated. The input and output files are included as a check on program installation. The definition of variables, input requirements, flow chart, and program listing are included in the attachments. (USGS)

Condition Number Estimation of Preconditioned Matrices

PubMed Central

Kushida, Noriyuki

2015-01-01

The present paper introduces a condition number estimation method for preconditioned matrices. The newly developed method provides reasonable results, while the conventional method which is based on the Lanczos connection gives meaningless results. The Lanczos connection based method provides the condition numbers of coefficient matrices of systems of linear equations with information obtained through the preconditioned conjugate gradient method. Estimating the condition number of preconditioned matrices is sometimes important when describing the effectiveness of new preconditionerers or selecting adequate preconditioners. Operating a preconditioner on a coefficient matrix is the simplest method of estimation. However, this is not possible for large-scale computing, especially if computation is performed on distributed memory parallel computers. This is because, the preconditioned matrices become dense, even if the original matrices are sparse. Although the Lanczos connection method can be used to calculate the condition number of preconditioned matrices, it is not considered to be applicable to large-scale problems because of its weakness with respect to numerical errors. Therefore, we have developed a robust and parallelizable method based on Hager’s method. The feasibility studies are curried out for the diagonal scaling preconditioner and the SSOR preconditioner with a diagonal matrix, a tri-daigonal matrix and Pei’s matrix. As a result, the Lanczos connection method contains around 10% error in the results even with a simple problem. On the other hand, the new method contains negligible errors. In addition, the newly developed method returns reasonable solutions when the Lanczos connection method fails with Pei’s matrix, and matrices generated with the finite element method. PMID:25816331

An efficient method for model refinement in diffuse optical tomography

NASA Astrophysics Data System (ADS)

Zirak, A. R.; Khademi, M.

2007-11-01

Diffuse optical tomography (DOT) is a non-linear, ill-posed, boundary value and optimization problem which necessitates regularization. Also, Bayesian methods are suitable owing to measurements data are sparse and correlated. In such problems which are solved with iterative methods, for stabilization and better convergence, the solution space must be small. These constraints subject to extensive and overdetermined system of equations which model retrieving criteria specially total least squares (TLS) must to refine model error. Using TLS is limited to linear systems which is not achievable when applying traditional Bayesian methods. This paper presents an efficient method for model refinement using regularized total least squares (RTLS) for treating on linearized DOT problem, having maximum a posteriori (MAP) estimator and Tikhonov regulator. This is done with combination Bayesian and regularization tools as preconditioner matrices, applying them to equations and then using RTLS to the resulting linear equations. The preconditioning matrixes are guided by patient specific information as well as a priori knowledge gained from the training set. Simulation results illustrate that proposed method improves the image reconstruction performance and localize the abnormally well.

A generalized Poisson and Poisson-Boltzmann solver for electrostatic environments.

PubMed

Fisicaro, G; Genovese, L; Andreussi, O; Marzari, N; Goedecker, S

2016-01-07

The computational study of chemical reactions in complex, wet environments is critical for applications in many fields. It is often essential to study chemical reactions in the presence of applied electrochemical potentials, taking into account the non-trivial electrostatic screening coming from the solvent and the electrolytes. As a consequence, the electrostatic potential has to be found by solving the generalized Poisson and the Poisson-Boltzmann equations for neutral and ionic solutions, respectively. In the present work, solvers for both problems have been developed. A preconditioned conjugate gradient method has been implemented for the solution of the generalized Poisson equation and the linear regime of the Poisson-Boltzmann, allowing to solve iteratively the minimization problem with some ten iterations of the ordinary Poisson equation solver. In addition, a self-consistent procedure enables us to solve the non-linear Poisson-Boltzmann problem. Both solvers exhibit very high accuracy and parallel efficiency and allow for the treatment of periodic, free, and slab boundary conditions. The solver has been integrated into the BigDFT and Quantum-ESPRESSO electronic-structure packages and will be released as an independent program, suitable for integration in other codes.

An efficient flexible-order model for 3D nonlinear water waves

NASA Astrophysics Data System (ADS)

Engsig-Karup, A. P.; Bingham, H. B.; Lindberg, O.

2009-04-01

The flexible-order, finite difference based fully nonlinear potential flow model described in [H.B. Bingham, H. Zhang, On the accuracy of finite difference solutions for nonlinear water waves, J. Eng. Math. 58 (2007) 211-228] is extended to three dimensions (3D). In order to obtain an optimal scaling of the solution effort multigrid is employed to precondition a GMRES iterative solution of the discretized Laplace problem. A robust multigrid method based on Gauss-Seidel smoothing is found to require special treatment of the boundary conditions along solid boundaries, and in particular on the sea bottom. A new discretization scheme using one layer of grid points outside the fluid domain is presented and shown to provide convergent solutions over the full physical and discrete parameter space of interest. Linear analysis of the fundamental properties of the scheme with respect to accuracy, robustness and energy conservation are presented together with demonstrations of grid independent iteration count and optimal scaling of the solution effort. Calculations are made for 3D nonlinear wave problems for steep nonlinear waves and a shoaling problem which show good agreement with experimental measurements and other calculations from the literature.

A generalized Poisson and Poisson-Boltzmann solver for electrostatic environments

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

Fisicaro, G., E-mail: giuseppe.fisicaro@unibas.ch; Goedecker, S.; Genovese, L.

2016-01-07

The computational study of chemical reactions in complex, wet environments is critical for applications in many fields. It is often essential to study chemical reactions in the presence of applied electrochemical potentials, taking into account the non-trivial electrostatic screening coming from the solvent and the electrolytes. As a consequence, the electrostatic potential has to be found by solving the generalized Poisson and the Poisson-Boltzmann equations for neutral and ionic solutions, respectively. In the present work, solvers for both problems have been developed. A preconditioned conjugate gradient method has been implemented for the solution of the generalized Poisson equation and themore » linear regime of the Poisson-Boltzmann, allowing to solve iteratively the minimization problem with some ten iterations of the ordinary Poisson equation solver. In addition, a self-consistent procedure enables us to solve the non-linear Poisson-Boltzmann problem. Both solvers exhibit very high accuracy and parallel efficiency and allow for the treatment of periodic, free, and slab boundary conditions. The solver has been integrated into the BigDFT and Quantum-ESPRESSO electronic-structure packages and will be released as an independent program, suitable for integration in other codes.« less

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

NASA Astrophysics Data System (ADS)

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

2017-02-01

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

Extending substructure based iterative solvers to multiple load and repeated analyses

NASA Technical Reports Server (NTRS)

Farhat, Charbel

1993-01-01

Direct solvers currently dominate commercial finite element structural software, but do not scale well in the fine granularity regime targeted by emerging parallel processors. Substructure based iterative solvers--often called also domain decomposition algorithms--lend themselves better to parallel processing, but must overcome several obstacles before earning their place in general purpose structural analysis programs. One such obstacle is the solution of systems with many or repeated right hand sides. Such systems arise, for example, in multiple load static analyses and in implicit linear dynamics computations. Direct solvers are well-suited for these problems because after the system matrix has been factored, the multiple or repeated solutions can be obtained through relatively inexpensive forward and backward substitutions. On the other hand, iterative solvers in general are ill-suited for these problems because they often must restart from scratch for every different right hand side. In this paper, we present a methodology for extending the range of applications of domain decomposition methods to problems with multiple or repeated right hand sides. Basically, we formulate the overall problem as a series of minimization problems over K-orthogonal and supplementary subspaces, and tailor the preconditioned conjugate gradient algorithm to solve them efficiently. The resulting solution method is scalable, whereas direct factorization schemes and forward and backward substitution algorithms are not. We illustrate the proposed methodology with the solution of static and dynamic structural problems, and highlight its potential to outperform forward and backward substitutions on parallel computers. As an example, we show that for a linear structural dynamics problem with 11640 degrees of freedom, every time-step beyond time-step 15 is solved in a single iteration and consumes 1.0 second on a 32 processor iPSC-860 system; for the same problem and the same parallel processor, a pair of forward/backward substitutions at each step consumes 15.0 seconds.

Parallel conjugate gradient algorithms for manipulator dynamic simulation

NASA Technical Reports Server (NTRS)

Fijany, Amir; Scheld, Robert E.

1989-01-01

Parallel conjugate gradient algorithms for the computation of multibody dynamics are developed for the specialized case of a robot manipulator. For an n-dimensional positive-definite linear system, the Classical Conjugate Gradient (CCG) algorithms are guaranteed to converge in n iterations, each with a computation cost of O(n); this leads to a total computational cost of O(n sq) on a serial processor. A conjugate gradient algorithms is presented that provide greater efficiency using a preconditioner, which reduces the number of iterations required, and by exploiting parallelism, which reduces the cost of each iteration. Two Preconditioned Conjugate Gradient (PCG) algorithms are proposed which respectively use a diagonal and a tridiagonal matrix, composed of the diagonal and tridiagonal elements of the mass matrix, as preconditioners. Parallel algorithms are developed to compute the preconditioners and their inversions in O(log sub 2 n) steps using n processors. A parallel algorithm is also presented which, on the same architecture, achieves the computational time of O(log sub 2 n) for each iteration. Simulation results for a seven degree-of-freedom manipulator are presented. Variants of the proposed algorithms are also developed which can be efficiently implemented on the Robot Mathematics Processor (RMP).

Using Chebyshev polynomials and approximate inverse triangular factorizations for preconditioning the conjugate gradient method

NASA Astrophysics Data System (ADS)

Kaporin, I. E.

2012-02-01

In order to precondition a sparse symmetric positive definite matrix, its approximate inverse is examined, which is represented as the product of two sparse mutually adjoint triangular matrices. In this way, the solution of the corresponding system of linear algebraic equations (SLAE) by applying the preconditioned conjugate gradient method (CGM) is reduced to performing only elementary vector operations and calculating sparse matrix-vector products. A method for constructing the above preconditioner is described and analyzed. The triangular factor has a fixed sparsity pattern and is optimal in the sense that the preconditioned matrix has a minimum K-condition number. The use of polynomial preconditioning based on Chebyshev polynomials makes it possible to considerably reduce the amount of scalar product operations (at the cost of an insignificant increase in the total number of arithmetic operations). The possibility of an efficient massively parallel implementation of the resulting method for solving SLAEs is discussed. For a sequential version of this method, the results obtained by solving 56 test problems from the Florida sparse matrix collection (which are large-scale and ill-conditioned) are presented. These results show that the method is highly reliable and has low computational costs.

Brain Injury Lesion Imaging Using Preconditioned Quantitative Susceptibility Mapping without Skull Stripping.

PubMed

Soman, S; Liu, Z; Kim, G; Nemec, U; Holdsworth, S J; Main, K; Lee, B; Kolakowsky-Hayner, S; Selim, M; Furst, A J; Massaband, P; Yesavage, J; Adamson, M M; Spincemallie, P; Moseley, M; Wang, Y

2018-04-01

Identifying cerebral microhemorrhage burden can aid in the diagnosis and management of traumatic brain injury, stroke, hypertension, and cerebral amyloid angiopathy. MR imaging susceptibility-based methods are more sensitive than CT for detecting cerebral microhemorrhage, but methods other than quantitative susceptibility mapping provide results that vary with field strength and TE, require additional phase maps to distinguish blood from calcification, and depict cerebral microhemorrhages as bloom artifacts. Quantitative susceptibility mapping provides universal quantification of tissue magnetic property without these constraints but traditionally requires a mask generated by skull-stripping, which can pose challenges at tissue interphases. We evaluated the preconditioned quantitative susceptibility mapping MR imaging method, which does not require skull-stripping, for improved depiction of brain parenchyma and pathology. Fifty-six subjects underwent brain MR imaging with a 3D multiecho gradient recalled echo acquisition. Mask-based quantitative susceptibility mapping images were created using a commonly used mask-based quantitative susceptibility mapping method, and preconditioned quantitative susceptibility images were made using precondition-based total field inversion. All images were reviewed by a neuroradiologist and a radiology resident. Ten subjects (18%), all with traumatic brain injury, demonstrated blood products on 3D gradient recalled echo imaging. All lesions were visible on preconditioned quantitative susceptibility mapping, while 6 were not visible on mask-based quantitative susceptibility mapping. Thirty-one subjects (55%) demonstrated brain parenchyma and/or lesions that were visible on preconditioned quantitative susceptibility mapping but not on mask-based quantitative susceptibility mapping. Six subjects (11%) demonstrated pons artifacts on preconditioned quantitative susceptibility mapping and mask-based quantitative susceptibility mapping; they were worse on preconditioned quantitative susceptibility mapping. Preconditioned quantitative susceptibility mapping MR imaging can bring the benefits of quantitative susceptibility mapping imaging to clinical practice without the limitations of mask-based quantitative susceptibility mapping, especially for evaluating cerebral microhemorrhage-associated pathologies, such as traumatic brain injury. © 2018 by American Journal of Neuroradiology.

Scalable Evaluation of Polarization Energy and Associated Forces in Polarizable Molecular Dynamics: II.Towards Massively Parallel Computations using Smooth Particle Mesh Ewald.

PubMed

Lagardère, Louis; Lipparini, Filippo; Polack, Étienne; Stamm, Benjamin; Cancès, Éric; Schnieders, Michael; Ren, Pengyu; Maday, Yvon; Piquemal, Jean-Philip

2014-02-28

In this paper, we present a scalable and efficient implementation of point dipole-based polarizable force fields for molecular dynamics (MD) simulations with periodic boundary conditions (PBC). The Smooth Particle-Mesh Ewald technique is combined with two optimal iterative strategies, namely, a preconditioned conjugate gradient solver and a Jacobi solver in conjunction with the Direct Inversion in the Iterative Subspace for convergence acceleration, to solve the polarization equations. We show that both solvers exhibit very good parallel performances and overall very competitive timings in an energy-force computation needed to perform a MD step. Various tests on large systems are provided in the context of the polarizable AMOEBA force field as implemented in the newly developed Tinker-HP package which is the first implementation for a polarizable model making large scale experiments for massively parallel PBC point dipole models possible. We show that using a large number of cores offers a significant acceleration of the overall process involving the iterative methods within the context of spme and a noticeable improvement of the memory management giving access to very large systems (hundreds of thousands of atoms) as the algorithm naturally distributes the data on different cores. Coupled with advanced MD techniques, gains ranging from 2 to 3 orders of magnitude in time are now possible compared to non-optimized, sequential implementations giving new directions for polarizable molecular dynamics in periodic boundary conditions using massively parallel implementations.

Scalable Evaluation of Polarization Energy and Associated Forces in Polarizable Molecular Dynamics: II.Towards Massively Parallel Computations using Smooth Particle Mesh Ewald

PubMed Central

Lagardère, Louis; Lipparini, Filippo; Polack, Étienne; Stamm, Benjamin; Cancès, Éric; Schnieders, Michael; Ren, Pengyu; Maday, Yvon; Piquemal, Jean-Philip

2015-01-01

In this paper, we present a scalable and efficient implementation of point dipole-based polarizable force fields for molecular dynamics (MD) simulations with periodic boundary conditions (PBC). The Smooth Particle-Mesh Ewald technique is combined with two optimal iterative strategies, namely, a preconditioned conjugate gradient solver and a Jacobi solver in conjunction with the Direct Inversion in the Iterative Subspace for convergence acceleration, to solve the polarization equations. We show that both solvers exhibit very good parallel performances and overall very competitive timings in an energy-force computation needed to perform a MD step. Various tests on large systems are provided in the context of the polarizable AMOEBA force field as implemented in the newly developed Tinker-HP package which is the first implementation for a polarizable model making large scale experiments for massively parallel PBC point dipole models possible. We show that using a large number of cores offers a significant acceleration of the overall process involving the iterative methods within the context of spme and a noticeable improvement of the memory management giving access to very large systems (hundreds of thousands of atoms) as the algorithm naturally distributes the data on different cores. Coupled with advanced MD techniques, gains ranging from 2 to 3 orders of magnitude in time are now possible compared to non-optimized, sequential implementations giving new directions for polarizable molecular dynamics in periodic boundary conditions using massively parallel implementations. PMID:26512230

Nonuniform update for sparse target recovery in fluorescence molecular tomography accelerated by ordered subsets.

PubMed

Zhu, Dianwen; Li, Changqing

2014-12-01

Fluorescence molecular tomography (FMT) is a promising imaging modality and has been actively studied in the past two decades since it can locate the specific tumor position three-dimensionally in small animals. However, it remains a challenging task to obtain fast, robust and accurate reconstruction of fluorescent probe distribution in small animals due to the large computational burden, the noisy measurement and the ill-posed nature of the inverse problem. In this paper we propose a nonuniform preconditioning method in combination with L (1) regularization and ordered subsets technique (NUMOS) to take care of the different updating needs at different pixels, to enhance sparsity and suppress noise, and to further boost convergence of approximate solutions for fluorescence molecular tomography. Using both simulated data and phantom experiment, we found that the proposed nonuniform updating method outperforms its popular uniform counterpart by obtaining a more localized, less noisy, more accurate image. The computational cost was greatly reduced as well. The ordered subset (OS) technique provided additional 5 times and 3 times speed enhancements for simulation and phantom experiments, respectively, without degrading image qualities. When compared with the popular L (1) algorithms such as iterative soft-thresholding algorithm (ISTA) and Fast iterative soft-thresholding algorithm (FISTA) algorithms, NUMOS also outperforms them by obtaining a better image in much shorter period of time.

Efficient block preconditioned eigensolvers for linear response time-dependent density functional theory

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

Vecharynski, Eugene; Brabec, Jiri; Shao, Meiyue

Within this paper, we present two efficient iterative algorithms for solving the linear response eigenvalue problem arising from the time dependent density functional theory. Although the matrix to be diagonalized is nonsymmetric, it has a special structure that can be exploited to save both memory and floating point operations. In particular, the nonsymmetric eigenvalue problem can be transformed into an eigenvalue problem that involves the product of two matrices M and K. We show that, because MK is self-adjoint with respect to the inner product induced by the matrix K, this product eigenvalue problem can be solved efficiently by amore » modified Davidson algorithm and a modified locally optimal block preconditioned conjugate gradient (LOBPCG) algorithm that make use of the K-inner product. Additionally, the solution of the product eigenvalue problem yields one component of the eigenvector associated with the original eigenvalue problem. We show that the other component of the eigenvector can be easily recovered in an inexpensive postprocessing procedure. As a result, the algorithms we present here become more efficient than existing methods that try to approximate both components of the eigenvectors simultaneously. In particular, our numerical experiments demonstrate that the new algorithms presented here consistently outperform the existing state-of-the-art Davidson type solvers by a factor of two in both solution time and storage.« less

Efficient block preconditioned eigensolvers for linear response time-dependent density functional theory

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

Vecharynski, Eugene; Brabec, Jiri; Shao, Meiyue

In this article, we present two efficient iterative algorithms for solving the linear response eigenvalue problem arising from the time dependent density functional theory. Although the matrix to be diagonalized is nonsymmetric, it has a special structure that can be exploited to save both memory and floating point operations. In particular, the nonsymmetric eigenvalue problem can be transformed into an eigenvalue problem that involves the product of two matrices M and K. We show that, because MK is self-adjoint with respect to the inner product induced by the matrix K, this product eigenvalue problem can be solved efficiently by amore » modified Davidson algorithm and a modified locally optimal block preconditioned conjugate gradient (LOBPCG) algorithm that make use of the K-inner product. The solution of the product eigenvalue problem yields one component of the eigenvector associated with the original eigenvalue problem. We show that the other component of the eigenvector can be easily recovered in an inexpensive postprocessing procedure. As a result, the algorithms we present here become more efficient than existing methods that try to approximate both components of the eigenvectors simultaneously. In particular, our numerical experiments demonstrate that the new algorithms presented here consistently outperform the existing state-of-the-art Davidson type solvers by a factor of two in both solution time and storage.« less

Efficient block preconditioned eigensolvers for linear response time-dependent density functional theory

DOE PAGES

Vecharynski, Eugene; Brabec, Jiri; Shao, Meiyue; ...

2017-12-01

In this article, we present two efficient iterative algorithms for solving the linear response eigenvalue problem arising from the time dependent density functional theory. Although the matrix to be diagonalized is nonsymmetric, it has a special structure that can be exploited to save both memory and floating point operations. In particular, the nonsymmetric eigenvalue problem can be transformed into an eigenvalue problem that involves the product of two matrices M and K. We show that, because MK is self-adjoint with respect to the inner product induced by the matrix K, this product eigenvalue problem can be solved efficiently by amore » modified Davidson algorithm and a modified locally optimal block preconditioned conjugate gradient (LOBPCG) algorithm that make use of the K-inner product. The solution of the product eigenvalue problem yields one component of the eigenvector associated with the original eigenvalue problem. We show that the other component of the eigenvector can be easily recovered in an inexpensive postprocessing procedure. As a result, the algorithms we present here become more efficient than existing methods that try to approximate both components of the eigenvectors simultaneously. In particular, our numerical experiments demonstrate that the new algorithms presented here consistently outperform the existing state-of-the-art Davidson type solvers by a factor of two in both solution time and storage.« less

Efficient block preconditioned eigensolvers for linear response time-dependent density functional theory

DOE PAGES

Vecharynski, Eugene; Brabec, Jiri; Shao, Meiyue; ...

2017-08-24

Within this paper, we present two efficient iterative algorithms for solving the linear response eigenvalue problem arising from the time dependent density functional theory. Although the matrix to be diagonalized is nonsymmetric, it has a special structure that can be exploited to save both memory and floating point operations. In particular, the nonsymmetric eigenvalue problem can be transformed into an eigenvalue problem that involves the product of two matrices M and K. We show that, because MK is self-adjoint with respect to the inner product induced by the matrix K, this product eigenvalue problem can be solved efficiently by amore » modified Davidson algorithm and a modified locally optimal block preconditioned conjugate gradient (LOBPCG) algorithm that make use of the K-inner product. Additionally, the solution of the product eigenvalue problem yields one component of the eigenvector associated with the original eigenvalue problem. We show that the other component of the eigenvector can be easily recovered in an inexpensive postprocessing procedure. As a result, the algorithms we present here become more efficient than existing methods that try to approximate both components of the eigenvectors simultaneously. In particular, our numerical experiments demonstrate that the new algorithms presented here consistently outperform the existing state-of-the-art Davidson type solvers by a factor of two in both solution time and storage.« less

Galilean-invariant preconditioned central-moment lattice Boltzmann method without cubic velocity errors for efficient steady flow simulations

NASA Astrophysics Data System (ADS)

Hajabdollahi, Farzaneh; Premnath, Kannan N.

2018-05-01

Lattice Boltzmann (LB) models used for the computation of fluid flows represented by the Navier-Stokes (NS) equations on standard lattices can lead to non-Galilean-invariant (GI) viscous stress involving cubic velocity errors. This arises from the dependence of their third-order diagonal moments on the first-order moments for standard lattices, and strategies have recently been introduced to restore Galilean invariance without such errors using a modified collision operator involving corrections to either the relaxation times or the moment equilibria. Convergence acceleration in the simulation of steady flows can be achieved by solving the preconditioned NS equations, which contain a preconditioning parameter that can be used to tune the effective sound speed, and thereby alleviating the numerical stiffness. In the present paper, we present a GI formulation of the preconditioned cascaded central-moment LB method used to solve the preconditioned NS equations, which is free of cubic velocity errors on a standard lattice, for steady flows. A Chapman-Enskog analysis reveals the structure of the spurious non-GI defect terms and it is demonstrated that the anisotropy of the resulting viscous stress is dependent on the preconditioning parameter, in addition to the fluid velocity. It is shown that partial correction to eliminate the cubic velocity defects is achieved by scaling the cubic velocity terms in the off-diagonal third-order moment equilibria with the square of the preconditioning parameter. Furthermore, we develop additional corrections based on the extended moment equilibria involving gradient terms with coefficients dependent locally on the fluid velocity and the preconditioning parameter. Such parameter dependent corrections eliminate the remaining truncation errors arising from the degeneracy of the diagonal third-order moments and fully restore Galilean invariance without cubic defects for the preconditioned LB scheme on a standard lattice. Several conclusions are drawn from the analysis of the structure of the non-GI errors and the associated corrections, with particular emphasis on their dependence on the preconditioning parameter. The GI preconditioned central-moment LB method is validated for a number of complex flow benchmark problems and its effectiveness to achieve convergence acceleration and improvement in accuracy is demonstrated.

New preconditioning strategy for Jacobian-free solvers for variably saturated flows with Richards’ equation

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

Lipnikov, Konstantin; Moulton, David; Svyatskiy, Daniil

2016-04-29

We develop a new approach for solving the nonlinear Richards’ equation arising in variably saturated flow modeling. The growing complexity of geometric models for simulation of subsurface flows leads to the necessity of using unstructured meshes and advanced discretization methods. Typically, a numerical solution is obtained by first discretizing PDEs and then solving the resulting system of nonlinear discrete equations with a Newton-Raphson-type method. Efficiency and robustness of the existing solvers rely on many factors, including an empiric quality control of intermediate iterates, complexity of the employed discretization method and a customized preconditioner. We propose and analyze a new preconditioningmore » strategy that is based on a stable discretization of the continuum Jacobian. We will show with numerical experiments for challenging problems in subsurface hydrology that this new preconditioner improves convergence of the existing Jacobian-free solvers 3-20 times. Furthermore, we show that the Picard method with this preconditioner becomes a more efficient nonlinear solver than a few widely used Jacobian-free solvers.« less

Preconditioned upwind methods to solve 3-D incompressible Navier-Stokes equations for viscous flows

NASA Technical Reports Server (NTRS)

Hsu, C.-H.; Chen, Y.-M.; Liu, C. H.

1990-01-01

A computational method for calculating low-speed viscous flowfields is developed. The method uses the implicit upwind-relaxation finite-difference algorithm with a nonsingular eigensystem to solve the preconditioned, three-dimensional, incompressible Navier-Stokes equations in curvilinear coordinates. The technique of local time stepping is incorporated to accelerate the rate of convergence to a steady-state solution. An extensive study of optimizing the preconditioned system is carried out for two viscous flow problems. Computed results are compared with analytical solutions and experimental data.

Preconditioned conjugate gradient wave-front reconstructors for multiconjugate adaptive optics

NASA Astrophysics Data System (ADS)

Gilles, Luc; Ellerbroek, Brent L.; Vogel, Curtis R.

2003-09-01

Multiconjugate adaptive optics (MCAO) systems with 104-105 degrees of freedom have been proposed for future giant telescopes. Using standard matrix methods to compute, optimize, and implement wave-front control algorithms for these systems is impractical, since the number of calculations required to compute and apply the reconstruction matrix scales respectively with the cube and the square of the number of adaptive optics degrees of freedom. We develop scalable open-loop iterative sparse matrix implementations of minimum variance wave-front reconstruction for telescope diameters up to 32 m with more than 104 actuators. The basic approach is the preconditioned conjugate gradient method with an efficient preconditioner, whose block structure is defined by the atmospheric turbulent layers very much like the layer-oriented MCAO algorithms of current interest. Two cost-effective preconditioners are investigated: a multigrid solver and a simpler block symmetric Gauss-Seidel (BSGS) sweep. Both options require off-line sparse Cholesky factorizations of the diagonal blocks of the matrix system. The cost to precompute these factors scales approximately as the three-halves power of the number of estimated phase grid points per atmospheric layer, and their average update rate is typically of the order of 10-2 Hz, i.e., 4-5 orders of magnitude lower than the typical 103 Hz temporal sampling rate. All other computations scale almost linearly with the total number of estimated phase grid points. We present numerical simulation results to illustrate algorithm convergence. Convergence rates of both preconditioners are similar, regardless of measurement noise level, indicating that the layer-oriented BSGS sweep is as effective as the more elaborated multiresolution preconditioner.

Effective dimensional reduction algorithm for eigenvalue problems for thin elastic structures: A paradigm in three dimensions

PubMed Central

Ovtchinnikov, Evgueni E.; Xanthis, Leonidas S.

2000-01-01

We present a methodology for the efficient numerical solution of eigenvalue problems of full three-dimensional elasticity for thin elastic structures, such as shells, plates and rods of arbitrary geometry, discretized by the finite element method. Such problems are solved by iterative methods, which, however, are known to suffer from slow convergence or even convergence failure, when the thickness is small. In this paper we show an effective way of resolving this difficulty by invoking a special preconditioning technique associated with the effective dimensional reduction algorithm (EDRA). As an example, we present an algorithm for computing the minimal eigenvalue of a thin elastic plate and we show both theoretically and numerically that it is robust with respect to both the thickness and discretization parameters, i.e. the convergence does not deteriorate with diminishing thickness or mesh refinement. This robustness is sine qua non for the efficient computation of large-scale eigenvalue problems for thin elastic structures. PMID:10655469

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

NASA Astrophysics Data System (ADS)

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

2018-05-01

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

Weighted SGD for ℓ p Regression with Randomized Preconditioning.

PubMed

Yang, Jiyan; Chow, Yin-Lam; Ré, Christopher; Mahoney, Michael W

2016-01-01

In recent years, stochastic gradient descent (SGD) methods and randomized linear algebra (RLA) algorithms have been applied to many large-scale problems in machine learning and data analysis. SGD methods are easy to implement and applicable to a wide range of convex optimization problems. In contrast, RLA algorithms provide much stronger performance guarantees but are applicable to a narrower class of problems. We aim to bridge the gap between these two methods in solving constrained overdetermined linear regression problems-e.g., ℓ 2 and ℓ 1 regression problems. We propose a hybrid algorithm named pwSGD that uses RLA techniques for preconditioning and constructing an importance sampling distribution, and then performs an SGD-like iterative process with weighted sampling on the preconditioned system.By rewriting a deterministic ℓ p regression problem as a stochastic optimization problem, we connect pwSGD to several existing ℓ p solvers including RLA methods with algorithmic leveraging (RLA for short).We prove that pwSGD inherits faster convergence rates that only depend on the lower dimension of the linear system, while maintaining low computation complexity. Such SGD convergence rates are superior to other related SGD algorithm such as the weighted randomized Kaczmarz algorithm.Particularly, when solving ℓ 1 regression with size n by d , pwSGD returns an approximate solution with ε relative error in the objective value in (log n ·nnz( A )+poly( d )/ ε 2 ) time. This complexity is uniformly better than that of RLA methods in terms of both ε and d when the problem is unconstrained. In the presence of constraints, pwSGD only has to solve a sequence of much simpler and smaller optimization problem over the same constraints. In general this is more efficient than solving the constrained subproblem required in RLA.For ℓ 2 regression, pwSGD returns an approximate solution with ε relative error in the objective value and the solution vector measured in prediction norm in (log n ·nnz( A )+poly( d ) log(1/ ε )/ ε ) time. We show that for unconstrained ℓ 2 regression, this complexity is comparable to that of RLA and is asymptotically better over several state-of-the-art solvers in the regime where the desired accuracy ε , high dimension n and low dimension d satisfy d ≥ 1/ ε and n ≥ d 2 / ε . We also provide lower bounds on the coreset complexity for more general regression problems, indicating that still new ideas will be needed to extend similar RLA preconditioning ideas to weighted SGD algorithms for more general regression problems. Finally, the effectiveness of such algorithms is illustrated numerically on both synthetic and real datasets, and the results are consistent with our theoretical findings and demonstrate that pwSGD converges to a medium-precision solution, e.g., ε = 10 -3 , more quickly.

Weighted SGD for ℓp Regression with Randomized Preconditioning*

PubMed Central

Yang, Jiyan; Chow, Yin-Lam; Ré, Christopher; Mahoney, Michael W.

2018-01-01

In recent years, stochastic gradient descent (SGD) methods and randomized linear algebra (RLA) algorithms have been applied to many large-scale problems in machine learning and data analysis. SGD methods are easy to implement and applicable to a wide range of convex optimization problems. In contrast, RLA algorithms provide much stronger performance guarantees but are applicable to a narrower class of problems. We aim to bridge the gap between these two methods in solving constrained overdetermined linear regression problems—e.g., ℓ2 and ℓ1 regression problems. We propose a hybrid algorithm named pwSGD that uses RLA techniques for preconditioning and constructing an importance sampling distribution, and then performs an SGD-like iterative process with weighted sampling on the preconditioned system.By rewriting a deterministic ℓp regression problem as a stochastic optimization problem, we connect pwSGD to several existing ℓp solvers including RLA methods with algorithmic leveraging (RLA for short).We prove that pwSGD inherits faster convergence rates that only depend on the lower dimension of the linear system, while maintaining low computation complexity. Such SGD convergence rates are superior to other related SGD algorithm such as the weighted randomized Kaczmarz algorithm.Particularly, when solving ℓ1 regression with size n by d, pwSGD returns an approximate solution with ε relative error in the objective value in 𝒪(log n·nnz(A)+poly(d)/ε2) time. This complexity is uniformly better than that of RLA methods in terms of both ε and d when the problem is unconstrained. In the presence of constraints, pwSGD only has to solve a sequence of much simpler and smaller optimization problem over the same constraints. In general this is more efficient than solving the constrained subproblem required in RLA.For ℓ2 regression, pwSGD returns an approximate solution with ε relative error in the objective value and the solution vector measured in prediction norm in 𝒪(log n·nnz(A)+poly(d) log(1/ε)/ε) time. We show that for unconstrained ℓ2 regression, this complexity is comparable to that of RLA and is asymptotically better over several state-of-the-art solvers in the regime where the desired accuracy ε, high dimension n and low dimension d satisfy d ≥ 1/ε and n ≥ d2/ε. We also provide lower bounds on the coreset complexity for more general regression problems, indicating that still new ideas will be needed to extend similar RLA preconditioning ideas to weighted SGD algorithms for more general regression problems. Finally, the effectiveness of such algorithms is illustrated numerically on both synthetic and real datasets, and the results are consistent with our theoretical findings and demonstrate that pwSGD converges to a medium-precision solution, e.g., ε = 10−3, more quickly. PMID:29782626

On linearization and preconditioning for radiation diffusion coupled to material thermal conduction equations

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

Feng, Tao, E-mail: fengtao2@mail.ustc.edu.cn; Graduate School of China Academy Engineering Physics, Beijing 100083; An, Hengbin, E-mail: an_hengbin@iapcm.ac.cn

2013-03-01

Jacobian-free Newton–Krylov (JFNK) method is an effective algorithm for solving large scale nonlinear equations. One of the most important advantages of JFNK method is that there is no necessity to form and store the Jacobian matrix of the nonlinear system when JFNK method is employed. However, an approximation of the Jacobian is needed for the purpose of preconditioning. In this paper, JFNK method is employed to solve a class of non-equilibrium radiation diffusion coupled to material thermal conduction equations, and two preconditioners are designed by linearizing the equations in two methods. Numerical results show that the two preconditioning methods canmore » improve the convergence behavior and efficiency of JFNK method.« less

User's Guide for ENSAERO_FE Parallel Finite Element Solver

NASA Technical Reports Server (NTRS)

Eldred, Lloyd B.; Guruswamy, Guru P.

1999-01-01

A high fidelity parallel static structural analysis capability is created and interfaced to the multidisciplinary analysis package ENSAERO-MPI of Ames Research Center. This new module replaces ENSAERO's lower fidelity simple finite element and modal modules. Full aircraft structures may be more accurately modeled using the new finite element capability. Parallel computation is performed by breaking the full structure into multiple substructures. This approach is conceptually similar to ENSAERO's multizonal fluid analysis capability. The new substructure code is used to solve the structural finite element equations for each substructure in parallel. NASTRANKOSMIC is utilized as a front end for this code. Its full library of elements can be used to create an accurate and realistic aircraft model. It is used to create the stiffness matrices for each substructure. The new parallel code then uses an iterative preconditioned conjugate gradient method to solve the global structural equations for the substructure boundary nodes.

Implicit preconditioned WENO scheme for steady viscous flow computation

NASA Astrophysics Data System (ADS)

Huang, Juan-Chen; Lin, Herng; Yang, Jaw-Yen

2009-02-01

A class of lower-upper symmetric Gauss-Seidel implicit weighted essentially nonoscillatory (WENO) schemes is developed for solving the preconditioned Navier-Stokes equations of primitive variables with Spalart-Allmaras one-equation turbulence model. The numerical flux of the present preconditioned WENO schemes consists of a first-order part and high-order part. For first-order part, we adopt the preconditioned Roe scheme and for the high-order part, we employ preconditioned WENO methods. For comparison purpose, a preconditioned TVD scheme is also given and tested. A time-derivative preconditioning algorithm is devised and a discriminant is devised for adjusting the preconditioning parameters at low Mach numbers and turning off the preconditioning at intermediate or high Mach numbers. The computations are performed for the two-dimensional lid driven cavity flow, low subsonic viscous flow over S809 airfoil, three-dimensional low speed viscous flow over 6:1 prolate spheroid, transonic flow over ONERA-M6 wing and hypersonic flow over HB-2 model. The solutions of the present algorithms are in good agreement with the experimental data. The application of the preconditioned WENO schemes to viscous flows at all speeds not only enhances the accuracy and robustness of resolving shock and discontinuities for supersonic flows, but also improves the accuracy of low Mach number flow with complicated smooth solution structures.

Efficient Radiative Transfer for Dynamically Evolving Stratified Atmospheres

NASA Astrophysics Data System (ADS)

Judge, Philip G.

2017-12-01

We present a fast multi-level and multi-atom non-local thermodynamic equilibrium radiative transfer method for dynamically evolving stratified atmospheres, such as the solar atmosphere. The preconditioning method of Rybicki & Hummer (RH92) is adopted. But, pressed for the need of speed and stability, a “second-order escape probability” scheme is implemented within the framework of the RH92 method, in which frequency- and angle-integrals are carried out analytically. While minimizing the computational work needed, this comes at the expense of numerical accuracy. The iteration scheme is local, the formal solutions for the intensities are the only non-local component. At present the methods have been coded for vertical transport, applicable to atmospheres that are highly stratified. The probabilistic method seems adequately fast, stable, and sufficiently accurate for exploring dynamical interactions between the evolving MHD atmosphere and radiation using current computer hardware. Current 2D and 3D dynamics codes do not include this interaction as consistently as the current method does. The solutions generated may ultimately serve as initial conditions for dynamical calculations including full 3D radiative transfer. The National Center for Atmospheric Research is sponsored by the National Science Foundation.

Acoustic 3D modeling by the method of integral equations

NASA Astrophysics Data System (ADS)

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

2018-02-01

This paper presents a parallel algorithm for frequency-domain acoustic modeling by the method of integral equations (IE). The algorithm is applied to seismic simulation. The IE method reduces the size of the problem but leads to a dense system matrix. A tolerable memory consumption and numerical complexity were achieved by applying an iterative solver, accompanied by an effective matrix-vector multiplication operation, based on the fast Fourier transform (FFT). We demonstrate that, the IE system matrix is better conditioned than that of the finite-difference (FD) method, and discuss its relation to a specially preconditioned FD matrix. We considered several methods of matrix-vector multiplication for the free-space and layered host models. The developed algorithm and computer code were benchmarked against the FD time-domain solution. It was demonstrated that, the method could accurately calculate the seismic field for the models with sharp material boundaries and a point source and receiver located close to the free surface. We used OpenMP to speed up the matrix-vector multiplication, while MPI was used to speed up the solution of the system equations, and also for parallelizing across multiple sources. The practical examples and efficiency tests are presented as well.

A scalable block-preconditioning strategy for divergence-conforming B-spline discretizations of the Stokes problem

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

Cortes, Adriano M.; Dalcin, Lisandro; Sarmiento, Adel F.

The recently introduced divergence-conforming B-spline discretizations allow the construction of smooth discrete velocity–pressure pairs for viscous incompressible flows that are at the same time inf–sup stable and pointwise divergence-free. When applied to the discretized Stokes problem, these spaces generate a symmetric and indefinite saddle-point linear system. The iterative method of choice to solve such system is the Generalized Minimum Residual Method. This method lacks robustness, and one remedy is to use preconditioners. For linear systems of saddle-point type, a large family of preconditioners can be obtained by using a block factorization of the system. In this paper, we show howmore » the nesting of “black-box” solvers and preconditioners can be put together in a block triangular strategy to build a scalable block preconditioner for the Stokes system discretized by divergence-conforming B-splines. Lastly, besides the known cavity flow problem, we used for benchmark flows defined on complex geometries: an eccentric annulus and hollow torus of an eccentric annular cross-section.« less

A scalable block-preconditioning strategy for divergence-conforming B-spline discretizations of the Stokes problem

DOE PAGES

Cortes, Adriano M.; Dalcin, Lisandro; Sarmiento, Adel F.; ...

2016-10-19

The recently introduced divergence-conforming B-spline discretizations allow the construction of smooth discrete velocity–pressure pairs for viscous incompressible flows that are at the same time inf–sup stable and pointwise divergence-free. When applied to the discretized Stokes problem, these spaces generate a symmetric and indefinite saddle-point linear system. The iterative method of choice to solve such system is the Generalized Minimum Residual Method. This method lacks robustness, and one remedy is to use preconditioners. For linear systems of saddle-point type, a large family of preconditioners can be obtained by using a block factorization of the system. In this paper, we show howmore » the nesting of “black-box” solvers and preconditioners can be put together in a block triangular strategy to build a scalable block preconditioner for the Stokes system discretized by divergence-conforming B-splines. Lastly, besides the known cavity flow problem, we used for benchmark flows defined on complex geometries: an eccentric annulus and hollow torus of an eccentric annular cross-section.« less

Incomplete Sparse Approximate Inverses for Parallel Preconditioning

DOE PAGES

Anzt, Hartwig; Huckle, Thomas K.; Bräckle, Jürgen; ...

2017-10-28

In this study, we propose a new preconditioning method that can be seen as a generalization of block-Jacobi methods, or as a simplification of the sparse approximate inverse (SAI) preconditioners. The “Incomplete Sparse Approximate Inverses” (ISAI) is in particular efficient in the solution of sparse triangular linear systems of equations. Those arise, for example, in the context of incomplete factorization preconditioning. ISAI preconditioners can be generated via an algorithm providing fine-grained parallelism, which makes them attractive for hardware with a high concurrency level. Finally, in a study covering a large number of matrices, we identify the ISAI preconditioner as anmore » attractive alternative to exact triangular solves in the context of incomplete factorization preconditioning.« less

A preconditioned formulation of the Cauchy-Riemann equations

NASA Technical Reports Server (NTRS)

Phillips, T. N.

1983-01-01

A preconditioning of the Cauchy-Riemann equations which results in a second-order system is described. This system is shown to have a unique solution if the boundary conditions are chosen carefully. This choice of boundary condition enables the solution of the first-order system to be retrieved. A numerical solution of the preconditioned equations is obtained by the multigrid method.

Use of general purpose graphics processing units with MODFLOW

USGS Publications Warehouse

Hughes, Joseph D.; White, Jeremy T.

2013-01-01

To evaluate the use of general-purpose graphics processing units (GPGPUs) to improve the performance of MODFLOW, an unstructured preconditioned conjugate gradient (UPCG) solver has been developed. The UPCG solver uses a compressed sparse row storage scheme and includes Jacobi, zero fill-in incomplete, and modified-incomplete lower-upper (LU) factorization, and generalized least-squares polynomial preconditioners. The UPCG solver also includes options for sequential and parallel solution on the central processing unit (CPU) using OpenMP. For simulations utilizing the GPGPU, all basic linear algebra operations are performed on the GPGPU; memory copies between the central processing unit CPU and GPCPU occur prior to the first iteration of the UPCG solver and after satisfying head and flow criteria or exceeding a maximum number of iterations. The efficiency of the UPCG solver for GPGPU and CPU solutions is benchmarked using simulations of a synthetic, heterogeneous unconfined aquifer with tens of thousands to millions of active grid cells. Testing indicates GPGPU speedups on the order of 2 to 8, relative to the standard MODFLOW preconditioned conjugate gradient (PCG) solver, can be achieved when (1) memory copies between the CPU and GPGPU are optimized, (2) the percentage of time performing memory copies between the CPU and GPGPU is small relative to the calculation time, (3) high-performance GPGPU cards are utilized, and (4) CPU-GPGPU combinations are used to execute sequential operations that are difficult to parallelize. Furthermore, UPCG solver testing indicates GPGPU speedups exceed parallel CPU speedups achieved using OpenMP on multicore CPUs for preconditioners that can be easily parallelized.

A framework for directional and higher-order reconstruction in photoacoustic tomography

NASA Astrophysics Data System (ADS)

Boink, Yoeri E.; Lagerwerf, Marinus J.; Steenbergen, Wiendelt; van Gils, Stephan A.; Manohar, Srirang; Brune, Christoph

2018-02-01

Photoacoustic tomography is a hybrid imaging technique that combines high optical tissue contrast with high ultrasound resolution. Direct reconstruction methods such as filtered back-projection, time reversal and least squares suffer from curved line artefacts and blurring, especially in the case of limited angles or strong noise. In recent years, there has been great interest in regularised iterative methods. These methods employ prior knowledge of the image to provide higher quality reconstructions. However, easy comparisons between regularisers and their properties are limited, since many tomography implementations heavily rely on the specific regulariser chosen. To overcome this bottleneck, we present a modular reconstruction framework for photoacoustic tomography, which enables easy comparisons between regularisers with different properties, e.g. nonlinear, higher-order or directional. We solve the underlying minimisation problem with an efficient first-order primal-dual algorithm. Convergence rates are optimised by choosing an operator-dependent preconditioning strategy. A variety of reconstruction methods are tested on challenging 2D synthetic and experimental data sets. They outperform direct reconstruction approaches for strong noise levels and limited angle measurements, offering immediate benefits in terms of acquisition time and quality. This work provides a basic platform for the investigation of future advanced regularisation methods in photoacoustic tomography.

Crustal wavespeed structure of North Texas and Oklahoma based on ambient noise cross-correlation functions and adjoint tomography

NASA Astrophysics Data System (ADS)

Zhu, H.

2017-12-01

Recently, seismologists observed increasing seismicity in North Texas and Oklahoma. Based on seismic observations and other geophysical measurements, some studies suggested possible links between the increasing seismicity and wastewater injection during unconventional oil and gas exploration. To better monitor seismic events and investigate their mechanisms, we need an accurate 3D crustal wavespeed model for North Texas and Oklahoma. Considering the uneven distribution of earthquakes in this region, seismic tomography with local earthquake records have difficulties to achieve good illumination. To overcome this limitation, in this study, ambient noise cross-correlation functions are used to constrain subsurface variations in wavespeeds. I use adjoint tomography to iteratively fit frequency-dependent phase differences between observed and predicted band-limited Green's functions. The spectral-element method is used to numerically calculate the band-limited Green's functions and the adjoint method is used to calculate misfit gradients with respect to wavespeeds. 25 preconditioned conjugate gradient iterations are used to update model parameters and minimize data misfits. Features in the new crustal model M25 correlates with geological units in the study region, including the Llano uplift, the Anadarko basin and the Ouachita orogenic front. In addition, these seismic anomalies correlate with gravity and magnetic observations. This new model can be used to better constrain earthquake source parameters in North Texas and Oklahoma, such as epicenter location and moment tensor solutions, which are important for investigating potential relations between seismicity and unconventional oil and gas exploration.

An M-step preconditioned conjugate gradient method for parallel computation

NASA Technical Reports Server (NTRS)

Adams, L.

1983-01-01

This paper describes a preconditioned conjugate gradient method that can be effectively implemented on both vector machines and parallel arrays to solve sparse symmetric and positive definite systems of linear equations. The implementation on the CYBER 203/205 and on the Finite Element Machine is discussed and results obtained using the method on these machines are given.

Detailed qualitative dynamic knowledge representation using a BioNetGen model of TLR-4 signaling and preconditioning.

PubMed

An, Gary C; Faeder, James R

2009-01-01

Intracellular signaling/synthetic pathways are being increasingly extensively characterized. However, while these pathways can be displayed in static diagrams, in reality they exist with a degree of dynamic complexity that is responsible for heterogeneous cellular behavior. Multiple parallel pathways exist and interact concurrently, limiting the ability to integrate the various identified mechanisms into a cohesive whole. Computational methods have been suggested as a means of concatenating this knowledge to aid in the understanding of overall system dynamics. Since the eventual goal of biomedical research is the identification and development of therapeutic modalities, computational representation must have sufficient detail to facilitate this 'engineering' process. Adding to the challenge, this type of representation must occur in a perpetual state of incomplete knowledge. We present a modeling approach to address this challenge that is both detailed and qualitative. This approach is termed 'dynamic knowledge representation,' and is intended to be an integrated component of the iterative cycle of scientific discovery. BioNetGen (BNG), a software platform for modeling intracellular signaling pathways, was used to model the toll-like receptor 4 (TLR-4) signal transduction cascade. The informational basis of the model was a series of reference papers on modulation of (TLR-4) signaling, and some specific primary research papers to aid in the characterization of specific mechanistic steps in the pathway. This model was detailed with respect to the components of the pathway represented, but qualitative with respect to the specific reaction coefficients utilized to execute the reactions. Responsiveness to simulated lipopolysaccharide (LPS) administration was measured by tumor necrosis factor (TNF) production. Simulation runs included evaluation of initial dose-dependent response to LPS administration at 10, 100, 1000 and 10,000, and a subsequent examination of preconditioning behavior with increasing LPS at 10, 100, 1000 and 10,000 and a secondary dose of LPS at 10,000 administered at approximately 27h of simulated time. Simulations of 'knockout' versions of the model allowed further examination of the interactions within the signaling cascade. The model demonstrated a dose-dependent TNF response curve to increasing stimulus by LPS. Preconditioning simulations demonstrated a similar dose-dependency of preconditioning doses leading to attenuation of response to subsequent LPS challenge - a 'tolerance' dynamic. These responses match dynamics reported in the literature. Furthermore, the simulated 'knockout' results suggested the existence and need for dual negative feedback control mechanisms, represented by the zinc ring-finger protein A20 and inhibitor kappa B proteins (IkappaB), in order for both effective attenuation of the initial stimulus signal and subsequent preconditioned 'tolerant' behavior. We present an example of detailed, qualitative dynamic knowledge representation using the TLR-4 signaling pathway, its control mechanisms and overall behavior with respect to preconditioning. The intent of this approach is to demonstrate a method of translating the extensive mechanistic knowledge being generated at the basic science level into an executable framework that can provide a means of 'conceptual model verification.' This allows for both the 'checking' of the dynamic consequences of a mechanistic hypothesis and the creation of a modular component of an overall model directed at the engineering goal of biomedical research. It is hoped that this paper will increase the use of knowledge representation and communication in this fashion, and facilitate the concatenation and integration of community-wide knowledge.

Preconditioned conjugate gradient wave-front reconstructors for multiconjugate adaptive optics.

PubMed

Gilles, Luc; Ellerbroek, Brent L; Vogel, Curtis R

2003-09-10

Multiconjugate adaptive optics (MCAO) systems with 10(4)-10(5) degrees of freedom have been proposed for future giant telescopes. Using standard matrix methods to compute, optimize, and implement wavefront control algorithms for these systems is impractical, since the number of calculations required to compute and apply the reconstruction matrix scales respectively with the cube and the square of the number of adaptive optics degrees of freedom. We develop scalable open-loop iterative sparse matrix implementations of minimum variance wave-front reconstruction for telescope diameters up to 32 m with more than 10(4) actuators. The basic approach is the preconditioned conjugate gradient method with an efficient preconditioner, whose block structure is defined by the atmospheric turbulent layers very much like the layer-oriented MCAO algorithms of current interest. Two cost-effective preconditioners are investigated: a multigrid solver and a simpler block symmetric Gauss-Seidel (BSGS) sweep. Both options require off-line sparse Cholesky factorizations of the diagonal blocks of the matrix system. The cost to precompute these factors scales approximately as the three-halves power of the number of estimated phase grid points per atmospheric layer, and their average update rate is typically of the order of 10(-2) Hz, i.e., 4-5 orders of magnitude lower than the typical 10(3) Hz temporal sampling rate. All other computations scale almost linearly with the total number of estimated phase grid points. We present numerical simulation results to illustrate algorithm convergence. Convergence rates of both preconditioners are similar, regardless of measurement noise level, indicating that the layer-oriented BSGS sweep is as effective as the more elaborated multiresolution preconditioner.

Numerical Aspects of Nonhydrostatic Implementations Applied to a Parallel Finite Element Tsunami Model

NASA Astrophysics Data System (ADS)

Fuchs, A.; Androsov, A.; Harig, S.; Hiller, W.; Rakowsky, N.

2012-04-01

Based on the jeopardy of devastating tsunamis and the unpredictability of such events, tsunami modelling as part of warning systems is still a contemporary topic. The tsunami group of Alfred Wegener Institute developed the simulation tool TsunAWI as contribution to the Early Warning System in Indonesia. Although the precomputed scenarios for this purpose qualify for satisfying deliverables, the study of further improvements continues. While TsunAWI is governed by the Shallow Water Equations, an extension of the model is based on a nonhydrostatic approach. At the arrival of a tsunami wave in coastal regions with rough bathymetry, the term containing the nonhydrostatic part of pressure, that is neglected in the original hydrostatic model, gains in importance. In consideration of this term, a better approximation of the wave is expected. Differences of hydrostatic and nonhydrostatic model results are contrasted in the standard benchmark problem of a solitary wave runup on a plane beach. The observation data provided by Titov and Synolakis (1995) serves as reference. The nonhydrostatic approach implies a set of equations that are similar to the Shallow Water Equations, so the variation of the code can be implemented on top. However, this additional routines cause a lot of issues you have to cope with. So far the computations of the model were purely explicit. In the nonhydrostatic version the determination of an additional unknown and the solution of a large sparse system of linear equations is necessary. The latter constitutes the lion's share of computing time and memory requirement. Since the corresponding matrix is only symmetric in structure and not in values, an iterative Krylov Subspace Method is used, in particular the restarted Generalized Minimal Residual Algorithm GMRES(m). With regard to optimization, we present a comparison of several combinations of sequential and parallel preconditioning techniques respective number of iterations and setup/application time. Since the used software package pARMS 3.2, that provides solving and preconditioning techniques, works via MPI parallelism, in an auxiliary branch we adapted TsunAWI and switched from OpenMP to MPI with attached importance to internal partition management.

Angular Multigrid Preconditioner for Krylov-Based Solution Techniques Applied to the Sn Equations with Highly Forward-Peaked Scattering

NASA Astrophysics Data System (ADS)

Turcksin, Bruno; Ragusa, Jean C.; Morel, Jim E.

2012-01-01

It is well known that the diffusion synthetic acceleration (DSA) methods for the Sn equations become ineffective in the Fokker-Planck forward-peaked scattering limit. In response to this deficiency, Morel and Manteuffel (1991) developed an angular multigrid method for the 1-D Sn equations. This method is very effective, costing roughly twice as much as DSA per source iteration, and yielding a maximum spectral radius of approximately 0.6 in the Fokker-Planck limit. Pautz, Adams, and Morel (PAM) (1999) later generalized the angular multigrid to 2-D, but it was found that the method was unstable with sufficiently forward-peaked mappings between the angular grids. The method was stabilized via a filtering technique based on diffusion operators, but this filtering also degraded the effectiveness of the overall scheme. The spectral radius was not bounded away from unity in the Fokker-Planck limit, although the method remained more effective than DSA. The purpose of this article is to recast the multidimensional PAM angular multigrid method without the filtering as an Sn preconditioner and use it in conjunction with the Generalized Minimal RESidual (GMRES) Krylov method. The approach ensures stability and our computational results demonstrate that it is also significantly more efficient than an analogous DSA-preconditioned Krylov method.

Efficient block preconditioned eigensolvers for linear response time-dependent density functional theory

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

Vecharynski, Eugene; Brabec, Jiri; Shao, Meiyue

We present two efficient iterative algorithms for solving the linear response eigen- value problem arising from the time dependent density functional theory. Although the matrix to be diagonalized is nonsymmetric, it has a special structure that can be exploited to save both memory and floating point operations. In particular, the nonsymmetric eigenvalue problem can be transformed into a product eigenvalue problem that is self-adjoint with respect to a K-inner product. This product eigenvalue problem can be solved efficiently by a modified Davidson algorithm and a modified locally optimal block preconditioned conjugate gradient (LOBPCG) algorithm that make use of the K-innermore » product. The solution of the product eigenvalue problem yields one component of the eigenvector associated with the original eigenvalue problem. However, the other component of the eigenvector can be easily recovered in a postprocessing procedure. Therefore, the algorithms we present here are more efficient than existing algorithms that try to approximate both components of the eigenvectors simultaneously. The efficiency of the new algorithms is demonstrated by numerical examples.« less

Effects of Ordering Strategies and Programming Paradigms on Sparse Matrix Computations

NASA Technical Reports Server (NTRS)

Oliker, Leonid; Li, Xiaoye; Husbands, Parry; Biswas, Rupak; Biegel, Bryan (Technical Monitor)

2002-01-01

The Conjugate Gradient (CG) algorithm is perhaps the best-known iterative technique to solve sparse linear systems that are symmetric and positive definite. For systems that are ill-conditioned, it is often necessary to use a preconditioning technique. In this paper, we investigate the effects of various ordering and partitioning strategies on the performance of parallel CG and ILU(O) preconditioned CG (PCG) using different programming paradigms and architectures. Results show that for this class of applications: ordering significantly improves overall performance on both distributed and distributed shared-memory systems, that cache reuse may be more important than reducing communication, that it is possible to achieve message-passing performance using shared-memory constructs through careful data ordering and distribution, and that a hybrid MPI+OpenMP paradigm increases programming complexity with little performance gains. A implementation of CG on the Cray MTA does not require special ordering or partitioning to obtain high efficiency and scalability, giving it a distinct advantage for adaptive applications; however, it shows limited scalability for PCG due to a lack of thread level parallelism.

A fast Chebyshev method for simulating flexible-wing propulsion

NASA Astrophysics Data System (ADS)

Moore, M. Nicholas J.

2017-09-01

We develop a highly efficient numerical method to simulate small-amplitude flapping propulsion by a flexible wing in a nearly inviscid fluid. We allow the wing's elastic modulus and mass density to vary arbitrarily, with an eye towards optimizing these distributions for propulsive performance. The method to determine the wing kinematics is based on Chebyshev collocation of the 1D beam equation as coupled to the surrounding 2D fluid flow. Through small-amplitude analysis of the Euler equations (with trailing-edge vortex shedding), the complete hydrodynamics can be represented by a nonlocal operator that acts on the 1D wing kinematics. A class of semi-analytical solutions permits fast evaluation of this operator with O (Nlog ⁡ N) operations, where N is the number of collocation points on the wing. This is in contrast to the minimum O (N2) cost of a direct 2D fluid solver. The coupled wing-fluid problem is thus recast as a PDE with nonlocal operator, which we solve using a preconditioned iterative method. These techniques yield a solver of near-optimal complexity, O (Nlog ⁡ N) , allowing one to rapidly search the infinite-dimensional parameter space of all possible material distributions and even perform optimization over this space.

Hessian-based norm regularization for image restoration with biomedical applications.

PubMed

Lefkimmiatis, Stamatios; Bourquard, Aurélien; Unser, Michael

2012-03-01

We present nonquadratic Hessian-based regularization methods that can be effectively used for image restoration problems in a variational framework. Motivated by the great success of the total-variation (TV) functional, we extend it to also include second-order differential operators. Specifically, we derive second-order regularizers that involve matrix norms of the Hessian operator. The definition of these functionals is based on an alternative interpretation of TV that relies on mixed norms of directional derivatives. We show that the resulting regularizers retain some of the most favorable properties of TV, i.e., convexity, homogeneity, rotation, and translation invariance, while dealing effectively with the staircase effect. We further develop an efficient minimization scheme for the corresponding objective functions. The proposed algorithm is of the iteratively reweighted least-square type and results from a majorization-minimization approach. It relies on a problem-specific preconditioned conjugate gradient method, which makes the overall minimization scheme very attractive since it can be applied effectively to large images in a reasonable computational time. We validate the overall proposed regularization framework through deblurring experiments under additive Gaussian noise on standard and biomedical images.

M-step preconditioned conjugate gradient methods

NASA Technical Reports Server (NTRS)

Adams, L.

1983-01-01

Preconditioned conjugate gradient methods for solving sparse symmetric and positive finite systems of linear equations are described. Necessary and sufficient conditions are given for when these preconditioners can be used and an analysis of their effectiveness is given. Efficient computer implementations of these methods are discussed and results on the CYBER 203 and the Finite Element Machine under construction at NASA Langley Research Center are included.

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

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

Efficient Multi-Stage Time Marching for Viscous Flows via Local Preconditioning

NASA Technical Reports Server (NTRS)

Kleb, William L.; Wood, William A.; vanLeer, Bram

1999-01-01

A new method has been developed to accelerate the convergence of explicit time-marching, laminar, Navier-Stokes codes through the combination of local preconditioning and multi-stage time marching optimization. Local preconditioning is a technique to modify the time-dependent equations so that all information moves or decays at nearly the same rate, thus relieving the stiffness for a system of equations. Multi-stage time marching can be optimized by modifying its coefficients to account for the presence of viscous terms, allowing larger time steps. We show it is possible to optimize the time marching scheme for a wide range of cell Reynolds numbers for the scalar advection-diffusion equation, and local preconditioning allows this optimization to be applied to the Navier-Stokes equations. Convergence acceleration of the new method is demonstrated through numerical experiments with circular advection and laminar boundary-layer flow over a flat plate.

Sound transmission through a poroelastic layered panel

NASA Astrophysics Data System (ADS)

Nagler, Loris; Rong, Ping; Schanz, Martin; von Estorff, Otto

2014-04-01

Multi-layered panels are often used to improve the acoustics in cars, airplanes, rooms, etc. For such an application these panels include porous and/or fibrous layers. The proposed numerical method is an approach to simulate the acoustical behavior of such multi-layered panels. The model assumes plate-like structures and, hence, combines plate theories for the different layers. The poroelastic layer is modelled with a recently developed plate theory. This theory uses a series expansion in thickness direction with subsequent analytical integration in this direction to reduce the three dimensions to two. The same idea is used to model either air gaps or fibrous layers. The latter are modeled as equivalent fluid and can be handled like an air gap, i.e., a kind of `air plate' is used. The coupling of the layers is done by using the series expansion to express the continuity conditions on the surfaces of the plates. The final system is solved with finite elements, where domain decomposition techniques in combination with preconditioned iterative solvers are applied to solve the final system of equations. In a large frequency range, the comparison with measurements shows very good agreement. From the numerical solution process it can be concluded that different preconditioners for the different layers are necessary. A reuse of the Krylov subspace of the iterative solvers pays if several excitations have to be computed but not that much in the loop over the frequencies.

Large-scale computation of incompressible viscous flow by least-squares finite element method

NASA Technical Reports Server (NTRS)

Jiang, Bo-Nan; Lin, T. L.; Povinelli, Louis A.

1993-01-01

The least-squares finite element method (LSFEM) based on the velocity-pressure-vorticity formulation is applied to large-scale/three-dimensional steady incompressible Navier-Stokes problems. This method can accommodate equal-order interpolations and results in symmetric, positive definite algebraic system which can be solved effectively by simple iterative methods. The first-order velocity-Bernoulli function-vorticity formulation for incompressible viscous flows is also tested. For three-dimensional cases, an additional compatibility equation, i.e., the divergence of the vorticity vector should be zero, is included to make the first-order system elliptic. The simple substitution of the Newton's method is employed to linearize the partial differential equations, the LSFEM is used to obtain discretized equations, and the system of algebraic equations is solved using the Jacobi preconditioned conjugate gradient method which avoids formation of either element or global matrices (matrix-free) to achieve high efficiency. To show the validity of this scheme for large-scale computation, we give numerical results for 2D driven cavity problem at Re = 10000 with 408 x 400 bilinear elements. The flow in a 3D cavity is calculated at Re = 100, 400, and 1,000 with 50 x 50 x 50 trilinear elements. The Taylor-Goertler-like vortices are observed for Re = 1,000.

Orderings for conjugate gradient preconditionings

NASA Technical Reports Server (NTRS)

Ortega, James M.

1991-01-01

The effect of orderings on the rate of convergence of the conjugate gradient method with SSOR or incomplete Cholesky preconditioning is examined. Some results also are presented that help to explain why red/black ordering gives an inferior rate of convergence.

Crustal wavespeed structure of North Texas and Oklahoma based on ambient noise cross-correlation functions and adjoint tomography

NASA Astrophysics Data System (ADS)

Zhu, Hejun

2018-04-01

Recently, seismologists observed increasing seismicity in North Texas and Oklahoma. Based on seismic observations and other geophysical measurements, numerous studies suggested links between the increasing seismicity and wastewater injection during unconventional oil and gas exploration. To better monitor seismic events and investigate their triggering mechanisms, we need an accurate 3D crustal wavespeed model for the study region. Considering the uneven distribution of earthquakes in this area, seismic tomography with local earthquake records have difficulties achieving even illumination. To overcome this limitation, in this study, ambient noise cross-correlation functions are used to constrain subsurface variations in wavespeeds. I use adjoint tomography to iteratively fit frequency-dependent phase differences between observed and predicted band-limited Green's functions. The spectral-element method is used to numerically calculate the band-limited Green's functions and the adjoint method is used to calculate misfit gradients with respect to wavespeeds. Twenty five preconditioned conjugate gradient iterations are used to update model parameters and minimize data misfits. Features in the new crustal model TO25 correlates well with geological provinces in the study region, including the Llano uplift, the Anadarko basin and the Ouachita orogenic front, etc. In addition, there are relatively good correlations between seismic results with gravity and magnetic observations. This new crustal model can be used to better constrain earthquake source parameters in North Texas and Oklahoma, such as epicenter location as well as moment tensor solutions, which are important for investigating triggering mechanisms between these induced earthquakes and unconventional oil and gas exploration activities.

A numerical study of steady crystal growth in a vertical Bridgman device

NASA Astrophysics Data System (ADS)

Jalics, Miklos Kalman

Electronics based on semiconductors creates an enormous demand for high quality semiconductor single crystals. The vertical Bridgman device is commonly used for growing single crystals for a variety of materials such as GaAs, InP and HgCdTe. A mathematical model is presented for steady crystal growth under conditions where crystal growth is determined strictly by heat transfer. The ends of the ampoule are chosen far away from the insulation zone to allow for steady growth. A numerical solution is sought for this mathematical model. The equations are transformed into a rectangular geometry and appropriate finite difference techniques are applied on the transformed equations. Newton's method solves the nonlinear problem. To improve efficiency GMRES with preconditioning is used to compute the Newton iterates. The numerical results are used to compare with two current asymptotic theories that assume small Biot numbers. Results indicate that one of the asymptotic theories is accurate for even moderate Biot numbers.

Function-Space-Based Solution Scheme for the Size-Modified Poisson-Boltzmann Equation in Full-Potential DFT.

PubMed

Ringe, Stefan; Oberhofer, Harald; Hille, Christoph; Matera, Sebastian; Reuter, Karsten

2016-08-09

The size-modified Poisson-Boltzmann (MPB) equation is an efficient implicit solvation model which also captures electrolytic solvent effects. It combines an account of the dielectric solvent response with a mean-field description of solvated finite-sized ions. We present a general solution scheme for the MPB equation based on a fast function-space-oriented Newton method and a Green's function preconditioned iterative linear solver. In contrast to popular multigrid solvers, this approach allows us to fully exploit specialized integration grids and optimized integration schemes. We describe a corresponding numerically efficient implementation for the full-potential density-functional theory (DFT) code FHI-aims. We show that together with an additional Stern layer correction the DFT+MPB approach can describe the mean activity coefficient of a KCl aqueous solution over a wide range of concentrations. The high sensitivity of the calculated activity coefficient on the employed ionic parameters thereby suggests to use extensively tabulated experimental activity coefficients of salt solutions for a systematic parametrization protocol.

A Comparison of Solver Performance for Complex Gastric Electrophysiology Models

PubMed Central

Sathar, Shameer; Cheng, Leo K.; Trew, Mark L.

2016-01-01

Computational techniques for solving systems of equations arising in gastric electrophysiology have not been studied for efficient solution process. We present a computationally challenging problem of simulating gastric electrophysiology in anatomically realistic stomach geometries with multiple intracellular and extracellular domains. The multiscale nature of the problem and mesh resolution required to capture geometric and functional features necessitates efficient solution methods if the problem is to be tractable. In this study, we investigated and compared several parallel preconditioners for the linear systems arising from tetrahedral discretisation of electrically isotropic and anisotropic problems, with and without stimuli. The results showed that the isotropic problem was computationally less challenging than the anisotropic problem and that the application of extracellular stimuli increased workload considerably. Preconditioning based on block Jacobi and algebraic multigrid solvers were found to have the best overall solution times and least iteration counts, respectively. The algebraic multigrid preconditioner would be expected to perform better on large problems. PMID:26736543

Adaptive truncation of matrix decompositions and efficient estimation of NMR relaxation distributions

NASA Astrophysics Data System (ADS)

Teal, Paul D.; Eccles, Craig

2015-04-01

The two most successful methods of estimating the distribution of nuclear magnetic resonance relaxation times from two dimensional data are data compression followed by application of the Butler-Reeds-Dawson algorithm, and a primal-dual interior point method using preconditioned conjugate gradient. Both of these methods have previously been presented using a truncated singular value decomposition of matrices representing the exponential kernel. In this paper it is shown that other matrix factorizations are applicable to each of these algorithms, and that these illustrate the different fundamental principles behind the operation of the algorithms. These are the rank-revealing QR (RRQR) factorization and the LDL factorization with diagonal pivoting, also known as the Bunch-Kaufman-Parlett factorization. It is shown that both algorithms can be improved by adaptation of the truncation as the optimization process progresses, improving the accuracy as the optimal value is approached. A variation on the interior method viz, the use of barrier function instead of the primal-dual approach, is found to offer considerable improvement in terms of speed and reliability. A third type of algorithm, related to the algorithm known as Fast iterative shrinkage-thresholding algorithm, is applied to the problem. This method can be efficiently formulated without the use of a matrix decomposition.

Preconditioning for Numerical Simulation of Low Mach Number Three-Dimensional Viscous Turbomachinery Flows

NASA Technical Reports Server (NTRS)

Tweedt, Daniel L.; Chima, Rodrick V.; Turkel, Eli

1997-01-01

A preconditioning scheme has been implemented into a three-dimensional viscous computational fluid dynamics code for turbomachine blade rows. The preconditioning allows the code, originally developed for simulating compressible flow fields, to be applied to nearly-incompressible, low Mach number flows. A brief description is given of the compressible Navier-Stokes equations for a rotating coordinate system, along with the preconditioning method employed. Details about the conservative formulation of artificial dissipation are provided, and different artificial dissipation schemes are discussed and compared. The preconditioned code was applied to a well-documented case involving the NASA large low-speed centrifugal compressor for which detailed experimental data are available for comparison. Performance and flow field data are compared for the near-design operating point of the compressor, with generally good agreement between computation and experiment. Further, significant differences between computational results for the different numerical implementations, revealing different levels of solution accuracy, are discussed.

On polynomial preconditioning for indefinite Hermitian matrices

NASA Technical Reports Server (NTRS)

Freund, Roland W.

1989-01-01

The minimal residual method is studied combined with polynomial preconditioning for solving large linear systems (Ax = b) with indefinite Hermitian coefficient matrices (A). The standard approach for choosing the polynomial preconditioners leads to preconditioned systems which are positive definite. Here, a different strategy is studied which leaves the preconditioned coefficient matrix indefinite. More precisely, the polynomial preconditioner is designed to cluster the positive, resp. negative eigenvalues of A around 1, resp. around some negative constant. In particular, it is shown that such indefinite polynomial preconditioners can be obtained as the optimal solutions of a certain two parameter family of Chebyshev approximation problems. Some basic results are established for these approximation problems and a Remez type algorithm is sketched for their numerical solution. The problem of selecting the parameters such that the resulting indefinite polynomial preconditioners speeds up the convergence of minimal residual method optimally is also addressed. An approach is proposed based on the concept of asymptotic convergence factors. Finally, some numerical examples of indefinite polynomial preconditioners are given.

Preconditioned characteristic boundary conditions based on artificial compressibility method for solution of incompressible flows

NASA Astrophysics Data System (ADS)

Hejranfar, Kazem; Parseh, Kaveh

2017-09-01

The preconditioned characteristic boundary conditions based on the artificial compressibility (AC) method are implemented at artificial boundaries for the solution of two- and three-dimensional incompressible viscous flows in the generalized curvilinear coordinates. The compatibility equations and the corresponding characteristic variables (or the Riemann invariants) are mathematically derived and then applied as suitable boundary conditions in a high-order accurate incompressible flow solver. The spatial discretization of the resulting system of equations is carried out by the fourth-order compact finite-difference (FD) scheme. In the preconditioning applied here, the value of AC parameter in the flow field and also at the far-field boundary is automatically calculated based on the local flow conditions to enhance the robustness and performance of the solution algorithm. The code is fully parallelized using the Concurrency Runtime standard and Parallel Patterns Library (PPL) and its performance on a multi-core CPU is analyzed. The incompressible viscous flows around a 2-D circular cylinder, a 2-D NACA0012 airfoil and also a 3-D wavy cylinder are simulated and the accuracy and performance of the preconditioned characteristic boundary conditions applied at the far-field boundaries are evaluated in comparison to the simplified boundary conditions and the non-preconditioned characteristic boundary conditions. It is indicated that the preconditioned characteristic boundary conditions considerably improve the convergence rate of the solution of incompressible flows compared to the other boundary conditions and the computational costs are significantly decreased.

Finding Chemical Reaction Paths with a Multilevel Preconditioning Protocol

PubMed Central

2015-01-01

Finding transition paths for chemical reactions can be computationally costly owing to the level of quantum-chemical theory needed for accuracy. Here, we show that a multilevel preconditioning scheme that was recently introduced (Tempkin et al. J. Chem. Phys.2014, 140, 184114) can be used to accelerate quantum-chemical string calculations. We demonstrate the method by finding minimum-energy paths for two well-characterized reactions: tautomerization of malonaldehyde and Claissen rearrangement of chorismate to prephanate. For these reactions, we show that preconditioning density functional theory (DFT) with a semiempirical method reduces the computational cost for reaching a converged path that is an optimum under DFT by several fold. The approach also shows promise for free energy calculations when thermal noise can be controlled. PMID:25516726

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.

MPSalsa Version 1.5: A Finite Element Computer Program for Reacting Flow Problems: Part 1 - Theoretical Development

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

Devine, K.D.; Hennigan, G.L.; Hutchinson, S.A.

1999-01-01

The theoretical background for the finite element computer program, MPSalsa Version 1.5, is presented in detail. MPSalsa is designed to solve laminar or turbulent low Mach number, two- or three-dimensional incompressible and variable density reacting fluid flows on massively parallel computers, using a Petrov-Galerkin finite element formulation. The code has the capability to solve coupled fluid flow (with auxiliary turbulence equations), heat transport, multicomponent species transport, and finite-rate chemical reactions, and to solve coupled multiple Poisson or advection-diffusion-reaction equations. The program employs the CHEMKIN library to provide a rigorous treatment of multicomponent ideal gas kinetics and transport. Chemical reactions occurringmore » in the gas phase and on surfaces are treated by calls to CHEMKIN and SURFACE CHEMK3N, respectively. The code employs unstructured meshes, using the EXODUS II finite element database suite of programs for its input and output files. MPSalsa solves both transient and steady flows by using fully implicit time integration, an inexact Newton method and iterative solvers based on preconditioned Krylov methods as implemented in the Aztec. solver library.« less

Performance of fully-coupled algebraic multigrid preconditioners for large-scale VMS resistive MHD

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

Lin, P. T.; Shadid, J. N.; Hu, J. J.

Here, we explore the current performance and scaling of a fully-implicit stabilized unstructured finite element (FE) variational multiscale (VMS) capability for large-scale simulations of 3D incompressible resistive magnetohydrodynamics (MHD). The large-scale linear systems that are generated by a Newton nonlinear solver approach are iteratively solved by preconditioned Krylov subspace methods. The efficiency of this approach is critically dependent on the scalability and performance of the algebraic multigrid preconditioner. Our study considers the performance of the numerical methods as recently implemented in the second-generation Trilinos implementation that is 64-bit compliant and is not limited by the 32-bit global identifiers of themore » original Epetra-based Trilinos. The study presents representative results for a Poisson problem on 1.6 million cores of an IBM Blue Gene/Q platform to demonstrate very large-scale parallel execution. Additionally, results for a more challenging steady-state MHD generator and a transient solution of a benchmark MHD turbulence calculation for the full resistive MHD system are also presented. These results are obtained on up to 131,000 cores of a Cray XC40 and one million cores of a BG/Q system.« less

Performance of fully-coupled algebraic multigrid preconditioners for large-scale VMS resistive MHD

DOE PAGES

Lin, P. T.; Shadid, J. N.; Hu, J. J.; ...

2017-11-06

Here, we explore the current performance and scaling of a fully-implicit stabilized unstructured finite element (FE) variational multiscale (VMS) capability for large-scale simulations of 3D incompressible resistive magnetohydrodynamics (MHD). The large-scale linear systems that are generated by a Newton nonlinear solver approach are iteratively solved by preconditioned Krylov subspace methods. The efficiency of this approach is critically dependent on the scalability and performance of the algebraic multigrid preconditioner. Our study considers the performance of the numerical methods as recently implemented in the second-generation Trilinos implementation that is 64-bit compliant and is not limited by the 32-bit global identifiers of themore » original Epetra-based Trilinos. The study presents representative results for a Poisson problem on 1.6 million cores of an IBM Blue Gene/Q platform to demonstrate very large-scale parallel execution. Additionally, results for a more challenging steady-state MHD generator and a transient solution of a benchmark MHD turbulence calculation for the full resistive MHD system are also presented. These results are obtained on up to 131,000 cores of a Cray XC40 and one million cores of a BG/Q system.« less

An implicit numerical scheme for the simulation of internal viscous flows on unstructured grids

NASA Technical Reports Server (NTRS)

Jorgenson, Philip C. E.; Pletcher, Richard H.

1994-01-01

The Navier-Stokes equations are solved numerically for two-dimensional steady viscous laminar flows. The grids are generated based on the method of Delaunay triangulation. A finite-volume approach is used to discretize the conservation law form of the compressible flow equations written in terms of primitive variables. A preconditioning matrix is added to the equations so that low Mach number flows can be solved economically. The equations are time marched using either an implicit Gauss-Seidel iterative procedure or a solver based on a conjugate gradient like method. A four color scheme is employed to vectorize the block Gauss-Seidel relaxation procedure. This increases the memory requirements minimally and decreases the computer time spent solving the resulting system of equations substantially. A factor of 7.6 speed up in the matrix solver is typical for the viscous equations. Numerical results are obtained for inviscid flow over a bump in a channel at subsonic and transonic conditions for validation with structured solvers. Viscous results are computed for developing flow in a channel, a symmetric sudden expansion, periodic tandem cylinders in a cross-flow, and a four-port valve. Comparisons are made with available results obtained by other investigators.

Preconditioning methods influence tumor property in an orthotopic bladder urothelial carcinoma rat model

PubMed Central

MIYAZAKI, KOZO; MORIMOTO, YUJI; NISHIYAMA, NOBUHIRO; SATOH, HIROYUKI; TANAKA, MASAMITSU; SHINOMIYA, NARIYOSHI; ITO, KEIICHI

2014-01-01

Urothelial carcinoma (UC) is an extremely common type of cancer that occurs in the bladder. It has a particularly high rate of recurrence. Therefore, preclinical studies using animal models are essential to determine effective forms of treatment. In the present study, in order to establish an orthotopic bladder UC animal model with clinical relevance, the effects of preconditioning methods on properties of the developed tumor were evaluated. The bladder cavity was pretreated with phosphate-buffered saline (PBS), acid-base, trypsin (TRY) or poly (L-lysine) (PLL) and then rat UC cells (AY-27) (4×106 cells) were inoculated. The results demonstrated that, two weeks later, the tumorigenic rate (88%) and tumor count (2.3 per rat) were not significantly different among the preconditioning methods, whereas tumor volume and invasion depth into bladder tissue were significantly different. Average tumor volumes were >50 mm3 in the PBS and acid-base-treated groups and <10 mm3 in the TRY- and PLL-treated groups. The percentage of invasive tumors (T2 or more advanced stage) was ∼75% of total tumors in the PBS- and acid-base-treated groups, whereas the percentages were reduced in the TRY- and PLL-treated groups (58 and 32%, respectively). Non-invasive tumors (Ta or T1) accounted for 54% of tumors in the PLL-treated group, which was 2-5-fold higher than the percentages in the remaining groups. Properties of the developed tumor in the rat orthotopic UC model were different depending on preconditioning methods. Therefore, different animal models suitable for a discrete preclinical examination may be established by using the appropriate preconditioning condition. PMID:24649309

Comparison of an algebraic multigrid algorithm to two iterative solvers used for modeling ground water flow and transport

USGS Publications Warehouse

Detwiler, R.L.; Mehl, S.; Rajaram, H.; Cheung, W.W.

2002-01-01

Numerical solution of large-scale ground water flow and transport problems is often constrained by the convergence behavior of the iterative solvers used to solve the resulting systems of equations. We demonstrate the ability of an algebraic multigrid algorithm (AMG) to efficiently solve the large, sparse systems of equations that result from computational models of ground water flow and transport in large and complex domains. Unlike geometric multigrid methods, this algorithm is applicable to problems in complex flow geometries, such as those encountered in pore-scale modeling of two-phase flow and transport. We integrated AMG into MODFLOW 2000 to compare two- and three-dimensional flow simulations using AMG to simulations using PCG2, a preconditioned conjugate gradient solver that uses the modified incomplete Cholesky preconditioner and is included with MODFLOW 2000. CPU times required for convergence with AMG were up to 140 times faster than those for PCG2. The cost of this increased speed was up to a nine-fold increase in required random access memory (RAM) for the three-dimensional problems and up to a four-fold increase in required RAM for the two-dimensional problems. We also compared two-dimensional numerical simulations of steady-state transport using AMG and the generalized minimum residual method with an incomplete LU-decomposition preconditioner. For these transport simulations, AMG yielded increased speeds of up to 17 times with only a 20% increase in required RAM. The ability of AMG to solve flow and transport problems in large, complex flow systems and its ready availability make it an ideal solver for use in both field-scale and pore-scale modeling.

Approximation of the Newton Step by a Defect Correction Process

NASA Technical Reports Server (NTRS)

Arian, E.; Batterman, A.; Sachs, E. W.

1999-01-01

In this paper, an optimal control problem governed by a partial differential equation is considered. The Newton step for this system can be computed by solving a coupled system of equations. To do this efficiently with an iterative defect correction process, a modifying operator is introduced into the system. This operator is motivated by local mode analysis. The operator can be used also for preconditioning in Generalized Minimum Residual (GMRES). We give a detailed convergence analysis for the defect correction process and show the derivation of the modifying operator. Numerical tests are done on the small disturbance shape optimization problem in two dimensions for the defect correction process and for GMRES.

Technical note: Avoiding the direct inversion of the numerator relationship matrix for genotyped animals in single-step genomic best linear unbiased prediction solved with the preconditioned conjugate gradient.

PubMed

Masuda, Y; Misztal, I; Legarra, A; Tsuruta, S; Lourenco, D A L; Fragomeni, B O; Aguilar, I

2017-01-01

This paper evaluates an efficient implementation to multiply the inverse of a numerator relationship matrix for genotyped animals () by a vector (). The computation is required for solving mixed model equations in single-step genomic BLUP (ssGBLUP) with the preconditioned conjugate gradient (PCG). The inverse can be decomposed into sparse matrices that are blocks of the sparse inverse of a numerator relationship matrix () including genotyped animals and their ancestors. The elements of were rapidly calculated with the Henderson's rule and stored as sparse matrices in memory. Implementation of was by a series of sparse matrix-vector multiplications. Diagonal elements of , which were required as preconditioners in PCG, were approximated with a Monte Carlo method using 1,000 samples. The efficient implementation of was compared with explicit inversion of with 3 data sets including about 15,000, 81,000, and 570,000 genotyped animals selected from populations with 213,000, 8.2 million, and 10.7 million pedigree animals, respectively. The explicit inversion required 1.8 GB, 49 GB, and 2,415 GB (estimated) of memory, respectively, and 42 s, 56 min, and 13.5 d (estimated), respectively, for the computations. The efficient implementation required <1 MB, 2.9 GB, and 2.3 GB of memory, respectively, and <1 sec, 3 min, and 5 min, respectively, for setting up. Only <1 sec was required for the multiplication in each PCG iteration for any data sets. When the equations in ssGBLUP are solved with the PCG algorithm, is no longer a limiting factor in the computations.

Finding Chemical Reaction Paths with a Multilevel Preconditioning Protocol

DOE PAGES

Kale, Seyit; Sode, Olaseni; Weare, Jonathan; ...

2014-11-07

Finding transition paths for chemical reactions can be computationally costly owing to the level of quantum-chemical theory needed for accuracy. Here, we show that a multilevel preconditioning scheme that was recently introduced (Tempkin et al. J. Chem. Phys. 2014, 140, 184114) can be used to accelerate quantum-chemical string calculations. We demonstrate the method by finding minimum-energy paths for two well-characterized reactions: tautomerization of malonaldehyde and Claissen rearrangement of chorismate to prephanate. For these reactions, we show that preconditioning density functional theory (DFT) with a semiempirical method reduces the computational cost for reaching a converged path that is an optimum undermore » DFT by several fold. In conclusion, the approach also shows promise for free energy calculations when thermal noise can be controlled.« less

Preconditioning of the background error covariance matrix in data assimilation for the Caspian Sea

NASA Astrophysics Data System (ADS)

Arcucci, Rossella; D'Amore, Luisa; Toumi, Ralf

2017-06-01

Data Assimilation (DA) is an uncertainty quantification technique used for improving numerical forecasted results by incorporating observed data into prediction models. As a crucial point into DA models is the ill conditioning of the covariance matrices involved, it is mandatory to introduce, in a DA software, preconditioning methods. Here we present first studies concerning the introduction of two different preconditioning methods in a DA software we are developing (we named S3DVAR) which implements a Scalable Three Dimensional Variational Data Assimilation model for assimilating sea surface temperature (SST) values collected into the Caspian Sea by using the Regional Ocean Modeling System (ROMS) with observations provided by the Group of High resolution sea surface temperature (GHRSST). We also present the algorithmic strategies we employ.

Flap preconditioning by pressure-controlled cupping in a rat model.

PubMed

Koh, Kyung S; Park, Sung Woo; Oh, Tae Suk; Choi, Jong Woo

2016-08-01

Flap survival is essential for the success of soft-tissue reconstruction. Accordingly, various surgical and medical methods aim to increase flap survival. Because flap survival is affected by the innate vascular supply, traditional preconditioning methods mainly target vasodilatation or vascular reorientation to increase blood flow to the tissue. External stress on the skin, such as an external volume expander or cupping, induces vascular remodeling, and these approaches have been used in the fat grafting field and in traditional Asian medicine. In the present study, we used a rat random-pattern dorsal flap model to study the effectiveness of preconditioning with an externally applied device (cupping) at the flap site that directly applied negative pressure to the skin. The device, the pressure-controlled cupping, is connected to negative pressure vacuum device providing accurate pressure control from 0 mm Hg to -200 mm Hg. Flap surgery was performed after preconditioning under -25 mm Hg suction pressure for 30 min a day for 5 d, followed by 9 d of postoperative observation. Flap survival was assessed as the area of viable tissue and was compared between the preconditioned group and a control group. The preconditioned group showed absolute percentage increase of flap viability relative to the entire flap by 19.0± 7.6% (average 70.1% versus 51.0%). Tissue perfusion of entire flap, evaluated by laser Doppler imaging system, was improved with absolute percentage increase by 24.2± 10.4% (average 77.4% versus 53.1%). Histologic analysis of hematoxylin and eosin, CD31, and Masson-trichrome staining showed increased vascular density in the subdermal plexus and more organized collagen production with hypertrophy of the attached muscle. Our study suggests that flap preconditioning caused by controlled noninvasive suction induces vascular remodeling that increases tissue perfusion and improves flap survival in a rat model. Copyright © 2016 Elsevier Inc. All rights reserved.

Scalable Nonlinear Solvers for Fully Implicit Coupled Nuclear Fuel Modeling. Final Report

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

Cai, Xiao-Chuan; Keyes, David; Yang, Chao

2014-09-29

The focus of the project is on the development and customization of some highly scalable domain decomposition based preconditioning techniques for the numerical solution of nonlinear, coupled systems of partial differential equations (PDEs) arising from nuclear fuel simulations. These high-order PDEs represent multiple interacting physical fields (for example, heat conduction, oxygen transport, solid deformation), each is modeled by a certain type of Cahn-Hilliard and/or Allen-Cahn equations. Most existing approaches involve a careful splitting of the fields and the use of field-by-field iterations to obtain a solution of the coupled problem. Such approaches have many advantages such as ease of implementationmore » since only single field solvers are needed, but also exhibit disadvantages. For example, certain nonlinear interactions between the fields may not be fully captured, and for unsteady problems, stable time integration schemes are difficult to design. In addition, when implemented on large scale parallel computers, the sequential nature of the field-by-field iterations substantially reduces the parallel efficiency. To overcome the disadvantages, fully coupled approaches have been investigated in order to obtain full physics simulations.« less

An optimization-based approach for solving a time-harmonic multiphysical wave problem with higher-order schemes

NASA Astrophysics Data System (ADS)

Mönkölä, Sanna

2013-06-01

This study considers developing numerical solution techniques for the computer simulations of time-harmonic fluid-structure interaction between acoustic and elastic waves. The focus is on the efficiency of an iterative solution method based on a controllability approach and spectral elements. We concentrate on the model, in which the acoustic waves in the fluid domain are modeled by using the velocity potential and the elastic waves in the structure domain are modeled by using displacement. Traditionally, the complex-valued time-harmonic equations are used for solving the time-harmonic problems. Instead of that, we focus on finding periodic solutions without solving the time-harmonic problems directly. The time-dependent equations can be simulated with respect to time until a time-harmonic solution is reached, but the approach suffers from poor convergence. To overcome this challenge, we follow the approach first suggested and developed for the acoustic wave equations by Bristeau, Glowinski, and Périaux. Thus, we accelerate the convergence rate by employing a controllability method. The problem is formulated as a least-squares optimization problem, which is solved with the conjugate gradient (CG) algorithm. Computation of the gradient of the functional is done directly for the discretized problem. A graph-based multigrid method is used for preconditioning the CG algorithm.

On adaptive weighted polynomial preconditioning for Hermitian positive definite matrices

NASA Technical Reports Server (NTRS)

Fischer, Bernd; Freund, Roland W.

1992-01-01

The conjugate gradient algorithm for solving Hermitian positive definite linear systems is usually combined with preconditioning in order to speed up convergence. In recent years, there has been a revival of polynomial preconditioning, motivated by the attractive features of the method on modern architectures. Standard techniques for choosing the preconditioning polynomial are based only on bounds for the extreme eigenvalues. Here a different approach is proposed, which aims at adapting the preconditioner to the eigenvalue distribution of the coefficient matrix. The technique is based on the observation that good estimates for the eigenvalue distribution can be derived after only a few steps of the Lanczos process. This information is then used to construct a weight function for a suitable Chebyshev approximation problem. The solution of this problem yields the polynomial preconditioner. In particular, we investigate the use of Bernstein-Szego weights.

Spectral analysis and multigrid preconditioners for two-dimensional space-fractional diffusion equations

NASA Astrophysics Data System (ADS)

Moghaderi, Hamid; Dehghan, Mehdi; Donatelli, Marco; Mazza, Mariarosa

2017-12-01

Fractional diffusion equations (FDEs) are a mathematical tool used for describing some special diffusion phenomena arising in many different applications like porous media and computational finance. In this paper, we focus on a two-dimensional space-FDE problem discretized by means of a second order finite difference scheme obtained as combination of the Crank-Nicolson scheme and the so-called weighted and shifted Grünwald formula. By fully exploiting the Toeplitz-like structure of the resulting linear system, we provide a detailed spectral analysis of the coefficient matrix at each time step, both in the case of constant and variable diffusion coefficients. Such a spectral analysis has a very crucial role, since it can be used for designing fast and robust iterative solvers. In particular, we employ the obtained spectral information to define a Galerkin multigrid method based on the classical linear interpolation as grid transfer operator and damped-Jacobi as smoother, and to prove the linear convergence rate of the corresponding two-grid method. The theoretical analysis suggests that the proposed grid transfer operator is strong enough for working also with the V-cycle method and the geometric multigrid. On this basis, we introduce two computationally favourable variants of the proposed multigrid method and we use them as preconditioners for Krylov methods. Several numerical results confirm that the resulting preconditioning strategies still keep a linear convergence rate.

Implementation of the SPH Procedure Within the MOOSE Finite Element Framework

NASA Astrophysics Data System (ADS)

Laurier, Alexandre

The goal of this thesis was to implement the SPH homogenization procedure within the MOOSE finite element framework at INL. Before this project, INL relied on DRAGON to do their SPH homogenization which was not flexible enough for their needs. As such, the SPH procedure was implemented for the neutron diffusion equation with the traditional, Selengut and true Selengut normalizations. Another aspect of this research was to derive the SPH corrected neutron transport equations and implement them in the same framework. Following in the footsteps of other articles, this feature was implemented and tested successfully with both the PN and S N transport calculation schemes. Although the results obtained for the power distribution in PWR assemblies show no advantages over the use of the SPH diffusion equation, we believe the inclusion of this transport correction will allow for better results in cases where either P N or SN are required. An additional aspect of this research was the implementation of a novel way of solving the non-linear SPH problem. Traditionally, this was done through a Picard, fixed-point iterative process whereas the new implementation relies on MOOSE's Preconditioned Jacobian-Free Newton Krylov (PJFNK) method to allow for a direct solution to the non-linear problem. This novel implementation showed a decrease in calculation time by a factor reaching 50 and generated SPH factors that correspond to those obtained through a fixed-point iterative process with a very tight convergence criteria: epsilon < 10-8. The use of the PJFNK SPH procedure also allows to reach convergence in problems containing important reflector regions and void boundary conditions, something that the traditional SPH method has never been able to achieve. At times when the PJFNK method cannot reach convergence to the SPH problem, a hybrid method is used where by the traditional SPH iteration forces the initial condition to be within the radius of convergence of the Newton method. This new method was tested on a simplified model of INL's TREAT reactor, a problem that includes very important graphite reflector regions as well as vacuum boundary conditions with great success. To demonstrate the power of PJFNK SPH on a more common case, the correction was applied to a simplified PWR reactor core from the BEAVRS benchmark that included 15 assemblies and the water reflector to obtain very good results. This opens up the possibility to apply the SPH correction to full reactor cores in order to reduce homogenization errors for use in transient or multi-physics calculations.

Performance of a parallel thermal-hydraulics code TEMPEST

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

Fann, G.I.; Trent, D.S.

The authors describe the parallelization of the Tempest thermal-hydraulics code. The serial version of this code is used for production quality 3-D thermal-hydraulics simulations. Good speedup was obtained with a parallel diagonally preconditioned BiCGStab non-symmetric linear solver, using a spatial domain decomposition approach for the semi-iterative pressure-based and mass-conserved algorithm. The test case used here to illustrate the performance of the BiCGStab solver is a 3-D natural convection problem modeled using finite volume discretization in cylindrical coordinates. The BiCGStab solver replaced the LSOR-ADI method for solving the pressure equation in TEMPEST. BiCGStab also solves the coupled thermal energy equation. Scalingmore » performance of 3 problem sizes (221220 nodes, 358120 nodes, and 701220 nodes) are presented. These problems were run on 2 different parallel machines: IBM-SP and SGI PowerChallenge. The largest problem attains a speedup of 68 on an 128 processor IBM-SP. In real terms, this is over 34 times faster than the fastest serial production time using the LSOR-ADI solver.« less

Numerical Solution of the Gyrokinetic Poisson Equation in TEMPEST

NASA Astrophysics Data System (ADS)

Dorr, Milo; Cohen, Bruce; Cohen, Ronald; Dimits, Andris; Hittinger, Jeffrey; Kerbel, Gary; Nevins, William; Rognlien, Thomas; Umansky, Maxim; Xiong, Andrew; Xu, Xueqiao

2006-10-01

The gyrokinetic Poisson (GKP) model in the TEMPEST continuum gyrokinetic edge plasma code yields the electrostatic potential due to the charge density of electrons and an arbitrary number of ion species including the effects of gyroaveraging in the limit kρ1. The TEMPEST equations are integrated as a differential algebraic system involving a nonlinear system solve via Newton-Krylov iteration. The GKP preconditioner block is inverted using a multigrid preconditioned conjugate gradient (CG) algorithm. Electrons are treated as kinetic or adiabatic. The Boltzmann relation in the adiabatic option employs flux surface averaging to maintain neutrality within field lines and is solved self-consistently with the GKP equation. A decomposition procedure circumvents the near singularity of the GKP Jacobian block that otherwise degrades CG convergence.

Aerodynamic Shape Sensitivity Analysis and Design Optimization of Complex Configurations Using Unstructured Grids

NASA Technical Reports Server (NTRS)

Taylor, Arthur C., III; Newman, James C., III; Barnwell, Richard W.

1997-01-01

A three-dimensional unstructured grid approach to aerodynamic shape sensitivity analysis and design optimization has been developed and is extended to model geometrically complex configurations. The advantage of unstructured grids (when compared with a structured-grid approach) is their inherent ability to discretize irregularly shaped domains with greater efficiency and less effort. Hence, this approach is ideally suited for geometrically complex configurations of practical interest. In this work the nonlinear Euler equations are solved using an upwind, cell-centered, finite-volume scheme. The discrete, linearized systems which result from this scheme are solved iteratively by a preconditioned conjugate-gradient-like algorithm known as GMRES for the two-dimensional geometry and a Gauss-Seidel algorithm for the three-dimensional; similar procedures are used to solve the accompanying linear aerodynamic sensitivity equations in incremental iterative form. As shown, this particular form of the sensitivity equation makes large-scale gradient-based aerodynamic optimization possible by taking advantage of memory efficient methods to construct exact Jacobian matrix-vector products. Simple parameterization techniques are utilized for demonstrative purposes. Once the surface has been deformed, the unstructured grid is adapted by considering the mesh as a system of interconnected springs. Grid sensitivities are obtained by differentiating the surface parameterization and the grid adaptation algorithms with ADIFOR (which is an advanced automatic-differentiation software tool). To demonstrate the ability of this procedure to analyze and design complex configurations of practical interest, the sensitivity analysis and shape optimization has been performed for a two-dimensional high-lift multielement airfoil and for a three-dimensional Boeing 747-200 aircraft.

Classical and all-floating FETI methods for the simulation of arterial tissues

PubMed Central

Augustin, Christoph M.; Holzapfel, Gerhard A.; Steinbach, Olaf

2015-01-01

High-resolution and anatomically realistic computer models of biological soft tissues play a significant role in the understanding of the function of cardiovascular components in health and disease. However, the computational effort to handle fine grids to resolve the geometries as well as sophisticated tissue models is very challenging. One possibility to derive a strongly scalable parallel solution algorithm is to consider finite element tearing and interconnecting (FETI) methods. In this study we propose and investigate the application of FETI methods to simulate the elastic behavior of biological soft tissues. As one particular example we choose the artery which is – as most other biological tissues – characterized by anisotropic and nonlinear material properties. We compare two specific approaches of FETI methods, classical and all-floating, and investigate the numerical behavior of different preconditioning techniques. In comparison to classical FETI, the all-floating approach has not only advantages concerning the implementation but in many cases also concerning the convergence of the global iterative solution method. This behavior is illustrated with numerical examples. We present results of linear elastic simulations to show convergence rates, as expected from the theory, and results from the more sophisticated nonlinear case where we apply a well-known anisotropic model to the realistic geometry of an artery. Although the FETI methods have a great applicability on artery simulations we will also discuss some limitations concerning the dependence on material parameters. PMID:26751957

Impact of remote ischemic preconditioning on wound healing in small bowel anastomoses

PubMed Central

Holzner, Philipp Anton; Kulemann, Birte; Kuesters, Simon; Timme, Sylvia; Hoeppner, Jens; Hopt, Ulrich Theodor; Marjanovic, Goran

2011-01-01

AIM: To investigate the influence of remote ischemic preconditioning (RIPC) on anastomotic integrity. METHODS: Sixty male Wistar rats were randomized to six groups. The control group (n = 10) had an end-to-end ileal anastomosis without RIPC. The preconditioned groups (n = 34) varied in time of ischemia and time of reperfusion. One group received the amino acid L-arginine before constructing the anastomosis (n = 9). On postoperative day 4, the rats were re-laparotomized, and bursting pressure, hydroxyproline concentration, intra-abdominal adhesions, and a histological score concerning the mucosal ischemic injury were collected. The data are given as median (range). RESULTS: On postoperative day 4, median bursting pressure was 124 mmHg (60-146 mmHg) in the control group. The experimental groups did not show a statistically significant difference (P > 0.05). Regarding the hydroxyproline concentration, we did not find any significant variation in the experimental groups. We detected significantly less mucosal injury in the RIPC groups. Furthermore, we assessed more extensive intra-abdominal adhesions in the preconditioned groups than in the control group. CONCLUSION: RIPC directly before performing small bowel anastomosis does not affect anastomotic stability in the early period, as seen in ischemic preconditioning. PMID:21455330

Comparing implementations of penalized weighted least-squares sinogram restoration.

PubMed

Forthmann, Peter; Koehler, Thomas; Defrise, Michel; La Riviere, Patrick

2010-11-01

A CT scanner measures the energy that is deposited in each channel of a detector array by x rays that have been partially absorbed on their way through the object. The measurement process is complex and quantitative measurements are always and inevitably associated with errors, so CT data must be preprocessed prior to reconstruction. In recent years, the authors have formulated CT sinogram preprocessing as a statistical restoration problem in which the goal is to obtain the best estimate of the line integrals needed for reconstruction from the set of noisy, degraded measurements. The authors have explored both penalized Poisson likelihood (PL) and penalized weighted least-squares (PWLS) objective functions. At low doses, the authors found that the PL approach outperforms PWLS in terms of resolution-noise tradeoffs, but at standard doses they perform similarly. The PWLS objective function, being quadratic, is more amenable to computational acceleration than the PL objective. In this work, the authors develop and compare two different methods for implementing PWLS sinogram restoration with the hope of improving computational performance relative to PL in the standard-dose regime. Sinogram restoration is still significant in the standard-dose regime since it can still outperform standard approaches and it allows for correction of effects that are not usually modeled in standard CT preprocessing. The authors have explored and compared two implementation strategies for PWLS sinogram restoration: (1) A direct matrix-inversion strategy based on the closed-form solution to the PWLS optimization problem and (2) an iterative approach based on the conjugate-gradient algorithm. Obtaining optimal performance from each strategy required modifying the naive off-the-shelf implementations of the algorithms to exploit the particular symmetry and sparseness of the sinogram-restoration problem. For the closed-form approach, the authors subdivided the large matrix inversion into smaller coupled problems and exploited sparseness to minimize matrix operations. For the conjugate-gradient approach, the authors exploited sparseness and preconditioned the problem to speed up convergence. All methods produced qualitatively and quantitatively similar images as measured by resolution-variance tradeoffs and difference images. Despite the acceleration strategies, the direct matrix-inversion approach was found to be uncompetitive with iterative approaches, with a computational burden higher by an order of magnitude or more. The iterative conjugate-gradient approach, however, does appear promising, with computation times half that of the authors' previous penalized-likelihood implementation. Iterative conjugate-gradient based PWLS sinogram restoration with careful matrix optimizations has computational advantages over direct matrix PWLS inversion and over penalized-likelihood sinogram restoration and can be considered a good alternative in standard-dose regimes.

Comparing implementations of penalized weighted least-squares sinogram restoration

PubMed Central

Forthmann, Peter; Koehler, Thomas; Defrise, Michel; La Riviere, Patrick

2010-01-01

Purpose: A CT scanner measures the energy that is deposited in each channel of a detector array by x rays that have been partially absorbed on their way through the object. The measurement process is complex and quantitative measurements are always and inevitably associated with errors, so CT data must be preprocessed prior to reconstruction. In recent years, the authors have formulated CT sinogram preprocessing as a statistical restoration problem in which the goal is to obtain the best estimate of the line integrals needed for reconstruction from the set of noisy, degraded measurements. The authors have explored both penalized Poisson likelihood (PL) and penalized weighted least-squares (PWLS) objective functions. At low doses, the authors found that the PL approach outperforms PWLS in terms of resolution-noise tradeoffs, but at standard doses they perform similarly. The PWLS objective function, being quadratic, is more amenable to computational acceleration than the PL objective. In this work, the authors develop and compare two different methods for implementing PWLS sinogram restoration with the hope of improving computational performance relative to PL in the standard-dose regime. Sinogram restoration is still significant in the standard-dose regime since it can still outperform standard approaches and it allows for correction of effects that are not usually modeled in standard CT preprocessing. Methods: The authors have explored and compared two implementation strategies for PWLS sinogram restoration: (1) A direct matrix-inversion strategy based on the closed-form solution to the PWLS optimization problem and (2) an iterative approach based on the conjugate-gradient algorithm. Obtaining optimal performance from each strategy required modifying the naive off-the-shelf implementations of the algorithms to exploit the particular symmetry and sparseness of the sinogram-restoration problem. For the closed-form approach, the authors subdivided the large matrix inversion into smaller coupled problems and exploited sparseness to minimize matrix operations. For the conjugate-gradient approach, the authors exploited sparseness and preconditioned the problem to speed up convergence. Results: All methods produced qualitatively and quantitatively similar images as measured by resolution-variance tradeoffs and difference images. Despite the acceleration strategies, the direct matrix-inversion approach was found to be uncompetitive with iterative approaches, with a computational burden higher by an order of magnitude or more. The iterative conjugate-gradient approach, however, does appear promising, with computation times half that of the authors’ previous penalized-likelihood implementation. Conclusions: Iterative conjugate-gradient based PWLS sinogram restoration with careful matrix optimizations has computational advantages over direct matrix PWLS inversion and over penalized-likelihood sinogram restoration and can be considered a good alternative in standard-dose regimes. PMID:21158306

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

NASA Astrophysics Data System (ADS)

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

2018-05-01

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

Exercise preconditioning improves behavioral functions following transient cerebral ischemia induced by 4-vessel occlusion (4-VO) in rats.

PubMed

Tahamtan, Mahshid; Allahtavakoli, Mohammad; Abbasnejad, Mehdi; Roohbakhsh, Ali; Taghipour, Zahra; Taghavi, Mohsen; Khodadadi, Hassan; Shamsizadeh, Ali

2013-12-01

There is evidence that exercise decreases ischemia/reperfusion injury in rats. Since behavioral deficits are the main outcome in patients after stroke, our study was designed to investigate whether exercise preconditioning improves the acute behavioral functions and also brain inflammatory injury following cerebral ischemia. Male rats weighing 250-300 g were randomly allocated into five experimental groups. Exercise was performed on a treadmill 30min/day for 3 weeks. Ischemia was induced by 4-vessel occlusion method. Recognition memory was assessed by novel object recognition task (NORT) and step-through passive avoidance task. Sensorimotor function and motor movements were evaluated by adhesive removal test and ledged beam-walking test, respectively. Brain inflammatory injury was evaluated by histological assessment. In NORT, the discrimination ratio was decreased after ischemia (P < 0.05) and exercise preconditioning improved it in ischemic animals. In the passive avoidance test, a significant reduction in response latency was observed in the ischemic group. Exercise preconditioning significantly decreased the response latency in the ischemic rats (P < 0.001). In the adhesive removal test, latency to touch and remove the sticky labels from forepaw was increased following induction of ischemia (all P < 0.001) and exercise preconditioning decreased these indices compared to the ischemic group (all P < 0.001). In the ledged beam-walking test, the slip ratio was increased following ischemia (P < 0.05).  In the ischemia group, marked neuronal injury in hippocampus was observed. These neuropathological changes were attenuated by exercise preconditioning (P < 0.001). Our results showed that exercise preconditioning improves behavioral functions and maintains more viable cells in the dorsal hippocampus of the ischemic brain.

Mechanical preconditioning enables electrophysiologic coupling of skeletal myoblast cells to myocardium

PubMed Central

Treskes, Philipp; Cowan, Douglas B.; Stamm, Christof; Rubach, Martin; Adelmann, Roland; Wittwer, Thorsten; Wahlers, Thorsten

2015-01-01

Objective The effect of mechanical preconditioning on skeletal myoblasts in engineered tissue constructs was investigated to resolve issues associated with conduction block between skeletal myoblast cells and cardiomyocytes. Methods Murine skeletal myoblasts were used to generate engineered tissue constructs with or without application of mechanical strain. After in vitro myotube formation, engineered tissue constructs were co-cultured for 6 days with viable embryonic heart slices. With the use of sharp electrodes, electrical coupling between engineered tissue constructs and embryonic heart slices was assessed in the presence or absence of pharmacologic agents. Results The isolation and expansion procedure for skeletal myoblasts resulted in high yields of homogeneously desmin-positive (97.1% ± 0.1%) cells. Mechanical strain was exerted on myotubes within engineered tissue constructs during gelation of the matrix, generating preconditioned engineered tissue constructs. Electrical coupling between preconditioned engineered tissue constructs and embryonic heart slices was observed; however, no coupling was apparent when engineered tissue constructs were not subjected to mechanical strain. Coupling of cells from engineered tissue constructs to cells in embryonic heart slices showed slower conduction velocities than myocardial cells with the embryonic heart slices (preconditioned engineered tissue constructs vs embryonic heart slices: 0.04 ± 0.02 ms vs 0.10 ± 0.05 ms, P = .011), lower stimulation frequencies (preconditioned engineered tissue constructs vs maximum embryonic heart slices: 4.82 ± 1.42 Hz vs 10.58 ± 1.56 Hz; P = .0009), and higher sensitivities to the gap junction inhibitor (preconditioned engineered tissue constructs vs embryonic heart slices: 0.22 ± 0.07 mmol/L vs 0.93 ± 0.15 mmol/L; P = .0004). Conclusions We have generated skeletal myoblast–based transplantable grafts that electrically couple to myocardium. PMID:22980065

Liquid hydrogen turbopump rapid start program. [thermal preconditioning using coatings

NASA Technical Reports Server (NTRS)

Wong, G. S.

1973-01-01

This program was to analyze, test, and evaluate methods of achieving rapid-start of a liquid hydrogen feed system (inlet duct and turbopump) using a minimum of thermal preconditioning time and propellant. The program was divided into four tasks. Task 1 includes analytical studies of the testing conducted in the other three tasks. Task 2 describes the results from laboratory testing of coating samples and the successful adherence of a KX-635 coating to the internal surfaces of the feed system tested in Task 4. Task 3 presents results of testing an uncoated feed system. Tank pressure was varied to determine the effect of flowrate on preconditioning. The discharge volume and the discharge pressure which initiates opening of the discharge valve were varied to determine the effect on deadhead (no through-flow) start transients. Task 4 describes results of testing a similar, internally coated feed system and illustrates the savings in preconditioning time and propellant resulting from the coatings.

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.

Mitigating nonlinearity in full waveform inversion using scaled-Sobolev pre-conditioning

NASA Astrophysics Data System (ADS)

Zuberi, M. AH; Pratt, R. G.

2018-04-01

The Born approximation successfully linearizes seismic full waveform inversion if the background velocity is sufficiently accurate. When the background velocity is not known it can be estimated by using model scale separation methods. A frequently used technique is to separate the spatial scales of the model according to the scattering angles present in the data, by using either first- or second-order terms in the Born series. For example, the well-known `banana-donut' and the `rabbit ear' shaped kernels are, respectively, the first- and second-order Born terms in which at least one of the scattering events is associated with a large angle. Whichever term of the Born series is used, all such methods suffer from errors in the starting velocity model because all terms in the Born series assume that the background Green's function is known. An alternative approach to Born-based scale separation is to work in the model domain, for example, by Gaussian smoothing of the update vectors, or some other approach for separation by model wavenumbers. However such model domain methods are usually based on a strict separation in which only the low-wavenumber updates are retained. This implies that the scattered information in the data is not taken into account. This can lead to the inversion being trapped in a false (local) minimum when sharp features are updated incorrectly. In this study we propose a scaled-Sobolev pre-conditioning (SSP) of the updates to achieve a constrained scale separation in the model domain. The SSP is obtained by introducing a scaled Sobolev inner product (SSIP) into the measure of the gradient of the objective function with respect to the model parameters. This modified measure seeks reductions in the L2 norm of the spatial derivatives of the gradient without changing the objective function. The SSP does not rely on the Born prediction of scale based on scattering angles, and requires negligible extra computational cost per iteration. Synthetic examples from the Marmousi model show that the constrained scale separation using SSP is able to keep the background updates in the zone of attraction of the global minimum, in spite of using a poor starting model in which conventional methods fail.

Investigation of Reperfusion Injury and Ischemic Preconditioning in Microsurgry

PubMed Central

Wang, Wei Zhong

2008-01-01

Ischemia/reperfusion (I/R) is inevitable in many vascular and musculoskeletal traumas, diseases, free tissue transfers, and during time-consuming reconstructive surgeries in the extremities. Salvage of a prolonged ischemic extremity or flap still remains a challenge for the microvascular surgeon. One of the common complications after microsurgery is I/R-induced tissue death or I/R injury. Twenty years after the discovery, ischemic preconditioning (IPC) has emerged as a powerful method for attenuating I/R injury in a variety of organs or tissues. However, its therapeutic expectations still need to be fulfilled. In this article, the author reviews some important experimental evidences of I/R injury as well as preconditioning-induced protection in the fields relevant to microsurgery. PMID:18946882

40 CFR 80.52 - Vehicle preconditioning.

Code of Federal Regulations, 2013 CFR

2013-07-01

... 40 Protection of Environment 17 2013-07-01 2013-07-01 false Vehicle preconditioning. 80.52 Section...) REGULATION OF FUELS AND FUEL ADDITIVES Reformulated Gasoline § 80.52 Vehicle preconditioning. (a) Initial vehicle preconditioning and preconditioning between tests with different fuels shall be performed in...

40 CFR 80.52 - Vehicle preconditioning.

Code of Federal Regulations, 2010 CFR

2010-07-01

... 40 Protection of Environment 16 2010-07-01 2010-07-01 false Vehicle preconditioning. 80.52 Section...) REGULATION OF FUELS AND FUEL ADDITIVES Reformulated Gasoline § 80.52 Vehicle preconditioning. (a) Initial vehicle preconditioning and preconditioning between tests with different fuels shall be performed in...

40 CFR 80.52 - Vehicle preconditioning.

Code of Federal Regulations, 2014 CFR

2014-07-01

... 40 Protection of Environment 17 2014-07-01 2014-07-01 false Vehicle preconditioning. 80.52 Section...) REGULATION OF FUELS AND FUEL ADDITIVES Reformulated Gasoline § 80.52 Vehicle preconditioning. (a) Initial vehicle preconditioning and preconditioning between tests with different fuels shall be performed in...

40 CFR 80.52 - Vehicle preconditioning.

Code of Federal Regulations, 2012 CFR

2012-07-01

... 40 Protection of Environment 17 2012-07-01 2012-07-01 false Vehicle preconditioning. 80.52 Section...) REGULATION OF FUELS AND FUEL ADDITIVES Reformulated Gasoline § 80.52 Vehicle preconditioning. (a) Initial vehicle preconditioning and preconditioning between tests with different fuels shall be performed in...

40 CFR 80.52 - Vehicle preconditioning.

Code of Federal Regulations, 2011 CFR

2011-07-01

... 40 Protection of Environment 16 2011-07-01 2011-07-01 false Vehicle preconditioning. 80.52 Section...) REGULATION OF FUELS AND FUEL ADDITIVES Reformulated Gasoline § 80.52 Vehicle preconditioning. (a) Initial vehicle preconditioning and preconditioning between tests with different fuels shall be performed in...

2-D weighted least-squares phase unwrapping

DOEpatents

Ghiglia, Dennis C.; Romero, Louis A.

1995-01-01

Weighted values of interferometric signals are unwrapped by determining the least squares solution of phase unwrapping for unweighted values of the interferometric signals; and then determining the least squares solution of phase unwrapping for weighted values of the interferometric signals by preconditioned conjugate gradient methods using the unweighted solutions as preconditioning values. An output is provided that is representative of the least squares solution of phase unwrapping for weighted values of the interferometric signals.

2-D weighted least-squares phase unwrapping

DOEpatents

Ghiglia, D.C.; Romero, L.A.

1995-06-13

Weighted values of interferometric signals are unwrapped by determining the least squares solution of phase unwrapping for unweighted values of the interferometric signals; and then determining the least squares solution of phase unwrapping for weighted values of the interferometric signals by preconditioned conjugate gradient methods using the unweighted solutions as preconditioning values. An output is provided that is representative of the least squares solution of phase unwrapping for weighted values of the interferometric signals. 6 figs.

The performance of monotonic and new non-monotonic gradient ascent reconstruction algorithms for high-resolution neuroreceptor PET imaging.

PubMed

Angelis, G I; Reader, A J; Kotasidis, F A; Lionheart, W R; Matthews, J C

2011-07-07

Iterative expectation maximization (EM) techniques have been extensively used to solve maximum likelihood (ML) problems in positron emission tomography (PET) image reconstruction. Although EM methods offer a robust approach to solving ML problems, they usually suffer from slow convergence rates. The ordered subsets EM (OSEM) algorithm provides significant improvements in the convergence rate, but it can cycle between estimates converging towards the ML solution of each subset. In contrast, gradient-based methods, such as the recently proposed non-monotonic maximum likelihood (NMML) and the more established preconditioned conjugate gradient (PCG), offer a globally convergent, yet equally fast, alternative to OSEM. Reported results showed that NMML provides faster convergence compared to OSEM; however, it has never been compared to other fast gradient-based methods, like PCG. Therefore, in this work we evaluate the performance of two gradient-based methods (NMML and PCG) and investigate their potential as an alternative to the fast and widely used OSEM. All algorithms were evaluated using 2D simulations, as well as a single [(11)C]DASB clinical brain dataset. Results on simulated 2D data show that both PCG and NMML achieve orders of magnitude faster convergence to the ML solution compared to MLEM and exhibit comparable performance to OSEM. Equally fast performance is observed between OSEM and PCG for clinical 3D data, but NMML seems to perform poorly. However, with the addition of a preconditioner term to the gradient direction, the convergence behaviour of NMML can be substantially improved. Although PCG is a fast convergent algorithm, the use of a (bent) line search increases the complexity of the implementation, as well as the computational time involved per iteration. Contrary to previous reports, NMML offers no clear advantage over OSEM or PCG, for noisy PET data. Therefore, we conclude that there is little evidence to replace OSEM as the algorithm of choice for many applications, especially given that in practice convergence is often not desired for algorithms seeking ML estimates.

Multigrid Solution of the Navier-Stokes Equations at Low Speeds with Large Temperature Variations

NASA Technical Reports Server (NTRS)

Sockol, Peter M.

2002-01-01

Multigrid methods for the Navier-Stokes equations at low speeds and large temperature variations are investigated. The compressible equations with time-derivative preconditioning and preconditioned flux-difference splitting of the inviscid terms are used. Three implicit smoothers have been incorporated into a common multigrid procedure. Both full coarsening and semi-coarsening with directional fine-grid defect correction have been studied. The resulting methods have been tested on four 2D laminar problems over a range of Reynolds numbers on both uniform and highly stretched grids. Two of the three methods show efficient and robust performance over the entire range of conditions. In addition none of the methods have any difficulty with the large temperature variations.

A Pragmatic Approach to Guide Implementation Evaluation Research: Strategy Mapping for Complex Interventions.

PubMed

Huynh, Alexis K; Hamilton, Alison B; Farmer, Melissa M; Bean-Mayberry, Bevanne; Stirman, Shannon Wiltsey; Moin, Tannaz; Finley, Erin P

2018-01-01

Greater specification of implementation strategies is a challenge for implementation science, but there is little guidance for delineating the use of multiple strategies involved in complex interventions. The Cardiovascular (CV) Toolkit project entails implementation of a toolkit designed to reduce CV risk by increasing women's engagement in appropriate services. The CV Toolkit project follows an enhanced version of Replicating Effective Programs (REP), an evidence-based implementation strategy, to implement the CV Toolkit across four phases: pre-conditions, pre-implementation, implementation, and maintenance and evolution. Our current objective is to describe a method for mapping implementation strategies used in real time as part of the CV Toolkit project. This method supports description of the timing and content of bundled strategies and provides a structured process for developing a plan for implementation evaluation. We conducted a process of strategy mapping to apply Proctor and colleagues' rubric for specification of implementation strategies, constructing a matrix in which we identified each implementation strategy, its conceptual group, and the corresponding REP phase(s) in which it occurs. For each strategy, we also specified the actors involved, actions undertaken, action targets, dose of the implementation strategy, and anticipated outcome addressed. We iteratively refined the matrix with the implementation team, including use of simulation to provide initial validation. Mapping revealed patterns in the timing of implementation strategies within REP phases. Most implementation strategies involving the development of stakeholder interrelationships and training and educating stakeholders were introduced during the pre-conditions or pre-implementation phases. Strategies introduced in the maintenance and evolution phase emphasized communication, re-examination, and audit and feedback. In addition to its value for producing valid and reliable process evaluation data, mapping implementation strategies has informed development of a pragmatic blueprint for implementation and longitudinal analyses and evaluation activities. We update recent recommendations on specification of implementation strategies by considering the implications for multi-strategy frameworks and propose an approach for mapping the use of implementation strategies within complex, multi-level interventions, in support of rigorous evaluation. Developing pragmatic tools to aid in operationalizing the conduct of implementation and evaluation activities is essential to enacting sound implementation research.

The role of hypoxia-inducible factor-1α and vascular endothelial growth factor in late-phase preconditioning with xenon, isoflurane and levosimendan in rat cardiomyocytes

PubMed Central

Goetzenich, Andreas; Hatam, Nima; Preuss, Stephanie; Moza, Ajay; Bleilevens, Christian; Roehl, Anna B.; Autschbach, Rüdiger; Bernhagen, Jürgen; Stoppe, Christian

2014-01-01

OBJECTIVES The protective effects of late-phase preconditioning can be triggered by several stimuli. Unfortunately, the transfer from bench to bedside still represents a challenge, as concomitant medication or diseases influence the complex signalling pathways involved. In an established model of primary neonatal rat cardiomyocytes, we analysed the cardioprotective effects of three different stimulating pharmaceuticals of clinical relevance. The effect of additional β-blocker treatment was studied as these were previously shown to negatively influence preconditioning. METHODS Twenty-four hours prior to hypoxia, cells pre-treated with or without metoprolol (0.55 µg/ml) were preconditioned with isoflurane, levosimendan or xenon. The influences of these stimuli on hypoxia-inducible factor-1α (HIF-1α), vascular endothelial growth factor (VEGF) as well as inducible and endothelial nitric synthase (iNOS/eNOS) and cyclooxygenase-2 (COX-2) were analysed by polymerase chain reaction and western blotting. The preconditioning was proved by trypan blue cell counts following 5 h of hypoxia and confirmed by fluorescence staining. RESULTS Five hours of hypoxia reduced cell survival in unpreconditioned control cells to 44 ± 4%. Surviving cell count was significantly higher in cells preconditioned either by 2 × 15 min isoflurane (70 ± 16%; P = 0.005) or by xenon (59 ± 8%; P = 0.049). Xenon-preconditioned cells showed a significantly elevated content of VEGF (0.025 ± 0.010 IDV [integrated density values when compared with GAPDH] vs 0.003 ± 0.006 IDV in controls; P = 0.0003). The protein expression of HIF-1α was increased both by levosimendan (0.563 ± 0.175 IDV vs 0.142 ± 0.042 IDV in controls; P = 0.0289) and by xenon (0.868 ± 0.222 IDV; P < 0.0001) pretreatment. A significant elevation of mRNA expression of iNOS was measureable following preconditioning by xenon but not by the other chosen stimuli. eNOS mRNA expression was found to be suppressed by β-blocker treatment for all stimuli. In our model, independently of the chosen stimulus, β-blocker treatment had no significant effect on cell survival. CONCLUSIONS We found that the stimulation of late-phase preconditioning involves several distinct pathways that are variably addressed by the different stimuli. In contrast to isoflurane treatment, xenon-induced preconditioning does not lead to an increase in COX-2 gene transcription but to a significant increase in HIF-1α and subsequently VEGF. PMID:24351506

Ultraviolet B preconditioning enhances the hair growth-promoting effects of adipose-derived stem cells via generation of reactive oxygen species.

PubMed

Jeong, Yun-Mi; Sung, Young Kwan; Kim, Wang-Kyun; Kim, Ji Hye; Kwack, Mi Hee; Yoon, Insoo; Kim, Dae-Duk; Sung, Jong-Hyuk

2013-01-01

Hypoxia induces the survival and regenerative potential of adipose-derived stem cells (ASCs), but there are tremendous needs to find alternative methods for ASC preconditioning. Therefore, this work investigated: (1) the ability of low-dose ultraviolet B (UVB) radiation to stimulate the survival, migration, and tube-forming activity of ASCs in vitro; (2) the ability of UVB preconditioning to enhance the hair growth-promoting capacity of ASCs in vivo; and (3) the mechanism of action for ASC stimulation by UVB. Although high-dose UVB decreased the proliferation of ASCs, low-dose (10 or 20 mJ/cm(2)) treatment increased their survival, migration, and tube-forming activity. In addition, low-dose UVB upregulated the expression of ASC-derived growth factors, and a culture medium conditioned by UVB-irradiated ASCs increased the proliferation of dermal papilla and outer root sheet cells. Notably, injection of UVB-preconditioned ASCs into C(3)H/HeN mice significantly induced the telogen-to-anagen transition and increased new hair weight in vivo. UVB treatment significantly increased the generation of reactive oxygen species (ROS) in cultured ASCs, and inhibition of ROS generation by diphenyleneiodonium chloride (DPI) significantly attenuated UVB-induced ASC stimulation. Furthermore, NADPH oxidase 4 (Nox4) expression was induced in ASCs by UVB irradiation, and Nox4 silencing by small interfering RNA, like DPI, significantly reduced UVB-induced ROS generation. These results suggest that the primary involvement of ROS generation in UVB-mediated ASC stimulation occurs via the Nox4 enzyme. This is the first indication that a low dose of UVB radiation and/or the control of ROS generation could potentially be incorporated into a novel ASC preconditioning method for hair regeneration.

A Molecular Approach to Epilepsy Management: from Current Therapeutic Methods to Preconditioning Efforts.

PubMed

Amini, Elham; Rezaei, Mohsen; Mohamed Ibrahim, Norlinah; Golpich, Mojtaba; Ghasemi, Rasoul; Mohamed, Zahurin; Raymond, Azman Ali; Dargahi, Leila; Ahmadiani, Abolhassan

2015-08-01

Epilepsy is the most common and chronic neurological disorder characterized by recurrent unprovoked seizures. The key aim in treating patients with epilepsy is the suppression of seizures. An understanding of focal changes that are involved in epileptogenesis may therefore provide novel approaches for optimal treatment of the seizure. Although the actual pathogenesis of epilepsy is still uncertain, recently growing lines of evidence declare that microglia and astrocyte activation, oxidative stress and reactive oxygen species (ROS) production, mitochondria dysfunction, and damage of blood-brain barrier (BBB) are involved in its pathogenesis. Impaired GABAergic function in the brain is probably the most accepted hypothesis regarding the pathogenesis of epilepsy. Clinical neuroimaging of patients and experimental modeling have demonstrated that seizures may induce neuronal apoptosis. Apoptosis signaling pathways are involved in the pathogenesis of several types of epilepsy such as temporal lobe epilepsy (TLE). The quality of life of patients is seriously affected by treatment-related problems and also by unpredictability of epileptic seizures. Moreover, the available antiepileptic drugs (AED) are not significantly effective to prevent epileptogenesis. Thus, novel therapies that are proficient to control seizure in people who are suffering from epilepsy are needed. The preconditioning method promises to serve as an alternative therapeutic approach because this strategy has demonstrated the capability to curtail epileptogenesis. For this reason, understanding of molecular mechanisms underlying brain tolerance induced by preconditioning is crucial to delineate new neuroprotective ways against seizure damage and epileptogenesis. In this review, we summarize the work to date on the pathogenesis of epilepsy and discuss recent therapeutic strategies in the treatment of epilepsy. We will highlight that novel therapy targeting such as preconditioning process holds great promise. In addition, we will also highlight the role of gene reprogramming and mitochondrial biogenesis in the preconditioning-mediated neuroprotective events.

Voltage Preconditioning Allows Modulated Gene Expression in Neurons Using PEI-complexed siRNA

PubMed Central

Sridharan, Arati; Patel, Chetan; Muthuswamy, Jit

2013-01-01

We present here a high efficiency, high viability siRNA-delivery method using a voltage-controlled chemical transfection strategy to achieve modulated delivery of polyethylenimine (PEI) complexed with siRNA in an in vitro culture of neuro2A cells and neurons. Low voltage pulses were applied to adherent cells before the administration of PEI-siRNA complexes. Live assays of neuro2a cells transfected with fluorescently tagged siRNA showed an increase in transfection efficiency from 62 ± 14% to 98 ± 3.8% (after −1 V). In primary hippocampal neurons, transfection efficiencies were increased from 30 ± 18% to 76 ± 18% (after −1 V). Negligible or low-level transfection was observed after preconditioning at higher voltages, suggesting an inverse relationship with applied voltage. Experiments with propidium iodide ruled out the role of electroporation in the transfection of siRNAs suggesting an alternate electro-endocytotic mechanism. In addition, image analysis of preconditioned and transfected cells demonstrates siRNA uptake and loading that is tuned to preconditioning voltage levels. There is approximately a fourfold increase in siRNA loading after preconditioning at −1 V compared with the same at ±2–3 V. Modulated gene expression is demonstrated in a functional knockdown of glyceraldehyde 3-phosphate dehydrogenase (GAPDH) in neuro2A cells using siRNA. Cell density and dendritic morphological changes are also demonstrated in modulated knockdown of brain derived neurotrophic factor (BDNF) in primary hippocampal neurons. The method reported here has potential applications in the development of high-throughput screening systems for large libraries of siRNA molecules involving difficult-to-transfect cells like neurons. PMID:23531602

Voltage Preconditioning Allows Modulated Gene Expression in Neurons Using PEI-complexed siRNA.

PubMed

Sridharan, Arati; Patel, Chetan; Muthuswamy, Jit

2013-03-26

We present here a high efficiency, high viability siRNA-delivery method using a voltage-controlled chemical transfection strategy to achieve modulated delivery of polyethylenimine (PEI) complexed with siRNA in an in vitro culture of neuro2A cells and neurons. Low voltage pulses were applied to adherent cells before the administration of PEI-siRNA complexes. Live assays of neuro2a cells transfected with fluorescently tagged siRNA showed an increase in transfection efficiency from 62 ± 14% to 98 ± 3.8% (after -1 V). In primary hippocampal neurons, transfection efficiencies were increased from 30 ± 18% to 76 ± 18% (after -1 V). Negligible or low-level transfection was observed after preconditioning at higher voltages, suggesting an inverse relationship with applied voltage. Experiments with propidium iodide ruled out the role of electroporation in the transfection of siRNAs suggesting an alternate electro-endocytotic mechanism. In addition, image analysis of preconditioned and transfected cells demonstrates siRNA uptake and loading that is tuned to preconditioning voltage levels. There is approximately a fourfold increase in siRNA loading after preconditioning at -1 V compared with the same at ±2-3 V. Modulated gene expression is demonstrated in a functional knockdown of glyceraldehyde 3-phosphate dehydrogenase (GAPDH) in neuro2A cells using siRNA. Cell density and dendritic morphological changes are also demonstrated in modulated knockdown of brain derived neurotrophic factor (BDNF) in primary hippocampal neurons. The method reported here has potential applications in the development of high-throughput screening systems for large libraries of siRNA molecules involving difficult-to-transfect cells like neurons.Molecular Therapy-Nucleic Acids (2013) 2, e82; doi:10.1038/mtna.2013.10; published online 26 March 2013.

HFEM3D

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

Weiss, Chester J

Software solves the three-dimensional Poisson equation div(k(grad(u)) = f, by the finite element method for the case when material properties, k, are distributed over hierarchy of edges, facets and tetrahedra in the finite element mesh. Method is described in Weiss, CJ, Finite element analysis for model parameters distributed on a hierarchy of geometric simplices, Geophysics, v82, E155-167, doi:10.1190/GEO2017-0058.1 (2017). A standard finite element method for solving Poisson’s equation is augmented by including in the 3D stiffness matrix additional 2D and 1D stiffness matrices representing the contributions from material properties associated with mesh faces and edges, respectively. The resulting linear systemmore » is solved iteratively using the conjugate gradient method with Jacobi preconditioning. To minimize computer storage for program execution, the linear solver computes matrix-vector contractions element-by-element over the mesh, without explicit storage of the global stiffness matrix. Program output vtk compliant for visualization and rendering by 3rd party software. Program uses dynamic memory allocation and as such there are no hard limits on problem size outside of those imposed by the operating system and configuration on which the software is run. Dimension, N, of the finite element solution vector is constrained by the the addressable space in 32-vs-64 bit operating systems. Total storage requirements for the problem. Total working space required for the program is approximately 13*N double precision words.« less

Modelling sea ice dynamics

NASA Astrophysics Data System (ADS)

Murawski, Jens; Kleine, Eckhard

2017-04-01

Sea ice remains one of the frontiers of ocean modelling and is of vital importance for the correct forecasts of the northern oceans. At large scale, it is commonly considered a continuous medium whose dynamics is modelled in terms of continuum mechanics. Its specifics are a matter of constitutive behaviour which may be characterised as rigid-plastic. The new developed sea ice dynamic module bases on general principles and follows a systematic approach to the problem. Both drift field and stress field are modelled by a variational property. Rigidity is treated by Lagrangian relaxation. Thus one is led to a sensible numerical method. Modelling fast ice remains to be a challenge. It is understood that ridging and the formation of grounded ice keels plays a role in the process. The ice dynamic model includes a parameterisation of the stress associated with grounded ice keels. Shear against the grounded bottom contact might lead to plastic deformation and the loss of integrity. The numerical scheme involves a potentially large system of linear equations which is solved by pre-conditioned iteration. The entire algorithm consists of several components which result from decomposing the problem. The algorithm has been implemented and tested in practice.

Investigation of Conjugate Heat Transfer in Turbine Blades and Vanes

NASA Technical Reports Server (NTRS)

Kassab, A. J.; Kapat, J. S.

2001-01-01

We report on work carried out to develop a 3-D coupled Finite Volume/BEM-based temperature forward/flux back (TFFB) coupling algorithm to solve the conjugate heat transfer (CHT) which arises naturally in analysis of systems exposed to a convective environment. Here, heat conduction within a structure is coupled to heat transfer to the external fluid which is convecting heat into or out of the solid structure. There are two basic approaches to solving coupled fluid structural systems. The first is a direct coupling where the solution of the different fields is solved simultaneously in one large set of equations. The second approach is a loose coupling strategy where each set of field equations is solved to provide boundary conditions for the other. The equations are solved in turn until an iterated convergence criterion is met at the fluid-solid interface. The loose coupling strategy is particularly attractive when coupling auxiliary field equations to computational fluid dynamics codes. We adopt the latter method in which the BEM is used to solve heat conduction inside a structure which is exposed to a convective field which in turn is resolved by solving the NASA Glenn compressible Navier-Stokes finite volume code Glenn-HT. The BEM code features constant and bi-linear discontinuous elements and an ILU-preconditioned GMRES iterative solver for the resulting non-symmetric algebraic set arising in the conduction solution. Interface of flux and temperature is enforced at the solid/fluid interface, and a radial-basis function scheme is used to interpolated information between the CFD and BEM surface grids. Additionally, relaxation is implemented in passing the fluxes from the conduction solution to the fluid solution. Results from a simple test example are reported.

Virtual patient design: exploring what works and why. A grounded theory study

PubMed Central

Bateman, James; Allen, Maggie; Samani, Dipti; Kidd, Jane; Davies, David

2013-01-01

Objectives Virtual patients (VPs) are online representations of clinical cases used in medical education. Widely adopted, they are well placed to teach clinical reasoning skills. International technology standards mean VPs can be created, shared and repurposed between institutions. A systematic review has highlighted the lack of evidence to support which of the numerous VP designs may be effective, and why. We set out to research the influence of VP design on medical undergraduates. Methods This is a grounded theory study into the influence of VP design on undergraduate medical students. Following a review of the literature and publicly available VP cases, we identified important design properties. We integrated them into two substantial VPs produced for this research. Using purposeful iterative sampling, 46 medical undergraduates were recruited to participate in six focus groups. Participants completed both VPs, an evaluation and a 1-hour focus group discussion. These were digitally recorded, transcribed and analysed using grounded theory, supported by computer-assisted analysis. Following open, axial and selective coding, we produced a theoretical model describing how students learn from VPs. Results We identified a central core phenomenon designated ‘learning from the VP’. This had four categories: VP Construction; External Preconditions; Student–VP Interaction, and Consequences. From these, we constructed a three-layer model describing the interactions of students with VPs. The inner layer consists of the student's cognitive and behavioural preconditions prior to sitting a case. The middle layer considers the VP as an ‘encoded object’, an e-learning artefact and as a ‘constructed activity’, with associated pedagogic and organisational elements. The outer layer describes cognitive and behavioural change. Conclusions This is the first grounded theory study to explore VP design. This original research has produced a model which enhances understanding of how and why the delivery and design of VPs influence learning. The model may be of practical use to authors, institutions and researchers. PMID:23662877

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

Weston, Brian T.

This dissertation focuses on the development of a fully-implicit, high-order compressible ow solver with phase change. The work is motivated by laser-induced phase change applications, particularly by the need to develop large-scale multi-physics simulations of the selective laser melting (SLM) process in metal additive manufacturing (3D printing). Simulations of the SLM process require precise tracking of multi-material solid-liquid-gas interfaces, due to laser-induced melting/ solidi cation and evaporation/condensation of metal powder in an ambient gas. These rapid density variations and phase change processes tightly couple the governing equations, requiring a fully compressible framework to robustly capture the rapid density variations ofmore » the ambient gas and the melting/evaporation of the metal powder. For non-isothermal phase change, the velocity is gradually suppressed through the mushy region by a variable viscosity and Darcy source term model. The governing equations are discretized up to 4th-order accuracy with our reconstructed Discontinuous Galerkin spatial discretization scheme and up to 5th-order accuracy with L-stable fully implicit time discretization schemes (BDF2 and ESDIRK3-5). The resulting set of non-linear equations is solved using a robust Newton-Krylov method, with the Jacobian-free version of the GMRES solver for linear iterations. Due to the sti nes associated with the acoustic waves and thermal and viscous/material strength e ects, preconditioning the GMRES solver is essential. A robust and scalable approximate block factorization preconditioner was developed, which utilizes the velocity-pressure (vP) and velocity-temperature (vT) Schur complement systems. This multigrid block reduction preconditioning technique converges for high CFL/Fourier numbers and exhibits excellent parallel and algorithmic scalability on classic benchmark problems in uid dynamics (lid-driven cavity ow and natural convection heat transfer) as well as for laser-induced phase change problems in 2D and 3D.« less

Algorithms for the Euler and Navier-Stokes equations for supercomputers

NASA Technical Reports Server (NTRS)

Turkel, E.

1985-01-01

The steady state Euler and Navier-Stokes equations are considered for both compressible and incompressible flow. Methods are found for accelerating the convergence to a steady state. This acceleration is based on preconditioning the system so that it is no longer time consistent. In order that the acceleration technique be scheme-independent, this preconditioning is done at the differential equation level. Applications are presented for very slow flows and also for the incompressible equations.

Preconditioned conjugate gradient methods for the Navier-Stokes equations

NASA Technical Reports Server (NTRS)

Ajmani, Kumud; Ng, Wing-Fai; Liou, Meng-Sing

1994-01-01

A preconditioned Krylov subspace method (GMRES) is used to solve the linear systems of equations formed at each time-integration step of the unsteady, two-dimensional, compressible Navier-Stokes equations of fluid flow. The Navier-Stokes equations are cast in an implicit, upwind finite-volume, flux-split formulation. Several preconditioning techniques are investigated to enhance the efficiency and convergence rate of the implicit solver based on the GMRES algorithm. The superiority of the new solver is established by comparisons with a conventional implicit solver, namely line Gauss-Seidel relaxation (LGSR). Computational test results for low-speed (incompressible flow over a backward-facing step at Mach 0.1), transonic flow (trailing edge flow in a transonic turbine cascade), and hypersonic flow (shock-on-shock interactions on a cylindrical leading edge at Mach 6.0) are presented. For the Mach 0.1 case, overall speedup factors of up to 17 (in terms of time-steps) and 15 (in terms of CPU time on a CRAY-YMP/8) are found in favor of the preconditioned GMRES solver, when compared with the LGSR solver. The corresponding speedup factors for the transonic flow case are 17 and 23, respectively. The hypersonic flow case shows slightly lower speedup factors of 9 and 13, respectively. The study of preconditioners conducted in this research reveals that a new LUSGS-type preconditioner is much more efficient than a conventional incomplete LU-type preconditioner.

Myocardial protection using diadenosine tetraphosphate with pharmacological preconditioning.

PubMed

Ahmet, I; Sawa, Y; Nishimura, M; Yamaguchi, T; Kitakaze, M; Matsuda, H

2000-09-01

We have reported a similar cardioprotective effect and mechanism of diadenosine tetraphosphate (AP4A) and ischemic preconditioning in rat hearts. In this study, the applicability of AP4A administration to cardiac surgery was tested by using a canine cardiopulmonary bypass model. Hearts underwent 60 minutes of cardioplegic arrest (34 degrees C) by a single dose of cardioplegia. Cardioplegia contained either AP4A (40 micromol/L; n = 6) or saline (n = 6). Beagles were weaned from cardiopulmonary bypass 30 minutes after reperfusion, and left ventricular function was evaluated after another 30 minutes by using the cardiac loop analysis system. Administration of AP4A significantly improved the postischemic recovery of cardiac function and reduced the leakage of serum creatine kinase compared with saline. Systemic vascular resistance, mean aortic blood pressure, and the electrocardiographic indices were not significantly altered by AP4A administration. Administration of AP4A was cardioprotective without apparent adverse effects. Because the cardioprotective mechanism may be similar to that of ischemic preconditioning, the addition of AP4A into cardioplegia may be a novel safe method for clinical application of preconditioning cardioprotection.

Limb remote-preconditioning protects against focal ischemia in rats and contradicts the dogma of therapeutic time windows for preconditioning

PubMed Central

Ren, Chuancheng; Gao, Xuwen; Steinberg, Gary K.; Zhao, Heng

2009-01-01

Remote ischemic preconditioning is an emerging concept for stroke treatment, but its protection against focal stroke has not been established. We tested whether remote preconditioning, performed in the ipsilateral hind limb, protects against focal stroke and explored its protective parameters. Stroke was generated by a permanent occlusion of the left distal middle cerebral artery (MCA) combined with a 30 minute occlusion of the bilateral common carotid arteries (CCA) in male rats. Limb preconditioning was generated by 5 or 15 minute occlusion followed with the same period of reperfusion of the left hind femoral artery, and repeated for 2 or 3 cycles. Infarct was measured 2 days later. The results showed that rapid preconditioning with 3 cycles of 15 minutes performed immediately before stroke reduced infarct size from 47.7±7.6% of control ischemia to 9.8±8.6%; at 2 cycles of 15 minutes, infarct was reduced to 24.7±7.3%; at 2 cycles of 5 minutes, infarct was not reduced. Delayed preconditioning with 3 cycles of 15 minutes conducted 2 days before stroke also reduced infarct to 23.0 ±10.9%, but with 2 cycles of 15 minutes it offered no protection. The protective effects at these two therapeutic time windows of remote preconditioning are consistent with those of conventional preconditioning, in which the preconditioning ischemia is induced in the brain itself. Unexpectedly, intermediate preconditioning with 3 cycles of 15 minutes performed 12 hours before stroke also reduced infarct to 24.7±4.7%, which contradicts the current dogma for therapeutic time windows for the conventional preconditioning that has no protection at this time point. In conclusion, remote preconditioning performed in one limb protected against ischemic damage after focal cerebral ischemia. PMID:18201834

Loss of glycogen during preconditioning is not a prerequisite for protection of the rabbit heart.

PubMed

Weinbrenner, C; Wang, P; Downey, J M

1996-01-01

Depletion of glycogen has been proposed as the mechanism of protection from ischemic preconditioning. The hypothesis was tested by seeing whether pharmacological manipulation of preconditioning causes parallel changes in cardiac glycogen content. Five groups of isolated rabbit hearts were studied. Group 1 experienced 30 min of ischemia only. Group 2 (PC) was preconditioned with 5 min of global ischemia followed by 10 min of reperfusion. Group 3 was preconditioned with 5 min exposure to 400 nM bradykinin followed by a 10 min washout period. Group 4 experienced exposure to 10 microM adenosine followed by a 10 min washout period, and the fifth group was also preconditioned with 5 min ischemia and 10 min reperfusion but 100 microM 8-(p-sulfophenyl)theophylline (SPT), which blocks adenosine receptors, was included in the buffer to block preconditioning's protection. Transmural biopsies were taken before treatment, just prior to the 30 min period of global ischemia, and after 30 min of global ischemia. Glycogen in the samples was digested with amyloglucosidase and the resulting glucose was assayed. Baseline glycogen averaged 17.3 +/- 0.6 mumol glucose/g wet weight. After preconditioning glycogen decreased to 13.3 +/- 1.3 mumol glucose/g wet weight (p < 0.005 vs. baseline). Glycogen was similarly depleted after pharmacological preconditioning with adenosine (14.0 +/- 1.0 mumol glucose/g wet weight, p < 0.05 vs. baseline) suggesting a correlation. However, when preconditioning was performed in the presence of SPT, which blocks protection, glycogen was also depleted by the same amount (13.3 +/- 0.7 mumol glucose/g wet weight, p = ns vs. PC). Bradykinin, which also mimics preconditioning, caused no depletion of glycogen (16.3 +/- 0.8 mumol glucose/g wet weight, p = ns vs. baseline). Because preconditioning with bradykinin did not deplete glycogen and because glycogen continued to be low when protection from preconditioning was blocked with SPT, we conclude that loss of glycogen per se does not cause the protection of preconditioning.

Laparoscopic ischemic conditioning of the stomach increases neovascularization of the gastric conduit in patients undergoing esophagectomy for cancer.

PubMed

Pham, Thai H; Melton, Shelby D; McLaren, Patrick J; Mokdad, Ali A; Huerta, Sergio; Wang, David H; Perry, Kyle A; Hardaker, Hope L; Dolan, James P

2017-09-01

Gastric ischemic preconditioning has been proposed to improve blood flow and reduce the incidence of anastomotic complications following esophagectomy with gastric pull-up. This study aimed to evaluate the effect of prolonged ischemic preconditioning on the degree of neovascularization in the distal gastric conduit at the time of esophagectomy. A retrospective review of a prospectively maintained database identified 30 patients who underwent esophagectomy. The patients were divided into three groups: control (no preconditioning, n = 9), partial (short gastric vessel ligation only, n = 8), and complete ischemic preconditioning (left and short gastric vessel ligation, n = 13). Microvessel counts were assessed, using immunohistologic analysis to determine the degree of neovascularization at the distal gastric margin. The groups did not differ in age, gender, BMI, pathologic stage, or cancer subtype. Ischemic preconditioning durations were 163 ± 156 days for partial ischemic preconditioning, compared to 95 ± 50 days for complete ischemic preconditioning (P = 0.2). Immunohistologic analysis demonstrated an increase in microvessel counts of 29% following partial ischemic preconditioning (P = 0.3) and 67% after complete ischemic preconditioning (P < 0.0001), compared to controls. Our study indicates that prolonged ischemic preconditioning is safe and does not interfere with subsequent esophagectomy. Complete ischemic preconditioning increased neovascularization in the distal gastric conduit. © 2017 Wiley Periodicals, Inc.

Weighted graph based ordering techniques for preconditioned conjugate gradient methods

NASA Technical Reports Server (NTRS)

Clift, Simon S.; Tang, Wei-Pai

1994-01-01

We describe the basis of a matrix ordering heuristic for improving the incomplete factorization used in preconditioned conjugate gradient techniques applied to anisotropic PDE's. Several new matrix ordering techniques, derived from well-known algorithms in combinatorial graph theory, which attempt to implement this heuristic, are described. These ordering techniques are tested against a number of matrices arising from linear anisotropic PDE's, and compared with other matrix ordering techniques. A variation of RCM is shown to generally improve the quality of incomplete factorization preconditioners.

Isoflurane preconditioning protects neurons from male and female mice against oxygen and glucose deprivation and is modulated by estradiol only in neurons from female mice.

PubMed

Johnsen, D; Murphy, S J

2011-12-29

The volatile anesthetic, isoflurane, can protect the brain if administered before an insult such as an ischemic stroke. However, this protective "preconditioning" response to isoflurane is specific to males, with females showing an increase in brain damage following isoflurane preconditioning and subsequent focal cerebral ischemia. Innate cell sex is emerging as an important player in neuronal cell death, but its role in the sexually dimorphic response to isoflurane preconditioning has not been investigated. We used an in vitro model of isoflurane preconditioning and ischemia (oxygen and glucose deprivation, OGD) to test the hypotheses that innate cell sex dictates the response to isoflurane preconditioning and that 17β-estradiol attenuates any protective effect from isoflurane preconditioning in neurons via nuclear estrogen receptors. Sex-segregated neuron cultures derived from postnatal day 0-1 mice were exposed to either 0% or 3% isoflurane preconditioning for 1 h. In separate experiments, 17β-estradiol and the non-selective estrogen receptor antagonist ICI 182,780 were added 24 h before preconditioning and then removed at the end of the preconditioning period. Twenty-three hours after preconditioning, all cultures underwent 2 h of OGD. Twenty-four hours following OGD, cell viability was quantified using calcein-AM fluorescence. We observed that isoflurane preconditioning increased cell survival following subsequent OGD regardless of innate cell sex, but that the presence of 17β-estradiol before and during isoflurane preconditioning attenuated this protection only in female neurons independent of nuclear estrogen receptors. We also found that independent of preconditioning treatment, female neurons were less sensitive to OGD compared with male neurons and that transient treatment with 17β-estradiol protected both male and female neurons from subsequent OGD. More studies are needed to determine how cell type, cell sex, and sex steroids like 17β-estradiol may impact on anesthetic preconditioning and subsequent ischemic outcomes in the brain. Copyright © 2011 IBRO. Published by Elsevier Ltd. All rights reserved.

Preconditioning, postconditioning and their application to clinical cardiology.

PubMed

Kloner, Robert A; Rezkalla, Shereif H

2006-05-01

Ischemic preconditioning is a well-established phenomenon first described in experimental preparations in which brief episodes of ischemia/reperfusion applied prior to a longer coronary artery occlusion reduce myocardial infarct size. There are ample correlates of ischemic preconditioning in the clinical realm. Preconditioning mimetic agents that stimulate the biochemical pathways of ischemic preconditioning and protect the heart without inducing ischemia have been examined in numerous experimental studies. However, despite the effectiveness of ischemic preconditioning and preconditioning mimetics for protecting ischemic myocardium, there are no preconditioning-based therapies that are routinely used in clinical medicine at the current time. Part of the problem is the need to administer therapy prior to the known ischemic event. Other issues are that percutaneous coronary intervention technology has advanced so far (with the development of stents and drug-eluting stents) that ischemic preconditioning or preconditioning mimetics have not been needed in most interventional cases. Recent clinical trials such as AMISTAD I and II (Acute Myocardial Infarction STudy of ADenosine) suggest that some preconditioning mimetics may reduce myocardial infarct size when given along with reperfusion or, as in the IONA trial, have benefit on clinical events when administered chronically in patients with known coronary artery disease. It is possible that some of the benefit described for adenosine in the AMISTAD 1 and 2 trials represents a manifestation of the recently described postconditioning phenomenon. It is probable that postconditioning--in which reperfusion is interrupted with brief coronary occlusions and reperfusion sequences--is more likely than preconditioning to be feasible as a clinical application to patients undergoing percutaneous coronary intervention for acute myocardial infarction.

A mass, momentum, and energy conserving, fully implicit, scalable algorithm for the multi-dimensional, multi-species Rosenbluth-Fokker-Planck equation

NASA Astrophysics Data System (ADS)

Taitano, W. T.; Chacón, L.; Simakov, A. N.; Molvig, K.

2015-09-01

In this study, we demonstrate a fully implicit algorithm for the multi-species, multidimensional Rosenbluth-Fokker-Planck equation which is exactly mass-, momentum-, and energy-conserving, and which preserves positivity. Unlike most earlier studies, we base our development on the Rosenbluth (rather than Landau) form of the Fokker-Planck collision operator, which reduces complexity while allowing for an optimal fully implicit treatment. Our discrete conservation strategy employs nonlinear constraints that force the continuum symmetries of the collision operator to be satisfied upon discretization. We converge the resulting nonlinear system iteratively using Jacobian-free Newton-Krylov methods, effectively preconditioned with multigrid methods for efficiency. Single- and multi-species numerical examples demonstrate the advertised accuracy properties of the scheme, and the superior algorithmic performance of our approach. In particular, the discretization approach is numerically shown to be second-order accurate in time and velocity space and to exhibit manifestly positive entropy production. That is, H-theorem behavior is indicated for all the examples we have tested. The solution approach is demonstrated to scale optimally with respect to grid refinement (with CPU time growing linearly with the number of mesh points), and timestep (showing very weak dependence of CPU time with time-step size). As a result, the proposed algorithm delivers several orders-of-magnitude speedup vs. explicit algorithms.

Stimulus-triggered enhancement of chilling tolerance in zebrafish embryos

PubMed Central

Szabó, Katalin; Budai, Csilla; Losonczi, Eszter; Bernáth, Gergely; Csenki-Bakos, Zsolt; Urbányi, Béla; Pribenszky, Csaba; Horváth, Ákos; Cserepes, Judit

2017-01-01

Background Cryopreservation of zebrafish embryos is still an unsolved problem despite market demand and massive efforts to preserve genetic variation among numerous existing lines. Chilled storage of embryos might be a step towards developing successful cryopreservation, but no methods to date have worked. Methods In the present study, we applied a novel strategy to improve the chilling tolerance of zebrafish embryos by introducing a preconditioning hydrostatic pressure treatment to the embryos. In our experiments, 26-somites and Prim-5 stage zebrafish embryos were chilled at 0°C for 24 hours after preconditioning. Embryo survival rate, ability to reach maturation and fertilizing capacity were tested. Results Our results indicate that applied preconditioning technology made it possible for the chilled embryos to develop normally until maturity, and to produce healthy offspring as normal, thus passing on their genetic material successfully. Treated embryos had a significantly higher survival and better developmental rate, moreover the treated group had a higher ratio of normal morphology during continued development. While all controls from chilled embryos died by 30 day-post-fertilization, the treated group reached maturity (~90–120 days) and were able to reproduce, resulting in offspring in expected quantity and quality. Conclusions Based on our results, we conclude that the preconditioning technology represents a significant improvement in zebrafish embryo chilling tolerance, thus enabling a long-time survival. Furthermore, as embryonic development is arrested during chilled storage this technology also provides a solution to synchronize or delay the development. PMID:28166301

[The relationship between ischemic preconditioning-induced infarction size limitation and duration of test myocardial ischemia].

PubMed

Blokhin, I O; Galagudza, M M; Vlasov, T D; Nifontov, E M; Petrishchev, N N

2008-07-01

Traditionally infarction size reduction by ischemic preconditioning is estimated in duration of test ischemia. This approach limits the understanding of real antiischemic efficacy of ischemic preconditioning. Present study was performed in the in vivo rat model of regional myocardial ischemia-reperfusion and showed that protective effect afforded by ischemic preconditioning progressively decreased with prolongation of test ischemia. There were no statistically significant differences in infarction size between control and preconditioned animals when the duration of test ischemia was increased up to 1 hour. Preconditioning ensured maximal infarction-limiting effect in duration of test ischemia varying from 20 to 40 minutes.

Substitution of Hospital Care with Primary Care: Defining the Conditions of Primary Care Plus

PubMed Central

Kroese, Mariëlle Elisabeth Aafje Lydia; Spreeuwenberg, Marieke Dingena; Elissen, Arianne Mathilda Josephus; Meerlo, Ronald Johan; Hanraets, Monique Margaretha Henriëtte; Ruwaard, Dirk

2016-01-01

Objective: To analyse barriers and facilitators in substituting hospital care with primary care to define preconditions for successful implementation. Methods: A descriptive feasibility study was performed to collect information on the feasibility of substituting hospital care with primary care. General practitioners were able to refer patients, about whom they had doubts regarding diagnosis, treatment and/or the need to refer to hospital care, to medical specialists who performed low-complex consultations at general practitioner practices. Qualitative data were collected through interviews with general practitioners and medical specialists, focus groups and notes from meetings in the Netherlands between April 2013 and January 2014. Data were analysed using a conventional content analysis which resulted in categorised barriers, facilitators and policy adjustments, after which preconditions were formulated. Results: The most important preconditions were make arrangements on governmental level, arrange a collective integrated IT-system, determine the appropriate profile for medical specialists, design a referral protocol for eligible patients, arrange deliberation possibilities for general practitioners and medical specialists and formulate a diagnostic protocol. Conclusions: The barriers, facilitators and formulated preconditions provided relevant input to change the design of substituting hospital care with primary care. PMID:27616956

Hypoxic-Preconditioned Bone Marrow Stem Cell Medium Significantly Improves Outcome After Retinal Ischemia in Rats

PubMed Central

Roth, Steven; Dreixler, John C.; Mathew, Biji; Balyasnikova, Irina; Mann, Jacob R.; Boddapati, Venkat; Xue, Lai; Lesniak, Maciej S.

2016-01-01

Purpose We have previously demonstrated the protective effect of bone marrow stem cell (BMSC)-conditioned medium in retinal ischemic injury. We hypothesized here that hypoxic preconditioning of stem cells significantly enhances the neuroprotective effect of the conditioned medium and thereby augments the protective effect in ischemic retina. Methods Rats were subjected to retinal ischemia by increasing intraocular pressure to 130 to 135 mm Hg for 55 minutes. Hypoxic-preconditioned, hypoxic unconditioned, or normoxic medium was injected into the vitreous 24 hours after ischemia ended. Recovery was assessed 7 days after injections by comparing electroretinography measurements, histologic examination, and apoptosis (TUNEL, terminal deoxynucleotidyl transferase–mediated dUTP nick end labeling assay). To compare proteins secreted into the medium in the groups and the effect of hypoxic exposure, we used rat cytokine arrays. Results Eyes injected with hypoxic BMSC–conditioned medium 24 hours after ischemia demonstrated significantly enhanced return of retinal function, decreased retinal ganglion cell layer loss, and attenuated apoptosis compared to those administered normoxic or hypoxic unconditioned medium. Hypoxic-preconditioned medium had 21 significantly increased protein levels compared to normoxic medium. Conclusions The medium from hypoxic-preconditioned BMSCs robustly restored retinal function and prevented cell loss after ischemia when injected 24 hours after ischemia. The protective effect was even more pronounced than in our previous studies of normoxic conditioned medium. Prosurvival signals triggered by the secretome may play a role in this neuroprotective effect. PMID:27367588

Research on the Changes to the Lipid/Polymer Membrane Used in the Acidic Bitterness Sensor Caused by Preconditioning

PubMed Central

Harada, Yuhei; Noda, Junpei; Yatabe, Rui; Ikezaki, Hidekazu; Toko, Kiyoshi

2016-01-01

A taste sensor that uses lipid/polymer membranes can evaluate aftertastes felt by humans using Change in membrane Potential caused by Adsorption (CPA) measurements. The sensor membrane for evaluating bitterness, which is caused by acidic bitter substances such as iso-alpha acid contained in beer, needs an immersion process in monosodium glutamate (MSG) solution, called “MSG preconditioning”. However, what happens to the lipid/polymer membrane during MSG preconditioning is not clear. Therefore, we carried out three experiments to investigate the changes in the lipid/polymer membrane caused by the MSG preconditioning, i.e., measurements of the taste sensor, measurements of the amount of the bitterness substance adsorbed onto the membrane and measurements of the contact angle of the membrane surface. The CPA values increased as the preconditioning process progressed, and became stable after 3 d of preconditioning. The response potentials to the reference solution showed the same tendency of the CPA value change during the preconditioning period. The contact angle of the lipid/polymer membrane surface decreased after 7 d of MSG preconditioning; in short, the surface of the lipid/polymer membrane became hydrophilic during MSG preconditioning. The amount of adsorbed iso-alpha acid was increased until 5 d preconditioning, and then it decreased. In this study, we revealed that the CPA values increased with the progress of MSG preconditioning in spite of the decrease of the amount of iso-alpha acid adsorbed onto the lipid/polymer membrane, and it was indicated that the CPA values increase because the sensor sensitivity was improved by the MSG preconditioning. PMID:26891299

Fully Implicit, Nonlinear 3D Extended Magnetohydrodynamics

NASA Astrophysics Data System (ADS)

Chacon, Luis; Knoll, Dana

2003-10-01

Extended magnetohydrodynamics (XMHD) includes nonideal effects such as nonlinear, anisotropic transport and two-fluid (Hall) effects. XMHD supports multiple, separate time scales that make explicit time differencing approaches extremely inefficient. While a fully implicit implementation promises efficiency without sacrificing numerical accuracy,(D. A. Knoll et al., phJ. Comput. Phys.) 185 (2), 583-611 (2003) the nonlinear nature of the XMHD system and the numerical stiffness associated with the fast waves make this endeavor difficult. Newton-Krylov methods are, however, ideally suited for such a task. These synergistically combine Newton's method for nonlinear convergence, and Krylov techniques to solve the associated Jacobian (linear) systems. Krylov methods can be implemented Jacobian-free and can be preconditioned for efficiency. Successful preconditioning strategies have been developed for 2D incompressible resistive(L. Chacón et al., phJ. Comput. Phys). 178 (1), 15- 36 (2002) and Hall(L. Chacón and D. A. Knoll, phJ. Comput. Phys.), 188 (2), 573-592 (2003) MHD models. These are based on ``physics-based'' ideas, in which knowledge of the physics is exploited to derive well-conditioned (diagonally-dominant) approximations to the original system that are amenable to optimal solver technologies (multigrid). In this work, we will describe the status of the extension of the 2D preconditioning ideas for a 3D compressible, single-fluid XMHD model.

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

NASA Astrophysics Data System (ADS)

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

2017-06-01

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

Preconditioning Strategies for Solving Elliptic Difference Equations on a Multiprocessor.

DTIC Science & Technology

1982-01-01

162, 1977. (MiGr8O] Mitchell, A., Griffiths, D., The Finite Difference Method in Partial Differential Equations , John Wiley & Sons, 1980. [Munk80...ADAL1b T35 AIR FO"CE INST OF TECH WRITG-PATTERSON AFS OH F/6 12/17PR CO ITIONIN STRATEGIES FOR SOLVING ELLIPTIC DIFFERENCE EWA-ETClU) 9UN S C K...TI TLE (ard S.tbr,,I) 5 TYPE OF REP’ORT & F IFIOD C_JVEFO Preconditioning Strategies for Solving Elliptic THESIS/VYYRY#YY0N Difference Equations on

Comparison between iteration schemes for three-dimensional coordinate-transformed saturated-unsaturated flow model

NASA Astrophysics Data System (ADS)

An, Hyunuk; Ichikawa, Yutaka; Tachikawa, Yasuto; Shiiba, Michiharu

2012-11-01

SummaryThree different iteration methods for a three-dimensional coordinate-transformed saturated-unsaturated flow model are compared in this study. The Picard and Newton iteration methods are the common approaches for solving Richards' equation. The Picard method is simple to implement and cost-efficient (on an individual iteration basis). However it converges slower than the Newton method. On the other hand, although the Newton method converges faster, it is more complex to implement and consumes more CPU resources per iteration than the Picard method. The comparison of the two methods in finite-element model (FEM) for saturated-unsaturated flow has been well evaluated in previous studies. However, two iteration methods might exhibit different behavior in the coordinate-transformed finite-difference model (FDM). In addition, the Newton-Krylov method could be a suitable alternative for the coordinate-transformed FDM because it requires the evaluation of a 19-point stencil matrix. The formation of a 19-point stencil is quite a complex and laborious procedure. Instead, the Newton-Krylov method calculates the matrix-vector product, which can be easily approximated by calculating the differences of the original nonlinear function. In this respect, the Newton-Krylov method might be the most appropriate iteration method for coordinate-transformed FDM. However, this method involves the additional cost of taking an approximation at each Krylov iteration in the Newton-Krylov method. In this paper, we evaluated the efficiency and robustness of three iteration methods—the Picard, Newton, and Newton-Krylov methods—for simulating saturated-unsaturated flow through porous media using a three-dimensional coordinate-transformed FDM.

Coral thermal tolerance: tuning gene expression to resist thermal stress.

PubMed

Bellantuono, Anthony J; Granados-Cifuentes, Camila; Miller, David J; Hoegh-Guldberg, Ove; Rodriguez-Lanetty, Mauricio

2012-01-01

The acclimatization capacity of corals is a critical consideration in the persistence of coral reefs under stresses imposed by global climate change. The stress history of corals plays a role in subsequent response to heat stress, but the transcriptomic changes associated with these plastic changes have not been previously explored. In order to identify host transcriptomic changes associated with acquired thermal tolerance in the scleractinian coral Acropora millepora, corals preconditioned to a sub-lethal temperature of 3°C below bleaching threshold temperature were compared to both non-preconditioned corals and untreated controls using a cDNA microarray platform. After eight days of hyperthermal challenge, conditions under which non-preconditioned corals bleached and preconditioned corals (thermal-tolerant) maintained Symbiodinium density, a clear differentiation in the transcriptional profiles was revealed among the condition examined. Among these changes, nine differentially expressed genes separated preconditioned corals from non-preconditioned corals, with 42 genes differentially expressed between control and preconditioned treatments, and 70 genes between non-preconditioned corals and controls. Differentially expressed genes included components of an apoptotic signaling cascade, which suggest the inhibition of apoptosis in preconditioned corals. Additionally, lectins and genes involved in response to oxidative stress were also detected. One dominant pattern was the apparent tuning of gene expression observed between preconditioned and non-preconditioned treatments; that is, differences in expression magnitude were more apparent than differences in the identity of genes differentially expressed. Our work revealed a transcriptomic signature underlying the tolerance associated with coral thermal history, and suggests that understanding the molecular mechanisms behind physiological acclimatization would be critical for the modeling of reefs in impending climate change scenarios.

Coral Thermal Tolerance: Tuning Gene Expression to Resist Thermal Stress

PubMed Central

Bellantuono, Anthony J.; Granados-Cifuentes, Camila; Miller, David J.; Hoegh-Guldberg, Ove; Rodriguez-Lanetty, Mauricio

2012-01-01

The acclimatization capacity of corals is a critical consideration in the persistence of coral reefs under stresses imposed by global climate change. The stress history of corals plays a role in subsequent response to heat stress, but the transcriptomic changes associated with these plastic changes have not been previously explored. In order to identify host transcriptomic changes associated with acquired thermal tolerance in the scleractinian coral Acropora millepora, corals preconditioned to a sub-lethal temperature of 3°C below bleaching threshold temperature were compared to both non-preconditioned corals and untreated controls using a cDNA microarray platform. After eight days of hyperthermal challenge, conditions under which non-preconditioned corals bleached and preconditioned corals (thermal-tolerant) maintained Symbiodinium density, a clear differentiation in the transcriptional profiles was revealed among the condition examined. Among these changes, nine differentially expressed genes separated preconditioned corals from non-preconditioned corals, with 42 genes differentially expressed between control and preconditioned treatments, and 70 genes between non-preconditioned corals and controls. Differentially expressed genes included components of an apoptotic signaling cascade, which suggest the inhibition of apoptosis in preconditioned corals. Additionally, lectins and genes involved in response to oxidative stress were also detected. One dominant pattern was the apparent tuning of gene expression observed between preconditioned and non-preconditioned treatments; that is, differences in expression magnitude were more apparent than differences in the identity of genes differentially expressed. Our work revealed a transcriptomic signature underlying the tolerance associated with coral thermal history, and suggests that understanding the molecular mechanisms behind physiological acclimatization would be critical for the modeling of reefs in impending climate change scenarios. PMID:23226355

Roles of thioredoxin in nitric oxide-dependent preconditioning-induced tolerance against MPTP neurotoxin

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

Chiueh, C.C.; Andoh, Tsugunobu; Chock, P. Boon

2005-09-01

Hormesis, a stress tolerance, can be induced by ischemic preconditioning stress. In addition to preconditioning, it may be induced by other means, such as gas anesthetics. Preconditioning mechanisms, which may be mediated by reprogramming survival genes and proteins, are obscure. A known neurotoxicant, 1-Methyl-4-phenyl-1,2,3,6-tetrahydropyridine (MPTP), causes less neurotoxicity in the mice that are preconditioned. Pharmacological evidences suggest that the signaling pathway of {center_dot}NO-cGMP-PKG (protein kinase G) may mediate preconditioning phenomenon. We developed a human SH-SY5Y cell model for investigating {sup {center_dot}}NO-mediated signaling pathway, gene regulation, and protein expression following a sublethal preconditioning stress caused by a brief 2-h serum deprivation.more » Preconditioned human SH-SY5Y cells are more resistant against severe oxidative stress and apoptosis caused by lethal serum deprivation and 1-mehtyl-4-phenylpyridinium (MPP{sup +}). Both sublethal and lethal oxidative stress caused by serum withdrawal increased neuronal nitric oxide synthase (nNOS/NOS1) expression and {sup {center_dot}}NO levels to a similar extent. In addition to free radical scavengers, inhibition of nNOS, guanylyl cyclase, and PKG blocks hormesis induced by preconditioning. S-nitrosothiols and 6-Br-cGMP produce a cytoprotection mimicking the action of preconditioning tolerance. There are two distinct cGMP-mediated survival pathways: (i) the up-regulation of a redox protein thioredoxin (Trx) for elevating mitochondrial levels of antioxidant protein Mn superoxide dismutase (MnSOD) and antiapoptotic protein Bcl-2, and (ii) the activation of mitochondrial ATP-sensitive potassium channels [K(ATP)]. Preconditioning induction of Trx increased tolerance against MPP{sup +}, which was blocked by Trx mRNA antisense oligonucleotide and Trx reductase inhibitor. It is concluded that Trx plays a pivotal role in {sup {center_dot}}NO-dependent preconditioning hormesis against MPTP/MPP{sup +}.« less

Preconditioning mesenchymal stem cells with the mood stabilizers lithium and valproic acid enhances therapeutic efficacy in a mouse model of Huntington's disease.

PubMed

Linares, Gabriel R; Chiu, Chi-Tso; Scheuing, Lisa; Leng, Yan; Liao, Hsiao-Mei; Maric, Dragan; Chuang, De-Maw

2016-07-01

Huntington's disease (HD) is a fatal neurodegenerative disorder caused by CAG repeat expansions in the huntingtin gene. Although, stem cell-based therapy has emerged as a potential treatment for neurodegenerative diseases, limitations remain, including optimizing delivery to the brain and donor cell loss after transplantation. One strategy to boost cell survival and efficacy is to precondition cells before transplantation. Because the neuroprotective actions of the mood stabilizers lithium and valproic acid (VPA) induce multiple pro-survival signaling pathways, we hypothesized that preconditioning bone marrow-derived mesenchymal stem cells (MSCs) with lithium and VPA prior to intranasal delivery to the brain would enhance their therapeutic efficacy, and thereby facilitate functional recovery in N171-82Q HD transgenic mice. MSCs were treated in the presence or absence of combined lithium and VPA, and were then delivered by brain-targeted single intranasal administration to eight-week old HD mice. Histological analysis confirmed the presence of MSCs in the brain. Open-field test revealed that ambulatory distance and mean velocity were significantly improved in HD mice that received preconditioned MSCs, compared to HD vehicle-control and HD mice transplanted with non-preconditioned MSCs. Greater benefits on motor function were observed in HD mice given preconditioned MSCs, while HD mice treated with non-preconditioned MSCs showed no functional benefits. Moreover, preconditioned MSCs reduced striatal neuronal loss and huntingtin aggregates in HD mice. Gene expression profiling of preconditioned MSCs revealed a robust increase in expression of genes involved in trophic effects, antioxidant, anti-apoptosis, cytokine/chemokine receptor, migration, mitochondrial energy metabolism, and stress response signaling pathways. Consistent with this finding, preconditioned MSCs demonstrated increased survival after transplantation into the brain compared to non-preconditioned cells. Our results suggest that preconditioning stem cells with the mood stabilizers lithium and VPA before transplantation may serve as an effective strategy for enhancing the therapeutic efficacy of stem cell-based therapies. Copyright © 2016. Published by Elsevier Inc.

A nonrecursive 'Order N' preconditioned conjugate gradient/range space formulation of MDOF dynamics

NASA Technical Reports Server (NTRS)

Kurdila, A. J.; Menon, R.; Sunkel, John

1991-01-01

This paper addresses the requirements of present-day mechanical system simulations of algorithms that induce parallelism on a fine scale and of transient simulation methods which must be automatically load balancing for a wide collection of system topologies and hardware configurations. To this end, a combination range space/preconditioned conjugage gradient formulation of multidegree-of-freedon dynamics is developed, which, by employing regular ordering of the system connectivity graph, makes it possible to derive an extremely efficient preconditioner from the range space metric (as opposed to the system coefficient matrix). Because of the effectiveness of the preconditioner, the method can achieve performance rates that depend linearly on the number of substructures. The method, termed 'Order N' does not require the assembly of system mass or stiffness matrices, and is therefore amenable to implementation on work stations. Using this method, a 13-substructure model of the Space Station was constructed.

Numerical Computation of Subsonic Conical Diffuser Flows with Nonuniform Turbulent Inlet Conditions

DTIC Science & Technology

1977-09-01

Gauss - Seidel Point Iteration Method . . . . . . . . . . . . . . . 7.0 FACTORS AFFECTING THE RATE OF CONVERGENCE OF THE POINT...can be solved in several ways. For simplicity, a standard Gauss - Seidel iteration method is used to obtain the solution . The method updates the...FACTORS AFFECTING THE RATE OF CONVERGENCE OF THE POINT ITERATION ,ŘETHOD The advantage of using the Gauss - Seidel point iteration method to

Variational iteration method — a promising technique for constructing equivalent integral equations of fractional order

NASA Astrophysics Data System (ADS)

Wang, Yi-Hong; Wu, Guo-Cheng; Baleanu, Dumitru

2013-10-01

The variational iteration method is newly used to construct various integral equations of fractional order. Some iterative schemes are proposed which fully use the method and the predictor-corrector approach. The fractional Bagley-Torvik equation is then illustrated as an example of multi-order and the results show the efficiency of the variational iteration method's new role.

A novel iterative scheme and its application to differential equations.

PubMed

Khan, Yasir; Naeem, F; Šmarda, Zdeněk

2014-01-01

The purpose of this paper is to employ an alternative approach to reconstruct the standard variational iteration algorithm II proposed by He, including Lagrange multiplier, and to give a simpler formulation of Adomian decomposition and modified Adomian decomposition method in terms of newly proposed variational iteration method-II (VIM). Through careful investigation of the earlier variational iteration algorithm and Adomian decomposition method, we find unnecessary calculations for Lagrange multiplier and also repeated calculations involved in each iteration, respectively. Several examples are given to verify the reliability and efficiency of the 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.

Myeloablation-associated deletion of ORF4 in a human coronavirus 229E infection.

PubMed

Greninger, Alexander L; Pepper, Gregory; Shean, Ryan C; Cent, Anne; Palileo, Isabel; Kuypers, Jane M; Schiffer, Joshua T; Jerome, Keith R

2017-01-01

We describe metagenomic next-generation sequencing (mNGS) of a human coronavirus 229E from a patient with AML and persistent upper respiratory symptoms, who underwent hematopoietic cell transplantation (HCT). mNGS revealed a 548-nucleotide deletion, which comprised the near entirety of the ORF4 gene, and no minor allele variants were detected to suggest a mixed infection. As part of her pre-HCT conditioning regimen, the patient received myeloablative treatment with cyclophosphamide and 12 Gy total body irradiation. Iterative sequencing and RT-PCR confirmation of four respiratory samples over the 4-week peritransplant period revealed that the pre-conditioning strain contained an intact ORF4 gene, while the deletion strain appeared just after conditioning and persisted over a 2.5-week period. This sequence represents one of the largest genomic deletions detected in a human RNA virus and describes large-scale viral mutation associated with myeloablation for HCT.

Iterative Methods for the Non-LTE Transfer of Polarized Radiation: Resonance Line Polarization in One-dimensional Atmospheres

NASA Astrophysics Data System (ADS)

Trujillo Bueno, Javier; Manso Sainz, Rafael

1999-05-01

This paper shows how to generalize to non-LTE polarization transfer some operator splitting methods that were originally developed for solving unpolarized transfer problems. These are the Jacobi-based accelerated Λ-iteration (ALI) method of Olson, Auer, & Buchler and the iterative schemes based on Gauss-Seidel and successive overrelaxation (SOR) iteration of Trujillo Bueno and Fabiani Bendicho. The theoretical framework chosen for the formulation of polarization transfer problems is the quantum electrodynamics (QED) theory of Landi Degl'Innocenti, which specifies the excitation state of the atoms in terms of the irreducible tensor components of the atomic density matrix. This first paper establishes the grounds of our numerical approach to non-LTE polarization transfer by concentrating on the standard case of scattering line polarization in a gas of two-level atoms, including the Hanle effect due to a weak microturbulent and isotropic magnetic field. We begin demonstrating that the well-known Λ-iteration method leads to the self-consistent solution of this type of problem if one initializes using the ``exact'' solution corresponding to the unpolarized case. We show then how the above-mentioned splitting methods can be easily derived from this simple Λ-iteration scheme. We show that our SOR method is 10 times faster than the Jacobi-based ALI method, while our implementation of the Gauss-Seidel method is 4 times faster. These iterative schemes lead to the self-consistent solution independently of the chosen initialization. The convergence rate of these iterative methods is very high; they do not require either the construction or the inversion of any matrix, and the computing time per iteration is similar to that of the Λ-iteration method.

The in vitro preconditioning of myoblasts to enhance subsequent survival in an in vivo tissue engineering chamber model.

PubMed

Tilkorn, Daniel J; Davies, E Michele; Keramidaris, Effie; Dingle, Aaron M; Gerrand, Yi-Wen; Taylor, Caroline J; Han, Xiao Lian; Palmer, Jason A; Penington, Anthony J; Mitchell, Christina A; Morrison, Wayne A; Dusting, Gregory J; Mitchell, Geraldine M

2012-05-01

The effects of in vitro preconditioning protocols on the ultimate survival of myoblasts implanted in an in vivo tissue engineering chamber were examined. In vitro testing: L6 myoblasts were preconditioned by heat (42 °C; 1.5 h); hypoxia (<8% O(2); 1.5 h); or nitric oxide donors: S-nitroso-N-acetylpenicillamine (SNAP, 200 μM, 1.5 h) or 1-[N-(2-aminoethyl)-N-(2-aminoethyl)amino]-diazen-1-ium-1,2-diolate (DETA-NONOate, 500 μM, 7 h). Following a rest phase preconditioned cells were exposed to 24 h hypoxia, and demonstrated minimal overall cell loss, whilst controls (not preconditioned, but exposed to 24 h hypoxia) demonstrated a 44% cell loss. Phosphoimmunoblot analysis of pro-survival signaling pathways revealed significant activation of serine threonine kinase Akt with DETA-NONOate (p < 0.01) and heat preconditioning (p < 0.05). DETA-NONOate also activated ERK 1/2 signaling (p < 0.05). In vivo implantation: 100,000 preconditioned (heat, hypoxia, or DETA-NONOate) myoblasts were implanted in SCID mouse tissue engineering chambers. 100,000 (not preconditioned) myoblasts were implanted in control chambers. At 3 weeks, morphometric assessment of surviving myoblasts indicated myoblast percent volume (p = 0.012) and myoblasts/mm(2) (p = 0.0005) overall significantly increased in preconditioned myoblast chambers compared to control, with DETA-NONOate-preconditioned myoblasts demonstrating the greatest increase in survival (p = 0.007 and p = 0.001 respectively). DETA-NONOate therefore has potential therapeutic benefits to significantly improve survival of transplanted cells. Copyright © 2012 Elsevier Ltd. All rights reserved.

Preconditioning Provides Neuroprotection in Models of CNS Disease: Paradigms and Clinical Significance

PubMed Central

Stetler, R. Anne; Leak, Rehana K.; Gan, Yu; Li, Peiying; Hu, Xiaoming; Jing, Zheng; Chen, Jun; Zigmond, Michael J.; Gao, Yanqin

2014-01-01

Preconditioning is a phenomenon in which brief episodes of a sublethal insult induce robust protection against subsequent lethal injuries. Preconditioning has been observed in multiple organisms and can occur in the brain as well as other tissues. Extensive animal studies suggest that the brain can be preconditioned to resist acute injuries, such as ischemic stroke, neonatal hypoxia/ischemia, trauma, and agents that are used in models of neurodegenerative diseases, such as Parkinson’s disease and Alzheimer’s disease. Effective preconditioning stimuli are numerous and diverse, ranging from transient ischemia, hypoxia, hyperbaric oxygen, hypothermia and hyperthermia, to exposure to neurotoxins and pharmacological agents. The phenomenon of “cross-tolerance,” in which a sublethal stress protects against a different type of injury, suggests that different preconditioning stimuli may confer protection against a wide range of injuries. Research conducted over the past few decades indicates that brain preconditioning is complex, involving multiple effectors such as metabolic inhibition, activation of extra- and intracellular defense mechanisms, a shift in the neuronal excitatory/inhibitory balance, and reduction in inflammatory sequelae. An improved understanding of brain preconditioning should help us identify innovative therapeutic strategies that prevent or at least reduce neuronal damage in susceptible patients. In this review, we focus on the experimental evidence of preconditioning in the brain and systematically survey the models used to develop paradigms for neuroprotection, and then discuss the clinical potential of brain preconditioning. In a subsequent components of this two-part series, we will discuss the cellular and molecular events that are likely to underlie these phenomena. PMID:24389580

Exploring the Role of TRPV and CGRP in Adenosine Preconditioning and Remote Hind Limb Preconditioning-Induced Cardioprotection in Rats.

PubMed

Singh, Amritpal; Randhawa, Puneet Kaur; Bali, Anjana; Singh, Nirmal; Jaggi, Amteshwar Singh

2017-04-01

The cardioprotective effects of remote hind limb preconditioning (RIPC) are well known, but mechanisms by which protection occurs still remain to be explored. Therefore, the present study was designed to investigate the role of TRPV and CGRP in adenosine and remote preconditioning-induced cardioprotection, using sumatriptan, a CGRP release inhibitor and ruthenium red, a TRPV inhibitor, in rats. For remote preconditioning, a pressure cuff was tied around the hind limb of the rat and was inflated with air up to 150 mmHg to produce ischemia in the hind limb and during reperfusion pressure was released. Four cycles of ischemia and reperfusion, each consisting of 5 min of inflation and 5 min of deflation of pressure cuff were used to produce remote limb preconditioning. An ex vivo Langendorff's isolated rat heart model was used to induce ischemia reperfusion injury by 30 min of global ischemia followed by 120 min of reperfusion. RIPC demonstrated a significant decrease in ischemia reperfusion-induced significant myocardial injury in terms of increase in LDH, CK, infarct size and decrease in LVDP, +dp/dt max and -dp/dt min . Moreover, pharmacological preconditioning with adenosine produced cardioprotective effects in a similar manner to RIPC. Pretreatment with sumatriptan, a CGRP release blocker, abolished RIPC and adenosine preconditioning-induced cardioprotective effects. Administration of ruthenium red, a TRPV inhibitor, also abolished adenosine preconditioning-induced cardioprotection. It may be proposed that the cardioprotective effects of adenosine and remote preconditioning are possibly mediated through activation of a TRPV channels and consequent, release of CGRP.

Effect of preconditioning on silver leaching and bromide removal properties of silver-impregnated activated carbon (SIAC).

PubMed

Rajaeian, Babak; Allard, Sébastien; Joll, Cynthia; Heitz, Anna

2018-07-01

Silver impregnated activated carbon (SIAC) has been found to be effective in mitigating the formation of brominated-disinfection by products during drinking water treatment. However, there are still uncertainties regarding its silver leaching properties, and strategies for the prevention of silver leaching have remained elusive. This study focused on the evaluation of one type of commercially available SIAC for its ability to remove bromide while minimising silver leaching from the material. Both synthetic and real water matrices were tested. Depending on solution pH, it was found that changing the surface charge properties of SIAC, as measured by the point of zero charge pH, can result in additional bromide removal while minimising the extent of silver leaching. To better understand the mechanism of silver leaching from the SIAC, eight preconditioning environments, i.e. variable pH and ionic strength were tested for a fixed amount of SIAC and two preconditioning environments were selected for a more detailed investigation. Experiments carried out in synthetic water showed that preconditioning at pH 10.4 did not deteriorate the capacity of SIAC to remove bromide, but significantly decreased the release of silver in the form of ionic silver (Ag + ), silver bromide (AgBr) and silver chloride (AgCl) from 40% for the pristine to 3% for the treated SIAC. This was confirmed using a groundwater sample. These results suggest that preconditioned SIAC has the potential to be an effective method for bromide removal with minimised silver leaching in a long-term field application for drinking water production. Copyright © 2018 Elsevier Ltd. All rights reserved.

Possible role of thromboxane A2 in remote hind limb preconditioning-induced cardioprotection.

PubMed

Sharma, Roohani; Randhawa, Puneet Kaur; Singh, Nirmal; Jaggi, Amteshwar Singh

2016-01-01

Remote hind limb preconditioning (RIPC) is a protective strategy in which short episodes of ischemia and reperfusion in a remote organ (hind limb) protects the target organ (heart) against sustained ischemic reperfusion injury. The present study was designed to investigate the possible role of thromboxane A2 in RIPC-induced cardioprotection in rats. Remote hind limb preconditioning was performed by four episodes of 5 min of inflation and 5 min of deflation of pressure cuff. Occlusion of the hind limb with blood pressure cuff is most feasible, non-invasive, clinically relevant, and safe method for inducing RIPC. Isolated rat hearts were perfused on Langendorff apparatus and were subjected to global ischemia for 30 min followed by 120-min reperfusion. The levels of lactate dehydrogenase (LDH) and creatine kinase (CK) were measured in coronary effluent to assess the degree of myocardial injury. The extent of myocardial infarct size along with the functional parameters including left ventricular developed pressure (LVDP), dp/dtmax, and dp/dtmin were also measured. Ozagrel (thromboxane synthase inhibitor) and seratrodast (thromboxane A2 receptor antagonist) were employed as pharmacological modulators of thromboxane A2. Remote hind limb preconditioning significantly attenuated ischemia/reperfusion-induced myocardial injury and produced cardioprotective effects. However, administration of ozagrel and seratrodast completely abolished the cardioprotective effects of RIPC suggesting the key role of thromboxane A2 in RIPC-induced cardioprotection. It may be concluded that brief episodes of preconditioning ischemia and reperfusion activates the thromboxane synthase enzyme that produces thromboxane A2, which may elicit cardioprotection either involving humoral or neurogenic pathway.

Enhanced shock wave generation via pre-breakdown acceleration using water electrolysis in negative streamer pulsed spark discharges

NASA Astrophysics Data System (ADS)

Lee, Kern; Chung, Kyoung-Jae; Hwang, Y. S.

2018-03-01

This paper presents a method for enhancement of shock waves generated from underwater pulsed spark discharges with negative (anode-directed) subsonic streamers, for which the pre-breakdown process is accelerated by preconditioning a gap with water electrolysis. Hydrogen microbubbles are produced at the cathode by the electrolysis and move towards the anode during the preconditioning phase. The numbers and spatial distributions of the microbubbles vary with the amplitude and duration of each preconditioning pulse. Under our experimental conditions, the optimum pulse duration is determined to be ˜250 ms at a pulse voltage of 400 V, where the buoyancy force overwhelms the electric force and causes the microbubbles to be swept out from the water gap. When a high-voltage pulse is applied to the gap just after the preconditioning pulse, the pre-breakdown process is significantly accelerated in the presence of the microbubbles. At the optimum preconditioning pulse duration, the average breakdown delay is reduced by 87% and, more importantly, the energy consumed during the pre-breakdown period decreases by 83%. This reduced energy consumption during the pre-breakdown period, when combined with the morphological advantages of negative streamers, such as thicker and longer stalks, leads to a significant improvement in the measured peak pressure (˜40%) generated by the underwater pulsed spark discharge. This acceleration of pre-breakdown using electrolysis overcomes the biggest drawback of negative subsonic discharges, which is slow vapor bubble formation due to screening effects, and thus enhances the efficiency of the shock wave generation process using pulsed spark discharges in water.

Optimised Iteration in Coupled Monte Carlo - Thermal-Hydraulics Calculations

NASA Astrophysics Data System (ADS)

Hoogenboom, J. Eduard; Dufek, Jan

2014-06-01

This paper describes an optimised iteration scheme for the number of neutron histories and the relaxation factor in successive iterations of coupled Monte Carlo and thermal-hydraulic reactor calculations based on the stochastic iteration method. The scheme results in an increasing number of neutron histories for the Monte Carlo calculation in successive iteration steps and a decreasing relaxation factor for the spatial power distribution to be used as input to the thermal-hydraulics calculation. The theoretical basis is discussed in detail and practical consequences of the scheme are shown, among which a nearly linear increase per iteration of the number of cycles in the Monte Carlo calculation. The scheme is demonstrated for a full PWR type fuel assembly. Results are shown for the axial power distribution during several iteration steps. A few alternative iteration method are also tested and it is concluded that the presented iteration method is near optimal.

miR-21 Contributes to Xenon-conferred Amelioration of Renal Ischemia–Reperfusion Injury in Mice

PubMed Central

Jia, Ping; Teng, Jie; Zou, Jianzhou; Fang, Yi; Zhang, Xiaoyan; Bosnjak, Zeljko J.; Liang, Mingyu; Ding, Xiaoqiang

2015-01-01

Background MicroRNAs participate in the regulation of numerous physiological and disease processes. The in vivo role of microRNAs in anesthetics-conferred organoprotection is unknown. Methods Mice were exposed for 2 h to either 70% xenon, or 70% nitrogen, 24 h before the induction of renal ischemia-reperfusion injury. The role of microRNA, miR-21, in renal protection conferred by the delayed xenon preconditioning was examined using in vivo knockdown of miR-21 and analysis of miR-21 target pathways. Results Xenon preconditioning provided morphologic and functional protection against renal ischemia-reperfusion injury (n = 6), characterized by attenuation of renal tubular damage, apoptosis, and oxidative stress. Xenon preconditioning significantly increased the expression of miR-21 in the mouse kidney. A locked nucleic acid-modified anti–miR-21, given before xenon preconditioning, knocked down miR-21 effectively, and exacerbated subsequent renal ischemia-reperfusion injury. Mice treated with anti–miR-21 and ischemia-reperfusion injury showed significantly higher serum creatinine than antiscrambled oligonucleotides-treated mice, 24 h after ischemia-reperfusion (1.37 ± 0.28 vs. 0.81 ± 0.14 mg/dl; n = 5; P < 0.05). Knockdown of miR-21 induced significant up-regulation of programmed cell death protein 4 and phosphatase and tensin homolog deleted on chromosome 10, two proapoptotic target effectors of miR-21, and resulted in significant down-regulation of phosphorylated protein kinase B and increased tubular cell apoptosis. In addition, xenon preconditioning up-regulated hypoxia-inducible factor-1α and its downstream effector vascular endothelial growth factor in a time-dependent manner. Knockdown of miR-21 resulted in a significant decrease of hypoxia-inducible factor-1α. Conclusions These results indicate that miR-21 contributes to the renoprotective effect of xenon preconditioning. PMID:23681145

An iterative method for near-field Fresnel region polychromatic phase contrast imaging

NASA Astrophysics Data System (ADS)

Carroll, Aidan J.; van Riessen, Grant A.; Balaur, Eugeniu; Dolbnya, Igor P.; Tran, Giang N.; Peele, Andrew G.

2017-07-01

We present an iterative method for polychromatic phase contrast imaging that is suitable for broadband illumination and which allows for the quantitative determination of the thickness of an object given the refractive index of the sample material. Experimental and simulation results suggest the iterative method provides comparable image quality and quantitative object thickness determination when compared to the analytical polychromatic transport of intensity and contrast transfer function methods. The ability of the iterative method to work over a wider range of experimental conditions means the iterative method is a suitable candidate for use with polychromatic illumination and may deliver more utility for laboratory-based x-ray sources, which typically have a broad spectrum.

New methods of testing nonlinear hypothesis using iterative NLLS estimator

NASA Astrophysics Data System (ADS)

Mahaboob, B.; Venkateswarlu, B.; Mokeshrayalu, G.; Balasiddamuni, P.

2017-11-01

This research paper discusses the method of testing nonlinear hypothesis using iterative Nonlinear Least Squares (NLLS) estimator. Takeshi Amemiya [1] explained this method. However in the present research paper, a modified Wald test statistic due to Engle, Robert [6] is proposed to test the nonlinear hypothesis using iterative NLLS estimator. An alternative method for testing nonlinear hypothesis using iterative NLLS estimator based on nonlinear hypothesis using iterative NLLS estimator based on nonlinear studentized residuals has been proposed. In this research article an innovative method of testing nonlinear hypothesis using iterative restricted NLLS estimator is derived. Pesaran and Deaton [10] explained the methods of testing nonlinear hypothesis. This paper uses asymptotic properties of nonlinear least squares estimator proposed by Jenrich [8]. The main purpose of this paper is to provide very innovative methods of testing nonlinear hypothesis using iterative NLLS estimator, iterative NLLS estimator based on nonlinear studentized residuals and iterative restricted NLLS estimator. Eakambaram et al. [12] discussed least absolute deviation estimations versus nonlinear regression model with heteroscedastic errors and also they studied the problem of heteroscedasticity with reference to nonlinear regression models with suitable illustration. William Grene [13] examined the interaction effect in nonlinear models disused by Ai and Norton [14] and suggested ways to examine the effects that do not involve statistical testing. Peter [15] provided guidelines for identifying composite hypothesis and addressing the probability of false rejection for multiple hypotheses.

LONG-TERM PRECONDITIONING OF PLANTLETS: A PRACTICAL METHOD FOR ENHANCING SURVIVAL OF PINEAPPLE (Ananas comosus Merr.) SHOOT TIPS CRYOPRESERVED USING VITRIFICATION.

PubMed

Hu, W H; Liu, S F; Liaw, S I

2015-01-01

The purpose of this study was to develop an efficient cryopreservation protocol for pineapple (Ananas comosus Merr.) shoot tips. The optimal state of pineapple plantlets was investigated by using sucrose preconditioning to enhance survival after cryostorage. To achieve a suitable state of plantlets before cryopreservation, 0.2 M to 0.4 M sucrose concentrations combined with short- (0-7 days), medium- (15-30 days), and long-term (75-150 days) preconditioning periods were compared. The highest survival (100 %) was achieved using the following procedure: intact plantlets underwent long-term preconditioning with 0.2 M sucrose for 135 days, dissected shoot tips were treated with a loading solution containing 2.0 M glycerol + 0.4 M sucrose for 60 min at 25 degree and the shoot tips were dehydrated in PVS2 for 2h at 0 degree C before being plunged in liquid nitrogen. Rewarming was conducted in a water-bath for 30 s at 40 degree C and PVS2 was replaced with a 1.2 M sucrose solution for 30 min at 25 degree C. The shoot tips were transferred on semisolid medium and left in the dark for 1 week, then in dim light for 3 weeks.

Ischemic preconditioning protects against gap junctional uncoupling in cardiac myofibroblasts.

PubMed

Sundset, Rune; Cooper, Marie; Mikalsen, Svein-Ole; Ytrehus, Kirsti

2004-01-01

Ischemic preconditioning increases the heart's tolerance to a subsequent longer ischemic period. The purpose of this study was to investigate the role of gap junction communication in simulated preconditioning in cultured neonatal rat cardiac myofibroblasts. Gap junctional intercellular communication was assessed by Lucifer yellow dye transfer. Preconditioning preserved intercellular coupling after prolonged ischemia. An initial reduction in coupling in response to the preconditioning stimulus was also observed. This may protect neighboring cells from damaging substances produced during subsequent regional ischemia in vivo, and may preserve gap junctional communication required for enhanced functional recovery during subsequent reperfusion.

Solution of Cubic Equations by Iteration Methods on a Pocket Calculator

ERIC Educational Resources Information Center

Bamdad, Farzad

2004-01-01

A method to provide students a vision of how they can write iteration programs on an inexpensive programmable pocket calculator, without requiring a PC or a graphing calculator is developed. Two iteration methods are used, successive-approximations and bisection methods.

Role of Phosphatidylinositol-3 Kinase Pathway in NMDA Preconditioning: Different Mechanisms for Seizures and Hippocampal Neuronal Degeneration Induced by Quinolinic Acid.

PubMed

Constantino, Leandra C; Binder, Luisa B; Vandresen-Filho, Samuel; Viola, Giordano G; Ludka, Fabiana K; Lopes, Mark W; Leal, Rodrigo B; Tasca, Carla I

2018-04-20

N-methyl D-aspartate (NMDA) preconditioning is evoked by the administration of a subtoxic dose of NMDA and is protective against neuronal excitotoxicity. This effect may involve a diversity of targets and cell signaling cascades associated to neuroprotection. Phosphatidylinositol-3 kinase/protein kinase B (PI3K/Akt) and mitogen-activated protein kinases (MAPKs) such as extracellular regulated protein kinase 1/2 (ERK1/2) and p38 MAPK pathways play a major role in neuroprotective mechanisms. However, their involvement in NMDA preconditioning was not yet fully investigated. The present study aimed to evaluate the effect of NMDA preconditioning on PI3K/Akt, ERK1/2, and p38 MAPK pathways in the hippocampus of mice and characterize the involvement of PI3K on NMDA preconditioning-evoked prevention of seizures and hippocampal cell damage induced by quinolinic acid (QA). Thus, mice received wortmannin (a PI3K inhibitor) and 15 min later a subconvulsant dose of NMDA (preconditioning) or saline. After 24 h of this treatment, an intracerebroventricular QA infusion was administered. Phosphorylation levels and total content of Akt, glycogen synthase protein kinase-3β (GSK-3β), ERK1/2, and p38 MAPK were not altered after 24 h of NMDA preconditioning with or without wortmmanin pretreatment. Moreover, after QA administration, behavioral seizures, hippocampal neuronal degeneration, and Akt activation were evaluated. Inhibition of PI3K pathway was effective in abolishing the protective effect of NMDA preconditioning against QA-induced seizures, but did not modify neuronal protection promoted by preconditioning as evaluated by Fluoro-Jade B staining. The study confirms that PI3K participates in the mechanism of protection induced by NMDA preconditioning against QA-induced seizures. Conversely, NMDA preconditioning-evoked protection against neuronal degeneration is not altered by PI3K signaling pathway inhibition. These results point to differential mechanisms regarding protection against a behavioral and cellular manifestation of neural damage.

Direct determination of one-dimensional interphase structures using normalized crystal truncation rod analysis

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

Kawaguchi, Tomoya; Liu, Yihua; Reiter, Anthony

Here, a one-dimensional non-iterative direct method was employed for normalized crystal truncation rod analysis. The non-iterative approach, utilizing the Kramers–Kronig relation, avoids the ambiguities due to an improper initial model or incomplete convergence in the conventional iterative methods. The validity and limitations of the present method are demonstrated through both numerical simulations and experiments with Pt(111) in a 0.1 M CsF aqueous solution. The present method is compared with conventional iterative phase-retrieval methods.

Direct determination of one-dimensional interphase structures using normalized crystal truncation rod analysis

DOE PAGES

Kawaguchi, Tomoya; Liu, Yihua; Reiter, Anthony; ...

2018-04-20

Here, a one-dimensional non-iterative direct method was employed for normalized crystal truncation rod analysis. The non-iterative approach, utilizing the Kramers–Kronig relation, avoids the ambiguities due to an improper initial model or incomplete convergence in the conventional iterative methods. The validity and limitations of the present method are demonstrated through both numerical simulations and experiments with Pt(111) in a 0.1 M CsF aqueous solution. The present method is compared with conventional iterative phase-retrieval methods.

Fourth-order numerical solutions of diffusion equation by using SOR method with Crank-Nicolson approach

NASA Astrophysics Data System (ADS)

Muhiddin, F. A.; Sulaiman, J.

2017-09-01

The aim of this paper is to investigate the effectiveness of the Successive Over-Relaxation (SOR) iterative method by using the fourth-order Crank-Nicolson (CN) discretization scheme to derive a five-point Crank-Nicolson approximation equation in order to solve diffusion equation. From this approximation equation, clearly, it can be shown that corresponding system of five-point approximation equations can be generated and then solved iteratively. In order to access the performance results of the proposed iterative method with the fourth-order CN scheme, another point iterative method which is Gauss-Seidel (GS), also presented as a reference method. Finally the numerical results obtained from the use of the fourth-order CN discretization scheme, it can be pointed out that the SOR iterative method is superior in terms of number of iterations, execution time, and maximum absolute error.

Leapfrog variants of iterative methods for linear algebra equations

NASA Technical Reports Server (NTRS)

Saylor, Paul E.

1988-01-01

Two iterative methods are considered, Richardson's method and a general second order method. For both methods, a variant of the method is derived for which only even numbered iterates are computed. The variant is called a leapfrog method. Comparisons between the conventional form of the methods and the leapfrog form are made under the assumption that the number of unknowns is large. In the case of Richardson's method, it is possible to express the final iterate in terms of only the initial approximation, a variant of the iteration called the grand-leap method. In the case of the grand-leap variant, a set of parameters is required. An algorithm is presented to compute these parameters that is related to algorithms to compute the weights and abscissas for Gaussian quadrature. General algorithms to implement the leapfrog and grand-leap methods are presented. Algorithms for the important special case of the Chebyshev method are also given.

Nonlinear study of the parallel velocity/tearing instability using an implicit, nonlinear resistive MHD solver

NASA Astrophysics Data System (ADS)

Chacon, L.; Finn, J. M.; Knoll, D. A.

2000-10-01

Recently, a new parallel velocity instability has been found.(J. M. Finn, Phys. Plasmas), 2, 12 (1995) This mode is a tearing mode driven unstable by curvature effects and sound wave coupling in the presence of parallel velocity shear. Under such conditions, linear theory predicts that tearing instabilities will grow even in situations in which the classical tearing mode is stable. This could then be a viable seed mechanism for the neoclassical tearing mode, and hence a non-linear study is of interest. Here, the linear and non-linear stages of this instability are explored using a fully implicit, fully nonlinear 2D reduced resistive MHD code,(L. Chacon et al), ``Implicit, Jacobian-free Newton-Krylov 2D reduced resistive MHD nonlinear solver,'' submitted to J. Comput. Phys. (2000) including viscosity and particle transport effects. The nonlinear implicit time integration is performed using the Newton-Raphson iterative algorithm. Krylov iterative techniques are employed for the required algebraic matrix inversions, implemented Jacobian-free (i.e., without ever forming and storing the Jacobian matrix), and preconditioned with a ``physics-based'' preconditioner. Nonlinear results indicate that, for large total plasma beta and large parallel velocity shear, the instability results in the generation of large poloidal shear flows and large magnetic islands even in regimes when the classical tearing mode is absolutely stable. For small viscosity, the time asymptotic state can be turbulent.

Boundary conditions in Chebyshev and Legendre methods

NASA Technical Reports Server (NTRS)

Canuto, C.

1984-01-01

Two different ways of treating non-Dirichlet boundary conditions in Chebyshev and Legendre collocation methods are discussed for second order differential problems. An error analysis is provided. The effect of preconditioning the corresponding spectral operators by finite difference matrices is also investigated.

Distributed Kalman filtering compared to Fourier domain preconditioned conjugate gradient for laser guide star tomography on extremely large telescopes.

PubMed

Gilles, Luc; Massioni, Paolo; Kulcsár, Caroline; Raynaud, Henri-François; Ellerbroek, Brent

2013-05-01

This paper discusses the performance and cost of two computationally efficient Fourier-based tomographic wavefront reconstruction algorithms for wide-field laser guide star (LGS) adaptive optics (AO). The first algorithm is the iterative Fourier domain preconditioned conjugate gradient (FDPCG) algorithm developed by Yang et al. [Appl. Opt.45, 5281 (2006)], combined with pseudo-open-loop control (POLC). FDPCG's computational cost is proportional to N log(N), where N denotes the dimensionality of the tomography problem. The second algorithm is the distributed Kalman filter (DKF) developed by Massioni et al. [J. Opt. Soc. Am. A28, 2298 (2011)], which is a noniterative spatially invariant controller. When implemented in the Fourier domain, DKF's cost is also proportional to N log(N). Both algorithms are capable of estimating spatial frequency components of the residual phase beyond the wavefront sensor (WFS) cutoff frequency thanks to regularization, thereby reducing WFS spatial aliasing at the expense of more computations. We present performance and cost analyses for the LGS multiconjugate AO system under design for the Thirty Meter Telescope, as well as DKF's sensitivity to uncertainties in wind profile prior information. We found that, provided the wind profile is known to better than 10% wind speed accuracy and 20 deg wind direction accuracy, DKF, despite its spatial invariance assumptions, delivers a significantly reduced wavefront error compared to the static FDPCG minimum variance estimator combined with POLC. Due to its nonsequential nature and high degree of parallelism, DKF is particularly well suited for real-time implementation on inexpensive off-the-shelf graphics processing units.

Fast preconditioned multigrid solution of the Euler and Navier-Stokes equations for steady, compressible flows

NASA Astrophysics Data System (ADS)

Caughey, David A.; Jameson, Antony

2003-10-01

New versions of implicit algorithms are developed for the efficient solution of the Euler and Navier-Stokes equations of compressible flow. The methods are based on a preconditioned, lower-upper (LU) implementation of a non-linear, symmetric Gauss-Seidel (SGS) algorithm for use as a smoothing algorithm in a multigrid method. Previously, this method had been implemented for flows in quasi-one-dimensional ducts and for two-dimensional flows past airfoils on boundary-conforming O-type grids for a variety of symmetric limited positive (SLIP) spatial approximations, including the scalar dissipation and convective upwind split pressure (CUSP) schemes. Here results are presented for both inviscid and viscous (laminar) flows past airfoils on boundary-conforming C-type grids. The method is significantly faster than earlier explicit or implicit methods for inviscid problems, allowing solution of these problems to the level of truncation error in three to five multigrid cycles. Viscous solutions still require as many as twenty multigrid cycles.

High resolution x-ray CMT: Reconstruction methods

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

Brown, J.K.

This paper qualitatively discusses the primary characteristics of methods for reconstructing tomographic images from a set of projections. These reconstruction methods can be categorized as either {open_quotes}analytic{close_quotes} or {open_quotes}iterative{close_quotes} techniques. Analytic algorithms are derived from the formal inversion of equations describing the imaging process, while iterative algorithms incorporate a model of the imaging process and provide a mechanism to iteratively improve image estimates. Analytic reconstruction algorithms are typically computationally more efficient than iterative methods; however, analytic algorithms are available for a relatively limited set of imaging geometries and situations. Thus, the framework of iterative reconstruction methods is better suited formore » high accuracy, tomographic reconstruction codes.« less

Matrix preconditioning: a robust operation for optical linear algebra processors.

PubMed

Ghosh, A; Paparao, P

1987-07-15

Analog electrooptical processors are best suited for applications demanding high computational throughput with tolerance for inaccuracies. Matrix preconditioning is one such application. Matrix preconditioning is a preprocessing step for reducing the condition number of a matrix and is used extensively with gradient algorithms for increasing the rate of convergence and improving the accuracy of the solution. In this paper, we describe a simple parallel algorithm for matrix preconditioning, which can be implemented efficiently on a pipelined optical linear algebra processor. From the results of our numerical experiments we show that the efficacy of the preconditioning algorithm is affected very little by the errors of the optical system.

CPDES3: A preconditioned conjugate gradient solver for linear asymmetric matrix equations arising from coupled partial differential equations in three dimensions

NASA Astrophysics Data System (ADS)

Anderson, D. V.; Koniges, A. E.; Shumaker, D. E.

1988-11-01

Many physical problems require the solution of coupled partial differential equations on three-dimensional domains. When the time scales of interest dictate an implicit discretization of the equations a rather complicated global matrix system needs solution. The exact form of the matrix depends on the choice of spatial grids and on the finite element or finite difference approximations employed. CPDES3 allows each spatial operator to have 7, 15, 19, or 27 point stencils and allows for general couplings between all of the component PDE's and it automatically generates the matrix structures needed to perform the algorithm. The resulting sparse matrix equation is solved by either the preconditioned conjugate gradient (CG) method or by the preconditioned biconjugate gradient (BCG) algorithm. An arbitrary number of component equations are permitted only limited by available memory. In the sub-band representation used, we generate an algorithm that is written compactly in terms of indirect induces which is vectorizable on some of the newer scientific computers.

CPDES2: A preconditioned conjugate gradient solver for linear asymmetric matrix equations arising from coupled partial differential equations in two dimensions

NASA Astrophysics Data System (ADS)

Anderson, D. V.; Koniges, A. E.; Shumaker, D. E.

1988-11-01

Many physical problems require the solution of coupled partial differential equations on two-dimensional domains. When the time scales of interest dictate an implicit discretization of the equations a rather complicated global matrix system needs solution. The exact form of the matrix depends on the choice of spatial grids and on the finite element or finite difference approximations employed. CPDES2 allows each spatial operator to have 5 or 9 point stencils and allows for general couplings between all of the component PDE's and it automatically generates the matrix structures needed to perform the algorithm. The resulting sparse matrix equation is solved by either the preconditioned conjugate gradient (CG) method or by the preconditioned biconjugate gradient (BCG) algorithm. An arbitrary number of component equations are permitted only limited by available memory. In the sub-band representation used, we generate an algorithm that is written compactly in terms of indirect indices which is vectorizable on some of the newer scientific computers.

On coupling fluid plasma and kinetic neutral physics models

DOE PAGES

Joseph, I.; Rensink, M. E.; Stotler, D. P.; ...

2017-03-01

The coupled fluid plasma and kinetic neutral physics equations are analyzed through theory and simulation of benchmark cases. It is shown that coupling methods that do not treat the coupling rates implicitly are restricted to short time steps for stability. Fast charge exchange, ionization and recombination coupling rates exist, even after constraining the solution by requiring that the neutrals are at equilibrium. For explicit coupling, the present implementation of Monte Carlo correlated sampling techniques does not allow for complete convergence in slab geometry. For the benchmark case, residuals decay with particle number and increase with grid size, indicating that theymore » scale in a manner that is similar to the theoretical prediction for nonlinear bias error. Progress is reported on implementation of a fully implicit Jacobian-free Newton–Krylov coupling scheme. The present block Jacobi preconditioning method is still sensitive to time step and methods that better precondition the coupled system are under investigation.« less

Effective matrix-free preconditioning for the augmented immersed interface method

NASA Astrophysics Data System (ADS)

Xia, Jianlin; Li, Zhilin; Ye, Xin

2015-12-01

We present effective and efficient matrix-free preconditioning techniques for the augmented immersed interface method (AIIM). AIIM has been developed recently and is shown to be very effective for interface problems and problems on irregular domains. GMRES is often used to solve for the augmented variable(s) associated with a Schur complement A in AIIM that is defined along the interface or the irregular boundary. The efficiency of AIIM relies on how quickly the system for A can be solved. For some applications, there are substantial difficulties involved, such as the slow convergence of GMRES (particularly for free boundary and moving interface problems), and the inconvenience in finding a preconditioner (due to the situation that only the products of A and vectors are available). Here, we propose matrix-free structured preconditioning techniques for AIIM via adaptive randomized sampling, using only the products of A and vectors to construct a hierarchically semiseparable matrix approximation to A. Several improvements over existing schemes are shown so as to enhance the efficiency and also avoid potential instability. The significance of the preconditioners includes: (1) they do not require the entries of A or the multiplication of AT with vectors; (2) constructing the preconditioners needs only O (log ⁡ N) matrix-vector products and O (N) storage, where N is the size of A; (3) applying the preconditioners needs only O (N) flops; (4) they are very flexible and do not require any a priori knowledge of the structure of A. The preconditioners are observed to significantly accelerate the convergence of GMRES, with heuristical justifications of the effectiveness. Comprehensive tests on several important applications are provided, such as Navier-Stokes equations on irregular domains with traction boundary conditions, interface problems in incompressible flows, mixed boundary problems, and free boundary problems. The preconditioning techniques are also useful for several other problems and methods.

On an adaptive preconditioned Crank-Nicolson MCMC algorithm for infinite dimensional Bayesian inference

NASA Astrophysics Data System (ADS)

Hu, Zixi; Yao, Zhewei; Li, Jinglai

2017-03-01

Many scientific and engineering problems require to perform Bayesian inference for unknowns of infinite dimension. In such problems, many standard Markov Chain Monte Carlo (MCMC) algorithms become arbitrary slow under the mesh refinement, which is referred to as being dimension dependent. To this end, a family of dimensional independent MCMC algorithms, known as the preconditioned Crank-Nicolson (pCN) methods, were proposed to sample the infinite dimensional parameters. In this work we develop an adaptive version of the pCN algorithm, where the covariance operator of the proposal distribution is adjusted based on sampling history to improve the simulation efficiency. We show that the proposed algorithm satisfies an important ergodicity condition under some mild assumptions. Finally we provide numerical examples to demonstrate the performance of the proposed method.

MO-G-17A-07: Improved Image Quality in Brain F-18 FDG PET Using Penalized-Likelihood Image Reconstruction Via a Generalized Preconditioned Alternating Projection Algorithm: The First Patient Results

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

Schmidtlein, CR; Beattie, B; Humm, J

2014-06-15

Purpose: To investigate the performance of a new penalized-likelihood PET image reconstruction algorithm using the 1{sub 1}-norm total-variation (TV) sum of the 1st through 4th-order gradients as the penalty. Simulated and brain patient data sets were analyzed. Methods: This work represents an extension of the preconditioned alternating projection algorithm (PAPA) for emission-computed tomography. In this new generalized algorithm (GPAPA), the penalty term is expanded to allow multiple components, in this case the sum of the 1st to 4th order gradients, to reduce artificial piece-wise constant regions (“staircase” artifacts typical for TV) seen in PAPA images penalized with only the 1stmore » order gradient. Simulated data were used to test for “staircase” artifacts and to optimize the penalty hyper-parameter in the root-mean-squared error (RMSE) sense. Patient FDG brain scans were acquired on a GE D690 PET/CT (370 MBq at 1-hour post-injection for 10 minutes) in time-of-flight mode and in all cases were reconstructed using resolution recovery projectors. GPAPA images were compared PAPA and RMSE-optimally filtered OSEM (fully converged) in simulations and to clinical OSEM reconstructions (3 iterations, 32 subsets) with 2.6 mm XYGaussian and standard 3-point axial smoothing post-filters. Results: The results from the simulated data show a significant reduction in the 'staircase' artifact for GPAPA compared to PAPA and lower RMSE (up to 35%) compared to optimally filtered OSEM. A simple power-law relationship between the RMSE-optimal hyper-parameters and the noise equivalent counts (NEC) per voxel is revealed. Qualitatively, the patient images appear much sharper and with less noise than standard clinical images. The convergence rate is similar to OSEM. Conclusions: GPAPA reconstructions using the 1{sub 1}-norm total-variation sum of the 1st through 4th-order gradients as the penalty show great promise for the improvement of image quality over that currently achieved with clinical OSEM reconstructions.« less

A Least-Squares Commutator in the Iterative Subspace Method for Accelerating Self-Consistent Field Convergence.

PubMed

Li, Haichen; Yaron, David J

2016-11-08

A least-squares commutator in the iterative subspace (LCIIS) approach is explored for accelerating self-consistent field (SCF) calculations. LCIIS is similar to direct inversion of the iterative subspace (DIIS) methods in that the next iterate of the density matrix is obtained as a linear combination of past iterates. However, whereas DIIS methods find the linear combination by minimizing a sum of error vectors, LCIIS minimizes the Frobenius norm of the commutator between the density matrix and the Fock matrix. This minimization leads to a quartic problem that can be solved iteratively through a constrained Newton's method. The relationship between LCIIS and DIIS is discussed. Numerical experiments suggest that LCIIS leads to faster convergence than other SCF convergence accelerating methods in a statistically significant sense, and in a number of cases LCIIS leads to stable SCF solutions that are not found by other methods. The computational cost involved in solving the quartic minimization problem is small compared to the typical cost of SCF iterations and the approach is easily integrated into existing codes. LCIIS can therefore serve as a powerful addition to SCF convergence accelerating methods in computational quantum chemistry packages.

Annual Copper Mountain Conferences on Multigrid and Iterative Methods, Copper Mountain, Colorado

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

McCormick, Stephen F.

This project supported the Copper Mountain Conference on Multigrid and Iterative Methods, held from 2007 to 2015, at Copper Mountain, Colorado. The subject of the Copper Mountain Conference Series alternated between Multigrid Methods in odd-numbered years and Iterative Methods in even-numbered years. Begun in 1983, the Series represents an important forum for the exchange of ideas in these two closely related fields. This report describes the Copper Mountain Conference on Multigrid and Iterative Methods, 2007-2015. Information on the conference series is available at http://grandmaster.colorado.edu/~copper/.

Preconditioning to Reduce Decompression Stress in Scuba Divers.

PubMed

Germonpré, Peter; Balestra, Costantino

2017-02-01

Using ultrasound imaging, vascular gas emboli (VGE) are observed after asymptomatic scuba dives and are considered a key element in the potential development of decompression sickness (DCS). Diving is also accompanied with vascular dysfunction, as measured by flow-mediated dilation (FMD). Previous studies showed significant intersubject variability to VGE for the same diving exposure and demonstrated that VGE can be reduced with even a single pre-dive intervention. Several preconditioning methods have been reported recently, seemingly acting either on VGE quantity or on endothelial inflammatory markers. Nine male divers who consistently showed VGE postdive performed a standardized deep pool dive (33 m/108 ft, 20 min in 33°C water temperature) to investigate the effect of three different preconditioning interventions: heat exposure (a 30-min session of dry infrared sauna), whole-body vibration (a 30-min session on a vibration mattress), and dark chocolate ingestion (30 g of chocolate containing 86% cocoa). Dives were made one day per week and interventions were administered in a randomized order. These interventions were shown to selectively reduce VGE, FMD, or both compared to control dives. Vibration had an effect on VGE (39.54%, SEM 16.3%) but not on FMD postdive. Sauna had effects on both parameters (VGE: 26.64%, SEM 10.4%; FMD: 102.7%, SEM 2.1%), whereas chocolate only improved FMD (102.5%, SEM 1.7%). This experiment, which had the same subjects perform all control and preconditioning dives in wet but completely standardized diving conditions, demonstrates that endothelial dysfunction appears to not be solely related to VGE.Germonpré P, Balestra C. Preconditioning to reduce decompression stress in scuba divers. Aerosp Med Hum Perform. 2017; 88(2):114-120.

Platelet rich plasma clot releasate preconditioning induced PI3K/AKT/NFκB signaling enhances survival and regenerative function of rat bone marrow mesenchymal stem cells in hostile microenvironments.

PubMed

Peng, Yan; Huang, Sha; Wu, Yan; Cheng, Biao; Nie, Xiaohu; Liu, Hongwei; Ma, Kui; Zhou, Jiping; Gao, Dongyun; Feng, Changjiang; Yang, Siming; Fu, Xiaobing

2013-12-15

Mesenchymal stem cells (MSCs) have been optimal targets in the development of cell based therapies, but their limited availability and high death rate after transplantation remains a concern in clinical applications. This study describes novel effects of platelet rich clot releasate (PRCR) on rat bone marrow-derived MSCs (BM-MSCs), with the former driving a gene program, which can reduce apoptosis and promote the regenerative function of the latter in hostile microenvironments through enhancement of paracrine/autocrine factors. By using reverse transcription-polymerase chain reaction, immunofluorescence and western blot analyses, we showed that PRCR preconditioning could alleviate the apoptosis of BM-MSCs under stress conditions induced by hydrogen peroxide (H2O2) and serum deprivation by enhancing expression of vascular endothelial growth factor and platelet-derived growth factor (PDGF) via stimulation of the platelet-derived growth factor receptor (PDGFR)/PI3K/AKT/NF-κB signaling pathways. Furthermore, the effects of PRCR preconditioned GFP-BM-MSCs subcutaneously transplanted into rats 6 h after wound surgery were examined by histological and other tests from days 0-22 after transplantation. Engraftment of the PRCR preconditioned BM-MSCs not only significantly attenuated apoptosis and wound size but also improved epithelization and blood vessel regeneration of skin via regulation of the wound microenvironment. Thus, preconditioning with PRCR, which reprograms BM-MSCs to tolerate hostile microenvironments and enhance regenerative function by increasing levels of paracrine factors through PDGFR-α/PI3K/AKT/NF-κB signaling pathways would be a safe method for boosting the effectiveness of transplantation therapy in the clinic.

Smooth muscle cell seeding of decellularized scaffolds: the importance of bioreactor preconditioning to development of a more native architecture for tissue-engineered blood vessels.

PubMed

Yazdani, Saami K; Watts, Benjamin; Machingal, Masood; Jarajapu, Yagna P R; Van Dyke, Mark E; Christ, George J

2009-04-01

Vascular smooth muscle cells (VSMCs) impart important functional characteristics in the native artery and, therefore, should logically be incorporated in the development of tissue-engineered blood vessels. However, the native architecture and low porosity of naturally derived biomaterials (i.e., decellularized vessels) have impeded efforts to seed and incorporate a VSMC layer in tissue-engineered blood vessels. To this end, the goal of this study was to develop improved methods for seeding, proliferation, and maturation of VSMCs on decellularized porcine carotid arteries. Decellularized vessels were prepared in the absence and presence of the adventitial layer, and statically seeded with a pipette containing a suspension of rat aortic VSMCs. After cell seeding, recellularized engineered vessels were placed in a custom bioreactor system for 1-2 weeks to enhance cellular proliferation, alignment, and maturation. Initial attachment of VSMCs was dramatically enhanced by removing the adventitial layer of the decellularized porcine artery. Moreover, cyclic bioreactor conditioning (i.e., flow and pressure) resulted in increased VSMC proliferation and accelerated formation of a muscularized medial layer in the absence of the adventitial layer during the first week of preconditioning. Fura-2-based digital imaging microscopy revealed marked and reproducible depolarization-induced calcium mobilization after bioreactor preconditioning in the absence, but not in the presence, of the adventitia. The major finding of this investigation is that bioreactor preconditioning accelerates the formation of a significant muscular layer on decellularized scaffolds, in particular on adventitia-denuded scaffolds. Further, the VSMC layer of bioreactor-preconditioned vessels was capable of mobilizing calcium in response to cellular depolarization. These findings represent an important first step toward the development of tissue-engineered vascular grafts that more closely mimic native vasculature.

Krylov subspace iterative methods for boundary element method based near-field acoustic holography.

PubMed

Valdivia, Nicolas; Williams, Earl G

2005-02-01

The reconstruction of the acoustic field for general surfaces is obtained from the solution of a matrix system that results from a boundary integral equation discretized using boundary element methods. The solution to the resultant matrix system is obtained using iterative regularization methods that counteract the effect of noise on the measurements. These methods will not require the calculation of the singular value decomposition, which can be expensive when the matrix system is considerably large. Krylov subspace methods are iterative methods that have the phenomena known as "semi-convergence," i.e., the optimal regularization solution is obtained after a few iterations. If the iteration is not stopped, the method converges to a solution that generally is totally corrupted by errors on the measurements. For these methods the number of iterations play the role of the regularization parameter. We will focus our attention to the study of the regularizing properties from the Krylov subspace methods like conjugate gradients, least squares QR and the recently proposed Hybrid method. A discussion and comparison of the available stopping rules will be included. A vibrating plate is considered as an example to validate our results.

An implicit-iterative solution of the heat conduction equation with a radiation boundary condition

NASA Technical Reports Server (NTRS)

Williams, S. D.; Curry, D. M.

1977-01-01

For the problem of predicting one-dimensional heat transfer between conducting and radiating mediums by an implicit finite difference method, four different formulations were used to approximate the surface radiation boundary condition while retaining an implicit formulation for the interior temperature nodes. These formulations are an explicit boundary condition, a linearized boundary condition, an iterative boundary condition, and a semi-iterative boundary method. The results of these methods in predicting surface temperature on the space shuttle orbiter thermal protection system model under a variety of heating rates were compared. The iterative technique caused the surface temperature to be bounded at each step. While the linearized and explicit methods were generally more efficient, the iterative and semi-iterative techniques provided a realistic surface temperature response without requiring step size control techniques.

Upwind relaxation methods for the Navier-Stokes equations using inner iterations

NASA Technical Reports Server (NTRS)

Taylor, Arthur C., III; Ng, Wing-Fai; Walters, Robert W.

1992-01-01

A subsonic and a supersonic problem are respectively treated by an upwind line-relaxation algorithm for the Navier-Stokes equations using inner iterations to accelerate steady-state solution convergence and thereby minimize CPU time. While the ability of the inner iterative procedure to mimic the quadratic convergence of the direct solver method is attested to in both test problems, some of the nonquadratic inner iterative results are noted to have been more efficient than the quadratic. In the more successful, supersonic test case, inner iteration required only about 65 percent of the line-relaxation method-entailed CPU time.

AIR-MRF: Accelerated iterative reconstruction for magnetic resonance fingerprinting.

PubMed

Cline, Christopher C; Chen, Xiao; Mailhe, Boris; Wang, Qiu; Pfeuffer, Josef; Nittka, Mathias; Griswold, Mark A; Speier, Peter; Nadar, Mariappan S

2017-09-01

Existing approaches for reconstruction of multiparametric maps with magnetic resonance fingerprinting (MRF) are currently limited by their estimation accuracy and reconstruction time. We aimed to address these issues with a novel combination of iterative reconstruction, fingerprint compression, additional regularization, and accelerated dictionary search methods. The pipeline described here, accelerated iterative reconstruction for magnetic resonance fingerprinting (AIR-MRF), was evaluated with simulations as well as phantom and in vivo scans. We found that the AIR-MRF pipeline provided reduced parameter estimation errors compared to non-iterative and other iterative methods, particularly at shorter sequence lengths. Accelerated dictionary search methods incorporated into the iterative pipeline reduced the reconstruction time at little cost of quality. Copyright © 2017 Elsevier Inc. All rights reserved.

Eigenmode Analysis of Boundary Conditions for One-Dimensional Preconditioned Euler Equations

NASA Technical Reports Server (NTRS)

Darmofal, David L.

1998-01-01

An analysis of the effect of local preconditioning on boundary conditions for the subsonic, one-dimensional Euler equations is presented. Decay rates for the eigenmodes of the initial boundary value problem are determined for different boundary conditions. Riemann invariant boundary conditions based on the unpreconditioned Euler equations are shown to be reflective with preconditioning, and, at low Mach numbers, disturbances do not decay. Other boundary conditions are investigated which are non-reflective with preconditioning and numerical results are presented confirming the analysis.

Hypoxia preconditioning protection of corneal stromal cells requires HIF1alpha but not VEGF.

PubMed

Xing, Dongmei; Bonanno, Joseph A

2009-05-18

Hypoxia preconditioning protects corneal stromal cells from stress-induced death. This study determined whether the transcription factor HIF-1alpha (Hypoxia Inducible Factor) is responsible and whether this is promulgated by VEGF (Vascular Endothelial Growth Factor). Cultured bovine stromal cells were preconditioned with hypoxia in the presence of cadmium chloride, a chemical inhibitor of HIF-1alpha, and HIF-1alpha siRNA to test if HIF-1alpha activity is needed for hypoxia preconditioning protection from UV-irradiation induced cell death. TUNEL assay was used to detect cell apoptosis after UV-irradiation. RT-PCR and western blot were used to detect the presence of HIF-1alpha and VEGF in transcriptional and translational levels. During hypoxia (0.5% O2), 5 muM cadmium chloride completely inhibited HIF-1alpha expression and reversed the protection by hypoxia preconditioning. HIF-1alpha siRNA (15 nM) reduced HIF-1alpha expression by 90% and produced a complete loss of protection provided by hypoxia preconditioning. Since VEGF is induced by hypoxia, can be HIF-1alpha dependent, and is often protective, we examined the changes in transcription of VEGF and its receptors after 4 h of hypoxia preconditioning. VEGF and its receptors Flt-1 and Flk-1 are up-regulated after hypoxia preconditioning. However, the transcription and translation of VEGF were paradoxically increased by siHIF-1alpha, suggesting that VEGF expression in stromal cells is not down-stream of HIF-1alpha. These findings demonstrate that hypoxia preconditioning protection in corneal stromal cells requires HIF-1alpha, but that VEGF is not a component of the protection.

The effect of brain death in rat steatotic and non-steatotic liver transplantation with previous ischemic preconditioning.

PubMed

Jiménez-Castro, Mónica B; Meroño, Noelia; Mendes-Braz, Mariana; Gracia-Sancho, Jordi; Martínez-Carreres, Laia; Cornide-Petronio, Maria Eugenia; Casillas-Ramirez, Araní; Rodés, Juan; Peralta, Carmen

2015-01-01

Most liver grafts undergoing transplantation derive from brain dead donors, which may also show hepatic steatosis, being both characteristic risk factors in liver transplantation. Ischemic preconditioning shows benefits when applied in non-brain dead clinical situations like hepatectomies, whereas it has been less promising in the transplantation from brain dead patients. This study examined how brain death affects preconditioned steatotic and non-steatotic liver grafts undergoing transplantation. Steatotic and non-steatotic grafts from non-brain dead and brain dead-donors were cold stored for 6h and then transplanted. After 2, 4, and 16 h of reperfusion, hepatic damage was analysed. In addition, two therapeutic strategies, ischemic preconditioning and/or acetylcholine pre-treatment, and their underlying mechanisms were characterized. Preconditioning benefits in non-brain dead donors were associated with nitric oxide and acetylcholine generation. In brain dead donors, preconditioning generated nitric oxide but did not promote acetylcholine upregulation, and this resulted in inflammation and damage. Acetylcholine treatment in brain dead donors, through PKC, increased antioxidants and reduced lipid peroxidation, nitrotyrosines and neutrophil accumulation, altogether protecting against damage. The combination of acetylcholine and preconditioning conferred stronger protection against damage, oxidative stress and neutrophil accumulation than acetylcholine treatment alone. These superior beneficial effects were due to a selective preconditioning-mediated generation of nitric oxide and regulation of PPAR and TLR4 pathways, which were not observed when acetylcholine was administered alone. Our findings propose the combination of acetylcholine+preconditioning as a feasible and highly protective strategy to reduce the adverse effects of brain death and to ultimately improve liver graft quality. Copyright © 2014 European Association for the Study of the Liver. Published by Elsevier B.V. All rights reserved.

Gadolinium and ruthenium red attenuate remote hind limb preconditioning-induced cardioprotection: possible role of TRP and especially TRPV channels.

PubMed

Randhawa, Puneet Kaur; Jaggi, Amteshwar Singh

2016-08-01

Remote ischemic preconditioning is a well reported therapeutic strategy that induces cardioprotective effects but the underlying intracellular mechanisms have not been widely explored. The current study was designed to investigate the involvement of TRP and especially TRPV channels in remote hind limb preconditioning-induced cardioprotection. Remote hind limb preconditioning stimulus (4 alternate cycles of inflation and deflation of 5 min each) was delivered using a blood pressure cuff tied on the hind limb of the anesthetized rat. Using Langendorff's system, the heart was perfused and subjected to 30-min ischemia and 120-min reperfusion. The myocardial injury was assessed by measuring infarct size, lactate dehydrogenase (LDH), creatine kinase (CK), LVDP, +dp/dtmax, -dp/dtmin, heart rate, and coronary flow rate. Gadolinium, TRP blocker, and ruthenium red, TRPV channel blocker, were employed as pharmacological tools. Remote hind limb preconditioning significantly reduced the infarct size, LDH release, CK release and improved coronary flow rate, hemodynamic parameters including LVDP, +dp/dtmax, -dp/dtmin, and heart rate. However, gadolinium (7.5 and 15 mg kg(-1)) and ruthenium red (4 and 8 mg kg(-1)) significantly attenuated the cardioprotective effects suggesting the involvement of TRP especially TRPV channels in mediating remote hind limb preconditioning-induced cardioprotection. Remote hind limb preconditioning stimulus possibly activates TRPV channels on the heart or sensory nerve fibers innervating the heart to induce cardioprotective effects. Alternatively, remote hind limb preconditioning stimulus may also activate the mechanosensitive TRP and especially TRPV channels on the sensory nerve fibers innervating the skeletal muscles to trigger cardioprotective neurogenic signaling cascade. The cardioprotective effects of remote hind limb preconditioning may be mediated via activation of mechanosensitive TRP and especially TRPV channels.

A Two-Dimensional Helmholtz Equation Solution for the Multiple Cavity Scattering Problem

DTIC Science & Technology

2013-02-01

obtained by using the block Gauss – Seidel iterative meth- od. To show the convergence of the iterative method, we define the error between two...models to the general multiple cavity setting. Numerical examples indicate that the convergence of the Gauss – Seidel iterative method depends on the...variational approach. A block Gauss – Seidel iterative method is introduced to solve the cou- pled system of the multiple cavity scattering problem, where

Blended learning in CME: the perception of GP trainers.

PubMed

Te Pas, E; Meinema, J G; Visser, M R M; van Dijk, N

2016-05-01

Blended learning (the combination of electronic methods with traditional teaching methods) has the potential to combine the best of traditional education with the best of computer-mediated training. We chose to develop such an intervention for GP trainers who were undertaking a Continuing Medical Education (CME) course in evidence-based medicine (EBM). This study reports on our experience and investigated the factors influencing the perception on usefulness and logistics of blended learning for learners in CME. In total, 170 GP trainers participated in the intervention. We used questionnaires, observations during the four face-to-face meetings and evaluations in the e-course over one year. Additionally we organised focus groups to gain insight in some of the outcomes of the questionnaires and interpretations of the observations. The GP trainers found the design and the educational method (e-course in combination with meetings) attractive, instructive and complementary. Factors influencing their learning were (1) educational design, (2) educational method, (3) topic of the intervention, (4) time (planning), (5) time (intervention), (6) learning style, (7) technical issues, (8) preconditions and (9) level of difficulty. A close link between daily practice and the educational intervention was considered an important precondition for the success of the intervention in this group of learners. GP trainers were positive about blended learning: they found e-learning a useful way to gain knowledge and the meetings a pleasant way of transferring the knowledge into practice. Although some preconditions should be taken into consideration during its development and implementation, they would participate in similarly designed learning in the future.

40 CFR 1065.518 - Engine preconditioning.

Code of Federal Regulations, 2014 CFR

2014-07-01

... 40 Protection of Environment 33 2014-07-01 2014-07-01 false Engine preconditioning. 1065.518... CONTROLS ENGINE-TESTING PROCEDURES Performing an Emission Test Over Specified Duty Cycles § 1065.518 Engine preconditioning. (a) This section applies for engines where measured emissions are affected by prior operation...

GENE EXPRESSION CHANGES AFTER SEIZURE PRECONDITIONING IN THE THREE MAJOR HIPPOCAMPAL CELL LAYERS

PubMed Central

Borges, Karin; Shaw, Renee; Dingledine, Raymond

2008-01-01

Rodents experience hippocampal damage after status epilepticus (SE) mainly in pyramidal cells while sparing the dentate granule cell layer (DGCL). Hippocampal damage was prevented in rats that had been preconditioned by brief seizures on two consecutive days before SE. To identify neuroprotective genes and biochemical pathways changed after preconditioning we compared the effect of preconditioning on gene expression in the CA1 and CA3 pyramidal and DGCLs, harvested by laser capture microscopy. In the DGCL the expression of 632 genes was altered, compared to only 151 and 58 genes in CA1 and CA3 pyramidal cell layers. Most of the differentially expressed genes regulate tissue structure and intra- and extracellular signaling, including neurotransmission. A selective upregulation of energy metabolism transcripts occurred in CA1 pyramidal cells relative to the DGCL. These results reveal a broad transcriptional response of the DGCL to preconditioning, and suggest several mechanisms underlying the neuroprotective effect of preconditioning seizures. PMID:17239605

Analysis of physics-based preconditioning for single-phase subchannel equations

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

Hansel, J. E.; Ragusa, J. C.; Allu, S.

2013-07-01

The (single-phase) subchannel approximations are used throughout nuclear engineering to provide an efficient flow simulation because the computational burden is much smaller than for computational fluid dynamics (CFD) simulations, and empirical relations have been developed and validated to provide accurate solutions in appropriate flow regimes. Here, the subchannel equations have been recast in a residual form suitable for a multi-physics framework. The Eigen spectrum of the Jacobian matrix, along with several potential physics-based preconditioning approaches, are evaluated, and the the potential for improved convergence from preconditioning is assessed. The physics-based preconditioner options include several forms of reduced equations that decouplemore » the subchannels by neglecting crossflow, conduction, and/or both turbulent momentum and energy exchange between subchannels. Eigen-scopy analysis shows that preconditioning moves clusters of eigenvalues away from zero and toward one. A test problem is run with and without preconditioning. Without preconditioning, the solution failed to converge using GMRES, but application of any of the preconditioners allowed the solution to converge. (authors)« less

DEVELOPMENT OF LOW-DIFFUSION FLUX-SPLITTING METHODS FOR DENSE GAS-SOLID FLOWS

EPA Science Inventory

The development of a class of low-diffusion upwinding methods for computing dense gas-solid flows is presented in this work. An artificial compressibility/low-Mach preconditioning strategy is developed for a hyperbolic two-phase flow equation system consisting of separate solids ...

Robust iterative method for nonlinear Helmholtz equation

NASA Astrophysics Data System (ADS)

Yuan, Lijun; Lu, Ya Yan

2017-08-01

A new iterative method is developed for solving the two-dimensional nonlinear Helmholtz equation which governs polarized light in media with the optical Kerr nonlinearity. In the strongly nonlinear regime, the nonlinear Helmholtz equation could have multiple solutions related to phenomena such as optical bistability and symmetry breaking. The new method exhibits a much more robust convergence behavior than existing iterative methods, such as frozen-nonlinearity iteration, Newton's method and damped Newton's method, and it can be used to find solutions when good initial guesses are unavailable. Numerical results are presented for the scattering of light by a nonlinear circular cylinder based on the exact nonlocal boundary condition and a pseudospectral method in the polar coordinate system.

AMP-activated protein kinase (AMPK)-induced preconditioning in primary cortical neurons involves activation of MCL-1.

PubMed

Anilkumar, Ujval; Weisová, Petronela; Düssmann, Heiko; Concannon, Caoimhín G; König, Hans-Georg; Prehn, Jochen H M

2013-03-01

Neuronal preconditioning is a phenomenon where a previous exposure to a sub-lethal stress stimulus increases the resistance of neurons towards a second, normally lethal stress stimulus. Activation of the energy stress sensor, AMP-activated protein kinase (AMPK) has been shown to contribute to the protective effects of ischaemic and mitochondrial uncoupling-induced preconditioning in neurons, however, the molecular basis of AMPK-mediated preconditioning has been less well characterized. We investigated the effect of AMPK preconditioning using 5-aminoimidazole-4-carboxamide riboside (AICAR) in a model of NMDA-mediated excitotoxic injury in primary mouse cortical neurons. Activation of AMPK with low concentrations of AICAR (0.1 mM for 2 h) induced a transient increase in AMPK phosphorylation, protecting neurons against NMDA-induced excitotoxicity. Analysing potential targets of AMPK activation, demonstrated a marked increase in mRNA expression and protein levels of the anti-apoptotic BCL-2 family protein myeloid cell leukaemia sequence 1 (MCL-1) in AICAR-preconditioned neurons. Interestingly, over-expression of MCL-1 protected neurons against NMDA-induced excitotoxicity while MCL-1 gene silencing abolished the effect of AICAR preconditioning. Monitored intracellular Ca²⁺ levels during NMDA excitation revealed that MCL-1 over-expressing neurons exhibited improved bioenergetics and markedly reduced Ca²⁺ elevations, suggesting a potential mechanism through which MCL-1 confers neuroprotection. This study identifies MCL-1 as a key effector of AMPK-induced preconditioning in neurons. © 2012 International Society for Neurochemistry.

Effect of ozone oxidative preconditioning in preventing early radiation-induced lung injury in rats

PubMed Central

Bakkal, B.H.; Gultekin, F.A.; Guven, B.; Turkcu, U.O.; Bektas, S.; Can, M.

2013-01-01

Ionizing radiation causes its biological effects mainly through oxidative damage induced by reactive oxygen species. Previous studies showed that ozone oxidative preconditioning attenuated pathophysiological events mediated by reactive oxygen species. As inhalation of ozone induces lung injury, the aim of this study was to examine whether ozone oxidative preconditioning potentiates or attenuates the effects of irradiation on the lung. Rats were subjected to total body irradiation, with or without treatment with ozone oxidative preconditioning (0.72 mg/kg). Serum proinflammatory cytokine levels, oxidative damage markers, and histopathological analysis were compared at 6 and 72 h after total body irradiation. Irradiation significantly increased lung malondialdehyde levels as an end-product of lipoperoxidation. Irradiation also significantly decreased lung superoxide dismutase activity, which is an indicator of the generation of oxidative stress and an early protective response to oxidative damage. Ozone oxidative preconditioning plus irradiation significantly decreased malondialdehyde levels and increased the activity of superoxide dismutase, which might indicate protection of the lung from radiation-induced lung injury. Serum tumor necrosis factor alpha and interleukin-1 beta levels, which increased significantly following total body irradiation, were decreased with ozone oxidative preconditioning. Moreover, ozone oxidative preconditioning was able to ameliorate radiation-induced lung injury assessed by histopathological evaluation. In conclusion, ozone oxidative preconditioning, repeated low-dose intraperitoneal administration of ozone, did not exacerbate radiation-induced lung injury, and, on the contrary, it provided protection against radiation-induced lung damage. PMID:23969972

Assessing the feasibility of community health insurance in Uganda: A mixed-methods exploratory analysis.

PubMed

Biggeri, M; Nannini, M; Putoto, G

2018-03-01

Community health insurance (CHI) aims to provide financial protection and facilitate health care access among poor rural populations. Given common operational challenges that hamper the full development of the scheme, there is need to undertake systematic feasibility studies. These are scarce in the literature and usually they do not provide a comprehensive analysis of the local context. The present research intends to adopt a mixed-methods approach to assess ex-ante the feasibility of CHI. In particular, eight preconditions are proposed to inform the viability of introducing the micro insurance. A case study located in rural northern Uganda is presented to test the effectiveness of the mixed-methods procedure for the feasibility purpose. A household survey covering 180 households, 8 structured focus group discussions, and 40 key informant interviews were performed between October and December 2016 in order to provide a complete and integrated analysis of the feasibility preconditions. Through the data collected at the household level, the population health seeking behaviours and the potential insurance design were examined; econometric analyses were carried out to investigate the perception of health as a priority need and the willingness to pay for the scheme. The latter component, in particular, was analysed through a contingent valuation method. The results validated the relevant feasibility preconditions. Econometric estimates demonstrated that awareness of catastrophic health expenditures and the distance to the hospital play a critical influence on household priorities and willingness to pay. Willingness is also significantly affected by socio-economic status and basic knowledge of insurance principles. Overall, the mixed-methods investigation showed that a comprehensive feasibility analysis can shape a viable CHI model to be implemented in the local context. Copyright © 2018 Elsevier Ltd. All rights reserved.

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

NASA Astrophysics Data System (ADS)

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

2013-04-01

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

Twostep-by-twostep PIRK-type PC methods with continuous output formulas

NASA Astrophysics Data System (ADS)

Cong, Nguyen Huu; Xuan, Le Ngoc

2008-11-01

This paper deals with parallel predictor-corrector (PC) iteration methods based on collocation Runge-Kutta (RK) corrector methods with continuous output formulas for solving nonstiff initial-value problems (IVPs) for systems of first-order differential equations. At nth step, the continuous output formulas are used not only for predicting the stage values in the PC iteration methods but also for calculating the step values at (n+2)th step. In this case, the integration processes can be proceeded twostep-by-twostep. The resulting twostep-by-twostep (TBT) parallel-iterated RK-type (PIRK-type) methods with continuous output formulas (twostep-by-twostep PIRKC methods or TBTPIRKC methods) give us a faster integration process. Fixed stepsize applications of these TBTPIRKC methods to a few widely-used test problems reveal that the new PC methods are much more efficient when compared with the well-known parallel-iterated RK methods (PIRK methods), parallel-iterated RK-type PC methods with continuous output formulas (PIRKC methods) and sequential explicit RK codes DOPRI5 and DOP853 available from the literature.

Development of iterative techniques for the solution of unsteady compressible viscous flows

NASA Technical Reports Server (NTRS)

Sankar, Lakshmi N.; Hixon, Duane

1992-01-01

The development of efficient iterative solution methods for the numerical solution of two- and three-dimensional compressible Navier-Stokes equations is discussed. Iterative time marching methods have several advantages over classical multi-step explicit time marching schemes, and non-iterative implicit time marching schemes. Iterative schemes have better stability characteristics than non-iterative explicit and implicit schemes. In this work, another approach based on the classical conjugate gradient method, known as the Generalized Minimum Residual (GMRES) algorithm is investigated. The GMRES algorithm has been used in the past by a number of researchers for solving steady viscous and inviscid flow problems. Here, we investigate the suitability of this algorithm for solving the system of non-linear equations that arise in unsteady Navier-Stokes solvers at each time step.

40 CFR 92.125 - Pre-test procedures and preconditioning.

Code of Federal Regulations, 2014 CFR

2014-07-01

... 40 Protection of Environment 20 2014-07-01 2013-07-01 true Pre-test procedures and preconditioning... PROGRAMS (CONTINUED) CONTROL OF AIR POLLUTION FROM LOCOMOTIVES AND LOCOMOTIVE ENGINES Test Procedures § 92.125 Pre-test procedures and preconditioning. (a) Locomotive testing. (1) Determine engine lubricating...

Nested Krylov methods and preserving the orthogonality

NASA Technical Reports Server (NTRS)

Desturler, Eric; Fokkema, Diederik R.

1993-01-01

Recently the GMRESR inner-outer iteraction scheme for the solution of linear systems of equations was proposed by Van der Vorst and Vuik. Similar methods have been proposed by Axelsson and Vassilevski and Saad (FGMRES). The outer iteration is GCR, which minimizes the residual over a given set of direction vectors. The inner iteration is GMRES, which at each step computes a new direction vector by approximately solving the residual equation. However, the optimality of the approximation over the space of outer search directions is ignored in the inner GMRES iteration. This leads to suboptimal corrections to the solution in the outer iteration, as components of the outer iteration directions may reenter in the inner iteration process. Therefore we propose to preserve the orthogonality relations of GCR in the inner GMRES iteration. This gives optimal corrections; however, it involves working with a singular, non-symmetric operator. We will discuss some important properties, and we will show by experiments that, in terms of matrix vector products, this modification (almost) always leads to better convergence. However, because we do more orthogonalizations, it does not always give an improved performance in CPU-time. Furthermore, we will discuss efficient implementations as well as the truncation possibilities of the outer GCR process. The experimental results indicate that for such methods it is advantageous to preserve the orthogonality in the inner iteration. Of course we can also use iteration schemes other than GMRES as the inner method; methods with short recurrences like GICGSTAB are of interest.

Reducing the latency of the Fractal Iterative Method to half an iteration

NASA Astrophysics Data System (ADS)

Béchet, Clémentine; Tallon, Michel

2013-12-01

The fractal iterative method for atmospheric tomography (FRiM-3D) has been introduced to solve the wavefront reconstruction at the dimensions of an ELT with a low-computational cost. Previous studies reported the requirement of only 3 iterations of the algorithm in order to provide the best adaptive optics (AO) performance. Nevertheless, any iterative method in adaptive optics suffer from the intrinsic latency induced by the fact that one iteration can start only once the previous one is completed. Iterations hardly match the low-latency requirement of the AO real-time computer. We present here a new approach to avoid iterations in the computation of the commands with FRiM-3D, thus allowing low-latency AO response even at the scale of the European ELT (E-ELT). The method highlights the importance of "warm-start" strategy in adaptive optics. To our knowledge, this particular way to use the "warm-start" has not been reported before. Futhermore, removing the requirement of iterating to compute the commands, the computational cost of the reconstruction with FRiM-3D can be simplified and at least reduced to half the computational cost of a classical iteration. Thanks to simulations of both single-conjugate and multi-conjugate AO for the E-ELT,with FRiM-3D on Octopus ESO simulator, we demonstrate the benefit of this approach. We finally enhance the robustness of this new implementation with respect to increasing measurement noise, wind speed and even modeling errors.

40 CFR 85.2218 - Preconditioned idle test-EPA 91.

Code of Federal Regulations, 2011 CFR

2011-07-01

... 40 Protection of Environment 18 2011-07-01 2011-07-01 false Preconditioned idle test-EPA 91. 85.2218 Section 85.2218 Protection of Environment ENVIRONMENTAL PROTECTION AGENCY (CONTINUED) AIR PROGRAMS... Tests § 85.2218 Preconditioned idle test—EPA 91. (a) General requirements—(1) Exhaust gas sampling...

40 CFR 86.1232-96 - Vehicle preconditioning.

Code of Federal Regulations, 2013 CFR

2013-07-01

... awaiting testing, to prevent unusual loading of the canisters. During this time care must be taken to... vehicles with multiple canisters in a series configuration, the set of canisters must be preconditioned as... designed for vapor load or purge steps, the service port shall be used during testing to precondition the...

40 CFR 86.1232-96 - Vehicle preconditioning.

Code of Federal Regulations, 2012 CFR

2012-07-01

... 40 Protection of Environment 20 2012-07-01 2012-07-01 false Vehicle preconditioning. 86.1232-96... (CONTINUED) CONTROL OF EMISSIONS FROM NEW AND IN-USE HIGHWAY VEHICLES AND ENGINES (CONTINUED) Evaporative... Methanol-Fueled Heavy-Duty Vehicles § 86.1232-96 Vehicle preconditioning. (a) Fuel tank cap(s) of gasoline...

40 CFR 85.2218 - Preconditioned idle test-EPA 91.

Code of Federal Regulations, 2012 CFR

2012-07-01

... 40 Protection of Environment 19 2012-07-01 2012-07-01 false Preconditioned idle test-EPA 91. 85... Tests § 85.2218 Preconditioned idle test—EPA 91. (a) General requirements—(1) Exhaust gas sampling algorithm. The analysis of exhaust gas concentrations begins ten seconds after the applicable test mode...

The Galvanotactic Migration of Keratinocytes is Enhanced by Hypoxic Preconditioning

PubMed Central

Guo, Xiaowei; Jiang, Xupin; Ren, Xi; Sun, Huanbo; Zhang, Dongxia; Zhang, Qiong; Zhang, Jiaping; Huang, Yuesheng

2015-01-01

The endogenous electric field (EF)-directed migration of keratinocytes (galvanotaxis) into wounds is an essential step in wound re-epithelialization. Hypoxia, which occurs immediately after injury, acts as an early stimulus to initiate the healing process; however, the mechanisms for this effect, remain elusive. We show here that the galvanotactic migration of keratinocytes was enhanced by hypoxia preconditioning as a result of the increased directionality rather than the increased motility of keratinocytes. This enhancement was both oxygen tension- and preconditioning time-dependent, with the maximum effects achieved using 2% O2 preconditioning for 6 hours. Hypoxic preconditioning (2% O2, 6 hours) decreased the threshold voltage of galvanotaxis to < 25 mV/mm, whereas this value was between 25 and 50 mV/mm in the normal culture control. In a scratch-wound monolayer assay in which the applied EF was in the default healing direction, hypoxic preconditioning accelerated healing by 1.38-fold compared with the control conditions. Scavenging of the induced ROS by N-acetylcysteine (NAC) abolished the enhanced galvanotaxis and the accelerated healing by hypoxic preconditioning. Our data demonstrate a novel and unsuspected role of hypoxia in supporting keratinocyte galvanotaxis. Enhancing the galvanotactic response of cells might therefore be a clinically attractive approach to induce improved wound healing. PMID:25988491

Iterative deep convolutional encoder-decoder network for medical image segmentation.

PubMed

Jung Uk Kim; Hak Gu Kim; Yong Man Ro

2017-07-01

In this paper, we propose a novel medical image segmentation using iterative deep learning framework. We have combined an iterative learning approach and an encoder-decoder network to improve segmentation results, which enables to precisely localize the regions of interest (ROIs) including complex shapes or detailed textures of medical images in an iterative manner. The proposed iterative deep convolutional encoder-decoder network consists of two main paths: convolutional encoder path and convolutional decoder path with iterative learning. Experimental results show that the proposed iterative deep learning framework is able to yield excellent medical image segmentation performances for various medical images. The effectiveness of the proposed method has been proved by comparing with other state-of-the-art medical image segmentation methods.

Application of preconditioned alternating direction method of multipliers in depth from focal stack

NASA Astrophysics Data System (ADS)

Javidnia, Hossein; Corcoran, Peter

2018-03-01

Postcapture refocusing effect in smartphone cameras is achievable using focal stacks. However, the accuracy of this effect is totally dependent on the combination of the depth layers in the stack. The accuracy of the extended depth of field effect in this application can be improved significantly by computing an accurate depth map, which has been an open issue for decades. To tackle this issue, a framework is proposed based on a preconditioned alternating direction method of multipliers for depth from the focal stack and synthetic defocus application. In addition to its ability to provide high structural accuracy, the optimization function of the proposed framework can, in fact, converge faster and better than state-of-the-art methods. The qualitative evaluation has been done on 21 sets of focal stacks and the optimization function has been compared against five other methods. Later, 10 light field image sets have been transformed into focal stacks for quantitative evaluation purposes. Preliminary results indicate that the proposed framework has a better performance in terms of structural accuracy and optimization in comparison to the current state-of-the-art methods.

EXPOSURE METHOD CONSIDERATIONS FOR MEASURING VITELLOGENIN EXPRESSION IN LARVAL AND MALE FATHEAD MINNOWS (PIMEPHALES PROMELAS)

EPA Science Inventory

Our laboratory has developed methods for measuring the expression of the vitellogenin (Vg) gene in larval and adult male fathead minnows. During this development we found several conditions that affect background Vg levels and we observed preconditions for the expression of this...

Spectral multigrid methods for elliptic equations 2

NASA Technical Reports Server (NTRS)

Zang, T. A.; Wong, Y. S.; Hussaini, M. Y.

1983-01-01

A detailed description of spectral multigrid methods is provided. This includes the interpolation and coarse-grid operators for both periodic and Dirichlet problems. The spectral methods for periodic problems use Fourier series and those for Dirichlet problems are based upon Chebyshev polynomials. An improved preconditioning for Dirichlet problems is given. Numerical examples and practical advice are included.

Total variation superiorized conjugate gradient method for image reconstruction

NASA Astrophysics Data System (ADS)

Zibetti, Marcelo V. W.; Lin, Chuan; Herman, Gabor T.

2018-03-01

The conjugate gradient (CG) method is commonly used for the relatively-rapid solution of least squares problems. In image reconstruction, the problem can be ill-posed and also contaminated by noise; due to this, approaches such as regularization should be utilized. Total variation (TV) is a useful regularization penalty, frequently utilized in image reconstruction for generating images with sharp edges. When a non-quadratic norm is selected for regularization, as is the case for TV, then it is no longer possible to use CG. Non-linear CG is an alternative, but it does not share the efficiency that CG shows with least squares and methods such as fast iterative shrinkage-thresholding algorithms (FISTA) are preferred for problems with TV norm. A different approach to including prior information is superiorization. In this paper it is shown that the conjugate gradient method can be superiorized. Five different CG variants are proposed, including preconditioned CG. The CG methods superiorized by the total variation norm are presented and their performance in image reconstruction is demonstrated. It is illustrated that some of the proposed variants of the superiorized CG method can produce reconstructions of superior quality to those produced by FISTA and in less computational time, due to the speed of the original CG for least squares problems. In the Appendix we examine the behavior of one of the superiorized CG methods (we call it S-CG); one of its input parameters is a positive number ɛ. It is proved that, for any given ɛ that is greater than the half-squared-residual for the least squares solution, S-CG terminates in a finite number of steps with an output for which the half-squared-residual is less than or equal to ɛ. Importantly, it is also the case that the output will have a lower value of TV than what would be provided by unsuperiorized CG for the same value ɛ of the half-squared residual.

Dynamic simulation of concentrated macromolecular solutions with screened long-range hydrodynamic interactions: Algorithm and limitations

PubMed Central

Ando, Tadashi; Chow, Edmond; Skolnick, Jeffrey

2013-01-01

Hydrodynamic interactions exert a critical effect on the dynamics of macromolecules. As the concentration of macromolecules increases, by analogy to the behavior of semidilute polymer solutions or the flow in porous media, one might expect hydrodynamic screening to occur. Hydrodynamic screening would have implications both for the understanding of macromolecular dynamics as well as practical implications for the simulation of concentrated macromolecular solutions, e.g., in cells. Stokesian dynamics (SD) is one of the most accurate methods for simulating the motions of N particles suspended in a viscous fluid at low Reynolds number, in that it considers both far-field and near-field hydrodynamic interactions. This algorithm traditionally involves an O(N3) operation to compute Brownian forces at each time step, although asymptotically faster but more complex SD methods are now available. Motivated by the idea of hydrodynamic screening, the far-field part of the hydrodynamic matrix in SD may be approximated by a diagonal matrix, which is equivalent to assuming that long range hydrodynamic interactions are completely screened. This approximation allows sparse matrix methods to be used, which can reduce the apparent computational scaling to O(N). Previously there were several simulation studies using this approximation for monodisperse suspensions. Here, we employ newly designed preconditioned iterative methods for both the computation of Brownian forces and the solution of linear systems, and consider the validity of this approximation in polydisperse suspensions. We evaluate the accuracy of the diagonal approximation method using an intracellular-like suspension. The diffusivities of particles obtained with this approximation are close to those with the original method. However, this approximation underestimates intermolecular correlated motions, which is a trade-off between accuracy and computing efficiency. The new method makes it possible to perform large-scale and long-time simulation with an approximate accounting of hydrodynamic interactions. PMID:24089734

A fast and robust iterative algorithm for prediction of RNA pseudoknotted secondary structures

PubMed Central

2014-01-01

Background Improving accuracy and efficiency of computational methods that predict pseudoknotted RNA secondary structures is an ongoing challenge. Existing methods based on free energy minimization tend to be very slow and are limited in the types of pseudoknots that they can predict. Incorporating known structural information can improve prediction accuracy; however, there are not many methods for prediction of pseudoknotted structures that can incorporate structural information as input. There is even less understanding of the relative robustness of these methods with respect to partial information. Results We present a new method, Iterative HFold, for pseudoknotted RNA secondary structure prediction. Iterative HFold takes as input a pseudoknot-free structure, and produces a possibly pseudoknotted structure whose energy is at least as low as that of any (density-2) pseudoknotted structure containing the input structure. Iterative HFold leverages strengths of earlier methods, namely the fast running time of HFold, a method that is based on the hierarchical folding hypothesis, and the energy parameters of HotKnots V2.0. Our experimental evaluation on a large data set shows that Iterative HFold is robust with respect to partial information, with average accuracy on pseudoknotted structures steadily increasing from roughly 54% to 79% as the user provides up to 40% of the input structure. Iterative HFold is much faster than HotKnots V2.0, while having comparable accuracy. Iterative HFold also has significantly better accuracy than IPknot on our HK-PK and IP-pk168 data sets. Conclusions Iterative HFold is a robust method for prediction of pseudoknotted RNA secondary structures, whose accuracy with more than 5% information about true pseudoknot-free structures is better than that of IPknot, and with about 35% information about true pseudoknot-free structures compares well with that of HotKnots V2.0 while being significantly faster. Iterative HFold and all data used in this work are freely available at http://www.cs.ubc.ca/~hjabbari/software.php. PMID:24884954

Iterative Strain-Gage Balance Calibration Data Analysis for Extended Independent Variable Sets

NASA Technical Reports Server (NTRS)

Ulbrich, Norbert Manfred

2011-01-01

A new method was developed that makes it possible to use an extended set of independent calibration variables for an iterative analysis of wind tunnel strain gage balance calibration data. The new method permits the application of the iterative analysis method whenever the total number of balance loads and other independent calibration variables is greater than the total number of measured strain gage outputs. Iteration equations used by the iterative analysis method have the limitation that the number of independent and dependent variables must match. The new method circumvents this limitation. It simply adds a missing dependent variable to the original data set by using an additional independent variable also as an additional dependent variable. Then, the desired solution of the regression analysis problem can be obtained that fits each gage output as a function of both the original and additional independent calibration variables. The final regression coefficients can be converted to data reduction matrix coefficients because the missing dependent variables were added to the data set without changing the regression analysis result for each gage output. Therefore, the new method still supports the application of the two load iteration equation choices that the iterative method traditionally uses for the prediction of balance loads during a wind tunnel test. An example is discussed in the paper that illustrates the application of the new method to a realistic simulation of temperature dependent calibration data set of a six component balance.

Full seismic waveform tomography for upper-mantle structure in the Australasian region using adjoint methods

NASA Astrophysics Data System (ADS)

Fichtner, Andreas; Kennett, Brian L. N.; Igel, Heiner; Bunge, Hans-Peter

2009-12-01

We present a full seismic waveform tomography for upper-mantle structure in the Australasian region. Our method is based on spectral-element simulations of seismic wave propagation in 3-D heterogeneous earth models. The accurate solution of the forward problem ensures that waveform misfits are solely due to as yet undiscovered Earth structure and imprecise source descriptions, thus leading to more realistic tomographic images and source parameter estimates. To reduce the computational costs, we implement a long-wavelength equivalent crustal model. We quantify differences between the observed and the synthetic waveforms using time-frequency (TF) misfits. Their principal advantages are the separation of phase and amplitude misfits, the exploitation of complete waveform information and a quasi-linear relation to 3-D Earth structure. Fréchet kernels for the TF misfits are computed via the adjoint method. We propose a simple data compression scheme and an accuracy-adaptive time integration of the wavefields that allows us to reduce the storage requirements of the adjoint method by almost two orders of magnitude. To minimize the waveform phase misfit, we implement a pre-conditioned conjugate gradient algorithm. Amplitude information is incorporated indirectly by a restricted line search. This ensures that the cumulative envelope misfit does not increase during the inversion. An efficient pre-conditioner is found empirically through numerical experiments. It prevents the concentration of structural heterogeneity near the sources and receivers. We apply our waveform tomographic method to ~1000 high-quality vertical-component seismograms, recorded in the Australasian region between 1993 and 2008. The waveforms comprise fundamental- and higher-mode surface and long-period S body waves in the period range from 50 to 200 s. To improve the convergence of the algorithm, we implement a 3-D initial model that contains the long-wavelength features of the Australasian region. Resolution tests indicate that our algorithm converges after around 10 iterations and that both long- and short-wavelength features in the uppermost mantle are well resolved. There is evidence for effects related to the non-linearity in the inversion procedure. After 11 iterations we fit the data waveforms acceptably well; with no significant further improvements to be expected. During the inversion the total fitted seismogram length increases by 46 per cent, providing a clear indication of the efficiency and consistency of the iterative optimization algorithm. The resulting SV-wave velocity model reveals structural features of the Australasian upper mantle with great detail. We confirm the existence of a pronounced low-velocity band along the eastern margin of the continent that can be clearly distinguished against Precambrian Australia and the microcontinental Lord Howe Rise. The transition from Precambrian to Phanerozoic Australia (the Tasman Line) appears to be sharp down to at least 200 km depth. It mostly occurs further east of where it is inferred from gravity and magnetic anomalies. Also clearly visible are the Archean and Proterozoic cratons, the northward continuation of the continent and anomalously low S-wave velocities in the upper mantle in central Australia. This is, to the best of our knowledge, the first application of non-linear full seismic waveform tomography to a continental-scale problem.

Sensory Preconditioning in Newborn Rabbits: From Common to Distinct Odor Memories

ERIC Educational Resources Information Center

Coureaud, Gerard; Tourat, Audrey; Ferreira, Guillaume

2013-01-01

This study evaluated whether olfactory preconditioning is functional in newborn rabbits and based on joined or independent memory of odorants. First, after exposure to odorants A+B, the conditioning of A led to high responsiveness to odorant B. Second, responsiveness to B persisted after amnesia of A. Third, preconditioning was also functional…

40 CFR 85.2220 - Preconditioned two speed idle test-EPA 91.

Code of Federal Regulations, 2010 CFR

2010-07-01

... 40 Protection of Environment 18 2010-07-01 2010-07-01 false Preconditioned two speed idle test-EPA... Warranty Short Tests § 85.2220 Preconditioned two speed idle test—EPA 91. (a) General requirements—(1...-speed mode followed immediately by a first-chance idle mode. (ii) The second-chance test as described...

40 CFR 85.2220 - Preconditioned two speed idle test-EPA 91.

Code of Federal Regulations, 2011 CFR

2011-07-01

... 40 Protection of Environment 18 2011-07-01 2011-07-01 false Preconditioned two speed idle test-EPA... Warranty Short Tests § 85.2220 Preconditioned two speed idle test—EPA 91. (a) General requirements—(1...-speed mode followed immediately by a first-chance idle mode. (ii) The second-chance test as described...

Neuroprotective effects of ischemic preconditioning on hippocampal CA1 pyramidal neurons through maintaining calbindin D28k immunoreactivity following subsequent transient cerebral ischemia

PubMed Central

Kim, In Hye; Jeon, Yong Hwan; Lee, Tae-Kyeong; Cho, Jeong Hwi; Lee, Jae-Chul; Park, Joon Ha; Ahn, Ji Hyeon; Shin, Bich-Na; Kim, Yang Hee; Hong, Seongkweon; Yan, Bing Chun; Won, Moo-Ho; Lee, Yun Lyul

2017-01-01

Ischemic preconditioning elicited by a non-fatal brief occlusion of blood flow has been applied for an experimental therapeutic strategy against a subsequent fatal ischemic insult. In this study, we investigated the neuroprotective effects of ischemic preconditioning (2-minute transient cerebral ischemia) on calbindin D28k immunoreactivity in the gerbil hippocampal CA1 area following a subsequent fatal transient ischemic insult (5-minute transient cerebral ischemia). A large number of pyramidal neurons in the hippocampal CA1 area died 4 days after 5-minute transient cerebral ischemia. Ischemic preconditioning reduced the death of pyramidal neurons in the hippocampal CA1 area. Calbindin D28k immunoreactivity was greatly attenuated at 2 days after 5-minute transient cerebral ischemia and it was hardly detected at 5 days post-ischemia. Ischemic preconditioning maintained calbindin D28k immunoreactivity after transient cerebral ischemia. These findings suggest that ischemic preconditioning can attenuate transient cerebral ischemia-caused damage to the pyramidal neurons in the hippocampal CA1 area through maintaining calbindin D28k immunoreactivity. PMID:28761424

A comparison theorem for the SOR iterative method

NASA Astrophysics Data System (ADS)

Sun, Li-Ying

2005-09-01

In 1997, Kohno et al. have reported numerically that the improving modified Gauss-Seidel method, which was referred to as the IMGS method, is superior to the SOR iterative method. In this paper, we prove that the spectral radius of the IMGS method is smaller than that of the SOR method and Gauss-Seidel method, if the relaxation parameter [omega][set membership, variant](0,1]. As a result, we prove theoretically that this method is succeeded in improving the convergence of some classical iterative methods. Some recent results are improved.

Performance of uncertainty quantification methodologies and linear solvers in cardiovascular simulations

NASA Astrophysics Data System (ADS)

Seo, Jongmin; Schiavazzi, Daniele; Marsden, Alison

2017-11-01

Cardiovascular simulations are increasingly used in clinical decision making, surgical planning, and disease diagnostics. Patient-specific modeling and simulation typically proceeds through a pipeline from anatomic model construction using medical image data to blood flow simulation and analysis. To provide confidence intervals on simulation predictions, we use an uncertainty quantification (UQ) framework to analyze the effects of numerous uncertainties that stem from clinical data acquisition, modeling, material properties, and boundary condition selection. However, UQ poses a computational challenge requiring multiple evaluations of the Navier-Stokes equations in complex 3-D models. To achieve efficiency in UQ problems with many function evaluations, we implement and compare a range of iterative linear solver and preconditioning techniques in our flow solver. We then discuss applications to patient-specific cardiovascular simulation and how the problem/boundary condition formulation in the solver affects the selection of the most efficient linear solver. Finally, we discuss performance improvements in the context of uncertainty propagation. Support from National Institute of Health (R01 EB018302) is greatly appreciated.

A generalized Poisson solver for first-principles device simulations

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

Bani-Hashemian, Mohammad Hossein; VandeVondele, Joost, E-mail: joost.vandevondele@mat.ethz.ch; Brück, Sascha

2016-01-28

Electronic structure calculations of atomistic systems based on density functional theory involve solving the Poisson equation. In this paper, we present a plane-wave based algorithm for solving the generalized Poisson equation subject to periodic or homogeneous Neumann conditions on the boundaries of the simulation cell and Dirichlet type conditions imposed at arbitrary subdomains. In this way, source, drain, and gate voltages can be imposed across atomistic models of electronic devices. Dirichlet conditions are enforced as constraints in a variational framework giving rise to a saddle point problem. The resulting system of equations is then solved using a stationary iterative methodmore » in which the generalized Poisson operator is preconditioned with the standard Laplace operator. The solver can make use of any sufficiently smooth function modelling the dielectric constant, including density dependent dielectric continuum models. For all the boundary conditions, consistent derivatives are available and molecular dynamics simulations can be performed. The convergence behaviour of the scheme is investigated and its capabilities are demonstrated.« less

ForTrilinos Design Document

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

Young, Mitchell T.; Johnson, Seth R.; Prokopenko, Andrey V.

With the development of a Fortran Interface to Trilinos, ForTrilinos, modelers using modern Fortran will beable to provide their codes the capability to use solvers and other capabilities on exascale machines via astraightforward infrastructure that accesses Trilinos. This document outlines what Fortrilinos does andexplains briefly how it works. We show it provides a general access to packages via an entry point and usesan xml file from fortran code. With the first release, ForTrilinos will enable Teuchos to take xml parameterlists from Fortran code and set up data structures. It will provide access to linear solvers and eigensolvers.Several examples are providedmore » to illustrate the capabilities in practice. We explain what the user shouldhave already with their code and what Trilinos provides and returns to the Fortran code. We provideinformation about the build process for ForTrilinos, with a practical example. In future releases, nonlinearsolvers, time iteration, advanced preconditioning techniques, and inversion of control (IoC), to enablecallbacks to Fortran routines, will be available.« less

Hyperbaric oxygen therapy and preconditioning for ischemic and hemorrhagic stroke.

PubMed

Hu, Sheng-Li; Feng, Hua; Xi, Guo-Hua

2016-01-01

To date, the therapeutic methods for ischemic and hemorrhagic stroke are still limited. The lack of oxygen supply is critical for brain injury following stroke. Hyperbaric oxygen (HBO), an approach through a process in which patients breathe in 100% pure oxygen at over 101 kPa, has been shown to facilitate oxygen delivery and increase oxygen supply. Hence, HBO possesses the potentials to produce beneficial effects on stroke. Actually, accumulated basic and clinical evidences have demonstrated that HBO therapy and preconditioning could induce neuroprotective functions via different mechanisms. Nevertheless, the lack of clinical translational study limits the application of HBO. More translational studies and clinical trials are needed in the future to develop effective HBO protocols.

Iterative approach as alternative to S-matrix in modal methods

NASA Astrophysics Data System (ADS)

Semenikhin, Igor; Zanuccoli, Mauro

2014-12-01

The continuously increasing complexity of opto-electronic devices and the rising demands of simulation accuracy lead to the need of solving very large systems of linear equations making iterative methods promising and attractive from the computational point of view with respect to direct methods. In particular, iterative approach potentially enables the reduction of required computational time to solve Maxwell's equations by Eigenmode Expansion algorithms. Regardless of the particular eigenmodes finding method used, the expansion coefficients are computed as a rule by scattering matrix (S-matrix) approach or similar techniques requiring order of M3 operations. In this work we consider alternatives to the S-matrix technique which are based on pure iterative or mixed direct-iterative approaches. The possibility to diminish the impact of M3 -order calculations to overall time and in some cases even to reduce the number of arithmetic operations to M2 by applying iterative techniques are discussed. Numerical results are illustrated to discuss validity and potentiality of the proposed approaches.

S{sub 2}SA preconditioning for the S{sub n} equations with strictly non negative spatial discretization

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

Bruss, D. E.; Morel, J. E.; Ragusa, J. C.

2013-07-01

Preconditioners based upon sweeps and diffusion-synthetic acceleration have been constructed and applied to the zeroth and first spatial moments of the 1-D S{sub n} transport equation using a strictly non negative nonlinear spatial closure. Linear and nonlinear preconditioners have been analyzed. The effectiveness of various combinations of these preconditioners are compared. In one dimension, nonlinear sweep preconditioning is shown to be superior to linear sweep preconditioning, and DSA preconditioning using nonlinear sweeps in conjunction with a linear diffusion equation is found to be essentially equivalent to nonlinear sweeps in conjunction with a nonlinear diffusion equation. The ability to use amore » linear diffusion equation has important implications for preconditioning the S{sub n} equations with a strictly non negative spatial discretization in multiple dimensions. (authors)« less

Preconditioning with the traditional Chinese medicine Huang-Lian-Jie-Du-Tang initiates HIF-1α-dependent neuroprotection against cerebral ischemia in rats.

PubMed

Zhang, Qichun; Bian, Huimin; Li, Yu; Guo, Liwei; Tang, Yuping; Zhu, Huaxu

2014-06-11

Huang-Lian-Jie-Du-Tang (HLJDT) is a classical heat-clearing and detoxicating formula of traditional Chinese medicine that is widely used to treat stroke. The present study was designed to investigate the effects of HLJDT preconditioning on neurons under oxygen and glucose deprivation (OGD) and rats subjected to middle cerebral artery occlusion (MCAO). A stroke model of rats was obtained through MCAO. Following HLJDT preconditioning, the cerebral infarction volume, cerebral water content, and neurological deficient score were determined. Cerebral cortical neurons cultured in vitro were preconditioned with HLJDT and then subjected to OGD treatment. The release of lactate dehydrogenase (LDH) from neurons was detected. The levels of hypoxia-inducible factor-1α (HIF-1α) and PI3K/Akt signaling were analyzed by western blotting, and the levels of erythropoietin (EPO) and vascular endothelial growth factor (VEGF) in the supernatant of the neurons and the plasma of MCAO rats were measured through a radioimmunological assay. The apoptosis and proliferation of neurons were analyzed by immunohistochemistry. HLJDT preconditioning significantly reduced the cerebral infarction volume and cerebral water content and ameliorated the neurological deficient score of MCAO rats. In addition, HLJDT preconditioning protected neurons against OGD. Increased HIF-1α, EPO, and VEGF levels and the activation of PI3K/Akt signaling were observed as a result of HLJDT preconditioning. Furthermore, HLJDT preconditioning was found to inhibit ischemia-induced neuron apoptosis and to promote neuron proliferation under conditions of ischemia/reperfusion. Both rats and neurons subjected to HLJDT preconditioning were able to resist ischemia/reperfusion or hypoxia injury through the inhibition of apoptosis and the enhancement of proliferation, and these effects were primarily dependent on the activation of the PI3K/Akt signaling pathway and HIF-1α. Copyright © 2014 Elsevier Ireland Ltd. All rights reserved.

Toll-like receptor 3 pre-conditioning increases the therapeutic efficacy of umbilical cord mesenchymal stromal cells in a dextran sulfate sodium-induced colitis model.

PubMed

Fuenzalida, Patricia; Kurte, Mónica; Fernández-O'ryan, Catalina; Ibañez, Cristina; Gauthier-Abeliuk, Melanie; Vega-Letter, Ana María; Gonzalez, Paz; Irarrázabal, Carlos; Quezada, Nataly; Figueroa, Fernando; Carrión, Flavio

2016-05-01

Immunomodulatory properties of human umbilical cord-derived mesenchymal stromal cells (UCMSCs) can be differentially modulated by toll-like receptors (TLR) agonists. Here, the therapeutic efficacy of short TLR3 and TLR4 pre-conditioning of UCMSCs was evaluated in a dextran sulfate sodium (DSS)-induced colitis in mice. The novelty of this study is that although modulation of human MSCs activity by TLRs is not a new concept, this is the first time that short TLR pre-conditioning has been carried out in a murine inflammatory model of acute colitis. C57BL/6 mice were exposed to 2.5% dextran sulfate sodium (DSS) in drinking water ad libitum for 7 days. At days 1 and 3, mice were injected intraperitoneally with 1 × 10(6) UCMSCs untreated or TLR3 and TLR4 pre-conditioned UCMSCs. UCMSCs were pre-conditioned with poly(I:C) for TLR3 and LPS for TLR4 for 1 h at 37°C and 5% CO2. We evaluated clinical signs of disease and body weights daily. At the end of the experiment, colon length and histological changes were assessed. poly(I:C) pre-conditioned UCMSCs significantly ameliorated the clinical and histopathological severity of DSS-induced colitis compared with UCMSCs or LPS pre-conditioned UCMSCs. In contrast, infusion of LPS pre-conditioned UCMSCs significantly increased clinical signs of disease, colon shortening and histological disease index in DSS-induced colitis. These results show that short in vitro TLR3 pre-conditioning with poly(I:C) enhances the therapeutic efficacy of UCMSCs, which is a major breakthrough for developing improved treatments to patients with inflammatory bowel disease. Copyright © 2016 International Society for Cellular Therapy. Published by Elsevier Inc. All rights reserved.

Evidence that the adenosine A3 receptor may mediate the protection afforded by preconditioning in the isolated rabbit heart.

PubMed

Liu, G S; Richards, S C; Olsson, R A; Mullane, K; Walsh, R S; Downey, J M

1994-07-01

Agonists selective for the A1 adenosine receptor mimic the protective effect of ischaemic preconditioning against infarction in the rabbit heart. Unselective adenosine antagonists block this protection but, paradoxically, the A1 adenosine receptor selective antagonist 8-cyclopentyl- 1,3-dipropylxanthine (DPCPX) does not. The aim of this study was to test the hypothesis that the newly described A3 adenosine receptor, which has an agonist profile similar to the A1 receptor but is insensitive to DPCPX, might mediate preconditioning. Isolated rabbit hearts perfused with Krebs buffer experienced 30 min of regional ischaemia followed by 120 min of reperfusion. Infarct size was measured by tetrazolium staining. In control hearts infarction was 32.2(SEM 1.5)% of the risk zone. Preconditioning by 5 min ischaemia and 10 min reperfusion reduced infarct size to 8.8(2.3)%. Replacing the regional ischaemia with 5 min perfusion with 10 microM adenosine or 65 nM N6-[2-(4-aminophenyl)ethyl]adenosine (APNEA), an adenosine A3 receptor agonist, was equally protective. The unselective antagonist 8-p-sulphophenyl theophylline at 100 microM abolished protection by preconditioning, adenosine, and APNEA, but 200 nM DPCPX did not block protection by any of the interventions. Likewise the potent but unselective A3 receptor antagonist 8-(4-carboxyethenylphenyl)-1,3-dipropylxanthine (BW A1433) completely blocked protection from ischaemic preconditioning. Because protection against infarction afforded by ischaemic preconditioning, adenosine, or the A3 receptor agonist APNEA could not be blocked by DPCPX and because the potent A3 receptor antagonist BW A1433 blocked protection from ischaemic preconditioning, these data indicate that the protection of preconditioning is not exclusively mediated by the adenosine A1 receptor in rabbit heart and could involve the A3 receptor.

Aerodynamic shape optimization using preconditioned conjugate gradient methods

NASA Technical Reports Server (NTRS)

Burgreen, Greg W.; Baysal, Oktay

1993-01-01

In an effort to further improve upon the latest advancements made in aerodynamic shape optimization procedures, a systematic study is performed to examine several current solution methodologies as applied to various aspects of the optimization procedure. It is demonstrated that preconditioned conjugate gradient-like methodologies dramatically decrease the computational efforts required for such procedures. The design problem investigated is the shape optimization of the upper and lower surfaces of an initially symmetric (NACA-012) airfoil in inviscid transonic flow and at zero degree angle-of-attack. The complete surface shape is represented using a Bezier-Bernstein polynomial. The present optimization method then automatically obtains supercritical airfoil shapes over a variety of freestream Mach numbers. Furthermore, the best optimization strategy examined resulted in a factor of 8 decrease in computational time as well as a factor of 4 decrease in memory over the most efficient strategies in current use.

Efficient solution of the simplified P N equations

DOE PAGES

Hamilton, Steven P.; Evans, Thomas M.

2014-12-23

We show new solver strategies for the multigroup SPN equations for nuclear reactor analysis. By forming the complete matrix over space, moments, and energy a robust set of solution strategies may be applied. Moreover, power iteration, shifted power iteration, Rayleigh quotient iteration, Arnoldi's method, and a generalized Davidson method, each using algebraic and physics-based multigrid preconditioners, have been compared on C5G7 MOX test problem as well as an operational PWR model. These results show that the most ecient approach is the generalized Davidson method, that is 30-40 times faster than traditional power iteration and 6-10 times faster than Arnoldi's method.

An Improved Newton's Method.

ERIC Educational Resources Information Center

Mathews, John H.

1989-01-01

Describes Newton's method to locate roots of an equation using the Newton-Raphson iteration formula. Develops an adaptive method overcoming limitations of the iteration method. Provides the algorithm and computer program of the adaptive Newton-Raphson method. (YP)

An accelerated subspace iteration for eigenvector derivatives

NASA Technical Reports Server (NTRS)

Ting, Tienko

1991-01-01

An accelerated subspace iteration method for calculating eigenvector derivatives has been developed. Factors affecting the effectiveness and the reliability of the subspace iteration are identified, and effective strategies concerning these factors are presented. The method has been implemented, and the results of a demonstration problem are presented.

Albany/FELIX: A parallel, scalable and robust, finite element, first-order Stokes approximation ice sheet solver built for advanced analysis

DOE PAGES

Tezaur, I. K.; Perego, M.; Salinger, A. G.; ...

2015-04-27

This paper describes a new parallel, scalable and robust finite element based solver for the first-order Stokes momentum balance equations for ice flow. The solver, known as Albany/FELIX, is constructed using the component-based approach to building application codes, in which mature, modular libraries developed as a part of the Trilinos project are combined using abstract interfaces and template-based generic programming, resulting in a final code with access to dozens of algorithmic and advanced analysis capabilities. Following an overview of the relevant partial differential equations and boundary conditions, the numerical methods chosen to discretize the ice flow equations are described, alongmore » with their implementation. The results of several verification studies of the model accuracy are presented using (1) new test cases for simplified two-dimensional (2-D) versions of the governing equations derived using the method of manufactured solutions, and (2) canonical ice sheet modeling benchmarks. Model accuracy and convergence with respect to mesh resolution are then studied on problems involving a realistic Greenland ice sheet geometry discretized using hexahedral and tetrahedral meshes. Also explored as a part of this study is the effect of vertical mesh resolution on the solution accuracy and solver performance. The robustness and scalability of our solver on these problems is demonstrated. Lastly, we show that good scalability can be achieved by preconditioning the iterative linear solver using a new algebraic multilevel preconditioner, constructed based on the idea of semi-coarsening.« less

Hybrid Multiscale Finite Volume Method for Advection-Diffusion Equations Subject to Heterogeneous Reactive Boundary Conditions

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

Barajas-Solano, David A.; Tartakovsky, A. M.

2016-10-13

We present a hybrid scheme for the coupling of macro and microscale continuum models for reactive contaminant transport in fractured and porous media. The transport model considered is the advection-dispersion equation, subject to linear heterogeneous reactive boundary conditions. The Multiscale Finite Volume method (MsFV) is employed to define an approximation to the microscale concentration field defined in terms of macroscopic or \\emph{global} degrees of freedom, together with local interpolator and corrector functions capturing microscopic spatial variability. The macroscopic mass balance relations for the MsFV global degrees of freedom are coupled with the macroscopic model, resulting in a global problem for the simultaneous time-stepping of all macroscopic degrees of freedom throughout the domain. In order to perform the hybrid coupling, the micro and macroscale models are applied over overlapping subdomains of the simulation domain, with the overlap denoted as the handshake subdomainmore » $$\\Omega^{hs}$$, over which continuity of concentration and transport fluxes between models is enforced. Continuity of concentration is enforced by posing a restriction relation between models over $$\\Omega^{hs}$$. Continuity of fluxes is enforced by prolongating the macroscopic model fluxes across the boundary of $$\\Omega^{hs}$$ to microscopic resolution. The microscopic interpolator and corrector functions are solutions to local microscopic advection-diffusion problems decoupled from the global degrees of freedom and from each other by virtue of the MsFV decoupling ansatz. The error introduced by the decoupling ansatz is reduced iteratively by the preconditioned GMRES algorithm, with the hybrid MsFV operator serving as the preconditioner.« less

Cardioprotective Effects of Transfusion of Late-Phase Preconditioned Plasma May Be Induced by Activating the Reperfusion Injury Salvage Kinase Pathway but Not the Survivor Activating Factor Enhancement Pathway in Rats.

PubMed

Zhao, Yang; Zheng, Zhi-Nan; Pi, Yan-Na; Liang, Xue; Jin, San-Qing

2017-01-01

A previous study in our laboratory demonstrated that transfusion of plasma collected at the late phase of remote ischemic preconditioning (RIPC) could reduce myocardial infarct size. Here, we tested whether the reperfusion injury salvage kinase (RISK) and survivor activating factor enhancement (SAFE) pathways are involved in transferring protection. In a two-part study, donor rats ( n = 3) donated plasma 48 hours after RIPC (preconditioned plasma) or control (nonpreconditioned plasma). Normal (part 1) or ischemic (part 2) myocardia were collected from recipients ( n = 6) 24 hours after receiving normal saline, nonpreconditioned plasma, and preconditioned plasma or after further suffering ischemia reperfusion. Western blot was performed to analyze STAT3, Akt, and Erk1/2 phosphorylation in normal and ischemic myocardium (central area and border area). In normal myocardia, preconditioned plasma increased Akt and Erk1/2 phosphorylation significantly compared to nonpreconditioned plasma and normal saline; no STAT3 phosphorylation was detected. In ischemic myocardia, preconditioned plasma increased Akt and Erk1/2 phosphorylation significantly in both central and border areas compared to other fluids; no significant difference in STAT3 phosphorylation occurred among groups. Transfusion of preconditioned plasma collected at the late phase of RIPC could activate the RISK but not SAFE pathway, suggesting that RISK pathway may be involved in transferring protection.

Iterative CT reconstruction using coordinate descent with ordered subsets of data

NASA Astrophysics Data System (ADS)

Noo, F.; Hahn, K.; Schöndube, H.; Stierstorfer, K.

2016-04-01

Image reconstruction based on iterative minimization of a penalized weighted least-square criteria has become an important topic of research in X-ray computed tomography. This topic is motivated by increasing evidence that such a formalism may enable a significant reduction in dose imparted to the patient while maintaining or improving image quality. One important issue associated with this iterative image reconstruction concept is slow convergence and the associated computational effort. For this reason, there is interest in finding methods that produce approximate versions of the targeted image with a small number of iterations and an acceptable level of discrepancy. We introduce here a novel method to produce such approximations: ordered subsets in combination with iterative coordinate descent. Preliminary results demonstrate that this method can produce, within 10 iterations and using only a constant image as initial condition, satisfactory reconstructions that retain the noise properties of the targeted image.

Parallelized implicit propagators for the finite-difference Schrödinger equation

NASA Astrophysics Data System (ADS)

Parker, Jonathan; Taylor, K. T.

1995-08-01

We describe the application of block Gauss-Seidel and block Jacobi iterative methods to the design of implicit propagators for finite-difference models of the time-dependent Schrödinger equation. The block-wise iterative methods discussed here are mixed direct-iterative methods for solving simultaneous equations, in the sense that direct methods (e.g. LU decomposition) are used to invert certain block sub-matrices, and iterative methods are used to complete the solution. We describe parallel variants of the basic algorithm that are well suited to the medium- to coarse-grained parallelism of work-station clusters, and MIMD supercomputers, and we show that under a wide range of conditions, fine-grained parallelism of the computation can be achieved. Numerical tests are conducted on a typical one-electron atom Hamiltonian. The methods converge robustly to machine precision (15 significant figures), in some cases in as few as 6 or 7 iterations. The rate of convergence is nearly independent of the finite-difference grid-point separations.

40 CFR 86.153-98 - Vehicle and canister preconditioning; refueling test.

Code of Federal Regulations, 2012 CFR

2012-07-01

... controlled to 50±25 grains of water vapor per pound of dry air) maintained at a nominal flow rate of 0.8 cfm... preconditioning; refueling test. (a) Vehicle and canister preconditioning. Vehicles and vapor storage canisters... at least 1200 canister bed volumes of ambient air (with humidity controlled to 50±25 grains of water...

40 CFR 86.153-98 - Vehicle and canister preconditioning; refueling test.

Code of Federal Regulations, 2011 CFR

2011-07-01

... controlled to 50±25 grains of water vapor per pound of dry air) maintained at a nominal flow rate of 0.8 cfm... preconditioning; refueling test. (a) Vehicle and canister preconditioning. Vehicles and vapor storage canisters... at least 1200 canister bed volumes of ambient air (with humidity controlled to 50±25 grains of water...

40 CFR 86.153-98 - Vehicle and canister preconditioning; refueling test.

Code of Federal Regulations, 2014 CFR

2014-07-01

... controlled to 50±25 grains of water vapor per pound of dry air) maintained at a nominal flow rate of 0.8 cfm... preconditioning; refueling test. (a) Vehicle and canister preconditioning. Vehicles and vapor storage canisters... at least 1200 canister bed volumes of ambient air (with humidity controlled to 50±25 grains of water...

40 CFR 86.153-98 - Vehicle and canister preconditioning; refueling test.

Code of Federal Regulations, 2010 CFR

2010-07-01

... controlled to 50±25 grains of water vapor per pound of dry air) maintained at a nominal flow rate of 0.8 cfm... preconditioning; refueling test. (a) Vehicle and canister preconditioning. Vehicles and vapor storage canisters... at least 1200 canister bed volumes of ambient air (with humidity controlled to 50±25 grains of water...

40 CFR 86.153-98 - Vehicle and canister preconditioning; refueling test.

Code of Federal Regulations, 2013 CFR

2013-07-01

... controlled to 50±25 grains of water vapor per pound of dry air) maintained at a nominal flow rate of 0.8 cfm... preconditioning; refueling test. (a) Vehicle and canister preconditioning. Vehicles and vapor storage canisters... at least 1200 canister bed volumes of ambient air (with humidity controlled to 50±25 grains of water...

SU-D-206-03: Segmentation Assisted Fast Iterative Reconstruction Method for Cone-Beam CT

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

Wu, P; Mao, T; Gong, S

2016-06-15

Purpose: Total Variation (TV) based iterative reconstruction (IR) methods enable accurate CT image reconstruction from low-dose measurements with sparse projection acquisition, due to the sparsifiable feature of most CT images using gradient operator. However, conventional solutions require large amount of iterations to generate a decent reconstructed image. One major reason is that the expected piecewise constant property is not taken into consideration at the optimization starting point. In this work, we propose an iterative reconstruction method for cone-beam CT (CBCT) using image segmentation to guide the optimization path more efficiently on the regularization term at the beginning of the optimizationmore » trajectory. Methods: Our method applies general knowledge that one tissue component in the CT image contains relatively uniform distribution of CT number. This general knowledge is incorporated into the proposed reconstruction using image segmentation technique to generate the piecewise constant template on the first-pass low-quality CT image reconstructed using analytical algorithm. The template image is applied as an initial value into the optimization process. Results: The proposed method is evaluated on the Shepp-Logan phantom of low and high noise levels, and a head patient. The number of iterations is reduced by overall 40%. Moreover, our proposed method tends to generate a smoother reconstructed image with the same TV value. Conclusion: We propose a computationally efficient iterative reconstruction method for CBCT imaging. Our method achieves a better optimization trajectory and a faster convergence behavior. It does not rely on prior information and can be readily incorporated into existing iterative reconstruction framework. Our method is thus practical and attractive as a general solution to CBCT iterative reconstruction. This work is supported by the Zhejiang Provincial Natural Science Foundation of China (Grant No. LR16F010001), National High-tech R&D Program for Young Scientists by the Ministry of Science and Technology of China (Grant No. 2015AA020917).« less

Fetal asphyctic preconditioning modulates the acute cytokine response thereby protecting against perinatal asphyxia in neonatal rats

PubMed Central

2013-01-01

Background Perinatal asphyxia (PA) is a major cause of brain damage and neurodevelopmental impairment in infants. Recent investigations have shown that experimental sublethal fetal asphyxia (FA preconditioning) protects against a subsequent more severe asphyctic insult at birth. The molecular mechanisms of this protection have, however, not been elucidated. Evidence implicates that inflammatory cytokines play a protective role in the induction of ischemic tolerance in the adult brain. Accordingly, we hypothesize that FA preconditioning leads to changes in the fetal cytokine response, thereby protecting the newborn against a subsequent asphyctic insult. Methods In rats, FA preconditioning was induced at embryonic day 17 by clamping the uterine vasculature for 30 min. At term birth, global PA was induced by placing the uterine horns, containing the pups, in a saline bath for 19 min. We assessed, at different time points after FA and PA, mRNA and protein expression of several cytokines and related receptor mRNA levels in total hemispheres of fetal and neonatal brains. Additionally, we measured pSTAT3/STAT3 levels to investigate cellular responses to these cytokines. Results Prenatally, FA induced acute downregulation in IL-1β, TNF-α and IL-10 mRNA levels. At 96 h post FA, IL-6 mRNA and IL-10 protein expression were increased in FA brains compared with controls. Two hours after birth, all proinflammatory cytokines and pSTAT3/STAT3 levels decreased in pups that experienced FA and/or PA. Interestingly, IL-10 and IL-6 mRNA levels increased after PA. When pups were FA preconditioned, however, IL-10 and IL-6 mRNA levels were comparable to those in controls. Conclusions FA leads to prenatal changes in the neuroinflammatory response. This modulation of the cytokine response probably results in the protective inflammatory phenotype seen when combining FA and PA and may have significant implications for preventing post-asphyctic perinatal encephalopathy. PMID:23351591

Iteration, Not Induction

ERIC Educational Resources Information Center

Dobbs, David E.

2009-01-01

The main purpose of this note is to present and justify proof via iteration as an intuitive, creative and empowering method that is often available and preferable as an alternative to proofs via either mathematical induction or the well-ordering principle. The method of iteration depends only on the fact that any strictly decreasing sequence of…

IMPLEMENTATION AND VALIDATION OF A FULLY IMPLICIT ACCUMULATOR MODEL IN RELAP-7

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

Zhao, Haihua; Zou, Ling; Zhang, Hongbin

2016-01-01

This paper presents the implementation and validation of an accumulator model in RELAP-7 under the framework of preconditioned Jacobian free Newton Krylov (JFNK) method, based on the similar model used in RELAP5. RELAP-7 is a new nuclear reactor system safety analysis code being developed at the Idaho National Laboratory (INL). RELAP-7 is a fully implicit system code. The JFNK and preconditioning methods used in RELAP-7 is briefly discussed. The slightly modified accumulator model is summarized for completeness. The implemented model was validated with LOFT L3-1 test and benchmarked with RELAP5 results. RELAP-7 and RELAP5 had almost identical results for themore » accumulator gas pressure and water level, although there were some minor difference in other parameters such as accumulator gas temperature and tank wall temperature. One advantage of the JFNK method is its easiness to maintain and modify models due to fully separation of numerical methods from physical models. It would be straightforward to extend the current RELAP-7 accumulator model to simulate the advanced accumulator design.« less

Comparison of Implicit Schemes for the Incompressible Navier-Stokes Equations

NASA Technical Reports Server (NTRS)

Rogers, Stuart E.

1995-01-01

For a computational flow simulation tool to be useful in a design environment, it must be very robust and efficient. To develop such a tool for incompressible flow applications, a number of different implicit schemes are compared for several two-dimensional flow problems in the current study. The schemes include Point-Jacobi relaxation, Gauss-Seidel line relaxation, incomplete lower-upper decomposition, and the generalized minimum residual method preconditioned with each of the three other schemes. The efficiency of the schemes is measured in terms of the computing time required to obtain a steady-state solution for the laminar flow over a backward-facing step, the flow over a NACA 4412 airfoil, and the flow over a three-element airfoil using overset grids. The flow solver used in the study is the INS2D code that solves the incompressible Navier-Stokes equations using the method of artificial compressibility and upwind differencing of the convective terms. The results show that the generalized minimum residual method preconditioned with the incomplete lower-upper factorization outperforms all other methods by at least a factor of 2.

Fetal asphyctic preconditioning alters the transcriptional response to perinatal asphyxia.

PubMed

Cox-Limpens, Kimberly E M; Vles, Johan S H; LA van den Hove, Daniel; Zimmermann, Luc J I; Gavilanes, Antonio W D

2014-05-29

Genomic reprogramming is thought to be, at least in part, responsible for the protective effect of brain preconditioning. Unraveling mechanisms of this endogenous neuroprotection, activated by preconditioning, is an important step towards new clinical strategies for treating asphyctic neonates.Therefore, we investigated whole-genome transcriptional changes in the brain of rats which underwent perinatal asphyxia (PA), and rats where PA was preceded by fetal asphyctic preconditioning (FAPA). Offspring were sacrificed 6 h and 96 h after birth, and whole-genome transcription was investigated using the Affymetrix Gene1.0ST chip. Microarray data were analyzed with the Bioconductor Limma package. In addition to univariate analysis, we performed Gene Set Enrichment Analysis (GSEA) in order to derive results with maximum biological relevance. We observed minimal, 25% or less, overlap of differentially regulated transcripts across different experimental groups which leads us to conclude that the transcriptional phenotype of these groups is largely unique. In both the PA and FAPA group we observe an upregulation of transcripts involved in cellular stress. Contrastingly, transcripts with a function in the cell nucleus were mostly downregulated in PA animals, while we see considerable upregulation in the FAPA group. Furthermore, we observed that histone deacetylases (HDACs) are exclusively regulated in FAPA animals. This study is the first to investigate whole-genome transcription in the neonatal brain after PA alone, and after perinatal asphyxia preceded by preconditioning (FAPA). We describe several genes/pathways, such as ubiquitination and proteolysis, which were not previously linked to preconditioning-induced neuroprotection. Furthermore, we observed that the majority of upregulated genes in preconditioned animals have a function in the cell nucleus, including several epigenetic players such as HDACs, which suggests that epigenetic mechanisms are likely to play a role in preconditioning-induced neuroprotection.

Fetal asphyctic preconditioning alters the transcriptional response to perinatal asphyxia

PubMed Central

2014-01-01

Background Genomic reprogramming is thought to be, at least in part, responsible for the protective effect of brain preconditioning. Unraveling mechanisms of this endogenous neuroprotection, activated by preconditioning, is an important step towards new clinical strategies for treating asphyctic neonates. Therefore, we investigated whole-genome transcriptional changes in the brain of rats which underwent perinatal asphyxia (PA), and rats where PA was preceded by fetal asphyctic preconditioning (FAPA). Offspring were sacrificed 6 h and 96 h after birth, and whole-genome transcription was investigated using the Affymetrix Gene1.0ST chip. Microarray data were analyzed with the Bioconductor Limma package. In addition to univariate analysis, we performed Gene Set Enrichment Analysis (GSEA) in order to derive results with maximum biological relevance. Results We observed minimal, 25% or less, overlap of differentially regulated transcripts across different experimental groups which leads us to conclude that the transcriptional phenotype of these groups is largely unique. In both the PA and FAPA group we observe an upregulation of transcripts involved in cellular stress. Contrastingly, transcripts with a function in the cell nucleus were mostly downregulated in PA animals, while we see considerable upregulation in the FAPA group. Furthermore, we observed that histone deacetylases (HDACs) are exclusively regulated in FAPA animals. Conclusions This study is the first to investigate whole-genome transcription in the neonatal brain after PA alone, and after perinatal asphyxia preceded by preconditioning (FAPA). We describe several genes/pathways, such as ubiquitination and proteolysis, which were not previously linked to preconditioning-induced neuroprotection. Furthermore, we observed that the majority of upregulated genes in preconditioned animals have a function in the cell nucleus, including several epigenetic players such as HDACs, which suggests that epigenetic mechanisms are likely to play a role in preconditioning-induced neuroprotection. PMID:24885038

Morphine Preconditioning Downregulates MicroRNA-134 Expression Against Oxygen-Glucose Deprivation Injuries in Cultured Neurons of Mice.

PubMed

Meng, Fanjun; Li, Yan; Chi, Wenying; Li, Junfa

2016-07-01

Brain protection by narcotics such as morphine is clinically relevant due to the extensive use of narcotics in the perioperative period. Morphine preconditioning induces neuroprotection in neurons, but it remains uncertain whether microRNA-134 (miR-134) is involved in morphine preconditioning against oxygen-glucose deprivation-induced injuries in primary cortical neurons of mice. The present study examined this issue. After cortical neurons of mice were cultured in vitro for 6 days, the neurons were transfected by respective virus vector, such as lentiviral vector (LV)-miR-control-GFP, LV-pre-miR-134-GFP, LV-pre-miR-134-inhibitor-GFP for 24 hours; after being normally cultured for 3 days again, morphine preconditioning was performed by incubating the transfected primary neurons with morphine (3 μM) for 1 hour, and then neuronal cells were exposed to oxygen-glucose deprivation (OGD) for 1 hour and oxygen-glucose recovery for 12 hours. The neuronal cells survival rate and the amount of apoptotic neurons were determined by MTT assay or TUNEL staining at designated time; and the expression levels of miR-134 were detected using real-time reverse transcription polymerase chain reaction at the same time. The neuronal cell survival rate was significantly higher, and the amount of apoptotic neurons was significantly decreased in neurons preconditioned with morphine before OGD than that of OGD alone. The neuroprotection induced by morphine preconditioning was partially blocked by upregulating miR-134 expression, and was enhanced by downregulating miR-134 expression. The expression of miR-134 was significantly decreased in morphine-preconditioned neurons alone without transfection. By downregulating miR-134 expression, morphine preconditioning protects primary cortical neurons of mice against injuries induced by OGD.

The time dependence of the effect of ischemic preconditioning on successive sprint swimming performance.

PubMed

Lisbôa, Felipe D; Turnes, Tiago; Cruz, Rogério S O; Raimundo, João A G; Pereira, Gustavo S; Caputo, Fabrizio

2017-05-01

The present study aimed to determine the effects of ischemic preconditioning on performance in three successive 50-m swimming trials and to measure stroke rate, stroke length and blood lactate accumulation. Counterbalanced, repeated-measures cross-over study. On two separate days, eleven competitive male swimmers (20±3 years, 182±5cm, 77±5kg) performed three successive 50-m trials in a 50-m swimming pool, preceded by intermittent bilateral cuff inflation (4× 5-min of blood flow restriction+5-min of cuff deflation) at either 220 for thighs and 180mmHg for arms (ischemic preconditioning) or 20mmHg for both limbs (control-treatment). The 50-m trials were conducted 1-, 2-, and 8-h after the procedure. While no ergogenic effect of ischemic preconditioning was observed for 1-h (0.4%, 95% confidence limits of ±0.6%, p=0.215), there were clear beneficial effects of ischemic preconditioning on 2- and 8-h (1.0% and 1.2%, respectively; 95% confidence limits of ±0.6% in both cases, p≤0.002). Furthermore, ischemic preconditioning increased blood lactate accumulation in 2-(p<0.001) and 8-h (p=0.010) and stroke rate for 2- and 8-h in specific 10-m segments (p<0.05). These findings suggest a time-dependent effect of ischemic preconditioning on 50-m swimming performance for competitive athletes, with the time window of the beneficial effect starting after about 2-h and lasting for at least 8-h after ischemic preconditioning. This change in performance was accompanied by an increase in blood lactate accumulation and faster strokes in front crawl. Copyright © 2016 Sports Medicine Australia. Published by Elsevier Ltd. All rights reserved.

Remote ischemic preconditioning and endothelial function in patients with acute myocardial infarction and primary PCI.

PubMed

Manchurov, Vladimir; Ryazankina, Nadezda; Khmara, Tatyana; Skrypnik, Dmitry; Reztsov, Roman; Vasilieva, Elena; Shpektor, Alexander

2014-07-01

Remote ischemic preconditioning by transient limb ischemia reduces myocardial ischemia-reperfusion injury in patients undergoing percutaneous coronary intervention. The aim of the study we report here was to assess the effect of remote ischemic preconditioning on endothelial function in patients with acute myocardial infarction who underwent primary percutaneous coronary intervention. Forty-eight patients with acute myocardial infarction were enrolled. All participants were randomly divided into 2 groups. In Group I (n = 23), remote ischemic preconditioning was performed before primary percutaneous coronary intervention (intermittent arm ischemia-reperfusion through 4 cycles of 5-minute inflation and 5-minute deflation of a blood-pressure cuff to 200 mm Hg). In Group II (n = 25), standard percutaneous coronary intervention without preconditioning was performed. We assessed endothelial function using the flow-mediated dilation test on baseline, then within 1-3 hours after percutaneous coronary intervention, and again on days 2 and 7 after percutaneous coronary intervention. The brachial artery flow-mediated dilation results were significantly higher on the first day after primary percutaneous coronary intervention in the preconditioning group (Group I) than in the control group (Group II) (12.1% vs 0.0%, P = .03, and 11.1% vs 6.3%, P = .016, respectively), and this difference remained on the seventh day (12.3% vs 7.4%, P = .0005, respectively). We demonstrated for the first time that remote ischemic preconditioning before primary percutaneous coronary intervention significantly improves endothelial function in patients with acute myocardial infarction, and this effect remains constant for at least a week. We suppose that the improvement of endothelial function may be one of the possible explanations of the effect of remote ischemic preconditioning. Copyright © 2014 Elsevier Inc. All rights reserved.

Age-related reduction of cerebral ischemic preconditioning: myth or reality?

PubMed Central

Della-Morte, David; Cacciatore, Francesco; Salsano, Elisa; Pirozzi, Gilda; Genio, Maria Teresa Del; D’Antonio, Iole; Gargiulo, Gaetano; Palmirotta, Raffaele; Guadagni, Fiorella; Rundek, Tatjana; Abete, Pasquale

2013-01-01

Stroke is one of the leading causes of death in industrialized countries for people older than 65 years of age. The reasons are still unclear. A reduction of endogenous mechanisms against ischemic insults has been proposed to explain this phenomenon. The “cerebral” ischemic preconditioning mechanism is characterized by a brief episode of ischemia that renders the brain more resistant against subsequent longer ischemic events. This ischemic tolerance has been shown in numerous experimental models of cerebral ischemia. This protective mechanism seems to be reduced with aging both in experimental and clinical studies. Alterations of mediators released and/or intracellular pathways may be responsible for age-related ischemic preconditioning reduction. Agents able to mimic the “cerebral” preconditioning effect may represent a new powerful tool for the treatment of acute ischemic stroke in the elderly. In this article, animal and human cerebral ischemic preconditioning, its age-related difference, and its potential therapeutical applications are discussed. PMID:24204128

Rapamycin preconditioning attenuates transient focal cerebral ischemia/reperfusion injury in mice.

PubMed

Yin, Lele; Ye, Shasha; Chen, Zhen; Zeng, Yaoying

2012-12-01

Rapamycin, an mTOR inhibitor and immunosuppressive agent in clinic, has protective effects on traumatic brain injury and neurodegenerative diseases. But, its effects on transient focal ischemia/reperfusion disease are not very clear. In this study, we examined the effects of rapamycin preconditioning on mice treated with middle cerebral artery occlusion/reperfusion operation (MCAO/R). We found that the rapamycin preconditioning by intrahippocampal injection 20 hr before MCAO/R significantly improved the survival rate and longevity of mice. It also decreased the neurological deficit score, infracted areas and brain edema. In addition, rapamycin preconditioning decreased the production of NF-κB, TNF-α, and Bax, but not Bcl-2, an antiapoptotic protein in the ischemic area. From these results, we may conclude that rapamycin preconditioning attenuate transient focal cerebral ischemia/reperfusion injury and inhibits apoptosis induced by MCAO/R in mice.

A new iterative triclass thresholding technique in image segmentation.

PubMed

Cai, Hongmin; Yang, Zhong; Cao, Xinhua; Xia, Weiming; Xu, Xiaoyin

2014-03-01

We present a new method in image segmentation that is based on Otsu's method but iteratively searches for subregions of the image for segmentation, instead of treating the full image as a whole region for processing. The iterative method starts with Otsu's threshold and computes the mean values of the two classes as separated by the threshold. Based on the Otsu's threshold and the two mean values, the method separates the image into three classes instead of two as the standard Otsu's method does. The first two classes are determined as the foreground and background and they will not be processed further. The third class is denoted as a to-be-determined (TBD) region that is processed at next iteration. At the succeeding iteration, Otsu's method is applied on the TBD region to calculate a new threshold and two class means and the TBD region is again separated into three classes, namely, foreground, background, and a new TBD region, which by definition is smaller than the previous TBD regions. Then, the new TBD region is processed in the similar manner. The process stops when the Otsu's thresholds calculated between two iterations is less than a preset threshold. Then, all the intermediate foreground and background regions are, respectively, combined to create the final segmentation result. Tests on synthetic and real images showed that the new iterative method can achieve better performance than the standard Otsu's method in many challenging cases, such as identifying weak objects and revealing fine structures of complex objects while the added computational cost is minimal.

Periodic Pulay method for robust and efficient convergence acceleration of self-consistent field iterations

DOE PAGES

Banerjee, Amartya S.; Suryanarayana, Phanish; Pask, John E.

2016-01-21

Pulay's Direct Inversion in the Iterative Subspace (DIIS) method is one of the most widely used mixing schemes for accelerating the self-consistent solution of electronic structure problems. In this work, we propose a simple generalization of DIIS in which Pulay extrapolation is performed at periodic intervals rather than on every self-consistent field iteration, and linear mixing is performed on all other iterations. Lastly, we demonstrate through numerical tests on a wide variety of materials systems in the framework of density functional theory that the proposed generalization of Pulay's method significantly improves its robustness and efficiency.

Asymptotic (h tending to infinity) absolute stability for BDFs applied to stiff differential equations. [Backward Differentiation Formulas

NASA Technical Reports Server (NTRS)

Krogh, F. T.; Stewart, K.

1984-01-01

Methods based on backward differentiation formulas (BDFs) for solving stiff differential equations require iterating to approximate the solution of the corrector equation on each step. One hope for reducing the cost of this is to make do with iteration matrices that are known to have errors and to do no more iterations than are necessary to maintain the stability of the method. This paper, following work by Klopfenstein, examines the effect of errors in the iteration matrix on the stability of the method. Application of the results to an algorithm is discussed briefly.

A Build-Up Interior Method for Linear Programming: Affine Scaling Form

DTIC Science & Technology

1990-02-01

initiating a major iteration imply convergence in a finite number of iterations. Each iteration t of the Dikin algorithm starts with an interior dual...this variant with the affine scaling method of Dikin [5] (in dual form). We have also looked into the analogous variant for the related Karmarkar’s...4] G. B. Dantzig, Linear Programming and Extensions (Princeton University Press, Princeton, NJ, 1963). [5] I. I. Dikin , "Iterative solution of

Preconditioning principles for preventing sports injuries in adolescents and children.

PubMed

Dollard, Mark D; Pontell, David; Hallivis, Robert

2006-01-01

Preseason preconditioning can be accomplished well over a 4-week period with a mandatory period of rest as we have discussed. Athletic participation must be guided by a gradual increase of skills performance in the child assessed after a responsible preconditioning program applying physiologic parameters as outlined. Clearly, designing a preconditioning program is a dynamic process when accounting for all the variables in training discussed so far. Despite the physiologic demands of sport and training, we still need to acknowledge the psychologic maturity and welfare of the child so as to ensure that the sport environment is a wholesome and emotionally rewarding experience.

Effects of exercise preconditioning on intestinal ischemia-reperfusion injury.

PubMed

Gokbel, H; Oz, M; Okudan, N; Belviranli, M; Esen, H

2014-01-01

To investigate the effects of exercise preconditioning on oxidative injury in the intestinal tissue of rats. Sixty male Wistar rats were randomly divided into six groups as sham (n = 10), ischemia-reperfusion (n = 10), exercise (n = 10), exercise plus ischemia-reperfusion (n = 10), ischemic preconditioning (n = 10), and ischemic preconditioning plus ischemia-reperfusion groups (n = 10). Tissue levels of malondialdehyde and activities of myeloperoxidase and superoxide dismutase, and serum levels of tumor necrosis factor-alpha and interleukin-6 were measured. Intestinal tissue histopathology was also evaluated by light microscopy. Tumor necrosis factor-alpha concentrations significantly decreased in the exercise group compared to the sham group (p < 0.05). Myeloperoxidase activity significantly increased and superoxide dismutase activity significantly decreased in ischemia-reperfusion group compared to the sham group (p < 0.05). Superoxide dismutase activity in the ischemic preconditioning and ischemic preconditioning plus ischemia-reperfusion groups were significantly higher compared to the ischemia-reperfusion and exercise groups (p < 0.05). Histopathologically, intestinal injury significantly attenuated in the exercise plus ischemia-reperfusion group compared to the ischemia-reperfusion group. The results of the present study indicate that exercise training seems to have a protective role against intestinal ischemia-reperfusion injury (Tab. 3, Fig. 1, Ref. 35).

Iterative metal artifact reduction for x-ray computed tomography using unmatched projector/backprojector pairs

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

Zhang, Hanming; Wang, Linyuan; Li, Lei

2016-06-15

Purpose: Metal artifact reduction (MAR) is a major problem and a challenging issue in x-ray computed tomography (CT) examinations. Iterative reconstruction from sinograms unaffected by metals shows promising potential in detail recovery. This reconstruction has been the subject of much research in recent years. However, conventional iterative reconstruction methods easily introduce new artifacts around metal implants because of incomplete data reconstruction and inconsistencies in practical data acquisition. Hence, this work aims at developing a method to suppress newly introduced artifacts and improve the image quality around metal implants for the iterative MAR scheme. Methods: The proposed method consists of twomore » steps based on the general iterative MAR framework. An uncorrected image is initially reconstructed, and the corresponding metal trace is obtained. The iterative reconstruction method is then used to reconstruct images from the unaffected sinogram. In the reconstruction step of this work, an iterative strategy utilizing unmatched projector/backprojector pairs is used. A ramp filter is introduced into the back-projection procedure to restrain the inconsistency components in low frequencies and generate more reliable images of the regions around metals. Furthermore, a constrained total variation (TV) minimization model is also incorporated to enhance efficiency. The proposed strategy is implemented based on an iterative FBP and an alternating direction minimization (ADM) scheme, respectively. The developed algorithms are referred to as “iFBP-TV” and “TV-FADM,” respectively. Two projection-completion-based MAR methods and three iterative MAR methods are performed simultaneously for comparison. Results: The proposed method performs reasonably on both simulation and real CT-scanned datasets. This approach could reduce streak metal artifacts effectively and avoid the mentioned effects in the vicinity of the metals. The improvements are evaluated by inspecting regions of interest and by comparing the root-mean-square errors, normalized mean absolute distance, and universal quality index metrics of the images. Both iFBP-TV and TV-FADM methods outperform other counterparts in all cases. Unlike the conventional iterative methods, the proposed strategy utilizing unmatched projector/backprojector pairs shows excellent performance in detail preservation and prevention of the introduction of new artifacts. Conclusions: Qualitative and quantitative evaluations of experimental results indicate that the developed method outperforms classical MAR algorithms in suppressing streak artifacts and preserving the edge structural information of the object. In particular, structures lying close to metals can be gradually recovered because of the reduction of artifacts caused by inconsistency effects.« less

Electromagnetic scattering of large structures in layered earths using integral equations

NASA Astrophysics Data System (ADS)

Xiong, Zonghou; Tripp, Alan C.

1995-07-01

An electromagnetic scattering algorithm for large conductivity structures in stratified media has been developed and is based on the method of system iteration and spatial symmetry reduction using volume electric integral equations. The method of system iteration divides a structure into many substructures and solves the resulting matrix equation using a block iterative method. The block submatrices usually need to be stored on disk in order to save computer core memory. However, this requires a large disk for large structures. If the body is discretized into equal-size cells it is possible to use the spatial symmetry relations of the Green's functions to regenerate the scattering impedance matrix in each iteration, thus avoiding expensive disk storage. Numerical tests show that the system iteration converges much faster than the conventional point-wise Gauss-Seidel iterative method. The numbers of cells do not significantly affect the rate of convergency. Thus the algorithm effectively reduces the solution of the scattering problem to an order of O(N2), instead of O(N3) as with direct solvers.

Neuron specific metabolic adaptations following multi-day exposures to oxygen glucose deprivation.

PubMed

Zeiger, Stephanie L H; McKenzie, Jennifer R; Stankowski, Jeannette N; Martin, Jacob A; Cliffel, David E; McLaughlin, BethAnn

2010-11-01

Prior exposure to sub toxic insults can induce a powerful endogenous neuroprotective program known as ischemic preconditioning. Current models typically rely on a single stress episode to induce neuroprotection whereas the clinical reality is that patients may experience multiple transient ischemic attacks (TIAs) prior to suffering a stroke. We sought to develop a neuron-enriched preconditioning model using multiple oxygen glucose deprivation (OGD) episodes to assess the endogenous protective mechanisms neurons implement at the metabolic and cellular level. We found that neurons exposed to a five minute period of glucose deprivation recovered oxygen utilization and lactate production using novel microphysiometry techniques. Using the non-toxic and energetically favorable five minute exposure, we developed a preconditioning paradigm where neurons are exposed to this brief OGD for three consecutive days. These cells experienced a 45% greater survival following an otherwise lethal event and exhibited a longer lasting window of protection in comparison to our previous in vitro preconditioning model using a single stress. As in other models, preconditioned cells exhibited mild caspase activation, an increase in oxidized proteins and a requirement for reactive oxygen species for neuroprotection. Heat shock protein 70 was upregulated during preconditioning, yet the majority of this protein was released extracellularly. We believe coupling this neuron-enriched multi-day model with microphysiometry will allow us to assess neuronal specific real-time metabolic adaptations necessary for preconditioning. Copyright © 2010 Elsevier B.V. All rights reserved.

Hypoxic preconditioning facilitates acclimatization to hypobaric hypoxia in rat heart.

PubMed

Singh, Mrinalini; Shukla, Dhananjay; Thomas, Pauline; Saxena, Saurabh; Bansal, Anju

2010-12-01

Acute systemic hypoxia induces delayed cardioprotection against ischaemia-reperfusion injury in the heart. As cobalt chloride (CoCl₂) is known to elicit hypoxia-like responses, it was hypothesized that this chemical would mimic the preconditioning effect and facilitate acclimatization to hypobaric hypoxia in rat heart. Male Sprague-Dawley rats treated with distilled water or cobalt chloride (12.5 mg Co/kg for 7 days) were exposed to simulated altitude at 7622 m for different time periods (1, 2, 3 and 5 days). Hypoxic preconditioning with cobalt appreciably attenuated hypobaric hypoxia-induced oxidative damage as observed by a decrease in free radical (reactive oxygen species) generation, oxidation of lipids and proteins. Interestingly, the observed effect was due to increased expression of the antioxidant proteins hemeoxygenase and metallothionein, as no significant change was observed in antioxidant enzyme activity. Hypoxic preconditioning with cobalt increased hypoxia-inducible factor 1α (HIF-1α) expression as well as HIF-1 DNA binding activity, which further resulted in increased expression of HIF-1 regulated genes such as erythropoietin, vascular endothelial growth factor and glucose transporter. A significant decrease was observed in lactate dehydrogenase activity and lactate levels in the heart of preconditioned animals compared with non-preconditioned animals exposed to hypoxia. The results showed that hypoxic preconditioning with cobalt induces acclimatization by up-regulation of hemeoxygenase 1 and metallothionein 1 via HIF-1 stabilization. © 2010 The Authors. JPP © 2010 Royal Pharmaceutical Society of Great Britain.

An Upwind Solver for the National Combustion Code

NASA Technical Reports Server (NTRS)

Sockol, Peter M.

2011-01-01

An upwind solver is presented for the unstructured grid National Combustion Code (NCC). The compressible Navier-Stokes equations with time-derivative preconditioning and preconditioned flux-difference splitting of the inviscid terms are used. First order derivatives are computed on cell faces and used to evaluate the shear stresses and heat fluxes. A new flux limiter uses these same first order derivatives in the evaluation of left and right states used in the flux-difference splitting. The k-epsilon turbulence equations are solved with the same second-order method. The new solver has been installed in a recent version of NCC and the resulting code has been tested successfully in 2D on two laminar cases with known solutions and one turbulent case with experimental data.

Iteration with Spreadsheets.

ERIC Educational Resources Information Center

Smith, Michael

1990-01-01

Presents several examples of the iteration method using computer spreadsheets. Examples included are simple iterative sequences and the solution of equations using the Newton-Raphson formula, linear interpolation, and interval bisection. (YP)

Preconditioning for the Navier-Stokes equations with finite-rate chemistry

NASA Technical Reports Server (NTRS)

Godfrey, Andrew G.

1993-01-01

The extension of Van Leer's preconditioning procedure to generalized finite-rate chemistry is discussed. Application to viscous flow is begun with the proper preconditioning matrix for the one-dimensional Navier-Stokes equations. Eigenvalue stiffness is resolved and convergence-rate acceleration is demonstrated over the entire Mach-number range from nearly stagnant flow to hypersonic. Specific benefits are realized at the low and transonic flow speeds typical of complete propulsion-system simulations. The extended preconditioning matrix necessarily accounts for both thermal and chemical nonequilibrium. Numerical analysis reveals the possible theoretical improvements from using a preconditioner for all Mach number regimes. Numerical results confirm the expectations from the numerical analysis. Representative test cases include flows with previously troublesome embedded high-condition-number areas. Van Leer, Lee, and Roe recently developed an optimal, analytic preconditioning technique to reduce eigenvalue stiffness over the full Mach-number range. By multiplying the flux-balance residual with the preconditioning matrix, the acoustic wave speeds are scaled so that all waves propagate at the same rate, an essential property to eliminate inherent eigenvalue stiffness. This session discusses a synthesis of the thermochemical nonequilibrium flux-splitting developed by Grossman and Cinnella and the characteristic wave preconditioning of Van Leer into a powerful tool for implicitly solving two and three-dimensional flows with generalized finite-rate chemistry. For finite-rate chemistry, the state vector of unknowns is variable in length. Therefore, the preconditioning matrix extended to generalized finite-rate chemistry must accommodate a flexible system of moving waves. Fortunately, no new kind of wave appears in the system. The only existing waves are entropy and vorticity waves, which move with the fluid, and acoustic waves, which propagate in Mach number dependent directions. The nonequilibrium vibrational energies and species densities in the unknown state vector act strictly as convective waves. The essential concept for extending the preconditioning to generalized chemistry models is determining the differential variables which symmetrize the flux Jacobians. The extension is then straight-forward. This algorithm research effort will be released in a future version of the production level computational code coined the General Aerodynamic Simulation Program (GASP), developed by Walters, Slack, and McGrory.

[Effect of electroacupuncture and moxibustion preconditioning on blood endothelin and creatine kinase contents and myocardial HSP 70 expression in rabbits with myocardial ischemia-reperfusion injury].

PubMed

Wang, Chao; Xie, Wen-juan; Liu, Mi; Yan, Jie; Zhang, Jia-li; Liu, Zhao; Guo, Li-na

2014-10-01

To observe the effect of electroacupuncture (EA) and moxibustion (Moxi) preconditioning of bi- lateral "Neiguan" (PC 6) on plasma endothelin (ET) and serum creatine kinase (CK) contents and myocardial hot shock protein 70 (HSP 70) expression in myocardial ischemia-reperfusion injury (MIRI) rabbits, so as to revel their mechanisms underlying prevention of myocardial ischemia. A total of 72 New Zealand rabbits were randomly divided into sham operation, MIRI model, EA preconditioning and Moxi preconditioning groups (n = 18/group). Each group was further divided into 0 h, 24 h and 48 h (time-point) subgroups (n=6 in each subgroup). The MIRI model was established by occlusion of the anterior descending branch of the left coronary artery for 40 min and reperfusion for 60 min. The contents of plasma ET and serum CK were detected by ELISA, and myocardial HSP 70 expression was detected by immunohistochemistry. EA and Moxi preconditioning were respectively applied to bilateral PC 6 for 20 min, once daily for 5 days. Following MIRI, contents of plasma ET and serum CK contents were significantly increased at 0 h, 24 h and 48 h in comparison with the sham group (P<0.01, P<0.05), while myo- cardial HSP 70 expression at the 3 time-points was moderately increased (P>0.05). Compared with the model groups, plasma ET contents at both 24 h and 48 h in the EA preconditioning group and at 48 h in the Moxi preconditioning group, CK contents at both 24 h and 48 h only in the EA preconditioning group were significantly down-regulated (P<0.01, P<0.05). Myocardial HSP 70 expression levels in the EA and Moxi preconditioning groups were considerably up-regulated at the three time-points in comparison with the model group(P<0.05, P<0.01). Acupuncture and moxibustion pretreatment may suppress MIRI-induced increase of plasma ET and serum CK and up-regulate myocardial HSP 70 protein expression in MIRI rabbits, suggesting a preventive protection action on ischemic myocardium.

Iterative methods for tomography problems: implementation to a cross-well tomography problem

NASA Astrophysics Data System (ADS)

Karadeniz, M. F.; Weber, G. W.

2018-01-01

The velocity distribution between two boreholes is reconstructed by cross-well tomography, which is commonly used in geology. In this paper, iterative methods, Kaczmarz’s algorithm, algebraic reconstruction technique (ART), and simultaneous iterative reconstruction technique (SIRT), are implemented to a specific cross-well tomography problem. Convergence to the solution of these methods and their CPU time for the cross-well tomography problem are compared. Furthermore, these three methods for this problem are compared for different tolerance values.

Highly efficient and exact method for parallelization of grid-based algorithms and its implementation in DelPhi

PubMed Central

Li, Chuan; Li, Lin; Zhang, Jie; Alexov, Emil

2012-01-01

The Gauss-Seidel method is a standard iterative numerical method widely used to solve a system of equations and, in general, is more efficient comparing to other iterative methods, such as the Jacobi method. However, standard implementation of the Gauss-Seidel method restricts its utilization in parallel computing due to its requirement of using updated neighboring values (i.e., in current iteration) as soon as they are available. Here we report an efficient and exact (not requiring assumptions) method to parallelize iterations and to reduce the computational time as a linear/nearly linear function of the number of CPUs. In contrast to other existing solutions, our method does not require any assumptions and is equally applicable for solving linear and nonlinear equations. This approach is implemented in the DelPhi program, which is a finite difference Poisson-Boltzmann equation solver to model electrostatics in molecular biology. This development makes the iterative procedure on obtaining the electrostatic potential distribution in the parallelized DelPhi several folds faster than that in the serial code. Further we demonstrate the advantages of the new parallelized DelPhi by computing the electrostatic potential and the corresponding energies of large supramolecular structures. PMID:22674480

Pseudo-time methods for constrained optimization problems governed by PDE

NASA Technical Reports Server (NTRS)

Taasan, Shlomo

1995-01-01

In this paper we present a novel method for solving optimization problems governed by partial differential equations. Existing methods are gradient information in marching toward the minimum, where the constrained PDE is solved once (sometimes only approximately) per each optimization step. Such methods can be viewed as a marching techniques on the intersection of the state and costate hypersurfaces while improving the residuals of the design equations per each iteration. In contrast, the method presented here march on the design hypersurface and at each iteration improve the residuals of the state and costate equations. The new method is usually much less expensive per iteration step since, in most problems of practical interest, the design equation involves much less unknowns that that of either the state or costate equations. Convergence is shown using energy estimates for the evolution equations governing the iterative process. Numerical tests show that the new method allows the solution of the optimization problem in a cost of solving the analysis problems just a few times, independent of the number of design parameters. The method can be applied using single grid iterations as well as with multigrid solvers.

Remote ischaemic postconditioning protects the heart during acute myocardial infarction in pigs

PubMed Central

Andreka, Gyorgy; Vertesaljai, Marton; Szantho, Gergely; Font, Gusztav; Piroth, Zsolt; Fontos, Geza; Juhasz, Eszter D; Szekely, Laszlo; Szelid, Zsolt; Turner, Mark S; Ashrafian, Houman; Frenneaux, Michael P

2007-01-01

Background Ischaemic preconditioning results in a reduction in ischaemic‐reperfusion injury to the heart. This beneficial effect is seen both with direct local preconditioning of the myocardium and with remote preconditioning of easily accessible distant non‐vital limb tissue. Ischaemic postconditioning with a comparable sequence of brief periods of local ischaemia, when applied immediately after the ischaemic insult, confers benefits similar to preconditioning. Objective To test the hypothesis that limb ischaemia induces remote postconditioning and hence reduces experimental myocardial infarct size in a validated swine model of acute myocardial infarction. Methods Acute myocardial infarction was induced in 24 pigs with 90 min balloon inflations of the left anterior descending coronary artery. Remote ischaemic postconditioning was induced in 12 of the pigs by four 5 min cycles of blood pressure cuff inflation applied to the lower limb immediately after the balloon deflation. Infarct size was assessed by measuring 72 h creatinine kinase release, MRI scan and immunohistochemical analysis. Results Area under the curve of creatinine kinase release was significantly reduced in the postconditioning group compared with the control group with a 26% reduction in the infarct size (p<0.05). This was confirmed by MRI scanning and immunohistochemical analysis that revealed a 22% (p<0.05) and a 47.52% (p<0.01) relative reduction in the infarct size, respectively. Conclusion Remote ischaemic postconditioning is a simple technique to reduce infarct size without the hazards and logistics of multiple coronary artery balloon inflations. This type of conditioning promises clear clinical potential. PMID:17449499

Preconditioning 2D Integer Data for Fast Convex Hull Computations.

PubMed

Cadenas, José Oswaldo; Megson, Graham M; Luengo Hendriks, Cris L

2016-01-01

In order to accelerate computing the convex hull on a set of n points, a heuristic procedure is often applied to reduce the number of points to a set of s points, s ≤ n, which also contains the same hull. We present an algorithm to precondition 2D data with integer coordinates bounded by a box of size p × q before building a 2D convex hull, with three distinct advantages. First, we prove that under the condition min(p, q) ≤ n the algorithm executes in time within O(n); second, no explicit sorting of data is required; and third, the reduced set of s points forms a simple polygonal chain and thus can be directly pipelined into an O(n) time convex hull algorithm. This paper empirically evaluates and quantifies the speed up gained by preconditioning a set of points by a method based on the proposed algorithm before using common convex hull algorithms to build the final hull. A speedup factor of at least four is consistently found from experiments on various datasets when the condition min(p, q) ≤ n holds; the smaller the ratio min(p, q)/n is in the dataset, the greater the speedup factor achieved.

A New Newton-Like Iterative Method for Roots of Analytic Functions

ERIC Educational Resources Information Center

Otolorin, Olayiwola

2005-01-01

A new Newton-like iterative formula for the solution of non-linear equations is proposed. To derive the formula, the convergence criteria of the one-parameter iteration formula, and also the quasilinearization in the derivation of Newton's formula are reviewed. The result is a new formula which eliminates the limitations of other methods. There is…

The anti-apoptotic effect of fluid mechanics preconditioning by cells membrane and mitochondria in rats brain microvascular endothelial cells.

PubMed

Tian, Shan; Zhu, Fengping; Hu, Ruiping; Tian, Song; Chen, Xingxing; Lou, Dan; Cao, Bing; Chen, Qiulei; Li, Bai; Li, Fang; Bai, Yulong; Wu, Yi; Zhu, Yulian

2018-01-01

Exercise preconditioning is a simple and effective way to prevent ischemia. This paper further provided the mechanism in hemodynamic aspects at the cellular level. To study the anti-apoptotic effects of fluid mechanics preconditioning, Cultured rats brain microvascular endothelial cells were given fluid intervention in a parallel plate flow chamber before oxygen glucose deprivation. It showed that fluid mechanics preconditioning could inhibit the apoptosis of endothelial cells, and this process might be mediated by the shear stress activation of Tie-2 on cells membrane surface and Bcl-2 on the mitochondria surface. Copyright © 2017 Elsevier B.V. All rights reserved.

Iterative Nonlocal Total Variation Regularization Method for Image Restoration

PubMed Central

Xu, Huanyu; Sun, Quansen; Luo, Nan; Cao, Guo; Xia, Deshen

2013-01-01

In this paper, a Bregman iteration based total variation image restoration algorithm is proposed. Based on the Bregman iteration, the algorithm splits the original total variation problem into sub-problems that are easy to solve. Moreover, non-local regularization is introduced into the proposed algorithm, and a method to choose the non-local filter parameter locally and adaptively is proposed. Experiment results show that the proposed algorithms outperform some other regularization methods. PMID:23776560

Iterative integral parameter identification of a respiratory mechanics model.

PubMed

Schranz, Christoph; Docherty, Paul D; Chiew, Yeong Shiong; Möller, Knut; Chase, J Geoffrey

2012-07-18

Patient-specific respiratory mechanics models can support the evaluation of optimal lung protective ventilator settings during ventilation therapy. Clinical application requires that the individual's model parameter values must be identified with information available at the bedside. Multiple linear regression or gradient-based parameter identification methods are highly sensitive to noise and initial parameter estimates. Thus, they are difficult to apply at the bedside to support therapeutic decisions. An iterative integral parameter identification method is applied to a second order respiratory mechanics model. The method is compared to the commonly used regression methods and error-mapping approaches using simulated and clinical data. The clinical potential of the method was evaluated on data from 13 Acute Respiratory Distress Syndrome (ARDS) patients. The iterative integral method converged to error minima 350 times faster than the Simplex Search Method using simulation data sets and 50 times faster using clinical data sets. Established regression methods reported erroneous results due to sensitivity to noise. In contrast, the iterative integral method was effective independent of initial parameter estimations, and converged successfully in each case tested. These investigations reveal that the iterative integral method is beneficial with respect to computing time, operator independence and robustness, and thus applicable at the bedside for this clinical application.

A Universal Tare Load Prediction Algorithm for Strain-Gage Balance Calibration Data Analysis

NASA Technical Reports Server (NTRS)

Ulbrich, N.

2011-01-01

An algorithm is discussed that may be used to estimate tare loads of wind tunnel strain-gage balance calibration data. The algorithm was originally developed by R. Galway of IAR/NRC Canada and has been described in the literature for the iterative analysis technique. Basic ideas of Galway's algorithm, however, are universally applicable and work for both the iterative and the non-iterative analysis technique. A recent modification of Galway's algorithm is presented that improves the convergence behavior of the tare load prediction process if it is used in combination with the non-iterative analysis technique. The modified algorithm allows an analyst to use an alternate method for the calculation of intermediate non-linear tare load estimates whenever Galway's original approach does not lead to a convergence of the tare load iterations. It is also shown in detail how Galway's algorithm may be applied to the non-iterative analysis technique. Hand load data from the calibration of a six-component force balance is used to illustrate the application of the original and modified tare load prediction method. During the analysis of the data both the iterative and the non-iterative analysis technique were applied. Overall, predicted tare loads for combinations of the two tare load prediction methods and the two balance data analysis techniques showed excellent agreement as long as the tare load iterations converged. The modified algorithm, however, appears to have an advantage over the original algorithm when absolute voltage measurements of gage outputs are processed using the non-iterative analysis technique. In these situations only the modified algorithm converged because it uses an exact solution of the intermediate non-linear tare load estimate for the tare load iteration.

Cerenkov luminescence tomography based on preconditioning orthogonal matching pursuit

NASA Astrophysics Data System (ADS)

Liu, Haixiao; Hu, Zhenhua; Wang, Kun; Tian, Jie; Yang, Xin

2015-03-01

Cerenkov luminescence imaging (CLI) is a novel optical imaging method and has been proved to be a potential substitute of the traditional radionuclide imaging such as positron emission tomography (PET) and single-photon emission computed tomography (SPECT). This imaging method inherits the high sensitivity of nuclear medicine and low cost of optical molecular imaging. To obtain the depth information of the radioactive isotope, Cerenkov luminescence tomography (CLT) is established and the 3D distribution of the isotope is reconstructed. However, because of the strong absorption and scatter, the reconstruction of the CLT sources is always converted to an ill-posed linear system which is hard to be solved. In this work, the sparse nature of the light source was taken into account and the preconditioning orthogonal matching pursuit (POMP) method was established to effectively reduce the ill-posedness and obtain better reconstruction accuracy. To prove the accuracy and speed of this algorithm, a heterogeneous numerical phantom experiment and an in vivo mouse experiment were conducted. Both the simulation result and the mouse experiment showed that our reconstruction method can provide more accurate reconstruction result compared with the traditional Tikhonov regularization method and the ordinary orthogonal matching pursuit (OMP) method. Our reconstruction method will provide technical support for the biological application for Cerenkov luminescence.

TIGAR contributes to ischemic tolerance induced by cerebral preconditioning through scavenging of reactive oxygen species and inhibition of apoptosis

PubMed Central

Zhou, Jun-Hao; Zhang, Tong-Tong; Song, Dan-Dan; Xia, Yun-Fei; Qin, Zheng-Hong; Sheng, Rui

2016-01-01

Previous study showed that TIGAR (TP53-induced glycolysis and apoptosis regulator) protected ischemic brain injury via enhancing pentose phosphate pathway (PPP) flux and preserving mitochondria function. This study was aimed to study the role of TIGAR in cerebral preconditioning. The ischemic preconditioning (IPC) and isoflurane preconditioning (ISO) models were established in primary cultured cortical neurons and in mice. Both IPC and ISO increased TIGAR expression in cortical neurons. Preconditioning might upregulate TIGAR through SP1 transcription factor. Lentivirus mediated knockdown of TIGAR significantly abolished the ischemic tolerance induced by IPC and ISO. ISO also increased TIGAR in mouse cortex and hippocampus and alleviated subsequent brain ischemia-reperfusion injury, while the ischemic tolerance induced by ISO was eliminated with TIGAR knockdown in mouse brain. ISO increased the production of NADPH and glutathione (GSH), and scavenged reactive oxygen species (ROS), while TIGAR knockdown decreased GSH and NADPH production and increased the level of ROS. Supplementation of ROS scavenger NAC and PPP product NADPH effectively rescue the neuronal injury caused by TIGAR deficiency. Notably, TIGAR knockdown inhibited ISO-induced anti-apoptotic effects in cortical neurons. These results suggest that TIGAR participates in the cerebral preconditioning through reduction of ROS and subsequent cell apoptosis. PMID:27256465

Integrity of Cerebellar Fastigial Nucleus Intrinsic Neurons Is Critical for the Global Ischemic Preconditioning

PubMed Central

Regnier-Golanov, Angelique S.; Britz, Gavin W.

2017-01-01

Excitation of intrinsic neurons of cerebellar fastigial nucleus (FN) renders brain tolerant to local and global ischemia. This effect reaches a maximum 72 h after the stimulation and lasts over 10 days. Comparable neuroprotection is observed following sublethal global brain ischemia, a phenomenon known as preconditioning. We hypothesized that FN may participate in the mechanisms of ischemic preconditioning as a part of the intrinsic neuroprotective mechanism. To explore potential significance of FN neurons in brain ischemic tolerance we lesioned intrinsic FN neurons with excitotoxin ibotenic acid five days before exposure to 20 min four-vessel occlusion (4-VO) global ischemia while analyzing neuronal damage in Cornu Ammoni area 1 (CA1) hippocampal area one week later. In FN-lesioned animals, loss of CA1 cells was higher by 22% compared to control (phosphate buffered saline (PBS)-injected) animals. Moreover, lesion of FN neurons increased morbidity following global ischemia by 50%. Ablation of FN neurons also reversed salvaging effects of five-minute ischemic preconditioning on CA1 neurons and morbidity, while ablation of cerebellar dentate nucleus neurons did not change effect of ischemic preconditioning. We conclude that FN is an important part of intrinsic neuroprotective system, which participates in ischemic preconditioning and may participate in naturally occurring neuroprotection, such as “diving response”. PMID:28934119

Super-low dose endotoxin pre-conditioning exacerbates sepsis mortality.

PubMed

Chen, Keqiang; Geng, Shuo; Yuan, Ruoxi; Diao, Na; Upchurch, Zachary; Li, Liwu

2015-04-01

Sepsis mortality varies dramatically in individuals of variable immune conditions, with poorly defined mechanisms. This phenomenon complements the hypothesis that innate immunity may adopt rudimentary memory, as demonstrated in vitro with endotoxin priming and tolerance in cultured monocytes. However, previous in vivo studies only examined the protective effect of endotoxin tolerance in the context of sepsis. In sharp contrast, we report herein that pre-conditionings with super-low or low dose endotoxin lipopolysaccharide (LPS) cause strikingly opposite survival outcomes. Mice pre-conditioned with super-low dose LPS experienced severe tissue damage, inflammation, increased bacterial load in circulation, and elevated mortality when they were subjected to cecal-ligation and puncture (CLP). This is in opposite to the well-reported protective phenomenon with CLP mice pre-conditioned with low dose LPS. Mechanistically, we demonstrated that super-low and low dose LPS differentially modulate the formation of neutrophil extracellular trap (NET) in neutrophils. Instead of increased ERK activation and NET formation in neutrophils pre-conditioned with low dose LPS, we observed significantly reduced ERK activation and compromised NET generation in neutrophils pre-conditioned with super-low dose LPS. Collectively, our findings reveal a novel mechanism potentially responsible for the dynamic programming of innate immunity in vivo as it relates to sepsis risks.

Development of iterative techniques for the solution of unsteady compressible viscous flows

NASA Technical Reports Server (NTRS)

Sankar, Lakshmi N.; Hixon, Duane

1991-01-01

Efficient iterative solution methods are being developed for the numerical solution of two- and three-dimensional compressible Navier-Stokes equations. Iterative time marching methods have several advantages over classical multi-step explicit time marching schemes, and non-iterative implicit time marching schemes. Iterative schemes have better stability characteristics than non-iterative explicit and implicit schemes. Thus, the extra work required by iterative schemes can also be designed to perform efficiently on current and future generation scalable, missively parallel machines. An obvious candidate for iteratively solving the system of coupled nonlinear algebraic equations arising in CFD applications is the Newton method. Newton's method was implemented in existing finite difference and finite volume methods. Depending on the complexity of the problem, the number of Newton iterations needed per step to solve the discretized system of equations can, however, vary dramatically from a few to several hundred. Another popular approach based on the classical conjugate gradient method, known as the GMRES (Generalized Minimum Residual) algorithm is investigated. The GMRES algorithm was used in the past by a number of researchers for solving steady viscous and inviscid flow problems with considerable success. Here, the suitability of this algorithm is investigated for solving the system of nonlinear equations that arise in unsteady Navier-Stokes solvers at each time step. Unlike the Newton method which attempts to drive the error in the solution at each and every node down to zero, the GMRES algorithm only seeks to minimize the L2 norm of the error. In the GMRES algorithm the changes in the flow properties from one time step to the next are assumed to be the sum of a set of orthogonal vectors. By choosing the number of vectors to a reasonably small value N (between 5 and 20) the work required for advancing the solution from one time step to the next may be kept to (N+1) times that of a noniterative scheme. Many of the operations required by the GMRES algorithm such as matrix-vector multiplies, matrix additions and subtractions can all be vectorized and parallelized efficiently.

Global Asymptotic Behavior of Iterative Implicit Schemes

NASA Technical Reports Server (NTRS)

Yee, H. C.; Sweby, P. K.

1994-01-01

The global asymptotic nonlinear behavior of some standard iterative procedures in solving nonlinear systems of algebraic equations arising from four implicit linear multistep methods (LMMs) in discretizing three models of 2 x 2 systems of first-order autonomous nonlinear ordinary differential equations (ODEs) is analyzed using the theory of dynamical systems. The iterative procedures include simple iteration and full and modified Newton iterations. The results are compared with standard Runge-Kutta explicit methods, a noniterative implicit procedure, and the Newton method of solving the steady part of the ODEs. Studies showed that aside from exhibiting spurious asymptotes, all of the four implicit LMMs can change the type and stability of the steady states of the differential equations (DEs). They also exhibit a drastic distortion but less shrinkage of the basin of attraction of the true solution than standard nonLMM explicit methods. The simple iteration procedure exhibits behavior which is similar to standard nonLMM explicit methods except that spurious steady-state numerical solutions cannot occur. The numerical basins of attraction of the noniterative implicit procedure mimic more closely the basins of attraction of the DEs and are more efficient than the three iterative implicit procedures for the four implicit LMMs. Contrary to popular belief, the initial data using the Newton method of solving the steady part of the DEs may not have to be close to the exact steady state for convergence. These results can be used as an explanation for possible causes and cures of slow convergence and nonconvergence of steady-state numerical solutions when using an implicit LMM time-dependent approach in computational fluid dynamics.

Implementation of an improved adaptive-implicit method in a thermal compositional simulator

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

Tan, T.B.

1988-11-01

A multicomponent thermal simulator with an adaptive-implicit-method (AIM) formulation/inexact-adaptive-Newton (IAN) method is presented. The final coefficient matrix retains the original banded structure so that conventional iterative methods can be used. Various methods for selection of the eliminated unknowns are tested. AIM/IAN method has a lower work count per Newtonian iteration than fully implicit methods, but a wrong choice of unknowns will result in excessive Newtonian iterations. For the problems tested, the residual-error method described in the paper for selecting implicit unknowns, together with the IAN method, had an improvement of up to 28% of the CPU time over the fullymore » implicit method.« less

Hyperbaric oxygen preconditioning protects against traumatic brain injury at high altitude.

PubMed

Hu, S L; Hu, R; Li, F; Liu, Z; Xia, Y Z; Cui, G Y; Feng, H

2008-01-01

Recent studies have shown that preconditioning with hyperbaric oxygen (HBO) can reduce ischemic and hemorrhagic brain injury. We investigated effects of HBO preconditioning on traumatic brain injury (TBI) at high altitude and examined the role of matrix metalloproteinase-9 (MMP-9) in such protection. Rats were randomly divided into 3 groups: HBO preconditioning group (HBOP; n = 13), high-altitude group (HA; n = 13), and high-altitude sham operation group (HASO; n = 13). All groups were subjected to head trauma by weight-drop device, except for HASO group. HBOP rats received 5 sessions of HBO preconditioning (2.5 ATA, 100% oxygen, 1 h daily) and then were kept in hypobaric chamber at 0.6 ATA (to simulate pressure at 4000m altitude) for 3 days before operation. HA rats received control pretreatment (1 ATA, room air, 1 h daily), then followed the same procedures as HBOP group. HASO rats were subjected to skull opening only without brain injury. Twenty-four hours after TBI, 7 rats from each group were examined for neurological function and brain water content; 6 rats from each group were killed for analysis by H&E staining and immunohistochemistry. Neurological outcome in HBOP group (0.71 +/- 0.49) was better than HA group (1.57 +/- 0.53; p < 0.05). Preconditioning with HBO significantly reduced percentage of brain water content (86.24 +/- 0.52 vs. 84.60 +/- 0.37; p < 0.01). Brain morphology and structure seen by light microscopy was diminished in HA group, while fewer pathological injuries occurred in HBOP group. Compared to HA group, pretreatment with HBO significantly reduced the number of MMP-9-positive cells (92.25 +/- 8.85 vs. 74.42 +/- 6.27; p < 0.01). HBO preconditioning attenuates TBI in rats at high altitude. Decline in MMP-9 expression may contribute to HBO preconditioning-induced protection of brain tissue against TBI.

The role of hypoxia-inducible factor-1α and vascular endothelial growth factor in late-phase preconditioning with xenon, isoflurane and levosimendan in rat cardiomyocytes.

PubMed

Goetzenich, Andreas; Hatam, Nima; Preuss, Stephanie; Moza, Ajay; Bleilevens, Christian; Roehl, Anna B; Autschbach, Rüdiger; Bernhagen, Jürgen; Stoppe, Christian

2014-03-01

The protective effects of late-phase preconditioning can be triggered by several stimuli. Unfortunately, the transfer from bench to bedside still represents a challenge, as concomitant medication or diseases influence the complex signalling pathways involved. In an established model of primary neonatal rat cardiomyocytes, we analysed the cardioprotective effects of three different stimulating pharmaceuticals of clinical relevance. The effect of additional β-blocker treatment was studied as these were previously shown to negatively influence preconditioning. Twenty-four hours prior to hypoxia, cells pre-treated with or without metoprolol (0.55 µg/ml) were preconditioned with isoflurane, levosimendan or xenon. The influences of these stimuli on hypoxia-inducible factor-1α (HIF-1α), vascular endothelial growth factor (VEGF) as well as inducible and endothelial nitric synthase (iNOS/eNOS) and cyclooxygenase-2 (COX-2) were analysed by polymerase chain reaction and western blotting. The preconditioning was proved by trypan blue cell counts following 5 h of hypoxia and confirmed by fluorescence staining. Five hours of hypoxia reduced cell survival in unpreconditioned control cells to 44 ± 4%. Surviving cell count was significantly higher in cells preconditioned either by 2 × 15 min isoflurane (70 ± 16%; P = 0.005) or by xenon (59 ± 8%; P = 0.049). Xenon-preconditioned cells showed a significantly elevated content of VEGF (0.025 ± 0.010 IDV [integrated density values when compared with GAPDH] vs 0.003 ± 0.006 IDV in controls; P = 0.0003). The protein expression of HIF-1α was increased both by levosimendan (0.563 ± 0.175 IDV vs 0.142 ± 0.042 IDV in controls; P = 0.0289) and by xenon (0.868 ± 0.222 IDV; P < 0.0001) pretreatment. A significant elevation of mRNA expression of iNOS was measureable following preconditioning by xenon but not by the other chosen stimuli. eNOS mRNA expression was found to be suppressed by β-blocker treatment for all stimuli. In our model, independently of the chosen stimulus, β-blocker treatment had no significant effect on cell survival. We found that the stimulation of late-phase preconditioning involves several distinct pathways that are variably addressed by the different stimuli. In contrast to isoflurane treatment, xenon-induced preconditioning does not lead to an increase in COX-2 gene transcription but to a significant increase in HIF-1α and subsequently VEGF.

Calibration and compensation method of three-axis geomagnetic sensor based on pre-processing total least square iteration

NASA Astrophysics Data System (ADS)

Zhou, Y.; Zhang, X.; Xiao, W.

2018-04-01

As the geomagnetic sensor is susceptible to interference, a pre-processing total least square iteration method is proposed for calibration compensation. Firstly, the error model of the geomagnetic sensor is analyzed and the correction model is proposed, then the characteristics of the model are analyzed and converted into nine parameters. The geomagnetic data is processed by Hilbert transform (HHT) to improve the signal-to-noise ratio, and the nine parameters are calculated by using the combination of Newton iteration method and the least squares estimation method. The sifter algorithm is used to filter the initial value of the iteration to ensure that the initial error is as small as possible. The experimental results show that this method does not need additional equipment and devices, can continuously update the calibration parameters, and better than the two-step estimation method, it can compensate geomagnetic sensor error well.

Perturbation-iteration theory for analyzing microwave striplines

NASA Technical Reports Server (NTRS)

Kretch, B. E.

1985-01-01

A perturbation-iteration technique is presented for determining the propagation constant and characteristic impedance of an unshielded microstrip transmission line. The method converges to the correct solution with a few iterations at each frequency and is equivalent to a full wave analysis. The perturbation-iteration method gives a direct solution for the propagation constant without having to find the roots of a transcendental dispersion equation. The theory is presented in detail along with numerical results for the effective dielectric constant and characteristic impedance for a wide range of substrate dielectric constants, stripline dimensions, and frequencies.

Block Preconditioning to Enable Physics-Compatible Implicit Multifluid Plasma Simulations

NASA Astrophysics Data System (ADS)

Phillips, Edward; Shadid, John; Cyr, Eric; Miller, Sean

2017-10-01

Multifluid plasma simulations involve large systems of partial differential equations in which many time-scales ranging over many orders of magnitude arise. Since the fastest of these time-scales may set a restrictively small time-step limit for explicit methods, the use of implicit or implicit-explicit time integrators can be more tractable for obtaining dynamics at time-scales of interest. Furthermore, to enforce properties such as charge conservation and divergence-free magnetic field, mixed discretizations using volume, nodal, edge-based, and face-based degrees of freedom are often employed in some form. Together with the presence of stiff modes due to integrating over fast time-scales, the mixed discretization makes the required linear solves for implicit methods particularly difficult for black box and monolithic solvers. This work presents a block preconditioning strategy for multifluid plasma systems that segregates the linear system based on discretization type and approximates off-diagonal coupling in block diagonal Schur complement operators. By employing multilevel methods for the block diagonal subsolves, this strategy yields algorithmic and parallel scalability which we demonstrate on a range of problems.

Steady state numerical solutions for determining the location of MEMS on projectile

NASA Astrophysics Data System (ADS)

Abiprayu, K.; Abdigusna, M. F. F.; Gunawan, P. H.

2018-03-01

This paper is devoted to compare the numerical solutions for the steady and unsteady state heat distribution model on projectile. Here, the best location for installing of the MEMS on the projectile based on the surface temperature is investigated. Numerical iteration methods, Jacobi and Gauss-Seidel have been elaborated to solve the steady state heat distribution model on projectile. The results using Jacobi and Gauss-Seidel are shown identical but the discrepancy iteration cost for each methods is gained. Using Jacobi’s method, the iteration cost is 350 iterations. Meanwhile, using Gauss-Seidel 188 iterations are obtained, faster than the Jacobi’s method. The comparison of the simulation by steady state model and the unsteady state model by a reference is shown satisfying. Moreover, the best candidate for installing MEMS on projectile is observed at pointT(10, 0) which has the lowest temperature for the other points. The temperature using Jacobi and Gauss-Seidel for scenario 1 and 2 atT(10, 0) are 307 and 309 Kelvin respectively.

Material nonlinear analysis via mixed-iterative finite element method

NASA Technical Reports Server (NTRS)

Sutjahjo, Edhi; Chamis, Christos C.

1992-01-01

The performance of elastic-plastic mixed-iterative analysis is examined through a set of convergence studies. Membrane and bending behaviors are tested using 4-node quadrilateral finite elements. The membrane result is excellent, which indicates the implementation of elastic-plastic mixed-iterative analysis is appropriate. On the other hand, further research to improve bending performance of the method seems to be warranted.

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

NASA Astrophysics Data System (ADS)

Codd, A. L.; Gross, L.

2018-03-01

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

On the solution of evolution equations based on multigrid and explicit iterative methods

NASA Astrophysics Data System (ADS)

Zhukov, V. T.; Novikova, N. D.; Feodoritova, O. B.

2015-08-01

Two schemes for solving initial-boundary value problems for three-dimensional parabolic equations are studied. One is implicit and is solved using the multigrid method, while the other is explicit iterative and is based on optimal properties of the Chebyshev polynomials. In the explicit iterative scheme, the number of iteration steps and the iteration parameters are chosen as based on the approximation and stability conditions, rather than on the optimization of iteration convergence to the solution of the implicit scheme. The features of the multigrid scheme include the implementation of the intergrid transfer operators for the case of discontinuous coefficients in the equation and the adaptation of the smoothing procedure to the spectrum of the difference operators. The results produced by these schemes as applied to model problems with anisotropic discontinuous coefficients are compared.

Differential Characteristics Based Iterative Multiuser Detection for Wireless Sensor Networks

PubMed Central

Chen, Xiaoguang; Jiang, Xu; Wu, Zhilu; Zhuang, Shufeng

2017-01-01

High throughput, low latency and reliable communication has always been a hot topic for wireless sensor networks (WSNs) in various applications. Multiuser detection is widely used to suppress the bad effect of multiple access interference in WSNs. In this paper, a novel multiuser detection method based on differential characteristics is proposed to suppress multiple access interference. The proposed iterative receive method consists of three stages. Firstly, a differential characteristics function is presented based on the optimal multiuser detection decision function; then on the basis of differential characteristics, a preliminary threshold detection is utilized to find the potential wrongly received bits; after that an error bit corrector is employed to correct the wrong bits. In order to further lower the bit error ratio (BER), the differential characteristics calculation, threshold detection and error bit correction process described above are iteratively executed. Simulation results show that after only a few iterations the proposed multiuser detection method can achieve satisfactory BER performance. Besides, BER and near far resistance performance are much better than traditional suboptimal multiuser detection methods. Furthermore, the proposed iterative multiuser detection method also has a large system capacity. PMID:28212328

The application of contraction theory to an iterative formulation of electromagnetic scattering

NASA Technical Reports Server (NTRS)

Brand, J. C.; Kauffman, J. F.

1985-01-01

Contraction theory is applied to an iterative formulation of electromagnetic scattering from periodic structures and a computational method for insuring convergence is developed. A short history of spectral (or k-space) formulation is presented with an emphasis on application to periodic surfaces. To insure a convergent solution of the iterative equation, a process called the contraction corrector method is developed. Convergence properties of previously presented iterative solutions to one-dimensional problems are examined utilizing contraction theory and the general conditions for achieving a convergent solution are explored. The contraction corrector method is then applied to several scattering problems including an infinite grating of thin wires with the solution data compared to previous works.

A non-iterative extension of the multivariate random effects meta-analysis.

PubMed

Makambi, Kepher H; Seung, Hyunuk

2015-01-01

Multivariate methods in meta-analysis are becoming popular and more accepted in biomedical research despite computational issues in some of the techniques. A number of approaches, both iterative and non-iterative, have been proposed including the multivariate DerSimonian and Laird method by Jackson et al. (2010), which is non-iterative. In this study, we propose an extension of the method by Hartung and Makambi (2002) and Makambi (2001) to multivariate situations. A comparison of the bias and mean square error from a simulation study indicates that, in some circumstances, the proposed approach perform better than the multivariate DerSimonian-Laird approach. An example is presented to demonstrate the application of the proposed approach.

Preconditioning for the Navier-Stokes equations with finite-rate chemistry

NASA Technical Reports Server (NTRS)

Godfrey, Andrew G.; Walters, Robert W.; Van Leer, Bram

1993-01-01

The preconditioning procedure for generalized finite-rate chemistry and the proper preconditioning for the one-dimensional Navier-Stokes equations are presented. Eigenvalue stiffness is resolved and convergence-rate acceleration is demonstrated over the entire Mach-number range from the incompressible to the hypersonic. Specific benefits are realized at low and transonic flow speeds. The extended preconditioning matrix accounts for thermal and chemical non-equilibrium and its implementation is explained for both explicit and implicit time marching. The effect of higher-order spatial accuracy and various flux splittings is investigated. Numerical analysis reveals the possible theoretical improvements from using proconditioning at all Mach numbers. Numerical results confirm the expectations from the numerical analysis. Representative test cases include flows with previously troublesome embedded high-condition-number regions.

Couple of the Variational Iteration Method and Fractional-Order Legendre Functions Method for Fractional Differential Equations

PubMed Central

Song, Junqiang; Leng, Hongze; Lu, Fengshun

2014-01-01

We present a new numerical method to get the approximate solutions of fractional differential equations. A new operational matrix of integration for fractional-order Legendre functions (FLFs) is first derived. Then a modified variational iteration formula which can avoid “noise terms” is constructed. Finally a numerical method based on variational iteration method (VIM) and FLFs is developed for fractional differential equations (FDEs). Block-pulse functions (BPFs) are used to calculate the FLFs coefficient matrices of the nonlinear terms. Five examples are discussed to demonstrate the validity and applicability of the technique. PMID:24511303

Fisher's method of scoring in statistical image reconstruction: comparison of Jacobi and Gauss-Seidel iterative schemes.

PubMed

Hudson, H M; Ma, J; Green, P

1994-01-01

Many algorithms for medical image reconstruction adopt versions of the expectation-maximization (EM) algorithm. In this approach, parameter estimates are obtained which maximize a complete data likelihood or penalized likelihood, in each iteration. Implicitly (and sometimes explicitly) penalized algorithms require smoothing of the current reconstruction in the image domain as part of their iteration scheme. In this paper, we discuss alternatives to EM which adapt Fisher's method of scoring (FS) and other methods for direct maximization of the incomplete data likelihood. Jacobi and Gauss-Seidel methods for non-linear optimization provide efficient algorithms applying FS in tomography. One approach uses smoothed projection data in its iterations. We investigate the convergence of Jacobi and Gauss-Seidel algorithms with clinical tomographic projection data.

Validation and application of auxiliary density perturbation theory and non-iterative approximation to coupled-perturbed Kohn-Sham approach for calculation of dipole-quadrupole polarizability

NASA Astrophysics Data System (ADS)

Shedge, Sapana V.; Pal, Sourav; Köster, Andreas M.

2011-07-01

Recently, two non-iterative approaches have been proposed to calculate response properties within density functional theory (DFT). These approaches are auxiliary density perturbation theory (ADPT) and the non-iterative approach to the coupled-perturbed Kohn-Sham (NIA-CPKS) method. Though both methods are non-iterative, they use different techniques to obtain the perturbed Kohn-Sham matrix. In this Letter, for the first time, both of these two independent methods have been used for the calculation of dipole-quadrupole polarizabilities. To validate these methods, three tetrahedral molecules viz., P4,CH4 and adamantane (C10H16) have been used as examples. The comparison with MP2 and CCSD proves the reliability of the methodology.

On the convergence of an iterative formulation of the electromagnetic scattering from an infinite grating of thin wires

NASA Technical Reports Server (NTRS)

Brand, J. C.

1985-01-01

Contraction theory is applied to an iterative formulation of electromagnetic scattering from periodic structures and a computational method for insuring convergence is developed. A short history of spectral (or k-space) formulation is presented with an emphasis on application to periodic surfaces. The mathematical background for formulating an iterative equation is covered using straightforward single variable examples including an extension to vector spaces. To insure a convergent solution of the iterative equation, a process called the contraction corrector method is developed. Convergence properties of previously presented iterative solutions to one-dimensional problems are examined utilizing contraction theory and the general conditions for achieving a convergent solution are explored. The contraction corrector method is then applied to several scattering problems including an infinite grating of thin wires with the solution data compared to previous works.

A Generalized Sampling and Preconditioning Scheme for Sparse Approximation of Polynomial Chaos Expansions

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

Jakeman, John D.; Narayan, Akil; Zhou, Tao

We propose an algorithm for recovering sparse orthogonal polynomial expansions via collocation. A standard sampling approach for recovering sparse polynomials uses Monte Carlo sampling, from the density of orthogonality, which results in poor function recovery when the polynomial degree is high. Our proposed approach aims to mitigate this limitation by sampling with respect to the weighted equilibrium measure of the parametric domain and subsequently solves a preconditionedmore » $$\\ell^1$$-minimization problem, where the weights of the diagonal preconditioning matrix are given by evaluations of the Christoffel function. Our algorithm can be applied to a wide class of orthogonal polynomial families on bounded and unbounded domains, including all classical families. We present theoretical analysis to motivate the algorithm and numerical results that show our method is superior to standard Monte Carlo methods in many situations of interest. In conclusion, numerical examples are also provided to demonstrate that our proposed algorithm leads to comparable or improved accuracy even when compared with Legendre- and Hermite-specific algorithms.« less

A Generalized Sampling and Preconditioning Scheme for Sparse Approximation of Polynomial Chaos Expansions

DOE PAGES

Jakeman, John D.; Narayan, Akil; Zhou, Tao

2017-06-22

We propose an algorithm for recovering sparse orthogonal polynomial expansions via collocation. A standard sampling approach for recovering sparse polynomials uses Monte Carlo sampling, from the density of orthogonality, which results in poor function recovery when the polynomial degree is high. Our proposed approach aims to mitigate this limitation by sampling with respect to the weighted equilibrium measure of the parametric domain and subsequently solves a preconditionedmore » $$\\ell^1$$-minimization problem, where the weights of the diagonal preconditioning matrix are given by evaluations of the Christoffel function. Our algorithm can be applied to a wide class of orthogonal polynomial families on bounded and unbounded domains, including all classical families. We present theoretical analysis to motivate the algorithm and numerical results that show our method is superior to standard Monte Carlo methods in many situations of interest. In conclusion, numerical examples are also provided to demonstrate that our proposed algorithm leads to comparable or improved accuracy even when compared with Legendre- and Hermite-specific algorithms.« less

Improving multi-objective reservoir operation optimization with sensitivity-informed dimension reduction

NASA Astrophysics Data System (ADS)

Chu, J.; Zhang, C.; Fu, G.; Li, Y.; Zhou, H.

2015-08-01

This study investigates the effectiveness of a sensitivity-informed method for multi-objective operation of reservoir systems, which uses global sensitivity analysis as a screening tool to reduce computational demands. Sobol's method is used to screen insensitive decision variables and guide the formulation of the optimization problems with a significantly reduced number of decision variables. This sensitivity-informed method dramatically reduces the computational demands required for attaining high-quality approximations of optimal trade-off relationships between conflicting design objectives. The search results obtained from the reduced complexity multi-objective reservoir operation problems are then used to pre-condition the full search of the original optimization problem. In two case studies, the Dahuofang reservoir and the inter-basin multi-reservoir system in Liaoning province, China, sensitivity analysis results show that reservoir performance is strongly controlled by a small proportion of decision variables. Sensitivity-informed dimension reduction and pre-conditioning are evaluated in their ability to improve the efficiency and effectiveness of multi-objective evolutionary optimization. Overall, this study illustrates the efficiency and effectiveness of the sensitivity-informed method and the use of global sensitivity analysis to inform dimension reduction of optimization problems when solving complex multi-objective reservoir operation problems.

Stabilization of the SIESTA MHD Equilibrium Code Using Rapid Cholesky Factorization

NASA Astrophysics Data System (ADS)

Hirshman, S. P.; D'Azevedo, E. A.; Seal, S. K.

2016-10-01

The SIESTA MHD equilibrium code solves the discretized nonlinear MHD force F ≡ J X B - ∇p for a 3D plasma which may contain islands and stochastic regions. At each nonlinear evolution step, it solves a set of linearized MHD equations which can be written r ≡ Ax - b = 0, where A is the linearized MHD Hessian matrix. When the solution norm | x| is small enough, the nonlinear force norm will be close to the linearized force norm | r| 0 obtained using preconditioned GMRES. In many cases, this procedure works well and leads to a vanishing nonlinear residual (equilibrium) after several iterations in SIESTA. In some cases, however, | x|>1 results and the SIESTA code has to be restarted to obtain nonlinear convergence. In order to make SIESTA more robust and avoid such restarts, we have implemented a new rapid QR factorization of the Hessian which allows us to rapidly and accurately solve the least-squares problem AT r = 0, subject to the condition | x|<1. This avoids large contributions to the nonlinear force terms and in general makes the convergence sequence of SIESTA much more stable. The innovative rapid QR method is based on a pairwise row factorization of the tri-diagonal Hessian. It provides a complete Cholesky factorization while preserving the memory allocation of A. This work was supported by the U.S. D.O.E. contract DE-AC05-00OR22725.

The epidemiology of bovine respiratory disease: What is the evidence for preventive measures?

PubMed Central

Taylor, Jared D.; Fulton, Robert W.; Lehenbauer, Terry W.; Step, Douglas L.; Confer, Anthony W.

2010-01-01

Bovine respiratory disease (BRD) is the most common and costly disease of beef cattle in North America. Despite extensive research, industry practices are often more informed by dogma than by fact. Frequently advocated interventions, including vaccination, various processing procedures, and nutritional manipulation, have limited impact on morbidity and mortality. Evidence for use of oral antimicrobials, either in feed or water, appears to be equivocal. In contrast, preconditioning and metaphylaxis have significant scientific evidence of efficacy, with weaning prior to sale potentially being the most important component of preconditioning. The inability to reach more definitive conclusions in preventing BRD may be attributable to difficulties in investigating the disease. Study challenges include potential for extensive confounding, tremendous variability, the multi-factorial nature of the disease, and inadequate methods for diagnosis. PMID:21358927

Kelch-like ECH-associated Protein 1-dependent Nuclear Factor-E2-related Factor 2 Activation in Relation to Antioxidation Induced by Sevoflurane Preconditioning.

PubMed

Cai, Min; Tong, Li; Dong, Beibei; Hou, Wugang; Shi, Likai; Dong, Hailong

2017-03-01

The authors have reported that antioxidative effects play a crucial role in the volatile anesthetic-induced neuroprotection. Accumulated evidence shows that endogenous antioxidation could be up-regulated by nuclear factor-E2-related factor 2 through multiple pathways. However, whether nuclear factor-E2-related factor 2 activation is modulated by sevoflurane preconditioning and, if so, what is the signaling cascade underlying upstream of this activation are still unknown. Sevoflurane preconditioning in mice was performed with sevoflurane (2.5%) 1 h per day for five consecutive days. Focal cerebral ischemia/reperfusion injury was induced by middle cerebral artery occlusion. Expression of nuclear factor-E2-related factor 2, kelch-like ECH-associated protein 1, manganese superoxide dismutase, thioredoxin-1, and nicotinamide adenine dinucleotide phosphate quinolone oxidoreductase-1 was detected (n = 6). The antioxidant activities and oxidative product expression were also examined. To determine the role of kelch-like ECH-associated protein 1 inhibition-dependent nuclear factor-E2-related factor 2 activation in sevoflurane preconditioning-induced neuroprotection, the kelch-like ECH-associated protein 1-nuclear factor-E2-related factor 2 signal was modulated by nuclear factor-E2-related factor 2 knockout, kelch-like ECH-associated protein 1 overexpression lentivirus, and kelch-like ECH-associated protein 1 deficiency small interfering RNA (n = 8). The infarct volume, neurologic scores, and cellular apoptosis were assessed. Sevoflurane preconditioning elicited neuroprotection and increased nuclear factor-E2-related factor 2 nuclear translocation, which in turn up-regulated endogenous antioxidation and reduced oxidative injury. Sevoflurane preconditioning reduced kelch-like ECH-associated protein 1 expression. Nuclear factor-E2-related factor 2 ablation abolished neuroprotection and reversed sevoflurane preconditioning by mediating the up-regulation of antioxidants. Kelch-like ECH-associated protein 1 overexpression reversed nuclear factor-E2-related factor 2 up-regulation and abolished the neuroprotection induced by sevoflurane preconditioning. Kelch-like ECH-associated protein 1 small interfering RNA administration improved nuclear factor-E2-related factor 2 expression and the outcome of mice subjected to ischemia/reperfusion injury. Kelch-like ECH-associated protein 1 down-regulation-dependent nuclear factor-E2-related factor 2 activation underlies the ability of sevoflurane preconditioning to activate the endogenous antioxidant response, which elicits its neuroprotection.

Involvement of SIRT1 in hypoxic down-regulation of c-Myc and β-catenin and hypoxic preconditioning effect of polyphenols

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

Hong, Kyung-Soo; Research Center for Ischemic Tissue regeneration, Pusan National University School of Medicine, Yangsan; Park, Jun-Ik

2012-03-01

SIRT1 has been found to function as a Class III deacetylase that affects the acetylation status of histones and other important cellular nonhistone proteins involved in various cellular pathways including stress responses and apoptosis. In this study, we investigated the role of SIRT1 signaling in the hypoxic down-regulations of c-Myc and β-catenin and hypoxic preconditioning effect of the red wine polyphenols such as piceatannol, myricetin, quercetin and resveratrol. We found that the expression of SIRT1 was significantly increased in hypoxia-exposed or hypoxic preconditioned HepG2 cells, which was closely associated with the up-regulation of HIF-1α and down-regulation of c-Myc and β-cateninmore » expression via deacetylation of these proteins. In addition, blockade of SIRT1 activation using siRNA or amurensin G, a new potent SIRT1 inhibitor, abolished hypoxia-induced HIF-1α expression but increased c-Myc and β-catenin expression. SIRT1 was also found to stabilize HIF-1α protein and destabilize c-Myc, β-catenin and PHD2 under hypoxia. We also found that myricetin, quercetin, piceatannol and resveratrol up-regulated HIF-1α and down-regulated c-Myc, PHD2 and β-catenin expressions via SIRT1 activation, in a manner that mimics hypoxic preconditioning. This study provides new insights of the molecular mechanisms of hypoxic preconditioning and suggests that polyphenolic SIRT1 activators could be used to mimic hypoxic/ischemic preconditioning. -- Graphical abstract: Polyphenols mimicked hypoxic preconditioning by up-regulating HIF-1α and SIRT1 and down-regulating c-Myc, PHD2, and β-catenin. HepG2 cells were pretreated with the indicated doses of myricetin (MYR; A), quercetin (QUR; B), or piceatannol (PIC; C) for 4 h and then exposed to hypoxia for 4 h. Levels of HIF-1α, SIRT1, c-Myc, β-catenin, and PHD2 were determined by western blot analysis. The data are representative of three individual experiments. Highlights: ► SIRT1 expression is increased in hypoxia-exposed or hypoxic preconditioned cells. ► SIRT1 deacetylates c-Myc and β-catenin ► HIF-1α is up-regulated by down-regulation of c-Myc and β-catenin expression. ► Polyphenolic SIRT1 activators mimics hypoxic preconditioning.« less

Hypoxia preconditioning of mesenchymal stromal cells enhances PC3 cell lymphatic metastasis accompanied by VEGFR-3/CCR7 activation.

PubMed

Huang, Xin; Su, Kunkai; Zhou, Limin; Shen, Guofang; Dong, Qi; Lou, Yijia; Zheng, Shu

2013-12-01

Mesenchymal stromal cells (MSCs) in bone marrow may enhance tumor metastases through the secretion of chemokines. MSCs have been reported to home toward the hypoxic tumor microenvironment in vivo. In this study, we investigated prostate cancer PC3 cell behavior under the influence of hypoxia preconditioned MSCs and explored the related mechanism of prostate cancer lymphatic metastases in mice. Transwell assays revealed that VEGF-C receptor, VEGFR-3, as well as chemokine CCL21 receptor, CC chemokine receptor 7 (CCR7), were responsible for the migration of PC3 cells toward hypoxia preconditioned MSCs. Knock-in Ccr7 in PC3 cells also improved cell migration in vitro. Furthermore, when PC3 cells were labeled using the hrGfp-lentiviral vector, and were combined with hypoxia preconditioned MSCs for xenografting, it resulted in an enhancement of lymph node metastases accompanied by up-regulation of VEGFR-3 and CCR7 in primary tumors. Both PI3K/Akt/IκBα and JAK2/STAT3 signaling pathways were activated in xenografts in the presence of hypoxia-preconditioned MSCs. Unexpectedly, the p-VEGFR-2/VEGFR-2 ratio was attenuated accompanied by decreased JAK1 expression, indicating a switching-off of potential vascular signal within xenografts in the presence of hypoxia-preconditioned MSCs. Unlike results from other studies, VEGF-C maintained a stable expression in both conditions, which indicated that hypoxia preconditioning of MSCs did not influence VEGF-C secretion. Our results provide the new insights into the functional molecular events and signalings influencing prostate tumor metastases, suggesting a hopeful diagnosis and treatment in new approaches. © 2013 Wiley Periodicals, Inc.

The involvement of protein kinase C-ε in isoflurane induced preconditioning of human embryonic stem cell--derived Nkx2.5(+) cardiac progenitor cells.

PubMed

Song, In-Ae; Oh, Ah-Young; Kim, Jin-Hee; Choi, Young-Min; Jeon, Young-Tae; Ryu, Jung-Hee; Hwang, Jung-Won

2016-02-20

Anesthetic preconditioning can improve survival of cardiac progenitor cells exposed to oxidative stress. We investigated the role of protein kinase C and isoform protein kinase C-ε in isoflurane-induced preconditioning of cardiac progenitor cells exposed to oxidative stress. Cardiac progenitor cells were obtained from undifferentiated human embryonic stem cells. Immunostaining with anti-Nkx2.5 was used to confirm the differentiated cardiac progenitor cells. Oxidative stress was induced by H2O2 and FeSO4. For anesthetic preconditioning, cardiac progenitor cells were exposed to 0.25, 0.5, and 1.0 mM of isoflurane. PMA and chelerythrine were used for protein kinase C activation and inhibition, while εψRACK and εV1-2 were used for protein kinase C -ε activation and inhibition, respectively. Isoflurane-preconditioning decreased the death rate of Cardiac progenitor cells exposed to oxidative stress (death rates isoflurane 0.5 mM 12.7 ± 9.3%, 1.0 mM 12.0 ± 7.7% vs. control 31.4 ± 10.2%). Inhibitors of both protein kinase C and protein kinase C -ε abolished the preconditioning effect of isoflurane 0.5 mM (death rates 27.6 ± 13.5% and 25.9 ± 8.7% respectively), and activators of both protein kinase C and protein kinase C - ε had protective effects from oxidative stress (death rates 16.0 ± 3.2% and 10.6 ± 3.8% respectively). Both PKC and PKC-ε are involved in isoflurane-induced preconditioning of human embryonic stem cells -derived Nkx2.5(+) Cardiac progenitor cells under oxidative stress.

Effects and interaction, of cariporide and preconditioning on cardiac arrhythmias and infarction in rat in vivo

PubMed Central

Aye, Nu Nu; Komori, Sadayoshi; Hashimoto, Keitaro

1999-01-01

Although Na+-H+ exchange (NHE) inhibitors are reported to protect the myocardium against ischaemic injury, NHE activation has also been proposed as a potential mechanism of ischaemic preconditioning-induced protection. This study was performed to test any modifiable effect of cariporide, an NHE inhibitor, on cardioprotective effects of preconditioning.Anaesthetized rats were subjected to 30 min of coronary artery occlusion and 150 min of reperfusion. The preconditioning (PC) was induced by 3 min of ischaemia and 10 min of reperfusion (1PC) or three episodes of 3 min ischaemia and 5 min reperfusion (3PC). Cariporide (0.3 mg kg−1) an NHE inhibitor, was administered 30 min (cari(30)) or 45 min (cari(45)) before coronary ligation (n=8–11 for each group).Ventricular arrhythmias during 30 min ischaemia and infarct size (measured by triphenyltetrazolium (TTC) and expressed as a per cent area at risk (%AAR)) were determined. Cari(30) reduced ventricular fibrillation (VF) incidence and infarct size (from 45 to 0% and 34±4 to 9±2%; each P<0.05), whereas cari(45) did not. Likewise, 3PC reduced these variables (to 0% and 10±2%; P<0.05 in each case) whereas 1PC did not. Moreover, subthreshold preconditioning (1PC) and cariporide (cari(45)), when combined, reduced VF incidence and infarct size (to 0% and 15+3%; each P<0.05).In conclusion, changes in NHE activity do not seem to be responsible for the cardioprotective action of ischaemic preconditioning. Protective effects of NHE inhibition and subthreshold preconditioning appear to act additively. PMID:10433514

Cardioprotection of ischaemic preconditioning is associated with inhibition of translocation of MLKL within the plasma membrane.

PubMed

Szobi, Adrián; Farkašová-Ledvényiová, Veronika; Lichý, Martin; Muráriková, Martina; Čarnická, Slávka; Ravingerová, Tatiana; Adameová, Adriana

2018-06-19

Necroptosis, a form of cell loss involving the RIP1-RIP3-MLKL axis, has been identified in cardiac pathologies while its inhibition is cardioprotective. We investigated whether the improvement of heart function because of ischaemic preconditioning is associated with mitigation of necroptotic signaling, and these effects were compared with a pharmacological antinecroptotic approach targeting RIP1. Langendorff-perfused rat hearts were subjected to ischaemic preconditioning with or without a RIP1 inhibitor (Nec-1s). Necroptotic signaling and the assessment of oxidative damage and a putative involvement of CaMKII in this process were analysed in whole tissue and subcellular fractions. Ischaemic preconditioning, Nec-1s and their combination improved postischaemic heart function recovery and reduced infarct size to a similar degree what was in line with the prevention of MLKL oligomerization and translocation to the membrane. On the other hand, membrane peroxidation and apoptosis were unchanged by either approach. Ischaemic preconditioning failed to ameliorate ischaemia-reperfusion-induced increase in RIP1 and RIP3 while pSer229-RIP3 levels were reduced only by Nec-1s. In spite of the additive phosphorylation of CaMKII and PLN because of ditherapy, the postischaemic contractile force and relaxation was comparably improved in all the intervention groups while antiarrhythmic effects were observed in the ischaemic preconditioning group only. Necroptosis inhibition seems to be involved in cardioprotection of ischaemic preconditioning and is comparable but not intensified by an anti-RIP1 agent. Changes in oxidative stress nor CaMKII signaling are unlikely to explain the beneficial effects. © 2018 Comenius University in Bratislava, Faculty of Pharmacy. Journal of Cellular and Molecular Medicine published by John Wiley & Sons Ltd and Foundation for Cellular and Molecular Medicine.

Multiple Revolution Solutions for the Perturbed Lambert Problem using the Method of Particular Solutions and Picard Iteration

NASA Astrophysics Data System (ADS)

Woollands, Robyn M.; Read, Julie L.; Probe, Austin B.; Junkins, John L.

2017-12-01

We present a new method for solving the multiple revolution perturbed Lambert problem using the method of particular solutions and modified Chebyshev-Picard iteration. The method of particular solutions differs from the well-known Newton-shooting method in that integration of the state transition matrix (36 additional differential equations) is not required, and instead it makes use of a reference trajectory and a set of n particular solutions. Any numerical integrator can be used for solving two-point boundary problems with the method of particular solutions, however we show that using modified Chebyshev-Picard iteration affords an avenue for increased efficiency that is not available with other step-by-step integrators. We take advantage of the path approximation nature of modified Chebyshev-Picard iteration (nodes iteratively converge to fixed points in space) and utilize a variable fidelity force model for propagating the reference trajectory. Remarkably, we demonstrate that computing the particular solutions with only low fidelity function evaluations greatly increases the efficiency of the algorithm while maintaining machine precision accuracy. Our study reveals that solving the perturbed Lambert's problem using the method of particular solutions with modified Chebyshev-Picard iteration is about an order of magnitude faster compared with the classical shooting method and a tenth-twelfth order Runge-Kutta integrator. It is well known that the solution to Lambert's problem over multiple revolutions is not unique and to ensure that all possible solutions are considered we make use of a reliable preexisting Keplerian Lambert solver to warm start our perturbed algorithm.

Fast projection/backprojection and incremental methods applied to synchrotron light tomographic reconstruction.

PubMed

de Lima, Camila; Salomão Helou, Elias

2018-01-01

Iterative methods for tomographic image reconstruction have the computational cost of each iteration dominated by the computation of the (back)projection operator, which take roughly O(N 3 ) floating point operations (flops) for N × N pixels images. Furthermore, classical iterative algorithms may take too many iterations in order to achieve acceptable images, thereby making the use of these techniques unpractical for high-resolution images. Techniques have been developed in the literature in order to reduce the computational cost of the (back)projection operator to O(N 2 logN) flops. Also, incremental algorithms have been devised that reduce by an order of magnitude the number of iterations required to achieve acceptable images. The present paper introduces an incremental algorithm with a cost of O(N 2 logN) flops per iteration and applies it to the reconstruction of very large tomographic images obtained from synchrotron light illuminated data.

MO-DE-207A-07: Filtered Iterative Reconstruction (FIR) Via Proximal Forward-Backward Splitting: A Synergy of Analytical and Iterative Reconstruction Method for CT

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

Gao, H

Purpose: This work is to develop a general framework, namely filtered iterative reconstruction (FIR) method, to incorporate analytical reconstruction (AR) method into iterative reconstruction (IR) method, for enhanced CT image quality. Methods: FIR is formulated as a combination of filtered data fidelity and sparsity regularization, and then solved by proximal forward-backward splitting (PFBS) algorithm. As a result, the image reconstruction decouples data fidelity and image regularization with a two-step iterative scheme, during which an AR-projection step updates the filtered data fidelity term, while a denoising solver updates the sparsity regularization term. During the AR-projection step, the image is projected tomore » the data domain to form the data residual, and then reconstructed by certain AR to a residual image which is in turn weighted together with previous image iterate to form next image iterate. Since the eigenvalues of AR-projection operator are close to the unity, PFBS based FIR has a fast convergence. Results: The proposed FIR method is validated in the setting of circular cone-beam CT with AR being FDK and total-variation sparsity regularization, and has improved image quality from both AR and IR. For example, AIR has improved visual assessment and quantitative measurement in terms of both contrast and resolution, and reduced axial and half-fan artifacts. Conclusion: FIR is proposed to incorporate AR into IR, with an efficient image reconstruction algorithm based on PFBS. The CBCT results suggest that FIR synergizes AR and IR with improved image quality and reduced axial and half-fan artifacts. The authors was partially supported by the NSFC (#11405105), the 973 Program (#2015CB856000), and the Shanghai Pujiang Talent Program (#14PJ1404500).« less

Accurate Solution of Multi-Region Continuum Biomolecule Electrostatic Problems Using the Linearized Poisson-Boltzmann Equation with Curved Boundary Elements

PubMed Central

Altman, Michael D.; Bardhan, Jaydeep P.; White, Jacob K.; Tidor, Bruce

2009-01-01

We present a boundary-element method (BEM) implementation for accurately solving problems in biomolecular electrostatics using the linearized Poisson–Boltzmann equation. Motivating this implementation is the desire to create a solver capable of precisely describing the geometries and topologies prevalent in continuum models of biological molecules. This implementation is enabled by the synthesis of four technologies developed or implemented specifically for this work. First, molecular and accessible surfaces used to describe dielectric and ion-exclusion boundaries were discretized with curved boundary elements that faithfully reproduce molecular geometries. Second, we avoided explicitly forming the dense BEM matrices and instead solved the linear systems with a preconditioned iterative method (GMRES), using a matrix compression algorithm (FFTSVD) to accelerate matrix-vector multiplication. Third, robust numerical integration methods were employed to accurately evaluate singular and near-singular integrals over the curved boundary elements. Finally, we present a general boundary-integral approach capable of modeling an arbitrary number of embedded homogeneous dielectric regions with differing dielectric constants, possible salt treatment, and point charges. A comparison of the presented BEM implementation and standard finite-difference techniques demonstrates that for certain classes of electrostatic calculations, such as determining absolute electrostatic solvation and rigid-binding free energies, the improved convergence properties of the BEM approach can have a significant impact on computed energetics. We also demonstrate that the improved accuracy offered by the curved-element BEM is important when more sophisticated techniques, such as non-rigid-binding models, are used to compute the relative electrostatic effects of molecular modifications. In addition, we show that electrostatic calculations requiring multiple solves using the same molecular geometry, such as charge optimization or component analysis, can be computed to high accuracy using the presented BEM approach, in compute times comparable to traditional finite-difference methods. PMID:18567005

Leg ischaemia before circulatory arrest alters brain leucocyte count and respiratory chain redox state.

PubMed

Yannopoulos, Fredrik S; Arvola, Oiva; Haapanen, Henri; Herajärvi, Johanna; Miinalainen, Ilkka; Jensen, Hanna; Kiviluoma, Kai; Juvonen, Tatu

2014-03-01

Remote ischaemic preconditioning and its neuroprotective abilities are currently under investigation and the method has shown significant effects in several small and large animal studies. In our previous studies, leucocyte filtration during cardiopulmonary bypass reduced cerebrocortical adherent leucocyte count and mitigated cerebral damage after hypothermic circulatory arrest (HCA) in piglets. This study aimed to obtain and assess direct visual data of leucocyte behaviour in cerebral vessels after hypothermic circulatory arrest following remote ischaemic preconditioning. Twelve native stock piglets were randomized into a remote ischaemic preconditioning group (n = 6) and a control group (n = 6). The intervention group underwent hind-leg ischaemia, whereas the control group received a sham-treatment before a 60-min period of hypothermic circulatory arrest. An intravital microscope was used to obtain measurements from the cerebrocortical vessel in vivo. It included three sets of filters: a violet filter to visualize microvascular perfusion and vessel diameter, a green filter for visualization of rhodamine-labelled leucocytes and an ultraviolet filter for reduced nicotinamide adenine dinucleotide (NADH) analysis. The final magnification on the microscope was 400. After the experiment, cerebral and cerebellar biopsies were collected and analysed with transmission electron microscope by a blinded analyst. In the transmission electron microscope analysis, the entire intervention group had normal, unaffected rough endoplasmic reticulum's in their cerebellar tissue, whereas the control group had a mean score of 1.06 (standard deviation 0.41) (P = 0.026). The measured amount of adherent leucocytes was lower in the remote ischaemic preconditioning group. The difference was statistically significant at 5, 15 and 45 min after circulatory arrest. Statistically significant differences were seen also in the recovery phase at 90 and 120 min after reperfusion. Nicotinamide adenine dinucleotide autofluorescence had statistically significant differences at 10 min after cooling and at 120 and 180 min after hypothermic circulatory arrest. Remote ischaemic preconditioning seems to provide better mitochondrial respiratory chain function as indicated by the higher NADH content. It simultaneously provides a reduction of adherent leucocytes in cerebral vessels after hypothermic circulatory arrest. Additionally, it might provide some degree of cellular organ preservation as implied by the electron microscopy results.

Effect of non-invasive remote ischemic preconditioning on intra-renal perfusion in volunteers.

PubMed

Robert, René; Vinet, Mathieu; Jamet, Angéline; Coudroy, Rémi

2017-06-01

Remote ischemic preconditioning may attenuate renal injury and protect the kidney during subsequent inflammatory or ischemic stress. However, the mechanism of such a protection is not well understood. The aim of this study was to investigate the impact of remote ischemic preconditioning on renal resistivity index (RRI) in nine healthy volunteers. In six volunteers, four cycles of 4-min inflation of a blood pressure cuff were applied to one upper arm, followed by 4-min reperfusion with the cuff deflated. RRI was determined using Doppler echography during each cuff deflated period. Measures were also performed in three volunteers without preconditioning. The median value of RRI significantly decreased progressively from 0.59 [0.53-0.62] before the remote conditioning (baseline) to 0.49 [0.46-0.53] at the end of the experiment (p < 0.001) whereas there was no change in controls. In this study, for the first time, we have clearly shown in a small group of subjects that remote ischemic preconditioning can induce a significantly decrease in RRI through increased intra-renal perfusion.

AdVEGF-All6A+ Preconditioning of Murine Ischemic Skin Flaps Is Comparable to Surgical Delay

PubMed Central

Gersch, Robert P.; Fourman, Mitchell S.; Phillips, Brett T.; Nasser, Ahmed; McClain, Steve A.; Khan, Sami U.; Dagum, Alexander B.

2015-01-01

Background: Surgical flap delay is commonly used in preconditioning reconstructive flaps to prevent necrosis. However, staged procedures are not ideal. Pharmacologic up-regulation of angiogenic and arteriogenic factors before flap elevation poses a nonsurgical approach to improve flap survival. Methods: Male Sprague Dawley rats were divided into control (n = 16), surgical delay (Delay), AdNull, AdEgr-1, and AdVEGF (n ≥ 9/group) groups. Delay rats had a 9 cm × 3 cm cranial based pedicle skin flap incised 10 days prior to elevation. Adenoviral groups received 28 intradermal injections (109 pu/animal total) throughout the distal two thirds of the flap 1 week prior to elevation. At postoperative day (POD) 0 flaps were elevated and silicone sheeting was placed between flap and wound bed. Perfusion analysis in arbitrary perfusion units of the ischemic middle third of the flap using laser Doppler imaging was conducted preoperatively and on POD 0, 3, and 7. Clinical and histopathologic assessments of the skin flaps were performed on POD 7. Results: AdVEGF (50.8 ± 10.9 APU) and AdEgr-1 (39.3 ± 10.6 APU) perfusion levels were significantly higher than controls (16.5 ± 4.2 APU) on POD 7. Delay models were equivalent to controls (25.9 ± 6.8 APU). AdVEGF and Delay animals showed significantly more viable surface area on POD 7 (14.4 ± 1.3 cm2, P < 0.01 and 12.4 ± 1.2 cm2, P < 0.05, respectively) compared with Controls (8.7 ± 0.7 cm2). Conclusions: AdVEGF preconditioning resulted in flap survival comparable to surgical delay. Adenoviral preconditioning maintained perfusion levels postoperatively while surgical delay did not. PMID:26495207

Females transplanted with ovaries subjected to hypoxic preconditioning show impair of ovarian function

PubMed Central

2014-01-01

Background Cryopreservation of the ovarian tissue has shown promising results. However, there remain controversial issues such as the short half-life of grafts. In this aspect, there are some evidences that preconditioning the ovarian tissue before transplantation is beneficial. Objective To determine the effect of hypoxic preconditioning in vitro on ovarian tissue prior to transplantation. Methods Eighteen female adult Wistar rats, were sorted into three experimental groups. Ovaries were maintained in DMEM low glucose serum free at 37°C with 5% CO2, at atmospheric oxigen concentration (normoxia) or 1% O2 (hypoxia) for 16 hours. Oxigen concentration was determined by injection of nitrogen in the incubator. Animals submitted to ovarian transplantation immediately after oophorectomy were the Control Group (C). After this, the ovaries were implanted in the retroperitoneum with nonabsorbable suture and animals evaluated for thirty days after transplantation. Beginning on postoperative (PO) day 11, a daily collection of vaginal smear was carried out. Analyses comprised morphological, morphometric (counting ovarian follicles and corpora lutea) and immunohistochemistry for cleaved caspase-3 (apoptosis). Results In normoxia and control groups all animals recovered their estrous cycles, while in the hypoxia group, two animals did not ovulate but, among those which did, resumption took longer than in the other groups (p < 0.05). The number of ovarian follicles and corpora lutea decreased significantly in the hypoxia group when compared to the other two groups (p < 0.001) and apoptosis was increased in the few ovarian follicles which remained viable (p < 0.001). Conclusion The hypoxic preconditioning in vitro was not beneficial to the graft and worsened their viability, compromising its functionality or delaying the return of this. PMID:24655551

Teko: A block preconditioning capability with concrete example applications in Navier--Stokes and MHD

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

Cyr, Eric C.; Shadid, John N.; Tuminaro, Raymond S.

This study describes the design of Teko, an object-oriented C++ library for implementing advanced block preconditioners. Mathematical design criteria that elucidate the needs of block preconditioning libraries and techniques are explained and shown to motivate the structure of Teko. For instance, a principal design choice was for Teko to strongly reflect the mathematical statement of the preconditioners to reduce development burden and permit focus on the numerics. Additional mechanisms are explained that provide a pathway to developing an optimized production capable block preconditioning capability with Teko. Finally, Teko is demonstrated on fluid flow and magnetohydrodynamics applications. In addition to highlightingmore » the features of the Teko library, these new results illustrate the effectiveness of recent preconditioning developments applied to advanced discretization approaches.« less

Teko: A block preconditioning capability with concrete example applications in Navier--Stokes and MHD

DOE PAGES

Cyr, Eric C.; Shadid, John N.; Tuminaro, Raymond S.

2016-10-27

This study describes the design of Teko, an object-oriented C++ library for implementing advanced block preconditioners. Mathematical design criteria that elucidate the needs of block preconditioning libraries and techniques are explained and shown to motivate the structure of Teko. For instance, a principal design choice was for Teko to strongly reflect the mathematical statement of the preconditioners to reduce development burden and permit focus on the numerics. Additional mechanisms are explained that provide a pathway to developing an optimized production capable block preconditioning capability with Teko. Finally, Teko is demonstrated on fluid flow and magnetohydrodynamics applications. In addition to highlightingmore » the features of the Teko library, these new results illustrate the effectiveness of recent preconditioning developments applied to advanced discretization approaches.« less

Accelerating the weighted histogram analysis method by direct inversion in the iterative subspace.

PubMed

Zhang, Cheng; Lai, Chun-Liang; Pettitt, B Montgomery

The weighted histogram analysis method (WHAM) for free energy calculations is a valuable tool to produce free energy differences with the minimal errors. Given multiple simulations, WHAM obtains from the distribution overlaps the optimal statistical estimator of the density of states, from which the free energy differences can be computed. The WHAM equations are often solved by an iterative procedure. In this work, we use a well-known linear algebra algorithm which allows for more rapid convergence to the solution. We find that the computational complexity of the iterative solution to WHAM and the closely-related multiple Bennett acceptance ratio (MBAR) method can be improved by using the method of direct inversion in the iterative subspace. We give examples from a lattice model, a simple liquid and an aqueous protein solution.

Improved Savitzky-Golay-method-based fluorescence subtraction algorithm for rapid recovery of Raman spectra.

PubMed

Chen, Kun; Zhang, Hongyuan; Wei, Haoyun; Li, Yan

2014-08-20

In this paper, we propose an improved subtraction algorithm for rapid recovery of Raman spectra that can substantially reduce the computation time. This algorithm is based on an improved Savitzky-Golay (SG) iterative smoothing method, which involves two key novel approaches: (a) the use of the Gauss-Seidel method and (b) the introduction of a relaxation factor into the iterative procedure. By applying a novel successive relaxation (SG-SR) iterative method to the relaxation factor, additional improvement in the convergence speed over the standard Savitzky-Golay procedure is realized. The proposed improved algorithm (the RIA-SG-SR algorithm), which uses SG-SR-based iteration instead of Savitzky-Golay iteration, has been optimized and validated with a mathematically simulated Raman spectrum, as well as experimentally measured Raman spectra from non-biological and biological samples. The method results in a significant reduction in computing cost while yielding consistent rejection of fluorescence and noise for spectra with low signal-to-fluorescence ratios and varied baselines. In the simulation, RIA-SG-SR achieved 1 order of magnitude improvement in iteration number and 2 orders of magnitude improvement in computation time compared with the range-independent background-subtraction algorithm (RIA). Furthermore the computation time of the experimentally measured raw Raman spectrum processing from skin tissue decreased from 6.72 to 0.094 s. In general, the processing of the SG-SR method can be conducted within dozens of milliseconds, which can provide a real-time procedure in practical situations.

Multiscale optical simulation settings: challenging applications handled with an iterative ray-tracing FDTD interface method.

PubMed

Leiner, Claude; Nemitz, Wolfgang; Schweitzer, Susanne; Kuna, Ladislav; Wenzl, Franz P; Hartmann, Paul; Satzinger, Valentin; Sommer, Christian

2016-03-20

We show that with an appropriate combination of two optical simulation techniques-classical ray-tracing and the finite difference time domain method-an optical device containing multiple diffractive and refractive optical elements can be accurately simulated in an iterative simulation approach. We compare the simulation results with experimental measurements of the device to discuss the applicability and accuracy of our iterative simulation procedure.

Iterative solution of the inverse Cauchy problem for an elliptic equation by the conjugate gradient method

NASA Astrophysics Data System (ADS)

Vasil'ev, V. I.; Kardashevsky, A. M.; Popov, V. V.; Prokopev, G. A.

2017-10-01

This article presents results of computational experiment carried out using a finite-difference method for solving the inverse Cauchy problem for a two-dimensional elliptic equation. The computational algorithm involves an iterative determination of the missing boundary condition from the override condition using the conjugate gradient method. The results of calculations are carried out on the examples with exact solutions as well as at specifying an additional condition with random errors are presented. Results showed a high efficiency of the iterative method of conjugate gradients for numerical solution

Efficiency trade-offs of steady-state methods using FEM and FDM. [iterative solutions for nonlinear flow equations

NASA Technical Reports Server (NTRS)

Gartling, D. K.; Roache, P. J.

1978-01-01

The efficiency characteristics of finite element and finite difference approximations for the steady-state solution of the Navier-Stokes equations are examined. The finite element method discussed is a standard Galerkin formulation of the incompressible, steady-state Navier-Stokes equations. The finite difference formulation uses simple centered differences that are O(delta x-squared). Operation counts indicate that a rapidly converging Newton-Raphson-Kantorovitch iteration scheme is generally preferable over a Picard method. A split NOS Picard iterative algorithm for the finite difference method was most efficient.

Continuous analog of multiplicative algebraic reconstruction technique for computed tomography

NASA Astrophysics Data System (ADS)

Tateishi, Kiyoko; Yamaguchi, Yusaku; Abou Al-Ola, Omar M.; Kojima, Takeshi; Yoshinaga, Tetsuya

2016-03-01

We propose a hybrid dynamical system as a continuous analog to the block-iterative multiplicative algebraic reconstruction technique (BI-MART), which is a well-known iterative image reconstruction algorithm for computed tomography. The hybrid system is described by a switched nonlinear system with a piecewise smooth vector field or differential equation and, for consistent inverse problems, the convergence of non-negatively constrained solutions to a globally stable equilibrium is guaranteed by the Lyapunov theorem. Namely, we can prove theoretically that a weighted Kullback-Leibler divergence measure can be a common Lyapunov function for the switched system. We show that discretizing the differential equation by using the first-order approximation (Euler's method) based on the geometric multiplicative calculus leads to the same iterative formula of the BI-MART with the scaling parameter as a time-step of numerical discretization. The present paper is the first to reveal that a kind of iterative image reconstruction algorithm is constructed by the discretization of a continuous-time dynamical system for solving tomographic inverse problems. Iterative algorithms with not only the Euler method but also the Runge-Kutta methods of lower-orders applied for discretizing the continuous-time system can be used for image reconstruction. A numerical example showing the characteristics of the discretized iterative methods is presented.

The Möbius domain wall fermion algorithm

NASA Astrophysics Data System (ADS)

Brower, Richard C.; Neff, Harmut; Orginos, Kostas

2017-11-01

We present a review of the properties of generalized domain wall Fermions, based on a (real) Möbius transformation on the Wilson overlap kernel, discussing their algorithmic efficiency, the degree of explicit chiral violations measured by the residual mass (mres) and the Ward-Takahashi identities. The Möbius class interpolates between Shamir's domain wall operator and Boriçi's domain wall implementation of Neuberger's overlap operator without increasing the number of Dirac applications per conjugate gradient iteration. A new scaling parameter (α) reduces chiral violations at finite fifth dimension (Ls) but yields exactly the same overlap action in the limit Ls → ∞. Through the use of 4d Red/Black preconditioning and optimal tuning for the scaling α(Ls) , we show that chiral symmetry violations are typically reduced by an order of magnitude at fixed Ls. We argue that the residual mass for a tuned Möbius algorithm with α = O(1 /Lsγ) for γ < 1 will eventually fall asymptotically as mres = O(1 /Ls1+γ) in the case of a 5D Hamiltonian with out a spectral gap.

Time integration algorithms for the two-dimensional Euler equations on unstructured meshes

NASA Technical Reports Server (NTRS)

Slack, David C.; Whitaker, D. L.; Walters, Robert W.

1994-01-01

Explicit and implicit time integration algorithms for the two-dimensional Euler equations on unstructured grids are presented. Both cell-centered and cell-vertex finite volume upwind schemes utilizing Roe's approximate Riemann solver are developed. For the cell-vertex scheme, a four-stage Runge-Kutta time integration, a fourstage Runge-Kutta time integration with implicit residual averaging, a point Jacobi method, a symmetric point Gauss-Seidel method and two methods utilizing preconditioned sparse matrix solvers are presented. For the cell-centered scheme, a Runge-Kutta scheme, an implicit tridiagonal relaxation scheme modeled after line Gauss-Seidel, a fully implicit lower-upper (LU) decomposition, and a hybrid scheme utilizing both Runge-Kutta and LU methods are presented. A reverse Cuthill-McKee renumbering scheme is employed for the direct solver to decrease CPU time by reducing the fill of the Jacobian matrix. A comparison of the various time integration schemes is made for both first-order and higher order accurate solutions using several mesh sizes, higher order accuracy is achieved by using multidimensional monotone linear reconstruction procedures. The results obtained for a transonic flow over a circular arc suggest that the preconditioned sparse matrix solvers perform better than the other methods as the number of elements in the mesh increases.

A heuristic statistical stopping rule for iterative reconstruction in emission tomography.

PubMed

Ben Bouallègue, F; Crouzet, J F; Mariano-Goulart, D

2013-01-01

We propose a statistical stopping criterion for iterative reconstruction in emission tomography based on a heuristic statistical description of the reconstruction process. The method was assessed for MLEM reconstruction. Based on Monte-Carlo numerical simulations and using a perfectly modeled system matrix, our method was compared with classical iterative reconstruction followed by low-pass filtering in terms of Euclidian distance to the exact object, noise, and resolution. The stopping criterion was then evaluated with realistic PET data of a Hoffman brain phantom produced using the GATE platform for different count levels. The numerical experiments showed that compared with the classical method, our technique yielded significant improvement of the noise-resolution tradeoff for a wide range of counting statistics compatible with routine clinical settings. When working with realistic data, the stopping rule allowed a qualitatively and quantitatively efficient determination of the optimal image. Our method appears to give a reliable estimation of the optimal stopping point for iterative reconstruction. It should thus be of practical interest as it produces images with similar or better quality than classical post-filtered iterative reconstruction with a mastered computation time.