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| Funder | Engineering and Physical Sciences Research Council |
|---|---|
| Recipient Organization | Imperial College London |
| Country | United Kingdom |
| Start Date | Sep 30, 2024 |
| End Date | Sep 29, 2028 |
| Duration | 1,460 days |
| Number of Grantees | 2 |
| Roles | Student; Supervisor |
| Data Source | UKRI Gateway to Research |
| Grant ID | 2930586 |
The mass exchanger is configured as a bank of microchannels through which, in the absorption phase, CO2-laden gas flows over liquid-infused trenches containing the immobilized CO2-reactive liquid sorbent (e.g., amine or ionic liquid).
Momentum, mass, and heat transfer effects are important in both phases; the sorbent phase adds the complexity of reacting species.
The mathematical models involve two-phase advection-diffusion-reaction systems of non-linear PDEs for the fluid flow, temperature and concentration fields for all species.
The PDEs are coupled through boundary conditions at the gas-liquid interfaces - velocity and shear stress continuity, temperature and heat flux continuity, and mass flux and a gas law (Henry's law) for the concentration equations. Longer term, additional boundary conditions will capture evaporation of the compounds in the sorbent solution.
The objective is to utilise mathematics to simplify and solve these equations and efficiently generate accurate solutions to use in general models of the impact of this device on global CO2 capture.
Direct numerical simulations will inform reduced-order models solved with spectral in-house codes, bridging analysis and CFD.
Furthermore, asymptotic methods will be applied to generate analytical or quasi-analytical models of the transport phenomena, providing useful, simple and physically informed expressions to be used in design, optimisation and estimates of large scale techno-economic models on the global impact of the devices.
These solutions will also be used in generating data for machine-learning implementations.
The project will be informed by planned partner experiments (Tufts, UT Austin) and the candidate is expected to visit and collaborate with the partner labs. resilience in the face of climate change.
Imperial College London
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