Kings Buildings, Hudson Beare Building, Classroom 4
Title: Process modelling and optimisation for low carbon technologies
The 4th carbon budget published by the UK Climate Change Committee (CCC) recommends pathways for the UK to reach the legally binding target of 80% CO2 emissions reductions by 2050 compared to 1990 levels. The CCC strategy for the decarbonation of the power sector by 2030 and beyond depends on a mix of different low-carbon technologies, e.g. offshore wind and CCS. However, these low carbon technologies are not yet competitive, cost and otherwise, with conventional energy conversion.
Mathematical and computational methods can play a crucial role in the development of low carbon technologies. Mathematical models are used for the analysis of experimental data to gain insight into different physical effects and to extract device and process parameters. Furthermore, mathematical models are used in combination with computational methods to optimise experiments and designs over a wide range of parameters and configurations. This is often faster and more cost effective than by experiments alone. However, to get the most from mathematical modelling it is crucial to have a good understanding of the engineering application and to validate the models against experimental data.
In this talk, I will give an overview of my research with particular emphasis on the use of mathematical methods in the design of Pressure Swing Adsorption (PSA) systems for carbon capture and the integration of Thermal Energy Storage (TES) systems in the wider energy landscape.
Daniel Friedrich received a Diplom in Technomathematik from Universität Karlsruhe (TH), Germany, in 2005. In the same year, he joined the Optoelectronics Research Centre at the University of Southampton, where he obtained his PhD in 2010. In 2009 he joined the School of Engineering, at the University of Edinburgh, to continue his research activity as a post-doctoral researcher and, in March 2013, he was appointed as a Chancellor’s Fellow in Mathematics for Engineering Applications. Daniel has been working extensively on the mathematical modelling and optimisation of engineering systems with particular focus on microfluidic systems and Pressure Swing Adsorption (PSA) systems. During his PhD he simulated and designed microfluidic systems for bioanalysis applications. This includes biosensors with improved analyte transport and microfluidic gradient generators. During his post-doc he developed a general adsorption cycle simulator which is used for the analysis of the experimental PSA systems in the adsorption lab and for the design of improved PSA cycle configurations for Carbon Capture and Storage and air separation. Since starting the fellowship, Daniel has started to broaden his research towards the simulation of Thermal Energy Storage systems.
The seminar team would like to thank the Engineering Graduate Society (EngGradSoc) for its funding and support of this seminar series.
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