Mechanics of Advanced Materials and Structures,
Год журнала:
2024,
Номер
unknown, С. 1 - 22
Опубликована: Май 17, 2024
This
paper
demonstrates
a
thorough
examination
of
the
bending
behavior
sandwich
concrete
building
structures
that
are
reinforced
with
graphene
nanoplatelets
(GPLs).
The
analysis
is
confirmed
using
machine
learning
technique.
Sandwich
have
notable
benefits
in
terms
strength,
longevity,
and
thermal
insulation,
making
them
well-suited
for
many
applications.
Integrating
GPLs
into
matrix
improves
mechanical
characteristics
performance
these
structures,
especially
behavior.
study
utilizes
technique
to
verify
characterization
temporary
structure
nanoplatelets.
approach
dataset
consisting
simulated
data
create
prediction
model
can
reliably
estimate
response
under
different
loading
situations.
algorithm's
effectiveness
dependability
optimizing
design
demonstrated
through
validation
against
results.
provides
engineers
designers
powerful
tool.
enhances
comprehension
use
approaches
analyzing
designing
sophisticated
structural
materials
systems.
Materials Today Sustainability,
Год журнала:
2024,
Номер
27, С. 100930 - 100930
Опубликована: Июль 26, 2024
The
production
and
use
of
traditional
building
materials
contribute
to
environmental
pollution
natural
resource
depletion.
Besides,
disposal
agricultural,
industrial,
construction
waste
other
solid
wastes
is
a
significant
contemporary
for
both
developing
developed
countries.
Consequently,
this
study
comprehensively
examines
sustainable
(SCMs)
sourced
from
materials.
It
analyzes
190
peer-reviewed
papers,
evaluating
their
properties,
engineering
suitability,
impacts
on
the
environment,
economy,
society.
Findings
reveal
that
most
SCMs
have
good
performance,
yet
improvements
are
needed
in
demonstrating
(33.3%),
economic
(40%),
social
sustainability
(73.3%).
Also,
experimental
stages,
requiring
further
research
human
toxicity,
long-term
savings,
maintenance
costs,
vital
indicators.
This
review
highlights
some
current
challenges
facing
promote
studies,
reduce
non-renewable
energy
consumption
recycling,
facilitate
application
green
buildings.
The
growing
demand
for
fiber-reinforced
polymer
(FRP)
in
industrial
applications
has
prompted
the
exploration
of
natural
fiber-based
composites
as
a
viable
alternative
to
synthetic
fibers.
Using
jute–rattan
composite
offers
potential
environmentally
sustainable
waste
material
decomposition
and
cost
reduction
compared
conventional
fiber
materials.
This
article
focuses
on
impact
different
machining
constraints
surface
roughness
delamination
during
drilling
process
FRP
composite.
Inspired
by
this
unexplored
research
area,
emphasizes
influence
various
Response
methodology
designs
experiment
using
drill
bit
material,
spindle
speed,
feed
rate
input
variables
measure
factors.
technique
order
preference
similarity
ideal
solution
method
is
used
optimize
parameters,
predicting
delamination,
two
machine
learning-based
models
named
random
forest
(RF)
support
vector
(SVM)
are
utilized.
To
evaluate
accuracy
predicted
values,
correlation
coefficient
(R2),
mean
absolute
percentage
error,
squared
error
were
used.
RF
performed
better
comparison
with
SVM,
higher
value
R2
both
testing
training
datasets,
which
0.997,
0.981,
0.985
roughness,
entry
exit
respectively.
Hence,
study
presents
an
innovative
through
learning
techniques.
Mechanics of Advanced Materials and Structures,
Год журнала:
2024,
Номер
unknown, С. 1 - 20
Опубликована: Апрель 27, 2024
This
article
presents
a
new
method
called
the
artificial
neural
networks-genetic
programming
(ANNs-GP)
algorithm,
which
effectively
predicts
bending
behavior
of
functionally
graded
graphene
origami-enabled
auxetic
metamaterial
(FG-GORAM)
structures
under
transient
conditions.
Functionally
materials
(FGMs)
display
spatial
heterogeneity
in
their
composition
and
microstructure,
resulting
distinctive
mechanical
characteristics
that
make
them
well-suited
for
wide
range
engineering
applications.
The
objective
this
study
is
to
create
prediction
model
can
accurately
capture
intricate
FGM
structures.
To
do
this,
researchers
have
used
ANN-GP
technique,
combines
ANNs
with
GP.
ANN
component
acquires
knowledge
from
dataset
including
actual
or
simulated
data,
while
GP
fine-tunes
structure
parameters
network
improve
its
ability
accurate
predictions.
proposed
algorithm
strengths
predict
FG-GORAM
robust
efficient,
allowing
designers
engineers
optimize
performance
reliability
these
various
effectiveness
proved
by
comparing
it
experimental
data.
shows
has
potential
be
useful
tool
designing
analyzing
sophisticated
Case Studies in Thermal Engineering,
Год журнала:
2024,
Номер
55, С. 104117 - 104117
Опубликована: Фев. 12, 2024
According
to
the
Global
Climate
Risk
Index,
Pakistan
is
fifth
most
vulnerable
nation
in
world
climate
change.
The
growing
phenomena
of
change
and
global
warming
have
increased
on
a
worldwide
level.
To
combat
effects
change,
transition
sustainable
transportation
system
essential.
Developed
countries
evaluated
costs
benefits
such
transition.
However,
developing
like
rarely
investigated
this
matter
thoroughly.
So,
context,
paper
case
study
analyzing
transport
sector
Punjab-Pakistan
achieve
some
targets
for
transportation.
analysis
carried
out
by
using
energy
model
Low
Emission
Analysis
Platform
(LEAP)
from
2019
2050.
Three
scenarios
are
made,
i.e.,
Business
as
Usual
Scenario
(BAUS)
following
current
policies,
Efficient
Combustion
(ECS),
Electrical
Vehicle
(EVS)
figure
environmental
social
costs.
It
concluded
that
2050,
ECS
EVS
will
reduce
carbon
dioxide
emissions
21.6
18.5
million
metric
tons
equivalent,
compared
Business-as-Usual
Scenario.
These
savings
terms
cost
be
$
157.1
134.6
Electric
This
research
may
help
find
suitable
policy
decisions
at
provincial
level
enhance
sustainability
increasing
share
electric
vehicles
Punjab,
results
replicated
whole
country
South
Asia.
