Developing machine learning frameworks to predict mechanical properties of ultra-high performance concrete mixed with various industrial byproducts

Developing machine learning frameworks to predict mechanical properties of ultra-high performance concrete mixed with various industrial byproducts

Abstract This research investigates the predictive modeling of ultra-high-performance concrete (UHPC) incorporating industrial byproducts, focusing on compressive strength (Fc), flexural strength (Ff), workability (Slump), and porosity. Various machine learning models, including Kstar, M5Rules, Elas...

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Bibliographic Details
Main Authors: Kennedy C. Onyelowe, Shadi Hanandeh, Nestor Ulloa, Ruth Barba-Vera, Arif Ali Baig Moghal, Ahmed M. Ebid, Krishna Prakash Arunachalam, Ateekh Ur Rehman
Format: Article
Language:English
Published: Nature Portfolio 2025-07-01
Series:Scientific Reports
Subjects:
Structural concrete
Ultra-high-performance
Compressive strength
Flexural strength
Slump
Porosity
Online Access:https://doi.org/10.1038/s41598-025-08780-y
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