Enhancing design and efficiency of rotating thermal processors: a modeling and experimental approach

Rotating thermal processing equipment plays a pivotal role in industry, providing the controlled and uniform heating essential for processing bulk materials. Optimizing such equipment depends on understanding the dynamics of the system, as this has a direct impact on energy consumption, processing time, and the mechanical integrity of the materials involved. This PhD project will investigate the optimization of granular material behavior in rotating thermal processing equipment using the Discrete Element Method (DEM) for simulations complemented by experimental validations. DEM simulations will be performed to model discrete particle interactions in order to optimize the dynamical behavior of these materials. Experimental work will validate and refine these models to ensure their accuracy and applicability in industrial settings. The synergy of simulation and experimental results aims to improve equipment design and process efficiency, with broader implications for the materials processing industry.

Required education and skills

• Master’s degree in chemical engineering, mathematical modeling, and computer science;
• high motivation, willingness to learn new things; team spirit.