... for the first time to enable efficient uncertainty propagation, which is currently a major bottleneck when using accurate physics-based models. Design/methodology/approach In this paper, the state-of-the-art Kriging, polynomial chaos expansions (PCE) and PCK are applied to “a^ vs a”-based...

... surface method, surrogate methods, polynomial chaos expansion, perturbation method, stochastic collocation method, etc. The review and comparison tests comment and conclude not only on accuracy and efficiency of each method but also their applicability in different types of uncertainty propagation...

... Resource allocation Uncertainty propagation Code development Coupled simulations Model calibration Model validation Partitioned analysis enables independently developed constituent models to affect each other’s input and output through iterative coupling operations (Matthies and Steindorf...

... propagation in periodic structures with periodic uncertain parameters. The approach proposed allows the evaluation of the dispersion of kinematic and energetic parameters. Findings – The authors have found that even though this approach was originally designed to deal with uncertainty propagation...

... subsections.Prior to being used in the RO context, the implementation of both techniques were exhaustively tested (Motta, 2009). The MC method is the most popular non intrusive method and can be used for any problem related to uncertainty propagation. Given the joint probability distribution function...