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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| Main Authors: | Yasitha Alahakoon, Hirushan Sajindra, Ashen Krishantha, Janaka Alawatugoda, Imesh U. Ekanayake, Upaka Rathnayake |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Springer
2025-04-01
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| Series: | Discover Applied Sciences |
| Subjects: | |
| Online Access: | https://doi.org/10.1007/s42452-025-06880-y |
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