A Computational Approach for Optimization of Different Parameter of a Solar Air Heater with Smooth Flat Plate and Artificial Roughness

Teaching-Learning-Based Optimization (TLBO) is a newly and advance meta-heuristic optimization method adopted in this paper for optimizing a set of design and operating parameters for solar air heater. In this paper an attempt has been done to optimize the thermal performance of solar air heater with smooth flat plate and with artificially roughness by considering the different operating parameters. Thermal performance is obtained for different values of Reynolds number, Relative roughness pitch, Relative roughness height, Relative groove position and chamfered angle by using Teaching Learning base optimization algorithm. The result obtained from TLBO is more effective and efficient than the other optimization techniques which are consider for mechanical design optimization problems. The final results obtained from this algorithm are compared with experimental results and found to be satisfactory as far as flexibility, convergence rate and computational effort.