Application of machine learning in predicting mechanical properties of sandcrete blocks made from quarry dust:a review  

作　　者：John Igeimokhia Braimah Wasiu Olabamiji Ajagbe Kolawole Adisa Olonade 

机构地区：[1]Department of Civil Engineering,University of Ibadan,Ibadan,Nigeria [2]Department of Civil and Environmental Engineering,University of Lagos,Akoka,Nigeria

出　　处：《AI in Civil Engineering》2024年第1期192-210,共19页智能建造(英文)

摘　　要：Quarry dust,conventionally considered waste,has emerged as a potential solution for sustainable construction materials.This paper comprehensively review the mechanical properties of blocks manufactured from quarry dust,with a particular focus on the transformative role of machine learning(ML)in predicting and optimizing these properties.By systematically reviewing existing literature and case studies,this paper evaluates the efficacy of ML methodologies,addressing challenges related to data quality,feature selection,and model optimization.It underscores how ML can enhance accuracy in predicting mechanical properties,providing a valuable tool for engineers and researchers to optimize the design and composition of blocks made from quarry dust.This synthesis of mechanical properties and ML applications contributes to advancing sustainable construction practices,offering insights into the future integration of technology for predictive modeling in material science.

关 键 词：Quarry dust Blocks production Machine learning Sustainable construction 

分 类 号：TG1[金属学及工艺—金属学]