ArticleMaterials (Basel, Switzerland)2025
A New Mesoscopic Parameter Inverse Analysis Method of Hydraulic Concrete Based on the SVR-HGWO Intelligent Algorithm.
Article in Materials (Basel, Switzerland), 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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1 citing paper in PubMed.
- Advanced Experimental Technology, Theory and Numerical Methods in Geomaterials and Concrete Materials.Materials (Basel, Switzerland) · 2026Article
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Abstract
Accurate identification of mesoscopic parameters is critical for understanding the cracking and failure mechanisms of hydraulic concrete and for improving the reliability of numerical simulations. Traditional trial-and-error methods for parameter calibration are inefficient and often lack robustness. To address this issue, this study proposes a novel inversion method combining Support Vector Regression (SVR) with a Hybrid Grey Wolf Optimization (HGWO) algorithm. First, a mesoscopic simulation dataset of three-point bending (TPB) tests was constructed using 3D numerical models with varying mesoscopic parameters. Then, an SVR-based surrogate model was trained to learn the nonlinear mapping between mesoscopic parameters and load-CMOD (Crack Mouth Opening Displacement) curves. The HGWO algorithm was employed to optimize the SVR hyperparameters (penalty factor
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