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
This paper was presented at the 3rd Micro and Nano Flows Conference (MNF2011), which was held at the...
Uncertainty is a common feature in first-principles models that are widely used in various engineeri...
The uncertainties can generate fluctuations with aerodynamic characteristics. Uncertainty Quantifica...
This book presents applications of spectral methods to problems of uncertainty propagation and quant...
Uncertainty quantification techniques based on the spectral approach have been studied extensively i...
Uncertainty quantification is an emerging research area aiming at quantifying the variation in engin...
Uncertainty quantification seeks to provide a quantitative means to understand complex systems that ...
Uncertainty quantication (UQ) in CFD computations is receiving increased in-terest, due in large par...
This thesis has investigated the field of Uncertainty Quantification with regard to differential equ...
Uncertainty Quantification (UQ) is a rel-atively new research area where there over the past years h...
The flow-driven spectral chaos (FSC) is a recently developed method for tracking and quantifying unc...
We consider Uncertainty Quanti¿cation (UQ) by expanding the solution in so-called generalized Polyno...
This paper describes a fully spectral, Polynomial Chaos method for the propagation of uncertainty in...
This paper examines uncertainty quantification in computational fluid dynamics (CFD) with non-intrus...
Uncertainty quantification is an important part of a probabilistic design of structures. Nonetheles...
This paper was presented at the 3rd Micro and Nano Flows Conference (MNF2011), which was held at the...
Uncertainty is a common feature in first-principles models that are widely used in various engineeri...
The uncertainties can generate fluctuations with aerodynamic characteristics. Uncertainty Quantifica...
This book presents applications of spectral methods to problems of uncertainty propagation and quant...
Uncertainty quantification techniques based on the spectral approach have been studied extensively i...
Uncertainty quantification is an emerging research area aiming at quantifying the variation in engin...
Uncertainty quantification seeks to provide a quantitative means to understand complex systems that ...
Uncertainty quantication (UQ) in CFD computations is receiving increased in-terest, due in large par...
This thesis has investigated the field of Uncertainty Quantification with regard to differential equ...
Uncertainty Quantification (UQ) is a rel-atively new research area where there over the past years h...
The flow-driven spectral chaos (FSC) is a recently developed method for tracking and quantifying unc...
We consider Uncertainty Quanti¿cation (UQ) by expanding the solution in so-called generalized Polyno...
This paper describes a fully spectral, Polynomial Chaos method for the propagation of uncertainty in...
This paper examines uncertainty quantification in computational fluid dynamics (CFD) with non-intrus...
Uncertainty quantification is an important part of a probabilistic design of structures. Nonetheles...
This paper was presented at the 3rd Micro and Nano Flows Conference (MNF2011), which was held at the...
Uncertainty is a common feature in first-principles models that are widely used in various engineeri...
The uncertainties can generate fluctuations with aerodynamic characteristics. Uncertainty Quantifica...