Partial Differential Equations in Applied Mathematics,
Journal Year:
2024,
Volume and Issue:
11, P. 100852 - 100852
Published: July 31, 2024
In
this
paper,
studied
the
impact
of
heat
generation
Nanofluid
movement
over
a
stretching
sheet
by
consideration
Thermophoresis,
Brownian
motion
&
first
order
chemical
react
parameters
etc.
Constructed
modelling
equations
with
based
on
assumptions
and
introducing
emerging
parameters.
The
converted
to
third
ODE
through
stream
functions.
FDM
collocation
polynomial
technique
(bvp4c)
employed
solve
those
MATLAB
software.
results
are
presented
graphical
form
influence
Thickness
thermal
boundary
stratum
decreased
as
enhancing
Prandtl
number.
Influence
parameter,
fluid
temperature
raised
fall
down
concentration.
Temperature
concentration
enhancement
thermophoresis.
A
decrease
in
transfer
rate
an
increase
mass
observed
thermophoresis,
motion,
parameter
values
increasing.
reaction
intensifies
driving
forces
gradients,
which
govern
transfer,
leading
increased
rates
both
transfer.
Validation
model
present
align
well
past
reported
studies.
This
can
extent
analyse
hybrid
nanofluid
manufacturing
process
detergent,
painting
lubricants,
analysis
blood
flow
artery
ZAMM ‐ Journal of Applied Mathematics and Mechanics / Zeitschrift für Angewandte Mathematik und Mechanik,
Journal Year:
2024,
Volume and Issue:
104(5)
Published: March 13, 2024
Abstract
This
study
investigates
the
flow
and
heat
transfer
characteristics
of
a
second‐grade
fluid
over
flat
surface
with
variable
flux.
Utilizing
mathematical
model
based
on
distributed
order
fractional
derivatives,
we
offer
more
precise
representation
non‐Newtonian
behavior.
The
associated
highly
nonlinear
equations
are
tackled
numerically
through
an
innovative
amalgamation
finite
difference
scheme
technique.
Our
investigation
thoroughly
evaluates
influence
several
critical
parameters
fluid's
motion
thermal
characteristics.
Notably,
magnetic
parameter
significantly
inhibits
velocity,
illustrating
impact
forces.
Additionally,
power
law
leads
to
decrease
in
both
velocity
temperature
profiles,
highlighting
its
dynamics.
Furthermore,
changes
Reynold
number
observed
cause
substantial
increase
skin
friction,
by
approximately
40%
50%.
These
simulation
results
provide
valuable
insights
into
complex
interaction
between
characteristics,
enhancing
our
understanding
such
systems
industrial
applications.
Heat Transfer,
Journal Year:
2024,
Volume and Issue:
53(8), P. 4551 - 4571
Published: Aug. 12, 2024
Abstract
This
study
investigates
the
heat
and
mass
transfer
dynamics
in
exothermic,
chemically
reactive
fluids
over
variable‐thickness
surfaces
using
advanced
numerical
methods
artificial
neural
networks
(ANN).
The
importance
of
understanding
these
processes
lies
their
significant
industrial
applications,
such
as
chemical
reactors
exchangers.
We
transformed
nonlinear
partial
differential
equations
into
ordinary
used
bvp4c
method
to
generate
a
comprehensive
data
set.
ANN
model,
trained
with
Levenberg–Marquardt
algorithm,
was
evaluated
for
its
accuracy
simulating
complex
fluid
thermosolutal
transport
phenomena.
Our
results
revealed
that
increasing
second‐grade
parameter
enhanced
skin
friction
by
20.38%,
rate
1.16%,
4.06%.
model
demonstrated
high
predictive
precision
validation
mean
squared
error
.
These
findings
highlight
effectiveness
methodology
providing
precise
simulations
dynamics,
which
is
crucial
optimizing
processes.
Partial Differential Equations in Applied Mathematics,
Journal Year:
2024,
Volume and Issue:
11, P. 100852 - 100852
Published: July 31, 2024
In
this
paper,
studied
the
impact
of
heat
generation
Nanofluid
movement
over
a
stretching
sheet
by
consideration
Thermophoresis,
Brownian
motion
&
first
order
chemical
react
parameters
etc.
Constructed
modelling
equations
with
based
on
assumptions
and
introducing
emerging
parameters.
The
converted
to
third
ODE
through
stream
functions.
FDM
collocation
polynomial
technique
(bvp4c)
employed
solve
those
MATLAB
software.
results
are
presented
graphical
form
influence
Thickness
thermal
boundary
stratum
decreased
as
enhancing
Prandtl
number.
Influence
parameter,
fluid
temperature
raised
fall
down
concentration.
Temperature
concentration
enhancement
thermophoresis.
A
decrease
in
transfer
rate
an
increase
mass
observed
thermophoresis,
motion,
parameter
values
increasing.
reaction
intensifies
driving
forces
gradients,
which
govern
transfer,
leading
increased
rates
both
transfer.
Validation
model
present
align
well
past
reported
studies.
This
can
extent
analyse
hybrid
nanofluid
manufacturing
process
detergent,
painting
lubricants,
analysis
blood
flow
artery
