shen and korpus - 2015 - numerical simulations of ship self-propulsion and

8/19/2019 Shen and Korpus - 2015 - Numerical Simulations of Ship Self-Propulsion and

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NUMERICAL SIMULATIONS OF SHIP SELF-PROPULSION AND MANEUVERING

USING DYNAMIC OVERSET GRIDS IN OPENFOAM

Zhirong Shen (American Bureau of Shipping, USA)

Richard Korpus (American Bureau of Shipping, USA)

1. SUMMARY

Dynamic overset grids provide a powerful tool forCFD calculations that model relative motion between

body components. This paper presents a new oversetmethod utilizing OpenFOAM to simulate the self- propulsion and maneuvering of ships. The methoduses one set of overset cells fixed to the Earth, asecond set fixed to the hull, a third set rotating withthe propellers, and a fourth set rotating with therudders. Prescribed motions move the propeller and

rudder blocks relative to the hull, and the entire hullassemblage moves relative to Earth using 6-DOFmotions derived from CFD forces. A digital autopilotcontrols rudder rotation for course keeping. Overset boundary conditions and hole cutting are updateddynamically at run time for every time step.

The method is demonstrated using two ship models

for which extensive validation data exists: the JapanBulk Carrier (JBC); and the Office of Naval Research

Tumblehome ship (ONRT). JBC self-propulsionresults include cases with and without an EnergySaving Device (ESD). ONRT results include freerunning maneuvers in regular head seas and

quartering waves.

2. INTRODUCTION

Predictions of ship self-propulsion, maneuvering andcourse keeping, whether in calm water or waves, areone of the most demanding challenges in shiphydrodynamics. Interactions between the hull, rudder,and propeller all have to be accurately resolved, andthis proves impossible for potential flow codes andother linear methods. Computational Fluid Dynamic(CFD) is one of the most effective alternatives because it resolves the complex viscous turbulent

flow around a stern using the Naiver-Stokesequations. However, relative motion between thevarious components (propellers, rudders, heavinghulls) remains a critical challenge because traditional

dynamic grids distort (causing a loss of accuracy),and sliding mesh methods lack robustness (e.g.

rudders moving close to rotating propellers).

The dynamic overset grid technique has a longhistory of accurate, efficient and robust applications(Rogers, et al., 1994, Korpus, et al., 1997, 2005, 2007,

Meakin, 1999, Suhs, et al., 2002). Individualgeometry elements are usually moved using a nested

hierarchy approach wherein any group of objectsmoves relative to its parent using prescribed motions,free dynamics, or some combination of the two.Propellers, for example, can rotate around oneship-fixed axis while rudders rotate about a differentone. The whole collection of elements can either be

made to translate at a known speed (such as during aship resistance test), or under the influence of forces

from waves, propellers, or towing forces. The type ofmovement can even change part way through asimulation – as might be required for a storesseparation problem. The potential permutations are

endless.

More recent developments with dynamic overset

grids include demonstrations of hull-propeller-rudderinteractions and zig-zag maneuvering for the KCSCFD validation model (Mofidi and Carrica 2014),Carrica et al. (2015) extended that work to includethe ability to perform maneuvering simulations inwaves, and demonstrated a great step forward incomputational ship hydrodynamics. Shen et al.

(2014a, 2014b, 2015) implemented overset gridtechnique in the open source toolkit OpenFOAM by

coupling with the SUGGAR library (Noack, 2005).The resulting dynamic overset grid technique wasvalidated for self-propulsion, seakeeping andmaneuvering using the KCS, KVLCC2 and DTMB5415M CFD validation data sets.

The present paper introduces a new implementation

of dynamic overset gridding for OpenFOAM solvers.Domain Connectivity Information (DCI), hole cutting,and overlap minimization are provided using astandalone overset grid assembler. Dynamic linkingof the grid assembler and OpenFOAM solvers allowscomputations of complex ship hydrodynamic

problems including self-propulsion and free-runningmaneuvering simulations.

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Two categories of simulations are performed todemonstrate the method. This first category coversself-propulsion simulations of the Japan Bulk Carrier

(JBC) with and without an Energy Saving Device(ESD). The second category covers course-keepingsimulation of the ONR Tumblehome ship (ONRT) in

waves. The ONRT model is equipped with twin propellers, twin rudders, and a digital autopilot forcourse keeping.

3. COMPUTATIONAL METHODS

All simulation results presented in this paper werecreated using OpenFOAM version 2.3.1. Minormodifications to the standard interDyMFoam solver

are necessary to enable inclusion of dynamic oversetgrids. InterDyMFoam discretizes the incompressibleReynolds-Averaged Navier-Stokes (RANS) equationsusing a finite volume technique, and captures the free

surface using the Volume of Fluid (VOF) method toresolve interfaces between air and water. The � SST model provides turbulence closure.

The method uses a stand-alone DCI grid assembler toestablish connectivity among independent moving

overset grids. Coding uses the new C++11 standardand dynamic library calls OpenFOAM to fetch andreturn grid information for fast DCI searches and boundary condition specifications. The softwarecurrently handles up to two-levels of grid blockhierarchy, which is sufficient for the self-propulsion

and maneuvering simulations presented herein. An

overlap minimization procedure reduces duplicatedgrid regions to the smallest allowable for a givenorder of accuracy, and therefore improvesinterpolation accuracy. The assembler is capable of processing OpenFOAM grids with arbitrary cellshape, including general polyhedron, and thereforeallows grid importation from a wide range of mesh

generation tools. Additions are under development toimprove stability and run time efficiency.

4. JAPAN BULK CARRIER (JBC)

4.1 Test Conditions

JBC is a new self-propulsion benchmark model forthe Tokyo 2015 Workshop. The model has a length of7.00 meters and test speed of 1.179 meters per second(corresponding to Fr = 0.142). Test conditionsinclude self-propelled cases with and without a

duct-like ESD mounted upstream of the propeller.Table 1 summarizes the test conditions. The test

series also includes resistance measurements made incalm water with the propeller removed.Corresponding CFD simulations include both theresistance and self-propelled configurations, each performed with and without the ESD. In all cases, themodel is free to sink and trim and the computational

domain moves forward at ship speed.

4.2 Overset Grids

The computational grids consist of several oversetcomponent cell groups. Each component grid iscreated using HEXPRESS from NUMECA, and thenassembled using stand-along DCI software. Figure 1

illustrates an assembled grid for the case with ESDand propeller. The grid is composed of separatecomponents for the hull (including ESD), propellerand background – each shown in a different color.

Tables 2 and 3 demonstrate the results of grid sizesfrom a grid convergence study performed for JBC.Results for three grid levels are shown to demonstrate

how a refinement ratio of √ 2 affects accuracy. Totalcell counts range from O(1.0e+6) to O(5.7e+6) forthe conditions without propeller (Cases 1.1 and 1.2),and from O(1.5e+6) to O(7.4e+6) for the conditions

with propeller (Cases 1.5 and 1.6).

Simulating the four separate cases demonstrates oneadvantage of the overset technique. Changing between cases only requires swapping out one or twocomponent grids. Switching from Case 1.5 to Case1.6, for example, requires changing only the hull grid.Reusing the propeller and background grids (asindicated in Table 3) saves immeasurable time.

(a) Surface Grid of ESD and Propeller

(b) Global View

(c)

Close Up of Stern RegionFig. 1 Overset Grids of JBC, ESD and Propeller

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Table 1 Summary of JBC Test conditions

Case ID Case 1.1 Case 1.2 Case 1.5 Case 1.6

ESD No Yes No Yes

Propeller No No Yes Yes

Table 2 Overset Grids for JBC without Propeller

Grid Hull Background Total

Without ESD (Case 1.1)

Coarse 461,728 562,500 1,024,228

Medium 1,097,591 1,208,380 2,305,971

Fine 2,663,514 2,818,520 5,482,034

With ESD (Case 1.2)

Coarse 500,747 562,500 1,063,247

Medium 1,142,667 1,208,380 2,351,047

Fine 2,908,232 2,818,520 5,726,752

Table 3 Overset Grids for JBC with Propeller

Grids Hull Propeller Background Total

Without ESD (Case 1.5)

Coarse 608,906 349,517 562,500 1,520,923

Medium 1,219,223 843,611 1,208,380 3,271,214

Fine 2,673,358 1,879,165 2,818,520 7,371,043

With ESD (Case 1.6)

Coarse 773,460 349,517 562,500 1,685,477

Medium 1,383,455 843,611 1,208,380 3,435,446

Fine 2,754,647 1,879,165 2,818,520 7,452,332

4.3 Results

Table 4 shows resistance predictions for JBC withoutESD (Case 1.1). All quantities come from after thesolution converges to a steady state solution. Errorsof CT

for medium and fine girds are less than 1%.Table 5 shows resistance predictions with the ESD(Case 1.2), and demonstrates that CT, CP and CV showmonotonic convergence. Predictions of sinkage and

trim are diverged, but are notably small values at thislow Froude number. They will have limited impact onresistance. The medium grid obtains good resistance predictions with less than 1% relative error for CT.Fine grid results are only marginally better.

For the self-propulsion tests, a PI controller adjusts propeller speed during the simulations in order toachieve target speed and thrust/drag balance. The

controller monitors the difference between ship speedand target speed and updates propeller rotation rateaccordingly. Figure 2 demonstrates the method forthe self-propelled JBC with ESD (Case 1.6), andshows how ship and propeller speed eventually reacha steady state. The initial condition is with the ship attarget speed (1.179 m/s) and propeller at zerorevolutions per second (RPS). Note that ship speed

first drops due to insufficient propeller rotation. After

a few seconds, the thrust catches up and ship speedapproaches its target. Once ship speed reaches its

target, the propeller RPS defines the self-propulsion point. In order to capture blade-rate force fluctuations

accurately, the time step for self-propulsionsimulations is set to 0.0006 seconds (~ 200 time steps per propeller revolution).

Fig. 2 Time History of Propeller RPS and Ship Speedfor Self-Propelled JBC with ESD (Case 1.6, MediumGrid)

Table 4 Resistance of JBC without ESD (Case 1.1)

EFD Fine Medium CoarseCT (x103) 4.29 4.2621 4.2928 4.6197

Error -0.65% 0.064% 7.684%

CP (x103) 1.1195 1.1851 1.4489

CV (x103) 3.1426 3.1077 3.1708

Sinkage [%LPP] -0.086 -0.0873 -0.0882 -0.0895

Error 1.547% 2.588% 4.069%

Trim [%LPP] -0.18 -0.1915 -0.1925 -0.1936

Error 6.405% 6.94% 7.573%

Table 5 Resistance of JBC with ESD (Case 1.2)

EFD Fine Medium Coarse

CT (x103) 4.26 4.275 4.287 4.479Error 0.351% 0.637% 5.146%

CP (x103) 1.175 1.184 1.346

CV (x103) 3.1 3.103 3.134

Sinkage [%LPP] -0.085 -0.0871 -0.088 -0.0888

Error 2.513% 3.582% 4.507%

Trim [%LPP] -0.182 -0.195 -0.194 -0.191

Error 7.027% 6.344% 5.173%

Table 6 Self-Propulsion of JBC without ESD

(Case 1.5)


CT (x103) 4.81 4.768 4.866 5.039

Error -0.88% 1.17% 4.76%

n (RPS) 7.8 7.842 7.962 8.194

Error 0.54% 2.07% 5.05%

K T 0.217 0.2125 0.2138 0.2148

Error -2.06% -1.48% -0.99%

K Q 0.0279 0.02836 0.02835 0.02825

Error 1.68% 1.60% 1.24%

Table 6 summarizes results of self-propulsion testsfor the JBC without ESD (Case 1.5). CT, propeller

speed (n) and K Q all show monotonic convergence.

Although K T fails to converge, the maximum error isless than 2.1%. As for the total resistance and propeller speed, both medium and fine grids obtain

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better results than the coarse grid. Table 7 lists theself-propulsion results with ESD (Case 1.6), andshows a similar trend as Case 1.5. Both total

resistance and propeller speed are well predicted bythe medium and fine grid. K T shows oscillatory

convergence and K Q is diverged, indicating that it is

relatively more difficult to achieve convergence for propeller forces and moments than for hull resistance.

Table 7 Self-propulsion of JBC with ESD (Case 1.6)


CT (x103) 4.762 4.786 4.752 5.024

Error 0.50% -0.22% 5.50%

n (RPS) 7.5 7.673 7.632 7.96

Error 2.30% 1.75% 6.10%

K T 0.233 0.2266 0.2256 0.2286

Error -2.75% -3.18% -1.89%

K Q 0.0295 0.02966 0.02933 0.02952

Error 0.54% -0.56% 0.07%

5. ONR TUMBLEHOME (ONRT)

5.1 Test Conditions

Similar to the JBC, ONRT is a new benchmark shipmodel for Tokyo 2015. The model has a length of3.147 meters and speed of 1.11 meters per second(corresponding to Fr = 0.20). ONRT has twin rudders

and twin propellers. Table 8 lists the threefree-running maneuvering cases simulated using theoverset system described herein. The comparablemodel tests tow a model at a fixed attitude for a prescribed period and then release it from the carriageinto six degree-of-freedom motion controlled only bythe rudder autopilot. Rudders are activated by a PIDcontroller for course keeping. For Cases 3.12 and

3.13, the model is sailing in regular waves of length3.147 meters and wave height of 0.06294 meters.

Table 8 Free-Running Test Conditions for ONRT

Case No. Case 3.9 Case 3.12 Case 3.13

Condition Calm water Head wave Quarteringwave (135o)

Motion 6DoF 6DoF 6DoF

Propellers Yes Yes Yes

Rudders Active Active Active

5.2 Overset Grids

The computational grid for ONRT consists of sixoverset cell groupings as listed in Table 9. In additionto the background grid, the moving componentsinclude the hull, two rudders and two propellers.

Each overset grouping of cells can move relative to

all the other groupings and is generated usingHEXPRESS. The components are prepared using thedescribed overset grid assembler. Figure 3 shows a

global view of the complete grid, and close ups of therelevant details. Note that a different background gridin the shape of a cylindrical is used in Case 3.13 for

quartering wave simulations

(a) Side View

(b) Hull Surface Grid

(c) Overset Component Grids at Stern RegionFig. 3 Overset Grids for ONRT

Table 9 Summary of Overset Grids for ONRT

Grid Name Case 3.9 & 3.12 Case 3.13

Hull 1,911,782 1,876,649

Propeller x 2 1,178,626 1,178,626

Rudder x 2 424,951 424,951

Background 1,208,380 1,383,300

Total 6,327,316 6,467,103

5.3 Results

Before any free-running simulations start, weinitialize the calculation by making self-propelledsimulations to determine the propeller speed needed

for thrust balance at a ship speed of 1.11 m/s. Thesimulation follows the same procedure as described

in Section 4.3. For ONRT the final predicted propeller speed is 8.80 RPS, or 1.9% less than themodel-test value of 8.97 RPS.

For free-running simulation in calm water (Case 3.9),the ship model has full 6-DOF motion and a constant propeller speed of 8.80 RPS. Table 10 shows the

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results, and indicates a non-dimensional final speedof 1.001 (1.27% less than the experimental value of1.01). Predicted sinkage is 2.89% larger than the

experimental result and trim angle has a slightlyworse error at 6.6%. As with JBC though, theabsolute differences in value are small.

Table 10 Free-Running Test of ONRT in Calm Water

Case 3.9 EFD CFD Error

Speed � 1.01 1.001 -1.27 %

Sinkage σ×102(m) 0.226 0.2327 2.89%

Trim (deg) -0.0386 -0.0411 6.63%

n (RPS) 8.97 8.8 -1.90%

For Case 3.12, the model is sailing in head waves andFigure 4 shows the time history of ship motions. Thesolid lines represent CFD predictions and the circles

experimental measurements. The predicted heave and

pitch motions match well with measurements. Thespeed loss is due to added resistance induced by theincident waves, and matches well given the limiteddata acquisition rate. Figures 5 and 6 show fourinstantaneous snapshots of free-surface motion and

vortices near the stern (evenly spaced over oneencounter period). Waves breaking at the bow andviolent motions at the stern are both apparent inFigure 5. Figure 6 demonstrates the complexinteractions between propeller vortices, rudders, shipmotions and incoming waves.

Fig. 4 Time History of Ship Motions (CFD: solidline; Experiment: circle)

Fig. 5 Four Snapshots of Free-Surface and ShipMotion for One Encounter Period

Fig. 6 Four Snapshots of Vortical Structures near theStern during One Encounter Period

Fig. 7 Wave Generating Zone for Quartering Waves

For Case 3.13, the ONRT model sails in obliquequartering regular waves. OpenFOAM’s third party

library, waves2Foam (Jacobsen et al., 2012), createswaves in the far field region and applies a relaxationzone to transmit them into the near field. A relaxationmethod blends the far field analytic solution with the

near field computed one. Figure 7 demonstrates thewave generation region and computational domain.

Fig. 8 Time History of Ship Motion and Rudder

(CFD: solid line; Experiment: circle)

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Fig. 9 Free-Surface and Ship Motion at the Momentof Maximum Roll Angle

Fig. 10 Vortical Structures near the Stern: Vorticity

Represented by ISO-Surface of Q.

Figure 8 shows time histories of ship motion and

rudder angle resulting from the simulation. The heaveand pitch motions are in good agreement withmeasurements. The amplitude of roll motion isover-predicted, which may be due to an inaccurate

vertical center of gravity. The angle of yaw deviationreaches a maximum value right after model release,

but the deviation angle returns to an average of zero(with oscillations) due to the countering effects of

waves and autopilot. Since the rudder angle isdependent on the yaw deviation angle, the curve presents a similar trend as that of the yaw angle.Figure 9 presents the evolution of free surface and

ship motion during one encounter wave period. Theship is undergoing large-amplitude roll motions.

Figure 10 shows a close-up view of the vorticalstructures in the stern region. The vortices arerepresented using an ISO-surface of Q and colored by

the axial velocity. The axial velocity is projected ontothe x-axis of ship coordinate system.

6. CONCLUSIONS

This paper presents numerical simulations of two new

benchmark ships using an overset grid techniquedeveloped for OpenFOAM. Self-propulsion

simulations of the JBC model indicate total resistanceand propulsion points are in good agreement withexperimental results. Free-running course keepingsimulations with the ONRT model in both calm waterand regular waves reveal a good match with model

measurements. The comparisons demonstrate thatdynamic overset grids work well with OpenFOAMand greatly simplify marine and offshore simulations.

REFERENCES

Carrica, P.M., Mofidi, A., Martin, E., (2015),“Progress toward direct CFD simulation ofmanoeuvres in waves”, Proceedings of MARINE2015, Rome, Italy.

Jacobsen, N.G., Fuhrman, D.R., Fredsøe, J., (2012),“A wave generation toolbox for the open-source CFDlibrary: OpenFoam®”, International Journal for Numerical Methods in Fluids, Volume 70, No 9, pp1073–1088.

Korpus, R., Hubbard, B., Jones, P., Stromgren, C.,and Bennett, J., (1998), “Hydrodynamic Design ofIntegrated Propulsor/Stern Concepts byReynolds-Averaged Navier-Stokes Technique”,Proceedings of the 7th PRADS, The Hague, Netherlands.

Korpus, R., and Liapis, S., (2005), “Active andPassive Control of SPAR Platform Vortex-InducedMotions”, Proceedings of OMAE 2005, Halkidiki,Greece.

Korpus, R., (2007), “Performance Prediction withoutEmpiricism: A RANS-Based VPP and DesignOptimization Capability”, Proceedings of the 18th

CSYS, Annapolis, Maryland, USA.

Meakin, Robert L., (1999), “Composite OversetStructured Grids”, Chapter 11, Handbook of GridGeneration, CRC Press.

Mofidi, A., Carrica, P.M., (2014), “Simulations of

zigzag maneuvers for a container ship with movingrudder and propeller”, Computers & Fluids, Volume96, pp 191–203.

Noack, R.W., (2005), “SUGGAR: a generalcapability for moving body overset grid assembly”,AIAA Paper 2005-5117.

Rogers, S. E. and Pulliam, T. H., (1994), “AccuracyEnhancements for Overset Grids Using a DefectCorrection Approach”, AIAA Paper 94-0523.

Shen, Z., Carrica, P.M., Wan, D., (2014a), “Shipmotions of KCS in head waves with rotating

propeller using overset grid method”, Proceedings ofOMAE 2014, San Francisco, USA.

Shen, Z., Wan, D., Carrica, P.M., (2014b), “RANSSimulations of Free Maneuvers with Moving Rudders

and Propellers Using Overset Grids in OpenFOAM”,Proceedings of SIMMAN 2014, Lyngby, Denmark.

Shen, Z., Wan, D., Carrica, P.M., (2015), “Dynamic

Overset Grids in OpenFOAM with Application toKCS Self-Propulsion and Maneuvering”, Ocean Engineering , Volume 108, pp 287-306.

Suhs, Norman E. and Rogers, Stuart E. and Dietz, W.E., (2002), “PEGASUS 5: An Automatic

Pre-Processor for Overset-Grid CFD”, AIAA Paper2002-3186.

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shen and korpus - 2015 - numerical simulations of ship self-propulsion and

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