Fuzzy TOPSIS optimization of MHD trihybrid nanofluid in heat pipes

Heat pipes have the potential to benefit from nanofluid flow between coaxial cylinders. Heat is effectively transferred from one place to another by means of heat pipes. Heat pipes can be used for electronics cooling, spacecraft thermal management, and heat recovery systems by adding nanofluids, which enhances the heat pipe's thermal conductivity and heat transfer capability. This work aims to discover an approximate solution for the flow of a trihybrid nanofluid (THNF) consisting of graphene, copper, and silver between two coaxial cylinders in magneto-hydrodynamics, taking into account the broad variety of applications. The nanomaterial is tested in a system with a fixed inner cylinder and a rotating outer cylinder. It contains graphene, copper, silver, and kerosene oil as the base fluid. For examining the flow characteristics, magnetic field is applied along radial direction of the cylinder, while inner cylinder is fixed, and outer cylinder is rotating. Moreover, temperature of the outer cylinder is higher than the lower cylinder. The objective of this study is to develop a mathematical model of the problem and solve the governing equation numerically using the MATLAB built-in routine called bvp4c. Additionally, we identify the most effective physical parameter to optimize the heat transfer rate using Fuzzy Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS). Using a variety of factors, we calculate fluid velocity, skin friction, temperature, and Nusselt number graphically. According to the study, higher Brinkman numbers $\left(Br\right)$ and magnetic parameter $\left(M\right)$ characteristics lead to higher temperatures. Furthermore, Fuzzy TOPSIS shows that alternative A11 $\left(\varphi =\left(0.9,1.0,1.0\right),M=\left(0.5,0.7,0.9\right),Br=\left(0.9,1.0,1.0\right)\right)$ has the maximum heat transfer rate, while another A8 $\left(\varphi =\left(0,0,0.1\right),M=\left(0,0,0.1\right),Br=\left(0,0,0.1\right)\right)$ has the lowest.