Coupled effects of corrugation and rotation on the phase transition and thermal process in a vented cavity under MHD convection - Selimefendigil, Fatih; Öztop, Hakan Fehmi (Elsevier, 2024)
Therefore, for effective usage of PCMs in thermal systems, novel methods for phase change process control such as geometry modification and incorporating different boundary conditions can be adopted. In this study, phase transition and thermal process in a triangular shaped wavy enclosure equipped with spherical shaped encapsulated PCM are explored under magneto-convection of nanofluid. The inner walls of region where PCM is embedded is rotating and sinusoidal form of corrugation is considered for the wavy wall of the triangular cavity. Numerical calculations are done for different values of Re (200 <= Re <= 1000), Rew (-2500 <= Rew <= 2500), Ha (0 <= Ha <= 60), wave amplitude (0 <= Ap <= 0.1H) and wave frequency (2 <= Np <= 8). It is observed that when rotations are active at Rew=100, phase transition time (TF) is reduced by 12.5% while it is increased by 16.6% at Rew=0. Magnetic field is effective when used without rotation of the inner part. The amount of reduction of TF with magnetic field at the highest strength is obtained as 15.8%. The heat transfer is reduced with higher Ha for stationary and rotating cases while reduction amount up to 14% can be achieved. Amplitude of the wavy form of cavity wall is influential on the phase change process at Rew=0 and TF is reduced by about 14.5%. The contribution of amplitude and frequency of the wave form on the heat transfer is very slight. Optimum parameter set for lowest TF is obtained at (Re, Rew, Ha, Ap, Np) = (600, 2500, 60, 0.075H, 2) while for highest heat transfer rate it becomes (Re, Rew, Ha, Ap, Np) = (1000, 2500, 0, 0.1H, 8). Generalized neural network based modeling is found to be an efficient way of predicting the time dependent behavior of phase change process with respect to changes in operating parameters such as Re, Rew and Ha.
Keywords: Wavy vented cavity; Rotation; Phase change material; Computational fluid dynamics; Generalized neural network