Please use this identifier to cite or link to this item: https://idr.nitk.ac.in/jspui/handle/123456789/12129
Title: Multi-criteria optimization of fly ash and iron ore tailing based concretes subjected to elevated temperatures
Authors: Yaragal, S.C.
Babu, Narayan, K.S.
Chethan, Kumar, B.
Francis, J.G.
Issue Date: 2019
Citation: Indian Concrete Journal, 2019, Vol.93, 10, pp.44-52
Abstract: Due to the rapid increase in concrete utilization all over the world, there is increased consumption of Ordinary Portland Cement (OPC), natural fine aggregate (NFA), and natural coarse aggregates. Increased use of OPC, is posing a serious threat due to excess CO2 emissions, and its production is highly energy intensive. On the other hand, extraction and processing stone-based fine and coarse aggregates too, is energy intensive, and the virgin resources are fast depleting. Therefore, for sustainable development, efforts are on all over the world to look for alternative materials in place of conventional ones. In this study, it is attempted to partly replace OPC with fly ash (FA) and partly replace NFA by iron ore tailings (IOT) in concretes. The performance of such concretes at ambient and elevated temperatures is also presented. Full factorial design of experiments was adopted with two control factors under three levels of replacement, i.e., FA (0, 15, and 30% by weight of OPC) and IOT (0, 50, and 100% by volume of NFA). Total nine concrete mixes were prepared and tested for their compressive strengths at room temperature, and residual compressive strengths when subjected to various levels of elevated temperatures (200, 400, 600, and 800 C), and cost of these concretes has also been analyzed. Further, three traditional multi criteria optimization methods, i.e., grey relational analysis (GRA), technique for order of preference by similarity to ideal solution (TOPSIS), and desirability function approach (DFA) were used to optimize concrete mixes. Results showed that TOPSIS based optimization method is more significant when compared to other two methods. Further, FA-based concrete mixes showed improved performance under multi-criteria optimization. 2019, Associated Cement Companies Ltd. All rights reserved.
URI: http://idr.nitk.ac.in/jspui/handle/123456789/12129
Appears in Collections:1. Journal Articles

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