Prediction Model-based Multi-objective Optimization for Mix-ratio Design of Recycled Aggregate Concrete  

作　　者：CHEN Tao WU Di YAO Xiaojun 陈涛;姚小俊

机构地区：[1]School of Civil Engineering,Fuzhou University,Fuzhou 350108,China [2]School of Civil and Transportation Engineering,Hebei University of Technology,Tianjin 300401,China

出　　处：《Journal of Wuhan University of Technology(Materials Science)》2024年第6期1507-1517,共11页武汉理工大学学报（材料科学英文版）

基　　金：Funded by the National Natural Science Foundation of China(No.51908183);the Natural Science Foundation of Hebei Province(No.E2023202101)。

摘　　要：The prediction model for mechanical properties of RAC was established through the Bayesian optimization-based Gaussian process regression(BO-GPR)method,where the input variables in BO-GPR model depend on the mix ratio of concrete.Then the compressive strength prediction model,the material cost,and environmental factors were simultaneously considered as objectives,while a multi-objective gray wolf optimization algorithm was developed for finding the optimal mix ratio.A total of 730 RAC datasets were used for training and testing the predication model,while the optimal design method for mix ratio was verified through RAC experiments.The experimental results show that the predicted,testing,and expected compressive strengths are nearly consistent,illustrating the effectiveness of the proposed method.

关 键 词：recycled coarse aggregate mix ratio multi-objective optimization prediction model compressive strength 

分 类 号：TU528[建筑科学—建筑技术科学]