ZAMM ‐ Journal of Applied Mathematics and Mechanics / Zeitschrift für Angewandte Mathematik und Mechanik,
Год журнала:
2024,
Номер
unknown
Опубликована: Ноя. 13, 2024
Abstract
The
effects
of
viscous
force
on
magnetohydrodynamic
flow
in
coaxial
cylinders
are
discussed
this
article.
inner
cylinder
stretches
linearly
along
the
axis,
while
outer
rotates
with
some
fixed
angular
velocity.
movement
fluid
between
these
concentric
depends
stretching
and
cylinder's
rotation.
Understanding
type
is
crucial
for
applications
engineering
industrial
processes,
such
as
magnetic
materials
processing
transport
rotating
machinery.
surface
also
considered
slippery,
that
is,
first
order
slip
condition
incorporated
internal
surface.
impact
dissipation
calculated
current
study.
After
using
suitable
transformations,
we
turn
mass
conservation,
Navier‐stokes,
energy
equations
into
dimensionless
ordinary
differential
equations.
Meanwhile,
numerical
solutions
conducted
via
shooting
method.
outcomes
graphically
presented
by
varying
values
certain
parameters
like
curvature
parameter,
gap
cylinders,
so
forth.
It
noted
expanding
size
enhances
velocity
fluid,
accompanied
a
rise
temperature.
Additionally,
findings
indicate
smaller
exhibit
higher
heat
flux
rate.
novelty
work
lies
combined
dissipation,
conditions,
MHD
transfer,
offering
insights
beyond
what
has
been
previously
explored
literature.
ZAMM ‐ Journal of Applied Mathematics and Mechanics / Zeitschrift für Angewandte Mathematik und Mechanik,
Год журнала:
2025,
Номер
105(1)
Опубликована: Янв. 1, 2025
Abstract
The
present
study
examines
the
thermal
characteristics
and
stresses
at
boundary
for
peristaltic
motion
of
Reiner‐Philippoff
fluid
through
a
symmetric
channel.
(R‐P)
model
is
widely
recognized
its
ability
to
provide
comprehensive
representation
unique
properties
exhibited
by
non‐Newtonian
fluids.
One
notable
aspect
that
initiates
this
nonlinear
relationship
between
velocity
gradient
shear
stress.
Moreover,
captures
implicit
connection
deformation
rate
Additionally,
R‐P
exhibits
distinct
characteristics,
acting
as
dilatant
,
exhibiting
pseudoplastic
behavior
behaving
Newtonian
when
.
Governing
equations
are
mathematically
modeled
under
consideration
mixed
convection,
viscous
dissipation,
magnetic
field,
Joule
heating
effects.
Long
wavelength
small
Reynolds
number
approximations
used
simplify
system.
To
compute
numerical
solution
simplified
system,
BVP4c
technique
employed
via
MATLAB.
influences
key
parameters
on
flow
physically
visualized
graphs.
A
detailed
analysis
heat
transfer
dilatant,
pseudoplastic,
fluids
also
provided.
assessments
wall
presented
tables.
Outcomes
reveal
temperature
profile
decreases
due
parameter
Bingham
number.
findings
case
indicate
both
enhanced
Grashof
Hartmann
numbers
lead
an
increase
in
profile.
Tabular
results
improved
developing
values
Brinkman
numbers,
while
exhibit
opposite
behavior.
decrease
with
greater
Furthermore,
more
effective
improving
reducing
compared
Multidiscipline Modeling in Materials and Structures,
Год журнала:
2024,
Номер
unknown
Опубликована: Сен. 1, 2024
Purpose
The
main
focus
is
to
provide
a
non-similar
solution
for
the
magnetohydrodynamic
(MHD)
flow
of
Casson
fluid
over
curved
stretching
surface
through
novel
technique
artificial
intelligence
(AI)-based
Lavenberg–Marquardt
scheme
an
neural
network
(ANN).
effects
joule
heating,
viscous
dissipation
and
non-linear
thermal
radiation
are
discussed
in
relation
behavior
fluid.
Design/methodology/approach
coupled
boundary
layer
equations
transformed
into
dimensionless
Partial
Differential
Equation
(PDE)
by
using
transformation.
local
utilized
truncate
system
up
2nd
order,
which
treated
as
ordinary
differential
(ODEs).
ODEs
solved
numerically
via
bvp4c.
data
sets
constructed
then
implemented
ANN.
Findings
results
indicate
that
parameter
increases
temperature.
reduces
velocity
well
mean
squared
error
(MSE),
regression
plot,
histogram,
analysis
skin
friction,
Nusselt
number
presented.
Furthermore,
values
friction
obtained
0.99993
0.99997,
respectively.
ANN
predicted
show
stability
convergence
with
high
accuracy.
Originality/value
AI-based
ANNs
have
not
been
applied
solutions
surfaces
model,
dissipation.
Moreover,
authors
this
study
employed
Levenberg–Marquardt
supervised
learning
investigate
MHD
model
heating.
governing
non-linear,
PDE
ODEs.
