Multiobjective optimization for the optimal heat pipe working parameters based on Taguchi's design of experiments

Abstract

AbstractA heat pipe (HP) is a device transferring large quantities of heat through a small area of the cross‐section with very small deviations in temperature. The thermal impedance of HP is lower while thermal conductance is higher. HPs are designed for controlling temperature, amplification of heat flux, and diminution. HPs are being used in the cooling of aircraft and electronics, solar energy, systems of heat recovery, and nuclear reactors. Complex mathematical formulation demands experimentation to acquire the physical phenomena. Performing experiments is a tedious task with increasing the working parameters and their assigned levels. In such situations, a systematic statistical approach (viz., the Taguchi method) has to be adopted to minimize the number of experiments and to provide the information for the full factorial design of experiments. This paper adopts the modified Taguchi method and applies a simple and reliable multiobjective optimization concept to determine the optimal HP working parameters (viz., heat input, inclination angle, and flow rate). In the optimization process, efficiency, thermal resistance, and overall heat transfer coefficient are the performance indicators (PIs). Empirical relations are developed and validated for the PIs in terms of the HP working parameters. The recommended Taguchi's orthogonal array to perform a few tests may not have the set of optimal working parameters. Additional tests are to be performed to confirm the estimates of the PIs for the optimal working parameters. Confirmation test results in the present study indicate close‐to/within the estimated range.