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The Applicability of TOPSIS- and Fuzzy TOPSIS-Based Taguchi Optimization Approaches in Obtaining Optimal Fiber-Reinforced Concrete Mix Proportions

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Medium: journal article
Language(s): English
Published in: Buildings, , n. 6, v. 12
Page(s): 796
DOI: 10.3390/buildings12060796
Abstract:

This research aims to illustrate and express the impact of analytical techniques such as TOPSIS- and FTOPSIS-based Taguchi models on obtaining the optimum design of fiber-reinforced concrete (FRC).Three levels of silica fume content, fly ash content, water-to-cementitious (W/C) ratio, and superplasticizer content were examined in the present work. However, the steel fiber content (1%) and the maximum aggregate size of 14 mm were kept constant for all mixes. Once the experimental results were obtained following Taguchi’s method, it was used as input data to the TOPSIS and FTOPSIS models. The optimum set of mixture factor levels was determined by identifying the two modules. The optimal FRC mix proportions obtained from the TOPSIS- and FTOPSIS-based Taguchi model were 5% silica fume content, 0% fly ash content, 0.27 W/C ratio, and 0.5% superplasticizer. Multi-response optimization approaches are essential to optimize the concrete mix proportions to achieve the required strengths, workability, and production cost. ANOVA was used to analyze the experimental results to find the contribution of each independent variable to the compressive strength and splitting tensile strength of FRC. ANOVA showed that the most predominant factor that affects the FRC mix proportions was the W/C ratio, followed by the fly ash, silica fume, and superplasticizer contents, respectively, in descending order.

Copyright: © 2022 by the authors; licensee MDPI, Basel, Switzerland.
License:

This creative work has been published under the Creative Commons Attribution 4.0 International (CC-BY 4.0) license which allows copying, and redistribution as well as adaptation of the original work provided appropriate credit is given to the original author and the conditions of the license are met.

  • About this
    data sheet
  • Reference-ID
    10679440
  • Published on:
    17/06/2022
  • Last updated on:
    10/11/2022
 
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