Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Machine learning assisted modeling of thermohydraulic correlations for
  heat exchangers with twisted tape inserts   This article presents the application of machine learning (ML) algorithms in
modeling of the heat transfer correlations (e.g. Nusselt number and friction
factor) for a heat exchanger with twisted tape inserts. The experimental data
for the heat exchanger at different Reynolds numbers and twist ratios were used
for the correlation modeling. Three machine learning algorithms: Polynomial
Regression (PR), Random Forest (RF), and Artificial Neural Network (ANN) were
used in the data-driven surrogate modeling. The hyperparameters of the ML
models are carefully optimized to ensure generalizability. The performance
parameters (e. g. $R^2$ and $MSE$) of different ML algorithms are analyzed. It
was observed that the ANN predictions of heat transfer coefficients outperform
the predictions of PR and RF across different test datasets. Based on our
analysis we make recommendations for future data-driven modeling efforts of
heat transfer correlations and similar studies.

25
The categories of this paper are: patt-sol
19
The categories of this paper are: eess
21
The categories of this paper are: adap-org
18
The categories of this paper are: econ
29
The categories of this paper are: funct-an
28
The categories of this paper are: alg-geom
20
The categories of this paper are: acc-phys
35
The categories of this paper are: mtrl-th
37
The categories of this paper are: supr-con
27
The categories of this paper are: comp-gas
16
The categories of this paper are: stat
36
The categories of this paper are: cmp-lg
2
The categories of this paper are: math
32
The categories of this paper are: atom-ph
22
The categories of this paper are: chao-dyn
12
The categories of this paper are: nucl-th