Integrated steam production design and control using physics-based non-linear MPC as system int[...]

Integrated steam production design and control using physics-based non-linear MPC as system integrator

At the division of Applied Mechanics and Energy Conversion (TME) of the Department of Mechanical Engineering at KU Leuven, the Thermal Systems Simulation (The SySi) Team aims to sustainably use resources through integration and optimisation of thermal systems performance in the built and industrial environment, including other energy vectors. System integration is key and we leverage profound domain knowledge with advanced modelling and optimization techniques to get there.
Their scientific expertise can mainly be found in: (1) physics-based modelling and simulation, (2) integrated optimal control and design (co-design); (3) field tests and real-life demonstrations to verify and validate models and methods as a proof-of-concept. Starting from domain knowledge is key.
Research topics (most of them investigated in the frame of PhD research) include among others: data-enriched physics-based modelling, Model Predictive Control (MPC), Building (and District) Optimization Testing Framework (B(D)OPTEST), collective concepts for clusters of buildings, multi-sectorial integration, thermal networks (THERNET) for heating and cooling, flexibility through Demand Response (DR) in multi energy vector systems, including uncertainties towards robust design and robust control.
The SySi Team, led by prof. Lieve Helsen, has gained significant expertise and international recognition in the field of system integration for performance optimisation of thermal systems. White-box MPC in large buildings is being commercialised through the start-up BUILTWINS. Today, The SySi Team consists of 1 professor, 1 innovation manager, 2 post-doctoral researchers and 3 PhD students. In Fall 2026 the group will be extended with 2 researchers. The research has very close links and is integrated within EnergyVille, a research collaboration between KU Leuven, VITO, imec and UHasselt on sustainable energy and intelligent energy systems.

This PhD position is framed in the FLEX-SMR project (Integration of Small Modular Reactors in the Chemical Industry), funded by the Belgian Energy Transition Fund. FLEX-SMR is a collaboration between three research teams of KU Leuven (focusing respectively on the nuclear reactors, the thermal systems and the energy market) and two companies: The Binding Energy and INEOS-INOVYN. FLEX-SMR will develop cost-effective, integrated solutions to provide flexible electricity and steam supply for chemical production sites. The project will advance control strategies and optimize the design of the nuclear-based steam plant and its supporting systems to ensure safe, reliable, and cost-effective steam production.

The PhD position in The SySi Team will focus on the integrated steam system design and control in a multi-energy vector context, using physics-based non-linear Model Predictive Control (MPC). To this end, the current in-house physics-based MPC workflow (tailored to the built environment) needs to be transferred to steam processes in the chemical industry. This MPC is then incorporated in a co-design framework (integrated optimal control and sizing) for the steam system to determine optimal component sizes, while exploiting flexibility, intrinsically available in the chemical processes and/or utility system, or added through storage technologies. The PhD student will work in close interaction with the two PhD students of the other KU Leuven teams and a post-doctoral researcher, assisted by the innovation manager Dr. Glenn Reynders and supervised by Prof. Lieve Helsen, in collaboration with The Binding Energy and INEOS-INOVYN.

Profile

We are looking for a highly motivated, enthusiastic, dynamic, mobile and communicative researcher with a Master of Science degree in Engineering (preferably mechanical, energy, chemical or computer science). The candidate should have a strong background and interest in energy, and especially in thermal energy systems (for steam production), (optimal) control (MPC), physics-based modelling and optimization. Numerical optimization, scientific computing (in C/C++) and general coding (python, Java) are important parts of this PhD track. The candidate starts from insights in the system and physics-based modelling. Data-driven approaches are not the focus of this project.

The candidate is expected to:

• Be proficient in English (spoken and written) to allow effective communication
• Be able to work independently, accurately and methodically
• Be a team player, using the multidisciplinary network offered
• Be an active player in the broader team, attending brainstorm sessions, sharing approaches, insights and vision
• Present research findings at national and international conferences
• Publish research findings in international top-journals
• Contribute to the FLEX-SMR project as one of the main r