Obtaining high H2-rich syngas yield and carbon conversion efficiency from biomass gasification: From characterization to process optimization using machine learning with experimental validation
Fuel,
Год журнала:
2024,
Номер
378, С. 132931 - 132931
Опубликована: Авг. 31, 2024
Язык: Английский
Enhanced co-pyrolysis of textile and leather waste with Ca/Fe-enriched sludge ash: Catalytic effect on thermal behavior, volatile composition, and biochar formation
Yanjun Hu,
Zhipeng Xia,
Xu Wang
и другие.
Fuel,
Год журнала:
2024,
Номер
373, С. 132272 - 132272
Опубликована: Июль 4, 2024
Язык: Английский
Kinetics, reaction mechanism and product distribution of lignocellulosic biomass pyrolysis using triple-parallel reaction model, combined kinetics, Py-GC/MS, and artificial neural networks
Industrial Crops and Products,
Год журнала:
2024,
Номер
224, С. 120308 - 120308
Опубликована: Дек. 16, 2024
Язык: Английский
Prediction of product yields and heating value of bio-oil from biomass fast pyrolysis: Explainable predictive modeling and evaluation
Energy,
Год журнала:
2025,
Номер
unknown, С. 136087 - 136087
Опубликована: Апрель 1, 2025
Язык: Английский
Dynamical Sphere Regrouping Particle Swarm Optimization Programming: An Automatic Programming Algorithm Avoiding Premature Convergence
Mathematics,
Год журнала:
2024,
Номер
12(19), С. 3021 - 3021
Опубликована: Сен. 27, 2024
Symbolic
regression
plays
a
crucial
role
in
machine
learning
and
data
science
by
allowing
the
extraction
of
meaningful
mathematical
models
directly
from
without
imposing
specific
structure.
This
level
adaptability
is
especially
beneficial
scientific
engineering
fields,
where
comprehending
articulating
underlying
relationships
just
as
important
making
accurate
predictions.
Genetic
Programming
(GP)
has
been
extensively
utilized
for
symbolic
demonstrated
remarkable
success
diverse
domains.
However,
GP’s
heavy
reliance
on
evolutionary
mechanisms
makes
it
computationally
intensive
challenging
to
handle.
On
other
hand,
Particle
Swarm
Optimization
(PSO)
performance
numerical
optimization
with
parallelism,
simplicity,
rapid
convergence.
These
attributes
position
PSO
compelling
option
Automatic
(AP),
which
focuses
automatic
generation
programs
or
models.
(PSP)
emerged
an
alternative
(GP),
emphasis
harnessing
efficiency
regression.
PSP
remains
unsolved
due
high-dimensional
search
spaces
local
optimal
regions
AP,
traditional
can
encounter
issues
such
premature
convergence
stagnation.
To
tackle
these
challenges,
we
introduce
Dynamical
Sphere
Regrouping
(DSRegPSOP),
innovative
implementation
that
integrates
DSRegPSO’s
dynamical
sphere
regrouping
momentum
conservation
mechanisms.
DSRegPSOP
specifically
developed
deal
large-scale,
featuring
numerous
optima,
thus
proving
effective
behavior
tasks.
We
assess
generating
10
expressions
mapping
points
functions
varying
complexity,
including
noise
cost
evaluation.
Moreover,
also
evaluate
its
using
real-world
datasets.
Our
results
show
effectively
addresses
shortcomings
producing
entirely
generated
AP
achieve
accuracy
similar
algorithms
optimized
tasks
involving
structures.
Additionally,
combines
benefits
PSO.
Язык: Английский
Prediction of Chemical Composition of Gas Combustion Products from Thermal Waste Conversion
Processes,
Год журнала:
2024,
Номер
12(12), С. 2728 - 2728
Опубликована: Дек. 2, 2024
The
current
global
energy
crisis
is
driving
the
need
to
search
for
alternative
raw
materials
and
fuels
that
will
be
able
ensure
continuity
of
strategic
industries,
such
as
steel
industry.
A
chance
reduce
consumption
traditional
(e.g.,
natural
gas)
utilise
potential
gases
from
thermal
conversion
waste,
and,
in
particular,
pyrolysis
gas.
Unfortunately,
despite
its
high
calorific
value,
this
gas
not
always
suitable
direct,
energy-related
use.
limitation
type
waste
subjected
pyrolysis,
particularly
plastics,
rubber
textiles.
Due
above,
article
proposes
co-combustion
a
ratio
1:10
with
pusher
reheating
furnace
employed
heat
charge
before
forming.
chemical
composition
flue
generated
during
combustion
alone
various
wastes
was
modelled,
namely,
two
types
refuse-derived
fuel
(RDF)
mixture
pine
chips
polypropylene
alder
polypropylene.
calculations
were
performed
using
Ansys
Chemkin-Pro
software
(ver.
2021
R1).
computer
simulations
showed
addition
most
analysed
variants
did
significantly
affect
gases.
For
biomass
(PP),
higher
concentrations
CO
H2
unburned
hydrocarbons
observed
than
other
mixtures.
reason
differences
explained
by
conducting
formation
path
analysis
sensitivity
selected
products.
Язык: Английский
Measurement of Dielectric Characteristics of Bulk Cellulose-containing Materials at a Frequency of 2.45GHz
2022 Photonics & Electromagnetics Research Symposium (PIERS),
Год журнала:
2024,
Номер
unknown, С. 1 - 4
Опубликована: Апрель 21, 2024
Язык: Английский
Characterization of the Structure of Rice and Wheat Straw Pretreated with Trichoderma sp. AH
Chuan-Yong Yan,
Liang Xin,
Quan-Xi Zheng
и другие.
ACS Omega,
Год журнала:
2024,
Номер
9(47), С. 46743 - 46750
Опубликована: Ноя. 15, 2024
Trichoderma
sp.
AH
pretreatment
(PT)
enhances
the
conversion
and
selectivity
of
RS
WS
in
supercritical
methanolysis.
In
this
work,
we
investigated
how
AH-containing
PT
affected
structure
wheat
straw
(WS)
rice
(RS).
The
enhanced
methanolysis
was
mostly
ascribed
to
structural
changes
during
based
on
thorough
investigations
by
thermogravimetry/differential
thermogravimetry
(TG/DTG),
X-ray
diffraction
(XRD),
photoelectron
spectroscopy
(XPS).
TG/DTG
study
revealed
that
could
only
partially
degrade
without
significantly
changing
makeup
their
group.
is
effective
at
breaking
because
XRD
research
showed
it
somewhat
alter
crystal
WS,
decreasing
crystallinity.
primary
way
affects
decrystallization
cellulose
hemicelluloses
into
an
amorphous
material.
comparative
concentrations
certain
molecules
are
altered
PT,
according
XPS
examination
these
compounds.
efficient
biomass
liquefaction
preparation
minimizes
carbohydrate
loss
disrupting
biomass.
Язык: Английский