Resolving discrepancies in detailed kinetic models of combustion via automated transition state theory calculations

通过自动过渡态理论计算解决详细燃烧动力学模型中的差异

• 批准号: 1605568
• 负责人: Richard West
• 金额: $ 26万
• 依托单位: Northeastern University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2016
• 资助国家: 美国
• 起止时间: 2016-07-01 至 2020-04-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1605568&HistoricalAwards=false
• 关键词: Resolving; discrepancies; detailed; kinetic; models

1605568 WestIn order to develop cleaner and more efficient engines, and to make better use of both petroleum-derived and alternative fuels, engineers need a better understanding of combustion. Computer models that can accurately predict how different fuels burn in different conditions will help us develop new engines and new fuels. The goal of this research is predictive, detailed kinetic modeling of combustion, in which many thousands of relevant chemical reactions are calculated accurately. As a step towards this goal, the research will detect and correct major discrepancies in the reaction rates currently used in detailed kinetic models, and in so doing create a database of reaction transition states, as well as algorithms to predict them. The proposed work will use several novel techniques to identify and correct mistakes, uncertainties, and approximations currently hidden throughout detailed kinetic models of combustion. The project will remove the human bottle-neck in performing quantum mechanical calculations of chemical kinetics, enabling effective use of High Performance Computing for accurate calculation of reaction rate expressions in the future. This high-throughput calculation of reaction kinetics has been identified as a "basic research need for clean and efficient combustion of 21st century transportation fuels", and by the Combustion Energy Frontier Research Center as an "important grand challenge".This three year project proposes to: (1) automate the performance of quantum mechanics (QM) based Transition State Theory (TST) calculations for combustion-relevant reactions in the open-source, kinetic model building software Reaction Mechanism Generator (RMG); (2) use a newly developed kinetic model importer tool to identify every elementary reaction published in recent combustion models; (3) use the automated methods from step one to calculate the rates of reactions from step two, creating a public database of reactions, rates from the literature, rates calculated by TST, QM calculation results, and transition state geometries; and (4) identify discrepancies between reaction rates in published models and those calculated via TST, and quantify the effect these discrepancies have on the model predictions. Additionally, we will develop a related suite of Python-based teaching materials suitable for undergraduate chemical engineering curriculum, to introduce combustion science to a wider audience. A PhD student and several undergraduate students will gain valuable research experience and training whilst working on this project.

为了开发更清洁、更高效的发动机，并更好地利用石油衍生燃料和替代燃料，工程师们需要更好地了解燃烧。能够准确预测不同燃料在不同条件下如何燃烧的计算机模型将有助于我们开发新发动机和新燃料。这项研究的目标是预测性的，详细的燃烧动力学建模，其中精确计算了数千个相关的化学反应。作为实现这一目标的一步，该研究将检测和纠正目前用于详细动力学模型的反应速率中的主要差异，并在此过程中创建反应过渡态数据库以及预测它们的算法。拟议的工作将使用几种新的技术来识别和纠正错误，不确定性和近似值目前隐藏在整个详细的燃烧动力学模型。该项目将消除人类在进行化学动力学量子力学计算方面的瓶颈，使高性能计算在未来能够有效地用于精确计算反应速率表达式。这一高通量的反应动力学计算已被确定为“21世纪世纪运输燃料清洁高效燃烧的基础研究需求”，并被燃烧能源前沿研究中心确定为“重要的重大挑战”。（1）在开源中自动执行用于燃烧相关反应的基于量子力学（QM）的过渡态理论（TST）计算，动力学建模软件Reaction Mechanism Generator（RMG）：（2）使用新开发的动力学模型导入工具识别最近发表的燃烧模型中的每一个基元反应;（3）使用来自步骤一的自动化方法来计算来自步骤二的反应速率，创建反应、来自文献的速率、通过TST计算的速率、QM计算结果的公共数据库，和过渡态的几何形状;（4）确定在已公布的模型和那些通过TST计算的反应速率之间的差异，并量化这些差异对模型预测的影响。此外，我们将开发一套适用于本科化学工程课程的基于Python的相关教材，以向更广泛的受众介绍燃烧科学。一个博士生和几个本科生将获得宝贵的研究经验和培训，同时在这个项目上工作。

项目成果

The impact of roaming radicals on the combustion properties of transportation fuels

漫游自由基对运输燃料燃烧性能的影响

• DOI: 10.1016/j.combustflame.2018.05.020
• 发表时间: 2018
• 期刊: Combustion and Flame
• 影响因子: 4.4
• 作者: West, Richard H.;Goldsmith, C. Franklin
• 通讯作者: Goldsmith, C. Franklin