PyFR: Towards Industry and Exascale

PyFR：迈向工业和百亿亿次计算

• 批准号: EP/R030340/1
• 负责人: Peter Vincent
• 金额: $ 137.73万
• 依托单位: Imperial College London
• 依托单位国家: 英国
• 项目类别: Fellowship
• 财政年份: 2018
• 资助国家: 英国
• 起止时间: 2018 至 无数据
• 项目状态: 已结题
• 来源: https://gtr.ukri.org/projects?ref=EP%2FR030340%2F1
• 关键词: PyFR; Towards; Industry; Exascale

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.

这是该奖学金的延伸：“开发瞬态可压缩流现象高阶模拟软件：应用于无人机设计”- EP/K 027379/1。在过去的几十年里，流体流动的计算机模拟已经成为一个重要的工具，用于设计一系列领域的复杂系统。然而，很明显，对于一系列流动问题，当前生成的软件不适合于目的。需要更新的软件，可以有效地利用当前和未来的计算平台，在复杂的几何配置上执行高度精确的所谓的“尺度分辨”非定常流现象的模拟。这样的能力将导致设计更有效和更有能力的技术，跨越一系列领域，包括航空航天、国防、建筑、汽车和绿色能源。目前在EP/K 027379/1下的活动已经导致PyFR（www.example.com）的开发www.pyfr.org，PyFR是一种新的软件，可以有效地利用并行计算平台的能力，目的是对复杂无人机（UAV）外形上的非定常气流进行迄今为止难以处理的模拟。拟议的奖学金延期将解决目前阻碍PyFR更广泛的工业应用的一系列悬而未决的问题，进一步“走向工业”，以及解决一系列阻碍PyFR在下一代艾级超级计算机上开发的问题，进一步“走向艾级”。此外，PyFR的应用领域也将从无人机扩展到一系列领域，包括涡轮机叶片、导弹、建筑物和潜艇的绕流测试。该研究项目将由帝国理工学院航空系的Peter Vincent博士领导。它将与各种工业合作伙伴合作，包括MTU航空发动机，MBDA，Arup，BAE系统潜艇，BAE系统MAI，NASA Glenn，NASA兰利，NVIDIA，Pointwise，Kitware，Zenotech和橡树岭国家实验室，以及各种学术合作伙伴，包括斯坦福大学和马萨诸塞州理工学院。这个项目合作伙伴团队由世界领先的公司和精英研究机构组成，将确保该项目成功实现其目标。

项目成果

A New 3D OpenFoam Solver with Improved Resolution for Hyperbolic Systems on Hybrid Unstructured Grids

• DOI: 10.1016/j.apm.2022.03.022
• 发表时间: 2022-04
• 期刊: Applied Mathematical Modelling
• 影响因子: 5
• 作者: Lidong Cheng;X. Deng;B. Xie;Yi Jiang;Feng Xiao

Optimization of Triangular Airfoils for Martian Helicopters Using Direct Numerical Simulations

使用直接数值模拟优化火星直升机的三角翼

• DOI: 10.2514/1.j063164
• 发表时间: 2023
• 期刊: AIAA Journal
• 影响因子: 2.5
• 作者: Caros L

A unified framework for non-linear reconstruction schemes in a compact stencil. Part 1: Beyond second order

• DOI: 10.1016/j.jcp.2023.112052
• 发表时间: 2023-03
• 期刊: J. Comput. Phys.
• 作者: X. Deng

Synthetic Turbulence Generation in PyFR

PyFR 中的合成湍流生成

• DOI: 10.52843/cassyni.249z01
• 发表时间: 2021
• 作者: Giangaspero G

A new paradigm of dissipation-adjustable, multi-scale resolving schemes for compressible flows

• DOI: 10.1016/j.jcp.2022.111287
• 发表时间: 2022-05
• 期刊: J. Comput. Phys.
• 作者: X. Deng;Zhen-hua Jiang;P. Vincent;F. Xiao;Chao Yan