Modelling to Predict Moisture Ratio in Infrared Drying of Machine Plaster by Particle Swarm Optimization

Abstract

Background: Gypsum plaster is one of the most important building materials. The use of gypsum plasters is very common due to their many advantages. The drying process is an important stage in the production of gypsum materials and applications. Modelling of drying phenomenon can benefit drying technology. Recently, Particle Swarm Optimization (PSO) technique has been used to obtain optimum model equations for drying processes. Objective: The aim of this study was to determine a new modeling approach to infrared drying of machine plaster by using PSO. Methods: Experimental studies supplied by previous work in the literature have been performed by a laboratory scale infrared dryer in the temperature range of 50-70°C and at atmospheric conditions. Experimental moisture ratio values were compared with various mathematical model equations developed for the drying process by using Particle Swarm Optimization (PSO) technique. Results: Fitting tests indicate that the results obtained from the PSO technique are better than those of the previous study because of lower χ2, RMSE, and RSS values. The best model equation was the model equation based on the Newton drying equation existing in the previous study. However, the model equation derived by Modified Page has been determined as the most compatible model with the experimental data. Conclusion: It can be said that PSO is successively and reliably used to predict or optimize the experimental data of drying phenomena.