Sustainability,
Journal Year:
2024,
Volume and Issue:
16(15), P. 6469 - 6469
Published: July 29, 2024
This
study
investigated
the
impact
of
blockchain-driven
supply
chain
analytics
on
dimensions
lean,
agile,
resilient,
green,
and
sustainable
(LARGS)
management,
as
well
innovation
(SCI)
performance
(SSCP).
The
research
involved
262
managers
vice
presidents
chains
from
large-
medium-sized
manufacturing
companies
listed
in
Tehran
Stock
Exchange.
A
hybrid
approach
utilizing
structural
equations
modelling
with
partial
least
squares-structural
equation
modeling
(PLS-SEM)
adaptive
neuro-fuzzy
inference
systems
(ANFIS)
technique
was
employed
for
data
analysis.
findings
demonstrated
a
significantly
positive
effect
SCI,
LARGS
chain,
SSCP.
Additionally,
SCI
exhibited
Moreover,
shown
to
have
influence
Both
played
significant
mediating
roles
Furthermore,
also
acted
mediator
Lastly,
had
role
chain.
In
conclusion,
it
can
be
inferred
that
contributes
enhancement
SSCP
through
facilitation
promotion
principles.
Case Studies in Thermal Engineering,
Journal Year:
2024,
Volume and Issue:
61, P. 104819 - 104819
Published: July 14, 2024
The
heat-absorbing
and
heat-releasing
properties
of
phase-change
materials
(PCMs)
at
specific
temperatures
make
them
ideal
for
improving
the
thermal
management
solar
systems.
Thermal
conductivity
PCMs
is
increased
when
combined
with
nanoparticles,
leading
to
significant
improvements
their
ability
manage
transfer
heat
efficiently.
objective
this
article
anticipate
liquid
fraction
(LF)
a
suitable
level
accuracy
by
utilizing
machine
learning
predictive
models
in
building-integrated
photovoltaic
(PV)
system.
Four
different
system
configurations
were
proposed,
namely
PCM
without
fins,
longitudinal
additional
nanomaterials
Y-shaped
fins.
After
accomplishing
numerical
simulation
data,
order
save
computational
cost
maintain
accurate
predictions,
following
chosen
accomplish
objective:
linear
regression,
lasso
polynomial
an
Auto-Regressive
Integrated
Moving
Average
(ARIMA)
model.
Then,
comparison
all
cases,
using
root
mean
squared
error
(RMSE),
as
well
absolute
(MAE).
ARIMA
model
had
superior
performance
predicting
LF,
achieving
RMSE
0.0149
MAE
0.0093.
This
technique
has
been
used
predict
LF
other
situations.
results
indicated
that
case
incorporating
inclusion
nanoparticles
fins
exhibited
shortest
time
required
reach
value
1.
approach
study
reduces
reliability
on
computationally
expensive
simulations,
which
provides
more
efficient
method
optimizing
PV
also
highlights
potential
enhance
cells,
contributing
sustainable
energy
solutions.
ZAMM ‐ Journal of Applied Mathematics and Mechanics / Zeitschrift für Angewandte Mathematik und Mechanik,
Journal Year:
2024,
Volume and Issue:
unknown
Published: Oct. 9, 2024
Abstract
The
significance
of
the
present
article
is
to
enhance
thermal
management
and
energy
efficiency
complex
engineering
infrastructures
such
as
storage
systems,
modern
electric
vehicles,
insulations,
heavy‐duty
machinery,
production
units.
This
research
aims
understand
intricate
relationship
between
conductivity
performance
ternary
()
hybrid
nanomaterial
entropy
generation
optimize
material
design
efficacy.
A
synergetic
combination
three
distinct
nanomaterials
silicon
dioxide,
ferric
oxide,
titanium
oxide
with
ethylene
glycol
water
in
ratio
3:2
a
base
solvent
comprised
contributing
unique
thermophysical
properties.
To
elucidate
impact
this
composition
on
conductivity,
various
factors
are
analyzed.
advanced
computational
technique
Artificial
intelligent
feed‐forward
neural
network
(AIFFNN)
utilized.
problem
governed
system
PDEs,
which
transformed
into
ODEs
by
dimensionless
similarity.
Adams
method
provided
dataset
filtered
embedded
Marquardt–Levenberg
Algorithm
(LMA).
study
examines
role
constituents,
morphology,
boundary
conditions
generation.
Graphical
analysis
velocity,
temperature,
respect
varying
parameters,
including
surface
absorption
(
λ
),
magnetic
strength
(Tesla
M
radiation
parameter
Rd
Brownian
motion
Br
Eckert
number
Ec
).
findings
have
practical
for
optimizing
industrial
applications.
