Uncertainty quantification and reduction for combustion kinetic Modeling: A case study of NH3/H2 models

IF 6.7 1区 工程技术 Q2 ENERGY & FUELS
Fuel Pub Date : 2025-05-28 DOI:10.1016/j.fuel.2025.135810
Gongrui Huang , Hongxin Wang , Liang Tian , Oskar Haidn , Nadezda Slavinskaya
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引用次数: 0

Abstract

Variations in the selection of parameters for reaction rate constant (RRC) contributes to uncertainties in combustion kinetic models. To quantify and reduce these uncertainties, this study proposes an efficient framework integrating sensitivity analysis and Monte Carlo simulation capable of simultaneously considering numerous experimental conditions, while incorporating the probabilistic distribution of simulation errors and RRCs. In this framework, a vast number of modified models, generated based on the initial uncertainty bounds of the RRCs for highly sensitive reactions identified through a comprehensive sensitivity analysis, are used to simulate experimental measurements and obtain the distribution of prediction errors. The posterior probability distributions for each RRC are further derived, ultimately leading to the determination of reduced uncertainty bounds. The proposed framework was successfully applied to reduce the uncertainties in ammonia (NH3)/hydrogen (H2) models, utilizing over 2,500 experimental data points, including ignition delay times, premixed laminar flame speeds, and species concentrations. By conducting a comprehensive sensitivity analysis on 11 representative NH3/H2 models, 52 highly sensitive reactions contributing significantly to the uncertainty were identified. The RRCs for these 52 reactions from measurements, theoretical calculations, and reviews were collected, with their initial uncertainty bounds determined statistically. A new comprehensive NH3/H2 combustion kinetic model with 42 species and 346 reactions was developed and extensively validated over a wide range of conditions. Following this, the reduced uncertainty bounds of RRCs for 52 reactions were obtained through Monte Carlo simulation, resulting in the uncertainty reduction of NH3/H2 models, which provides valuable insights for model optimization. This framework offers a robust tool for uncertainty quantification and reduction in combustion kinetic models and can be broadly applied to other fuel systems.
燃烧动力学模型的不确定性量化与降低:以NH3/H2模型为例
反应速率常数(RRC)参数选择的变化导致了燃烧动力学模型的不确定性。为了量化和减少这些不确定性,本研究提出了一个有效的框架,将敏感性分析和蒙特卡罗模拟结合起来,能够同时考虑多个实验条件,同时考虑模拟误差和rcs的概率分布。在该框架中,根据综合灵敏度分析确定的高敏感反应rcs的初始不确定界限生成大量修正模型,用于模拟实验测量并获得预测误差的分布。进一步推导每个RRC的后验概率分布,最终确定降低的不确定性界限。该框架成功地应用于减少氨(NH3)/氢(H2)模型的不确定性,利用超过2500个实验数据点,包括点火延迟时间、预混层流火焰速度和物质浓度。通过对11个具有代表性的NH3/H2模型进行综合敏感性分析,鉴定出52个对不确定性有显著影响的高敏感反应。从测量、理论计算和综述中收集了这52种反应的RRCs,并统计确定了它们的初始不确定界限。建立了包含42种物质和346种反应的NH3/H2燃烧动力学模型,并在多种条件下进行了验证。在此基础上,通过蒙特卡罗模拟得到了52个反应的rcs的不确定边界,从而降低了NH3/H2模型的不确定性,为模型优化提供了有价值的见解。该框架为不确定性量化和减少燃烧动力学模型提供了一个强大的工具,可以广泛应用于其他燃料系统。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Fuel
Fuel 工程技术-工程:化工
CiteScore
12.80
自引率
20.30%
发文量
3506
审稿时长
64 days
期刊介绍: The exploration of energy sources remains a critical matter of study. For the past nine decades, fuel has consistently held the forefront in primary research efforts within the field of energy science. This area of investigation encompasses a wide range of subjects, with a particular emphasis on emerging concerns like environmental factors and pollution.
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