The ability of a morphing blade to change its geometry according to the different operating conditions represents a challenging approach for the optimization of turbomachinery performance. In this paper, experimental and computational fluid dynamics (CFD) numerical analyses on a morphing blade for a heavy-duty automotive cooling axial fan are proposed. Starting from the experimental results proposed in the first part of this work, a morphing blade, made of shape memory alloy (SMA) strips embedded in a polymeric structure, was thoroughly tested. In order to assess the ability of the strips to reach a progressive and smooth shape changing evolution, several experiments were performed in a purpose-built wind tunnel. The morphing blade changed its shape as the strips were thermally activated by means of air stream flow. The bending deformation evolution with the increasing number of thermal cycles was evaluated by digital image analysis techniques. After the analyses in the wind tunnel, CFD numerical simulations of a partially shrouded fan composed of five morphing blades were performed in order to highlight the evolution of the fan performance according to air temperature conditions. In particular, the capability of the blade activation was evaluated by the comparison between the fan performance with nonactivated blades and with activated blades. The results show a progressive stabilization of the shape memory behavior after the first cycle. The blade deformation led to a significant improvement in the fan performance at a constant rotational velocity. The CFD numerical simulation points out the differences in the overall performance and of three-dimensional fluid dynamic behavior of the fan. This innovative concept is aimed at realizing a sensorless smart fan control, permitting (i) an energy saving that leads to fuel saving in the automotive application fields and (ii) an increase in engine life, thanks to a strong relationship between the engine thermal request and the cooling fan performance.

References

1.
Lin
,
W.
, and
Sunden
,
B.
,
2010
, “
Vehicle Cooling Systems for Reducing Fuel, Consumption and Carbon Dioxide: Literature Survey
,”
SAE
Technical Paper No. 2010-01-1509.
2.
Chalgren
,
R. D.
,
2004
, “
Thermal Comfort and Engine Warm-Up Optimization of a Low-Flow Advanced Thermal Management System
,”
SAE
Technical Paper No. 2004-01-0047.
3.
Nessim
,
W.
,
Zhang
,
F.
,
Changlu
,
Z.
, and
Zhenxia
,
Z.
,
2012
, “
A Simulation Study of an Advanced Thermal Management System for Heavy Duty Diesel Engines
,”
International Conference on Mechanical Engineering and Material Science
(
MEMS 2012
), Paris, Jan. 29–Feb. 2, pp.
287
290
.
4.
Lehner
,
C.
,
Parker
,
G.
,
Arici
,
O.
, and
Johnson
,
J.
,
2006
, “
Design and Development of a Model Based Feedback Controlled Cooling System for Heavy Duty Diesel Truck Applications Using a Vehicle Engine Cooling System Simulation
,”
SAE
Technical Paper No. 2001-01-0336.
5.
Baniasadi
,
E.
,
Aydin
,
M.
,
Dincer
,
I.
, and
Naterer
,
G. F.
,
2013
, “
Computational Aerodynamic Study of Automotive Cooling Fan in Blocked Conditions
,”
Eng. Appl. Comput. Fluid Mech.
,
7
(
1
), pp.
66
73
.
6.
Fortini
,
A.
,
Suman
,
A.
,
Aldi
,
N.
,
Merlin
,
M.
, and
Pinelli
,
M.
,
2016
, “
A Shape Memory Alloy-Based Morphing Axial Fan Blade—Part I: Blade Structure Design and Functional Characterization
,”
ASME J. Eng. Gas Turbines Power
,
138
(
2
), p.
022601
.
7.
Kim
,
K. B.
,
Choi
,
K. W.
,
Lee
,
K. H.
, and
Lee
,
K. S.
,
2010
, “
Active Coolant Control Strategies in Automotive Engines
,”
Int. J. Automot. Technol.
,
11
(
6
), pp.
767
772
.
8.
Pang
,
S. C.
,
Kalam
,
M. A.
,
Masjuki
,
H. H.
, and
Hazrat
,
M. A.
,
2012
, “
A Review on Air Flow and Coolant Flow Circuit in Vehicles Cooling System
,”
Int. J. Heat Mass Transfer
,
55
(23–24), pp.
6295
6306
.
9.
Oliet
,
C.
,
Oliva
,
A.
,
Castro
,
J.
, and
Pérez-Segarra
,
C. D.
,
2007
, “
Parametric Studies on Automotive Radiators
,”
Appl. Therm. Eng.
,
27
(11–12), pp.
2033
2043
.
10.
Hallqvist
,
T.
,
2008
, “
The Cooling Airflow of Heavy Trucks–A Parametric Study
,”
SAE
Technical Paper No. 2008-01-1171.
11.
Mao
,
S.
,
Feng
,
Z.
, and
Michaelides
,
E. E.
,
2010
, “
Off-Highway Heavy-Duty Truck Under-Hood Thermal Analysis
,”
Appl. Therm. Eng.
,
30
(
13
), pp.
1726
1733
.
12.
Pang
,
S. C.
,
Kalam
,
M. A.
,
Masjuki
,
H. H.
,
Badruddin
,
I. A.
,
Ramli
,
R.
, and
Hazrat
,
M. A.
,
2012
, “
Underhood Geometry Modification and Transient Coolant Temperature Modelling for Robust Cooling Networks
,”
Int. J. Mech. Mater. Eng.
,
7
(3), pp.
251
258
.
13.
Senatore
,
A.
,
Cardone
,
M.
,
Buono
,
D.
, and
Dominici
,
A.
,
2008
, “
High Performance Engine Warm-Up Thermo-Fluid-Dynamic Analysis
,”
ASME
Paper No. IMECE2008-67426.
14.
Sofla
,
A. Y. N.
,
Meguid
,
S. A.
,
Tan
,
K. T.
, and
Yeo
,
W. K.
,
2010
, “
Shape Morphing of Aircraft Wing: Status and Challenges
,”
Mater. Des.
,
31
(
3
), pp.
1284
1292
.
15.
Epps
,
J.
, and
Chopra
,
I.
,
2001
, “
In-Flight Tracking of Helicopter Rotor Blades Using Shape Memory Alloy Actuators
,”
Smart Mater. Struct.
,
10
(
1
), pp.
104
111
.
16.
Lachenal
,
X.
,
Daynes
,
S.
, and
Weaver
,
P. M.
,
2013
, “
Review of Morphing Concepts and Materials for Wind Turbine Blade Applications
,”
Wind Energy
,
16
(
2
), pp.
283
307
.
17.
Gonzalez-Jorge
,
H.
,
Riveiro
,
B.
,
Vazquez-Fernandez
,
E.
,
Martínez-Sánchez
,
J.
, and
Arias
,
P.
,
2013
, “
Metrological Evaluation of Microsoft Kinect and Asus Xtion Sensors
,”
Measurement
,
46
(
6
), pp.
1800
1806
.
18.
Khoshelham
,
K.
, and
Elberink
,
S. O.
,
2012
, “
Accuracy and Resolution of Kinect Depth Data for Indoor Mapping Applications
,”
Sensors
,
12
(
12
), pp.
1437
1454
.
19.
Yue
,
H.
,
Chen
,
W.
,
Wu
,
X.
, and
Liu
,
J.
,
2014
, “
Fast 3D Modeling in Complex Environments Using a Single Kinect Sensor
,”
Opt. Lasers Eng.
,
53
(2), pp.
104
111
.
20.
Schwenke
,
H.
,
Neuschaefer-Rube
,
U.
,
Pfeifer
,
T.
, and
Kunzmann
,
H.
,
2002
, “
Optical Methods for Dimensional Metrology in Production Engineering
,”
CIRP Annu.-Manuf. Technol.
,
51
(
2
), pp.
685
699
.
21.
Sansoni
,
G.
, and
Docchio
,
F.
,
2005
, “
In-Field Performance of an Optical Digitizer for the Reverse Engineering of Free-Form Surfaces
,”
Int. J. Adv. Manuf. Technol.
,
26
(11), pp.
1353
1361
.
22.
Carbone
,
V.
,
Carocci
,
M.
,
Savio
,
E.
,
Sansoni
,
G.
, and
De Chiffre
,
L.
,
2001
, “
Combination of a Vision System and a Coordinate Measuring Machine for the Reverse Engineering of Free-Form Surfaces
,”
Int. J. Adv. Manuf. Technol.
,
17
(
4
), pp.
263
271
.
23.
Chen
,
L.-C.
, and
Lin
,
G. C. I.
,
1997
, “
An Integrated Reverse Engineering Approach to Reconstructing Free-Form Surfaces
,”
Comput. Integr. Manuf. Syst.
,
10
(
1
), pp.
49
60
.
24.
Fortini
,
A.
,
Suman
,
A.
,
Merlin
,
M.
, and
Garagnani
,
G. L.
,
2015
, “
Morphing Blades With Embedded SMA Strips: An Experimental Investigation
,”
Mater. Des.
,
85
(11), pp.
785
795
.
25.
Cornelius
,
C.
,
Biesinger
,
T.
,
Galpin
,
P.
, and
Braune
,
A.
,
2014
, “
Experimental and Computational Analysis of a Multistage Axial Compressor Including Stall Prediction by Steady and Transient CFD Methods
,”
ASME J. Turbomach.
,
136
(6), p.
061013
.
26.
Abdullah
,
E. J.
,
Bil
,
C.
, and
Watkins
,
S.
,
2009
, “
Application of Smart Materials for Adaptive Airfoil Control
,”
AIAA
Paper No. 2009-1359.
27.
Mertmann
,
M.
, and
Vergani
,
G.
,
2008
, “
Design and Application of Shape Memory Actuators
,”
Eur. Phys. J. Spec. Top.
,
158
(
1
), pp.
221
230
.
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