The visionary objective of this project is to develop an upscaling technology through the concept of a digital twin for thermal processing of raw material in industry-scale reactors. A digital twin offers opportunities to improve processes by increasing efficiency, quality and performance.
Furthermore, it enables engineers to communicate with ease designs to team members, manufactures and prospective clients. Thus, a digital twin contributes to a more time and cost-effective product development that in return offers a faster economic growth at higher profit margins.
The Extended Discrete Element Method (XDEM) developed at the University of Luxembourg by Peters is an advanced numerical simulation technology for generating a digital twin with desired up-scaling capabilities. The project is to apply the XDEM technology to both tungsten oxide reduction and a blast furnace.
It is believed that these applications spanning already a large geometrical length scale from powder to cm-sized ore particles are well suited to proof the predictive capabilities of XDEM for a digital twin. Both engineering applications are carried out by 2 post-doctoral students, respectively.
They will employ the advanced features of the XDEM software platform to predict the above-mentioned processes in particular tungsten oxide reduction for hard metal processing and steel making in a blast furnace.
A significant part of the work includes a comparison with experimental data as to validate the concept of a digital twin and to offer the opportunity to improve its concept.