Optimization of production parameters for rice husk ash-based geopolymer cement using response surface methodology
The use of agro-waste in geopolymers, to serve as alternative material to Ordinary Portland Cement (OPC) presents a great potential to the sustainability of the construction sector. Accordingly, this study aimed to optimize the production parameters of geopolymer cement using response surface method...
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doaj-cb2a64564fd64c06bcb487efa82cb5732020-12-25T05:09:46ZengElsevierCase Studies in Construction Materials2214-50952020-12-0113e00461Optimization of production parameters for rice husk ash-based geopolymer cement using response surface methodologyKasumba A. Buyondo0Peter W. Olupot1John B. Kirabira2Abdulfatah A. Yusuf3Department of Mechanical Engineering, Makerere University Kampala, P. O. Box 7062, Kampala Uganda; Department of Mechanical Engineering, Kampala International University, P. O. Box 20000, Kampala, Uganda; Corresponding author at: Department of Mechanical Engineering, Makerere University Kampala, P. O. Box 7062, Kampala Uganda.Department of Mechanical Engineering, Makerere University Kampala, P. O. Box 7062, Kampala UgandaDepartment of Mechanical Engineering, Makerere University Kampala, P. O. Box 7062, Kampala UgandaDepartment of Mechanical Engineering, Makerere University Kampala, P. O. Box 7062, Kampala UgandaThe use of agro-waste in geopolymers, to serve as alternative material to Ordinary Portland Cement (OPC) presents a great potential to the sustainability of the construction sector. Accordingly, this study aimed to optimize the production parameters of geopolymer cement using response surface methodology (RSM) with rice husk ask (RHA), metakaolin (MK) and an alkaline activator as reactants. During the experiment, two-factorial design was run using the central composite design (CCD) to generate 13 combinations of cement (reactant) mixtures with standard sand in order to cast mortar prisms whose compressive strength was evaluated according to BS EN standard. Data analysis on the compressive strength was carried out using MATLAB software. Models for compressive strengths with RHA and MK as predictors were generated for samples cured at 7 and 14 days. Result showed that the overall R2 of these models were 0.8951 and 0.63, respectively. The β values for the multiple linear model for the strength at 7 days of curing was <0.05, which makes the model a reliable predictor for the geopolymer strength. The performance tests carried out on the optimal cement sample showed the consistency of 52.9 %, initial and final setting time of 7 and 13.5 h respectively. The optimal geopolymer cement also had a bulk density of 1546.4 kg/m3, and water absorption of 19.19 % with the optimum compressive strength of 0.80 MPa at 7 days.http://www.sciencedirect.com/science/article/pii/S2214509520301339RHAMetakaolinRSMStrengthOptimizationGeopolymers |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Kasumba A. Buyondo Peter W. Olupot John B. Kirabira Abdulfatah A. Yusuf |
spellingShingle |
Kasumba A. Buyondo Peter W. Olupot John B. Kirabira Abdulfatah A. Yusuf Optimization of production parameters for rice husk ash-based geopolymer cement using response surface methodology Case Studies in Construction Materials RHA Metakaolin RSM Strength Optimization Geopolymers |
author_facet |
Kasumba A. Buyondo Peter W. Olupot John B. Kirabira Abdulfatah A. Yusuf |
author_sort |
Kasumba A. Buyondo |
title |
Optimization of production parameters for rice husk ash-based geopolymer cement using response surface methodology |
title_short |
Optimization of production parameters for rice husk ash-based geopolymer cement using response surface methodology |
title_full |
Optimization of production parameters for rice husk ash-based geopolymer cement using response surface methodology |
title_fullStr |
Optimization of production parameters for rice husk ash-based geopolymer cement using response surface methodology |
title_full_unstemmed |
Optimization of production parameters for rice husk ash-based geopolymer cement using response surface methodology |
title_sort |
optimization of production parameters for rice husk ash-based geopolymer cement using response surface methodology |
publisher |
Elsevier |
series |
Case Studies in Construction Materials |
issn |
2214-5095 |
publishDate |
2020-12-01 |
description |
The use of agro-waste in geopolymers, to serve as alternative material to Ordinary Portland Cement (OPC) presents a great potential to the sustainability of the construction sector. Accordingly, this study aimed to optimize the production parameters of geopolymer cement using response surface methodology (RSM) with rice husk ask (RHA), metakaolin (MK) and an alkaline activator as reactants. During the experiment, two-factorial design was run using the central composite design (CCD) to generate 13 combinations of cement (reactant) mixtures with standard sand in order to cast mortar prisms whose compressive strength was evaluated according to BS EN standard. Data analysis on the compressive strength was carried out using MATLAB software. Models for compressive strengths with RHA and MK as predictors were generated for samples cured at 7 and 14 days. Result showed that the overall R2 of these models were 0.8951 and 0.63, respectively. The β values for the multiple linear model for the strength at 7 days of curing was <0.05, which makes the model a reliable predictor for the geopolymer strength. The performance tests carried out on the optimal cement sample showed the consistency of 52.9 %, initial and final setting time of 7 and 13.5 h respectively. The optimal geopolymer cement also had a bulk density of 1546.4 kg/m3, and water absorption of 19.19 % with the optimum compressive strength of 0.80 MPa at 7 days. |
topic |
RHA Metakaolin RSM Strength Optimization Geopolymers |
url |
http://www.sciencedirect.com/science/article/pii/S2214509520301339 |
work_keys_str_mv |
AT kasumbaabuyondo optimizationofproductionparametersforricehuskashbasedgeopolymercementusingresponsesurfacemethodology AT peterwolupot optimizationofproductionparametersforricehuskashbasedgeopolymercementusingresponsesurfacemethodology AT johnbkirabira optimizationofproductionparametersforricehuskashbasedgeopolymercementusingresponsesurfacemethodology AT abdulfatahayusuf optimizationofproductionparametersforricehuskashbasedgeopolymercementusingresponsesurfacemethodology |
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