Optimal design of heat exchangers using the progressive quadratic response surface model

The optimal values of the design variables which minimize the pressure loss under the required temperature rise are obtained numerically in a plate-fin heat sink. In thermal/fluid systems, three fundamental difficulties such as a high computational cost for function evaluations (i.e., pressure drop and thermal resistance), the absence of design sensitivity information, and the occurrence of numerical noise are commonly confronted. Thus, sequential approximate optimization (SAO) algorithms have been used to overcome the above mentioned problems. In the present work, the progressive quadratic response surface method (PQRSM), which is one of the SAO algorithms, is proposed for constrained nonlinear optimization problems and is coupled with the computational fluid dynamics (CFD) for the optimization of heat sink. The optimal solutions obtained from the PQRSM are also compared with those of the sequential quadratic programming (SQP) method, which is one of the gradient-based optimization algorithms, to validate the efficiency and fidelity of the PQRSM.