Numerical simulation of large-scale dynamical systems plays a fundamental role in studying
a wide range of complex physical phenomena; however, the inherent large-scale nature of …

Aerodynamic modeling plays an important role in multiphysics and design problems, in
addition to experiment and numerical simulation, due to its low-dimensional representation …

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

This article addresses the inference of physics models from data, from the perspectives of
inverse problems and model reduction. These fields develop formulations that integrate data …

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 …

SUMMARY A new approach for the dimensional reduction via projection of nonlinear
computational models based on the concept of local reduced‐order bases is presented. It is …

We address the solution of large-scale statistical inverse problems in the framework of
Bayesian inference. The Markov chain Monte Carlo (MCMC) method is the most popular …

Surrogate-based optimization has been used in aerodynamic shape optimization, but it has
been limited due to the curse of dimensionality. Although a large number of variables are …

Active flutter suppression, which is a part of the group of flight vehicle technologies known as
active controls, is an important contributor to the effective solution of aeroelastic instability …

The computational efficiency of a typical, projection‐based, nonlinear model reduction
method hinges on the efficient approximation, for explicit computations, of the scalar …