Applicability of the response surface method in the optimization of compressive strengths of banana-fiber-reinforced concrete using waste glass as partial cement replacement

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作者
Oluwole Malomo Olukayode
Abayomi Adewale Akinwande
Oluwatosin Abiodun Balogun
Abiola Oluwasogo Oyediran
Seun Ganiyu Mosuru
Mohanad Yaseen Abdulwahid
Valentin Romanovski
机构
[1] Federal University of Technology Akure,Department of Civil and Environmental Engineering
[2] Federal University of Technology Akure,Department of Metallurgical and Materials Engineering
[3] Federal University of Technology Akure,Construction Economics Section, Department of Quantity Survey
[4] Federal University of Agriculture,Department of Forestry and Wildlife Management
[5] Koya University,Department of Civil Engineering
[6] National University of Science and Technology,Center for Functional Nano
[7] “MISIS”,Ceramics
[8] University of Virginia,Department of Materials Science and Engineering
来源
Innovative Infrastructure Solutions | 2023年 / 8卷
关键词
RSM (response surface method); Fiber-reinforced concrete; Banana fiber; Waste glass; Cement replacement; Compressive strength optimization;
D O I
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中图分类号
学科分类号
摘要
Natural fibers and pozzolan have gained prominence in the development of concrete; however, there are few studies that have considered the combination of banana fiber and waste glass powder. In this work, 0.5%, 1.0%, and 1.5% banana fiber (BF) was employed as fiber reinforcement, while glass powder (GP) was used as pozzolan, partially replacing cement at 10%, 20%, and 30%. Using the response surface method (RSM), the experimental data on the 7-, 28-, and 56-day concrete compressive strengths were analysed, modeled and optimized via the response surface approach. The result revealed that the variables played an important role on the trend of the 7-, 28-, and 56-day compressive strengths. The optimal combination of 1.0%, 1.1%, and 1.0% banana fiber at 17.4%, 20.8%, and 21.0% GP cement replacement yielded improvements of 11.0, 22.1, and 27.0% over the reference concrete at 7, 28, and 56 days, respectively. The developed predictive models for compressive strength were affirmed to be statistically fit for future prediction.
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