Zhang Aofei, Li Shuo, Ling Ling, Li Li
State Key Laboratory of Intelligent Manufacturing Equipment and Technology, School of Mechanical Science and Engineering, Huazhong University of Science and Technology, Wuhan 430074, China.
Polymers (Basel). 2025 Mar 14;17(6):769. doi: 10.3390/polym17060769.
The current limitations in predicting mechanical properties arise from an incomplete understanding of surface-induced size effects in variable-density polymer lattice metastructures. Through large-scale, high-fidelity finite element simulations, we identify a novel variable-density surface law governing the surface intrinsic length at the macroscopic scale. Capitalizing on this surface law discovery, we propose a surface-enhanced computational homogenization framework. By incorporating the surface intrinsic length parameters with the variable-density surface law and an offline database constructed through high-throughput numerical simulations, we develop an efficient predictive model capable of online analysis for the mechanical behavior of variable-density polymeric lattice metastructures. This innovative approach preserves critical configuration-dependent surface effects while achieving both efficiency and precision in predicting the macro-scale mechanical performance of such metastructures.
目前在预测力学性能方面的局限性源于对可变密度聚合物晶格亚结构中表面诱导尺寸效应的不完全理解。通过大规模、高保真的有限元模拟，我们确定了一种在宏观尺度上控制表面固有长度的新型可变密度表面定律。基于这一表面定律的发现，我们提出了一种表面增强计算均匀化框架。通过将表面固有长度参数与可变密度表面定律以及通过高通量数值模拟构建的离线数据库相结合，我们开发了一种能够对可变密度聚合物晶格亚结构的力学行为进行在线分析的高效预测模型。这种创新方法在预测此类亚结构的宏观力学性能时，既能保留关键的与构型相关的表面效应，又能实现效率和精度。
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