A Two-Step Sequential Hyper-Reduction Method for Efficient Concurrent Nonlinear FE2 Analyses

In this paper, we propose a two-step sequential hyper-reduction method to significantly enhance computational efficiency for both macro- and micro-level analyses in concurrent nonlinear FE2 multiscale simulations. In general, one of the major computational burdens of nonlinear FE2 problems is the repetitive micro-level analysis, which must be performed at all integration points of the macroscopic structure. We propose adopting the discrete empirical interpolation method (DEIM) for both macroscopic and microscopic problems, achieving a significant reduction in the number of integration points in both models. The proposed two-step sequential framework aligns with reduced-order modeling, enabling an efficient multiscale procedure for concurrent nonlinear FE2 analysis in the online stage. We verified the accuracy and efficiency of FE2 analysis using the proposed method through a simple example.

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Publication Details

Journal
Mathematics
Published
2025-05-27
DOI
https://doi.org/10.3390/math13111790
Citations
1
Primary Topic
Advanced Fiber Optic Sensors
Type
article
Field-Weighted Citation Impact
0.73

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article

A Two-Step Sequential Hyper-Reduction Method for Efficient Concurrent Nonlinear FE2 Analyses

Jaehun Lee, Yujin So
1 citations
Mathematics
Advanced Fiber Optic Sensors
0.73
article

A Two-Step Sequential Hyper-Reduction Method for Efficient Concurrent Nonlinear FE2 Analyses

Jaehun Lee, Yujin So
article en
1 citations

Abstract

In this paper, we propose a two-step sequential hyper-reduction method to significantly enhance computational efficiency for both macro- and micro-level analyses in concurrent nonlinear FE2 multiscale simulations. In general, one of the major computational burdens of nonlinear FE2 problems is the repetitive micro-level analysis, which must be performed at all integration points of the macroscopic structure. We propose adopting the discrete empirical interpolation method (DEIM) for both macroscopic and microscopic problems, achieving a significant reduction in the number of integration points in both models. The proposed two-step sequential framework aligns with reduced-order modeling, enabling an efficient multiscale procedure for concurrent nonlinear FE2 analysis in the online stage. We verified the accuracy and efficiency of FE2 analysis using the proposed method through a simple example.

MathematicsVol. 13(11)
Dongguk University (KR)
National Research Foundation, National Research Foundation of Korea, Ministry of Education, Science and Technology
Openalex Percentile: Top 28%
Advanced Fiber Optic Sensors
0.73
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A Two-Step Sequential Hyper-Reduction Method for Efficient Concurrent Nonlinear FE2 Analyses — Jaehun Lee, Yujin So · Mathematics (2025) | TGRS Research Map | TGRS