Characterization of Post-Production Waste from Winemaking of Selected Vitis vinifera L. Varieties Grown in Temperate Climates and Their Energy Valorization
Energies,
Journal Year:
2025,
Volume and Issue:
18(3), P. 663 - 663
Published: Jan. 31, 2025
The
study
assessed
the
yield
and
quality
as
well
energy
potential
of
biomass
from
stalks
pomace
four
grape
varieties,
Riesling,
Chardonnay,
Zweigelt,
Merlot
Vitis
vinifera
L.,
grown
in
temperate
climate
conditions.
research
is
innovative
because
evaluation
originating
L.
has
not
been
carried
out
so
far
northern
wine-growing
regions.
Field
studies
were
conducted
2023
Experimental
Vineyard
University
Life
Sciences
Lublin,
located
southeastern
Poland.
Biometric
assessment
showed
that
Chardonnay
vines
characterized
by
lowest
mass
clusters
peduncles,
number
berries
cluster,
berry
diameter,
peduncle
size,
at
same
time
highest
among
biotypes.
largest
peduncles.
Riesling
had
most
heaviest
share
peduncles
cluster
(8.99%).
For
pomace,
LHV
values
range
15.98
MJ
kg−1
for
variety
to
16.91
while
these
15.11
MJ·kg−1
15.26
Chardonnay.
differences
pollutant
emissions
are
more
pronounced
between
grapevine
varieties
than
types
(pomace
vs.
peduncles).
greatest
variation
was
observed
carbon
dioxide
(CO2)
category,
smallest
noted
sulfur
(SO2)
emissions.
Total
gas
Zweigelt
(7.72
Nm3
kg−1)
(6.99
kg−1),
stalks,
(6.77
(7.32
kg−1).
category.
These
results
indicate
exhaust
different
plant
parts
which
relevant
optimizing
production
processes
ensuring
sustainable
development.
Language: Английский
Cascade-Forward, Multi-Parameter Artificial Neural Networks for Predicting the Energy Efficiency of Photovoltaic Modules in Temperate Climate
Applied Sciences,
Journal Year:
2024,
Volume and Issue:
14(7), P. 2764 - 2764
Published: March 26, 2024
Solar
energy
is
a
promising
and
efficient
source
of
electricity
in
countries
with
stable
high
sunshine
duration.
However,
less
favorable
conditions,
for
example
continental,
temperate
climates,
the
process
requires
optimization
to
be
cost-effective.
This
cannot
done
without
support
appropriate
mathematical
numerical
methods.
work
presents
procedure
construction
an
artificial
neural
network
(ANN),
along
its
practical
application
under
conditions
mentioned
above.
In
study,
data
gathered
from
photovoltaic
system
457
consecutive
days
were
utilized.
The
includes
measurements
generated
power,
as
well
meteorological
records.
cascade-forward
ANN
was
trained
resilient
backpropagation
sum
squared
error
performance
function.
final
has
two
hidden
layers
nine
six
nodes.
resulted
relative
10.78%
R2
0.92–0.97
depending
on
sample.
case
study
used
present
potential
tool.
approach
proved
real
benefits
consumption.
Language: Английский
Briquette Production from Vineyard Winter Pruning Using Two Different Approaches
Agriculture,
Journal Year:
2024,
Volume and Issue:
14(7), P. 1109 - 1109
Published: July 9, 2024
Worldwide,
different
strategies
are
being
developed
in
order
to
ensure
optimum
conditions
for
the
development
and
growth
of
economic
competitiveness,
as
well
increasing
quality
life
environmental
protection.
All
these
closely
linked
modernization
systems
producing
energy
from
clean
renewable
sources.
In
this
context,
present
paper
presents
results
research
regarding
evaluation
sustainability
briquette
production
using
biomass
resulting
vine
winter
pruning
raw
material.
An
analysis
scientific
literature
indicates
that
nearly
8
Mt
would
result
over
7.4
million
hectares
plantations
world,
could
be
valorized
through
densification
produce
solid
biofuels
with
a
lower
calorific
value
more
than
17
MJ/kg.
This
study
examines
briquettes
vineyard
consideration
two
types
technologies:
baling
natural
drying
tendrils,
collection,
shredding,
artificial
lignocellulose
debris.
The
indices
consumption
efficiency
were
evaluated
determine
their
feasibility
an
alternative
fuel
source.
When
designing
endeavor,
following
aspects
considered:
defining
aim
objectives
research;
algorithm;
collecting,
preparing,
conditioning
biomass;
conducting
chemical
briquettes;
evaluating
briquettes,
taking
into
account
methods
(natural
drying).
meantime,
some
specific
laboratory
equipment
was
designed
built
biomass,
mechanical
durability,
measurement
consumption,
etc.
Analysis
experimental
data
has
led
conclusion
agricultural
waste
can
constitute
important
sustainable
source
form
fulfill
most
requirements
imposed
by
international
standards.
Language: Английский
A mathematical modeling of the turbulence combustion biodiesel in a compression ignition engine
Silniki Spalinowe/Combustion Engines,
Journal Year:
2024,
Volume and Issue:
unknown
Published: Nov. 7, 2024
The
present
work
proposes
a
new
model
for
biodiesel
combustion
in
an
internal
engine.
This
first
includes
the
balance
equations
of
gas
dynamics
with
heat
release.
Secondly,
special
properties
that
take
into
account
turbulence
effects
is
incorporated.
chemical
models
implemented
this
study
are
biofuel
used
at
less
than
100%
and
biodiesel-diesel
blends.
resulting
coupling
describing
premixing.
obtained
interesting
applicable
to
wide
range
problems
without
major
modifications.
It
then
proposed
scientific
community
order
develop
engines
capable
meeting
future
political
expectations
regarding
reduction
pollutant
emissions
from
engines.
Language: Английский
Application of triple-branch artificial neural network system for catalytic pellets combustion
Journal of Environmental Management,
Journal Year:
2024,
Volume and Issue:
366, P. 121678 - 121678
Published: July 10, 2024
On
the
international
level,
it
is
common
to
act
on
reducing
emissions
from
energy
systems.
However,
in
addition
industrial
emissions,
low-stack
also
make
a
significant
contribution.
A
good
step
its
environmental
impact,
move
biofuels,
including
biomass.
This
paper
examines
impact
of
placing
catalytic
system
retort
boiler
minimize
greenhouse
gases,
dust
and
other
pollutants
when
burning
pellets.
The
effect
platinum,
oxides
selected
metals
placed
deflector
as
solid
catalyst
was
studied.
Based
experimental
data,
branched
artificial
neural
network
constructed
trained.
routing
three
parallel
topologies
made
possible
achieve
high
accuracy
while
keeping
input
data
relatively
simple.
showed
an
average
error
3.54%
against
arbitrary
test
data.
basis
well
predictions
returned
by
network,
recommendations
were
shown
for
catalysts
used
their
amounts.
Depending
biomass
which
pellet
produced,
experiment
suggested
use
titanium
or
copper
oxides.
In
case
able
select
better
system,
based
improving
emission
reductions
up
more
than
19%,
depending
type
used.
Language: Английский