کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
10415582 897571 2011 20 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
Stochastic multiscale fracture analysis of three-dimensional functionally graded composites
موضوعات مرتبط
مهندسی و علوم پایه سایر رشته های مهندسی مهندسی مکانیک
پیش نمایش صفحه اول مقاله
Stochastic multiscale fracture analysis of three-dimensional functionally graded composites
چکیده انگلیسی
A new moment-modified polynomial dimensional decomposition (PDD) method is presented for stochastic multiscale fracture analysis of three-dimensional, particle-matrix, functionally graded materials (FGMs) subject to arbitrary boundary conditions. The method involves Fourier-polynomial expansions of component functions by orthonormal polynomial bases, an additive control variate in conjunction with Monte Carlo simulation for calculating the expansion coefficients, and a moment-modified random output to account for the effects of particle locations and geometry. A numerical verification conducted on a two-dimensional FGM reveals that the new method, notably the univariate PDD method, produces the same crude Monte Carlo results with a five-fold reduction in the computational effort. The numerical results from a three-dimensional, edge-cracked, FGM specimen under a mixed-mode deformation demonstrate that the statistical moments or probability distributions of crack-driving forces and the conditional probability of fracture initiation can be efficiently generated by the univariate PDD method. There exist significant variations in the probabilistic characteristics of the stress-intensity factors and fracture-initiation probability along the crack front. Furthermore, the results are insensitive to the subdomain size from concurrent multiscale analysis, which, if selected judiciously, leads to computationally efficient estimates of the probabilistic solutions.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Engineering Fracture Mechanics - Volume 78, Issue 1, January 2011, Pages 27-46
نویسندگان
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