Machine learning approach for investigating chloride diffusion coefficient of concrete containing supplementary cementitious materials

Van Quan Tran

doi:10.1016/j.conbuildmat.2022.127103

Machine learning approach for investigating chloride diffusion coefficient of concrete containing supplementary cementitious materials — Van Quan Tran (2022) | RDL Network

Back

Home
Publications
Machine learning approach for investigating chloride diffusion coefficient of concrete containing supplementary cementitious materials

Shared by

Van Quan Tran

Machine learning approach for investigating chloride diffusion coefficient of concrete containing supplementary cementitious materials

Article 2022 en

Authors

VT
Van Quan Tran

Discussion(0)

No comments yet. Be the first to comment.

Related publications

Article2023

Understanding Chloride Diffusion Coefficient in Cementitious Materials

Zhiyuan Xu, Ye Guang

Article2018

A model for predicting the relative chloride diffusion coefficient in unsaturated cementitious materials

Yong Zhang, Ye Guang

Publication Info

DOI: 10.1016/j.conbuildmat.2022.127103
Year: 2022
Published: —
Language: en

Article Details

Volume: 328
Link Of The Paper: https://doi.org/10.1016/j.conbuildmat.2022.127103

Timeline

Created:June 19, 2026

Article2019

Influence of Pore Structure on Relative Chloride Diffusion Coefficient in Unsaturated Cementitious Materials

Yong Zhang, Ye Guang

Article2022

Machine learning approach in investigating carbonation depth of concrete containing Fly ash

Van Quan Tran, Hai‐Van Thi, Quynh Trang To, May Huu Nguyen

Article2022

Using machine learning techniques for predicting autogenous shrinkage of concrete incorporating superabsorbent polymers and supplementary cementitious materials

Benoît Hilloulin, Van Quan Tran