The Impact of Various Factors on Long-Term Storage of Biodiesel and Its Prevention: A Review
Energies,
Journal Year:
2024,
Volume and Issue:
17(14), P. 3449 - 3449
Published: July 13, 2024
With
the
continuous
growth
of
global
energy
demand
and
increasingly
prominent
environmental
issues,
research
utilization
renewable
as
a
substitute
for
traditional
fossil
fuels
have
gained
significant
importance.
Biofuels,
recognized
key
source,
are
widely
considered
viable
alternative
to
fuels.
The
primary
component
biodiesel
is
fatty
acid
methyl
esters
(FAMEs),
which
prone
oxidative
degradation
due
their
unsaturated
nature
during
storage
transportation.
Various
studies
identified
several
factors
influencing
stability
biodiesel,
including
oxygen,
temperature,
light,
water
content,
microbial
growth,
corrosion
metal
tanks.
This
article
provides
comprehensive
summary
effects
different
on
explores
interrelationships
between
these
factors.
To
enhance
strategies
been
proposed,
such
optimizing
production
processes,
adding
antioxidants,
controlling
environments,
conducting
regular
inspections.
review
aims
provide
theoretical
basis
long-term
promote
its
widespread
application
in
practical
scenarios.
Language: Английский
Implications of Waste Cooking Oil Biodiesel on Carbon Steel Alloy in Automobiles: Corrosion Degradation
International Journal of Thermofluids,
Journal Year:
2025,
Volume and Issue:
unknown, P. 101143 - 101143
Published: Feb. 1, 2025
Language: Английский
Performance and spray characteristics of fossil JET A-1 and bioJET fuel: A comprehensive review
Renewable and Sustainable Energy Reviews,
Journal Year:
2024,
Volume and Issue:
207, P. 114970 - 114970
Published: Oct. 14, 2024
Language: Английский
Predictive Modeling and Optimization of Noise Emissions in a Palm Oil Methyl Ester-Fueled Diesel Engine Using Response Surface Methodology and Artificial Neural Network Integrated with Genetic Algorithm
International Journal of Thermofluids,
Journal Year:
2025,
Volume and Issue:
unknown, P. 101103 - 101103
Published: Jan. 1, 2025
Language: Английский
The effect of TiO2 nanoadditive on emissions, exergetic performance, and enviro/social/economic indicators in a small UAV jet engine fuelled with kerosene
Fuel,
Journal Year:
2025,
Volume and Issue:
390, P. 134725 - 134725
Published: Feb. 19, 2025
Language: Английский
Application of PCA-GBRT/RF model for predicting heat flux on boiler water-cooled wall
Jiahui Yang,
No information about this author
Chenxi Jiang,
No information about this author
Ruiyu Li
No information about this author
et al.
Applied Thermal Engineering,
Journal Year:
2025,
Volume and Issue:
unknown, P. 126580 - 126580
Published: April 1, 2025
Language: Английский
Machine learning and experimental emission assessment in high temperature air premixed charged compression ignition engines using the Pugh matrix
Mohammed Al Awadh,
No information about this author
Kah Ong Michael Goh
No information about this author
Scientific Reports,
Journal Year:
2025,
Volume and Issue:
15(1)
Published: May 6, 2025
This
research
explores
the
performance,
exhaust
emissions,
and
combustion
properties
of
a
Premixed
Charged
Compression
Ignition
(PCCI)
engine
using
combinations
Andropogon
narudus
(AN)
Sapota
Oil
Methyl
Ester
(SOME)
blended
as
substitute
fuels.
A
split-fuel
injection
system
was
used,
supplying
70%
fuel
with
direct
30%
through
intake
air
manifold.
The
test
fuels
considered
were
D100
(commercial
diesel),
AN20
+
D80,
SOME20
their
corresponding
mixture
nano-additives
CeO₂
Al₂O₃
(10
ppm).Performance
analysis
showed
that
highest
brake
thermal
efficiency
(BTE)
attained
by
D80
Al₂O₃,
which
rose
2.5%
respect
to
diesel,
2.3%
rise
in
BTE.
Brake-specific
consumption
(BSFC)
reduced
0.10
g/kWh
for
diesel
due
its
lower
viscosity.
Emission
hydrocarbon
(HC)
emission
decrease
up
7
ppm
all
blends
tested,
although
CO₂
NOx
emissions
higher
AN
SOME
nano-additives.
Combustion
studies
revealed
had
maximum
peak
pressure
net
heat
release
rate,
supports
effect
on
behavior.
For
improving
predictive
accuracy,
machine
learning-augmented
modeling
utilized
Multiple
Linear
Regression
(MLR),
Random
Forest
(RF),
Support
Vector
Machine
(SVMR).
RF
model
performed
better
efficiency,
giving
R²
=
0.97
NOx,
0.99
Smoke,
0.95
CO,
capturing
nonlinear
relationships
well.
MLR
good
fits
BTE
(R²
0.99)
BSFC
0.94),
whereas
SVMR
poorer
predictions
(e.g.,
Smoke:
0.19,
CO₂:
0.30).A
sustainability
ranking
situated
at
most
viable
biofuel
position,
particularly
addition
Al₂O₃.
Predictive
analytics
derived
from
ML
study
focus
role
achieving
maximal
alternative
mixtures,
less
reliance
huge
experimental
trials,
more
cleaner
efficient
burning
systems.
Language: Английский
Comparative Analysis of Aeroshell 500 Oil Effects on Jet A and Diesel-Powered Aviation Microturbines
Grigore Cican,
No information about this author
Radu Mirea,
No information about this author
Maria Căldărar
No information about this author
et al.
Fuels,
Journal Year:
2024,
Volume and Issue:
5(3), P. 347 - 363
Published: Aug. 1, 2024
This
study
aims
to
analyze
the
influence
of
adding
Aeroshell
500
oil
on
physicochemical
properties.
It
was
found
that
oil’s
kinematic
viscosity
is
much
higher
than
diesel
and
Jet
A,
with
a
density
flash
point
as
well.
Elemental
analysis
revealed
carbon
content
lower
hydrogen
in
compared
A
diesel,
calorific
power.
Adding
5%
increases
mixture
viscosity,
point,
density;
decreases
power;
for
both
A.
In
second
part,
mathematical
models
determined
combustion
temperatures
plus
oil,
based
an
air
excess
from
one
five.
oxygen
quantities
these
mixtures
stoichiometric
reaction
CO2
H2O.
Regarding
quantity,
it
3.143
kg
3.159
each
kilogram
burned
reaction.
Similarly,
proportion
quantity
3.175
3.190
Through
experimentation
Cat
P80
microturbine
engine
across
four
operating
regimes,
observed
chamber
temperature
fuel
flow
rate
are
when
using
addition
same
additive.
However,
thrust
slightly
+
oil.
Moreover,
specific
consumption
regimes
two
while
differences
negligible
three
four.
At
maximum
conditions,
measured
values,
comparing
calculated
value,
7%
error,
extrapolating
results
scenario
not
used.
Also,
during
testing
campaign,
concentrations
CO
SO2
exhaust
gas
jet
were
measured,
Language: Английский