EAGER: Development of a Heterogeneous Multiscale Model as Scale-Bridging Method for Chemically Reacting Systems

EAGER:开发异质多尺度模型作为化学反应系统的尺度桥接方法

基本信息

项目摘要

1139338IhmeWith the rapidly growing energy demand and environmental concerns, the utilization of advanced combustion technologies and alternative fuels is gaining increasing attention. However, associated with these emerging energy-conversion strategies is an increasing need for accurate and reliable information about reaction rates, transport properties, and other constitutive relations that are required for the system characterization on a macroscopic level. Since our current knowledge about these constitutive relations and rate coefficients primarily relies on experiments, a critical need exists to complement these studies with computational investigations that extend current modeling efforts and are able to fully account for the coupling between processes occurring on macroscopic and atomistic scales.The objective of this exploratory research program is the development of a heterogeneous multiscale method (HMM) for chemically reacting systems. In this HMM-formulation, the macroscopic model is described by the conservation equations for mass, momentum, energy, and species, and incomplete or unreliable data for constitutive relations, reaction rates, and other macroscopic quantities are evaluated from a detailed atomistic model. To demonstrate the potential of this approach, a canonical combustion problem is considered. To facilitate the successful application of HMM, fundamental scientific issues associated with the rigorous definition of scale-bridging operators for micro-macro coupling and the necessary reduction of the HMM model complexity will be systematically addressed in this research. If successful, the proposed exploratory research program enables the holistic investigation of complex combustion systems, and eliminates dependencies on incomplete and unreliable information about constitutive relations. Algorithmic developments addressing the reduction of the computational model complexity will be critical to enable the HMM application to complex combustion problems. More broadly, this research on the HMM model is general and can be applied to a wide range of industrial problems, including catalytic processes, combustion in fluidized beds, surface oxidation, and other problems for which information about detailed chemical mechanisms and other constitutive relations are not available.The broader impact of this research arises from the improved understanding about chemical kinetics and combustion processes, which will complement experimental investigations. The research program closely integrates education and outreach activities. Specifically, courses on combustion and propulsion will be complemented by lectures on alternative energy systems. In addition, research activities for undergraduate students will be organized during the academic year and the summer. In these research activities, students will work on topics related to sustainable energy generation and address fundamental aspects on basic thermodynamics and combustion physics.
随着能源需求的快速增长和对环境的关注,先进燃烧技术和替代燃料的利用越来越受到重视。然而,与这些新出现的能量转换策略相关联的是,越来越需要关于反应速率、输运性质和其他本构关系的准确和可靠的信息,这些信息是在宏观水平上表征系统所需的。由于我们目前对这些本构关系和速率系数的了解主要依赖于实验,因此迫切需要用计算研究来补充这些研究,这些研究扩展了当前的建模工作,并能够完全解释发生在宏观和原子尺度上的过程之间的耦合。这一探索性研究计划的目标是开发一种用于化学反应体系的非均相多尺度方法(HMM)。在这种隐马尔可夫模型中,宏观模型由质量、动量、能量和物种的守恒方程描述,本构关系、反应速率和其他宏观量的不完整或不可靠的数据由详细的原子模型来评估。为了证明这种方法的潜力,我们考虑了一个正则燃烧问题。为了促进隐马尔可夫模型的成功应用,本研究将系统地解决与微观-宏观耦合的尺度桥算子的严格定义以及必要的降低隐马尔可夫模型复杂性相关的基本科学问题。如果成功,拟议的探索性研究计划将使复杂燃烧系统的整体调查成为可能,并消除对不完整和不可靠的本构关系信息的依赖。解决降低计算模型复杂性的算法开发将是使HMM应用于复杂燃烧问题的关键。更广泛地说,这项关于隐马尔可夫模型的研究是一般性的,可以应用于广泛的工业问题,包括催化过程、流化床中的燃烧、表面氧化以及其他没有关于详细的化学机理和其他本构关系的信息的问题。这项研究的更广泛的影响源于对化学动力学和燃烧过程的更广泛的理解,这将补充实验研究。该研究计划将教育和外展活动紧密结合在一起。具体来说,关于燃烧和推进的课程将由关于替代能源系统的讲座来补充。此外,还将在学年和暑期为本科生组织研究活动。在这些研究活动中,学生将致力于与可持续能源发电相关的主题,并解决基本热力学和燃烧物理的基本方面。

项目成果

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Matthias Ihme其他文献

Augmenting filtered flame front displacement models for LES using machine learning with a posteriori simulations
使用机器学习和后验模拟增强 LES 的过滤火焰锋位移模型
  • DOI:
  • 发表时间:
    2024
  • 期刊:
  • 影响因子:
    3.4
  • 作者:
    Jen Zen Ho;Mohsen Talei;D. Brouzet;Wai Tong Chung;Pushan Sharma;Matthias Ihme
  • 通讯作者:
    Matthias Ihme
FireBench: A High-fidelity Ensemble Simulation Framework for Exploring Wildfire Behavior and Data-driven Modeling
FireBench:用于探索野火行为和数据驱动建模的高保真集成仿真框架
  • DOI:
  • 发表时间:
    2024
  • 期刊:
  • 影响因子:
    0
  • 作者:
    Qing Wang;Matthias Ihme;Cenk Gazen;Yi;John Anderson
  • 通讯作者:
    John Anderson
Stable supercritical interfaces do not exist without surface tension
没有表面张力,稳定的超临界界面就不存在。
  • DOI:
    10.1038/s41467-024-53175-8
  • 发表时间:
    2024-10-29
  • 期刊:
  • 影响因子:
    15.700
  • 作者:
    Nguyen Ly;Matthias Ihme
  • 通讯作者:
    Matthias Ihme
Analysis of weak secondary waves in a rotating detonation engine using large-eddy simulation and wavenumber-domain filtering
使用大涡模拟和波数域滤波分析旋转爆震发动机中的弱次级波
  • DOI:
    10.1016/j.combustflame.2024.113387
  • 发表时间:
    2024
  • 期刊:
  • 影响因子:
    4.4
  • 作者:
    Guillaume Vignat;D. Brouzet;M. Bonanni;Matthias Ihme
  • 通讯作者:
    Matthias Ihme
Predictions of instantaneous temperature fields in jet-in-hot-coflow flames using a multi-scale U-Net model
  • DOI:
    10.1016/j.proci.2024.105330
  • 发表时间:
    2024-01-01
  • 期刊:
  • 影响因子:
  • 作者:
    Jordan A.C. Kildare;Wai Tong Chung;Michael J. Evans;Zhao F. Tian;Paul R. Medwell;Matthias Ihme
  • 通讯作者:
    Matthias Ihme

Matthias Ihme的其他文献

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{{ truncateString('Matthias Ihme', 18)}}的其他基金

Conference: Western States Section of the Combustion Institute Spring Meeting 2022
会议:燃烧研究所西部各州分会 2022 年春季会议
  • 批准号:
    2210261
  • 财政年份:
    2022
  • 资助金额:
    $ 5.99万
  • 项目类别:
    Standard Grant
OAC Core: Small: Enabling High-fidelity Turbulent Reacting-Flow Simulations through Advanced Algorithms, Code Acceleration, and High-order Methods for Extreme-scale Computing
OAC 核心:小型:通过高级算法、代码加速和超大规模计算的高阶方法实现高保真湍流反应流模拟
  • 批准号:
    1909379
  • 财政年份:
    2019
  • 资助金额:
    $ 5.99万
  • 项目类别:
    Standard Grant
Fundamental Physical Understanding of Matrix-stabilized Combustion in Porous Media
多孔介质中基体稳定燃烧的基本物理理解
  • 批准号:
    1800906
  • 财政年份:
    2018
  • 资助金额:
    $ 5.99万
  • 项目类别:
    Standard Grant
EAGER: Development of a Heterogeneous Multiscale Model as Scale-Bridging Method for Chemically Reacting Systems
EAGER:开发异质多尺度模型作为化学反应系统的尺度桥接方法
  • 批准号:
    1347565
  • 财政年份:
    2013
  • 资助金额:
    $ 5.99万
  • 项目类别:
    Standard Grant
CAREER: Fundamental Analysis and Computational Modeling of Acoustic Radiation in Turbulent Reacting Flows
职业:湍流反应流中声辐射的基础分析和计算模型
  • 批准号:
    1347566
  • 财政年份:
    2013
  • 资助金额:
    $ 5.99万
  • 项目类别:
    Standard Grant
NSF/DOE Advanced Combustion Engines: Development of a Dynamic Wall Layer Model for LES of Internal Combustion Engines
NSF/DOE 先进内燃机:内燃机 LES 动态壁层模型的开发
  • 批准号:
    1258609
  • 财政年份:
    2013
  • 资助金额:
    $ 5.99万
  • 项目类别:
    Continuing Grant
CAREER: Fundamental Analysis and Computational Modeling of Acoustic Radiation in Turbulent Reacting Flows
职业:湍流反应流中声辐射的基础分析和计算模型
  • 批准号:
    0844587
  • 财政年份:
    2009
  • 资助金额:
    $ 5.99万
  • 项目类别:
    Standard Grant

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GOALI: Frameworks: At-Scale Heterogeneous Data based Adaptive Development Platform for Machine-Learning Models for Material and Chemical Discovery
GOALI:框架:基于大规模异构数据的自适应开发平台,用于材料和化学发现的机器学习模型
  • 批准号:
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Collaborative Research: RUI: Instrument Development: Ångström-Scale Operando Spectroscopic Imaging at Heterogeneous Electrochemical Interfaces
合作研究:RUI:仪器开发:异质电化学界面的埃级操作光谱成像
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Development and evaluation of equating methods for heterogeneous test scores
异质测试分数等值方法的开发和评估
  • 批准号:
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MRI: Development of Heterogeneous Edge Computing Platform for Real-Time Scientific Machine Learning
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