Volume 3, Issue 5, May – 2018 International Journal of Innovative Science and Research Technology

ISSN No:-2456-2165

Numerical Investigation of Ejectors for Ejector

Refrigeration System
Likhitha R Reddy
Department of Mechanical Engineering
R V College of Engineering

Abstract:- This paper presents the numerical analysis

performed on ejectors to optimize operating conditions like
evaporator temperature, condenser temperature and
generator temperature. R245fa was the working fluid used.
Parametric analysis was performed to study the effect of
mixing chamber geometry on ejector performance which
has direct impact on coefficient of performance of ejector
refrigeration cycles. Results show that operating conditions
and geometric parameters have a value or range of values
for which entrainment ratio of ejector is maximum.

Keywords:- Ejector, entrainment ratio, CFD, ANSYS,

optimization, operating conditions .

I. INTRODUCTION

The jet refrigeration cycle is like conventional Fig 2:- A schematic representation of an ejector
refrigeration cycle; all the basic system components are the
same except that the compressor is replaced by a sub-system Referring to Figure 1, the ejector refrigerator operates
made up from a liquid feed-pump, a vapour generator, and the as follows: heat is absorbed by the generator and this causes
ejector. The ejector is used to compress refrigerant vapour liquid refrigerant to be vaporised at a high pressure. This vapor
from the evaporator pressure to the condenser pressure. The (mp) is fed to the primary nozzle of the ejector, (shown in
generator is used to produce high pressure vapour to drive the Figure 2), through which it is accelerated to supersonic
ejector and the feed-pump is used to return liquid refrigerant velocity. At the nozzle exit, a jet is formed, which entrains the
coming from the condenser to the vapour generator. suction or secondary stream (ms) coming from the evaporator.
The primary and secondary streams combine within the
mixing section. The kinetic energy of this combined stream is
transformed into pressure energy in the diffuser section of the
ejector from where the combined vapor stream is fed to the
condenser [Eames et al (1995b)]. The heat of condensation is
rejected to the environment via the condenser and part of the
resulting condensate is fed back to the generator via feed-
pump whilst the remainder is expanded, via a throttling valve,
to the evaporator where it absorbs heat at low temperature,
causing it to vaporise and produce the desired refrigeration
effect.
A. Description of Ejectors
Fig 2 shows a schematic structure of an ejector. The
high-pressure gaseous working fluid is sent to ejector and pass
through the nozzle section. While passing, the gas is
accelerated and expands with decreasing pressure. The
supersonic primary flow becomes supersonic. As the pressure
of the primary flow is lower than the pressure in evaporator,
the working fluid in the evaporator flows as the secondary
flow at supersonic speeds.

In the suction chamber of ejector, the primary and

Fig 1:- A schematic representation of ejector refrigeration
secondary flows begin mixing and in the mixing section the
System two flows are mixed completely. In the diffuser, this mixed
flow raises its own pressure with a transverse shockwave, and
Figures 1. and 2. provide schematic representations of
enter into condenser. In condenser, the working fluid changes
an ejector refrigeration system and of the ejector, respectively.
from gaseous state to liquid state. The liquid is sent to
generator by pump. Power consumption by pump is small,

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Volume 3, Issue 5, May – 2018 International Journal of Innovative Science and Research Technology
ISSN No:-2456-2165
which can be provided by photovoltaic cells. Some of the the simulations for lesser memory requirements and less
liquid is sent to evaporator through expansion valve. computational time

In evaporator, the liquid working fluid evaporates at

lower pressure and absorbs heat from the ambient. Advantage
of this cycle is that the cycle is activated by heat input, even if
low grade thermal energy at about 600C. Therefore, heat
resources such as solar thermal energy, geothermal energy and
exhaust heat from factories etc. can be effectively utilized.
And, ejector itself is simple, so this cycle would require only
light maintenance.
B. Ejector performance
Eames et al (1995b) defined the coefficient of
performance (COP) of a jet-pump refrigerator as:
Fig 3:- 3D ejector model, modeled in Solidworks

[1-1]

The power absorbed by the circulation pump is

typically less than 1% of the heat supplied to the generator and
thus it is usually ignored to simplify thermodynamics
calculation. Therefore, for the calculation of overall system
performance, COP, equation [1-3] is used:

Fig 4:- 1/4th symmetry model of ejector

Fig 5:- Axisymmetric model of ejector

Where Rm is the entrainment ratio of the jet-pump defined as:
Ejector geometrical specifications (dimensions)
[1-4] Geometry was borrowed from literature work of
Huang, Chang [2]. The geometrical dimensions/specifications
of ejector are presented below in table 1.
Entrainment ratio is a function of jet-pump geometry
and operating conditions; thus, the corresponding COP of the
system will vary dependently. However, for fixed jet-pump
geometry, designed for specific refrigerator operating
conditions, the maximum COP of the system is obtained at the
maximum value Of Rm.

II. CFD METHODOLOGY

Fig 6:- Geometry of ejector
A. Geometric modelling
3 D surface modelling of ejector was modelled using Length Dimensions (mm) Radii Dimensions(mm)
SolidWorks CAD package due to easy commercial L1 40 r1 6.65
availability. However, for Computational simulations 2D L2 32.24 r2 1.32
planar and axisymmetric modelling was considered. L3 35.6 r3 2.25
Simulations were performed using both 2D planar and L4 56.94 r4 11.55
axisymmetric models for couple of operating conditions. It L5 18.32 r5 3.49
was seen that both type of models provided almost same L6 18.32 r6 7.04
results. Hence, 2D axisymmetric model was used for rest of Table 1. Geometric parameters of an ejector

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Volume 3, Issue 5, May – 2018 International Journal of Innovative Science and Research Technology
ISSN No:-2456-2165
B. CFD Setup required. The graph of entrainment ratio Vs no of elements is
ANSYS Fluent is used for computational simulations plotted in figure 8.
because due to reasons like commercial licensed version of
software available. Technically, ANSYS works using Finite
Volume method (FVM) unlike other packages like COSMOS
use Finite element method (FEM) which saves computation
time. ANSYS also captures shocks due to FVM technique.
Along with this, ANSYS is used to capture both far-field and
boundary characteristics.
 Mesh generation
Meshing is highly important in CFD approach as
whole entity is broken down into small 2-D or 3-D elements
and properties are calculated at nodes. Face meshing with edge
sizing along inlet and axis is employed. The element size is
defined as 0.4mm for axis and 0.5 mm for inlet. It is a quad
element with 4 nodes
Fig 8:- Graph of Entrainment Ratio Vs Number of elements
(Grid Independence test)
 Boundary conditions
From the experimental data in ICER lab, the
boundary conditions are showed in table 3. Certain properties
like condenser pressure is varied to note determine the effect
of variation of operating conditions.

Fig 7:- Meshing of ejector

Pressure at inlet 1 0.4MPa
 Mesh attributes
Pressure at inlet 2 0.04MPa
The table 2 shows the mesh attributes or important
characteristics of a mesh. Mesh quality is defined by these Pressure at outlet 0.06MPa
mesh attributes. Skewness of the mesh is a measure of how
close the element shape is to the equilateral shape (0 being Table 3. Boundary Conditions
best and 1 being worst). Orthogonality relates how close the
angles between adjacent element faces are to some optimal Refprop is used to determine temperature and other thermal
angle. (For ex, 900 for quad element). Aspect ratio is defined properties.
as ratio of largest edge length to shortest edge length.  FLUENT Setup
There are different types of turbulent models: k-
omega model, k-epsilon model, k-omega SST model. K-
omega SST model is used as it captures both far field and
Mesh attribute value boundary characteristics. All of these turbulence models are
based on RANS (Reynold’s Averaged Navier Stokes)
Orthogonal quality 0.95 Equation. Pressure based steady state axisymmetric solver is
used.
Skewness 0.05
K-omega SST model is a two-equation eddy viscosity
Aspect ratio 4.8 model which is given by the below equations.
Turbulence Kinetic energy (k):
No. of nodes 10396

No. of elements 9946

Table 2. Mesh Attributes

 Grid Independence Test Specific dissipation rate (omega):
Determining the minimum number of elements or
nodes required to get converging and accurate result is
important to optimise the computational power and time

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Volume 3, Issue 5, May – 2018 International Journal of Innovative Science and Research Technology
ISSN No:-2456-2165
A. Effect of operating conditions on ejector performance
Solver Type Pressure based solver- steady-
Effect of generator temperature on ejector
axisymmetric
entrainment ratio is studied. Simulations for primary inlet
Wall Ideal-Stationary temperature (generator temperature) from 800C to 1000C with
constant evaporator temperature of 80C and condenser
Navier Stokes Energy-on: K-omega SST temperature of 280C was performed. The result was plotted as
Activated Turbulence model graph is shown in figure 10. The plot shows one value of Tg
for which E.R is maximum.
Material R245fa refrigerant

Table 4. FLUENT Setup

 Solution Setup
Gradients of solution variables are required in order
to evaluate diffusive fluxes, velocity derivatives, and for
higher-order discretization schemes.

Green-gauss cell based, Green-gauss node based,

least square cell based are three different gradient solving
techniques. Least square cell based is preferred in this case as
it best suits polyhedral meshes (in this case, quad mesh) while Fig 10:- Predicted effect of Generator temperature/ pressure
Green-gauss node method is suitable for tri/tet meshes. (Tg, Pg) on ejector performance
SIMPLE algorithm is used as pressure-velocity coupling
algorithm because of the faster convergence achieved. The optimum value of generator temperature is
obtained at 860C. With Tg = 860C and Te= 80C and 120C,
Initialization Hybrid simulations were performed to determine critical condenser
temperature. Critical condenser pressure/ temperature is a
Conditions computed from Inlet characteristic after which entrainment ratio starts varying. If
condenser temperature is maintained below critical
Modelling Implicit temperature, entrainment ratio is maintained constant and also
both primary and secondary flow is choked. For T e= 80C,
Gradient solving Least square cell based critical condenser temperature is 280C and for Te= 120C,
critical condenser temperature is 310C.
Upwind scheme Second order upwind

Table 5. Solution Setup

III. RESULTS

Computational simulations carried out for different

conditions and different geometry profiles. For each
computation, Mach contours and entrainment ratios are
recorded. Mach contours of all the conditions looks the same
and hence one such contour is shown in figure 9.

Fig 11:- Predicted effect of Condenser temperature/ pressure

(Tc, Pc) on ejector performance

Using optimum values of both condenser temperature

and generator temperature, the variation of entrainment ratio
with evaporator temperature is determined and shown in figure
12. It is seen that entrainment ratio increases with increase in
Fig 9:- Mach contour (ANSYS 16.0)

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Volume 3, Issue 5, May – 2018 International Journal of Innovative Science and Research Technology
ISSN No:-2456-2165
evaporator temperature. But due to certain limitations, it can’t
be increased beyond certain value.

Fig 14:- predicted effect of mixing chamber length on ejector

performance
C. Validation of CFD results
Fig 12:- Predicted effect of Evaporator temperature/ pressure To validate the accuracy of CFD simulation results, a
(Tc, Pc) on ejector performance set of CFD simulations were run using operating conditions
and geometry of nozzle identical to Haung, Chang [2] and
B. Effect of geometric parameters on ejector performance Scott et al [10]. It was found that the results were close to the
(Parametric Analysis) results obtained by Haung in one dimensional analysis of
ejector and Scott’s Computational simulations. The error was
limited to ±5%. Hence, the same method was extended to
other boundary conditions. Table containing boundary
conditions, results and error is represented in the figure 15

Fig 13:- predicted effect of mixing chamber diameter on

ejector performance
After determining the optimum operating conditions,
these conditions are used to perform parametric analysis.
Parametric analysis is very important to understand the Fig 15:- Chart comparing experimental and numerical data
importance of geometrical parameters of the ejector. Mixing of
primary and secondary flow plays a major role in determining AB and AG represent two different geometries of
the performance of ejector. Hence, mixing chamber geometry ejector and are analysed for 3 different operating conditions
is analyzed. maintaining the outlet pressure (condenser pressure) at 0.06
MPa. ANSYS fluent was used to run computational
simulations. E.R CFD gives the entrainment ratio obtained by
Effect of mixing chamber diameter and mixing
CFD simulations and E.R EXP is the experimentally
chamber length is represented in figure 13 and 14 respectively.
determined entrainment ratio.
It is seen that for one mixing chamber diameter of 3.7mm, the
entrainment ratio is maximum. While, there is range of mixing The results of current study can also be validated
chamber length for which entrainment ratio change is very comparing the results obtained numerically with analytical
small. results. The graphs below show the variation of entrainment

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Volume 3, Issue 5, May – 2018 International Journal of Innovative Science and Research Technology
ISSN No:-2456-2165
ratio with Condenser temperature numerically and analytical. had a bell curve with one optimum point and decreasing on
Both the graphs have identical behaviour as shown in figure either side
16. and 17.
V. ACKNOWLEDGMENT

I will take this opportunity to extend special thanks to

Dr. Pramod Kumar, Professor of Indian Institute of Science,
Bangalore for his guidance and support/.

REFERENCES

[1] J.H. Keenan, E.P. Neumann, Cambridge, Mass, F.

Lustwerk “An Investigation of ejector design by analysis
and experiment,” ASME Journal of Applied Mechanics,
1950.

[2] B.J. Huang, J.M. Chang, C.P. Wang, Petrenko, “A 1-D

analysis of ejector performance,” International Journal of
Refrigeration 22 (1999) 354–364, 1999.

[3] José M. Cardemil, Sergio Colle, “A general model for

evaluation of vapor ejectors performance for application
in refrigeration,” Energy Conversion and Management 64
(2012) 79–86, 2012.
Fig 16:- Graph of Entrainment Ratio Vs Condenser Pressure
obtained numerically [4] Natthawut Ruangtrakoon, Satha Aphornratanaa,
Thanarath Sriveerakul, “Experimental studies of a steam
jet refrigeration cycle: Effect of the primary nozzle
geometries to system performance,” Experimental
Thermal and Fluid Science 35 (2011) 676–683, 2011.

[5] Hongqiang Wu, Zhongliang Liu, Bing Han, Yanxia Li,

“Numerical investigation of the influences of mixing
chamber geometries on steam ejector performance,”
Desalination 353 (2014) 15–20, 2014 .

[6] R. Yapici, H.K. Ersoy, A.Aktoprakoglu, H.S. Halkaci, O.

Yigit, “Experimental determination of the optimum
performance of ejector refrigeration system depending on
Fig 17:- Graph of Entrainment Ratio Vs Condenser Pressure ejector area ratio,” International journal of refrigeration
(Analytical) 31 (2008) 1183–1189, 2008.

[7] John T. Munday, David F. Bagster, “A New Ejector

IV. CONCLUSION Theory Applied to Steam Jet Refrigeration,” Ind.
Chemical Engineering., Process Des. Dev., Vol. 16, No. 4,
The ejector cycle refrigeration is a green refrigeration 1977.
technique. To improve the performance of the ejector
refrigeration system, the understanding of the flow of the fluid [8] Z Ma, H Bao, A Paul Roskilly, “Thermodynamic
in the ejector is very essential. In the present study, the flow of modelling and parameter determination of ejector for
the primary fluid after the exit of the nozzle, subjected to a ejection refrigeration systems,” international journal of
drastic pressure difference is investigated. The effect of the refrigeration 75 (2017) 117–128, 2017.
deflection of the primary flow on the secondary flow is
[9] A Jakub, “Mathematical model of ejector and
determined. It can be observed from the results that due to the
experimental verification,” SETKÁNÍ KATEDER
deflection of the primary flow, the choking of the secondary
MECHANIKY TEKUTIN A TERMOMECHANIKY,
flow occurs much earlier than anticipated, thus causing the
2012.
mixing to occur in the convergent section of the ejector itself.
This has profound implications on the performance of the [10] Scott, D., Aidoun, Z., Bellache, O. and Ouzzane, M.,
ejector as the pressure after mixing will not remain constant “CFD Simulations of a Supersonic Ejector for Use in
but will vary according to the variation in the area of the Refrigeration Applications,” Proceedings at International
convergent section of the ejector. CFD simulations was Refrigeration and Air Conditioning Conference at Purdue
performed to identify optimum geometry and optimum University, West Lafayette, IN., July 14-17, 2008.
operating conditions. It was mostly observed that all properties

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