This PhD thesis focused on developing advanced modeling and control strategies for a CO₂-based Thermal Compressor Heat Pump (TCHP), a thermally driven system proposed as an energy-efficient alternative to conventional gas boilers. The work first investigated the thermal compressor (TC) through a review of Stirling-type machines, an experimental campaign on a single-stage heat pump, and a finite-volume model that quantified exergy destruction and identified optimal operating conditions. Because this detailed model is too slow for dynamic simulations, several data-driven models were developed to provide fast and reliable predictions. The analysis was then extended to the complete three-stage TCHP cycle, combining experimental measurements with a dynamic FV model and reduced-order recurrent neural network representations of the system. Building on these tools, a model predictive control (MPC) strategy was designed to enhance the overall performance of the TCHP. The approach and its benefits were validated using both component-level and system-level experimental data.
Videoconference available on Teams
Antonino Federico Maria Torre will defend publicly his PhD thesis on "The experimental aerodynamics of a research high-speed low-pressure turbine stage" and on the PhD channel .
Nicolas Corthouts will defend publicly his PhD thesis on "A Monolithic High-Order Multi-Domain Solver for Inductively Coupled Plasma".
Ali Gholizadeh will defend publicly his PhD thesis on "Design and Characterization of a Microfluidic Well Plate for Advanced Liquid Handling and Sample Preparation: Applications in Proteomics".
