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Optimization of sustainable high-strength–high-volume fly ash concrete with and without steel fiber using Taguchi method and multi-regression analysis

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Abstract

The progression of high-strength–high-volume fly ash concrete addresses fly ash as a resource productive material with the sustainability of the construction industry. This paper presents the evaluation and optimization of the sustainable mechanical properties of concrete with and without crimped steel fibers. In the first phase, the experimental tests are conducted to know the compressive strength, split tensile strength, and flexural strength obtained from the optimal mixes of concrete. Taguchi L16 orthogonal array experimental design is applied to optimize the performance of mechanical properties of concrete by using the design of experiments. The level of influence of fly ash percentage on mechanical properties of a concrete mixture is determined by multiple regression analysis. However, after multiple regression analysis, it is found that the error related to the correlation between experimental and analytical value strength is about 5%. Hence, it can be strongly recommended that the developed regression model is sufficient and has a competent approach to optimize the experimental as well as analytical value simultaneously. However, it is concluded that the Taguchi technique is an effective methodical model to reduce the overall investigational work. It is also an efficient approach to optimize designs for performance and quality. The present research confirms that with the mechanical properties of the high-strength–high-volume fly ash steel fiber concrete, it is a more suitable alternative sustainable solution to the concrete industry.

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Acknowledgement

The authors are thankful to Anil Patil, Sangram Jadhav and Madhav Raul for their support and proofreading the manuscript.

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Correspondence to Gunavant K. Kate.

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Kate, G.K., Nayak, C.B. & Thakare, S.B. Optimization of sustainable high-strength–high-volume fly ash concrete with and without steel fiber using Taguchi method and multi-regression analysis. Innov. Infrastruct. Solut. 6, 102 (2021). https://doi.org/10.1007/s41062-021-00472-6

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