| Abstrakt: |
Thermal performance modeling and performance prediction of a solar still which is single basin single slope (SBSS) for the typical climatic condition of India at Jalandhar (31.3260° N, 75.5762° E) is analyzed in the present work. A numerical investigation of an SBSS solar still is conducted during the month of June 2022 using the ANSYS Fluent 2021 computational fluid dynamics (CFD) package and artificial neural network (ANN) prediction model. A user define function is written and used in fluent to formulate the problem with 9‐h solar radiation flux, on solar still glass surface. The simulation outcomes for surface temperature at three different water depths were compared with the existing experimental study. Water temperature and productivity of freshwater were well aligned with experimental results. Three‐dimensional domain is used with a two‐phase volume of fluid model for the condensation and evaporation processes in a solar still. The performance evaluation parameters, that is, coefficients of convective, evaporative, and radiative heat transfer, different temperature values, distillation output, and system efficiency were calculated numerically. The parametric analysis is expanded, and an ANN model in MATLAB R2020a is utilized to estimate yearly performance and reduce the high computational cost of numerical analysis. The data for solar radiation, design, and operational parameters are fed into the ANN model, and as a result, the water temperature at various depths is computed. The ANN model was trained using numerical results computed for the month of June and tested, showing 99.7% accuracy with CFD results. The annual performance of the solar still was evaluated using ANN models for 9 h of the day and with different boundary conditions. To decrease computational and experimental costs, the recommended technique of combined CFD and ANN models for computing the annual performance of (SBSS) solar still is the most effective option. [ABSTRACT FROM AUTHOR] |
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