Maximising the Performance of Complex Energy Systems

With increased interest in zero emission power and propulsion energy systems, there is a requirement for a method from which to choose the optimal system configuration and then maximise its performance for a specific application under given operating conditions. This is complicated further by rapid developments in specific component technology levels and sales market variation. A method is therefore required to quickly analyse and optimise the performance of these new, more complex cycles due to the inherent uncertainty of future technology levels and because current analysis methods, which use knowledge gained from previous experience to identify the best design parameters to optimise and improve system performance, cannot be used with these new complex cycles, due to the possible drastic changes in system architecture. Therefore, a new generalisable method is required to determine which parameter to optimise in each sub-system of a complex cycle, in order to maximise the performance of the cycle as a whole. Investigation into the limitations of current analysis methods has suggested a possible solution by including a consideration of the breakdown of individual exergy component performances in each component of the cycle in the analysis method. This will allow the real potential work of different cycles to be determined rather than the maximum potential work using perfect machines, as is determined in current total exergy calculations. This type of adjusted exergy analysis called 'Mechanical Work Potential' or 'Euergy' is outlined for a turbomachine in Miller 2013 [1], and has already been implemented successfully in Jardine 2019 [2] to explain the effect of turbine blade cooling on stage performance.
A set of key objectives that need to be met in order to reach the goal of the project are outlined as follows:
1. To expand current fuel cell low order models to include temperature and pressure effects, whilst also removing calibrated constants. Replacing them with non-dimensional groups to further the physical understanding of parameter changes on the performance characteristics. Also, to concentrate on improving the accuracy of models under varying operating conditions away from calibrated ranges.
2. To develop a combination of cycle analysis tools to allow rapid and accurate assessment of different power and propulsion cycles, with a focus on generalisable models for a wide range of user applications.
3. To understand and predict future technology levels to allow fair comparison of the future potential of different cycle performances through the developed cycle analysis tool.
4. To develop a generalisable method to find which parameter to optimise within each system component to maximise the performance of the cycle as a whole. This will be done by developing the current exergy and euergy analysis methods to include a consideration of the relative efficiencies of the energy systems at extracting different forms of exergy.
5. The overall goal is to be able to use the developed cycle tool, optimisation code and analysis method together to be able to answer questions such as, "Should I burn hydrogen in a gas turbine or react it in a fuel cell in order to provide best performance under a given set of operating conditions and criteria?"

[1] Miller, R. J. (2013) "Mechanical Work Potential." ASME Turbo Expo 2013: Power for Land, Sea and Air
[2] Jardine, J. L. and Miller, R. J. (2019) "The Effect of Heat Transfer on Turbine Performance." ASME Turbo Expo 2019: Power for Land, Sea and Air

1. Impact on the UK Aero-Propulsion and Power Generation Industry
The UK Propulsion and Power sector is undergoing disruptive change. Electrification is allowing a new generation of Urban Air Vehicles to be developed, with over 70 active programmes planning a first flight by 2024. In the middle of the aircraft market, companies like Airbus and Rolls-Royce, are developing boundary layer ingestion propulsion systems. At high speed, Reaction Engines Ltd are developing complex new air breathing engines. In the aero gas turbine sector Rolls-Royce is developing UltraFan, its first new architecture since the 1970s. In the turbocharger markets UK companies such as Cummins and Napier are developing advanced turbochargers for use in compounded engines with electrical drive trains. In the power generation sector, Mitsubishi Heavy Industries and Siemens are developing new gas turbines which have the capability for rapid start up to enable increased supply from renewables. In the domestic turbomachinery market, Dyson are developing a whole new range of miniature high speed compressors. All of these challenges require a new generation of engineers to be trained. These engineers will need a combination of the traditional Aero-thermal skills, and new Data Science and Systems Integration skills. The Centre has been specifically designed to meet this challenge.

Over the next 20 years, Rolls-Royce estimates that the global market opportunities in the gas turbine-related aftercare services will be worth over US$700 billion. Gas turbines will have 'Digital Twins' which are continually updated using engine health data. To ensure that the UK leads this field it is important that a new generation of engineer is trained in both the underpinning Aero-thermal knowledge and in new Data Science techniques. The Centre will provide this training by linking the University and Industry Partners with the Alan Turing Institute, and with industrial data labs such as R2 Data Labs at Rolls-Royce and the 'MindSphere' centres at Siemens.

2. Impact on UK Propulsion and Power Research Landscape
The three partner institutions (Cambridge, Oxford and Loughborough) are closely linked to the broader UK Propulsion and Power community. This is through collaborations with universities such as Imperial, Cranfield, Southampton, Bath, Surrey and Sussex. This will allow the research knowledge developed in the Centre to benefit the whole of the UK Propulsion and Power research community.

The Centre will also have impact on the Data Science research community through links with the CDT in Data Centric Engineering (DCE) at Imperial College and with the Alan Turning Institute. This will allow cross-fertilization of ideas related to data science and the use of advanced data analytics in the Propulsion and Power sectors.

3. Impact of training a new generation of engineering students
The cohort-based training programme of the current CDT in Gas Turbine Aerodynamics has proved highly successful. The Centre's independent Advisory Group has noted that the multi-institution, multi-disciplinary nature of the Centre is unique within the global gas turbine training community, and the feedback from cohorts of current students has been extremely positive (92% satisfaction rating in the 2015 PRES survey). The new CDT in Future Propulsion and Power will combine the core underlying Aero-thermal knowledge of the previous CDT with the Data Science and Systems Integration skills required to meet the challenges of the next generation. This will provide the UK with a unique cohort of at least 90 students trained both to understand the real aero-thermal problems and to have the Data Science and Systems Integration skills necessary to solve the challenges of the future.