Experimental and machine learning prediction of compressive strength of chemically activated RHA based RAC using SHAP and PDP analysis.

Ahmed A Alawi Al-Naghi, Tariq Ali, Inamullah Inam, Muhammad Zeeshan Qureshi, Muhammad Sarmad Mahmood, Nabil Ben Kahla, Nejib Ghazouani

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Article in Scientific reports, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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5 · Who and what money

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7 authors.

Ahmed A Alawi Al-NaghiCivil Engineering Department, University of Ha'il, 55476, Ha'il, Saudi Arabia. a.alnaghi@uoh.edu.sa.

Tariq AliDepartment of Civil Engineering, Swedish College of Engineering and Technology, Wah, 47080, Pakistan.

Inamullah InamDepartment of Civil Engineering, Engineering Faculty, Laghman University, Mehtarlam, Afghanistan. inam.azizi@gmail.com.

Muhammad Zeeshan QureshiDepartment of Civil Engineering, University of Engineering and Technology, Taxila, Pakistan. qureshizeeshan746@gmail.com.

Muhammad Sarmad MahmoodDepartment of Civil Engineering, Swedish College of Engineering and Technology, Wah, 47080, Pakistan.

Nabil Ben KahlaDepartment of Civil Engineering, College of Engineering, King Khalid University, PO Box 394, 61411, Abha, Kingdom of Saudi Arabia.

Nejib GhazouaniMining Research Center, Northern Border University, 73213, Arar, Saudi Arabia.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The increasing demand for sustainable construction materials necessitates the effective reuse of industrial and agricultural waste in high-performance concrete (HPC). However, challenges such as strength loss due to recycled concrete aggregates (RCA) and variable performance of supplementary cementitious materials hinder widespread adoption. This study addresses these challenges by investigating the synergistic effect of chemically activated rice husk ash (RHA), RCA (0-100%), and foundry sand on the compressive strength and durability of HPC. Six experimental groups were prepared: one with inactivated RHA and five with chemically activated RHA using 3.5% sodium sulfate (Na

Indexed as

Machine learningMechanical and durability propertiesRecycled concrete aggregateRice husk ashSilica fume

Identifiers

PMID41345473

DOI10.1038/s41598-025-25592-2

PMCPMC12678409

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