The concept of multiscale modelling has emerged over the last few decades to describe
procedures that seek to simulate continuum-scale behaviour using information gleaned from …

Global sensitivity analysis (SA) aims at quantifying the respective effects of input random
variables (or combinations thereof) onto the variance of the response of a physical or …

The quantification of uncertainty in computational fluid dynamics (CFD) predictions is both a
significant challenge and an important goal. Probabilistic uncertainty quantification (UQ) …

In this paper, the computation of Sobol's sensitivity indices from the polynomial chaos
expansion of a model output involving uncertain inputs is investigated. It is shown that when …

Since real petroleum fuels are composed of a huge variety of hydrocarbon components,
surrogate mixtures of various hydrocarbon fuels are typically employed in computational …

The optimal selection of experimental conditions is essential to maximizing the value of data
for inference and prediction, particularly in situations where experiments are time …

Two critical steps towards soot production in combustors are the decomposition of the fuel
and the subsequent formation of aromatic hydrocarbons with one to three benzenoid rings …

The current interest in the combustion chemistry of hydrocarbon fuels, including the various
alcohol and biodiesel compounds, motivates this review of the methods and application of …

This paper gives an overview of the use of polynomial chaos (PC) expansions to represent
stochastic processes in numerical simulations. Several methods are presented for …

We present a reformulation of the Bayesian approach to inverse problems, that seeks to
accelerate Bayesian inference by using polynomial chaos (PC) expansions to represent …