Physics informed machine learning for fluid dynamics

Lead Research Organisation: University of Leeds
Department Name: Sch of Computing

Abstract

This will be a fundamental project that looks to develop new approaches to combine deep learning and physics-based models in order to improve simulation capabilities in fluid dynamics. The first phase of the project will be to gain awareness and understanding of the approaches that have been developed in the past three years, before identifying the areas/approaches that will be targeted for focus in this project.

Planned Impact

The CDT will address the continued need of the UK for highly trained graduates in Fluid Dynamics and deliver impact through the novel research conducted by CDT students. The impact and benefits will reach multiple stakeholders.

Impacts on Skills and People:

Key beneficiaries of the CDT will be the alumni of our current and future programme and the organisations who employ them. Through the technical and professional development training, and the CDT environment, our graduates will have expertise in fundamental theory, analytical and numerical approaches, experimental techniques and application, and in-depth technical knowledge in their PhD area. Moreover they will have leadership, communication, responsible innovation and team working skills, combined with experience of working with academic and industry partners in a diverse and cross-disciplinary environment. This breadth and depth sets our CDT graduates apart from their peers, and positions them to become future leaders in industry, society and academia across a range of sectors. They will obtain the underpinning skills, and long term support through our Alumni Association, to drive future innovation across multiple sectors and act as life-long ambassadors for Fluid Dynamics.

The impact on people and skills will also include staff in our partner organisations in industry and non-profit sectors. Through participation in CDT activities, benefits will include new professional contacts and collaborations and knowledge of cutting edge methods and techniques. Through the CDT and the wider activities of Leeds Institute for Fluid Dynamics (LIFD) we will enhance the skills base in Fluid Dynamics and be the "go to" place to support high level training in end-user organisations.

Impact on Industry and the Economy:

In addition to the availability of trained graduates with excellent technical, professional and personal skills, impacts will arise from the direct innovation in research projects within the CDT. Research outcomes will influence processes, technologies, tools, guidelines and methodologies for our industry partners and other related organisations, leading to economic benefits such as new products, services and spin out companies. For example our current CDT has already led to 2 new patents (BAE Systems), student delivery of consultancy (Akzo Nobel), a flood demonstrator unit (JBA Trust) and a new method for hydraulic analysis (Hydrotec). Partners will also gain an enhanced reputation through being involved in successful and novel project outcomes. Skilled graduates and technology enhancement are key to economic growth, and our CDT will contribute to challenge areas such as energy, transport, the environment, the health sector, as well as those with chronic skills shortage such as the nuclear industry. Many of our partners are non-profit organisations, particularly in the environment and health sectors (e.g. NHS, PHE, Met Office). Impacts here derive through skilled graduates with the training and awareness to apply their expertise in organisations that deal with complex problems of societal importance, and novel research at the interface of disciplines. The cross-disciplinary nature of the CDT particularly supports this.

Impact on Society:

Beyond those who partner directly, many of the research projects have potential to lead to innovations with direct societal benefits (e.g. new techniques for detecting or controlling disease, new innovations in controlling flood risk or pollution, new insights into forecasting extreme weather). Beneficiaries here include professional bodies and government agencies who set policy, define guidance or influence the direction of innovation and research in the UK. The benefits to society will also stem from enhanced public awareness of Fluid Dynamics, both benefiting general public knowledge of science and inspiring the next generation (from all sectors of society) to undertake STEM careers.

Publications

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Studentship Projects

Project Reference Relationship Related To Start End Student Name
EP/S022732/1 01/10/2019 31/03/2028
2599100 Studentship EP/S022732/1 01/10/2021 30/09/2025 Jose Lopez Florido