ZAMM ‐ Journal of Applied Mathematics and Mechanics / Zeitschrift für Angewandte Mathematik und Mechanik,
Год журнала:
2024,
Номер
unknown
Опубликована: Дек. 17, 2024
Abstract
This
study
investigates
strain
rates
in
internally
pressurized
rotating
cylinders
with
varying
density,
using
Norton's
law
to
analyze
the
effects
of
anisotropy
and
creep
exponent
n
.
The
research
is
significant
for
optimizing
design
durability
such
engineering
applications.
A
detailed
analysis
revealed
distinct
rate
patterns
among
anisotropic
materials
Types
I
II
exhibited
lower
circumferential
compared
isotropic
Type
III
materials,
while
showed
reduced
axial
relative
materials.
These
findings
suggest
that
offer
superior
stress‐related
performance,
enhancing
under
pressure
rotation.
study's
novelty
lies
its
comprehensive
examination
anisotropy's
influence
on
rates,
extending
beyond
prior
work
by
demonstrating
how
specific
outperform
ones
reducing
deformation
improving
structural
resilience.
ZAMM ‐ Journal of Applied Mathematics and Mechanics / Zeitschrift für Angewandte Mathematik und Mechanik,
Год журнала:
2025,
Номер
105(3)
Опубликована: Март 1, 2025
Abstract
Entropy
generation
refers
to
the
energy
losses
and
irreversibilities
in
dynamics
of
non‐linear
flow
heat
transfer
process.
Its
applications
span
a
wide
range,
including
exchangers,
turbomachinery,
chemical
reactors,
microfluidic
devices,
many
others.
In
this
study,
we
analyze
irreversibility
deionized
water‐based
Casson–Williamson
hybrid
ferrofluid
flowing
over
continuously
moving
cylinder.
A
magnetic
field
with
non‐changing
intensity
is
exerted
transversely
direction
which
fluid
streams.
The
bivariate
spectral
local
linearization
method
on
multiple
overlapping
single
grids
used
solve
resulting
equations.
results
are
validated
by
comparing
them
existing
studies
under
certain
limiting
conditions.
Graphical
presented
show
effects
parametric
values,
such
as
volumetric
fraction
()
ferrous
oxide
aluminum
oxide,
Casson
Williamson
parameters
thermal
radiation
parameter
velocity,
temperature
distribution,
entropy
generation,
Bejan
numbers.
Findings
indicate
that
fractions
increase
magnitude
generated
system.
ABSTRACT
The
present
study
enlightens
the
analysis
of
transient
disturbances
in
a
nonlocal
micropolar
thermodiffusive
medium
with
two
temperatures
and
variable
thermal
conductivity
on
account
mechanical
load.
theoretical
model
is
established
framework
Eringen's
elasticity
theory
Green–Lindsay
theory.
By
addressing
scientific
engineering
domains,
mathematical
holds
potential
to
stimulate
practical
innovations
design
optimization
advanced
materials
devices
tailored
for
real‐world
applications.
analytical
solution
procured
by
employing
normal
mode
displacement
components,
stresses,
temperatures,
concentration
space–time
domain.
A
numerical
simulation
magnesium
crystal
material
carried
out
using
MATLAB
software
investigate
impacts
various
parameters
thermophysical
quantities,
outcomes
are
illustrated
graphically.
graphical
results
demonstrate
that
micropolarity
diffusivity
have
significant
effects
physical
fields.
Temperature
fields
increasingly
influenced
conductivity,
which
signifies
importance
this
parameter.
comparative
two‐temperature
one‐temperature
generalized
thermoelasticity
presents
difference
magnitudes
quantities
constituting
model.
reveal
all
distributions
restricted
bounded
region,
exhibiting
finite
speed
thermoelastic
signals.
Some
specific
cases
been
derived
from
particularly
noteworthy.
To
best
authors'
knowledge,
no
research
emphasizing
dynamic
response
microstructured
has
conducted,
significantly
defines
novelty
conducted
research.
Processes,
Год журнала:
2025,
Номер
13(4), С. 1055 - 1055
Опубликована: Апрель 1, 2025
This
research
investigates
the
impact
of
second-order
slip
conditions,
Stefan
flow,
and
convective
boundary
constraints
on
stagnation-point
flow
couple
stress
nanofluids
over
a
solid
sphere.
The
nanofluid
density
is
expressed
as
nonlinear
function
temperature,
while
diffusion-thermo
effect,
chemical
reaction,
thermal
radiation
are
incorporated
through
linear
models.
governing
equations
transformed
using
appropriate
non-similar
transformations
solved
numerically
via
finite
difference
method
(FDM).
Key
physical
parameters,
including
heat
transfer
rate,
analyzed
in
relation
to
Dufour
number,
velocity,
parameters
an
artificial
neural
network
(ANN)
framework.
Furthermore,
response
surface
methodology
(RSM)
employed
optimize
skin
friction,
transfer,
mass
by
considering
influence
radiation,
slip,
reaction
rate.
Results
indicate
that
velocity
enhances
behavior
reducing
temperature
concentration
distributions.
Additionally,
increase
number
leads
higher
profiles,
ultimately
lowering
overall
ANN-based
predictive
model
exhibits
high
accuracy
with
minimal
errors,
offering
robust
tool
for
analyzing
optimizing
transport
characteristics
nanofluids.
ABSTRACT
This
study
investigates
magnetohydrodynamic
fluids
in
converging
and
diverging
channels,
with
a
focus
on
melting
heat
transfer
effects.
The
investigation
utilizes
combination
of
numerical
techniques,
specifically
the
finite
element
Galerkin
method,
artificial
neural
network
(ANN)
modeling
to
examine
fluid
flow
behavior
thermal
patterns
various
channel
configurations.
Numerical
explanations
are
provided
for
effect
these
factors
temperature,
velocity,
local
skin
friction,
Nusselt
number
distributions.
Upon
careful
analysis
graphical
presentation,
acquired
data
provide
significant
understanding
how
different
physical
parameters
affect
properties.
contrast
between
current
past
findings
reveals
good
agreement.
have
important
applications
engineering
fields
where
specific
control
is
essential,
including
plastic
sheet
extrusion,
electronic
device
cooling,
metal
casting.
Additionally,
research
employs
ANN
enhance
prediction
characteristics,
demonstrating
strong
correlation
predicted
theoretical
results.
Accurate
regulation
transmission
crucial
technical
areas,
such
as
casting,
cooling.
ZAMM ‐ Journal of Applied Mathematics and Mechanics / Zeitschrift für Angewandte Mathematik und Mechanik,
Год журнала:
2025,
Номер
105(5)
Опубликована: Май 1, 2025
Abstract
Several
physical
phenomena
associated
with
fluid–solid
interaction
occur
in
the
presence
of
granular,
micro,
nanoscale,
and
crystal
structures.
Heat
transfer
fluids
containing
such
microbodies
cannot
be
studied
using
conventional
rheological
stress–strain
relations.
Eringen
developed
micropolar
theory
for
rheology
to
investigate
related
fields
flow
behavior.
In
contrast
classical
law
heat
conduction,
polymeric
liquids
display
thermal
relaxation
time
conduction.
To
avoid
any
discrepancy,
a
generalized
non‐Fourier
is
used
studying
transfer.
A
theoretical
approach
via
flux
theories
conservation
laws.
The
Galerkin
finite
element
method
implemented
visualize
record
simulations
study
mixed
convection
exhibiting
couple
stresses,
microinertia,
spin
gradients,
viscosity
effects,
wall
vorticity
rate
has
highest
value
comparison
mono
di
nanofluids.
shear
stress
ternary
nanofluids
on
surface
sheet
noted
relative
hybrid
Moreover,
Newtonian
fluid
less
than
that
fluid.
phenomenon
strong
‐micropolar
fluids.
nanofluid
bears
maximum
retarding
force
from
porous
medium
case
weaker
International Journal of Numerical Methods for Heat & Fluid Flow,
Год журнала:
2025,
Номер
unknown
Опубликована: Май 7, 2025
Purpose
This
paper
aims
to
investigate
the
effects
of
thermal
radiation
on
magnetohydrodynamics
(MHD)
bioconvection
nonlinear
complex
structure
flow
non-Newtonian
fluids
such
as
Casson,
Williamson
and
Sisko
fluids.
Design/methodology/approach
The
coupled
fundamental
equations
governing
steady,
incompressible
combined
with
Casson–Williamson–Sisko
over
an
exponential
sheet
are
reduced
ordinary
differential
using
appropriate
transformations.
Open-source
platforms
Google
Colab
Python
used.
Results,
performance,
accuracy
correlation
examined
neural
networking,
Levenberg-Marquardt,
machine
learning,
artificial
intelligence
(AI)
algorithms
linear
regression.
Findings
Numerical
graphical
results
presented
observe
impact
physical
parameters.
prospect
AI
tools,
particularly
increases
developed
fluid
dynamics
models.
Besides,
further
scope
learning
in
hybrid
nature
is
also
presented.
It
concluded
that
Levenberg-Marquardt
algorithm
most
suitable
for
simulation
boundary
layer
high
accuracy,
smooth
regression
curves
minimum
rate
error.
observed
range
10
−8
mean
squared
error
shows
good
fit
model.
noted
by
increasing
Casson
fluids’
parameters,
velocity
profile
decreases.
Both
concentration
motile
density
decrease
values
Schmidt
Peclet
numbers.
Originality/value
existing
literature
lacks
a
comparative
analysis
networks
predicting
AI-based
approaches,
MHD
literature.
effort
devoted
fill
said
gap.
Proceedings of the Institution of Mechanical Engineers Part C Journal of Mechanical Engineering Science,
Год журнала:
2025,
Номер
unknown
Опубликована: Май 17, 2025
This
research
rigorously
investigates
the
heat
transfer
dynamics
between
parallel
disks
through
a
combined
experimental
and
machine
learning
methodology,
focusing
on
flux,
Reynolds
number,
gap
ratio.
Conducting
100
experiments
across
varied
numbers,
fluxes,
ratios,
study
identifies
optimal
parameter
values
where
Nusselt
number
maximizes,
attributing
this
to
enhanced
convective
transfer.
An
artificial
neural
network
(ANN)
model,
refined
using
Teaching-Learning-Based
Optimization
(TLBO)
JAYA
algorithms,
accurately
predicts
confirming
findings
providing
robust
tool
for
optimizing
systems
in
applications
like
gas
turbines
exchangers.
The
underscores
critical
importance
of
precise
flow
control,
offering
significant
advancements
design
optimization
engineering
involving
disks.
Results
demonstrate
highest
average
48.132
at
ratio
20.38,
flux
444.30
W/m
2
,
99.99,
validating
reliability
proposed
models.