An uncertainty quantification and validation framework is presented to account for both
aleatory and epistemic uncertainties in stochastic simulations of turbine engine components …

This paper investigates model validation under a variety of different data scenarios and
clarifies how different validation metrics may be appropriate for different scenarios. In the …

This paper presents a methodology to propagate the uncertainties in the manufacturing
process parameters to bulk material properties through multiscale modeling. Randomness …

In this paper, two new sampling strategies are proposed to estimate the Morris' screening
sensitivity measure and its improved version. The two new sampling strategies, which …

With a great capability of dealing with epistemic uncertainty, evidence theory has been
utilised to conduct reliability analysis for engineering systems recently. Unfortunately, the …

Aleatory uncertainty and epistemic uncertainty generally exist simultaneously in engineering
design. A variety of studies, including, eg, the Monte Carlo simulation, orthogonal …

This paper develops a methodology to assess the validity of computational models when
some quantities may be affected by epistemic uncertainty. Three types of epistemic …

In engineering design, uncertainty is inevitable and can cause a significant deviation in the
performance of a system. Uncertainty in input parameters can be categorized into two …

An well-established tool for probabilistic analysis is the Monte Carlo simulation (MCS),
which can be used to gain insight into an unknown system behavior. The variability of the …

This paper focuses on sensitivity analysis of results from computer models in which both
epistemic and aleatory uncertainties are present. Sensitivity is defined in the sense of …