Turbulence at the exascale: application to wind energy, green aviation, air quality and net-zero combustion

百亿亿级湍流:在风能、绿色航空、空气质量和净零燃烧中的应用

基本信息

  • 批准号:
    EP/W026686/1
  • 负责人:
  • 金额:
    $ 340.25万
  • 依托单位:
  • 依托单位国家:
    英国
  • 项目类别:
    Research Grant
  • 财政年份:
    2021
  • 资助国家:
    英国
  • 起止时间:
    2021 至 无数据
  • 项目状态:
    未结题

项目摘要

This proposal brings together communities from the UK Turbulence Consortium (UKTC) and the UK Consortium on Reacting Flows (UKCRF) to ensure a smooth transition to exascale computing, with the aim to develop transformative techniques for future-proofing their production simulation software ecosystems dedicated to the study of turbulent flows. Understanding, predicting and controlling turbulent flows is of central importance and a limiting factor to a vast range of industries. Many of the environmental and energy-related issues we face today cannot possibly be tackled without a better understanding of turbulence.The UK is preparing for the exascale era through the ExCALIBUR programme to develop exascale-ready algorithms and software. Based on the findings from the Design and Development Working Group (DDWG) on turbulence at the exascale, this project is bringing together communities representing two of the seven UK HEC Consortia, the UKTC and the UKCTRF, to re-engineer or extend the capabilities of four of their production and research flow solvers for exascale computing: XCOMPACT3D, OPENSBLI, UDALES and SENGA+. These open-source, well-established, community flow solvers are based on finite-difference methods on structured meshes and will be developed to meet the challenges associated with exascale computing while taking advantage of the significant opportunities afforded by exascale systems. A key aim of this project is to leverage the well-established Domain Specific Language (DLS) framework OPS and the 2DECOMP&FFT library to allow XCOMPACT3D, OPENSBLI, UDALES and SENGA+ to run on large-scale heterogeneous computers. OPS was developed in the UK in the last ten years and it targets applications on multi-block structured meshes. It can currently generate code using CUDA, OPENACC/OPENMP5.0, OPENCL, SYCL/ONEAPI, HIP and their combinations with MPI. The OPS DSLs' capabilities will be extended in this project, specifically its code-generation tool-chain for robust, fail-safe parallel code generation. A related strand of work will use the 2DECOMP&FFT a Fortran-based library based on a 2D domain decomposition for spatially implicit numerical algorithms on monobloc structured meshes. The library includes a highly scalable and efficient interface to perform Fast Fourier Transforms (FFTs) and relies on MPI providing a user-friendly programming interface that hides communication details from application developers. 2DECOMP&FFT will be completely redesigned for a use on heterogeneous supercomputers (CPUs and GPUS from different vendors) using a hybrid strategy.The project will also combine exascale-ready coupling interfaces, UQ capabilities, I/O & visualisation tools to our flow solvers, as well as machine learning based algorithms, to address some of the key challenges and opportunities identified by the DDWG on turbulence at the exascale. This will be done in collaboration with several of the recently funded ExCALIBUR cross-cutting projects.The project will focus on four high-priority use cases (one for each solver), defined as high quality, high impact research made possible by a step-change in simulation performance. The use cases will focus on wind energy, green aviation, air quality and net-zero combustion. Exascale computing will be a game changer in these areas and will contribute to make the UK a greener nation (The UK commits to net zero carbon emissions by 2050). The use cases will be used to demonstrate the potential of the re-designed flow solvers based on OPS and 2DECOMP&FFT, for a wide range of hardware and parallel paradigms.
该提案汇集了来自英国湍流联盟(UKTC)和英国反应流联盟(UKCRF)的社区,以确保向艾级计算的平稳过渡,旨在开发变革性技术,以适应未来的生产模拟软件生态系统,致力于湍流的研究。了解、预测和控制湍流对于许多行业来说都至关重要,也是一个限制因素。如果不更好地了解湍流,我们今天面临的许多环境和能源相关问题就不可能得到解决。英国正在通过ExCALIBUR计划为艾级时代做准备,以开发艾级算法和软件。基于设计和开发工作组(DDWG)对exascale湍流的研究结果,该项目将代表七个英国HEC财团中的两个,UKTC和UKCTRF的社区聚集在一起,重新设计或扩展他们的四个生产和研究流解算器的能力,用于exascale计算:XCOMPACT 3D,OPENSBLI,UDALES和SENGA+。这些开源的、成熟的社区流求解器基于结构化网格上的有限差分方法,将被开发以应对与exascale计算相关的挑战,同时利用exascale系统提供的重大机会。该项目的一个主要目标是利用成熟的领域特定语言(DLS)框架OPS和2DECOMP&FFT库,使XCOMPACT 3D,OPENSBLI,UDALES和SENGA+能够在大规模异构计算机上运行。OPS是近十年来在英国发展起来的,它的目标是应用于多块结构网格。它目前可以使用CUDA,OPENACC/OPENMP5.0,OPENCL,SYCL/ONEAPI,HIP及其与MPI的组合生成代码。OPS DSL的功能将在这个项目中得到扩展,特别是它的代码生成工具链,用于健壮的、故障安全的并行代码生成。一个相关的工作链将使用2DECOMP&FFT,一个基于Fortran的库,基于2D区域分解,用于单块结构网格上的空间隐式数值算法。该库包括一个高度可扩展和高效的接口来执行快速傅立叶变换(FFT),并依赖于MPI提供一个用户友好的编程接口,对应用程序开发人员隐藏通信细节。2DECOMP&FFT将完全重新设计,以使用混合策略在异构超级计算机(来自不同供应商的CPU和GPU)上使用。该项目还将结合联合收割机的exascale就绪耦合接口,UQ功能,I/O和可视化工具到我们的流解算器,以及基于机器学习的算法,以解决DDWG在exascale湍流方面确定的一些关键挑战和机遇。这将与最近资助的几个ExCALIBUR交叉项目合作完成。该项目将重点关注四个高优先级用例(每个求解器一个),定义为通过模拟性能的阶跃变化实现的高质量,高影响力研究。这些用例将侧重于风能、绿色航空、空气质量和净零燃烧。Exascale计算将成为这些领域的游戏规则改变者,并将有助于使英国成为一个更加绿色的国家(英国承诺到2050年实现净零碳排放)。这些用例将用于展示基于OPS和2DECOMP&FFT的重新设计的流解算器在各种硬件和并行范例中的潜力。

项目成果

期刊论文数量(8)
专著数量(0)
科研奖励数量(0)
会议论文数量(0)
专利数量(0)
High-fidelity simulations of wake-to-wake interaction in an atmospheric boundary layer over a complex terrain
对复杂地形上大气边界层中尾流与尾流相互作用的高保真模拟
  • DOI:
    10.1088/1742-6596/2505/1/012033
  • 发表时间:
    2023
  • 期刊:
  • 影响因子:
    0
  • 作者:
    Jané-Ippel C
  • 通讯作者:
    Jané-Ippel C
Analytical all-induction state model for wind turbine wakes
风力机尾流的解析全感应状态模型
  • DOI:
    10.1103/physrevfluids.7.034605
  • 发表时间:
    2022
  • 期刊:
  • 影响因子:
    2.7
  • 作者:
    Bempedelis N
  • 通讯作者:
    Bempedelis N
A Direct Numerical Simulation Assessment of Turbulent Burning Velocity Parametrizations for Non-Unity Lewis Numbers
非统一路易斯数湍流燃烧速度参数化的直接数值模拟评估
  • DOI:
    10.3390/en16062590
  • 发表时间:
    2023
  • 期刊:
  • 影响因子:
    3.2
  • 作者:
    Mohan V
  • 通讯作者:
    Mohan V
A Cartesian Immersed Boundary Method Based on 1D Flow Reconstructions for High-Fidelity Simulations of Incompressible Turbulent Flows Around Moving Objects
  • DOI:
    10.1007/s10494-022-00364-4
  • 发表时间:
    2022-09
  • 期刊:
  • 影响因子:
    0
  • 作者:
    A. E. Giannenas;Nikolaos Bempedelis;F. Schuch;S. Laizet
  • 通讯作者:
    A. E. Giannenas;Nikolaos Bempedelis;F. Schuch;S. Laizet
Quantifying uncertainties in direct numerical simulations of a turbulent channel flow
  • DOI:
    10.1016/j.compfluid.2023.106108
  • 发表时间:
    2023-11-11
  • 期刊:
  • 影响因子:
    2.8
  • 作者:
    O'Connor,Joseph;Laizet,Sylvain;Coveney,Peter V.
  • 通讯作者:
    Coveney,Peter V.
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Sylvain Laizet其他文献

Unsupervised Random Quantum Networks for PDEs
用于偏微分方程的无监督随机量子网络
  • DOI:
    10.48550/arxiv.2312.14975
  • 发表时间:
    2023
  • 期刊:
  • 影响因子:
    0
  • 作者:
    Josh Dees;Antoine Jacquier;Sylvain Laizet
  • 通讯作者:
    Sylvain Laizet
Simulation numérique directe de l'influence de la forme aval d'une plaque séparatrice sur une couche de mélange
模拟数字直接影响形状 aval dune 牌匾分离 sur une couche de mélange
  • DOI:
    10.1016/j.crme.2006.06.005
  • 发表时间:
    2006
  • 期刊:
  • 影响因子:
    0.8
  • 作者:
    Sylvain Laizet;E. Lamballais
  • 通讯作者:
    E. Lamballais
FR3D: Three-dimensional flow reconstruction and force estimation for unsteady flows around extruded bluff bodies via conformal mapping aided convolutional autoencoders
  • DOI:
    10.1016/j.ijheatfluidflow.2023.109199
  • 发表时间:
    2023-10-01
  • 期刊:
  • 影响因子:
  • 作者:
    Ali Girayhan Özbay;Sylvain Laizet
  • 通讯作者:
    Sylvain Laizet
A high-order finite-difference solver for direct numerical simulations of magnetohydrodynamic turbulence
  • DOI:
    10.1016/j.cpc.2024.109400
  • 发表时间:
    2025-02-01
  • 期刊:
  • 影响因子:
  • 作者:
    Jian Fang;Sylvain Laizet;Alex Skillen
  • 通讯作者:
    Alex Skillen
Multi-fidelity Bayesian Optimisation of Wind Farm Wake Steering using Wake Models and Large Eddy Simulations
  • DOI:
    10.1007/s10494-024-00629-0
  • 发表时间:
    2024-12-23
  • 期刊:
  • 影响因子:
    2.400
  • 作者:
    Andrew Mole;Sylvain Laizet
  • 通讯作者:
    Sylvain Laizet

Sylvain Laizet的其他文献

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{{ truncateString('Sylvain Laizet', 18)}}的其他基金

The UK Turbulence Consortium
英国湍流协会
  • 批准号:
    EP/X035484/1
  • 财政年份:
    2023
  • 资助金额:
    $ 340.25万
  • 项目类别:
    Research Grant
[EnAble]: Developing and Exploiting Intelligent Approaches for Turbulent Drag Reduction
[EnAble]:开发和利用减少湍流阻力的智能方法
  • 批准号:
    EP/T021144/1
  • 财政年份:
    2021
  • 资助金额:
    $ 340.25万
  • 项目类别:
    Research Grant
CCP Turbulence
中共动荡
  • 批准号:
    EP/T026170/1
  • 财政年份:
    2020
  • 资助金额:
    $ 340.25万
  • 项目类别:
    Research Grant
Turbulent Flow Simulations at the Exascale: Application to Wind Energy and Green Aviation
百亿亿级湍流模拟:在风能和绿色航空中的应用
  • 批准号:
    EP/V000942/1
  • 财政年份:
    2020
  • 资助金额:
    $ 340.25万
  • 项目类别:
    Research Grant
UK Turbulence Consortium
英国湍流协会
  • 批准号:
    EP/R029326/1
  • 财政年份:
    2018
  • 资助金额:
    $ 340.25万
  • 项目类别:
    Research Grant
Plasma-actuator controlled turbulent jets
等离子体致动器控制的湍流射流
  • 批准号:
    EP/M022676/1
  • 财政年份:
    2015
  • 资助金额:
    $ 340.25万
  • 项目类别:
    Research Grant

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基于NIC的Exascale级计算机聚合通信卸载关键技术研究
  • 批准号:
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