PyFR: Towards Industry and Exascale
Lead Research Organisation:
Imperial College London
Department Name: Aeronautics
Abstract
This is an extension of the Fellowship: 'Developing Software for High-Order Simulation of Transient Compressible Flow Phenomena: Application to Design of Unmanned Aerial Vehicles' - EP/K027379/1.
Over the past decades, computer simulations of fluid flow have emerged as an important tool for design of complex systems across a range of sectors. It is apparent, however, that for a range of flow problem current generation software is not fit for purpose. Newer software is required, that can make effective use of current and future computing platforms, to perform highly accurate so called 'scale-resolving' simulations of unsteady flow phenomena over complex geometric configurations. Such capability would lead to design of more efficient and capable technology across a range of sectors, including aerospace, defense, architecture, automotive, and green energy.
Current activities under award EP/K027379/1 have led to development of PyFR (www.pyfr.org), a new software that can effectively leverage capabilities of massively-parallel computing platforms, with a view to undertaking hitherto intractable simulations of unsteady airflow over complex Unmanned Aerial Vehicle (UAV) configurations. The proposed Fellowship extension will address a range of outstanding issues currently blocking wider industrial adoption of PyFR, taking it further "Towards Industry", as well as addressing a range of issues that will block exploitation of PyFR on next-generation exascale supercomputers, taking it further "Towards Exascale". The proposed Fellowship extension will also look to expand the application space of PyFR beyond just UAVs to a range of sectors, and includes test cases involving flow over turbine blades, missiles, buildings, and submarines.
The research program will be lead by Dr. Peter Vincent, a Reader in the department of Aeronautics at Imperial College. It will be undertaken in collaboration with various industrial partners including MTU Aeroengines, MBDA, Arup, BAE Systems Submarines, BAE Systems MAI, NASA Glenn, Nasa Langley, NVIDIA, Pointwise, Kitware, Zenotech, and Oak Ridge National Lab, and with various academic partners including Stanford University, and the Massachusetts Institute of Technology. This assembled team of project partners, comprising a selection of the world's leading companies and elite research institutions, will ensure the project successfully delivers its objectives.
Over the past decades, computer simulations of fluid flow have emerged as an important tool for design of complex systems across a range of sectors. It is apparent, however, that for a range of flow problem current generation software is not fit for purpose. Newer software is required, that can make effective use of current and future computing platforms, to perform highly accurate so called 'scale-resolving' simulations of unsteady flow phenomena over complex geometric configurations. Such capability would lead to design of more efficient and capable technology across a range of sectors, including aerospace, defense, architecture, automotive, and green energy.
Current activities under award EP/K027379/1 have led to development of PyFR (www.pyfr.org), a new software that can effectively leverage capabilities of massively-parallel computing platforms, with a view to undertaking hitherto intractable simulations of unsteady airflow over complex Unmanned Aerial Vehicle (UAV) configurations. The proposed Fellowship extension will address a range of outstanding issues currently blocking wider industrial adoption of PyFR, taking it further "Towards Industry", as well as addressing a range of issues that will block exploitation of PyFR on next-generation exascale supercomputers, taking it further "Towards Exascale". The proposed Fellowship extension will also look to expand the application space of PyFR beyond just UAVs to a range of sectors, and includes test cases involving flow over turbine blades, missiles, buildings, and submarines.
The research program will be lead by Dr. Peter Vincent, a Reader in the department of Aeronautics at Imperial College. It will be undertaken in collaboration with various industrial partners including MTU Aeroengines, MBDA, Arup, BAE Systems Submarines, BAE Systems MAI, NASA Glenn, Nasa Langley, NVIDIA, Pointwise, Kitware, Zenotech, and Oak Ridge National Lab, and with various academic partners including Stanford University, and the Massachusetts Institute of Technology. This assembled team of project partners, comprising a selection of the world's leading companies and elite research institutions, will ensure the project successfully delivers its objectives.
Planned Impact
Beneficiaries
Beneficiaries of the research include UK Government and the general public (via its impact on UK defence capabilities, green aviation, and knowledge/skills - see Societal Impact below), and UK business/industry (via its impact on high-tech exports, and knowledge/skills - see Economic Impact below). Academic beneficiaries and impact are discussed in Academic Beneficiaries.
Societal Impact
It is becoming increasingly important that the UK Government leverage technological advances to maintain and improve defence capabilities on a reduced budget. Outcomes from the proposed Fellowship extension will help advance a range of UK defence capabilities. These include Unmanned Aerial Vehicles (UAVs), missile systems, and submarines. UAVs will increasingly support key components of UK defence strategy and policy, and hence UK national security. Their importance was highlighted in the 2010 Strategic Defence and Security Review which, whilst cutting several more established capabilities, explicitly mentioned UAV technology as an area to be explored further. Missile systems are employed across all services, and underpin the effective function of many platforms. They are a critical technology in terms of UK national security. Submarines form a vital component of the UK's nuclear deterrent, which is currently being renewed. Via collaboration with BAE Systems Submarines, PyFR (www.pyfr.org) is likely to play an important role in this project "Submarines are seen by the HMG as having great importance especially Vanguard replacement, i.e. Dreadnought ... We see PyFR and its future development as one of a number of very important tools in a very important part of national defence." - David Hankey, Future Capability Manager, BAE Systems Submarines. Taken together, the proposed work will have a significant impact on various important UK defence capabilities, and hence have significant societal impact.
Air transportation moves over 3.5Bn passengers annually and produces upwards of 700M tonnes of CO2 and other Greenhouse Gases (GG), which are a significant driver of climate change. Global demand for air transportation is rising, particularly in emerging markets. The total number of passengers increased by 6.5% in 2015 alone, with similar growth forecast for the foreseeable future. Outcomes from the proposed Fellowship extension will help reduce GG emissions from commercial aircraft via e.g. design of more efficient low-pressure turbines. This will help make growth in commercial aviation environmentally viable, and will hence have significant societal impact.
Knowledge/skills generated in the areas of numerical methods, and massively-parallel computing can be applied in various other fields of research, including weather prediction, and climate modelling, both of which have significant societal impacts.
Economic Impact
Outcomes from the proposed Fellowship extension will help advance a range of high-tech high-value export industries. These include aerospace (turnover £32.0Bn in 2016, exports of £28.0Bn), architecture (turnover £2.5Bn in 2016, exports of £474M), defence (turnover £23.0Bn in 2016, exports of 8.7Bn per year for the period 2012-2015), automotive (turnover £77.5Bn in 2016, exports of £60.5Bn), and green energy (turnover £43.1Bn in 2015, exports of £4.1Bn). This will consequently have a significant economic impact.
Knowledge/skills generated in the areas of numerical methods and massively-parallel computing will also benefit other important UK industries, such as the financial sector, which relies heavily on efficient algorithms and is keen to explore the benefits of modern massively-parallel computing technology. Having the aforementioned knowledge/skills in the UK will also drive further international R&D investment in the UK, across all the above-mentioned sectors.
Beneficiaries of the research include UK Government and the general public (via its impact on UK defence capabilities, green aviation, and knowledge/skills - see Societal Impact below), and UK business/industry (via its impact on high-tech exports, and knowledge/skills - see Economic Impact below). Academic beneficiaries and impact are discussed in Academic Beneficiaries.
Societal Impact
It is becoming increasingly important that the UK Government leverage technological advances to maintain and improve defence capabilities on a reduced budget. Outcomes from the proposed Fellowship extension will help advance a range of UK defence capabilities. These include Unmanned Aerial Vehicles (UAVs), missile systems, and submarines. UAVs will increasingly support key components of UK defence strategy and policy, and hence UK national security. Their importance was highlighted in the 2010 Strategic Defence and Security Review which, whilst cutting several more established capabilities, explicitly mentioned UAV technology as an area to be explored further. Missile systems are employed across all services, and underpin the effective function of many platforms. They are a critical technology in terms of UK national security. Submarines form a vital component of the UK's nuclear deterrent, which is currently being renewed. Via collaboration with BAE Systems Submarines, PyFR (www.pyfr.org) is likely to play an important role in this project "Submarines are seen by the HMG as having great importance especially Vanguard replacement, i.e. Dreadnought ... We see PyFR and its future development as one of a number of very important tools in a very important part of national defence." - David Hankey, Future Capability Manager, BAE Systems Submarines. Taken together, the proposed work will have a significant impact on various important UK defence capabilities, and hence have significant societal impact.
Air transportation moves over 3.5Bn passengers annually and produces upwards of 700M tonnes of CO2 and other Greenhouse Gases (GG), which are a significant driver of climate change. Global demand for air transportation is rising, particularly in emerging markets. The total number of passengers increased by 6.5% in 2015 alone, with similar growth forecast for the foreseeable future. Outcomes from the proposed Fellowship extension will help reduce GG emissions from commercial aircraft via e.g. design of more efficient low-pressure turbines. This will help make growth in commercial aviation environmentally viable, and will hence have significant societal impact.
Knowledge/skills generated in the areas of numerical methods, and massively-parallel computing can be applied in various other fields of research, including weather prediction, and climate modelling, both of which have significant societal impacts.
Economic Impact
Outcomes from the proposed Fellowship extension will help advance a range of high-tech high-value export industries. These include aerospace (turnover £32.0Bn in 2016, exports of £28.0Bn), architecture (turnover £2.5Bn in 2016, exports of £474M), defence (turnover £23.0Bn in 2016, exports of 8.7Bn per year for the period 2012-2015), automotive (turnover £77.5Bn in 2016, exports of £60.5Bn), and green energy (turnover £43.1Bn in 2015, exports of £4.1Bn). This will consequently have a significant economic impact.
Knowledge/skills generated in the areas of numerical methods and massively-parallel computing will also benefit other important UK industries, such as the financial sector, which relies heavily on efficient algorithms and is keen to explore the benefits of modern massively-parallel computing technology. Having the aforementioned knowledge/skills in the UK will also drive further international R&D investment in the UK, across all the above-mentioned sectors.
Organisations
- Imperial College London (Fellow, Lead Research Organisation)
- Pointwise (Collaboration)
- BAE Systems (United Kingdom) (Collaboration, Project Partner)
- Zenotech (United Kingdom) (Project Partner)
- National Aeronautics and Space Administration (Project Partner)
- Oak Ridge National Laboratory (Project Partner)
- Pointwise (United States) (Project Partner)
- Massachusetts Institute of Technology (Project Partner)
- MBDA (United Kingdom) (Project Partner)
- MTU Aero Engines (Germany) (Project Partner)
- Stanford University (Project Partner)
- Kitware (United States) (Project Partner)
- Nvidia (United States) (Project Partner)
- Arup Group (United Kingdom) (Project Partner)
People |
ORCID iD |
Peter Vincent (Principal Investigator / Fellow) |
Publications
Akkurt S
(2022)
Cache blocking strategies applied to flux reconstruction
in Computer Physics Communications
Akkurt S
(2021)
Cache Blocking Strategies Applied to Flux Reconstruction
Caros L
(2023)
Optimization of Triangular Airfoils for Martian Helicopters Using Direct Numerical Simulations
in AIAA Journal
Caros L
(2022)
Direct Numerical Simulation of Flow over a Triangular Airfoil Under Martian Conditions
in AIAA Journal
Caros L.
(2022)
Comparing Strategies for DNS Based Optimization of Airfoils for Martian Rotorcraft
in 78th Vertical Flight Society Annual Forum and Technology Display, FORUM 2022
Cheng L
(2022)
A new 3D OpenFoam solver with improved resolution for hyperbolic systems on hybrid unstructured grids
in Applied Mathematical Modelling
Cheng L
(2021)
Low-dissipation BVD schemes for single and multi-phase compressible flows on unstructured grids
in Journal of Computational Physics
Deng X
(2022)
A new paradigm of dissipation-adjustable, multi-scale resolving schemes for compressible flows
in Journal of Computational Physics
Deng X
(2023)
A unified framework for non-linear reconstruction schemes in a compact stencil. Part 1: Beyond second order
in Journal of Computational Physics
Giangaspero G
(2022)
Synthetic Turbulence Generation for High-Order Scale-Resolving Simulations on Unstructured Grids
in AIAA Journal
Description | Development of software for very accurate simulations of unsteday turbulent fluid flow using supercomputers: - PyFR https://pyfr.org Development of techniques to: - Inject turbulence into flow simulations https://arc.aiaa.org/doi/abs/10.2514/1.J061046 - Speed up flow simulations using cache blocking https://www.sciencedirect.com/science/article/abs/pii/S0010465521003052 - Speed up flow simulations using locally adaptive pseudo time stepping https://www.sciencedirect.com/science/article/pii/S0021999119306187 Use of technology for both scientific and industrially relevant test cases with project partners, specifically: - Application to simulation of flow over a low pressure turbine blade (part of a jet engine) with MTU Aeroengines https://www.sciencedirect.com/science/article/pii/S0045793021001560 - Application to simulation of flow over high-rise buildings with Arup https://www.sciencedirect.com/science/article/pii/S0167610522002653 - Application to fundamentals of turbulent flow https://www.cambridge.org/core/journals/journal-of-fluid-mechanics/article/identifying-eigenmodes-of-averaged-smallamplitude-perturbations-to-turbulent-channel-flow/EF03E2FFFF1A481FC55448B3F11496F2 |
Exploitation Route | The software that was developed (PyFR) is now being used around the world by academics and industrial partners. See: https://cassyni.com/s/pyfr |
Sectors | Aerospace Defence and Marine |
URL | https://pyfr.org |
Description | PyFR now has an active international user/developer base, as evidenced by activity on the the PyFR Discourse Forum https://pyfr.discourse.group/ and the PyFR Seminar Series https://cassyni.com/s/pyfr in which users and developers from around the world have presented their latest work using PyFR e.g. https://doi.org/10.52843/cassyni.536kkl (Agency for Defense Development, Korea) https://doi.org/10.52843/cassyni.nqp2sp (Concordia, Canada)) https://doi.org/10.52843/cassyni.wnnxmp (Kyushu, Japan)) https://doi.org/10.52843/cassyni.bq69kg (ISAE-SUPAERO, France)) https://doi.org/10.52843/cassyni.t2ms3w (Texas A&M, USA) https://doi.org/10.52843/cassyni.pw9418 (Aachen, Germany) https://doi.org/10.52843/cassyni.nd09lk (Technion, Israel) https://doi.org/10.52843/cassyni.hkqms2 (University of Hannover) https://doi.org/10.52843/cassyni.br5jn1 (University of Science and Technology of China) https://doi.org/10.52843/cassyni.w15qsz (Leonardo Company) |
First Year Of Impact | 2021 |
Sector | Aerospace, Defence and Marine |
Impact Types | Societal Economic |
Description | BAE Systems |
Organisation | BAE Systems |
Country | United Kingdom |
Sector | Academic/University |
PI Contribution | Visits. Share findings. |
Collaborator Contribution | Share findings. |
Impact | Multi-disciplinary - mathematics, computer science, computational fluid dynamics, aerospace engineering. |
Start Year | 2013 |
Description | Pointwise |
Organisation | Pointwise |
Country | United States |
Sector | Private |
PI Contribution | Provided them with meshing challenges! And insight into PyFR mesh format. |
Collaborator Contribution | Added PyFr mesh output to Pointwise meshing software, and have started to make us meshes. |
Impact | - |
Start Year | 2015 |
Title | PyFR v1.10.0 |
Description | High-order flow solver. |
Type Of Technology | Software |
Year Produced | 2020 |
Open Source License? | Yes |
Impact | Ongoing use of the solver. |
URL | https://www.pyfr.org/ |
Title | PyFR v1.11.0 |
Description | High-order flow solver. |
Type Of Technology | Software |
Year Produced | 2021 |
Open Source License? | Yes |
Impact | Ongoing use of the software. |
URL | https://www.pyfr.org/ |
Title | PyFR v1.12.0 |
Description | High-order flow solver. |
Type Of Technology | Software |
Year Produced | 2021 |
Open Source License? | Yes |
Impact | Ongoing use of the software. |
URL | https://www.pyfr.org/ |
Title | PyFR v1.13.0 |
Description | High-order flow solver. |
Type Of Technology | Software |
Year Produced | 2022 |
Open Source License? | Yes |
Impact | Ongoing use of the software. |
URL | https://www.pyfr.org/ |
Title | PyFR v1.7.6 |
Description | PyFR is an open-source Python based framework for solving advection-diffusion type problems on streaming architectures using the Flux Reconstruction approach of Huynh. The framework is designed to solve a range of governing systems on mixed unstructured grids containing various element types. It is also designed to target a range of hardware platforms via use of an in-built domain specific language derived from the Mako templating engine. |
Type Of Technology | Software |
Year Produced | 2018 |
Open Source License? | Yes |
Impact | Further funding. Preliminary industrial adoption. |
URL | http://www.pyfr.org |
Title | PyFR v1.8.0 |
Description | PyFR is an open-source Python based framework for solving advection-diffusion type problems on streaming architectures using the Flux Reconstruction approach of Huynh. The framework is designed to solve a range of governing systems on mixed unstructured grids containing various element types. It is also designed to target a range of hardware platforms via use of an in-built domain specific language derived from the Mako templating engine. |
Type Of Technology | Software |
Year Produced | 2018 |
Open Source License? | Yes |
Impact | Further funding. Preliminary industrial adoption. |
URL | http://www.pyfr.org |
Title | PyFR v1.8.5 |
Description | PyFR is an open-source Python based framework for solving advection-diffusion type problems on streaming architectures using the Flux Reconstruction approach of Huynh. The framework is designed to solve a range of governing systems on mixed unstructured grids containing various element types. It is also designed to target a range of hardware platforms via use of an in-built domain specific language derived from the Mako templating engine. |
Type Of Technology | Software |
Year Produced | 2019 |
Open Source License? | Yes |
Impact | - |
URL | http://www.pyfr.org |
Title | PyFR v1.9.0 |
Description | PyFR is an open-source Python based framework for solving advection-diffusion type problems on streaming architectures using the Flux Reconstruction approach of Huynh. The framework is designed to solve a range of governing systems on mixed unstructured grids containing various element types. It is also designed to target a range of hardware platforms via use of an in-built domain specific language derived from the Mako templating engine. |
Type Of Technology | Software |
Year Produced | 2019 |
Open Source License? | Yes |
Impact | - |
URL | http://www.pyfr.org |