Spectral Representations of Uncertainty: Algorithms and Applications

Karniadakis, George Em

Brown University, Providence, RI

关键词: Partial Differential Equations;    Polynomials;    Algorithms;    Simulation;    99 General And Miscellaneous//Mathematics, Computing, And Information Science;   

DOI  :  10.2172/862197
RP-ID  :  DOE/FG/029-final
RP-ID  :  FG02-95ER25239
RP-ID  :  862197

美国|英语

来源: UNT Digital Library

【 摘 要 】

The objectives of this project were: (1) Develop a general algorithmic framework for stochastic ordinary and partial differential equations. (2) Set polynomial chaos method and its generalization on firm theoretical ground. (3) Quantify uncertainty in large-scale simulations involving CFD, MHD and microflows. The overall goal of this project was to provide DOE with an algorithmic capability that is more accurate and three to five orders of magnitude more efficient than the Monte Carlo simulation.