A comprehensive literature mining and machine learning to decipher and predict effects of concrete materials on concrete corrosion of sewer pipe-Reference-Cited by-同舟云学术

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A comprehensive literature mining and machine learning to decipher and predict effects of concrete materials on concrete corrosion of sewer pipe

Published:2024-05-14 Issue:6 Volume:21 Page:727-744
ISSN:1573-062X
Container-title:Urban Water Journal
language:en
Short-container-title:Urban Water Journal

Author:

Wang Wenhao¹,Cao Jingguo¹,Zeng Ming²,Qiao Yongxiang³

Affiliation:

1. College of Chemical Engineering and Material Science, Tianjin University of Science & Technology, Tianjin, China

2. College of Marine and Environmental Sciences, Tianjin University of Science & Technology, Tianjin, China

3. IKT - Institute for Underground Infrastructure, Gelsenkirchen, Germany

Funder

specific grant from funding agencies in the public, commercial, or not-for-profit sectors

Publisher

Informa UK Limited

Link

https://www.tandfonline.com/doi/pdf/10.1080/1573062X.2024.2352599

Reference68 articles.

1. An Experimental Study on Carbonation of Plain and Blended Cement Concrete;Alhassan Y.;International Journal of Scientific & Technology Research,2017

2. Prediction of compressive strength in plain and blended cement concretes using a hybrid artificial intelligence model

3. Carbonation of hybrid concrete with high blast furnace slag content and its impact on structural steel corrosion

4. Durability and corrosion studies in prestressed concrete made with blended cement

5. Accelerated carbonation and testing of concrete made with fly ash

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