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.
Progress in Aerospace Sciences,
Год журнала:
2024,
Номер
149, С. 101021 - 101021
Опубликована: Июль 17, 2024
Lattice
structures,
produced
by
repeated
unit
cells
in
the
particular
pattern,
offer
a
high
strength-to-weight
ratio.
The
current
advancement
Additive
manufacturing
(AM)
technology,
creating
complex
geometries
like
lattice
structures
has
revolutionized
production
across
various
industries.
While
several
reviews
have
focused
on
different
specific
aspects
of
comprehensive
overview
recent
advancements
aerospace
structural
applications
is
lacking.
Therefore,
review
used
lightweight
manufactured
through
AM
presented
here.
Basic
classification
structure
followed
detailed
study
factors
influencing
mechanical
properties
crucial
for
application.
Current
trends
technologies
are
analyzed
detail
with
identification
capabilities
and
limitations.
Furthermore,
literature
optimization
techniques
engineering
lightweight,
along
fabrication
processes
involved,
challenges
future
research
directions
reported.
By
providing
insights
into
directions,
this
serves
as
valuable
resource
researchers
engineers
involved
design
development
structures.
It
lays
groundwork
exploration
new
innovative
tailored
to
meet
evolving
needs
industry.
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
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.
Materials Testing,
Год журнала:
2024,
Номер
66(10), С. 1539 - 1556
Опубликована: Авг. 26, 2024
Abstract
Build
orientation
in
additive
manufacturing
technology
is
a
pre-process
application
that
affects
many
parameters,
such
as
the
volume
of
support
structure,
part
quality,
build
time,
and
cost.
Determining
optimum
for
one
or
more
objectives
complex
parts
an
error-prone
puzzle.
This
study
evaluates
behavior
cuckoo
search
algorithm,
differential
evolution,
firefly
genetic
gray
wolf
optimizer,
Harris
hawks
optimization,
jaya
moth
flame
multi-verse
particle
swarm
A
Sine
cosine
salp
whale
optimization
algorithm
to
determine
component
be
manufactured
additively.
The
efficiency
these
algorithms
evaluated
on
problem
two
components
considering
undercut
area
height
objective
functions.
Thus,
feasibility
real-world
problems
revealed.
According
results
obtained
from
extensive
analysis,
best
alternative
minimizing
area,
its
robustness.
However,
required
time
solve
much
almost
twice
other
algorithms.
are
alternatives
height.
