Eigenvalue Problems of a Tensor and a Tensor-Block Matrix (TMB) of Any Even Rank with Some Applications in Mechanics

2016 ◽  
pp. 279-317 ◽  
Author(s):  
Mikhail U. Nikabadze
Keyword(s):  
Eigenvalue Problems ◽  
Block Matrix

A method for solving stochastic eigenvalue problems II

2013 ◽  
Vol 219 (9) ◽  
pp. 4729-4744 ◽  
Author(s):  
M.M.R. Williams
Keyword(s):  
Eigenvalue Problems

Re-analysis method for inversion of block matrix based on change threshold

2021 ◽  
Vol 94 ◽  
pp. 780-790
Author(s):  
Biliang Cheng ◽  
Huping Mao ◽  
Quan Sun ◽  
Feng Jia ◽  
Peng Zhang
Keyword(s):  
Block Matrix ◽  
Analysis Method ◽  
Change Threshold

scholarly journals A Revisit to CMFD Schemes: Fourier Analysis and Enhancement

Energies ◽  
2021 ◽  
Vol 14 (2) ◽  
pp. 424
Author(s):  
Dean Wang ◽  
Zuolong Zhu
Keyword(s):  
Fourier Analysis ◽  
Eigenvalue Problems ◽  
Neutron Transport ◽  
Coarse Mesh ◽  
Successive Overrelaxation ◽  
Computational Cell ◽  
Artificial Diffusion ◽  
Acceleration Method ◽  
The Stability ◽  
Partial Current

The coarse-mesh finite difference (CMFD) scheme is a very effective nonlinear diffusion acceleration method for neutron transport calculations. CMFD can become unstable and fail to converge when the computational cell optical thickness is relatively large in k-eigenvalue problems or diffusive fixed-source problems. Some variants and fixups have been developed to enhance the stability of CMFD, including the partial current-based CMFD (pCMFD), optimally diffusive CMFD (odCMFD), and linear prolongation-based CMFD (lpCMFD). Linearized Fourier analysis has proven to be a very reliable and accurate tool to investigate the convergence rate and stability of such coupled high-order transport/low-order diffusion iterative schemes. It is shown in this paper that the use of different transport solvers in Fourier analysis may have some potential implications on the development of stabilizing techniques, which is exemplified by the odCMFD scheme. A modification to the artificial diffusion coefficients of odCMFD is proposed to improve its stability. In addition, two explicit expressions are presented to calculate local optimal successive overrelaxation (SOR) factors for lpCMFD to further enhance its acceleration performance for fixed-source problems and k-eigenvalue problems, respectively.

Representations for the image-kernel (p,q)-inverses of block matrices in rings

2020 ◽  
Vol 27 (2) ◽  
pp. 297-305
Author(s):  
Dijana Mosić
Keyword(s):  
Block Matrix ◽  
Block Matrices ◽  
Schur Form

AbstractWe present the conditions for a block matrix of a ring to have the image-kernel{(p,q)}-inverse in the generalized Banachiewicz–Schur form. We give representations for the image-kernel inverses of the sum and the product of two block matrices. Some characterizations of the image-kernel{(p,q)}-inverse in a ring with involution are investigated too.

Block matrix models for dynamic networks

2021 ◽  
Vol 402 ◽  
pp. 126121
Author(s):  
Mohammed Al Mugahwi ◽  
Omar De La Cruz Cabrera ◽  
Caterina Fenu ◽  
Lothar Reichel ◽  
Giuseppe Rodriguez
Keyword(s):  
Matrix Models ◽  
Dynamic Networks ◽  
Block Matrix
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