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篇名
Optimization of mixture proportions for self-compacting concrete using TOPSIS method
並列篇名
Optimization of mixture proportions for self-compacting concrete using TOPSIS method
作者 Kesavamoorthi. R (Kesavamoorthi. R)Mohan Ganesh. G (Mohan Ganesh. G)
英文摘要
The process of concrete mix design encompasses numerous parameters. Finding the ideal mix design may be quite challenging for self-compacting concrete (SCC). This research aims to identify the best optimum mix proportions for SCC using TOPSIS (Technique for Order Preference by Similarity to Ideal Solution) method. In this methodology, SCC mixtures with an extensive set of experimental data and performance measures are combined into a single value for optimizing. For this the required data sets of twenty-one SCC mixtures were developed utilizing the Nan-Su method with M50 grade of concrete and cast for finding fresh and mechanical properties. The slump flow was measured using EFNARC standards and compressive strength was measured. The input parameters for the TOPSIS method were slump flow, compressive strength, superplasticizer (SP), viscosity modifying agent (VMA), and the W/C ratio which were among the five criteria used to choose as alternatives among the twenty-one different mix proportions. Therefore, the experimental data set of SCC provides the essential data for the decision matrix. TOPSIS is a ranking algorithm for condensing the results of many different criteria into a single value. By evaluating and rating the various mixture proportions, the optimal one was identified which reduces the number of trail mixtures in future, as seen in the details given in this study. Further, the study will evaluate the effect of supplementary cementitious materials (SCMs) on the properties of SCC. The replacement of SCMs improves the fresh and mechanical properties compared to the control mix and SCMs promotes the sustainable and environmentally friendly construction practices.
起訖頁 1-13
關鍵詞 EFNARCNan-Su methodSelf-compacting concreteTOPSIS
刊名 國際應用科學與工程學刊  
期數 202503 (22:1期)
出版單位 朝陽科技大學理工學院
該期刊-上一篇 Enhancing cybersecurity vulnerability detection using different machine learning severity prediction models
該期刊-下一篇 Experimental and theoretical investigations of prifinium bromide: structural insights, spectroscopic features, topological aspects, and biological properties
 

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