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INTERNATIONALADVISORY BOARD
Shyam Singh Chauhan
Ex. Director
R.R. Institute of Modern Technology
Bakshi Ka Talab, Sitapur Road
Lucknow, U.P., India
R.K. Sharma
Infra red Division
SSPL
Lucknow Road, Timarpur
Delhi - 110 054, India
P.J. George
Kurukshetra Institute of Technology
and Management (KITM)
Pehwa Road, Bhorasida,
Kurukshetra - 136 119, Haryana, India
Nawal Kishore
Department of Applied Physics
Guru Jambheshwar University
Hisar - 125 001, Haryana, India
I.P. Jain
Director
Centre for Non-conventional Energy Sources
14, Vigyan Bhavan
University of Rajasthan, Jaipur - 302 004
Rajasthan, India
Naresh Padha
Department of Physics & Electronics
University of Jammu, Jammu - 180 006
India
Bhaskar Bhattacharya
Director
School of Engineering and Technology
Sharda University, Knowledge Park 3
Greater Noida - 201 306, U.P., India
Kishan Pal Singh
Principal
University Polytechnic
Mangalayatan University
Aligarh Mathura Highway
Aligarh - 202145, India
Avinashi Kapoor
Department of Electronic Science
University of Delhi, South Campus
New Delhi - 110 021
India
Amitava Majumdar
Sr. General Manager-Technical & Corp. R&D
Moser Baer India (MBI)
66, Udyog Vihar, G B Nagar
Greater Noida - 201 306, U.P,
India
C A N Fernando
Department of Electronics
Wayamba University of Sri Lanka,
Kuliyapitiya
Sri Lanka
R.C. Maheshwari
Advisor,
Hindustan College of Science & Technology
Agra - 211 011, U.P.
India
G.D. Sharma
Physics Department, JNV University
Jodhpur - 342 005
Rajasthan, India
Z.H. Zaidi
Chief Editor
Invertis Journal of Science & Technology
New Delhi - 110 060
India
Abdol Rahim Baharvand
Researcher and University Teacher
Lorestan University, Khorramabad
Iran

INVERTIS JOURNAL OF RENEWABLE ENERGY
Volume 7 July-September 2017 No. 3
Owned, Published and Printed by Sanjeev Gautam, 60/10, Old Rajinder Nagar, New Delhi - 110 060
Printed at Alpha Printers, WZ-35/C, Naraina Ring Road, New Delhi - 110 028. Ph : 9810804196
Chief Editor : Prof. Z.H. Zaidi, Ph. : 09213888999, E-mail : ijre2011@gmail.com
CONTENTS
The energy transfer/flow management algorithm 115
for a photovoltaic solar home
Osama Shaukat
Numerical analysis of friction factors in smooth and rough 123
microchannels
Mohd Owais Qidwai, M.M. Hasan and Mohd Ariz
Effect of operating conditions on the performance of vapor 131
absorption refrigeration system
Md. Meraj, Rashid Imam and Md. Ashfaque Alam
Study and analysis of plate type heat exchanger 137
Numan Ansari, Mohd. Islam and Sayyed Haider
Study of CFD approach to discretise first derivative 142
of partial differential equation
Hasan Shamim, Shadab Ahmad and Shah Alam
Thermal design of liquid cooled charge air cooler: 147
A computational approach
Tribhuwan Chandra Joshi and Yogendra Singh Kushwah
Utilisation of exhaust gases of automobile 158
Jitendra Singh and Shahbaz Mozammil
Life cycle analysis of multi-split Variable Refrigerant 165
Flow (VRF) system : case study
Md. Khurshid Alam and Shah Alam
Patron
Umesh Gautam
R.M. Mehra
Sharda University
Mohd Parvez
Al-Falah University
Assistant Editor
Sumit Kumar Gautam
Editors
Chief Editor
Z.H. Zaidi

Ranjana Jha
N S I T, Delhi University

The energy transfer/flow management algorithm for a photovoltaic solar home
115
The energy transfer/flow management algorithm
for a photovoltaic solar home
OSAMA SHAUKAT
Departmentof Mechanical Engineering Al-Falah University, Faridabad, Haryana
*E-mail: osama_shaukat@yahoo.com
Abstract
In this research paper, an energy flow management algorithm for a grid-connected-photovoltaic
system with battery storage devoted to supply a home is presented. Modeling of photovoltaic
(PV) and wind farms (WF) stations to take into account these renewable energies into the power
flow formulation are summarized. This algorithm favors the fulfillment of the home energy demand
by the energy produced by the photovoltaic generator or stored in the batteries than that got
from the grid. This algorithm manages the flow of energy in the house through the combination
of four switches. It was applied to the case of a home installed in a coastal region of Bou-Ismaïl
(Algeria).The efficiency of the algorithm was tested for two weeks, a favorable week in summer
and an unfavorable week in winter regarding the weather conditions. The simulation of the on
grid PV system was done using real data of the irradiation and the temperature acquired by the
meteorological station of the Bou-Ismaïl site and a home load profile for each season. The results
obtained revealed that the energy demand satisfaction for the house is high in the favorable
summer week and is only 33% in the winter unfavorable week. To meet a high rate of self-
consumption a Home Energy Management is required.
Key words : Photovoltaic (PV); solar home; energy management; consumption profiles.
1. Introduction
Solar energy is radiant light and heat from the
Sun that is harnessed using a range of ever-evolving
technologies such as solar heating, photovoltaic, solar
thermal energy, solar architecture, molten salt power
plants and artificial photosynthesis.
It is an important source of renewable energy and
its technologies are broadly characterized as either
passive solar or active solar depending on how they
capture and distribute solar energy or convert it into
solar power.
In 2011, the International Energy Agency said
that "the development of affordable, inexhaustible
and clean solar energy technologies will have huge
longer-term benefits. It will increase countries' energy
security through reliance on an indigenous,
inexhaustible and mostly importindependent
resource, enhance sustainability, reduce pollution,
Invertis Journal of Renewable Energy, Vol. 7, No. 3, 2017 ; pp. 115-122
lower the costs of mitigating global warming, and
keep fossil fuel prices lower than otherwise.
In 2000, the United Nations Development
Program me, UN Department of Economic and Social
Affairs, and World Energy Council published an
estimate of the potential solar energy that could be
used by humans each year that took into account
factors such as insolation, cloud cover, and the land
that is usable by humans.
These renewable energy sources are a very good
solution in the global energy problem. The energy
generated by the photovoltaic systems constitutes a
large part of the total amount of energy produced by
renewable energy sources. Photo voltaic cells belong
to the group of distributed generations. These cells
produce power by utilizing the sunlight. There have
been many research efforts to improve the efficiency
of photovoltaic systems. In this context, photovoltaic
(PV) generation appears as the most promising
DOI No. : 10.5958/2454-7611.2017.00016.9

116
Osama Shaukat
alternative thanks to its maturity, its environmentally
friendly characteristics, low maintenance and the fact
that the sun is everywhere. The residential and
building sector is in many countries the first energy
consumer, about 40% of the global energy
consumption[1], therefore efficient utilization and
control of energy consumption at household level is
crucial[2]. The challenge resides in the matching of
the intermittent energy production with the dynamic
power demand[3]. This needs to design an energy
management strategy in order to optimize the use of
PV source and storage and to match the local
production with local consumption. In the literature,
several works are particularly focused on optimizing
the energy. Consequently, studies have been directed
to "smart homes"[4-7]. In this paper the case of a home
powered by on grid photovoltaic system with storage
is investigated. An energy flow management
algorithm was developed. It manages the energy flow
available in the home through a combination of
switches to meet the energy demand optimally using
the energy produced by the photovoltaic generator
and/or the energy stored in the batteries and/or the
energy drawn from the grid. The purpose is to
minimize this last and ultimately reach the self-
consumption mode. Two particular weeks have been
chosen, one in summer and one in winter, in order to
tests the algorithm. The paper is organized as follows.
In Section 2, the chosen photovoltaic system which
feeds the home to satisfy the energy demand profile
is presented. The models used to simulate the PV
system are given in section 3. The proposed energy
flow management algorithm and the operating mode
of the system are presented in section 4, while in
Section 5, the obtained simulation results, using the
MATLAB-SIMULINK are given and interpreted.
2. PV System description and energy demand of
the home
2.1 Description of the proposed PV system
In order to study how to meet the energy needs
of a family by using mainly the energy produced by
a photovoltaic installation, the sizing of the PV system
has been done by using PVSST 1.0 locally developed
software[8]. The optimal PV system configuration
obtained is an array of 3.2kWp and a battery bank of
12kWh. To feed the loads of the house, 4kW DC/AC
converter has been chosen. In order to prevent the
batteries from a total discharge, the lowest level of
the State Of Charge (SOC) was set to 25%. This SOC
corresponds to a capacity of 3kWh. The SOCmax was
set to 85% which corresponds to 10 kWh. As shown
on figure 1, the PV system operation depends on the
combination status of four switches (K1, K2, K3, K4)
which is related to the energy demand, the energy
Fig. 1. Grid-connected PV system with storage for the solar home

117
available from the PV generator, the SOC of the
battery bank and the energy taken off from the grid.
In order to meet optimally the energy needs of the
home, an energy flow management algorithm has
been developed.
2.2 Solar home energy demand
The case treated in this paper is a house of 57 m2
area situated in the coastal region of Bou-Ismaîl
(Latitude: 36° 38' 33'' North and Longitude: 36° 38'
33'' North) occupied by a family of three members.
The energy demand of a home depends on many
factors such as the number of appliances, the electrical
power used by each appliance and the amount of use
of appliances determined by the behavior of the
occupants in the home.
Solar cell : A solar cell (also called photovoltaic
cell or photoelectric cell) is a solid state electrical
device that converts the energy of light directly into
electricity by the photovoltaic effect. The following
are the different types of solar cells.
 Amorphous Silicon solar cell (a-Si)
 Bio hybrid solar cell
 Buried contact solar cell
 Cadmium telluride solar cell (CdTe)
 Concentrated PV cell (CVP and HCVP)
2.3 Home energy demand
To design the most efficient PV power system for
supplying the dwelling, the solar energy resources
of a site and the energy consumption of the household
should be known. Unfortunately, the electricity
demand is rarely available, so the daily load profile
must be generated. A home energy management
(HEM) system is an integral part of a smart grid that
can potentially enable demand response applications
for residential customers. This paper presents an
intelligent HEM algorithm for managing high power
consumption household appliances with simulation
for demand response (DR) analysis. The proposed
algorithm manages household loads according to
their preset priority and guarantees the total
household power consumption below certain levels.
A simulation tool is developed to showcase the
applicability of the proposed algorithm in performing
DR at an appliance level. This paper demonstrates
that the tool can be used to analyze DR potentials for
residential customers. Given the lack of under-
standing about DR potentials in this market, this work
serves as an essential stepping-stone toward
providing an insight into how much DR can be
performed for residential customers. In the studied
case, the home load profile has been determined by
considering the daily load profile of each appliance,
their power ratings and their estimated operating
time per day, then their summation leads to the daily
consumption home profile. For the summer, the daily
energy demand varies between 13.87 kWh and 16.27
kWh. For the winter, the energy demand varies
between 12.03 kWh and 18.30 kWh. For these two
seasons, the high energy demand is explained by the
use of energy intensive equipment for heating and
air conditioning.
3. PV system modeling
In this section, the modeling of the PV generator,
the batteries and the power converter will be
presented. For PV system modeling, a one diode
model for the PV generator has been used[10]. For the
batteries, the Copetti's model has been chosen as it is
well suited for lead acid batteries allowing the
simulation of the whole operating process charge-
discharge-overcharge while considering the
temperature change of the battery[11, 12]. For the DC/
DC converter, a boost converter controlled by a MPPT
Fuzzy logic Controller has been used[13, 14] and the
DC/AC converter has been modeled by its yield
curve.
Solar energy : Solar is scaling up rapidly, with
capacity more than trebling over the past four years.
New installations totaling more than 50 GW in 2015
took global solar PV power generating capacity to
231 GW by year end, a 28.1% increase versus the end
of 2014. Capacity has more than trebled in the past
four years. The largest increments in 2015 were
recorded in the Asia Pacific region; China added 15.2
GW, just ahead of Japan with 12 GW, together
accounting for more than half of the growth in global
solar capacity. The US provided the third largest
addition (7.3 GW). China's cumulative installed
capacity (43.5 GW) moved it ahead of Germany (39.7
GW), with Japan (35.4 GW) in third place, and the
US (25.6 GW) overtaking Italy (18.9 GW) to take
fourth place. Solar power generation enjoyed another
year of very rapid growth in 2015, with a 33%

118
Osama Shaukat
increase. Its overall share of global power generation
remains low (1.1%), but that share has almost doubled
in just two years. Solar is starting to have a noticeable
impact in terms of sources of power generation
growth, contributing more than 30% of the growth
of global power in 2015.
Energy plays a pivotal role in our daily activities.
The degree of development and civilization of a
country is measured by the amount of utilization of
energy by human beings. Energy demand is
increasing day by day due to increase in population,
urbanization and industrialization. The world's fossil
fuel supply viz. coal, petroleum and natural gas will
thus be depleted in a few hundred years. The rate of
energy consumption increasing, supply is depleting
resulting in inflation and energy shortage. This is
called energy crisis. Hence alternative or renewable
sources of energy have to be developed to meet future
energy requirement.
4. Energy Classification
Energy can be classified into several types:
4.1 Primary and Secondary Energy
Primary energy sources are those that are either
found or stored in nature. Common primary energy
sources are coal, oil, natural gas, and biomass (such
as wood). Other primary energy sources available
include nuclear energy from radioactive substances,
thermal energy stored in earth's interior, and potential
energy due to earth's gravity. The major primary and
secondary energy sources are Coal, hydro power,
natural gas, petroleum etc. Primary energy sources
are mostly converted in industrial utilities into
secondary energy sources; for example coal, oil or gas
converted into steam and electricity. Primary energy
can also be used directly.
4.2 Commercial Energy and Non Commercial Energy
The energy sources that are available in the
market for a definite price are known as commercial
energy. By far the most important forms of
commercial energy are electricity, coal and refined
petroleum products. Commercial energy forms the
basis of industrial, agricultural, transport and
commercial development in the modern world.
The energy sources that are not available in the
commercial market for a price are classified as non-
commercial energy. Non-commercial energy sources
include fuels such as firewood, cattle dung and
agricultural wastes, which are traditionally gathered,
and not bought at a price used especially in rural
households. These are also called traditional fuels.
Non-commercial energy is often ignored in energy
accounting.
Fig. 2. Solar PV generation capacity

119
"energizes" our computers, lights, refrigerators,
washing machines, and air conditioners, to name only
a few uses[1]. We use energy to run our cars and
trucks. Both the gasoline used in our cars, and the
diesel fuel used in our trucks are made from oil. The
propane that fuels our outdoor grills and makes hot
air balloons soar is made from oil and natural gas.
4.4 Renewable Energy and Trends in Solar
Photovoltaic Energy Production
4.4.1 Energy Scenario
The present energy scenario is discussed under
categorical division of World, Bangladesh.
4.4.2 World Energy Scenario
Global economic recession drove energy
consumption lower in 2009 - the first decline since
1982. World primary energy consumption - including
oil, natural gas, coal, nuclear and hydro power - fell
by 1.1% in 2009. The issues at hand are numerous
and include increasing atmospheric carbon dioxide
concentrations from greenhouse gas emissions,
environmental safety of energy production
techniques, volatile energy prices, and depleting
carbon based fuel reserves to name a few (Nguyen
and Pearce 2010; Choi et al. 2011)[5]. As a result,
countries are facing an increasing challenge to
diversify energy sources and bringing renewable
generation to the forefront of policy discussion.
4.3 Renewable and Non-Renewable Energy
All forms of energy are stored in different ways,
in the energy sources that we use every day. These
sources are divided into two groups --renewable (an
energy source that we can use over and over again)
and nonrenewable (an energy source that we are
using up and cannot recreate in a short period of
time). [2] Figure
Renewable and nonrenewable energy sources can
be used to produce secondary energy sources
including electricity and hydrogen. Renewable
energy sources include solar energy, which comes
from the sun and can be turned into electricity and
heat. Wind, geothermal energy from inside the earth,
biomass from plants, and hydropower and ocean
energy from water are also renewable energy sources.
However, we get most of our energy from non-
renewable energy sources, which include the fossil
fuels --oil, natural gas, and coal[2]. They're called fossil
fuels because they were formed over millions and
millions of years by the action of heat from the Earth's
core and pressure from rock and soil on the remains
(or "fossils") of dead plants and animals. Another
nonrenewable energy source is the element.
Uranium, whose atoms we split (through a
process called nuclear fission) to create heat and
ultimately electricity. We use all these energy sources
to generate the electricity we need for our homes,
businesses, schools, and factories. Electricity
Fig. 1.1. Renewable Energy Sources and Non-Renewable Energy Sources

120
Osama Shaukat
In the United States, a rise in renewable energy
generation has been supported by the availability of
federal tax credits and programs in individual states
(U.S. Energy Information Administration 2013a)[3].
Many states are implementing renewable portfolio
standards, or renewable energy standards, that
outline goals to increase electricity generation from
renewable resources (U.S. Energy Information
Administration 2013a). These policies seek to remove
barriers to install renewable generation and can
include grant programs, loan programs, and state
renewable electricity tax credits. The Database of State
Incentives for Renewables & Efficiency (DSIRE)
provides an outline of state renewable portfolio
standards available throughout the nation (NorthGraph 1.1 : Power generation capacity in
world by source, 2008

121
Carolina State University 2013)[8]. In 2012, about 12
percent of U.S. electricity was generated from
renewable sources (U.S. Energy Information
Administration 2013b). The United States Energy
Information Administration states that the five
renewable sources most often utilized include
biomass, water, geothermal, wind and solar (U.S.
Energy Information &!!
4.5 Energy transfer/flow management algorithm
The figure 3 depicts the detailed flowchart of the
flow energy management algorithm. The main idea
is that the photovoltaic production should be utilized
as much as possible to reach the self-consumption.
The priority is given to the supply of the loads, then
the charge of the batteries and at last, the excess
energy is fed into the grid. The algorithm operation
is based mainly on the PV production, the SOC of
the battery and the Ibat which indicates if the battery
is in charge or discharge and if it is able to feed the
loads or not. Depending on the state of theses
parameters one of the modes indicated in the
previous paragraph is used.
5. Simulation Results and Discussion
In order to test the efficiency of the flow energy
management algorithm the satisfaction of the energy
demand of the solar home by the photovoltaic system,
has been evaluated for two chosen cases. The first
one is 'a favorable week' for the PV production
relatively to weather conditions in summer and the
second one is 'an unfavorable week' in the winter.
For each case, depending on the PV produced and
the load energy profile a combination of the switches,
directs the energy flow to the given target. The
simulations were done using the irradiation and the
temperature data acquired by the meteorological
station of the site of Bou-Ismaïl. The PV electrical
production was calculated using the PV system model
presented briefly in paragraph 3. The algorithm was
performed using the appropriate load profile of each
season. The figures 4 and 5 show the states of the K1,
K2, K3 and K4 switches and the variation of the
photovoltaic production, the energy demand (load
profile), the energy battery storage and the grid
energy for the summer and winter week respectively.
From the results presented in figure 4 and 5, the
excess energy produced in the favorable week in
summer is 8.5%, this percentage corresponds to an
energy of 9kWh which is injected to the grid. On the
other hand, in winter, 67% of the energy demand of
the unfavorable week is satisfied by the grid (65kWh)
this is due to the low photovoltaic energy production
during this season. To better explain the energy flow
in the studied PV system, two particular cases will
be discussed. The first one corresponds to a favorable
day in summer (25/08/2015), and the second
corresponds to an unfavorable day in winner (03/
02/2015).
As it can be seen on figure 6, between midnight
and 5am there is no PV production and the energy
demand is very low, the battery is at its low level
(25%). Between 5 am and 5 pm, the PV array produces
2kWh. After 5 pm, as the PV production is low, the
batteries supply a part of the demand. Between 7 pm
and 9 pm all the energy needed is taken from the
batteries. After 9 pm the batteries continues to
discharge in the loads but the demand is so high that
the rest of the energy needed was withdrawn from
the grid. Indicates that, for the chosen day it can be
noticed that the irradiation is at low level all the day
and this conducts to a low PV production. In this case,
the energy demand is exclusively satisfied by the grid.
The battery bank is all day long near its lowest level
(25%). The highest energy demand is situated
between 5 pm and 9 pm.
6. Conclusion
Thanks to the decreasing of the cost of PV
installations, the grid parity comes a reality.
Nowadays, it is not profitable as before to sale the
produced photovoltaic electricity. It is more
interesting for the PV owners to use it for their own
needs and try to reach their self-consumption. In this
article, as a first step an energy flow management
algorithm which directs the energy flow according
to priorities set was presented. It appears that even
if the energy flow algorithm is necessary it is not
sufficient. To go further and to use the PV electricity
produced as much as possible, a Home Energy
Management (HEM) is needed. This last will allow
the balancing between the demand and the
generation, by controlling the deferrable loads,
reduces the energy consumption for example by using

122
Osama Shaukat
natural light as long as possible, exchanging excess
energy produced between neighbors instead of
drawing off energy from the grid.
7. Acknowledgements
We would like to thank Dr Shahzad Ahmad
Siddiqui, for his valuable advices on the writing of
this research paper.
References
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buildings. Strategies and opportunities to 2050.
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[7] Tascikaraoglu A., Boynuegri A.R. and
Uzunoglu M., A demand side management
strategy based on forecasting of residential
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[8] Chikh M., Mahrane A.and Bouachri F., PVSST
1.0 sizing and simulation tool for PV systems.
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systems incorporating solar irradiance model,
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549.

Numerical analysis of friction factors in smooth and rough microchannels
123
Numerical analysis of friction factors in
smooth and rough microchannels
MOHD OWAIS QIDWAI1, M.M. HASAN1 and MOHD ARIZ2
1Department of Mechanical Engineering, F/o Engineering and Technology, Jamia Millia Islamia, New Delhi, India
2Global Evolutionary Energy Design, New Delhi, India
*E-mail: owais00738@gmail.com
Abstract
Based on the available literature, the researchers are divided that transition in smooth channel
occurs in low Reynolds region or not, and various experimental results contradicts each other.
Also, the effect of surface roughness has any considerable effects on early transition behavior or
not. The numerical procedures are used these days and various researches are ongoing with the
help of numerical methods on studying the flow characteristics. The author aims in understanding
the flow behavior in low Reynolds regime between 100 - 1400 for smooth and rough channel
with roughness to hydraulic diameter ratio of 0.264. The flow remains in laminar regime for
smooth channel and rough channel, and no significant effect of roughness obtains in both the
cases. The early transition effects are not seen in the analysis. The friction factor decreases with
increase in Reynolds number.
Key words : CFD, Friction Factor, Laminar, Reynolds Number, Single phase, Transition,
Turbulent, Velocity profile.
1. Introduction
For successful operation of electronic devices, the
microchannel heat sink is best available option for
decades. As per Garimella et al.[1] liquid cooling has
lot of potential as discussed in the TCO decision
criterion for high density and high computing
electronic devices. In the development of liquid
cooling microchannel heat sink various researches
regarding friction factor[2,3], pressure drop[4] and
thermal resistance[5] has been published in recent
years.
Most of the investigation performed in earlier
phase were experimental, but recent development in
mathematical models open ways for numerical
studies and consistent results were obtained by
various researchers[6,7,8], proving the validity of the
numerical simulations.
Mala and Li[9] performed experimental studies
on circular cross sectional microchannel of stainless
steel, with one channel with hydraulic diameter in
the range of 50-254. The ratio of surface roughness to
the hydraulic diameter in the channel varies from
0.69-3.5. They found that for Reynolds number 80 -
2500, the critical Reynolds number obtained was in
the range of 300-900. As per their observation early
transition is obtained with increase in friction factor.
Brackbill and Kandlikar[10] also obtained early
transition from laminar to turbulent regime in the
range of 572-2367, for introducing saw tooth profile
roughness in the microchannel.
Many authors published results with higher
range of critical Reynolds number. Tam et al.[11,12]
obtained critical Reynolds number in the range of
2100-2700. Baviere et al.[13] found critical Reynolds
number in the range of 2417- 2822.
Based on the literature review, and applicability
of numerical procedures to the study of microchannel
flow characteristics, the authors aims at finding out
the region of transition in the microchannel with the
help of friction factor obtained theoretically and
DOI No. : 10.5958/2454-7611.2017.00017.0

124
through numerical procedures for Reynolds number
varying from 100-1400, for single phase water flow
in the microchannel with constant thermos-physical
properties.
Classical conventional theory from open
literature consists of relations of friction factor (Darcy
and Fanning) with the pressure drop. The fanning
friction is defined as
21
2


= w
Ff
u
(1)
Darcy friction factor and fanning friction factor
are related as
4=D Ff f (2)
And Darcy friction factor in terms of pressure
drop is given by
2
2


= H
D
P D
f
L u
(3)
Where P is the pressure drop across the length
of microchannel.
The Poiseuille number (Po) is defined as the
product of Darcy friction factor and Reynolds number
(Re), where Reynolds number is defined as,

Re = HuD
(4)
The friction factor obtained in the above relation
is evaluated based on assumption that Steady,
laminar, incompressible flow takes place. The
Poiseuille number on the other hand is obtained for
the same assumption along with fully developed flow
between two parallel infinite plates. For a finite
dimension rectangular cross sectional microchannel,
Poiseuille number is defined based on the aspect ratio
 by Shah and London[14].
  
 
2 3
4 5
= 96(1 – 1.3553 + 1.9647 – 1.7012
+ 0.09564 – 0.2537 )
Po
(5)
Various experimental investigations have
confirmed that microscale friction factor can be
obtained by macroscale theories. Therefore Navier-
Stokes equation can be used to study incompressible,
Newtonian liquids in laminar regime[15]. Several
numerical studies have been performed earlier which
confirm the applicability of numerical schemes
available for thorough analysis Xu et al.[16], Lee et
al.[17], Jones et al.[18].
The present paper aims at investigating the effect
of laminar to turbulent transition with the increase
in Reynolds number for smooth and rough channel
with roughness to hydraulic diameter ratio of 0.264.
The numerical scheme is validated with the
experimental work of Hao et al.[19].
2. Mathematical Model
Figure 1 Shows the schematic diagram of smooth
channel with the dimensions as used in Hao et al.[19].
The average surface roughness in the experimentation
was obtained 0.032 micron, on the inside surface of
the channel.
To study the entire domain is computationally
expensive process and hence single channel with
exact dimensions are considered for the analysis.
For the rough channel as shown in Figure 2, the
ribs are introduced only on one side of the channel to
analyse its effect on the friction factor and transition
regime. The first roughness element is introduced at
x= L1=6.8 mm from the inlet boundary and thereafter
a pitch value of 2.95 mm is chosen to place the ribs,
so that L2= L3= L4= L5= L6= 2.95 mm. Length L1 is
selected with a higher value so that fully developed
flow is obtained in the region. The ribs have cross-
sectional dimension of hr = wr = 50 ?m are introduced
Fig. 1. Schematic Diagram of Smooth Microchannel
Fig. 2. Ribs of square cross section with hr = wr are
introduces in the smooth channel as roughness element

125
in the smooth channel as roughness element as shown
as shown in Figure 3.
Three-dimensional geometry of the model for
smooth and rough channelis shown in Figure
4&Figure 5 respectively.
Assumption
1. The flow takes place under steady state
conditions.
2. No phase change during the flow.
3. No slip boundary condition.
4. Viscous dissipation, flow mal distribution
and external heat transfer are neglected.
5. Thermophysical properties of the fluid
remain constants.
6. Developing flow at inlet boundary.
The governing equation is along with the
boundary conditions for 3D, laminar incompressible
flow in cartesian coordinates are:
Continuity equation
  
  
+ + = 0
u w
x y z (6)
The boundary conditions are
2 2 2
2 2 2
1




   
   
   
     
+ + w = –
+ + +
u u u P
u
x y z x
u u u
x y z
(7)
2 2 2
2 2 2
1 


   

   
   
   
     
+ + w = –
+ + +
u P
u
x y z z
x y z
(8)
2 2 2
2 2 2
1




   
   
   
     
+ + w = –
+ + +
w w w P
u
x y z z
w w w
x y z
(9)
The boundary conditions are
At z = 0 At z = L
w = Uin, u=v=0


= u = v = 0
w
x
At x = 0 At x = w
u=v=w=0 u=v=w=0
At y = 0 At y = h
u=v=w=0 u=v=w=0
The above equation is solved using CFD software
CFX., the pressure and velocity distribution are
identified in the fluid domain for smooth and rough
channels.
Fig. 3. Schematic diagram of channel with roughness element
Fig. 4. Smooth channel
Fig. 5. Rough channel

126
3. Numerical Solution
Ansys CFX is used to solve the continuity and
momentum equation using Finite volume method
(FVM). A mesh of fluid domain is generated for the
channel with dimension of length L = 23 mm; height
h = 0.146 mm andwidth w = 0.027 mm. The
dimensions considered are same as that of Hao et
al.[19] for the smooth channel with no ribs. The
numerical solution also involves surface roughness
effect of 0.032 micron as mentioned by Hao et al.[19].
For a flow of Re = 100 three mesh sizes were used as
shown in Table 1. The number of nodes are increased
for each solution and the resultant pressure drop from
inlet to outlet boundary is mentioned along with the
central velocity in fully developed region about 18
mm down the inlet boundary. The convergence
criterion adopted for the solution of momentum and
continuity equations is to be less than 10-6.
4. Result and Discussion
From Fig. 6, it is observed that frictional factor
decreases with increase in Reynolds number for both
smooth and rough microchannel. There is no
significant deviation from Darcy friction factor and
numerical frictional factor for both smooth and rough
microchannels. However, the slight deviation starts
taking place at Re=600 for friction factor in rough
microchannel, which is not so significant for which
early transition effect in rough channel can be
concluded. Though a higher value of friction factor
is obtained for Re > 900 in case of rough channel. But,
it can be said that there is no effect of surface
roughness on transition for flow with low Reynolds
number.
From Fig. 7 it appears that the velocity profile is
parabolic for low Reynolds number, and as the
Reynolds number is increased the parabolic velocity
Table 1. Grid independence study
Mesh Number of Pressure Drop Fully developed
Configuration Nodes P (Pa) central velocity (m s–1
)
1 429229 8482.00 0.955027
2 576000 8478.65 0.950493
3 792000 8474.30 0.948219
Fig. 6. Comparison of Friction Factor obtained using pressure drop for smooth and rough microchannel from
numerical solution and C/Re., where C is obtained from equation 5 for smooth channel

127
Fig. 7. Fully developed velocity profile across the channel at 18 mm down the inlet boundary in smooth channel
distribution tends to become blunter, which suggest
early transition from laminar to turbulent regime.
Fig. 6 shows the shift from Darcy friction profile is
started early around Re=600. and considerable shift
takes between the Darcy friction factor and numerical
friction factor around Re=1000. The flow is still in the
laminar regime, but this could be the understanding
of earlier authors that some of them may concluded
this as the early shift in transition. The velocity profile
at Re=900 and Re=1000 are presented in Fig. 9 for
comparison. Based on the profile obtained it may be
said that it marks the beginning of transition but does
Fig. 8. Fully developed velocity profile across the channel at 18 mm down the inlet boundary in rough channel
not reach critical Reynolds value in smooth channel.
Fig. 8 shows almost parabolic velocity profile except
the slight deviation is due to the presence of
roughness element in the microchannel. The
deviation from parabolic velocity profile increases
with the increase in Reynolds number.
As shown in Fig. 10, the velocity profile for rough
channel at Re = 500 have a sharp parabolic peak, while
the profile for Re = 600 is considerably blunter. Both
the profiles are deviated from central mean position
because of the presence of roughness element. As

128
Fig. 9. Comparison of fully developed velocity profile in smooth channel
(a)
Fig. 10. Comparison of fully developed Velocity profile in rough channel
(b)
(a) (b)
shown in Fig. 11 and Fig. 12, the flow recirculation
increases with increase in Reynolds number. Since
the flow is not shifted into transition or turbulent
phase either, otherwise due to stronger transverse
momentum exchange in turbulent regime, the case
would have obtained wise versa, with length of flow
recirculation zone smaller and blunter profile at
Re=1300.

129
Fig. 11. Flow Recirculation in rough
channel for Re=600
Fig. 12. Flow Recirculation in rough
channel for Re=1300
5. Conclusion
Based on the above discussion, following points may
be concluded:
1. Roughness to hydraulic diameter ratio of
0.264 has no significant effect in early
transition from laminar to turbulent regime
in the range of Re = 100 to 1400.
2. The friction factor has higher value for
Re>900 for both the channels, but based on
streamwise velocity, it cannot be asserted that
profile obtained in Fig. 9 & Fig. 10, is not
parabolic in nature.
3. Conventional theories are in good agreement
with experimental results mostly. Only in the
studies where entrance loss, exit loss and
developing flow are not considered, reports
deviation from it [2].
Nomenclature Subscript
 Shear Stress w wall
 Fluid Density F Fanning Factor
¯u Average flow velocity D Darcy Factor
f Friction Factor H Hydraulic
 Difference
P Pressure
D Diameter
L Length
 Viscosity
 aspect ratio (h/w)
h Height of Channel
w Width of channel
References
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L.T., "Technological drivers in data centers and
telecom systems: Multiscale thermal, electrical,
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roughness on liquid friction and transition
characteristics in micro- and mini-channels,"
Appl. Therm. Eng., 67(1-2), (2014) 283-293.
[3] Steinke M.E. and Kandlikar S.G., "Single-
phase liquid friction factors in microchannels,"
Int. J. Therm. Sci., 45(11), (2006) 1073-1083.
[4] Gunnasegaran P., Mohammed H. and Shuaib
N.H., "Pressure Drop and Friction Factor for
Different Shapes of Microchannels," 7-8, (2009).
[5] Qu W. and Mudawar I., "Experimental and
numerical study of pressure drop and heat
transfer in a single-phase micro-channel heat
sink," Int. J. Heat Mass Transf., 45(12), (2002)
2549-2565.
[6] Lee P.S. and Garimella S.V., "Thermally
developing flow and heat transfer in
rectangular microchannels of different aspect
ratios," Int. J. Heat Mass Transf., 49(17-18),
(2006) 3060-3067.
[7] Li J. and Peterson G.P., "3-Dimensional
numerical optimization of silicon-based high
performance parallel microchannel heat sink
with liquid flow,"Int. J. Heat Mass Transf.,50(15-
16), (2007) 2895-2904.
[8] Sahar A.M., Özdemir M.R., Fayyadh E.M.,
Wissink J., Mahmoud M.M. and Karayiannis
T.G., "Single phase flow pressure drop and heat
transfer in rectangular metallic microchannels,"
Appl. Therm. Eng., 93, (2015) 1324-1336.
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characteristics of water in microtubes," Int. J.
Heat Fluid Flow, 20(2), (1999) 142-148.
[10] Brackbill T.P. and Kandlikar S.G., "Effect of
Sawtooth Roughness on Pressure Drop and
Turbulent Transition in Microchannels," Heat
Transf. Eng., 28(8-9), (2007) 662-669.
[11] Tam L.M. et al., "The Effect of Inner Surface
Roughness and Heating on Friction Factor in
Horizontal Micro-Tubes," 44403, (2011) 2971-
2978.
[12] Tam L.M., Tam H.K. and Ghajar A.J.,
"Simultaneous Heat Transfer and Pressure
Drop Measurements for a Horizontal Micro-
Tube," 38921, (2011) T10122-T10122-8.
[13] Conference I., June M. and York N.,
"ICMM2004-2338," 0, (2016) 1-8.
[14] Shah R.K. and London A.L., Laminar Flow
Forced Convection in Ducts: A Source Book for
Compact Heat Exchanger Analytical Data.
(1978).
[15] Xu B., Ooti K.T., Wong N.T. and Choi W.K.,
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liquid flow in microchannels," Int. Commun.
Heat Mass Transf., 27(8), (2000) 1165-1176.
[16] Lee P.S., Garimella S.V. and Liu D.,
"Investigation of heat transfer in rectangular
microchannels," Int. J. Heat Mass Transf., 48(9),
(2005) 1688-1704.
[17] He Y., Shao B.D., Cheng H.M. and Tang Y.J.,
"Numerical Simulation and Size Optimization
of the Flow Channel of Rectangular Micro-
Channel Heat Sink," Appl. Mech. Mater., 444-
445, (2013) 568-573.
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J. Micromech. Microeng, 16, (2006) 1397-1402.

Effect of operating conditions on the performance of vapor absorption refrigeration system
131
Effect of operating conditions on the performance
of vapor absorption refrigeration system
MD. MERAJ1, RASHID IMAM2 and MD. ASHFAQUE ALAM3
1
Engineering & Technology, Department of Mechanical Engineering, JMI, New Delhi-110025, India
2
Department of Mechanical Engineering, Vishveshwarya Group of Institution, Noida, UP-203207, India
3
Department of Mechanical Engineering, NIT, Jamshedpur, Jharkhand-831014, India
*E-mail: md.meraj1221@gmail.com
Abstract
In this paper, a thermodynamic analysis of single effect vapor absorption refrigeration system
(VARS) is carried out. LiBr-Water is used as working fluid during the analysis. This analysis is
carried out to study the effect of operating conditions on the performance of vapour absorption
refrigeration system. The generator temperature, the condenser temperature and the evaporator
temperature are taken as operating conditions for the analysis. From the result and discussion,
it is found that the coefficient of performance (COP) of the system increases with increasing the
generator and evaporator temperature up to a certain limit but decreases with increasing the
condenser temperature.
Key words : VARS, LiBr-Water, COP, generator temperature, condenser temperature, and
evaporator temperature.
1. Introduction
Present day, the rate at which the non-renewable
energy sources are being utilized has become a major
concern for the world. The future prospect of non-
renewable sources of energy like coal, natural gases
and petroleum products are going to be scarce. To
preserve these energy sources for our future
generation, we have to reduce its consumption by
using alternative sources of energy like solar energy,
geothermal energy, waste heat, hydro-energy etc.
There are many ideas has been developed to utilized
these alternative sources of energy and researches has
also been under the processes to improve the systems
which utilize these sources. In this regard vapor
absorption refrigeration systems are the best
alternative system to reduce the rate of consumption
of non-renewable energy sources.
Vapor absorption refrigeration system (VARS)
invented much earlier than vapor compression
refrigeration system (VCRS) but due to law coefficient
of performance and inven-tion of high performance
refrigerant for VCRS during Second World War, the
popularity of VARS decreases. But, in present
scenario of energy crisis has forced the world to use
vapor absorption refrigeration system in place of
vapor compression system to reduce the rate of
consumption of non-renewable energy sources.
VARS is one of the best replacement for the VCRS,
from the energy point of view as well as environ-
mental,because this system works on law grade of
energy such as solar energy, geothermal-energy,
waste-heat from industries, cheap available energy
etc., and VARS uses such type of refrigerant-absorbent
combination which do not contributes in global
warming and ozone depletion like LiBr2-H2O,
H2O -NH3, LiNO3-NH3, NaSCN-NH3 etc. From
construction point of view absorption system and
compression system are similar but only the
differenceis that the compressor in case of
compression system is replaced by the generator-
solution heatexchanger-pump-absorber assembly
which is used to circulate the working fluid entire
the system by creating pressure differ-ences[8-9].
DOI No. : 10.5958/2454-7611.2017.00018.2

132
Aphornratna. S and Sriveerakul. T[1] performed
an experimental investigation of single-effect
absorption. They have usedaqueous lithium-bromide
as working fluid. They have done their analysis on
2 kW cooling capacity experimental refrigerators
which was tested with various operating
temperatures. From results, it was found that the
system performance is strongly dependent on
thesolution circulation ratio (SCR)and also on
solution heat exchanger. They have resulted that
energy input to the generator is reduced to 60% by
usingsolution heat exchanger. Darwish A. N. et. al.[2]
presented the performance analysis and evaluation
of the roburabsorption-refrigeration water-ammonia
(ARWA) system.The system is analysed by using
aspen plus flowsheet simulator.They analysed COP,
heat duties of the evaporator, absorber, and the
condenser and the flow rate of refrigerant passing
through the evaporator.The results obtained by them
is compared with some manufacturer data and
experimental data reported in the journal literature.
Saghiruddin and Siddiqui[3] perfor-medthe economic
analysis of ordinary and evacuated tubular type flat-
plate collectors for operating absorption cycles with
and without heat recovery absorber. Water-
Ammonia, NaSCN3 and LiNO3-NH3 mixtures has
been selected as the working fluids in the cycles. Use
of heat recovery absorber, in addition to the primary
absorber in the conventional absorption cycles lead
to the improvement in COP by 20-30 % in Water-
Ammonia and 33-36% in NaSCN-NH3 and LiNO3-
NH3 mixtures. Kaushik and Kumar[4] performed
thermodynamic analysisof two-stage vapour
absorption refrigeration system using ammonia-
water (NH3-H2O) and ammonia-lithium nitrate
(NH3-LiNO3) as working fluid. They havefound that
minimum evaporator temperature is achieved in
NH3-LiNO3 combination, and COP of the NH3-
LiNO3 is higher than the NH3-H2O. Marcos et al.[5]
performed optimization of COP in single and double
effect LiBr-H2O absorption chillers. They analyzed
water cooling system and air cooling system and
found that solution concentration is an important
parameter to improve COP. With this, they also
found the crystallization limit. Their study showed
that COP of single effect becomes 0.85 to 0.74 in water
cooled and 0.72 to 0.65 in air cooled system. Similarly,
in double effect cycle it was 1.18-1.2 in the water
cooled and 1.15-1.07 in the air cooled system. Talbi
M. M. and AgnewB.[6] presented an exergy analysis
on a single effect absorption refrigeration cycle with
lithium-bromide-water as the working fluid pair.
They calculated the loads on each component of
absorption system, exergy of each components and
total exergy of system. However, some of the research
has been done on the energy and exergy analysis of
the double effect absorption refrigeration system[10,
11,12].
From literature survey it is absorbed that there
is no work has been done on the effect of operating
condition on the performance of vapour absorption
refrigeration system. Therefore this paper present a
thermodynamic analysis which shows variation of
performance of VARS with the operating conditions
like the generator temperature, the condenser
temperature and the evaporator temperature in the
presented analysis.
2. System Description
A schematic diagram of vapour absorption
refrigeration system is shown in Fig. 1. on which
analysis has beendone. This system consists of an
Evaporator (E), Absorber (A), Generator (G),
Condenser(C), Throttle valve (TV), Pre-cooler (PC),
Fig. 1. Schematic diagram of single effect vapour
absorption refrigeration system.

133
Preheater (PH) and Pump.The operating temperature
of generator, condenser, evaporator and absorber is
shown byTg, Tc, Te and Ta respectively in figure 1.
There are two pressure levels in this system; the
generator and condenser operate at high pressure
level while evaporator and absorber operate at low
pressure level. LiBr-H2O mixture is used as working
fluid in the system in which LiBr works as an
absorbent and H2O works as refrigerant. LiBr-H2O
mixture circulate in the generator-solution heat
exchanger-pump-throttle valve-absorber assembly,
generating the water vapor in the generator which
flows through condenser, throttle valve, solution heat
exchanger and evaporator. The working fluid having
the different state condition while circulating inthe
system is shown in figure by different state point.
3. Thermodynamic Analysis
The thermodynamic analysis of single effect
vapour absorption refrigeration system is based on
the application of mass, concentration and energy
conservations. For performing these applications,
there are some assumptions are made to simplify the
analysis, these are as follows :
 The systems are in steady state.
 The refrigerant (water) at the outlet of the
condenser is saturated liquid.
 The refrigerant (water) at the outlet of the
evaporator is saturated vapour.
 Temperature of absorber and condenser are
same.
 Expansion process in throttle valve is
isenthalpic.
 Heat loss to environment and pressure drop
in the systems are negligible.
 No leakage of air in the system.
Mass, concentration and energy conservation
equation of generator are respectively expressed by:
5 6 10 m m m (1)
5 5 6 6 10 10 m X m X m X (2)
6 6 10 10 5 5= –EQ m h m h m h (3)
Mass, concentration and energy conservation
equation of absorber are respectively expressed by:
3 2 12m m m  (4)
3 3 2 2 12 12m X m X m X  (5)
2 2 12 12 3 3= –aQ m h m h m h (6)
Energy consumption of solution pump can be
defined as:
4 4 3 3= –pW m h m h (7)
Energy conservation of condenser and
evaporator is given by :
6 6 7 7= –cQ m h m h (8)
1 1 9 9= –eQ m h m h (9)
The coefficient of performance of the system can
be expressed as follows :
/( )e E DCOP Q Q W  (10)
A computer program has been developed
using FORTRAN language to carry out the system
simulation of the single effect vapour absorption
refrigeration system. The analysis has been done for
1 Ton of refrigeration. Properties of LiBr-water have
been evaluated by the correlation from[7]. The
calculation parameters for the simulation are
summarized in table 1.
Table 1
Calculation Parameters
Evaporator temperature (Te in °C) 5-(2.5)-12.5
Absorber temperature (Ta in °C) 30-(5)-40
Condenser Temperature (Tc in °C) 30-(5)-40
Effectiveness of pre-heater (%) 75
Effectiveness of pre-cooler (%) 75
Cooling load (kJ/h) 12600
4. Results and Discussion
Figure 2 shows the variation of coefficient of
performance (COP) of single effect vapour absorption
system with genera-tor temperature at which heat
is supplied at different values of evaporator
temperature (i.e. Te = 5.0, 7.5, 10.0 and 12.5 °C), the
condenser temperature and absorber temperature at
which heat is rejected to the surroundings are equal
and kept constant i.e. Ta = Tc = 30 °C. From this graph,
it is seen that the coefficient of performance of single
effect increases drastically from low values at low
generator temperature, reach to maximum value and

134
Fig. 3. Variation of coefficient of performance (COP) with condenser temperature (Tc)
for different evaporator temperature (Te).
Fig. 2. Variation of coefficient of performance (COP) with generator temperature (Tg)
for different evaporator temperature (Te).

135
then with further increase in the increase in the
generator temperature slightly decreases i.e. the
results show an optima. From this result it is also
observed that with increasing the evaporator
temperature for a particular generator coefficient of
performance increases.
Figure 3 shows the variation of coefficient
of performance (COP) of single effect vapour
absorption system with con-denser temperature at
which heat is rejected to surrounding at different
values of evaporator temperature (i.e. Te = 5.0, 7.5,
10.0 and 12.5 °C). From this graph, it is seen that the
coefficient of performance decreases gradually with
increases in condenser temperature for a particular
evaporator temperature. From this result it is also
observed that with decreasing the evaporator
temperature for a particular condenser temperature
coefficient of performance decreases.
Figure 4 shows the variation of coefficient of
performance of single effect absorption system with
evaporator temperature at which the refrigerated
space should be maintained at different values of
condenser temperature (Tc = 30, 35, 40 & 45 °C). From
the graph, it is observed that the coefficient of
performance increases gradually with increase in
evaporator temperature for a particular condenser
temperature. From this result it is also observed that
with increasing condenser temperature for a
particular evaporator temperature coefficient of
performance increases.
5. Conclusions
From the above result and discussion it is concluded
that coefficient of performance system has strong
effect on the operation condition. The performance
of system is dependent on generator temperature,
evaporator temperature and condenser temperature
simultaneously. It is found that the coefficient of
performance of presented single effect vapour
absorption refrigeration system increases with
increasing the generator and evaporator temperature
up to a certain limit but decreases with increasing
the condenser temperature. Therefore, to obtain
efficient performance of single effect vapour
absorption refrigeration system, it should be operated
at moderate generator, evaporator and condenser
temperature of vapour absorption refrigeration.
Fig. 4. Variation of coefficient of performance (COP) with evaporator temperature (Te)
for different condenser temperature (Tc).

136
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absorption refrigerator using aqueous lithium-
bromide: Effect of operating condition to
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Study and analysis of plate type heat exchanger
137
NUMAN ANSARI1, MOHD. ISLAM1 and SAYYED HAIDER2
1
Department of Mechanical Engg. Faculty of Engg.& Technology, Jamia Millia Islamia,New Delhi-110025,India
2
Department of Mechanical Engg., Al-Falah School of Engineering & Technology, Haryana-121004, India
*E-mail: numan.ansari5@gmail.com
Abstract
With the emerging trend in technology heat transfer dissipation from those device which required
certain temperature for their efficient operation in the major problem. In this regards high
technology is required to cool such devices. As far as heat exchanger is the major solution of such
problem. Plate heat exchanger are the exchangers having a number of plates combined together
having different corrugation for transfer the heat between the two fluid. An experimental
investigation are done on the plate type heat exchanger to estimate the value of heat transfer
characteristics by changing the mass flow rate and study the pressure drop. And from the
experiment estimate the value of heat transfer characteristics for hot and cold fluid, nusselt
number, pressure drop and effectiveness. It is shown that Nusselt number, pressure drop and
effectiveness are depends on the mass flow rate. This paper is concerned with the plate type heat
exchanger and investigation is carried out by considering the different works published in the
field of heat exchangers.
Key words : Plate heat exchanger (PHX), heat exchanger (HXCH), chevron angle, gaskets,
plate, flow arrangement, domestic hot water (DHW).
1. Introduction
Plate heat exchanger (PHE) are the exchangers
having a number of plates combined together having
different corrugation for transfer the heat between
the two fluid. Plate heat exchanger are widely used
in the industry and are commonly designed with the
corrugated channel surface resulting in the enhanced
heat transfer performance by increasing the area over
which heat transfer take place and generating a
vigorous mixing of effect within the working fluid.
Component of plate type heat exchanger are shown
in figure.
As shown in Figure 1, the plate heat exchanger is
basically a series of individual plates pressed between
two heavy end covers. These plates are gasketed,
welded or brazed together depending on the
application of the heat exchanger. The basic geometry
of plates used in plate heat exchanger is shown in
figure 2. Stainless steel is a commonly used metal
for the plates because of its ability to withstand
high temperatures, its strength, and its corrosion
resistance[1]. The entire assembly is held together by
the tie bolts. This has a major advantage over a
conventional heat exchanger in that the fluids are
exposed to a much larger surface area because the
fluids spread out over the plates. This facilitates the
transfer of heat, and greatly increases the speed of
the temperature change.
The concept behind a heat exchanger is the use
of pipes or other containment vessels to heat or cool
one fluid by transferring heat between it and another
fluid. In most cases, the exchanger consists of a coiled
pipe containing one fluid that passes through a
chamber containing another fluid. The walls of the
pipe are usually made of metal or another substance
with a high thermal conductivity to facilitate the
interchange, whereas the outer casing of the larger
chamber is made of a plastic or coated with thermal
insulation, to discourage heat from escaping from the
exchanger.
DOI No. : 10.5958/2454-7611.2017.00019.4

138
Chevron Angle , Typically varying from 20° to
65°,  is the measure of softness (small , low thermal
efficiencyand pressure drop) and hardness (large ,
high thermal efficiency and pressure drop) of thermal
and hydraulic characteristics of plates. Some authors
define "/2- " as the chevron angle[1].
Pressure drop (p) is in direct relationship to the
size of the plate heat exchanger. If it is possible to
increase the allowable pressure drop, and incidentally
accept higher pumping costs, then the heat exchanger
will be smaller and less expensive. As a guide,
allowable pressure drops between 20 and 100 kPa are
accepted as normal for water/water duties.
2. PHE Parts and their function
Plate with gaskets Plate heat exchangers consist
of pressed plates; the separating gaskets between each
plate; the end plates used to clamp the plate stack
together and the frame to hold the plate stack in place.
The plate is pressed metal. A wide range of metals
and corrugation shapes can be used that suit the
chemical, flow and corrosive properties of the media
passing across the plates[4].
Plates for an exchanger have indentations and
corruga-tions to encourage more turbulent flow
across them and to make thinner films of media to
promote better heat transfer. The headers to feed and
remove the fluids pass through all plates. Unwanted
headers are blocked off on a plate.
Gaskets, each plate have a gasket that produces
a sealing and channel system through the entire plate
pack in which the two heats exchanging media flow
in a counter-current direction.
The circular portion of a gasket stops the fluid
from going across the heat transfer plate and sends it
to next open channel. The remaining portion or field
gaskets directs the opposing fluid across the heat
transfer surface. The gaskets separate the plates and
create the thin chamber through which the fluid film
swirls and flows. They also serve the purpose of
directing the media from the entry port to the exit
port.
The frame is made up of thick steel pressure
retaining parts, the fixed cover and the movable cover
that when pulled together with the tightening bolts
from the pres-sure retaining structure for the plates.
The carrying bar and guide bar act as a carrier and
guide both the plates and movable cover. The heat
exchangers plates, which make up the heat transfer
surface, are clamped between two plates of steel with
the use of the tightening bolts. The heat exchanger
construction allows a plate heat exchanger to be easily
opened for inspection and cleaning. In a plate heat
exchanger corrugated plate like this one are used
between the barrier of hot fluid and cold fluid. The
corrugated plate increases the area of heat transfer.
PHE plate usually made of advance material like
titanium which makes plate stronger and durable.
The thickness of plate is 0.5 mm to 0.6 mm.
Fig. 1. Various parts of PHE
Fig. 2. Geometry of plate [1]

139
Flow arrangement, Plate heat exchangers are
very easy counter flow where hot and cold fluid flow
in opposite direction as shown in figure. The plate is
placed in such a way that the flow bond by each
successive plate alter-nates the hot fluid and cold
fluid.
The heat exchangers plates with gaskets are
arranged in an alternating pattern of left hand flow
and right hand flow to direct the fluids in an opposing
direction within the heat exchanger. The complete
assembly of all the plates and gaskets is called the
"Plate Pack".
3. Modelling of PHX and analysis of heat transfer
performance
The experimental set up presents the principal
geometry parameters and illustrates the experimental
setup established to investigate the heat transfer
characteristics in the corrugated channel for different
flow conditions. The basic components of the
experimental apparatus include a water loop, an air
loop, and a measurement system. The water loop
comprises a water tank containing a heater, a pump,
a flow meter, and a temperature controller.
Fig. 5. Flow arrangement of PHE
Fig. 3. Plate with gaskets [4]
port ring gasket
Flow ports
Fig. 4. Gaskets [4]
Fig. 6. Experimental set up of PHE
Importantly, all of the components in the water
system are thermally insulated such that wall
temperature of the corrugated channel can be
maintained at a nearly constant temperature. The air
loop consists of the test section containing the
corrugated channel, a blower, an air flow meter, and
a number of valves which enable the flow rate to be
adjusted. Additionally, a flow straightner can be
installed at the entrance of the test section to maintain
a uniform inlet flow. The test section is constructed
from Galvanized Iron (GI) sheets, each with
corrugated surface on both the sides. The two cases
are clipped between two corrugated plates, metal
plates to form the corrugated channel through which
the working fluid is passed. During experiments, hot
water was flowed through the two hollow cases to
maintain the channel surfaces at an approximately
constant temperature and thermocouples wrapped

140
in copper tubes and inserted in upper metal plates
were used to record the corresponding air
temperature. The side effect was avoided by
specifying a small aspect ratio for the channel such
that variations in the channel height could be
neglected. In the experiments, the temperature
distribution in the horizontal, middle plane of the
channel was monitored using thermocouples
positioned at different locations along the length of
the channel in the water loop and in air loop.The
temperature of the inlet and outlet water is measured
using mercury thermometers. The pressure of the air
at the inlet and outlet of the test section is measured
using the pressure gauges.
4. Results and Discussion
The experiments described herein represent the
study of fully developed heat transfer for water
flowing in a cor-rugated duct. The duct had a
corrugation angle of 29 degree and interval spacing
equal to the corrugation height. The Reynolds number
based on hydraulic diameter was varied from 1500
to 25,000, and the prandtl number was varied from 4
to 8.
Table 2. Counter Flow Condition (Air)
Air Position Distance Xm TX Tb hx Nux × 103
channel of X (cm) ºC ºC (KW/m2k)
Ma thermocouple (cm)
2.0×10–3 kg/s 1 9.7 29.1 42 43.75 7.13 45.43
2 48.5 66.5 45.5 47.25 9.43 66.93
3 84.5 49
hxm=8.28 Nux=56.18
Table 1. Counter Flow Condition (Water)
Surface temperature for 100 LPM
Water Position Distance Xm TX Tb hx Nux × 103
channel of X (cm) ºC ºC (KW/m2k)
Mw thermocouple (cm)
0.133 kg/s 6 12 11.25 70 67.5 88.30 8.79
5 10.5 29.25 65 66.5 38.25 12.73
4 48 46.75 68 66 85.43 8.43
3 45.5 66.25 64 65 18.57 6.01
2 87 86.20 66 64.75 81.93 7.34
1 85.5 63.5 hxm=62.49 Nux=8.66
Experimental investigation are done by changing
the mass flow rate in the experimental setup and
study the pressure drop and heat transfer
characteristics in the corrugated channel of the plate
heat exchanger. The experimental data are
substituted into the correlations to identify the
characteristics and effect on the Nusselt number by
changing the mass flow rate. The analytical results
show that local Nu and effectiveness are affected by
the change into the flow condition for a given set.
5. Conclusions
Although a conclusion may review the main points
of the paper, do not replicate the abstract as the
conclusion. A conclusion might elaborate on the
importance of the work or suggest applications and
extensions. Authors are strongly encouraged not to
call out multiple figures or tables in the conclusion-
these should be referenced in the body of the paper.
6. Conclusions
The authors wish to thank A, B, C. This work was
supported in part by a lished manuscript).

141
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142
Study of CFD approach to discretise first derivative
of partial differential equation
HASAN SHAMIM, SHADAB AHMAD and SHAH ALAM
Jamia Millia Islamia, New Delhi
*E-mail: hasanshmm@gmail.com
Abstract
The process of converting governing partial differential equations into algebraic equation is
known as discretisation. The finite difference method is one of the most powerful and simple
method to convert partial differential equation (PDE) into algebraic equation. The accuracy of
finite difference method increases with refining grid size. In this present study the finite difference
method (FDM) is used to determine the shear stress over a flat plate. This shear stress is function
of velocity gradient as given by Newton's Law of viscosity. The first derivative of velocity gradient
is replaced by forward difference, Reward difference and the central difference approaches. The
exact solution of equation is compared with approximate solution and the errors are determined
for different values of grid points spacing. It is found that central approach is more accurate
than forward and reward approaches. The effect of order of accuracy such as O(y), O(y)2,
O(y)3 has been also studied. It shows as order of accuracy increases, computational errors
decreases.
Key words : Discretisation, PDE, Finite difference method, Forward difference, Reward
difference, Central difference, Order of accuracy, Mesh spacing,
1. Introduction
Computational Fluid Dynamics (CFD) provides
a qualitative (sometimes even quantitative)
prediction of fluid flows by means of mathematical
modelling, Numerical methods and software tools[1].
These advantages of CFD over experiment based
approach are given as :
 Substantial reduction of lead time and cost
of new designs.
 Ability to study systems where controlled
experiments are difficult or impossible to
perform.
 Ability to study systems under hazardous
conditions.
The main problem with CFD is that code user
must have high skilled position. The assumptions,
made regarding type of flow e.g. two dimensional,
three dimensional, Compressible, Non compressible,
Viscous, Non viscous. Laminar, Turbulent should be
realistic and must also be able to handle convergence,
consistent, stability associated problems in the
solution[2]. However there are several applications
of CFD in different fields of daily life and engineering.
While analysing problems with CFD approach, we
get PDE[3]. These equations are first converted into
algebraic equations;only then solution of PDE is
possible. This process is known as Discretisation.
There are three different methods to discretise the
PDEs into algebraic equations. These methods are
finite difference method (FDM), Finite element
method (FEM) and Finite volume method (FVM)[4].
In this present analysis we are using FDM to discretise
PDE and observe the accuracy of solution.
2. Statement of Problem
In this we want to determine shear stress over a
flat plate, when air is flowing over it. The velocity
profile is vertical direction is assumed as :
DOI No. : 10.5958/2454-7611.2017.00020.0

Study of CFD approach to discretise first derivative of partial differential equation
143
 
  
 
= 1 –
y
L
u c e
Where c = 480
L is the length of plate (Let L = 3 cm)
We determine shear stress at a distance of
0.35 cm with step size of 0.10 cm, 0.15 cm, 0.20 cm,
0.25 cm, 0.30 cm, 0.35 cm, 0.40 cm.
Dynamic viscosity of air at 15°C, µ = 1.81×10–5
Pa-s
3. Methodology
i. On the basis of above parameters, We want
to find out shear stress near wall by using
Newton's law of viscosity, Given as :
wall = 
 
 
 
du
dy wall
ii. The velocity gradient which is first order
differential equation is discretised by using
Finite difference approach.
iii FDM for 1st order accuracy i.e. forward,
reward and central difference approaches
are used to discretise the equation. The
expressions are as given below[1,5]:
1
 

, i, j–
+ O( y)
i ju uu
dy y
Forward

 

, i, j – 1–
+ O( y)
i ju uu
dy y
Reward
1
2

 

, i, j – 1–
+ O( y)
*
i ju uu
dy y
Central
iv FDM for 2nd order accuracy i.e. forward,
reward/backward & central difference
approaches are used to discretise the
equation[6].
The expressions are as given below:-
2 3
2

 

, i, j + 1 , 2
+ 4* – *
+ O( y )
*
i j i ju u uu
dy y
Forward
23
2

 

, i, j – 1 , 2
* – 4*
+ O( y )
*
i j i ju u uu
dy y Reward
2 1 24
4
  
 

, i, j + 1 , , – 2
– + 4* – *
+ O( y )
*
i j i j i ju u u uu
dy y
Central
v. FDM for 3rd order accuracy i.e. forward,
reward/backward & central difference
approaches are used to discretise the
equation[7, 8].
The expressions are as given below :
3 13 18 11
6
 
 

, i, j + 2 , , 3
* + 9* * – *
+ ( y )
*
i j i j i ju u u uu
dy y
Forward
2 311 9 2
6

 

, i, j –1 , – , – 3
* – 18* * – *
+ ( y )
*
i j i j i ju u u uu
dy y
Reward
3 1 1 2 32 18 18 9 2
12
    
 

, i, j +2 , , , , – 3
* – 9* * – * * – *
+ O( y )
*
i j i j i j i j i ju u u u u uu
dy y
Central
vi The approximate solution of equation is
compared with exact solution at (y=.35) for
different step sizes (y) i.e. 0.10, 0.15, 0.20,
0.25, 0.30, 0.35, 0.40.
vii The effect of order of accuracy on solution
has been also observed. The order of accuracy
is taken as O(y), O(y)2, O(y)3 for
FORWARD, BACKWARD/REWARD &
CENTRAL difference method.
viii The errors are also represented in graph for
different step sizes and order of accuracy.

144
4. Result
Table 1. Errors in forward difference approach for 1st, 2nd & 3rd order of accuracy
S.l. No. Step size Error (%) Error (%) Error (%)
O(Y) O(Y)2 O(Y)3
1 0.1 1.65 0.04 0.001
2 0.15 2.46 0.08 0.003
3 0.2 3.26 0.14 0.007
4 0.25 4.05 0.22 0.013
5 0.3 4.84 0.31 0.022
6 0.35 5.61 0.42 0.035
7 0.4 6.38 0.54 0.051
Table 2. Errors in reward difference approach for 1st, 2nd & 3rd order of accuracy
O(Y) O(Y)2 O(Y)3
1 0.1 -1.69 0.04 -0.001
2 0.15 -2.54 0.09 -0.003
3 0.2 -3.41 0.16 -0.008
4 0.25 -4.28 0.25 -0.016
5 0.3 -5.17 0.36 -0.028
6 0.35 -6.07 0.50 -0.046
7 0.4 -6.97 0.66 -0.070
Table 3. Errors in central difference approach for 1st, 2nd & 3rd order of accuracy
O(Y) O(Y)2 O(Y)3
1 0.1 -0.02 0.04 -3.70E-05
2 0.15 -0.04 0.08 -1.88E-04
3 0.2 -0.07 0.15 -5.94E-04
4 0.25 -0.12 0.23 -1.45E-03
5 0.3 -0.17 0.33 -3.01E-03
6 0.35 -0.23 0.46 -5.58E-03
7 0.4 -0.30 0.60 -9.54E-03
Table 1. 1st order accuracy for forward, reward and central difference accuracy
forward reward central
1 0.1 1.65 -1.69 -0.02
2 0.15 2.46 -2.54 -0.04
3 0.2 3.26 -3.41 -0.07
4 0.25 4.05 -4.28 -0.12
5 0.3 4.84 -5.17 -0.17
6 0.35 5.61 -6.07 -0.23
7 0.4 6.38 -6.97 -0.30

Study of CFD approach to discretise first derivative of partial differential equation
145
Fig. 2. Errors in forward (series 1), reward (series 2) and central (series3) approach using O( y)2
Table 2. 2nd order accuracy for forward, reward and central difference approach
1 0.1 0.04 0.04 0.04
2 0.15 0.08 0.09 0.08
3 0.2 0.14 0.16 0.15
4 0.25 0.22 0.25 0.23
5 0.3 0.31 0.36 0.33
6 0.35 0.42 0.50 0.46
7 0.4 0.54 0.66 0.60
Fig. 1. Errors in forward (series 1), reward (series 2) and central (series3) approach using O( y)
ERROR(%)ERROR(%)

146
Table 3. 3rd order accuracy for forward, reward and central difference approach
1 0.1 0.001 -0.001 -3.70E-05
2 0.15 0.003 -0.003 -1.88E-04
3 0.2 0.007 -0.008 -5.94E-04
4 0.25 0.013 -0.016 -1.45E-03
5 0.3 0.022 -0.028 -3.01E-03
6 0.35 0.035 -0.046 -5.58E-03
7 0.4 0.051 -0.070 -9.54E-03
Fig. 3. Errors in forward (series 1), reward (series 2) and central (series3) approach using O( y)3
ERROR(%)
5. Conclusion
 The effect of grid spacing and order of
accuracy has been observed by calculating
shear stress.
 It is found the central difference approach has
least error for fix step size compare to
forward and backward difference approach.
 Higher order of accuracy has least error in
each approach.
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Dynamics: Basic with applications" Tata
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Main Page.

Thermal design of liquid cooled charge air cooler: A computational approach
147
Thermal design of liquid cooled charge air
cooler: A computational approach
TRIBHUWAN CHANDRA JOSHI* and YOGENDRA SINGH KUSHWAH
Subros Technical Centre, India
*E-mail: tribhuwan.joshi@subros.com
Abstract
Successive advent of vehicle emissions norms & strong emphasis on fuel efficiency have enforced
vehicle manufactures to deploy turbo charging of intake air prior to intake manifold. However
introduction of turbochargers also signify need of a heat exchanger called charge air cooler or
intercooler to reduce the temperature of turbocharged air to optimum limit prior to intake manifold
of engine. The major limitation of conventional air to air charge air coolers is that they yield low
heat transfer rate to weight ratio & low heat transfer rate to frontal area ratio characteristics.
Beside this at higher boost pressure and higher temperature conditions there are metallurgical
challenges for conventional air to air charge air coolers. Therefore; design optimization aimed at
improved heat transfer from charge air is the need of strict environmental norms (Euro V onward).
Rapid growth of automobile sector coupled with cutting edge technology development is also
leading demand for highly efficient as well as compact solutions for charge air cooler. This provide
motivation and challenge to design highly optimized new technology based system, which can
provide increased rate of heat transfer with lesser pressure drop & overall compact size. To
overcome discussed limitations of conventional air to air charge air cooler; the present research
explores thermal design of liquid cooled charge air cooling device with unique charge air flow
mechanism. The new design of liquid cooled charge air cooler provides multiple flow passes in
order to achieve advantages of both cross flow as well as counter flow type heat exchangers.
Multiple flow passes basically ensure maximum interaction of two heat exchanging fluids; hence
heat exchanger effectiveness gets improved. Charge air is introduced to the heat exchanger with
the help of an inlet tank header. The flow of charge air around the heat exchanger is precisely
controlled by a casing, which ensures a uniform guided flow to successive passes of heat exchanger.
An outlet tank header serves the purpose of supplying charge air to the engine intake manifold.
A Computational Fluid Dynamics (CFD) methodology is used to optimize flow dynamics of two
working fluids, namely liquid water and charged air coming out of turbocharger.
Key words : Automotive, CFD, Heat Transfer, Liquid Cooled Charge Air Cooler, Radiator,
Emission, Turbocharger
1. Introduction
With the rapid advancement of emission norms,
Turbochargers has become the integral part of engine
system these days. It not only helps to reduce the
pollutant emissions but also improves the fuel
efficiency.
Turbochargers are used to compress the ambient
air to a certain boost pressure prior to its admission
into the intake manifold in internal combustion
engines. So by compressing the air in turbocharger,
large amount of charge air is being inducted into
combustion chamber, So as to improve combustion
efficiency along with reduced pollutant emission.
However along with the compression, it also raises
the temperature of air; which in turns results in
decrease in density of combustion air.
To overcome this limitation a heat exchanger,
DOI No. : 10.5958/2454-7611.2017.00021.2

148
commonly known as Charge Air Cooler is being used
between turbo-charger and the intake manifold.
Wherein high temperature & high pressure air loses
its heat to cooling media (air or water). This basically
results in increased density of combustion air &
ultimately improved combustion/fuel efficiency of
vehicle. Further high boost pressure requirements of
intake air to meet latest emission norms (Euro V/
Euro VI) has emphasized the need of highly efficient
and durable design of heat exchangers. This will
ensure increased heat transfer rate along and less
charge air side pressure drop & overall compactness.
This requirement has enforced the technology
developers to explore liquid based charge air cooling
instead of traditional air to air charge air coolers.
To achieve the aforementioned objective, some
work has been done by researchers in the areas of
liquid cooled charge air coolers, Lamich et al. [1] has
disclosed a cross flow type liquid charge air cooler,
where liquid water is flowing in a U flow manner
through equally spaced tube banks, whereas charge
air flows through inter tube spacing to make a Charge
air flow path.
Maceroni et al.[2] has disclosed a Liquid cooled
charge air cooler directly integrated with Intake
manifold, in this arrangement charge air from inlet
tank flows through heat exchanger, where it loses its
heat with liquid water flowing through heat
exchanger tubes.
The majority of the work reported in existing
literature suggests either straight or U flow type
flow arrangement for liquid water, whereas
charge air flows through tube banks in the direction
normal to tube bank, to form a Cross flow type heat
exchanger. Thus better heat transfer characteristics
possible with counter flow type arrangements can't
be utilized.
Hence there is a scope of flow path optimization,
So as to achieve advantages of both cross as well as
counter flow type arrangements. Present study
explores an innovative charge air flow mechanism,
to form a cross- counter flow type arrangement[3]. So
as to ensure increased heat transfer rate along with
comparable charge air side pressure drop and overall
heat exchanger compactness.
A CFD methodology to evaluate the various
performance parameters of heat exchanger is used.
Fin Surfaces associated with the heat exchanger has
been modeled as a shell region[4], So as to take into
account conduction heat transfer though fins. The
CFD modeling strategy for heat exchangers has been
correlated with test results of baseline liquid to air
heat exchanger (radiator configuration) & it has been
found that CFD results are in close agreement with
test results. In a different study to develop correlation
between liquid water temperature and cooling air
Anders et al.[5] have also used CFD modeling strategy
for estimating the liquid water temperatures at
radiator inlet and found that estimated values were
within ± 4°C of the experimental data.
2. Theoretical Background
Overall heat transfer rate (Q) for heat exchangers
can be expressed by equation (1), (2) & (3).
Q =  .Cmin. (Tca_in-Tc_in)/3600 (1)
Charge Air Side :
Qca = mca .Cp_ca . (Tca_in-Tca_out) /3600 (2)
Liquid Water Side :
Qc = mc .Cp_c . (Tc_in-Tc_out) /3600 (3)
In perfect isolated system, heat gained by the cold
fluid (liquid) will be equal to heat lost by the hot fluid
(charge air).
Qc = Qca (4)
Where Heat exchanger effectiveness () is defined
as the ratio of the actual heat transfer rate (Q) to the
maximum possible heat transfer rate (Qmax); and
Cmin is minimum of heat capacities of both the fluids:
 = Q/Qmax (5)
Qmax = Cmin. (Tca_in-Tc_in) (6)
Cmin =Min. (mca .Cp_ca, mc .Cp_c) (7)
In current study a detailed investigation of
various flow configurations & their impact on various
design parameters has been discussed.
Where :
WHX : Weight of heat exchanger (kg)
VHX : Heat exchanger volume (m3)
W* H* D* fp : Width* Height* Depth* fin pitch (all in
mm)

149
Q : Heat rejection capacity (kW)
Qc : Liquid water (liquid) side heat rejection
capacity (kW)
Qca : Charge air side heat rejection capacity
(kW)
 : Heat exchanger effectiveness
mca : Mass flow rate of charge air (kg/h)
Va : Flow velocity of cooling air (m/s)
Cp_ca : Specific heat of charge air (kJ/kg. K)
Ta_in : Cooling air inlet temperature (ºC)
Tca_in : Charge air inlet temperature (ºC)
Tca_out : Charge air out temperature (ºC)
mc : Mass flow rate of liquid water (kg/min)
Cp_c : Specific heat of liquid water (kJ/kg. K)
Tc_in : Liquid water inlet temperature (ºC)
Tc_out : Liquid water out temperature (ºC)
(cs) : Heat exchanger Section
BC : Boundary conditions
Temp. : Temperature (ºC)
3. CFD Modeling
This section presents CFD model considered for
the analysis, governing assumptions and validation
of CFD results with test data. Modeling of Heat
exchanger geometry has been done in commercially
available preprocessing software called ANSA
(Version 15.1.2).
A commercial CFD code called Star CCM V 11.04
has been used as a solver and as a post processer.
Volume meshing has been carried out in the same
software. For the simplicity of the analysis following
assumptions has been considered.
 Steady state based solver has been considered
for both heat exchanging fluids.
 Within heat exchanger liquid water side as
well as charge air side flow is incompressible.
 Liquid water flow rate through heat
exchanger tubes is uniformly distributed
 Charge air side inlet/outlet headers have
been considered as longitudinally extending
rectangular ducts. Further size of rectangular
duct is defined by available free flow area
with various flow configurations.
 To take into account effect of change in fluid
properties, all the properties specified to the
CFD code are based on estimated mean
temperature values of hot and cold fluid.
3.1 Heat Exchanger Geometry Modeling & Result
Deduction Methodology
For the simplification of the analysis & to save
the overall computational time, a small section (Fig.
1) of heat exchanger has been modeled. This model
consists of geometry of two fins separated apart by a
tube. Further both the fins are covered by half tube
sections on both the sides. Liquid water flows
through both single tube & half tube sections &
spacing between tubes forms the flow path for air.
Inlet mass flow rate for both the working fluids (i.e.
liquid water & air) has been calculated based on
overall mass flow rate through the complete heat
exchanger. Complete flow length (i.e. tube length for
the liquid water side & core depth for the air Side)
for both the heat exchanging mediums has been
modeled, So as to closely estimate the outlet
temperatures for both the fluids leaving the heat
exchanger.
Fig. 1. Tube, fin Heat Exchanger cut
Section for CFD modeling
A lot of complexity involved with design of
charge air side inlet-outlet headers; which depends
on specific packaging space & piping layout
associated with turbo charger & air intake manifold,
Therefore; in current study charge air inlet and outlet
headers for various flow configurations mentioned
in section 4, has been considered as rectangular ducts
extended from available free flow area for a particular
flow configuration (D1-D4). This will ensure uniform
flow through inlet headers.
As complete flow length of both the fluids being
considered in CFD model, hence outlet temperatures
for both the fluids calculated from CFD analysis can

150
be used for calculating the various performance
parameters of complete heat exchanger.
3.2 Solver Numeric & Boundary Condition's
Governing momentum and energy equations are
Reynolds-averaged Navier-Stokes equations and
realizable k- turbulence model with all Y+ wall
treatment being used for modeling turbulent nature
of flow.
All the heat exchanger surfaces, where modeling
of wall thickness & subsequently mesh generation
was possible have been modeled as a solid. However,
in case of fins, where modeling of thickness is not
possible; all the fin walls has been modeled as a zero
thickness surfaces. Further to take into account heat
conduction through fins, three dimensional Shell
feature of Star CCM software has been used.
Following type of BC specification method has
been used for the analysis.
 Inlet boundaries for both the fluids have been
defined as Mass Flow inlets with associated
fluid temperatures.
 However outlet boundaries have been
defined as Pressure outlets.
3.3 Validation of CFD Approach & Results
To validate the CFD modeling strategy, an
available reference heat exchanger also called as
radiator having certain tube fin configuration has
been first tested in calorimeter lab (Fig. 2). CFD
results have been extracted for a range of liquid water
flow rates with fixed liquid water in temperature.
However, cooling air side parameters at the inlet have
been kept fixed for all the cases. Typical specifications
& Boundary conditions for reference heat exchanger
have been specified in Table 1.
Fig. 3 shows temperature distribution at the
centre plane of the heat exchanger obtained from CFD
simulations. From temperature profile it is quite
evident that high temperature water is flowing
through tubes, whereas cooling air is allowed to flow
through inter tube spacing & external fins.
Table 1. BC & Corce size specification for radiator sample
Radiator Core Air Liquid Flow Liquid Air
Velocity (100% Water) Inlet Temp. Inlet Temp.
Width : 295 mm; Height : 202.6 mm;
Depth : 16 mm; Fin Pitch :2.4 mm 4.5 m/s (40 - 60) kg/min 85 °C 20 °C
Fig. 2. Component Calorimeter test setup
for radiator testing
Fig. 3. Temperature distribution across the
HX obtained from CFD
The comparisons of CFD results and calorimeter
lab have been presented in Fig. 4 & 5. From Fig. 4, it
is evident that liquid water out temperature obtained
from CFD are in close agreement with calorimeter
results. Further liquid water side heat rejection rate
(Fig. 5) calculated from CFD results are closely
matching with test results with an accuracy of ± 5 %.

151
Fig. 4. Liquid water out Temp Vs Liquid
water mass flow rate
Fig. 6. Single Pass Cross Flow Heat Exchanger
Fig. 5. Heat Rejection Capacity Vs Liquid
water mass flow rate
4. Investigations of various flow configurations of
liquid cooled charge air cooler
Based on physics several flow configurations are
possible in liquid cooled charge air coolers. To
identify the optimum flow configuration following
four flow configurations (D1 to D4) has been studied.
A "flat-tube & fin" type heat exchanger having core
Size of Width 295mm*Height 202.6mm*depth
16mm*fin pitch 2.4 mm, is being considered for all
the flow configurations. Further In case of
configuration D2, two heat exchanger core's are
spaced at a gap of 4 mm.
4.1 Flow Configuration 1 (D1)
Fig. 6 shows the flow configuration for single
pass cross flow heat exchanger (D1). In this
arrangement charge air (fluid 1) enters normal to
tube bank, whereas liquid water (fluid 2) is flowing
through tubes.
Fig. 7 shows the flow configuration for two banks
cross flow heat exchanger (D2). In this arrangement
charge air (fluid 1) enters normal to front tube bank
and exits through rear tube bank, whereas liquid
water (fluid 2) is allowed to flow from rear tube bank
first and then it is transferred to front tube bank via
intermediate headers.
Fig. 7. Two Bank Cross Flow Heat Exchanger
Fig. 8 shows the flow configuration for two pass
cross-counter flow heat exchanger (D3). In this
arrangement charge air (fluid 1) is being circulated
around the tube bank in two numbers of passes.
Charge air is first allowed to flow through 50% of

Ijre published paper 7(3), 2017

Ijre published paper 7(3), 2017

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