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Article 2024 · 2 citations

Utilizing genetic programming to evaluate and predict roller-compacted concrete pavements reinforced with coal powder and basalt fiber

Yilmaz, Ahmet, Yildizel, Sadik Alper, Bahrami, Alireza, Kaplan, Gokhan

Abstract

Roller-compacted concrete (RCC) pavement technology has drawn significant attention in recent years, thanks to its many advantages over conventional paving materials. The main benefits of RCC include decreased shrinkage, reduced life-cycle expenses, early access to traffic and a decrease in the urban heat island effect. This study proposed a cost-effective method to address the disposal of coal powder (CP), which is an important contributor of environmental problems, by integrating it into the manufacturing of RCC. Cement was replaced with CP at weight ratios of 5%, 10%, 15%, and 20%. CP was substituted for cement, with weight ratios of 5%, 10%, 15% and 20%. The albedo and mechanical properties of the obtained RCC mixtures were measured. The albedo of the RCC mixture with 20% CP decreased approximately 2.3 times in comparison to that of the reference mixture. After 28 days, RCC mixes had compressive strengths of 26-38 MPa and flexural strengths of 4.3-6.1 MPa. Flexural and splitting tensile strengths increased substantially with BF. RCC mixtures with 5% CP and 0.5% BF improved freeze-thaw resilience after 100 cycles. The genetic algorithm approach may improve RCC design optimisation. Thus, RCC made with CP may be environmentally friendly and Sustainable.

Keywords
Roller-compacted concrete coal powder basalt fiber pavement genetic programming frost resistance SPLITTING TENSILE-STRENGTH MECHANICAL-PROPERTIES COMPRESSIVE STRENGTH SOLAR REFLECTANCE MIX DESIGN WASTE CEMENT
WoS Categories
Construction & Building Technology Engineering, Civil Materials Science, Characterization & Testing
Sustainable Development Goals
Citation
Journal
INTERNATIONAL JOURNAL OF PAVEMENT ENGINEERING
Year
2024
Volume
25
Issue
1
ISSN
1029-8436
eISSN
1477-268X
DOI
10.1080/10298436.2024.2382328
WoS UID
WOS:001292506700001
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