The reconstruction of thermo-chemical scalars in combustion from a reduced set of their principal components
The reconstruction of thermo-chemical scalars in combustion from a reduced set of their principal components
复制标题
从一组减少的主成分重建燃烧中的热化学标量
DOI：
10.1016/j.combustflame.2014.11.027
复制
发表时间：
2015
影响因子：
4.4
通讯作者：
T. Echekki
中科院分区：
文献类型：
--
作者：
H. Mirgolbabaei;T. Echekki
我们比较了两种重建方法的热化学标量（TCS）在湍流燃烧中使用主成分分析。第一种方法是基于TCSs和它们的主成分（PC）之间的线性关系的反演。第二种是基于回归的TCS与减少使用人工神经网络的PC集。研究基于Sandia Flame F.我们发现，回归潜在地提供了上级重建的反演表达式时，截断的原始PC集使用。
We compare two reconstruction approaches for thermo-chemical scalars (TCSs) in turbulent combustion using principal component analysis. The first approach is based on the inversion of the linear relation between the TCSs and their principal components (PCs). The second is based on a regression of TCSs with a reduced set of the PCs using artificial neural networks. The study is based on one-dimensional turbulence simulation data of Sandia Flame F. We find that regression potentially offers superior reconstruction to the inversion expression when a truncated set of the original PCs is used.