Machine learning-based modelling and analysis of carbonation depth of recycled aggregate concrete

Machine learning-based modelling and analysis of carbonation depth of recycled aggregate concrete

This paper used machine learning to model the prediction of carbonation depth and the analysis of feature parameters for recycled aggregate concrete (RAC). Specifically, a database containing 579 sets of RAC carbonation test data was developed. Twelve parameters representing material characteristics...

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Bibliographic Details
Main Authors: Xuyong Chen, Xuan Liu, Shukai Cheng, Xiaoya Bian, Xixuan Bai, Xin Zheng, Xiong Xu, Zhifeng Xu
Format: Article
Language:English
Published: Elsevier 2025-07-01
Series:Case Studies in Construction Materials
Subjects:
Recycled aggregate concrete
Carbonation depth
Machine learning
SHAP analysis
Online Access:http://www.sciencedirect.com/science/article/pii/S2214509524013147
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