应用数学和力学2026，Vol.47Issue(3)：354-366,13.DOI:10.21656/1000-0887.450326
基于SISSO算法的混凝土细观模型压缩行为分析
Analysis of Compressive Behaviors of Concrete Mesoscale Models Based on the SISSO Algorithm
摘要
Abstract
The mechanical properties of concrete under external loads are influenced by its mesoscale compo-nents.Due to their heterogeneity,experimental and numerical methods struggle to reveal the impacts of me-soscale structures on the macroscopic mechanical behaviors of concrete.To effectively predict the peak stress of a 3-phase(aggregate,mortar and voids)mesoscale model of concrete under uniaxial compression,a frame-work for mesoscopic concrete was established with PYTHON and ABAQUS,to generate a dataset of models with varying aggregate volume fractions,porosities and peak compressive stresses.The sure independence screening and sparsifying operator(SISSO)machine learning algorithm,combined with the K-fold cross valida-tion for hyperparameter optimization,was employed to derive a formula describing the effects of the aggregate volume fraction and the porosity on the peak stress.The formula accurately describes the peak stress variation trend,thereby achieving precise predictions and offering physical interpretability.Compared to traditional ma-chine learning algorithms,the SISSO demonstrates advantages of maintaining precision while reducing computa-tion costs and improving interpretability.It overcomes the"black box"limitations of conventional methods,of-fering new insights for multiscale mechanical analyses of composite materials.关键词
混凝土细观模型/单轴压缩/多尺度力学研究/符号回归/峰值应力Key words
mesoscale concrete model/uniaxial compression/multiscale mechanical analysis/symbolic re-gression/peak stress分类
建筑与水利引用本文复制引用
白宇飞,张新宇,亓晓鹏,张煜航,王志勇..基于SISSO算法的混凝土细观模型压缩行为分析[J].应用数学和力学,2026,47(3):354-366,13.基金项目
国家自然科学基金(12272257) （12272257）
山西省基础研究计划(202203021211169) （202203021211169）
