Grove configuration has a direct influence on the performance of the labyrinth seal. In this study, the geometry of the groove cavities in a water balance drum labyrinth seal was varied to investigate the effects on fluid leakage. A design of experiments (DOEs) study varied the groove cavity cross section through various trapezoidal shapes with one or both internal base angles obtuse. The grooves are parameterized by the groove width connected to the jet-flow region, the internal entrance and exit angles, the flat width inside the groove, and the depth. The corners inside the groove cavity are filleted with equal radii. As with the baseline model, the grooves are evenly spaced along the seal length and identical copies of each other. The flow path starting at the rear of the pump impeller and proceeding through the seal was created as a 5-deg sector computational fluid dynamics (CFD) model in ansys cfx. Three five-level factorial designs were selected for the cases where the entrance angle is obtuse and the exit angle is acute, the exit angle obtuse and entrance angle acute, and both angles were obtuse. The feasible geometries from each factorial design were selected based on the nonlinear geometric constraints, and CFD simulation experiments were performed in ansys cfx. The leakage results from these simulation experiments were then analyzed by multifactor linear regression to create prediction equations relating the geometric design variables to leakage and enable geometric optimization for minimum leakage. Streamline plots along the seal cross section were then used to visualize the flow and understand regression trends. This study investigates the effect of groove cavities with obtuse internal entrance and exit angles on vortex size and position and subsequent seal leakage.

References

1.
Childs
,
D.
,
1993
,
Turbomachinery Rotordynamics
,
Wiley
,
New York
.
2.
Arghir
,
M.
, and
Frêne
,
J.
,
1997
, “
Rotordynamic Coefficients of Circumferentially-Grooved Liquid Seals Using the Averaged Navier-Stokes Equations
,”
ASME J. Tribol.
,
119
(
3
), pp.
556
567
.
3.
Kim
,
N.
, and
Rhode
,
D. L.
,
2000
, “
A New CFD-Perturbation Model for the Rotordynamics of Incompressible Flow Seals
,”
ASME
Paper No. 2000-GT-0402.
4.
Moore
,
J. J.
, and
Palazzolo
,
A. B.
,
2001
, “
Rotordynamic Force Prediction of Whirling Centrifugal Impeller Shroud Passages Using Computational Fluid Dynamic Techniques
,”
ASME J. Eng. Gas Turbines Power
,
123
(
4
), pp.
910
918
.
5.
Untaroiu
,
A.
,
Untaroiu
,
C. D.
,
Wood
,
H. G.
, and
Allaire
,
P. E.
,
2013
, “
Numerical Modeling of Fluid-Induced Rotordynamic Forces in Seals With Large Aspect Ratios
,”
ASME J. Eng. Gas Turbines Power
,
135
(
1
), p.
012501
.
6.
Migliorini
,
P. J.
,
Untaroiu
,
A.
,
Wood
,
H. G.
, and
Allaire
,
P. E.
,
2012
, “
A Computational Fluid Dynamics/Bulk-Flow Hybrid Method for Determining Rotordynamic Coefficients of Annular Gas Seals
,”
ASME J. Tribol.
,
134
(
2
), p.
022202
.
7.
Untaroiu
,
A.
,
Hayrapetian
,
V.
,
Untaroiu
,
C. D.
,
Wood
,
H. G.
,
Schiavello
,
B.
, and
McGuire
,
J.
,
2013
, “
On the Dynamic Properties of Pump Liquid Seals
,”
ASME J. Fluids Eng.
,
135
(
5
), p.
051104
.
8.
Morgan
,
N. R.
,
Untaroiu
,
A.
,
Migliorini
,
P. J.
, and
Wood
,
H. G.
,
2014
, “
Design of Experiments to Investigate Geometric Effects on Fluid Leakage Rate in a Balance Drum Seal
,”
ASME J. Eng. Gas Turbines Power
,
137
(
3
), p.
032501
.
9.
Morgan
,
N. R.
,
Wood
,
H. G.
,
Migliorini
,
P. J.
, and
Untaroiu
,
A.
,
2014
, “
Groove Geometry Optimization of Balance Drum Labyrinth Seal to Minimize Leakage Rate by Experimental Design
,”
13th EDF/Pprime Workshop: Energy Saving in Seals
, Poitier, France, Oct. 2.
10.
Draper
,
N. R.
, and
Smith
,
H.
,
1998
,
Applied Regression Analysis
, 3rd ed.,
Wiley
,
New York
.
11.
Fisher
,
R. A.
,
1974
,
Design of Experiments
,
Hafner Press
,
New York
.
12.
Deming
,
S. N.
, and
Morgan
,
S. L.
,
1993
,
Experimental Design: A Chemometric Approach
,
Elsevier
,
Amsterdam
.
13.
Kennard
,
R. W.
, and
Stone
,
L. A.
,
1969
, “
Computer Aided Design of Experiments
,”
Technometrics
,
11
(
1
), pp.
137
148
.
14.
Schramm
,
V.
,
Denecke
,
J.
,
Kim
,
S.
, and
Wittig
,
S.
,
2004
, “
Shape Optimization of a Labyrinth Seal Applying the Simulated Annealing Method
,”
Int. J. Rotating Mach.
,
10
(
5
), pp.
365
371
.
15.
Asok
,
S. P.
,
Sankaranarayanasamy
,
K.
,
Sundararajan
,
T.
,
Rajesh
,
K.
, and
Sankar
,
G.
,
2007
, “
Neural Network and CFD-Based Optimisation of Square Cavity and Curved Cavity Static Labyrinth Seals
,”
Tribol. Int.
,
40
(
7
), pp.
1204
1216
.
16.
Untaroiu
,
A.
,
Liu
,
C.
,
Migliorini
,
P. J.
,
Wood
,
H. G.
, and
Untaroiu
,
C. D.
,
2014
, “
Hole-Pattern Seals Performance Evaluation Using Computational Fluid Dynamics and Design of Experiment Techniques
,”
ASME J. Eng. Gas Turbines Power
,
136
(
10
), p.
102501
.
17.
Box
,
G. E. P.
,
Hunter
,
J. S.
, and
Hunter
,
W. G.
,
2005
,
Statistics for Experimenters: Design, Innovation, and Discovery
, 2nd ed.,
Wiley
,
Hoboken, NJ
.
18.
The Mathworks, Inc.
,
2012
,
Optimization Toolbox User's Guide
,
The Mathworks, Inc.
,
Natick, MA
.
You do not currently have access to this content.