Modeling and simulation is transforming modern materials science, becoming an important
tool for the discovery of new materials and material phenomena, for gaining insight into the …

Abstract Basis adaptation in Homogeneous Chaos spaces rely on a suitable rotation of the
underlying Gaussian germ. Several rotations have been proposed in the literature resulting …

Engine design heavily relies on numerical simulation of engine environments, which greatly
accelerates the design iteration and increases efficiency. Nonetheless, for a long time, the …

Model error estimation remains one of the key challenges in uncertainty quantification and
predictive science. For computational models of complex physical systems, model error, also …

An ensemble approach to generating turbulent inflow boundary conditions using the
Synthetic Eddy Method is proposed that improves signal accuracy in recovering target …

Uncertainty quantification is essential in preventing inaccurate predictions of neural
networks. A vanilla neural network for regression does not intrinsically provide explicit …

Compressive sensing is a powerful technique for recovering sparse solutions of
underdetermined linear systems, which is often encountered in uncertainty quantification …

We consider the problem of modeling heterogeneous materials where microscale dynamics
and interactions affect global behavior. In the presence of heterogeneities in material …

To support accidental spill rapid response efforts, oil spill simulations may generally need to
account for uncertainties concerning the nature and properties of the spill, which compound …

Uncertainty is common in the life cycle of an aircraft, and Robust Aerodynamic Optimization
(RAO) that considers uncertainty is important in aircraft design. To avoid the curse of …