Prediction of thermal and energy transport of MHD Sutterby hybrid nanofluid flow with activation energy using Group Method of Data Handling (GMDH)

• Published in: Computational & applied mathematics Vol. 41; no. 7
• Main Authors: Krishna, S. Gopi, Shanmugapriya, M., Alsinai, Ammar, Alameri, Abdu
• Format: Journal Article
• Language: English
• Published: Cham Springer International Publishing 01-10-2022; Springer Nature B.V
• Subjects: Activation energy; Applications of Mathematics; Applied physics; Chemical reactions; Coefficient of friction; Computational mathematics; Computational Mathematics and Numerical Analysis; Deborah number; Energy transfer; Ethylene glycol; Fluid flow; Group method of data handling; Iron oxides; Magnetic properties; Magnetohydrodynamics; Mathematical Applications in Computer Science; Mathematical Applications in the Physical Sciences; Mathematical models; Mathematics; Mathematics and Statistics; Nanofluids; Nanoparticles; Ordinary differential equations; Parameters; Partial differential equations; Reynolds number; Root-mean-square errors; Runge-Kutta method; Thermophoresis; Two dimensional flow; Hybrid Sutterby nanofluid; 34A38; 35B38; C; O2; H; GMDH; Activation energy; 81T17; Fe; O; CNTs–Fe
• ISSN: 2238-3603; 1807-0302
• DOI: 10.1007/s40314-022-01995-z

The present research work pursues GMDH for predicting thermal and energy transport of 2-D radiative magnetohydrodynamic (MHD) flow of hybrid Sutterby nanofluid across a moving wedge with activation energy. An exclusive class of nanoparticles
SWCNT
–
Fe
3
O
4
and
MWCNT
–
Fe
3
O
4
are dispersed into the ethylene glycol as regular fluid. The hybrid nanofluid mathematical model has been written as a system of partial differential equations (PDEs), which are then converted into ordinary differential equations (ODEs) through similarity replacements. Numerical solutions are attained Runge–Kutta–Fehlberg’s fourth fifth-order (RKF-45) scheme by adopting the shooting technique. The ranges of diverse sundry parameters used in our study are Hartree parameter
0.1
≤
m
≤
0.5
, magnetic parameter
0.3
≤
M
≤
1
, Deborah number
0.1
≤
De
≤
1
, moving wedge parameter
0.3
≤
γ
≤
0.9
, Reynolds number
0
≤
Re
≤
2.5
, solid volume fraction of
Fe
3
O
4
and
CNT
s
0.005
≤
φ
1
≤
0.1
,
0.005
≤
φ
2
≤
0.06
, Browanian motion
0.1
≤
Nb
≤
0.4
, thermophoresis parameter
0.1
≤
Nt
≤
0.25
, Eckeret number
0.05
≤
Ec
≤
1
, radiation parameter
1
≤
R
d
≤
2.5
, Lewis number
0.5
≤
Le
≤
1.5
, chemical reaction rate
0.1
≤
σ
≤
0.7
, heat source parameter,
0
≤
δ
≤
1.5
and activation energy
1
≤
E
≤
4
which shows up during the speed, thermal, and focus for
Fe
3
O
4
/
C
2
H
6
O
2
nanofluid and
CNTs
-
Fe
3
O
4
/
C
2
H
6
O
2
hybrid nanofluid. Additionally, the friction coefficient (
C
⌣
fx
), rate of heat transport
(
H
⌣
tx
)
, and rate of nanoparticle transport (
N
⌣
t
x
are calculated using GMDH. The numerical results for the current analysis are illustrated via tables, graphs, and contour plots. The efficiency of the proposed GMDH models is assessed using statistical measures such as MSE, MAE, RMSE,
R
, Error mean and Error StD. The predicted values are very close to the numerical results, and the coefficient of determination
R
2
of
C
⌣
fx
,
N
⌣
tx
, and
H
⌣
t
x
are 1, 0.97836 and 0.9960, respectively, which shows the best settlement.