The reconstruction of thermo-chemical scalars in combustion from a reduced set of their principal components

Hessam Mirgolbabaei; Tarek Echekki

doi:10.1016/j.combustflame.2014.11.027

The reconstruction of thermo-chemical scalars in combustion from a reduced set of their principal components

Hessam Mirgolbabaei, Tarek Echekki

Research output: Contribution to journal › Article › peer-review

25 Scopus citations

Abstract

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.

Original language	English (US)
Pages (from-to)	1650-1652
Number of pages	3
Journal	Combustion and Flame
Volume	162
Issue number	5
DOIs	https://doi.org/10.1016/j.combustflame.2014.11.027
State	Published - May 1 2015
Externally published	Yes

Bibliographical note

Publisher Copyright:
© 2014 The Combustion Institute.

Keywords

Principal component analysis
Turbulent combustion

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10.1016/j.combustflame.2014.11.027

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abstract = "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.",

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AU - Mirgolbabaei, Hessam

AU - Echekki, Tarek

PY - 2015/5/1

Y1 - 2015/5/1

N2 - 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.

AB - 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.

KW - Principal component analysis

KW - Turbulent combustion

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JO - Combustion and Flame

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ER -

The reconstruction of thermo-chemical scalars in combustion from a reduced set of their principal components

Abstract

Bibliographical note

Keywords

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