Process systems engineering (PSE)
We aim to develop and pioneer innovative application of PSE methods and tools and their validation with data across different production scales (from pilot to full-scale manufacturing) in collaboration with our industrial partners and experimental research centers across DTU Chemical Engineering. Our emphasis is on validation of models, methods and tools that we research and develop at industrial relevant scale and data. This is achieved through close collaboration with our industrial partners from Denmark (with strong biotech and biopharma focus) and international companies (see e.g. KT Consortium) mainly from fermentation, bio/pharmaceuticals, food and environmental biotechnology and renewable fuels and chemicals. Ultimately, we aim to contribute to development of cost-competitive processing and manufacturing excellence in targeted process industries and help them realize a sustainable and circular economy vision.
Our research aims at developing systematic methodologies embedded in computer-aided frameworks for efficient and reliable process simulation; for systematic synthesis, design and analysis of sustainable chemical products and their manufacturing processes; for robust control, operation and monitoring of processes. These can range from industrial scale processes in chemical, bio-/pharmaceutical and agro-chemical industries to microsystems, and more recently also extended to molecular and bio-molecular systems.
To this end, computer-aided systems are developed based on fundamental and/or data-based modelling studies that incorporate correlation and estimation of thermo-physical and phase equilibrium properties as well as modelling the underlying principles and behaviour of the processes and products. While the application horizon is wide (oil and gas, petrochemical, chemical and specialty chemical, pharmaceutical, food, water and bio-based industrial sectors), the focus is on the use of a systems approach which enables managing the complexity of product-process development challenges in an efficient manner. With respect to methodological research, we are combining traditional model-based PSE tools and methods with emerging data-based approaches including big data analytics and machine learning methods and tools.
Our research keywords include the following PSE areas: Process intensification & synthesis, Process Design, Predictive modeling (Artificial Intelligence(AI), Machine Learning (ML), Mechanistic Modelling), Process Operation/control (modern control theory + AI), Property prediction, Design of chemicals, Integrated process & product design, Monte Carlo Simulations (Global Uncertainty and Sensitivity Analysis).
Dissemination activities: We contribute to the management of the KT industrial consortium together with the AT-CERE research center to disseminate our results and engage with our industrial stakeholders. We also organize international workshops and summer schools in important PSE thematic areas (global uncertainty and sensitivity analysis, optimization, process synthesis and design, PAT for crystallization, …). PROSYS faculty regularly contribute with editing special issue/research topics in a number of open source publications (Frontiers energy and process systems engineering, MDBI PROCESS, etc) as well as we contribute to creating a web-based hub and repository for the global PSE community (LAPSE).