Stochastic simulations of ocean waves: An uncertainty quantification study

Stochastic simulations of ocean waves: An uncertainty quantification study

Keywords: Ocean wave modeling Uncertainty quantification Generalized polynomial chaos Sparse grid collocation Sensitivity analysis Karhunen–Loeve decomposition a b s t r a c t The primary objective of this study is to introduce a stochastic framework based on generalized polynomial chaos (gPC) for uncertainty quantification in numerical ocean wave simulations. The techniques we present can be e...

Uncertainty Quantification in Irreversible Electroporation Simulations

One recent area of cancer research is irreversible electroporation (IRE). Irreversible electroporation is a minimally invasive procedure where needle electrodes are inserted into the body to ablate tumor cells with electricity. The aim of this paper is to investigate how uncertainty in tissue and tumor conductivity propagate into final ablation predictions used for treatment planning. Two dimen...

Sparse multiresolution stochastic approximation for uncertainty quantification

Most physical systems are inevitably affected by uncertainties due to natural variabili-ties or incomplete knowledge about their governing laws. To achieve predictive computer simulations of such systems, a major task is, therefore, to study the impact of these uncertainties on response quantities of interest. Within the probabilistic framework, uncertainties may be represented in the form of r...

Quantification of Uncertainty in Flow Simulations Using Probabilistic Methods

Uncertainty Quantification for Stochastic Subspace Identification of Multi-Setup Measurements

In Operational Modal Analysis, the modal parameters (natural frequencies, damping ratios and mode shapes) obtained from Stochastic Subspace Identification (SSI) of a structure, are afflicted with statistical uncertainty. For evaluating the quality of the obtained results it is essential to know the appropriate confidence intervals of these figures. In this paper we present algorithms that autom...