Modeling and optimization for solvent removal coupled with moisture adsorption in pre-drying of propellant grains

Abstract

Pre-drying is a crucial step for removing excess solvents from nitrocellulose-based propellants. This study aims to optimize the multi-coupled mass transfer and thermal transport processes involved in the industrial-scale pre-drying of propellant grains. Dynamic modeling and statistical analyses were used to develop predictive models for the volatiles content in propellant grains and to evaluate the significance of process parameters. A multi-objective optimization algorithm was applied to determine the optimal pre-drying conditions, considering quality metrics and the range of process parameters used in actual production. Air temperature was the primary factor influencing changes in the liquid ethanol and moisture contents within propellant grains, whereas processing time predominantly affected the variation in liquid ether content. Higher air temperature and mass flow rate enhanced solvent removal during the initial stage of pre-drying. Raising air temperature increased the moisture adsorption rate during the early stages of pre-drying and improved the moisture adsorption capacity of the propellant grains. The optimal conditions were identified as an air temperature of 316.4 K, relative humidity of 86.5 %, mass flow rate of 361.7 kg·h⁻¹, and processing time of 113.6 min. The predictive models for volatiles content in propellant grains exhibit high accuracy and can effectively guide industrial production processes.