Cfd simulation of flow heat and mass transfer

Chapter 6: CFD Simulation of Flow, Heat and Mass Transfer
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6.1 Introduction
A one dimensional mathematical model was developed (chapter 5) for predicting heat
exchanger performance. However, the shortcoming of this model is that it cannot model
complicated changes in the heat exchanger design parameters such as changing the
number of flow ribs. In addition, the mathematical model does not provide the flow,
temperature and moisture distribution in the heat exchanger. To provide detailed
information on both sensible and latent characteristics, a detailed model of the heat and
mass transfer distribution in the heat exchanger is needed.
To obtain the detailed information on the temperature, flow and moisture distribution in
the heat exchanger, Computational Fluid Dynamics (CFD) simulation is used.
Computational modelling has advantages over experimental techniques in the
investigation of flow, temperature and moisture distribution in the heat exchanger where
the introduction of instrumentation into the flow paths would influence the flow structure
and the heat and moisture transfer behaviour. With numerical simulation, it is possible to
obtain information on temperature, velocity, moisture and flow rate that sometimes
cannot be measured using conventional instrumentation. The effect of various parameters
on the heat and moisture transfer and fluid flow can be investigated in a parametric study
once a simulation model has been developed and validated against experimental data.

93
In this study, a computational fluid dynamics package, FLUENT, is used to simulate the
heat and moisture transfer in the membrane heat exchanger.
The literature review in chapter 2 shows that previous researchers have developed CFD
models for simple geometry heat exchangers such as square and rectangular shapes.
However, it is difficult for these codes to model more complicated heat exchanger
geometries. Therefore, to perform such modelling, this chapter is focused on the use of a
commercial Computational Fluid Dynamics (CFD) model which is able to model more
complicated heat exchanger geometry similar to the Z shape flow configuration heat
exchanger used in this research.
In this chapter the CFD modelling of a Z type flow enthalpy heat exchanger is presented
and the performance of the heat exchanger is determined numerically. The experimental
results obtained from the heat exchanger experimental test rig (chapter 4) were used as
benchmark cases to validate the CFD simulation results. The CFD package (FLUENT) is
also used to model Niu and Zhang’s (2001) square shaped membrane heat exchanger and
the results were validated against Niu’s and Zhang’s (2001) published results.
6.2 Computational fluid dynamics
Computational Fluid Dynamics (CFD) is the analysis of systems involving fluid flow,
heat transfer and associated phenomena such as chemical reactions, by means of
computer-based simulation. CFD is a powerful technique and can be used in a wide range
of applications, both industrial and non-industrial.
Computer based simulations work out the consequences of a mathematical model, rather
than those of an actual physical model. The mathematical models consist of a set of
differential equations. Analytical solutions for the equations governing many phenomena
of practical interest are seldom possible. Computer based simulations can offer an

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alternative solution of a problem in place of oversimplified analytic solution of the
problem.
The physical aspects of fluid flow are governed by the three fundamental principles: mass
conservation, momentum conservation and energy conservation. These equations are
usually so complicated that an analytic solution is unavailable and it is necessary to seek
a computational solution. Thus, CFD is the art of replacing the integral or the partial
derivatives in these equations with discretised algebraic forms, which in turn are solved
to obtain solutions for the flow field at discrete points in time and/or space (Anderson
1995). Currently, most of the commercial CFD codes such as FLUENT are structured
around numerical algorithms that can deal with fluid flow and heat transfer problems. A
common feature among all these codes is the existence of three main stages: a pre-
processor, a solver and a postprocessor. The process of determining practical information
about problems involving fluid motion can be presented schematically in more detail in
Fig 6.1.

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Fig 6.1 Overview of computational fluid dynamics (Fletcher, 1997)

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6.3 Pre-processor
At the pre-processor stage, most of the known data about the problem under investigation
is entered into the CFD code. The steps involved in this stage are presented schematically
in Fig 6.2. The main goal of the pre-processor stage is the transformation of a flow
problem into a form suitable for use by the solver. The solution to a flow problem is
defined at the node inside each cell. Therefore, the number of cells in the grid has a major
effect on the accuracy of a CFD solution. In general, the larger the number of cells the
more accurate is the solution. However, increasing accuracy comes at high computational
cost. Therefore, a compromise needs to be achieved between the number of cells and the
required accuracy of the solution.
Fig 6.2 Steps involved at the pre-processor stage for
modelling heat transfer between two flows

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6.4 Solver
The main two stages executed by the solver are discretisation and solution of the Algebric
equations. The two stages are represented schematically in Fig 6.3. Discretisation is
concerned with the conversion of the continuous partial differential equations and
boundary conditions into a discrete system of algebraic equations. There are three distinct
streams of numerical solution techniques: finite difference, finite element and spectral
methods. Finite volume method is another numerical technique that is widely used in
commercial CFD codes such as FLUENT. The main difference between these approaches
is the way in which the flow variables are approximated with the discretisation processes.
The finite volume numerical algorithm consists of the following steps (Versteeg and
Malalasekera, 1999):
• Formal integration of the governing equations of fluid flow over all cells of the
computational domain.
• Substitution of a variety of finite difference type approximations for the terms in the
integrated equations which will convert the integral equations into a system of algebraic
equations.
• Solution of the algebraic equations by an iterative method.
Fig 6.3 Steps involved at the solver stage

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The second stage of the solution process requires an equation solver to provide the
solution of the system of algebraic equations. Systems of algebraic equations typically
arise in solving steady flow problems where the implicit technique is commonly used.
The implicit technique implies the existence of mutual dependence between two points;
that we cannot solve one point without knowing the other one.
6.5 Post-processor
The last stage in the CFD process is the post-processor stage where the output of a
numerical simulation is visualised using external or built-in visualisation programs. In
these programs, the domain geometry and the grid can be displayed, as can the field’s
velocity vectors and pressure contours.
6.6 Governing equation
The fundamental equations of fluid motion are based on three conservation laws: mass,
momentum and energy. Additional equations will also be required if, for example, a fluid
is composed of various chemical species with mass diffusion. The derivation of the
governing equations, which is detailed in Appendix D, is based on the assumption that all
dependent variables of interest obey generalised conservation principles. If the dependent
variable is denoted by ĳ, the general differential equation is
( )
+ . ( ) . ( )V S
t
φ φ
ρφ
ρφ φ
∂
∇ = ∇ Γ ∇ +
∂
(6.1)
where ȡ is the density, V is the velocity vector, (φ = u, v, w, T, k or İ), īĳ is the diffusion
coefficient and Sĳ is the source term. The four terms in the general differential equation
are the unsteady term (first term) which represent the rate of increase of φ of the fluid
element, the convection term (second term) expresses the net rate of flow of φ out of
fluid element, the diffusion term (third term) represents the rate of increase of φ due to

99
diffusion and the source term (forth term) articulate for the rate of increase of φ due to a
source in the element.
The incompressible steady moist air flow equation is represented as
. ( ) . ( )Vmoist air Sφ φρ φ φ∇ = ∇ Γ ∇ + (6.2)
Where ȡmoist air represent moist air density
6.7 Boundary conditions
In order to obtain a unique solution of the governing equations, a set of supplementary
conditions must be provided to determine the arbitrary functions that result from the
integration of the governing equations. The supplementary conditions are classified as
boundary or initial conditions. A boundary condition is a requirement that the dependent
variable or its derivative must satisfy on the boundary of the domain of a problem.
The various boundary conditions implemented in the current study are those used by the
general-purpose CFD code, FLUENT (2003). Fig 6.2 shows a simplified view of the
different boundaries in use. The following sections will detail the nature of each type and
usage.
6.7.1 Velocity inlet boundary condition
Throughout the current study velocity inlet boundary condition is used where, the
distribution of all flow variables needs to be specified at the inlet boundary. The inputs
into this boundary are the velocity magnitude and direction and the other scalar
properties.

100
6.7.2 Outflow boundary condition
Outflow boundary condition is used to model the exit flow where the details of the flow
velocity and pressure are not known prior to a solution of the flow problem. Defining any
conditions at outflow boundaries is not needed in this boundary condition.
6.7.3 Wall boundary condition
A wall boundary condition is used to bound both the fluid and solid regions. The no slip
condition (fluid velocity equal to zero) has been enforced at this boundary.
6.7.4 Symmetry boundary condition
Symmetry boundary conditions are used when the physical geometry of interest, and the
expected pattern of the flow/thermal solution, has mirrored symmetry. It is not necessary
to define boundary conditions at symmetry boundaries. Symmetry boundaries are used to
reduce the extent of the computational model to a symmetric subsection of the overall
physical system.
FLUENT assumes a zero flux of all quantities across a symmetry boundary. There is no
convective flux across a symmetry plane, the normal velocity component at the symmetry
plane is thus zero. There is no diffusion flux across a symmetry plane, the normal
gradients of all flow variables are thus zero at the symmetry plane.

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6.8 CFD modelling of the membrane heat exchanger
In order to model heat and moisture transfer in a Z type flow configuration, the
commercial CFD package (FLUENT) was adopted to obtain the temperature and
moisture distribution in the heat exchanger.
To model the heat exchanger, one flow passage from the hot stream and another flow
passage from the adjacent cold stream passage were used in the CFD model with half of
each flow passage volume modelled on each side of the paper surface. Hence symmetry
boundary conditions are used as shown in Fig 6.4.
To study the heat exchanger performance, flow, heat and moisture distribution in the heat
exchanger flow passages have to be investigated. However, available CFD packages
suffer from limitations when it comes to modelling moisture diffusion across a porous
paper similar to the heat exchanger being investigated. The only available porous
boundary option in FLUENT is the porous jump boundary which models a thin
membrane. The porous jump boundary condition considers the flow of air through the
porous surface based on solving the Darcy equation (FLUENT 2003).
This boundary condition does not model the mass transfer phenomena occurring due to
the vapour pressure gradient across the enthalpy heat exchanger, which is the reason
Fig 6.4 Cross section of the heat exchanger flow passage

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behind the moisture transfer from the hot and humid stream to the cold and less humid
stream in the heat exchanger. As a consequence a new method of handling the boundary
condition is needed to describe the nature of moisture transfer from the hot and humid
stream to the cold and less humid stream in order to obtain the air moisture distribution in
the heat exchanger passages.
In this research, two methods were adopted to model the moisture transfer and they are as
follows:
6.8.1 Effectiveness ratio method
To overcome the limitation in moisture transfer modelling, the porous paper is modelled
as a solid thin wall. However, the wall boundary will only allow heat to be transferred.
Moisture transfer is modelled based on introducing a non-dimensional ratio that relates
the air temperature to the air moisture content. This ratio is the sensible-latent
effectiveness ratio (ER) and is expressed as
( ) ( )
( ) ( )
p hi h fg hi Cis
L p hi Ci fg hi h
mC T T mh
ER
mC T T mh
ω ωε
ε ω ω
− −
= = ×
− −
(6.3)
( ) ( )
( ) ( )
p C Ci fg hi Cis
L p hi Ci fg C Ci
mC T T mh
ER
mC T T mh
ω ωε
ε ω ω
− −
= = ×
− −
(6.4)

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Where Th, TC, ωh and ωc represent the air temperature and moisture content at each grid
point on the membrane surface in the hot and cold streams (Fig 6.5). Fig 6.5 depicts the
process of modelling the moisture transfer of a simplified square shaped heat exchanger
with structured grid. To obtain the air moisture distribution in the hot stream, equation
(6.3) is solved, where the simplified mathematical model (chapter 5) is used to calculate
the sensible-latent effectiveness ratio, ER. The air inlet temperature and moisture content
(Thi, TCi, ωhi, and ωci) were determined by the operating conditions and the CFD code is
used to obtain Th values at each grid point on the membrane surface boundary by solving
equation (6.1), hence the air moisture content (ωh) at each grid point on the membrane
surface in the hot stream is obtained from equation 6.2. In a similar way equation 6.4 is
used in the cold stream to obtain the air moisture content (ωc) at each grid point on the
Fig 6.5 Numerical domain and boundary conditions
utilising effectiveness ratio method

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membrane surface in this stream. By determining the moisture content on the membrane
surface in the hot and cold streams, the moisture will be transferred from the hot and
humid stream inlet to the membrane surface due to the air moisture content difference
between the hot air inlet stream and the membrane surface causing a decrease in air
moisture content at the heat exchanger hot stream outlet. In the cold and less humid
stream the moisture will be transferred from the membrane surface to the cold inlet
stream due to the moisture difference, where the moisture content at the membrane
surface is higher than the air moisture content at the cold stream inlet, consequently the
air moisture content increases at the heat exchanger cold stream outlet. Hence moisture
distribution in both hot and cold stream flow passages is obtained (details of the
effectiveness ratio user define function code are shown in Appendix D 7.1).
The effectiveness ratio can be used to determine the air moisture distribution profile in
the heat exchanger; however, this modelling requires using the mathematical model
detailed in chapter 5 to obtain the value of the effectiveness ratio. From the effectiveness
values obtained from the mathematical model, the effectiveness ratio for 45gsm paper at
air face velocity of 2.9m/s was found to be 1.9 and for the 60gsm paper it was 1.3. In
chapter 5, Figs 5.8 and 5.9 show the sensible effectiveness for both 45 and 60gsm paper
were same. However, the latent values for 60gsm paper were higher due to the lower
moisture transfer resistance of 60gsm Kraft paper; as a result the effectiveness ratio value
was lower for the 60gsm paper.

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6.8.1.1 Effectiveness ratio simulation conditions
A three-dimensional model of the heat exchanger is developed to study the velocity,
temperature and moisture distribution in the heat exchanger using Finite-volume
differencing scheme segregated solver with implicit technique to solve the algebraic
equations forming the discritisation of equation 6.1. The semi implicit method for
pressure linked equation-consistent (SIMPLEC) algorithm is employed for the
calculation of the pressure and thus the velocity field. Second order upwind discretisation
scheme is used to discritise the steady state version of equation 6.1.
The Reynolds number in a flow passage ranges (for the 45gsm paper experimental
measurement) from 2300 to 5500 for typical application conditions. Therefore, the
turbulent k-İ renormalisation group (k-İ RNG) turbulence model is utilised.
The velocity inlet boundary condition is used to define the velocity of the moist air inlet
to each flow path in the heat exchanger. Outflow boundary condition is used for the heat
exchanger outlets to model the flow exits the heat exchanger.
6.8.1.2 Validation of CFD results using effectiveness ratio method
Although CFD is an effective tool, and has been used in many applications for many
years, code validation is always necessary. In some fields, the use of CFD has become
common practice and CFD has been tested and trusted by engineers. Nevertheless, in
most areas, CFD still needs to be validated.
The method of measuring the accuracy of the representation is achieved by comparing
CFD simulations with experimental data and previous research performed. Experimental
data can be obtained from measurements and the accuracy of the measurement must be
high enough to give an accurate representation of the modelled system. In addition, the
experimental data can be obtained from the published work of other researchers. Code

106
validation, in the current study, relies on both the published work found in the literature
and experimental measurements performed during this project.
To validate the code against previous research results, the heat exchanger investigated by
Niu and Zhang (2001), presented in the literature review (chapter 2), is modelled using
FLUENT correlated with the effectiveness ratio method. As mentioned in chapter 2, Niu
and Zhang modelled a squared shaped heat exchanger (Fig 6.6) using in-house code due
to the limitations of available commercial CFD packages when it comes to modelling
moisture diffusion across a porous boundary.
As a result Niu and Zhang developed their in-house CFD code to study the temperature
and moisture distribution in simple heat exchanger geometry such as square and
rectangular shapes.
The square heat exchanger modelled by Niu and Zhang has a total heat and moisture
transfer area of 0.25m2
and consists of 15 square shaped inlet flow path frames on each
stream. The membrane thickness is 20ȝm and the flow path width is 5mm. This heat
exchanger is modelled using the effectiveness ratio method. Fig 6.7 shows that the
effectiveness obtained using the effectiveness ratio method is in agreement with Niu and
Zhang’s effectiveness results.
Fig 6.6 Niu and Zhang square shaped membrane heat exchanger (2001)

107
Further, the temperature and moisture contours in the hot and cold streams are in
reasonable agreement with Niu’s and Zhang’s contours (Fig 6.8). However, there were
minor qualitative differences between the present CFD model temperature and moisture
contours and Niu’s and Zhang’s contours, the reason for the differences maybe explained
as follows:
The finite differencing numerical solution technique used by Niu and Zhang, is less
accurate than the finite volume method used in this research (Versteeg and Malalasekera,
1999).
Another reason for the differences could be the discretisation scheme used, as Niu and
Zhang used the upwind scheme at the exchanger air streams and central-difference
scheme at the membrane, whereas in the present research a second order upwind scheme
is used. It is well known that the central-difference scheme is not as accurate as the
second order upwind and may cause the solution to be unstable (Versteeg and
Malalasekera, 1999).
It should also be noted that Niu and Zhang did not present mesh sensitivity analysis and
therefore it is not possible to ascertain that their solution is mesh independent.
Fig 6.7 Comparison of Niu and Zhang (2001) effectiveness and
CFD effectiveness ratio method results

108
The accuracy of the flow, temperature and moisture fields obtained in this research is
further examined by a mesh sensitivity analysis presented in the next section.
Fig 6.8 Comparison of CFD solutions from effectiveness ratio method and Niu and
Zhang (2001) CFD solutions (temperature in Celsius and moisture content in kg/kg)
Modelled heat
exchanger mesh

109
6.8.1.3 Mesh sensitivity study
CFD solutions to fluid dynamics and heat transfer problems always contain errors due to
the evaluation of continuous problems using discrete analysis. In general, these errors can
be minimised by discretising the flow domain into a large number of mesh points (cells).
In practice, there is a trade off between the accuracy of the solution and the computing
time; hence an optimum number of grid points have to be used for the simulation domain.
In this study mesh refinement investigation has been carried out to optimise the number
of cells used. It is apparent that the more cells used in the model the more time consumed
to complete the simulation. Different numbers of cells were tested to optimise the number
of cells to be used in the final modelling of the heat exchanger. Fig 6.9 shows that when
200,000 cells were used the effectiveness was higher than the measured effectiveness.
However, by increasing the number of cells to 250,000, the predicted CFD effectiveness
was the same as the measured effectiveness. By increasing the number of cells to 300,000
and 350,000, the results show no difference from the 250,000 cells model. Hence,
250,000 cells was selected to be the optimum number of cells that can be used to obtain
reliable and accurate results and consume less time than other models.
0.1
0.15
0.2
0.25
0.3
0.35
0.4
0.45
0.5
150,000 200,000 250,000 300,000 350,000 400,000
Number of Cells
Effectiveness
Sensible effectiveness
Measured Sensible effectiveness
Latent effectiveness
Measured Latent effectiveness
Fig 6.9 Mesh sensitivity study at air face velocity of 2.93m/s

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6.8.1.4 Effectiveness ratio method validation against measurements
The Z type heat exchanger used in this study is modelled to validate the numerical
simulation results against the experimental results. Fig 6.10 shows that the numerical
CFD predictions of sensible, latent and total effectiveness are in reasonable agreement
with the measured results. Therefore, this model can be used to study the detailed flow,
temperature and moisture content distribution in the heat exchanger.
0
0.1
0.2
0.3
0.4
0.5
0.6
1 1.5 2 2.5 3 3.5
Face velocity (m/s)
Effectiveness
Measured performance
CFD model
Latent
Sensible
Total
6.63m/s
5.33m/s
3.33m/s
7.3m/s
To study the temperature and moisture distribution in 45gsm paper heat exchanger, the
hot and humid stream temperature distribution contours (Fig 6.11) show when the hot and
moist air enters the heat exchanger a flow circulation zone occurs at the corner of the
flow path ribs (details of flow recirculation is shown in Fig 6.12).
Fig 6.10 CFD and experimental effectiveness results (figures shown
represent air velocity at the inlet of heat exchanger flow channels)

111
At these circulation zones the temperature has decreased and this is due to low velocity
and flow circulation occurring in that zone (Fig 6.11, circles represents low velocity and
circulation zone). This circulation is more noticeable and has more effect in flow path 1
where a sharp right angle change in the flow direction towards the outlet has occurred
(Fig 6.11, dotted rectangles at flow path 1 and 6). Fig 6.11 also illustrates that the highest
reduction in temperature occurred along flow path 1 by 4.15K. The reduction of
temperature along paths 2, 3, 4, 5 and 6 was 4, 3.65, 3.3, 3 and 2.78K respectively.
The high decrease in temperature occurred at flow path 1 is attributed to the location of
this flow path, when the air flow enters flow path 1 the flow arrangement at the entrance
is counter flow. As the flow changes its direction (vertical direction) the flow
arrangement at that zone is cross flow and it is located adjacent to the cold air inlet at the
adjacent frame, as a result the temperature gradient between the hot and cold streams in
that zone is the highest and the amount of heat transfer is higher. Therefore the highest
reduction in temperature occurs along flow path 1. At flow path 2 the location of this path
is the second nearest to the cold air inlet at the adjacent frame, therefore the decrease in
temperature was larger than flow profiles 3, 4, 5 and 6 and less than flow path 1. It can
also be seen that the decrease in temperature at the circulation zones located nearest to
the cold inlet stream at the adjacent frame is more noticeable than in other flow
circulation zones.

112
Fig 6.11 Temperature contours in the hot and humid stream of 45gsm paper
heat exchanger at air face velocity of 2.93 m/s (temperature in Kelvin)
Z shaped heat exchanger
mesh

113
Fig 6.12 Velocity vectors showing recirculation zones in the
hot and humid stream of 45gsm paper heat exchanger at air
face velocity of 2.93 m/s

114
Similar to the hot stream, at the cold stream, the increase in temperature is higher for flow
path 1 as the temperature increased by 4.2K. In streams 2, 3, 4, 5 and 6 the increase in
temperature recorded was 4, 3.7, 3.4, 3and 2.9K respectively (Fig 6.13)
Fig 6.13 Temperature contours in the cold stream of 45gsm paper heat
exchanger at air face velocity of 2.93 m/s (temperature in Kelvin and
moisture content in kg/kg)

115
The location of the flow paths has a similar effect on moisture transfer. The hot flow
moisture distribution contours for 45gsm paper (Fig 6.14) show that when the air passes
the last bend a flow circulation zone occurs at the corner of the flow paths ribs (Fig 6.14
circles represent low velocity and circulation zone nearest to the adjacent cold and less
humid stream). Here, the moisture content recorded its lowest values. This is attributed to
the low velocity and flow circulation occurring in that zone. Similar to the temperature
contour, the flow circulation is more noticeable in flow path 1 where a sharp right angle
change in the flow direction towards the outlet has occurred (Fig 6.14, dotted rectangle).
The moisture distribution contour indicates that the location of flow paths have a
significant effect on the moisture distribution in the heat exchanger. The highest
reduction in the air moisture content occurred in flow path 1 as it is located adjacent to
the cold and less humid stream inlet, where the moisture content gradient is the highest;
hence the highest decrease in the moisture content recorded is 0.000573 kg/kg. The
reduction in the air moisture content in stream 2, 3, 4, 5 and 6 was 0.000553, 0.000503,
0.000453, 0.000403 and 0.000353 kg/kg respectively.
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Fig 6.14 moisture content contour in the hot and humid stream of
45gsm paper heat exchanger at air face velocity of 2.93 m/s
(moisture content in kg/kg)

116
In the cold and less humid stream the increase in the moisture transfer follows the same
trend as the heat transfer. As shown in Fig 6.15 the highest increase in moisture transfer
recorded was in flow path 1 where 0.00058kg/kg increase is recorded and is attributed to
the location of this flow path which is nearest to the hot and humid air inlet at the
adjacent stream.
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6.8.2 Lewis number method
As mentioned previously, the shortcoming in using the effectiveness ratio method is that
it relies on the mathematical model to obtain the effectiveness ratio value. Therefore an
alternative method is developed which can predict the heat exchanger performance if the
design parameters are changed without the need of using the mathematical model
effectiveness approach.
The new method of modelling the moisture transfer in the heat exchanger is to utilise the
Lewis number to obtain the moisture boundary conditions at the paper heat exchanger
surface. The Lewis number is represented as
Fig 6.15 moisture content contour in the cold and less humid stream
of 45gsm paper heat exchanger at air face velocity of 2.93 m/s
(moisture content in kg/kg)

117
Air thermal conductivity (Ȝair) and water in air diffusivity (Dwater-air) were obtained from
air property tables and plotted versus temperature. Plotting this data versus temperature, a
line of best fit is found, as illustrated in Fig 6.16. The equation for these lines of best fit is
then used in the calculation of air thermal conductivity and water in air diffusivity for
different values of temperature by incorporating them in the code, where the temperature
at the paper boundary is obtained from FLUENT by solving equation 6.1.
K = 7E-05T + 0.0042
0.024
0.0245
0.025
0.0255
0.026
0.0265
0.027
0.0275
0.028
275 280 285 290 295 300 305 310 315 320 325
Temperature (K)
AirthermalconductivityK(kW/m.C)
D = 2E-07T - 3E-05
1.50E-05
1.70E-05
1.90E-05
2.10E-05
2.30E-05
2.50E-05
2.70E-05
2.90E-05
275 280 285 290 295 300 305 310 315
Temperature (K)
DiffusivityofwaterinairD(m^2/s)
To simplify the modelling, it was assumed that Cp moist air value is 1.0273 kJ/kg K. For
Lewis number of 0.81, moist air density at the paper surface boundary in the hot and
moist stream is obtained. The vapour density in the air is represented as
The dry air density was obtained from air property tables and plotted versus temperature.
Similar to the air thermal conductivity, dry air density was obtained.
air
p moist air water air moist air
Le
C D
λ
ρ−
= (6.5)
vapour moist air dry airρ ρ ρ= − (6.6)
Fig 6.16 Air thermal conductivity and water diffusivity in air versus
temperature

118
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The dry air density is a function of air temperature at the paper boundary in the hot air
stream. FLUENT provides the air temperature at the paper boundary, thus the density of
the dry air is obtained from the equation for the line of best fit (Fig 6.17)
The air moisture content per kilogram of moist air at the paper surface boundary is
represented as
Substituting ȡvap from equation 6.6 and ȡmoist air obtained from Lewis correlation into
equation 6.7, the moisture content per kilogram of moist air at the paper surface boundary
in the hot stream is obtained (details of the Lewis number user define function code are
shown in Appendix D 7.2).
Fig 6.18 depicts the moisture transfer method using Lewis correlation in a simple square
shaped geometry heat exchanger. As can be seen in the cold stream, the amount of
moisture at the paper surface boundary is obtained from the moist air mass flow rate at
each cell in the CFD model on the paper surface boundary, and is calculated as follows:
vapour
hot stream
moist air
ρ
ω
ρ
= (6.7)
Fig 6.17 Dry air density versus temperature

119
The amount of moisture transferred from the paper surface boundary in the hot stream to
the paper boundary at the cold stream is represented as
The air moisture content at the paper boundary in the cold stream is represented as
where moist airm represent the moist air mass flow rate through the cell at the cold stream
paper boundary surface in the CFD model.
Substituting equation 6.9 into equation 6.8 and rearranging gives
tan
( )paper hot stream paper cold stream
moisture
moisture resis ce
m
R
ω ω−
= (6.8)
moistur cell moist air paper cold streamm m ω= (6.9)
Fig 6.18 Moisture transfer simulation using Lewis correlation method

120
Hence the air moisture content at the paper surface boundary in the cold stream is
obtained.
Using the same simulation conditions in the effectiveness ratio method, the Lewis
correlation method is used to model Niu and Zhang’s (2001) membrane heat exchanger.
This heat exchanger has been previously modelled using the effectiveness ratio method to
obtain the moisture distribution in the heat exchanger and it will be used as a benchmark
to validate the Lewis correlation method. For Lewis number of 0.81 the temperature and
moisture distribution contours in the heat exchanger hot and cold stream shows
reasonable agreement with Niu and Zhang’s contours (Fig 6.19).
tan
paper hot stream
paper cold stream
cell moist air moisture resis cem R
ω
ω = (6.10)

121
Fig 6.19 Comparison of CFD model with Lewis correlation and Niu and Zhang
(2001) CFD model (temperature in Celsius and moisture content in kg/kg)

122
After validating the Lewis correlation method against Niu and Zhang’s results, this
method is also used to model the existing Z type heat exchanger that utilises 45gsm paper
in order to compare the results with the effectiveness ratio method.
For Lewis number of 0.81, Fig 6.20 shows that the moisture contours were similar for
both models. The effectiveness ratio method contour shows an overall decrease in the
moisture content in the hot and humid stream of 0.000474 kg/kg and Lewis correlation
contour recorded a decrease of 0.00048.
Fig 6.20 Moisture transfer contours using Lewis correlation and
effectiveness ratio methods (temperature in Kelvin and moisture
content in kg/kg)

123
Fig 6.21 shows that the effectiveness values determined when the Lewis correlation
method is used are in reasonable agreement with the measured effectiveness values.
Since this method has been validated with experimental and previous researchers work, it
can now be used to model different heat exchanger configurations and to study
temperature and moisture distribution throughout the heat exchanger.
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Fig 6.21 CFD effectiveness results using Lewis correlation and
experimental effectiveness results

Chapter 7: CFD Simulation Results
124
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7.1 Introduction
In chapter 6, effectiveness ratio and Lewis correlation simulation methods were
developed to model moisture transfer in the membrane heat exchanger using the
FLUENT CFD package. These methods were validated against experimental
measurements and previous research results. In this chapter the design parameters of the
heat exchanger are varied and the above methods are used to predict the temperature,
flow and moisture distribution in the modified heat exchangers.
CFD simulation using the effectiveness ratio method is used to model the effect of
changing the heat exchanger grade of paper on the heat exchanger performance. The
Lewis correlation method is used to predict temperature, flow, and moisture distribution
when the number of flow divider ribs in the heat exchanger is varied. This method is also
used to model different flow configurations such as L shaped heat exchangers and predict
their performance.
Temperature, flow and moisture distribution contours of the modified heat exchangers are
presented in this chapter together with the heat exchanger predicted effectiveness.

125
7.2 Effect of changing the grade of paper
When 60gsm paper is used as the heat and moisture transfer surface, Fig 4.11 in chapter 4
shows the sensible effectiveness values for both 45 and 60gsm papers were the same
under the same operating conditions. Hence, the heat exchanger temperature distribution
contours for both 45 and 60gsm paper are similar. However, the moisture distribution
contours shown in Fig 7.1 show a significant difference with higher moisture transfer
recorded when 60gsm paper is used due to the considerable reduction of paper moisture
transfer resistance (Rpaper).
Similar to the 45gsm paper heat exchanger, the highest decrease in the moisture content
occurred in flow path 1 as the moisture content decreased by 0.0009 kg/kg. The reduction
in the air moisture content at flow paths 2, 3, 4, 5 and 6 was 0.00084, 0.00077, 0.00069
0.00062, and 0.00055 kg/kg respectively.
At the cold and less humid stream, analogous to the hot stream the highest increase in the
moisture content was in flow path 1, where 0.00088kg/kg increase is recorded. The
increase in flow path 2, 3, and 4 was 0.00082, 0.00075 and 0.00067kg/kg respectively,
and the increase in flow path 5 and 6 were 0.0006 and 0.00054kg/kg respectively.
In general the over all moisture transfer analysis of the hot and cold contours shows a
higher moisture transfer rate occurred when 60gsm paper was used, resulting in higher
latent effectiveness values. This is due to the lower moisture transfer resistance of 60gsm
paper in comparison with 45gsm paper.

126
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Fig 7.1 Moisture content contour in the hot and cold streams of 60gsm paper
heat exchanger at air face velocity 2.93 m/s (moisture content in kg/kg)

127
7.3 Effect of changing the number of flow divider ribs
As previously mentioned, the existing heat exchanger consists of five flow divider ribs.
The Lewis correlation method of modelling the moisture transfer is used to study the
effect of varying the number of ribs on the heat exchanger temperature and moisture
distribution and effectiveness. For Lewis number of 0.81 at air face velocity of 2.93m/s,
the FLUENT model incorporating the Lewis correlation is used to model the heat
exchanger without flow divider ribs, with one rib, two ribs, three ribs, five ribs (existing
heat exchanger) and eleven ribs.
Fig 7.2 shows the temperature, moisture and velocity distribution contours of the heat
exchanger without the flow dividers (ribs) at duct face velocity of 2.93 m/s. The hot and
humid stream contour shows that low velocity zones have been generated due to the flow
recirculation in zones A and B due to the sharp corners. The temperature and moisture
content recorded its lowest values in zone A, as the flow remains circulating at zone A
which is located adjacent to the cold air inlet where the gradient in temperature and
moisture content is high. As a result the temperature and moisture content recoded in
zone A is lower than in zone B.

128
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Similarly at the cold and less humid stream, the air temperature and moisture content at
zone A recorded its highest values in comparison with zone B, as the air circulating at
zone A is adjacent to the air hot inlet stream where the gradient in air temperature and
moisture content is high (Fig 7.3).
Fig 7.2 Hot and humid stream temperature, moisture and velocity distribution
contours for heat exchanger without ribs (temperature in Kelvin moisture
content in kg/kg and velocity in m/s)
Recirculation
zone

129
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When the heat exchanger is modelled with a single rib, the air circulation is divided into
three zones (zones A, B and C). As can be seen in Figs 7.4 and 7.5, the recirculation flow
zones at A and B became smaller in comparison with the heat exchanger with no ribs and
the flow distribution became more uniform. Nevertheless, the lowest temperature and
moisture content recorded at zone A and the temperature and moisture content at zone C
were less than zone B, which is attributed to the location of the circulation zone, as zone
Fig 7.3 Cold and less humid stream temperature, moisture and velocity
distribution contours for heat exchanger without ribs (temperature in
Kelvin, moisture content in kg/kg and velocity in m/s)

130
A is located adjacent to the cold air stream inlet, and zone C located nearer to the cold
inlet stream than zone B, therefore the temperature and moisture content recorded at zone
A were lower than zone B and C.
It can also be seen that the decease in air temperature and moisture content in flow path 1
was higher than flow path 2, where 3.54K and 0.00051 kg/kg decrease in temperature and
moisture content is recorded in flow path 1, in comparison with 2.7K and 0.0004 kg/kg
decrease recorded in temperature and moisture content in flow path 2, which is attributed
to the location of flow path 1, as the gradient in temperature and moisture content is high,
thereby the highest decrease is temperature and moisture content has occurred in flow
path 1.
Fig 7.4 Hot and humid stream temperature, moisture and velocity
distribution contours for single rib heat exchanger (temperature in
Kelvin moisture content in kg/kg and velocity in m/s)

131
Colored By Velocity Magnitude (m/s)
FLUENT 6.1 (3d, segregated, rngke)
Jan 13, 2008
Z
Y
X
Fig 7.5 Hot and humid stream velocity distribution vectors showing
recirculation zones for single rib heat exchanger (velocity in m/s)

132
The cold stream follows the same trend as in the hot and humid stream. Fig 7.6 shows the
highest temperature and moisture content recorded at zone A which is located adjacent to
the hot and humid steam inlet, hence the air circulating at zone A was heated and the
moisture content has increased. Whereas, the air temperature and moisture content at
zone C were higher than zone B due to the location of zone C nearer to the hot inlet
stream than zones B. Similar to the hot stream, the highest increase in temperature and
moisture content is recorded in flow path 1 in the cold stream, where 3.55K and 0.00048
kg/kg increase in temperature and moisture content is recorded which is higher than the
increase in temperature and moisture content at flow path 2.
distribution contours for single rib heat exchanger (temperature in Kelvin,
moisture content in kg/kg and velocity in m/s)

133
By increasing the number of flow dividing ribs to two, Figs 7.7 and 7.8 show that the
flow, temperature and moisture content distribution became more uniform and the
recirculation zones size has decreased, especially zone A. From Fig 7.7, it can be seen
that zone A recorded the lowest temperature and moisture content in comparison with
zone B, C and D. As zone A is located nearer to the cold air inlet at the adjacent cold
stream flow path. Therefore, the temperature and moisture content is lower.
Analogous to the heat exchanger with single flow divider, the highest heat and moisture
transfer has occurred in flow path 1, as it is located nearest to the cold air inlet in the
adjacent cold stream. Where 3.73K and 0.00067 kg/kg decrease in temperature and
moisture content is recorded in flow path 1, which is 13% higher than flow path 2 and
28% higher than flow path 3. The decrease in temperature and moisture content at flow
path 1 is 6% higher than the decrease recorded in the single rib heat exchanger. This
shows as the flow becomes more uniform by increasing the number of ribs the heat and
moisture transfer will improve.

134
distribution contours for two ribs heat exchanger (temperature in

135
Fig 7.8 Hot and humid stream temperature, velocity distribution
vectors showing recirculation zones for two ribs heat exchanger
(velocity in m/s)

136
The cold stream in 2 ribs heat exchanger follow the same trend as in the hot stream as
shown in Fig 7.9.
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distribution contours for two ribs heat exchanger (temperature in Kelvin,

137
Subsequent to the increase in the number of flow dividers to 2, increasing the flow
dividers ribs to 3 caused the flow, temperature and moisture distribution to be more
uniform and the flow recirculation zones became smaller in comparison with single and
double ribs heat exchangers.
Figs 7.10 and 7.11 show that the size of the circulation zone A has decreased and a
similar reduction has occurred in other flow circulation zones. Fig 7.10, also illustrates
that the reduction in temperature and moisture content were higher in flow path 1, where
3.74K and 0.00054 kg/kg decrease in the temperature and moisture content has occurred
in flow path 1 which is 7.5% higher than flow path 2, 18% higher than flow path 3, and
25.6% higher than flow 4 in the heat transfer and 13%, 24% and 38% higher than flow
paths 2, 3, and 4 respectively in the moisture transfer.
It can be seen that the temperature and moisture content difference at the flow path
outlets became less substantial than single and double rib heat exchangers indicating that
as the flow distribution became more uniform the temperature and moisture content
variation between the flow paths became less.
By comparing the amount of heat and moisture transferred at flow path 1, we can see that
the temperature has decreased by 3.54K, 3.73K, and 3.75K in single, double and 3 ribs
heat exchangers respectively. On the moisture content the decrease recoded is 0.00051
kg/kg, 0.00067 kg/kg, and 0.00077 kg/kg in single, double and 3 ribs heat exchanger
respectively. This shows that improving the uniformity in flow distribution would
improve the heat and moisture transfer.

138
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distribution contours for three ribs heat exchanger (temperature in

139
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X
Z
Y
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Fig 7.11 Hot and humid stream velocity distribution vectors showing
recirculation zones for three ribs heat exchanger (velocity in m/s)

140
The improvement in the flow, temperature and moisture content distribution can also be
seen in the cold stream (Fig 7.12). Where, the cold stream follows similar trend as in the
hot stream; as the circulation zones sizes has decreased and the highest increase in
temperature and moisture content recorded is at flow path 1 in comparison with flow path
2, 3 and 4.
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distribution contours for three ribs heat exchanger (temperature in

141
The study on the effect of changing the number of ribs has been extended to the existing
heat exchanger with 5 ribs (the detail analysis of the heat and moisture transfer has been
discussed in chapter 5). 7KH temperature and moisture contours for both hot and cold
streams shows the highest heat and moisture transfer has occurred in flow path 1 similar
to the previous modelled heat exchangers (single, double, and 3 rib heat exchangers). The
flow, temperature and moisture distribution became more uniform and the circulation
zones became smaller (Fig 7.13).
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Fig 7.14 shows that when the number of ribs in the heat exchanger has been increased to
11. The heat exchanger temperature and moisture contours illustrates that the
recirculation zones (red dotted circles and rectangles) became smaller and similar to the
Fig 7.13 Hot and cold streams temperature, and moisture contours
for five ribs heat exchanger (existing heat exchanger, (temperature in
Kelvin and moisture content in kg/kg)

142
previous heat exchangers the lowest decrease in temperature is recorded at flow path 1.
However, the temperature and moisture variation between the flow paths 12 outlets were
smaller.
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Fig 7.15 shows that analogous to the hot stream, the 11 ribs heat exchanger cold stream
follows the same trend as in the hot stream
Fig 7.14 Hot and humid stream temperature, moisture, and velocity
contours for eleven ribs heat exchanger (temperature in Kelvin,

143
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Fig 7.15 Cold and less humid stream temperature, moisture, and
velocity contours for eleven ribs heat exchanger (temperature
in Kelvin, moisture content in kg/kg and velocity in m/s)

144
The effect of varying the number of ribs on the overall effectiveness is shown in Figs
7.16 and 7.17. As can be seen the effectiveness increased rapidly when one rib is used.
The sensible and latent effectiveness increased by 9% relative to the heat exchanger
without ribs. However, when the number of ribs was increased to two, both sensible and
latent effectiveness increased by about 4% relative to the single rib heat exchanger. The
effectiveness, values increased further by approximately 7% when the number of ribs
increased to three relative to the 2 ribs heat exchanger and by 5% when 5 ribs were used.
However, the increase in the effectiveness values became marginal when an 11-rib heat
exchanger is used as the effectiveness value increased by only 0.8% relative to the 5 ribs
design.
0.1
0.15
0.2
0.25
0.3
0.35
0.4
0.45
0.5
0.55
1 1.5 2 2.5 3 3.5
Face velocity (m/s)
Effectiveness
Sensible without ribs
Sensible 1 rib
Sensible 2 ribs
Sensible 3 ribs
Sensible 5 ribs (existing heat exchanger)
Sensible 11 ribs
Fig 7.16 Sensible effectiveness for 45gsm paper heat exchanger
using different number of ribs

145
0
0.05
0.1
0.15
0.2
0.25
0.3
0.35
1 1.5 2 2.5 3 3.5
Face velocity (m/s)
Effectiveness
Latent without ribs
Latent 1 rib
Latent 2 ribs
Latent 3 ribs
Latent 5 ribs (existing heat exchanger)
Latent 11 ribs
From the contour analysis and Figs 7.16 and 7.17 for sensible and latent effectiveness we
can conclude that increasing the number of ribs will make the temperature, flow and
moisture distribution throughout the heat exchanger more uniform. The recirculation
zones will be smaller hence heat and moisture transfer have improved. However,
increasing the number of ribs from 5 to 11 has only a minor effect on effectiveness as the
flow, temperature and moisture distribution are already uniform. Therefore, no significant
improvement is noticed when the number of ribs is increased to 11.
7.4 Effect of using L shape flow configuration heat exchanger
The effect of changing the heat exchanger flow profile on the heat exchanger
performance is investigated for an L shape flow configuration shown in Fig 7.18 using
Lewis correlation method. As can be seen with this new flow configuration the heat and
moisture transfer area consists of 50% counter flow and 50% cross flow. Consequently it
is expected that the effectiveness would increase relative to the Z shape heat exchanger.
Fig 7.17 Latent effectiveness for 45gsm paper heat exchanger
using different number of ribs

146
The temperature and moisture distribution contours shown in Fig 7.19 indicate that the
highest heat and moisture transfer occurred in flow path 1. Obviously it is due to the large
heat and moisture transfer area of this flow path in comparison with other flow paths. As
flow path 1 is longer than other paths (2, 3, 4, 5, and 6). In addition when the flow
changes direction from vertical flow to horizontal towards the outlet, that zone is located
adjacent to the cold air inlet in the adjacent frame and gradient in temperature and
moisture content is highest. Hence the amount of heat and moisture transfer is higher in
comparison with other flow path. As a result the temperature and moisture content
recorded were the lowest compared with flow paths 2, 3, 4, 5, and 6.
Fig 7.18 L shape heat exchanger

147
Fig 7.19 Hot and humid stream temperature, and moisture
contours for L shape heat exchanger (temperature in Kelvin,
and moisture content in kg/kg)

148
Similarly, the cold and less humid contours shown in Fig 7.20 shows the highest heat and
moisture transfer recorded at flow path 1.
Fig 7.20 Cold and less humid stream temperature, and moisture
contours for L shape heat exchanger (temperature in Kelvin and
moisture content in kg/kg)

149
Fig 7.21 shows that the sensible and latent effectiveness are both 4% higher for the L
shaped heat exchanger than the Z shape flow heat exchanger. That is attributed to the
increase in the counter flow area in comparison with the Z shape heat exchanger.
0
0.1
0.2
0.3
0.4
0.5
0.6
1 1.5 2 2.5 3 3.5
Face velocity (m/s)
Effectiveness
Sensible L shape heat exchanger
Latent Lshape heat exchanger
Latent Z shape heat exchanger
Sensible Z shape heat exchanger
7.5 Pressure drop
As mentioned in chapter 4, the pressure drop across the Z shape heat exchanger was
measured. FLUENT was also used to predict the pressure drop through the different heat
exchangers. Fig 7.22 shows that the CFD predicted and measured pressure drop are in
reasonable agreement. Hence the CFD code (FLUENT) is used to predict the pressure
drop that applies when the number of ribs is varied.
Fig 7.21 Sensible and latent effectiveness for L shape and Z
shape heat exchangers

150
0
50
100
150
200
250
300
350
400
450
500
1 1.5 2 2.5 3 3.5
Face Velocity (m/s)
PressureDrop(Pa)
Measured pressure drop
Predicted pressure drop (CFD)
As can be seen in Fig 7.23 the heat exchanger with no ribs has the lowest pressure drop,
and the pressure drop increases as the number of ribs increased and the highest pressure
drop was predicted when 11 ribs are used.
0
50
100
150
200
250
300
350
400
450
500
1 1.5 2 2.5 3 3.5
Face velocity (m/s)
Pressuredrop(Pa)
Zero rib Press Drop
Single rib Press Drop
2 ribs Press Drop
3 ribs Press Drop
5 ribs Press Drop
11 ribs Press Drop
Fig 7.22 Measured and CFD predicted pressure drop through Z
shape existing heat exchanger
Fig 7.23 Predicted pressure drop through Z shape heat
exchanger with different number of ribs

151
In conclusion, although increasing the number of ribs increase the heat exchanger
sensible and latent effectiveness (Figs 7.16 and 7.17); the increase in the number of ribs
results in an increase in pressure drop. Figs 7.17 and 7.18 show that increasing the
number of ribs from 5 to 11 results in only minor increase in the effectiveness. However,
the increase in pressure drop was significant (30 Pa). The value of the increase in
effectiveness with increasing number of ribs depends on the relative cost of the heat and
moisture transfer and the cost of increasing the frames. From the results presented here it
is clear that increasing the number of ribs above 5 would result in a nil benefit.

Chapter 8: Annual Energy Analysis
152
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8.1 Introduction
The research presented in this chapter is directed at the investigation of annual
performance for an air conditioner coupled with an enthalpy heat exchanger which
supplies 100% fresh air. The combined air conditioner and enthalpy heat exchanger is
compared to a conventional air conditioning system that operates based on mixing of
fresh air with the room exhaust air.
The most accurate way to determine the performance of an air conditioner is to use a
calorimeter measurement. However, these measurements are costly and time consuming
(Morrison, 2004). Therefore, research on heat pumps is often based on computer
simulation programs based on energy and thermodynamic equations of the refrigeration
and air cycles and performing energy balance for the system. Most of the previous
research has been based on fixing the air set point conditions in order to simplify the
computer simulation (Niu and Zhang (2001), Zhang et al. (2005) and Zhang (2006)).
However, in real air conditioning cycles the air conditions exiting the evaporator and
condenser change according to the ambient air conditions. For the above research when
an enthalpy heat exchanger was incorporated into a performance modelling programme,
sensible effectiveness of 0.9 is used for the heat exchanger (Zhang 2006). In fact for
enthalpy heat exchangers, achieving an effectiveness of 0.9 requires the use of a very low
air velocity which means the heat exchanger face area has to be very large.
Unfortunately, Zhang (2006) did not give the size of the heat exchanger used in his
simulation.

153
From their computer simulation they obtained the energy consumption by assuming the
compressor efficiency. To determine the efficiency of an air conditioner that incorporates
an enthalpy heat exchanger, Zhang (2006) performed a similar simulation for an air
conditioning system which uses 100% fresh air. Their energy analysis shows that a
system that incorporates an enthalpy heat exchanger consumes less energy than a system
that uses 100% fresh air without an energy recovery device. Unfortunately, no attempt
was made to model a conventional air conditioning system that operates based on mixing
of fresh air with room exhaust air which is widely used in air conditioning.
Therefore, the need arises for a method for assessing the performance of various
combinations of energy recovery devices with a standard air conditioner under varying
operating conditions throughout the year. Australian standard AS 3823.3 specifies a
method of performance evaluation using a computer simulation tool such as HPRate.
HPRate is a performance rating tool that evaluates the performance of vapour
compression air conditioning cycles (Morrison 2004). The HPRate simulation package is
a graphical interface to the ORNL MarkV heat pump model developed by the Oak Ridge
National Laboratory Tennessee for the USA Department of Energy. The program predicts
the steady state performance of electrically driven, vapour compression, air to air heat
pumps in both heating and cooling modes. It consists of FORTRAN model of the heat
pump components.
The model is based on underlying physical principles and generalised correlations in
order to make the program applicable to a wide range of equipment configurations. The
basic model does not incorporate empirical correlations derived for particular products. A
first principles thermodynamic model of the heat transfer processes in the coils and
analysis of the refrigerant states around the circuit are combined with psychometric
analysis of the air side of the coils to determine the operating state and provide an
assessment of equipment performance.

154
Transient (cyclic or frosting/defrosting) effects are not considered and the program has
physically based heat transfer models for single and two phase refrigerant regions of fin –
and-tube air to refrigerant heat exchangers. Parallel and series refrigerant circuiting is
evaluated and air-side dehumidification and evaporator sensible heat supply are
calculated.
The features of the model adopted within the HPRATE graphical front end allow the user
to specify system operating conditions such as indoor and outdoor air wet and dry bulb
temperatures and the arrangement of the compressor and fans in the air flow stream.
Compressor characteristics, refrigerant flow control devices, specified refrigerant sub-
cooling at the condenser exit, capillary tube or TX valve, fin and tube heat exchangers,
tube size, spacing, number of rows and parallel circuits, fin pitch, thickness, material,
type of fin (smooth, wavy or louvered), air flow rates, refrigerant lines, lengths, diameters
of interconnecting pipes, and heat losses from suction and discharge liquid lines are
modelled in HPRate.
The main restriction in the current model is that the user cannot specify the refrigerant
charge; instead it is assumed that the system is charged with the correct amount of
refrigerant for the specified operating conditions.
The HPRate code was modified to model an air conditioner which includes the effect of
adding a sensible and latent heat recovery heat exchanger to a conventional air
conditioning system. HPRate was combined with a model of an office space in order to
determine the transient operating states of the heat exchanger/air conditioner throughout
the year. HPRate was used to evaluate the cooling capacity, power consumption and
energy efficiency ratio on a 5 minute time step throughout the year. The HPRate model
was used to simulate off design performance so that the annual performance of a
combined cooling/heating system could be determined.
This chapter outlines the modifications that were made to HPRate to evaluate the annual
energy consumption of an air conditioner that utilises an enthalpy heat exchanger to

155
cool/heat an office space. HPRate was modified to read hourly weather data for ambient
temperature and humidity. By using the enthalpy heat exchanger effectiveness equations
the condition of air that exits the heat exchanger and then enters the air conditioning unit
is obtained and HPRate is used to compute the air-off conditions that leaves the
evaporator coil and enters the office space. The new model calculates the exhaust air
condition that exits the office space before the air enters the enthalpy heat exchanger
through using energy balance equations for the room; HPRate also computes the energy
consumed by the air conditioner. HPRate is also used to model a conventional air
conditioner which operates based on mixing of 65% room exhaust air with 35% of fresh
air. The details of HPRate modelling and code development are presented in this chapter.
8.2 HPRate flow chart and subroutines
The Mark V Oakridge model adopted by HPRate consists of a series of FORTRAN
subroutines that have been compiled into an executable file known as oakunsw.exe. The
simulation process starts by reading system specifications from the input file (simfile.in)
and outputs its results to two files: simfile.ou and simfile.gr (Fig 8.1), where simfile.gr
allows the visual basic front end of HPRate to display the conditions around the heat
pump refrigerant circuit including pressure, temperature, saturation temperature and
enthalpy.
The executable file of oakunsw.exe contains the subroutines shown in Fig 8.2
HPRate Simfile.in
oakunsw
Simfile.o
Simfile.g
Created
Fig 8.1 Relationship between HPRate and oakunsw

156
The program CONDRV is responsible for getting the air conditioner data from simfile.in
which is represented by the block HPDATA in Fig 8.2, calling appropriate subroutines to
convert values into imperial units and performing calculations on the compressor,
evaporator and the condenser iteratively. The following subroutines are the major
components of CONDRV (Morrison, 2002):
8.2.1 DATAIN
In DATAIN, the information contained in simfile.in is read into the subroutine and
subsequently printed on the output file simfile.ou.
8.2.2 TABLES
In TABLES, the transport and thermodynamic properties of R22 refrigerant are
developed. Similarly, these values are stored in BLOCKDATA for use in evaporator and
condenser routines.
CONDRV
SUMRPT
SSDRVCALCTABLESDATAIN
OUTPUT
BLOCK DATA MOGEDN
HPDATA
HX
DISPLAY
Fig 8.2 Flow chart of oakunsw

157
8.2.3 HX
Based on the dry bulb and wet bulb temperatures and flow rates of air entering the
condenser and evaporator, various properties such as the overall heat transfer coefficient
(U) are determined.
8.2.4 CALC
In CALC, the geometry related data of the evaporator and condenser are being computed.
This data includes the total heat transfer surface for air and refrigerant, frontal area and
length of the heat exchanger tubing.
8.2.5 SSDRV
SSDRV stands for the steady state driver where the majority of the calculations are
performed. Data such as the evaporator and condenser air-off conditions are determined.
Furthermore, the performance related data such as the cooling capacity, total input power
of the system and energy efficiency ratio (EER) are also determined in this subroutine.
The subroutine DISPLAY is also included in SSDRV to create the output file as simfile.gr.
The function of simfile.gr is to allow the visual basic front end of HPRate to artificially
display the conditions around the heat pump refrigerant circuit including pressure,
temperature, saturation temperature and enthalpy.
8.3 Accuracy assessment
Several studies have been conducted on air conditioners to assess the accuracy of HPRate
in term of its cooling capacity, power consumption and energy efficient ratio prediction
(Morrison 2004).
For standard air conditioner operation, the prediction of air conditioner operation were
found to have deviations from measured conditions of 2.6% in cooling capacity, 1.7% in
power consumption and 2.8% for EER (Morrison 2004).

158
In general, the predictions generated by HPRate are in close agreement with the measured
values. Therefore, HPRate is used in conjunction with the FORTRAN code model
developed by the author to evaluate the combination of an enthalpy energy heat
exchanger and an air conditioner used for cooling/heating of an office space.
Two systems were studied, the first is an air conditioning system coupled with an
enthalpy heat exchanger. The second system is a conventional air conditioning system
which operates based on mixing of 35% of fresh air mixed with 65% room exhaust air
(Fig 8.3). For both systems 1000L/s air flow is supplied to the evaporator and 1500L/s is
supplied to the condenser, However, for the enthalpy heat exchanger system 1000L/s
room exhaust air is mixed with 500L/s ambient fresh and supplied to the condenser coil.
For the conventional system 350L/s room exhaust air is mixed with 1150L/s ambient
fresh air and supplied to the condenser.

159
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8.4 Code development
HPRate is used to study the annual performance of an air conditioner that incorporates an
enthalpy heat exchanger. As mentioned previously HPRate is designed to predict the
cooling and heating performance of a standard air conditioner and in this study the
HPRate model is modified to include the membrane heat exchanger in the system. The
original HPRate code was designed to quantify the performance of air conditioner at
standard AS 38523 rating point conditions. In the code developed here, HPRate has been
extended to model air conditioner performance throughout a year for variable operating
Fig 8.3 Schematic diagrams of enthalpy heat exchanger
and conventional air conditioning systems

160
conditions specified by ambient temperature and humidity in standard typical
meteorological year weather files for the location of interest (Morrison and Litvak, 1988).
The new code reads the hourly weather data (dry and wet bulb temperature) for any city
around the globe presented in the typical meteorological year (TMY) format for
evaluation of an air conditioner coupled with enthalpy energy recovery system.
FORTRAN was selected as the platform of code development due to the fact that
oakunsw model was written in FORTRAN and its computational power is fast. A
FORTRAN model will allow the communication link between this code and Mark V
Oakridge model to be established easily.
The modelled HPRate code reads the hourly weather data and interpolates for shorter
time steps to achieve high sensitivity in the system modelling. Under this simulation, the
modelled HPRate code loops through 8760 hours of the weather data and at each hour the
weather data was interpolated into 5 minute time steps. As the energy recovered is
significantly affected by the heat exchanger effectiveness, the heat exchanger
effectiveness determined from the mathematical model to obtain the air-on conditions
supplied to the condenser and evaporator. For given outdoor conditions, the annual
energy consumed by the air conditioner to cool/ heat any room can be determined.
In situations when the temperature of the supplied air to the air conditioner is between
24°C and 18°C, the air conditioner compressor is turned off and the heat exchanger acts
as a passive cooling or heating device for the room. Since the air conditioner compressor
is not operating under these conditions, the simulated result in terms of energy
consumption will be the energy consumed to operate the fans only. If the air conditioner
is turned off most of the time, then the energy recovered will be high. This is because
cooling and heating can be achieved without operating the compressor which consumes a
large amount of energy.
To enable HPRate to execute the above tasks, the following subroutines and
modifications were developed and included in the simulation package:

161
8.4.1 GETDAT subroutine
Annual weather data presented in typical meteorological year (TMY) format is used in
this simulation. The GETDAT subroutine, the dry and wet bulb temperatures of the
outside air are read and stored in the real variables Ta and Twet respectively.
Subsequently, these variables are passed as arguments to the rest of the program.
8.4.2 INTERP subroutine
As the weather data is available in the hourly format, the data must be interpolated for
shorter time step analysis. The analysis of the operation of the heat exchanger and air
conditioner is carried out at 5 minutes intervals in order to follow the time averaging
operating conditions and to model air conditioner ON/OFF cycling. The air conditioner is
turned OFF when the air temperature that enters the evaporator coil is in the range 18-
24°C.
8.4.3 ERV subroutine
To incorporate energy recovery devices such as enthalpy heat exchanger in the program
algorithm of HPRate, a subroutine known as ERV was written to incorporate the enthalpy
heat exchanger effectiveness. The hourly weather temperature is read in GEDAT and
interpolated into 5 minute time steps in INTERP subroutine. The temperature is then read
into the ERV subroutine and the air conditions exiting the heat exchanger are determined
from the following equations 8.1 to 8.4 as shown in Fig 8.4.
( )evap a s a roomT T T Tε= − − (8.1)
( )cond room s a roomT T T Tε= + − (8.2)
( )evap a L a roomω ω ε ω ω= − − (8.3)

162
From the above equations, the air conditioner inlet air conditions to the coils are obtained.
( )evap a s a roomT T T Tε= − −
( )evap a L a roomω ω ε ω ω= − −
ω
ω
roomω ( )cond room s a roomT T T Tε= + −
( )cond room L a roomω ω ε ω ω= + −
aω
In order to model a conventional air conditioner that operates based on mixing of 35%
fresh air with 65% room exhaust air, the ERV subroutine will calculate the air
conditioner air-on conditions from the following equations
air on room ambient=(0.65 )+(0.35 )ω ω ω (8.5)
room room room roomh =(1.005T )+( (2501+(1.83T )))ω (8.6)
ambient ambient ambient ambienth =(1.005T )+( (2501+(1.83T )))ω (8.7)
air on room ambient=(0.65 )+(0.35 )h h h (8.8)
hence the air conditioner air-on temperature is obtained as follows
air on air on air on air onT =(h -(2501 ))/(1.005+(1.83 ))ω ω (8.9)
If the air-on temperature entering the air conditioner is less than 18o
C, the operation
mode of the heat pump will be changed to heating mode. However, if the air-on
temperature is higher than 240
C, the operation mode is switched to cooling mode.
As mentioned earlier the subroutine CONDRV reads equipment input data from
simfile.in which is represented by the block HPDATA in Fig 8.2, calls the appropriate
( )cond room L a roomω ω ε ω ω= + − (8.4)
Fig 8.4 Data flow of ERV.for

163
subroutines to convert values into imperial units and performs calculations of the
compressor, evaporator and the condenser performance iteratively. A subroutine called
MODSIM was written to perform the function of a real time updating mechanism which
the air-on air conditions leaving the enthalpy heat exchanger or the air mixing zone and
entering the air conditioner will be transferred through the MODSIM subroutine and
modify the file simfile.in as per the hourly weather data air conditions and update the
operating mode (heating or cooling mode).
The operation of the modified HPRate code is represented in the flow chart shown in Fig
8.6. The rectangular box represents process, the parallelogram represents data input and
the rhombus represents decision making. Each process is executed by a subroutine shown
in oval shape box adjacent to the process box.

164
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165
After modifying simefile.in, HPRate performs the simulation based on the supplied air
conditions (air-on conditions). This analysis is continued throughout the year using the
five minute time step weather data.
Room temperature is calculated from energy balance on the space as follows:
The cooling/heating provided by air conditioner
cooling/heatingQ = ( )air pair room evapm C T T− (8.10)
The heat transfer through the walls is
heatQ = ( )office ambient roomAU T T− (8.11)
By equating the above equations and adding the sensible load in the room the temperature
is obtained as follows
heat coolingQ =Q loadQ+ (8.12)
substituting 8.10 and 8.11 into 8.12, the space temperature is given by
ambient air p air evap Load
room
air p air
AUT m C T Q
T =
m C AU
+ +
+
(8.13)
To enable the FORTRAN code to perform the first calculation where the room air
conditions are unknown, it was assumed that for the first 5 minutes the room temperature
and relative humidity are 24 °C and 50% respectively. The hourly ambient dry and wet
bulb temperature is read in GETDAT subroutine and interpolated into 5 minute time
steps in INTERP subroutine. From psychometric calculation, the ambient moisture
content is obtained. The ambient air temperature and moisture content is then read in the
ERV subroutine. When the enthalpy heat exchanger is used, the heat exchanger
effectiveness equations are incorporated in the subroutine (equations 8.1 to 8.4). In the
case where air mixing process is used (35% fresh air mixed with 65% room exhaust air)
the air mixing equations are incorporated into the subroutine (equations 8.5 to 8.9).
Hence the conditions of air entering the evaporator and condenser are obtained.
The MODSIM subroutine functions as a real time updating mechanism and transfers the
air-on conditions leaving the enthalpy heat exchanger or the air mixing zone and entering

166
the air conditioner to the file simfile.in together with the hourly weather data air
conditions and operating modes (heating or cooling mode). The CONDRV subroutine
then reads data from simfile.in and performs calculations of the compressor, evaporator
and the condenser performance iteratively.
From CONDRV, the air temperature and moisture content at the condenser and
evaporator outlets are obtained. Using equation 8.13 which is incorporated in CONDRV,
the room temperature and moisture content is calculated for the next 5 minute time step.

Chapter 9: System Energy Analysis Results
167
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9.1 Introduction
The details of HPRate modelling of an air conditioner that utilises an enthalpy heat
exchanger and an air conditioner that operates based on air mixing were presented in
chapter 8. The aim of this chapter is to study the annual energy consumption for these
systems and to perform a comparison on the annual energy use for cooling and heating of
each system in different locations. The last part of this study is extended to evaluate the
energy consumption of an air conditioner for a range of enthalpy heat exchanger face
areas.
9.2 Simulation performance of air conditioner and enthalpy heat exchanger
HPRate simulation was performed for Sydney and Kuala Lumpur weather conditions.
The weather in Sydney is moderate, while the weather in Kuala Lumpur is hot and
humid. The simulation was performed for an air conditioning system coupled with an
enthalpy heat exchanger and a conventional air conditioning system based on air mixing.
In cases where the air temperature entering the evaporator is between 24 and 18°C, the
compressor is switched off and the heat exchanger or the air mixing zone will then act as
a passive cooling or heating device for the room. Under these conditions when the air
conditioner compressor is not operating, the simulated result in terms of energy
consumption will be the energy used to operate the evaporator and condenser fans only.
The analysis is conducted for an office space of 300 m2
area for operating hours from 9
am till 6pm and for an internal load of 1kW. The AU value of the building envelope used
was 2kW/K.
In this simulation the air volumetric flow rate supplied to the evaporator is 1000 L/s and
1500L/s is supplied to the condenser (chapter 8 Fig 8.3) and the refrigerant used by

168
HPRate is R22. Enthalpy heat exchanger inlet stream face area is 3.3m2
and air face
velocity of the heat exchanger is 0.3m/s. The enthalpy heat exchanger sensible, total and
latent effectiveness for an air face velocity of 0.3m/s were 0.71, 0.66 and 0.61
respectively. The effectiveness was obtained from the 60gsm paper heat exchanger
effectiveness curves shown in chapter 5, Fig 5.9.
The evaporator and condenser specification are shown in Fig 9.1
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The compressor specifications are shown in Fig 9.2
Fig 9.1 Evaporator and condenser size and components

169
The simulation results are presented as follows:
9.3 Annual energy analysis of an air conditioner for Sydney
HPRate simulation of an air conditioner coupled with an enthalpy heat exchanger and
conventional air recirculation air conditioner is performed using Sydney hourly weather
data. Energy consumption of the air conditioner obtained from the above simulation is
presented in Fig 9.3 and shows that the air conditioning system that utilises an enthalpy
heat exchanger consumes less energy than the conventional air conditioning system that
operates based on air mixing. The enthalpy air conditioner has achieved lower operating
cost while simultaneously providing 100% fresh air.
Fig 9.3 shows that when the weather is hot and humid in summer and the sensible and
latent cooling load is high, the amount of energy consumed by enthalpy heat exchanger
system was 5%, 8.3% and 4.6% less in December, January and February respectively
than a conventional air conditioning system.
Fig 9.2 Compressor details and capacity

170
Similarly in March the air conditioning system coupled with an enthalpy heat exchanger
consumes less energy than the conventional system. Whereas in April, the amount of
energy consumed recorded its lowest values, the energy consumption for both systems
was almost the same and that is due to the moderate weather.
Fig 9.3 also shows that the energy consumption started to increase in winter season (from
May till July) as the weather became colder and heating load becomes higher.
Nonetheless, the system coupled with enthalpy exchanger system consumes 6.4% less
energy than the conventional reverse cycle air conditioning system.
When spring season began, the energy consumption decreases and the air conditioning
system coupled with enthalpy heat exchanger continue to consume less energy. However,
the energy consumption difference between both systems was less in the winter heating
season than in the summer cooling season.
0
0.5
1
1.5
2
2.5
3
3.5
4
4.5
5
Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec
Month
Energyconsumptionbyanairconditioner(GJ)
Air mixing (conventional system)
Membrane heat exchanger
8.3%
4.6%
7.1%
0.2%
5%
3.7%
6.4%
3.5%
1.7% 0.1%
0.1%
5%
Seasonal energy analysis shows that the energy saving recorded by an air conditioning system
coupled with an enthalpy heat exchanger in winter season was 4.7% less than
conventional air conditioning system (Fig 9.4). In summer the humidity and temperature
Fig 9.3 Sydney monthly energy consumption for reverse cycle air
conditioner (figures show difference in energy used by the two systems)

171
increase in Sydney, hence, the heat exchanger acts as both an energy recovery and
dehumidifying tool which will reduce the latent load. Consequently, in summer, energy
consumption of an air conditioning system coupled with enthalpy heat exchanger was
6.2% less than the conventional system.
This shows the importance of utilising the enthalpy heat exchanger in an air conditioning
system as an energy recovery and dehumidifying tool to reduce the latent load while
simultaneously providing 100% fresh air.
0
2
4
6
8
10
12
Winter Spring Summer Autumn
Season
4.7%
1%
6.2%
4.7%
9.4 Annual energy analysis of an air conditioner for Kuala Lumpur
In a tropical climate like Kuala Lumpur, the weather is hot and humid throughout the
year and the latent load is high. Fig 9.5 shows the annual monthly energy consumption is
almost the same throughout the year. However, it can be seen that the air conditioning
system coupled with an enthalpy heat exchanger consumes less energy than the
conventional air conditioning system. The enthalpy exchanger system consumes between
5.7 to 9% less energy than the conventional system resulting in energy saving throughout
Fig 9.4 Sydney seasonal energy consumption for
reverse cycle air conditioning systems

172
the whole year. This is due to the hot and humid climate in Kuala Lumpur throughout the
year, where the amount of energy required to dehumidify the air by an air conditioner is
large. Hence, utilising an enthalpy heat exchanger to dehumidify the air before it enters
the air conditioning system will contribute significantly in reducing the latent load,
resulting in energy saving.
0
1
2
3
4
5
6
7
8
Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec
Month
Air mixing (conventional)
7.3% 6.3%
6.9%
6.8%
5.7%
6% 7% 6.8%
8.8%
7.3%
9%
7.6%
HPRate simulation and energy analysis were then performed on different cities such as
London, Miami, Tokyo and Dubai (the detailed monthly and seasonal energy
consumption for these cities are presented in appendix E).
The summary of the total annual energy analysis shown in Fig 9.6 illustrates that the
highest annual energy consumption recorded was in Kuala Lumpur. Where, using
enthalpy heat exchanger system resulted in 4.9GJ energy saving in comparison with the
conventional air conditioning system.
In Miami, utilising enthalpy heat exchanger in an air conditioning system has recorded
4.23GJ energy saving. In Dubai, due to the hot and humid climate in spring, summer and
Fig 9.5 Kuala Lumpur monthly energy consumption for
reverse cycle air conditioner

173
autumn, enthalpy heat exchanger system annual energy consumption was 3.12GJ less
than the conventional system.
In Tokyo, the annual energy saving was 1.61GJ. Although the annual energy
consumption in Sydney was the lowest in comparison with other cities, however air
conditioning system coupled with enthalpy heat exchanger consumes 1.36GJ less than the
conventional air conditioning system.
In London, the annual energy consumption was relatively high due to the cold climate.
Nevertheless, an air conditioning system coupled with an enthalpy exchanger consumes
1.16GJ less than the conventional air conditioning system.
0
10
20
30
40
50
60
70
80
Sydney London Miami Kuala Lumpur Dubai Tokyo
1.36 GJ
1.16 GJ
4.23 GJ
4.9 GJ
3.12 GJ
1.61 GJ
The above energy analysis shows that an air conditioning system coupled with an
enthalpy heat exchanger performed well in terms of energy consumption in comparison
with conventional air conditioning system in all locations investigated.
Fig 9.6 Annual energy consumption for reverse cycle air conditioner
(figures show the energy difference between the two systems)

174
In addition to the sensible energy recovered, the enthalpy heat exchanger also decreases
energy consumption in hot and humid climate by reducing the latent load where the heat
exchanger dehumidifies the air before it enters the air conditioning system, causing a
decrease in energy consumption. Hence, the decrease in energy consumption was higher
in hot and humid climates like Miami, Kuala Lumpur and Dubai. This shows the
importance of reducing the latent load to achieve lower energy consumption.
To study the effect of varying the heat exchanger face area on energy consumption,
Kuala Lumpur weather data was used as a bench mark to perform this investigation since
enthalpy heat exchanger performs well and consumes less energy in a hot and humid
climate.
In this study the energy saving is calculated as the difference between the energy
consumption of an air conditioner that incorporates an enthalpy heat exchanger and a
conventional air conditioner that operates based on air mixing
saving
= Enthalpy exchanger system conventional system
E E E− (9.1)
The area ratio (Aratio) shown in Fig 9.7 represents the ratio of the enthalpy heat exchanger
face area to the face area of the evaporator coil (0.5m2
). Fig 9.7 shows as the enthalpy
heat exchanger face area increases, the amount of energy saved increases. As increasing
the heat exchanger face area will decrease the air velocity and subsequently the heat
exchanger effectiveness has increased.

175
0
1
2
3
4
5
6
0 1 2 3 4 5 6 7 8
A ratio
Esaving(GJ)
Air face velocity
1.5 m/s
Air face velocity
0.5 m/s
Air face velocity
0.7 m/s
Air face velocity
1 m/s
It can be seen that a substantial amount of energy is saved when the enthalpy heat
exchanger is incorporated in an air conditioner especially in tropical climates. In addition
to the energy saving, an air conditioner coupled with an enthalpy heat exchanger also has
the advantage of providing 100% fresh air which significantly improves indoor air
quality.
Fig 9.7 Effect of changing enthalpy heat exchanger face area on annual energy
saving in Kuala Lumpur (air face velocity indicated on top of each point)

Chapter 10: Conclusions and Recommendations
176
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10.1 Conclusion
This thesis evaluated the performance of an enthalpy Z type flow fixed-plate air-to-air
heat exchanger used to recover both sensible and latent heat in HVAC systems. The heat
exchanger performance was evaluated experimentally and numerically.
It was found that the heat exchanger performance was significantly influenced by the heat
exchanger configuration (cross flow and counter flow), flow profile, heat and moisture
transfer area, inlet area, inlet air velocity, heat and moisture transfer material
characteristics and inlet air conditions (air moisture content).
To study the above parameters on the enthalpy heat exchanger performance, experimental
investigations were carried out using laboratory scale test rig to determine the
effectiveness of the heat exchanger with various air velocities. Several materials were
used in this investigation, including thin 45gsm and 60gsm porous paper.
It was found that sensible effectiveness was the same for both papers. This is attributed to
the small effect of the conduction thermal resistance of the heat transfer surfaces due to
the small thickness of the paper surfaces. However, the latent effectiveness was different
where up to 28% increase in the latent effectiveness was achieved when 60gsm paper was
used. This is attributed to the significant effect of the moisture resistance of the paper
which has a considerable effect on the moisture transfer and consequently latent heat
transferred.

177
It was also found that reducing air velocity will cause an increase in the enthalpy heat
exchanger effectiveness. Which is due to the air resident time in the heat exchanger, the
more resident time the air is given, the more heat and moisture transfer is allowed to take
place. It was observed that as the velocity of the air flow decreases, higher effectiveness
values were recorded.
The use of experiments to study the effects of varying the design and operating
parameters on the performance of the enthalpy heat exchanger is expensive and time
consuming. Therefore, numerical studies were undertaken to develop mathematical
models using effectiveness-NTU method and Nusselt and Sherwood number correlations
to be used as a design aid to predict the heat exchanger performance when the heat
exchanger design parameters are changed. The outcomes from the experimental
measurements were used as benchmark cases to validate the results from numerical
simulations.
Due to the substantial effect of moisture transfer resistance of the paper on the heat
exchanger latent performance, permeability measurements were undertaken according to
the ASTM standard E 96-00 requirements.
The experimental permeability measurements show that unlike the conduction thermal
resistance which remain constant under different conditions, the membrane moisture
transfer resistance is influenced by the membrane material and operating conditions. The
measurements also show that moisture transfer resistance of 45gsm paper was around
50% higher than the 60gsm paper. Hence higher latent effectiveness values were
achieved when 60gsm paper was utilised.
The mathematical model was then used to study the effect of decreasing the heat
exchanger flow path hydraulic diameter on the heat exchanger performance. It was found
that reducing the heat exchanger flow path width by 30% has boosted the latent and
sensible effectiveness by around 20%. Decreasing the flow path width decreases the air
mass flow rate and this increases the Number of Transfer Units (NTU) which resulted in

178
an increase of effectiveness. However, this increase was achieved at the expenses of
increasing pressure drop through the heat exchanger.
The mathematical model was also used to predict the effectiveness of another Z shape
heat exchanger which has 13% less counter flow heat and moisture transfer area than the
existing Z type heat exchanger. The result shows that the sensible and latent effectiveness
decreased by around 6% in comparison with the existing Z type flow heat exchanger.
Understanding the performance of the enthalpy heat exchanger requires in depth
knowledge the temperature and moisture distribution in the heat exchanger. Therefore,
this research was extended to perform numerical simulation modelling study using a
Computational Fluid Dynamics (CFD) package, FLUENT. However, the available CFD
packages such as FLUENT suffer from limitations when it comes to modelling moisture
diffusion across a porous boundary. The shortcoming of this software is that it cannot
model the moisture diffusion through porous materials. Therefore, two methods have
been introduced to model the moisture transfer in the heat exchanger. Firstly, a non-
dimensional sensible-latent effectiveness ratio was used to determine the moisture
content at the paper boundary. The second method in modelling the moisture transfer in
the heat exchanger is to utilise Lewis number correlation to obtain the moisture boundary
conditions at the paper heat exchanger surface. Both methods were validated against the
experimental results and reasonable agreement was achieved.
The existing Z shape heat exchanger flow paths consists of 5 flow dividers ribs which
provide more uniform flow distribution in the heat exchanger The developed CFD
methods were used to study the effect of varying the number of flow dividers ribs on the
heat exchanger performance.
It was found that a 21% increase in the effectiveness was achieved when the number of
ribs was increased from no ribs to 5 ribs. Increasing the number of ribs contributed
significantly to making temperature, flow and moisture distribution more uniform
throughout the heat exchanger. However, increasing the number of ribs from 5 to 11 have

179
only minor effect on effectiveness as the flow, temperature and moisture distribution are
already uniform. Therefore, no significant improvement is noticed when the number of
ribs is increased beyond 5.
The effect of changing the heat exchanger flow profile on the heat exchanger
performance was also investigated. The L shape flow configuration heat exchanger was
modelled which has a larger counter flow area than the Z flow heat exchanger. The result
shows a 4% increase in the sensible and latent effectiveness is achieved in comparison
with the existing Z shape flow heat exchanger.
The effective utilisation and annual performance of an air conditioner coupled with
enthalpy heat exchanger was investigated in relation to a conventional air conditioning
system that operates based on mixing of fresh air with the room exhaust air. Performing
annual experimental investigation on a real air conditioner to study the annual energy
consumption for both enthalpy heat exchanger and conventional system is expensive and
time consuming. Therefore, HPRate software which is performance rating software that
is able to predict the steady state heating and cooling performance of a vapour
compression, electrically driven, air to air reverse cycle heat pumps was used to carry out
the investigation. The annual performance investigation was achieved by developing a
modelled version of HPRate which reads the yearly weather data of different cities
around the globe, and incorporates the enthalpy heat exchanger effectiveness functions.
Energy analysis shows that an air conditioning system coupled with an enthalpy heat
exchanger performed well in hot and humid climates and contributed significantly in
reducing the latent load where systems coupled with enthalpy exchangers consumed 8%
(4.9GJ) less energy throughout the year than the conventional air conditioning system in
Kuala Lumpur. Similarly for Miami and Dubai, energy analysis shows that an air
conditioning system coupled with enthalpy heat exchanger consumes 8% (4.23GJ) and
5% (3.12GJ) less energy than the conventional air conditioning system. Whereas, in a
moderate climate like Sydney, systems coupled with enthalpy heat exchanger consumed
4% (1.36GJ) less energy than the conventional air conditioning system.

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