Neural Network Based Assessment the performance of the triangular in-tegrated collector

Abstract

A numerical study was achieved on a new design of storage solar collector by using neural network (NN). The storage collector is a triangular face and a right triangular pyramid for the volumetric shape. It is obtained by cutting a cube from one upper corner at 45o, down to the opposite hypotenuse of the base of the cube. The numerical study was carried out using the computational fluid dynamics code (ANSYS-Fluent) software with natural convection phenomenon in the pyramid enclosure. The results show that, the temperature and velocity distributions throughout the operating period were obtained. The influence of introducing an internal partition inside the triangular storage collector was investigated. Also the optimum geometry and location for this partition were obtained. The enhancement was best at y= 0.25 m whereas the height of triangular collector was 0.5 m. The hourly system performance was evaluated for all test conditions. The performance of the NN to train a model for this work was 0.000207, while the error of the calculation was 1*10^-2 as average.