Transcript CFD for pump design: a tutorial

Pump CFD - performance prediction:
a tutorial
Niels P. Kruyt
Engineering Fluid Dynamics, Department of Mechanical Engineering,
University of Twente,
P.O. Box 217, 7500 AE Enschede, The Netherlands
[email protected]
www.ts.wb.utwente.nl/kruyt/
5th International Symposium on Pumping Machinery,
2005 ASME Fluids Engineering Division Summer Meeting and Exhibition,
19-23 June, Houston, TX, USA
CFD
CFD for
for pump
pump design:
design:
Pump CFD
- performance
prediction
pitfalls
and
opportunities
a magic bullet?
Overview of tutorial








Why is fluid dynamics important for pump design?
What is Computational Fluid Dynamics (CFD)?
Opportunities provided by CFD
Components of CFD
Essential fluid dynamics
Examples of performance prediction
Trends
“Do’s” and “don’t’s” of CFD
3
Characteristics of centrifugal pumps
4
Basics of pump design/analysis

One-dimensional flow model
 Euler pump relation
gH
h
  r2 
2
1 Q

tan  2 2b2
– Slip factor is empirical
– Hydraulic efficiency is empirical
5
What is Computational Fluid
Dynamics (CFD)?
Determination of flow:
Analytical  impossible
 Experiments  expensive
 Numerical  CFD
(“computer test-rig”)

6
Benefits of CFD for pump design

Improved designs
 More reliable design methods
 Cheaper design process
7
Design phases

Conceptual design
 Preliminary design
 Detailed design

Use different CFD-methods for different design
phases!
8
Components of CFD

Model formulation
– geometry
– flow model
– boundary conditions

Grid/mesh generation
 Discretisation of governing equations
 Solution of discretised equations
 Interpretation
9
Selection of modelled geometry

Single channel of impeller
 Full pump: impeller & volute/diffusor
– steady
– unsteady

Leakage-flow region
 Piping system / pump intake
 Single stage vs. multi-stage
10
Turbulent flow
11
Closure problem
Averaging over time Reynolds-averaged
Navier-Stokes equations (RANS)
 Contains ‘Reynolds stresses’
  uv
 Extra quantities in equations ‘closure’
problem
 Model required for Reynolds stresses in terms
of time-averaged velocities u, v

12
Turbulence models

Mixing-length model

k-e models (k-w

Reynolds-stress models


“Turbulent viscosity”
u
T  l
y
 T  c k 2 e
2
m
Increasing complexity
 turb,xy
u
 uv   T

y
Pope (2000); Bradshaw (1996)
13
Flow models
Stream-surface methods
 Potential-flow model
 Euler flow model
 RANS-based models
 Large-eddy simulations (LES)
 Direct Navier-Stokes simulations (DNS)
Increasing complexity

14
Boundary layers

High Reynolds numbers
 Main flow is inviscid
 Boundary-layer flow is
viscous
 Boundary-layer is thin
 Large variation of velocity
in direction normal to wall
Re = 107:
L = 25 cm; d = 0.4 cm
L = 9.8 in; d0.1in
15
Logarithmic layer

Large variation of velocity
perpendicular to wall 
many grid points
 ‘Universal’ behaviour near
wall “logarithmic layer”
 “Wall functions” in RANSbased CFD-methods 
boundary conditions

u 
1


ln y  B
Craft et al. (2002); Pope (2000)
16
Separation
Attached boundary-layer
Separated boundary-layer
17
Grid/mesh (1)
Structured
Unstructured
18
Viscous accuracy
Grid/mesh (2)
Structured
multi-block
Unstructured
Ease of use
Baker (2005)
19
Discretisation

Replace partial differential equations by a finite
set of equations
– Finite difference method
– Finite volume method
– Finite element method

Discretisation error
solution depends on grid/mesh size!
20
Sources of errors
in CFD-predictions

Modelling errors
– Geometrical uncertainties
– Limited validity of adopted flow model
– Uncertain boundary conditions

Numerical errors
– Discretisation error due to finite grid-size
– Lack of convergence in iterative solution process
– Insufficient mesh/grid quality

User/programmer errors
21
‘Around’ design
point
Cost
Choice of flow model
DNS
RSM
k, e
Potential
& B.L.
Potential
1D
Accuracy
22
Performance prediction with
potential-flow model
0.13
0.13
0.13
100
100
100
0.11
0.11
0.11
9090
90
0.09
0.09
0.09
YY
Y
0.07
0.07
0.07
8080
80


experiments
experiments
experiments
experiments
inviscid
inviscid
'' + leakage flow
experiments
inviscid
'''' ++ leakage
flow
disk friction
inviscid
'' + leakage flow
hydr.friction
losses
'''' ++ disk
7070
70
0.05
0.05
0.05
6060
60
0.03
0.03
0.03
4040
40
5050
50
4040
40
6060
60
8080
80
100
120
100
120
100
120
QQ[%BEP]
[%BEP]
Q [%BEP]
140
140
140
160
160
160
6060
60
8080
80
100 120
120
100
100
120
QQ[%BEP]
[%BEP]
Q [%BEP]
140
140
140
160
160
160
van Esch & Kruyt (2001)
23
Inviscid-viscous interaction methods
Outer flow inviscid flow equations
 Boundary-layer flow  boundary-layer equations
 Coupled solution  mildy separated flows

RAE101 wing
Milewski (1997)
24
Comparison of RANS-predictions

Different machines
 Many contributors

Draft tube
 Wing/body
25
Turbine draft tube
Turbine draft tube flow;
Engström et al. (2001)
Pressure recovery (local)
Loss coefficient (average)
0.2
1.8
Experimental
0.15
1.4
z
cp
1.6
0.1
1.2
0.05
1
0
1
2
3
4
5
6
7
Contributor
8
9
10 11
1
2
3
4
5
6
7
8
9
10 11
Contributor
26
Wing/body
DLR F6 wing/body study
Baker (2005)
27
Differences CFD
pump  aerospace applications

Compressibility effects are absent; no shock waves

Cavitation is important
Rotating/stationary parts
More boundary layers need to be resolved
Flow separation more important for off-design
conditions
Effect rotation and curvature on turbulence




28
Implementation of CFD
in pump-design process







Integrate CFD in all design phases
Different CFD-models for each design phase
Simple models give more insight
Tune model parameters from database
RANS-methods require intense use
Set accuracy targets clearly
Be cautious of designs from CFD that deviate strongly
from experience
29
Trends

Maturing of commercial/general-purpose CFD-packages
 Main problem remains turbulence modelling
 Multi-phase CFD-methods
 Adaptive mesh refinement
 Open-source CFD-methods (“GNU-CFD”)
 Verification of CFD-methods “blind” tests
 Design-oriented CFD-methods
– Optimisation methods
– Inverse-design methods
30
Inverse-design method

Specified
– meridional plane
– duty
– “blade loading”

Obtained
– Blade angles
Westra et al. (2005)
[Click on figure to start movie]
31
“Don’t’s” of CFD

Use CFD-package as a black-box tool
 Forget that turbulence needs to be modelled
 Use RANS-methods for all design phases
32
“Do’s” of CFD

Choose right tool for the task
 Analyse and interpret results
 Use common-sense
 Use/develop knowledge of fluid dynamics
 Check grid/mesh convergence
 Check sensitivity of results to model parameters
33
Conclusions
CFD is not a “magic bullet”
 CFD is a powerful tool
 Many pitfalls; many opportunities
 CFD does not replace a smart designer
 CFD provides great potential for improved
pump-design process
 CFD is (still) an art

34
Questions and comments

Thank you for your attention!

Questions and comments?

Presentation can be downloaded from:
www.ts.wb.utwente.nl/kruyt/asme2005.pps

E-mail:
[email protected]
35
Literature









Baker, T.J. (2005). “Mesh generation: art or science”, Progress in Aerospace Sciences 41 29-63.
Craft, T.J. & Gerasimov, A.V. & Iacovides, H. & Launder, B.E. (2002). “Progress in the generalization of wallfunction treatments”, International Journal of Heat and Fluid Flow 23 148-160.
Bradshaw, P. (1996). “Turbulence modelling with application to turbomachinery”, Progress in Aerospace
Sciences 32 575-624.
Engström, T.F. & Gustavsson, L.H. & Karlsson, R.I. (2001). “Proceedings of Turbine 99 – Worskshop 2. The
second ERCOFTAC Workshop on draft tube flow”, http://www.sirius.luth.se/strl/Turbine-99/.
Esch, B.P.M. van & Kruyt, N.P. (2001). “Hydraulic performance of a mixed-flow pump: unsteady inviscid
computations and loss models”, Journal of Fluids Engineering 123 256-264.
Jameson, A. (2001). “A perspective on computational algorithms for aerodynamic analysis and design”,
Progress in Aerospace Sciences 37 197-243.
Milewski, W.M. (1997). “Three-dimensional viscous flow computations using the integral boundary-layer
equations simultaneously coupled with a low-order panel method”, Ph.D. Thesis, MIT, Cambridge, USA.
Westra, R.W. & Kruyt, N.P. & Hoeijmakers, H.W.M. (2005). “An inverse-design method for centrifugal pump
impellers”, 2005 ASME 5th International Symposium on Pumping Machinery, Paper FEDSM2005-77283.
Pope, S.B. (2000). “Turbulent flows”, Cambridge University Press, Cambridge, UK.
36
Notes
37