. "[7C8C87DAC1F2]" . . . "0021-9991" . . . "RIV/68407700:21110/10:00169181!RIV11-GA0-21110___" . "Accelerating a FFT-based solver for numerical homogenization of periodic media by conjugate gradients" . "RIV/68407700:21110/10:00169181" . "21" . . . . "Nov\u00E1k, Jan" . "7"^^ . . "Vond\u0159ejc, Jaroslav" . . "P(GA103/09/1748), P(GA201/09/1544), P(GP103/09/P490), S" . "Accelerating a FFT-based solver for numerical homogenization of periodic media by conjugate gradients"@en . . . . . "Accelerating a FFT-based solver for numerical homogenization of periodic media by conjugate gradients"@en . "000282118500001" . "Marek, Ivo" . "NL - Nizozemsko" . "Accelerating a FFT-based solver for numerical homogenization of periodic media by conjugate gradients" . "Journal of Computational Physics" . . "Zeman, Jan" . . . "4"^^ . "In this short note, we present a new technique to accelerate the convergence of a FFT-based solver for numerical homogenization of complex periodic media proposed by Moulinec and Suquet. The approach proceeds from discretization of the governing integral equation by the trigonometric collocation method due to Vainikko, to give a linear system which can be efficiently solved by conjugate gradient methods. Computational experiments confirm robustness of the algorithm with respect to its internal parameters and demonstrate significant increase of the convergence rate for problems with high-contrast coefficients at a low overhead per iteration." . "21110" . . "245159" . "Numerical homogenization; FFT-based solvers; Trigonometric collocation method; Conjugate gradient solvers"@en . . . "229" . "4"^^ . "In this short note, we present a new technique to accelerate the convergence of a FFT-based solver for numerical homogenization of complex periodic media proposed by Moulinec and Suquet. The approach proceeds from discretization of the governing integral equation by the trigonometric collocation method due to Vainikko, to give a linear system which can be efficiently solved by conjugate gradient methods. Computational experiments confirm robustness of the algorithm with respect to its internal parameters and demonstrate significant increase of the convergence rate for problems with high-contrast coefficients at a low overhead per iteration."@en . . .