Suscripción a Biblioteca: Guest
International Journal for Uncertainty Quantification

Publicado 6 números por año

ISSN Imprimir: 2152-5080

ISSN En Línea: 2152-5099

The Impact Factor measures the average number of citations received in a particular year by papers published in the journal during the two preceding years. 2017 Journal Citation Reports (Clarivate Analytics, 2018) IF: 1.7 To calculate the five year Impact Factor, citations are counted in 2017 to the previous five years and divided by the source items published in the previous five years. 2017 Journal Citation Reports (Clarivate Analytics, 2018) 5-Year IF: 1.9 The Immediacy Index is the average number of times an article is cited in the year it is published. The journal Immediacy Index indicates how quickly articles in a journal are cited. Immediacy Index: 0.5 The Eigenfactor score, developed by Jevin West and Carl Bergstrom at the University of Washington, is a rating of the total importance of a scientific journal. Journals are rated according to the number of incoming citations, with citations from highly ranked journals weighted to make a larger contribution to the eigenfactor than those from poorly ranked journals. Eigenfactor: 0.0007 The Journal Citation Indicator (JCI) is a single measurement of the field-normalized citation impact of journals in the Web of Science Core Collection across disciplines. The key words here are that the metric is normalized and cross-disciplinary. JCI: 0.5 SJR: 0.584 SNIP: 0.676 CiteScore™:: 3 H-Index: 25

Indexed in

A MULTIMODES MONTE CARLO FINITE ELEMENT METHOD FOR ELLIPTIC PARTIAL DIFFERENTIAL EQUATIONS WITH RANDOM COEFFICIENTS

Volumen 6, Edición 5, 2016, pp. 429-443
DOI: 10.1615/Int.J.UncertaintyQuantification.2016016805
Get accessGet access

SINOPSIS

This paper develops and analyzes an efficient numerical method for solving elliptic partial differential equations, where the diffusion coefficients are random perturbations of deterministic diffusion coefficients. The method is based upon a multimodes representation of the solution as a power series of the perturbation parameter, and the Monte Carlo technique for sampling the probability space. One key feature of the proposed method is that the governing equations for all the expanded mode functions share the same deterministic diffusion coefficient; thus an efficient direct solver by repeatedly using the LU decomposition of the discretized common deterministic diffusion operator can be employed for solving the finite element discretized linear systems. It is shown that the computational complexity of the algorithm is comparable to that of solving a few deterministic elliptic partial differential equations using the director solver. Error estimates are derived for the method, and numerical experiments are provided to test the efficiency of the algorithm and validate the theoretical results.

CITADO POR
  1. Feng Xiaobing, Lin Junshan, Lorton Cody, A Multi-modes Monte Carlo Interior Penalty Discontinuous Galerkin Method for the Time-Harmonic Maxwell’s Equations with Random Coefficients, Journal of Scientific Computing, 80, 3, 2019. Crossref

  2. Nicholls David, A high-order perturbation of envelopes (HOPE) method for scattering by periodic inhomogeneous media, Quarterly of Applied Mathematics, 78, 4, 2020. Crossref

  3. Yang Zihao, Huang Jizu, Feng Xiaobing, Guan Xiaofei, An Efficient MultiModes Monte Carlo Homogenization Method for Random Materials, SIAM Journal on Scientific Computing, 44, 3, 2022. Crossref

  4. Feng Xiaobing, Luo Yan, Vo Liet, Wang Zhu, An Efficient Iterative Method for Solving Parameter-Dependent and Random Convection–Diffusion Problems, Journal of Scientific Computing, 90, 2, 2022. Crossref

Portal Digitalde Biblioteca Digital eLibros Revistas Referencias y Libros de Ponencias Colecciones Precios y Políticas de Suscripcione Begell House Contáctenos Language English 中文 Русский Português German French Spain