Deep learning-based prediction for time-dependent chloride penetration in concrete exposed to coastal environment-Reference-Cited by-同舟云学术

Deep learning-based prediction for time-dependent chloride penetration in concrete exposed to coastal environment

Published:2023-06 Issue:6 Volume:9 Page:e16869
ISSN:2405-8440
Container-title:Heliyon
language:en
Short-container-title:Heliyon

Author:

Wu Lingjie^ORCID,Wang Weiqiang,Jiang Chenchi

Publisher

Elsevier BV

Subject

Multidisciplinary

Reference40 articles.

1. Experimental and theoretical investigation of chloride ingress into concrete exposed to real marine environment;Bao;Cem. Concr. Compos.,2022

2. Chloride threshold value and initial corrosion time of steel bars in concrete exposed to saline soil environments;Yang;Construct. Build. Mater.,2021

3. Prediction of chloride resistance level of concrete using machine learning for durability and service life assessment of building structures;Taffese;J. Build. Eng.,2022

4. Prediction of chloride permeability of concretes containing ground pozzolans by artificial neural networks;Inthata;Mater. Struct.,2013

5. Predicting rapid chloride permeability of self-consolidating concrete: a comparative study on statistical and neural network models;Ghafoori;Construct. Build. Mater.,2013

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