Abstract For turbulent flames involving intense turbulence-chemistry interaction, quantifying the uncertainty originating from the parameters of chemical kinetics and physical models leads to a more rigorous assessment of the predictability of simulations. In the present work, a successive dimension reduction framework based on the active subspace (AS) method is formulated to efficiently quantify modeling uncertainties associated with chemical kinetics, and turbulent combustion model parameters in turbulent flame simulations. The approach is demonstrated in simulating a turbulent H2/O2 lifted wall-jet flame. The reduction of the high-dimensional kinetic uncertainty space is first achieved through cheap surrogate autoignition tests, and a single active uncertain kinetic variable is identified. Then a one-dimensional active subspace of the uncertainty space consisting of such an active kinetic variable and four turbulent combustion model parameters are further identified using 25 runs of turbulent flame simulations. Finally, the probability distribution function (PDF) of the flame lift-off length is characterized through Monte Carlo simulations within a cheap response surface that is constructed within the active subspace. The components of the active subspace reveal that both chemical kinetics and turbulent mixing are critical for the flame stabilization. Further analysis shows that the uncertainty in the turbulent heat diffusion could change the dominant reactions between R1 (H+O2 ⇋ O+OH) and R9 (H+O2 (+M) ⇋ HO2 (+M)) through varying the local temperature in the flame stabilization zone. In addition, comparisons of the PDFs of the flame lift-off length show that the uncertainty induced by chemical kinetics is comparable with that induced by turbulent combustion model parameters. The successive dimension reduction of uncertain physicochemical parameter space via AS enables efficient uncertainty quantification for turbulent flames, meanwhile providing insights into the controlling physiochemical processes.

中文翻译：

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通过连续降维量化湍流火焰中的建模不确定性

摘要 对于涉及强烈湍流-化学相互作用的湍流火焰，量化源自化学动力学和物理模型参数的不确定性可以更严格地评估模拟的可预测性。在目前的工作中，制定了基于主动子空间 (AS) 方法的连续降维框架，以有效量化与化学动力学相关的建模不确定性，以及湍流火焰模拟中的湍流燃烧模型参数。该方法在模拟湍流 H2/O2 提升壁射流火焰中得到了证明。高维动力学不确定性空间的减少首先通过廉价的替代自燃测试来实现，并识别出单个活动的不确定动力学变量。然后，使用 25 次湍流火焰模拟进一步确定不确定空间的一维活动子空间，该子空间由这种活动动力学变量和四个湍流燃烧模型参数组成。最后，火焰升起长度的概率分布函数 (PDF) 通过在活动子空间内构建的廉价响应面内的蒙特卡罗模拟进行表征。活性子空间的成分表明，化学动力学和湍流混合对于火焰稳定至关重要。进一步分析表明，湍流热扩散的不确定性可以通过改变局部温度来改变 R1 (H+O2 ⇋ O+OH) 和 R9 (H+O2 (+M) ⇋ HO2 (+M)) 之间的主要反应。火焰稳定区。此外，火焰升起长度 PDF 的比较表明，由化学动力学引起的不确定性与由湍流燃烧模型参数引起的不确定性相当。通过 AS 对不确定物理化学参数空间的连续降维可以对湍流火焰进行有效的不确定性量化，同时提供对控制物理化学过程的见解。