Abstract

Abstract This article describes how optimization studies were carried out on a selection of optimal heat transfer fluids (HTFs) for solar applications with multiresponse characteristics based on the multi-criteria decision-making methodology (MCDM) using the Technique for Order Preference by Similarity Ideal Solution approach and grey relational analysis among 16 alternatives. The processing parameters’ thermophysical properties and the environmental, safety, and economic conditions are optimized with multiresponse characteristics, including the viscosity, thermal conductivity, specific heat capacity, density of fluid, thermal diffusivity, ozone depletion potential, global warming potential, flammability, toxicity, and cost of the fluid. In the proposed technique, the grade ratings and weights allocated by decision-makers are averaged and normalized into a comparable scale. By comparing both these techniques, deionized water is selected as the perfect HTF to operate the solar thermal applications. Hence, both of the techniques are suitable to establish the best possible solution for the set of input parameters depending upon the required performance characteristics. This article highlights a novel vision into MCDM methods to evaluate the best HTF for the decision-makers such as solar manufactures and research and development engineers to meet the low-cost, quick, appropriate, and environmentally friendly fluid selection.

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