Special Aspects of Wind Wave Simulations for Surge Flood Forecasting and Prevention

AbstractThe paper is focused on several issues of wind wave simulations with SWAN model for the tasks related to prevention of surge floods in St. Petersburg. It introduces main objectives that are pursued through the use of the model as well as covers problems of computational mesh generation and model parameter calibration. We also examined several assumptions on the necessity to take ice fraction and sea level rise into account in wind wave simulations

Uncertainty quantification patterns for multiscale models

Uncertainty quantification (UQ) is a key component when using computational models that involve uncertainties, e.g. in decision-making scenarios. In this work, we present uncertainty quantification patterns (UQPs) that are designed to support the analysis of uncertainty in coupled multi-scale and multi-domain applications. UQPs provide the basic building blocks to create tailored UQ for multiscale models. The UQPs are implemented as generic templates, which can then be customized and aggregated to create a dedicated UQ procedure for multiscale applications. We present the implementation of the UQPs with multiscale co

Non-intrusive and semi-intrusive uncertainty quantification of a multiscale in-stent restenosis model

The In-Stent Restenosis 2D model is a full y coupled multiscale simulation of post-stenting tissue growth, in which the most costly submodel is the blood flow simulation. This paper presents uncertainty estimations of the response of this model, as obtained by both non-intrusive and semi-intrusive uncertainty quantification. A surrogate model based on Gaussian process regression for non-intrusive uncertainty quantification takes the whole model as a black-box and maps directly the three uncertain inputs to the quantity of interest, the neointimal area. The corresponding uncertain estimates matched the results from quasi-Monte Carlo simulations well. In the semi-intrusive uncertaint