Artificial Neural Network Approach to Predict Carbonation Depth in Metakaolin, Brick Powder and Calcined Sediments-Modified Mortars

Artificial Neural Network Approach to Predict Carbonation Depth in Metakaolin, Brick Powder and Calcined Sediments-Modified Mortars

This research uses Artificial Neural Network (ANN) as a soft computing technique to predict the carbonation depth and service life of cementitious materials with low clinker content. For this purpose, different mortars were prepared with 0, 10, 15, 20, 25 and 30% replacement levels of cement by meta...

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Bibliographic Details
Main Authors: Benamar Souheyla, Kameche Zine El Abidine, Mamoune Sidi Mohamed Aissa, Siad Hocine, Houmadi Youcef
Format: Article
Language:English
Published: Sciendo 2023-06-01
Series:Modelling in Civil Environmental Engineering
Subjects:
mortar
carbonation depth prediction
artificial neural network
metakaolin
brick powder
calcined sediments
Online Access:https://doi.org/10.2478/mmce-2023-0009
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https://doi.org/10.2478/mmce-2023-0009

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