Approximation of Quantities of Interest in Stochastic PDEs by the Random Discrete L^2 Projection on Polynomial Spaces

Mathematics

• Polynomial 100%
• PDE 100%
• Stochastics 100%
• Input Parameter 80%
• Random Input 60%
• Number 60%
• Optimality 20%
• Navier-Stokes Equation 20%
• Least Square 20%
• Polynomial Function 20%
• Differential Equation Model 20%
• Independent Sample 20%
• Linear Elasticity 20%
• Uncertainty Quantification 20%
• Monte Carlo Approach 20%

Keyphrases

• Random Input Parameters 60%
• Random Parameters 40%
• Elastic Coefficient 20%
• Linear Growth 20%
• Random Geometry 20%
• Partial Differential Equation Model 20%
• Quadratic Growth 20%
• Polynomial Function 20%
• Fluid Viscosity 20%
• Random Permeability 20%
• High-dimensional Uncertainty Quantification 20%