The maximum likelihood ensemble filter for computational flame and fluid dynamics
The maximum likelihood ensemble filter for computational flame and fluid dynamics
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用于计算火焰和流体动力学的最大似然系综滤波器
DOI：
10.1093/imamat/hxab010
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发表时间：
2021
影响因子：
1.2
通讯作者：
Xinfeng Gao
中科院分区：
文献类型：
--
作者：
Yijun Wang;S. Guzik;M. Zupanski;Xinfeng Gao
由于动力学系统的多尺度性质和需要解决小尺度物理特征，支配具有湍流和燃烧的流体动力学的偏微分方程的数值解具有挑战性。此外，动力系统中的不确定性，包括物理模型和参数，初始和边界条件以及数值方法中的不确定性，影响湍流和化学反应的计算流体动力学（CFD）预测。为了提高计算流体动力学预测，本研究的重点是开发和应用的最大似然集合滤波器（MLEF），一个基于集合的数据同化（DA），具有燃烧和/或湍流流。MLEF通过最大化后验概率密度函数找到最优分析及其不确定性。该研究的新奇在于先进的DA和CFD方法的结合，用于预测工程流体动力学的新的综合应用。该研究结合了重要的方面，包括一个集成的DA与分析和不确定性估计，一个增强的控制向量，同时调整初始条件和模型的经验参数和应用DA的CFD建模的燃烧和流动的复杂几何形状。通过湍流Couette流验证了DA的性能。新的CFD-DA系统，然后应用于解决随时间变化的剪切层混合与甲烷-空气燃烧和湍流流动的钝体几何形状。结果表明，改进的模型参数的估计和不确定性减少初始条件（IC）的火焰和流动的CFD模拟的MLEF方法。
The numerical solution of partial differential equations that govern fluid dynamics with turbulence and combustion is challenging due to the multiscale nature of the dynamical system and the need to resolve small-scale physical features. In addition, the uncertainties in the dynamical system, including those in the physical models and parameters, initial and boundary conditions and numerical methods, impact the computational fluid dynamics (CFD) prediction of turbulence and chemical reactions. To improve the CFD prediction, this study focuses on the development and application of a maximum likelihood ensemble filter (MLEF), an ensemble-based data assimilation (DA), for flows featuring combustion and/or turbulence. MLEF finds the optimal analysis and its uncertainty by maximizing the posterior probability density function. The novelty of the study lies in the combination of advanced DA and CFD methods for a new comprehensive application to predict engineering fluid dynamics. The study combines important aspects, including an ensemble-based DA with analysis and uncertainty estimation, an augmented control vector that simultaneously adjusts initial conditions and model empirical parameters and an application of DA to CFD modeling of combustion and flows with complex geometry. The DA performance is validated by a turbulent Couette flow. The new CFD–DA system is then applied to solve the time-evolving shear-layer mixing with methane-air combustion and the turbulent flow over a bluff-body geometry. Results demonstrate the improvement of estimates of model parameters and the uncertainty reduction in initial conditions (ICs) for CFD modeling of flames and flows by the MLEF method.
利用数据同化对钝体稳定预混火焰进行 CFD 建模
DOI：
10.2514/6.2020-0352
发表时间：
2020
期刊：
AIAA meeting papers on disc
影响因子：
--
作者：
Wang, Y.;Walters, S.;Overton, N.;Guzik, S. M.;Gao, X.
通讯作者：
Gao, X.