Exponential time propagators for elastodynamics
Paavai Pari, Bikash Kanungo, Vikram Gavini

TL;DR
This paper introduces an efficient elastodynamics simulation method using exponential propagators and Magnus expansion, achieving larger time-steps and significant speed-ups over traditional schemes for both linear and nonlinear systems.
Contribution
It develops a systematically convergent approach employing Magnus expansion and Krylov subspaces, enabling larger time-steps and faster computations in elastodynamics simulations.
Findings
Achieves 10-100x larger time-steps than conventional methods.
Provides 1000x speed-up for linear elastodynamics.
Demonstrates high accuracy on multiple benchmark systems.
Abstract
We propose a computationally efficient and systematically convergent approach for elastodynamics simulations. We recast the second-order dynamical equation of elastodynamics into an equivalent first-order system of coupled equations, so as to express the solution in the form of a Magnus expansion. With any spatial discretization, it entails computing the exponential of a matrix acting upon a vector. We employ an adaptive Krylov subspace approach to inexpensively and and accurately evaluate the action of the exponential matrix on a vector. In particular, we use an apriori error estimate to predict the optimal Kyrlov subspace size required for each time-step size. We show that the Magnus expansion truncated after its first term provides quadratic and superquadratic convergence in the time-step for nonlinear and linear elastodynamics, respectively. We demonstrate the accuracy and…
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Taxonomy
TopicsStructural Health Monitoring Techniques · Numerical methods in inverse problems · Dynamics and Control of Mechanical Systems
