Case Studies in Thermal Engineering,
Год журнала:
2024,
Номер
60, С. 104672 - 104672
Опубликована: Июнь 7, 2024
In
recent
years,
the
rise
of
machine
learning
(ML)
has
prompted
researchers
to
expand
datasets
required
for
optimizing
and
designing
thermal
systems.
Also,
development
widespread
use
electric
vehicles
(EVs)
have
surged
significantly.
However,
one
major
challenges
associated
with
EVs
is
efficient
cooling
Lithium-ion
batteries
(LIBs).
Therefore,
exploration
innovative
methods
can
contribute
greatly
rapidly
growing
vehicle
industry.
This
study
focused
on
investigating
impact
embedding
a
nickel
porous
medium
around
single
38,120
LiFeO4
cell.
To
conduct
study,
LIB,
along
medium,
was
placed
inside
duct
that
received
flow
water
Nano-encapsulated
phase
change
materials
(NEPCMs).
The
results
obtained
from
indicate
media
LIB
led
significant
decrease
in
maximum
temperature
more
than
40
C,
remarkable
increase
pressure
drop
100
times.
Additionally,
it
observed
porosity
1
0.97
had
pronounced
effect
LIB's
surface,
compared
0.95.
Case Studies in Thermal Engineering,
Год журнала:
2024,
Номер
60, С. 104647 - 104647
Опубликована: Июнь 4, 2024
A
novel
thermal
integration
approach
is
introduced
for
a
biomass-driven
gas
turbine
power
plant
that
generates
electricity,
coolant,
and
liquefied
hydrogen.
The
designed
scheme
encompassed
an
organic
flash
cycle,
bi-evaporator
ejector
refrigeration
unit,
high-temperature
water
electrolyzer
hydrogen
production,
multi-effect
desalination
cycle
supplying
electrolysis
process,
Claude
liquefaction.
system's
importance
comes
back
to
using
biomass
feedstock
as
the
input
fuel
utilizing
liquefaction
method.
In
addition
possibility
of
deploying
system
in
remote
areas,
it
provides
opportunity
storage
smaller
volume
more
accessible
transportation.
On
other
hand,
comparative
method
selecting
environmentally
friendly
fluid
heat
recovery
subsystem
another
crucial
aspect
present
study
from
environmental
aspect.
It
found
R161
appropriate
choice
among
seven
studied
working
fluids.
Subsequently,
comprehensive
evaluation
entire
thermodynamic
aspects
performed
intelligent
process.
By
considering
energy
exergy
efficiencies
along
with
CO2
emissions
objective
functions,
thorough
sensitivity
analysis
triple-objective
optimization
are
carried
out.
Hence,
artificial
neural
networks
objectives
developed
integrated
into
NSGA-II
Employing
LINMAP
decision-making,
values
attained,
exhibiting
39.6%
efficiency,
36.1%
631.7
kg/MWh
emissions.
Considering
optimum
solution,
proposed
capable
producing
cooling,
capacities
4526
kW,
1875
21.22
m3/day,
respectively.
Additionally,
scenario
yields
exergoenvironmental
index
0.579
exergetic
stability
0.61.
generation
rate
m3/day.
Case Studies in Thermal Engineering,
Год журнала:
2024,
Номер
61, С. 105046 - 105046
Опубликована: Сен. 1, 2024
This
study
presents
a
comprehensive
technical,
environmental,
and
economic
analysis
of
thermal
power
plant
utilizing
solid
oxide
fuel
cells
(SOFC)
to
meet
urban
demands
for
electrical
power,
fresh
water,
hydrogen.
The
integrated
system
includes
SOFC
with
anode
cathode
recycling,
multi-effect
desalination,
generation
cycle
heat
recovery
unit
using
thermoelectric
generator,
hydrogen
compression
unit.
A
detailed
parametric
was
conducted
identify
optimal
conditions
key
outputs
such
as
total
cost
rate
exergy
efficiency,
employing
genetic
algorithms
artificial
neural
networks.
According
the
evaluation,
stack
accounts
65.11
%
costs
at
139.8
$/h,
inverter
contributing
11.9
%.
environmental
shows
that
proposed
emits
least
CO2
per
energy
compared
SOFC/GT
SOFC/GT/RC
systems.
indicates
increasing
pressure
ratio
enhances
output
production
gas
turbine.
However,
this
also
leads
higher
compressor
consumption,
thereby
reducing
net
power.
Furthermore,
current
density
results
in
greater
electricity,
hydrogen,
freshwater,
while
raising
exhaust
temperature,
which
aids
desalination
process.
optimization
show
an
efficiency
61.38
132.9
networks
time
from
124
h
14
min.
