Predication of air velocity in Solar Chimney using RBFNN

Summary

A radial basis function neural network is trained on analytically generated data to estimate peak airflow speed in a solar chimney used to cool photovoltaic panels, taking chimney height, width, thickness and wall temperature as inputs. Its predictions agree closely with the analytical values, and they are also used to estimate how much the panel temperature drops.

Description written by Solar Tower. The original abstract is available from the publisher via the link below.