Exploiting DNS in 3D Design

Research Aims
Currently, unsteady numerical studies with DNS still rely on time averaged quantities. This means that, even today, unsteady flows are still viewed from a fundamentally steady point of view with no existing framework to switch to a truly unsteady perspective. Establishing a truly unsteady framework with which to characterise flows is the first aim of this project.

Following on from this, the unsteady framework developed will be applied to a radial impeller to predict the unsteady losses, especially from the gap between the blade tip and the wall (tip gap). This serves to fill two gaps in knowledge: firstly, it is currently known that reducing the tip gap in radial impellers reduces the loss, but it is still unknown how the loss can be reduced for a fixed tip gap e.g. if it minimum tip gap is limited by manufacturing constraints. Secondly, the ability to predict radial impeller performance lags behind that for axial compressors. Achieving this aim will provide a step forward in reducing this discrepancy.

Finally, from the DNS data and unsteady framework, develop a reduced order model for radial impeller loss that is fast enough to be used in the 3D design stage.

Research Approach

To achieve the first aim, DNS will be performed on a cascade version of the radial impeller (this is a simpler version of the geometry) in order to test different unsteady frameworks.

Once a framework has been selected, the second aim will be achieved by performing DNS of the full radial impeller geometry with tip gaps under full operating conditions. Using the unsteady framework, unsteady flow behaviour can be linked to loss which will allow prediction of radial impeller performance.

Methodology for achieving the third aim will likely involve the identification of the flow features within a radial impeller which dominates loss, with others being stripped from the loss prediction model.

Novel Engineering/Physical Sciences

Truly unsteady framework for characterising unsteady and turbulent flows
Development of loss reduction methods in radial impellers with a fixed tip gap
Higher accuracy radial impeller performance prediction

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.