Mathematical modeling of melting point and viscosity of a new molten salt for concentrating solar plant

Selecting the best type of molten medium as energy storage needs a good insight into various properties, which change with temperature and the combination of different compositions. This research aims to understand the influences of the temperature and composition of different mass percent of metal nitrates on the viscosity and thermal conductivity of new molten salt for concentrating solar plants. The experimental outcomes indicate that the viscosity of molten salt strongly changes with the salt composition. In addition, the thermal conductivity and density of molten salt composed of 30 mass% LiNO3, 13 mass% NaNO3, and 57 mass% KNO3 with increasing temperature experience severe decrement. To determine useful correlations for the melting point and viscosity of proposed molten salt, an Artificial Neural Network based on the Group Method of Data Handling is employed. Two polynomials for melting point temperature and viscosity of molten salt are carried out. Results indicate that suggested models predict the experimental values for viscosity and melting point temperature with high accuracy. Calculations of $${R}^{2}$$ values for viscosity and melting pointe are 0.9289 and 0.9678 that show reasonable accuracy of models.