One important safety issue in automotive industry is the efficient cooling of brake system. This research work aims to introduce an optimized cooling vane geometry to enhance heat removal performance of ventilated brake disks. The novel idea of using airfoil vanes is followed as the basis of this investigation (Nejat et al., 2011, “Heat Transfer Enhancement in Ventilated Brake Disk Using Double Airfoil Vanes,” ASME J. Therm. Sci. Eng. Appl., 3(4), p. 045001). In order to perform the optimization technique efficiently, an integrated shape optimization process is designed. According to the aerodynamic and heat transfer considerations, first an appropriate airfoil is selected as the base profile to be optimized. For the shape modification purpose, a curve parameterization method named class shape transformation (CST) is utilized. The control parameters defined in CST method are then established as the geometrical design variables of an improved territorial particle swarm optimization (TPSO) algorithm. In order to overcome the potential bottleneck of high computational cost associated with the required computational fluid dynamics (CFD)-based function evaluations, TPSO algorithm is coupled with a predictive artificial neural networks (ANN), well trained with an input dataset designed based on the Taguchi method. The obtained profile shows an evident convective heat dissipation improvement accomplished mainly via airflow acceleration over the vanes, avoiding early flow detachment and adjusting the flow separation region at the rear part of the suction sides. The results also reveal the approaches by which such a superior performance is achieved by means of the modified surface curvatures.

References

References
1.
Day
,
A. J.
, and
Newcomb
,
T. P.
,
1984
, “
The Dissipation of Frictional Energy From the Interface of an Annular Disc Brake
,”
Proc. Inst. Mech. Eng., Part D
,
198
(
3
), pp.
201
209
.
2.
Lee
,
K.
,
1999
, “
Numerical Prediction of Brake Fluid Temperature Rise During Braking and Heat Soaking
,”
SAE Trans.
,
108
(
6, Part 1
), pp.
897
905
.
3.
Hunter
,
J. E.
,
Cartier
,
S. S.
,
Temple
,
D. J.
, and
Mason
,
R. C.
,
1998
, “
Brake Fluid Vaporization as a Contributing Factor in Motor Vehicle Collisions
,”
SAE
Paper No. 980371.
4.
Mackin
,
T. J.
,
Noe
,
S. C.
,
Ball
,
K. J.
,
Bedell
,
B. C.
,
Bim-Merle
,
D. P.
,
Bingaman
,
M. C.
,
Bomleny
,
D. M.
,
Chemlir
,
G. J.
,
Clayton
,
D. B.
,
Evans
,
H. A.
, and
Gau
,
R.
,
2002
, “
Thermal Cracking in Disc Brakes
,”
Eng. Failure Anal.
,
9
(
1
), pp.
63
76
.
5.
Gao
,
C. H.
,
Huang
,
J. M.
,
Lin
,
X. Z.
, and
Tang
,
X. S.
,
2007
, “
Stress Analysis of Thermal Fatigue Fracture of Brake Disks Based on Thermomechanical Coupling
,”
ASME J. Tribol.
,
129
(
3
), pp.
536
543
.
6.
Orthwein
,
W. C.
,
2004
,
Clutches and Brakes Design and Selection
,
2nd ed.
,
Marcel Dekker
,
New York
.
7.
Limpert
,
R.
,
1999
,
Brake Design and Safety
,
2nd ed.
,
SAE International
,
Warrendale, PA
.
8.
Limpert
,
R.
,
1975
, “
Cooling Analysis of Disc Brake Rotors
,”
SAE
Paper No. 751014.
9.
Belhocine
,
A.
, and
Bouchetara
,
M.
,
2012
, “
Thermal Behavior of Full and Ventilated Disc Brakes of Vehicles
,”
J. Mech. Sci. Technol.
,
26
(
11
), pp.
3643
3652
.
10.
Johnson
,
D. A.
,
Sperandei
,
B. A.
, and
Gilbert
,
R.
,
2003
, “
Analysis of the Flow Through a Vented Automotive Brake Rotor
,”
ASME J. Fluids Eng.
,
125
(
6
), pp.
979
986
.
11.
Sakamoto
,
H.
,
2004
, “
Heat Convection and Design of Brake Discs
,”
Proc. Inst. Mech. Eng. Part F
,
218
(
3
), pp.
203
212
.
12.
McPhee
,
A. D.
, and
Johnson
,
D. A.
,
2008
, “
Experimental Heat Transfer and Flow Analysis of a Vented Brake Rotor
,”
Int. J. Therm. Sci.
,
47
(
4
), pp.
458
467
.
13.
Wallis
,
L.
,
Leonardi
,
E.
,
Milton
,
B.
, and
Joseph
,
P.
,
2002
, “
Air Flow and Heat Transfer in Ventilated Disc Brake Rotors With Diamond and Tear-Drop Pillars
,”
Numer. Heat Transfer, Part A
,
41
(
6–7
), pp.
643
655
.
14.
Nejat
,
A.
,
Aslani
,
M.
,
Mirzakhalili
,
E.
, and
Asl
,
R. N.
,
2011
, “
Heat Transfer Enhancement in Ventilated Brake Disk Using Double Airfoil Vanes
,”
ASME J. Therm. Sci. Eng. Appl.
,
3
(
4
), p.
045001
.
15.
Yan
,
H. B.
,
Zhang
,
Q. C.
, and
Lu
,
T. J.
,
2015
, “
An X-Type Lattice Cored Ventilated Brake Disc With Enhanced Cooling Performance
,”
Int. J. Heat Mass Transfer
,
80
, pp.
458
468
.
16.
Yan
,
H. B.
,
Zhang
,
Q. C.
, and
Lu
,
T. J.
,
2016
, “
Heat Transfer Enhancement by X-Type Lattice in Ventilated Brake Disc
,”
Int. J. Therm. Sci.
,
107
, pp.
39
55
.
17.
Yan
,
H. B.
,
Mew
,
T.
,
Lee
,
M. G.
,
Kang
,
K. J.
,
Lu
,
T. J.
,
Kienhöfer
,
F. W.
, and
Kim
,
T.
,
2015
, “
Thermofluidic Characteristics of a Porous Ventilated Brake Disk
,”
ASME J. Heat Transfer
,
137
(
2
), p.
022601
.
18.
Xie
,
G.
,
Song
,
Y.
,
Asadi
,
M.
, and
Lorenzini
,
G.
,
2015
, “
Optimization of Pin-Fins for a Heat Exchanger by Entropy Generation Minimization and Constructal Law
,”
ASME J. Heat Transfer
,
137
(
6
), p.
061901
.
19.
Najafi
,
H.
,
Najafi
,
B.
, and
Hoseinpoori
,
P.
,
2011
, “
Energy and Cost Optimization of a Plate and Fin Heat Exchanger Using Genetic Algorithm
,”
Appl. Therm. Eng.
,
31
(
10
), pp.
1839
1847
.
20.
Hajmohammadi
,
M. R.
,
Shirani
,
E.
,
Salimpour
,
M. R.
, and
Campo
,
A.
,
2012
, “
Constructal Placement of Unequal Heat Sources on a Plate Cooled by Laminar Forced Convection
,”
Int. J. Therm. Sci.
,
60
, pp.
13
22
.
21.
Madadi
,
R. R.
, and
Balaji
,
C.
,
2008
, “
Optimization of the Location of Multiple Discrete Heat Sources in a Ventilated Cavity Using Artificial Neural Networks and Micro Genetic Algorithm
,”
Int. J. Heat Mass Transfer
,
51
(
9
), pp.
2299
2312
.
22.
Palmer
,
E.
,
Mishra
,
R.
, and
Fieldhouse
,
J.
,
2009
, “
An Optimization Study of a Multiple-Row Pin-Vented Brake Disc to Promote Brake Cooling Using Computational Fluid Dynamics
,”
Proc. Inst. Mech. Eng., Part D
,
223
(
7
), pp.
865
875
.
23.
Galindo-Lopez
,
C. H.
, and
Tirovic
,
M.
,
2008
, “
Understanding and Improving the Convective Cooling of Brake Discs With Radial Vanes
,”
Proc. Inst. Mech. Eng., Part D
,
222
(
7
), pp.
1211
1229
.
24.
Munisamy
,
K. M.
,
Shuaib
,
N. H.
,
Yusoff
,
M. Z.
, and
Thangaraju
,
S. K.
,
2013
, “
Heat Transfer Enhancement on Ventilated Brake Disk With Blade Inclination Angle Variation
,”
Int. J. Autom. Technol.
,
14
(
4
), pp.
569
577
.
25.
Chi
,
Z.
,
He
,
Y.
, and
Naterer
,
G.
,
2009
, “
Convective Heat Transfer Optimization of Automotive Brake Discs
,”
SAE Int. J. Passenger Cars-Mech. Syst.
,
2
(
1
), pp.
961
969
.
26.
Qian
,
C.
,
2002
, “
Aerodynamic Shape Optimization Using CFD Parametric Model With Brake Cooling Application
,”
SAE
Paper No. 2002-01-0599.
27.
Kulfan
,
B. M.
,
2008
, “
Universal Parametric Geometry Representation Method
,”
J. Aircr.
,
45
(
1
), pp.
142
158
.
28.
Ceze
,
M.
,
Hayashi
,
M.
, and
Volpe
,
E.
,
2009
, “
A Study of the CST Parameterization Characteristics
,”
AIAA
Paper No. 2009-3767.
29.
Namgoong
,
H.
,
2005
, “
Airfoil Optimization for Morphing Aircraft
,”
Ph.D. dissertation
, Purdue University, West Lafayette, IN.http://docs.lib.purdue.edu/dissertations/AAI3210757/
30.
Keane
,
A.
, and
Nair
,
P.
,
2005
,
Computational Approaches for Aerospace Design: The Pursuit of Excellence
,
Wiley
,
Chichester, UK
.
31.
Wang
,
X.
, and
Damodaran
,
M.
,
2001
, “
Aerodynamic Shape Optimization Using Computational Fluid Dynamics and Parallel Simulated Annealing Algorithms
,”
AIAA J.
,
39
(
8
), pp.
1500
1508
.
32.
Arani
,
B. O.
,
Mirzabeygi
,
P.
, and
Shariat Panahi
,
M.
,
2013
, “
An Improved PSO Algorithm With a Territorial Diversity-Preserving Scheme and Enhanced Exploration–Exploitation Balance
,”
Swarm Evol. Comput.
,
11
, pp.
1
15
.
33.
Khurana
,
M.
,
Sinha
,
A.
, and
Winarto
,
H.
,
2008
, “
Multi-Mission Reconfigurable UAV-Airfoil Optimization Through Swarm Approach and Low Fidelity Solver
,”
23rd International Conference on Unmanned Air Vehicle Systems
, Bristol, UK, Apr. 7–9, pp.
1180
1192
.
34.
Wickramasinghe
,
U. K.
,
Carrese
,
R.
, and
Li
,
X.
,
2010
, “
Designing Airfoils Using a Reference Point Based Evolutionary Many-Objective Particle Swarm Optimization Algorithm
,”
IEEE Congress on Evolutionary Computation
(
CEC
), Barcelona, Spain, July 18–23, pp.
1
8
.
35.
Suribabu
,
C. R.
, and
Neelakantan
,
T. R.
,
2006
, “
Particle Swarm Optimization Compared to Other Heuristic Search Techniques for Pipe Sizing
,”
J. Environ. Inf.
,
8
(
1
), pp.
1
9
.
36.
Xia
,
C. C.
,
Jiang
,
T. T.
, and
Chen
,
W. F.
,
2017
, “
Particle Swarm Optimization of Aerodynamic Shapes With Nonuniform Shape Parameter–Based Radial Basis Function
,”
J. Aerosp. Eng.
,
30
(
3
), p.
04016089
.
37.
Robinson
,
J.
, and
Rahmat-Samii
,
Y.
,
2004
, “
Particle Swarm Optimization in Electromagnetics
,”
IEEE Trans. Antennas Propag.
,
52
(
2
), pp.
397
407
.
38.
Suganthan
,
P. N.
,
Hansen
,
N.
,
Liang
,
J. J.
,
Deb
,
K.
,
Chen
,
Y. P.
,
Auger
,
A.
, and
Tiwari
,
S.
,
2005
, “
Problem Definitions and Evaluation Criteria for the CEC 2005 Special Session on Real-Parameter Optimization
,” IIT Kanpur, Kanpur, India, Nanyang Technological University, Singapore, and KanGAL Report No.
2005005
.https://www.lri.fr/~hansen/Tech-Report-May-30-05.pdf
39.
Nejat
,
A.
,
Mirzabeygi
,
P.
,
Shariat-Panahi
,
M.
, and
Mirzakhalili
,
E.
,
2012
, “
Heat Transfer Enhancement Across a Pair of Confined Cylinders Using Improved Particle Swarm Optimization Algorithm
,”
ASME
Paper No. IMECE2012-88833.
40.
Nejat
,
A.
,
Mirzabeygi
,
P.
, and
Shariat-Panahi
,
M.
,
2012
, “
Aerodynamic Shape Optimization Using Improved Territorial Particle Swarm Algorithm
,”
ASME
Paper No. IMECE2012-88828.
41.
Anderson
,
D.
, and
McNeill
,
G.
,
1992
, “
Artificial Neural Networks Technology
,” Kaman Science Corporation, Data & Analysis Center for Software, Utica, NY, Contract No. F30602-89-C-0082.
42.
Khurana
,
M. S.
,
Winarto
,
H.
, and
Sinha
,
A. K.
,
2008
, “
Application of Swarm Approach and Artificial Neural Networks for Airfoil Shape Optimization
,”
AIAA
Paper No. 2008-5954.
43.
Hacioglu
,
A.
,
2007
, “
Fast Evolutionary Algorithm for Airfoil Design Via Neural Network
,”
AIAA J.
,
45
(
9
), pp.
2196
2203
.
44.
Duvigneau
,
R.
, and
Visonneau
,
M.
,
2002
, “
Hybrid Genetic Algorithms and Neural Networks for Fast CFD-Based Design
,”
AIAA
Paper No. 2002-5465.
45.
Ghadimi
,
B.
,
Kowsary
,
F.
, and
Khorami
,
M.
,
2015
, “
Heat Flux On-Line Estimation in a Locomotive Brake Disc Using Artificial Neural Networks
,”
Int. J. Therm. Sci.
,
90
, pp.
203
213
.
46.
May
,
R.
,
Dandy
,
G.
, and
Maier
,
H.
,
2011
, “
Review of Input Variable Selection Methods for Artificial Neural Networks
,”
Artificial Neural Networks—Methodological Advances and Biomedical Applications
,
K.
Suzuki
, ed.,
InTech
,
Rijeka, Croatia
, pp.
19
44
.
47.
Taguchi
,
G.
, and
Konishi
,
S.
,
1987
, “
Taguchi Methods, Orthogonal Arrays and Linear Graphs: Tools for Quality Engineering
,” American Supplier Institute, Dearborn, MI, pp.
8
35
.
48.
Roy
,
R. K.
,
1990
,
A Primer on the Taguchi Method
(
Competitive Manufacturing Series
),
Springer, New York
, pp.
7
80
.
49.
Ranjit
,
K. R.
,
2001
,
Design of Experiments Using the Taguchi Approach: 16 Steps to Product and Process Improvement
,
Wiley
,
Hoboken, NJ
.
50.
Kalogirou
,
S. A.
,
2012
, “
Combination of Taguchi Method and Artificial Intelligence Techniques for the Optimal Design of Flat-Plate Collectors
,”
World Renewable Energy Forum
(
WREF
), Denver, CO, May 13–17, Vol.
6
, pp.
4435
4442
.http://ktisis.cut.ac.cy/handle/10488/7586
51.
Athreya
,
S.
, and
Venkatesh
,
Y. D.
,
2012
, “
Application of Taguchi Method for Optimization of Process Parameters in Improving the Surface Roughness of Lathe Facing Operation
,”
Int. Refereed J. Eng. Sci.
,
1
(
3
), pp.
13
19
.http://www.bibsonomy.org/bibtex/20b6fdbeb7dd120c87a2d7a0d98c0b362/miikkah
52.
Huang
,
C. N.
, and
Yu
,
C. C.
,
2016
, “
Integration of Taguchi’s Method and Multiple-Input Multiple-Output ANFIS Inverse Model for the Optimal Design of a Water-Cooled Condenser
,”
Appl. Therm. Eng.
,
98
, pp.
605
609
.
53.
Talati
,
F.
, and
Jalalifar
,
S.
,
2008
, “
Investigation of Heat Transfer Phenomena in a Ventilated Disk Brake Rotor With Straight Radial Rounded Vanes
,”
J. Appl. Sci.
,
8
(
20
), pp.
3583
3592
.
54.
Yano
,
M.
, and
Murata
,
M.
,
1993
, “
Heat Flow on Disc Brakes
,”
SAE
Paper No. 931084.http://papers.sae.org/931084/
55.
Shih
,
T. H.
,
Liou
,
W. W.
,
Shabbir
,
A.
,
Yang
,
Z.
, and
Zhu
,
J.
,
1995
, “
A New k–ε Eddy Viscosity Model for High Reynolds Number Turbulent Flows
,”
Comput. Fluids
,
24
(
3
), pp.
227
238
.
56.
Hourigan
,
K.
,
Welch
,
L. W.
,
Thompson
,
M. C.
,
Cooper
,
P. I.
, and
Welsh
,
M. C.
,
1991
, “
Augmented Forced Convection Heat Transfer in Separated Flow Around a Blunt Flat Plate
,”
Exp. Therm. Fluid Sci.
,
4
(
2
), pp.
182
191
.
57.
Iacovides
,
H.
, and
Raisee
,
M.
,
1999
, “
Recent Progress in the Computation of Flow and Heat Transfer in Internal Cooling Passages of Turbine Blades
,”
Int. J. Heat Fluid Flow
,
20
(
3
), pp.
320
328
.
58.
Häring
,
M.
,
Bölcs
,
A.
,
Harasgama
,
S. P.
, and
Richter
,
J.
,
1994
, “
Heat Transfer Measurements on Turbine Airfoils Using the Naphthalene Sublimation Technique
,”
ASME
Paper No. 94-GT-171.
59.
Krall
,
K. M.
, and
Sparrow
,
E. M.
,
1966
, “
Turbulent Heat Transfer in the Separated, Reattached, and Redevelopment Regions of a Circular Tube
,”
ASME J. Heat Transfer
,
88
(
1
), pp.
131
136
.
60.
Togun
,
H.
,
Kazi
,
S. N.
, and
Badarudin
,
A.
,
2011
, “
A Review of Experimental Study of Turbulent Heat Transfer in Separated Flow
,”
Aust. J. Basic Appl. Sci.
,
5
(
10
), pp.
489
505
.http://repository.um.edu.my/17406/1/489-505.pdf
61.
Ota
,
T.
, and
Kon
,
N.
,
1974
, “
Heat Transfer in the Separated and Reattached Flow on a Blunt Flat Plate
,”
ASME J. Heat Transfer
,
96
(
4
), pp.
459
462
.
62.
Kasabov
,
N. K.
,
1996
,
Foundations of Neural Networks, Fuzzy Systems, and Knowledge Engineering
,
MIT Press
,
Cambridge, UK
.
63.
Vemuri
,
V. R.
, and
Rogers
,
R. D.
,
1994
,
Artificial Neural Networks-Forecasting Time Series
,
IEEE Computer Society Press
,
Los Alamitos, CA
.
64.
Rajkumar
,
T.
, and
Bardina
,
J.
,
2003
, “
Training Data Requirement for a Neural Network to Predict Aerodynamic Coefficients
,”
Proc. SPIE
,
5102
, pp.
92
103
.
65.
Kenndy
,
J.
, and
Eberhart
,
R. C.
,
1995
, “
Particle Swarm Optimization
,”
IEEE International Conference on Neural Networks
, Perth, Western Australia, Nov. 27–Dec. 1, Vol.
4
, pp.
1942
1948
.https://www.cs.tufts.edu/comp/150GA/homeworks/hw3/_reading6%201995%20particle%20swarming.pdf
66.
Riget
,
J.
, and
Vesterstrøm
,
J. S.
,
2002
, “
A Diversity-Guided Particle Swarm Optimizer—The ARPSO
,” Department of Computer Science, University of Aarhus, Aarhus, Denmark, Technical Report No.
2002-02
.http://pure.au.dk/portal/en/publications/a-diversityguided-particle-swarm-optimizer--the-arpso(d4676ba0-3522-11dc-bee9-02004c4f4f50).html
67.
Ghalia
,
M. B.
,
2008
, “
Particle Swarm Optimization With an Improved Exploration-Exploitation Balance
,”
51st Midwest Symposium on Circuits and Systems
(
MWSCAS
), Knoxville, TN, Aug. 10–13, pp.
759
762
.
You do not currently have access to this content.