A Hybrid Approach for Predicting Properties of Recycled Aggregate Concrete using Experimental Testing, Artificial Neural Networks, and Regression Modeling
| International Journal of Civil Engineering |
| © 2026 by SSRG - IJCE Journal |
| Volume 13 Issue 2 |
| Year of Publication : 2026 |
| Authors : Ali A. Mahamied, Amjad A. Yasin, Jamal AlAdwan, Omar M. Qteishat, Ahmad Al-elwan, Aziz A. Al-Muhtaseb |
10.14445/23488352/IJCE-V13I2P117
How to Cite?
Ali A. Mahamied, Amjad A. Yasin, Jamal AlAdwan, Omar M. Qteishat, Ahmad Al-elwan, Aziz A. Al-Muhtaseb, "A Hybrid Approach for Predicting Properties of Recycled Aggregate Concrete using Experimental Testing, Artificial Neural Networks, and Regression Modeling," SSRG International Journal of Civil Engineering, vol. 13, no. 2, pp. 247-265, 2026. Crossref, https://doi.org/10.14445/23488352/IJCE-V13I2P117
Abstract:
This paper looks into mechanical and fresh characteristics of Recycled Aggregate Concrete (RAC) using a broad experimental and predictive modeling approach. An extensive experimental database on 144 concrete mixes was established, including compressive strength of between 15 and 40 MPa. The aggregate that was also used as a replacement for the natural coarse aggregate was Recycled Aggregate (RA), which was used as a percentage of 0-100 with an increment of 20 percent. Three specimens were cast and also tested for every mix, with the average values of compressive strength, slump, and density recorded. The main aim of the research was to measure the effect of adding RA content on the concrete performance as well as to establish valid prediction models with the help of Artificial Neural Networks (ANNs) and regression analysis, which were executed and approved with the help of MATLAB and Python, respectively. The results of the experiments showed a definite and gradual decrease in the concrete properties as the content of RA increased. Compressive strength was decreased by up to around 35 percent, slump by an average of 38 percent, and density by close to 15 percent at full replacement of the RA relative to the comparison mixes with natural aggregates. These tendencies could be explained by high porosity, lower interfacial transition zones, and greater water uptake of recycled aggregates. An ANN model that uses tansig activation was created, and its predictive accuracy is very high, with the error margins of about ±2.5 MPa when predicting compressive strength, ±3 mm when predicting slump, and ±25 kg/m3 when predicting density. The ANN model showed good statistical results, and the R2 values were found to be higher than 0.976, and the MSE and RMSE values were low in all the outputs. Python-based regression models showed moderately good predictive performance with comparatively somewhat larger errors and lower R2 values. These were further verified by the correlation matrices, actual versus predicted plots, and residual analysis that indicated the higher robustness and stability of the ANN method. Overall, the findings demonstrate the efficiency of data-driven modeling methods, especially ANN, to predict RAC properties in an accurate way and justify sustainable concrete mix design.
Keywords:
ANN, Regression analysis, Predictive modeling, Compressive strength, Slump, Density.
References:
[1] Zehra Funda Akbulut et al., “Toward Sustainable Construction: A Critical Review of Recycled Aggregate Concrete Properties and Future Opportunities,” Case Studies in Construction Materials, vol. 23, pp. 1-34, 2025.
[CrossRef] [Google Scholar] [Publisher Link]
[2] Markssuel Marvila et al., “Recycled Aggregate: A Viable Solution for Sustainable Concrete Production,” Materials, vol. 15, no. 15, pp. 1-16, 2022.
[CrossRef] [Google Scholar] [Publisher Link]
[3] P. Jagadesh et al., “Examining the Influence of Recycled Aggregates on the Fresh and Mechanical Characteristics of High-Strength Concrete: A Comprehensive Review,” Sustainability, vol. 16, no. 20, pp. 1-35, 2024.
[CrossRef] [Google Scholar] [Publisher Link]
[4] Jiangwei Zhang et al., “Research Progress of the Recycled Aggregate Concrete in Life Cycle Assessment,” Journal of Building Design and Environment, vol. 2, no. 2, pp. 1-13, 2024.
[CrossRef] [Google Scholar] [Publisher Link]
[5] Zainab Abdulrdha Thoeny, “A Study of Properties of Recycled concrete Aggregate and Use in Construction Applications,” Journal of Engineering Science and Technology, Special Issue on Research Studies and Applications in Engineering and Applied Sciences (RSAEAS), pp. 68-76, 2022.
[Google Scholar] [Publisher Link]
[6] Zhong Xu et al., “Research Progress on Mechanical Properties of Geopolymer Recycled Aggregate Concrete,” Advance Material Science, vol. 60, no. 1, pp. 158-172, 2021.
[CrossRef] [Google Scholar] [Publisher Link]
[7] Xinchen Pan et al., “Use of Artificial Intelligence Methods for Predicting the Strength of Recycled Aggregate Concrete and the Influence of Raw Ingredients,” Materials, vol. 15, no. 12, pp. 1-21, 2022.
[CrossRef] [Google Scholar] [Publisher Link]
[8] Ma Xuetong, and Gao Debin, “Experimental Study of Compressive Properties and Environmental Impact of Recycled Aggregate,” Frontiers in Materials, vol. 8, pp. 1-8, 2021.
[CrossRef] [Google Scholar] [Publisher Link]
[9] Kho Pin Veriana, Warda Ashrafb, and Yizheng Caoc, “Properties of Recycled Concrete Aggregate and their Influence in New Concrete Production,” Resources, Conservation & Recycling, vol. 133, pp. 30-49, 2018.
[CrossRef] [Google Scholar] [Publisher Link]
[10] Mmasetlhomo Tommy Gumede, and Shodolapo Oluyemi Franklin, “Studies on Strength and Related Properties of Concrete Incorporating Aggregates from Demolished Wastes: Part 2-Compressive and Flexural Strengths,” Journal of Civil Engineering, vol. 5, no. 2, pp. 175-184, 2015.
[CrossRef] [Google Scholar] [Publisher Link]
[11] Panxiu Wang et al., “Two-Stage Deterioration Mechanisms in Recycled Aggregate Concrete: From Pore Interface Degradation to Aggregate Interface Defect Control,” Buildings, vol. 15, no. 24, pp. 1-20, 2025.
[CrossRef] [Google Scholar] [Publisher Link]
[12] Hyun-Kyoung Kim, and Hyo-Gyoung Kwak, “Quantification of Resistance Reduction of Recycled Aggregate Concrete (RAC) Members and Compensatory Section Adjustment,” Engineering Structures, vol. 342, pp. 1-36, 2025.
[CrossRef] [Google Scholar] [Publisher Link]
[13] Harshit Varshney, Rizwan A. Khan, and Iqbal Khaleel Khan, “Investigation of Biomineralization on the Strength, Durability Properties of Fiber-Based RAC,” IJRASET International Journal for Research in Applied Science and Engineering Technology, vol. 13, no. 4, pp. 1-9, 2025.
[CrossRef] [Publisher Link]
[14] Farshad Ameri, and Ildiko Merta, “Second-Generation Recycled Concrete Aggregates: Comprehensive Characterization of Physical, Mechanical, and Microstructural Properties,” Recycling, vol. 10, no. 5, pp. 1-27, 2025.
[CrossRef] [Google Scholar] [Publisher Link]
[15] Ram Prasad Neupane et al., “Use of Recycled Aggregate Concrete in Structural Members: A Review Focused on Southeast Asia,” Journal of Asian Architecture and Building Engineering, vol. 24, no. 3, pp. 1197-1220, 2023.
[CrossRef] [Google Scholar] [Publisher Link]
[16] Zia Ul Islam et al., “Evaluating the Mechanical Properties of Recycled Aggregate Concrete with Variable Coarse and Fine Aggregate Replacements,” Discover Civil Engineering, vol. 2, no. 1, pp. 1-16, 2025.
[CrossRef] [Google Scholar] [Publisher Link]
[17] Tariq Ali et al., “Optimizing Recycled Aggregate Concrete Performance with Chemically and Mechanically Activated Fly Ash in Combination with Coconut Fiber,” Scientific Reports, vol. 15, no. 1, pp. 1-19, 2025.
[CrossRef] [Google Scholar] [Publisher Link]
[18] Rafat Siddique, Paratibha Aggarwal, and Yogesh Aggarwal, “Prediction of Compressive Strength of Self-Compacting Concrete Containing Bottom Ash using Artificial Neural Networks,” Advances in Engineering Software, vol. 42, no. 10, pp. 780-786, 2011.
[CrossRef] [Google Scholar] [Publisher Link]
[19] Xiaolong Yang et al., “Straightening Methods for RCA and RAC-A Review,” Cement and Concrete Composites, vol. 141, 2023.
[CrossRef] [Google Scholar] [Publisher Link]
[20] Faroq Maraqa et al., “Artificial Neural Network-Based Prediction of Physical and Mechanical Properties of Concrete Containing Glass Aggregates,” Civil Engineering Journal, vol. 10, no. 5, pp. pp. 1627-1644, 2024.
[CrossRef] [Google Scholar] [Publisher Link]
[21] ASTM C150/C150M-22, “Standard Specification for Portland Cement,” ASTM-Standards, 2024.
[CrossRef] [Google Scholar] [Publisher Link]
[22] ASTM C33/C33M-16e1, “Standard Specification for Concrete Aggregates,” ASTM International, 2018.
[CrossRef] [Google Scholar] [Publisher Link]
[23] ASTM C192/C192M-16a, “Standard Practice for Making and Curing Concrete Test Specimens in the Laboratory,” ASTM International, 2019.
[CrossRef] [Google Scholar] [Publisher Link]
[24] ASTM C494/C494M-17, “Standard Specification for Chemical Admixtures for Concrete,” ASTM International, 2020.
[CrossRef] [Google Scholar] [Publisher Link]
[25] ASTM C143/C143M-15a, “Standard Test Method for Slump of Hydraulic-Cement Concrete,” ASTM International, 2015.
[CrossRef] [Google Scholar] [Publisher Link]
[26] ASTM C138/C138M-24a, “Standard Test Method for Density (Unit Weight), Yield, and Air Content (Gravimetric) of Concrete,” ASTM International, 2023.
[CrossRef] [Google Scholar] [Publisher Link]