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Details of Grant 

EPSRC Reference: EP/T033800/1
Title: Optimal fuel blends for ammonia fuelled thermal propulsion systems
Principal Investigator: Paykani, Dr A
Other Investigators:
Valera-Medina, Dr A
Researcher Co-Investigators:
Project Partners:
University of Connecticut
Department: School of Engineering and Technology
Organisation: University of Hertfordshire
Scheme: New Investigator Award
Starts: 01 August 2020 Ends: 31 July 2022 Value (£): 204,705
EPSRC Research Topic Classifications:
Combustion Fluid Dynamics
EPSRC Industrial Sector Classifications:
No relevance to Underpinning Sectors
Related Grants:
Panel History:
Panel DatePanel NameOutcome
10 Jun 2020 Engineering Prioritisation Panel Meeting 10 and 11 June 2020 Announced
Summary on Grant Application Form
Renewable, carbon-free fuels as well as optimised combustion systems have recently drawn a lot of attention in engine research to further reduce emissions of criteria pollutants and greenhouse gases (GHGs) in transport. Whilst significant investment is being currently allocated to electric and Electrochemical energy systems, there remains significant doubts as to whether batteries will provide cost-effective national energy security over medium-duration periods. Moreover, the transport sector produces about 10% of the world's GHG emissions and replacing combustion engines with "zero emission" alternatives has only a limited potential in reducing global GHG emissions. Since around 80% of useful energy such as heat, propulsion energy and electricity is produced via combustion processes and due to the high energy density and storability of fuels, combustion will remain for several decade the technologically, economically and ecologically best solution for many applications in transport and power generation.

The UK's long-term emissions target is currently for a 100% reduction in GHG emissions by 2050 compared to 1990. Meeting future UK carbon budgets will require the grand challenge of carbon-free energy systems to be addressed. Ammonia (NH3) has been identified as one of the most promising hydrogen energy carriers, and will play an important role during the process of decarbonisation of power sector and transport. Ammonia is carbon-free, has no direct GHG effect, and can be synthesised with an entirely carbon-free process from renewable power sources. The greatest advantage of ammonia is its high energy density (comparable to that of fossil fuels), which makes it an effective fuel and energy storage option. Studies have shown that to make ammonia a viable fuel in combustion engines, it needs to be mixed with other fuels (e.g., hydrogen) as combustion promoters due to ammonia's low flame speed and high resistance to auto-ignition.

Gas turbines are high-efficiency candidates for use of ammonia and have the potential to reduce the cost per kWh produced whilst providing clean, green energy for power generation and propulsion systems. Although, recent studies have shown that ammonia/hydrogen blends could be burned efficiently with low emissions and high efficiencies in gas turbines, they require optimisation study in terms of choice of fuel composition and development of advanced injection strategies to achieve acceptable NOx levels while maintaining high thermal efficiencies.

The aim of the proposed project is to develop a computationally cost-effective numerical tool for Co-Optimisation of fuel blend and combustion system in a systematic way, and to examine how the conflicting requirements can be met by adding gaseous fuels (e.g., methane, hydrogen and syngas) to ammonia so that engine can be operated stably and reliably with improved thermal efficiency and minimal NOx emissions. This computational study requires development of a reduced reaction mechanism for fuel blends with the goal of further reduction in the number of reactions under engine relevant conditions. While computational fluid dynamics (CFD) simulations in combination with reaction mechanisms can capture complex phenomena with high accuracy, they have high computational cost and, therefore, are not efficient for the optimisation studies. Thus, a reliable and comprehensive 0D phenomenological model with reduced chemistry will be developed for combustion modelling of the engine fuelled with ammonia-based fuel blends. A genetic algorithm (GA) optimisation model coupled to the 0D model will be developed to simultaneously optimise fuel composition and engine input parameters(e.g., fuel injection strategy, inlet conditions, equivalence ratio). Finally, the performance of the optimal blend and optimised engine parameters will be experimentally studied in the relevant engine experiments at Gas Turbine Research Centre (GTRC), in Cardiff University.
Key Findings
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Organisation Website: http://www.herts.ac.uk