首页> 外文会议>ASME Turbo Expo: Turbomachinery Technical Conference and Exposition >QUANTIFYING THE EFFECT OF KINETIC UNCERTAINTIES ON NO PREDICTIONS AT ENGINE-RELEVANT PRESSURES IN PREMIXED METHANE-AIR FLAMES
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QUANTIFYING THE EFFECT OF KINETIC UNCERTAINTIES ON NO PREDICTIONS AT ENGINE-RELEVANT PRESSURES IN PREMIXED METHANE-AIR FLAMES

机译:量化运动不确定性对甲烷混合气火焰中与发动机有关的压力下无预测的影响

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Accurate and robust thermochemical models are required to identify future low-NO_x technologies that can meet the increasingly stringent emissions regulations in the gas turbine industry. These mechanisms are generally optimized and validated for specific ranges of operating conditions, which result in an abundance of models offering accurate nominal solutions over different parameter ranges. At atmospheric conditions, and for methane combustion, a relatively good agreement between models and experiments is currently observed. At engine-relevant pressures, however, a large variability in predictions is obtained as the models are often used outside their validation region. The high levels of uncertainty found in chemical kinetic rates enable such discrepancies between models, even as the reactions are within recommended rate values. The current work investigates the effect of such kinetic uncertainties in NO predictions by propagating the uncertainties of 30 reactions, that are both uncertain and important to NO formation, through the combustion model at engine-relevant pressures. Understanding the uncertainty sources in model predictions and their effect on emissions at these pressures is key in developing accurate thermochemical models to design future combustion chambers with any confidence. Lean adiabatic, freely-propagating, laminar flames are therefore chosen to study the effect of parametric kinetic uncertainties. A non-intrusive, level 2, nested sparse-grid approach is used to obtain accurate surrogate models to quantify NO prediction intervals at various pressures. The forward analysis is carried up to 32 atm to quantify the uncertainty in emissions predictions to pressures relevant to the gas turbine community, which reveals that the NO prediction uncertainty decreases with pressure. After performing a Reaction Pathway Analysis, this reduction is attributed to the decreasing contribution of the prompt-NO pathway to total emissions, as the peak CH concentration and the CH layer thickness decrease with pressure. In the studied lean condition, the contribution of the pressure-dependent N_2O production route increases rapidly up to 10 atm before stabilizing towards engine-relevant pressures. The uncertain prediction ranges provide insight into the accuracy and precision of simulations at high pressures and warrant fuerther research to constrain the uncertainty limits of kinetic rates to capture NO concentrations with confidence in early design phases.
机译:准确且坚固的热化学型号需要识别未来的低NO_X技术,可以满足燃气轮机行业日益严格的排放法规。这些机制通常针对特定的操作条件进行了优化和验证,这导致丰富的模型提供了在不同参数范围内提供精确的标称解。在大气条件下,对于甲烷燃烧,目前观察到模型与实验之间的相对良好的一致性。然而,在发动机相关的压力下,获得预测的大变异性,因为模型通常在其验证区域之外使用。化学动力学率中发现的高水平不确定性使得模型之间存在差异,即使反应在推荐的速率值内。目前的工作通过传播30个反应的不确定性来研究这种动力学不确定因素在没有预测中,这对于在发动机相关压力下的燃烧模型中不确定和不确定并且不确定。了解模型预测中的不确定性来源及其对这些压力排放的影响是开发准确的热化学模型,以设计未来燃烧室的任何信心。因此,选择瘦绝热,自由繁殖,层状火焰,以研究参数动力学不确定因素的效果。非侵入式级别2嵌套稀疏电网方法用于获得准确的代理模型,以在各种压力下量化预测间隔。前瞻性分析最多可达32个ATM,以量化排放预测的不确定性,以与燃气轮机群落相关的压力,这揭示了没有预测不确定性随压力降低。在进行反应途径分析之后,这种减少归因于提示-NO途径对总排放的贡献降低,因为峰值CH浓度和CH层厚度随压而降低。在所研究的瘦条件下,在稳定发动机相关压力之前,压力依赖性N_2O生产路径的贡献增加至10atm。不确定的预测范围可以深入了解仿真的准确性和精度,并且需要屈服研究,以限制动力速率的不确定性限制,以利用早期设计阶段的信心捕捉浓度。

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