| Title |
Development and strength prediction of sustainable concrete having binary and ternary cementitious blends and incorporating recycled aggregates from demolished UAE buildings: Experimental and machine learning-based studies |
| ID_Doc |
25914 |
| Authors |
Al Martini, S; Sabouni, R; Khartabil, A; Wakjira, TG; Alam, MS |
| Title |
Development and strength prediction of sustainable concrete having binary and ternary cementitious blends and incorporating recycled aggregates from demolished UAE buildings: Experimental and machine learning-based studies |
| Year |
2023 |
| Published |
|
| DOI |
10.1016/j.conbuildmat.2023.131278 |
| Abstract |
This study investigates the mechanical properties of concrete mixes containing recycled concrete aggregate (RCA) from demolished buildings in Abu Dhabi, aiming to promote sustainable construction practices. Ground granulated blast-furnace slag and fly ash were used as supplementary cementitious materials in 70 concrete mixes, incorporating varying RCA replacement levels (0%, 20%, 40%, 60%, and 100%). Uniaxial compressive and flexural tests were conducted, revealing that concrete with 20% RCA can be utilized in structural applica-tions, as its strength exceeded 45 MPa. Most ternary blend mixes achieved the target design strength, excluding 100% RCA mixes. Analysis of variance evaluated the significance of strength differences across RCA levels, and accurate machine learning-based models were developed for predicting the compressive and flexural strengths of eco-friendly concrete containing RCA. The findings encourage wider adoption of RCA in structural applications, contributing to more sustainable concrete practices in the construction industry. |
| Author Keywords |
Recycled aggregates; Strength; Sustainability; Supplementary cementitious materials; Circular economy; Machine learning |
| Index Keywords |
Index Keywords |
| Document Type |
Other |
| Open Access |
Open Access |
| Source |
Science Citation Index Expanded (SCI-EXPANDED) |
| EID |
WOS:000976364900001 |
| WoS Category |
Construction & Building Technology; Engineering, Civil; Materials Science, Multidisciplinary |
| Research Area |
Construction & Building Technology; Engineering; Materials Science |
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