Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Data-driven Analysis of Turbulent Flame Images   Turbulent premixed flames are important for power generation using gas
turbines. Improvements in characterization and understanding of turbulent
flames continue particularly for transient events like ignition and extinction.
Pockets or islands of unburned material are features of turbulent flames during
these events. These features are directly linked to heat release rates and
hydrocarbons emissions. Unburned material pockets in turbulent CH$_4$/air
premixed flames with CO$_2$ addition were investigated using OH Planar
Laser-Induced Fluorescence images. Convolutional Neural Networks (CNN) were
used to classify images containing unburned pockets for three turbulent flames
with 0%, 5%, and 10% CO$_2$ addition. The CNN model was constructed using three
convolutional layers and two fully connected layers using dropout and weight
decay. The CNN model achieved accuracies of 91.72%, 89.35% and 85.80% for the
three flames, respectively.

22
The categories of this paper are: chao-dyn
18
The categories of this paper are: econ
14
The categories of this paper are: math-ph
4
The categories of this paper are: cond-mat
12
The categories of this paper are: nucl-th
26
The categories of this paper are: bayes-an
15
The categories of this paper are: nucl-ex
25
The categories of this paper are: patt-sol
10
The categories of this paper are: q-bio
21
The categories of this paper are: adap-org
5
The categories of this paper are: gr-qc
30
The categories of this paper are: q-alg
28
The categories of this paper are: alg-geom
2
The categories of this paper are: math
7
The categories of this paper are: hep-th
24
The categories of this paper are: dg-ga