Development of Crack Width Prediction Models for RC Beam-Column Joint Subjected to Lateral Cyclic Loading Using Machine Learning

Development of Crack Width Prediction Models for RC Beam-Column Joint Subjected to Lateral Cyclic Loading Using Machine Learning

In recent years, researchers have investigated the development of artificial neural networks (ANN) and finite element models (FEM) for predicting crack propagation in reinforced concrete (RC) members. However, most of the developed prediction models have been limited to focus on individual isolated...

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Bibliographic Details
Main Authors: Reventheran Ganasan, Chee Ghuan Tan, Zainah Ibrahim, Fadzli Mohamed Nazri, Muhammad M. Sherif, Ahmed El-Shafie
Format: Article
Language:English
Published: MDPI AG 2021-08-01
Series:Applied Sciences
Subjects:
crack widths
RC beam-column joint
drift ratio
machine learning
prediction models
Online Access:https://www.mdpi.com/2076-3417/11/16/7700

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