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

Identifiability is a fundamental concept in parameter estimation, and therefore key to the
large majority of environmental modeling applications. Parameter identifiability analysis …

Nearly all model-reduction techniques project the governing equations onto a linear
subspace of the original state space. Such subspaces are typically computed using methods …

Traditional linear subspace reduced order models (LS-ROMs) are able to accelerate
physical simulations in which the intrinsic solution space falls into a subspace with a small …

A reduced basis method based on a physics-informed machine learning framework is
developed for efficient reduced-order modeling of parametrized partial differential equations …

Numerical simulation of parametrized differential equations is of crucial importance in the
study of real-world phenomena in applied science and engineering. Computational methods …

飞机结构安全性设计思想经历了从静强度设计, 安全寿命设计, 损伤容限与耐久性设计到单机
追踪的演变, 未来有进一步向结构数字孪生的方向发展的趋势. 飞机结构数字孪生是数字线程 …

Parametric model order reduction using reduced basis methods can be an effective tool for
obtaining quickly solvable reduced order models of parametrized partial differential equation …

This work presents a model reduction approach for problems with coherent structures that
propagate over time, such as convection-dominated flows and wave-type phenomena …

Closure modeling based on the Mori-Zwanzig formalism has proven effective to improve the
stability and accuracy of projection-based model order reduction. However, closure models …