The focus of the PSE 4.0 research group is on applying and developing mathematical toolboxes. The toolboxes enable effective and inherent communication of data and process at the multi-scale level. The computational approach is an efficient way to virtually connect multi-facet information for a complete view to support different decision making levels from process and product design to operation. Anticipating the needed changes for the climate objectives, all products, process design and operation need to cope with the intrinsic intermittent fluctuation of renewable energy and recycling in addition to efficiency. Hence, the approach is believed to have a strong position to review radically state-of-the-art complex processes, give detail insight for design, development and optimization new products and innovative processes in a holistic view ensuring environmental and economic values. Considering the system characterization via the entire life cycle, the PSE calibrated toolboxes target as well for sustainable operation via user friendly digital virtual deployment on cyber physical systems.
To achieve the target globally, three main research pillars are embedded in PSE 4.0 group:
- Development of physical-based models at different scales from thermodynamics, kinetics, and process units in close collaboration with experimental partners. The developed models provide a fundamental platform for further steps such as: sensitivity analysis, process and product design, and process integration and intensification as well as optimization. The model framework will follow modular approach that can be transversely applied in multidisciplinary environment, especially focusing on battery, electrolysis and pharmaceutical processes.
- Development of data science approach for various source of data to provide templates and guidelines for data processing, data-driven-modeling approaches and further interface deployment. With the ever increasing power of data analytics, the data in different size and format can be seen as a critical raw material for knowledge extraction and agile decision-making support in different processes, especially in real-time information that reflects changes in the processes, characterizes uncertainty, and indicates emerging situations.
- Complete integration of data-driven based models and physical based models in one holistic, connected and integrated platform for value creation in term of supporting global and aggressive design, optimization and operation.