The PhD project focuses on modelling and optimizing carbon capture processes by evaluating uncertainties present and applying optimization techniques to enhance process performance.
The PhD project titled “Modelling and Optimization of Carbon Capture Processes”, part of CERE's CapSim project, aims to develop robust and accurate computational tools to be used within process simulators for the simulation and optimization of CO₂ capture systems.
Central to this work is the application of uncertainty analysis to systematically evaluate the distribution of various parameters, process input values, and the dependencies among them.
Uncertainties can be present in thermodynamic model, mass transfer model, reaction kinetics as well as process parameters.
Once uncertainties have been quantified, the project will investigate how this parametric uncertainty propagates throughout the process model and how it affects carbon capture efficiency, CO₂ purity, reboiler duty, solvent degradation rate, and other key performance indicators.
Effectively, at this stage, we will perform a sensitivity analysis to evaluate how parametric uncertainty generates process output uncertainty and will seek to provide insight into the discrepancies between pilot plant data and process simulation.
Using these insights, the project will apply multilevel process optimization methods to enhance the performance of carbon capture systems in terms of design, analysis, and operation.
The project will focus on classical amine-based aqueous solvent systems as well as alternative solvents such as chilled ammonia, potassium carbonate solutions, demixing (phase-change) solvents, non-aqueous solvents, ionic liquids, and others.
The expected outcome is a set of accurate and robust software tools to be used in process simulators for both standard and novel carbon capture systems.
Main supervisor:
Nicolas Von Solms
Co- supervisors:
Phillip Loldrup Fosbøl
Xiaodong Liang