Effect of Graphene Oxide as a Nanomaterial on the Durability Behaviors of Engineered Cementitious Composites by Applying RSM Modelling and Optimization
Engineered Cementitious Composites (ECC) are widely used in various structures due to their high strength, durability, and ductility. However, they are still vulnerable to environmental factors such as sulphate and acid attack. These attacks damage the concrete matrix, which leads to cracking and co...
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Multidisciplinary Digital Publishing Institute (MDPI)
2023
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oai:scholars.utp.edu.my:374242023-10-04T12:43:45Z http://scholars.utp.edu.my/id/eprint/37424/ Effect of Graphene Oxide as a Nanomaterial on the Durability Behaviors of Engineered Cementitious Composites by Applying RSM Modelling and Optimization Bheel, N. Mohammed, B.S. Liew, M.S. Zawawi, N.A.W.A. Engineered Cementitious Composites (ECC) are widely used in various structures due to their high strength, durability, and ductility. However, they are still vulnerable to environmental factors such as sulphate and acid attack. These attacks damage the concrete matrix, which leads to cracking and corrosion of the reinforcing steel. To mitigate these issues, various techniques have been developed, including the addition of graphene oxide to the ECC mix. Graphene oxide has shown potential in improving the mechanical properties and durability of ECC. The purpose of this study was to use multi-objective optimization to identify an appropriate GO by the weight of the cement and polyvinyl alcohol (PVA) fiber volume fraction in an ECC mixture. Using RSM�s central composite design (CCD), thirteen mixtures of various possible combinations of variables (GO: 0.05 percent to 0.08 percent, PVA: 1�2 percent) were established, and eight response responses (compressive strength, change in length, weight loss, pH test, weight gain, expansion, rapid chloride permeability test and water absorption) were examined. However, analysis of variance was used to effectively design and evaluate eight (six quadratic and two linear) response models. All the models had extremely high R2 values, ranging from 84 percent to 99 percent. The multi-objective optimization produced ideal variable values (GO: 0.05 percent and PVA: 1) and projected optimum response values. The predicted values were verified experimentally and found to correlate extremely well with the experimental data, with less than a 5 error. The outcome showed that the maximum increase of 30 in the compressive strength was recorded at 0.05 of GO as a nanomaterial in ECC. In addition, the expansion due to sulfate resistance and change in length due to acid attack were decreased by 0.0023 and 0.28, respectively, when the use of 0.08 of GO as a nanomaterial in the ECC matrix was reinforced with 1 PVA fiber for 28 days. Moreover, the weight loss and weight gain of ECC combined with 1 of PVA fiber due to chemical attack decreased by 66.70 and 77.80, respectively, at 0.08 of GO as a nanoscale particle than that of the reference mix for 28 days. In addition, the pH value due to acid attack, rapid chloride permeability test value, water absorption, and slump flow of the fresh mixture were decreased as the concentration of GO rose in ECC. The results indicated that the incorporation of 0.05 GO as a nanomaterial and 1 to 1.5 of PVA fiber will provide the best outcomes for the construction industry. © 2023 by the authors. Multidisciplinary Digital Publishing Institute (MDPI) 2023 Article NonPeerReviewed Bheel, N. and Mohammed, B.S. and Liew, M.S. and Zawawi, N.A.W.A. (2023) Effect of Graphene Oxide as a Nanomaterial on the Durability Behaviors of Engineered Cementitious Composites by Applying RSM Modelling and Optimization. Buildings, 13 (8). ISSN 20755309 https://www.scopus.com/inward/record.uri?eid=2-s2.0-85169141438&doi=10.3390%2fbuildings13082026&partnerID=40&md5=6b251526b6b27f9e96704d5b720db0a4 10.3390/buildings13082026 10.3390/buildings13082026 10.3390/buildings13082026 |
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Engineered Cementitious Composites (ECC) are widely used in various structures due to their high strength, durability, and ductility. However, they are still vulnerable to environmental factors such as sulphate and acid attack. These attacks damage the concrete matrix, which leads to cracking and corrosion of the reinforcing steel. To mitigate these issues, various techniques have been developed, including the addition of graphene oxide to the ECC mix. Graphene oxide has shown potential in improving the mechanical properties and durability of ECC. The purpose of this study was to use multi-objective optimization to identify an appropriate GO by the weight of the cement and polyvinyl alcohol (PVA) fiber volume fraction in an ECC mixture. Using RSM�s central composite design (CCD), thirteen mixtures of various possible combinations of variables (GO: 0.05 percent to 0.08 percent, PVA: 1�2 percent) were established, and eight response responses (compressive strength, change in length, weight loss, pH test, weight gain, expansion, rapid chloride permeability test and water absorption) were examined. However, analysis of variance was used to effectively design and evaluate eight (six quadratic and two linear) response models. All the models had extremely high R2 values, ranging from 84 percent to 99 percent. The multi-objective optimization produced ideal variable values (GO: 0.05 percent and PVA: 1) and projected optimum response values. The predicted values were verified experimentally and found to correlate extremely well with the experimental data, with less than a 5 error. The outcome showed that the maximum increase of 30 in the compressive strength was recorded at 0.05 of GO as a nanomaterial in ECC. In addition, the expansion due to sulfate resistance and change in length due to acid attack were decreased by 0.0023 and 0.28, respectively, when the use of 0.08 of GO as a nanomaterial in the ECC matrix was reinforced with 1 PVA fiber for 28 days. Moreover, the weight loss and weight gain of ECC combined with 1 of PVA fiber due to chemical attack decreased by 66.70 and 77.80, respectively, at 0.08 of GO as a nanoscale particle than that of the reference mix for 28 days. In addition, the pH value due to acid attack, rapid chloride permeability test value, water absorption, and slump flow of the fresh mixture were decreased as the concentration of GO rose in ECC. The results indicated that the incorporation of 0.05 GO as a nanomaterial and 1 to 1.5 of PVA fiber will provide the best outcomes for the construction industry. © 2023 by the authors. |
| format |
Article |
| author |
Bheel, N. Mohammed, B.S. Liew, M.S. Zawawi, N.A.W.A. |
| spellingShingle |
Bheel, N. Mohammed, B.S. Liew, M.S. Zawawi, N.A.W.A. Effect of Graphene Oxide as a Nanomaterial on the Durability Behaviors of Engineered Cementitious Composites by Applying RSM Modelling and Optimization |
| author_facet |
Bheel, N. Mohammed, B.S. Liew, M.S. Zawawi, N.A.W.A. |
| author_sort |
Bheel, N. |
| title |
Effect of Graphene Oxide as a Nanomaterial on the Durability Behaviors of Engineered Cementitious Composites by Applying RSM Modelling and Optimization |
| title_short |
Effect of Graphene Oxide as a Nanomaterial on the Durability Behaviors of Engineered Cementitious Composites by Applying RSM Modelling and Optimization |
| title_full |
Effect of Graphene Oxide as a Nanomaterial on the Durability Behaviors of Engineered Cementitious Composites by Applying RSM Modelling and Optimization |
| title_fullStr |
Effect of Graphene Oxide as a Nanomaterial on the Durability Behaviors of Engineered Cementitious Composites by Applying RSM Modelling and Optimization |
| title_full_unstemmed |
Effect of Graphene Oxide as a Nanomaterial on the Durability Behaviors of Engineered Cementitious Composites by Applying RSM Modelling and Optimization |
| title_sort |
effect of graphene oxide as a nanomaterial on the durability behaviors of engineered cementitious composites by applying rsm modelling and optimization |
| publisher |
Multidisciplinary Digital Publishing Institute (MDPI) |
| publishDate |
2023 |
| url |
http://scholars.utp.edu.my/id/eprint/37424/ https://www.scopus.com/inward/record.uri?eid=2-s2.0-85169141438&doi=10.3390%2fbuildings13082026&partnerID=40&md5=6b251526b6b27f9e96704d5b720db0a4 |
| _version_ |
1779441380925374464 |
| score |
13.211869 |