Sensitivity analysis (SA) is en route to becoming an integral part of mathematical modeling.
The tremendous potential benefits of SA are, however, yet to be fully realized, both for …

In the framework of uncertainty treatment in numerical simulation, Global sensitivity analysis
(GSA) aims at determining (qualitatively or quantitatively) how the variability of the uncertain …

In many fields, such as environmental risk assessment, agronomic system behavior,
aerospace engineering, and nuclear safety, mathematical models turned into computer code …

Sensitivity analysis and reliability assessment are two important aspects of structural and
system safety. Epistemic uncertainty with respect to probabilistic model of input parameters …

This paper presents an extended polynomial chaos formalism for epistemic uncertainties
and a new framework for evaluating sensitivities and variations of output probability density …

Reliability assessment in presence of epistemic uncertainty leads to consider the failure
probability as a quantity depending on the state of knowledge about uncertain input …

For structural systems with both epistemic and aleatory uncertainties, the effect of epistemic
uncertainty on failure probability is measured by the variance based sensitivity analysis …

The failure probability-based global sensitivity is proposed to evaluate the influence of input
variables on the failure probability. But for the problem that the distribution parameters of …

Sensitivity analysis (SA) of a numerical model, for instance simulating physical phenomena,
is useful to quantify the influence of the inputs on the model responses. This paper proposes …

This paper aims at presenting sensitivity estimators of a rare event probability in the context
of uncertain distribution parameters (which are often not known precisely or poorly estimated …