Materials Testing,
Год журнала:
2022,
Номер
64(5), С. 690 - 696
Опубликована: Май 1, 2022
Abstract
Optimization
of
the
heat
recovery
devices
such
as
exchangers
(HEs)
and
cooling
towers
is
a
complex
task.
In
this
article,
widely
used
fin
tube
HE
(FTHE)
optimized
in
terms
total
costs
by
novel
gradient-based
optimization
(GBO)
algorithm.
The
FTHE
s
have
cylindrical
with
transverse
or
longitudinal
enhanced
on
it.
For
study,
various
constraints
design
variables
are
considered,
cost
objective
function.
study
reveals
that
GBO
provides
promising
results
for
present
case
highest
success
rate.
Also,
comparative
suggest
robust
optimizer
best-optimized
values
fitness
function
vis-à-vis
variables.
This
builds
future
implications
wide
range
engineering
fields.
Abstract
This
work
proposed
a
new
metaheuristic
dubbed
as
Chaotic
Lévy
flight
distribution
(CLFD)
algorithm,
to
address
physical
world
engineering
optimization
problems
that
incorporate
the
chaotic
maps
in
elementary
(LFD).
Hybridization
aims
increase
LFD
rate
of
convergence
while
also
providing
problem‐free
approach.
The
methodology
is
investigated
for
five
case
studies
constrained
issues
followed
by
shape
structural
design.
outcomes
from
CFLD
algorithm
are
further
contrasted
with
its
fundamental
version
and
other
distinguished
recently
introduced
algorithms.
computational
analysis
illustrates
dominance
CLFD
over
considered
optimizers.
Moreover,
present
investigation
shows
robust
technique
can
efficiently
find
optimal
mechanical
design
proper
map
selection.
Materials Testing,
Год журнала:
2022,
Номер
64(4), С. 524 - 532
Опубликована: Апрель 1, 2022
Abstract
The
modernization
in
automobile
industries
has
been
booming
recent
times,
which
led
to
the
development
of
lightweight
and
fuel-efficient
design
different
components.
Furthermore,
metaheuristic
algorithms
play
a
significant
role
obtaining
superior
optimized
designs
for
vehicle
Hence,
hunger
game
search
(HGS)
algorithm
is
applied
optimize
suspension
arm
(SA)
by
reduction
mass
vis-à-vis
volume.
performance
HGS
was
accomplished
comparing
achieved
results
with
well-established
metaheuristics
(MHs),
such
as
salp
swarm
optimizer,
equilibrium
Harris
Hawks
optimizer
(HHO),
chaotic
HHO,
slime
mould
marine
predator
artificial
bee
colony
ant
lion
it
found
that
able
pursue
best
solution
subjecting
critical
constraints.
Moreover,
can
realize
least
weight
SA
subjected
maximum
stress
values.
adopted
be
robust
terms
global
optimum
solution.
Materials Testing,
Год журнала:
2023,
Номер
65(8), С. 1230 - 1236
Опубликована: Июнь 29, 2023
Abstract
Thermal
system
optimization
is
always
a
challenging
task
due
to
several
constraints
and
critical
concepts
of
thermo-hydraulic
aspects.
Heat
exchangers
are
one
those
devices
that
widely
adopted
in
thermal
industries
for
various
applications
such
as
cryogenics,
heat
recovery,
transfer
applications.
According
the
flow
configurations
enhancement
fins,
classified
plate-fin
exchangers,
shell
tube
tube-fin
exchangers.
This
article
addresses
economic
challenge
using
cheetah
(CO)
algorithm.
The
design
variables
were
optimized
CO
algorithm,
statistical
results
compared
with
eight
well-established
algorithms.
study
revealed
algorithm
prominent
terms
realizing
minimizing
overall
cost
exchanger
100
%
success
rate.
Furthermore,
suggests
adopting
optimizer
solving
challenges
different
fields.
Materials Testing,
Год журнала:
2023,
Номер
65(12), С. 1767 - 1775
Опубликована: Окт. 13, 2023
Abstract
Nature-inspired
metaheuristic
algorithms
are
gaining
popularity
with
their
easy
applicability
and
ability
to
avoid
local
optimum
points,
they
spreading
wide
application
areas.
Meta-heuristic
optimization
used
achieve
an
design
in
engineering
problems
aiming
obtain
lightweight
designs.
In
this
article,
structural
methods
the
process
of
achieving
a
seat
bracket.
As
result
topology
optimization,
new
concept
bracket
was
created
shape
optimization.
mass
stress
values
obtained
depending
on
variables,
constraint,
objective
functions
were
by
using
artificial
neural
networks.
The
problem
based
minimization
is
solved
applying
dandelion
algorithm
verified
finite
element
analysis.
Materials Testing,
Год журнала:
2023,
Номер
65(9), С. 1396 - 1404
Опубликована: Июль 5, 2023
Abstract
In
this
article,
a
new
prairie
dog
optimization
algorithm
(PDOA)
is
analyzed
to
realize
the
optimum
economic
design
of
three
well-known
heat
exchangers.
These
exchangers
found
numerous
applications
in
industries
and
are
an
imperative
part
entire
thermal
systems.
Optimization
these
includes
knowledge
thermo-hydraulic
designs,
parameters
critical
constraints.
Moreover,
cost
factor
always
challenging
task
optimize.
Accordingly,
total
optimization,
including
initial
maintenance,
has
been
achieved
using
multi
strategy
enhanced
PDOA
combining
with
Gaussian
mutation
chaotic
local
search
(MSPDOA).
Shell
tube,
fin-tube
plate-fin
special
class
that
utilized
many
recovery
applications.
Furthermore,
numerical
evidences
accomplished
confirm
prominence
MSPDOA
terms
statistical
results.
The
obtained
results
were
also
compared
algorithms
literature.
comparison
revealed
best
performance
rest
algorithm.
article
further
suggests
adaptability
for
various
real-world
engineering
cases.
Materials Testing,
Год журнала:
2023,
Номер
65(1), С. 134 - 143
Опубликована: Янв. 1, 2023
Abstract
In
this
present
work,
mechanical
engineering
optimization
problems
are
solved
by
employing
a
novel
optimizer
(HFDO-DOBL)
based
on
physics-based
flow
direction
(FDO)
and
dynamic
oppositional-based
learning.
Five
real-world
problems,
viz.
planetary
gear
train,
hydrostatic
thrust
bearing,
robot
gripper,
rolling
multiple
disc
clutch
brake,
considered.
The
computational
results
obtained
HFDO-DOBL
compared
with
several
newly
proposed
algorithms.
statistical
analysis
demonstrates
the
dominance
in
finding
optimal
solutions
relatively
competitiveness
solving
constraint
design
problems.
