A comprehensive parametric study on heat transfer optimization of a triangular enclosure subjected to a magnetic field using neural network machine learning. (December 2022) - Vahedi, Seyed Masoud
Abstract: The free heat convection of Al2 O3 -water nanofluids considering the radiation effects in an isosceles right triangle under the influence of a uniform magnetic field is numerically simulated. The SIMPLE algorithm is used in a staggered-grid structure to study the effects of Rayleigh number, Ra, Hartmann number, Ha, the location and the length of the hot part, solid volume fraction, radiation parameter, and the angles of the magnetic field and enclosure on the flow characteristics, heat transfer, entropy generation. The results show that the heater length and the radiation strength are the two most effective factors, followed by Ra and Ha . The maximum potential of the enclosure to reach the highest heat transfer rate is shown to be 22 times in Nu ave, which is accompanied by a mere 7 times increase in entropy generation. In the best and worst cases of design, with respect to the second law of thermodynamics, the entropy generation does not increase significantly. Sensitivity analysis indicates that designers should not be casual about the length of the heater as it has the highest impact on the Nu ave and S tot necessitating paying much attention to its tolerance, especially in its larger values.