Simulation and optimization of sludge hygienization research irradiator

This paper presents an approach to optimize a computational fluid dynamics problem coupled with radiation physics for sludge hygienization research irradiator. This was implemented by mapping results of computational fluid dynamics using recurrent artificial neural network with simplified dose rate evaluation using modified Sievert integral. This methodology led to considerable reduction of computation time while maintaining enough accuracy to validate the experimental results as well as suggest an optimum placement of source pencils using reference point based multi-objective optimization.