GHGT-16

Dr Jude Ejeh and Mathew Wilkes attended the 16th International Conference on Greenhouse Gas Control Technologies, 23-27th October 2022 in Lyon, France.
Dr Jude Ejeh presented work on 
Mathew Wilkes presented a techno-economic study of small-scale CO2 capture for dispatchable gas turbines. This work utilised process models developed in earlier publication and used the design parameters to calculate the levelized cost of electricity (LCOE) for dispatchable Gas-CCS.
ghgt16_mdw.pdf
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ESCAPE-32 
Several group members attended the 32nd European Symposium on Computer Aided Process Engineering, 12-15th June 2022 in Toulouse, France. 
Flora Biggins presented a poster on using energy storage to maximise wind farm profits under uncertainty. Findings suggest that adding a hydrogen electrolyser is more economical than a battery and allows greater for use of otherwise curtailed wind.​
Aaron Yeardley​ presented a poster on using predictive maintenance in the digital era. The research robustly tests machine learning algorithms on a large-scale cyber-physical production system using a rigorous comparative approach. The results showed methods adopted were accurate in predicting faults and suitable for predictive maintenance in the digital era. Finally, the work concluded by considering the importance of a predictive maintenance model in a design framework to be used as a tool to implement a successful maintenance schedule.
Mathew Wilkes delivered a keynote presentation on the flexible operation of vacuum-pressure swing adsorption (VPSA) for CO2 capture from modern gas turbines. The study highlighted VPSA is comparable to the benchmark MEA capture process.
Peter Bugryniec​
escape_2022_fb.pdf
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escape_2022_ay.pdf
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escape_2022_mw.pdf
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SAMO

Dr Robert Milton attended the Sensitivity Analysis of Model Outputs (SAMO) Conference, March 2022 in Tallahassee, Florida. He ​gave a talk on novel sensitivity analysis, with uncertainty quantification, of multiple outputs. He also presented a poster showing how this analysis can be used to dramatically reduce dimensions by locating an active subspace. 
samo_2022_presentation_-_milton.pptx
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samo_2022_poster_-_milton.pptx
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