Predictions of vapor pressures of aqueous desiccants for cooling applications by using artificial neural networks

This paper presents a new approach based on artificial neural networks (ANNs) to determine the vapor pressure of three widely used inorganic desiccant solutions, namely, calcium chloride, lithium chloride, and lithium bromide. The vapor pressure of liquid desiccants depends on temperature and concentration. Empirical expressions generally provide vapor pressure with limited accuracy. Further, the expressions currently in use are tedious and valid for narrow ranges and must be adjusted constantly. In this paper neural networks were trained to predict vapor pressure of desiccant solutions with a reasonable accuracy without mathematical formulae. Trained neural network models provided wide ranges of vapor pressure for desiccant solutions without the need to cross reference several tables or charts. Results showed potential of using ANNs for the prediction of vapor pressure of desiccant solution for cooling applications.