Design Analysis of Bamboo Drying Oven Using CFD Software
Kurniawan
a
, Heri Setiawan, Dede Sujana and Rivaldi Muhammad Alyansyah
Manufacturing Polytechnic Bandung, Kanayakan, Bandung, Indonesia
dede_edo@polman-bandung.ac.id, rivaldiam24@gmail.com
Keywords: Heat Transfer, CFD, Oven, Drying Bamboo.
Abstract: There is a design validation stage in the process of designing an oven. This step is crucial to demonstrate the
oven's ability to perform as planned, which was to be able to dry 700 kg of bamboo material with an initial
humidity of 14.08% and dry to a humidity of 10% in 8 hours. A trial tool is typically used for validation.
However, it takes a lot of effort and money to create a prototype tool for trailing. As a result, with current
technical advancements, software simulation can take the role of the trail tool method. Ansys software was
used in this investigation to assess the oven. The program receives the oven specs as well as the outcomes of
the calculations that have been done. A simulation of the heat distribution, oven temperature, and heat
absorbed by the material will be calculated by Ansys and displayed.
1 INTRODUCTION
There is a design validation stage in the design
process. This stage is required to demonstrate that the
designed solution serves the intended purpose. This is
crucial to prevent a mismatch between the designer's
expectations and the final product.
In the construction of an oven whose primary
purpose is to dry materials. It is necessary to analyze
the heat produced in the oven space. It is intended that
by using the application to observe the simulation
approach, the oven design may be verified to dry the
material to a specific humidity level in the anticipated
amount of time.
The oven in the situation under investigation
must be capable of drying 700 kg of bamboo material
in 8 hours. Bamboo that was previously 14.08
percent humid was dried till it reached 10%
humidity.
It is envisaged that performing an examination of
the oven space using the ansys application will allow
the simulation results to validate the accomplishment
of the oven's intended function.
a
https://orcid.org/0000-0003-4323-3325
2 RESEARCH STAGES
The research flow chart below is referenced in the
analysis study addressing the finding of hot air in this
oven.
Figure 1: Research stages.
Kurniawan, ., Setiawan, H., Sujana, D. and Alyansyah, R.
Design Analysis of Bamboo Drying Oven Using CFD Software.
DOI: 10.5220/0011766300003575
In Proceedings of the 5th International Conference on Applied Science and Technology on Engineering Science (iCAST-ES 2022), pages 317-323
ISBN: 978-989-758-619-4; ISSN: 2975-8246
Copyright © 2023 by SCITEPRESS – Science and Technology Publications, Lda. Under CC license (CC BY-NC-ND 4.0)
317
3 STUDY
3.1 Carculation Parameter
Identification
Figure 2: Dimension bamboo.
The humidity level of the bamboo that needs to be
dried is 14.08%.(Tri Wulandari, 2020) Bamboo must
be dried untuk humidity level of bamboo 10%. The
properties of bamboo have a specific heat of
1.700J/kg⁰C. Bamboo to be dried has a size of
25x10x375mm.
Figure 3: Design oven.
The oven must have be able to dry 700kg/day
material bamboo. Knowing the heater and blower
specs as calculation inputs is essential for heat
transfer analysis.The oven have 4 blower, 2 blower
each side and 3 finned coil heater each side in total 6
heater.
Figure 4: Finned coil heater.
The oven uses a finned coil heater with a 1500
watt power rating and a 240 volt operating voltage
each heater.
Figure 5: Catalog of blower by Hanil.
The blower being used is a Hanil KE-400
industrial blower. The specification of blower have
dimension blade 400mm with airflow 1540 𝑚
/
ℎ𝑜𝑢𝑟.
3.2 Calculation
3.2.1 Heat Requirement
Heat is required to dry the skewer material, which
initially had a humidity of 14,08% to 10%. Up until it
reaches a humidity of 10%, bamboo material's heat
demand is calculated.
Table 1: Calculation of heat requirement.
N
o Description Value
1
Temperature
normal
27℃
2
Temperature
when dr
y
in
g
70℃
3
∆𝑇 70℃ 27℃ 43℃
4
Characteristic
termal of
bamboo(𝐶
1.700J/kg⁰C
5
𝑄
𝑀∙𝐶
∙∆𝑇
51201798,5 𝐽
6
Mass of
water to be
evaporated
(m)
700 𝑘𝑔
∙
14,08% 10%
28,56 𝑘𝑔
7
Specific laten
water (L)
22,6x10
J/kg
8 Q2 𝑚 ∙ 𝐿 64545600𝐽
9
Heat
requirement
(Q
Q1 + Q2
= 1,157 𝑥 10
𝐽
So to dry bamboo material to a humidity of 10
requires 1,157 𝑥 10
𝐽 of calor (Tobing et al., 2019).
3.2.2 Heat Transfer
The item being dried receives heat either directly
from the heat source or indirectly in the instance of
drying bamboo in an oven. The material will dry more
quickly or slower depending on how quickly heat is
transferred during this drying process(Putra, 2010).
Temperature, wind speed, material, and the surface
area that needs to be dried all affect how quickly heat
transfers. The anticipated drying time can be
calculated using the rate of heat transfer that takes
place. The bamboo material in this instance weighs
700 kg, and the drying procedure aims to reduce the
humidity from 14.08% to 10% in under 8 hours.
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318
Table 2: Calculation of heat transfer.
N
o Desc
r
iption Value
1
Area of
projection
blower blade
(
𝐴
r
∙ 𝜋 125600mm
2
Air volume
(𝑄
1540 𝑚
/ℎ𝑜𝑢𝑟
3
Velocity of
air (𝑉
𝑄
𝐴
3,404 𝑚/𝑠
4
Lenght of
p
late (L)
3,210𝑚
5
Kinematic
Viscosit
y
(v)
27,8 𝑥 10
𝑚
/𝑑𝑒𝑡𝑖𝑘
6
Reylond
number (Re)
∙
= 3,926
7
Conductivity
termal (k)
0,03489 W/m.K
8
Prandtl
number(Pr)
0,684
9
coefficient of
heat transfer
(h)
0,664 ∙
𝑘
𝐿
∙𝑅𝑒
.
∙𝑃𝑟
.
3,985 𝑊/𝑚
⁰𝐶
10
Surface area
perpendicular
to the
direction of
the heat flux
(A)
375𝑚𝑚 ∙ 10𝑚𝑚
∙ 9595𝑠𝑡𝑖𝑐𝑘
4,556𝑚
11
Temperature
coil (𝑡
250℃
12
Temperature
room(𝑡
27℃
13
Heat
transfer(𝑞
ℎ
𝐴
𝑡
𝑡
4,049 𝑘𝐽/𝑠𝑒𝑐
14
The time
required for
the drying
process
(𝑡
𝑄
𝑞
7,941 ℎ𝑜𝑢𝑟
Accordingly, it takes 7,941 hours for bamboo
material to dry to 10% humidity with a heat
transmission coefficient of 4,049 𝑘𝐽/𝑠𝑒𝑐 (Hadi,
2012).
3.3 CFD (Computational Fluid Dynamic)
The term "computational fluid dynamics" is derived
from the phrases "computational" and "dynamics,"
where computational refers to anything having to do
with mathematics, numerical computing, or
computational methods. By definition, CFD refers to
the study of predicting fluid flow, heat transfer,
chemical reactions, and other phenomena by the
solution of mathematical models. PDEs, or partial
differential equations, which stand in for the
principles of conservation of mass, momentum, and
energy, are the fundamental building blocks upon
which mathematical model fluid equations are
constructed and studied. When running CFD
simulations, there are three steps that must be
completed: pre-processing, solution, and post
processing. (Damayanti, 2012)
a. Pre-Processing
The first step in creating and analysing a CFD model
is pre-processing. The process entails building a
model using a CAD (Computer Aided Design)
program, meshing the model as necessary to complete
it, and setting up the model in accordance with the
boundary conditions and fluid parameters that will be
simulated.(Damayanti, 2012)
b. Resolving
The pre-processing phases from earlier are used by
the CFD solution search algorithm to determine the
conditions that arise.(Damayanti, 2012)
c. Post Processing
The final stage of CFD analysis is postprocessing.
Organize and evaluate the CFD simulation data that
has been obtained at this point by contrasting it with
manual calculations.(Damayanti, 2012)
With a model that closely resembles the actual
state of the oven, this simulation is used to examine
the convection heat distribution circumstances that
arise between the coil heater and the wind from the
blower. Moreover, to guarantee that the dried material
receives the necessary heat and energy. The following
steps are carried out as the simulation progresses
through various stages.
3.3.1 Model
Figure 6: Model for simulation.
The simulation model receives tray construction as
input. The tray model is then deleted and the
"boolean" tool is used to turn the tray into an empty
space in the rectangle model. When using the
Design Analysis of Bamboo Drying Oven Using CFD Software
319
"boolean" feature, the blower model is still present
and is not deleted. Figure above depicts the model's
shape in its final form.
3.3.2 Mesh
Choose the type of CFD and Fluent in the "Defaults"
setting based on the simulation that will be run. Given
that the oven has a pretty large size, the "Max Face
Size" setting in the "Sizing" parameter is quite large
at 0.1m. The "Min Size" setting, however, is now set
at 0.0025m or 25mm. This size is narrower than the
model's narrowest size, which is 50mm apart from the
trays.
Figure 7: Setting mesh.
To achieve better
simulation outcomes, the "Body
Sizing" function is set to a smaller mesh size in the
blower section. The mesh size is set to 0.005 meters,
or 50 millimeters.
Figure 8: Result mesh.
3.3.3 Setup
Figure 9: Setup energy.
Viscous is in SST k-omega mode, radiation is in DO
mode, and the energy parameter is set at setup time.
settings due to the simulation's inclusion of heat-
related elements.
Figure 10: Setup heater.
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Then use the preceding formula to determine the
heater's heat, which is 523K with a 0.88 emissivity.
The other six heaters all have this setting.
Figure 11: Setup tray.
The tray's material character in the simulation is set
to wood or wood. This is due to the bamboo material
not being used in the application; instead, it must be
brought very close to the wood in order to be used.
According to the outcomes of manual calculations,
where the thermal coefficient (h) occurs at 3.985
W/m20C, the value of "heat transfer coefficient" is
changed. The material is initially heated to the same
270C or 300K temperature as a typical room, and the
oven temperature of 700C or 343K is entered in the
value column for "external radiation temperature".
Figure 12: Setup blower.
The blower is programmed to increase the
pressure. The coefficients for the pressure jump value
are 496 and -50.
Figure 13: Setup air condition.
The oven room temperature before being operated
is set by changing the “wall-solid” parameter to have
a temperature of 300K or 27⁰C.
3.3.4 Result
a. Heat Absorption
To be able to determine the amount of heat absorbed,
it is necessary to observe the heat flux that occurs.
Figure 14: Heatflux on tray.
The average heat flux value is determined from 9
different sites using the simulation data. The table
below shows the outcomes of the 9 point.
Table 3: Average heatflux.
Titik
Heat Flux
W/m^2
1 16.2552
2 18.6113
3 13.7863
4 16.7524
5 18.4016
6 13.1118
7 14.258
8 19.8712
9 12.3409
Rata-Rata 15.93207778
The table shows that the average heat flux value
in the tray is 15,932
.. The heat energy that the
material has received can be calculated using the heat
flow value. The heat requirements that have
previously been established by manual calculations
can be directly correlated to these results. Here is how
to calculate it:
Design Analysis of Bamboo Drying Oven Using CFD Software
321
Table 4: Calculation of heat absorption.
No Descri
p
tion Value
1
Area of surface
material
b
amboo(
𝐴
0,028𝑚
2
Total area of
surface
material
b
amboo(
𝐴
𝐴
. 9595𝑠𝑡𝑖𝑐𝑘
268,18𝑚
3
Heat flux (ø
)
15,932
𝑤𝑎𝑡𝑡
𝑚
4
The time
required for
the drying
process
(𝑡
7,941 ℎ𝑜𝑢𝑟
5
Heat
absorption
Q
ø
.𝐿
.𝑡
1,221 ∙ 10
𝐽
In the simulation, the energy absorbed is s
1,221 ∙ 10
𝐽 if the drying process lasts for 7.941
hours. If the drying time necessary until heat energy
absorption happens as needed (Q tot) with the heat
flux value is calculated as follows.
Table 5: Calculation of time drying procces.
No Description Value
1
Heat
requirement
(Q
0,028𝑚
2
Heat flux (ø
15,932
𝑤𝑎𝑡𝑡
𝑚
3
Total area of
surface material
bamboo(
𝐴
268,18𝑚
5
The time
happend for the
drying process
in simulation
result t
Q
ø
.𝐿
7,525ℎ𝑜𝑢𝑟
So based on the conditions that occur in the
simulation, the results of the calculation of the time
needed are 7.525 hours.
b. Room Temperature
Figure 15: Temperature of room actual model.
The temperature of the tray was initially set at
300K to 330K or 57⁰C. Previously, the target
temperature was 70⁰C, but in the simulation results,
the tray temperature was 57⁰C .. This is not a concern
because what matters is that the required amount of
heat is absorbed.
In calculation with 300 iterations, it is impossible
to accurately examine the spread of heat while going
to do so. As a result, changes to the Ansys settings
were made to better understand how heat spreads
because of the device's limited characteristics.
The tray settings were changed from "mixed" to
"heat flux" with a value of 180
. Author may
observe the heat spread when absorption is good even
though only 300 iterations have been performed by
using a large heat flux value to speed up the heat
absorption process.
Figure 16: Heat distribution side view.
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322
Figure 17: Heat distribution up view.
The results show the evenness of heat that occurs
in the tray. It can be seen that the bottom of the trolley
has a temperature of 370K to 396K or 97⁰C to 119⁰C.
This temperature is lower than that which occurs in
each tray, which is an average temperature of 408K
or 135⁰C.
4 CONCLUSIONS
The heat flow value from the simulation results is
converted into energy received by the material, it can
be estimated. The findings of the thermal energy
acquired by the calculation material when done
manually and those from simulations differ. As a
consequence, when compared to the manual
calculation results, as follows.
The temperature in the oven space is below the
desired temperature, according to the temperature
observation. Nevertheless, it doesn't matter because
the substance has already absorbed enough heat
energy to meet its needs.
Table 6: Compare data between manual calculation and
simulation.
Manual
calculation
Simulation
calculation
Result
difference
Heat
requirement
(Q
)
Heat absorb
(Q
)
1,157
∙10
𝐽
1,221
∙10
𝐽
5.53%
Dr
y
in
g
time Dr
y
in
g
time
7,941
j
a
m
7,525
j
a
m
5,24%
Room
temperature
Room
temperature
70⁰C 57⁰C
18,57%
ACKNOWLEDGEMENTS
If any, should be placed before the references section
without numbering.
REFERENCES
Damayanti, Y. P. (2012). SIMULASI TEMPERATURE
CONTROL SYSTEM PADA INTERNAL FLOW
FLUIDA VISCOUS DENGAN MENGGUNAKAN
PERANGKAT LUNAK CFD (COMPUTATIONAL
FLUID DYNAMICS). Skripsi Universitas Sebelas
Maret.
Hadi, P. S. (2012). PENGERING PADI ENERGI SURYA
DENGAN VARIASI TINGGI CEROBONG. TUGAS
AKHIR.
Putra, A. K. (2010). RANCANG BANGUN OVEN
UNTUK MENGERINGKAN. Tugas Akhir.
Tobing, I. F., Agustina, R., Studi, P., Pertanian, T.,
Pertanian, F., & Syiah, U. (2019). Modifikasi Pengering
Tipe Tray Dryer Dengan Penambahan Insulator (
Modification Of Tray Dryer With Insulator ). Jurnal
Ilmiah, 4(November).
Tri Wulandari, F. (2020). KARATERISTIK SIFAT
FISIKA BAMBU TALI ( GIGANTOLOCHLOA
APUS KURZ ) SEBAGAI BAHAN BAKU BAMBU
KERAJINAN. Jurnal Fakultas Pertanian Universitass
Mataram, 3(1), 69–77.
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