CRII:OAC: Novel techniques for improving convergence and scalability of a Monte Carlo radiation solver for large-scale combustion simulations

CRII:OAC：用于提高大规模燃烧模拟蒙特卡罗辐射解算器的收敛性和可扩展性的新技术

• 批准号: 1756005
• 负责人: Somesh Roy
• 金额: $ 17.5万
• 依托单位: Marquette University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2018
• 资助国家: 美国
• 起止时间: 2018-03-01 至 2021-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1756005&HistoricalAwards=false
• 关键词: CRII; OAC; Novel; techniques; improving

Combustion has been an important source of energy for ages and will continue to be so for considerable future. With the help of high-performance computing (HPC), predictive and accurate combustion simulations have a tremendous potential to emerge as a cost-effective and reliable design, assessment, and decision-making tool for practical systems (e.g., gas turbines, internal combustion engines, furnaces, etc.).  Detailed predictive modeling of combustion system requires, among other things, detailed and accurate modeling of thermal radiation. However, models for thermal radiation used in combustion simulations are usually over-simplified. The main bottlenecks in using detailed radiation model are its high computational cost and poor parallel efficiency in HPC.  This project explores several novel ideas to increase efficiency and robustness of a high-fidelity radiation solver in HPC combustion simulations, leading to the possibility of performing predictive and accurate simulations of practical combustion systems in a realistic time-frame.  The ability to perform such large-scale reliable predictive simulation is not only important in the design process of real combustion devices but also essential to further our understanding of fundamentals of combustion processes.  Considering the ever-increasing need for cleaner combustion devices, this predictive capability can potentially have a significant effect in academic research, as well as in energy and transportation industry. The project will also have an impact in popularizing computer programming in undergraduate students. Therefore, this research aligns with the NSF's mission to promote the progress of science and to advance the national health, prosperity, and welfare.  The radiation solver of choice in this project is a Monte-Carlo ray tracing-based (MCRT) solver. It is one of the most accurate radiation solver available, and typically outshines all other radiation solvers as the complexity of the problem increases.  To achieve improvements in efficiency and scalability of the MCRT solver in HPC simulations of large-scale combustion systems, this research brings together ideas from different disciplines of mathematics, statistical theory, and computer science and applies them to solve an engineering problem.  Considering the fact that the performance of an MCRT solver in HPC primarily depends on the underlying statistical algorithm and computational load-balancing, the current research is divided into three primary tasks. First, the project is developing new algorithms for improved convergence using special statistical distributions with low discrepancy. Second, novel strategies for MCRT load management, both in terms of computational time and memory utilization, are being explored to improve scalability of the solver in HPC simulations.  Third, the improved MCRT solver are planned to be created as a modular, platform-independent solver module with standardized interfaces so that it can be used with any combustion and/or CFD solver without significant sacrifice of its performance.  By enhancing efficiency and scalability of MCRT, this work aims to enable more accurate predictive HPC simulations of large-scale combustion systems in a realistic timescale.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

燃烧一直是一个重要的能源的年龄，并将继续如此相当长的未来。 在高性能计算（HPC）的帮助下，预测性和准确的燃烧模拟具有巨大的潜力，可以成为实用系统（例如，燃气轮机、内燃机、熔炉等）。 燃烧系统的详细预测建模尤其需要对热辐射进行详细且准确的建模。 然而，用于燃烧模拟的热辐射模型通常过于简化。 在HPC中使用详细辐射模型的主要瓶颈是其高计算成本和低并行效率。本项目探索了几种新颖的想法来提高HPC燃烧模拟中高保真辐射求解器的效率和鲁棒性，从而有可能在现实的时间范围内对实际燃烧系统进行预测和准确的模拟。规模可靠的预测模拟不仅在真实的燃烧装置的设计过程中非常重要，而且对于加深我们对燃烧过程基本原理的理解也是必不可少的，考虑到对清洁燃烧装置的日益增长的需求，这种预测能力在学术研究以及能源和运输工业中具有潜在的重要影响。 该项目还将对在本科生中普及计算机编程产生影响。 因此，本研究符合美国国家科学基金会的使命，以促进科学的进步和促进国家的健康，繁荣和福利。在这个项目中的辐射求解器的选择是一个蒙特-卡罗射线跟踪为基础的（MCRT）求解器。 它是目前最精确的辐射求解器之一，随着问题复杂性的增加，它通常会超越所有其他辐射求解器。为了提高MCRT求解器在大规模燃烧系统HPC模拟中的效率和可扩展性，本研究汇集了数学，统计理论，考虑到高性能计算中MCRT求解器的性能主要取决于底层的统计算法和计算负载平衡，本文将MCRT求解器的研究分为三个主要任务。 首先，该项目正在开发新的算法，以改善收敛使用特殊的统计分布与低差异。 第二，MCRT负载管理的新策略，无论是在计算时间和内存利用率，正在探索，以提高求解器在HPC模拟的可扩展性。第三，改进的MCRT求解器计划被创建为一个模块，具有标准化接口的独立于平台的求解器模块，因此可用于任何燃烧和/或或CFD求解器，而不会显著牺牲其性能。通过提高MCRT的效率和可扩展性，这项工作的目的是使更准确的预测HPC模拟的大型，该奖项反映了NSF的法定使命，并被认为值得通过使用基金会的知识价值和更广泛的影响进行评估来支持审查标准。

项目成果

AN EFFICIENT MONTE CARLO-BASED SOLVER FOR THERMAL RADIATION IN PARTICIPATING MEDIA

一种基于蒙特卡罗的高效参与介质热辐射求解器

• DOI: 10.1615/tfec2019.rad.027584
• 发表时间: 2019
• 期刊: Proceeding of 4th Thermal and Fluids Engineering Conference
• 作者: Farmer, Joseph A.;Roy, Somesh P.
• 通讯作者: Roy, Somesh P.

Comparison of Spherical Harmonics Method and Discrete Ordinates Method for Radiative Transfer in a Turbulent Jet Flame

湍流射流火焰中辐射传输的球谐函数法与离散坐标法的比较

• DOI: 10.1016/j.jqsrt.2022.108459
• 发表时间: 2022
• 期刊: Journal of Quantitative Spectroscopy and Radiative Transfer
• 影响因子: 2.3
• 作者: Ge, Wenjun;David, Chloe;Modest, Michael F.;Sankaran, Ramanan;Roy, Somesh
• 通讯作者: Roy, Somesh

A quasi-Monte Carlo solver for thermal radiation in participating media

• DOI: 10.1016/j.jqsrt.2019.106753
• 发表时间: 2020-02
• 期刊: Journal of Quantitative Spectroscopy and Radiative Transfer
• 影响因子: 2.3
• 作者: Joseph A. Farmer;Somesh P. Roy

Comparison of Radiation Models for a Turbulent Piloted Methane/Air Jet Flame: A Frozen-Field Study

湍流先导甲烷/空气喷射火焰辐射模型的比较：冻结场研究

• DOI: 10.1115/ht2021-62417
• 发表时间: 2021
• 期刊: ASME 2021 Heat Transfer Summer Conference
• 作者: David, Chloe;Ge, Wenjun;Roy, Somesh P.;Modest, Michael F.;Sankaran, Ramanan
• 通讯作者: Sankaran, Ramanan

A PHOTON MONTE CARLO SOLVER UTILIZING A LOW DISCREPANCY SEQUENCE FOR THERMAL RADIATION IN COMBUSTION SYSTEMS

利用低差异序列求解燃烧系统热辐射的光子蒙特卡洛求解器

• DOI: 10.1615/rad-19.10
• 发表时间: 2019
• 期刊: Proceedings of The 9th International Symposium on Radiative Transfer
• 作者: Farmer, Joseph A.;Roy, Somesh P.
• 通讯作者: Roy, Somesh P.