This work focuses on the conservation of quantities such as Hamiltonians, mass, and
momentum when solution fields of partial differential equations are approximated with …

This work presents a nonintrusive physics-preserving method to learn reduced-order models
(ROMs) of Lagrangian systems, which includes nonlinear wave equations. Existing intrusive …

In this paper, we study the identification problem of strictly passive systems from frequency
response data. We present a simple construction approach based on the Mayo–Antoulas …

Digital twins have become popular for their ability to monitor and optimize a process or a
machine during its lifetime using simulations and sensor data. In this paper, we focus on the …

An essential tool in data-driven modeling of dynamical systems from frequency response
measurements is the barycentric form of the underlying rational transfer function. In this …

In this paper, we consider the problem of finding surrogate models for large-scale second-
order linear time-invariant systems with inhomogeneous initial conditions. For this class of …

Abstract Model order reduction techniques allow the construction of low-dimensional
surrogate models that can accelerate engineering design processes. Often, these …

This paper studies a structure-preserving model reduction problem for large-scale second-
order dynamical systems via the framework of time-domain moment matching. The moments …

Consistent description of the physical world uses mathematics under the assumption of
computability. The development of mathematics equipped the natural sciences with …

Consistent description of the physical world uses mathematics under the assumption of
computability. The development of mathematics equipped the natural sciences with …