کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
498628 863005 2011 11 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
Stochastic computation based on orthogonal expansion of random fields
موضوعات مرتبط
مهندسی و علوم پایه مهندسی کامپیوتر نرم افزارهای علوم کامپیوتر
پیش نمایش صفحه اول مقاله
Stochastic computation based on orthogonal expansion of random fields
چکیده انگلیسی

In solving stochastic differential equations, recently a random variable based Polynomial Chaos (rv-PC) method has been developed as a major numerical solver. For many realistic random media problems the rv-PC method however confronts a critical challenge of curse-of-dimensionality. Since a random field is represented by random variables, the use of various optimal sampling techniques and conventional high dimensional methods still faces the curse-of-dimensionality. Distinguished from all the random variable based methods, in this study a novel Random Field based Orthogonal Expansion (RF-OE) method is proposed in aim to circumvent the curse-of-dimensionality for many physical systems whereas the input information is represented as random fields or stochastic processes, e.g. seismic/ocean wave, wind load, shock wave, and geophysical media. Multiscale modeling of random media problems is selected as the benchmark problem to test the RF-OE method. Especially, the RF-OE method provides a perfect matching with the higher-order Mehler’s formula. By replacing high dimensional random variable representations with a series of orthogonal expansion terms about an underlying random field/process, the RF-OE method reduces the number of dimensions of a stochastic differential equation exponentially. In the first example the RF-OE method is verified with Monte Carlo simulation on a lognormal random media flow transport problem. In the second example the RF-OE method is applied to a time domain problem involving orthogonal expansion of random excitations. In the conclusion the items for further development of the RF-OE method are identified.


► Formulate novel random field based expansions.
► Tackle the high dimensional issue.
► Applicable to both spatial and temporal processes.

ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Computer Methods in Applied Mechanics and Engineering - Volume 200, Issues 41–44, 1 October 2011, Pages 2871–2881
نویسندگان
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