Integrated Experimental and Data-Driven Approach to Strength Prediction of Mortars Incorporating Thermally Activated Construction Waste Powder

Abstract This study investigated the feasibility of waste construction powder (WCP), a by-product generated from construction waste recycling plants, as a partial replacement for Portland cement through thermal activation. Mortar specimens were prepared using thermally activated WCP at 600 °C and 800 °C, replacing cement at rates of 6%, 13%, and 20%. The flowability, compressive strength, and flexural strength were evaluated. The results showed that mortar with WCP activated at 800 °C met the KS L 5201 industrial standard even at a 20% replacement ratio, achieving up to 21% and 6% increases in compressive strength and flexural strength, respectively. In addition, a machine learning (ML) model based on the light gradient boosting (LGB) algorithm was developed using 405 literature-derived data entries to predict the compressive strength of cementitious composites incorporating thermally activated WCP. The predictive performance was validated against experimental results, achieving strong correlation with the measured data ( R 2 = 0.813), and yielding an RMSE of 3.044 MPa, MAE of 2.507 MPa, and SMAPE of 5.675%. More than 90% of the predictions fell within a ± 10% error margin. These findings demonstrate the practical applicability of the proposed ML model for strength prediction of WCP-based cementitious materials, as well as the technical feasibility of thermally activated WCP as cement replacement.

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Publication Details

Journal
International Journal of Concrete Structures and Materials
Published
2026-03-12
DOI
https://doi.org/10.1186/s40069-025-00871-4
Primary Topic
Recycled Aggregate Concrete Performance
Type
article
Field-Weighted Citation Impact
0.00

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article

Integrated Experimental and Data-Driven Approach to Strength Prediction of Mortars Incorporating Thermally Activated Construction Waste Powder

Donwoo Lee, Hyeongjun Ji, Jeonghyun Kim, Namho Kim
International Journal of Concrete Structures and Materials
Recycled Aggregate Concrete Performance
article

Integrated Experimental and Data-Driven Approach to Strength Prediction of Mortars Incorporating Thermally Activated Construction Waste Powder

Donwoo Lee, Hyeongjun Ji, Jeonghyun Kim, Namho Kim
article en

Abstract

Abstract This study investigated the feasibility of waste construction powder (WCP), a by-product generated from construction waste recycling plants, as a partial replacement for Portland cement through thermal activation. Mortar specimens were prepared using thermally activated WCP at 600 °C and 800 °C, replacing cement at rates of 6%, 13%, and 20%. The flowability, compressive strength, and flexural strength were evaluated. The results showed that mortar with WCP activated at 800 °C met the KS L 5201 industrial standard even at a 20% replacement ratio, achieving up to 21% and 6% increases in compressive strength and flexural strength, respectively. In addition, a machine learning (ML) model based on the light gradient boosting (LGB) algorithm was developed using 405 literature-derived data entries to predict the compressive strength of cementitious composites incorporating thermally activated WCP. The predictive performance was validated against experimental results, achieving strong correlation with the measured data ( R 2 = 0.813), and yielding an RMSE of 3.044 MPa, MAE of 2.507 MPa, and SMAPE of 5.675%. More than 90% of the predictions fell within a ± 10% error margin. These findings demonstrate the practical applicability of the proposed ML model for strength prediction of WCP-based cementitious materials, as well as the technical feasibility of thermally activated WCP as cement replacement.

International Journal of Concrete Structures and MaterialsVol. 20(1)
Wrocław University of Science and Technology (PL), Korea University of Technology and Education (KR), AGH University of Krakow (PL)
National Research Foundation, National Research Foundation of Korea, Narodowym Centrum Nauki
Industry, innovation and infrastructure
Openalex Percentile: Top 26%
Recycled Aggregate Concrete Performance
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