SNAME H-8 Panel Meeting No. 124 Oct. 18, 2004 NSWC-CD Research Update from UT Austin

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SNAME H-8 Panel Meeting No. 124Oct. 18, 2004
NSWC-CDResearch Update from UT Austin

• Ocean Engineering Group
• Department of Civil Engineering
• The University of Texas at Austin
• Prof. Spyros A. Kinnas
• Dr. Hanseong Lee, Research Associate
• Mr. Hua Gu, Doctoral Graduate Student
• Ms. Hong Sun, Doctoral Graduate Student
• Mr. Yumin Deng, Graduate student

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Topics

• MPUF/HULLFPP .vs. PROPCAV/HULLFPP
• Effective wake evaluation at blade control points
• Modeling of cavitating ducted propeller
• Blade design using optimization method

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MPUF3A- and PROPCAV- /HULLFPP (Steady wetted
case H03861 Propeller)

• Propeller and hull geometries

• 4 blades
• User input thickness
• User input camber

uniform wake Froude number Fr9999.0
Advance Ratio Js 0.976 IHUB OFF
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MPUF3A- and PROPCAV- /HULLFPP(Pressure
distribution on the hull)

• From PROPCAV/HULLFPP

• From MPUF3A/HULLFPP

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MPUF3A- and PROPCAV- /HULLFPP

• Circulations from MPUF3A and PROPCAV

• Not considering induced velocity effect
  
• Match the transition wake geometry from
  PROPCAV with that from MPUF3A

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MPUF3A- and PROPCAV- /HULLFPP

• Field Point Potential from MPUF3A and PROPCAV

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MPUF3A/HULLFPP (Effects of the ultimate wake
singularities)

• Previously, it was assumed that only the steady
  part of the circulation at the blade TE shed
  into the ultimate wake, and a decay function was
  applied to the transition wake
• In the improved approximation the unsteady
  vorticity is shed into the ultimate wake
• This improvement was verified by several cases
  using uniform inflow

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MPUF-3A/HULLFPP

• General wake geometry

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MPUF-3A/HULLFPP(Steady cavitating case)

• Hull geometry and run conditions

Uniform wake IHUB ON TLC ON
Cavitation number Froude number Fr
3.0789 Advance Ratio Js 1.177
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MPUF-3A/HULLFPP(Pressure distribution on the
hull)

• Improved Approximation

• Using decay function

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MPUF-3A/HULLFPP (Unsteady cavitating case)

• Cavitating run conditions
• Effective wake
• Cavitation number
• Froude number Fr4.0
• Advance Ratio Js 1.0
• IHUB OFF
• TLC ON

• Cavity patterns

20x18
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MPUF-3A/HULLFPP(Pressure distribution on the
hull)

• Improved approximation

• Using decay function

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NEW EFFECTIVE WAKE CALCULATION
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Effective wake evaluation at blade control points
Previous method evaluates effective wake at a
plane ahead (by one cell) of the blade.
New method Evaluates the effective wake at the
blade control points.
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Effective wake evaluation at blade control points
Interpolation of total axial velocity on control
points
Interpolation of total tangential velocity on
control points
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Effective wake evaluation at blade control points
At the MPUF-3A control points, the induced
velocity may be in error due to the local effect
of blade singularities. The bad points need to be
removed before the induced velocity is (time)
averaged. The figure shows the induced velocity
at a control point at chord index 9 and span
index 8.
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Effective wake evaluation at blade control points
At each control point, Ue Ua -Uin is applied,
the expected effective wake should be 1.00 at all
points, there is still a maximum of 4 error in
this case.
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Effective wake evaluation at blade control points
The error brings lower circulation for this case,
which still needs improvement.
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CAVITATING DUCTED PROPELLER
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Modeling of cavitating ducted propeller(duct
panel method, propeller PROPCAV)

• NACA0015 Duct

Straight Panel
Paneled with pitch angle (45o)
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Modeling of ducted propeller

• NACA0015 Duct

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Modeling of ducted propeller

• NACA0010 Duct

Straight Panel
Paneled with pitch angle (45o)
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Modeling of ducted propeller

• NACA0010 Duct

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Modeling of ducted propeller

• NACA0015 Duct N3745 Propeller

Uniform wake Advance ratio Js 0.6
Circulation Distribution
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BLADE DESIGNVIA OPTIMIZATION
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CAVOPT-3D (CAVitating Propeller Blade
OPTimization method)Mishima (PhD, MIT, 96),
Mishima Kinnas (JSR 97), Griffin Kinnas
(JFE98)
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CAVOPT-3D

• Allows for design of propeller in
  non-axisymmetric inflow and includes the effects
  of sheet cavitation DURING the design process
• MPUF-3A is running inside the optimization scheme
  until all requirements and constraints are
  satisfied
• Takes about 600-1000 MPUF-3A runs to produce the
  final design (3-6 hrs)
• New versions of MPUF-3A (that include duct, pod,
  etc) can be incorporated
• Not practical as a web based instructional tool

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New Optimization Method

• Start with a base propeller geometry.
• Given conditions are Js, inflow (can be
  non-axisymmetric), cavitation number, Froude
  number, and thrust coefficient.
• The optimum design is searched for within a
  family of propeller geometries such that

X1, X2, X3 are factors (constant initially, to be
varied later)
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• Hydrodynamic coefficients and cavity planform
  area are expressed in terms of polynomial
  functions of X1, X2 and X3.

While
The function coefficients are determined by Least
Square Method (LSM), using the predictions of a
large array (e.g. 10x10x10) of MPUF-3A runs
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The Optimization Scheme (based on CAVOPT-2D,
optimization method for cavitating 2-D hydrofoils)

• The optimization problem of the propeller design
  is

Minimize
Subject to
Where is the objective function to be
minimized. is the solution vector of n
components. ( i1m ) are
inequality constrains and (
i1l ) are equality constrains.
The constrained optimization problem is changed
to an unconstrained optimization problem by using
Lagrange multipliers and penalty functions. For
more information, please refer to the JSR paper
by Mishima Kinnas, 1996.
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In current case, the problem reduces to
Augmented Lagrange function
With
and are user defined.
The function to be minimized is , while
x is the vector (X1, X2, X3), and are
Lagrange multipliers, and are penalty
function coefficients.
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Optimization Samples
Sample 1 Fully wetted run based on N4148
propeller (with prescribed skew distribution)
-- Design conditions

• , to be minimized
• , ,
• uniform inflow
• 20x9 grid size

-- Range of variables
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-- Database and Interpolation
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How good is the interpolation method?
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-- Optimum solution and comparisons with CAVOPT-3D
3rd order functions are used to approximate both
KT and KQ
code KT 10KQ Efficiency
OPT 0.1490 0.2994 0.7921
CAVOPT-3D 0.1504 0.2996 0.7991
The solution of OPT are
X1 1.28865 X2 0.80000 X3 2.00000
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Propeller geometry comparison OPT vs. CAVOPT-3D
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Circulation comparison OPT vs. CAVOPT-3D
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Pressure distribution comparison OPT vs.
CAVOPT-3D
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Blade geometry comparison OPT vs. CAVOPT-3D
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Sample 2 Cavitating run based on N4148 propeller
and presribed skew distribution
-- Design conditions

• , to be minimized
• , ,
• effective wake file
• 10x9 and 20x9 grid size

-- Range of variables
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-- Wake file used
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-- Database and Interpolation
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-- Optimization solution from OPT (MPUF-3A 10X9)
and comparisons with CAVOPT-3D (MPUF-3A 10X9)
4th order functions are used for KT, KQ and CAMAX
Initial guess ( 0.8, 1.0, 1.0 )
code KT 10KQ CA Efficiency
OPT (10x9) 0.2505778 0.5528295 18.51 86.6
CAVOPT-3D 0.2267294 0.5193282 18.97 83.4
The solution of OPT are
X1 1.43586 X2 2.00000 X3 1.89869
Several initial guesses were tested, they led to
the almost same optimization results.
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Propeller geometry comparison OPT (10x9) vs.
CAVOPT-3D (10x9)
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Circulation comparison OPT (10x9) vs. CAVOPT-3D
(10x9)
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Blade geometry comparison OPT (10x9) vs.
CAVOPT-3D (10x9)
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Cavitations comparison OPT (10x9) vs. CAVOPT-3D
(10x9)
18.97
18.51
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-- Optimization solution of OPT (20x9)
4th order functions are used for KT, KQ and CAMAX
Initial guess ( 0.8, 1.0, 1.0 )
code Grid KT 10KQ CA Efficiency
OPT 20x9 0.2497656 0.5558742 20.85 85.8
CAVOPT-3D 10x9 0.2267294 0.5193282 18.97 83.4
The solution of OPT are
X1 1.44072 X2 1.94383 X3 2.00000
Several initial guesses were tested, they led to
almost the same optimization results.
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Propeller geometry of OPT (20x9)
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Circulation of OPT
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Blade geometry and cavity of OPT (20x9)
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Conclusions and Future work (on optimization)

• The interpolation scheme can approximate the
  database very well using higher order functions.
• The optimization scheme works well for the fully
  wetted run. For cavitating runs, both CAVOPT-3D
  and OPT should be improved.
• Include more parameters in current optimization
  scheme.
• Improve the approximation of cavity area.