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.
Authors
- Baolei Wei (ORCID: https://orcid.org/0000-0002-8709-4980)
- Longchun Tao
- Mengxi Ma
- Ning Liu (ORCID: https://orcid.org/0000-0002-8367-6617)
Institutions
- Nanjing University of Science and Technology (CN)
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
- Field-Weighted Citation Impact
- 0.00