CFD Analysis for Flow through Glass Wool as Porous Domain in

IJISET - International Journal of Innovative Science, Engineering & Technology, Vol. 1 Issue 7, September 2014.
www.ijiset.com
ISSN 2348 – 7968
CFD Analysis for Flow through Glass Wool as Porous Domain in
Exhaust Muffler
S.Rajadurai1, Suraj Sukumaran2, P.Madhusudhanan2
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1
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Head R&D, Sharda Motor
Chennai, Tamilnadu, India
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Sr. Engg R&D, Sharda Motor
Chennai, Tamilnadu, India
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Abstract
The paper summarizes a candid methodology of simulating a
precise pressure drop analysis using computational fluid
dynamics (CFD) for an exhaust muffler assembly having glass
wool. The traditional CFD methodology does not consider glass
wool because the pressure drop simulation with glass wool gives
a deviation of 20-40% with experimental data due to inconsistent
structure. A novel modeling approach is presented which
includes the glass wool region as POROUS DOMAIN in exhaust
muffler. Coefficient of porosity in glass wool is calculated from
one dimensional gas simulation software - WAVE by Ricardo.
Analysis is simulated using CFD code via Star CCM+ by CDAdapco. The simulated pressure drop results using CFD with
glass wool are compared with those of the experimental data
which are in very good agreement.
Keywords: co-efficient of porosity, exhaust muffler, glass wool,
porous domain, precise, pressure drop, 1D analysis.
1. Introduction
Stern demand for exhaust system development from
OEM’s, necessitates tier-1 suppliers to develop systems in
a stringent time frame. Simulation comes into play to
cover up these design and development (D&D) time and
consecutively to reduce prototype cost. Even though
precise analytical prediction helps in reducing D&D time
frame, analyst always has to follow the experimental
results. Finite volume methods are used to obtain flow
characteristics and backpressure values of mufflers.
Absorptive mufflers are difficult to analyze using CFD
because of its inconsistency and complexity in modeling
glass wool (porous media). CFD and experimental results
deviates while validating pressure drop across the glass
wool muffler system. Coefficients of porosity are
calculated from experimental data but preparing an exhaust
muffler proto initially and then analyzing using CFD does
not give an optimum and cost effective solution.
Therefore, it requires a highly fidelity 1D tool like WAVE
which can calculate pressure drop values of an exhaust
muffler including glass wool properties. Hence, coefficient of porosity can also be calculated from 1D
pressure drop. Having used of this method, effect of
backpressure on different parameters can be examined
without prototyping and best suitable muffler can be
determined in the design phase itself. Further value
targeted product can be achieved in time and low cost.
Design and analysis of flow characteristics of exhaust
system by Atul A. Patil studies the effect of backpressure
on engine performance [1]. Change in porosity of internal
tube has pronounced effect on the backpressure. If the
porous area increases the back pressure will increase
respectively [2]. Muffler pre-processing methodology and
comparative study by Rajadurai et al. points out preprocessing methodology of CFD tool having glass wool
inserted into an exhaust chamber should split as a separate
collector region for assigning glass wool properties [3].
Studies on mathematical modeling of porous media to find
inertial resistance and viscous resistances, explains
pressure drop test on a porous media should initially
conduct and subsequently the corresponding analysis are
simulated using CFD for precise pressure drop analysis
across porous media [4].
Conventionally CFD analysis is performed for reactive
mufflers [5-8]. CFD analysis on absorptive mufflers using
glass wool is very uncommon. A novel approach is
undertaken to model a glass wool region in CFD and also
effective method to calculate porous coefficients for glass
wool. By this method a precise and specific flow
characteristics could attain for absorptive type of exhaust
mufflers.
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IJISET - International Journal of Innovative Science, Engineering & Technology, Vol. 1 Issue 7, September 2014.
www.ijiset.com
ISSN 2348 – 7968
𝜕𝑢𝑗
�=0
𝜕𝑥𝑗
2. Simulation Model
CAD model of the present muffler which will be examined
in the paper is shown in fig.1. As shown, in fig.1 the
muffler consists of perforated inlet and outlet pipes and
one perforated tube and two non-perforated baffles. The
perforated rates of inlet pipe, outlet pipe and tube are
approximately 31%, 34% & 34% respectively.
Furthermore the muffler has three expansion chambers.
Glass wool is packed in perforated parts i.e. in middle
chamber. Perforated parts of inlet and outlet pipes create a
cross flow inside the muffler.
𝜌�
Momentum:
𝜌
𝜕
𝜕𝑝 𝜕𝜏𝑖𝑗
(𝑢𝑗𝑢𝑖) = −
+
+ 𝑆𝑐𝑜𝑟 + 𝑆𝑐𝑓𝑔
𝜕𝑥𝑗
𝜕𝑥𝑗 𝜕𝑥𝑗
Where ρ is density, 𝑢𝑗 is jth Cartesian velocity, p is static
pressure, 𝜏𝑖𝑗 is viscous stress tensor.
R
R
R
R
4. Boundary Conditions
Air is used as fluid media, which is assumed to be steady
and comparable. High Reynolds number k-ε turbulence
model is used in the CFD model. This turbulence model is
widely used in industrial applications. The equations of
mass and momentum are solved using SIMPLE algorithm
to get velocity and pressure in the fluid domain. The
assumption of an isotropic turbulence field used in this
turbulence model is valid for the current application.
The CFD analysis of this model would be passing air at
fixed mass flow rate through the muffler and measuring
pressure drop across the glass wool muffler system under
ambient temperature. The time conditions implemented are
steady state. The mass flow input is 50 kg/h to 200 kg/h at
303K and outlet pressure of 1 atm.
Fig. 1 CAD model of base muffler
5. Post Processing Results - Traditional
Methodology (Without Glass Wool)
3. Three Dimensional Study
A three-dimensional model of exhaust muffler with glass
wool is generated in CFD tool Star CCM+ v9.02 for the
analysis.
The velocity, pressure and temperature contour for the
muffler test in CFD without considering glass wool is
shown in fig 2.
3.1 Modeling and Meshing
The geometry of the element is made as polyhedral mesh,
with a refined prism layer mesh near the wall. The k-ε
turbulence model is used, with standard wall functions for
near-wall treatment. The model has approximately 1.4
million cells with maximum skewness angle of 85 degree.
3.2 Governing Equations
CFD solver Star CCM+ is used for this analyze. It is a
finite volume approach based solver which is widely used
in industries. Governing equations solved by the software
for these analyze in tensor Cartesian form are following:
Continuity:
(a) Velocity (m/s) contour plot
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IJISET - International Journal of Innovative Science, Engineering & Technology, Vol. 1 Issue 7, September 2014.
www.ijiset.com
ISSN 2348 – 7968
and boundary conditions except glass wool have been kept
same as in the experimental analysis of muffler system.
The actual test setup is shown in fig 4. The CFD results
without considering glass wool are shown in table I and
comparison chart is shown in fig. 5. CFD and experimental
values shows 21% to 44% of deviation which evidently
shows flaws in traditional methodology.
(b) Pressure (kPa) contour plot
Fig. 4 Muffler tested in lab
(c) Temperature (K) contour plot
Table I: Test Lab Vs CFD (without glass wool) results
Fig. 2 Post processing results - Without considering glass wool
6. Experimental Setup
MFR (kg/h)
𝚫𝐩 (kPa)
Test Lab
𝚫𝐩 (kPa)
CFD
% Error
50
100
150
200
0.16
0.46
1
1.74
0.089
0.34
0.77
1.36
-44
-26
-23
-21
Fig. 3 Experimental setup for back pressure
The experimental setup of cold flow air control system for
backpressure measurement is shown in fig 3. Backpressure
across the system is analyzed with the aid of differential
pressure sensor by placing the front & rear measuring ends
at 50mm distance form inlet & outlet of muffler assembly
respectively. Mass flow rate is increased from 50 to 200
kg/h & the measurements are acquired for two minutes
time span at all stages.
Fig.5 Pressure drop comparison of experimental and CFD (without glass
wool) value
CFD analysis of the muffler tested in experiment has been
performed. All the solver conditions, turbulence modeling
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IJISET - International Journal of Innovative Science, Engineering & Technology, Vol. 1 Issue 7, September 2014.
www.ijiset.com
ISSN 2348 – 7968
7. Problem Definition
The problem is to correlate CFD boundary conditions with
real time simulations which necessitate reducing design
and development time. Porous coefficients of glass wool
can also be calculated from experimental data. But to
reduce prototype cost and design process, it can also be
calculated from 1D simulation (e.g. WAVE).
8. Glass Wool Modeling - Novel Approach
(b) Porous Domain
Glass wool is packed in perforated parts. In CFD a 3D
geometry glass wool part cannot be merged and meshed
with perforated geometry pipes. Therefore the novel
approach to model glass wool region is to close all the
upper layer of the perforated holes as shown in fig 6.
Fig. 7 Muffler Surface Topology
9. Mathematical Modeling - Porous Glass
Wool
For porous media, it is assumed that, within the volume
containing the distributed resistance there exists a local
balance everywhere between pressure and resistance forces
such that [4].
𝜕𝑝
−𝐾𝑖𝑣𝑖 =
𝜕𝜉𝑖
Fig. 6 Closing the upper layer of perforated holes
After closing all the upper layer of perforated holes and
non-manifold edges the muffler surface topology will be
split up in to two domains i.e. fluid domain and porous
domain (middle chamber) as shown in fig 7.
Where 𝜉𝑖 (i = 1, 2, 3) represents the (mutually orthogonal)
orthotropic directions. 𝐾𝑖 is the permeability, 𝑣𝑖 is the
superficial velocity in direction 𝜉𝑖 The permeability 𝐾𝑖 is
assumed to be a quasi linear function of the superficial
velocity. Superficial velocity at any cross section through
the porous medium is defined as the volume flow rate
divided by the total cross sectional area (i.e. area occupied
by both fluid and solid).
To find the inertial resistance and viscous resistance the
pressure drop analysis was conducted in 1D WAVE
simulation for mass flow rates from 50 kg/h to 200 kg/h.
The mass flow values are converted to velocities using the
flow area and air density and corresponding pressure drop
results are shown in table 2. Velocity (U) v/s Pressure drop
(Δp) plotted in the graphical representation. From the plot
we can find the polynomial function for the pressure drop
shown in fig. 8.
Table 2: 1D Data from WAVE
(a) Fluid Domain
Velocity (m/s)
ΔP (kPa) WAVE
0
0.5
1
1.5
2
0
0.11
0.5
1.08
1.79
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IJISET - International Journal of Innovative Science, Engineering & Technology, Vol. 1 Issue 7, September 2014.
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ISSN 2348 – 7968
(b) Pressure (kPa) contour plot
Fig.8 Regression curve showing Velocity Vs Pressure Drop Plot
For porous media,
Δp
= −(𝑃𝑖𝗅v𝗅 + Pv)v
𝐿
Where, L is the length of the porous media in stream wise
𝑎
𝑏
direction. 𝑃𝑖 = is porous inertial resistance. 𝑃𝑣 =
is
𝐿
𝐿
porous viscous resistance. v is the superficial velocity
The polynomial equation for unit length,
Δp = 2035.484𝑥2 + 444.1935𝑥
Calculated Porosity Coefficients from 1D analysis,
Porous Inertial Resistance (Pi) = 2035.484 kg/m^4
Porous Viscous Resistance (Pv) = 444.193 kg/m^3-s
10. Observations
The velocity, pressure and temperature contours for the
muffler test in CFD considering porous glass wool along
cross- stream directions is shown in fig 9. From post
processing results it can be observed that with glass wool
temperature flow is less and pressure drop value is high
across the glass wool muffler system. With glass wool
velocity decrease and pressure drop increase, hence more
sound will attenuate for absorptive type of exhaust
mufflers.
(c) Temperature (K) contour plot
Fig.9 Post processing results - With considering glass wool
The CFD results considering glass wool are shown in table
3 and comparison chart is shown in fig.10. Both CFD and
experimental values have less than 2% deviation which
clearly indicates that the novel approach followed
correlates with the real time condition of glass wool
muffler system. Unlike 1D WAVE simulation, in CFD gas
distribution can be well studied across glass wool muffler
system which will be constructive to optimization for
internal exhaust parts.
Table 3: Test Lab Vs CFD (with glass wool)
MFR (kg/h)
𝚫𝐩 (kPa)
Test Lab
𝚫𝐩 (kPa)
CFD
% Error
50
0.16
0.118
-26
100
0.46
0.453
-1.5
150
1
1.008
0.8
200
1.74
1.764
1.3
(a) Velocity (m/s) contour plot
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IJISET - International Journal of Innovative Science, Engineering & Technology, Vol. 1 Issue 7, September 2014.
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ISSN 2348 – 7968
"An analysis of geometric parameters effects on flow
characteristic of a reactive muffler", Istanbul Technical
University, 17th International Research Expert Conference,
sept-2013.
[10] Star CCM+ User Guide.
Acknowledgement
Fig.10 Pressure drop comparison of experimental and CFD (with glass
wool) values
11. Conclusion
Fully utilizing the 1D WAVE simulation, porous
calculation for glass wool can be done. These data proved
to be useful in calculating a precise backpressure
distribution and flow characteristics for an exhaust muffler
assembly. Thus helping in validating the muffler system
for various experimental test like thermal shock, acoustics,
etc.
References
[1]
Atul A. Patil, L.G. Navale and V.S. Patil, "Design, Analysis of
Flow Characteristics of Exhaust System and Effect of Back
Pressure on Engine Performance", IJEBEA, 2014.
[2]
Sudarshan Dilip Pangavhane, Amol Bhimrao Ubale, Vikram
A Tandon and Dilip R Pangavhane, "Experimental and CFD
Analysis of a Perforated Inner Pipe Muffler for the Prediction
of Backpressure, IJET, Oct-Nov 2013.
[3]
S. Rajadurai, Suresh Natarajan and N. Manikandan, "Muffler
Pre-Processing Methodology and Comparative Study Using
Hypermesh", HTC conference, 2012.
[4]
P.Karuppusamy and R. Senthil, “Design, analysis of flow
characteristics of catalytic converter and effects of
backpressure on engine performance", IJREAT, Issue 1,
Volume 1, March-2013.
[5]
D. Tutunea, M.X. Calbureanu and M. Lungu, "The
computational fluid dynamics (CFD) study of fluid dynamics
performances of a resistance muffler", IJOM, Issue 4, Volume
7, 2013.
[6]
Dragos Tutunea, Madalina and lungu Mihai, "Computational
fluid dynamics analysis of a resistance muffler", Recent
Advances in Fluid Mechanics and Heat & Mass Transfer,
1978.
[7]
Yunshi Yao, Shaodong Wei, Jinpeng Zhao, Shibin Chen,
Zhongxu Feng and Jinxi Yue, "Experiment and CFD Analysis
of Reactive Muffler", RJASET, March-2013.
[8]
Zeynep Parlar, Sengul Ari, Rıfat Yilmaz, Erdem Ozdemir, and
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[9]
The authors would like to thank Mr. S. Ananth, Sharda
Motor, R&D for designing the CAD geometry and also
Mr. Aditya Prabakar, Technical Support Engineer from
CD-Adapco for his help in Star CCM+ software.
Biographies
Dr. S. Rajadurai, Ph. D.
Dr. S Rajadurai, born in Mylaudy,
Kanyakumari District, Tamil Nadu, India,
received his Ph.D. in Chemistry from IIT
Chennai in 1979. He has devoted nearly 35 years
to scientific innovation, pioneering theory and
application through the 20th century, and
expanding strides of advancement into the 21st
century. By authoring hundreds of published papers and reports and
creating several patents, his research on solid oxide solutions, free
radicals, catalyst structure sensitivity, and catalytic converter and exhaust
system design has revolutionized the field of chemistry and automobile
industry.
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Dr. Rajadurai had various leadership position such has the Director
of Research at Cummins Engine Company, Director of Advanced
Development at Tenneco Automotive, Director of Emissions at
ArvinMeritor, Vice-President of ACS Industries and since 2009 he is the
Head of R&D Sharda Motor Industries Ltd. He was a panelist of the
Scientists and Technologists of Indian Origin, New Delhi 2004. He is a
Fellow of the Society of Automotive Engineers. He was the UNESCO
representative of India on low-cost analytical studies (1983-85). He is a
Life Member of the North American Catalysis Society, North American
Photo Chemical Society, Catalysis Society of India, Instrumental Society
of India, Bangladesh Chemical Society and Indian Chemical Society.
Suraj Sukumaran
Suraj Sukumaran is a Sr. Engineer at Sharda
Motor, R&D, Chennai. During his academic
year, he was awarded in merit list for
achieving 44th rank among 2407 students in
Mechanical Engineering department from
Anna University, Chennai. He has been
involved in simulating Flow Thermal analysis
in CFD for automobile exhaust system of
passenger cars and off road vehicles. His area is mainly on flow & heat
transfer simulation including uniformity index, velocity index, pressure
drop, HEGO index, conjugate heat transfer analysis and chemical
modeling. He is currently working on methodologies and strategies in
CFD analysis for better optimization of exhaust system development. He
is also involved in various advanced development research like SCR,
DPF, CO 2 & NH 3 .
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Erdem Ozdemir, Rifat Yılmaz, Zeynep Parlar and Sengul Arı,
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IJISET - International Journal of Innovative Science, Engineering & Technology, Vol. 1 Issue 7, September 2014.
www.ijiset.com
ISSN 2348 – 7968
P. Madhusudhanan
P. Madhusudhanan is a Sr. Engineer at Sharda
Motor, R&D, Chennai. He is a multi role performer
in the path of excellence in flow sciences. His job
profile as flow lab in charge come CFD analyst
paved the ways to understanding the virtual & real
condition flow behavior and also his pursuing
master degree in engineering is assisting him to
broaden his view point from theory to application.
The current researches over know-how of flow behavior in emission &
sound control devices has led to the development of 1-d tools which is
evaluated with virtual & real condition analysis. .
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