Optimization of Mortar Compressive Strength Prepared with Waste Glass Aggregate and Coir Fiber Addition Using Response Surface Methodology

被引:0
|
作者
Rahmawati C. [1 ,2 ]
Handayani L. [3 ]
Muhtadin [4 ]
Faisal M. [4 ]
Zardi M. [1 ]
Sapuan S.M. [5 ]
Hadi A.E. [6 ]
Ahmad J. [7 ]
Isleem H.F. [8 ]
机构
[1] Department of Civil Engineering, Universitas Abulyatama, Aceh Besar
[2] Advanced Engineering Materials and Nano Technology Research Center, Universitas Abulyatama, Aceh Besar
[3] Faculty of Fisheries, Universitas Abulyatama, Aceh Besar
[4] Department of Mechanical Engineering, Universitas Abulyatama, Aceh Besar
[5] Advanced Engineering Materials and Composites Research Center (AEMC), Department of Mechanical and Manufacturing Engineering, Universiti Putra Malaysia, Selangor
[6] Department of Mechanical Engineering, Universitas Malahayati, Lampung
[7] Department of Civil Engineering, Millitary College of Engineering, Risalpur
[8] Department of Construction Management, Qujing Normal University, Qujing
关键词
Cellulose; coir fiber; composite; response surface methodology; waste glass;
D O I
10.32604/jrm.2023.028987
中图分类号
学科分类号
摘要
Waste Glass (WGs) and Coir Fiber (CF) are not widely utilized, even though their silica and cellulose content can be used to create construction materials. This study aimed to optimize mortar compressive strength using Response Surface Methodology (RSM). The Central Composite Design (CCD) was applied to determine the optimization of WGs and CF addition to the mortar compressive strength. Compressive strength and microstructure testing with Scanning Electron Microscope (SEM), Fourier-transform Infrared Spectroscopy (FT-IR), and X-Ray Diffraction (XRD) were conducted to specify the mechanical ability and bonding between the matrix, CF, and WGs. The results showed that the chemical treatment of CF produced 49.15% cellulose, with an average particle size of 1521 µm. The regression of a second-order polynomial model yielded an optimum composition consisting of 12.776% WGs and 2.344% CF with a predicted compressive strength of 19.1023 MPa. C–S–H gels were identified in the mortars due to the dissolving of SiO2 in WGs and cement. The silica from WGs increased the C–S–H phase. CF plays a role in preventing, bridging, and branching micro-cracks before reaching maximum stress. WGs aggregates and chemically treated CF are suitable to be composited in mortar to increase compressive strength. © 2023, Tech Science Press. All rights reserved.
引用
收藏
页码:3751 / 3767
页数:16
相关论文
共 50 条
  • [21] Optimization of Food Waste Bioevaporation Process Using Response Surface Methodology
    Yang, Benqin
    Jahng, Deokjin
    DRYING TECHNOLOGY, 2015, 33 (10) : 1188 - 1198
  • [22] Optimization of calcined bentonite caly utilization in cement mortar using response surface methodology
    Reddy S.S.
    Reddy M.A.K.
    International Journal of Engineering, Transactions A: Basics, 2021, 34 (07): : 1623 - 1631
  • [23] Optimization of Calcined Bentonite Caly Utilization in Cement Mortar using Response Surface Methodology
    Reddy, S. Sahith
    Reddy, M. Achyutha Kumar
    INTERNATIONAL JOURNAL OF ENGINEERING, 2021, 34 (07): : 1623 - 1631
  • [24] Biotransformation of flower waste composting: Optimization of waste combinations using response surface methodology
    Sharma, Dayanand
    Yadav, Kunwar D.
    Kumar, Sunil
    BIORESOURCE TECHNOLOGY, 2018, 270 : 198 - 207
  • [25] Evaluating the effectiveness of waste glass powder for the compressive strength improvement of cement mortar using experimental and machine learning methods
    Khan, Kaffayatullah
    Ahmad, Waqas
    Amin, Muhammad Nasir
    Rafiq, Muhammad Isfar
    Abu Arab, Abdullah Mohammad
    Alabdullah, Inas Abdulalim
    Alabduljabbar, Hisham
    Mohamed, Abdullah
    HELIYON, 2023, 9 (05)
  • [26] Modeling the compressive strength of green mortar modified with waste glass granules and fly ash using soft computing techniques
    Soran Abdrahman Ahmad
    Serwan Khwrshed Rafiq
    Rabar H. Faraj
    Innovative Infrastructure Solutions, 2023, 8
  • [27] Probabilistic Modelling of Compressive Strength of Concrete Using Response Surface Methodology and Neural Networks
    S. M. A. Boukli Hacene
    F. Ghomari
    F. Schoefs
    A. Khelidj
    Arabian Journal for Science and Engineering, 2014, 39 : 4451 - 4460
  • [28] Modeling the compressive strength of green mortar modified with waste glass granules and fly ash using soft computing techniques
    Ahmad, Soran Abdrahman
    Rafiq, Serwan Khwrshed
    Faraj, Rabar H.
    INNOVATIVE INFRASTRUCTURE SOLUTIONS, 2023, 8 (01)
  • [29] Prediction on compressive strength of hybrid textile reinforced concrete using response surface methodology
    Sudha, M. Raga
    Muthadhi, A.
    INNOVATIVE INFRASTRUCTURE SOLUTIONS, 2024, 9 (05)
  • [30] Probabilistic Modelling of Compressive Strength of Concrete Using Response Surface Methodology and Neural Networks
    Hacene, S. M. A. Boukli
    Ghomari, F.
    Schoefs, F.
    Khelidj, A.
    ARABIAN JOURNAL FOR SCIENCE AND ENGINEERING, 2014, 39 (06) : 4451 - 4460