Electromagnetic buffer optimization using multi-response grey hierarchical clustering

Purpose This paper aims to optimize the structural parameters of a newly developed coaxial electromagnetic buffer of artillery that integrates an eddy-current recoil brake and a spring-type recuperator to achieve low-recoil and stable braking performance. Design/methodology/approach The dynamic equations governing the recoil and counter-recoil processes are formulated, followed by a finite element model incorporating the nonlinear hysteresis and temperature-dependent characteristics of NdFeB permanent magnets. Multi-response grey hierarchical clustering is then proposed to identify key structural parameters. Based on the screened design variables, a Kriging surrogate model is constructed, and a hybrid multi-objective optimization strategy combining the multi-island genetic algorithm and sequential quadratic programming is developed to determine the optimal structural design. Findings The finite element model achieves high prediction accuracy, with dynamic response errors below 5% under three charge conditions. The optimized design reduces the peak recoil resistance from 39.81 kN to 34.68 kN, representing a 12.89% reduction, while satisfying the prescribed recoil displacement constraint. Practical implications The proposed electromagnetic buffer provides an effective alternative to conventional hydraulic recoil systems. The physically validated finite element model and surrogate-based optimization framework can support the structural design and performance improvement of recoil mechanisms for artillery systems. Originality/value This work proposes a multi-response grey hierarchical clustering method for design-variable sensitivity analysis, enabling comprehensive variable screening by jointly accounting for their influence across multiple performance responses.

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Publication Details

Journal
Grey Systems Theory and Application
Published
2026-10-16
DOI
https://doi.org/10.1108/gs-05-2026-0132
Primary Topic
Optimal Experimental Design Methods
Type
article
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article

Electromagnetic buffer optimization using multi-response grey hierarchical clustering

Baolei Wei, Longchun Tao, Mengxi Ma, Ning Liu
Grey Systems Theory and Application
Optimal Experimental Design Methods
article

Electromagnetic buffer optimization using multi-response grey hierarchical clustering

Baolei Wei, Longchun Tao, Mengxi Ma, Ning Liu
article en

Abstract

Purpose This paper aims to optimize the structural parameters of a newly developed coaxial electromagnetic buffer of artillery that integrates an eddy-current recoil brake and a spring-type recuperator to achieve low-recoil and stable braking performance. Design/methodology/approach The dynamic equations governing the recoil and counter-recoil processes are formulated, followed by a finite element model incorporating the nonlinear hysteresis and temperature-dependent characteristics of NdFeB permanent magnets. Multi-response grey hierarchical clustering is then proposed to identify key structural parameters. Based on the screened design variables, a Kriging surrogate model is constructed, and a hybrid multi-objective optimization strategy combining the multi-island genetic algorithm and sequential quadratic programming is developed to determine the optimal structural design. Findings The finite element model achieves high prediction accuracy, with dynamic response errors below 5% under three charge conditions. The optimized design reduces the peak recoil resistance from 39.81 kN to 34.68 kN, representing a 12.89% reduction, while satisfying the prescribed recoil displacement constraint. Practical implications The proposed electromagnetic buffer provides an effective alternative to conventional hydraulic recoil systems. The physically validated finite element model and surrogate-based optimization framework can support the structural design and performance improvement of recoil mechanisms for artillery systems. Originality/value This work proposes a multi-response grey hierarchical clustering method for design-variable sensitivity analysis, enabling comprehensive variable screening by jointly accounting for their influence across multiple performance responses.

Grey Systems Theory and Application
Nanjing University of Science and Technology (CN)
Openalex Percentile: Top 10%
Optimal Experimental Design Methods
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