Abstract
ABSTRACT Conventional single slope solar still integrated with a parabolic trough collector in addition to packaged glass ball layer was used in water desalination. Experimental work carried and data obtained were used in modeling the influential parameters affecting water desalination using principal component analysis to reduce parameters’ numbers. These parameters were then applied in constructing a Response Surface Model (RSM). System’s Performance has been predicted in terms of temperatures; saline water temperatures (Tw), glass cover temperatures (Tg), dry bulb temperature (Tdb), and wet bulb temperature (Twb) inside the conventional solar still. Along with the above temperatures, ambient air temperature (Ta), Oil inlet temperature (Toi) and solar intensity (I). The impact of these parameters can highly effect the water desalination yield. The RSM is developed to predict the impact of these parameters. Principal Component Analysis (PCA) reduced and categorized the number of effective parameters to three components containing the parameters (Tw, Twb, and Tdb), (I, Ta, and Tg) and (Ta, Toi, and I) respectively. These combinations were then tested using the two different RSM optimized models; Modified Reduced Quadratic and Two-Factor Interaction (2FI) model. These models were tested by monitoring nine statistical indices namely: RMSE, P-value, F-value, R2, R2 adj, R2 pred, BIC, PRESS, and AICc. Results obtained for this model showed minimum RMSE value and higher values of R2, R2 adj and R2 pred as well as lowest values for BIC and AICc. Concluding supremacy of (I, Ta, and Tg) Modified Reduced 2FI model over the others.
Published Version
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