Machine learning guided design of microencapsulated phase change materials-incorporated concretes for enhanced freeze-thaw durability-Reference-Cited by-同舟云学术

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Machine learning guided design of microencapsulated phase change materials-incorporated concretes for enhanced freeze-thaw durability

Published:2023-07 Issue: Volume:140 Page:105090
ISSN:0958-9465
Container-title:Cement and Concrete Composites
language:en
Short-container-title:Cement and Concrete Composites

Author:

Li He-Wen-Xuan^ORCID,Lyngdoh Gideon,Krishnan N.M. Anoop,Das Sumanta^ORCID

Funder

University of Rhode Island

US Department of Transportation University Transportation Centers Program

U.S. Department of Transportation

Publisher

Elsevier BV

Subject

General Materials Science,Building and Construction

Reference69 articles.

1. Evaluation of freeze-thaw damage on concrete material and prestressed concrete specimens;Qin;Construct. Build. Mater.,2016

2. Increasing the service life of bridge decks by incorporating phase-change materials to reduce freeze-thaw cycles;Sakulich;J. Mater. Civ. Eng.,2012

3. Deterioration of concrete under the coupling effects of freeze–thaw cycles and other actions: a review;Wang;Construct. Build. Mater.,2022

4. Steel reinforcement corrosion in concrete under combined actions: the role of freeze-thaw cycles, chloride ingress, and surface impregnation;Zhang;Construct. Build. Mater.,2017

Cited by 8 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Computationally effective machine learning approach for modular thermal energy storage design;Applied Energy;2025-01

2. Elucidating the evolution of pore structure, microstructural damage, and micromechanical response in cement pastes containing microencapsulated phase change materials under freeze-thaw conditions;Cement and Concrete Composites;2024-11

3. Frost Resistance Differences of Concrete in Frequent Natural Freeze–Thaw versus Standard Rapid Method;Buildings;2024-08-12

4. Explainable artificial intelligence framework for FRP composites design;Composite Structures;2024-08

5. Machine learning-guided optimization of coarse aggregate mix proportion based on CO2 intensity index;Journal of CO2 Utilization;2024-07

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