Computational
Fluid
Dynamics
coupled
with
Discrete
Element
Method
(CFD-DEM)
has
been
extensively
utilized
for
studying
hydrodynamics
and
heat
transfer
in
fluidization
processes.
This
study
specifically
focuses
on
improving
a
biomass
fluidized
bed
combustor
immersed
tubes.
The
investigation
involves
the
use
of
mixed
biomass,
exploring
effects
types,
loading,
blending
ratios
to
propose
criteria
selecting
suitable
fuel
system.
Design
parameters
related
tubes,
such
as
angle
between
tube
diameters,
distance
were
also
considered.
A
data-driven
model
was
developed
based
CFD-DEM
results
predict
system
parameters.
offers
potential
applications
real-time
practical
engineering
without
need
simulation.
cylindrical
spherical
silica
sand
particles,
incorporating
an
appropriate
drag
force
model.
showed
that
ratio
1:3
wood
chips
coarse
bagasse,
5%
loading
using
average
equivalent
diameter
biomasses
4.44,
identified
conditions
general
case
obtain
most
efficient
hydrodynamic
this
study.
are
greater
than
sand.
Additionally,
proportion
should
be
less
bagasse.
Furthermore,
through
2k
factorial
design
analysis,
it
determined
tubes
had
significant
influence
behaviors.
Moreover,
development
Artificial
Neural
Network
(ANN)
models
successful
simulation
dataset,
enabling
accurate
predictions
mixing
index,
solid
volume
fraction,
temperature
within
enhances
understanding
systems
provides
valuable
insights
optimizing
operation
involving
International Journal of Food Properties,
Год журнала:
2024,
Номер
27(1), С. 1 - 18
Опубликована: Июль 18, 2024
In
this
study,
the
discrete
element
model
of
YCJ
particles
was
established
using
reverse
engineering
reconstruction
technology
and
EDEM
software,
physical
virtual
simulation
experiments
were
conducted
to
calibrate
contact
parameters.
addition,
intrinsic
parameters
during
brittle
ripening
period
measured
directly.
The
heap
angle
obtained
through
stacking
box
extraction
method,
MATLAB
Origin
utilized
obtain
angle.
Factors
their
ranges
significantly
affecting
selected
Plackett-Burman
steepest
ascent
as
evaluation
index.
17.45°.
optimal
combination
static
dynamic
friction
coefficients
between
determined
be
0.395
0.446
variance
analysis
optimization
calculations
response
surface
experiment.
Using
parameter
for
simulated
experiments,
a
17.3°
measured,
with
an
error
0.86%
compared
results
grading
validated,
accuracy
under
same
operating
conditions
3.28%,
particle
motion
state
being
basically
consistent
in
experiments.
research
indicate
that
calibrated
are
reliable,
providing
reference
calibration
fresh-eating
jujubes.
Computational
Fluid
Dynamics
coupled
with
Discrete
Element
Method
(CFD-DEM)
has
been
extensively
utilized
for
studying
hydrodynamics
and
heat
transfer
in
fluidization
processes.
This
study
specifically
focuses
on
improving
a
biomass
fluidized
bed
combustor
immersed
tubes.
The
investigation
involves
the
use
of
mixed
biomass,
exploring
effects
types,
loading,
blending
ratios
to
propose
criteria
selecting
suitable
fuel
system.
Design
parameters
related
tubes,
such
as
angle
between
tube
diameters,
distance
were
also
considered.
A
data-driven
model
was
developed
based
CFD-DEM
results
predict
system
parameters.
offers
potential
applications
real-time
practical
engineering
without
need
simulation.
cylindrical
spherical
silica
sand
particles,
incorporating
an
appropriate
drag
force
model.
showed
that
ratio
1:3
wood
chips
coarse
bagasse,
5%
loading
using
average
equivalent
diameter
biomasses
4.44,
identified
conditions
general
case
obtain
most
efficient
hydrodynamic
this
study.
are
greater
than
sand.
Additionally,
proportion
should
be
less
bagasse.
Furthermore,
through
2k
factorial
design
analysis,
it
determined
tubes
had
significant
influence
behaviors.
Moreover,
development
Artificial
Neural
Network
(ANN)
models
successful
simulation
dataset,
enabling
accurate
predictions
mixing
index,
solid
volume
fraction,
temperature
within
enhances
understanding
systems
provides
valuable
insights
optimizing
operation
involving
