An estimation of the distillate output from a CSS based on multivariable regression analysis

In this research article, a multivariable regression model has been proposed for the estimation of the distillate yield from a conventional solar still (CSS). For a set of data comprising of distillate yield, water and glass temperature difference, solar radiation intensity, and atmospheric temperature as an input variable, a regression analysis has been performed to determine the coefficients and indices. The Distillate output, which is predicted by the proposed model, is compared with some of the available heat and mass transfer models. It has been observed that the proposed regression model has predicted the distillate output with a deviation of 1.16% from the experimental results. Whereas the models proposed by Dunkle, Tsilingiris and Kumar & Tiwari have deviations of 38.16%, 26.95% and 4.36%, respectively.