AI Chat Paper
Note: Please note that the following content is generated by AMiner AI. SciOpen does not take any responsibility related to this content.
{{lang === 'zh_CN' ? '文章概述' : 'Summary'}}
{{lang === 'en_US' ? '中' : 'Eng'}}
Chat more with AI
PDF (987 KB)
Collect
Submit Manuscript AI Chat Paper
Show Outline
Outline
Show full outline
Hide outline
Outline
Show full outline
Hide outline
Review

Development on Machine Learning for Durability Prediction of Concrete Materials

Xiao LIU1,2( )Simai WANG1,2Lei LU1,2Meizhu CHEN3Yue ZHAI1,2Suping CUI1,2
National Engineering Laboratory for Industrial Big-Data Application Technology, Faculty of Materials and Manufacturing, Beijing University of Technology, Beijing 100124, China
Key Laboratory of Advanced Functional Materials of Ministry of Education, Faculty of Materials and Manufacturing, Beijing University of Technology, Beijing 100124, China
State Key Laboratory of Silicate Materials for Architectures, Wuhan University of Technology, Wuhan 430070, China
Show Author Information

Abstract

The durability evaluation of concrete materials based on the related experiments has a low economic efficiency ratio. The prediction accuracy of the conventional empirical formula for durability is restricted and the proportions of concrete mix cannot be calculated according to the performance. It is thus necessary to develop a novel and efficient material quality control and performance prediction tool. In this review, the process of building machine learning models was stated. The basic working flow and advantages of common algorithms, as well as the durability index prediction algorithms based on machine learning were summarized. Its application effects and development direction were discussed. This review can provide a basis for the in-depth development and application of machine learning technology in the field of concrete.

CLC number: TP181; TQ178 Document code: A Article ID: 0454-5648(2023)08-2062-12

References

【1】
【1】
 
 
Journal of the Chinese Ceramic Society
Pages 2062-2073

{{item.num}}

Comments on this article

Go to comment

< Back to all reports

Review Status: {{reviewData.commendedNum}} Commended , {{reviewData.revisionRequiredNum}} Revision Required , {{reviewData.notCommendedNum}} Not Commended Under Peer Review

Review Comment

Close
Close
Cite this article:
LIU X, WANG S, LU L, et al. Development on Machine Learning for Durability Prediction of Concrete Materials. Journal of the Chinese Ceramic Society, 2023, 51(8): 2062-2073. https://doi.org/10.14062/j.issn.0454-5648.20220973

1084

Views

13

Downloads

0

Crossref

0

Web of Science

17

Scopus

Received: 11 November 2022
Revised: 10 December 2022
Published: 05 May 2023
© 2023 Journal of the Chinese Ceramic Society