Recent progress in computer science and stringent requirements of the design of “greener”
buildings put forwards the research and applications of simulation-based optimization …

A building system is highly nonlinear and commonly includes a variety of parameters
ranging from the architectural design to the building mechanical and energy system. Serving …

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 …

Abstract The Surrogate Modeling Toolbox (SMT) is an open-source Python package that
offers a collection of surrogate modeling methods, sampling techniques, and a set of sample …

Understanding elementary excitations and their couplings in condensed matter systems is
critical for developing better energy-conversion devices. In thermoelectric materials, the heat …

Uncertainty quantification serves a central role for simulation-based analysis of physical,
engineering, and biological applications using mechanistic models. From a broad …

The Dakota (Design Analysis Kit for Optimization and Terascale Applications) toolkit
provides a exible and extensible interface between simulation codes and iterative analysis …

Digital Twins (DTs) are receiving considerable attention from multiple disciplines. Much of
the literature at this time is dedicated to the conceptualization of digital twins, and associated …

Deep neural operators, such as DeepONet, have changed the paradigm in high-
dimensional nonlinear regression, paving the way for significant generalization and speed …

Eighty years ago, it was proposed that solid hydrogen would become metallic at sufficiently
high density. Despite numerous investigations, this transition has not yet been …