Process controller
for wood drying

Under construction

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MODEL
COMPRESSOR
Nominal Power Consumed
LRA , 1 ph
RLA , 1 ph
Nominal Running Current
Refrigerant Charge; R134a
MAIN FAN
Air Flow
Max External Static Pressure
Motor Rating
FLA:- 1 ph
DEHUMIDIFICATION DUTY LITRES/HR
Via HEAT PUMP (50deg C/60% RH)
HEAT TO AIR KW
Via HEAT PUMP
Via Resistance heaters and Heat Pump
HEATERS
Heater Rating
FLA
ELECTRICAL
Voltage
Total Power Consumed, Dehum & Heater (nominal)
Nominal Running Amps
Min’ Supply Capacity
Max’ Supply Fuse
DIMENSIONS
Height
Length

High Performance
● High efficiency hermetic compressor
● Tuned for optimum extraction rate per kWhr of
energy consumed
● Pressure switch and delay timer protection on
compressor circuit
● Latest R134a HFC refrigerant used
● Low energy centrifugal fan
Calorex DH60AHP Dehumidifier
Performance Chart
High Quality Construction
● Plastic galvanised steel cover
● Epoxy polyester coated AI fin/Cu tube exchangers
● Corrosion resistant galvanised sub-frame
High Temperature Process Drying
Dehumidifier
The DH60AHP dehumidifier is specifically designed
for use in low volume process drying applications.
The unit can operate in temperatures up to 55°C.
The unit’s compact size, integral 4kW electric air
heater and simple controls allow an inexpensive
drying system to be created.
The unit has found favour in the joinery trade,
drying timber for furniture manufacture
R
C O M M E R C I A L / I N D U S T R I A L
Industrial Process
Drying
Drying by Dehumidification
● Ceramic
● Timber
● Confectionery
● Brick, Block and Tile
● Food Manufacture
● Textile
● Paper/Cardboard
● And Many Others
Key Benefits ● Reduced Energy Costs Applications
● Reduced Drying Times
● Reduced Rejection Rates
● Short Payback Periods
● Increased Energy Efficiency
● Increased Product Quality
● Increased Profits
Control Options
Calorex can offer control options from a simple
control panel to a complex system capable of
programming a fully timed drying schedule.
● Single stage
● Four stage
● Six stage
● PLC control
Why Dehumidifiers for Drying
● Rapid water removal at lowest cost per litre
extracted
● Latent energy reclaimed to reduce power
consumption
● Drying at lower temperatures reduces risk of
heat damage
● Even drying improves product quality
● Low maintenance
Method of Operation
Air is re-circulated within the chamber by a set of fans positioned above a false ceiling. The velocity
past the product being critical to the drying speed The temperature of the chamber is increased to
speed the release of moisture from the product. The higher the temperature the quicker the drying
process. The moisture released by the product is extracted by the dehumidifier. The heat pump
dehumidifier converts the latent energy into heat which is returned back into the drying chamber.
This reduces the energy required to maintain the operating temperature. The condensed moisture is
rejected to a waste water drain.
Industrial Process and Product Drying
For All Your Process Drying Applications
Advantages Against Conventional
Hot Air Ovens
● Less aggressive drying process and increased
control of drying environment
● Increases product quality and reduces
rejection rates
● Reduced space required for drying gives
increased space for production
● Reduced energy costs and increased energy
efficiency give short payback period
The DH334BH dehumidifier is specifically designed for use
in high temperature process drying applications.
The unit can operate in temperatures up to 70°C.
Used in conjunction with a Calorex process drying control
panel to create the perfect drying environment for your
product. Calorex also manufactures a standard range that
can operate at up to 40°C which have also been used
successfully in many process drying applications.

MODEL
COMPRESSOR
Nominal Power Consumed
LRA, 3 ph N
RLA, 3 ph N
Nominal Running Current
Refrigerant Charge; R134a
MAIN FAN
Air flow
Max External Static Pressure
Motor Rating
FLA:- 3 ph N
DEHUMIDIFICATION DUTY LITRES/HR
Via HEAT PUMP (45deg C/80% RH)
HEAT TO AIR KW
Via HEAT PUMP
Via Resistance Heaters and Heat Pump
HEATERS
Heater Rating
FLA
ELECTRICAL
Voltage
Total Power Consumed (nominal)
Min’ Supply Capacity
Max’ Supply Fuse
DIMENSIONS
Width
Depth
Height
Noise[at] 3m
WEIGHT APPROX
Calorex DH334BH Dehumidifier
Performance Chart
High Temperature Process Drying Dehumidifier
Options Available
Drying by dehumidification is the most effective, energy efficient
and economic way to dry your products

Drying Radiata Pine Timber under Dehumidifier
Conditions: Comparison of Modelled Results with
Experimental Results
Z. F. Sun Physics Department, University of Otago, PO Box 56, Dunedin, New Zealand
C. G. Carrington Physics Department, University of Otago, PO Box 56, Dunedin, New Zealand
C. Davis Physics Department, University of Otago, PO Box 56, Dunedin, New Zealand
Q. Sun Physics Department, University of Otago, PO Box 56, Dunedin, New Zealand
S. Pang Department of Chemical and Process Engineering, University of Canterbury,
Christchurch, New Zealand
ABSTRACT
A dynamic kiln-wide wood drying model was developed previously by the Otago research group. For the airflow
inside a stack, the model solves the integral form of the unsteady-state mass, momentum and energy balance
equations. For the wood side, an empirical model, characteristic drying curve, for the internal moisture movement is
used, which was obtained for low and medium temperature drying of Pinus radiata, with a medium velocity of 1.4-
4.1 m s–1. As part of the programme to improve the design and control of dehumidifier wood drying kilns, the wood
drying model has been assessed using the experimental data measured at the NZ Forest Research Institute and
University of Otago. It is noted that good agreement between the modelled results and the experimental data can be
obtained for Pinus radiata drying processes with a medium air velocity (< 5 m s–1). However, larger discrepancy
between the modelled results and the measured data has been produced with a higher velocity (8 m s–1). To solve this
problem a new characteristic drying curve, based on a two-zone diffusion model, has been used in the kiln-wide
wood drying model and more accurate results have been obtained.
INTRODUCTION
Modelling the kiln-wide drying processes is
essential for improving the design and analysis of wood
drying equipment. A dynamic wood drying model has
been developed by the Otago research group, which
solves the mass, momentum and energy balance
equations for both the air flow and wood boards in
drying three types of stack: normal stack, aligned stack
and staggered stack (Sun and Carrington, 1999a; Sun
and Carrington, 1999b; Sun, Carrington & Bannister,
2000). For the airflow inside a stack, the model solves
the integral form of the unsteady-state mass, momentum
and energy balance equations. For the wood side, the
characteristic drying curve method (Keey, 1992) is
adopted for the description of the internal moisture
transfer processes inside the wood boards.
Models for detailed internal moisture transfer and
heat transfer within wood boards have been established
by previous authors (e.g. Stanish et al., 1986; Perré,
1996). However, it is difficult to use these models for
modeling kiln-wide wood drying processes, since very
large computational time and storage are required. On
the basis of the moisture movement mechanisms, a
characteristic drying curve correlation was obtained for
low and medium temperature drying of Pinus radiata
sapwood, with a medium velocity of 1.4-4.1 m s–1 (Sun
et al., 1996). This correlation relates the normalized
drying rate to the conventional normalized moisture
content using the equilibrium moisture content, the
critical moisture content and the normalized moisture
content defined in terms of the fibre saturation point
(FSP) and the critical moisture content. In particular,
two constant parameters were used in the correlation,
which were noted previously to be dependent on board
geometry and wood structure properties (Sun et al.,
1996). However, the effect of drying conditions, such as
air velocity, temperature, and humidity on the two
parameters has not been considered. Consequently, the
application of this characteristic drying curve may be
restricted.
8th International IUFRO Wood Drying Conference - 2003
40
In this paper, the kiln-wide drying model and the
characteristic drying curve have been further assessed
by comparison of calculated results with the measured
data obtained by Pang (1999) at the NZ Forest Research
Institute and by Davis (2001) at University of Otago. In
order to solve the difficulty that the present drying
TABLE 1. Experimental kiln operating conditions (Pang, 1999)
Run 1 Run 2 Run 3 Run 4 Run 5
Measured drying time, hours
Initial moisture content of moist wood, %
Final average MC of wood board, %
Basic density of wood, kg/m³
Number of wood boards in a layer of the stack
Layer number of stack
Total volume of timber in the kiln, m³
Total width of the stack, m
Total depth of the stack, m
Board thickness, mm
Fillet thickness, mm
Air velocity between boards, m s–1
Air-flow reversal period, hours
Dry-bulb/wet-bulb target temperatures, °C

curve relation is not accurate for cases where the air
velocity is high, a new characteristic drying curve,
based on the two-zone diffusion model developed by
Davis (2001), has been established and tested.
WOOD DRYING MODEL
The dynamic model used in modelling kiln-wide
wood drying processes has been described in detail in
previous papers (Sun and Carrington, 1999a; Sun and
Carrington, 1999b; Sun, Carrington & Bannister, 2000).
For simplicity, the air flow model is one-dimensional,
but two parallel air streams for the central stack and
side stack are used.
The characteristic drying curve method (Keey,
1992) was adopted for the description of the internal
moisture transfer processes inside wood boards. When
the surface of the moist-wood is no longer saturated
with moisture, the characteristic drying-curve concept
can be used to factor the unhindered drying rate from a
saturated surface to estimate the diminished drying rate
(Ashworth, 1977; Keey, 1992). Thus, from the Fick’s
first law of diffusion, the real drying rate can be written
as: = (1)
where f is the normalized drying rate, which is defined
as the ratio of the diminished drying rate to the
unhindered drying rate and kω is the mass transfer
coefficient, on the basis of the vapour mass fraction
difference between the surface of wood boards and the
bulk air stream.
An empirical characteristic drying curve relation
for the internal moisture movement was proposed for
drying of Pinus radiata sapwood (Sun et al., 1996). For
the constant rate period (X ≥ Xc)
f = 1.0 (2)
For the falling rate period (X < Xc),
A B fsp f − Φ = Φ (3)

In the equations above, Xc is the critical moisture
content; Xe is the equilibrium moisture content; Xfsp is
the fibre saturation point. The two constant parameters,
A and B, in Eq.(3) were noted previously to be
dependent on board geometry and wood structure
properties, of which fitted values were obtained for
Pinus radiata sapwood at low and medium
temperatures, with a velocity range of 1.4-4.1 m s–1
(Sun et al., 1996).
In the wood drying model, the external masstransfer
and heat-transfer coefficients are evaluated by
using empirical correlations. Due to the boundary layer
separation, reattachment, and redevelopment of flow,
measured mass and heat transfer data over blunt-edged
flat plates show a common characteristic that the
transfer rate is maximum at the point of reattachment
and passes through a minimum at a point between the
leading edge and the reattachment point (Sørensen,
1969; Kho, 1993). The correlations for mass and heat
transfer j-factors over blunt boards have been
8th International IUFRO Wood Drying Conference - 2003
41
established by Sun (2002) and used in the kiln-wide
wood drying model, which are given by
( α β) ( γ β) = − − − − −x
x x j 0.0288 Re Re 0.2 Re (6)
where α, β, and γ are positive parameters. Using the
mass transfer data over blunt boards in a board stack
measured by Kho (1993), the fitted correlations for the
parameters α, β, and γ are obtained as follows:
2.1513 10 6 Re1.1106 Re0.6501 D S
α = × − (7)
0.1542 Re0.1410 Re0.0437 D S β = (8)
and
8.5197 10 5 Re1.1172 Re0.5240 D S
γ = × − (9)
where ReD (=4400~22,000) and ReS (=4400~10,300)
are the Reynolds numbers based on the board thickness
and the space size between two board layers. For the
region from the leading edge to the minimum point, the
conventional power law relation for a turbulent
boundary layer is used, with α = 0, β = 0, and γ = 0 in
Eq.(6) (Sun, 2002).
COMPARISON OF MODELLED RESULTS
WITH THE MEASURED DATA
Simulation runs have been carried out under the
experimental conditions of the five experiments
performed by Pang (1999) at the NZ Forest Research
Institute and the experiments conducted by Davis
(2001) at Otago University. Here, only the simulation
results of the five experimental runs of Pang are
presented. The simulation results of the experimental
runs of Davis are presented elsewhere (Davis, 2001),
which are consistent with the results shown below.
The material for the five experimental runs of Pang
was Pinus radiata sapwood and all the runs were
conducted in a tunnel dryer, using varying air
temperature, humidity and air velocity (Pang, 1999).
The measured data of green moisture content and wood
density for each run have been used in the calculation
as initial conditions. The total drying time for each run
is based on the experimental values. The measured
stack-on air velocity, dry-bulb temperature, and wetbulb
temperature were used as the boundary conditions
for the calculation.
Table 1 lists the experimental operating conditions.
The number of control volumes used in each of the
simulation runs is the same as the number of the boards
in a board layer in the experimental stacks.
In runs 1 and 2, the dimensions of the sample
timber are 200×40×580 mm³ with 10 boards in each
layer of the four-layer stack. The stack-on drybulb/
wet-bulb temperatures are 45/35°C and 71/60°C
respectively in runs 1 and 2. The air velocity is 8 m s–1
and airflow is reversed every 12 hours in both run 1 and
run 2. In runs 3, 4, and 5, the dimension of the sample
timber is 100×40×590 mm³ with 23 boards in each
layer of the four-layer stack. The stack-on drybulb/
wet-bulb temperatures 71/60.7°C, 71/60.8°C, and
60/47°C are used in runs 3, 4, and 5 respectively. The
stack-on wet-bulb temperatures used in the model are
slightly different from the target values given in Table
1. These have been adjusted to agree with the measured
stack-on wet-bulb temperatures obtained by Pang
(1999). There is no basis for making this adjustment for
runs 1 and 2, since no measured values were provided
for the stack-on wet-bulb temperatures in runs 1 and 2.
The airflow velocity used was 3, 5, and 3 m s–1 for runs
3, 4, and 5 respectively. In run 3, the airflow is reversed
every 12 hours.

Time (hour)
Moisture content (%)
Measurements by Pang (1999)
Drying curve of Sun et al. (1996)
Drying curve of Davis (2001)
FIGURE 1. Variation of the average moisture content
in run 1.

Time (hour)
Moisture content (%)
Measurements by Pang (1999)
Drying curve of Sun et al. (1996)
Drying curve of Davis (2001)
FIGURE 2. Variation of the average moisture content
in run 2.
Figures 1 and 2 show the modelled and measured
average moisture content profiles. In these figures and
Figures 3 to 7 below, the dashed lines represent the
results obtained using the characteristic drying curve of
Sun et al. (1996) and the points denote the measured
values of Pang (1999). The dot-dashed lines represent
the results obtained using another characteristic drying
curve based on the two-zone diffusion model developed
by Davis (2001), which is described below. Referring
just to the drying curve of Sun et al. (1996), these
figures indicate that there are large discrepancies
between the modelled moisture contents and the
measured moisture contents in the early period of the
8th International IUFRO Wood Drying Conference - 2003
42
wood drying processes. The drying rate is
overestimated by the model. One of the possible
reasons for the calculation errors is that the
characteristic drying curve used in the model was
obtained based on the measured data obtained in a
lower velocity range of 1.4-4 m s–1 (Sun et al., 1996),
which is much lower than the air velocity of 8 m s–1 in
both run 1 and run 2. For a drying process with a high
air velocity (>5 m s–1), this drying curve may not be
applicable.
Figures 3, 4, and 5 show the modelled and
measured average moisture content profiles for runs 3
to 5. It is seen that the discrepancies between the results
obtained using the drying curve of Sun et al. (1996) and
the measured values are much smaller than those shown
in Figures 1 and 2 for runs 1 and 2. It is noted that the
airflow velocity, 3 m s–1, in runs 3 and 5 is in the
velocity range of 1.4-4 m s–1, at which the characteristic
drying curve was obtained (Sun et al., 1996). The air
velocity, 5 m s–1, in run 4 is close to the velocity range.
This suggests that the kiln-wide wood drying model and
the characteristic drying curve of Sun et al. (1996) can
only be used for modeling drying processes with an air
velocity less than 5 m s–1.

Time (hour)
Moisture content (%)
Measurements by Pang (1999)
Drying curve of Sun et al. (1996)
Drying curve of Davis (2001)
FIGURE 3. Variation of the average moisture content
in run 3.

Drying time (hours)
Moisture content (%)
Measurements by Pang (1999)
Drying curve of Sun et al. (1996)
Drying curve of Davis (2001)
FIGURE 4. Variation of the average moisture content
in run 4.
Figures 6 and 7 show the modelled and measured
moisture content distributions along the stack in run 3
and run 4 respectively. In these figures, the dashed lines
represent the results obtained using the characteristic
drying curve of Sun et al. (1996) and the points denote
the values measured by Pang (1999). These figures also
indicate that the drying process of Pinus radiata
sapwood with a lower velocity (< 5 m s–1) can be
described by the kiln-wide wood drying model and the
characteristic drying curve expressed by Eqns.(2)-(5),
with reasonable accuracy.

Drying time (hours)
Moisture content (%)
Measurements by Pang (1999)
Drying curve of Sun et al. (1996)
Drying curve of Davis (2001)
FIGURE 5. Variation of the average moisture content
in run 5.

FIGURE 7. Moisture content distribution along the
stack in run 4.
8th International IUFRO Wood Drying Conference - 2003
43
It is seen from Figure 6 that due to the airflow
reversal in run 3, the moisture contents at the stack-on
and stack-off positions of the stack are lower than that
at the middle of the stack. Since the air stream is not
reversed in run 4, Figure 7 shows that the moisture
content at the stack-on is significantly lower than that at
the stack-off.
The modelled and measured stack-off dry-bulb
temperatures in runs 4 and 5 are compared in Figure 8.
The thinner solid lines represent the results obtained using
the drying curve of Sun et al. (1996) and the points denote
the values measured by Pang (1999). There are no
measured stack-off dry-bulb temperatures for runs 1 and 2
and no measured stack-off wet-bulb temperatures for
comparison with the modelled results. Figure 8 indicates
that the modelled stack-off dry-bulb temperatures are in
reasonable agreement with the measured values. However,
the calculated results of the stack-off temperature are
generally larger than the measured values. The errors may
be due to that we have neglected the heat losses between
the air streams and the surroundings and the energy used
for heating up the stack chamber in the calculation, which
causes higher stack-off air temperatures compared with the
measured values.
Run 5
Figure 8. Comparison of the measured and calculated
stack-off dry-bulb temperatures in runs 4 and 5.
CHARACTERISTIC DRYING CURVE BASED
ON AN ISOTHERMAL DIFFUSION MODEL
As indicated by Figures 1 and 2, for drying
processes of Pinus radiata with high airflow velocities,
a more accurate drying curve is necessary.
An isothermal diffusion model has been developed
by Davis (2001) for the analysis of Pinus radiata
drying processes. Using an established desorption
function, the model gives approximate analytic drying
curve functions, which can be further converted to a
characteristic drying curve.
The isothermal diffusion model assumes that the
diffusion coefficient varies exponentially with moisture
content below the fibre saturation point and is constant
above the fibre saturation point, as follows (Davis,
2001),

where A is a constant parameter, D0 is the local
diffusion coefficient above FSP, and X0 is the initial
moisture content. The parameters A and D0 are
dependent on the properties of the material being dried
and the operating conditions (Davis, 2001).
The boundary condition at the surfaces of wood
boards utilises an apparent mass transfer coefficient,
m h′ , which accounts for the effect of an initial thin dry
layer. An empirical relationship was established
between the actual mass transfer coefficient, m h′ , and
the mass transfer coefficient of boundary layer theory,

where T∞ is the temperature of the bulk airflow in the
unit of Kelvin. This relation, along with the relations
(10) and (11), allows straightforward prediction of
drying curves for different types of Pinus radiata in
different drying conditions and board dimensions. The
resulting approximate drying curves are
computationally inexpensive, and therefore suitable for
kiln-wide models.
The conversion of the analytic drying curves to the
characteristic drying curves is made by the
transformation (Davis, 2001),
Bi′
f = F (13)
where F is the dimensionless drying rate, and Bi′ is the
mass transfer Biot number which represents the ratio of
internal mass transfer resistance to external mass
transfer resistance.
The fitted values of A and D0 used in modelling the
experimental runs 1-5 of Pang (1999) are listed in Table
2. Sensitivity analyses indicate that the kiln-wide wood
drying model is much less sensitive to the parameter A
than the parameter D0.
The new characteristic drying curve, which is based
on the isothermal diffusion model, has been
incorporated into the kiln-wide wood drying model.
The modeled average moisture content profiles for runs
1-5 are shown in Figures 1 to 5 as the dot-dashed lines.
The modelled moisture content distributions along the
stacks for runs 3 and 4 are shown in Figures 6 and 7 as
the dot-dashed lines. The modelled dry-bulb
8th International IUFRO Wood Drying Conference - 2003
44
temperatures for runs 4 and 5 are shown in Figure 8 as
the thicker solid lines. All these figures show that the
modelled results using the new characteristic drying
curve are in good agreement with the measured data. In
particular, the large discrepancies between the modelled
results, obtained using the drying curve of Sun et al.
(1996), and the measured data for runs 1 and 2 with a
high air velocity have been reduced significantly.
TABLE 2. Reference parameters in the drying curve of
Davis
(1996) have been assessed using
the experimental data obtained by Pang (1999) at the
NZ Forest Research Institute, under dehumidifier
drying conditions with low to medium temperatures.
It has been found that at a medium velocity (< 5m s–1),
the kiln-wide wood drying model together with the
characteristic drying curve can give reasonably accurate
descriptions of kiln performances. However, at a high air
velocity (8m s–1), large discrepancies between the results
obtained using the characteristic drying curve of Sun et al.
(1996) and the measurements have been noticed.
To solve this problem, a new characteristic drying
curve, based on an isothermal diffusion model developed
by Davis (2001), has been established and incorporated
into the kiln-wide wood drying model. This new
characteristic drying curve considers evaporation from a
surface below a thin layer saturated at some temperature
between the wet- and dry-bulb temperatures and takes
account of the effect of an initial dry thin surface layer on
mass transfer. The results obtained using the new
characteristic drying curve are in good agreement with the
measured data. In particular, the large discrepancies
between the modelled results and measured data in the
cases of high air velocities have been reduced
significantly. This suggests that the new characteristic
drying curve can be successfully used for a wider range of
velocities up to 8 m s–1.

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