Abstract

Topology optimization (TO) is a powerful method of generating structures that have desirable functional performance, to date most commonly used to improve structural behavior or to optimize pressure drops in laminar flow environments. In this study, we use TO to generate free-form pressure-staging geometries for the purposes of cavitation suppression in a turbulent flow device, an industrial flow control application which has not heretofore been addressed. Using variable permeability gradient-based adjoint TO in conjunction with both an out-of-plane resistance modified two-dimensional (2D) flow model and a penalty-term extended k–ε turbulence model, we generated flow channels of predetermined capacity that gradually reduce static pressure to suppress the initiation of cavitation. Three-dimensional (3D) extrusions of the 2D geometries were then printed using a masked stereolithography apparatus and evaluated using a water flow test in conjunction with acoustic cavitation detection. After testing, the results were compared to single and dual orifice baseline devices of equivalent capacity. The results of the experimental validations showed capacity deviations from target of up to 7% with performance improvements, as characterized by the delay of incipient cavitation, of up to 13% over the capacity-equivalent two-stage baseline device. This study demonstrates a new ability to rapidly generate fit-to-purpose devices at significantly reduced engineering effort using topology optimization methods.

References

1.
Hammitt
,
F. G.
,
1980
,
Cavitation and Multiphase Flow Phenomena
, 1st ed.,
McGraw-Hill
, New York.
2.
Young
,
F. R.
,
1999
,
Cavitation
, 2nd ed.,
Imperial College Press, London, UK
.
3.
Sigmund
,
O.
, and
Maute
,
K.
,
2013
, “
Topology Optimization Approaches: A Comparative Review
,”
Struct. Multidiscip. Optim.
,
48
(
6
), pp.
1031
1055
.10.1007/s00158-013-0978-6
4.
Deaton
,
J. D.
, and
Grandhi
,
R. V.
,
2014
, “
A Survey of Structural and Multidisciplinary Continuum Topology Optimization: Post 2000
,”
Struct. Multidiscip. Optim.
,
49
(
1
), pp.
1
38
.10.1007/s00158-013-0956-z
5.
Pedersen
,
C. B.
, and
Allinger
,
P.
,
2006
, “
Industrial Implementation and Applications of Topology Optimization and Future Needs
,”
Solid Mech. Appl.
,
137
, pp.
229
238
.10.1007/1-4020-4752-5_23
6.
Liu
,
J.
,
Gaynor
,
A. T.
,
Chen
,
S.
,
Kang
,
Z.
,
Suresh
,
K.
,
Takezawa
,
A.
,
Li
,
L.
, et al.,
2018
, “
Current and Future Trends in Topology Optimization for Additive Manufacturing
,”
Struct. Multidiscip. Optim.
,
57
(
6
), pp.
2457
2483
.10.1007/s00158-018-1994-3
7.
Bendsøe
,
M. P.
, and
Kikuchi
,
N.
,
1988
, “
Generating Optimal Topologies in Structural Design Using a Homogenization Method
,”
Comput. Methods Appl. Mech. Eng.
,
71
(
2
), pp.
197
224
.10.1016/0045-7825(88)90086-2
8.
Bendsøe
,
M.
, and
Sigmund
,
O.
,
2002
,
Topology Optimization: Theory, Methods, and Applications
,
Springer
, Berlin-Heidelberg, Germany.
9.
Borrvall
,
T.
, and
Petersson
,
J.
,
2003
, “
Topology Optimization of Fluids in Stokes Flow
,”
Int. J. Numer. Methods Fluids
,
41
(
1
), pp.
77
107
.10.1002/fld.426
10.
Gersborg-Hansen
,
A.
,
Sigmund
,
O.
, and
Haber
,
R. B.
,
2005
, “
Topology Optimization of Channel Flow Problems
,”
Struct. Multidiscip. Optim.
,
30
(
3
), pp.
181
192
.10.1007/s00158-004-0508-7
11.
Olesen
,
L. H.
,
Okkels
,
F.
, and
Bruus
,
H.
,
2006
, “
A High-Level Programming-Language Implementation of Topology Optimization Applied to Steady-State Navier-Stokes Flow
,”
Int. J. Numer. Methods Eng.
,
65
(
7
), pp.
975
1001
.10.1002/nme.1468
12.
Othmer
,
C.
,
2008
, “
A Continuous Adjoint Formulation for the Computation of Topological and Surface Sensitivities of Ducted Flows
,”
Int. J. Numer. Methods Fluids
,
58
(
8
), pp.
861
877
.10.1002/fld.1770
13.
Kontoleontos
,
E. A.
,
Papoutsis-Kiachagias
,
E. M.
,
Zymaris
,
A. S.
,
Papadimitriou
,
D. I.
, and
Giannakoglou
,
K. C.
,
2013
, “
Adjoint-Based Constrained Topology Optimization for Viscous Flows, Including Heat Transfer
,”
Eng. Optim.
,
45
(
8
), pp.
941
961
.10.1080/0305215X.2012.717074
14.
Yoon
,
G. H.
,
2016
, “
Topology Optimization for Turbulent Flow With Spalart–Allmaras Model
,”
Comput. Methods Appl. Mech. Eng.
,
303
, pp.
288
311
.10.1016/j.cma.2016.01.014
15.
Dilgen
,
C. B.
,
Dilgen
,
S. B.
,
Fuhrman
,
D. R.
,
Sigmund
,
O.
, and
Lazarov
,
B. S.
,
2018
, “
Topology Optimization of Turbulent Flows
,”
Comput. Methods Appl. Mech. Eng.
,
331
, pp.
363
393
.10.1016/j.cma.2017.11.029
16.
Yoon
,
G. H.
,
2020
, “
Topology Optimization Method With Finite Elements Based on the k-ε Turbulence Model
,”
Comput. Methods Appl. Mech. Eng.
,
361
, p.
112784
.10.1016/j.cma.2019.112784
17.
Alonso
,
D. H.
,
Romero Saenz
,
J. S.
,
Picelli
,
R.
, and
Silva
,
E. C. N.
,
2022
, “
Topology Optimization Method Based on the Wray–Agarwal Turbulence Model
,”
Struct. Multidiscip. Optim.
,
65
(
3
), p.
82
.10.1007/s00158-021-03106-8
18.
Alexandersen
,
J.
, and
Andreasen
,
C. S.
,
2020
, “
A Review of Topology Optimisation for Fluid-Based Problems
,”
Fluids
,
5
(
1
), p.
29
.10.3390/fluids5010029
19.
Hanimann
,
L.
,
Mangani
,
L.
,
Casartelli
,
E.
, and
Widmer
,
M.
,
2016
, “
Cavitation Modeling for Steady-State CFD Simulations
,”
IOP Conf. Ser.: Earth Environ. Sci.
,
49
(
9
), p.
092005
.10.1088/1755-1315/49/9/092005
20.
Ferrarese
,
G.
,
Messa
,
G. V.
,
Rossi
,
M. M.
, and
Malavasi
,
S.
,
2015
, “
New Method for Predicting the Incipient Cavitation Index by Means of Single-Phase Computational Fluid Dynamics Model
,”
Adv. Mech. Eng.
,
7
(
3
), pp.
1
11
.10.1177/1687814015575974
21.
Tang
,
T.
,
Gao
,
L.
,
Li
,
B.
,
Liao
,
L.
,
Xi
,
Y.
, and
Yang
,
G.
,
2019
, “
Cavitation Optimization of a Throttle Orifice Plate Based on Three-Dimensional Genetic Algorithm and Topology Optimization
,”
Struct. Multidiscip. Optim.
,
60
(
3
), pp.
1227
1244
.10.1007/s00158-019-02249-z
22.
Dilgen
,
S. B.
,
Dilgen
,
C. B.
,
Fuhrman
,
D. R.
,
Sigmund
,
O.
, and
Lazarov
,
B. S.
,
2018
, “
Density Based Topology Optimization of Turbulent Flow Heat Transfer Systems
,”
Struct. Multidiscip. Optim.
,
57
(
5
), pp.
1905
1918
.10.1007/s00158-018-1967-6
23.
NIST
,
2010
, “
NIST Standard Reference Database 23
,” NIST, U.S. Department of Commerce, Gaithersburg, MD.
24.
Weiwei
,
J.
,
2024
, “
Derivation of ‘Double-Loop’ Theory and Mechanism of Cavitation-Vortex Interaction in Turbulent Cavitation Boundary Layer
,”
ASME J. Fluids Eng.
,
146
(
9
), p.
094501
.10.1115/1.4064532
25.
Perali
,
P.
,
Hauville
,
F.
,
Leroyer
,
A.
,
Astolfi
,
J. A.
, and
Visonneau
,
M.
,
2024
, “
Experimental and Numerical Study of the Flow Around Rigid and Flexible Hydrofoils for Wetted and Cavitating Flow Conditions
,”
ASME J. Fluids Eng.
,
146
(
11
), p.
111201
.10.1115/1.4065296
26.
Malavasi
,
S.
,
Messa
,
G. V.
,
Fratino
,
U.
, and
Pagano
,
A.
,
2015
, “
On Cavitation Occurrence in Perforated Plates
,”
Flow Meas. Instrum.
,
41
, pp.
129
139
.10.1016/j.flowmeasinst.2014.11.002
27.
COMSOL AB
,
2023
,
CFD Module User's Guide
, COMSOL Multiphysics v. 6.0, COMSOL AB, Stockholm, Sweden, pp.
207
211
.
28.
Alexandersen
,
J.
,
2022
, “
Topography Optimisation of Fluid Flow Between Parallel Plates of Spatially-Varying Spacing: Revisiting the Origin of Fluid Flow Topology Optimisation
,”
Struct. Multidiscip. Optim.
,
65
(
5
), p.
152
.10.1007/s00158-022-03243-8
29.
Kuzmin
,
D.
,
Mierka
,
O.
, and
Turek
,
S.
,
2007
, “
On the Implementation of the kε Turbulence Model in Incompressible Flow Solvers Based on a Finite Element Discretisation
,”
Int. J. Comput. Sci. Math.
,
1
(
2/3/4
), pp.
193
206
.10.1504/IJCSM.2007.016531
30.
Ghosh
,
S.
,
Wardell
,
R.
,
Mondal
,
S.
,
Fernandez
,
E.
,
Ray
,
A.
, and
Kapat
,
J.
,
2022
, “
Topology Optimization and Experimental Validation of an Additively Manufactured U-Bend Channel
,”
ASME J. Fluids Eng.
,
144
(
7
), p.
071206
.10.1115/1.4052928
31.
IEC
,
2011
, “
Noise considerations—Laboratory Measurement of Noise Generated by Hydrodynamic Flow Through Control Valves
,” IEC, Geneva, Switzerland, Standard No. IEC 60534-8-2:2011.
32.
COMSOL AB
,
2023
,
Optimization Module User's Guide
, COMSOL Multiphysics v. 6.0, COMSOL AB, Stockholm, Sweden.
33.
Lazarov
,
B. S.
, and
Sigmund
,
O.
,
2011
, “
Filters in Topology Optimization Based on Helmholtz-Type Differential Equations
,”
Int. J. Numer. Methods Eng.
,
86
(
6
), pp.
765
781
.10.1002/nme.3072
34.
Svanberg
,
K.
,
2002
, “
A Class of Globally Convergent Optimization Methods Based on Conservative Convex Separable Approximations
,”
SIAM J. Optim.
,
12
(
2
), pp.
555
573
.10.1137/S1052623499362822
35.
Coleman
,
H.
, and
Steele
,
W. G.
,
2018
,
Experimentation, Validation, and Uncertainty Analysis for Engineers
, 4th ed.,
Wiley
, Hoboken, NJ.
You do not currently have access to this content.