Materials Testing,
Год журнала:
2024,
Номер
67(2), С. 297 - 312
Опубликована: Дек. 17, 2024
Abstract
The
primary
objective
of
numerous
optimization
problems
is
to
enhance
a
single
metric
whose
lowest
or
highest
value
accurately
reflects
the
response
quality
system.
However,
in
some
instances,
relying
solely
on
one
not
practical,
leading
consideration
multi-objective
(MO)
that
aim
improve
multiple
performance
indicators
simultaneously.
This
approach
requires
use
method
adept
at
handling
intricacies
scenarios
with
various
indices.
Consequently,
researchers
have
explored
truss
as
extensively
single-objective
(SO)
scenarios.
novel
Lichtenberg
algorithm
two
archives
(MOLA-2arc)
has
been
developed
address
this.
efficacy
MOLA-2arc
evaluated
against
eight
other
MO
algorithms,
including
bat
(MOBA),
crystal
structure
(MOCRY),
cuckoo
search
(MOCS),
firefly
(MOFA),
flower
pollination
(MOFPA),
harmony
(MOHS),
jellyfish
(MOJS)
algorithm,
and
original
(MOLA).
challenge
minimize
structural
mass
compliance
while
adhering
stress
limitations.
outcomes
demonstrate
shows
notable
improvements
over
its
predecessor,
MOLA,
surpasses
all
competing
algorithms
this
study.
Materials Testing,
Год журнала:
2024,
Номер
unknown
Опубликована: Авг. 30, 2024
Abstract
This
paper
introduces
and
investigates
an
enhanced
Partial
Reinforcement
Optimization
Algorithm
(E-PROA),
a
novel
evolutionary
algorithm
inspired
by
partial
reinforcement
theory
to
efficiently
solve
complex
engineering
optimization
problems.
The
proposed
combines
the
(PROA)
with
quasi-oppositional
learning
approach
improve
performance
of
pure
PROA.
E-PROA
was
applied
five
distinct
design
components:
speed
reducer
design,
step-cone
pulley
weight
optimization,
economic
cantilever
beams,
coupling
bolted
rim
vehicle
suspension
arm
An
artificial
neural
network
as
metamodeling
is
used
obtain
equations
for
shape
optimization.
Comparative
analyses
other
benchmark
algorithms,
such
ship
rescue
algorithm,
mountain
gazelle
optimizer,
cheetah
demonstrated
superior
in
terms
convergence
rate,
solution
quality,
computational
efficiency.
results
indicate
that
holds
excellent
promise
technique
addressing
Journal of Composites Science,
Год журнала:
2024,
Номер
8(7), С. 273 - 273
Опубликована: Июль 15, 2024
The
incorporation
of
fiber
reinforcements
into
polymer
matrices
has
emerged
as
an
effective
strategy
to
enhance
the
mechanical
properties
composites.
This
study
investigated
tensile
and
fracture
behavior
3D-printed
polylactic
acid
(PLA)
composites
reinforced
with
chopped
carbon
fibers
(CCFs)
through
experimental
characterization
finite
element
analysis
(FEA).
Composite
samples
varying
CCF
orientations
(0°,
0°/90°,
+45°/−45°,
0°/+45°/−45°/90°)
were
fabricated
via
fused
filament
fabrication
(FFF)
subjected
single-edge
notched
bend
(SENB)
tests.
results
revealed
a
significant
improvement
in
strength,
elastic
modulus,
toughness
compared
unreinforced
PLA.
0°/+45°/90°
orientation
exhibited
3.6%
increase
while
+45°/−45°
displayed
29.9%
enhancement
modulus
(259.12
MPa)
relative
neat
PLA
(199.34
MPa√m).
An
inverse
correlation
between
strength
was
observed,
attributed
mechanisms
such
crack
deflection,
bridging,
pull-out
facilitated
by
multi-directional
orientations.
FEA
simulations
incorporating
transversely
isotropic
material
model
J-integral
approach
conducted
using
Abaqus,
accurately
predicting
trends
maximum
discrepancy
8%
data.
Fractographic
elucidated
strengthening
mechanisms,
highlighting
potential
tailoring
optimize
performance
for
structural
applications.
Materials Testing,
Год журнала:
2024,
Номер
66(9), С. 1510 - 1518
Опубликована: Авг. 13, 2024
Abstract
In
this
study,
a
novel
multi-cell
crash
box
was
designed
and
produced
using
15
%
short
carbon
fiber
reinforced
polyethylene
terephthalate
(CF15PET),
polylactic
acid
(PLA),
acrylonitrile
butadiene
styrene
(ABS)
filaments
one
of
the
additive
manufacturing
methods,
melt
deposition
method
(FDM).
All
structures’
maximum
force
energy
absorption
performances
have
been
investigated.
As
result
test,
it
determined
that
box,
which
best
meets
high
folding
properties,
expected
features
in
boxes,
has
parts
manufactured
ABS
CF15PET
materials.
According
to
test
result,
found
is
11
higher
than
approximately
4.5
PLA.
It
response
value
5
12
materials
can
be
used
boxes
form
an
idea
about
design
by
designing
analyzing
finite
element
programs.
Materials Testing,
Год журнала:
2024,
Номер
66(10), С. 1557 - 1563
Опубликована: Авг. 8, 2024
Abstract
This
research
is
the
first
attempt
in
literature
to
combine
design
for
additive
manufacturing
and
hybrid
flood
algorithms
optimal
of
battery
holders
an
electric
vehicle.
article
uses
a
recent
metaheuristic
explore
optimization
holder
A
polylactic
acid
(PLA)
material
preferred
during
manufacturing.
Specifically,
both
algorithm
(FLA-SA)
water
wave
optimizer
(WWO)
are
utilized
generate
holder.
The
hybridized
with
simulated
annealing
algorithm.
An
artificial
neural
network
employed
acquire
meta-model,
enhancing
efficiency.
results
underscore
robustness
achieving
designs
car
components,
suggesting
its
potential
applicability
various
product
development
processes.
