Spectral Representations of Uncertainty: Algorithms and Applications | Zendy

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Spectral Representations of Uncertainty: Algorithms and Applications

Author(s) -

George Em Karniadakis

Publication year - 2005

Publication title -

osti oai (u.s. department of energy office of scientific and technical information)

Language(s) - English

Resource type - Reports

DOI - 10.2172/862197

Subject(s) - polynomial chaos , generalization , uncertainty quantification , set (abstract data type) , computer science , monte carlo method , algorithm , scale (ratio) , ordinary differential equation , representation (politics) , mathematical optimization , partial differential equation , computational fluid dynamics , mathematics , differential equation , machine learning , engineering , statistics , mathematical analysis , physics , quantum mechanics , aerospace engineering , politics , law , political science , programming language

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

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