Prediction of alkali-silica reaction expansion of concrete using explainable machine learning methods

Prediction of alkali-silica reaction expansion of concrete using explainable machine learning methods

Abstract Traditionally, ASR expansion is determined using experimental and finite element method (FEM) based numerical modelling. However, these methods are time-consuming and computationally costly, which makes ASR prediction challenging. Machine learning (ML) techniques can serve as effective alte...

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Bibliographic Details
Main Authors: Yasitha Alahakoon, Hirushan Sajindra, Ashen Krishantha, Janaka Alawatugoda, Imesh U. Ekanayake, Upaka Rathnayake
Format: Article
Language:English
Published: Springer 2025-04-01
Series:Discover Applied Sciences
Subjects:
Alkali silica reaction expansion
Machine learning
XGBoost
Random forest
Online Access:https://doi.org/10.1007/s42452-025-06880-y
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https://doi.org/10.1007/s42452-025-06880-y

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