Block-conjugate-gradient method
International Nuclear Information System (INIS)
McCarthy, J.F.
1989-01-01
It is shown that by using the block-conjugate-gradient method several, say s, columns of the inverse Kogut-Susskind fermion matrix can be found simultaneously, in less time than it would take to run the standard conjugate-gradient algorithm s times. The method improves in efficiency relative to the standard conjugate-gradient algorithm as the fermion mass is decreased and as the value of the coupling is pushed to its limit before the finite-size effects become important. Thus it is potentially useful for measuring propagators in large lattice-gauge-theory calculations of the particle spectrum
Preconditioning the modified conjugate gradient method ...
African Journals Online (AJOL)
In this paper, the convergence analysis of the conventional conjugate Gradient method was reviewed. And the convergence analysis of the modified conjugate Gradient method was analysed with our extension on preconditioning the algorithm. Convergence of the algorithm is a function of the condition number of M-1A.
Approximate error conjugation gradient minimization methods
Kallman, Jeffrey S
2013-05-21
In one embodiment, a method includes selecting a subset of rays from a set of all rays to use in an error calculation for a constrained conjugate gradient minimization problem, calculating an approximate error using the subset of rays, and calculating a minimum in a conjugate gradient direction based on the approximate error. In another embodiment, a system includes a processor for executing logic, logic for selecting a subset of rays from a set of all rays to use in an error calculation for a constrained conjugate gradient minimization problem, logic for calculating an approximate error using the subset of rays, and logic for calculating a minimum in a conjugate gradient direction based on the approximate error. In other embodiments, computer program products, methods, and systems are described capable of using approximate error in constrained conjugate gradient minimization problems.
Nonlinear conjugate gradient methods in micromagnetics
Directory of Open Access Journals (Sweden)
J. Fischbacher
2017-04-01
Full Text Available Conjugate gradient methods for energy minimization in micromagnetics are compared. The comparison of analytic results with numerical simulation shows that standard conjugate gradient method may fail to produce correct results. A method that restricts the step length in the line search is introduced, in order to avoid this problem. When the step length in the line search is controlled, conjugate gradient techniques are a fast and reliable way to compute the hysteresis properties of permanent magnets. The method is applied to investigate demagnetizing effects in NdFe12 based permanent magnets. The reduction of the coercive field by demagnetizing effects is μ0ΔH = 1.4 T at 450 K.
M-step preconditioned conjugate gradient methods
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.
The multigrid preconditioned conjugate gradient method
Tatebe, Osamu
1993-01-01
A multigrid preconditioned conjugate gradient method (MGCG method), which uses the multigrid method as a preconditioner of the PCG method, is proposed. The multigrid method has inherent high parallelism and improves convergence of long wavelength components, which is important in iterative methods. By using this method as a preconditioner of the PCG method, an efficient method with high parallelism and fast convergence is obtained. First, it is considered a necessary condition of the multigrid preconditioner in order to satisfy requirements of a preconditioner of the PCG method. Next numerical experiments show a behavior of the MGCG method and that the MGCG method is superior to both the ICCG method and the multigrid method in point of fast convergence and high parallelism. This fast convergence is understood in terms of the eigenvalue analysis of the preconditioned matrix. From this observation of the multigrid preconditioner, it is realized that the MGCG method converges in very few iterations and the multigrid preconditioner is a desirable preconditioner of the conjugate gradient method.
Dai-Kou type conjugate gradient methods with a line search only using gradient.
Huang, Yuanyuan; Liu, Changhe
2017-01-01
In this paper, the Dai-Kou type conjugate gradient methods are developed to solve the optimality condition of an unconstrained optimization, they only utilize gradient information and have broader application scope. Under suitable conditions, the developed methods are globally convergent. Numerical tests and comparisons with the PRP+ conjugate gradient method only using gradient show that the methods are efficient.
New Conjugacy Conditions and Related Nonlinear Conjugate Gradient Methods
International Nuclear Information System (INIS)
Dai, Y.-H.; Liao, L.-Z.
2001-01-01
Conjugate gradient methods are a class of important methods for unconstrained optimization, especially when the dimension is large. This paper proposes a new conjugacy condition, which considers an inexact line search scheme but reduces to the old one if the line search is exact. Based on the new conjugacy condition, two nonlinear conjugate gradient methods are constructed. Convergence analysis for the two methods is provided. Our numerical results show that one of the methods is very efficient for the given test problems
Several Guaranteed Descent Conjugate Gradient Methods for Unconstrained Optimization
Directory of Open Access Journals (Sweden)
San-Yang Liu
2014-01-01
Full Text Available This paper investigates a general form of guaranteed descent conjugate gradient methods which satisfies the descent condition gkTdk≤-1-1/4θkgk2 θk>1/4 and which is strongly convergent whenever the weak Wolfe line search is fulfilled. Moreover, we present several specific guaranteed descent conjugate gradient methods and give their numerical results for large-scale unconstrained optimization.
Comparison of genetic algorithms with conjugate gradient methods
Bosworth, J. L.; Foo, N. Y.; Zeigler, B. P.
1972-01-01
Genetic algorithms for mathematical function optimization are modeled on search strategies employed in natural adaptation. Comparisons of genetic algorithms with conjugate gradient methods, which were made on an IBM 1800 digital computer, show that genetic algorithms display superior performance over gradient methods for functions which are poorly behaved mathematically, for multimodal functions, and for functions obscured by additive random noise. Genetic methods offer performance comparable to gradient methods for many of the standard functions.
Modified conjugate gradient method for diagonalizing large matrices.
Jie, Quanlin; Liu, Dunhuan
2003-11-01
We present an iterative method to diagonalize large matrices. The basic idea is the same as the conjugate gradient (CG) method, i.e, minimizing the Rayleigh quotient via its gradient and avoiding reintroducing errors to the directions of previous gradients. Each iteration step is to find lowest eigenvector of the matrix in a subspace spanned by the current trial vector and the corresponding gradient of the Rayleigh quotient, as well as some previous trial vectors. The gradient, together with the previous trial vectors, play a similar role as the conjugate gradient of the original CG algorithm. Our numeric tests indicate that this method converges significantly faster than the original CG method. And the computational cost of one iteration step is about the same as the original CG method. It is suitable for first principle calculations.
A feasible DY conjugate gradient method for linear equality constraints
LI, Can
2017-09-01
In this paper, we propose a feasible conjugate gradient method for solving linear equality constrained optimization problem. The method is an extension of the Dai-Yuan conjugate gradient method proposed by Dai and Yuan to linear equality constrained optimization problem. It can be applied to solve large linear equality constrained problem due to lower storage requirement. An attractive property of the method is that the generated direction is always feasible and descent direction. Under mild conditions, the global convergence of the proposed method with exact line search is established. Numerical experiments are also given which show the efficiency of the method.
A Modified Conjugacy Condition and Related Nonlinear Conjugate Gradient Method
Directory of Open Access Journals (Sweden)
Shengwei Yao
2014-01-01
Full Text Available The conjugate gradient (CG method has played a special role in solving large-scale nonlinear optimization problems due to the simplicity of their very low memory requirements. In this paper, we propose a new conjugacy condition which is similar to Dai-Liao (2001. Based on this condition, the related nonlinear conjugate gradient method is given. With some mild conditions, the given method is globally convergent under the strong Wolfe-Powell line search for general functions. The numerical experiments show that the proposed method is very robust and efficient.
A Spectral Conjugate Gradient Method for Unconstrained Optimization
International Nuclear Information System (INIS)
Birgin, E. G.; Martinez, J. M.
2001-01-01
A family of scaled conjugate gradient algorithms for large-scale unconstrained minimization is defined. The Perry, the Polak-Ribiere and the Fletcher-Reeves formulae are compared using a spectral scaling derived from Raydan's spectral gradient optimization method. The best combination of formula, scaling and initial choice of step-length is compared against well known algorithms using a classical set of problems. An additional comparison involving an ill-conditioned estimation problem in Optics is presented
Deflation in preconditioned conjugate gradient methods for Finite Element Problems
Vermolen, F.J.; Vuik, C.; Segal, A.
2002-01-01
We investigate the influence of the value of deflation vectors at interfaces on the rate of convergence of preconditioned conjugate gradient methods applied to a Finite Element discretization for an elliptic equation. Our set-up is a Poisson problem in two dimensions with continuous or discontinuous
Accurate conjugate gradient methods for families of shifted systems
Eshof, J. van den; Sleijpen, G.L.G.
We present an efficient and accurate variant of the conjugate gradient method for solving families of shifted systems. In particular we are interested in shifted systems that occur in Tikhonov regularization for inverse problems since these problems can be sensitive to roundoff errors. The
preconditioning the modified conjugate gradient method
African Journals Online (AJOL)
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steepest descent method, the number of matrix-vector products per iteration .... modified CGM algorithm is used for large class of problems that is not ..... New Trends in the Mathematical and Computer Sciences with Applications to Real World.
Application of Conjugate Gradient methods to tidal simulation
Barragy, E.; Carey, G.F.; Walters, R.A.
1993-01-01
A harmonic decomposition technique is applied to the shallow water equations to yield a complex, nonsymmetric, nonlinear, Helmholtz type problem for the sea surface and an accompanying complex, nonlinear diagonal problem for the velocities. The equation for the sea surface is linearized using successive approximation and then discretized with linear, triangular finite elements. The study focuses on applying iterative methods to solve the resulting complex linear systems. The comparative evaluation includes both standard iterative methods for the real subsystems and complex versions of the well known Bi-Conjugate Gradient and Bi-Conjugate Gradient Squared methods. Several Incomplete LU type preconditioners are discussed, and the effects of node ordering, rejection strategy, domain geometry and Coriolis parameter (affecting asymmetry) are investigated. Implementation details for the complex case are discussed. Performance studies are presented and comparisons made with a frontal solver. ?? 1993.
Moving force identification based on modified preconditioned conjugate gradient method
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.
Gadolinium burnable absorber optimization by the method of conjugate gradients
International Nuclear Information System (INIS)
Drumm, C.R.; Lee, J.C.
1987-01-01
The optimal axial distribution of gadolinium burnable poison in a pressurized water reactor is determined to yield an improved power distribution. The optimization scheme is based on Pontryagin's maximum principle, with the objective function accounting for a target power distribution. The conjugate gradients optimization method is used to solve the resulting Euler-Lagrange equations iteratively, efficiently handling the high degree of nonlinearity of the problem
Program generator for the Incomplete Cholesky Conjugate Gradient (ICCG) method
International Nuclear Information System (INIS)
Kuo-Petravic, G.; Petravic, M.
1978-04-01
The Incomplete Cholesky Conjugate Gradient (ICCG) method has been found very effective for the solution of sparse systems of linear equations. Its implementation on a computer, however, requires a considerable amount of careful coding to achieve good machine efficiency. Furthermore, the resulting code is necessarily inflexible and cannot be easily adapted to different problems. We present in this paper a code generator GENIC which, given a small amount of information concerning the sparsity pattern and size of the system of equations, generates a solver package. This package, called SOLIC, is tailor made for a particular problem and can be easily incorporated into any user program
Total variation superiorized conjugate gradient method for image reconstruction
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.
Shang, Shang; Bai, Jing; Song, Xiaolei; Wang, Hongkai; Lau, Jaclyn
2007-01-01
Conjugate gradient method is verified to be efficient for nonlinear optimization problems of large-dimension data. In this paper, a penalized linear and nonlinear combined conjugate gradient method for the reconstruction of fluorescence molecular tomography (FMT) is presented. The algorithm combines the linear conjugate gradient method and the nonlinear conjugate gradient method together based on a restart strategy, in order to take advantage of the two kinds of conjugate gradient methods and compensate for the disadvantages. A quadratic penalty method is adopted to gain a nonnegative constraint and reduce the illposedness of the problem. Simulation studies show that the presented algorithm is accurate, stable, and fast. It has a better performance than the conventional conjugate gradient-based reconstruction algorithms. It offers an effective approach to reconstruct fluorochrome information for FMT.
Aerodynamic shape optimization using preconditioned conjugate gradient methods
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.
Accurate reanalysis of structures by a preconditioned conjugate gradient method
Czech Academy of Sciences Publication Activity Database
Kirsch, U.; Kočvara, Michal; Zowe, J.
2002-01-01
Roč. 55, č. 2 (2002), s. 233-251 ISSN 0029-5981 R&D Projects: GA AV ČR IAA1075005 Grant - others:BMBF(DE) 03ZOM3ER Institutional research plan: CEZ:AV0Z1075907 Keywords : preconditioned conjugate gradient s * structural reanalysis Subject RIV: BA - General Mathematics Impact factor: 1.468, year: 2002
Acceleration of monte Carlo solution by conjugate gradient method
International Nuclear Information System (INIS)
Toshihisa, Yamamoto
2005-01-01
The conjugate gradient method (CG) was applied to accelerate Monte Carlo solutions in fixed source problems. The equilibrium model based formulation enables to use CG scheme as well as initial guess to maximize computational performance. This method is available to arbitrary geometry provided that the neutron source distribution in each subregion can be regarded as flat. Even if it is not the case, the method can still be used as a powerful tool to provide an initial guess very close to the converged solution. The major difference of Monte Carlo CG to deterministic CG is that residual error is estimated using Monte Carlo sampling, thus statistical error exists in the residual. This leads to a flow diagram specific to Monte Carlo-CG. Three pre-conditioners were proposed for CG scheme and the performance was compared with a simple 1-D slab heterogeneous test problem. One of them, Sparse-M option, showed an excellent performance in convergence. The performance per unit cost was improved by four times in the test problem. Although direct estimation of efficiency of the method is impossible mainly because of the strong problem-dependence of the optimized pre-conditioner in CG, the method seems to have efficient potential as a fast solution algorithm for Monte Carlo calculations. (author)
International Nuclear Information System (INIS)
Chen, G.S.
1997-01-01
We apply and compare the preconditioned generalized conjugate gradient methods to solve the linear system equation that arises in the two-dimensional neutron and photon transport equation in this paper. Several subroutines are developed on the basis of preconditioned generalized conjugate gradient methods for time-independent, two-dimensional neutron and photon transport equation in the transport theory. These generalized conjugate gradient methods are used. TFQMR (transpose free quasi-minimal residual algorithm), CGS (conjuage gradient square algorithm), Bi-CGSTAB (bi-conjugate gradient stabilized algorithm) and QMRCGSTAB (quasi-minimal residual variant of bi-conjugate gradient stabilized algorithm). These sub-routines are connected to computer program DORT. Several problems are tested on a personal computer with Intel Pentium CPU. (author)
Ledoux, L.A.F.; Berkhoff, Arthur P.; Thijssen, J.M.
The Conjugate Gradient Rayleigh method for the calculation of acoustic reflection and transmission at a rough interface between two media was experimentally verified. The method is based on a continuous version of the conjugate gradient technique and plane-wave expansions. We measured the beam
Weighted graph based ordering techniques for preconditioned conjugate gradient methods
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.
Preconditioned Conjugate Gradient methods for low speed flow calculations
Ajmani, Kumud; Ng, Wing-Fai; Liou, Meng-Sing
1993-01-01
An investigation is conducted into the viability of using a generalized Conjugate Gradient-like method as an iterative solver to obtain steady-state solutions of very low-speed fluid flow problems. Low-speed flow at Mach 0.1 over a backward-facing step is chosen as a representative test problem. The unsteady form of the two dimensional, compressible Navier-Stokes equations are integrated in time using discrete time-steps. The Navier-Stokes equations are cast in an implicit, upwind finite-volume, flux split formulation. The new iterative solver is used to solve a linear system of equations at each step of the time-integration. Preconditioning techniques are used with the new solver to enhance the stability and the convergence rate of the solver and are found to be critical to the overall success of the solver. A study of various preconditioners reveals that a preconditioner based on the lower-upper (L-U)-successive symmetric over-relaxation iterative scheme is more efficient than a preconditioner based on incomplete L-U factorizations of the iteration matrix. The performance of the new preconditioned solver is compared with a conventional line Gauss-Seidel relaxation (LGSR) solver. Overall speed-up factors of 28 (in terms of global time-steps required to converge to a steady-state solution) and 20 (in terms of total CPU time on one processor of a CRAY-YMP) are found in favor of the new preconditioned solver, when compared with the LGSR solver.
Conjugate Gradient like methods and their application to fixed source neutron diffusion problems
International Nuclear Information System (INIS)
Suetomi, Eiichi; Sekimoto, Hiroshi
1989-01-01
This paper presents a number of fast iterative methods for solving systems of linear equations appearing in fixed source problems for neutron diffusion. We employed the conjugate gradient and conjugate residual methods. In order to accelerate the conjugate residual method, we proposed the conjugate residual squared method by transforming the residual polynomial of the conjugate residual method. Since the convergence of these methods depends on the spectrum of coefficient matrix, we employed the incomplete Choleski (IC) factorization and the modified IC (MIC) factorization as preconditioners. These methods were applied to some neutron diffusion problems and compared with the successive overrelaxation (SOR) method. The results of these numerical experiments showed superior convergence characteristics of the conjugate gradient like method with MIC factorization to the SOR method, especially for a problem involving void region. The CPU time of the MICCG, MICCR and MICCRS methods showed no great difference. In order to vectorize the conjugate gradient like methods based on (M)IC factorization, the hyperplane method was used and implemented on the vector computers, the HITAC S-820/80 and ETA10-E (one processor mode). Significant decrease of the CPU times was observed on the S-820/80. Since the scaled conjugate gradient (SCG) method can be vectorized with no manipulation, it was also compared with the above methods. It turned out the SCG method was the fastest with respect to the CPU times on the ETA10-E. These results suggest that one should implement suitable algorithm for different vector computers. (author)
A three-term conjugate gradient method under the strong-Wolfe line search
Khadijah, Wan; Rivaie, Mohd; Mamat, Mustafa
2017-08-01
Recently, numerous studies have been concerned in conjugate gradient methods for solving large-scale unconstrained optimization method. In this paper, a three-term conjugate gradient method is proposed for unconstrained optimization which always satisfies sufficient descent direction and namely as Three-Term Rivaie-Mustafa-Ismail-Leong (TTRMIL). Under standard conditions, TTRMIL method is proved to be globally convergent under strong-Wolfe line search. Finally, numerical results are provided for the purpose of comparison.
Application of the conjugate-gradient method to ground-water models
Manteuffel, T.A.; Grove, D.B.; Konikow, Leonard F.
1984-01-01
The conjugate-gradient method can solve efficiently and accurately finite-difference approximations to the ground-water flow equation. An aquifer-simulation model using the conjugate-gradient method was applied to a problem of ground-water flow in an alluvial aquifer at the Rocky Mountain Arsenal, Denver, Colorado. For this application, the accuracy and efficiency of the conjugate-gradient method compared favorably with other available methods for steady-state flow. However, its efficiency relative to other available methods depends on the nature of the specific problem. The main advantage of the conjugate-gradient method is that it does not require the use of iteration parameters, thereby eliminating this partly subjective procedure. (USGS)
A finite element conjugate gradient FFT method for scattering
Collins, Jeffery D.; Ross, Dan; Jin, J.-M.; Chatterjee, A.; Volakis, John L.
1991-01-01
Validated results are presented for the new 3D body of revolution finite element boundary integral code. A Fourier series expansion of the vector electric and mangnetic fields is employed to reduce the dimensionality of the system, and the exact boundary condition is employed to terminate the finite element mesh. The mesh termination boundary is chosen such that is leads to convolutional boundary operatores of low O(n) memory demand. Improvements of this code are discussed along with the proposed formulation for a full 3D implementation of the finite element boundary integral method in conjunction with a conjugate gradiant fast Fourier transformation (CGFFT) solution.
International Nuclear Information System (INIS)
Chen, G.S.; Yang, D.Y.
1998-01-01
We apply and compare the preconditioned generalized conjugate gradient methods to solve the linear system equation that arises in the two-dimensional neutron and photon transport equation in this paper. Several subroutines are developed on the basis of preconditioned generalized conjugate gradient methods for time-independent, two-dimensional neutron and photon transport equation in the transport theory. These generalized conjugate gradient methods are used: TFQMR (transpose free quasi-minimal residual algorithm) CGS (conjugate gradient square algorithm), Bi-CGSTAB (bi-conjugate gradient stabilized algorithm) and QMRCGSTAB (quasi-minimal residual variant of bi-conjugate gradient stabilized algorithm). These subroutines are connected to computer program DORT. Several problems are tested on a personal computer with Intel Pentium CPU. The reasons to choose the generalized conjugate gradient methods are that the methods have better residual (equivalent to error) control procedures in the computation and have better convergent rate. The pointwise incomplete LU factorization ILU, modified pointwise incomplete LU factorization MILU, block incomplete factorization BILU and modified blockwise incomplete LU factorization MBILU are the preconditioning techniques used in the several testing problems. In Bi-CGSTAB, CGS, TFQMR and QMRCGSTAB method, we find that either CGS or Bi-CGSTAB method combined with preconditioner MBILU is the most efficient algorithm in these methods in the several testing problems. The numerical solution of flux by preconditioned CGS and Bi-CGSTAB methods has the same result as those from Cray computer, obtained by either the point successive relaxation method or the line successive relaxation method combined with Gaussian elimination
Blockwise conjugate gradient methods for image reconstruction in volumetric CT.
Qiu, W; Titley-Peloquin, D; Soleimani, M
2012-11-01
Cone beam computed tomography (CBCT) enables volumetric image reconstruction from 2D projection data and plays an important role in image guided radiation therapy (IGRT). Filtered back projection is still the most frequently used algorithm in applications. The algorithm discretizes the scanning process (forward projection) into a system of linear equations, which must then be solved to recover images from measured projection data. The conjugate gradients (CG) algorithm and its variants can be used to solve (possibly regularized) linear systems of equations Ax=b and linear least squares problems minx∥b-Ax∥2, especially when the matrix A is very large and sparse. Their applications can be found in a general CT context, but in tomography problems (e.g. CBCT reconstruction) they have not widely been used. Hence, CBCT reconstruction using the CG-type algorithm LSQR was implemented and studied in this paper. In CBCT reconstruction, the main computational challenge is that the matrix A usually is very large, and storing it in full requires an amount of memory well beyond the reach of commodity computers. Because of these memory capacity constraints, only a small fraction of the weighting matrix A is typically used, leading to a poor reconstruction. In this paper, to overcome this difficulty, the matrix A is partitioned and stored blockwise, and blockwise matrix-vector multiplications are implemented within LSQR. This implementation allows us to use the full weighting matrix A for CBCT reconstruction without further enhancing computer standards. Tikhonov regularization can also be implemented in this fashion, and can produce significant improvement in the reconstructed images. Copyright © 2011 Elsevier Ireland Ltd. All rights reserved.
Ghani, N. H. A.; Mohamed, N. S.; Zull, N.; Shoid, S.; Rivaie, M.; Mamat, M.
2017-09-01
Conjugate gradient (CG) method is one of iterative techniques prominently used in solving unconstrained optimization problems due to its simplicity, low memory storage, and good convergence analysis. This paper presents a new hybrid conjugate gradient method, named NRM1 method. The method is analyzed under the exact and inexact line searches in given conditions. Theoretically, proofs show that the NRM1 method satisfies the sufficient descent condition with both line searches. The computational result indicates that NRM1 method is capable in solving the standard unconstrained optimization problems used. On the other hand, the NRM1 method performs better under inexact line search compared with exact line search.
PRECONDITIONED BI-CONJUGATE GRADIENT METHOD FOR RADIATIVE TRANSFER IN SPHERICAL MEDIA
International Nuclear Information System (INIS)
Anusha, L. S.; Nagendra, K. N.; Paletou, F.; Leger, L.
2009-01-01
A robust numerical method called the Preconditioned Bi-Conjugate Gradient (Pre-BiCG) method is proposed for the solution of the radiative transfer equation in spherical geometry. A variant of this method called Stabilized Preconditioned Bi-Conjugate Gradient (Pre-BiCG-STAB) is also presented. These are iterative methods based on the construction of a set of bi-orthogonal vectors. The application of the Pre-BiCG method in some benchmark tests shows that the method is quite versatile, and can handle difficult problems that may arise in astrophysical radiative transfer theory.
Application of conjugate gradient method to Commix-1B three-dimensional momentum equation
International Nuclear Information System (INIS)
King, J.B.; Domanus, H.
1987-01-01
Conjugate gradient method which is a special case of the variational method was implemented in the momentum section of the COMMIX-1B thermal hydraulics code. The comparisons between this method and the conventional iterative method of Successive Over Relation (S.O.R.) were made. Using COMMIX-1B, three steady state problems were analyzed. These problems were flow distribution in a scaled model of the Clinch River Fast Breeder Reactor outlet plenum, flow of coolant in the cold leg and downcomer of a PWR and isothermal air flow through a partially blocked pipe. It was found that if the conjugate gradient method is used, the execution time required to solve the resulting COMMIX-1B system of equations can be reduced by a factor of about 2 for the first two problems. For the isothermal air flow problem, the conjugate gradient method did not improve the execution time
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
Two-level preconditioned conjugate gradient methods with applications to bubbly flow problems
Tang, J.M.
2008-01-01
The Preconditioned Conjugate Gradient (PCG) method is one of the most popular iterative methods for solving large linear systems with a symmetric and positive semi-definite coefficient matrix. However, if the preconditioned coefficient matrix is ill-conditioned, the convergence of the PCG method
Directory of Open Access Journals (Sweden)
San-Yang Liu
2014-01-01
Full Text Available Two unified frameworks of some sufficient descent conjugate gradient methods are considered. Combined with the hyperplane projection method of Solodov and Svaiter, they are extended to solve convex constrained nonlinear monotone equations. Their global convergence is proven under some mild conditions. Numerical results illustrate that these methods are efficient and can be applied to solve large-scale nonsmooth equations.
Analysis and performance estimation of the Conjugate Gradient method on multiple GPUs
Verschoor, M.; Jalba, A.C.
2012-01-01
The Conjugate Gradient (CG) method is a widely-used iterative method for solving linear systems described by a (sparse) matrix. The method requires a large amount of Sparse-Matrix Vector (SpMV) multiplications, vector reductions and other vector operations to be performed. We present a number of
Accurate conjugate gradient methods for families of shifted systems
Eshof, J. van den; Sleijpen, G.L.G.
2003-01-01
We consider the solution of the linear system (ATA + σI)xσ = ATb, for various real values of σ. This family of shifted systems arises, for example, in Tikhonov regularization and computations in lattice quantum chromodynamics. For each single shift σ this system can be solved using the conjugate
Necessary and sufficient conditions for the existence of a conjugate gradient method
International Nuclear Information System (INIS)
Faber, V.; Manteuffel, T.
1984-01-01
The authors characterize the class CG(s) of matrices A for which the linear system Ax = b can be solved by an s-term conjugate gradient method. The authors show that, except for a few anomalies, the class CG(s) consists of matrices A for which conjugate gradient methods are already known. These matrices are the Hermitian matrices, A* = A, and the matrices of the form A = e/sup i theta/(dI + B), with B* = -B. 7 references
Global Convergence of a Spectral Conjugate Gradient Method for Unconstrained Optimization
Directory of Open Access Journals (Sweden)
Jinkui Liu
2012-01-01
Full Text Available A new nonlinear spectral conjugate descent method for solving unconstrained optimization problems is proposed on the basis of the CD method and the spectral conjugate gradient method. For any line search, the new method satisfies the sufficient descent condition gkTdk<−∥gk∥2. Moreover, we prove that the new method is globally convergent under the strong Wolfe line search. The numerical results show that the new method is more effective for the given test problems from the CUTE test problem library (Bongartz et al., 1995 in contrast to the famous CD method, FR method, and PRP method.
On the solution of the Hartree-Fock-Bogoliubov equations by the conjugate gradient method
International Nuclear Information System (INIS)
Egido, J.L.; Robledo, L.M.
1995-01-01
The conjugate gradient method is formulated in the Hilbert space for density and non-density dependent Hamiltonians. We apply it to the solution of the Hartree-Fock-Bogoliubov equations with constraints. As a numerical application we show calculations with the finite range density dependent Gogny force. The number of iterations required to reach convergence is reduced by a factor of three to four as compared with the standard gradient method. (orig.)
An M-step preconditioned conjugate gradient method for parallel computation
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.
Application of preconditioned conjugate gradient-like methods to reactor kinetics
International Nuclear Information System (INIS)
Yang, D.Y.; Chen, G.S.; Chou, H.P.
1993-01-01
Several conjugate gradient-like (CG-like) methods are applied to solve the nonsymmetric linear systems of equations derived from the time-dependent two-dimensional two-energy-group neutron diffusion equations by a finite difference approximation. The methods are: the generalized conjugate residual method; the generalized conjugate gradient least-square method; the generalized minimal residual method (GMRES); the conjugate gradient square method; and a variant of bi-conjugate gradient method (Bi-CGSTAB). In order to accelerate these methods, six preconditioning techniques are investigated. Two are based on pointwise incomplete factorization: the incomplete LU (ILU) and the modified incomplete LU (MILU) decompositions; two, based on the block tridiagonal structure of the coefficient matrix, are blockwise and modified blockwise incomplete factorizations, BILU and MBILU; two are the alternating-direction implicit and symmetric successive overrelaxation (SSOR) preconditioners, derived from the basic iterative schemes. Comparisons are made by using CG-like methods combined with different preconditioners to solve a sequence of time-step reactor transient problems. Numerical tests indicate that preconditioned BI-CGSTAB with the preconditioner MBILU requires less CPU time and fewer iterations than other methods. The preconditioned CG-like methods are less sensitive to the time-step size used than the Chebyshev semi-iteration method and line SOR method. The indication is that the CGS, Bi-CGSTAB and GMRES methods are, on average, better than the other methods in reactor kinetics computation and that a good preconditioner is more important than the choice of CG-like methods. The MILU decomposition based on the conventional row-sum criterion has difficulty yielding a convergent solution and an improved version is introduced. (author)
The influence of deflation vectors at interfaces on the deflated conjugate gradient method
Vermolen, F.J.; Vuik, C.
2001-01-01
We investigate the influence of the value of deflation vectors at interfaces on the rate of convergence of preconditioned conjugate gradient methods. Our set-up is a Laplace problem in two dimensions with continuous or discontinuous coeffcients that vary in several orders of magnitude. In the
A fast nonlinear conjugate gradient based method for 3D frictional contact problems
Zhao, J.; Vollebregt, E.A.H.; Oosterlee, C.W.
2014-01-01
This paper presents a fast numerical solver for a nonlinear constrained optimization problem, arising from a 3D frictional contact problem. It incorporates an active set strategy with a nonlinear conjugate gradient method. One novelty is to consider the tractions of each slip element in a polar
A fast nonlinear conjugate gradient based method for 3D concentrated frictional contact problems
J. Zhao (Jing); E.A.H. Vollebregt (Edwin); C.W. Oosterlee (Cornelis)
2015-01-01
htmlabstractThis paper presents a fast numerical solver for a nonlinear constrained optimization problem, arising from 3D concentrated frictional shift and rolling contact problems with dry Coulomb friction. The solver combines an active set strategy with a nonlinear conjugate gradient method. One
Efficient two-level preconditionined conjugate gradient method on the GPU
Gupta, R.; Van Gijzen, M.B.; Vuik, K.
2011-01-01
We present an implementation of Two-Level Preconditioned Conjugate Gradient Method for the GPU. We investigate a Truncated Neumann Series based preconditioner in combination with deflation and compare it with Block Incomplete Cholesky schemes. This combination exhibits fine-grain parallelism and
A nonsmooth nonlinear conjugate gradient method for interactive contact force problems
DEFF Research Database (Denmark)
Silcowitz, Morten; Abel, Sarah Maria Niebe; Erleben, Kenny
2010-01-01
of a nonlinear complementarity problem (NCP), which can be solved using an iterative splitting method, such as the projected Gauss–Seidel (PGS) method. We present a novel method for solving the NCP problem by applying a Fletcher–Reeves type nonlinear nonsmooth conjugate gradient (NNCG) type method. We analyze...... and present experimental convergence behavior and properties of the new method. Our results show that the NNCG method has at least the same convergence rate as PGS, and in many cases better....
Solving Optimal Control Problem of Monodomain Model Using Hybrid Conjugate Gradient Methods
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Kin Wei Ng
2012-01-01
Full Text Available We present the numerical solutions for the PDE-constrained optimization problem arising in cardiac electrophysiology, that is, the optimal control problem of monodomain model. The optimal control problem of monodomain model is a nonlinear optimization problem that is constrained by the monodomain model. The monodomain model consists of a parabolic partial differential equation coupled to a system of nonlinear ordinary differential equations, which has been widely used for simulating cardiac electrical activity. Our control objective is to dampen the excitation wavefront using optimal applied extracellular current. Two hybrid conjugate gradient methods are employed for computing the optimal applied extracellular current, namely, the Hestenes-Stiefel-Dai-Yuan (HS-DY method and the Liu-Storey-Conjugate-Descent (LS-CD method. Our experiment results show that the excitation wavefronts are successfully dampened out when these methods are used. Our experiment results also show that the hybrid conjugate gradient methods are superior to the classical conjugate gradient methods when Armijo line search is used.
Bhaya, Amit; Kaszkurewicz, Eugenius
2004-01-01
It is pointed out that the so called momentum method, much used in the neural network literature as an acceleration of the backpropagation method, is a stationary version of the conjugate gradient method. Connections with the continuous optimization method known as heavy ball with friction are also made. In both cases, adaptive (dynamic) choices of the so called learning rate and momentum parameters are obtained using a control Liapunov function analysis of the system.
Conjugate gradient type methods for linear systems with complex symmetric coefficient matrices
Freund, Roland
1989-01-01
We consider conjugate gradient type methods for the solution of large sparse linear system Ax equals b with complex symmetric coefficient matrices A equals A(T). Such linear systems arise in important applications, such as the numerical solution of the complex Helmholtz equation. Furthermore, most complex non-Hermitian linear systems which occur in practice are actually complex symmetric. We investigate conjugate gradient type iterations which are based on a variant of the nonsymmetric Lanczos algorithm for complex symmetric matrices. We propose a new approach with iterates defined by a quasi-minimal residual property. The resulting algorithm presents several advantages over the standard biconjugate gradient method. We also include some remarks on the obvious approach to general complex linear systems by solving equivalent real linear systems for the real and imaginary parts of x. Finally, numerical experiments for linear systems arising from the complex Helmholtz equation are reported.
A Projected Conjugate Gradient Method for Sparse Minimax Problems
DEFF Research Database (Denmark)
Madsen, Kaj; Jonasson, Kristjan
1993-01-01
A new method for nonlinear minimax problems is presented. The method is of the trust region type and based on sequential linear programming. It is a first order method that only uses first derivatives and does not approximate Hessians. The new method is well suited for large sparse problems...... as it only requires that software for sparse linear programming and a sparse symmetric positive definite equation solver are available. On each iteration a special linear/quadratic model of the function is minimized, but contrary to the usual practice in trust region methods the quadratic model is only...... with the method are presented. In fact, we find that the number of iterations required is comparable to that of state-of-the-art quasi-Newton codes....
A family of conjugate gradient methods for large-scale nonlinear equations
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Dexiang Feng
2017-09-01
Full Text Available Abstract In this paper, we present a family of conjugate gradient projection methods for solving large-scale nonlinear equations. At each iteration, it needs low storage and the subproblem can be easily solved. Compared with the existing solution methods for solving the problem, its global convergence is established without the restriction of the Lipschitz continuity on the underlying mapping. Preliminary numerical results are reported to show the efficiency of the proposed method.
A family of conjugate gradient methods for large-scale nonlinear equations.
Feng, Dexiang; Sun, Min; Wang, Xueyong
2017-01-01
In this paper, we present a family of conjugate gradient projection methods for solving large-scale nonlinear equations. At each iteration, it needs low storage and the subproblem can be easily solved. Compared with the existing solution methods for solving the problem, its global convergence is established without the restriction of the Lipschitz continuity on the underlying mapping. Preliminary numerical results are reported to show the efficiency of the proposed method.
A conjugate gradient method for the spectral partitioning of graphs
Kruyt, Nicolaas P.
1997-01-01
The partitioning of graphs is a frequently occurring problem in science and engineering. The spectral graph partitioning method is a promising heuristic method for this class of problems. Its main disadvantage is the large computing time required to solve a special eigenproblem. Here a simple and
Feng, Shuo; Ji, Jim
2014-04-01
Parallel excitation (pTx) techniques with multiple transmit channels have been widely used in high field MRI imaging to shorten the RF pulse duration and/or reduce the specific absorption rate (SAR). However, the efficiency of pulse design still needs substantial improvement for practical real-time applications. In this paper, we present a detailed description of a fast pulse design method with Fourier domain gridding and a conjugate gradient method. Simulation results of the proposed method show that the proposed method can design pTx pulses at an efficiency 10 times higher than that of the conventional conjugate-gradient based method, without reducing the accuracy of the desirable excitation patterns.
Bernal, Javier; Torres-Jimenez, Jose
2015-01-01
SAGRAD (Simulated Annealing GRADient), a Fortran 77 program for computing neural networks for classification using batch learning, is discussed. Neural network training in SAGRAD is based on a combination of simulated annealing and Møller's scaled conjugate gradient algorithm, the latter a variation of the traditional conjugate gradient method, better suited for the nonquadratic nature of neural networks. Different aspects of the implementation of the training process in SAGRAD are discussed, such as the efficient computation of gradients and multiplication of vectors by Hessian matrices that are required by Møller's algorithm; the (re)initialization of weights with simulated annealing required to (re)start Møller's algorithm the first time and each time thereafter that it shows insufficient progress in reaching a possibly local minimum; and the use of simulated annealing when Møller's algorithm, after possibly making considerable progress, becomes stuck at a local minimum or flat area of weight space. Outlines of the scaled conjugate gradient algorithm, the simulated annealing procedure and the training process used in SAGRAD are presented together with results from running SAGRAD on two examples of training data.
Directory of Open Access Journals (Sweden)
Zhongbo Sun
2014-01-01
Full Text Available Two modified three-term type conjugate gradient algorithms which satisfy both the descent condition and the Dai-Liao type conjugacy condition are presented for unconstrained optimization. The first algorithm is a modification of the Hager and Zhang type algorithm in such a way that the search direction is descent and satisfies Dai-Liao’s type conjugacy condition. The second simple three-term type conjugate gradient method can generate sufficient decent directions at every iteration; moreover, this property is independent of the steplength line search. Also, the algorithms could be considered as a modification of the MBFGS method, but with different zk. Under some mild conditions, the given methods are global convergence, which is independent of the Wolfe line search for general functions. The numerical experiments show that the proposed methods are very robust and efficient.
International Nuclear Information System (INIS)
Kowsary, F.; Pooladvand, K.; Pourshaghaghy, A.
2007-01-01
In this paper, an appropriate distribution of the heating elements' strengths in a radiation furnace is estimated using inverse methods so that a pre-specified temperature and heat flux distribution is attained on the design surface. Minimization of the sum of the squares of the error function is performed using the variable metric method (VMM), and the results are compared with those obtained by the conjugate gradient method (CGM) established previously in the literature. It is shown via test cases and a well-founded validation procedure that the VMM, when using a 'regularized' estimator, is more accurate and is able to reach at a higher quality final solution as compared to the CGM. The test cases used in this study were two-dimensional furnaces filled with an absorbing, emitting, and scattering gas
Conjugate gradient method for phase retrieval based on the Wirtinger derivative.
Wei, Zhun; Chen, Wen; Qiu, Cheng-Wei; Chen, Xudong
2017-05-01
A conjugate gradient Wirtinger flow (CG-WF) algorithm for phase retrieval is proposed in this paper. It is shown that, compared with recently reported Wirtinger flow and its modified methods, the proposed CG-WF algorithm is able to dramatically accelerate the convergence rate while keeping the dominant computational cost of each iteration unchanged. We numerically illustrate the effectiveness of our method in recovering 1D Gaussian signals and 2D natural color images under both Gaussian and coded diffraction pattern models.
Preconditioned conjugate gradient methods for the Navier-Stokes equations
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.
New generalized conjugate gradient methods for the non-quadratic model in unconstrained optimization
International Nuclear Information System (INIS)
Al-Bayati, A.
2001-01-01
This paper present two new conjugate gradient algorithms which use the non-quadratic model in unconstrained optimization. The first is a new generalized self-scaling variable metric algorithm based on the sloboda generalized conjugate gradient method which is invariant to a nonlinear scaling of a stricity convex quadratic function; the second is an interleaving between the generalized sloboda method and the first algorithm; all these algorithm use exact line searches. Numerical comparisons over twenty test functions show that the interleaving algorithm is best overall and requires only about half the function evaluations of the Sloboda method: interleaving algorithms are likely to be preferred when the dimensionality of the problem is increased. (author). 29 refs., 1 tab
Use of a preconditioned Bi-conjugate gradient method for hybrid plasma stability analysis
International Nuclear Information System (INIS)
Mikic, Z.; Morse, E.C.
1985-01-01
The numerical stability analysis of compact toroidal plasmas using implicit time differencing requires the solution of a set of coupled, 2-dimensional, elliptic partial differential equations for the field quantities at every timestep. When the equations are spatially finite-differenced and written in matrix form, the resulting matrix is large, sparse, complex, non-Hermitian, and indefinite. The use of the preconditioned bi-conjugate gradient method for solving these equations is discussed. The effect of block-diagonal preconditioning and incomplete block-LU preconditionig on the convergence of the method is investigated. For typical matrices arising in our studies, the eigenvalue spectra of the original and preconditioned matrices are calculated as an illustration of the effectiveness of the preconditioning. We show that the preconditioned bi-conjugate gradient method coverages more rapidly than the conjugate gradient method applied to the normal equations, and that it is an effective iterative method for the class of non-Hermitian, indefinite problems of interest
Orderings for conjugate gradient preconditionings
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.
HIRFL-SSC trim coil currents calculation by conjugate gradients method
International Nuclear Information System (INIS)
Liu, W.
2005-01-01
For accelerating different kinds of ions to various energies, the HIRFL-SSC should form the corresponding isochronous magnetic field by its main coil and trim coils. Previously, there were errors in fitting the theoretical isochronous magnetic field in the small radius region, which led to some operation difficulties for ion acceleration in the inject region. After further investigation of the restrictive condition of the maximum current limitation, the trim coil currents for fitting the theoretical isochronous magnetic field were recalculated by the conjugate gradients method. Better results were obtained in the operation of HIRFL-SSC. This article introduces the procedure to calculate the trim coil currents. The calculation method of conjugate gradients is introduced and the fitting error is analysed. (author)
New hybrid conjugate gradient methods with the generalized Wolfe line search.
Xu, Xiao; Kong, Fan-Yu
2016-01-01
The conjugate gradient method was an efficient technique for solving the unconstrained optimization problem. In this paper, we made a linear combination with parameters β k of the DY method and the HS method, and putted forward the hybrid method of DY and HS. We also proposed the hybrid of FR and PRP by the same mean. Additionally, to present the two hybrid methods, we promoted the Wolfe line search respectively to compute the step size α k of the two hybrid methods. With the new Wolfe line search, the two hybrid methods had descent property and global convergence property of the two hybrid methods that can also be proved.
A conjugate gradient method with descent properties under strong Wolfe line search
Zull, N.; ‘Aini, N.; Shoid, S.; Ghani, N. H. A.; Mohamed, N. S.; Rivaie, M.; Mamat, M.
2017-09-01
The conjugate gradient (CG) method is one of the optimization methods that are often used in practical applications. The continuous and numerous studies conducted on the CG method have led to vast improvements in its convergence properties and efficiency. In this paper, a new CG method possessing the sufficient descent and global convergence properties is proposed. The efficiency of the new CG algorithm relative to the existing CG methods is evaluated by testing them all on a set of test functions using MATLAB. The tests are measured in terms of iteration numbers and CPU time under strong Wolfe line search. Overall, this new method performs efficiently and comparable to the other famous methods.
Problem of unstable pivots in the incomplete LU-conjugate gradient method
International Nuclear Information System (INIS)
Kershaw, D.S.
1978-01-01
Incomplete LU and incomplete-Cholesky conjugate gradient methods are becoming widely used in both laser and magnetic fusion research. In my original presentation of these methods, the problem of what to do if a pivot [L/sub ii/U/sub ii/) becomes very small or zero was raised and only partially answered by the suggestion that it be arbitrarily set to some non-zero value. In what follows it will be shown precisely how small the pivot can become before it must be fixed and precisely what value it should be set to in order to minimize the error in LU. Numerical examples will be given to show that not only does this prescription improve incomplete LU-conjugate gradient methods , but exact LU decomposition carried out with this prescription for handling small pivots and followed by a few linear or conjugate gradient iterations can be much faster than the permutations of rows and columns usually employed to circumvent small pivot problems
Du, Shouqiang; Chen, Miao
2018-01-01
We consider a kind of nonsmooth optimization problems with [Formula: see text]-norm minimization, which has many applications in compressed sensing, signal reconstruction, and the related engineering problems. Using smoothing approximate techniques, this kind of nonsmooth optimization problem can be transformed into a general unconstrained optimization problem, which can be solved by the proposed smoothing modified three-term conjugate gradient method. The smoothing modified three-term conjugate gradient method is based on Polak-Ribière-Polyak conjugate gradient method. For the Polak-Ribière-Polyak conjugate gradient method has good numerical properties, the proposed method possesses the sufficient descent property without any line searches, and it is also proved to be globally convergent. Finally, the numerical experiments show the efficiency of the proposed method.
A Projected Non-linear Conjugate Gradient Method for Interactive Inverse Kinematics
DEFF Research Database (Denmark)
Engell-Nørregård, Morten; Erleben, Kenny
2009-01-01
Inverse kinematics is the problem of posing an articulated figure to obtain a wanted goal, without regarding inertia and forces. Joint limits are modeled as bounds on individual degrees of freedom, leading to a box-constrained optimization problem. We present A projected Non-linear Conjugate...... Gradient optimization method suitable for box-constrained optimization problems for inverse kinematics. We show application on inverse kinematics positioning of a human figure. Performance is measured and compared to a traditional Jacobian Transpose method. Visual quality of the developed method...
Frequency domain optical tomography using a conjugate gradient method without line search
International Nuclear Information System (INIS)
Kim, Hyun Keol; Charette, Andre
2007-01-01
A conjugate gradient method without line search (CGMWLS) is presented. This method is used to retrieve the local maps of absorption and scattering coefficients inside the tissue-like test medium, with the synthetic data. The forward problem is solved with a discrete-ordinates finite-difference method based on the frequency domain formulation of radiative transfer equation. The inversion results demonstrate that the CGMWLS can retrieve simultaneously the spatial distributions of optical properties inside the medium within a reasonable accuracy, by reducing cross-talk between absorption and scattering coefficients
Microwave imaging of dielectric cylinder using level set method and conjugate gradient algorithm
International Nuclear Information System (INIS)
Grayaa, K.; Bouzidi, A.; Aguili, T.
2011-01-01
In this paper, we propose a computational method for microwave imaging cylinder and dielectric object, based on combining level set technique and the conjugate gradient algorithm. By measuring the scattered field, we tried to retrieve the shape, localisation and the permittivity of the object. The forward problem is solved by the moment method, while the inverse problem is reformulate in an optimization one and is solved by the proposed scheme. It found that the proposed method is able to give good reconstruction quality in terms of the reconstructed shape and permittivity.
Directory of Open Access Journals (Sweden)
Zhifeng Dai
2014-01-01
Full Text Available Combining the Rosen gradient projection method with the two-term Polak-Ribière-Polyak (PRP conjugate gradient method, we propose a two-term Polak-Ribière-Polyak (PRP conjugate gradient projection method for solving linear equality constraints optimization problems. The proposed method possesses some attractive properties: (1 search direction generated by the proposed method is a feasible descent direction; consequently the generated iterates are feasible points; (2 the sequences of function are decreasing. Under some mild conditions, we show that it is globally convergent with Armijio-type line search. Preliminary numerical results show that the proposed method is promising.
Multi-color incomplete Cholesky conjugate gradient methods for vector computers. Ph.D. Thesis
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.
Penalty Algorithm Based on Conjugate Gradient Method for Solving Portfolio Management Problem
Directory of Open Access Journals (Sweden)
Wang YaLin
2009-01-01
Full Text Available A new approach was proposed to reformulate the biobjectives optimization model of portfolio management into an unconstrained minimization problem, where the objective function is a piecewise quadratic polynomial. We presented some properties of such an objective function. Then, a class of penalty algorithms based on the well-known conjugate gradient methods was developed to find the solution of portfolio management problem. By implementing the proposed algorithm to solve the real problems from the stock market in China, it was shown that this algorithm is promising.
Czech Academy of Sciences Publication Activity Database
Strakoš, Zdeněk; Tichý, Petr
2002-01-01
Roč. 13, - (2002), s. 56-80 ISSN 1068-9613 R&D Projects: GA ČR GA201/02/0595 Institutional research plan: AV0Z1030915 Keywords : conjugate gradient method * Gauss kvadrature * evaluation of convergence * error bounds * finite precision arithmetic * rounding errors * loss of orthogonality Subject RIV: BA - General Mathematics Impact factor: 0.565, year: 2002 http://etna.mcs.kent.edu/volumes/2001-2010/vol13/abstract.php?vol=13&pages=56-80
Multigrid preconditioned conjugate-gradient method for large-scale wave-front reconstruction.
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.
International Nuclear Information System (INIS)
Andrei, Petru; Oniciuc, Liviu; Stancu, Alexandru; Stoleriu, Laurentiu
2007-01-01
An identification technique for the parameters of phenomenological models of hysteresis is presented. The basic idea of our technique is to set up a system of equations for the parameters of the model as a function of known quantities on the major or minor hysteresis loops (e.g. coercive force, susceptibilities at various points, remanence), or other magnetization curves. This system of equations can be either over or underspecified and is solved by using the conjugate gradient method. Numerical results related to the identification of parameters in the Energetic, Jiles-Atherton, and Preisach models are presented
International Nuclear Information System (INIS)
Kari, R.E.; Mezey, P.G.; Csizmadia, I.G.
1975-01-01
Expressions are given for calculating the energy gradient vector in the exponent space of Gaussian basis sets and a technique to optimize orbital exponents using the method of conjugate gradients is described. The method is tested on the (9/sups/5/supp/) Gaussian basis space and optimum exponents are determined for the carbon atom. The analysis of the results shows that the calculated one-electron properties converge more slowly to their optimum values than the total energy converges to its optimum value. In addition, basis sets approximating the optimum total energy very well can still be markedly improved for the prediction of one-electron properties. For smaller basis sets, this improvement does not warrant the necessary expense
Method of T2 spectrum inversion with conjugate gradient algorithm from NMR data
International Nuclear Information System (INIS)
Li Pengju; Shi Shangming; Song Yanjie
2010-01-01
Based on the optimization techniques, the T 2 spectrum inversion method of conjugate gradient that is easy to realize non-negativity constraint of T2 spectrum is proposed. The method transforms the linear mixed-determined problem of T2 spectrum inversion into the typical optimization problem of searching the minimum of objective function by building up the objective function according to the basic idea of geophysics modeling. The optimization problem above is solved with the conjugate gradient algorithm that has quick convergence rate and quadratic termination. The method has been applied to the inversion of noise free echo train generated from artificial spectrum, artificial echo train with signal-to-noise ratio (SNR)=25 and NMR experimental data of drilling core. The comparison between the inversion results of this paper and artificial spectrum or the result of software imported in NMR laboratory shows that the method can correctly invert T 2 spectrum from artificial NMR relaxation data even though SNR=25 and that inversion T 2 spectrum with good continuity and smoothness from core NMR experimental data accords perfectly with that of laboratory software imported, and moreover,the absolute error between the NMR porosity computed from T 2 spectrum and helium (He) porosity in laboratory is 0.65%. (authors)
Three-Dimensional Induced Polarization Parallel Inversion Using Nonlinear Conjugate Gradients Method
Directory of Open Access Journals (Sweden)
Huan Ma
2015-01-01
Full Text Available Four kinds of array of induced polarization (IP methods (surface, borehole-surface, surface-borehole, and borehole-borehole are widely used in resource exploration. However, due to the presence of large amounts of the sources, it will take much time to complete the inversion. In the paper, a new parallel algorithm is described which uses message passing interface (MPI and graphics processing unit (GPU to accelerate 3D inversion of these four methods. The forward finite differential equation is solved by ILU0 preconditioner and the conjugate gradient (CG solver. The inverse problem is solved by nonlinear conjugate gradients (NLCG iteration which is used to calculate one forward and two “pseudo-forward” modelings and update the direction, space, and model in turn. Because each source is independent in forward and “pseudo-forward” modelings, multiprocess modes are opened by calling MPI library. The iterative matrix solver within CULA is called in each process. Some tables and synthetic data examples illustrate that this parallel inversion algorithm is effective. Furthermore, we demonstrate that the joint inversion of surface and borehole data produces resistivity and chargeability results are superior to those obtained from inversions of individual surface data.
An Efficient Hybrid Conjugate Gradient Method with the Strong Wolfe-Powell Line Search
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Ahmad Alhawarat
2015-01-01
Full Text Available Conjugate gradient (CG method is an interesting tool to solve optimization problems in many fields, such as design, economics, physics, and engineering. In this paper, we depict a new hybrid of CG method which relates to the famous Polak-Ribière-Polyak (PRP formula. It reveals a solution for the PRP case which is not globally convergent with the strong Wolfe-Powell (SWP line search. The new formula possesses the sufficient descent condition and the global convergent properties. In addition, we further explained about the cases where PRP method failed with SWP line search. Furthermore, we provide numerical computations for the new hybrid CG method which is almost better than other related PRP formulas in both the number of iterations and the CPU time under some standard test functions.
A conjugate gradient method for solving the non-LTE line radiation transfer problem
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.
Conjugate-gradient optimization method for orbital-free density functional calculations.
Jiang, Hong; Yang, Weitao
2004-08-01
Orbital-free density functional theory as an extension of traditional Thomas-Fermi theory has attracted a lot of interest in the past decade because of developments in both more accurate kinetic energy functionals and highly efficient numerical methodology. In this paper, we developed a conjugate-gradient method for the numerical solution of spin-dependent extended Thomas-Fermi equation by incorporating techniques previously used in Kohn-Sham calculations. The key ingredient of the method is an approximate line-search scheme and a collective treatment of two spin densities in the case of spin-dependent extended Thomas-Fermi problem. Test calculations for a quartic two-dimensional quantum dot system and a three-dimensional sodium cluster Na216 with a local pseudopotential demonstrate that the method is accurate and efficient. (c) 2004 American Institute of Physics.
He, Xiaowei; Liang, Jimin; Wang, Xiaorui; Yu, Jingjing; Qu, Xiaochao; Wang, Xiaodong; Hou, Yanbin; Chen, Duofang; Liu, Fang; Tian, Jie
2010-11-22
In this paper, we present an incomplete variables truncated conjugate gradient (IVTCG) method for bioluminescence tomography (BLT). Considering the sparse characteristic of the light source and insufficient surface measurement in the BLT scenarios, we combine a sparseness-inducing (ℓ1 norm) regularization term with a quadratic error term in the IVTCG-based framework for solving the inverse problem. By limiting the number of variables updated at each iterative and combining a variable splitting strategy to find the search direction more efficiently, it obtains fast and stable source reconstruction, even without a priori information of the permissible source region and multispectral measurements. Numerical experiments on a mouse atlas validate the effectiveness of the method. In vivo mouse experimental results further indicate its potential for a practical BLT system.
Conjugate-gradient preconditioning methods for shift-variant PET image reconstruction.
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.
International Nuclear Information System (INIS)
Huang, C.-H.; Wu, H.-H.
2006-01-01
In the present study an inverse hyperbolic heat conduction problem is solved by the conjugate gradient method (CGM) in estimating the unknown boundary heat flux based on the boundary temperature measurements. Results obtained in this inverse problem will be justified based on the numerical experiments where three different heat flux distributions are to be determined. Results show that the inverse solutions can always be obtained with any arbitrary initial guesses of the boundary heat flux. Moreover, the drawbacks of the previous study for this similar inverse problem, such as (1) the inverse solution has phase error and (2) the inverse solution is sensitive to measurement error, can be avoided in the present algorithm. Finally, it is concluded that accurate boundary heat flux can be estimated in this study
Use of the preconditioned conjugate gradient method to accelerate S/sub n/ iterations
International Nuclear Information System (INIS)
Derstine, K.L.; Gelbard, E.M.
1985-01-01
It is well known that specially tailored diffusion difference equations are required in the synthetic method. The tailoring process is not trivial, and for some S/sub n/ schemes (e.g., in hexagonal geometry) tailored diffusion operators are not available. The need for alternative acceleration methods has been noted by Larsen who has, in fact, proposed two alternatives. The proposed methods, however, do not converge to the S/sub n/ solution, and their accuracy is still largely unknown. Los Alamos acceleration methods are required to converge for any mesh, no matter how coarse. Since negative flux-fix ups (normally involved when mesh widths are large) may impede convergence, it is not clear that such a strict condition is really practical. Here a lesser objective is chosen. The authors wish to develop an acceleration method useful for a wide (though finite) range of mesh widths, but to avoid the use of special diffusion difference equations. It is shown that the conjugate gradient (CG) method, with the standard box-centered (BC) diffusion equation as a preconditioner, yields an algorithm that, for fixed-source problems with isotropic scattering, is mechanically very similar to the synthetic method; but, in two-dimensional test problems in various geometries, the CG method is substantially more stable
A modified conjugate gradient method based on the Tikhonov system for computerized tomography (CT).
Wang, Qi; Wang, Huaxiang
2011-04-01
During the past few decades, computerized tomography (CT) was widely used for non-destructive testing (NDT) and non-destructive examination (NDE) in the industrial area because of its characteristics of non-invasiveness and visibility. Recently, CT technology has been applied to multi-phase flow measurement. Using the principle of radiation attenuation measurements along different directions through the investigated object with a special reconstruction algorithm, cross-sectional information of the scanned object can be worked out. It is a typical inverse problem and has always been a challenge for its nonlinearity and ill-conditions. The Tikhonov regulation method is widely used for similar ill-posed problems. However, the conventional Tikhonov method does not provide reconstructions with qualities good enough, the relative errors between the reconstructed images and the real distribution should be further reduced. In this paper, a modified conjugate gradient (CG) method is applied to a Tikhonov system (MCGT method) for reconstructing CT images. The computational load is dominated by the number of independent measurements m, and a preconditioner is imported to lower the condition number of the Tikhonov system. Both simulation and experiment results indicate that the proposed method can reduce the computational time and improve the quality of image reconstruction. Copyright © 2010 ISA. Published by Elsevier Ltd. All rights reserved.
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.
Missing value imputation in DNA microarrays based on conjugate gradient method.
Dorri, Fatemeh; Azmi, Paeiz; Dorri, Faezeh
2012-02-01
Analysis of gene expression profiles needs a complete matrix of gene array values; consequently, imputation methods have been suggested. In this paper, an algorithm that is based on conjugate gradient (CG) method is proposed to estimate missing values. k-nearest neighbors of the missed entry are first selected based on absolute values of their Pearson correlation coefficient. Then a subset of genes among the k-nearest neighbors is labeled as the best similar ones. CG algorithm with this subset as its input is then used to estimate the missing values. Our proposed CG based algorithm (CGimpute) is evaluated on different data sets. The results are compared with sequential local least squares (SLLSimpute), Bayesian principle component analysis (BPCAimpute), local least squares imputation (LLSimpute), iterated local least squares imputation (ILLSimpute) and adaptive k-nearest neighbors imputation (KNNKimpute) methods. The average of normalized root mean squares error (NRMSE) and relative NRMSE in different data sets with various missing rates shows CGimpute outperforms other methods. Copyright © 2011 Elsevier Ltd. All rights reserved.
International Nuclear Information System (INIS)
King, J.B.; Anghaie, S.; Domanus, H.M.
1987-01-01
Finite difference approximations to the continuity, momentum, and energy equations in thermal hydraulics codes result in a system of N by N equations for a problem having N field points. In a three dimensional problem, N increases as the problem becomes larger or more complex, and more rapidly as the computational mesh size is reduced. As a consequence, the execution time required to solve the problem increases, which may lead to placing limits on the problem resolution or accuracy. A conventinal method of solution of these systems of equations is the Successive Over Relaxation (SOR) technique. However, for a wide range of problems the execution time may be reduced by using a more efficient linear equation solver. One such method is the conjugate gradient method which was implemented in COMMIX-1B thermal hydraulics code. It was found that the execution time required to solve the resulting system of equations was reduced by a factor of about 2 for some problems. This paper summarizes the characteristics of these iterative solution procedures and compares their performance in modeling of a variety of reactor thermal hydraulic problems, using the COMMIX-1B computer code
Adjustment technique without explicit formation of normal equations /conjugate gradient method/
Saxena, N. K.
1974-01-01
For a simultaneous adjustment of a large geodetic triangulation system, a semiiterative technique is modified and used successfully. In this semiiterative technique, known as the conjugate gradient (CG) method, original observation equations are used, and thus the explicit formation of normal equations is avoided, 'huge' computer storage space being saved in the case of triangulation systems. This method is suitable even for very poorly conditioned systems where solution is obtained only after more iterations. A detailed study of the CG method for its application to large geodetic triangulation systems was done that also considered constraint equations with observation equations. It was programmed and tested on systems as small as two unknowns and three equations up to those as large as 804 unknowns and 1397 equations. When real data (573 unknowns, 965 equations) from a 1858-km-long triangulation system were used, a solution vector accurate to four decimal places was obtained in 2.96 min after 1171 iterations (i.e., 2.0 times the number of unknowns).
A new family of Polak-Ribiere-Polyak conjugate gradient method with the strong-Wolfe line search
Ghani, Nur Hamizah Abdul; Mamat, Mustafa; Rivaie, Mohd
2017-08-01
Conjugate gradient (CG) method is an important technique in unconstrained optimization, due to its effectiveness and low memory requirements. The focus of this paper is to introduce a new CG method for solving large scale unconstrained optimization. Theoretical proofs show that the new method fulfills sufficient descent condition if strong Wolfe-Powell inexact line search is used. Besides, computational results show that our proposed method outperforms to other existing CG methods.
Generalized conjugate-gradient methods for the Navier-Stokes equations
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.
Tripathi, Ashish; McNulty, Ian; Shpyrko, Oleg G
2014-01-27
Ptychographic coherent x-ray diffractive imaging is a form of scanning microscopy that does not require optics to image a sample. A series of scanned coherent diffraction patterns recorded from multiple overlapping illuminated regions on the sample are inverted numerically to retrieve its image. The technique recovers the phase lost by detecting the diffraction patterns by using experimentally known constraints, in this case the measured diffraction intensities and the assumed scan positions on the sample. The spatial resolution of the recovered image of the sample is limited by the angular extent over which the diffraction patterns are recorded and how well these constraints are known. Here, we explore how reconstruction quality degrades with uncertainties in the scan positions. We show experimentally that large errors in the assumed scan positions on the sample can be numerically determined and corrected using conjugate gradient descent methods. We also explore in simulations the limits, based on the signal to noise of the diffraction patterns and amount of overlap between adjacent scan positions, of just how large these errors can be and still be rendered tractable by this method.
Czech Academy of Sciences Publication Activity Database
Gutknecht, M. H.; Rozložník, Miroslav
2002-01-01
Roč. 41, - (2002), s. 7-22 ISSN 0168-9274 R&D Projects: GA AV ČR IAA1030103; GA ČR GA101/00/1035 Institutional research plan: AV0Z1030915 Keywords : sparse linear systems * Krylov space method * orthogonal residual method * minimal residual method * conjugate gradient method * residual smoothing * CG * CGNE * CGNR * CR * FOM * GMRES * PRES Subject RIV: BA - General Mathematics Impact factor: 0.504, year: 2002
Directory of Open Access Journals (Sweden)
Chein-Shan Liu
2012-04-01
Full Text Available It is well known that the numerical algorithms of the steepest descent method (SDM, and the conjugate gradient method (CGM are effective for solving well-posed linear systems. However, they are vulnerable to noisy disturbance for solving ill-posed linear systems. We propose the modifications of SDM and CGM, namely the modified steepest descent method (MSDM, and the modified conjugate gradient method (MCGM. The starting point is an invariant manifold defined in terms of a minimum functional and a fictitious time-like variable; however, in the final stage we can derive a purely iterative algorithm including an acceleration parameter. Through the Hopf bifurcation, this parameter indeed plays a major role to switch the situation of slow convergence to a new situation that the functional is stepwisely decreased very fast. Several numerical examples are examined and compared with exact solutions, revealing that the new algorithms of MSDM and MCGM have good computational efficiency and accuracy, even for the highly ill-conditioned linear equations system with a large noise being imposed on the given data.
Solving groundwater flow problems by conjugate-gradient methods and the strongly implicit procedure
Hill, Mary C.
1990-01-01
The performance of the preconditioned conjugate-gradient method with three preconditioners is compared with the strongly implicit procedure (SIP) using a scalar computer. The preconditioners considered are the incomplete Cholesky (ICCG) and the modified incomplete Cholesky (MICCG), which require the same computer storage as SIP as programmed for a problem with a symmetric matrix, and a polynomial preconditioner (POLCG), which requires less computer storage than SIP. Although POLCG is usually used on vector computers, it is included here because of its small storage requirements. In this paper, published comparisons of the solvers are evaluated, all four solvers are compared for the first time, and new test cases are presented to provide a more complete basis by which the solvers can be judged for typical groundwater flow problems. Based on nine test cases, the following conclusions are reached: (1) SIP is actually as efficient as ICCG for some of the published, linear, two-dimensional test cases that were reportedly solved much more efficiently by ICCG; (2) SIP is more efficient than other published comparisons would indicate when common convergence criteria are used; and (3) for problems that are three-dimensional, nonlinear, or both, and for which common convergence criteria are used, SIP is often more efficient than ICCG, and is sometimes more efficient than MICCG.
3D DC Resistivity Inversion with Topography Based on Regularized Conjugate Gradient Method
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Jian-ke Qiang
2013-01-01
Full Text Available During the past decades, we observed a strong interest in 3D DC resistivity inversion and imaging with complex topography. In this paper, we implemented 3D DC resistivity inversion based on regularized conjugate gradient method with FEM. The Fréchet derivative is assembled with the electric potential in order to speed up the inversion process based on the reciprocity theorem. In this study, we also analyzed the sensitivity of the electric potential on the earth’s surface to the conductivity in each cell underground and introduced an optimized weighting function to produce new sensitivity matrix. The synthetic model study shows that this optimized weighting function is helpful to improve the resolution of deep anomaly. By incorporating topography into inversion, the artificial anomaly which is actually caused by topography can be eliminated. As a result, this algorithm potentially can be applied to process the DC resistivity data collected in mountain area. Our synthetic model study also shows that the convergence and computation speed are very stable and fast.
Optimization of gadolinium burnable poison loading by the conjugate gradients method
International Nuclear Information System (INIS)
Drumm, C.R.
1984-01-01
Improved use of burnable poison is suggested for pressurized water reactors (PWR's) to insure a sufficiently negative moderator temperature coefficient of reactivity for extended burnup cycles and low leakage refueling patterns. The use of gadolinium as a burnable poison can lead to large axial fluctuations in the power distribution through the cycle. The goal of this work is to determine the optimal axial distribution of gadolinium burnable poison in a PWR to overcome the axial fluctuations, yielding an improved power distribution. The conjugate gradients optimization method is used in this work because of the high degree of nonlinearity of the problem. The neutron diffusion and depletion equations are solved for a one-dimensional one-group core model. The state variables are the flux, the critical soluble boron concentration, and the burnup. The control variables are the number of gadolinium pins per assembly and the beginning-of-cycle gadolinium concentration, which determine the gadolinium cross section. Two separate objectives are considered: 1) to minimize the power peaking factor, which will minimize the capital cost of the plant; and 2) to maximize the cycle length, which will minimize the fuel cost for the plant. It is shown in this work that optimizing the gadolinium distribution can yield an improved power distribution
International Nuclear Information System (INIS)
Biffle, J.H.
1991-01-01
1 - Description of program or function: JAC is a two-dimensional finite element program for solving large deformation, temperature dependent, quasi-static mechanics problems with the nonlinear conjugate gradient (CG) technique. Either plane strain or axisymmetric geometry may be used with material descriptions which include temperature dependent elastic-plastic, temperature dependent secondary creep, and isothermal soil models. The nonlinear effects examined include material and geometric nonlinearities due to large rotations, large strains, and surface which slide relative to one another. JAC is vectorized to perform efficiently on the Cray1 computer. A restart capability is included. 2 - Method of solution: The nonlinear conjugate gradient method is employed in a two-dimensional plane strain or axisymmetric setting with various techniques for accelerating convergence. Sliding interface conditions are also implemented. A four-node Lagrangian uniform strain element is used with orthogonal hourglass viscosity to control the zero energy modes. Three sets of continuum equations are needed - kinematic statements, constitutive equations, and equations of equilibrium - to describe the deformed configuration of the body. 3 - Restrictions on the complexity of the problem - Maxima of: 10 load and solution control functions, 4 materials. The strain rate is assumed constant over a time interval. Current large rotation theory is applicable to a maximum shear strain of 1.0. JAC should be used with caution for large shear strains. Problem size is limited only by available memory
Experience with the Incomplete Cholesky Conjugate Gradient method in a diffusion code
International Nuclear Information System (INIS)
Hoebel, W.
1985-01-01
For the numerical solution of sparse systems of linear equations arising from finite difference approximation of the multidimensional neutron diffusion equation fast methods are needed. Effective algorithms for scalar computers may not be likewise suitable on vector computers. In the improved version DIXY2 of the Karlsruhe two-dimensional neutron diffusion code for rectangular geometries an Incomplete Cholesky Conjugate Gradient (ICCG) algorithm has been combined with the originally implemented Cyclically Reduced 4-Lines SOR (CR4LSOR) inner iteration method. The combined procedure is automatically activated for slowly converging applications, thus leading to a drastic reduction of iterations as well as CPU-times on a scalar computer. In a follow-up benchmark study necessary modifications to ICCG and CR4LSOR for their use on a vector computer were investigated. It was found that a modified preconditioning for the ICCG algorithm restricted to the block diagonal matrix is an effective method both on scalar and vector computers. With a splitting of the 9-band-matrix in two triangular Cholesky matrices necessary inversions are performed on a scalar machine by recursive forward and backward substitutions. On vector computers an additional factorization of the triangular matrices into four bidiagonal matrices enables Buneman reduction and the recursive inversion is restricted to a small system. A similar strategy can be realized with CR4LSOR if the unvectorizable Gauss-Seidel iteration is replaced by Double Jacobi and Buneman technique for a vector computer. Compared to single line blocking over the original mesh the cyclical 4-lines reduction of the DIXY inner iteration scheme reduces numbers of iterations and CPU-times considerably
Experience with the incomplete Cholesky conjugate gradient method in a diffusion code
International Nuclear Information System (INIS)
Hoebel, W.
1986-01-01
For the numerical solution of sparse systems of linear equations arising from the finite difference approximation of the multidimensional neutron diffusion equation, fast methods are needed. Effective algorithms for scalar computers may not be likewise suitable on vector computers. In the improved version (DIXY2) of the Karlsruhe two-dimensional neutron diffusion code for rectangular geometries, an incomplete Cholesky conjugate gradient (ICCG) algorithm has been combined with the originally implemented cyclically reduced four-line successive overrelaxation (CR4LSOR) inner iteration method. The combined procedure is automatically activated for slowly converging applications, thus leading to a drastic reduction of iterations as well as CPU times on a scalar computer. In a follow-up benchmark study, necessary modifications to ICCG and CR4LSOR for use on a vector computer were investigated. It was found that a modified preconditioning for the ICCG algorithm restricted to the block diagonal matrix is an effective method both on scalar and vector computers. With a splitting of the nine-band matrix in two triangular Cholesky matrices, necessary inversions are performed on a scalar machine by recursive forward and backward substitutions. On vector computers an additional factorization of the triangular matrices into four bidiagonal matrices enables Buneman reduction, and the recursive inversion is restricted to a small system. A similar strategy can be realized with CR4LSOR if the unvectorizable Gauss-eidel iteration is replaced by Double Jacobi and Buneman techniques for a vector computer. Compared to single-line blocking over the original mesh, the cyclical four-line reduction of the DIXY inner iteration scheme reduces numbers of iterations and CPU times considerably
Conjugate gradient algorithms using multiple recursions
Energy Technology Data Exchange (ETDEWEB)
Barth, T.; Manteuffel, T.
1996-12-31
Much is already known about when a conjugate gradient method can be implemented with short recursions for the direction vectors. The work done in 1984 by Faber and Manteuffel gave necessary and sufficient conditions on the iteration matrix A, in order for a conjugate gradient method to be implemented with a single recursion of a certain form. However, this form does not take into account all possible recursions. This became evident when Jagels and Reichel used an algorithm of Gragg for unitary matrices to demonstrate that the class of matrices for which a practical conjugate gradient algorithm exists can be extended to include unitary and shifted unitary matrices. The implementation uses short double recursions for the direction vectors. This motivates the study of multiple recursion algorithms.
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.
Preconditioned conjugate-gradient methods for low-speed flow calculations
Ajmani, Kumud; Ng, Wing-Fai; Liou, Meng-Sing
1993-01-01
An investigation is conducted into the viability of using a generalized Conjugate Gradient-like method as an iterative solver to obtain steady-state solutions of very low-speed fluid flow problems. Low-speed flow at Mach 0.1 over a backward-facing step is chosen as a representative test problem. The unsteady form of the two dimensional, compressible Navier-Stokes equations is integrated in time using discrete time-steps. The Navier-Stokes equations are cast in an implicit, upwind finite-volume, flux split formulation. The new iterative solver is used to solve a linear system of equations at each step of the time-integration. Preconditioning techniques are used with the new solver to enhance the stability and convergence rate of the solver and are found to be critical to the overall success of the solver. A study of various preconditioners reveals that a preconditioner based on the Lower-Upper Successive Symmetric Over-Relaxation iterative scheme is more efficient than a preconditioner based on Incomplete L-U factorizations of the iteration matrix. The performance of the new preconditioned solver is compared with a conventional Line Gauss-Seidel Relaxation (LGSR) solver. Overall speed-up factors of 28 (in terms of global time-steps required to converge to a steady-state solution) and 20 (in terms of total CPU time on one processor of a CRAY-YMP) are found in favor of the new preconditioned solver, when compared with the LGSR solver.
Conjugate Gradient Algorithms For Manipulator Simulation
Fijany, Amir; Scheid, Robert E.
1991-01-01
Report discusses applicability of conjugate-gradient algorithms to computation of forward dynamics of robotic manipulators. Rapid computation of forward dynamics essential to teleoperation and other advanced robotic applications. Part of continuing effort to find algorithms meeting requirements for increased computational efficiency and speed. Method used for iterative solution of systems of linear equations.
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.
Directory of Open Access Journals (Sweden)
Shoubin Wang
2017-01-01
Full Text Available The compound variable inverse problem which comprises boundary temperature distribution and surface convective heat conduction coefficient of two-dimensional steady heat transfer system with inner heat source is studied in this paper applying the conjugate gradient method. The introduction of complex variable to solve the gradient matrix of the objective function obtains more precise inversion results. This paper applies boundary element method to solve the temperature calculation of discrete points in forward problems. The factors of measuring error and the number of measuring points zero error which impact the measurement result are discussed and compared with L-MM method in inverse problems. Instance calculation and analysis prove that the method applied in this paper still has good effectiveness and accuracy even if measurement error exists and the boundary measurement points’ number is reduced. The comparison indicates that the influence of error on the inversion solution can be minimized effectively using this method.
International Nuclear Information System (INIS)
Dinh Nho Hao; Nguyen Trung Thanh; Sahli, Hichem
2008-01-01
In this paper we consider a multi-dimensional inverse heat conduction problem with time-dependent coefficients in a box, which is well-known to be severely ill-posed, by a variational method. The gradient of the functional to be minimized is obtained by aids of an adjoint problem and the conjugate gradient method with a stopping rule is then applied to this ill-posed optimization problem. To enhance the stability and the accuracy of the numerical solution to the problem we apply this scheme to the discretized inverse problem rather than to the continuous one. The difficulties with large dimensions of discretized problems are overcome by a splitting method which only requires the solution of easy-to-solve one-dimensional problems. The numerical results provided by our method are very good and the techniques seem to be very promising.
Kim, Hwi; Min, Sung-Wook; Lee, Byoungho
2008-12-01
Geometrical optics analysis of the structural imperfection of retroreflection corner cubes is described. In the analysis, a geometrical optics model of six-beam reflection patterns generated by an imperfect retroreflection corner cube is developed, and its structural error extraction is formulated as a nonlinear optimization problem. The nonlinear conjugate gradient method is employed for solving the nonlinear optimization problem, and its detailed implementation is described. The proposed method of analysis is a mathematical basis for the nondestructive optical inspection of imperfectly fabricated retroreflection corner cubes.
MODIFIED ARMIJO RULE ON GRADIENT DESCENT AND CONJUGATE GRADIENT
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ZURAIDAH FITRIAH
2017-10-01
Full Text Available Armijo rule is an inexact line search method to determine step size in some descent method to solve unconstrained local optimization. Modified Armijo was introduced to increase the numerical performance of several descent algorithms that applying this method. The basic difference of Armijo and its modified are in existence of a parameter and estimating the parameter that is updated in every iteration. This article is comparing numerical solution and time of computation of gradient descent and conjugate gradient hybrid Gilbert-Nocedal (CGHGN that applying modified Armijo rule. From program implementation in Matlab 6, it's known that gradient descent was applying modified Armijo more effectively than CGHGN from one side: iteration needed to reach some norm of the gradient (input by the user. The amount of iteration was representing how long the step size of each algorithm in each iteration. In another side, time of computation has the same conclusion.
Error Estimation in Preconditioned Conjugate Gradients
Czech Academy of Sciences Publication Activity Database
Strakoš, Zdeněk; Tichý, Petr
2005-01-01
Roč. 45, - (2005), s. 789-817 ISSN 0006-3835 R&D Projects: GA AV ČR 1ET400300415; GA AV ČR KJB1030306 Institutional research plan: CEZ:AV0Z10300504 Keywords : preconditioned conjugate gradient method * error bounds * stopping criteria * evaluation of convergence * numerical stability * finite precision arithmetic * rounding errors Subject RIV: BA - General Mathematics Impact factor: 0.509, year: 2005
Conjugate gradient optimization programs for shuttle reentry
Powers, W. F.; Jacobson, R. A.; Leonard, D. A.
1972-01-01
Two computer programs for shuttle reentry trajectory optimization are listed and described. Both programs use the conjugate gradient method as the optimization procedure. The Phase 1 Program is developed in cartesian coordinates for a rotating spherical earth, and crossrange, downrange, maximum deceleration, total heating, and terminal speed, altitude, and flight path angle are included in the performance index. The programs make extensive use of subroutines so that they may be easily adapted to other atmospheric trajectory optimization problems.
International Nuclear Information System (INIS)
Wang, J.J.H.; Dubberley, J.R.
1989-01-01
Electromagnetic (EM) fields in a three-dimensional, arbitrarily shaped heterogeneous dielectric or biological body illuminated by a plane wave are computed by an iterative conjugate gradient method. The method is a generalized method of moments applied to the volume integral equation. Because no matrix is explicitly involved or stored, the present iterative method is capable of computing EM fields in objects an order of magnitude larger than those that can be handled by the conventional method of moments. Excellent numerical convergence is achieved. Perfect convergence to the result of the conventional moment method using the same basis and weighted with delta functions is consistently achieved in all the cases computed, indicating that these two algorithms (direct and interactive) are equivalent
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Bakhtawar Baluch
2017-01-01
Full Text Available A new modified three-term conjugate gradient (CG method is shown for solving the large scale optimization problems. The idea relates to the famous Polak-Ribière-Polyak (PRP formula. As the numerator of PRP plays a vital role in numerical result and not having the jamming issue, PRP method is not globally convergent. So, for the new three-term CG method, the idea is to use the PRP numerator and combine it with any good CG formula’s denominator that performs well. The new modification of three-term CG method possesses the sufficient descent condition independent of any line search. The novelty is that by using the Wolfe Powell line search the new modification possesses global convergence properties with convex and nonconvex functions. Numerical computation with the Wolfe Powell line search by using the standard test function of optimization shows the efficiency and robustness of the new modification.
International Nuclear Information System (INIS)
Wang Hua; Liu Feng; Crozier, Stuart; Xia Ling
2008-01-01
This paper presents a stabilized Bi-conjugate gradient algorithm (BiCGstab) that can significantly improve the performance of the impedance method, which has been widely applied to model low-frequency field induction phenomena in voxel phantoms. The improved impedance method offers remarkable computational advantages in terms of convergence performance and memory consumption over the conventional, successive over-relaxation (SOR)-based algorithm. The scheme has been validated against other numerical/analytical solutions on a lossy, multilayered sphere phantom excited by an ideal coil loop. To demonstrate the computational performance and application capability of the developed algorithm, the induced fields inside a human phantom due to a low-frequency hyperthermia device is evaluated. The simulation results show the numerical accuracy and superior performance of the method.
Wang, Hua; Liu, Feng; Xia, Ling; Crozier, Stuart
2008-11-21
This paper presents a stabilized Bi-conjugate gradient algorithm (BiCGstab) that can significantly improve the performance of the impedance method, which has been widely applied to model low-frequency field induction phenomena in voxel phantoms. The improved impedance method offers remarkable computational advantages in terms of convergence performance and memory consumption over the conventional, successive over-relaxation (SOR)-based algorithm. The scheme has been validated against other numerical/analytical solutions on a lossy, multilayered sphere phantom excited by an ideal coil loop. To demonstrate the computational performance and application capability of the developed algorithm, the induced fields inside a human phantom due to a low-frequency hyperthermia device is evaluated. The simulation results show the numerical accuracy and superior performance of the method.
On the Strong Convergence of a Sufficient Descent Polak-Ribière-Polyak Conjugate Gradient Method
Directory of Open Access Journals (Sweden)
Min Sun
2014-01-01
Full Text Available Recently, Zhang et al. proposed a sufficient descent Polak-Ribière-Polyak (SDPRP conjugate gradient method for large-scale unconstrained optimization problems and proved its global convergence in the sense that lim infk→∞∥∇f(xk∥=0 when an Armijo-type line search is used. In this paper, motivated by the line searches proposed by Shi et al. and Zhang et al., we propose two new Armijo-type line searches and show that the SDPRP method has strong convergence in the sense that limk→∞∥∇f(xk∥=0 under the two new line searches. Numerical results are reported to show the efficiency of the SDPRP with the new Armijo-type line searches in practical computation.
International Nuclear Information System (INIS)
Krishnamoorthy, Gautham
2017-01-01
Highlights: • The P_1 radiation model was interfaced with high performance linear solvers. • Pre-conditioned conjugate gradient (PC CG) method improved convergence by 50% • PC CG was more than 30 times faster than classical iterative methods. • The time to solution scaled linearly with increase in problem size employing PC CG. • Employing WSGGM with P_1 model compared reasonably well against benchmark data. - Abstract: The iterative convergence of the P_1 radiation model can be slow in optically thin scenarios when employing classical iterative methods. In order to remedy this shortcoming, an in-house P_1 radiation model was interfaced with high performance, scalable, linear solver libraries. Next, the accuracies of P_1 radiation model calculations was assessed by comparing its predictions against discrete ordinates (DO) model calculations for prototypical problems representative of modern combustion systems. Corresponding benchmark results were also included for comparison. Utilizing Pre-Conditioners (PC) to the Conjugate Gradients (CG) method, the convergence time of the P_1 radiation model reduced by a factor of 30 for modest problem sizes and a factor of 70 for larger sized problems when compared against classical Gauss Seidel sweeps. Further, PC provided 50% computational savings compared to employing CG in a standalone mode. The P_1 model calculation times were about 25–30% of the DO model calculation time. The time to solution also scaled linearly with an increase in problem size. The weighted sum of gray gases model employed in this study in conjunction with the P_1 model provided good agreement against benchmark data with L_2 error norms (defined relative to corresponding DO calculations) improving when isotropic intensities were prevalent.
Tavakoli, Behnoosh; Zhu, Quing
2013-01-01
Ultrasound-guided diffuse optical tomography (DOT) is a promising method for characterizing malignant and benign lesions in the female breast. We introduce a new two-step algorithm for DOT inversion in which the optical parameters are estimated with the global optimization method, genetic algorithm. The estimation result is applied as an initial guess to the conjugate gradient (CG) optimization method to obtain the absorption and scattering distributions simultaneously. Simulations and phantom experiments have shown that the maximum absorption and reduced scattering coefficients are reconstructed with less than 10% and 25% errors, respectively. This is in contrast with the CG method alone, which generates about 20% error for the absorption coefficient and does not accurately recover the scattering distribution. A new measure of scattering contrast has been introduced to characterize benign and malignant breast lesions. The results of 16 clinical cases reconstructed with the two-step method demonstrates that, on average, the absorption coefficient and scattering contrast of malignant lesions are about 1.8 and 3.32 times higher than the benign cases, respectively.
International Nuclear Information System (INIS)
Kim, Hyun Keol; Charette, Andre
2007-01-01
The Sensitivity Function-based Conjugate Gradient Method (SFCGM) is described. This method is used to solve the inverse problems of function estimation, such as the local maps of absorption and scattering coefficients, as applied to optical tomography for biomedical imaging. A highly scattering, absorbing, non-reflecting, non-emitting medium is considered here and simultaneous reconstructions of absorption and scattering coefficients inside the test medium are achieved with the proposed optimization technique, by using the exit intensity measured at boundary surfaces. The forward problem is solved with a discrete-ordinates finite-difference method on the framework of the frequency-domain full equation of radiative transfer. The modulation frequency is set to 600 MHz and the frequency data, obtained with the source modulation, is used as the input data. The inversion results demonstrate that the SFCGM can retrieve simultaneously the spatial distributions of optical properties inside the medium within a reasonable accuracy, by significantly reducing a cross-talk between inter-parameters. It is also observed that the closer-to-detector objects are better retrieved
Barkeshli, Kasra; Volakis, John L.
1991-01-01
The theoretical and computational aspects related to the application of the Conjugate Gradient FFT (CGFFT) method in computational electromagnetics are examined. The advantages of applying the CGFFT method to a class of large scale scattering and radiation problems are outlined. The main advantages of the method stem from its iterative nature which eliminates a need to form the system matrix (thus reducing the computer memory allocation requirements) and guarantees convergence to the true solution in a finite number of steps. Results are presented for various radiators and scatterers including thin cylindrical dipole antennas, thin conductive and resistive strips and plates, as well as dielectric cylinders. Solutions of integral equations derived on the basis of generalized impedance boundary conditions (GIBC) are also examined. The boundary conditions can be used to replace the profile of a material coating by an impedance sheet or insert, thus, eliminating the need to introduce unknown polarization currents within the volume of the layer. A general full wave analysis of 2-D and 3-D rectangular grooves and cavities is presented which will also serve as a reference for future work.
Directory of Open Access Journals (Sweden)
Shuang Rong
2015-12-01
Full Text Available Aiming to relieve the large amount of wind power curtailment during the heating period in the North China region, a thermal-electric decoupling (TED approach is proposed to both bring down the constraint of forced power output of combined heat and power plants and increase the electric load level during valley load times that assist the power grid in consuming more wind power. The operating principles of the thermal-electric decoupling approach is described, the mathematical model of its profits is developed, the constraint conditions of its operation are listed, also, an improved parallel conjugate gradient is utilized to bypass the saddle problem and accelerate the optimal speed. Numerical simulations are implemented and reveal an optimal allocation of TED which with a rated power of 280 MW and 185 MWh heat storage capacity are possible. This allocation of TED could bring approximately 16.9 billion Yuan of economic profit and consume more than 80% of the surplus wind energy which would be curtailed without the participation of TED. The results in this article verify the effectiveness of this method that could provide a referential guidance for thermal-electric decoupling system allocation in practice.
Jung, Youngkyoo; Samsonov, Alexey A; Bydder, Mark; Block, Walter F
2011-04-01
To remove phase inconsistencies between multiple echoes, an algorithm using a radial acquisition to provide inherent phase and magnitude information for self correction was developed. The information also allows simultaneous support for parallel imaging for multiple coil acquisitions. Without a separate field map acquisition, a phase estimate from each echo in multiple echo train was generated. When using a multiple channel coil, magnitude and phase estimates from each echo provide in vivo coil sensitivities. An algorithm based on the conjugate gradient method uses these estimates to simultaneously remove phase inconsistencies between echoes, and in the case of multiple coil acquisition, simultaneously provides parallel imaging benefits. The algorithm is demonstrated on single channel, multiple channel, and undersampled data. Substantial image quality improvements were demonstrated. Signal dropouts were completely removed and undersampling artifacts were well suppressed. The suggested algorithm is able to remove phase cancellation and undersampling artifacts simultaneously and to improve image quality of multiecho radial imaging, the important technique for fast three-dimensional MRI data acquisition. Copyright © 2011 Wiley-Liss, Inc.
An Introduction to the Conjugate Gradient Method that Even an Idiot Can Understand
1994-03-07
to Omar Ghattas, who taught me much of what I know about numerical methods, and provided me with extensive comments on the first draft of this article...Dongarra, Victor Eijkhout, Roldan Pozo, Charles Romine, and Henk van der Vorst, Templates for the solution of linear systems: Building blocks for iterative
On the use of rigid body modes in the deflated preconditioned conjugate gradient method
Jönsthövel, T.B.; Van Gijzen, M.B.; Vuik, C.; Scarpas, A.
2013-01-01
Large discontinuities in material properties, such as those encountered in composite materials, lead to ill-conditioned systems of linear equations. These discontinuities give rise to small eigenvalues that may negatively affect the convergence of iterative solution methods such as the
On the use of rigid body modes in the deflated preconditioned conjugate gradient method
Jönsthövel, T.B.; Van Gijzen, M.B.; Vuik, C.; Scarpas, A.
2011-01-01
Large discontinuities in material properties, such as encountered in composite materials, lead to ill-conditioned systems of linear equations. These discontinuities give rise to small eigenvalues that may negatively affect the convergence of iterative solution methods such as the Preconditioned
Jönsthövel, T.B.; Van Gijzen, M.B.; MacLachlan, S.; Vuik, C.; Scarpas, A.
2011-01-01
The demand for large FE meshes increases as parallel computing becomes the standard in FE simulations. Direct and iterative solution methods are used to solve the resulting linear systems. Many applications concern composite materials, which are characterized by large discontinuities in the material
A fast, preconditioned conjugate gradient Toeplitz solver
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.
Three-dimensional reconstruction from real data using a conjugate gradient-coupled dipole method
International Nuclear Information System (INIS)
Chaumet, Patrick C; Belkebir, Kamal
2009-01-01
The aim of the present work is to validate a full vectorial electromagnetic inverse scattering algorithm against experimental data. Data were provided courtesy of Institut Fresnel, Marseille, France. These data were carried out in an anechoic chamber and correspond to different canonical targets as well as one mysterious object which is known only by experimentalists who measured the associated scattered field. The inverse algorithm was first developed in the optical domain and is adapted herein to the microwave domain. It is an iterative approach where the parameter of interest, namely the relative permittivity distribution, is updated gradually by minimizing a cost function describing the discrepancy between data and those that would be obtained via a forward solver for the best available estimate of the relative permittivity. The forward solver is based on the coupled dipole method which was introduced in the seventies to study the scattering of light by non-spherical dielectric grains. The forward and inverse schemes are briefly described and various examples are presented that demonstrate the efficiency of the inverse algorithm
Ge, Lan; Kino, Aya; Lee, Daniel; Dharmakumar, Rohan; Carr, James C; Li, Debiao
2010-01-01
First-pass perfusion magnetic resonance imaging (MRI) is a promising technique for detecting ischemic heart disease. However, the diagnostic value of the method is limited by the low spatial coverage, resolution, signal-to-noise ratio (SNR), and cardiac motion-related image artifacts. A combination of sliding window and conjugate-gradient HighlY constrained back-PRojection reconstruction (SW-CG-HYPR) method has been proposed in healthy volunteer studies to reduce the acquisition window for each slice while maintaining the temporal resolution of 1 frame per heartbeat in myocardial perfusion MRI. This method allows for improved spatial coverage, resolution, and SNR. In this study, we use a controlled animal model to test whether the myocardial territory supplied by a stenotic coronary artery can be detected accurately by SW-CG-HYPR perfusion method under pharmacological stress. Results from 6 mongrel dogs (15-25 kg) studies demonstrate the feasibility of SW-CG-HYPR to detect regional perfusion defects. Using this method, the acquisition time per cardiac cycle was reduced by a factor of 4, and the spatial coverage was increased from 2 to 3 slices to 6 slices as compared with the conventional techniques including both turbo-Fast Low Angle Short (FLASH) and echoplanar imaging (EPI). The SNR of the healthy myocardium at peak enhancement with SW-CG-HYPR (12.68 ± 2.46) is significantly higher (P < 0.01) than the turbo-FLASH (8.65 ± 1.93) and EPI (5.48 ± 1.24). The spatial resolution of SW-CG-HYPR images is 1.2 × 1.2 × 8.0 mm, which is better than the turbo-FLASH (1.8 × 1.8 × 8.0 mm) and EPI (2.0 × 1.8 × 8.0 mm). Sliding-window CG-HYPR is a promising technique for myocardial perfusion MRI. This technique provides higher image quality with respect to significantly improved SNR and spatial resolution of the myocardial perfusion images, which might improve myocardial perfusion imaging in a clinical setting.
The Lanczos and Conjugate Gradient Algorithms in Finite Precision Arithmetic
Czech Academy of Sciences Publication Activity Database
Meurant, G.; Strakoš, Zdeněk
2006-01-01
Roč. 15, - (2006), s. 471-542 ISSN 0962-4929 R&D Projects: GA AV ČR 1ET400300415 Institutional research plan: CEZ:AV0Z10300504 Keywords : Lanczos method * conjugate gradient method * finite precision arithmetic * numerical stability * iterative methods Subject RIV: BA - General Mathematics
Experiments with conjugate gradient algorithms for homotopy curve tracking
Irani, Kashmira M.; Ribbens, Calvin J.; Watson, Layne T.; Kamat, Manohar P.; Walker, Homer F.
1991-01-01
There are algorithms for finding zeros or fixed points of nonlinear systems of equations that are globally convergent for almost all starting points, i.e., with probability one. The essence of all such algorithms is the construction of an appropriate homotopy map and then tracking some smooth curve in the zero set of this homotopy map. HOMPACK is a mathematical software package implementing globally convergent homotopy algorithms with three different techniques for tracking a homotopy zero curve, and has separate routines for dense and sparse Jacobian matrices. The HOMPACK algorithms for sparse Jacobian matrices use a preconditioned conjugate gradient algorithm for the computation of the kernel of the homotopy Jacobian matrix, a required linear algebra step for homotopy curve tracking. Here, variants of the conjugate gradient algorithm are implemented in the context of homotopy curve tracking and compared with Craig's preconditioned conjugate gradient method used in HOMPACK. The test problems used include actual large scale, sparse structural mechanics problems.
International Nuclear Information System (INIS)
Aruchunan, E.
2015-01-01
In this paper, we have examined the effectiveness of the quarter-sweep iteration concept on conjugate gradient normal residual (CGNR) iterative method by using composite Simpson's (CS) and finite difference (FD) discretization schemes in solving Fredholm integro-differential equations. For comparison purposes, Gauss- Seidel (GS) and the standard or full- and half-sweep CGNR methods namely FSCGNR and HSCGNR are also presented. To validate the efficacy of the proposed method, several analyses were carried out such as computational complexity and percentage reduction on the proposed and existing methods. (author)
Computing several eigenpairs of Hermitian problems by conjugate gradient iterations
International Nuclear Information System (INIS)
Ovtchinnikov, E.E.
2008-01-01
The paper is concerned with algorithms for computing several extreme eigenpairs of Hermitian problems based on the conjugate gradient method. We analyse computational strategies employed by various algorithms of this kind reported in the literature and identify their limitations. Our criticism is illustrated by numerical tests on a set of problems from electronic structure calculations and acoustics
Conjugate-Gradient Algorithms For Dynamics Of Manipulators
Fijany, Amir; Scheid, Robert E.
1993-01-01
Algorithms for serial and parallel computation of forward dynamics of multiple-link robotic manipulators by conjugate-gradient method developed. Parallel algorithms have potential for speedup of computations on multiple linked, specialized processors implemented in very-large-scale integrated circuits. Such processors used to stimulate dynamics, possibly faster than in real time, for purposes of planning and control.
Bates, Kevin R.; Daniels, Andrew D.; Scuseria, Gustavo E.
1998-01-01
We report a comparison of two linear-scaling methods which avoid the diagonalization bottleneck of traditional electronic structure algorithms. The Chebyshev expansion method (CEM) is implemented for carbon tight-binding calculations of large systems and its memory and timing requirements compared to those of our previously implemented conjugate gradient density matrix search (CG-DMS). Benchmark calculations are carried out on icosahedral fullerenes from C60 to C8640 and the linear scaling memory and CPU requirements of the CEM demonstrated. We show that the CPU requisites of the CEM and CG-DMS are similar for calculations with comparable accuracy.
PET regularization by envelope guided conjugate gradients
International Nuclear Information System (INIS)
Kaufman, L.; Neumaier, A.
1996-01-01
The authors propose a new way to iteratively solve large scale ill-posed problems and in particular the image reconstruction problem in positron emission tomography by exploiting the relation between Tikhonov regularization and multiobjective optimization to obtain iteratively approximations to the Tikhonov L-curve and its corner. Monitoring the change of the approximate L-curves allows us to adjust the regularization parameter adaptively during a preconditioned conjugate gradient iteration, so that the desired solution can be reconstructed with a small number of iterations
Conjugate gradient heat bath for ill-conditioned actions.
Ceriotti, Michele; Bussi, Giovanni; Parrinello, Michele
2007-08-01
We present a method for performing sampling from a Boltzmann distribution of an ill-conditioned quadratic action. This method is based on heat-bath thermalization along a set of conjugate directions, generated via a conjugate-gradient procedure. The resulting scheme outperforms local updates for matrices with very high condition number, since it avoids the slowing down of modes with lower eigenvalue, and has some advantages over the global heat-bath approach, compared to which it is more stable and allows for more freedom in devising case-specific optimizations.
Two New PRP Conjugate Gradient Algorithms for Minimization Optimization Models.
Directory of Open Access Journals (Sweden)
Gonglin Yuan
Full Text Available Two new PRP conjugate Algorithms are proposed in this paper based on two modified PRP conjugate gradient methods: the first algorithm is proposed for solving unconstrained optimization problems, and the second algorithm is proposed for solving nonlinear equations. The first method contains two aspects of information: function value and gradient value. The two methods both possess some good properties, as follows: 1 βk ≥ 0 2 the search direction has the trust region property without the use of any line search method 3 the search direction has sufficient descent property without the use of any line search method. Under some suitable conditions, we establish the global convergence of the two algorithms. We conduct numerical experiments to evaluate our algorithms. The numerical results indicate that the first algorithm is effective and competitive for solving unconstrained optimization problems and that the second algorithm is effective for solving large-scale nonlinear equations.
Two New PRP Conjugate Gradient Algorithms for Minimization Optimization Models.
Yuan, Gonglin; Duan, Xiabin; Liu, Wenjie; Wang, Xiaoliang; Cui, Zengru; Sheng, Zhou
2015-01-01
Two new PRP conjugate Algorithms are proposed in this paper based on two modified PRP conjugate gradient methods: the first algorithm is proposed for solving unconstrained optimization problems, and the second algorithm is proposed for solving nonlinear equations. The first method contains two aspects of information: function value and gradient value. The two methods both possess some good properties, as follows: 1) βk ≥ 0 2) the search direction has the trust region property without the use of any line search method 3) the search direction has sufficient descent property without the use of any line search method. Under some suitable conditions, we establish the global convergence of the two algorithms. We conduct numerical experiments to evaluate our algorithms. The numerical results indicate that the first algorithm is effective and competitive for solving unconstrained optimization problems and that the second algorithm is effective for solving large-scale nonlinear equations.
Momentum-weighted conjugate gradient descent algorithm for gradient coil optimization.
Lu, Hanbing; Jesmanowicz, Andrzej; Li, Shi-Jiang; Hyde, James S
2004-01-01
MRI gradient coil design is a type of nonlinear constrained optimization. A practical problem in transverse gradient coil design using the conjugate gradient descent (CGD) method is that wire elements move at different rates along orthogonal directions (r, phi, z), and tend to cross, breaking the constraints. A momentum-weighted conjugate gradient descent (MW-CGD) method is presented to overcome this problem. This method takes advantage of the efficiency of the CGD method combined with momentum weighting, which is also an intrinsic property of the Levenberg-Marquardt algorithm, to adjust step sizes along the three orthogonal directions. A water-cooled, 12.8 cm inner diameter, three axis torque-balanced gradient coil for rat imaging was developed based on this method, with an efficiency of 2.13, 2.08, and 4.12 mT.m(-1).A(-1) along X, Y, and Z, respectively. Experimental data demonstrate that this method can improve efficiency by 40% and field uniformity by 27%. This method has also been applied to the design of a gradient coil for the human brain, employing remote current return paths. The benefits of this design include improved gradient field uniformity and efficiency, with a shorter length than gradient coil designs using coaxial return paths. Copyright 2003 Wiley-Liss, Inc.
Minimizing inner product data dependencies in conjugate gradient iteration
Vanrosendale, J.
1983-01-01
The amount of concurrency available in conjugate gradient iteration is limited by the summations required in the inner product computations. The inner product of two vectors of length N requires time c log(N), if N or more processors are available. This paper describes an algebraic restructuring of the conjugate gradient algorithm which minimizes data dependencies due to inner product calculations. After an initial start up, the new algorithm can perform a conjugate gradient iteration in time c*log(log(N)).
International Nuclear Information System (INIS)
Biffle, J.H.; Blanford, M.L.
1994-05-01
JAC2D is a two-dimensional finite element program designed to solve quasi-static nonlinear mechanics problems. A set of continuum equations describes the nonlinear mechanics involving large rotation and strain. A nonlinear conjugate gradient method is used to solve the equations. The method is implemented in a two-dimensional setting with various methods for accelerating convergence. Sliding interface logic is also implemented. A four-node Lagrangian uniform strain element is used with hourglass stiffness to control the zero-energy modes. This report documents the elastic and isothermal elastic/plastic material model. Other material models, documented elsewhere, are also available. The program is vectorized for efficient performance on Cray computers. Sample problems described are the bending of a thin beam, the rotation of a unit cube, and the pressurization and thermal loading of a hollow sphere
International Nuclear Information System (INIS)
Biffle, J.H.
1993-02-01
JAC3D is a three-dimensional finite element program designed to solve quasi-static nonlinear mechanics problems. A set of continuum equations describes the nonlinear mechanics involving large rotation and strain. A nonlinear conjugate gradient method is used to solve the equation. The method is implemented in a three-dimensional setting with various methods for accelerating convergence. Sliding interface logic is also implemented. An eight-node Lagrangian uniform strain element is used with hourglass stiffness to control the zero-energy modes. This report documents the elastic and isothermal elastic-plastic material model. Other material models, documented elsewhere, are also available. The program is vectorized for efficient performance on Cray computers. Sample problems described are the bending of a thin beam, the rotation of a unit cube, and the pressurization and thermal loading of a hollow sphere
International Nuclear Information System (INIS)
Yoon, Jong Seon; Choi, Hyoung Gwon; Jeon, Byoung Jin; Jung, Hye Dong
2016-01-01
A parallel algorithm of bi-conjugate gradient method was developed based on CUDA for parallel computation of the incompressible Navier-Stokes equations. The governing equations were discretized using splitting P2P1 finite element method. Asymmetric stenotic flow problem was solved to validate the proposed algorithm, and then the parallel performance of the GPU was examined by measuring the elapsed times. Further, the GPU performance for sparse matrix-vector multiplication was also investigated with a matrix of fluid-structure interaction problem. A kernel was generated to simultaneously compute the inner product of each row of sparse matrix and a vector. In addition, the kernel was optimized to improve the performance by using both parallel reduction and memory coalescing. In the kernel construction, the effect of warp on the parallel performance of the present CUDA was also examined. The present GPU computation was more than 7 times faster than the single CPU by double precision.
Energy Technology Data Exchange (ETDEWEB)
Yoon, Jong Seon; Choi, Hyoung Gwon [Seoul Nat’l Univ. of Science and Technology, Seoul (Korea, Republic of); Jeon, Byoung Jin [Yonsei Univ., Seoul (Korea, Republic of); Jung, Hye Dong [Korea Electronics Technology Institute, Seongnam (Korea, Republic of)
2016-09-15
A parallel algorithm of bi-conjugate gradient method was developed based on CUDA for parallel computation of the incompressible Navier-Stokes equations. The governing equations were discretized using splitting P2P1 finite element method. Asymmetric stenotic flow problem was solved to validate the proposed algorithm, and then the parallel performance of the GPU was examined by measuring the elapsed times. Further, the GPU performance for sparse matrix-vector multiplication was also investigated with a matrix of fluid-structure interaction problem. A kernel was generated to simultaneously compute the inner product of each row of sparse matrix and a vector. In addition, the kernel was optimized to improve the performance by using both parallel reduction and memory coalescing. In the kernel construction, the effect of warp on the parallel performance of the present CUDA was also examined. The present GPU computation was more than 7 times faster than the single CPU by double precision.
New preconditioned conjugate gradient algorithms for nonlinear unconstrained optimization problems
International Nuclear Information System (INIS)
Al-Bayati, A.; Al-Asadi, N.
1997-01-01
This paper presents two new predilection conjugate gradient algorithms for nonlinear unconstrained optimization problems and examines their computational performance. Computational experience shows that the new proposed algorithms generally imp lone the efficiency of Nazareth's [13] preconditioned conjugate gradient algorithm. (authors). 16 refs., 1 tab
Conjugate gradient coupled with multigrid for an indefinite problem
Gozani, J.; Nachshon, A.; Turkel, E.
1984-01-01
An iterative algorithm for the Helmholtz equation is presented. This scheme was based on the preconditioned conjugate gradient method for the normal equations. The preconditioning is one cycle of a multigrid method for the discrete Laplacian. The smoothing algorithm is red-black Gauss-Seidel and is constructed so it is a symmetric operator. The total number of iterations needed by the algorithm is independent of h. By varying the number of grids, the number of iterations depends only weakly on k when k(3)h(2) is constant. Comparisons with a SSOR preconditioner are presented.
Solving large mixed linear models using preconditioned conjugate gradient iteration.
Strandén, I; Lidauer, M
1999-12-01
Continuous evaluation of dairy cattle with a random regression test-day model requires a fast solving method and algorithm. A new computing technique feasible in Jacobi and conjugate gradient based iterative methods using iteration on data is presented. In the new computing technique, the calculations in multiplication of a vector by a matrix were recorded to three steps instead of the commonly used two steps. The three-step method was implemented in a general mixed linear model program that used preconditioned conjugate gradient iteration. Performance of this program in comparison to other general solving programs was assessed via estimation of breeding values using univariate, multivariate, and random regression test-day models. Central processing unit time per iteration with the new three-step technique was, at best, one-third that needed with the old technique. Performance was best with the test-day model, which was the largest and most complex model used. The new program did well in comparison to other general software. Programs keeping the mixed model equations in random access memory required at least 20 and 435% more time to solve the univariate and multivariate animal models, respectively. Computations of the second best iteration on data took approximately three and five times longer for the animal and test-day models, respectively, than did the new program. Good performance was due to fast computing time per iteration and quick convergence to the final solutions. Use of preconditioned conjugate gradient based methods in solving large breeding value problems is supported by our findings.
Numerical Simulation of Solid Combustion with a Robust Conjugate-Gradient Solution for Pressure
National Research Council Canada - National Science Library
Wang, Yi-Zun
2002-01-01
A Bi-Conjugate Gradient method (Bi-CGSTAB) is studied and tested for solid combustion in which the gas and solid phases are coupled by a set of conditions describing mass, momentum and heat transport across the interface...
International Nuclear Information System (INIS)
Gelebart, Lionel; Mondon-Cancel, Romain
2013-01-01
FFT-based methods are used to solve the problem of a heterogeneous unit-cell submitted to periodic boundary conditions, which is of a great interest in the context of numerical homogenization. Recently (in 2010), Brisard and Zeman proposed simultaneously to use Conjugate Gradient based solvers in order to improve the convergence properties (when compared to the basic scheme, proposed initially in 1994). The purpose of the paper is to extend this idea to the case of non-linear behaviors. The proposed method is based on a Newton-Raphson algorithm and can be applied to various kinds of behaviors (time dependant or independent, with or without internal variables) through a conventional integration procedure as used in finite element codes. It must be pointed out that this approach is fundamentally different from the traditional FFT-based approaches which rely on a fixed-point algorithm (e.g. basic scheme, Eyre and Milton accelerated scheme, Augmented Lagrangian scheme, etc.). The method is compared to the basic scheme on the basis of a simple application (a linear elastic spherical inclusion within a non-linear elastic matrix): a low sensitivity to the reference material and an improved efficiency, for a soft or a stiff inclusion, are observed. At first proposed for a prescribed macroscopic strain, the method is then extended to mixed loadings. (authors)
Parallel preconditioned conjugate gradient algorithm applied to neutron diffusion problem
International Nuclear Information System (INIS)
Majumdar, A.; Martin, W.R.
1992-01-01
Numerical solution of the neutron diffusion problem requires solving a linear system of equations such as Ax = b, where A is an n x n symmetric positive definite (SPD) matrix; x and b are vectors with n components. The preconditioned conjugate gradient (PCG) algorithm is an efficient iterative method for solving such a linear system of equations. In this paper, the authors describe the implementation of a parallel PCG algorithm on a shared memory machine (BBN TC2000) and on a distributed workstation (IBM RS6000) environment created by the parallel virtual machine parallelization software
Adaptive Regularization of Neural Networks Using Conjugate Gradient
DEFF Research Database (Denmark)
Goutte, Cyril; Larsen, Jan
1998-01-01
Andersen et al. (1997) and Larsen et al. (1996, 1997) suggested a regularization scheme which iteratively adapts regularization parameters by minimizing validation error using simple gradient descent. In this contribution we present an improved algorithm based on the conjugate gradient technique........ Numerical experiments with feedforward neural networks successfully demonstrate improved generalization ability and lower computational cost...
International Nuclear Information System (INIS)
Yang, Xiaoli; Hofmann, Ralf; Dapp, Robin; Van de Kamp, Thomas; Rolo, Tomy dos Santos; Xiao, Xianghui; Moosmann, Julian; Kashef, Jubin; Stotzka, Rainer
2015-01-01
High-resolution, three-dimensional (3D) imaging of soft tissues requires the solution of two inverse problems: phase retrieval and the reconstruction of the 3D image from a tomographic stack of two-dimensional (2D) projections. The number of projections per stack should be small to accommodate fast tomography of rapid processes and to constrain X-ray radiation dose to optimal levels to either increase the duration o fin vivo time-lapse series at a given goal for spatial resolution and/or the conservation of structure under X-ray irradiation. In pursuing the 3D reconstruction problem in the sense of compressive sampling theory, we propose to reduce the number of projections by applying an advanced algebraic technique subject to the minimisation of the total variation (TV) in the reconstructed slice. This problem is formulated in a Lagrangian multiplier fashion with the parameter value determined by appealing to a discrete L-curve in conjunction with a conjugate gradient method. The usefulness of this reconstruction modality is demonstrated for simulated and in vivo data, the latter acquired in parallel-beam imaging experiments using synchrotron radiation
Yang, Xiaoli; Hofmann, Ralf; Dapp, Robin; van de Kamp, Thomas; dos Santos Rolo, Tomy; Xiao, Xianghui; Moosmann, Julian; Kashef, Jubin; Stotzka, Rainer
2015-03-09
High-resolution, three-dimensional (3D) imaging of soft tissues requires the solution of two inverse problems: phase retrieval and the reconstruction of the 3D image from a tomographic stack of two-dimensional (2D) projections. The number of projections per stack should be small to accommodate fast tomography of rapid processes and to constrain X-ray radiation dose to optimal levels to either increase the duration of in vivo time-lapse series at a given goal for spatial resolution and/or the conservation of structure under X-ray irradiation. In pursuing the 3D reconstruction problem in the sense of compressive sampling theory, we propose to reduce the number of projections by applying an advanced algebraic technique subject to the minimisation of the total variation (TV) in the reconstructed slice. This problem is formulated in a Lagrangian multiplier fashion with the parameter value determined by appealing to a discrete L-curve in conjunction with a conjugate gradient method. The usefulness of this reconstruction modality is demonstrated for simulated and in vivo data, the latter acquired in parallel-beam imaging experiments using synchrotron radiation.
Improved Conjugate Gradient Bundle Adjustment of Dunhuang Wall Painting Images
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.
IMPROVED CONJUGATE GRADIENT BUNDLE ADJUSTMENT OF DUNHUANG WALL PAINTING IMAGES
Directory of Open Access Journals (Sweden)
K. Hu
2017-09-01
Full Text Available 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.
Liu, Youshan; Teng, Jiwen; Xu, Tao; Badal, José; Liu, Qinya; Zhou, Bing
2017-05-01
We carry out full waveform inversion (FWI) in time domain based on an alternative frequency-band selection strategy that allows us to implement the method with success. This strategy aims at decomposing the seismic data within partially overlapped frequency intervals by carrying out a concatenated treatment of the wavelet to largely avoid redundant frequency information to adapt to wavelength or wavenumber coverage. A pertinent numerical test proves the effectiveness of this strategy. Based on this strategy, we comparatively analyze the effects of update parameters for the nonlinear conjugate gradient (CG) method and step-length formulas on the multiscale FWI through several numerical tests. The investigations of up to eight versions of the nonlinear CG method with and without Gaussian white noise make clear that the HS (Hestenes and Stiefel in J Res Natl Bur Stand Sect 5:409-436, 1952), CD (Fletcher in Practical methods of optimization vol. 1: unconstrained optimization, Wiley, New York, 1987), and PRP (Polak and Ribière in Revue Francaise Informat Recherche Opertionelle, 3e Année 16:35-43, 1969; Polyak in USSR Comput Math Math Phys 9:94-112, 1969) versions are more efficient among the eight versions, while the DY (Dai and Yuan in SIAM J Optim 10:177-182, 1999) version always yields inaccurate result, because it overestimates the deeper parts of the model. The application of FWI algorithms using distinct step-length formulas, such as the direct method ( Direct), the parabolic search method ( Search), and the two-point quadratic interpolation method ( Interp), proves that the Interp is more efficient for noise-free data, while the Direct is more efficient for Gaussian white noise data. In contrast, the Search is less efficient because of its slow convergence. In general, the three step-length formulas are robust or partly insensitive to Gaussian white noise and the complexity of the model. When the initial velocity model deviates far from the real model or the
Implementing the conjugate gradient algorithm on multi-core systems
Wiggers, W.A.; Bakker, Vincent; Kokkeler, Andre B.J.; Smit, Gerardus Johannes Maria; Nurmi, J.; Takala, J.; Vainio, O.
2007-01-01
In linear solvers, like the conjugate gradient algorithm, sparse-matrix vector multiplication is an important kernel. Due to the sparseness of the matrices, the solver runs relatively slow. For digital optical tomography (DOT), a large set of linear equations have to be solved which currently takes
Parallel conjugate gradient algorithms for manipulator dynamic simulation
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).
Fourier domain preconditioned conjugate gradient algorithm for atmospheric tomography.
Yang, Qiang; Vogel, Curtis R; Ellerbroek, Brent L
2006-07-20
By 'atmospheric tomography' we mean the estimation of a layered atmospheric turbulence profile from measurements of the pupil-plane phase (or phase gradients) corresponding to several different guide star directions. We introduce what we believe to be a new Fourier domain preconditioned conjugate gradient (FD-PCG) algorithm for atmospheric tomography, and we compare its performance against an existing multigrid preconditioned conjugate gradient (MG-PCG) approach. Numerical results indicate that on conventional serial computers, FD-PCG is as accurate and robust as MG-PCG, but it is from one to two orders of magnitude faster for atmospheric tomography on 30 m class telescopes. Simulations are carried out for both natural guide stars and for a combination of finite-altitude laser guide stars and natural guide stars to resolve tip-tilt uncertainty.
Conjugated polymer nanoparticles, methods of using, and methods of making
Habuchi, Satoshi
2017-03-16
Embodiments of the present disclosure provide for conjugated polymer nanoparticle, method of making conjugated polymer nanoparticles, method of using conjugated polymer nanoparticle, polymers, and the like.
Conjugated polymer nanoparticles, methods of using, and methods of making
Habuchi, Satoshi; Piwonski, Hubert Marek; Michinobu, Tsuyoshi
2017-01-01
Embodiments of the present disclosure provide for conjugated polymer nanoparticle, method of making conjugated polymer nanoparticles, method of using conjugated polymer nanoparticle, polymers, and the like.
Conjugate gradient minimisation approach to generating holographic traps for ultracold atoms.
Harte, Tiffany; Bruce, Graham D; Keeling, Jonathan; Cassettari, Donatella
2014-11-03
Direct minimisation of a cost function can in principle provide a versatile and highly controllable route to computational hologram generation. Here we show that the careful design of cost functions, combined with numerically efficient conjugate gradient minimisation, establishes a practical method for the generation of holograms for a wide range of target light distributions. This results in a guided optimisation process, with a crucial advantage illustrated by the ability to circumvent optical vortex formation during hologram calculation. We demonstrate the implementation of the conjugate gradient method for both discrete and continuous intensity distributions and discuss its applicability to optical trapping of ultracold atoms.
Inelastic scattering with Chebyshev polynomials and preconditioned conjugate gradient minimization.
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.
Pixel-based OPC optimization based on conjugate gradients.
Ma, Xu; Arce, Gonzalo R
2011-01-31
Optical proximity correction (OPC) methods are resolution enhancement techniques (RET) used extensively in the semiconductor industry to improve the resolution and pattern fidelity of optical lithography. In pixel-based OPC (PBOPC), the mask is divided into small pixels, each of which is modified during the optimization process. Two critical issues in PBOPC are the required computational complexity of the optimization process, and the manufacturability of the optimized mask. Most current OPC optimization methods apply the steepest descent (SD) algorithm to improve image fidelity augmented by regularization penalties to reduce the complexity of the mask. Although simple to implement, the SD algorithm converges slowly. The existing regularization penalties, however, fall short in meeting the mask rule check (MRC) requirements often used in semiconductor manufacturing. This paper focuses on developing OPC optimization algorithms based on the conjugate gradient (CG) method which exhibits much faster convergence than the SD algorithm. The imaging formation process is represented by the Fourier series expansion model which approximates the partially coherent system as a sum of coherent systems. In order to obtain more desirable manufacturability properties of the mask pattern, a MRC penalty is proposed to enlarge the linear size of the sub-resolution assistant features (SRAFs), as well as the distances between the SRAFs and the main body of the mask. Finally, a projection method is developed to further reduce the complexity of the optimized mask pattern.
Chowdhary, J; Keyes, T
2002-02-01
Instantaneous normal modes (INM's) are calculated during a conjugate-gradient (CG) descent of the potential energy landscape, starting from an equilibrium configuration of a liquid or crystal. A small number (approximately equal to 4) of CG steps removes all the Im-omega modes in the crystal and leaves the liquid with diffusive Im-omega which accurately represent the self-diffusion constant D. Conjugate gradient filtering appears to be a promising method, applicable to any system, of obtaining diffusive modes and facilitating INM theory of D. The relation of the CG-step dependent INM quantities to the landscape and its saddles is discussed.
MILC staggered conjugate gradient performance on Intel KNL
DeTar, Carleton; Doerfler, Douglas; Gottlieb, Steven; Jha, Ashish; Kalamkar, Dhiraj; Li, Ruizi; Toussaint, Doug
2016-01-01
We review our work done to optimize the staggered conjugate gradient (CG) algorithm in the MILC code for use with the Intel Knights Landing (KNL) architecture. KNL is the second gener- ation Intel Xeon Phi processor. It is capable of massive thread parallelism, data parallelism, and high on-board memory bandwidth and is being adopted in supercomputing centers for scientific research. The CG solver consumes the majority of time in production running, so we have spent most of our effort on it. ...
A partitioned conjugate gradient algorithm for lattice Green functions
International Nuclear Information System (INIS)
Bowler, K.C.; Kenway, R.D.; Pawley, G.S.; Wallace, D.J.
1984-01-01
Partitioning reduces by one the dimensionality of the lattice on which a propagator need be calculated using, for example, the conjugate gradient algorithm. Thus the quark propagator in lattice QCD may be determined by a computation on a single spatial hyperplane. For free fermions on a 16 3 x N lattice 2N-bit accuracy in the propagator is required to avoid rounding errors. (orig.)
A constrained conjugate gradient algorithm for computed tomography
Energy Technology Data Exchange (ETDEWEB)
Azevedo, S.G.; Goodman, D.M. [Lawrence Livermore National Lab., CA (United States)
1994-11-15
Image reconstruction from projections of x-ray, gamma-ray, protons and other penetrating radiation is a well-known problem in a variety of fields, and is commonly referred to as computed tomography (CT). Various analytical and series expansion methods of reconstruction and been used in the past to provide three-dimensional (3D) views of some interior quantity. The difficulties of these approaches lie in the cases where (a) the number of views attainable is limited, (b) the Poisson (or other) uncertainties are significant, (c) quantifiable knowledge of the object is available, but not implementable, or (d) other limitations of the data exist. We have adapted a novel nonlinear optimization procedure developed at LLNL to address limited-data image reconstruction problems. The technique, known as nonlinear least squares with general constraints or constrained conjugate gradients (CCG), has been successfully applied to a number of signal and image processing problems, and is now of great interest to the image reconstruction community. Previous applications of this algorithm to deconvolution problems and x-ray diffraction images for crystallography have shown the great promise.
Solving large test-day models by iteration on data and preconditioned conjugate gradient.
Lidauer, M; Strandén, I; Mäntysaari, E A; Pösö, J; Kettunen, A
1999-12-01
A preconditioned conjugate gradient method was implemented into an iteration on a program for data estimation of breeding values, and its convergence characteristics were studied. An algorithm was used as a reference in which one fixed effect was solved by Gauss-Seidel method, and other effects were solved by a second-order Jacobi method. Implementation of the preconditioned conjugate gradient required storing four vectors (size equal to number of unknowns in the mixed model equations) in random access memory and reading the data at each round of iteration. The preconditioner comprised diagonal blocks of the coefficient matrix. Comparison of algorithms was based on solutions of mixed model equations obtained by a single-trait animal model and a single-trait, random regression test-day model. Data sets for both models used milk yield records of primiparous Finnish dairy cows. Animal model data comprised 665,629 lactation milk yields and random regression test-day model data of 6,732,765 test-day milk yields. Both models included pedigree information of 1,099,622 animals. The animal model ¿random regression test-day model¿ required 122 ¿305¿ rounds of iteration to converge with the reference algorithm, but only 88 ¿149¿ were required with the preconditioned conjugate gradient. To solve the random regression test-day model with the preconditioned conjugate gradient required 237 megabytes of random access memory and took 14% of the computation time needed by the reference algorithm.
A complete implementation of the conjugate gradient algorithm on a reconfigurable supercomputer
International Nuclear Information System (INIS)
Dubois, David H.; Dubois, Andrew J.; Connor, Carolyn M.; Boorman, Thomas M.; Poole, Stephen W.
2008-01-01
The conjugate gradient is a prominent iterative method for solving systems of sparse linear equations. Large-scale scientific applications often utilize a conjugate gradient solver at their computational core. In this paper we present a field programmable gate array (FPGA) based implementation of a double precision, non-preconditioned, conjugate gradient solver for fmite-element or finite-difference methods. OUf work utilizes the SRC Computers, Inc. MAPStation hardware platform along with the 'Carte' software programming environment to ease the programming workload when working with the hybrid (CPUIFPGA) environment. The implementation is designed to handle large sparse matrices of up to order N x N where N <= 116,394, with up to 7 non-zero, 64-bit elements per sparse row. This implementation utilizes an optimized sparse matrix-vector multiply operation which is critical for obtaining high performance. Direct parallel implementations of loop unrolling and loop fusion are utilized to extract performance from the various vector/matrix operations. Rather than utilize the FPGA devices as function off-load accelerators, our implementation uses the FPGAs to implement the core conjugate gradient algorithm. Measured run-time performance data is presented comparing the FPGA implementation to a software-only version showing that the FPGA can outperform processors running up to 30x the clock rate. In conclusion we take a look at the new SRC-7 system and estimate the performance of this algorithm on that architecture.
The Modified HZ Conjugate Gradient Algorithm for Large-Scale Nonsmooth Optimization.
Yuan, Gonglin; Sheng, Zhou; Liu, Wenjie
2016-01-01
In this paper, the Hager and Zhang (HZ) conjugate gradient (CG) method and the modified HZ (MHZ) CG method are presented for large-scale nonsmooth convex minimization. Under some mild conditions, convergent results of the proposed methods are established. Numerical results show that the presented methods can be better efficiency for large-scale nonsmooth problems, and several problems are tested (with the maximum dimensions to 100,000 variables).
The Modified HZ Conjugate Gradient Algorithm for Large-Scale Nonsmooth Optimization.
Directory of Open Access Journals (Sweden)
Gonglin Yuan
Full Text Available In this paper, the Hager and Zhang (HZ conjugate gradient (CG method and the modified HZ (MHZ CG method are presented for large-scale nonsmooth convex minimization. Under some mild conditions, convergent results of the proposed methods are established. Numerical results show that the presented methods can be better efficiency for large-scale nonsmooth problems, and several problems are tested (with the maximum dimensions to 100,000 variables.
Energy Technology Data Exchange (ETDEWEB)
Biffle, J.H.
1993-02-01
JAC3D is a three-dimensional finite element program designed to solve quasi-static nonlinear mechanics problems. A set of continuum equations describes the nonlinear mechanics involving large rotation and strain. A nonlinear conjugate gradient method is used to solve the equation. The method is implemented in a three-dimensional setting with various methods for accelerating convergence. Sliding interface logic is also implemented. An eight-node Lagrangian uniform strain element is used with hourglass stiffness to control the zero-energy modes. This report documents the elastic and isothermal elastic-plastic material model. Other material models, documented elsewhere, are also available. The program is vectorized for efficient performance on Cray computers. Sample problems described are the bending of a thin beam, the rotation of a unit cube, and the pressurization and thermal loading of a hollow sphere.
Energy Technology Data Exchange (ETDEWEB)
Biffle, J.H.; Blanford, M.L.
1994-05-01
JAC2D is a two-dimensional finite element program designed to solve quasi-static nonlinear mechanics problems. A set of continuum equations describes the nonlinear mechanics involving large rotation and strain. A nonlinear conjugate gradient method is used to solve the equations. The method is implemented in a two-dimensional setting with various methods for accelerating convergence. Sliding interface logic is also implemented. A four-node Lagrangian uniform strain element is used with hourglass stiffness to control the zero-energy modes. This report documents the elastic and isothermal elastic/plastic material model. Other material models, documented elsewhere, are also available. The program is vectorized for efficient performance on Cray computers. Sample problems described are the bending of a thin beam, the rotation of a unit cube, and the pressurization and thermal loading of a hollow sphere.
Efficient conjugate gradient algorithms for computation of the manipulator forward dynamics
Fijany, Amir; Scheid, Robert E.
1989-01-01
The applicability of conjugate gradient algorithms for computation of the manipulator forward dynamics is investigated. The redundancies in the previously proposed conjugate gradient algorithm are analyzed. A new version is developed which, by avoiding these redundancies, achieves a significantly greater efficiency. A preconditioned conjugate gradient algorithm is also presented. A diagonal matrix whose elements are the diagonal elements of the inertia matrix is proposed as the preconditioner. In order to increase the computational efficiency, an algorithm is developed which exploits the synergism between the computation of the diagonal elements of the inertia matrix and that required by the conjugate gradient algorithm.
MILC staggered conjugate gradient performance on Intel KNL
Energy Technology Data Exchange (ETDEWEB)
Li, Ruiz [Indiana Univ., Bloomington, IN (United States). Dept. of Physics; Detar, Carleton [Univ. of Utah, Salt Lake City, UT (United States). Dept. of Physics and Astronomy; Doerfler, Douglas W. [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States). National Energy Research Scientific Computing Center (NERSC); Gottlieb, Steven [Indiana Univ., Bloomington, IN (United States). Dept. of Physics; Jha, Asish [Intel Corp., Hillsboro, OR (United States). Sofware and Services Group; Kalamkar, Dhiraj [Intel Labs., Bangalore (India). Parallel Computing Lab.; Toussaint, Doug [Univ. of Arizona, Tucson, AZ (United States). Physics Dept.
2016-11-03
We review our work done to optimize the staggered conjugate gradient (CG) algorithm in the MILC code for use with the Intel Knights Landing (KNL) architecture. KNL is the second gener- ation Intel Xeon Phi processor. It is capable of massive thread parallelism, data parallelism, and high on-board memory bandwidth and is being adopted in supercomputing centers for scientific research. The CG solver consumes the majority of time in production running, so we have spent most of our effort on it. We compare performance of an MPI+OpenMP baseline version of the MILC code with a version incorporating the QPhiX staggered CG solver, for both one-node and multi-node runs.
Conjugate gradient based projection - A new explicit methodology for frictional contact
Tamma, Kumar K.; Li, Maocheng; Sha, Desong
1993-01-01
With special attention towards the applicability to parallel computation or vectorization, a new and effective explicit approach for linear complementary formulations involving a conjugate gradient based projection methodology is proposed in this study for contact problems with Coulomb friction. The overall objectives are focussed towards providing an explicit methodology of computation for the complete contact problem with friction. In this regard, the primary idea for solving the linear complementary formulations stems from an established search direction which is projected to a feasible region determined by the non-negative constraint condition; this direction is then applied to the Fletcher-Reeves conjugate gradient method resulting in a powerful explicit methodology which possesses high accuracy, excellent convergence characteristics, fast computational speed and is relatively simple to implement for contact problems involving Coulomb friction.
Large Airborne Full Tensor Gradient Data Inversion Based on a Non-Monotone Gradient Method
Sun, Yong; Meng, Zhaohai; Li, Fengting
2018-03-01
Following the development of gravity gradiometer instrument technology, the full tensor gravity (FTG) data can be acquired on airborne and marine platforms. Large-scale geophysical data can be obtained using these methods, making such data sets a number of the "big data" category. Therefore, a fast and effective inversion method is developed to solve the large-scale FTG data inversion problem. Many algorithms are available to accelerate the FTG data inversion, such as conjugate gradient method. However, the conventional conjugate gradient method takes a long time to complete data processing. Thus, a fast and effective iterative algorithm is necessary to improve the utilization of FTG data. Generally, inversion processing is formulated by incorporating regularizing constraints, followed by the introduction of a non-monotone gradient-descent method to accelerate the convergence rate of FTG data inversion. Compared with the conventional gradient method, the steepest descent gradient algorithm, and the conjugate gradient algorithm, there are clear advantages of the non-monotone iterative gradient-descent algorithm. Simulated and field FTG data were applied to show the application value of this new fast inversion method.
T2CG1, a package of preconditioned conjugate gradient solvers for TOUGH2
International Nuclear Information System (INIS)
Moridis, G.; Pruess, K.; Antunez, E.
1994-03-01
Most of the computational work in the numerical simulation of fluid and heat flows in permeable media arises in the solution of large systems of linear equations. The simplest technique for solving such equations is by direct methods. However, because of large storage requirements and accumulation of roundoff errors, the application of direct solution techniques is limited, depending on matrix bandwidth, to systems of a few hundred to at most a few thousand simultaneous equations. T2CG1, a package of preconditioned conjugate gradient solvers, has been added to TOUGH2 to complement its direct solver and significantly increase the size of problems tractable on PCs. T2CG1 includes three different solvers: a Bi-Conjugate Gradient (BCG) solver, a Bi-Conjugate Gradient Squared (BCGS) solver, and a Generalized Minimum Residual (GMRES) solver. Results from six test problems with up to 30,000 equations show that T2CG1 (1) is significantly (and invariably) faster and requires far less memory than the MA28 direct solver, (2) it makes possible the solution of very large three-dimensional problems on PCs, and (3) that the BCGS solver is the fastest of the three in the tested problems. Sample problems are presented related to heat and fluid flow at Yucca Mountain and WIPP, environmental remediation by the Thermal Enhanced Vapor Extraction System, and geothermal resources
Frequency-domain beamformers using conjugate gradient techniques for speech enhancement.
Zhao, Shengkui; Jones, Douglas L; Khoo, Suiyang; Man, Zhihong
2014-09-01
A multiple-iteration constrained conjugate gradient (MICCG) algorithm and a single-iteration constrained conjugate gradient (SICCG) algorithm are proposed to realize the widely used frequency-domain minimum-variance-distortionless-response (MVDR) beamformers and the resulting algorithms are applied to speech enhancement. The algorithms are derived based on the Lagrange method and the conjugate gradient techniques. The implementations of the algorithms avoid any form of explicit or implicit autocorrelation matrix inversion. Theoretical analysis establishes formal convergence of the algorithms. Specifically, the MICCG algorithm is developed based on a block adaptation approach and it generates a finite sequence of estimates that converge to the MVDR solution. For limited data records, the estimates of the MICCG algorithm are better than the conventional estimators and equivalent to the auxiliary vector algorithms. The SICCG algorithm is developed based on a continuous adaptation approach with a sample-by-sample updating procedure and the estimates asymptotically converge to the MVDR solution. An illustrative example using synthetic data from a uniform linear array is studied and an evaluation on real data recorded by an acoustic vector sensor array is demonstrated. Performance of the MICCG algorithm and the SICCG algorithm are compared with the state-of-the-art approaches.
Directory of Open Access Journals (Sweden)
Qiuyu Wang
2014-01-01
descent method at first finite number of steps and then by conjugate gradient method subsequently. Under some appropriate conditions, we show that the algorithm converges globally. Numerical experiments and comparisons by using some box-constrained problems from CUTEr library are reported. Numerical comparisons illustrate that the proposed method is promising and competitive with the well-known method—L-BFGS-B.
Benediktsson, J. A.; Swain, P. H.; Ersoy, O. K.
1993-01-01
Application of neural networks to classification of remote sensing data is discussed. Conventional two-layer backpropagation is found to give good results in classification of remote sensing data but is not efficient in training. A more efficient variant, based on conjugate-gradient optimization, is used for classification of multisource remote sensing and geographic data and very-high-dimensional data. The conjugate-gradient neural networks give excellent performance in classification of multisource data, but do not compare as well with statistical methods in classification of very-high-dimentional data.
Vogel, Curtis R; Yang, Qiang
2006-08-21
We present two different implementations of the Fourier domain preconditioned conjugate gradient algorithm (FD-PCG) to efficiently solve the large structured linear systems that arise in optimal volume turbulence estimation, or tomography, for multi-conjugate adaptive optics (MCAO). We describe how to deal with several critical technical issues, including the cone coordinate transformation problem and sensor subaperture grid spacing. We also extend the FD-PCG approach to handle the deformable mirror fitting problem for MCAO.
A fast pulse design for parallel excitation with gridding conjugate gradient.
Feng, Shuo; Ji, Jim
2013-01-01
Parallel excitation (pTx) is recognized as a crucial technique in high field MRI to address the transmit field inhomogeneity problem. However, it can be time consuming to design pTx pulses which is not desirable. In this work, we propose a pulse design with gridding conjugate gradient (CG) based on the small-tip-angle approximation. The two major time consuming matrix-vector multiplications are substituted by two operators which involves with FFT and gridding only. Simulation results have shown that the proposed method is 3 times faster than conventional method and the memory cost is reduced by 1000 times.
Cao, Xu; Zhang, Bin; Liu, Fei; Wang, Xin; Bai, Jing
2011-12-01
Limited-projection fluorescence molecular tomography (FMT) can greatly reduce the acquisition time, which is suitable for resolving fast biology processes in vivo but suffers from severe ill-posedness because of the reconstruction using only limited projections. To overcome the severe ill-posedness, we report a reconstruction method based on the projected restarted conjugate gradient normal residual. The reconstruction results of two phantom experiments demonstrate that the proposed method is feasible for limited-projection FMT. © 2011 Optical Society of America
Refined isogeometric analysis for a preconditioned conjugate gradient solver
Garcia, Daniel
2018-02-12
Starting from a highly continuous Isogeometric Analysis (IGA) discretization, refined Isogeometric Analysis (rIGA) introduces C0 hyperplanes that act as separators for the direct LU factorization solver. As a result, the total computational cost required to solve the corresponding system of equations using a direct LU factorization solver dramatically reduces (up to a factor of 55) Garcia et al. (2017). At the same time, rIGA enriches the IGA spaces, thus improving the best approximation error. In this work, we extend the complexity analysis of rIGA to the case of iterative solvers. We build an iterative solver as follows: we first construct the Schur complements using a direct solver over small subdomains (macro-elements). We then assemble those Schur complements into a global skeleton system. Subsequently, we solve this system iteratively using Conjugate Gradients (CG) with an incomplete LU (ILU) preconditioner. For a 2D Poisson model problem with a structured mesh and a uniform polynomial degree of approximation, rIGA achieves moderate savings with respect to IGA in terms of the number of Floating Point Operations (FLOPs) and computational time (in seconds) required to solve the resulting system of linear equations. For instance, for a mesh with four million elements and polynomial degree p=3, the iterative solver is approximately 2.6 times faster (in time) when applied to the rIGA system than to the IGA one. These savings occur because the skeleton rIGA system contains fewer non-zero entries than the IGA one. The opposite situation occurs for 3D problems, and as a result, 3D rIGA discretizations provide no gains with respect to their IGA counterparts when considering iterative solvers.
International Nuclear Information System (INIS)
Burkitt, A.N.; Irving, A.C.
1988-01-01
Two of the methods that are widely used in lattice gauge theory calculations requiring inversion of the fermion matrix are the Lanczos and the conjugate gradient algorithms. Those algorithms are already known to be closely related. In fact for matrix inversion, in exact arithmetic, they give identical results at each iteration and are just alternative formulations of a single algorithm. This equivalence survives rounding errors. We give the identities between the coefficients of the two formulations, enabling many of the best features of them to be combined. (orig.)
Inversion of the fermion matrix and the equivalence of the conjugate gradient and Lanczos algorithms
International Nuclear Information System (INIS)
Burkitt, A.N.; Irving, A.C.
1990-01-01
The Lanczos and conjugate gradient algorithms are widely used in lattice QCD calculations. The previously known close relationship between the two methods is explored and two commonly used implementations are shown to give identically the same results at each iteration, in exact arithmetic, for matrix inversion. The identities between the coefficients of the two algorithms are given, and many of the features of the two algorithms can now be combined. The effects of finite arithmetic are investigated and the particular Lanczos formulation is found to be most stable with respect to rounding errors. (orig.)
International Nuclear Information System (INIS)
Reifman, J.; Vitela, J.E.
1994-01-01
The method of conjugate gradients is used to expedite the learning process of feedforward multilayer artificial neural networks and to systematically update both the learning parameter and the momentum parameter at each training cycle. The mechanism for the occurrence of premature saturation of the network nodes observed with the back propagation algorithm is described, suggestions are made to eliminate this undesirable phenomenon, and the reason by which this phenomenon is precluded in the method of conjugate gradients is presented. The proposed method is compared with the standard back propagation algorithm in the training of neural networks to classify transient events in neural power plants simulated by the Midland Nuclear Power Plant Unit 2 simulator. The comparison results indicate that the rate of convergence of the proposed method is much greater than the standard back propagation, that it reduces both the number of training cycles and the CPU time, and that it is less sensitive to the choice of initial weights. The advantages of the method are more noticeable and important for problems where the network architecture consists of a large number of nodes, the training database is large, and a tight convergence criterion is desired
Wanto, Anjar; Zarlis, Muhammad; Sawaluddin; Hartama, Dedy
2017-12-01
Backpropagation is a good artificial neural network algorithm used to predict, one of which is to predict the rate of Consumer Price Index (CPI) based on the foodstuff sector. While conjugate gradient fletcher reeves is a suitable optimization method when juxtaposed with backpropagation method, because this method can shorten iteration without reducing the quality of training and testing result. Consumer Price Index (CPI) data that will be predicted to come from the Central Statistics Agency (BPS) Pematangsiantar. The results of this study will be expected to contribute to the government in making policies to improve economic growth. In this study, the data obtained will be processed by conducting training and testing with artificial neural network backpropagation by using parameter learning rate 0,01 and target error minimum that is 0.001-0,09. The training network is built with binary and bipolar sigmoid activation functions. After the results with backpropagation are obtained, it will then be optimized using the conjugate gradient fletcher reeves method by conducting the same training and testing based on 5 predefined network architectures. The result, the method used can increase the speed and accuracy result.
Gradient-type methods in inverse parabolic problems
International Nuclear Information System (INIS)
Kabanikhin, Sergey; Penenko, Aleksey
2008-01-01
This article is devoted to gradient-based methods for inverse parabolic problems. In the first part, we present a priori convergence theorems based on the conditional stability estimates for linear inverse problems. These theorems are applied to backwards parabolic problem and sideways parabolic problem. The convergence conditions obtained coincide with sourcewise representability in the self-adjoint backwards parabolic case but they differ in the sideways case. In the second part, a variational approach is formulated for a coefficient identification problem. Using adjoint equations, a formal gradient of an objective functional is constructed. A numerical test illustrates the performance of conjugate gradient algorithm with the formal gradient.
A forward model and conjugate gradient inversion technique for low-frequency ultrasonic imaging.
van Dongen, Koen W A; Wright, William M D
2006-10-01
Emerging methods of hyperthermia cancer treatment require noninvasive temperature monitoring, and ultrasonic techniques show promise in this regard. Various tomographic algorithms are available that reconstruct sound speed or contrast profiles, which can be related to temperature distribution. The requirement of a high enough frequency for adequate spatial resolution and a low enough frequency for adequate tissue penetration is a difficult compromise. In this study, the feasibility of using low frequency ultrasound for imaging and temperature monitoring was investigated. The transient probing wave field had a bandwidth spanning the frequency range 2.5-320.5 kHz. The results from a forward model which computed the propagation and scattering of low-frequency acoustic pressure and velocity wave fields were used to compare three imaging methods formulated within the Born approximation, representing two main types of reconstruction. The first uses Fourier techniques to reconstruct sound-speed profiles from projection or Radon data based on optical ray theory, seen as an asymptotical limit for comparison. The second uses backpropagation and conjugate gradient inversion methods based on acoustical wave theory. The results show that the accuracy in localization was 2.5 mm or better when using low frequencies and the conjugate gradient inversion scheme, which could be used for temperature monitoring.
Compensation of spatial system response in SPECT with conjugate gradient reconstruction technique
International Nuclear Information System (INIS)
Formiconi, A.R.; Pupi, A.; Passeri, A.
1989-01-01
A procedure for determination of the system matrix in single photon emission tomography (SPECT) is described which use a conjugate gradient reconstruction technique to take into account the variable system resolution of a camera equipped with parallel-hole collimators. The procedure involves acquisition of system line spread functions (LSF) in the region occupied by the object studied. Those data are used to generate a set of weighting factors based on the assumption that the LSFs of the collimated camera are of Gaussian shape with full width at half maximum (FWHM) linearly dependent on source depth in the span of image space. Factors are stored on a disc file for subsequent use in reconstruction. Afterwards reconstruction is performed using the conjugate gradient method with the system matrix modified by incorporation of these precalculated factors to take into account variable geometrical system response. The set of weighting factors is regenerated whenever acquisition conditions are changed (collimator, radius of rotation) with an ultra high resolution (UHR) collimator 2000 weighting factors need to be calculated. (author)
A new nonlinear conjugate gradient coefficient under strong Wolfe-Powell line search
Mohamed, Nur Syarafina; Mamat, Mustafa; Rivaie, Mohd
2017-08-01
A nonlinear conjugate gradient method (CG) plays an important role in solving a large-scale unconstrained optimization problem. This method is widely used due to its simplicity. The method is known to possess sufficient descend condition and global convergence properties. In this paper, a new nonlinear of CG coefficient βk is presented by employing the Strong Wolfe-Powell inexact line search. The new βk performance is tested based on number of iterations and central processing unit (CPU) time by using MATLAB software with Intel Core i7-3470 CPU processor. Numerical experimental results show that the new βk converge rapidly compared to other classical CG method.
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.
Wavelet methods in multi-conjugate adaptive optics
International Nuclear Information System (INIS)
Helin, T; Yudytskiy, M
2013-01-01
The next generation ground-based telescopes rely heavily on adaptive optics for overcoming the limitation of atmospheric turbulence. In the future adaptive optics modalities, like multi-conjugate adaptive optics (MCAO), atmospheric tomography is the major mathematical and computational challenge. In this severely ill-posed problem, a fast and stable reconstruction algorithm is needed that can take into account many real-life phenomena of telescope imaging. We introduce a novel reconstruction method for the atmospheric tomography problem and demonstrate its performance and flexibility in the context of MCAO. Our method is based on using locality properties of compactly supported wavelets, both in the spatial and frequency domains. The reconstruction in the atmospheric tomography problem is obtained by solving the Bayesian MAP estimator with a conjugate-gradient-based algorithm. An accelerated algorithm with preconditioning is also introduced. Numerical performance is demonstrated on the official end-to-end simulation tool OCTOPUS of European Southern Observatory. (paper)
METHOD OF CONJUGATED CIRCULAR ARCS TRACING
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N. Ageyev Vladimir
2017-01-01
Full Text Available The geometric properties of conjugated circular arcs connecting two points on the plane with set directions of tan- gent vectors are studied in the work. It is shown that pairs of conjugated circular arcs with the same conditions in frontier points create one-parameter set of smooth curves tightly filling all the plane. One of the basic properties of this set is the fact that all coupling points of circular arcs are on the circular curve going through the initially given points. The circle radius depends on the direction of tangent vectors. Any point of the circle curve, named auxiliary in this work, determines a pair of conjugated arcs with given boundary conditions. One more condition of the auxiliary circle curve is that it divides the plane into two parts. The arcs going from the initial point are out of the circle limited by this circle curve and the arcs coming to the final point are inside it. These properties are the basis for the method of conjugated circular arcs tracing pro- posed in this article. The algorithm is rather simple and allows to fulfill all the needed plottings using only the divider and ruler. Two concrete examples are considered. The first one is related to the problem of tracing of a pair of conjugated arcs with the minimal curve jump when going through the coupling point. The second one demonstrates the possibility of trac- ing of the smooth curve going through any three points on the plane under condition that in the initial and final points the directions of tangent vectors are given. The proposed methods of conjugated circular arcs tracing can be applied in solving of a wide variety of problems connected with the tracing of cam contours, for example pattern curves in textile industry or in computer-aided-design systems when programming of looms with numeric control.
Sun, Xiao-Dong; Ge, Zhong-Hui; Li, Zhen-Chun
2017-09-01
Although conventional reverse time migration can be perfectly applied to structural imaging it lacks the capability of enabling detailed delineation of a lithological reservoir due to irregular illumination. To obtain reliable reflectivity of the subsurface it is necessary to solve the imaging problem using inversion. The least-square reverse time migration (LSRTM) (also known as linearized reflectivity inversion) aims to obtain relatively high-resolution amplitude preserving imaging by including the inverse of the Hessian matrix. In practice, the conjugate gradient algorithm is proven to be an efficient iterative method for enabling use of LSRTM. The velocity gradient can be derived from a cross-correlation between observed data and simulated data, making LSRTM independent of wavelet signature and thus more robust in practice. Tests on synthetic and marine data show that LSRTM has good potential for use in reservoir description and four-dimensional (4D) seismic images compared to traditional RTM and Fourier finite difference (FFD) migration. This paper investigates the first order approximation of LSRTM, which is also known as the linear Born approximation. However, for more complex geological structures a higher order approximation should be considered to improve imaging quality.
A modified three-term PRP conjugate gradient algorithm for optimization models.
Wu, Yanlin
2017-01-01
The nonlinear conjugate gradient (CG) algorithm is a very effective method for optimization, especially for large-scale problems, because of its low memory requirement and simplicity. Zhang et al. (IMA J. Numer. Anal. 26:629-649, 2006) firstly propose a three-term CG algorithm based on the well known Polak-Ribière-Polyak (PRP) formula for unconstrained optimization, where their method has the sufficient descent property without any line search technique. They proved the global convergence of the Armijo line search but this fails for the Wolfe line search technique. Inspired by their method, we will make a further study and give a modified three-term PRP CG algorithm. The presented method possesses the following features: (1) The sufficient descent property also holds without any line search technique; (2) the trust region property of the search direction is automatically satisfied; (3) the steplengh is bounded from below; (4) the global convergence will be established under the Wolfe line search. Numerical results show that the new algorithm is more effective than that of the normal method.
A new modified conjugate gradient coefficient for solving system of linear equations
Hajar, N.; ‘Aini, N.; Shapiee, N.; Abidin, Z. Z.; Khadijah, W.; Rivaie, M.; Mamat, M.
2017-09-01
Conjugate gradient (CG) method is an evolution of computational method in solving unconstrained optimization problems. This approach is easy to implement due to its simplicity and has been proven to be effective in solving real-life application. Although this field has received copious amount of attentions in recent years, some of the new approaches of CG algorithm cannot surpass the efficiency of the previous versions. Therefore, in this paper, a new CG coefficient which retains the sufficient descent and global convergence properties of the original CG methods is proposed. This new CG is tested on a set of test functions under exact line search. Its performance is then compared to that of some of the well-known previous CG methods based on number of iterations and CPU time. The results show that the new CG algorithm has the best efficiency amongst all the methods tested. This paper also includes an application of the new CG algorithm for solving large system of linear equations
Stochastic Spectral and Conjugate Descent Methods
Kovalev, Dmitry
2018-02-11
The state-of-the-art methods for solving optimization problems in big dimensions are variants of randomized coordinate descent (RCD). In this paper we introduce a fundamentally new type of acceleration strategy for RCD based on the augmentation of the set of coordinate directions by a few spectral or conjugate directions. As we increase the number of extra directions to be sampled from, the rate of the method improves, and interpolates between the linear rate of RCD and a linear rate independent of the condition number. We develop and analyze also inexact variants of these methods where the spectral and conjugate directions are allowed to be approximate only. We motivate the above development by proving several negative results which highlight the limitations of RCD with importance sampling.
Stochastic Spectral and Conjugate Descent Methods
Kovalev, Dmitry; Gorbunov, Eduard; Gasanov, Elnur; Richtarik, Peter
2018-01-01
The state-of-the-art methods for solving optimization problems in big dimensions are variants of randomized coordinate descent (RCD). In this paper we introduce a fundamentally new type of acceleration strategy for RCD based on the augmentation of the set of coordinate directions by a few spectral or conjugate directions. As we increase the number of extra directions to be sampled from, the rate of the method improves, and interpolates between the linear rate of RCD and a linear rate independent of the condition number. We develop and analyze also inexact variants of these methods where the spectral and conjugate directions are allowed to be approximate only. We motivate the above development by proving several negative results which highlight the limitations of RCD with importance sampling.
Directory of Open Access Journals (Sweden)
Xiangrong Li
Full Text Available It is generally acknowledged that the conjugate gradient (CG method achieves global convergence--with at most a linear convergence rate--because CG formulas are generated by linear approximations of the objective functions. The quadratically convergent results are very limited. We introduce a new PRP method in which the restart strategy is also used. Moreover, the method we developed includes not only n-step quadratic convergence but also both the function value information and gradient value information. In this paper, we will show that the new PRP method (with either the Armijo line search or the Wolfe line search is both linearly and quadratically convergent. The numerical experiments demonstrate that the new PRP algorithm is competitive with the normal CG method.
Li, Xiangrong; Zhao, Xupei; Duan, Xiabin; Wang, Xiaoliang
2015-01-01
It is generally acknowledged that the conjugate gradient (CG) method achieves global convergence--with at most a linear convergence rate--because CG formulas are generated by linear approximations of the objective functions. The quadratically convergent results are very limited. We introduce a new PRP method in which the restart strategy is also used. Moreover, the method we developed includes not only n-step quadratic convergence but also both the function value information and gradient value information. In this paper, we will show that the new PRP method (with either the Armijo line search or the Wolfe line search) is both linearly and quadratically convergent. The numerical experiments demonstrate that the new PRP algorithm is competitive with the normal CG method.
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
Ghosh, A
1988-08-01
Lanczos and conjugate gradient algorithms are important in computational linear algebra. In this paper, a parallel pipelined realization of these algorithms on a ring of optical linear algebra processors is described. The flow of data is designed to minimize the idle times of the optical multiprocessor and the redundancy of computations. The effects of optical round-off errors on the solutions obtained by the optical Lanczos and conjugate gradient algorithms are analyzed, and it is shown that optical preconditioning can improve the accuracy of these algorithms substantially. Algorithms for optical preconditioning and results of numerical experiments on solving linear systems of equations arising from partial differential equations are discussed. Since the Lanczos algorithm is used mostly with sparse matrices, a folded storage scheme to represent sparse matrices on spatial light modulators is also described.
Mariano-Goulart, D; Fourcade, M; Bernon, J L; Rossi, M; Zanca, M
2003-01-01
Thanks to an experimental study based on simulated and physical phantoms, the propagation of the stochastic noise in slices reconstructed using the conjugate gradient algorithm has been analysed versus iterations. After a first increase corresponding to the reconstruction of the signal, the noise stabilises before increasing linearly with iterations. The level of the plateau as well as the slope of the subsequent linear increase depends on the noise in the projection data.
Directory of Open Access Journals (Sweden)
Jianfei Zhang
2013-01-01
Full Text Available Graphics processing unit (GPU has obtained great success in scientific computations for its tremendous computational horsepower and very high memory bandwidth. This paper discusses the efficient way to implement polynomial preconditioned conjugate gradient solver for the finite element computation of elasticity on NVIDIA GPUs using compute unified device architecture (CUDA. Sliced block ELLPACK (SBELL format is introduced to store sparse matrix arising from finite element discretization of elasticity with fewer padding zeros than traditional ELLPACK-based formats. Polynomial preconditioning methods have been investigated both in convergence and running time. From the overall performance, the least-squares (L-S polynomial method is chosen as a preconditioner in PCG solver to finite element equations derived from elasticity for its best results on different example meshes. In the PCG solver, mixed precision algorithm is used not only to reduce the overall computational, storage requirements and bandwidth but to make full use of the capacity of the GPU devices. With SBELL format and mixed precision algorithm, the GPU-based L-S preconditioned CG can get a speedup of about 7–9 to CPU-implementation.
A nonrecursive order N preconditioned conjugate gradient: Range space formulation of MDOF dynamics
Kurdila, Andrew J.
1990-01-01
While excellent progress has been made in deriving algorithms that are efficient for certain combinations of system topologies and concurrent multiprocessing hardware, several issues must be resolved to incorporate transient simulation in the control design process for large space structures. Specifically, strategies must be developed that are applicable to systems with numerous degrees of freedom. In addition, the algorithms must have a growth potential in that they must also be amenable to implementation on forthcoming parallel system architectures. For mechanical system simulation, this fact implies that algorithms are required that induce parallelism on a fine scale, suitable for the emerging class of highly parallel processors; and transient simulation methods must be automatically load balancing for a wider collection of system topologies and hardware configurations. These problems are addressed by employing a combination range space/preconditioned conjugate gradient formulation of multi-degree-of-freedom dynamics. The method described has several advantages. In a sequential computing environment, the method has the features that: by employing regular ordering of the system connectivity graph, an extremely efficient preconditioner can be derived from the 'range space metric', as opposed to the system coefficient matrix; because of the effectiveness of the preconditioner, preliminary studies indicate that the method can achieve performance rates that depend linearly upon the number of substructures, hence the title 'Order N'; and the method is non-assembling. Furthermore, the approach is promising as a potential parallel processing algorithm in that the method exhibits a fine parallel granularity suitable for a wide collection of combinations of physical system topologies/computer architectures; and the method is easily load balanced among processors, and does not rely upon system topology to induce parallelism.
STOCHASTIC GRADIENT METHODS FOR UNCONSTRAINED OPTIMIZATION
Directory of Open Access Journals (Sweden)
Nataša Krejić
2014-12-01
Full Text Available This papers presents an overview of gradient based methods for minimization of noisy functions. It is assumed that the objective functions is either given with error terms of stochastic nature or given as the mathematical expectation. Such problems arise in the context of simulation based optimization. The focus of this presentation is on the gradient based Stochastic Approximation and Sample Average Approximation methods. The concept of stochastic gradient approximation of the true gradient can be successfully extended to deterministic problems. Methods of this kind are presented for the data fitting and machine learning problems.
Acceptable solutions obtained by unfolding noisy data with a conjugate gradient technique
International Nuclear Information System (INIS)
Lang, D.W.
1976-01-01
A linear resolution function in a physical measurement leads to data values and standard deviations at, say, N points. It is noted that the associated resolution functions may require that a number n of particular linear combinations of the data values be each not significantly different from zero. One is left with at most N-n parameters to evaluate. If the resolution functions are reasonably behaved, one can show that one sensible way to describe the underlying spectrum treats it as a linear combination of the given resolution functions and includes all the significant information from the data. An iterative search for the best component available to minimize the chi-square of the next fit to the data leads to a conjugate gradient technique. Programs based on the technique have been successfully used to obtain neutron spectra as a function of energy; in raw data from a pulse height analysis of proton recoils in a proportional counter, and where the raw data are time of flight spectra from a time dependent pulse of known form. It is planned to incorporate these, together with working programs respectively for photonuclear analysis and to explore the impurity concentration profile in a surface, into a single ''work-bench'' type program. A suitably difficult model unfolding problem has been developed and used to show the strengths and weaknesses of a number of other methods that have been used for unfolding
International Nuclear Information System (INIS)
Perez, L; Autrique, L; Gillet, M
2008-01-01
The aim of this paper is to investigate the thermal diffusivity identification of a multilayered material dedicated to fire protection. In a military framework, fire protection needs to meet specific requirements, and operational protective systems must be constantly improved in order to keep up with the development of new weapons. In the specific domain of passive fire protections, intumescent coatings can be an effective solution on the battlefield. Intumescent materials have the ability to swell up when they are heated, building a thick multi-layered coating which provides efficient thermal insulation to the underlying material. Due to the heat aggressions (fire or explosion) leading to the intumescent phenomena, high temperatures are considered and prevent from linearization of the mathematical model describing the system state evolution. Previous sensitivity analysis has shown that the thermal diffusivity of the multilayered intumescent coating is a key parameter in order to validate the predictive numerical tool and therefore for thermal protection optimisation. A conjugate gradient method is implemented in order to minimise the quadratic cost function related to the error between predicted temperature and measured temperature. This regularisation algorithm is well adapted for a large number of unknown parameters.
Embedding SAS approach into conjugate gradient algorithms for asymmetric 3D elasticity problems
Energy Technology Data Exchange (ETDEWEB)
Chen, Hsin-Chu; Warsi, N.A. [Clark Atlanta Univ., GA (United States); Sameh, A. [Univ. of Minnesota, Minneapolis, MN (United States)
1996-12-31
In this paper, we present two strategies to embed the SAS (symmetric-and-antisymmetric) scheme into conjugate gradient (CG) algorithms to make solving 3D elasticity problems, with or without global reflexive symmetry, more efficient. The SAS approach is physically a domain decomposition scheme that takes advantage of reflexive symmetry of discretized physical problems, and algebraically a matrix transformation method that exploits special reflexivity properties of the matrix resulting from discretization. In addition to offering large-grain parallelism, which is valuable in a multiprocessing environment, the SAS scheme also has the potential for reducing arithmetic operations in the numerical solution of a reasonably wide class of scientific and engineering problems. This approach can be applied directly to problems that have global reflexive symmetry, yielding smaller and independent subproblems to solve, or indirectly to problems with partial symmetry, resulting in loosely coupled subproblems. The decomposition is achieved by separating the reflexive subspace from the antireflexive one, possessed by a special class of matrices A, A {element_of} C{sup n x n} that satisfy the relation A = PAP where P is a reflection matrix (symmetric signed permutation matrix).
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.
Chen, Weitian; Sica, Christopher T; Meyer, Craig H
2008-11-01
Off-resonance effects can cause image blurring in spiral scanning and various forms of image degradation in other MRI methods. Off-resonance effects can be caused by both B0 inhomogeneity and concomitant gradient fields. Previously developed off-resonance correction methods focus on the correction of a single source of off-resonance. This work introduces a computationally efficient method of correcting for B0 inhomogeneity and concomitant gradients simultaneously. The method is a fast alternative to conjugate phase reconstruction, with the off-resonance phase term approximated by Chebyshev polynomials. The proposed algorithm is well suited for semiautomatic off-resonance correction, which works well even with an inaccurate or low-resolution field map. The proposed algorithm is demonstrated using phantom and in vivo data sets acquired by spiral scanning. Semiautomatic off-resonance correction alone is shown to provide a moderate amount of correction for concomitant gradient field effects, in addition to B0 imhomogeneity effects. However, better correction is provided by the proposed combined method. The best results were produced using the semiautomatic version of the proposed combined method.
Preconditioned conjugate gradient wave-front reconstructors for multiconjugate adaptive optics
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.
Preconditioned conjugate gradient wave-front reconstructors for multiconjugate adaptive optics.
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.
Gradient-based methods for production optimization of oil reservoirs
Energy Technology Data Exchange (ETDEWEB)
Suwartadi, Eka
2012-07-01
Production optimization for water flooding in the secondary phase of oil recovery is the main topic in this thesis. The emphasis has been on numerical optimization algorithms, tested on case examples using simple hypothetical oil reservoirs. Gradientbased optimization, which utilizes adjoint-based gradient computation, is used to solve the optimization problems. The first contribution of this thesis is to address output constraint problems. These kinds of constraints are natural in production optimization. Limiting total water production and water cut at producer wells are examples of such constraints. To maintain the feasibility of an optimization solution, a Lagrangian barrier method is proposed to handle the output constraints. This method incorporates the output constraints into the objective function, thus avoiding additional computations for the constraints gradient (Jacobian) which may be detrimental to the efficiency of the adjoint method. The second contribution is the study of the use of second-order adjoint-gradient information for production optimization. In order to speedup convergence rate in the optimization, one usually uses quasi-Newton approaches such as BFGS and SR1 methods. These methods compute an approximation of the inverse of the Hessian matrix given the first-order gradient from the adjoint method. The methods may not give significant speedup if the Hessian is ill-conditioned. We have developed and implemented the Hessian matrix computation using the adjoint method. Due to high computational cost of the Newton method itself, we instead compute the Hessian-timesvector product which is used in a conjugate gradient algorithm. Finally, the last contribution of this thesis is on surrogate optimization for water flooding in the presence of the output constraints. Two kinds of model order reduction techniques are applied to build surrogate models. These are proper orthogonal decomposition (POD) and the discrete empirical interpolation method (DEIM
Gradient High Performance Liquid Chromatography Method ...
African Journals Online (AJOL)
Purpose: To develop a gradient high performance liquid chromatography (HPLC) method for the simultaneous determination of phenylephrine (PHE) and ibuprofen (IBU) in solid ..... nimesulide, phenylephrine. Hydrochloride, chlorpheniramine maleate and caffeine anhydrous in pharmaceutical dosage form. Acta Pol.
Bowman, D; Harte, T L; Chardonnet, V; De Groot, C; Denny, S J; Le Goc, G; Anderson, M; Ireland, P; Cassettari, D; Bruce, G D
2017-05-15
We demonstrate simultaneous control of both the phase and amplitude of light using a conjugate gradient minimisation-based hologram calculation technique and a single phase-only spatial light modulator (SLM). A cost function, which incorporates the inner product of the light field with a chosen target field within a defined measure region, is efficiently minimised to create high fidelity patterns in the Fourier plane of the SLM. A fidelity of F = 0.999997 is achieved for a pattern resembling an LG10 mode with a calculated light-usage efficiency of 41.5%. Possible applications of our method in optical trapping and ultracold atoms are presented and we show uncorrected experimental realisation of our patterns with F = 0.97 and 7.8% light efficiency.
Oliker, Leonid; Heber, Gerd; Biswas, Rupak
2000-01-01
The Conjugate Gradient (CG) algorithm is perhaps the best-known iterative technique to solve sparse linear systems that are symmetric and positive definite. A sparse matrix-vector multiply (SPMV) usually accounts for most of the floating-point operations within a CG iteration. In this paper, we investigate the effects of various ordering and partitioning strategies on the performance of parallel CG and SPMV using different programming paradigms and architectures. Results show that for this class of applications, ordering significantly improves overall performance, that cache reuse may be more important than reducing communication, and that it is possible to achieve message passing performance using shared memory constructs through careful data ordering and distribution. However, a multi-threaded implementation of CG on the Tera MTA does not require special ordering or partitioning to obtain high efficiency and scalability.
International Nuclear Information System (INIS)
Vecharynski, Eugene; Yang, Chao; Pask, John E.
2015-01-01
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 optimal 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
Shi, Junwei; Zhang, Bin; Liu, Fei; Luo, Jianwen; Bai, Jing
2013-09-15
For the ill-posed fluorescent molecular tomography (FMT) inverse problem, the L1 regularization can protect the high-frequency information like edges while effectively reduce the image noise. However, the state-of-the-art L1 regularization-based algorithms for FMT reconstruction are expensive in memory, especially for large-scale problems. An efficient L1 regularization-based reconstruction algorithm based on nonlinear conjugate gradient with restarted strategy is proposed to increase the computational speed with low memory consumption. The reconstruction results from phantom experiments demonstrate that the proposed algorithm can obtain high spatial resolution and high signal-to-noise ratio, as well as high localization accuracy for fluorescence targets.
Fully 3D PET image reconstruction using a fourier preconditioned conjugate-gradient algorithm
International Nuclear Information System (INIS)
Fessler, J.A.; Ficaro, E.P.
1996-01-01
Since the data sizes in fully 3D PET imaging are very large, iterative image reconstruction algorithms must converge in very few iterations to be useful. One can improve the convergence rate of the conjugate-gradient (CG) algorithm by incorporating preconditioning operators that approximate the inverse of the Hessian of the objective function. If the 3D cylindrical PET geometry were not truncated at the ends, then the Hessian of the penalized least-squares objective function would be approximately shift-invariant, i.e. G'G would be nearly block-circulant, where G is the system matrix. We propose a Fourier preconditioner based on this shift-invariant approximation to the Hessian. Results show that this preconditioner significantly accelerates the convergence of the CG algorithm with only a small increase in computation
Preconditioned conjugate gradient technique for the analysis of symmetric anisotropic structures
Noor, Ahmed K.; Peters, Jeanne M.
1987-01-01
An efficient preconditioned conjugate gradient (PCG) technique and a computational procedure are presented for the analysis of symmetric anisotropic structures. The technique is based on selecting the preconditioning matrix as the orthotropic part of the global stiffness matrix of the structure, with all the nonorthotropic terms set equal to zero. This particular choice of the preconditioning matrix results in reducing the size of the analysis model of the anisotropic structure to that of the corresponding orthotropic structure. The similarities between the proposed PCG technique and a reduction technique previously presented by the authors are identified and exploited to generate from the PCG technique direct measures for the sensitivity of the different response quantities to the nonorthotropic (anisotropic) material coefficients of the structure. The effectiveness of the PCG technique is demonstrated by means of a numerical example of an anisotropic cylindrical panel.
On computing quadrature-based bounds for the A-norm of the error in conjugate gradients
Czech Academy of Sciences Publication Activity Database
Meurant, G.; Tichý, Petr
2013-01-01
Roč. 62, č. 2 (2013), s. 163-191 ISSN 1017-1398 R&D Projects: GA AV ČR IAA100300802 Institutional research plan: CEZ:AV0Z10300504 Keywords : conjugate gradients * norm of the error * bounds for the error norm Subject RIV: BA - General Mathematics Impact factor: 1.005, year: 2013
On computing quadrature-based bounds for the A-norm of the error in conjugate gradients
Czech Academy of Sciences Publication Activity Database
Meurant, G.; Tichý, Petr
2013-01-01
Roč. 62, č. 2 (2013), s. 163-191 ISSN 1017-1398 R&D Projects: GA AV ČR IAA100300802 Institutional research plan: CEZ:AV0Z10300504 Keywords : conjugate gradient s * norm of the error * bounds for the error norm Subject RIV: BA - General Mathematics Impact factor: 1.005, year: 2013
Madyastha, Raghavendra K.; Aazhang, Behnaam; Henson, Troy F.; Huxhold, Wendy L.
1992-01-01
This paper addresses the issue of applying a globally convergent optimization algorithm to the training of multilayer perceptrons, a class of Artificial Neural Networks. The multilayer perceptrons are trained towards the solution of two highly nonlinear problems: (1) signal detection in a multi-user communication network, and (2) solving the inverse kinematics for a robotic manipulator. The research is motivated by the fact that a multilayer perceptron is theoretically capable of approximating any nonlinear function to within a specified accuracy. The algorithm that has been employed in this study combines the merits of two well known optimization algorithms, the Conjugate Gradients and the Trust Regions Algorithms. The performance is compared to a widely used algorithm, the Backpropagation Algorithm, that is basically a gradient-based algorithm, and hence, slow in converging. The performances of the two algorithms are compared with the convergence rate. Furthermore, in the case of the signal detection problem, performances are also benchmarked by the decision boundaries drawn as well as the probability of error obtained in either case.
Modern methods for the synthesis of peptide-oligonucleotide conjugates
International Nuclear Information System (INIS)
Zubin, Evgenii M; Oretskaya, Tat'yana S; Romanova, Elena A
2002-01-01
The published data on the methods of chemical solution and solid-phase synthesis of peptide-oligonucleotide conjugates are reviewed. The known methods are systematised and their advantages and disadvantages are considered. The approaches to the solution synthesis of peptide-oligonucleotide conjugates are systematised according to the type of chemical bonds between the fragments, whereas those to the solid-phase synthesis are classified according to the procedure used for the preparation of conjugates, viz., stepwise elongation of oligonucleotide and peptide chains on the same polymeric support or solid-phase condensation of two presynthesised fragments. The bibliography includes 141 references.
Aviat, Félix; Lagardère, Louis; Piquemal, Jean-Philip
2017-10-01
In a recent paper [F. Aviat et al., J. Chem. Theory Comput. 13, 180-190 (2017)], we proposed the Truncated Conjugate Gradient (TCG) approach to compute the polarization energy and forces in polarizable molecular simulations. The method consists in truncating the conjugate gradient algorithm at a fixed predetermined order leading to a fixed computational cost and can thus be considered "non-iterative." This gives the possibility to derive analytical forces avoiding the usual energy conservation (i.e., drifts) issues occurring with iterative approaches. A key point concerns the evaluation of the analytical gradients, which is more complex than that with a usual solver. In this paper, after reviewing the present state of the art of polarization solvers, we detail a viable strategy for the efficient implementation of the TCG calculation. The complete cost of the approach is then measured as it is tested using a multi-time step scheme and compared to timings using usual iterative approaches. We show that the TCG methods are more efficient than traditional techniques, making it a method of choice for future long molecular dynamics simulations using polarizable force fields where energy conservation matters. We detail the various steps required for the implementation of the complete method by software developers.
The application of projected conjugate gradient solvers on graphical processing units
International Nuclear Information System (INIS)
Lin, Youzuo; Renaut, Rosemary
2011-01-01
Graphical processing units introduce the capability for large scale computation at the desktop. Presented numerical results verify that efficiencies and accuracies of basic linear algebra subroutines of all levels when implemented in CUDA and Jacket are comparable. But experimental results demonstrate that the basic linear algebra subroutines of level three offer the greatest potential for improving efficiency of basic numerical algorithms. We consider the solution of the multiple right hand side set of linear equations using Krylov subspace-based solvers. Thus, for the multiple right hand side case, it is more efficient to make use of a block implementation of the conjugate gradient algorithm, rather than to solve each system independently. Jacket is used for the implementation. Furthermore, including projection from one system to another improves efficiency. A relevant example, for which simulated results are provided, is the reconstruction of a three dimensional medical image volume acquired from a positron emission tomography scanner. Efficiency of the reconstruction is improved by using projection across nearby slices.
The application of projected conjugate gradient solvers on graphical processing units
Energy Technology Data Exchange (ETDEWEB)
Lin, Youzuo [Los Alamos National Laboratory; Renaut, Rosemary [ARIZONA STATE UNIV.
2011-01-26
Graphical processing units introduce the capability for large scale computation at the desktop. Presented numerical results verify that efficiencies and accuracies of basic linear algebra subroutines of all levels when implemented in CUDA and Jacket are comparable. But experimental results demonstrate that the basic linear algebra subroutines of level three offer the greatest potential for improving efficiency of basic numerical algorithms. We consider the solution of the multiple right hand side set of linear equations using Krylov subspace-based solvers. Thus, for the multiple right hand side case, it is more efficient to make use of a block implementation of the conjugate gradient algorithm, rather than to solve each system independently. Jacket is used for the implementation. Furthermore, including projection from one system to another improves efficiency. A relevant example, for which simulated results are provided, is the reconstruction of a three dimensional medical image volume acquired from a positron emission tomography scanner. Efficiency of the reconstruction is improved by using projection across nearby slices.
Shi, Junwei; Liu, Fei; Zhang, Guanglei; Luo, Jianwen; Bai, Jing
2014-04-01
Owing to the high degree of scattering of light through tissues, the ill-posedness of fluorescence molecular tomography (FMT) inverse problem causes relatively low spatial resolution in the reconstruction results. Unlike L2 regularization, L1 regularization can preserve the details and reduce the noise effectively. Reconstruction is obtained through a restarted L1 regularization-based nonlinear conjugate gradient (re-L1-NCG) algorithm, which has been proven to be able to increase the computational speed with low memory consumption. The algorithm consists of inner and outer iterations. In the inner iteration, L1-NCG is used to obtain the L1-regularized results. In the outer iteration, the restarted strategy is used to increase the convergence speed of L1-NCG. To demonstrate the performance of re-L1-NCG in terms of spatial resolution, simulation and physical phantom studies with fluorescent targets located with different edge-to-edge distances were carried out. The reconstruction results show that the re-L1-NCG algorithm has the ability to resolve targets with an edge-to-edge distance of 0.1 cm at a depth of 1.5 cm, which is a significant improvement for FMT.
Directory of Open Access Journals (Sweden)
ChunPing Ren
2017-01-01
Full Text Available We propose a novel mathematical algorithm to offer a solution for the inverse random dynamic force identification in practical engineering. Dealing with the random dynamic force identification problem using the proposed algorithm, an improved maximum entropy (IME regularization technique is transformed into an unconstrained optimization problem, and a novel conjugate gradient (NCG method was applied to solve the objective function, which was abbreviated as IME-NCG algorithm. The result of IME-NCG algorithm is compared with that of ME, ME-CG, ME-NCG, and IME-CG algorithm; it is found that IME-NCG algorithm is available for identifying the random dynamic force due to smaller root mean-square-error (RMSE, lower restoration time, and fewer iterative steps. Example of engineering application shows that L-curve method is introduced which is better than Generalized Cross Validation (GCV method and is applied to select regularization parameter; thus the proposed algorithm can be helpful to alleviate the ill-conditioned problem in identification of dynamic force and to acquire an optimal solution of inverse problem in practical engineering.
International Nuclear Information System (INIS)
Kalkreuter, T.; Simma, H.
1995-07-01
The low-lying eigenvalues of a (sparse) hermitian matrix can be computed with controlled numerical errors by a conjugate gradient (CG) method. This CG algorithm is accelerated by alternating it with exact diagonalizations in the subspace spanned by the numerically computed eigenvectors. We study this combined algorithm in case of the Dirac operator with (dynamical) Wilson fermions in four-dimensional SU(2) gauge fields. The algorithm is numerically very stable and can be parallelized in an efficient way. On lattices of sizes 4 4 - 16 4 an acceleration of the pure CG method by a factor of 4 - 8 is found. (orig.)
Accelerated gradient methods for constrained image deblurring
International Nuclear Information System (INIS)
Bonettini, S; Zanella, R; Zanni, L; Bertero, M
2008-01-01
In this paper we propose a special gradient projection method for the image deblurring problem, in the framework of the maximum likelihood approach. We present the method in a very general form and we give convergence results under standard assumptions. Then we consider the deblurring problem and the generality of the proposed algorithm allows us to add a energy conservation constraint to the maximum likelihood problem. In order to improve the convergence rate, we devise appropriate scaling strategies and steplength updating rules, especially designed for this application. The effectiveness of the method is evaluated by means of a computational study on astronomical images corrupted by Poisson noise. Comparisons with standard methods for image restoration, such as the expectation maximization algorithm, are also reported.
Robust Approximate Inverse Preconditioning for the Conjugate Gradient Method
Czech Academy of Sciences Publication Activity Database
Benzi, M.; Cullum, J. K.; Tůma, Miroslav
2000-01-01
Roč. 22, č. 4 (2000), s. 1318-1332 ISSN 1064-8275 R&D Projects: GA AV ČR IAA2030706; GA AV ČR IAA2030801 Institutional research plan: AV0Z1030915 Subject RIV: BA - General Mathematics Impact factor: 1.421, year: 2000
The Deflated Preconditioned Conjugate Gradient Method Applied to Composite Materials
Jönsthövel, T.B.
2012-01-01
Simulations with composite materials often involve large jumps in the coefficients of the underlying stiffness matrix. These jumps can introduce unfavorable eigenvalues in the spectrum of the stiffness matrix. We show that the rigid body modes; the translations and rotations, of the disjunct rigid
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
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.
A method for easily customizable gradient gel electrophoresis.
Miller, Andrew J; Roman, Brandon; Norstrom, Eric
2016-09-15
Gradient polyacrylamide gel electrophoresis is a powerful tool for the resolution of polypeptides by relative mobility. Here, we present a simplified method for generating polyacrylamide gradient gels for routine analysis without the need for specialized mixing equipment. The method allows for easily customizable gradients which can be optimized for specific polypeptide resolution requirements. Moreover, the method eliminates the possibility of buffer cross contamination in mixing equipment, and the time and resources saved with this method in place of traditional gradient mixing, or the purchase of pre-cast gels, are noteworthy given the frequency with which many labs use gradient gel SDS-PAGE. Copyright © 2016 Elsevier Inc. All rights reserved.
Pan, Fan; Yang, Wende; Li, Wei; Yang, Xiao-Yan; Liu, Shuhao; Li, Xin; Zhao, Xiaoxu; Ding, Hui; Qin, Li; Pan, Yunlong
2017-07-01
Several studies have revealed the potential of normalizing tumor vessels in anti-angiogenic treatment. Recombinant human endostatin is an anti-angiogenic agent which has been applied in clinical tumor treatment. Our previous research indicated that gold nanoparticles could be a nanoparticle carrier for recombinant human endostatin delivery. The recombinant human endostatin-gold nanoparticle conjugates normalized vessels, which improved chemotherapy. However, the mechanism of recombinant human endostatin-gold nanoparticle-induced vascular normalization has not been explored. Anterior gradient 2 has been reported to be over-expressed in many malignant tumors and involved in tumor angiogenesis. To date, the precise efficacy of recombinant human endostatin-gold nanoparticles on anterior gradient 2-mediated angiogenesis or anterior gradient 2-related signaling cohort remained unknown. In this study, we aimed to explore whether recombinant human endostatin-gold nanoparticles could normalize vessels in metastatic colorectal cancer xenografts, and we further elucidated whether recombinant human endostatin-gold nanoparticles could interrupt anterior gradient 2-induced angiogenesis. In vivo, it was indicated that recombinant human endostatin-gold nanoparticles increased pericyte expression while inhibit vascular endothelial growth factor receptor 2 and anterior gradient 2 expression in metastatic colorectal cancer xenografts. In vitro, we uncovered that recombinant human endostatin-gold nanoparticles reduced cell migration and tube formation induced by anterior gradient 2 in human umbilical vein endothelial cells. Treatment with recombinant human endostatin-gold nanoparticles attenuated anterior gradient 2-mediated activation of MMP2, cMyc, VE-cadherin, phosphorylation of p38, and extracellular signal-regulated protein kinases 1 and 2 (ERK1/2) in human umbilical vein endothelial cells. Our findings demonstrated recombinant human endostatin-gold nanoparticles might normalize
Burrows, R. R.
1972-01-01
A particular type of three-impulse transfer between two circular orbits is analyzed. The possibility of three plane changes is recognized, and the problem is to optimally distribute these plane changes to minimize the sum of the individual impulses. Numerical difficulties and their solution are discussed. Numerical results obtained from a conjugate gradient technique are presented for both the case where the individual plane changes are unconstrained and for the case where they are constrained. Possibly not unexpectedly, multiple minima are found. The techniques presented could be extended to the finite burn case, but primarily the contents are addressed to preliminary mission design and vehicle sizing.
Wei, Yongjie; Ge, Baozhen; Wei, Yaolin
2009-03-20
In general, model-independent algorithms are sensitive to noise during laser particle size measurement. An improved conjugate gradient algorithm (ICGA) that can be used to invert particle size distribution (PSD) from diffraction data is presented. By use of the ICGA to invert simulated data with multiplicative or additive noise, we determined that additive noise is the main factor that induces distorted results. Thus the ICGA is amended by introduction of an iteration step-adjusting parameter and is used experimentally on simulated data and some samples. The experimental results show that the sensitivity of the ICGA to noise is reduced and the inverted results are in accord with the real PSD.
Collins, Jeffery D.; Volakis, John L.; Jin, Jian-Ming
1990-01-01
A new technique is presented for computing the scattering by 2-D structures of arbitrary composition. The proposed solution approach combines the usual finite element method with the boundary-integral equation to formulate a discrete system. This is subsequently solved via the conjugate gradient (CG) algorithm. A particular characteristic of the method is the use of rectangular boundaries to enclose the scatterer. Several of the resulting boundary integrals are therefore convolutions and may be evaluated via the fast Fourier transform (FFT) in the implementation of the CG algorithm. The solution approach offers the principal advantage of having O(N) memory demand and employs a 1-D FFT versus a 2-D FFT as required with a traditional implementation of the CGFFT algorithm. The speed of the proposed solution method is compared with that of the traditional CGFFT algorithm, and results for rectangular bodies are given and shown to be in excellent agreement with the moment method.
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
Minimum weight protection - Gradient method; Protection de poids minimum - Methode du gradient
Energy Technology Data Exchange (ETDEWEB)
Danon, R.
1958-12-15
After having recalled that, when considering a mobile installation, total weight has a crucial importance, and that, in the case of a nuclear reactor, a non neglectable part of weight is that of protection, this note presents an iterative method which results, for a given protection, to a configuration with a minimum weight. After a description of the problem, the author presents the theoretical formulation of the gradient method as it is applied to the concerned case. This application is then discussed, as well as its validity in terms of convergence and uniqueness. Its actual application is then reported, and possibilities of practical applications are evoked.
A new method of determining moisture gradient in wood
Zhiyong Cai
2008-01-01
Moisture gradient in wood and wood composites is one of most important factors that affects both physical stability and mechanical performance. This paper describes a method for measuring moisture gradient in lumber and engineering wood composites as it varies across material thickness. This innovative method employs a collimated radiation beam (x rays or [gamma] rays...
Gradient porous hydroxyapatite ceramics fabricated by freeze casting method
International Nuclear Information System (INIS)
Zuo Kaihui; Zhang Yuan; Jiang Dongliang; Zeng Yuping
2011-01-01
By controlling the cooling rates and the composition of slurries, the gradient porous hydroxyapatite ceramics are fabricated by the freeze casting method. According to the different cooling rate, the pores of HAP ceramics fabricated by gradient freeze casting are divided into three parts: one is lamellar pores, another is column pore and the last one is fine round pores. The laminated freeze casting is in favour of obtaining the gradient porous ceramics composed of different materials and the ceramics have unclear interfaces.
Discrete gradient methods for solving variational image regularisation models
International Nuclear Information System (INIS)
Grimm, V; McLachlan, Robert I; McLaren, David I; Quispel, G R W; Schönlieb, C-B
2017-01-01
Discrete gradient methods are well-known methods of geometric numerical integration, which preserve the dissipation of gradient systems. In this paper we show that this property of discrete gradient methods can be interesting in the context of variational models for image processing, that is where the processed image is computed as a minimiser of an energy functional. Numerical schemes for computing minimisers of such energies are desired to inherit the dissipative property of the gradient system associated to the energy and consequently guarantee a monotonic decrease of the energy along iterations, avoiding situations in which more computational work might lead to less optimal solutions. Under appropriate smoothness assumptions on the energy functional we prove that discrete gradient methods guarantee a monotonic decrease of the energy towards stationary states, and we promote their use in image processing by exhibiting experiments with convex and non-convex variational models for image deblurring, denoising, and inpainting. (paper)
Liu, Guhuan; Hu, Jinming; Zhang, Guoying; Liu, Shiyong
2015-07-15
Spatiotemporal switching of respective phototherapy modes at the cellular level with minimum side effects and high therapeutic efficacy is a major challenge for cancer phototherapy. Herein we demonstrate how to address this issue by employing photosensitizer-conjugated pH-responsive block copolymers in combination with intracellular endocytic pH gradients. At neutral pH corresponding to extracellular and cytosol milieu, the copolymers self-assemble into micelles with prominently quenched fluorescence emission and low (1)O2 generation capability, favoring a highly efficient photothermal module. Under mildly acidic pH associated with endolysosomes, protonation-triggered micelle-to-unimer transition results in recovered emission and enhanced photodynamic (1)O2 efficiency, which synergistically actuates release of encapsulated drugs, endosomal escape, and photochemical internalization processes.
Variational method for integrating radial gradient field
Legarda-Saenz, Ricardo; Brito-Loeza, Carlos; Rivera, Mariano; Espinosa-Romero, Arturo
2014-12-01
We propose a variational method for integrating information obtained from circular fringe pattern. The proposed method is a suitable choice for objects with radial symmetry. First, we analyze the information contained in the fringe pattern captured by the experimental setup and then move to formulate the problem of recovering the wavefront using techniques from calculus of variations. The performance of the method is demonstrated by numerical experiments with both synthetic and real data.
A Gradient Taguchi Method for Engineering Optimization
Hwang, Shun-Fa; Wu, Jen-Chih; He, Rong-Song
2017-10-01
To balance the robustness and the convergence speed of optimization, a novel hybrid algorithm consisting of Taguchi method and the steepest descent method is proposed in this work. Taguchi method using orthogonal arrays could quickly find the optimum combination of the levels of various factors, even when the number of level and/or factor is quite large. This algorithm is applied to the inverse determination of elastic constants of three composite plates by combining numerical method and vibration testing. For these problems, the proposed algorithm could find better elastic constants in less computation cost. Therefore, the proposed algorithm has nice robustness and fast convergence speed as compared to some hybrid genetic algorithms.
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.
A density gradient theory based method for surface tension calculations
DEFF Research Database (Denmark)
Liang, Xiaodong; Michelsen, Michael Locht; Kontogeorgis, Georgios
2016-01-01
The density gradient theory has been becoming a widely used framework for calculating surface tension, within which the same equation of state is used for the interface and bulk phases, because it is a theoretically sound, consistent and computationally affordable approach. Based on the observation...... that the optimal density path from the geometric mean density gradient theory passes the saddle point of the tangent plane distance to the bulk phases, we propose to estimate surface tension with an approximate density path profile that goes through this saddle point. The linear density gradient theory, which...... assumes linearly distributed densities between the two bulk phases, has also been investigated. Numerical problems do not occur with these density path profiles. These two approximation methods together with the full density gradient theory have been used to calculate the surface tension of various...
Fast gradient-based methods for Bayesian reconstruction of transmission and emission PET images
International Nuclear Information System (INIS)
Mumcuglu, E.U.; Leahy, R.; Zhou, Z.; Cherry, S.R.
1994-01-01
The authors describe conjugate gradient algorithms for reconstruction of transmission and emission PET images. The reconstructions are based on a Bayesian formulation, where the data are modeled as a collection of independent Poisson random variables and the image is modeled using a Markov random field. A conjugate gradient algorithm is used to compute a maximum a posteriori (MAP) estimate of the image by maximizing over the posterior density. To ensure nonnegativity of the solution, a penalty function is used to convert the problem to one of unconstrained optimization. Preconditioners are used to enhance convergence rates. These methods generally achieve effective convergence in 15--25 iterations. Reconstructions are presented of an 18 FDG whole body scan from data collected using a Siemens/CTI ECAT931 whole body system. These results indicate significant improvements in emission image quality using the Bayesian approach, in comparison to filtered backprojection, particularly when reprojections of the MAP transmission image are used in place of the standard attenuation correction factors
Woodward, Richard B; Spanias, John A; Hargrove, Levi J
2016-08-01
Powered lower limb prostheses have the ability to provide greater mobility for amputee patients. Such prostheses often have pre-programmed modes which can allow activities such as climbing stairs and descending ramps, something which many amputees struggle with when using non-powered limbs. Previous literature has shown how pattern classification can allow seamless transitions between modes with a high accuracy and without any user interaction. Although accurate, training and testing each subject with their own dependent data is time consuming. By using subject independent datasets, whereby a unique subject is tested against a pooled dataset of other subjects, we believe subject training time can be reduced while still achieving an accurate classification. We present here an intent recognition system using an artificial neural network (ANN) with a scaled conjugate gradient learning algorithm to classify gait intention with user-dependent and independent datasets for six unilateral lower limb amputees. We compare these results against a linear discriminant analysis (LDA) classifier. The ANN was found to have significantly lower classification error (P<;0.05) than LDA with all user-dependent step-types, as well as transitional steps for user-independent datasets. Both types of classifiers are capable of making fast decisions; 1.29 and 2.83 ms for the LDA and ANN respectively. These results suggest that ANNs can provide suitable and accurate offline classification in prosthesis gait prediction.
Conjugate descent formulation of backpropagation error in ...
African Journals Online (AJOL)
nique of backpropagation was popularized in a paper by Rumelhart, et al. ... the training of a multilayer neural network using a gradient descent approach applied to a .... superior convergence of the conjugate descent method over a standard ...
A hybrid optimization method for biplanar transverse gradient coil design
International Nuclear Information System (INIS)
Qi Feng; Tang Xin; Jin Zhe; Jiang Zhongde; Shen Yifei; Meng Bin; Zu Donglin; Wang Weimin
2007-01-01
The optimization of transverse gradient coils is one of the fundamental problems in designing magnetic resonance imaging gradient systems. A new approach is presented in this paper to optimize the transverse gradient coils' performance. First, in the traditional spherical harmonic target field method, high order coefficients, which are commonly ignored, are used in the first stage of the optimization process to give better homogeneity. Then, some cosine terms are introduced into the series expansion of stream function. These new terms provide simulated annealing optimization with new freedoms. Comparison between the traditional method and the optimized method shows that the inhomogeneity in the region of interest can be reduced from 5.03% to 1.39%, the coil efficiency increased from 3.83 to 6.31 mT m -1 A -1 and the minimum distance of these discrete coils raised from 1.54 to 3.16 mm
A composite step conjugate gradients squared algorithm for solving nonsymmetric linear systems
Chan, Tony; Szeto, Tedd
1994-03-01
We propose a new and more stable variant of the CGS method [27] for solving nonsymmetric linear systems. The method is based on squaring the Composite Step BCG method, introduced recently by Bank and Chan [1,2], which itself is a stabilized variant of BCG in that it skips over steps for which the BCG iterate is not defined and causes one kind of breakdown in BCG. By doing this, we obtain a method (Composite Step CGS or CSCGS) which not only handles the breakdowns described above, but does so with the advantages of CGS, namely, no multiplications by the transpose matrix and a faster convergence rate than BCG. Our strategy for deciding whether to skip a step does not involve any machine dependent parameters and is designed to skip near breakdowns as well as produce smoother iterates. Numerical experiments show that the new method does produce improved performance over CGS on practical problems.
An immersed-boundary method for conjugate heat transfer analysis
Energy Technology Data Exchange (ETDEWEB)
Song, Jeong Chul; Lee, Joon Sik [Seoul National University, Seoul (Korea, Republic of); Ahn, Joon [Kookmin University, Seoul (Korea, Republic of)
2017-05-15
An immersed-boundary method is proposed for the analysis of conjugate problems of convective heat transfer in conducting solids. In- side the solid body, momentum forcing is applied to set the velocity to zero. A thermal conductivity ratio and a heat capacity ratio, between the solid body and the fluid, are introduced so that the energy equation is reduced to the heat diffusion equation. At the solid fluid interface, an effective conductivity is introduced to satisfy the heat flux continuity. The effective thermal conductivity is obtained by considering the heat balance at the interface or by using a harmonic mean formulation. The method is first validated against the analytic solution to the heat transfer problem in a fully developed laminar channel flow with conducting solid walls. Then it is applied to a laminar channel flow with a heated, block-shaped obstacle to show its validity for geometry with sharp edges. Finally the validation for a curvilinear solid body is accomplished with a laminar flow through arrayed cylinders.
Myocardial perfusion MRI with sliding-window conjugate-gradient HYPR.
Ge, Lan; Kino, Aya; Griswold, Mark; Mistretta, Charles; Carr, James C; Li, Debiao
2009-10-01
First-pass perfusion MRI is a promising technique for detecting ischemic heart disease. However, the diagnostic value of the method is limited by the low spatial coverage, resolution, signal-to-noise ratio (SNR), and cardiac motion-related image artifacts. In this study we investigated the feasibility of using a method that combines sliding window and CG-HYPR methods (SW-CG-HYPR) to reduce the acquisition window for each slice while maintaining the temporal resolution of one frame per heartbeat in myocardial perfusion MRI. This method allows an increased number of slices, reduced motion artifacts, and preserves the relatively high SNR and spatial resolution of the "composite images." Results from eight volunteers demonstrate the feasibility of SW-CG-HYPR for accelerated myocardial perfusion imaging with accurate signal intensity changes of left ventricle blood pool and myocardium. Using this method the acquisition time per cardiac cycle was reduced by a factor of 4 and the number of slices was increased from 3 to 8 as compared to the conventional technique. The SNR of the myocardium at peak enhancement with SW-CG-HYPR (13.83 +/- 2.60) was significantly higher (P < 0.05) than the conventional turbo-FLASH protocol (8.40 +/- 1.62). Also, the spatial resolution of the myocardial perfection images was significantly improved. SW-CG-HYPR is a promising technique for myocardial perfusion MRI. (c) 2009 Wiley-Liss, Inc.
COVARIANCE ESTIMATION USING CONJUGATE GRADIENT FOR 3D CLASSIFICATION IN CRYO-EM.
Andén, Joakim; Katsevich, Eugene; Singer, Amit
2015-04-01
Classifying structural variability in noisy projections of biological macromolecules is a central problem in Cryo-EM. In this work, we build on a previous method for estimating the covariance matrix of the three-dimensional structure present in the molecules being imaged. Our proposed method allows for incorporation of contrast transfer function and non-uniform distribution of viewing angles, making it more suitable for real-world data. We evaluate its performance on a synthetic dataset and an experimental dataset obtained by imaging a 70S ribosome complex.
An improved conjugate gradient scheme to the solution of least squares SVM.
Chu, Wei; Ong, Chong Jin; Keerthi, S Sathiya
2005-03-01
The least square support vector machines (LS-SVM) formulation corresponds to the solution of a linear system of equations. Several approaches to its numerical solutions have been proposed in the literature. In this letter, we propose an improved method to the numerical solution of LS-SVM and show that the problem can be solved using one reduced system of linear equations. Compared with the existing algorithm for LS-SVM, the approach used in this letter is about twice as efficient. Numerical results using the proposed method are provided for comparisons with other existing algorithms.
Method to stimulate dose gradient in liquid media
International Nuclear Information System (INIS)
Scarlat, F.
1993-01-01
The depth absorbed dose from electrons with energy higher than 10 MeV shows a distribution with a big-percentage absorbed dose at the entrance surface and a small dose gradient. This is due to the big distance between the virtual focus and irradiated liquid medium. In order to stimulate dose gradient and decrease the surface dose, this paper presents a method for obtaining the second focus by means of a magnetostatic planar wiggler. Preliminary calculations indicated that the absorbed dose rate increases two-three times at the reference plane in the irradiated liquid medium. (Author)
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.
Pengpen, T; Soleimani, M
2015-06-13
Cone beam computed tomography (CBCT) is an imaging modality that has been used in image-guided radiation therapy (IGRT). For applications such as lung radiation therapy, CBCT images are greatly affected by the motion artefacts. This is mainly due to low temporal resolution of CBCT. Recently, a dual modality of electrical impedance tomography (EIT) and CBCT has been proposed, in which the high temporal resolution EIT imaging system provides motion data to a motion-compensated algebraic reconstruction technique (ART)-based CBCT reconstruction software. High computational time associated with ART and indeed other variations of ART make it less practical for real applications. This paper develops a motion-compensated conjugate gradient least-squares (CGLS) algorithm for CBCT. A motion-compensated CGLS offers several advantages over ART-based methods, including possibilities for explicit regularization, rapid convergence and parallel computations. This paper for the first time demonstrates motion-compensated CBCT reconstruction using CGLS and reconstruction results are shown in limited data CBCT considering only a quarter of the full dataset. The proposed algorithm is tested using simulated motion data in generic motion-compensated CBCT as well as measured EIT data in dual EIT-CBCT imaging. © 2015 The Author(s) Published by the Royal Society. All rights reserved.
A gradient activation method for direct methanol fuel cells
International Nuclear Information System (INIS)
Liu, Guicheng; Yang, Zhaoyi; Halim, Martin; Li, Xinyang; Wang, Manxiang; Kim, Ji Young; Mei, Qiwen; Wang, Xindong; Lee, Joong Kee
2017-01-01
Highlights: • A gradient activation method was reported firstly for direct methanol fuel cells. • The activity recovery of Pt-based catalyst was introduced into the novel activation process. • The new activation method led to prominent enhancement of DMFC performance. • DMFC performance was improved with the novel activation step by step within 7.5 h. - Abstract: To realize gradient activation effect and recover catalytic activity of catalyst in a short time, a gradient activation method has firstly been proposed for enhancing discharge performance and perfecting activation mechanism of the direct methanol fuel cell (DMFC). This method includes four steps, i.e. proton activation, activity recovery activation, H_2-O_2 mode activation and forced discharging activation. The results prove that the proposed method has gradually realized replenishment of water and protons, recovery of catalytic activity of catalyst, establishment of transfer channels for electrons, protons, and oxygen, and optimization of anode catalyst layer for methanol transfer in turn. Along with the novel activation process going on, the DMFC discharge performance has been improved, step by step, to more than 1.9 times higher than that of the original one within 7.5 h. This method provides a practicable activation way for the real application of single DMFCs and stacks.
Method to conjugate polysaccharide antigens to surfaces for the detection of antibodies.
Boas, Ulrik; Lind, Peter; Riber, Ulla
2014-11-15
A new generic method for the conjugation of lipopolysaccharide (LPS)-derived polysaccharide antigens from gram-negative bacteria has been developed using Salmonella as a model. After removal of lipid A from the LPS by mild acidolysis, the polysaccharide antigen was conjugated to polystyrene microbeads modified with N-alkyl hydroxylamine and N-alkyl-O-methyl hydroxylamine surface groups by incubation of antigen and beads for 16 h at 40 °C without the need for coupling agents. The efficiency of the new method was evaluated by flow cytometry in model samples and serum samples containing antibodies against Salmonella typhimurium and Salmonella dublin. The presented method was compared with a similar method for conjugation of Salmonella polysaccharide antigens to surfaces. Here, the new method showed higher antigen coupling efficiency by detecting low concentrations of antibodies. Furthermore, the polysaccharide-conjugated beads showed preserved bioactivity after 1 year of use. Copyright © 2014 Elsevier Inc. All rights reserved.
Application of heat-balance integral method to conjugate thermal explosion
Directory of Open Access Journals (Sweden)
Novozhilov Vasily
2009-01-01
Full Text Available Conjugate thermal explosion is an extension of the classical theory, proposed and studied recently by the author. The paper reports application of heat-balance integral method for developing phase portraits for systems undergoing conjugate thermal explosion. The heat-balance integral method is used as an averaging method reducing partical differential equation problem to the set of first-order ordinary differential equations. The latter reduced problem allows natural interpretation in appropriately chosen phase space. It is shown that, with the help of heat-balance integral technique, conjugate thermal explosion problem can be described with a good accuracy by the set of non-linear first-order differential equations involving complex error function. Phase trajectories are presented for typical regimes emerging in conjugate thermal explosion. Use of heat-balance integral as a spatial averaging method allows efficient description of system evolution to be developed.
Using nuclear methods for analyzing materials and determining concentration gradients
International Nuclear Information System (INIS)
Darras, R.
After reviewing the various type of nuclear chemical analysis methods, the possibilities of analysis by activation and direct observation of nuclear reactions are specifically described. These methods make it possible to effect analyses of trace-elements or impurities, even as traces, in materials, with selectivity, accuracy and great sensitivity. This latter property makes them advantageous too for determining major elements in small quantities of available matter. Furthermore, they lend themselves to carrying out superficial analyses and the determination of concentration gradients, given the careful choice of the nature and energy of the incident particles. The paper is illustrated with typical examples of analyses on steels, pure iron, refractory metals, etc [fr
Gradient augmented level set method for phase change simulations
Anumolu, Lakshman; Trujillo, Mario F.
2018-01-01
A numerical method for the simulation of two-phase flow with phase change based on the Gradient-Augmented-Level-set (GALS) strategy is presented. Sharp capturing of the vaporization process is enabled by: i) identification of the vapor-liquid interface, Γ (t), at the subgrid level, ii) discontinuous treatment of thermal physical properties (except for μ), and iii) enforcement of mass, momentum, and energy jump conditions, where the gradients of the dependent variables are obtained at Γ (t) and are consistent with their analytical expression, i.e. no local averaging is applied. Treatment of the jump in velocity and pressure at Γ (t) is achieved using the Ghost Fluid Method. The solution of the energy equation employs the sub-grid knowledge of Γ (t) to discretize the temperature Laplacian using second-order one-sided differences, i.e. the numerical stencil completely resides within each respective phase. To carefully evaluate the benefits or disadvantages of the GALS approach, the standard level set method is implemented and compared against the GALS predictions. The results show the expected trend that interface identification and transport are predicted noticeably better with GALS over the standard level set. This benefit carries over to the prediction of the Laplacian and temperature gradients in the neighborhood of the interface, which are directly linked to the calculation of the vaporization rate. However, when combining the calculation of interface transport and reinitialization with two-phase momentum and energy, the benefits of GALS are to some extent neutralized, and the causes for this behavior are identified and analyzed. Overall the additional computational costs associated with GALS are almost the same as those using the standard level set technique.
Güntürkün, Rüştü
2010-08-01
In this study, Elman recurrent neural networks have been defined by using conjugate gradient algorithm in order to determine the depth of anesthesia in the continuation stage of the anesthesia and to estimate the amount of medicine to be applied at that moment. The feed forward neural networks are also used for comparison. The conjugate gradient algorithm is compared with back propagation (BP) for training of the neural Networks. The applied artificial neural network is composed of three layers, namely the input layer, the hidden layer and the output layer. The nonlinear activation function sigmoid (sigmoid function) has been used in the hidden layer and the output layer. EEG data has been recorded with Nihon Kohden 9200 brand 22-channel EEG device. The international 8-channel bipolar 10-20 montage system (8 TB-b system) has been used in assembling the recording electrodes. EEG data have been recorded by being sampled once in every 2 milliseconds. The artificial neural network has been designed so as to have 60 neurons in the input layer, 30 neurons in the hidden layer and 1 neuron in the output layer. The values of the power spectral density (PSD) of 10-second EEG segments which correspond to the 1-50 Hz frequency range; the ratio of the total power of PSD values of the EEG segment at that moment in the same range to the total of PSD values of EEG segment taken prior to the anesthesia.
Method to create gradient index in a polymer
Dirk, Shawn M; Johnson, Ross Stefan; Boye, Robert; Descour, Michael R; Sweatt, William C; Wheeler, David R; Kaehr, Bryan James
2014-10-14
Novel photo-writable and thermally switchable polymeric materials exhibit a refractive index change of .DELTA.n.gtoreq.1.0 when exposed to UV light or heat. For example, lithography can be used to convert a non-conjugated precursor polymer to a conjugated polymer having a higher index-of-refraction. Further, two-photon lithography can be used to pattern high-spatial frequency structures.
Learning Unknown Structure in CRFs via Adaptive Gradient Projection Method
Directory of Open Access Journals (Sweden)
Wei Xue
2016-08-01
Full Text Available We study the problem of fitting probabilistic graphical models to the given data when the structure is not known. More specifically, we focus on learning unknown structure in conditional random fields, especially learning both the structure and parameters of a conditional random field model simultaneously. To do this, we first formulate the learning problem as a convex minimization problem by adding an l_2-regularization to the node parameters and a group l_1-regularization to the edge parameters, and then a gradient-based projection method is proposed to solve it which combines an adaptive stepsize selection strategy with a nonmonotone line search. Extensive simulation experiments are presented to show the performance of our approach in solving unknown structure learning problems.
Czech Academy of Sciences Publication Activity Database
Vlček, Jan; Lukšan, Ladislav
2015-01-01
Roč. 30, č. 3 (2015), s. 616-633 ISSN 1055-6788 R&D Projects: GA ČR GA13-06684S Institutional support: RVO:67985807 Keywords : unconstrained minimization * variable metric methods * limited-memory methods * the BFGS update * conjugate directions * numerical results Subject RIV: BA - General Mathematics Impact factor: 0.841, year: 2015
Directory of Open Access Journals (Sweden)
Zeng-Rong Hao
2014-11-01
Full Text Available The performance of modern heavy-duty gas turbines is greatly determined by the accurate numerical predictions of thermal loading on the hot-end components. The purpose of this paper is: (1 to present an approach applying a novel numerical technique—the discontinuous Galerkin (DG method—to conjugate heat transfer (CHT simulations, develop the engineering-oriented numerical platform, and validate the feasibility of the methodology and tool preliminarily; and (2 to utilize the constructed platform to investigate the aerothermodynamic features of a typical transonic turbine vane with convection cooling. Fluid dynamic and solid heat conductive equations are discretized into explicit DG formulations. A centroid-expanded Taylor basis is adopted for various types of elements. The Bassi-Rebay method is used in the computation of gradients. A coupled strategy based on a data exchange process via numerical flux on interface quadrature points is simply devised. Additionally, various turbulence Reynolds-Averaged-Navier-Stokes (RANS models and the local-variable-based transition model γ-Reθ are assimilated into the integral framework, combining sophisticated modelling with the innovative algorithm. Numerical tests exhibit good consistency between computational and analytical or experimental results, demonstrating that the presented approach and tool can handle well general CHT simulations. Application and analysis in the turbine vane, focusing on features around where there in cluster exist shock, separation and transition, illustrate the effects of Bradshaw’s shear stress limitation and separation-induced-transition modelling. The general overestimation of heat transfer intensity behind shock is conjectured to be associated with compressibility effects on transition modeling. This work presents an unconventional formulation in CHT problems and achieves its engineering applications in gas turbines.
Santos Basin Geological Structures Mapped by Cross-gradient Method
Jilinski, P.; Fontes, S. L.
2011-12-01
Introduction We mapped regional-scale geological structures localized in offshore zone Santos Basin, South-East Brazilian Coast. The region is dominated by transition zone from oceanic to continental crust. Our objective was to determine the imprint of deeper crustal structures from correlation between bathymetric, gravity and magnetic anomaly maps. The region is extensively studied for oil and gas deposits including large tectonic sub-salt traps. Our method is based on gradient directions and their magnitudes product. We calculate angular differences and cross-product and access correlation between properties and map structures. Theory and Method We used angular differences and cross-product to determine correlated region between bathymetric, free-air gravity and magnetic anomaly maps. This gradient based method focuses on borders of anomalies and uses its morphological properties to access correlation between their sources. We generated maps of angles and cross-product distribution to locate correlated regions. Regional scale potential fields maps of FA and MA are a reflection of the overlaying and overlapping effects of the adjacent structures. Our interest was in quantifying and characterizing the relation between shapes of magnetic anomalies and gravity anomalies. Results Resulting maps show strong correlation between bathymetry and gravity anomaly and bathymetry and magnetic anomaly for large strictures including Serra do Mar, shelf, continental slope and rise. All maps display the regional dominance of NE-SW geological structures alignment parallel to the shore. Special interest is presented by structures transgressing this tendency. Magnetic, gravity anomaly and bathymetry angles map show large correlated region over the shelf zone and smaller scale NE-SW banded structures over abyssal plane. From our interpretation the large band of inverse correlation adjacent to the shore is generated by the gravity effect of Serra do Mar. Disrupting structures including
Energy Technology Data Exchange (ETDEWEB)
Roberto, F.F.; Glenn, A.W.; Ward, T.E.
1990-08-07
A method of genetically manipulating an acidophilic bacteria is provided by two different procedures. Using electroporation, chimeric and broad-host range plasmids are introduced into Acidiphilium. Conjugation is also employed to introduce broad-host range plasmids into Acidiphilium at neutral pH.
Penyelesaian Persamaan Poisson 2D dengan Menggunakan Metode Gauss-Seidel dan Conjugate Gradien
Mahmudah, Dewi Erla; Naf'an, Muhammad Zidny
2017-01-01
In this paper we focus on solution of 2D Poisson equation numerically. 2D Poisson equation is a partial differential equation of second order elliptical type. This equation is a particular form or non-homogeneous form of the Laplace equation. The solution of 2D Poisson equation is performed numerically using Gauss Seidel method and Conjugate Gradient method. The result is the value using Gauss Seidel method and Conjugate Gradient method is same. But, consider the iteration process, the conver...
den Braver, Michiel W.; Vermeulen, Nico P.E.; Commandeur, Jan N.M.
2017-01-01
Modification of cellular macromolecules by reactive drug metabolites is considered to play an important role in the initiation of tissue injury by many drugs. Detection and identification of reactive intermediates is often performed by analyzing the conjugates formed after trapping by glutathione
Energy Technology Data Exchange (ETDEWEB)
Hu, Rui, E-mail: rhu@anl.gov; Yu, Yiqi
2016-11-15
Highlights: • Developed a computationally efficient method for full-core conjugate heat transfer modeling of sodium fast reactors. • Applied fully-coupled JFNK solution scheme to avoid the operator-splitting errors. • The accuracy and efficiency of the method is confirmed with a 7-assembly test problem. • The effects of different spatial discretization schemes are investigated and compared to the RANS-based CFD simulations. - Abstract: For efficient and accurate temperature predictions of sodium fast reactor structures, a 3-D full-core conjugate heat transfer modeling capability is developed for an advanced system analysis tool, SAM. The hexagon lattice core is modeled with 1-D parallel channels representing the subassembly flow, and 2-D duct walls and inter-assembly gaps. The six sides of the hexagon duct wall and near-wall coolant region are modeled separately to account for different temperatures and heat transfer between coolant flow and each side of the duct wall. The Jacobian Free Newton Krylov (JFNK) solution method is applied to solve the fluid and solid field simultaneously in a fully coupled fashion. The 3-D full-core conjugate heat transfer modeling capability in SAM has been demonstrated by a verification test problem with 7 fuel assemblies in a hexagon lattice layout. Additionally, the SAM simulation results are compared with RANS-based CFD simulations. Very good agreements have been achieved between the results of the two approaches.
International Nuclear Information System (INIS)
Favre, F.; Colomer, G.; Lehmkuhl, O.; Oliva, A.
2016-01-01
Dynamic and thermal interaction problems involving fluids and solids were studied through a finite volume-based Navier-Stokes solver, combined with immersed-boundary techniques and the net radiation method. Source terms were included in the momentum and energy equations to enforce the non-slip condition and the conjugate boundary condition including the radiative heat exchange. Code validation was performed through the simulation of two cases from the literature: conjugate natural convection in a square cavity with a conducting side wall; and a cubical cavity with conducting walls and a heat source. The accuracy of the methodology and the validation of the inclusion of moving bodies into the simulation was performed via a theoretical case (paper)
Hoekstra, A.G.; Sloot, P.M.A.; Haan, M.J.; Hertzberger, L.O.; van Leeuwen, J.
1991-01-01
New developments in Computer Science, both hardware and software, offer researchers, such as physicists, unprecedented possibilities to solve their computational intensive problems.However, full exploitation of e.g. new massively parallel computers, parallel languages or runtime environments
Free terminal time optimal control problem of an HIV model based on a conjugate gradient method.
Jang, Taesoo; Kwon, Hee-Dae; Lee, Jeehyun
2011-10-01
The minimum duration of treatment periods and the optimal multidrug therapy for human immunodeficiency virus (HIV) type 1 infection are considered. We formulate an optimal tracking problem, attempting to drive the states of the model to a "healthy" steady state in which the viral load is low and the immune response is strong. We study an optimal time frame as well as HIV therapeutic strategies by analyzing the free terminal time optimal tracking control problem. The minimum duration of treatment periods and the optimal multidrug therapy are found by solving the corresponding optimality systems with the additional transversality condition for the terminal time. We demonstrate by numerical simulations that the optimal dynamic multidrug therapy can lead to the long-term control of HIV by the strong immune response after discontinuation of therapy.
Jönsthövel, T.B.; Van Gijzen, M.B.; MacLachlan, S.; Vuik, C.; Scarpas, A.
2012-01-01
Many applications in computational science and engineering concern composite materials, which are characterized by large discontinuities in the material properties. Such applications require fine-scale finite-element meshes, which lead to large linear systems that are challenging to solve with
A camera based calculation of 99m Tc-MAG-3 clearance using conjugate views method
International Nuclear Information System (INIS)
Hojabr, M.; Rajabi, H.; Eftekhari, M.
2004-01-01
Background: measurement of absolute or different renal function using radiotracers plays an important role in the clinical management of various renal diseases. Gamma camera quantitative methods is approximations of renal clearance may potentially be as accurate as plasma clearance methods. However some critical factors such as kidney depth and background counts are still troublesome in the use of this technique. In this study the conjugate-view method along with some background correction technique have been used for the measurement of renal activity in 99m Tc- MAG 3 renography. Transmission data were used for attenuation correction and the source volume was considered for accurate background subtraction. Materials and methods: the study was performed in 35 adult patients referred to our department for conventional renography and ERPF calculation. Depending on patients weight approximately 10-15 mCi 99 Tc-MAG 3 was injected in the form of a sharp bolus and 60 frames of 1 second followed by 174 frames of 10 seconds were acquired for each patient. Imaging was performed on a dual-head gamma camera(SOLUS; SunSpark10, ADAC Laboratories, Milpitas, CA) anterior and posterior views were acquired simultaneously. A LEHR collimator was used to correct the scatter for the emission and transmission images. Buijs factor was applied on background counts before background correction (Rutland-Patlak equation). gamma camera clearance was calculated using renal uptake in 1-2, 1.5-2.5, 2-3 min. The same procedure was repeated for both renograms obtained from posterior projection and conjugated views. The plasma clearance was also directly calculated by three blood samples obtained at 40, 80, 120 min after injection. Results: 99 Tc-MAG 3 clearance using direct sampling method were used as reference values and compared to the results obtained from the renograms. The maximum correlation was found between conjugate view clearance at 2-3 min (R=0.99, R 2 =0.98, SE=15). Conventional
Ma, Heng; Yang, Jun; Liu, Jing; Ge, Lan; An, Jing; Tang, Qing; Li, Han; Zhang, Yu; Chen, David; Wang, Yong; Liu, Jiabin; Liang, Zhigang; Lin, Kai; Jin, Lixin; Bi, Xiaoming; Li, Kuncheng; Li, Debiao
2012-04-15
Myocardial perfusion magnetic resonance imaging (MRI) with sliding-window conjugate-gradient highly constrained back-projection reconstruction (SW-CG-HYPR) allows whole left ventricular coverage, improved temporal and spatial resolution and signal/noise ratio, and reduced cardiac motion-related image artifacts. The accuracy of this technique for detecting coronary artery disease (CAD) has not been determined in a large number of patients. We prospectively evaluated the diagnostic performance of myocardial perfusion MRI with SW-CG-HYPR in patients with suspected CAD. A total of 50 consecutive patients who were scheduled for coronary angiography with suspected CAD underwent myocardial perfusion MRI with SW-CG-HYPR at 3.0 T. The perfusion defects were interpreted qualitatively by 2 blinded observers and were correlated with x-ray angiographic stenoses ≥50%. The prevalence of CAD was 56%. In the per-patient analysis, the sensitivity, specificity, positive predictive value, negative predictive value, and accuracy of SW-CG-HYPR was 96% (95% confidence interval 82% to 100%), 82% (95% confidence interval 60% to 95%), 87% (95% confidence interval 70% to 96%), 95% (95% confidence interval 74% to100%), and 90% (95% confidence interval 82% to 98%), respectively. In the per-vessel analysis, the corresponding values were 98% (95% confidence interval 91% to 100%), 89% (95% confidence interval 80% to 94%), 86% (95% confidence interval 76% to 93%), 99% (95% confidence interval 93% to 100%), and 93% (95% confidence interval 89% to 97%), respectively. In conclusion, myocardial perfusion MRI using SW-CG-HYPR allows whole left ventricular coverage and high resolution and has high diagnostic accuracy in patients with suspected CAD. Copyright © 2012 Elsevier Inc. All rights reserved.
PHASE GRADIENT METHOD OF MAGNETIC FIELD MEASUREMENTS IN ELECTRIC VEHICLES
Directory of Open Access Journals (Sweden)
N. G. Ptitsyna
2013-01-01
Full Text Available Operation of electric and hybrid vehicles demands real time magnetic field control, for instance, for fire and electromagnetic safety. The article deals with a method of magnetic field measurements onboard electric cars taking into account peculiar features of these fields. The method is based on differential methods of measurements, and minimizes the quantity of magnetic sensors.
Hybridization of the probability perturbation method with gradient information
DEFF Research Database (Denmark)
Johansen, Kent; Caers, J.; Suzuki, S.
2007-01-01
Geostatistically based history-matching methods make it possible to devise history-matching strategies that will honor geologic knowledge about the reservoir. However, the performance of these methods is known to be impeded by slow convergence rates resulting from the stochastic nature of the alg...
A gradient-based method for segmenting FDG-PET images: methodology and validation
International Nuclear Information System (INIS)
Geets, Xavier; Lee, John A.; Gregoire, Vincent; Bol, Anne; Lonneux, Max
2007-01-01
A new gradient-based method for segmenting FDG-PET images is described and validated. The proposed method relies on the watershed transform and hierarchical cluster analysis. To allow a better estimation of the gradient intensity, iteratively reconstructed images were first denoised and deblurred with an edge-preserving filter and a constrained iterative deconvolution algorithm. Validation was first performed on computer-generated 3D phantoms containing spheres, then on a real cylindrical Lucite phantom containing spheres of different volumes ranging from 2.1 to 92.9 ml. Moreover, laryngeal tumours from seven patients were segmented on PET images acquired before laryngectomy by the gradient-based method and the thresholding method based on the source-to-background ratio developed by Daisne (Radiother Oncol 2003;69:247-50). For the spheres, the calculated volumes and radii were compared with the known values; for laryngeal tumours, the volumes were compared with the macroscopic specimens. Volume mismatches were also analysed. On computer-generated phantoms, the deconvolution algorithm decreased the mis-estimate of volumes and radii. For the Lucite phantom, the gradient-based method led to a slight underestimation of sphere volumes (by 10-20%), corresponding to negligible radius differences (0.5-1.1 mm); for laryngeal tumours, the segmented volumes by the gradient-based method agreed with those delineated on the macroscopic specimens, whereas the threshold-based method overestimated the true volume by 68% (p = 0.014). Lastly, macroscopic laryngeal specimens were totally encompassed by neither the threshold-based nor the gradient-based volumes. The gradient-based segmentation method applied on denoised and deblurred images proved to be more accurate than the source-to-background ratio method. (orig.)
Methods for Fabricating Gradient Alloy Articles with Multi-Functional Properties
Hofmann, Douglas C. (Inventor); Borgonia, John Paul C. (Inventor); Dillon, Robert P. (Inventor); Suh, Eric J. (Inventor); Mulder, Jerry L. (Inventor); Gardner, Paul B. (Inventor)
2015-01-01
Systems and methods for fabricating multi-functional articles comprised of additively formed gradient materials are provided. The fabrication of multi-functional articles using the additive deposition of gradient alloys represents a paradigm shift from the traditional way that metal alloys and metal/metal alloy parts are fabricated. Since a gradient alloy that transitions from one metal to a different metal cannot be fabricated through any conventional metallurgy techniques, the technique presents many applications. Moreover, the embodiments described identify a broad range of properties and applications.
Chen, Y.-M.; Koniges, A. E.; Anderson, D. V.
1989-10-01
The biconjugate gradient method (BCG) provides an attractive alternative to the usual conjugate gradient algorithms for the solution of sparse systems of linear equations with nonsymmetric and indefinite matrix operators. A preconditioned algorithm is given, whose form resembles the incomplete L-U conjugate gradient scheme (ILUCG2) previously presented. Although the BCG scheme requires the storage of two additional vectors, it converges in a significantly lesser number of iterations (often half), while the number of calculations per iteration remains essentially the same.
Directory of Open Access Journals (Sweden)
Melanie B. Berkmen
2014-08-01
Full Text Available Students are engaged and improve their critical thinking skills in laboratory courses when they have the opportunity to design and conduct inquiry-based experiments that generate novel results. A discovery-driven project for a microbiology, genetics, or multidisciplinary research laboratory course was developed to familiarize students with the scientific method. In this multi-lab module, students determine whether their chosen stress conditions induce conjugation and/or cell death of the model BSL-1 Gram-positive bacterium Bacillus subtilis. Through consultation of the primary literature, students identify conditions or chemicals that can elicit DNA damage, the SOS response, and/or cellular stress. In groups, students discuss their selected conditions, develop their hypotheses and experimental plans, and formulate their positive and negative controls. Students then subject the B. subtilis donor cells to the stress conditions, mix donors with recipients to allow mating, and plate serial dilutions of the mixtures on selective plates to measure how the treatments affect conjugation frequency and donor cell viability. Finally, students analyze and discuss their collective data in light of their controls. The goals of this module are to encourage students to be actively involved in the scientific process while contributing to our understanding of the conditions that stimulate horizontal gene transfer in bacteria.
International Nuclear Information System (INIS)
Roidl, B.; Meinke, M.; Schröder, W.
2014-01-01
Highlights: • Reformulated synthetic turbulence generation method (RSTGM) is applied. • Zonal RANS-LES method is applied to boundary layers at pressure gradients. • Good agreement with the pure LES and other reference data is obtained. • The RSTGM is applicable to pressure gradient flows without modification. • RANS-to-LES boundary should be located where -1·10 6 6 is satisfied. -- Abstract: The reformulated synthetic turbulence generation (RSTG) method is used to compute by a fully coupled zonal RANS-LES approach turbulent non-zero-pressure gradient boundary layers. The quality of the RSTG method, which is based on the same shape functions and length scale distributions as in zero-pressure gradient flow, is discussed by comparing the zonal RANS-LES findings with pure LES, pure RANS, direct numerical simulation (DNS), and experimental data. For the favorable pressure gradient (FPG) simulation the RANS-to-LES transition occurs in the accelerated flow region and for the adverse pressure gradient (APG) case it is located in the decelerated flow region. The results of the time and spanwise averaged skin-friction distributions, velocity profiles, and Reynolds stress distributions of the zonal RANS-LES simulation show a satisfactory to good agreement with the pure LES, reference DNS, and experimental data. The quality of the findings shows that the rigorous formulation of the synthetic turbulence generation makes the RSTG method applicable without a priori knowledge of the flow properties but those determined by the RANS solution and without using additional control planes to regulate the shear stress budget to a wide range of Reynolds numbers and pressure gradients. The method is a promising approach to formulate embedded RANS-to-LES boundaries in flow regions where the Pohlhausen or acceleration parameter satisfies -1·10 -6 ⩽K⩽2·10 -6
Zhou, J.; Danilov, D.; Notten, P.H.L.
2006-01-01
An electrochemical method has been developed for the in situ determination of concentration gradients in the electrolyte of sealed Li-ion batteries by measuring the potential difference between microreference electrodes. Formulas relating the concentration gradient and the potential difference
HNO3 fluxes to a deciduous forest derived using gradient and REA methods
DEFF Research Database (Denmark)
Pryor, S.C.; Barthelmie, R.J.; Jensen, B.
2002-01-01
Summertime nitric acid concentrations over a deciduous forest in the midwestern United States are reported, which range between 0.36 and 3.3 mug m(-3). Fluxes to the forest are computed using the relaxed eddy accumulation technique and gradient methods. In accord with previous studies, the results...... indicate substantial uncertainties in the gradient-based calculations. The relaxed eddy accumulation (REA) derived fluxes are physically reasonable and are shown to be of similar magnitude to dry deposition estimates from gradient sampling. The REA derived mean deposition velocity is approximately 3 cm s......(-1), which is also comparable to growing season estimates derived by Meyers et al. for a similar deciduous forest. Occasional inverted concentration gradients and fluxes are observed but most are not statistically significant. Data are also presented that indicate substantial through canopy...
Boundedness and convergence of online gradient method with penalty for feedforward neural networks.
Zhang, Huisheng; Wu, Wei; Liu, Fei; Yao, Mingchen
2009-06-01
In this brief, we consider an online gradient method with penalty for training feedforward neural networks. Specifically, the penalty is a term proportional to the norm of the weights. Its roles in the method are to control the magnitude of the weights and to improve the generalization performance of the network. By proving that the weights are automatically bounded in the network training with penalty, we simplify the conditions that are required for convergence of online gradient method in literature. A numerical example is given to support the theoretical analysis.
Subspace Barzilai-Borwein Gradient Method for Large-Scale Bound Constrained Optimization
International Nuclear Information System (INIS)
Xiao Yunhai; Hu Qingjie
2008-01-01
An active set subspace Barzilai-Borwein gradient algorithm for large-scale bound constrained optimization is proposed. The active sets are estimated by an identification technique. The search direction consists of two parts: some of the components are simply defined; the other components are determined by the Barzilai-Borwein gradient method. In this work, a nonmonotone line search strategy that guarantees global convergence is used. Preliminary numerical results show that the proposed method is promising, and competitive with the well-known method SPG on a subset of bound constrained problems from CUTEr collection
Gangarapu, S.; Marcelis, A.T.M.; Zuilhof, H.
2013-01-01
The pKa of the conjugate acids of alkanolamines, neurotransmitters, alkaloid drugs and nucleotide bases are calculated with density functional methods (B3LYP, M08-HX and M11-L) and ab initio methods (SCS-MP2, G3). Implicit solvent effects are included with a conductor-like polarizable continuum
Energetic Analysis of Conjugated Hydrocarbons Using the Interacting Quantum Atoms Method.
Jara-Cortés, Jesús; Hernández-Trujillo, Jesús
2018-07-05
A number of aromatic, antiaromatic, and nonaromatic organic molecules was analyzed in terms of the contributions to the electronic energy defined in the quantum theory of atoms in molecules and the interacting quantum atoms method. Regularities were found in the exchange and electrostatic interatomic energies showing trends that are closely related to those of the delocalization indices defined in the theory. In particular, the CC interaction energies between bonded atoms allow to rationalize the energetic stabilization associated with the bond length alternation in conjugated polyenes. This approach also provides support to Clar's sextet rules devised for aromatic systems. In addition, the H⋯H bonding found in some of the aromatic molecules studied was of an attractive nature, according to the stabilizing exchange interaction between the bonded H atoms. © 2017 Wiley Periodicals, Inc. © 2017 Wiley Periodicals, Inc.
Microreactor and method for preparing a radiolabeled complex or a biomolecule conjugate
Energy Technology Data Exchange (ETDEWEB)
Reichert, David E; Kenis, Paul J. A.; Wheeler, Tobias D; Desai, Amit V; Zeng, Dexing; Onal, Birce C
2015-03-17
A microreactor for preparing a radiolabeled complex or a biomolecule conjugate comprises a microchannel for fluid flow, where the microchannel comprises a mixing portion comprising one or more passive mixing elements, and a reservoir for incubating a mixed fluid. The reservoir is in fluid communication with the microchannel and is disposed downstream of the mixing portion. A method of preparing a radiolabeled complex includes flowing a radiometal solution comprising a metallic radionuclide through a downstream mixing portion of a microchannel, where the downstream mixing portion includes one or more passive mixing elements, and flowing a ligand solution comprising a bifunctional chelator through the downstream mixing portion. The ligand solution and the radiometal solution are passively mixed while in the downstream mixing portion to initiate a chelation reaction between the metallic radionuclide and the bifunctional chelator. The chelation reaction is completed to form a radiolabeled complex.
Syrakos, Alexandros; Varchanis, Stylianos; Dimakopoulos, Yannis; Goulas, Apostolos; Tsamopoulos, John
2017-12-01
Finite volume methods (FVMs) constitute a popular class of methods for the numerical simulation of fluid flows. Among the various components of these methods, the discretisation of the gradient operator has received less attention despite its fundamental importance with regards to the accuracy of the FVM. The most popular gradient schemes are the divergence theorem (DT) (or Green-Gauss) scheme and the least-squares (LS) scheme. Both are widely believed to be second-order accurate, but the present study shows that in fact the common variant of the DT gradient is second-order accurate only on structured meshes whereas it is zeroth-order accurate on general unstructured meshes, and the LS gradient is second-order and first-order accurate, respectively. This is explained through a theoretical analysis and is confirmed by numerical tests. The schemes are then used within a FVM to solve a simple diffusion equation on unstructured grids generated by several methods; the results reveal that the zeroth-order accuracy of the DT gradient is inherited by the FVM as a whole, and the discretisation error does not decrease with grid refinement. On the other hand, use of the LS gradient leads to second-order accurate results, as does the use of alternative, consistent, DT gradient schemes, including a new iterative scheme that makes the common DT gradient consistent at almost no extra cost. The numerical tests are performed using both an in-house code and the popular public domain partial differential equation solver OpenFOAM.
Accelerated gradient methods for total-variation-based CT image reconstruction
Energy Technology Data Exchange (ETDEWEB)
Joergensen, Jakob H.; Hansen, Per Christian [Technical Univ. of Denmark, Lyngby (Denmark). Dept. of Informatics and Mathematical Modeling; Jensen, Tobias L.; Jensen, Soeren H. [Aalborg Univ. (Denmark). Dept. of Electronic Systems; Sidky, Emil Y.; Pan, Xiaochuan [Chicago Univ., Chicago, IL (United States). Dept. of Radiology
2011-07-01
Total-variation (TV)-based CT image reconstruction has shown experimentally to be capable of producing accurate reconstructions from sparse-view data. In particular TV-based reconstruction is well suited for images with piecewise nearly constant regions. Computationally, however, TV-based reconstruction is demanding, especially for 3D imaging, and the reconstruction from clinical data sets is far from being close to real-time. This is undesirable from a clinical perspective, and thus there is an incentive to accelerate the solution of the underlying optimization problem. The TV reconstruction can in principle be found by any optimization method, but in practice the large scale of the systems arising in CT image reconstruction preclude the use of memory-intensive methods such as Newton's method. The simple gradient method has much lower memory requirements, but exhibits prohibitively slow convergence. In the present work we address the question of how to reduce the number of gradient method iterations needed to achieve a high-accuracy TV reconstruction. We consider the use of two accelerated gradient-based methods, GPBB and UPN, to solve the 3D-TV minimization problem in CT image reconstruction. The former incorporates several heuristics from the optimization literature such as Barzilai-Borwein (BB) step size selection and nonmonotone line search. The latter uses a cleverly chosen sequence of auxiliary points to achieve a better convergence rate. The methods are memory efficient and equipped with a stopping criterion to ensure that the TV reconstruction has indeed been found. An implementation of the methods (in C with interface to Matlab) is available for download from http://www2.imm.dtu.dk/~pch/TVReg/. We compare the proposed methods with the standard gradient method, applied to a 3D test problem with synthetic few-view data. We find experimentally that for realistic parameters the proposed methods significantly outperform the standard gradient method. (orig.)
A Gradient Weighted Moving Finite-Element Method with Polynomial Approximation of Any Degree
Directory of Open Access Journals (Sweden)
Ali R. Soheili
2009-01-01
Full Text Available A gradient weighted moving finite element method (GWMFE based on piecewise polynomial of any degree is developed to solve time-dependent problems in two space dimensions. Numerical experiments are employed to test the accuracy and effciency of the proposed method with nonlinear Burger equation.
An Improved Local Gradient Method for Sea Surface Wind Direction Retrieval from SAR Imagery
Directory of Open Access Journals (Sweden)
Lizhang Zhou
2017-06-01
Full Text Available Sea surface wind affects the fluxes of energy, mass and momentum between the atmosphere and ocean, and therefore regional and global weather and climate. With various satellite microwave sensors, sea surface wind can be measured with large spatial coverage in almost all-weather conditions, day or night. Like any other remote sensing measurements, sea surface wind measurement is also indirect. Therefore, it is important to develop appropriate wind speed and direction retrieval models for different types of microwave instruments. In this paper, a new sea surface wind direction retrieval method from synthetic aperture radar (SAR imagery is developed. In the method, local gradients are computed in frequency domain by combining the operation of smoothing and computing local gradients in one step to simplify the process and avoid the difference approximation. This improved local gradients (ILG method is compared with the traditional two-dimensional fast Fourier transform (2D FFT method and local gradients (LG method, using interpolating wind directions from the European Centre for Medium-Range Weather Forecast (ECMWF reanalysis data and the Cross-Calibrated Multi-Platform (CCMP wind vector product. The sensitivities to the salt-and-pepper noise, the additive noise and the multiplicative noise are analyzed. The ILG method shows a better performance of retrieval wind directions than the other two methods.
Deflection monitoring for a box girder based on a modified conjugate beam method
Chen, Shi-Zhi; Wu, Gang; Xing, Tuo
2017-08-01
After several years of operation, a box girder bridge would commonly experience excessive deflection, which endangers the bridge’s life span as well as the safety of vehicles travelling on it. In order to avoid potential risks, it is essential to constantly monitor the defection of box girders. However, currently, the direct deflection monitoring methods are limited by the complicated environments beneath the bridges, such as rivers or other traffic lanes, which severely impede the layouts of the sensors. The other indirect deflection monitoring methods mostly do not thoroughly consider the inherent shear lag effect and shear deformation in the box girder, resulting in a rather large error. Under these circumstances, a deflection monitoring method suiting box girders is proposed in this article, based on the conjugate beam method and distributed long-gauge fibre Bragg grating (FBG) sensor. A lab experiment was conducted to verify the reliability and feasibility of this method under practical application. Further, the serviceability under different span-depth ratios and web thicknesses was examined through a finite element model.
Duijnhoven, van F.G.H.; Bastiaansen, C.W.M.
1999-01-01
A new method is presented to generate and to fixate compositional gradients in blends of two miscible and amorphous polymers. A compositional gradient is introduced into a solution of a polymer in a monomer by use of a centrifugal field, and this gradient is subsequently fixated by polymerization of
Sozer, Emre; Brehm, Christoph; Kiris, Cetin C.
2014-01-01
A survey of gradient reconstruction methods for cell-centered data on unstructured meshes is conducted within the scope of accuracy assessment. Formal order of accuracy, as well as error magnitudes for each of the studied methods, are evaluated on a complex mesh of various cell types through consecutive local scaling of an analytical test function. The tests highlighted several gradient operator choices that can consistently achieve 1st order accuracy regardless of cell type and shape. The tests further offered error comparisons for given cell types, leading to the observation that the "ideal" gradient operator choice is not universal. Practical implications of the results are explored via CFD solutions of a 2D inviscid standing vortex, portraying the discretization error properties. A relatively naive, yet largely unexplored, approach of local curvilinear stencil transformation exhibited surprisingly favorable properties
Lin
2000-05-01
To reduce the calculating time for the summations over linearly independent and minimal conjugated circuits of benzenoid hydrocarbons (BHs), an approximate method is proposed that counts only the numbers of the first four classes of conjugated circuits R1, R2, R3, and R4, respectively. By representation of BHs as custom-made "ring-block chains" and use of the techniques of Database and visual computing, an application software is realized that is much faster and more powerful than the old one based on an enumeration technique.
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.
An optimized target-field method for MRI transverse biplanar gradient coil design
International Nuclear Information System (INIS)
Zhang, Rui; Xu, Jing; Huang, Kefu; Zhang, Jue; Fang, Jing; Fu, Youyi; Li, Yangjing
2011-01-01
Gradient coils are essential components of magnetic resonance imaging (MRI) systems. In this paper, we present an optimized target-field method for designing a transverse biplanar gradient coil with high linearity, low inductance and small resistance, which can well satisfy the requirements of permanent-magnet MRI systems. In this new method, the current density is expressed by trigonometric basis functions with unknown coefficients in polar coordinates. Following the standard procedures, we construct an objective function with respect to the total square errors of the magnetic field at all target-field points with the penalty items associated with the stored magnetic energy and the dissipated power. By adjusting the two penalty factors and minimizing the objective function, the appropriate coefficients of the current density are determined. Applying the stream function method to the current density, the specific winding patterns on the planes can be obtained. A novel biplanar gradient coil has been designed using this method to operate in a permanent-magnet MRI system. In order to verify the validity of the proposed approach, the gradient magnetic field generated by the resulted current density has been calculated via the Biot–Savart law. The results have demonstrated the effectiveness and advantage of this proposed method
Strong source heat transfer simulations based on a GalerKin/Gradient - least - squares method
International Nuclear Information System (INIS)
Franca, L.P.; Carmo, E.G.D. do.
1989-05-01
Heat conduction problems with temperature-dependent strong sources are modeled by an equation with a laplacian term, a linear term and a given source distribution term. When the linear-temperature-dependent source term is much larger than the laplacian term, we have a singular perturbation problem. In this case, boundary layers are formed to satisfy the Dirichlet boundary conditions. Although this is an elliptic equation, the standard Galerkin method solution is contaminated by spurious oscillations in the neighborhood of the boundary layers. Herein we employ a Galerkin/Gradient-least-squares method which eliminates all pathological phenomena of the Galerkin method. The method is constructed by adding to the Galerkin method a mesh-dependent term obtained by the least-squares form of the gradient of the Euler-Lagrange equation. Error estimates, numerical simulations in one-and multi-dimensions are given that attest the good stability and accuracy properties of the method [pt
Pilling evaluation of patterned fabrics based on a gradient field method
Czech Academy of Sciences Publication Activity Database
Techniková, L.; Tunák, M.; Janáček, Jiří
2016-01-01
Roč. 41, č. 1 (2016), s. 97-101 ISSN 0971-0426 Institutional support: RVO:67985823 Keywords : 3D surface reconstruction * fabric pilling * gradient field method * patterned fabric * pills detection Subject RIV: JS - Reliability ; Quality Management, Testing Impact factor: 0.430, year: 2016
A blind deconvolution method based on L1/L2 regularization prior in the gradient space
Cai, Ying; Shi, Yu; Hua, Xia
2018-02-01
In the process of image restoration, the result of image restoration is very different from the real image because of the existence of noise, in order to solve the ill posed problem in image restoration, a blind deconvolution method based on L1/L2 regularization prior to gradient domain is proposed. The method presented in this paper first adds a function to the prior knowledge, which is the ratio of the L1 norm to the L2 norm, and takes the function as the penalty term in the high frequency domain of the image. Then, the function is iteratively updated, and the iterative shrinkage threshold algorithm is applied to solve the high frequency image. In this paper, it is considered that the information in the gradient domain is better for the estimation of blur kernel, so the blur kernel is estimated in the gradient domain. This problem can be quickly implemented in the frequency domain by fast Fast Fourier Transform. In addition, in order to improve the effectiveness of the algorithm, we have added a multi-scale iterative optimization method. This paper proposes the blind deconvolution method based on L1/L2 regularization priors in the gradient space can obtain the unique and stable solution in the process of image restoration, which not only keeps the edges and details of the image, but also ensures the accuracy of the results.
Applicability of Stokes method for measuring viscosity of mixtures with concentration gradient
Directory of Open Access Journals (Sweden)
César Medina
2017-12-01
Full Text Available After measuring density and viscosity of a mixture of glycerin and water contained in a vertical pipe, a variation of these properties according to depth is observed. These gradients are typical of non-equilibrium states related to the lower density of water and the fact that relatively long times are necessary to achieve homogeneity. In the same pipe, the falling velocity of five little spheres is measured as a function of depth, and then a numerical fit is performed which agrees very well with experimental data. Based on the generalization of these results, the applicability of Stokes method is discussed for measuring viscosity of mixtures with a concentration gradient.
Development of the CARS method for measurement of pressure and temperature gradients in centrifuges
International Nuclear Information System (INIS)
Zeltmann, A.H.; Valentini, J.J.
1983-12-01
These experiments evaluated the feasibility of applying the CARS technique to the measurement of UF 6 concentrations and pressure gradients in a gas centrifuge. The resultant CARS signals were properly related to system parameters as suggested by theory. The results have been used to guide design of an apparatus for making CARS measurements in a UF 6 gas centrifuge. Ease of measurement is expected for pressures as low as 0.1 torr. Temperature gradients can be measured by this technique with changes in the data acquisition method. 16 references, 8 figures, 2 tables
Analytical free energy gradient for the molecular Ornstein-Zernike self-consistent-field method
Directory of Open Access Journals (Sweden)
N.Yoshida
2007-09-01
Full Text Available An analytical free energy gradient for the molecular Ornstein-Zernike self-consistent-field (MOZ-SCF method is presented. MOZ-SCF theory is one of the theories to considering the solvent effects on the solute electronic structure in solution. [Yoshida N. et al., J. Chem. Phys., 2000, 113, 4974] Molecular geometries of water, formaldehyde, acetonitrile and acetone in water are optimized by analytical energy gradient formula. The results are compared with those from the polarizable continuum model (PCM, the reference interaction site model (RISM-SCF and the three dimensional (3D RISM-SCF.
International Nuclear Information System (INIS)
Al-Ejeh, Fares; Darby, Jocelyn M.; Thierry, Benjamin; Brown, Michael P.
2009-01-01
Introduction: Antibodies covalently conjugated with chelators such as 1,4,7,10-tetraazacyclododecane-1,4,7,10-tetraacetic acid (DOTA) are required for radioimmunoscintigraphy and radioimmunotherapy, which are of growing importance in cancer medicine. Method: Here, we report a suite of simple methods that provide a preclinical assessment package for evaluating the effects of DOTA conjugation on the in vitro and in vivo performance of monoclonal antibodies. We exemplify the use of these methods by investigating the effects of DOTA conjugation on the biochemical properties of the DAB4 clone of the La/SSB-specific murine monoclonal autoantibody, APOMAB (registered) , which is a novel malignant cell death ligand. Results: We have developed a 96-well microtiter-plate assay to measure directly the concentration of DOTA and other chelators in antibody-chelator conjugate solutions. Coupled with a commercial assay for measuring protein concentration, the dual microtiter-plate method can rapidly determine chelator/antibody ratios in the same plate. The biochemical properties of DAB4 immunoconjugates were altered as the DOTA/Ab ratio increased so that: (i) mass/charge ratio decreased; (ii) hydrodynamic radius increased; (iii) antibody immunoactivity decreased; (iv) rate of chelation of metal ions and specific radioactivity both increased and in vivo, (v) tumor uptake decreased as nonspecific uptake by liver and spleen increased. Conclusion: This simplified suite of methods readily identifies biochemical characteristics of the DOTA-immunoconjugates such as hydrodynamic diameter and decreased mass/charge ratio associated with compromised immunotargeting efficiency and, thus, may prove useful for optimizing conjugation procedures in order to maximize immunoconjugate-mediated radioimmunoscintigraphy and radioimmunotherapy.
Monte Carlo method for polarized radiative transfer in gradient-index media
International Nuclear Information System (INIS)
Zhao, J.M.; Tan, J.Y.; Liu, L.H.
2015-01-01
Light transfer in gradient-index media generally follows curved ray trajectories, which will cause light beam to converge or diverge during transfer and induce the rotation of polarization ellipse even when the medium is transparent. Furthermore, the combined process of scattering and transfer along curved ray path makes the problem more complex. In this paper, a Monte Carlo method is presented to simulate polarized radiative transfer in gradient-index media that only support planar ray trajectories. The ray equation is solved to the second order to address the effect induced by curved ray trajectories. Three types of test cases are presented to verify the performance of the method, which include transparent medium, Mie scattering medium with assumed gradient index distribution, and Rayleigh scattering with realistic atmosphere refractive index profile. It is demonstrated that the atmospheric refraction has significant effect for long distance polarized light transfer. - Highlights: • A Monte Carlo method for polarized radiative transfer in gradient index media. • Effect of curved ray paths on polarized radiative transfer is considered. • Importance of atmospheric refraction for polarized light transfer is demonstrated
A projection gradient method for computing ground state of spin-2 Bose–Einstein condensates
Energy Technology Data Exchange (ETDEWEB)
Wang, Hanquan, E-mail: hanquan.wang@gmail.com [School of Statistics and Mathematics, Yunnan University of Finance and Economics, Kunming, Yunnan Province, 650221 (China); Yunnan Tongchang Scientific Computing and Data Mining Research Center, Kunming, Yunnan Province, 650221 (China)
2014-10-01
In this paper, a projection gradient method is presented for computing ground state of spin-2 Bose–Einstein condensates (BEC). We first propose the general projection gradient method for solving energy functional minimization problem under multiple constraints, in which the energy functional takes real functions as independent variables. We next extend the method to solve a similar problem, where the energy functional now takes complex functions as independent variables. We finally employ the method into finding the ground state of spin-2 BEC. The key of our method is: by constructing continuous gradient flows (CGFs), the ground state of spin-2 BEC can be computed as the steady state solution of such CGFs. We discretized the CGFs by a conservative finite difference method along with a proper way to deal with the nonlinear terms. We show that the numerical discretization is normalization and magnetization conservative and energy diminishing. Numerical results of the ground state and their energy of spin-2 BEC are reported to demonstrate the effectiveness of the numerical method.
A projection gradient method for computing ground state of spin-2 Bose–Einstein condensates
International Nuclear Information System (INIS)
Wang, Hanquan
2014-01-01
In this paper, a projection gradient method is presented for computing ground state of spin-2 Bose–Einstein condensates (BEC). We first propose the general projection gradient method for solving energy functional minimization problem under multiple constraints, in which the energy functional takes real functions as independent variables. We next extend the method to solve a similar problem, where the energy functional now takes complex functions as independent variables. We finally employ the method into finding the ground state of spin-2 BEC. The key of our method is: by constructing continuous gradient flows (CGFs), the ground state of spin-2 BEC can be computed as the steady state solution of such CGFs. We discretized the CGFs by a conservative finite difference method along with a proper way to deal with the nonlinear terms. We show that the numerical discretization is normalization and magnetization conservative and energy diminishing. Numerical results of the ground state and their energy of spin-2 BEC are reported to demonstrate the effectiveness of the numerical method
Research on n-γ discrimination method based on spectrum gradient analysis of signals
International Nuclear Information System (INIS)
Luo Xiaoliang; Liu Guofu; Yang Jun; Wang Yueke
2013-01-01
Having discovered that there are distinct differences between the spectrum gradient of the output neutron and γ-ray signal from liquid scintillator detectors, this paper presented a n-γ discrimination method called spectrum gradient analysis (SGA) based on frequency-domain features of the pulse signals. The basic principle and feasibility of SGA method were discussed and the validity of n-γ discrimination results of SGA was verified by the associated particle neutron flight experiment. The discrimination performance of SGA was evaluated under different conditions of sampling rates ranging from 5 G/s to 250 M/s. The results show that SGA method exhibits insensitivity to noise, strong anti-interference ability, stable discrimination performance and lower amount of calculation in contrast with time-domain n-γ discrimination methods. (authors)
Ananiev, Sergey
2006-01-01
The paper demonstrates the equivalence between the optimality criteria (OC) method, initially proposed by Bendsoe & Kikuchi for topology optimization problem, and the projected gradient method. The equivalence is shown using Hestenes definition of Lagrange multipliers. Based on this development, an alternative formulation of the Karush-Kuhn-Tucker (KKT) condition is suggested. Such reformulation has some advantages, which will be also discussed in the paper. For verification purposes the modi...
International Nuclear Information System (INIS)
Dadachova, E.; Chappell, L.L.; Brechbiel, M.W.
1999-01-01
A simple spectrophotometric assay for determination of bifunctional polyazacarboxylate-macrocyclic ligands of different sizes that are conjugated to proteins has been developed for: 12-membered macrocycle DOTA (2-[4-nitrobenzyl]-1, 4, 7, 10-tetraazacyclododecane-N,N',N'',N'''-tetraacetic acid) and analogs, the 15-membered PEPA macrocycle (2-[4-nitrobenzyl]-1,4,7,10,13-pentaazacyclopentadecane-N,N',N'',N''',N'''' -pentaacetic acid), and the large 18-membered macrocycle HEHA (1,4,7,10,13,16-hexaazacyclooctadecane-N,N',N'',N''',N''''-hexaacetic acid). The method is based on titration of the blue-colored 1:1 Pb(II)-Arsenazo III (AAIII) complex with the polyazacarboxylate macrocyclic ligand in the concentration range of 0-2.5 μM, wherein color change occurring upon transchelation of the Pb(II) from the AAIII to the polyazamacrocyclic ligand is monitored at 656 nm. The assay is performed at ambient temperature within 20 min without any interfering interaction between the protein and Pb(II)-AA(III) complex. Thus, this method also provides a ligand-to-protein ratio (L/P ratio) that reflects the effective number of ligands per protein molecule available to radiolabeling. The method is not suitable for 14-membered TETA macrocycle (2-[4-nitrobenzyl]-1, 4, 8, 11-tetraazacyclotetradecane N,N',N'',N'''-tetraacetic acid) because of low stability constant of Pb(II)-TETA complex. The method is rapid, simple and may be customized for other polyazacarboxylate macrocyclic ligands
Improvement of GaN epilayer by gradient layer method with molecular-beam epitaxy
International Nuclear Information System (INIS)
Chen, Yen-Liang; Lo, Ikai; Gau, Ming-Hong; Hsieh, Chia-Ho; Sham, Meng-Wei; Pang, Wen-Yuan; Hsu, Yu-Chi; Tsai, Jenn-Kai; Schuber, Ralf; Schaadt, Daniel
2012-01-01
We demonstrated a molecular beam epitaxy method to resolve the dilemma between structural and morphological quality in growth of the GaN epilayer. A gradient buffer layer was grown in such a way that the N/Ga ratio was gradually changed from nitrogen-rich to gallium-rich. The GaN epitaxial layer was then grown on the gradient buffer layer. In the X-ray diffraction analysis of GaN(002) rocking curves, we found that the full width at half-maximum was improved from 531.69″ to 59.43″ for the sample with a gradient buffer layer as compared to a purely gallium-rich grown sample. Atomic force microscopy analysis showed that the root-mean-square roughness of the surface was improved from 18.28 nm to 1.62 nm over an area of 5 × 5 μm 2 with respect to a purely nitrogen-rich grown sample. Raman scattering showed the presence of a slightly tilted plane in the gradient layer. Furthermore we showed that the gradient layer can also slash the strain force caused by either Ga-rich GaN epitaxial layer or AlN buffer layer. - Highlights: ► The samples were grown by plasma-assisted molecular beam epitaxy. ► The GaN epilayer was grown on sapphire substrate. ► The samples were characterized by X-ray diffraction and atomic force microscopy. ► The sample quality was improved by gradient buffer layer.
Improvement of GaN epilayer by gradient layer method with molecular-beam epitaxy
Energy Technology Data Exchange (ETDEWEB)
Chen, Yen-Liang [Department of Physics, Institute of Material Science and Engineering, Center for Nanoscience and Nanotechnology, National Sun Yat-Sen University, Kaohsiung 80424, Taiwan, ROC (China); Lo, Ikai, E-mail: ikailo@mail.phys.nsysu.edu.tw [Department of Physics, Institute of Material Science and Engineering, Center for Nanoscience and Nanotechnology, National Sun Yat-Sen University, Kaohsiung 80424, Taiwan, ROC (China); Gau, Ming-Hong; Hsieh, Chia-Ho; Sham, Meng-Wei; Pang, Wen-Yuan; Hsu, Yu-Chi [Department of Physics, Institute of Material Science and Engineering, Center for Nanoscience and Nanotechnology, National Sun Yat-Sen University, Kaohsiung 80424, Taiwan, ROC (China); Tsai, Jenn-Kai [Department of Electronics Engineering, National Formosa University, Hu-Wei, Yun-Lin County 63208, Taiwan, ROC (China); Schuber, Ralf; Schaadt, Daniel [Institute of Applied Physics/DFG-Center for Functional Nanostructures (CFN), Karlsruhe Institute of Technology (KIT), Karlsruhe (Germany)
2012-07-31
We demonstrated a molecular beam epitaxy method to resolve the dilemma between structural and morphological quality in growth of the GaN epilayer. A gradient buffer layer was grown in such a way that the N/Ga ratio was gradually changed from nitrogen-rich to gallium-rich. The GaN epitaxial layer was then grown on the gradient buffer layer. In the X-ray diffraction analysis of GaN(002) rocking curves, we found that the full width at half-maximum was improved from 531.69 Double-Prime to 59.43 Double-Prime for the sample with a gradient buffer layer as compared to a purely gallium-rich grown sample. Atomic force microscopy analysis showed that the root-mean-square roughness of the surface was improved from 18.28 nm to 1.62 nm over an area of 5 Multiplication-Sign 5 {mu}m{sup 2} with respect to a purely nitrogen-rich grown sample. Raman scattering showed the presence of a slightly tilted plane in the gradient layer. Furthermore we showed that the gradient layer can also slash the strain force caused by either Ga-rich GaN epitaxial layer or AlN buffer layer. - Highlights: Black-Right-Pointing-Pointer The samples were grown by plasma-assisted molecular beam epitaxy. Black-Right-Pointing-Pointer The GaN epilayer was grown on sapphire substrate. Black-Right-Pointing-Pointer The samples were characterized by X-ray diffraction and atomic force microscopy. Black-Right-Pointing-Pointer The sample quality was improved by gradient buffer layer.
Accelerated gradient methods for total-variation-based CT image reconstruction
DEFF Research Database (Denmark)
Jørgensen, Jakob Heide; Jensen, Tobias Lindstrøm; Hansen, Per Christian
2011-01-01
incorporates several heuristics from the optimization literature such as Barzilai-Borwein (BB) step size selection and nonmonotone line search. The latter uses a cleverly chosen sequence of auxiliary points to achieve a better convergence rate. The methods are memory efficient and equipped with a stopping...... reconstruction can in principle be found by any optimization method, but in practice the large scale of the systems arising in CT image reconstruction preclude the use of memory-demanding methods such as Newton’s method. The simple gradient method has much lower memory requirements, but exhibits slow convergence...
And still, a new beginning: the Galerkin least-squares gradient method
International Nuclear Information System (INIS)
Franca, L.P.; Carmo, E.G.D. do
1988-08-01
A finite element method is proposed to solve a scalar singular diffusion problem. The method is constructed by adding to the standard Galerkin a mesh-dependent term obtained by taking the gradient of the Euler-lagrange equation and multiplying it by its least-squares. For the one-dimensional homogeneous problem the method is designed to develop nodal exact solution. An error estimate shows that the method converges optimaly for any value of the singular parameter. Numerical results demonstrate the good stability and accuracy properties of the method. (author) [pt
Application of the gradient method to Hartree-Fock-Bogoliubov theory
International Nuclear Information System (INIS)
Robledo, L. M.; Bertsch, G. F.
2011-01-01
A computer code is presented for solving the equations of the Hartree-Fock-Bogoliubov (HFB) theory by the gradient method, motivated by the need for efficient and robust codes to calculate the configurations required by extensions of the HFB theory, such as the generator coordinate method. The code is organized with a separation between the parts that are specific to the details of the Hamiltonian and the parts that are generic to the gradient method. This permits total flexibility in choosing the symmetries to be imposed on the HFB solutions. The code solves for both even and odd particle-number ground states, with the choice determined by the input data stream. Application is made to the nuclei in the sd shell using the universal sd-shell interaction B (USDB) shell-model Hamiltonian.
International Nuclear Information System (INIS)
Miyazaki, T.; Koyama, T.; Kobayashi, S.
1996-01-01
A new experimental method to determine the phase boundary and phase equilibrium is accomplished by - means of analytical transmission electron microscopy for alloys with a macroscopic composition gradient. The various phase boundaries, i.e. the coherent binodal and spinodal lines, incoherent binodal line and order/disorder transformation line are distinctly determined for the Cu-Ti alloy and the other alloy systems. Furthermore, the equilibrium compositions at the interface of precipitate/matrix can experimentally be obtained for various particle sizes, and thus the Gibbs-Thomson's relation is verified. It is expected that the composition gradient method proposed in the present will become an important experimental method of the microstructural characterization
Universal field matching in craniospinal irradiation by a background-dose gradient-optimized method.
Traneus, Erik; Bizzocchi, Nicola; Fellin, Francesco; Rombi, Barbara; Farace, Paolo
2018-01-01
The gradient-optimized methods are overcoming the traditional feathering methods to plan field junctions in craniospinal irradiation. In this note, a new gradient-optimized technique, based on the use of a background dose, is described. Treatment planning was performed by RayStation (RaySearch Laboratories, Stockholm, Sweden) on the CT scans of a pediatric patient. Both proton (by pencil beam scanning) and photon (by volumetric modulated arc therapy) treatments were planned with three isocenters. An 'in silico' ideal background dose was created first to cover the upper-spinal target and to produce a perfect dose gradient along the upper and lower junction regions. Using it as background, the cranial and the lower-spinal beams were planned by inverse optimization to obtain dose coverage of their relevant targets and of the junction volumes. Finally, the upper-spinal beam was inversely planned after removal of the background dose and with the previously optimized beams switched on. In both proton and photon plans, the optimized cranial and the lower-spinal beams produced a perfect linear gradient in the junction regions, complementary to that produced by the optimized upper-spinal beam. The final dose distributions showed a homogeneous coverage of the targets. Our simple technique allowed to obtain high-quality gradients in the junction region. Such technique universally works for photons as well as protons and could be applicable to the TPSs that allow to manage a background dose. © 2017 The Authors. Journal of Applied Clinical Medical Physics published by Wiley Periodicals, Inc. on behalf of American Association of Physicists in Medicine.
International Nuclear Information System (INIS)
Caffrey, M.; Hing, F.S.
1987-01-01
A method that enables temperature-composition phase diagram construction at unprecedented rates is described and evaluated. The method involves establishing a known temperature gradient along the length of a metal rod. Samples of different compositions contained in long, thin-walled capillaries are positioned lengthwise on the rod and equilibrated such that the temperature gradient is communicated into the sample. The sample is then moved through a focused, monochromatic synchrotron-derived x-ray beam and the image-intensified diffraction pattern from the sample is recorded on videotape continuously in live-time as a function of position and, thus, temperature. The temperature at which the diffraction pattern changes corresponds to a phase boundary, and the phase(s) existing (coexisting) on either side of the boundary can be identified on the basis of the diffraction pattern. Repeating the measurement on samples covering the entire composition range completes the phase diagram. These additional samples can be conveniently placed at different locations around the perimeter of the cylindrical rod and rotated into position for diffraction measurement. Temperature-composition phase diagrams for the fully hydrated binary mixtures, dimyristoylphosphatidylcholine (DMPC)/dipalmitoylphosphatidylcholine (DPPC) and dipalmitoylphosphatidylethanolamine (DPPE)/DPPC, have been constructed using the new temperature gradient method. They agree well with and extend the results obtained by other techniques. In the DPPE/DPPC system structural parameters as a function of temperature in the various phases including the subgel phase are reported. The potential limitations of this steady-state method are discussed
Leone, Frank A., Jr.
2015-01-01
A method is presented to represent the large-deformation kinematics of intraply matrix cracks and delaminations in continuum damage mechanics (CDM) constitutive material models. The method involves the additive decomposition of the deformation gradient tensor into 'crack' and 'bulk material' components. The response of the intact bulk material is represented by a reduced deformation gradient tensor, and the opening of an embedded cohesive interface is represented by a normalized cohesive displacement-jump vector. The rotation of the embedded interface is tracked as the material deforms and as the crack opens. The distribution of the total local deformation between the bulk material and the cohesive interface components is determined by minimizing the difference between the cohesive stress and the bulk material stress projected onto the cohesive interface. The improvements to the accuracy of CDM models that incorporate the presented method over existing approaches are demonstrated for a single element subjected to simple shear deformation and for a finite element model of a unidirectional open-hole tension specimen. The material model is implemented as a VUMAT user subroutine for the Abaqus/Explicit finite element software. The presented deformation gradient decomposition method reduces the artificial load transfer across matrix cracks subjected to large shearing deformations, and avoids the spurious secondary failure modes that often occur in analyses based on conventional progressive damage models.
Research on a wavefront aberration calculation method for a laser energy gradient attenuator
International Nuclear Information System (INIS)
Dong, Tingting; Han, Xu; Chen, Chi; Fu, Yuegang; Li, Ming
2013-01-01
When a laser energy gradient attenuator is working, there is an inhomogeneous temperature distribution in the whole of the glass because of the non-uniform light energy absorption. This will lead to optical performance reduction. An integrated opto-thermal–mechanical method is proposed to calculate the wavefront aberration for analysis of the thermal effect of the system. Non-sequential optical analysis is used for computing the absorbed energy distribution. The finite element analysis program solves the temperature distribution and the deformations of nodes on the surfaces. An interface routine is created to fit the surface shape and the index field, and extended Zernike polynomials are introduced to get a higher fitting precision. Finally, the parameters are imported to the CodeV optical design program automatically, and the user defined gradient index material is ray traced to obtain the wavefront aberration. The method can also be used in other optical systems for thermal effect analysis. (letter)
Optimization of offshore wind turbine support structures using analytical gradient-based method
Chew, Kok Hon; Tai, Kang; Ng, E.Y.K.; Muskulus, Michael
2015-01-01
Design optimization of the offshore wind turbine support structure is an expensive task; due to the highly-constrained, non-convex and non-linear nature of the design problem. This report presents an analytical gradient-based method to solve this problem in an efficient and effective way. The design sensitivities of the objective and constraint functions are evaluated analytically while the optimization of the structure is performed, subject to sizing, eigenfrequency, extreme load an...
Asynchronous Gossip-Based Gradient-Free Method for Multiagent Optimization
Deming Yuan
2014-01-01
This paper considers the constrained multiagent optimization problem. The objective function of the problem is a sum of convex functions, each of which is known by a specific agent only. For solving this problem, we propose an asynchronous distributed method that is based on gradient-free oracles and gossip algorithm. In contrast to the existing work, we do not require that agents be capable of computing the subgradients of their objective functions and coordinating their...
Loizou, Nicolas
2017-12-27
In this paper we study several classes of stochastic optimization algorithms enriched with heavy ball momentum. Among the methods studied are: stochastic gradient descent, stochastic Newton, stochastic proximal point and stochastic dual subspace ascent. This is the first time momentum variants of several of these methods are studied. We choose to perform our analysis in a setting in which all of the above methods are equivalent. We prove global nonassymptotic linear convergence rates for all methods and various measures of success, including primal function values, primal iterates (in L2 sense), and dual function values. We also show that the primal iterates converge at an accelerated linear rate in the L1 sense. This is the first time a linear rate is shown for the stochastic heavy ball method (i.e., stochastic gradient descent method with momentum). Under somewhat weaker conditions, we establish a sublinear convergence rate for Cesaro averages of primal iterates. Moreover, we propose a novel concept, which we call stochastic momentum, aimed at decreasing the cost of performing the momentum step. We prove linear convergence of several stochastic methods with stochastic momentum, and show that in some sparse data regimes and for sufficiently small momentum parameters, these methods enjoy better overall complexity than methods with deterministic momentum. Finally, we perform extensive numerical testing on artificial and real datasets, including data coming from average consensus problems.
Loizou, Nicolas; Richtarik, Peter
2017-01-01
In this paper we study several classes of stochastic optimization algorithms enriched with heavy ball momentum. Among the methods studied are: stochastic gradient descent, stochastic Newton, stochastic proximal point and stochastic dual subspace ascent. This is the first time momentum variants of several of these methods are studied. We choose to perform our analysis in a setting in which all of the above methods are equivalent. We prove global nonassymptotic linear convergence rates for all methods and various measures of success, including primal function values, primal iterates (in L2 sense), and dual function values. We also show that the primal iterates converge at an accelerated linear rate in the L1 sense. This is the first time a linear rate is shown for the stochastic heavy ball method (i.e., stochastic gradient descent method with momentum). Under somewhat weaker conditions, we establish a sublinear convergence rate for Cesaro averages of primal iterates. Moreover, we propose a novel concept, which we call stochastic momentum, aimed at decreasing the cost of performing the momentum step. We prove linear convergence of several stochastic methods with stochastic momentum, and show that in some sparse data regimes and for sufficiently small momentum parameters, these methods enjoy better overall complexity than methods with deterministic momentum. Finally, we perform extensive numerical testing on artificial and real datasets, including data coming from average consensus problems.
Kou, Jisheng; Sun, Shuyu
2014-01-01
The gradient theory for the surface tension of simple fluids and mixtures is rigorously analyzed based on mathematical theory. The finite element approximation of surface tension is developed and analyzed, and moreover, an adaptive finite element method based on a physical-based estimator is proposed and it can be coupled efficiently with Newton's method as well. The numerical tests are carried out both to verify the proposed theory and to demonstrate the efficiency of the proposed method. © 2013 Elsevier B.V. All rights reserved.
Kou, Jisheng
2014-01-01
The gradient theory for the surface tension of simple fluids and mixtures is rigorously analyzed based on mathematical theory. The finite element approximation of surface tension is developed and analyzed, and moreover, an adaptive finite element method based on a physical-based estimator is proposed and it can be coupled efficiently with Newton\\'s method as well. The numerical tests are carried out both to verify the proposed theory and to demonstrate the efficiency of the proposed method. © 2013 Elsevier B.V. All rights reserved.
Hakiki, Farizal
2017-07-25
A study performed by Marbun et al. [1] claimed that “A new methodology to predict fracture pressure from former calculations, Matthew–Kelly and Eaton are proposed.” Also, Marbun et al.\\'s paper stated that “A new value of Poisson\\'s and a stress ratio of the formation were generated and the accuracy of fracture gradient was improved.” We found those all statements are incorrect and some misleading concepts are revealed. An attempt to expose the method of fracture gradient determination from industry practice also appears to solidify that our arguments are acceptable to against improper Marbun et al.\\'s claims.
Analytical Energy Gradients for Excited-State Coupled-Cluster Methods
Wladyslawski, Mark; Nooijen, Marcel
The equation-of-motion coupled-cluster (EOM-CC) and similarity transformed equation-of-motion coupled-cluster (STEOM-CC) methods have been firmly established as accurate and routinely applicable extensions of single-reference coupled-cluster theory to describe electronically excited states. An overview of these methods is provided, with emphasis on the many-body similarity transform concept that is the key to a rationalization of their accuracy. The main topic of the paper is the derivation of analytical energy gradients for such non-variational electronic structure approaches, with an ultimate focus on obtaining their detailed algebraic working equations. A general theoretical framework using Lagrange's method of undetermined multipliers is presented, and the method is applied to formulate the EOM-CC and STEOM-CC gradients in abstract operator terms, following the previous work in [P.G. Szalay, Int. J. Quantum Chem. 55 (1995) 151] and [S.R. Gwaltney, R.J. Bartlett, M. Nooijen, J. Chem. Phys. 111 (1999) 58]. Moreover, the systematics of the Lagrange multiplier approach is suitable for automation by computer, enabling the derivation of the detailed derivative equations through a standardized and direct procedure. To this end, we have developed the SMART (Symbolic Manipulation and Regrouping of Tensors) package of automated symbolic algebra routines, written in the Mathematica programming language. The SMART toolkit provides the means to expand, differentiate, and simplify equations by manipulation of the detailed algebraic tensor expressions directly. The Lagrangian multiplier formulation establishes a uniform strategy to perform the automated derivation in a standardized manner: A Lagrange multiplier functional is constructed from the explicit algebraic equations that define the energy in the electronic method; the energy functional is then made fully variational with respect to all of its parameters, and the symbolic differentiations directly yield the explicit
Ionospheric forecasting model using fuzzy logic-based gradient descent method
Directory of Open Access Journals (Sweden)
D. Venkata Ratnam
2017-09-01
Full Text Available Space weather phenomena cause satellite to ground or satellite to aircraft transmission outages over the VHF to L-band frequency range, particularly in the low latitude region. Global Positioning System (GPS is primarily susceptible to this form of space weather. Faulty GPS signals are attributed to ionospheric error, which is a function of Total Electron Content (TEC. Importantly, precise forecasts of space weather conditions and appropriate hazard observant cautions required for ionospheric space weather observations are limited. In this paper, a fuzzy logic-based gradient descent method has been proposed to forecast the ionospheric TEC values. In this technique, membership functions have been tuned based on the gradient descent estimated values. The proposed algorithm has been tested with the TEC data of two geomagnetic storms in the low latitude station of KL University, Guntur, India (16.44°N, 80.62°E. It has been found that the gradient descent method performs well and the predicted TEC values are close to the original TEC measurements.
Qiu, Zhixia; Yu, Jiaojiao; Dai, Yu; Yang, Yue; Lu, Xiaoyu; Xu, Jiaqiu; Qin, Zhiying; Huang, Fang; Li, Ning
2017-11-01
A simple LC-MS/MS method facilitated by salting-out assisted liquid-liquid extraction (SALLE) was applied to simultaneously investigate the pharmacokinetics of trans-resveratrol (Res) and its major glucuronide and sulfate conjugates in rat plasma. Acetonitrile-methanol (80:20, v/v) and ammonium acetate (10 mol L -1 ) were used as extractant and salting-out reagent to locate the target analytes in the supernatant after the aqueous and organic phase stratification, then the analytes were determined via gradient elution by LC-MS/MS in negative mode in a single run. The analytical method was validated with good selectivity, acceptable accuracy (>85%) and low variation of precision (extraction efficiency of target glucuronide and sulfate conjugates (>80%). The method was successfully applied to determine Res and its four conjugated metabolites in rat after Res administration (intragastric, 50 mg kg -1 ; intravenous, 10 mg kg -1 ). The systemic exposures to Res conjugates were much higher than those to Res (AUC 0-t , i.v., 7.43 μm h; p.o., 8.31 μm h); Res-3-O-β-d-glucuronide was the major metabolite (AUC 0-t , i.v., 66.1 μm h; p.o., 333.4 μm h). The bioavailability of Res was estimated to be ~22.4%. The reproducible SALLE method simplified the sample preparation, drastically improved the accuracy of the concomitant assay and gave full consideration of extraction recovery to each target analyte in bio-samples. Copyright © 2017 John Wiley & Sons, Ltd.
Ozcan, Aydin; Perego, Claudio; Salvalaglio, Matteo; Parrinello, Michele; Yazaydin, Ozgur
2017-05-01
In this study, we introduce a new non-equilibrium molecular dynamics simulation method to perform simulations of concentration driven membrane permeation processes. The methodology is based on the application of a non-conservative bias force controlling the concentration of species at the inlet and outlet of a membrane. We demonstrate our method for pure methane, ethane and ethylene permeation and for ethane/ethylene separation through a flexible ZIF-8 membrane. Results show that a stationary concentration gradient is maintained across the membrane, realistically simulating an out-of-equilibrium diffusive process, and the computed permeabilities and selectivity are in good agreement with experimental results.
A Sea-Sky Line Detection Method for Unmanned Surface Vehicles Based on Gradient Saliency.
Wang, Bo; Su, Yumin; Wan, Lei
2016-04-15
Special features in real marine environments such as cloud clutter, sea glint and weather conditions always result in various kinds of interference in optical images, which make it very difficult for unmanned surface vehicles (USVs) to detect the sea-sky line (SSL) accurately. To solve this problem a saliency-based SSL detection method is proposed. Through the computation of gradient saliency the line features of SSL are enhanced effectively, while other interference factors are relatively suppressed, and line support regions are obtained by a region growing method on gradient orientation. The SSL identification is achieved according to region contrast, line segment length and orientation features, and optimal state estimation of SSL detection is implemented by introducing a cubature Kalman filter (CKF). In the end, the proposed method is tested on a benchmark dataset from the "XL" USV in a real marine environment, and the experimental results demonstrate that the proposed method is significantly superior to other state-of-the-art methods in terms of accuracy rate and real-time performance, and its accuracy and stability are effectively improved by the CKF.
A Sea-Sky Line Detection Method for Unmanned Surface Vehicles Based on Gradient Saliency
Directory of Open Access Journals (Sweden)
Bo Wang
2016-04-01
Full Text Available Special features in real marine environments such as cloud clutter, sea glint and weather conditions always result in various kinds of interference in optical images, which make it very difficult for unmanned surface vehicles (USVs to detect the sea-sky line (SSL accurately. To solve this problem a saliency-based SSL detection method is proposed. Through the computation of gradient saliency the line features of SSL are enhanced effectively, while other interference factors are relatively suppressed, and line support regions are obtained by a region growing method on gradient orientation. The SSL identification is achieved according to region contrast, line segment length and orientation features, and optimal state estimation of SSL detection is implemented by introducing a cubature Kalman filter (CKF. In the end, the proposed method is tested on a benchmark dataset from the “XL” USV in a real marine environment, and the experimental results demonstrate that the proposed method is significantly superior to other state-of-the-art methods in terms of accuracy rate and real-time performance, and its accuracy and stability are effectively improved by the CKF.
A Robust Gradient Based Method for Building Extraction from LiDAR and Photogrammetric Imagery
Directory of Open Access Journals (Sweden)
Fasahat Ullah Siddiqui
2016-07-01
Full Text Available Existing automatic building extraction methods are not effective in extracting buildings which are small in size and have transparent roofs. The application of large area threshold prohibits detection of small buildings and the use of ground points in generating the building mask prevents detection of transparent buildings. In addition, the existing methods use numerous parameters to extract buildings in complex environments, e.g., hilly area and high vegetation. However, the empirical tuning of large number of parameters reduces the robustness of building extraction methods. This paper proposes a novel Gradient-based Building Extraction (GBE method to address these limitations. The proposed method transforms the Light Detection And Ranging (LiDAR height information into intensity image without interpolation of point heights and then analyses the gradient information in the image. Generally, building roof planes have a constant height change along the slope of a roof plane whereas trees have a random height change. With such an analysis, buildings of a greater range of sizes with a transparent or opaque roof can be extracted. In addition, a local colour matching approach is introduced as a post-processing stage to eliminate trees. This stage of our proposed method does not require any manual setting and all parameters are set automatically from the data. The other post processing stages including variance, point density and shadow elimination are also applied to verify the extracted buildings, where comparatively fewer empirically set parameters are used. The performance of the proposed GBE method is evaluated on two benchmark data sets by using the object and pixel based metrics (completeness, correctness and quality. Our experimental results show the effectiveness of the proposed method in eliminating trees, extracting buildings of all sizes, and extracting buildings with and without transparent roof. When compared with current state
Directory of Open Access Journals (Sweden)
Kang Ma
2017-01-01
Full Text Available Coherent gradient sensing (CGS method can be used to measure the slope of a reflective surface, and has the merits of full-field, non-contact, and real-time measurement. In this study, the thermal stress field of thermal barrier coating (TBC structures is measured by CGS method. Two kinds of powders were sprayed onto Ni-based alloy using a plasma spraying method to obtain two groups of film–substrate specimens. The specimens were then heated with an oxy-acetylene flame. The resulting thermal mismatch between the film and substrate led to out-of-plane deformation of the specimen. The deformation was measured by the reflective CGS method and the thermal stress field of the structure was obtained through calibration with the help of finite element analysis. Both the experiment and numerical results showed that the thermal stress field of TBC structures can be successfully measured by CGS method.
Antibody-nanoparticle conjugates to enhance the sensitivity of ELISA-based detection methods.
Directory of Open Access Journals (Sweden)
Margaret M Billingsley
Full Text Available Accurate antigen detection is imperative for clinicians to diagnose disease, assess treatment success, and predict patient prognosis. The most common technique used for the detection of disease-associated biomarkers is the enzyme linked immunosorbent assay (ELISA. In an ELISA, primary antibodies are incubated with biological samples containing the biomarker of interest. Then, detectible secondary antibodies conjugated with horseradish peroxidase (HRP bind the primary antibodies. Upon addition of a color-changing substrate, the samples provide a colorimetric signal that directly correlates to the targeted biomarker concentration. While ELISAs are effective for analyzing samples with high biomarker content, they lack the sensitivity required to analyze samples with low antigen levels. We hypothesized that the sensitivity of ELISAs could be enhanced by replacing freely delivered primary antibodies with antibody-nanoparticle conjugates that provide excess binding sites for detectible secondary antibodies, ultimately leading to increased signal. Here, we investigated the use of nanoshells (NS decorated with antibodies specific to epidermal growth factor receptor (EGFR as a model system (EGFR-NS. We incubated one healthy and two breast cancer cell lines, each expressing different levels of EGFR, with EGFR-NS, untargeted NS, or unconjugated EGFR antibodies, as well as detectable secondary antibodies. We found that EGFR-NS consistently increased signal intensity relative to unconjugated EGFR antibodies, with a substantial 13-fold enhancement from cells expressing high levels of EGFR. Additionally, 40x more unconjugated antibodies were required to detect EGFR compared to those conjugated to NS. Our results demonstrate that antibody-nanoparticle conjugates lower the detection limit of traditional ELISAs and support further investigation of this strategy with other antibodies and nanoparticles. Owing to their enhanced sensitivity, we anticipate that
Astawa, INGA; Gusti Ngurah Bagus Caturbawa, I.; Made Sajayasa, I.; Dwi Suta Atmaja, I. Made Ari
2018-01-01
The license plate recognition usually used as part of system such as parking system. License plate detection considered as the most important step in the license plate recognition system. We propose methods that can be used to detect the vehicle plate on mobile phone. In this paper, we used Sliding Window, Histogram of Oriented Gradient (HOG), and Support Vector Machines (SVM) method to license plate detection so it will increase the detection level even though the image is not in a good quality. The image proceed by Sliding Window method in order to find plate position. Feature extraction in every window movement had been done by HOG and SVM method. Good result had shown in this research, which is 96% of accuracy.
International Nuclear Information System (INIS)
Kaschner, R.; Graefenstein, J.; Ziesche, P.
1988-12-01
From the local momentum balance using density functional theory an expression for the local quantum-mechanical stress tensor (or stress field) σ(r) of non-relativistic Coulomb systems is found out within the Thomas-Fermi approximation and its generalizations including gradient expansion method. As an illustration the stress field σ(r) is calculated for the jellium model of the interface K-Cs, containing especially the adhesive force between the two half-space jellia. (author). 23 refs, 1 fig
Method of formation of a high gradient magnetic field and the device for division of substances
International Nuclear Information System (INIS)
Il'yashenko, E. I.; Glebov, V. A.; Skeltorp, A. T.
2005-01-01
Full text: The method and the device [1] are intended for use as a high-sensitivity magnetic separator for different types of paramagnetic substances and materials from diamagnetic ones, for division of paramagnetic substances and materials on the magnitudes of their paramagnetic susceptibility, for division of diamagnetic substances and materials on magnitudes of their diamagnetic susceptibility. Scopes: to produce pure and super pure substances and materials in electronics, metallurgy and chemistry, separation of biological objects (red blood cells, magnetic bacteria, etc.) in biology and medicine, water treatment removing heavy metals and organic impurities, etc. The main condition for magnetic separation is the magnetic force which acts on a particle of the substance and which is proportional to the magnetic susceptibility of the substance, magnetic induction B and gradient ∇B of the applied magnetic field. Therefore, to increase the sensitivity and selectivity of magnetic separation it will be required to use the largest possible values of the magnetic induction and the gradient of a magnetic field, or their product - B∇B. The device declared in the present work includes the magnetic system such as the open domain structure, consisting of permanent magnets with magnetic anisotropy much greater than the induction of a material of magnets. However, the declared device differs from the open domain structure in that [1]: *the surface of the neighbor poles of magnets is covered with a mask made from sheets of adjustable thickness of a soft magnetic material; *the soft magnetic material of the mask is selected on the basis of the magnitudes of the induction of saturation and magnetic permeability for achievement of the required magnitude of the induction and gradient of the magnetic field; *between the sheets of the mask there is an adjustable gap located symmetrically relative to the junction line of the magnets; *the size and the form of the gap between the
Piret, Cécile
2012-05-01
Much work has been done on reconstructing arbitrary surfaces using the radial basis function (RBF) method, but one can hardly find any work done on the use of RBFs to solve partial differential equations (PDEs) on arbitrary surfaces. In this paper, we investigate methods to solve PDEs on arbitrary stationary surfaces embedded in . R3 using the RBF method. We present three RBF-based methods that easily discretize surface differential operators. We take advantage of the meshfree character of RBFs, which give us a high accuracy and the flexibility to represent the most complex geometries in any dimension. Two out of the three methods, which we call the orthogonal gradients (OGr) methods are the result of our work and are hereby presented for the first time. © 2012 Elsevier Inc.
Yong, Peng; Liao, Wenyuan; Huang, Jianping; Li, Zhenchuan
2018-04-01
Full waveform inversion is an effective tool for recovering the properties of the Earth from seismograms. However, it suffers from local minima caused mainly by the limited accuracy of the starting model and the lack of a low-frequency component in the seismic data. Because of the high velocity contrast between salt and sediment, the relation between the waveform and velocity perturbation is strongly nonlinear. Therefore, salt inversion can easily get trapped in the local minima. Since the velocity of salt is nearly constant, we can make the most of this characteristic with total variation regularization to mitigate the local minima. In this paper, we develop an adaptive primal dual hybrid gradient method to implement total variation regularization by projecting the solution onto a total variation norm constrained convex set, through which the total variation norm constraint is satisfied at every model iteration. The smooth background velocities are first inverted and the perturbations are gradually obtained by successively relaxing the total variation norm constraints. Numerical experiment of the projection of the BP model onto the intersection of the total variation norm and box constraints has demonstrated the accuracy and efficiency of our adaptive primal dual hybrid gradient method. A workflow is designed to recover complex salt structures in the BP 2004 model and the 2D SEG/EAGE salt model, starting from a linear gradient model without using low-frequency data below 3 Hz. The salt inversion processes demonstrate that wavefield reconstruction inversion with a total variation norm and box constraints is able to overcome local minima and inverts the complex salt velocity layer by layer.
International Nuclear Information System (INIS)
Bakosi, Jozsef; Ristorcelli, Raymond J.
2010-01-01
Probability density function (PDF) methods are extended to variable-density pressure-gradient-driven turbulence. We apply the new method to compute the joint PDF of density and velocity in a non-premixed binary mixture of different-density molecularly mixing fluids under gravity. The full time-evolution of the joint PDF is captured in the highly non-equilibrium flow: starting from a quiescent state, transitioning to fully developed turbulence and finally dissipated by molecular diffusion. High-Atwood-number effects (as distinguished from the Boussinesq case) are accounted for: both hydrodynamic turbulence and material mixing are treated at arbitrary density ratios, with the specific volume, mass flux and all their correlations in closed form. An extension of the generalized Langevin model, originally developed for the Lagrangian fluid particle velocity in constant-density shear-driven turbulence, is constructed for variable-density pressure-gradient-driven flows. The persistent small-scale anisotropy, a fundamentally 'non-Kolmogorovian' feature of flows under external acceleration forces, is captured by a tensorial diffusion term based on the external body force. The material mixing model for the fluid density, an active scalar, is developed based on the beta distribution. The beta-PDF is shown to be capable of capturing the mixing asymmetry and that it can accurately represent the density through transition, in fully developed turbulence and in the decay process. The joint model for hydrodynamics and active material mixing yields a time-accurate evolution of the turbulent kinetic energy and Reynolds stress anisotropy without resorting to gradient diffusion hypotheses, and represents the mixing state by the density PDF itself, eliminating the need for dubious mixing measures. Direct numerical simulations of the homogeneous Rayleigh-Taylor instability are used for model validation.
Modification of the Armijo line search to satisfy the convergence properties of HS method
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Mohammed Belloufi
2013-07-01
Full Text Available The Hestenes-Stiefel (HS conjugate gradient algorithm is a useful tool of unconstrainednumerical optimization, which has good numerical performance but no global convergence result under traditional line searches. This paper proposes a line search technique that guarantee the globalconvergence of the Hestenes-Stiefel (HS conjugate gradient method. Numerical tests are presented tovalidate the diﬀerent approaches.
A Fast Gradient Method for Nonnegative Sparse Regression With Self-Dictionary
Gillis, Nicolas; Luce, Robert
2018-01-01
A nonnegative matrix factorization (NMF) can be computed efficiently under the separability assumption, which asserts that all the columns of the given input data matrix belong to the cone generated by a (small) subset of them. The provably most robust methods to identify these conic basis columns are based on nonnegative sparse regression and self dictionaries, and require the solution of large-scale convex optimization problems. In this paper we study a particular nonnegative sparse regression model with self dictionary. As opposed to previously proposed models, this model yields a smooth optimization problem where the sparsity is enforced through linear constraints. We show that the Euclidean projection on the polyhedron defined by these constraints can be computed efficiently, and propose a fast gradient method to solve our model. We compare our algorithm with several state-of-the-art methods on synthetic data sets and real-world hyperspectral images.
Li, Yi; Gu, Christine; Gruenhagen, Jason; Yehl, Peter; Chetwyn, Nik P; Medley, Colin D
2016-01-01
Antibody-drug conjugates (ADCs) are complex therapeutic agents that use the specific targeting properties of antibodies and the highly potent cytotoxicity of small molecule drugs to selectively eliminate tumor cells while limiting the toxicity to normal healthy tissues. Two critical quality attributes of ADCs are the purity and stability of the active small molecule drug linked to the ADC, but these are difficult to assess once the drug is conjugated to the antibody. In this study, we report a enzyme deconjugation approach to cleave small molecule drugs from ADCs, which allows the drugs to be subsequently characterized by reversed-phase high performance liquid chromatography. The model ADC we used in this study utilizes a valine-citrulline linker that is designed to be sensitive to endoproteases after internalization by tumor cells. We screened several proteases to determine the most effective enzyme. Among the 3 cysteine proteases evaluated, papain had the best efficiency in cleaving the small molecule drug from the model ADC. The deconjugation conditions were further optimized to achieve complete cleavage of the small molecule drug. This papain deconjugation approach demonstrated excellent specificity and precision. The purity and stability of the active drug on an ADC drug product was evaluated and the major degradation products of the active drug were identified. The papain deconjugation method was also applied to several other ADCs, with the results suggesting it could be applied generally to ADCs containing a valine-citrulline linker. Our results indicate that the papain deconjugation method is a powerful tool for characterizing the active small molecule drug conjugated to an ADC, and may be useful in ensuring the product quality, efficacy and the safety of ADCs.
Projection and nested force-gradient methods for quantum field theories
Energy Technology Data Exchange (ETDEWEB)
Shcherbakov, Dmitry
2017-07-26
For the Hybrid Monte Carlo algorithm (HMC), often used to study the fundamental quantum field theory of quarks and gluons, quantum chromodynamics (QCD), on the lattice, one is interested in efficient numerical time integration schemes which preserve geometric properties of the flow and are optimal in terms of computational costs per trajectory for a given acceptance rate. High order numerical methods allow the use of larger step sizes, but demand a larger computational effort per step; low order schemes do not require such large computational costs per step, but need more steps per trajectory. So there is a need to balance these opposing effects. In this work we introduce novel geometric numerical time integrators, namely, projection and nested force-gradient methods in order to improve the efficiency of the HMC algorithm in application to the problems of quantum field theories.
Song, Dandan; Qu, Xiaofeng; Liu, Yushen; Li, Li; Yin, Dehui; Li, Juan; Xu, Kun; Xie, Renguo; Zhai, Yue; Zhang, Huiwen; Bao, Hao; Zhao, Chao; Wang, Juan; Song, Xiuling; Song, Wenzhi
2017-03-01
Brucella spp. are facultative intracellular bacteria that cause zoonotic disease of brucellosis worldwide. Traditional methods for detection of Brucella spp. take 48-72 h that does not meet the need of rapid detection. Herein, a new rapid detection method of Brucella was developed based on polyclonal antibody-conjugating quantum dots and antibody-modified magnetic beads. First, polyclonal antibodies IgG and IgY were prepared and then the antibody conjugated with quantum dots (QDs) and immunomagnetic beads (IMB), respectively, which were activated by N-(3-dimethylaminopropyl)- N'-ethylcar-bodiimide hydrochloride (EDC) and N-hydroxysuccinimide (NHS) to form probes. We used the IMB probe to separate the Brucella and labeled by the QD probe, and then detected the fluorescence intensity with a fluorescence spectrometer. The detection method takes 105 min with a limit of detection of 103 CFU/mL and ranges from 10 to 105 CFU/mL ( R 2 = 0.9983), and it can be well used in real samples.
Energy Technology Data Exchange (ETDEWEB)
Shu, Yu-Chen, E-mail: ycshu@mail.ncku.edu.tw [Department of Mathematics, National Cheng Kung University, Tainan 701, Taiwan (China); Mathematics Division, National Center for Theoretical Sciences (South), Tainan 701, Taiwan (China); Chern, I-Liang, E-mail: chern@math.ntu.edu.tw [Department of Applied Mathematics, National Chiao Tung University, Hsin Chu 300, Taiwan (China); Department of Mathematics, National Taiwan University, Taipei 106, Taiwan (China); Mathematics Division, National Center for Theoretical Sciences (Taipei Office), Taipei 106, Taiwan (China); Chang, Chien C., E-mail: mechang@iam.ntu.edu.tw [Institute of Applied Mechanics, National Taiwan University, Taipei 106, Taiwan (China); Department of Mathematics, National Taiwan University, Taipei 106, Taiwan (China)
2014-10-15
Most elliptic interface solvers become complicated for complex interface problems at those “exceptional points” where there are not enough neighboring interior points for high order interpolation. Such complication increases especially in three dimensions. Usually, the solvers are thus reduced to low order accuracy. In this paper, we classify these exceptional points and propose two recipes to maintain order of accuracy there, aiming at improving the previous coupling interface method [26]. Yet the idea is also applicable to other interface solvers. The main idea is to have at least first order approximations for second order derivatives at those exceptional points. Recipe 1 is to use the finite difference approximation for the second order derivatives at a nearby interior grid point, whenever this is possible. Recipe 2 is to flip domain signatures and introduce a ghost state so that a second-order method can be applied. This ghost state is a smooth extension of the solution at the exceptional point from the other side of the interface. The original state is recovered by a post-processing using nearby states and jump conditions. The choice of recipes is determined by a classification scheme of the exceptional points. The method renders the solution and its gradient uniformly second-order accurate in the entire computed domain. Numerical examples are provided to illustrate the second order accuracy of the presently proposed method in approximating the gradients of the original states for some complex interfaces which we had tested previous in two and three dimensions, and a real molecule ( (1D63)) which is double-helix shape and composed of hundreds of atoms.
An online supervised learning method based on gradient descent for spiking neurons.
Xu, Yan; Yang, Jing; Zhong, Shuiming
2017-09-01
The purpose of supervised learning with temporal encoding for spiking neurons is to make the neurons emit a specific spike train encoded by precise firing times of spikes. The gradient-descent-based (GDB) learning methods are widely used and verified in the current research. Although the existing GDB multi-spike learning (or spike sequence learning) methods have good performance, they work in an offline manner and still have some limitations. This paper proposes an online GDB spike sequence learning method for spiking neurons that is based on the online adjustment mechanism of real biological neuron synapses. The method constructs error function and calculates the adjustment of synaptic weights as soon as the neurons emit a spike during their running process. We analyze and synthesize desired and actual output spikes to select appropriate input spikes in the calculation of weight adjustment in this paper. The experimental results show that our method obviously improves learning performance compared with the offline learning manner and has certain advantage on learning accuracy compared with other learning methods. Stronger learning ability determines that the method has large pattern storage capacity. Copyright © 2017 Elsevier Ltd. All rights reserved.
A self-reference PRF-shift MR thermometry method utilizing the phase gradient
International Nuclear Information System (INIS)
Langley, Jason; Potter, William; Phipps, Corey; Zhao Qun; Huang Feng
2011-01-01
In magnetic resonance (MR) imaging, the most widely used and accurate method for measuring temperature is based on the shift in proton resonance frequency (PRF). However, inter-scan motion and bulk magnetic field shifts can lead to inaccurate temperature measurements in the PRF-shift MR thermometry method. The self-reference PRF-shift MR thermometry method was introduced to overcome such problems by deriving a reference image from the heated or treated image, and approximates the reference phase map with low-order polynomial functions. In this note, a new approach is presented to calculate the baseline phase map in self-reference PRF-shift MR thermometry. The proposed method utilizes the phase gradient to remove the phase unwrapping step inherent to other self-reference PRF-shift MR thermometry methods. The performance of the proposed method was evaluated using numerical simulations with temperature distributions following a two-dimensional Gaussian function as well as phantom and in vivo experimental data sets. The results from both the numerical simulations and experimental data show that the proposed method is a promising technique for measuring temperature. (note)
Filtering Airborne LIDAR Data by AN Improved Morphological Method Based on Multi-Gradient Analysis
Li, Y.
2013-05-01
The technology of airborne Light Detection And Ranging (LIDAR) is capable of acquiring dense and accurate 3D geospatial data. Although many related efforts have been made by a lot of researchers in the last few years, LIDAR data filtering is still a challenging task, especially for area with high relief or hybrid geographic features. In order to address the bare-ground extraction from LIDAR point clouds of complex landscapes, a novel morphological filtering algorithm is proposed based on multi-gradient analysis in terms of the characteristic of LIDAR data distribution in this paper. Firstly, point clouds are organized by an index mesh. Then, the multigradient of each point is calculated using the morphological method. And, objects are removed gradually by choosing some points to carry on an improved opening operation constrained by multi-gradient iteratively. 15 sample data provided by ISPRS Working Group III/3 are employed to test the filtering algorithm proposed. These sample data include those environments that may lead to filtering difficulty. Experimental results show that filtering algorithm proposed by this paper is of high adaptability to various scenes including urban and rural areas. Omission error, commission error and total error can be simultaneously controlled in a relatively small interval. This algorithm can efficiently remove object points while preserves ground points to a great degree.
Variational Level Set Method for Two-Stage Image Segmentation Based on Morphological Gradients
Directory of Open Access Journals (Sweden)
Zemin Ren
2014-01-01
Full Text Available We use variational level set method and transition region extraction techniques to achieve image segmentation task. The proposed scheme is done by two steps. We first develop a novel algorithm to extract transition region based on the morphological gradient. After this, we integrate the transition region into a variational level set framework and develop a novel geometric active contour model, which include an external energy based on transition region and fractional order edge indicator function. The external energy is used to drive the zero level set toward the desired image features, such as object boundaries. Due to this external energy, the proposed model allows for more flexible initialization. The fractional order edge indicator function is incorporated into the length regularization term to diminish the influence of noise. Moreover, internal energy is added into the proposed model to penalize the deviation of the level set function from a signed distance function. The results evolution of the level set function is the gradient flow that minimizes the overall energy functional. The proposed model has been applied to both synthetic and real images with promising results.
International Nuclear Information System (INIS)
Maciejewski, W. J.
1985-01-01
A method and apparatus for measuring the differential or gradient of an earth variable within a well bore (e.g., the spontaneous earth potential) and producing improved logs of this gradient or differential and its integral variable essentially free of any accumulated instrument and base line drift or error. The differential spontaneous potential of an earth formation traversed by a well bore is measured at repeated multiple depths by moving a pair of closely spaced electrodes through the well bore wherein each electrode is electrically insulated externally from the other and from a third downhole local ground (such as the well tool cable) to which each is internally resistively referenced. The measured electrical potential across the closely spaced electrodes is amplified and digitized before being transmitted to the earth's surface, whereupon an averaged value of such differential measurements within a traveling data window of predetermined length and adjacent to each successive measurement is used to adjust for base line drift, noise and instrument induced error. The resulting compensated differential logs are integrated, resulting in spontaneous potential logs of improved character
International Nuclear Information System (INIS)
Fathizadeh, M.; Aroujalian, A.
2012-01-01
The boundary layer convective heat transfer equations with low pressure gradient over a flat plate are solved using Homotopy Perturbation Method, which is one of the semi-exact methods. The nonlinear equations of momentum and energy solved simultaneously via Homotopy Perturbation Method are in good agreement with results obtained from numerical methods. Using this method, a general equation in terms of Pr number and pressure gradient (λ) is derived which can be used to investigate velocity and temperature profiles in the boundary layer.
International Nuclear Information System (INIS)
Ohtakara, Kazuhiro; Hayashi, Shinya; Hoshi, Hiroaki
2011-01-01
The objective of our study was to describe the dose gradient characteristics of Linac-based stereotactic radiosurgery using Paddick's gradient index (GI) and to elucidate the factors influencing the GI value. Seventy-three plans for brain metastases using the dynamic conformal arcs were reviewed. The GI values were calculated at the 80% and 90% isodose surfaces (IDSs) and at the different target coverage IDSs (D99, D95, D90, and D85). The GI values significantly decreased as the target coverage of the reference IDS increased (the percentage of the IDS decreased). There was a significant inverse correlation between the GI values and target volume. The plans generated with the addition of a 1-mm leaf margin had worse GI values both at the D99 and D95 relative to those without leaf margin. The number and arrangement of arcs also affected the GI value. The GI values are highly sensitive to the IDS selection variability for dose prescription or evaluation, the target volume, and the planning method. To objectively compare the quality of dose gradient between rival plans, it would be preferable to employ the GI defined at the reference IDS indicating the specific target coverage (exempli gratia (e.g.), D95), irrespective of the intended marginal dose. The modified GI (mGI), defined in this study, substituting the denominator of the original GI with the target volume, would be useful to compensate for the false superior GI value in cases of target over-coverage with the reference IDS and to objectively evaluate the dose gradient outside the target boundary. (author)
Directory of Open Access Journals (Sweden)
Uttam Singh Baghel
2012-10-01
Full Text Available Objective: The aim of present work was to develop a gradient RP-HPLC method for simultaneous analysis of rosiglitazone and gliclazide, in a tablet dosage form. Method: Chromatographic system was optimized using a hypersil C18 (250mm x 4.6mm, 5毺 m column with potassium dihydrogen phosphate (pH-7.0 and acetonitrile in the ratio of 60:40, as mobile phase, at a flow rate of 1.0 ml/min. Detection was carried out at 225 nm by a SPD-20A prominence UV/Vis detector. Result: Rosiglitazone and gliclazide were eluted with retention times of 17.36 and 7.06 min, respectively. Beer’s Lambert ’s Law was obeyed over the concentration ranges of 5 to 70 毺 g/ml and 2 to 12 毺 g/ml for rosiglitazone and gliclazide, respectively. Conclusion: The high recovery and low coefficients of variation confirm the suitability of the method for simultaneous analysis of both drugs in a tablets dosage form. Statistical analysis proves that the method is sensitive and significant for the analysis of rosiglitazone and gliclazide in pure and in pharmaceutical dosage form without any interference from the excipients. The method was validated in accordance with ICH guidelines. Validation revealed the method is specific, rapid, accurate, precise, reliable, and reproducible.
Yeung, E.S.; Chen, G.
1990-05-01
A method and means are disclosed for a spatial and temporal probe for laser generated plumes based on density gradients includes generation of a plume of vaporized material from a surface by an energy source. The probe laser beam is positioned so that the plume passes through the probe laser beam. Movement of the probe laser beam caused by refraction from the density gradient of the plume is monitored. Spatial and temporal information, correlated to one another, is then derived. 15 figs.
A primal sub-gradient method for structured classification with the averaged sum loss
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Mančev Dejan
2014-12-01
Full Text Available We present a primal sub-gradient method for structured SVM optimization defined with the averaged sum of hinge losses inside each example. Compared with the mini-batch version of the Pegasos algorithm for the structured case, which deals with a single structure from each of multiple examples, our algorithm considers multiple structures from a single example in one update. This approach should increase the amount of information learned from the example. We show that the proposed version with the averaged sum loss has at least the same guarantees in terms of the prediction loss as the stochastic version. Experiments are conducted on two sequence labeling problems, shallow parsing and part-of-speech tagging, and also include a comparison with other popular sequential structured learning algorithms.
Accelerated gradient methods for the x-ray imaging of solar flares
Bonettini, S.; Prato, M.
2014-05-01
In this paper we present new optimization strategies for the reconstruction of x-ray images of solar flares by means of the data collected by the Reuven Ramaty high energy solar spectroscopic imager. The imaging concept of the satellite is based on rotating modulation collimator instruments, which allow the use of both Fourier imaging approaches and reconstruction techniques based on the straightforward inversion of the modulated count profiles. Although in the last decade, greater attention has been devoted to the former strategies due to their very limited computational cost, here we consider the latter model and investigate the effectiveness of different accelerated gradient methods for the solution of the corresponding constrained minimization problem. Moreover, regularization is introduced through either an early stopping of the iterative procedure, or a Tikhonov term added to the discrepancy function by means of a discrepancy principle accounting for the Poisson nature of the noise affecting the data.
Mixed gradient-Tikhonov methods for solving nonlinear ill-posed problems in Banach spaces
International Nuclear Information System (INIS)
Margotti, Fábio
2016-01-01
Tikhonov regularization is a very useful and widely used method for finding stable solutions of ill-posed problems. A good choice of the penalization functional as well as a careful selection of the topologies of the involved spaces is fundamental to the quality of the reconstructions. These choices can be combined with some a priori information about the solution in order to preserve desired characteristics like sparsity constraints for example. To prove convergence and stability properties of this method, one usually has to assume that a minimizer of the Tikhonov functional is known. In practical situations however, the exact computation of a minimizer is very difficult and even finding an approximation can be a very challenging and expensive task if the involved spaces have poor convexity or smoothness properties. In this paper we propose a method to attenuate this gap between theory and practice, applying a gradient-like method to a Tikhonov functional in order to approximate a minimizer. Using only available information, we explicitly calculate a maximal step-size which ensures a monotonically decreasing error. The resulting algorithm performs only finitely many steps and terminates using the discrepancy principle. In particular the knowledge of a minimizer or even its existence does not need to be assumed. Under standard assumptions, we prove convergence and stability results in relatively general Banach spaces, and subsequently, test its performance numerically, reconstructing conductivities with sparsely located inclusions and different kinds of noise in the 2D electrical impedance tomography. (paper)
Standard Test Method for Measuring Heat Flux Using Flush-Mounted Insert Temperature-Gradient Gages
American Society for Testing and Materials. Philadelphia
2009-01-01
1.1 This test method describes the measurement of the net heat flux normal to a surface using gages inserted flush with the surface. The geometry is the same as heat-flux gages covered by Test Method E 511, but the measurement principle is different. The gages covered by this standard all use a measurement of the temperature gradient normal to the surface to determine the heat that is exchanged to or from the surface. Although in a majority of cases the net heat flux is to the surface, the gages operate by the same principles for heat transfer in either direction. 1.2 This general test method is quite broad in its field of application, size and construction. Two different gage types that are commercially available are described in detail in later sections as examples. A summary of common heat-flux gages is given by Diller (1). Applications include both radiation and convection heat transfer. The gages used for aerospace applications are generally small (0.155 to 1.27 cm diameter), have a fast time response ...
A primal–dual hybrid gradient method for nonlinear operators with applications to MRI
Valkonen, Tuomo
2014-05-01
We study the solution of minimax problems min xmax yG(x) + K(x), y - F*(y) in finite-dimensional Hilbert spaces. The functionals G and F* we assume to be convex, but the operator K we allow to be nonlinear. We formulate a natural extension of the modified primal-dual hybrid gradient method, originally for linear K, due to Chambolle and Pock. We prove the local convergence of the method, provided various technical conditions are satisfied. These include in particular the Aubin property of the inverse of a monotone operator at the solution. Of particular interest to us is the case arising from Tikhonov type regularization of inverse problems with nonlinear forward operators. Mainly we are interested in total variation and second-order total generalized variation priors. For such problems, we show that our general local convergence result holds when the noise level of the data f is low, and the regularization parameter α is correspondingly small. We verify the numerical performance of the method by applying it to problems from magnetic resonance imaging (MRI) in chemical engineering and medicine. The specific applications are in diffusion tensor imaging and MR velocity imaging. These numerical studies show very promising performance. © 2014 IOP Publishing Ltd.
Csiba, Dominik
2017-09-09
In this paper we introduce two novel generalizations of the theory for gradient descent type methods in the proximal setting. First, we introduce the proportion function, which we further use to analyze all known (and many new) block-selection rules for block coordinate descent methods under a single framework. This framework includes randomized methods with uniform, non-uniform or even adaptive sampling strategies, as well as deterministic methods with batch, greedy or cyclic selection rules. Second, the theory of strongly-convex optimization was recently generalized to a specific class of non-convex functions satisfying the so-called Polyak-{\\\\L}ojasiewicz condition. To mirror this generalization in the weakly convex case, we introduce the Weak Polyak-{\\\\L}ojasiewicz condition, using which we give global convergence guarantees for a class of non-convex functions previously not considered in theory. Additionally, we establish (necessarily somewhat weaker) convergence guarantees for an even larger class of non-convex functions satisfying a certain smoothness assumption only. By combining the two abovementioned generalizations we recover the state-of-the-art convergence guarantees for a large class of previously known methods and setups as special cases of our general framework. Moreover, our frameworks allows for the derivation of new guarantees for many new combinations of methods and setups, as well as a large class of novel non-convex objectives. The flexibility of our approach offers a lot of potential for future research, as a new block selection procedure will have a convergence guarantee for all objectives considered in our framework, while a new objective analyzed under our approach will have a whole fleet of block selection rules with convergence guarantees readily available.
Calibration of groundwater vulnerability mapping using the generalized reduced gradient method.
Elçi, Alper
2017-12-01
Groundwater vulnerability assessment studies are essential in water resources management. Overlay-and-index methods such as DRASTIC are widely used for mapping of groundwater vulnerability, however, these methods mainly suffer from a subjective selection of model parameters. The objective of this study is to introduce a calibration procedure that results in a more accurate assessment of groundwater vulnerability. The improvement of the assessment is formulated as a parameter optimization problem using an objective function that is based on the correlation between actual groundwater contamination and vulnerability index values. The non-linear optimization problem is solved with the generalized-reduced-gradient (GRG) method, which is numerical algorithm based optimization method. To demonstrate the applicability of the procedure, a vulnerability map for the Tahtali stream basin is calibrated using nitrate concentration data. The calibration procedure is easy to implement and aims the maximization of correlation between observed pollutant concentrations and groundwater vulnerability index values. The influence of each vulnerability parameter in the calculation of the vulnerability index is assessed by performing a single-parameter sensitivity analysis. Results of the sensitivity analysis show that all factors are effective on the final vulnerability index. Calibration of the vulnerability map improves the correlation between index values and measured nitrate concentrations by 19%. The regression coefficient increases from 0.280 to 0.485. It is evident that the spatial distribution and the proportions of vulnerability class areas are significantly altered with the calibration process. Although the applicability of the calibration method is demonstrated on the DRASTIC model, the applicability of the approach is not specific to a certain model and can also be easily applied to other overlay-and-index methods. Copyright © 2017 Elsevier B.V. All rights reserved.
Csiba, Dominik; Richtarik, Peter
2017-01-01
In this paper we introduce two novel generalizations of the theory for gradient descent type methods in the proximal setting. First, we introduce the proportion function, which we further use to analyze all known (and many new) block-selection rules for block coordinate descent methods under a single framework. This framework includes randomized methods with uniform, non-uniform or even adaptive sampling strategies, as well as deterministic methods with batch, greedy or cyclic selection rules. Second, the theory of strongly-convex optimization was recently generalized to a specific class of non-convex functions satisfying the so-called Polyak-{\\L}ojasiewicz condition. To mirror this generalization in the weakly convex case, we introduce the Weak Polyak-{\\L}ojasiewicz condition, using which we give global convergence guarantees for a class of non-convex functions previously not considered in theory. Additionally, we establish (necessarily somewhat weaker) convergence guarantees for an even larger class of non-convex functions satisfying a certain smoothness assumption only. By combining the two abovementioned generalizations we recover the state-of-the-art convergence guarantees for a large class of previously known methods and setups as special cases of our general framework. Moreover, our frameworks allows for the derivation of new guarantees for many new combinations of methods and setups, as well as a large class of novel non-convex objectives. The flexibility of our approach offers a lot of potential for future research, as a new block selection procedure will have a convergence guarantee for all objectives considered in our framework, while a new objective analyzed under our approach will have a whole fleet of block selection rules with convergence guarantees readily available.
International Nuclear Information System (INIS)
Park, J.W.; Bae, J.H.; Seol, W.C.
2015-01-01
An integrated conjugate heat transfer analysis method for the thermal integrity of a reactor vessel under external reactor vessel cooling conditions is developed to resolve light metal layer focusing effect issue. The method calculates steady-state 3-dimensional temperature distribution of a reactor vessel using coupled conjugate heat transfer between in-vessel 3-layered stratified corium (metallic pool, oxide pool and heavy metal) and polar-angle dependent boiling heat transfer at the outer surface of a reactor vessel. The 3-layer corium heat transfer model is utilizing lumped-parameter thermal-resistance circuit method and ex-vessel boiling regimes are parametrically considered. The thermal integrity of a reactor vessel is addressed in terms of un-molten thickness profile. The vessel 3-dimensional heat conduction is validated against a commercial code. It is found that even though the internal heat flux from the metal layer goes far beyond critical heat flux (CHF) the heat flux from the outermost nodes of the vessel may be maintained below CHF due to massive vessel heat diffusion. The heat diffusion throughout the vessel is more pronounced for relatively low heat generation rate in an oxide pool. Parametric calculations are performed considering thermal conditions such as peak heat flux from a light metal layer, heat generation in an oxide pool and external boiling conditions. The major finding is that the most crucial factor for success of in-vessel retention is not the mass of the molten light metal above the oxide pool but the heat generation rate inside the oxide pool and the 3-dimensional vessel heat transfer provides a much larger minimum vessel wall thickness. (authors)
International Nuclear Information System (INIS)
Bozkaya, Uğur; Sherrill, C. David
2016-01-01
An efficient implementation is presented for analytic gradients of the coupled-cluster singles and doubles (CCSD) method with the density-fitting approximation, denoted DF-CCSD. Frozen core terms are also included. When applied to a set of alkanes, the DF-CCSD analytic gradients are significantly accelerated compared to conventional CCSD for larger molecules. The efficiency of our DF-CCSD algorithm arises from the acceleration of several different terms, which are designated as the “gradient terms”: computation of particle density matrices (PDMs), generalized Fock-matrix (GFM), solution of the Z-vector equation, formation of the relaxed PDMs and GFM, back-transformation of PDMs and GFM to the atomic orbital (AO) basis, and evaluation of gradients in the AO basis. For the largest member of the alkane set (C 10 H 22 ), the computational times for the gradient terms (with the cc-pVTZ basis set) are 2582.6 (CCSD) and 310.7 (DF-CCSD) min, respectively, a speed up of more than 8-folds. For gradient related terms, the DF approach avoids the usage of four-index electron repulsion integrals. Based on our previous study [U. Bozkaya, J. Chem. Phys. 141, 124108 (2014)], our formalism completely avoids construction or storage of the 4-index two-particle density matrix (TPDM), using instead 2- and 3-index TPDMs. The DF approach introduces negligible errors for equilibrium bond lengths and harmonic vibrational frequencies.
Energy Technology Data Exchange (ETDEWEB)
Zou, Wenli; Filatov, Michael; Cremer, Dieter, E-mail: dcremer@smu.edu [Computational and Theoretical Chemistry Group (CATCO), Department of Chemistry, Southern Methodist University, 3215 Daniel Ave, Dallas, Texas 75275-0314 (United States)
2015-06-07
The analytical gradient for the two-component Normalized Elimination of the Small Component (2c-NESC) method is presented. The 2c-NESC is a Dirac-exact method that employs the exact two-component one-electron Hamiltonian and thus leads to exact Dirac spin-orbit (SO) splittings for one-electron atoms. For many-electron atoms and molecules, the effect of the two-electron SO interaction is modeled by a screened nucleus potential using effective nuclear charges as proposed by Boettger [Phys. Rev. B 62, 7809 (2000)]. The effect of spin-orbit coupling (SOC) on molecular geometries is analyzed utilizing the properties of the frontier orbitals and calculated SO couplings. It is shown that bond lengths can either be lengthened or shortened under the impact of SOC where in the first case the influence of low lying excited states with occupied antibonding orbitals plays a role and in the second case the jj-coupling between occupied antibonding and unoccupied bonding orbitals dominates. In general, the effect of SOC on bond lengths is relatively small (≤5% of the scalar relativistic changes in the bond length). However, large effects are found for van der Waals complexes Hg{sub 2} and Cn{sub 2}, which are due to the admixture of more bonding character to the highest occupied spinors.
Zou, Wenli; Filatov, Michael; Cremer, Dieter
2015-06-01
The analytical gradient for the two-component Normalized Elimination of the Small Component (2c-NESC) method is presented. The 2c-NESC is a Dirac-exact method that employs the exact two-component one-electron Hamiltonian and thus leads to exact Dirac spin-orbit (SO) splittings for one-electron atoms. For many-electron atoms and molecules, the effect of the two-electron SO interaction is modeled by a screened nucleus potential using effective nuclear charges as proposed by Boettger [Phys. Rev. B 62, 7809 (2000)]. The effect of spin-orbit coupling (SOC) on molecular geometries is analyzed utilizing the properties of the frontier orbitals and calculated SO couplings. It is shown that bond lengths can either be lengthened or shortened under the impact of SOC where in the first case the influence of low lying excited states with occupied antibonding orbitals plays a role and in the second case the jj-coupling between occupied antibonding and unoccupied bonding orbitals dominates. In general, the effect of SOC on bond lengths is relatively small (≤5% of the scalar relativistic changes in the bond length). However, large effects are found for van der Waals complexes Hg2 and Cn2, which are due to the admixture of more bonding character to the highest occupied spinors.
Applying the Weighted Horizontal Magnetic Gradient Method to a Simulated Flaring Active Region
Korsós, M. B.; Chatterjee, P.; Erdélyi, R.
2018-04-01
Here, we test the weighted horizontal magnetic gradient (WG M ) as a flare precursor, introduced by Korsós et al., by applying it to a magnetohydrodynamic (MHD) simulation of solar-like flares. The preflare evolution of the WG M and the behavior of the distance parameter between the area-weighted barycenters of opposite-polarity sunspots at various heights is investigated in the simulated δ-type sunspot. Four flares emanated from this sunspot. We found the optimum heights above the photosphere where the flare precursors of the WG M method are identifiable prior to each flare. These optimum heights agree reasonably well with the heights of the occurrence of flares identified from the analysis of their thermal and ohmic heating signatures in the simulation. We also estimated the expected time of the flare onsets from the duration of the approaching–receding motion of the barycenters of opposite polarities before each single flare. The estimated onset time and the actual time of occurrence of each flare are in good agreement at the corresponding optimum heights. This numerical experiment further supports the use of flare precursors based on the WG M method.
Directory of Open Access Journals (Sweden)
Faming Zhang
2016-11-01
Full Text Available The prediction of travel times is challenging because of the sparseness of real-time traffic data and the intrinsic uncertainty of travel on congested urban road networks. We propose a new gradient–boosted regression tree method to accurately predict travel times. This model accounts for spatiotemporal correlations extracted from historical and real-time traffic data for adjacent and target links. This method can deliver high prediction accuracy by combining simple regression trees with poor performance. It corrects the error found in existing models for improved prediction accuracy. Our spatiotemporal gradient–boosted regression tree model was verified in experiments. The training data were obtained from big data reflecting historic traffic conditions collected by probe vehicles in Wuhan from January to May 2014. Real-time data were extracted from 11 weeks of GPS records collected in Wuhan from 5 May 2014 to 20 July 2014. Based on these data, we predicted link travel time for the period from 21 July 2014 to 25 July 2014. Experiments showed that our proposed spatiotemporal gradient–boosted regression tree model obtained better results than gradient boosting, random forest, or autoregressive integrated moving average approaches. Furthermore, these results indicate the advantages of our model for urban link travel time prediction.
Directory of Open Access Journals (Sweden)
Lu Yang
2018-01-01
Full Text Available Downward shortwave radiation (DSR is an essential parameter in the terrestrial radiation budget and a necessary input for models of land-surface processes. Although several radiation products using satellite observations have been released, coarse spatial resolution and low accuracy limited their application. It is important to develop robust and accurate retrieval methods with higher spatial resolution. Machine learning methods may be powerful candidates for estimating the DSR from remotely sensed data because of their ability to perform adaptive, nonlinear data fitting. In this study, the gradient boosting regression tree (GBRT was employed to retrieve DSR measurements with the ground observation data in China collected from the China Meteorological Administration (CMA Meteorological Information Center and the satellite observations from the Advanced Very High Resolution Radiometer (AVHRR at a spatial resolution of 5 km. The validation results of the DSR estimates based on the GBRT method in China at a daily time scale for clear sky conditions show an R2 value of 0.82 and a root mean square error (RMSE value of 27.71 W·m−2 (38.38%. These values are 0.64 and 42.97 W·m−2 (34.57%, respectively, for cloudy sky conditions. The monthly DSR estimates were also evaluated using ground measurements. The monthly DSR estimates have an overall R2 value of 0.92 and an RMSE of 15.40 W·m−2 (12.93%. Comparison of the DSR estimates with the reanalyzed and retrieved DSR measurements from satellite observations showed that the estimated DSR is reasonably accurate but has a higher spatial resolution. Moreover, the proposed GBRT method has good scalability and is easy to apply to other parameter inversion problems by changing the parameters and training data.
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.
Sun, Qi; Fu, Shujun
2017-09-20
Fringe orientation is an important feature of fringe patterns and has a wide range of applications such as guiding fringe pattern filtering, phase unwrapping, and abstraction. Estimating fringe orientation is a basic task for subsequent processing of fringe patterns. However, various noise, singular and obscure points, and orientation data degeneration lead to inaccurate calculations of fringe orientation. Thus, to deepen the understanding of orientation estimation and to better guide orientation estimation in fringe pattern processing, some advanced gradient-field-based orientation estimation methods are compared and analyzed. At the same time, following the ideas of smoothing regularization and computing of bigger gradient fields, a regularized singular-value decomposition (RSVD) technique is proposed for fringe orientation estimation. To compare the performance of these gradient-field-based methods, quantitative results and visual effect maps of orientation estimation are given on simulated and real fringe patterns that demonstrate that the RSVD produces the best estimation results at a cost of relatively less time.
Energy Technology Data Exchange (ETDEWEB)
Ledermüller, Katrin; Schütz, Martin, E-mail: martin.schuetz@chemie.uni-regensburg.de [Institute of Physical and Theoretical Chemistry, University of Regensburg, Universitätsstraße 31, D-93040 Regensburg (Germany)
2014-04-28
A multistate local CC2 response method for the calculation of analytic energy gradients with respect to nuclear displacements is presented for ground and electronically excited states. The gradient enables the search for equilibrium geometries of extended molecular systems. Laplace transform is used to partition the eigenvalue problem in order to obtain an effective singles eigenvalue problem and adaptive, state-specific local approximations. This leads to an approximation in the energy Lagrangian, which however is shown (by comparison with the corresponding gradient method without Laplace transform) to be of no concern for geometry optimizations. The accuracy of the local approximation is tested and the efficiency of the new code is demonstrated by application calculations devoted to a photocatalytic decarboxylation process of present interest.
Ledermüller, Katrin; Schütz, Martin
2014-04-28
A multistate local CC2 response method for the calculation of analytic energy gradients with respect to nuclear displacements is presented for ground and electronically excited states. The gradient enables the search for equilibrium geometries of extended molecular systems. Laplace transform is used to partition the eigenvalue problem in order to obtain an effective singles eigenvalue problem and adaptive, state-specific local approximations. This leads to an approximation in the energy Lagrangian, which however is shown (by comparison with the corresponding gradient method without Laplace transform) to be of no concern for geometry optimizations. The accuracy of the local approximation is tested and the efficiency of the new code is demonstrated by application calculations devoted to a photocatalytic decarboxylation process of present interest.
International Nuclear Information System (INIS)
Ledermüller, Katrin; Schütz, Martin
2014-01-01
A multistate local CC2 response method for the calculation of analytic energy gradients with respect to nuclear displacements is presented for ground and electronically excited states. The gradient enables the search for equilibrium geometries of extended molecular systems. Laplace transform is used to partition the eigenvalue problem in order to obtain an effective singles eigenvalue problem and adaptive, state-specific local approximations. This leads to an approximation in the energy Lagrangian, which however is shown (by comparison with the corresponding gradient method without Laplace transform) to be of no concern for geometry optimizations. The accuracy of the local approximation is tested and the efficiency of the new code is demonstrated by application calculations devoted to a photocatalytic decarboxylation process of present interest
Gangarapu, Satesh; Marcelis, Antonius T M; Zuilhof, Han
2013-04-02
The pKa of the conjugate acids of alkanolamines, neurotransmitters, alkaloid drugs and nucleotide bases are calculated with density functional methods (B3LYP, M08-HX and M11-L) and ab initio methods (SCS-MP2, G3). Implicit solvent effects are included with a conductor-like polarizable continuum model (CPCM) and universal solvation models (SMD, SM8). G3, SCS-MP2 and M11-L methods coupled with SMD and SM8 solvation models perform well for alkanolamines with mean unsigned errors below 0.20 pKa units, in all cases. Extending this method to the pKa calculation of 35 nitrogen-containing compounds spanning 12 pKa units showed an excellent correlation between experimental and computational pKa values of these 35 amines with the computationally low-cost SM8/M11-L density functional approach. Copyright © 2013 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.
Zou, Wenli; Filatov, Michael; Cremer, Dieter
2011-01-01
The analytical energy gradient of the normalized elimination of the small component (NESC) method is derived for the first time and implemented for the routine calculation of NESC geometries and other first order molecular properties. Essential for the derivation is the correct calculation of the
DEFF Research Database (Denmark)
Paidarová, Ivana; Sauer, Stephan P. A.
2012-01-01
We have compared the performance of density functional theory (DFT) using five different exchange-correlation functionals with four coupled cluster theory based wave function methods in the calculation of geometrical derivatives of the polarizability tensor of methane. The polarizability gradient...
Zhang, Shuwen; Gong, Yuansheng; Khanal, Som; Lu, Yanjie; Lucey, John A
2017-11-01
Covalent attachment of polysaccharides to proteins (conjugation) via the Maillard reaction has been extensively studied. Conjugation can lead to a significant improvement in protein functionality (e.g., solubility, emulsification, and heat stability). Caseins have previously been successfully conjugated with maltodextrin (Md), but the effect on the detailed acid gelation properties has not been examined. We studied the effect of conjugating sodium caseinate (NaCN) with 3 different sized Md samples via the Maillard reaction in aqueous solutions. The Md samples had dextrose equivalents of 4 to 7, 9 to 12, and 20 to 23 for Md40, Md100, and Md200, respectively. The conjugation reaction was performed in mixtures with 5% NaCN and 5% Md, which were heated at 90°C for 10 h. The degree of conjugation was estimated from the reduction in free amino groups as well as color changes. Sodium dodecyl sulfate-PAGE analysis was performed to confirm conjugation by employing staining of both protein and carbohydrate bands. The molar mass of samples was determined by size-exclusion chromatography coupled with multi-angle laser light scattering. After the conjugation reaction, samples were then gelled by the addition of 0.63% (wt/vol) glucono-δ-lactone at 30°C, such that samples reached pH 4.6 after about 13 h. The rheological properties of samples during acidification was monitored by small-strain dynamic oscillatory rheology. The microstructure of acid gels at pH 4.6 was examined by fluorescence microscopy. Conjugation resulted in a loss of 10.8, 8.8, and 11.9% of the available amino groups in the protein for the NaCN-Md40 conjugates (C40), NaCN-Md100 conjugates (C100), and NaCN-Md100 conjugates (C200), respectively. With a decrease in the size of the type of Md, an increase occurred in the molar mass of the resultant conjugate. The weight average molar masses of NaCN-Md samples were 340, 368, and 425 kDa for the conjugates C40, C100, and C200, respectively. Addition of Md to Na
International Nuclear Information System (INIS)
Oh, C.H.; Cho, Z.H.; California Univ., Irvine
1986-01-01
A new phase coding method using a selection gradient for high speed NMR flow velocity measurements is introduced and discussed. To establish a phase-velocity relationship of flow under the slice selection gradient and spin-echo RF pulse, the Bloch equation was numerically solved under the assumption that only one directional flow exists, i.e. in the direction of slice selection. Details of the numerical solution of the Bloch equation and techniques related to the numerical computations are also given. Finally, using the numerical calculation, high speed flow velocity measurement was attempted and found to be in good agreement with other complementary controlled measurements. (author)
Purification of SUMO conjugating enzymes and kinetic analysis of substrate conjugation
Yunus, Ali A.; Lima, Christopher D.
2009-01-01
SUMO conjugation to protein substrates requires the concerted action of a dedicated E2 ubiquitin conjugation enzyme (Ubc9) and associated E3 ligases. Although Ubc9 can directly recognize and modify substrate lysine residues that occur within a consensus site for SUMO modification, E3 ligases can redirect specificity and enhance conjugation rates during SUMO conjugation in vitro and in vivo. In this chapter, we will describe methods utilized to purify SUMO conjugating enzymes and model substrates which can be used for analysis of SUMO conjugation in vitro. We will also describe methods to extract kinetic parameters during E3-dependent or E3-independent substrate conjugation. PMID:19107417
International Nuclear Information System (INIS)
Bjorgaard, J. A.; Velizhanin, K. A.; Tretiak, S.
2015-01-01
This study describes variational energy expressions and analytical excited state energy gradients for time-dependent self-consistent field methods with polarizable solvent effects. Linear response, vertical excitation, and state-specific solventmodels are examined. Enforcing a variational ground stateenergy expression in the state-specific model is found to reduce it to the vertical excitation model. Variational excited state energy expressions are then provided for the linear response and vertical excitation models and analytical gradients are formulated. Using semiempiricalmodel chemistry, the variational expressions are verified by numerical and analytical differentiation with respect to a static external electric field. Lastly, analytical gradients are further tested by performing microcanonical excited state molecular dynamics with p-nitroaniline
International Nuclear Information System (INIS)
Kobayashi, Fujio; Yamaguchi, Shoichiro
1982-01-01
A method of the reconstruction of computed tomographic images was proposed to reduce the exposure dose to X-ray. The method is the small number of X-ray projection method by accelerative gradient method. The procedures of computation are described. The algorithm of these procedures is simple, the convergence of the computation is fast, and the required memory capacity is small. Numerical simulation was carried out to conform the validity of this method. A sample of simple shape was considered, projection data were given, and the images were reconstructed from 6 views. Good results were obtained, and the method is considered to be useful. (Kato, T.)
A temporal subtraction method for thoracic CT images based on generalized gradient vector flow
International Nuclear Information System (INIS)
Miyake, Noriaki; Kim, H.; Maeda, Shinya; Itai, Yoshinori; Tan, J.K.; Ishikawa, Seiji; Katsuragawa, Shigehiko
2010-01-01
A temporal subtraction image, which is obtained by subtraction of a previous image from a current one, can be used for enhancing interval changes (such as formation of new lesions and changes in existing abnormalities) on medical images by removing most of the normal structures. If image registration is incorrect, not only the interval changes but also the normal structures would be appeared as some artifacts on the temporal subtraction image. In a temporal subtraction technique for 2-D X-ray image, the effectiveness is shown through a lot of clinical evaluation experiments, and practical use is advancing. Moreover, the MDCT (Multi-Detector row Computed Tomography) can easily introduced on medical field, the development of a temporal subtraction for thoracic CT Images is expected. In our study, a temporal subtraction technique for thoracic CT Images is developed. As the technique, the vector fields are described by use of GGVF (Generalized Gradient Vector Flow) from the previous and current CT images. Afterwards, VOI (Volume of Interest) are set up on the previous and current CT image pairs. The shift vectors are calculated by using nearest neighbor matching of the vector fields in these VOIs. The search kernel on previous CT image is set up from the obtained shift vector. The previous CT voxel which resemble standard the current voxel is detected by voxel value and vector of the GGVF in the kernel. And, the previous CT image is transformed to the same coordinate of standard voxel. Finally, temporal subtraction image is made by subtraction of a warping image from a current one. To verify the proposal method, the result of application to 7 cases and the effectiveness are described. (author)
Porous materials with gradient and biporous structure, methods of their production
International Nuclear Information System (INIS)
Ilyuschenko, A.; Savich, V.; Pilinevich, L.; Rak, A.
2001-01-01
We have worked out the technology of production porous powder materials (PPMs) of bronze, nickel, corrosion resistant steel and titanium powders with gradient and (or) biporous structure: vibrating forming of metal powders (including in electromagnetic field); layer-by-layer forming of metal powders with pore-maker while different proportion of the latter in the layer; forming of powder polymer layer on the preliminary sintered metal PPM surface. We have worked out the technology of production biporous structure by the following methods: metal granules forming and sintering; forming and sintering of metal powder with granules (2-3 mm) and pores-forming powder (size of particles is 0,4-0,63 mm). The novelty is in creation of technological bases of pores sizes regulation from 5 mkm on one PPM surface to 120 mkm on the opposite PPM surface which thickness can be 2-6 mm. PPM porosity can be constant within 0,3-0,6 relative units. More effective are those PPM which pores sizes are changeable and also porosity (from 0,35 to 0,60) from one surface o the opposite one. Two-layer metal-polymer PPM have pores sizes of 20-40 mkm in polymer layer and porosity 0,4-0,5 and, correspondingly, in metal layer 80-100 mkm and 0,45-0,55. In biporous structures made of 2-3 mm metal granules the distance between granules is 300-600 mkm and in granules - 14-30 mkm. The integral porosity of such PPM is 0,55-0,70. The technology of forming and sintering metal powder with granules and pores-making powder (carbamide) enables to regulate the integral porosity within 0,7-0,8 and average pores sizes within 100-1000 mkm with average size of metal powder particles of 0,63-1,0 mm. (author)
Directory of Open Access Journals (Sweden)
Hao Shi
2018-02-01
Full Text Available With the rapid development of remote sensing technologies, SAR satellites like China’s Gaofen-3 satellite have more imaging modes and higher resolution. With the availability of high-resolution SAR images, automatic ship target detection has become an important topic in maritime research. In this paper, a novel ship detection method based on gradient and integral features is proposed. This method is mainly composed of three steps. First, in the preprocessing step, a filter is employed to smooth the clutters and the smoothing effect can be adaptive adjusted according to the statistics information of the sub-window. Thus, it can retain details while achieving noise suppression. Second, in the candidate area extraction, a sea-land segmentation method based on gradient enhancement is presented. The integral image method is employed to accelerate computation. Finally, in the ship target identification step, a feature extraction strategy based on Haar-like gradient information and a Radon transform is proposed. This strategy decreases the number of templates found in traditional Haar-like methods. Experiments were performed using Gaofen-3 single-polarization SAR images, and the results showed that the proposed method has high detection accuracy and rapid computational efficiency. In addition, this method has the potential for on-board processing.
Optimising a parallel conjugate gradient solver
Energy Technology Data Exchange (ETDEWEB)
Field, M.R. [O`Reilly Institute, Dublin (Ireland)
1996-12-31
This work arises from the introduction of a parallel iterative solver to a large structural analysis finite element code. The code is called FEX and it was developed at Hitachi`s Mechanical Engineering Laboratory. The FEX package can deal with a large range of structural analysis problems using a large number of finite element techniques. FEX can solve either stress or thermal analysis problems of a range of different types from plane stress to a full three-dimensional model. These problems can consist of a number of different materials which can be modelled by a range of material models. The structure being modelled can have the load applied at either a point or a surface, or by a pressure, a centrifugal force or just gravity. Alternatively a thermal load can be applied with a given initial temperature. The displacement of the structure can be constrained by having a fixed boundary or by prescribing the displacement at a boundary.
Regularized image denoising based on spectral gradient optimization
International Nuclear Information System (INIS)
Lukić, Tibor; Lindblad, Joakim; Sladoje, Nataša
2011-01-01
Image restoration methods, such as denoising, deblurring, inpainting, etc, are often based on the minimization of an appropriately defined energy function. We consider energy functions for image denoising which combine a quadratic data-fidelity term and a regularization term, where the properties of the latter are determined by a used potential function. Many potential functions are suggested for different purposes in the literature. We compare the denoising performance achieved by ten different potential functions. Several methods for efficient minimization of regularized energy functions exist. Most are only applicable to particular choices of potential functions, however. To enable a comparison of all the observed potential functions, we propose to minimize the objective function using a spectral gradient approach; spectral gradient methods put very weak restrictions on the used potential function. We present and evaluate the performance of one spectral conjugate gradient and one cyclic spectral gradient algorithm, and conclude from experiments that both are well suited for the task. We compare the performance with three total variation-based state-of-the-art methods for image denoising. From the empirical evaluation, we conclude that denoising using the Huber potential (for images degraded by higher levels of noise; signal-to-noise ratio below 10 dB) and the Geman and McClure potential (for less noisy images), in combination with the spectral conjugate gradient minimization algorithm, shows the overall best performance
Gradient heat flux measurement as monitoring method for the diesel engine
Sapozhnikov, S. Z.; Mityakov, V. Yu; Mityakov, A. V.; Vintsarevich, A. V.; Pavlov, A. V.; Nalyotov, I. D.
2017-11-01
The usage of gradient heat flux measurement for monitoring of heat flux on combustion chamber surface and optimization of diesel work process is proposed. Heterogeneous gradient heat flux sensors can be used at various regimes for an appreciable length of time. Fuel injection timing is set by the position of the maximum point on the angular heat flux diagram however, the value itself of the heat flux may not be considered. The development of such an approach can be productive for remote monitoring of work process in the cylinders of high-power marine engines.
Bell, Robert T; Jacobs, Alan G; Sorg, Victoria C; Jung, Byungki; Hill, Megan O; Treml, Benjamin E; Thompson, Michael O
2016-09-12
A high-throughput method for characterizing the temperature dependence of material properties following microsecond to millisecond thermal annealing, exploiting the temperature gradients created by a lateral gradient laser spike anneal (lgLSA), is presented. Laser scans generate spatial thermal gradients of up to 5 °C/μm with peak temperatures ranging from ambient to in excess of 1400 °C, limited only by laser power and materials thermal limits. Discrete spatial property measurements across the temperature gradient are then equivalent to independent measurements after varying temperature anneals. Accurate temperature calibrations, essential to quantitative analysis, are critical and methods for both peak temperature and spatial/temporal temperature profile characterization are presented. These include absolute temperature calibrations based on melting and thermal decomposition, and time-resolved profiles measured using platinum thermistors. A variety of spatially resolved measurement probes, ranging from point-like continuous profiling to large area sampling, are discussed. Examples from annealing of III-V semiconductors, CdSe quantum dots, low-κ dielectrics, and block copolymers are included to demonstrate the flexibility, high throughput, and precision of this technique.
Energy Technology Data Exchange (ETDEWEB)
Bozkaya, Uğur, E-mail: ugur.bozkaya@atauni.edu.tr [Department of Chemistry, Atatürk University, Erzurum 25240, Turkey and Department of Chemistry, Middle East Technical University, Ankara 06800 (Turkey)
2014-09-28
General analytic gradient expressions (with the frozen-core approximation) are presented for density-fitted post-HF methods. An efficient implementation of frozen-core analytic gradients for the second-order Møller–Plesset perturbation theory (MP2) with the density-fitting (DF) approximation (applying to both reference and correlation energies), which is denoted as DF-MP2, is reported. The DF-MP2 method is applied to a set of alkanes, conjugated dienes, and noncovalent interaction complexes to compare the computational cost of single point analytic gradients with MP2 with the resolution of the identity approach (RI-MP2) [F. Weigend and M. Häser, Theor. Chem. Acc. 97, 331 (1997); R. A. Distasio, R. P. Steele, Y. M. Rhee, Y. Shao, and M. Head-Gordon, J. Comput. Chem. 28, 839 (2007)]. In the RI-MP2 method, the DF approach is used only for the correlation energy. Our results demonstrate that the DF-MP2 method substantially accelerate the RI-MP2 method for analytic gradient computations due to the reduced input/output (I/O) time. Because in the DF-MP2 method the DF approach is used for both reference and correlation energies, the storage of 4-index electron repulsion integrals (ERIs) are avoided, 3-index ERI tensors are employed instead. Further, as in case of integrals, our gradient equation is completely avoid construction or storage of the 4-index two-particle density matrix (TPDM), instead we use 2- and 3-index TPDMs. Hence, the I/O bottleneck of a gradient computation is significantly overcome. Therefore, the cost of the generalized-Fock matrix (GFM), TPDM, solution of Z-vector equations, the back transformation of TPDM, and integral derivatives are substantially reduced when the DF approach is used for the entire energy expression. Further application results show that the DF approach introduce negligible errors for closed-shell reaction energies and equilibrium bond lengths.
International Nuclear Information System (INIS)
Bunting, R.W.; Callahan, R.J.; Finkelstein, S.; Lees, R.S.; Strauss, H.W.
1982-01-01
When labeling platelets with indium-111 oxine, albumin density-gradient separation minimizes the time spent to resuspend those platelets that have been centrifuged against a hard surface. Labeling efficiency or platelet viability, as measured by platelet survival or aggregation with adenosine diphosphate, are not adversely affected
Tumpa, Anja; Stajić, Ana; Jančić-Stojanović, Biljana; Medenica, Mirjana
2017-02-05
This paper deals with the development of hydrophilic interaction liquid chromatography (HILIC) method with gradient elution, in accordance with Analytical Quality by Design (AQbD) methodology, for the first time. The method is developed for olanzapine and its seven related substances. Following step by step AQbD methodology, firstly as critical process parameters (CPPs) temperature, starting content of aqueous phase and duration of linear gradient are recognized, and as critical quality attributes (CQAs) separation criterion S of critical pairs of substances are investigated. Rechtschaffen design is used for the creation of models that describe the dependence between CPPs and CQAs. The design space that is obtained at the end is used for choosing the optimal conditions (set point). The method is fully validated at the end to verify the adequacy of the chosen optimal conditions and applied to real samples. Copyright © 2016 Elsevier B.V. All rights reserved.
Development of conjugate methods with gas chromatography for inorganic compounds analysis
International Nuclear Information System (INIS)
Baccan, N.
1975-01-01
The application of gas chromatography combined with mass spectrometry or with nuclear methods for the analysis of inorganic compounds is studied. The advantages of the use of a gas chromatograph coupled with a quadrupole mass spectrometer or with a high resolution radiation detector, are discussed. We also studied the formation and solvent extraction of metal chelates; an aliquot of the organic phase was directly injected into the gas chromatograph and the eluted compounds were detected by mass spectrometry or, when radioactive, by nuclear methods. (author)
Method to conjugate polysaccharide antigens to surfaces for the detection of antibodies
DEFF Research Database (Denmark)
Boas, Ulrik; Lind, Peter; Riber, Ulla
2014-01-01
microbeads modified with N-alkyl hydroxylamine and N-alkyl-O-methyl hydroxylamine surface groups by incubation of antigen and beads for 16 h at 40 oC without the need for coupling agents. The efficiency of the new method was evaluated by flow cytometry in model samples and serum samples containing antibodies...
Mazor, Raphael D; Schiff, Kenneth; Ritter, Kerry; Rehn, Andy; Ode, Peter
2010-08-01
Biomonitoring programs are often required to assess streams for which assessment tools have not been developed. For example, low-gradient streams (slopeindices in the state were developed in high-gradient systems. This study evaluated the performance of three sampling methods [targeted riffle composite (TRC), reach-wide benthos (RWB), and the margin-center-margin modification of RWB (MCM)] and two indices [the Southern California Index of Biotic Integrity (SCIBI) and the ratio of observed to expected taxa (O/E)] in low-gradient streams in California for application in this habitat type. Performance was evaluated in terms of efficacy (i.e., ability to collect enough individuals for index calculation), comparability (i.e., similarity of assemblages and index scores), sensitivity (i.e., responsiveness to disturbance), and precision (i.e., ability to detect small differences in index scores). The sampling methods varied in the degree to which they targeted macroinvertebrate-rich microhabitats, such as riffles and vegetated margins, which may be naturally scarce in low-gradient streams. The RWB method failed to collect sufficient numbers of individuals (i.e., >or=450) to calculate the SCIBI in 28 of 45 samples and often collected fewer than 100 individuals, suggesting it is inappropriate for low-gradient streams in California; failures for the other methods were less common (TRC, 16 samples; MCM, 11 samples). Within-site precision, measured as the minimum detectable difference (MDD) was poor but similar across methods for the SCIBI (ranging from 19 to 22). However, RWB had the lowest MDD for O/E scores (0.20 versus 0.24 and 0.28 for MCM and TRC, respectively). Mantel correlations showed that assemblages were more similar within sites among methods than within methods among sites, suggesting that the sampling methods were collecting similar assemblages of organisms. Statistically significant disagreements among methods were not detected, although O/E scores were higher
International Nuclear Information System (INIS)
1983-01-01
Under the direction of the Cinematography and Photography Standards Committee, a British Standard method has been prepared for determining ISO speed and average gradient of direct-exposure medical and dental radiographic film/film-process combinations. The method determines the speed and gradient, i.e. contrast, of the X-ray films processed according to their manufacturer's recommendations. (U.K.)
Chichirov, A. A.; Chichirova, N. D.; Vlasov, S. M.; Lyapin, A. I.; Misbakhov, R. Sh.; Silov, I. Yu.; Murtazin, A. I.
2016-10-01
On Russian HPPs, conjugated closed-circuit cooling systems, where purge water is used as initial for water-treatment facilities, are widespread. For this reason, it is impossible to use general methods for the stabilization treatment of recycling water in order to prevent scale formation in the units of a system, namely, turbine condensers and cooling towers. In this paper, the methods for the decrease in the instability of recycling water using the methods of chemical engineering, such as stabilization and synchronization of flows and organization of recycles, are suggested. The results of an industrial experiment on the implementation of stabilization treatment of recycling water by the organization of recycle are given. The experiment was carried out on Kazan CHPP-3. The flow scheme involved the recycle of chemically purified water (CPW) for the heat network make-up to the closed-circuit cooling system. The experiment was carried out at three stages with the gradual change of the consumption of the recycle, namely, 0, 50, and 100 t/h. According to the results of experiments, the reliable decrease in the rate of the sedimentation was recorded on the units of the system, namely, turbine condenser and chimney-type cooling tower. This is caused by two reasons. Firstly, this is periodic excessive concentration of recycling water due to the nonstationary character of inlet and outlet flows. Secondly, this is seasonal (particularly, in the summer period) exceeding of the evaporation coefficient. As a result of stabilization and synchronization of flows and organization of recycles, the quality of clarified and chemically purified water for the heat network make-up increases and the corrosion of iron- and copper-containing structural materials decreases. A natural decrease in temperature drop on the operating turbine condensers is mentioned.
Mazaheri, Alireza; Ricchiuto, Mario; Nishikawa, Hiroaki
2016-01-01
In this paper, we introduce a new hyperbolic first-order system for general dispersive partial differential equations (PDEs). We then extend the proposed system to general advection-diffusion-dispersion PDEs. We apply the fourth-order RD scheme of Ref. 1 to the proposed hyperbolic system, and solve time-dependent dispersive equations, including the classical two-soliton KdV and a dispersive shock case. We demonstrate that the predicted results, including the gradient and Hessian (second derivative), are in a very good agreement with the exact solutions. We then show that the RD scheme applied to the proposed system accurately captures dispersive shocks without numerical oscillations. We also verify that the solution, gradient and Hessian are predicted with equal order of accuracy.
The Adjoint Method for Gradient-based Dynamic Optimization of UV Flash Processes
DEFF Research Database (Denmark)
Ritschel, Tobias Kasper Skovborg; Capolei, Andrea; Jørgensen, John Bagterp
2017-01-01
This paper presents a novel single-shooting algorithm for gradient-based solution of optimal control problems with vapor-liquid equilibrium constraints. Dynamic optimization of UV flash processes is relevant in nonlinear model predictive control of distillation columns, certain two-phase flow pro......-component flash process which demonstrate the importance of the optimization solver, the compiler, and the linear algebra software for the efficiency of dynamic optimization of UV flash processes....
Directory of Open Access Journals (Sweden)
Kolgotin Alexei
2016-01-01
Full Text Available Correlation relationships between aerosol microphysical parameters and optical data are investigated. The results show that surface-area concentrations and extinction coefficients are linearly correlated with a correlation coefficient above 0.99 for arbitrary particle size distribution. The correlation relationships that we obtained can be used as constraints in our inversion of optical lidar data. Simulation studies demonstrate a significant stabilization of aerosol microphysical data products if we apply the gradient correlation method in our traditional regularization technique.
The optimized gradient method for full waveform inversion and its spectral implementation
Wu, Zedong; Alkhalifah, Tariq Ali
2016-01-01
At the heart of the full waveform inversion (FWI) implementation is wavefield extrapolation, and specifically its accuracy and cost. To obtain accurate, dispersion free wavefields, the extrapolation for modelling is often expensive. Combining an efficient extrapolation with a novel gradient preconditioning can render an FWI implementation that efficiently converges to an accurate model. We, specifically, recast the extrapolation part of the inversion in terms of its spectral components for both data and gradient calculation. This admits dispersion free wavefields even at large extrapolation time steps, which improves the efficiency of the inversion. An alternative spectral representation of the depth axis in terms of sine functions allows us to impose a free surface boundary condition, which reflects our medium boundaries more accurately. Using a newly derived perfectly matched layer formulation for this spectral implementation, we can define a finite model with absorbing boundaries. In order to reduce the nonlinearity in FWI, we propose a multiscale conditioning of the objective function through combining the different directional components of the gradient to optimally update the velocity. Through solving a simple optimization problem, it specifically admits the smoothest approximate update while guaranteeing its ascending direction. An application to the Marmousi model demonstrates the capability of the proposed approach and justifies our assertions with respect to cost and convergence.
The optimized gradient method for full waveform inversion and its spectral implementation
Wu, Zedong
2016-03-28
At the heart of the full waveform inversion (FWI) implementation is wavefield extrapolation, and specifically its accuracy and cost. To obtain accurate, dispersion free wavefields, the extrapolation for modelling is often expensive. Combining an efficient extrapolation with a novel gradient preconditioning can render an FWI implementation that efficiently converges to an accurate model. We, specifically, recast the extrapolation part of the inversion in terms of its spectral components for both data and gradient calculation. This admits dispersion free wavefields even at large extrapolation time steps, which improves the efficiency of the inversion. An alternative spectral representation of the depth axis in terms of sine functions allows us to impose a free surface boundary condition, which reflects our medium boundaries more accurately. Using a newly derived perfectly matched layer formulation for this spectral implementation, we can define a finite model with absorbing boundaries. In order to reduce the nonlinearity in FWI, we propose a multiscale conditioning of the objective function through combining the different directional components of the gradient to optimally update the velocity. Through solving a simple optimization problem, it specifically admits the smoothest approximate update while guaranteeing its ascending direction. An application to the Marmousi model demonstrates the capability of the proposed approach and justifies our assertions with respect to cost and convergence.
An improved method of 18F peptide labeling: hydrazone formation with HYNIC-conjugated c(RGDyK)
International Nuclear Information System (INIS)
Lee, Yun-Sang; Jeong, Jae Min; Kim, Hyung Woo; Chang, Young Soo; Kim, Young Joo; Hong, Mee Kyung; Rai, Ganesha B.; Chi, Dae Yoon; Kang, Won Jun; Kang, Joo Hyun; Lee, Dong Soo; Chung, June-Key; Lee, Myung Chul; Suh, Young-Ger
2006-01-01
Radiolabeled α v β 3 -integrin antagonists are increasingly investigated as a means of imaging angiogenesis. Several methods of labeling α v β 3 -integrin binding peptide with 18 F have been reported recently. In the present study, we devised a straightforward means for labeling Arg-Gly-Asp (RGD) peptide with 18 F via hydrazone formation between c(RGDyK)-hydrazinonicotinic acid (HYNIC) (3) and 4-[ 18 F]-fluorobenzaldehyde ([ 18 F]4). The resulting reaction mixture was purified by HPLC to give 4'-[ 18 F]-fluorobenzylidenehydrazone-6-nicotinamide-c(RGDyK) ([ 18 F]5). The conjugation efficiency of 3 and 4 to form [ 18 F]5 was 95.2%, and the radiochemical purity of [ 18 F]5 after purification was >99%. The specific activity of [ 18 F]5 estimated by radio-HPLC was 20.5 GBq/μmol (end of synthesis). Competitive binding assay of c(RGDyK) (1) and 5 was performed using [ 125 I]iodo-c(RGDyK) as a radioligand, and K i values were found to be 2.8 and 21.7 nM, respectively. For the biodistribution study, the angiogenic mouse model was established by inducing unilateral ischemia on the left hindlimbs of ICR mice after femoral artery ablation. Seven days after inducing ischemia, [ 18 F]5 was administered to the mice through the tail vein. Ischemic muscle uptake of [ 18 F]5 was significantly higher than that of normal muscle (P 18 F]5. Here, we successfully labeled RGD peptide with 18 F via hydrazone formation between 3 and 4, resulting to [ 18 F]5. [ 18 F]5 was found to have high affinity for α v β 3 -integrin and to accumulate specifically in ischemic hindlimb muscle of mice. We suggest that 18 F labeling via formation of hydrazone between HYNIC peptide and [ 18 F]4 is a useful method for labeling c(RGDyK), which can be applied for imaging angiogenesis
Burt, Adam O.; Tinker, Michael L.
2014-01-01
In this paper, genetic algorithm based and gradient-based topology optimization is presented in application to a real hardware design problem. Preliminary design of a planetary lander mockup structure is accomplished using these methods that prove to provide major weight savings by addressing the structural efficiency during the design cycle. This paper presents two alternative formulations of the topology optimization problem. The first is the widely-used gradient-based implementation using commercially available algorithms. The second is formulated using genetic algorithms and internally developed capabilities. These two approaches are applied to a practical design problem for hardware that has been built, tested and proven to be functional. Both formulations converged on similar solutions and therefore were proven to be equally valid implementations of the process. This paper discusses both of these formulations at a high level.
Dimova, E.; Steflekova, V.; Karatodorov, S.; Kyoseva, E.
2018-03-01
We propose a way of achieving efficient and robust second-harmonic generation. The technique proposed is similar to the adiabatic population transfer in a two-state quantum system with crossing energies. If the phase mismatching changes slowly, e.g., due to a temperature gradient along the crystal, and makes the phase match for second-harmonic generation to occur, then the energy would be converted adiabatically to the second harmonic. As an adiabatic technique, the second-harmonic generation scheme presented is stable to variations in the crystal parameters, as well as in the input light, crystal length, input intensity, wavelength and angle of incidence.
Elgawish, Mohamed Saleh; Shimomai, Chikako; Kishikawa, Naoya; Ohyama, Kaname; Wada, Mitsuhiro; Kuroda, Naotaka
2013-09-16
Menadione (2-methyl-1,4-naphthoquinone, MQ), a component of multivitamin drugs with antihemorrhagic, antineoplastic, and antimalarial activity, is frequently used to investigate quinone-induced cytotoxicity. The formation of MQ conjugates with glutathione (GSH) by Michael addition and subsequent biotransformation to yield N-acetyl-l-cysteine conjugates is believed to be an important detoxification process. However, the resulting conjugates, 2-methyl-3-(glutathione-S-yl)-1,4-naphthoquinone (MQ-GS) and 2-methyl-3-(N-acetyl-l-cysteine-S-yl)-1,4-naphthoquinone (MQ-NAC), retain the ability to redox cycle and to arylate cellular nucleophiles. Although the nephrotoxicity and hepatotoxicity of MQ-thiol conjugates have been reported in vitro, methods for their determination in vivo have yet to be published. Herein, a highly sensitive, simple, and selective HPLC-chemiluminescence (HPLC-CL) coupled method is reported, allowing for the first time the simultaneous determination of MQ, MQ-GS, and MQ-NAC in rat plasma after MQ administration. Our method exploits the unique redox characteristics of MQ, MQ-GS, and MQ-NAC to react with dithiothreitol (DTT) to liberate reactive oxygen species (ROS) which are detected by a CL assay using luminol as a CL probe. To verify the proposed mechanism, MQ-GS and MQ-NAC were synthetically prepared. Specimen preparation involved solid-phase extraction on an Oasis HLB cartridge followed by isocratic elution on an ODS column. No interference from endogenous substances was detected. Linearity was observed in the range of 5-120 nM for MQ-GS and MQ-NAC and 10-240 nM for MQ, with detection limits (S/N of 3) of 1.4, 0.8, and 128 fmol for MQ-GS, MQ-NAC, and MQ, respectively. The application of our method reported here is the first to extensively study the stability and reversibility of thiol-quinones.
Zhang, Dong; Zhang, Ting-Ting; Zhang, Xiao-Lei; Yang, Yan; Hu, Ying; Qin, Qian-Qing
2013-05-01
We present a new method of three-dimensional (3-D) seismic ray tracing, based on an improvement to the linear traveltime interpolation (LTI) ray tracing algorithm. This new technique involves two separate steps. The first involves a forward calculation based on the LTI method and the dynamic successive partitioning scheme, which is applied to calculate traveltimes on cell boundaries and assumes a wavefront that expands from the source to all grid nodes in the computational domain. We locate several dynamic successive partition points on a cell's surface, the traveltimes of which can be calculated by linear interpolation between the vertices of the cell's boundary. The second is a backward step that uses Fermat's principle and the fact that the ray path is always perpendicular to the wavefront and follows the negative traveltime gradient. In this process, the first-arriving ray path can be traced from the receiver to the source along the negative traveltime gradient, which can be calculated by reconstructing the continuous traveltime field with cubic B-spline interpolation. This new 3-D ray tracing method is compared with the LTI method and the shortest path method (SPM) through a number of numerical experiments. These comparisons show obvious improvements to computed traveltimes and ray paths, both in precision and computational efficiency.
Rabizah Makhsin, Siti; Razak, Khairunisak Abdul; Noordin, Rahmah; Dyana Zakaria, Nor; Chun, Tan Soo
2012-12-01
This study describes the properties of colloidal gold nanoparticles (AuNPs) with sizes of 20, 30 and 40 nm, which were synthesized using citrate reduction or seeding-growth methods. Likewise, the conjugation of these AuNPs to mouse anti-human IgG4 (MαHIgG4) was evaluated for an immunochromatographic (ICG) strip test to detect brugian filariasis. The morphology of the AuNPs was studied based on the degree of ellipticity (G) of the transmission electron microscopy images. The AuNPs produced using the seeding-growth method showed lower ellipticity (G ≤ 1.11) as compared with the AuNPs synthesized using the citrate reduction method (G ≤ 1.18). Zetasizer analysis showed that the AuNPs that were synthesized using the seeding-growth method were almost monodispersed with a lower polydispersity index (PDI; PDI≤0.079), as compared with the AuNPs synthesized using the citrate reduction method (PDI≤0.177). UV-visible spectroscopic analysis showed a red-shift of the absorbance spectra after the reaction with MαHIgG4, which indicated that the AuNPs were successfully conjugated. The optimum concentration of the BmR1 recombinant antigen that was immobilized on the surface of the ICG strip on the test line was 1.0 mg ml-1. When used with the ICG test strip assay and brugian filariasis serum samples, the conjugated AuNPs-MαHIgG4 synthesized using the seeding-growth method had faster detection times, as compared with the AuNPs synthesized using the citrate reduction method. The 30 nm AuNPs-MαHIgG4, with an optical density of 4 from the seeding-growth method, demonstrated the best performance for labelling ICG strips because it displayed the best sensitivity and the highest specificity when tested with serum samples from brugian filariasis patients and controls.
Dondurur, Derman
2005-11-01
The Normalized Full Gradient (NFG) method was proposed in the mid 1960s and was generally used for the downward continuation of the potential field data. The method eliminates the side oscillations which appeared on the continuation curves when passing through anomalous body depth. In this study, the NFG method was applied to Slingram electromagnetic anomalies to obtain the depth of the anomalous body. Some experiments were performed on the theoretical Slingram model anomalies in a free space environment using a perfectly conductive thin tabular conductor with an infinite depth extent. The theoretical Slingram responses were obtained for different depths, dip angles and coil separations, and it was observed from NFG fields of the theoretical anomalies that the NFG sections yield the depth information of top of the conductor at low harmonic numbers. The NFG sections consisted of two main local maxima located at both sides of the central negative Slingram anomalies. It is concluded that these two maxima also locate the maximum anomaly gradient points, which indicates the depth of the anomaly target directly. For both theoretical and field data, the depth of the maximum value on the NFG sections corresponds to the depth of the upper edge of the anomalous conductor. The NFG method was applied to the in-phase component and correct depth estimates were obtained even for the horizontal tabular conductor. Depth values could be estimated with a relatively small error percentage when the conductive model was near-vertical and/or the conductor depth was larger.
International Nuclear Information System (INIS)
Ward, G.J.; Heckbert, P.S.; Technische Hogeschool Delft
1992-04-01
A new method for improving the accuracy of a diffuse interreflection calculation is introduced in a ray tracing context. The information from a hemispherical sampling of the luminous environment is interpreted in a new way to predict the change in irradiance as a function of position and surface orientation. The additional computation involved is modest and the benefit is substantial. An improved interpolation of irradiance resulting from the gradient calculation produces smoother, more accurate renderings. This result is achieved through better utilization of ray samples rather than additional samples or alternate sampling strategies. Thus, the technique is applicable to a variety of global illumination algorithms that use hemicubes or Monte Carlo sampling techniques
DEFF Research Database (Denmark)
Tatu, Aditya Jayant
This thesis deals with two unrelated issues, restricting curve evolution to subspaces and computing image patches in the equivalence class of Histogram of Gradient orientation based features using nonlinear projection methods. Curve evolution is a well known method used in various applications like...... tracking interfaces, active contour based segmentation methods and others. It can also be used to study shape spaces, as deforming a shape can be thought of as evolving its boundary curve. During curve evolution a curve traces out a path in the infinite dimensional space of curves. Due to application...... specific requirements like shape priors or a given data model, and due to limitations of the computer, the computed curve evolution forms a path in some finite dimensional subspace of the space of curves. We give methods to restrict the curve evolution to a finite dimensional linear or implicitly defined...
Faster PET reconstruction with a stochastic primal-dual hybrid gradient method
Ehrhardt, Matthias J.
2017-08-24
Image reconstruction in positron emission tomography (PET) is computationally challenging due to Poisson noise, constraints and potentially non-smooth priors-let alone the sheer size of the problem. An algorithm that can cope well with the first three of the aforementioned challenges is the primal-dual hybrid gradient algorithm (PDHG) studied by Chambolle and Pock in 2011. However, PDHG updates all variables in parallel and is therefore computationally demanding on the large problem sizes encountered with modern PET scanners where the number of dual variables easily exceeds 100 million. In this work, we numerically study the usage of SPDHG-a stochastic extension of PDHG-but is still guaranteed to converge to a solution of the deterministic optimization problem with similar rates as PDHG. Numerical results on a clinical data set show that by introducing randomization into PDHG, similar results as the deterministic algorithm can be achieved using only around 10 % of operator evaluations. Thus, making significant progress towards the feasibility of sophisticated mathematical models in a clinical setting.
Faster PET reconstruction with a stochastic primal-dual hybrid gradient method
Ehrhardt, Matthias J.; Markiewicz, Pawel; Chambolle, Antonin; Richtárik, Peter; Schott, Jonathan; Schönlieb, Carola-Bibiane
2017-08-01
Image reconstruction in positron emission tomography (PET) is computationally challenging due to Poisson noise, constraints and potentially non-smooth priors-let alone the sheer size of the problem. An algorithm that can cope well with the first three of the aforementioned challenges is the primal-dual hybrid gradient algorithm (PDHG) studied by Chambolle and Pock in 2011. However, PDHG updates all variables in parallel and is therefore computationally demanding on the large problem sizes encountered with modern PET scanners where the number of dual variables easily exceeds 100 million. In this work, we numerically study the usage of SPDHG-a stochastic extension of PDHG-but is still guaranteed to converge to a solution of the deterministic optimization problem with similar rates as PDHG. Numerical results on a clinical data set show that by introducing randomization into PDHG, similar results as the deterministic algorithm can be achieved using only around 10 % of operator evaluations. Thus, making significant progress towards the feasibility of sophisticated mathematical models in a clinical setting.
International Nuclear Information System (INIS)
Werner-Wasik, Maria; Nelson, Arden D.; Choi, Walter; Arai, Yoshio; Faulhaber, Peter F.; Kang, Patrick; Almeida, Fabio D.; Xiao, Ying; Ohri, Nitin; Brockway, Kristin D.; Piper, Jonathan W.; Nelson, Aaron S.
2012-01-01
Purpose: To evaluate the accuracy and consistency of a gradient-based positron emission tomography (PET) segmentation method, GRADIENT, compared with manual (MANUAL) and constant threshold (THRESHOLD) methods. Methods and Materials: Contouring accuracy was evaluated with sphere phantoms and clinically realistic Monte Carlo PET phantoms of the thorax. The sphere phantoms were 10–37 mm in diameter and were acquired at five institutions emulating clinical conditions. One institution also acquired a sphere phantom with multiple source-to-background ratios of 2:1, 5:1, 10:1, 20:1, and 70:1. One observer segmented (contoured) each sphere with GRADIENT and THRESHOLD from 25% to 50% at 5% increments. Subsequently, seven physicians segmented 31 lesions (7–264 mL) from 25 digital thorax phantoms using GRADIENT, THRESHOLD, and MANUAL. Results: For spheres 20 mm (p < 0.065) and <20 mm (p < 0.015). For digital thorax phantoms, GRADIENT was the most accurate (p < 0.01), with a mean absolute % error in volume of 10.99% (11.9% SD), followed by 25% THRESHOLD at 17.5% (29.4% SD), and MANUAL at 19.5% (17.2% SD). GRADIENT had the least systematic bias, with a mean % error in volume of –0.05% (16.2% SD) compared with 25% THRESHOLD at –2.1% (34.2% SD) and MANUAL at –16.3% (20.2% SD; p value <0.01). Interobserver variability was reduced using GRADIENT compared with both 25% THRESHOLD and MANUAL (p value <0.01, Levene’s test). Conclusion: GRADIENT was the most accurate and consistent technique for target volume contouring. GRADIENT was also the most robust for varying imaging conditions. GRADIENT has the potential to play an important role for tumor delineation in radiation therapy planning and response assessment.
International Nuclear Information System (INIS)
Fouillet, C.
2003-01-01
In this work, we simulate a nucleate boiling problem using direct numerical simulation. The numerical method used is the second gradient method based on a diffuse interface model which represents interfaces as volumetric regions of finite thickness across which the physical properties of the fluid vary continuously. First, this method is successfully applied to nucleate boiling of a pure fluid. Then, the model is extended to dilute binary mixtures. After studying its validity and its limits in simple configurations, it is then applied to nucleate boiling of a dilute mixture. These simulations show a strong decrease of the heat transfer coefficient as the concentration increases, in agreement with the numerous experimental studies published in this domain. (author) [fr
Cimpoiu, Claudia; Hosu, Anamaria; Puscas, Anitta
2012-02-03
The group of hydrophilic vitamins play an important role in human health, and their lack or excess produces specific diseases. Therefore, the analysis of these compounds is indispensable for monitoring their content in pharmaceuticals and food in order to prevent some human diseases. TLC was successfully applied in the analysis of hydrophilic vitamins, but the most difficult problem in the simultaneous analysis of all these compounds is to find an optimum stationary phase-mobile phase system due to different chemical characteristics of analytes. Unfortunately structural analogues are difficult to separate in one chromatographic run, and this is the case in hydrophilic vitamins investigations. TLC gives the possibility to perform two-dimensional separations by using stationary phase gradient achieving the highest resolution by combining two systems with different selectivity. The goal of this work was to develop a method of analysis enabling separation of hydrophilic vitamins using TLC with adsorbent gradient. The developed method was used for identifying the water-soluble vitamins in alcoholic extracts of Hippophae rhamnoides and of Ribes nigrum. Copyright © 2011 Elsevier B.V. All rights reserved.
Directory of Open Access Journals (Sweden)
Benn eMacdonald
2015-11-01
Full Text Available Parameter inference in mathematical models of biological pathways, expressed as coupled ordinary differential equations (ODEs, is a challenging problem in contemporary systems biology. Conventional methods involve repeatedly solving the ODEs by numerical integration, which is computationally onerous and does not scale up to complex systems. Aimed at reducing the computational costs, new concepts based on gradient matching have recently been proposed in the computational statistics and machine learning literature. In a preliminary smoothing step, the time series data are interpolated; then, in a second step, the parameters of the ODEs are optimised so as to minimise some metric measuring the difference between the slopes of the tangents to the interpolants, and the time derivatives from the ODEs. In this way, the ODEs never have to be solved explicitly. This review provides a concise methodological overview of the current state-of-the-art methods for gradient matching in ODEs, followed by an empirical comparative evaluation based on a set of widely used and representative benchmark data.
International Nuclear Information System (INIS)
Takahashi, Norio; Hiyama, Keiko; Kodaira, Mieko; Satoh, Chiyoko.
1990-05-01
We have examined the feasibility of denaturing gradient gel electrophoresis (DGGE) of RNA:DNA duplexes to detect variations in genomic and cloned DNAs. The result has demonstrated that use of RNA:DNA duplexes makes DGGE much more practical for screening a large number of samples than use of DNA:DNA heteroduplexes, because preparation of RNA probes is easier than that of DNA probes. Three different 32 P-labeled RNA probes were produced. Genomic or cloned DNAs were digested with restriction enzymes and hybridized to labeled RNA probes, and resulting RNA:DNA duplexes were examined by DGGE. The presence of a mismatch(es) was detected as a difference in the mobility of bands on the gel. The experimental conditions were determined using DNA segments from cloned normal and three thalassemic human β-globin genes. The results from experiments on the cloned DNAs suggest that DGGE of RNA:DNA duplexes will detect nucleotide substitutions and deletions in DNA. In the course of these studies, a polymorphism due to a single-base substitution at position 666 of IVS2 (IVS2-666) of the human β-globin gene was directly identified using genomic DNA samples. A study of 59 unrelated Japanese from Hiroshima was undertaken in which the frequency of the allele with C at IVS2-666 was 0.48 and that of the allele with T was 0.52. This approach was found to be very effective for detecting heritable variation and should be a powerful tool for detecting fresh mutations in DNA, which occur outside the known restriction sites. (author)
Double diffusive conjugate heat transfer: Part I
Azeem, Soudagar, Manzoor Elahi M.
2018-05-01
The present work is undertaken to investigate the effect of solid wall being placed at left of square cavity filled with porous medium. The presence of a solid wall in the porous medium turns the situation into a conjugate heat transfer problem. The boundary conditions are such that the left vertical surface is maintained at highest temperature and concentration whereas right vertical surface at lowest temperature and concentration in the medium. The top and bottom surfaces are adiabatic. The additional conduction equation along with the regular momentum and energy equations of porous medium are solved in an iterative manner with the help of finite element method. It is seen that the heat and mass transfer rate is lesser due to smaller thermal and concentration gradients.
Ono, Shunsuke
2017-04-01
Minimizing L 0 gradient, the number of the non-zero gradients of an image, together with a quadratic data-fidelity to an input image has been recognized as a powerful edge-preserving filtering method. However, the L 0 gradient minimization has an inherent difficulty: a user-given parameter controlling the degree of flatness does not have a physical meaning since the parameter just balances the relative importance of the L 0 gradient term to the quadratic data-fidelity term. As a result, the setting of the parameter is a troublesome work in the L 0 gradient minimization. To circumvent the difficulty, we propose a new edge-preserving filtering method with a novel use of the L 0 gradient. Our method is formulated as the minimization of the quadratic data-fidelity subject to the hard constraint that the L 0 gradient is less than a user-given parameter α . This strategy is much more intuitive than the L 0 gradient minimization because the parameter α has a clear meaning: the L 0 gradient value of the output image itself, so that one can directly impose a desired degree of flatness by α . We also provide an efficient algorithm based on the so-called alternating direction method of multipliers for computing an approximate solution of the nonconvex problem, where we decompose it into two subproblems and derive closed-form solutions to them. The advantages of our method are demonstrated through extensive experiments.
A project to study SOC evolution after land use change combining chronosequence and gradient methods
Gabarron-Galeote, Miguel A.; van Wesemael, Bas
2013-04-01
In the last decades the interest in the global C budget has increased enormously and soils have a great importance in this issue since they contain about twice as much carbon as the atmosphere. Land use change (LUC) can cause a change in land cover and an associated change in carbon stocks in soils, so it has a major impact in the balance between inputs and outputs of soil organic carbon (SOC). Improved understanding of land-use impacts on the world's terrestrial carbon balance is thus a necessary part of the global effort to mitigate climate change. The aim of this project is to predict the effects of land use and land management change on (SOC) stocks, characterizing the soil organic carbon cycle and its relationship to the vegetal cover in croplands abandoned different years ago and under different Mediterranean climatic conditions in South of Spain. The study area is located in the Cordillera Bética Litoral, in South of Spain. In this area, a climatic gradient can be observed from West to East: from >1,500 mm year-1 in the Strait of Gibraltar to <250 mm year-1 in the Cabo de Gata. More specifically, the study is focussed on three different areas from the climatic conditions point of view: Gaucín (1010 mm year-1), Almogía, (576 mm year-1) and Gérgal (240 mm year-1). By means of the analyses of aerial photographs (1956, 1977, 1984, 1998 and 2009) all the experimental plots will be selected. After this procedure, the three study areas will be composed by experimental plots of these classes: a) Lands with natural vegetation since 1956. b) Abandoned lands between 1956 and 1977. c) Abandoned lands between 1977 and 1984. d) Abandoned lands between 1984 and 1998. e) Abandoned lands between 1998 and 2005. f) Cultivated lands since 1956. The main expected outcomes of the research project are the characterization of the temporal evolution of SOC in soils, the compilation of experimental areas under different Mediterranean climatic conditions, and the characterization
Energy Technology Data Exchange (ETDEWEB)
Dall-Anese, Emiliano [National Renewable Energy Laboratory (NREL), Golden, CO (United States); Bernstein, Andrey [National Renewable Energy Laboratory (NREL), Golden, CO (United States); Simonetto, Andrea [IBM Research Center Ireland
2017-11-27
This paper develops an online optimization method to maximize the operational objectives of distribution-level distributed energy resources (DERs) while adjusting the aggregate power generated (or consumed) in response to services requested by grid operators. The design of the online algorithm is based on a projected-gradient method, suitably modified to accommodate appropriate measurements from the distribution network and the DERs. By virtue of this approach, the resultant algorithm can cope with inaccuracies in the representation of the AC power, it avoids pervasive metering to gather the state of noncontrollable resources, and it naturally lends itself to a distributed implementation. Optimality claims are established in terms of tracking of the solution of a well-posed time-varying optimization problem.
Projection methods for line radiative transfer in spherical media.
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).
Dobramysl, U; Holcman, D
2018-02-15
Is it possible to recover the position of a source from the steady-state fluxes of Brownian particles to small absorbing windows located on the boundary of a domain? To address this question, we develop a numerical procedure to avoid tracking Brownian trajectories in the entire infinite space. Instead, we generate particles near the absorbing windows, computed from the analytical expression of the exit probability. When the Brownian particles are generated by a steady-state gradient at a single point, we compute asymptotically the fluxes to small absorbing holes distributed on the boundary of half-space and on a disk in two dimensions, which agree with stochastic simulations. We also derive an expression for the splitting probability between small windows using the matched asymptotic method. Finally, when there are more than two small absorbing windows, we show how to reconstruct the position of the source from the diffusion fluxes. The present approach provides a computational first principle for the mechanism of sensing a gradient of diffusing particles, a ubiquitous problem in cell biology.
Gradient method for blind chaotic signal separation based on proliferation exponent
International Nuclear Information System (INIS)
Lü Shan-Xiang; Wang Zhao-Shan; Hu Zhi-Hui; Feng Jiu-Chao
2014-01-01
A new method to perform blind separation of chaotic signals is articulated in this paper, which takes advantage of the underlying features in the phase space for identifying various chaotic sources. Without incorporating any prior information about the source equations, the proposed algorithm can not only separate the mixed signals in just a few iterations, but also outperforms the fast independent component analysis (FastICA) method when noise contamination is considerable. (general)
Energy Technology Data Exchange (ETDEWEB)
Werner-Wasik, Maria, E-mail: Maria.Werner-wasik@jeffersonhospital.org [Department of Radiation Oncology, Thomas Jefferson University Hospital, Philadelphia, PA (United States); Nelson, Arden D. [MIM Software Inc., Cleveland, OH (United States); Choi, Walter [Department of Radiation Oncology, UPMC Health Systems, Pittsburgh, PA (United States); Arai, Yoshio [Department of Radiation Oncology, Beth Israel Medical Center, New York, NY (Israel); Faulhaber, Peter F. [University Hospitals Case Medical Center, Cleveland, OH (United States); Kang, Patrick [Department of Radiology, Beth Israel Medical Center, New York, NY (Israel); Almeida, Fabio D. [Division of Nuclear Medicine, University of Arizona Health Sciences Center, Tucson, AZ (United States); Xiao, Ying; Ohri, Nitin [Department of Radiation Oncology, Thomas Jefferson University Hospital, Philadelphia, PA (United States); Brockway, Kristin D.; Piper, Jonathan W.; Nelson, Aaron S. [MIM Software Inc., Cleveland, OH (United States)
2012-03-01
Purpose: To evaluate the accuracy and consistency of a gradient-based positron emission tomography (PET) segmentation method, GRADIENT, compared with manual (MANUAL) and constant threshold (THRESHOLD) methods. Methods and Materials: Contouring accuracy was evaluated with sphere phantoms and clinically realistic Monte Carlo PET phantoms of the thorax. The sphere phantoms were 10-37 mm in diameter and were acquired at five institutions emulating clinical conditions. One institution also acquired a sphere phantom with multiple source-to-background ratios of 2:1, 5:1, 10:1, 20:1, and 70:1. One observer segmented (contoured) each sphere with GRADIENT and THRESHOLD from 25% to 50% at 5% increments. Subsequently, seven physicians segmented 31 lesions (7-264 mL) from 25 digital thorax phantoms using GRADIENT, THRESHOLD, and MANUAL. Results: For spheres <20 mm in diameter, GRADIENT was the most accurate with a mean absolute % error in diameter of 8.15% (10.2% SD) compared with 49.2% (51.1% SD) for 45% THRESHOLD (p < 0.005). For larger spheres, the methods were statistically equivalent. For varying source-to-background ratios, GRADIENT was the most accurate for spheres >20 mm (p < 0.065) and <20 mm (p < 0.015). For digital thorax phantoms, GRADIENT was the most accurate (p < 0.01), with a mean absolute % error in volume of 10.99% (11.9% SD), followed by 25% THRESHOLD at 17.5% (29.4% SD), and MANUAL at 19.5% (17.2% SD). GRADIENT had the least systematic bias, with a mean % error in volume of -0.05% (16.2% SD) compared with 25% THRESHOLD at -2.1% (34.2% SD) and MANUAL at -16.3% (20.2% SD; p value <0.01). Interobserver variability was reduced using GRADIENT compared with both 25% THRESHOLD and MANUAL (p value <0.01, Levene's test). Conclusion: GRADIENT was the most accurate and consistent technique for target volume contouring. GRADIENT was also the most robust for varying imaging conditions. GRADIENT has the potential to play an important role for tumor delineation in
Comparison of methods for measuring flux gradients in type II superconductors
International Nuclear Information System (INIS)
Kroeger, D.M.; Koch, C.C.; Charlesworth, J.P.
1975-01-01
A comparison has been made of four methods of measuring the critical current density J/sub c/ in hysteretic type II superconductors, having a wide range of K and J/sub c/ values, in magnetic fields up to 70 kOe. Two of the methods, (a) resistive measurements and (b) magnetization measurements, were carried out in static magnetic fields. The other two methods involved analysis of the response of the sample to a small alternating field superimposed on the static field. The response was analyzed either (c) by measuring the third-harmonic content or (d) by integration of the waveform to obtain measure of flux penetration. The results are discussed with reference to the agreement between the different techniques and the consistency of the critical state hypothesis on which all these techniques are based. It is concluded that flux-penetration measurements by method (d) provide the most detailed information about J/sub c/ but that one must be wary of minor failures of the critical state hypothesis. Best results are likely to be obtained by using more than one method. (U.S.)
Steganalysis Method for LSB Replacement Based on Local Gradient of Image Histogram
Directory of Open Access Journals (Sweden)
M. Mahdavi
2008-10-01
Full Text Available In this paper we present a new accurate steganalysis method for the LSBreplacement steganography. The suggested method is based on the changes that occur in thehistogram of an image after the embedding of data. Every pair of neighboring bins of ahistogram are either inter-related or unrelated depending on whether embedding of a bit ofdata in the image could affect both bins or not. We show that the overall behavior of allinter-related bins, when compared with that of the unrelated ones, could give an accuratemeasure for the amount of the embedded data. Both analytical analysis and simulationresults show the accuracy of the proposed method. The suggested method has beenimplemented and tested for over 2000 samples and compared with the RS Steganalysismethod. Mean and variance of error were 0.0025 and 0.0037 for the suggested methodwhere these quantities were 0.0070 and 0.0182 for the RS Steganalysis. Using 4800samples, we showed that the performance of the suggested method is comparable withthose of the RS steganalysis for JPEG filtered images. The new approach is applicable forthe detection of both random and sequential LSB embedding.
Kendrick, B S; Kerwin, B A; Chang, B S; Philo, J S
2001-12-15
Characterizing the solution structure of protein-polymer conjugates and protein-ligand interactions is important in fields such as biotechnology and biochemistry. Size-exclusion high-performance liquid chromatography with online classical light scattering (LS), refractive index (RI), and UV detection offers a powerful tool in such characterization. Novel methods are presented utilizing LS, RI, and UV signals to rapidly determine the degree of conjugation and the molecular mass of the protein conjugate. Baseline resolution of the chromatographic peaks is not required; peaks need only be sufficiently separated to represent relatively pure fractions. An improved technique for determining the polypeptide-only mass of protein conjugates is also described. These techniques are applied to determining the degree of erythropoietin glycosylation, the degree of polyethylene glycol conjugation to RNase A and brain-derived neurotrophic factor, and the solution association states of these molecules. Calibration methods for the RI, UV, and LS detectors will also be addressed, as well as online methods to determine protein extinction coefficients and dn/dc values both unconjugated and conjugated protein molecules. (c)2001 Elsevier Science.
Reyes-Acosta, J Leonardo; Vandegehuchte, Maurits W; Steppe, Kathy; Lubczynski, Maciek W
2012-07-01
Sap flow measurements conducted with thermal dissipation probes (TDPs) are vulnerable to natural temperature gradient (NTG) bias. Few studies, however, attempted to explain the dynamics underlying the NTG formation and its influence on the sensors' signal. This study focused on understanding how the TDP signals are affected by negative and positive temperature influences from NTG and tested the novel cyclic heat dissipation (CHD) method to filter out the NTG bias. A series of three experiments were performed in which gravity-driven water flow was enforced on freshly cut stem segments of Fagus sylvatica L., while an artificial temperature gradient (ATG) was induced. The first experiment sought to confirm the incidence of the ATG on sensors. The second experiment established the mis-estimations caused by the biasing effect of the ATG on standard TDP measurements. The third experiment tested the accuracy of the CHD method to account for the ATG biasing effect, as compared with other cyclic correction methods. During experiments, sap flow measured by TDP was assessed against gravimetric measurements. The results show that negative and positive ATGs were comparable in pattern but substantially larger than field NTGs. Second, the ATG bias caused an overestimation of the standard TDP sap flux density of ∼17 cm(3) cm(-2) h(-1) by 76%, and the sap flux density of ∼2 cm(3) cm(-2) h(-1) by over 800%. Finally, the proposed CHD method successfully reduced the max. ATG bias to 25% at ∼11 cm(3) cm(-2) h(-1) and to 40% at ∼1 cm(3) cm(-2) h(-1). We concluded that: (i) the TDP method is susceptible to NTG especially at low flows; (ii) the CHD method successfully corrected the TDP signal and resulted in generally more accurate sap flux density estimates (mean absolute percentage error ranging between 11 and 21%) than standard constant power TDP method and other cyclic power methods; and (iii) the ATG enforcing system is a suitable way of re-creating NTG for future tests.
Optimization of Candu fuel management with gradient methods using generalized perturbation theory
International Nuclear Information System (INIS)
Chambon, R.; Varin, E.; Rozon, D.
2005-01-01
CANDU fuel management problems are solved using time-average representation of the core. Optimization problems based on this representation have been defined in the early nineties. The mathematical programming using the generalized perturbation theory (GPT) that was developed has been implemented in the reactor code DONJON. The use of the augmented Lagrangian (AL) method is presented and evaluated in this paper. This approach is mandatory for new constraint problems. Combined with the classical Lemke method, it proves to be very efficient to reach optimal solution in a very limited number of iterations. (authors)
GOCE in ocean modelling - Point mass method applied on GOCE gravity gradients
DEFF Research Database (Denmark)
Herceg, Matija; Knudsen, Per
This presentation is an introduction to my Ph.D project. The main objective of the study is to improve the methodology for combining GOCE gravity field models with satellite altimetry to derive optimal dynamic ocean topography models for oceanography. Here a method for geoid determination using...
A primal–dual hybrid gradient method for nonlinear operators with applications to MRI
Valkonen, Tuomo
2014-01-01
generalized variation priors. For such problems, we show that our general local convergence result holds when the noise level of the data f is low, and the regularization parameter α is correspondingly small. We verify the numerical performance of the method
Improvement of the variable storage coefficient method with water surface gradient as a variable
The variable storage coefficient (VSC) method has been used for streamflow routing in continuous hydrological simulation models such as the Agricultural Policy/Environmental eXtender (APEX) and the Soil and Water Assessment Tool (SWAT) for more than 30 years. APEX operates on a daily time step and ...
Akai, Takashi; Bijeljic, Branko; Blunt, Martin J.
2018-06-01
In the color gradient lattice Boltzmann model (CG-LBM), a fictitious-density wetting boundary condition has been widely used because of its ease of implementation. However, as we show, this may lead to inaccurate results in some cases. In this paper, a new scheme for the wetting boundary condition is proposed which can handle complicated 3D geometries. The validity of our method for static problems is demonstrated by comparing the simulated results to analytical solutions in 2D and 3D geometries with curved boundaries. Then, capillary rise simulations are performed to study dynamic problems where the three-phase contact line moves. The results are compared to experimental results in the literature (Heshmati and Piri, 2014). If a constant contact angle is assumed, the simulations agree with the analytical solution based on the Lucas-Washburn equation. However, to match the experiments, we need to implement a dynamic contact angle that varies with the flow rate.
Directory of Open Access Journals (Sweden)
Mahesh Jangid
2018-02-01
Full Text Available Handwritten character recognition is currently getting the attention of researchers because of possible applications in assisting technology for blind and visually impaired users, human–robot interaction, automatic data entry for business documents, etc. In this work, we propose a technique to recognize handwritten Devanagari characters using deep convolutional neural networks (DCNN which are one of the recent techniques adopted from the deep learning community. We experimented the ISIDCHAR database provided by (Information Sharing Index ISI, Kolkata and V2DMDCHAR database with six different architectures of DCNN to evaluate the performance and also investigate the use of six recently developed adaptive gradient methods. A layer-wise technique of DCNN has been employed that helped to achieve the highest recognition accuracy and also get a faster convergence rate. The results of layer-wise-trained DCNN are favorable in comparison with those achieved by a shallow technique of handcrafted features and standard DCNN.
CSIR Research Space (South Africa)
Wilke, DN
2012-07-01
Full Text Available problems that utilise remeshing (i.e. the mesh topology is allowed to change) between design updates. Here, changes in mesh topology result in abrupt changes in the discretization error of the computed response. These abrupt changes in turn manifests... in shape optimization but may be present whenever (partial) differential equations are ap- proximated numerically with non-constant discretization methods e.g. remeshing of spatial domains or automatic time stepping in temporal domains. Keywords: Complex...
Directory of Open Access Journals (Sweden)
Shweta Gupta
Full Text Available Efavirenz is an anti-viral agent of non-nucleoside reverse transcriptase inhibitor category used as a part of highly active retroviral therapy for the treatment of infections of human immune deficiency virus type-1. A simple, sensitive and rapid reversed-phase high performance liquid chromatographic gradient method was developed and validated for the determination of efavirenz in plasma. The method was developed with high performance liquid chromatography using Waters X-Terra Shield, RP18 50 x 4.6 mm, 3.5 μm column and a mobile phase consisting of phosphate buffer pH 3.5 and Acetonitrile. The elute was monitored with the UV-Visible detector at 260 nm with a flow rate of 1.5 mL/min. Tenofovir disoproxil fumarate was used as internal standard. The method was validated for linearity, precision, accuracy, specificity, robustness and data obtained were statistically analyzed. Calibration curve was found to be linear over the concentration range of 1-300 μg/mL. The retention times of efavirenz and tenofovir disoproxil fumarate (internal standard were 5.941 min and 4.356 min respectively. The regression coefficient value was found to be 0.999. The limit of detection and the limit of quantification obtained were 0.03 and 0.1 μg/mL respectively. The developed HPLC method can be useful for quantitative pharmacokinetic parameters determination of efavirenz in plasma.
Böhme, M.; Ilg, A.; Ossig, A.; Küchenhoff, H.
2006-06-01
Existing methods for determining paleoprecipitation are subject to large errors (±350 400 mm or more using mammalian proxies), or are restricted to wet climate systems due to their strong facies dependence (paleobotanical proxies). Here we describe a new paleoprecipitation tool based on an indexing of ecophysiological groups within herpetological communities. In recent communities these indices show a highly significant correlation to annual precipitation (r2 = 0.88), and yield paleoprecipitation estimates with average errors of ±250 280 mm. The approach was validated by comparison with published paleoprecipitation estimates from other methods. The method expands the application of paleoprecipitation tools to dry climate systems and in this way contributes to the establishment of a more comprehensive paleoprecipitation database. This method is applied to two high-resolution time intervals from the European Neogene: the early middle Miocene (early Langhian) and the early late Miocene (early Tortonian). The results indicate that both periods show significant meridional precipitation gradients in Europe, these being stronger in the early Langhian (threefold decrease toward the south) than in the early Tortonian (twofold decrease toward the south). This pattern indicates a strengthening of climatic belts during the middle Miocene climatic optimum due to Southern Hemisphere cooling and an increased contribution of Arctic low-pressure cells to the precipitation from the late Miocene onward due to Northern Hemisphere cooling.
Energy Technology Data Exchange (ETDEWEB)
Wei, Jun, E-mail: jvwei@umich.edu; Zhou, Chuan; Chan, Heang-Ping; Chughtai, Aamer; Agarwal, Prachi; Kuriakose, Jean; Hadjiiski, Lubomir; Patel, Smita; Kazerooni, Ella [Department of Radiology, University of Michigan, Ann Arbor, Michigan 48109 (United States)
2014-08-15
Purpose: The buildup of noncalcified plaques (NCPs) that are vulnerable to rupture in coronary arteries is a risk for myocardial infarction. Interpretation of coronary CT angiography (cCTA) to search for NCP is a challenging task for radiologists due to the low CT number of NCP, the large number of coronary arteries, and multiple phase CT acquisition. The authors conducted a preliminary study to develop machine learning method for automated detection of NCPs in cCTA. Methods: With IRB approval, a data set of 83 ECG-gated contrast enhanced cCTA scans with 120 NCPs was collected retrospectively from patient files. A multiscale coronary artery response and rolling balloon region growing (MSCAR-RBG) method was applied to each cCTA volume to extract the coronary arterial trees. Each extracted vessel was reformatted to a straightened volume composed of cCTA slices perpendicular to the vessel centerline. A topological soft-gradient (TSG) detection method was developed to prescreen for NCP candidates by analyzing the 2D topological features of the radial gradient field surface along the vessel wall. The NCP candidates were then characterized by a luminal analysis that used 3D geometric features to quantify the shape information and gray-level features to evaluate the density of the NCP candidates. With machine learning techniques, useful features were identified and combined into an NCP score to differentiate true NCPs from false positives (FPs). To evaluate the effectiveness of the image analysis methods, the authors performed tenfold cross-validation with the available data set. Receiver operating characteristic (ROC) analysis was used to assess the classification performance of individual features and the NCP score. The overall detection performance was estimated by free response ROC (FROC) analysis. Results: With our TSG prescreening method, a prescreening sensitivity of 92.5% (111/120) was achieved with a total of 1181 FPs (14.2 FPs/scan). On average, six features
International Nuclear Information System (INIS)
Wei, Jun; Zhou, Chuan; Chan, Heang-Ping; Chughtai, Aamer; Agarwal, Prachi; Kuriakose, Jean; Hadjiiski, Lubomir; Patel, Smita; Kazerooni, Ella
2014-01-01
Purpose: The buildup of noncalcified plaques (NCPs) that are vulnerable to rupture in coronary arteries is a risk for myocardial infarction. Interpretation of coronary CT angiography (cCTA) to search for NCP is a challenging task for radiologists due to the low CT number of NCP, the large number of coronary arteries, and multiple phase CT acquisition. The authors conducted a preliminary study to develop machine learning method for automated detection of NCPs in cCTA. Methods: With IRB approval, a data set of 83 ECG-gated contrast enhanced cCTA scans with 120 NCPs was collected retrospectively from patient files. A multiscale coronary artery response and rolling balloon region growing (MSCAR-RBG) method was applied to each cCTA volume to extract the coronary arterial trees. Each extracted vessel was reformatted to a straightened volume composed of cCTA slices perpendicular to the vessel centerline. A topological soft-gradient (TSG) detection method was developed to prescreen for NCP candidates by analyzing the 2D topological features of the radial gradient field surface along the vessel wall. The NCP candidates were then characterized by a luminal analysis that used 3D geometric features to quantify the shape information and gray-level features to evaluate the density of the NCP candidates. With machine learning techniques, useful features were identified and combined into an NCP score to differentiate true NCPs from false positives (FPs). To evaluate the effectiveness of the image analysis methods, the authors performed tenfold cross-validation with the available data set. Receiver operating characteristic (ROC) analysis was used to assess the classification performance of individual features and the NCP score. The overall detection performance was estimated by free response ROC (FROC) analysis. Results: With our TSG prescreening method, a prescreening sensitivity of 92.5% (111/120) was achieved with a total of 1181 FPs (14.2 FPs/scan). On average, six features
Comparison of gradient methods for gain tuning of a PD controller applied on a quadrotor system
Kim, Jinho; Wilkerson, Stephen A.; Gadsden, S. Andrew
2016-05-01
Many mechanical and electrical systems have utilized the proportional-integral-derivative (PID) control strategy. The concept of PID control is a classical approach but it is easy to implement and yields a very good tracking performance. Unmanned aerial vehicles (UAVs) are currently experiencing a significant growth in popularity. Due to the advantages of PID controllers, UAVs are implementing PID controllers for improved stability and performance. An important consideration for the system is the selection of PID gain values in order to achieve a safe flight and successful mission. There are a number of different algorithms that can be used for real-time tuning of gains. This paper presents two algorithms for gain tuning, and are based on the method of steepest descent and Newton's minimization of an objective function. This paper compares the results of applying these two gain tuning algorithms in conjunction with a PD controller on a quadrotor system.
Direct method of design and stress analysis of rotating disks with temperature gradient
Manson, S S
1950-01-01
A method is presented for the determination of the contour of disks, typified by those of aircraft gas turbines, to incorporate arbitrary elastic-stress distributions resulting from either centrifugal or combined centrifugal and thermal effects. The specified stress may be radial, tangential, or any combination of the two. Use is made of the finite-difference approach in solving the stress equations, the amount of computation necessary in the evolution of a design being greatly reduced by the judicious selection of point stations by the aid of a design chart. Use of the charts and of a preselected schedule of point stations is also applied to the direct problem of finding the elastic and plastic stress distribution in disks of a given design, thereby effecting a great reduction in the amount of calculation. Illustrative examples are presented to show computational procedures in the determination of a new design and in analyzing an existing design for elastic stress and for stresses resulting from plastic flow.
Kou, Jisheng
2015-08-01
Surface tension significantly impacts subsurface flow and transport, and it is the main cause of capillary effect, a major immiscible two-phase flow mechanism for systems with a strong wettability preference. In this paper, we consider the numerical simulation of the surface tension of multi-component mixtures with the gradient theory of fluid interfaces. Major numerical challenges include that the system of the Euler-Lagrange equations is solved on the infinite interval and the coefficient matrix is not positive definite. We construct a linear transformation to reduce the Euler-Lagrange equations, and naturally introduce a path function, which is proven to be a monotonic function of the spatial coordinate variable. By using the linear transformation and the path function, we overcome the above difficulties and develop the efficient methods for calculating the interface and its interior compositions. Moreover, the computation of the surface tension is also simplified. The proposed methods do not need to solve the differential equation system, and they are easy to be implemented in practical applications. Numerical examples are tested to verify the efficiency of the proposed methods. © 2014 Elsevier B.V.
Mixed-norm estimates for the M/EEG inverse problem using accelerated gradient methods.
Gramfort, Alexandre; Kowalski, Matthieu; Hämäläinen, Matti
2012-04-07
Magneto- and electroencephalography (M/EEG) measure the electromagnetic fields produced by the neural electrical currents. Given a conductor model for the head, and the distribution of source currents in the brain, Maxwell's equations allow one to compute the ensuing M/EEG signals. Given the actual M/EEG measurements and the solution of this forward problem, one can localize, in space and in time, the brain regions that have produced the recorded data. However, due to the physics of the problem, the limited number of sensors compared to the number of possible source locations, and measurement noise, this inverse problem is ill-posed. Consequently, additional constraints are needed. Classical inverse solvers, often called minimum norm estimates (MNE), promote source estimates with a small ℓ₂ norm. Here, we consider a more general class of priors based on mixed norms. Such norms have the ability to structure the prior in order to incorporate some additional assumptions about the sources. We refer to such solvers as mixed-norm estimates (MxNE). In the context of M/EEG, MxNE can promote spatially focal sources with smooth temporal estimates with a two-level ℓ₁/ℓ₂ mixed-norm, while a three-level mixed-norm can be used to promote spatially non-overlapping sources between different experimental conditions. In order to efficiently solve the optimization problems of MxNE, we introduce fast first-order iterative schemes that for the ℓ₁/ℓ₂ norm give solutions in a few seconds making such a prior as convenient as the simple MNE. Furthermore, thanks to the convexity of the optimization problem, we can provide optimality conditions that guarantee global convergence. The utility of the methods is demonstrated both with simulations and experimental MEG data.
Piret, Cé cile
2012-01-01
Much work has been done on reconstructing arbitrary surfaces using the radial basis function (RBF) method, but one can hardly find any work done on the use of RBFs to solve partial differential equations (PDEs) on arbitrary surfaces. In this paper
Badiani, Anna; Montellato, Lara; Bochicchio, Davide; Anfossi, Paola; Zanardi, Emanuela; Maranesi, Magda
2004-08-11
Proximate composition and fatty acid profile, conjugated linoleic acid (CLA) isomers included, were determined in separable lean of raw and cooked lamb rib loins. The cooking methods compared, which were also investigated for cooking yields and true nutrient retention values, were dry heating of fat-on cuts and moist heating of fat-off cuts; the latter method was tested as a sort of dietetic approach against the more traditional former type. With significantly (P cooking losses, dry heating of fat-on rib-loins produced slightly (although only rarely significantly) higher retention values for all of the nutrients considered, including CLA isomers. On the basis of the retention values obtained, both techniques led to a minimum migration of lipids into the separable lean, which was higher (P cooking of the class of CLA isomers (including that of the nutritionally most important isomer cis-9,trans-11) was more similar to that of the monounsaturated than the polyunsaturated fatty acids.
Focus measure method based on the modulus of the gradient of the color planes for digital microscopy
Hurtado-Pérez, Román; Toxqui-Quitl, Carina; Padilla-Vivanco, Alfonso; Aguilar-Valdez, J. Félix; Ortega-Mendoza, Gabriel
2018-02-01
The modulus of the gradient of the color planes (MGC) is implemented to transform multichannel information to a grayscale image. This digital technique is used in two applications: (a) focus measurements during autofocusing (AF) process and (b) extending the depth of field (EDoF) by means of multifocus image fusion. In the first case, the MGC procedure is based on an edge detection technique and is implemented in over 15 focus metrics that are typically handled in digital microscopy. The MGC approach is tested on color images of histological sections for the selection of in-focus images. An appealing attribute of all the AF metrics working in the MGC space is their monotonic behavior even up to a magnification of 100×. An advantage of the MGC method is its computational simplicity and inherent parallelism. In the second application, a multifocus image fusion algorithm based on the MGC approach has been implemented on graphics processing units (GPUs). The resulting fused images are evaluated using a nonreference image quality metric. The proposed fusion method reveals a high-quality image independently of faulty illumination during the image acquisition. Finally, the three-dimensional visualization of the in-focus image is shown.
Godinho, Bruno M D C; Gilbert, James W; Haraszti, Reka A; Coles, Andrew H; Biscans, Annabelle; Roux, Loic; Nikan, Mehran; Echeverria, Dimas; Hassler, Matthew; Khvorova, Anastasia
2017-12-01
Therapeutic oligonucleotides, such as small interfering RNAs (siRNAs), hold great promise for the treatment of incurable genetically defined disorders by targeting cognate toxic gene products for degradation. To achieve meaningful tissue distribution and efficacy in vivo, siRNAs must be conjugated or formulated. Clear understanding of the pharmacokinetic (PK)/pharmacodynamic behavior of these compounds is necessary to optimize and characterize the performance of therapeutic oligonucleotides in vivo. In this study, we describe a simple and reproducible methodology for the evaluation of in vivo blood/plasma PK profiles and tissue distribution of oligonucleotides. The method is based on serial blood microsampling from the saphenous vein, coupled to peptide nucleic acid hybridization assay for quantification of guide strands. Performed with minimal number of animals, this method allowed unequivocal detection and sensitive quantification without the need for amplification, or further modification of the oligonucleotides. Using this methodology, we compared plasma clearances and tissue distribution profiles of two different hydrophobically modified siRNAs (hsiRNAs). Notably, cholesterol-hsiRNA presented slow plasma clearances and mainly accumulated in the liver, whereas, phosphocholine-docosahexaenoic acid-hsiRNA was rapidly cleared from the plasma and preferably accumulated in the kidney. These data suggest that the PK/biodistribution profiles of modified hsiRNAs are determined by the chemical nature of the conjugate. Importantly, the method described in this study constitutes a simple platform to conduct pilot assessments of the basic clearance and tissue distribution profiles, which can be broadly applied for evaluation of new chemical variants of siRNAs and micro-RNAs.
Domain decomposition methods and parallel computing
International Nuclear Information System (INIS)
Meurant, G.
1991-01-01
In this paper, we show how to efficiently solve large linear systems on parallel computers. These linear systems arise from discretization of scientific computing problems described by systems of partial differential equations. We show how to get a discrete finite dimensional system from the continuous problem and the chosen conjugate gradient iterative algorithm is briefly described. Then, the different kinds of parallel architectures are reviewed and their advantages and deficiencies are emphasized. We sketch the problems found in programming the conjugate gradient method on parallel computers. For this algorithm to be efficient on parallel machines, domain decomposition techniques are introduced. We give results of numerical experiments showing that these techniques allow a good rate of convergence for the conjugate gradient algorithm as well as computational speeds in excess of a billion of floating point operations per second. (author). 5 refs., 11 figs., 2 tabs., 1 inset
Su, Cui; Su, Yunlan; Li, Zhiyong; Haq, Muhammad Abdul; Zhou, Yong; Wang, Dujin
2017-08-01
Bilayered poly(vinyl alcohol) (PVA)/hydroxyapatite (HA) composite hydrogels with anisotropic and gradient mechanical properties were prepared by the combination of directional freezing-thawing (DFT) and electrophoresis method. Firstly, PVA hydrogels with aligned channel structure were prepared by the DFT method. Then, HA nanoparticles were in situ synthesized within the PVA hydrogels via electrophoresis. By controlling the time of the electrophoresis process, a bilayered gradient hydrogel containing HA particles in only half of the gel region was obtained. The PVA/HA composite hydrogel exhibited gradient mechanical strength depending on the distance to the cathode. The gradient initial tensile modulus ranging from 0.18MPa to 0.27MPa and the gradient initial compressive modulus from 0.33MPa to 0.51MPa were achieved. The binding strength of the two regions was relatively high and no apparent internal stress or defect was observed at the boundary. The two regions of the bilayered hydrogel also showed different osteoblast cell adhesion properties. Copyright © 2017 Elsevier B.V. All rights reserved.
Radrizzani, Marina; Lo Cicero, Viviana; Soncin, Sabrina; Bolis, Sara; Sürder, Daniel; Torre, Tiziano; Siclari, Francesco; Moccetti, Tiziano; Vassalli, Giuseppe; Turchetto, Lucia
2014-09-27
Cardiovascular cell therapy represents a promising field, with several approaches currently being tested. The advanced therapy medicinal product (ATMP) for the ongoing METHOD clinical study ("Bone marrow derived cell therapy in the stable phase of chronic ischemic heart disease") consists of fresh mononuclear cells (MNC) isolated from autologous bone marrow (BM) through density gradient centrifugation on standard Ficoll-Paque. Cells are tested for safety (sterility, endotoxin), identity/potency (cell count, CD45/CD34/CD133, viability) and purity (contaminant granulocytes and platelets). BM-MNC were isolated by density gradient centrifugation on Ficoll-Paque. The following process parameters were optimized throughout the study: gradient medium density; gradient centrifugation speed and duration; washing conditions. A new manufacturing method was set up, based on gradient centrifugation on low density Ficoll-Paque, followed by 2 washing steps, of which the second one at low speed. It led to significantly higher removal of contaminant granulocytes and platelets, improving product purity; the frequencies of CD34+ cells, CD133+ cells and functional hematopoietic and mesenchymal precursors were significantly increased. The methodological optimization described here resulted in a significant improvement of ATMP quality, a crucial issue to clinical applications in cardiovascular cell therapy.
Directory of Open Access Journals (Sweden)
Shang Wang
2015-04-01
Full Text Available A methodology (HPLC proposed in this paper for simultaneously quantitative determination of ilaprazole and its related impurities in commercial tablets was developed and validated. The chromatographic separation was carried out by gradient elution using an Agilent C8 column (4.6 mm × 250 mm, 5 μm which was maintained at 25 °C. The mobile phase composed of solvent A (methanol and solvent B (solution consisting 0.02 mmol/l monopotassium phosphate and 0.025 mmol/l sodium hydroxide was at a flow rate of 1.0 ml/min. The samples were detected and quantified at 237 nm using an ultraviolet absorbance detector. Calibration curves of all analytes from 0.5 to 3.5 μg/ml were good linearity (r ≥ 0.9990 and recovery was greater than 99.5% for each analyte. The lower limit of detection (LLOD and quantification (LOQ of this analytical method were 10 ng/ml and 25 ng/ml for all impurities, respectively. The stress studies indicated that the degradation products could not interfere with the detection of ilaprazole and its related impurities and the assay can thus be considered stability-indicating. The method precisions were in the range of 0.41–1.21 while the instrument precisions were in the range of 0.38–0.95 in terms of peak area RSD% for all impurities, respectively. This method is considered stability-indicating and is applicable for accurate and simultaneous measuring of the ilaprazole and its related impurities in commercial enteric-coated tablets.
Krylov subspace methods for solving large unsymmetric linear systems
International Nuclear Information System (INIS)
Saad, Y.
1981-01-01
Some algorithms based upon a projection process onto the Krylov subspace K/sub m/ = Span(r 0 , Ar 0 ,...,A/sup m/-1r 0 ) are developed, generalizing the method of conjugate gradients to unsymmetric systems. These methods are extensions of Arnoldi's algorithm for solving eigenvalue problems. The convergence is analyzed in terms of the distance of the solution to the subspace K/sub m/ and some error bounds are established showing, in particular, a similarity with the conjugate gradient method (for symmetric matrices) when the eigenvalues are real. Several numerical experiments are described and discussed
Tietjen, Gregory T; Kong, Yupeng; Parthasarathy, Raghuveer
2008-07-07
Interparticle interaction energies and other useful physical characteristics can be extracted from the statistical properties of the motion of particles confined by an optical line trap. In practice, however, the potential energy landscape, U(x), imposed by the line provides an extra, and in general unknown, influence on particle dynamics. We describe a new class of line traps in which both the optical gradient and scattering forces acting on a trapped particle are designed to be linear functions of the line coordinate and in which their magnitude can be counterbalanced to yield a flat U(x). These traps are formed using approximate solutions to general relations concerning non-conservative optical forces that have been the subject of recent investigations [Y. Roichman, B. Sun, Y. Roichman, J. Amato-Grill, and D. G. Grier, Phys. Rev. Lett. 100, 013602-4 (2008).]. We implement the lines using holographic optical trapping and measure the forces acting on silica microspheres, demonstrating the tunability of the confining potential energy landscape. Furthermore, we show that our approach efficiently directs available laser power to the trap, in contrast to other methods.
On the numerical stability analysis of pipelined Krylov subspace methods
Czech Academy of Sciences Publication Activity Database
Carson, E.T.; Rozložník, Miroslav; Strakoš, Z.; Tichý, P.; Tůma, M.
submitted 2017 (2018) R&D Projects: GA ČR GA13-06684S Grant - others:GA MŠk(CZ) LL1202 Institutional support: RVO:67985807 Keywords : Krylov subspace methods * the conjugate gradient method * numerical stability * inexact computations * delay of convergence * maximal attainable accuracy * pipelined Krylov subspace methods * exascale computations
Energy Technology Data Exchange (ETDEWEB)
Peter W. Carr; K.M. Fuller; D.R. Stoll; L.D. Steinkraus; M.S. Pasha; Glenn G. Hardin
2005-12-30
A new approach has been developed by modifying a conventional gradient elution liquid chromatograph for the high throughput screening of biological samples to detect the presence of regulated intoxicants. The goal of this work was to improve the speed of a gradient elution screening method over current approaches by optimizing the operational parameters of both the column and the instrument without compromising the reproducibility of the retention times, which are the basis for the identification. Most importantly, the novel instrument configuration substantially reduces the time needed to re-equilibrate the column between gradient runs, thereby reducing the total time for each analysis. The total analysis time for each gradient elution run is only 2.8 minutes, including 0.3 minutes for column reequilibration between analyses. Retention times standard calibration solutes are reproducible to better than 0.002 minutes in consecutive runs. A corrected retention index was adopted to account for day-to-day and column-to-column variations in retention time. The discriminating power and mean list length were calculated for a library of 47 intoxicants and compared with previous work from other laboratories to evaluate fast gradient elution HPLC as a screening tool.
Bis-polymer lipid-peptide conjugates and nanoparticles thereof
Energy Technology Data Exchange (ETDEWEB)
Xu, Ting; Dong, He; Shu, Jessica; Dube, Nikhil
2018-04-24
The present invention provides bis-polymer lipid-peptide conjugates containing a hydrophobic block and headgroup containing a helical peptide and two polymer blocks. The conjugates can self-assemble to form helix bundle subunits, which in turn assemble to provide micellar nanocarriers for drug cargos and other agents. Particles containing the conjugates and methods for forming the particles are also disclosed.
Directory of Open Access Journals (Sweden)
Meliefste Kees
2006-06-01
Full Text Available Abstract Background Air pollution in São Paulo is constantly being measured by the State of Sao Paulo Environmental Agency, however there is no information on the variation between places with different traffic densities. This study was intended to identify a gradient of exposure to traffic-related air pollution within different areas in São Paulo to provide information for future epidemiological studies. Methods We measured NO2 using Palmes' diffusion tubes in 36 sites on streets chosen to be representative of different road types and traffic densities in São Paulo in two one-week periods (July and August 2000. In each study period, two tubes were installed in each site, and two additional tubes were installed in 10 control sites. Results Average NO2 concentrations were related to traffic density, observed on the spot, to number of vehicles counted, and to traffic density strata defined by the city Traffic Engineering Company (CET. Average NO2concentrations were 63μg/m3 and 49μg/m3 in the first and second periods, respectively. Dividing the sites by the observed traffic density, we found: heavy traffic (n = 17: 64μg/m3 (95% CI: 59μg/m3 – 68μg/m3; local traffic (n = 16: 48μg/m3 (95% CI: 44μg/m3 – 52μg/m3 (p Conclusion The differences in NO2 levels between heavy and local traffic sites are large enough to suggest the use of a more refined classification of exposure in epidemiological studies in the city. Number of vehicles counted, traffic density observed on the spot and traffic density strata defined by the CET might be used as a proxy for traffic exposure in São Paulo when more accurate measurements are not available.
International Nuclear Information System (INIS)
Roidl, B.; Meinke, M.; Schröder, W.
2013-01-01
Highlights: • A synthetic turbulence generation method (STGM) is presented. • STGM is applied to sub and supersonic flows at low and moderate Reynolds numbers. • STGM shows a convincing quality in zonal RANS–LES for flat-plate boundary layers (BLs). • A good agreement with the pure LES and reference DNS findings is obtained. • RANS-to-LES transition length is reduced to less than four boundary-layer thicknesses. -- Abstract: A synthetic turbulence generation (STG) method for subsonic and supersonic flows at low and moderate Reynolds numbers to provide inflow distributions of zonal Reynolds-averaged Navier–Stokes (RANS) – large-eddy simulation (LES) methods is presented. The STG method splits the LES inflow region into three planes where a local velocity signal is decomposed from the turbulent flow properties of the upstream RANS solution. Based on the wall-normal position and the local flow Reynolds number, specific length and velocity scales with different vorticity content are imposed at the inlet plane of the boundary layer. The quality of the STG method for incompressible and compressible zero-pressure gradient boundary layers is shown by comparing the zonal RANS–LES data with pure LES, pure RANS, and direct numerical simulation (DNS) solutions. The distributions of the time and spanwise wall-shear stress, Reynolds stress distributions, and two point correlations of the zonal RANS–LES simulations are smooth in the transition region and in good agreement with the pure LES and reference DNS findings. The STG approach reduces the RANS-to-LES transition length to less than four boundary-layer thicknesses
Batty, Christopher
2017-02-01
This paper introduces a two-dimensional cell-centred finite volume discretization of the Poisson problem on adaptive Cartesian quadtree grids which exhibits second order accuracy in both the solution and its gradients, and requires no grading condition between adjacent cells. At T-junction configurations, which occur wherever resolution differs between neighboring cells, use of the standard centred difference gradient stencil requires that ghost values be constructed by interpolation. To properly recover second order accuracy in the resulting numerical gradients, prior work addressing block-structured grids and graded trees has shown that quadratic, rather than linear, interpolation is required; the gradients otherwise exhibit only first order convergence, which limits potential applications such as fluid flow. However, previous schemes fail or lose accuracy in the presence of the more complex T-junction geometries arising in the case of general non-graded quadtrees, which place no restrictions on the resolution of neighboring cells. We therefore propose novel quadratic interpolant constructions for this case that enable second order convergence by relying on stencils oriented diagonally and applied recursively as needed. The method handles complex tree topologies and large resolution jumps between neighboring cells, even along the domain boundary, and both Dirichlet and Neumann boundary conditions are supported. Numerical experiments confirm the overall second order accuracy of the method in the L∞ norm.
Modelling conjugation with stochastic differential equations
DEFF Research Database (Denmark)
Philipsen, Kirsten Riber; Christiansen, Lasse Engbo; Hasman, Henrik
2010-01-01
Enterococcus faecium strains in a rich exhaustible media. The model contains a new expression for a substrate dependent conjugation rate. A maximum likelihood based method is used to estimate the model parameters. Different models including different noise structure for the system and observations are compared......Conjugation is an important mechanism involved in the transfer of resistance between bacteria. In this article a stochastic differential equation based model consisting of a continuous time state equation and a discrete time measurement equation is introduced to model growth and conjugation of two...... using a likelihood-ratio test and Akaike's information criterion. Experiments indicating conjugation on the agar plates selecting for transconjugants motivates the introduction of an extended model, for which conjugation on the agar plate is described in the measurement equation. This model is compared...
Iterative methods for weighted least-squares
Energy Technology Data Exchange (ETDEWEB)
Bobrovnikova, E.Y.; Vavasis, S.A. [Cornell Univ., Ithaca, NY (United States)
1996-12-31
A weighted least-squares problem with a very ill-conditioned weight matrix arises in many applications. Because of round-off errors, the standard conjugate gradient method for solving this system does not give the correct answer even after n iterations. In this paper we propose an iterative algorithm based on a new type of reorthogonalization that converges to the solution.
Layer-oriented multigrid wavefront reconstruction algorithms for multi-conjugate adaptive optics
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.
Czech Academy of Sciences Publication Activity Database
Lukšan, Ladislav; Vlček, Jan
1998-01-01
Roč. 8, č. 3-4 (1998), s. 201-223 ISSN 1055-6788 R&D Projects: GA ČR GA201/96/0918 Keywords : nonlinear equations * Armijo-type descent methods * Newton-like methods * truncated methods * global convergence * nonsymmetric linear systems * conjugate gradient -type methods * residual smoothing * computational experiments Subject RIV: BB - Applied Statistics, Operational Research
By how much can Residual Minimization Accelerate the Convergence of Orthogonal Residual Methods?
Czech Academy of Sciences Publication Activity Database
Gutknecht, M. H.; Rozložník, Miroslav
2001-01-01
Roč. 27, - (2001), s. 189-213 ISSN 1017-1398 R&D Projects: GA ČR GA201/98/P108 Institutional research plan: AV0Z1030915 Keywords : system of linear algebraic equations * iterative method * Krylov space method * conjugate gradient method * biconjugate gradient method * CG * CGNE * CGNR * CGS * FOM * GMRes * QMR * TFQMR * residual smoothing * MR smoothing * QMR smoothing Subject RIV: BA - General Mathematics Impact factor: 0.438, year: 2001
Huang, Hui; Gao, Yuan; Shi, Fanping; Wang, Guannan; Shah, Syed Mazhar; Su, Xingguang
2012-03-21
In this paper, a sensitive water-soluble fluorescent conjugated polymer biosensor for catecholamine (dopamine DA, adrenaline AD and norepinephrine NE) was developed. In the presence of horse radish peroxidase (HRP) and H(2)O(2), catecholamine could be oxidized and the oxidation product of catecholamine could quench the photoluminescence (PL) intensity of poly(2,5-bis(3-sulfonatopropoxy)-1,4-phenylethynylenealt-1,4-poly(phenylene ethynylene)) (PPESO(3)). The quenching PL intensity of PPESO(3) (I(0)/I) was proportional to the concentration of DA, AD and NE in the concentration ranges of 5.0 × 10(-7) to 1.4 × 10(-4), 5.0 × 10(-6) to 5.0 × 10(-4), and 5.0 × 10(-6) to 5.0 × 10(-4) mol L(-1), respectively. The detection limit for DA, AD and NE was 1.4 × 10(-7) mol L(-1), 1.0 × 10(-6) and 1.0 × 10(-6) mol L(-1), respectively. The PPESO(3)-enzyme hybrid system based on the fluorescence quenching method was successfully applied for the determination of catecholamine in human serum samples with good accuracy and satisfactory recovery. The results were in good agreement with those provided by the HPLC-MS method.
Sun, Huafei; Darmofal, David L.
2014-12-01
In this paper we propose a new high-order solution framework for interface problems on non-interface-conforming meshes. The framework consists of a discontinuous Galerkin (DG) discretization, a simplex cut-cell technique, and an output-based adaptive scheme. We first present a DG discretization with a dual-consistent output evaluation for elliptic interface problems on interface-conforming meshes, and then extend the method to handle multi-physics interface problems, in particular conjugate heat transfer (CHT) problems. The method is then applied to non-interface-conforming meshes using a cut-cell technique, where the interface definition is completely separate from the mesh generation process. No assumption is made on the interface shape (other than Lipschitz continuity). We then equip our strategy with an output-based adaptive scheme for an accurate output prediction. Through numerical examples, we demonstrate high-order convergence for elliptic interface problems and CHT problems with both smooth and non-smooth interface shapes.
Wang, Yaohui; Xin, Xuegang; Guo, Lei; Chen, Zhifeng; Liu, Feng
2018-05-01
The switching of a gradient coil current in magnetic resonance imaging will induce an eddy current in the surrounding conducting structures while the secondary magnetic field produced by the eddy current is harmful for the imaging. To minimize the eddy current effects, the stray field shielding in the gradient coil design is usually realized by minimizing the magnetic fields on the cryostat surface or the secondary magnetic fields over the imaging region. In this work, we explicitly compared these two active shielding design methods. Both the stray field and eddy current on the cryostat inner surface were quantitatively discussed by setting the stray field constraint with an ultra-low maximum intensity of 2 G and setting the secondary field constraint with an extreme small shielding ratio of 0.000 001. The investigation revealed that the secondary magnetic field control strategy can produce coils with a better performance. However, the former (minimizing the magnetic fields) is preferable when designing a gradient coil with an ultra-low eddy current that can also strictly control the stray field leakage at the edge of the cryostat inner surface. A wrapped-edge gradient coil design scheme was then optimized for a more effective control of the stray fields. The numerical simulation on the wrapped-edge coil design shows that the optimized wrapping angles for the x and z coils in terms of our coil dimensions are 40° and 90°, respectively.
DEFF Research Database (Denmark)
Helgesen, Martin; Carlé, Jon Eggert; Helt-Hansen, Jakob
2014-01-01
Irradiation of organic multilayer films is demonstrated as a powerful method to improve several properties of polymer thin films and devices derived from them. The chemical cross‐linking that is the direct result of the irradiation with ∼100 keV electrons is fast and has a penetration power...... stability. The method is fast, generic, contactless, and fully compatible with high‐speed roll‐to‐roll processing of i.e. polymer solar cells at web speeds in excess of 60 m min−1. We employ fully printed, flexible, and foil‐based indium‐tin‐oxide free polymer solar cells in this study to demonstrate...
International Nuclear Information System (INIS)
Hadley, S.W.; Wilbur, D.S.
1990-01-01
The preparations and conjugations of 2,3,5,6-tetrafluorophenyl 5-[125I/131I]iodo-4-pentenoate (7a) and 2,3,5,6-tetrafluorophenyl 3,3-dimethyl-5-[125I/131I]iodo-4-pentenoate (7b) to monoclonal antibodies are reported. Reagents 7a and 7b were prepared in high radiochemical yield by iododestannylation of their corresponding 5-tri-n-butylstannyl precursors. Radioiodinated antibody conjugates were prepared by reaction of 7a or 7b with the protein at basic pH. Evaluation of these conjugates by several in vitro procedures demonstrated that the radiolabel was attached to the antibody in a stable manner and that the conjugates maintained immunoreactivity. Comparative dual-isotope biodistribution studies of a monoclonal antibody Fab fragment conjugate of 7a and 7b with the same Fab fragment labeled with N-succinimidyl p-[131I]iodobenzoate (PIB, p-iodobenzoate, 2) or directly radioiodinated have been carried out in tumor-bearing nude mice. Coinjection of the Fab conjugate of 7a with the Fab conjugate of 2 demonstrated that the biodistributions were similar in most organs, except the neck tissue (thyroid-containing) and the stomach, which contained substantially increased levels of the 7a label. Coinjection of the Fab conjugate of 7a with the Fab fragment radioiodinated by using the chloramine-T method demonstrated that the biodistributions were remarkably similar, suggesting roughly equivalent in vivo deiodination of these labeled antibody fragments. Coinjection of the Fab conjugate of 7a with the Fab conjugate of 7b indicated that there was ∼ a 2-fold reduction in the amount of in vivo deiodination of the 7b conjugate as compared to the 7a conjugate