论文标题
使用动态双重分解的湍流化学相互作用减少订单建模
Reduced Order Modeling of Turbulence-Chemistry Interactions using Dynamically Bi-Orthonormal Decomposition
论文作者
论文摘要
评估了湍流化学相互作用的降低订单建模的动态双向异常（DBO）分解的性能。 DBO是一种直率的低级近似技术，其中反应性流场的瞬时组合物矩阵分解为一组正顺序的空间模式，组成空间中的一组正规矢量，以及低率校正矩阵的分解。基于主组件分析（PCA）区分DBO和减少订单模型（ROM）的两个因素是：（i）DBO不需要任何离线数据生成； （ii）在DBO中，低级别组成子空间与PCA中的静态子空间相反。由于这些功能，DBO可以在传输变量状态的固有和外部激发的瞬态变化中适应。为了进行演示，模拟是对暂时进化的射流中未固定的CO/H2火焰进行的。具有53种物种的Gri-Mech 3.0模型用于化学动力学建模。通过后验比较与通过同一火焰的全级直接数值模拟（DNS）以及DNS数据的PCA降低产生的数据来评估结果。 DBO还可以对热化学变量的各种统计数据产生出色的预测。
The performance of the dynamically bi-orthogonal (DBO) decomposition for the reduced order modeling of turbulence-chemistry interactions is assessed. DBO is an on-the-fly low-rank approximation technique, in which the instantaneous composition matrix of the reactive flow field is decomposed into a set of orthonormal spatial modes, a set of orthonormal vectors in the composition space, and a factorization of the low-rank correlation matrix. Two factors which distinguish between DBO and the reduced order models (ROMs) based on the principal component analysis (PCA) are: (i) DBO does not require any offline data generation; and (ii) in DBO the low-rank composition subspace is time-dependent as opposed to static subspaces in PCA. Because of these features, DBO can adapt on-the-fly to intrinsic and externally excited transient changes in state of the transport variables. For demonstration, simulations are conducted of a non-premixed CO/H2 flame in a temporally evolving jet. The GRI-Mech 3.0 model with 53 species is used for chemical kinetics modeling. The results are appraised via a posteriori comparisons against data generated via full-rank direct numerical simulation (DNS) of the same flame, and the PCA reduction of the DNS data. The DBO also yields excellent predictions of various statistics of the thermo-chemical variables.
