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Reference Number EP/J020184/2
Title Computational Modelling and Optimisation of Carbon Capture Reactors
Status Completed
Energy Categories FOSSIL FUELS: OIL, GAS and COAL(CO2 Capture and Storage, CO2 capture/separation) 100%;
Research Types Basic and strategic applied research 100%
Science and Technology Fields ENGINEERING AND TECHNOLOGY (Chemical Engineering) 50%;
ENGINEERING AND TECHNOLOGY (Mechanical, Aeronautical and Manufacturing Engineering) 50%;
UKERC Cross Cutting Characterisation Not Cross-cutting 100%
Principal Investigator Dr S (Sai ) Gu
No email address given
School of Engineering
Cranfield University
Award Type Standard
Funding Source EPSRC
Start Date 12 September 2015
End Date 11 November 2017
Duration 26 months
Total Grant Value £227,091
Industrial Sectors Energy
Region East of England
Programme Energy : Energy
 
Investigators Principal Investigator Dr S (Sai ) Gu , School of Engineering, Cranfield University (99.999%)
  Other Investigator Professor K Luo , School of Engineering Sciences, University of Southampton (0.001%)
  Industrial Collaborator Project Contact , E.ON New Build and Technology Ltd (0.000%)
Web Site
Objectives
Abstract This programme is proposed to answer the EPSRC call on "Carbon capture and storage for natural gas power stations" by forming a close partnership between the University of Southampton and E.ON. The proposed research has a strong focus on industrial needs by integrating with the industrial partner's existing activities for developing CCS technologies suitable for commercial gas power plants. E.ON is generating around 10% of the UK's electricity and is committed to reducing its CO2 emission by 50% by 2030 (1990 baseline). E.ON has setup a dedicated CCS unit to address the technical challenges while one of the priorities is to develop CCS technologies suitable for natural gas power stations. This research specifically targets at natural gas power plants, which has a lower concentration of CO2 approx. 4% compared to 13% from coal-fired plants, and harder to extract, representing the most challenging case for CCS.Carbon capture and storage involves separating the CO2 from emissions so it can be transported and stored away from the atmosphere. The most commercially viable approach to be fitted in natural gas power plants is the post-combustion capture which absorbs CO2 from the flue gas using a chemical reaction - also known as scrubbing, which E.ON has been actively pursuing and will be the focus of this research. Whilst research on the chemical processes has been taking place for several decades, CFD modelling of the reactor is a recent development. E.ON has recognised that CFD plays a vital role in the optimisation of current CCS reactors by including more CFD research in their future research strategy. University of Southampton is a prime place for CFD based research while the School of Engineering Sciences currently holds 5M CFD focused EPSRC projects. The combined expertise forms a strong academic and industrial partnership to tackle current barriers of reactor scale-up in carbon capture using advanced CFD models. By addressing all the challenges outlined in te EPSRC call, this research aims to design an optimised reactor using a novel CFD modelling approach that is capable of achieving in excess of 90% CO2 absorption whilst ensuring the cost of service energy is minimised to below 35%. The new concept idea will incorporate improved mixing designs and improved heat transfer whilst reducing reactor size. It is planned through the enhancement of current CFD multiphase models to incorporate reaction and the inclusion of flow control devices that an optimal structured packing arrangement, which promotes the reaction process whilst reducing pressure drop, can be found. This project will not only produce conceptual ideas developed through enhance CFD methods but will also perform tests, in a lab-scale reactor, to determine its validity with respect to its flow dynamics and would potentially lead to the production of intellectual property
Publications (none)
Final Report (none)
Added to Database 23/02/16