Self-consistent clustering analysis for homogenisation of heterogeneous plates

Menglei Li; Haolin Li; Bing Wang

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arXiv · 2508.20446

Self-consistent clustering analysis for homogenisation of heterogeneous plates

Menglei Li·Haolin Li·Bing Wang

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Abstract

This work introduces a reduced-order model for plate structures with periodic micro-structures by coupling self-consistent clustering analysis (SCA) with the Lippmann-Schwinger equation, enabling rapid multiscale homogenisation of heterogeneous plates. A plate-specific SCA scheme is derived for the first time and features two key elements: (i) an offline-online strategy that combines Green's functions with k-means data compression, and (ii) an online self-consistent update that exploits the weak sensitivity of the reference medium. The framework handles both linear and nonlinear problems in classical plate theory and first-order shear deformation theory, and its performance is verified on linear isotropic perforated plates and woven composites, as well as on non-linear elasto-plastic perforated plates and woven composites with damage. Across all cases the proposed model matches the accuracy of FFT-based direct numerical simulation while reducing computational cost by over an order of magnitude.

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Menglei Li, Haolin Li, Bing Wang. 2025-08-28. Self-consistent clustering analysis for homogenisation of heterogeneous plates. https://arxiv.org/abs/2508.20446

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