This paper reviews the mathematical foundation of the importance sampling technique and
discusses two general classes of methods to construct the importance sampling density (or …

In many situations across computational science and engineering, multiple computational
models are available that describe a system of interest. These different models have varying …

Full scale aerodynamic wind tunnel testing, numerical simulation of high dimensional (full-
order) aerodynamic models or flight testing are some of the fundamental but complex steps …

This article provides an overview of multi-fidelity modeling trends. Fidelity in modeling refers
to the level of detail and accuracy provided by a predictive model or simulation. Generally …

The present paper describes a method to enhance the capability of, or to broaden the scope
of computational mechanics by using deep learning, which is one of the machine learning …

Multifidelity surrogates are essential in cases where it is not affordable to have more than a
few high-fidelity samples, but it is affordable to have as many low-fidelity samples as …

Uncertainty quantification (UQ) includes the characterization, integration, and propagation of
uncertainties that result from stochastic variations and a lack of knowledge or data in the …

This work presents an optimal model management strategy that exploits multifidelity
surrogate models to accelerate the estimation of statistics of outputs of computationally …

Abstract Design optimization of structural and multidisciplinary systems under uncertainty
has been an active area of research due to its evident advantages over deterministic design …

Surrogate models are popular tool to approximate the functional relationship of expensive
simulation models in multiple scientific and engineering disciplines. Successful use of …