Abstract The Circular Economy concept aims to ensure environmental sustainability through
the recovery of durable products that have reached the end of their useable life. Recovery …

Tasks such as analysis, design optimization, and uncertainty quantification can be
computationally expensive. Surrogate modeling is often the tool of choice for reducing the …

Materials design calls for an optimal exploration and exploitation of the process-structure-
property (PSP) relationships to produce materials with targeted properties. Recently, we …

Materials design calls for the (inverse) exploitation of Process-Structure-Property (PSP)
relationships to produce materials with targeted properties. Unfortunately, most materials …

Sampling efficiency is important for simulation-based design optimization. While Bayesian
optimization (BO) has been successfully applied in engineering problems, the cost …

Bayesian optimization is a sample efficient sequential global optimization method for black-
box, expensive and multi-extremal functions. It generates, and keeps updated, a …

Searching for accurate machine and deep learning models is a computationally expensive
and awfully energivorous process. A strategy which has been recently gaining importance to …

This paper presents an effective sequence interval and correlation inverse strategy for the
uncertain inverse problem, aiming to identify the uncertainties and non-probabilistic …

This paper develops mfEGRA, a multifidelity active learning method using data-driven
adaptively refined surrogates for failure boundary location in reliability analysis. This work …

Multiobjective optimization is often a difficult task owing to the need to balance competing
objectives. A typical approach to handling this is to estimate a Pareto frontier in objective …