Estimation of Interfacial Evaporative Heat Flux using Inverse Heat Transfer Framework for Passive Solar Distillation System

Abstract

In the present study, a methodology is developed to estimate the evaporative heat flux in a solar still mimicking configuration. A distributed heat transfer analysis utilizing the air-water interface temperature instead of bulk temperature of water (lumped analysis) is performed to develop an improved correlation, for predicting interfacial evaporative heat flux. The physical problem is simulated numerically using the method of finite-differences. A surrogate model closely mimicking the physical problem is then developed using artificial neural networks to improve the computational economy. The surrogate model is combined with genetic algorithm in an inverse framework to estimate the parameters of the proposed correlation. Depth of water in the solar still is explicitly included in the correlation to study its effect on the rate of evaporation at the air-water interface. The parameters of the proposed correlation are estimated for a given water depths and initial water temperature using simulated measurements obtained from an ab initio model of simultaneous heat and mass transfer for the considered air-water system.