Hyper-reduction methods for accelerating nonlinear finite element simulations: open source implementation and reproducible benchmarks

2026-02-26

AI Summary

This study addresses the lack of systematic evaluation of hyper-reduction methods in nonlinear finite element models, particularly regarding the trade-off between accuracy and computational speedup. Within a unified open-source framework built on libROM, Laghos, and MFEM, the authors present the first reproducible benchmark comparing gappy POD interpolation and empirical quadrature (EQP) across diverse problems—nonlinear diffusion, elasticity, and Lagrangian hydrodynamics—and multiple time integrators. The results demonstrate that EQP achieves lower errors and higher efficiency with fewer integration points for diffusion and elasticity problems. However, in Lagrangian hydrodynamics, EQP incurs higher online costs, while the performance of interpolation-based methods is highly sensitive to the choice of time integration scheme. This work systematically reveals the dependence of hyper-reduction efficacy on both problem physics and numerical discretization choices.

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Abstract

Hyper-reduction methods have gained increasing attention for their potential to accelerate reduced order models for nonlinear systems, yet their comparative accuracy and computational efficiency are not well understood. Motivated by this gap, we evaluate a range of hyper-reduction techniques for nonlinear finite element models across benchmark problems of varying complexity, assessing the inevitable tradeoff between accuracy and speedup. More specifically, we consider interpolation methods based on the gappy proper orthogonal decomposition as well as the empirical quadrature procedure (EQP), and apply them to the hyper-reduction of problems in nonlinear diffusion, nonlinear elasticity and Lagrangian hydrodynamics. Our numerical results are generated using the open source libROM, Laghos and MFEM numerical libraries. Our findings reveal that the comparative performance between hyper-reduction methods depends on both the problem and the choice of time integration method. The EQP method generally achieves lower relative errors than interpolation methods and is more efficient in terms of quadrature point usage, resulting in a lower wall time for the nonlinear diffusion and elasticity problems. However, its online computational cost is observed to be relatively high for Lagrangian hydrodynamics problems. Conversely, interpolation methods exhibit greater variability, especially with respect to the use of different time integration methods in the Lagrangian hydrodynamics problems. The presented results underscore the need for problem specific method selection to balance accuracy and efficiency, while also offering useful guidance for future comparisons and refinements of hyper-reduction techniques.

Problem

• hyper-reduction
• nonlinear finite element
• reduced order models
• computational efficiency
• accuracy tradeoff

Innovation

• hyper-reduction
• empirical quadrature procedure
• gappy POD
• nonlinear finite element
• model order reduction