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Open access Jul 2026

Integrated Prediction Model for Normal and Recycled Aggregate Concrete Strength Using Ensemble Learning Techniques

Recycled aggregate concrete (RAC) is a sustainable alternative construction material to reduce natural resource exploitation and manage construction and demolition waste. However, predicting the mechanical performance of RAC remains a challenge due to the high variability of recycled aggregate properties. The purpose o...

Suji’at, Eko Wahyu Abryandoko, Ocha Silvia Kencana et al. · 0 citations
Open access Jul 2026

TabPFN-Based Prediction of Concrete Compressive Strength

The use of supplementary cementitious materials such as fly ash can reduce environmental impacts and improve the sustainability of concrete construction. However, the nonlinear interactions among mixture design parameters make accurate prediction of concrete compressive strength challenging. In this study, TabPFN, a pr...

Zhihao Zhao, Jinjin Wang, Guohui Ma et al. · 0 citations
Open access Aug 2026

Optuna ML Framework for SCBA Concrete Strength

The cement industry plays a crucial role in global CO2 emissions. As demand for cement continues to rise, innovative solutions are required to mitigate its environmental impact. Over a decade ago, the Paris Agreement (2015) established clear targets for reducing global carbon emissions. In response, the construction in...

Isaac Ajibola Fakoya, A. B. Folorunsho, Seungwon Kim et al. · 0 citations
Preprint Aug 2026

Interpretable machine learning for predicting splitting strength of asphalt concrete: insights from SHAP analysis

An interpretable machine-learning framework for predicting the splitting strength of asphalt concrete and supporting data-driven mixture design and a GUI platform integrating prediction and SHAP-based explanation was developed to improve the accessibility and practical applicability of the proposed framework.

J. Xing, Xiao Tan, Dong-Zhan Jin et al. · 0 citations
Open access Aug 2026

PERFORMANCE EVALUATION OF SLAG MODIFIED CONCRETE USING MACHINE LEARNING TECHNIQUES

Global demand for sustainable construction materials and concerns about environmental pollution from by-products of manufacturing industries have intensified research for viable alternatives to aggregates in concrete production. This research investigated steel slag aggregate (ssa) as a partial replacement for coarse a...

Akintayo Adeniji, W. Kupolati, E. Burger et al. · 0 citations
Open access Aug 2026

Novel interpretable machine learning models for predicting compressive strength of nano-silica concrete

This study provides a robust, interpretable, and generalizable ML framework for optimizing nano-silica concrete mix design and highlights the strong potential of ML, particularly ensemble models combined with explainable AI techniques, to improve prediction reliability, reduce trial-and-error experimentation, and suppo...

Yousif J. Bas, Jamal I. Kakrasul, Kamaran S. Ismail et al. · 0 citations

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