Abstract
Overall Conductance is considered to be the most important parameter to design hot water storage tank. This is computed in terms of equivalent thermal resistance considering the total heat loss from hot water storage tank. Computed results attained have been confirmed with an Artificial Neural Network (ANN) with three design input data. The back-propagation learning algorithm with the Levenberg–Marguardt (LM) was used in the artificial neural network with 608 known values. Thus, the network was prepared to provide various possible designs of hot water storage tank quickly and accurately. A maximum error of 2.62% was obtained with an ANN. Therefore, proposed innovative design approach can successfully be used for the designing of Overall Conductance of hot water storage tank in solar water heating system. In present work total 612 design combinations used which includes the diameter of the tank, thickness of insulation and conductivity of insulating material.
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