Actual microstructure-based modeling and failure evolution of SiC and SiC+B₄C reinforced Al matrix composites
Journal of Alloys and Compounds,
Год журнала:
2025,
Номер
unknown, С. 179365 - 179365
Опубликована: Фев. 1, 2025
Язык: Английский
Hot deformation behavior investigation of heat-resistant aluminum matrix composite based on Arrhenius model and machine learning
Journal of Materials Informatics,
Год журнала:
2025,
Номер
5(3)
Опубликована: Апрель 27, 2025
The
heat-resistant
aluminum
matrix
composite
(AMC)
exhibits
excellent
thermal
performance
due
to
the
presence
of
dispersed
nano-phases.
Accurately
characterizing
high-temperature
flow
stress
is
essential
for
comprehending
mechanisms
deformation
and
improving
material
workability.
To
enhance
accuracy
modeling
a
new
AMC
during
processing,
set
isothermal
compression
tests
at
elevated
temperatures
was
conducted.
This
testing
performed
on
under
varying
temperature
levels
(473,
523,
573,
623,
673
K)
distinct
strain
rates
(0.001,
0.01,
0.1
s<sup>-1</sup>).
accurately
characterize
high
temperatures,
three
models
were
devised:
(1)
an
Arrhenius
model
that
includes
compensation;
(2)
back-propagation
neural
network
(BPNN)
model;
(3)
BPNN
optimized
using
genetic
algorithm
(GA-BPNN).
compensation
theory
enhances
model’s
ability
capture
nonlinear
characteristics,
while
(GA)
optimizes
parameter
settings.
each
in
describing
compared
determine
their
effectiveness.
findings
demonstrate
GA-BPNN
achieved
superior
fitting
accuracy,
with
root
mean
square
error
(RMSE)
6.48,
accompanied
by
coefficient
determination
(R<sup>2</sup>)
0.991
absolute
(MAE)
5.4.
evaluate
generalization
capabilities
models,
data
utilized
verification.
verified
data.
demonstrates
outstanding
capability,
achieving
highest
prediction
datasets,
R<sup>2</sup>
=
0.9102,
RMSE
9.09,
MAE
7.83.
Using
results,
hot
processing
map
developed,
optimal
window
(573
identified.
study
serves
as
valuable
reference
optimizing
parameters
AMCs
proposes
novel
approach
combining
machine
learning
description.
While
current
framework
computational
robustness,
extending
conclusions
composites
significantly
different
compositions
requires
further
validation.
Язык: Английский
Synergistic effect of pre-induced dislocations and ZrB2 on mechanical and thermal properties of Al/SiC composite
Tahir Mehmood Bhatti,
Yangwei Wang,
Mirza Muhammad Abu Bakar Baig
и другие.
Ceramics International,
Год журнала:
2024,
Номер
unknown
Опубликована: Ноя. 1, 2024
Язык: Английский
Recent Developments in Plastic Deformation Behavior of Titanium and Its Alloys During the Rolling Process: A Review
Materials,
Год журнала:
2024,
Номер
17(24), С. 6060 - 6060
Опубликована: Дек. 11, 2024
Titanium
(Ti)
and
its
alloys
are
used
in
various
applications,
including
aircraft
frames,
ship
parts,
heat
exchangers,
evaporator
tubes,
because
of
their
extraordinary
properties,
such
as
high
specific
strength,
excellent
corrosion
resistance
at
temperatures,
good
castability,
weldability.
Plastic
deformation
plays
a
crucial
role
securing
the
appropriate
microstructure
strength
Ti
these
applications.
The
rolling
process,
one
most
useful
methods
for
plastic
deformation,
causes
efficient
inside
materials,
resulting
grain
refinement,
dislocation
slip,
twinning.
Recent
studies
on
behaviors
have
explored
crystallographic
mechanical
properties.
These
investigations
primarily
analyzed
microstructural
changes
influence
properties
under
different
temperatures
methods.
This
study
elucidates
complex
relationship
between
processing
conditions
Therefore,
this
paper
presents
comprehensive
review
state-of-the-art
rolling.
Various
key
aspects
verifying
discussed,
electron
backscatter
diffraction
analysis,
Schmidt
factor,
misorientation
distribution.
Язык: Английский