Advances in manufacturing process technology are key ensembles for the production of
integrated circuits in the sub-micrometer region. It is of paramount importance to assess the …

Uncertainty and sensitivity analysis (UA/SA) aid in assessing whether model complexity is
warranted and under what conditions. To support these analyses a variety of software tools …

Physics-informed neural networks (PINNs) have recently emerged as an alternative way of
numerically solving partial differential equations (PDEs) without the need of building …

We present a regression technique for data-driven problems based on polynomial chaos
expansion (PCE). PCE is a popular technique in the field of uncertainty quantification (UQ) …

Global sensitivity analysis (GSA), particularly for Sobol index, is a powerful tool to quantify
the variation of model response sourced from the uncertainty of input variables over the …

In reliability engineering, estimating the failure probability of a system is one of the most
challenging tasks. Since many applied engineering tasks are computationally expensive, it …

In view of increasing application of sensitivity assessment (SA) to environmental simulation
models, a relatively short, informal introduction to aims and methods of SA is given. Their …

In this paper, the uncertainty quantification and sensitivity analysis of a mathematical model
of the SARS-CoV-2 virus transmission dynamics with mass vaccination strategy has been …

In this paper, a framework for uncertainty quantification (UQ) and global sensitivity analysis
(GSA) of composite wind turbine blades is presented. Because of the presence of …

Constructing accurate and generalizable approximators (surrogate models) for complex
physico-chemical processes exhibiting highly non-smooth dynamics is challenging. The …