Materials Testing,
Год журнала:
2025,
Номер
unknown
Опубликована: Апрель 14, 2025
Abstract
This
paper
introduces
an
improved
optimization
algorithm
based
on
migration
patterns
of
greylag
geese,
known
for
their
efficient
flying
formations.
The
Modified
Greylag
Goose
Optimization
Algorithm
(MGGOA)
is
modified
by
augmenting
the
levy
flight
mechanism
and
artificial
neural
network
(ANN)
strategies.
detailed,
presenting
mathematical
formulations
both
phases.
Subsequently,
applies
MGGOA
to
various
engineering
problems,
including
heat
exchanger
design,
car
side
impact
spring
design
optimization,
disc
clutch
brake
structural
automobile
component.
Statistical
comparisons
with
benchmark
algorithms
demonstrate
efficacy
in
finding
optimal
solutions
these
problems.
Materials Testing,
Год журнала:
2024,
Номер
66(7), С. 1063 - 1073
Опубликована: Апрель 30, 2024
Abstract
In
this
article,
a
newly
developed
optimization
approach
based
on
mathematics
technique
named
the
geometric
mean
algorithm
is
employed
to
address
challenge
of
robot
gripper,
airplane
bracket,
and
suspension
arm
automobiles,
followed
by
an
additional
three
engineering
problems.
Accordingly,
other
challenges
are
ten-bar
truss,
three-bar
tubular
column,
spring
systems.
As
result,
demonstrates
promising
statistical
outcomes
when
compared
well-established
algorithms.
Additionally,
it
requires
less
iteration
achieve
global
optimum
solution.
Furthermore,
exhibits
minimal
deviations
in
results,
even
techniques
produce
better
or
similar
outcomes.
This
suggests
that
proposed
paper
can
be
effectively
utilized
for
wide
range
critical
industrial
real-world
challenges.
Materials Testing,
Год журнала:
2024,
Номер
66(5), С. 696 - 704
Опубликована: Фев. 19, 2024
Abstract
Thin-walled
structures
are
one
of
the
important
safety
components
used
in
vehicles.
They
placed
front
parts
vehicles
to
minimize
impacts
that
occur
event
a
collision,
and
they
absorb
impact
force
by
changing
shape
collision.
Crash
boxes
have
high-impact
absorption,
low
weight,
low-cost
expectations.
In
design
crash
boxes,
thin-walled
preferred
due
their
high
deformation
capability.
this
study,
additive
manufacturing
method
was
produce
structures.
were
produced
methods
using
PLA
ABS
materials.
The
manufactured
tested
an
test.
experimental
results,
energy
absorption
ability
from
materials
examined,
fragility
observed.
results
verified
finite
element
analysis
made
Materials Testing,
Год журнала:
2024,
Номер
66(8), С. 1230 - 1240
Опубликована: Июль 5, 2024
Abstract
This
paper
introduces
a
novel
approach,
the
Modified
Electric
Eel
Foraging
Optimization
(EELFO)
algorithm,
which
integrates
artificial
neural
networks
(ANNs)
with
metaheuristic
algorithms
for
solving
multidisciplinary
design
problems
efficiently.
Inspired
by
foraging
behavior
of
electric
eels,
algorithm
incorporates
four
key
phases:
interactions,
resting,
hunting,
and
migrating.
Mathematical
formulations
each
phase
are
provided,
enabling
to
explore
exploit
solution
spaces
effectively.
The
algorithm’s
performance
is
evaluated
on
various
real-world
optimization
problems,
including
weight
engineering
components,
economic
pressure
handling
vessels,
cost
welded
beams.
Comparative
analyses
demonstrate
superiority
MEELFO
in
achieving
optimal
solutions
minimal
deviations
computational
effort
compared
existing
methods.
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(8), С. 1267 - 1291
Опубликована: Май 22, 2024
Abstract
This
study
proposes
a
novel
human-inspired
metaheuristic
search
algorithm
called
marathon
runner
algorithm.
method
mimics
competitive
behaviors
observed
in
real
runners
through
mathematical
modeling.
Unlike
classical
elitist
algorithms
that
prioritize
position
of
the
best
agent,
introduces
concept
vision
point.
point
considers
quality
entire
population,
not
just
leader.
By
guiding
population
towards
point,
risk
getting
trapped
local
optima
is
reduced.
A
two-part
evaluation
was
conducted
to
thoroughly
assess
capabilities
First,
it
tested
against
set
unconstrained
benchmark
functions
and
algorithm’s
quantitative
attributes,
such
as
complexity,
accuracy,
stability,
diversity,
sensitivity,
convergence
rate
are
analyzed.
Subsequently,
applied
mechanical
structural
optimization
problems
with
both
continuous
discrete
variables.
application
demonstrated
effectiveness
solving
practical
engineering
challenges
constraints.
The
outcomes
compared
those
obtained
by
six
other
well-established
techniques.
results
indicate
yields
promising
solutions
for
mathematical,
mechanical,
problems.
