NUMERICAL AND EXPERIMENTAL EVALUATION OF WATERJET PROPELLED DELFT CATAMARANS

Transcription

1 11 th International Conference on Fast Sea Transportation FAST 2011, Honolulu, Hawaii, USA, September 2011 NUMERICAL AND EXPERIMENTAL EVALUATION OF WATERJET PROPELLED DELFT CATAMARANS Manivannan Kandasamy 1, Svetlozar Georgiev 2, Evgeni Milanov 2, Frederick Stern 1 1 IIHR-Hydroscience & Engineering, the University of Iowa 2 BSHC- Bulgarian Ship Hydrodynamics Centre ABSTRACT The accurate prediction of waterjet propulsion using CFD is of interest in the standpoint of performance analyses of existing waterjet designs as well as design optimization of new waterjet propulsion systems for high-speed marine vehicles. Currently, the design and analysis of waterjets follow the ITTC '05 recommended procedures and guidelines which was validated by a rigorous experimental campaign through standardized testing. The current study focuses on validation of detailed duct flow simulations on catamarans using the Delft catamaran as the model. The validation work is conducted as a pre-requisite for subsequent URANS based optimization. The Delft catamaran model was build at BSHC and a customized waterjet was designed for the model based on pre-existing stock waterjet designs. Data from the model testing using the ITTC '05 procedures include net jet thrust, thrustdeduction, water-jet volume flow-rate, sinkage, trim, and jet velocity surveys at nozzle exit. Simulations were performed over a speed range of 0.4<Fr<0.75 using URANS and an actuator disk body-force model. The computed net jet thrust, thrust deduction, sinkage and trim compare well with experiments indicating that the present approach is an efficient tool to predict the performance of waterjet propelled JHSS and paves way for future optimization work. KEY WORDS Water-jet, Self-propulsion, URANS, Validation, Catamaran 1.0 INTRODUCTION Nowadays, there is a growing interest in waterjet propulsion because it has a lot of benefits over conventional screw propeller such as shallow draft design, smooth engine load, less vibration, lower water borne noise, no appendage drag, better efficiency at high speeds and good maneuverability. These advantages have increased the demand of waterjet propulsion systems for a variety of marine vehicles including high-speed naval sealift. Since waterjet propulsion systems are relatively new, the powering performance analysis of waterjet appended hulls using tow tank model testing has been a recent, ongoing area of research. The ITTC Waterjet Performance Prediction Specialist Committee (Van Terwisga, 2005) developed a model testing procedure for waterjet propulsion. Rigorous experimental testing was conducted by nine separate ITTC member organizations using a 5.5 m scale model of the U.S. navy's research vessel Athena at Fr=0.6. The scatter in resistance, i.e., the difference between minimum and maximum measured resistance was 9% of the mean. Dynamic trim had an overall scatter of 10.6%, which was reduced to 2.9% if the outliers were removed. Heave had an overall scatter of 117%, reduced to 55% with the elimination of outliers. Looking at the quantities the dynamic trim was measurable to within 0.3 degrees and heave to within 16 mm. The scatter in inlet wake fraction was 7.6%. Of all the methods used to determine flow rate directly, the most accurate and repeatable was the use of a high density laser doppler survey at the inlet opening or internal to the waterjet system. The scatter in flow rate for equal impeller speed appeared was 0.8%. However, there was a 3.5% maximum deviation from the mean in the estimation of model waterjet speed for the self-propulsion point. Consequently, the scatter in the estimated model thrust at self propulsion at Fr=0.6 was 18%. The committee concluded that the mechanics of the experimental procedures applied for the submitted data sets were generally sound, but the complicated nature of the measurements and data reduction resulted in the substantial facility bias. Recent innovations in CFD and high performance computing have enabled faster and cost effective approach for predicting waterjet propulsive characteristics. This has enabled detailed analysis of the flow through the waterjet ducts, which would require prohibitively expensive Laser Doppler Velocimetry (LDV) measurements if the whole flow field has to be measured. Such detailed flow analysis is required for a deeper understanding of the flow physics giving insights into further improvement of the performance characteristics of the waterjet. However, the CFD has to be thoroughly validated before relying on it for performance analysis, design, and optimization. Bulten (2006) performed a detailed investigation both experimentally and numerically on a waterjet test setup where the waterjet inlet was mounted on top of a cavitation tunnel. The mass flow rate in the tunnel was adjusted to get the desired inlet velocity ratio (IVR) values. This was modeled in the CFD using a prescribed velocity profile at the inlet of the cavitation tunnel and a constant pressure boundary condition at the outflow plane. The waterjet stator and rotor geometry was also modeled. Validation demonstrated that the standard two equation turbulence model in combination with wall functions was able to predict the non uniformities in the duct flow field with 2011 American Society of Naval Engineers 217

2 acceptable accuracy. The results showed that the main inlet flow characteristics such as cavitation inception at cutwater where the flow to the duct separates from the main flow, velocity distribution at the impeller plane, flow separation at the inlet, the shape of the inlet stream tube are related to the IVR. The author recommends a dedicated inlet design for each ship since variations in design ship speed and power density of the installations cause the design IVR to vary. The analysis of waterjet for the use of amphibian vehicle was performed by Jang et al., (2004) to provide detail understanding of complicated three-dimensional viscous flow phenomena including interactions of intake duct, rotor, stator, and contracted discharge nozzle. RANS flow solver with moving, non-orthogonal multi-block grid system was used. The CFD results were compared with experimental fluid dynamics (EFD) and the complex viscous flow feature of the waterjet, such as the secondary flow inside of the intake duct, the recovery of axial flow by the action of the stator, and tip vortex were predicted. The performance prediction of waterjet for the use of similar vehicle by diameter sizes and weights were investigated both numerically and experimentally by Kim et al., (2009). An extensive study was undertaken to analyze the effect of integrating RANS calculations into experimental waterjet powering prediction by Delaney et al., (2009). The experimental data for the validation was provided by Jessup et al., (2007), who conducted model tests for the joint high speed sealift (JHSS) powered with four waterjet systems and testing incorporated all of the approaches explored by the ITTC. These included LDV surveys, bollard tests, single total head probes, and direct measure using weight scales. Two different JHSS models were considered; each model houses either axial-flow or mixed-flow waterjet. The hull, waterjet inlets, and shafts were modeled in the simulation. Multi-element unstructured grids and boundary layer prism elements were generated around waterjet geometry. The free surface was treated as a symmetry plane, and the ship was modeled at sinkage and trim prescribed by the propelled experiment. RANS simulation used experimentally determined volumetric flow rates through the pump as a condition for the thrust provided by the actuator disk model. The full scale simulations (Fn=0.35, Reynolds number Rn= ) were also performed in order to investigate the scaling effects by comparing boundary layers. The RANS delivered pump power predictions showed good agreement with EFD within one percent at model scale, and within two percent at full scale. Hino et al., (2009) performed RANS analysis of a free surface flow around waterjet propelled high-speed ship (Fn=1.0, Rn= ). Free surface location was predicted using single-phase level set approach. An actuator disk model in which duct geometry is modeled in a computational grid was used to simulate the self-propelled condition. The nozzle shape was not modeled, and dynamic motions were not predicted. The flow fields of waterjet propelled simulations, such as free surface elevations, pressure distributions in the duct center planes, and limiting streamlines on a ship were compared with the towed simulations; however, the detailed V&V results were not given. Takai et al., (2010) investigated the capability of URANS with an actuator disk model for the simulation of the JHSS appended with axial waterjets, including waterjethull interactions. The computational setup differs from Delaney et al., (2009) in that the waterjet-hull interactions and waterjet-wake interactions are also predicted with free surface and dynamic motions. The effects of waterjet-hull interaction are highly non-linear as they include the effect of the dynamic trim on boundary layer ingestion and shape of inflow stream tube, together with the effect of the waterjet induced vertical forces on the dynamic motion. The waterjet-wake interactions do not significantly affect the propulsion characteristics, but are of interest in the study of wake signatures. Self propulsion simulations are carried out at model scale with full scale thrust identity similarity. The simulations are carried out over a range of ship speed at different IVR ratios for the waterjet. On the finest grid with 13 million points, the jet volume flow rate was under predicted by 6% and was attributed to interpolation errors caused by extensive use of overset grids within the duct; each duct had five overset grids. It was recommended that the number of overset grids be restricted within the duct. An accurate flow rate measurement is very important since the estimation of power is dependent upon velocity cubed and thrust by the velocity squared. The current work extends Takai et al. (2010) to waterjet propelled catamarans. The Delft catamaran was selected as the candidate geometry and was fitted with a custom designed waterjet based on existing stock waterjets by BSHC. Data from the model testing using the ITTC '05 procedures include net jet thrust, thrust-deduction, water-jet volume flow-rate, sinkage, trim, and jet velocity surveys at nozzle exit. The model was shipped to INSEAN after testing to quantify facility bias, and testing is currently being performed in INSEAN. This CFD validation study was done as a prerequisite for subsequent design optimization of both the water-jet inlet and the hull form. In future, the optimized hull and waterjet will be built and model tested at INSEAN. Kandasamy et al., (2010) derived a simplified integral force/moment waterjet model for ship powering predictions that includes the effect of waterjet induced sinkage and trim on the powering performance without requiring detailed simulations for the waterjet system (nozzle, pump, ducting system, and inlet). The CFD waterjet model was also validated for the Delft catamaran since it will be used in the preliminary bare hull optimization, before resorting to the waterjet inlet shape optimization. The remainder of the paper will be structured as follows: section 2 presents an overview of the ITTC recommended procedure for model testing and the CFD waterjet model; section 3 presents the experimental method used at BSHC; section 4 presents the computational method; section 5 presents the results from the experiments and the computations, followed by the conclusions in section American Society of Naval Engineers

3 2.0 ITTC & CFD CONTROL VOLUME METHODS Fig. 1. ITTC control volume The ITTC waterjet model combines model testing with control volume/integral analysis for ship powering predictions. The selected control volume (Fig. 1) is defined by a streamtube consisting of the nozzle, pump, ducting system, inlet, and upstream imaginary surface BC in the flow through which it is assumed no mass transport occurs by definition with one outlet A 6 and inlet A 1A. Vertical reaction force, weight of the working fluid, and pressure and shear forces acting on BC are neglected. The inlet A 1A is selected to avoid major flow distortions by the intake geometry and as practical choice is usually one impeller diameter in front of the ramp tangency point. The first step is the resistance test and wake-field measurements where a resistance test is carried out for a bare hull model with closed intakes that is free to sink and trim. The total bare hull resistance R TBH is obtained and is used later to estimate the thrust deduction factor, t. During the resistance test the boundary layer velocity profile u 1AX (y,z) is measured at Station 1A. This profile will be used later to calculate the following items: the intake area at station 1A, the average velocity at station 1A,, and the momentum correction factor at Station 1A, c m1, which is calculated at any station N using Eq. (1-2) Q T A c cos m6 Jx 6 (3) The momentum correction factor at the jet exit c m6 is obtained from detailed jet velocity profiles using LDV. α is the jet angle relative to the horizontal at the nozzle (station 6). This calibration is assumed to hold good even with nonzero forward velocity, so that the Kiel probe measurements taken during self-propulsion tests could be used to estimate Q. After calibration, the propulsion test is carried out to determine relation between speed, flow-rate and thrust at self propulsion point. The calibrated Kiel probe measurements provide Q at the self-propulsion point. Q is then used to determine the size of the inlet capture area from the inlet wake-field measurements by applying conservation of mass. Once the capture area is determined c m1 can be calculated. All the relevant variables to predict the waterjet net thrust (R X ) from Eq. (4) are now known. 2 Q R c cos Qc U (4) X M 6 Min 0 A6 Note that the ITTC model ignores vertical forces and pitching moments. These are not relevant for the purposes of the original ITTC model, since sinkage and trim are measured during the thrust evaluation procedure. For a CFD simulation, however, it is desirable to estimate the resulting waterjet-induces forces and moments affecting sinkage and trim, since the final attitude of the ship affects the resistance and wave-generation characteristics of the ship. Hence, a modified control volume is selected as shown by the shaded area in Fig. 2. c MN 1 u da A A N V N (1) N 2 1 V N V n da (2) A AN N Next is the calibration and propulsion test. The purpose of the calibration test is to establish a relation between a measurement signal at the jet (often a differential pressure transducer or Kiel probe is used) and the jet-thrust (T Jx ) which is measured through the Bollard pull test. The flow rate (Q) is then calibrated through the momentum flux approach, since direct measurement of flow-rate is prone to higher uncertainties. Assuming negligible inlet axial velocity, T Jx is equal to the momentum flux at the jet nozzle providing Eq. (3) for estimating Q. Fig. 2. CFD control volume The choice of the proposed control volume which is for the waterjet is motivated by the possibility of experimentally measuring the pressure and velocities at the waterjet inlet, which allows for the computation of the inlet flow angle, momentum flux correction factor C Min, pressure force A, and pressure distribution at stern which provides P in in the waterjet/hull interaction stern force ΔF S. The model can then be used during early design optimization stages to includes the effect of waterjet induced sinkage and trim on the powering performance without requiring detailed simulations for the waterjet system (nozzle, pump, ducting system, and inlet) American Society of Naval Engineers 219

4 3.0 EXPERIMENTAL METHODS Table 1 provides the main particulars of the Delft catamaran model. Table 1. Main particulars for the Delft catamaran model Main Particulars Symbol Model Length overall, m L OA Length between perpendiculars, m L PP Length on waterline, m L WL Breadth moulded, single hull, m B Clearance b/n hull CPs, m Draft at FP, m T F Draft at AP, m T A Displacement volume, m 3 Δ Prismatic coefficient C P Block coefficient C B Longitudinal C.B. LCB Wetted surface area (bare hull), S m A waterjet propulsion unit, consisting of ducting system, inlet opening, axial flow pump and nozzle, was incorporated in each of the catamaran hulls. Fig. 3 shows the stock waterjet pump arrangement used for testing. Fig. 3. Waterjet propulsion unit used for testing The model testing was carried out in BSHC deep water towing tank. The towing tank main dimensions is 200 m length x 16 m breadth x 6.5 m depth. Two wave absorbing beaches are arranged, one front and one side dampers. The towing carriage has a maximum speed of 6 m/s. The carriage is used to guide the ship model and to hold the measuring and supplementary equipment. A propeller dynamometer was installed on the starboard hull for impeller generated thrust and torque (delivered power) measurements. Three forms of pressure reading instrumentation were used for the hull model testing: i) static pressure taps located around the inlet opening of starboard hull; ii) one static pitot tube was used to measure the hull boundary layer velocity profiles and one static pitot tube for measuring the reference dynamic pressure at the starboard hull nozzle exit; iii) a 5-hole probe was used to determine flow-field velocity distribution at the nozzle exit plane of starboard hull at bollard conditions, necessary to calculate the nozzle momentum correction factor and bollard flowrate. During the resistance test the boundary layer velocities were measured along a normal to hull surface, one inlet diameter upstream of inlet centerline, with the inlets closed. The runs were made at 7 different model speeds, corresponding to Froude numbers 0.4, 0.45, 0.5, 0.55, 0.6, 0.65 and 0.7. The measurements were performed by means of a static pitot tube. It was assumed that the velocity profiles thus obtained do not change in traverse direction (they vary only in z direction) and so they fully describe the flow pattern at Station 1A. The obtained velocity profiles were later used to calculate the intake area and the inlet momentum correction factor C m1. There is some controversy on whether the velocity survey should be made with closed intake (nominal wakefield) or with open intake and active waterjet (total wakefield). Terwisga (2005) states that ideally one would like to measure the effective wake ingested by the intake. That is the flow field including the suction effects on the flow about the hull, without any effect of the intake flow itself. This so called effective wake is however difficult to measure (intake flow is always present) and depends on the working point of the intake. For that reason, it is suggested to measure the boundary layer velocity profile with closed intake openings, which contradicts the previous tentative procedure described in the ITTC Quality Manual( ). Bollard pulling forces were measured with both pumps operating within a range of impeller revolutions. The obtained data were used later for flowrate calibration. The reference nozzle dynamic pressure (measurement signal) necessary for flowrate calibration was measured with a static pitot tube located at about 70% of nozzle exit radius, i.e. about the middle of the nozzle flow area, at 12 o clock position. The main objective of these tests was to define the model self-propulsion parameters and to gain data necessary for self-propulsion flowrate estimation. No skin friction correction force was applied during the tests, thus all results refer to model scale conditions. For all the tests, the model was free to heave and pitch, but was restrained in yaw and roll. The tests were performed with outward turning impellers. 3D velocity survey at nozzle exit (Station 6) was performed using 5-hole pressure probe. The obtained local axial velocity distribution was used to evaluate the nozzle momentum correction factor C m6 at that Station, used for flowrate calculation. 4.0 COMPUTATIONAL METHODS The Unsteady Reynolds-Averaged Navier Stokes (URANS)/ Detached Eddy Simulation (DES) flow solver, CFDSHIP- IOWA has been developed at IIHR Hydroscience & Engineering over the past 15 years for ship hydrodynamics applications (Carrica et al., 2007). For the present work, American Society of Naval Engineers

5 URANS with the blended k-ε/k-ω turbulent model is selected as a flow solver. The free surface location is predicted by a single phase level set method. A second order upwind scheme is used to discretize the convective terms of momentum equations for URANS. A pressure-implicit splitoperator (PISO) algorithm is used to enforce mass conservation on the collocated grids. The pressure Poisson equation is solved using the PETSc toolkit (Belay et al., 2002). All the other systems are solved using an alternating direction implicit (ADI) method. For a high performance parallel computing, a MPI-based domain decomposition approach is used, where each decomposed block is mapped to one processor. The code SUGGAR (Noack, 2005) runs as a separate process from the flow solver to compute interpolation coefficients for the overset grids and communicates with a motion controller (6DOF) within CFDSHIP at every timestep. The software USURP (Boger and Dreyer, 2006) is used to compute area and forces on the surface overlapped regions. In addition, a simplified body force model is used for waterjet propelled simulation to prescribe axisymmetric body force with axial and tangential components (Paterson et al., 2003). The propeller model requires thrust, torque, and advance coefficients as input and provides the torque and thrust forces. These forces appear as a body force term in the momentum equations for the fluid inside the propeller disk. The location of the propeller is defined in the static condition of the ship and moves according to the ship motions. Based on recommendations from Takai et al. 2010, care was taken to limit the number of overset grids in the duct and reduce interpolation errors for volume flow rate. The duct is discretized using a single structured grid which overlaps with the hull grid at the inlet ant the nozzle exit (Fig. 4). Fig. 4. Overset grid system for Delft catamaran with symmetry plane. A symmetry boundary condition was used and a body-fitted O type grids are generated around the port side ship hull geometry. A rectangular background grid is used with clustered grid near the free surface to resolve the wave field. A cylindrical refinement block was generated immediately following the nozzle exit to better resolve the exiting jet. In the present work, the shaft and the downstream rotor are not included in order to avoid the complexity of the grid design since the present work is prerequisite for optimization work. For self propelled simulations, a total of 6.4 million grid points is split into 64 blocks with an average of 100K grid points/block by the MPI based domain decomposition. The simulation domain is extended to [-0.5, 2.5], [-0.7, 0.7], [0, 1.3] in streamwise, vertical and spanwise directions, respectively. The boundary conditions are detailed in Table 2. In. Table 2. Boundary conditions Description p U V W Resist. Selfpropelled Exit Bottom, sides Top Symmetry No slip (ship hull) For barehull resistance computations, the ship is initially static on calm water. The ship is then allowed to pitch and heave under a constant inlet fluid velocity until a steady state is reached. Ship-fixed coordinate system is used, which means that there is no surge motion allowed for the ship and the background grid. For self-propulsion simulation, an actuator disk model is used to prescribe axisymmetric body force with axial and tangential components. The simulations mimic the experiment; the ship accelerates until the resistance equals the prescribed thrust and added tow force and converges to the self propulsion point. 2-5 nonlinear iterations are required for convergence of the flow field equations within each time step. Convergence of the pressure equation is reached when the residual imbalance of the Poisson equation drops six orders of magnitude. All other variables are assumed convergence when the residuals drop to RESULTS For all the tests, the model was free to heave and pitch, but was restrained in yaw and roll. The model resistance, sinkage and trim were investigated in a Froude number range , corresponding to towing speed range of m/s m/s. The measured barehull resistance, sinkage and trim are compared with the CFD calculations in Fig. 5. The sinkage was measured with two string pots for displacement measurements, one located on the leading post (1708 mm forward of midship) and a second located on the tow post (97 mm aft of midship). The measured data were used to calculate the trim angle. The sinkage is measured at the tow post location American Society of Naval Engineers 221

6 Table 2 shows the impeller rps, thrust and torque at model self-propulsion point. The flow rates Q during self propulsion were calculated using the reference pressure Pdref, at Station 6 which were taken at the same static pitot tube location as at bollard condition and the self propulsion flow rates were using the bollard flowrate calibration relation. The measurements were taken at the same Static Pitot tube location, as at bollard condition. Fig 6 compares the computed volume flow rates with the measured values. CFD underpredicts the volume flow rate by ~2% over the speed range. (a) Fig. 6. Comparison of volume flow rates (b) The flow rate was used to determine the size of the inlet capture area by applying conservation of mass. For all tested craft speeds, the inlet capture area was assumed to be rectangular and its size was determined from BH inlet velocity-field measurements. Fig. 7 shows the CFD inlet inlet capture area got by seeding the flow through the duct with stream lines which is elliptical similar to previous CFD simulations (Takai et al., 2010). Van Terwsaga (2005) concluded that the inlet capture area for Athena was also elliptical, but the shape does not have significant effect on the ingested momentum and energy flux. However, it was noted that there is at least one reference (Roberts and Walker, 1998) claiming that the choice of a rectangular capture area may lead to an under-prediction of gross thrust by ~10% for a typical high speed ferry. (c) Fig. 5. EFD vs CFD comparisons: (a) barehull resistance and net jet thrust; (b) Sinkage, and (c) trim Table 2. Model self-propulsion points V m/s Fn - n rps Q Nm Rx N Pd REF, kgf/m Fig. 7. Inlet capture area obtained from CFD for Fr= American Society of Naval Engineers

7 The net jet thrust Rx was determined using Eq. (4) and shown in figure 5a. Overall, the net jet thrust Rx is ~10% higher than the barehull resistance. Simulations using the CFD waterjet model, which include the effects of just the waterjet induced sinkage and trim on the barehull indicate an increase of ~5% in barehull resistance. The model scale thrust deduction fraction, t, accounting for all the interaction effects of the propulsion system on bare hull system is shown in Fig. 8. Fig. 10. Duct pressure distribution and exit jet splash Fig. 8. Thrust deduction factor Fig. 9 compares the EFD and CFD flow fields at Fr=0.55 and 0.53, respectively. The diverging wave fronts from the bow show qualitative agreement. EFD shows considerable splashing at the jet exit. The splash is qualitatively resolved by the CFD (Fig. 10), but without any air entrainment effects. Fig. 10 also shows the pressure distribution inside the duct with a rapid pressure rise after the actuator region, which get converted into kinetic energy while passing through the nozzle. Fig. 9. Flow field comparison 6.0 CONCLUSIONS URANS simulations for both barehull and waterjet propelled Delft catamaran is presented and compared with model test results. CFDSHIP-IOWA V.4 is employed as a flow solver, which solves URANS with the blended k-ε/k-ω turbulent model, single-phase level set method, and simplified body force model are adopted to simulate the waterjet propelled ship flow. The present work was performed to investigate the capability of URANS for the accurate simulation of waterjet propelled catamarans as a pre-requisite for CFD based design optimization of both the hull form and the intake duct shape. Due to the complexity of the EFD measurement process, significant facility bias errors were encountered during the validation of the standardized testing (Van Terwisga, 2005) by nine separate ITTC member organizations. Hence, the current Delft model which was built and model tested by BSHC was shipped to INSEAN to quantify facility bias errors and testing is currently being done. Overall, the CFD results match reasonably well with the experiments. The bare hull resistance was under predicted by ~2.5%. The flow rate was under-predicted by ~3%. Previous work on the JHSS (Takai et al., 2010) with the same code with multiple overset grids in the duct region showed ~6% underprediction of flow rate due to interpolation errors. The lower error for the current case can be attributed to the fact the duct is discretized using a single grid, and hence there are no interpolation errors. The CFD under-predicts the net jet thrust by ~5% over the entire speed range. It should be noted that certain evaluation procedures differ between CFD and EFD. The inlet capture area for CFD is elliptical based on streamtubes entering the duct, whereas a rectangular capture area was used for the EFD. Also, the velocity profiles used to determine the capture area in EFD were measured with the inlets closed as per ITTC recommendations, but this is not the case with CFD, where the elliptical capture area obtained with the ducts open was used. Differences are expected to be negligible as per Van Terwisga (2005). However, a thorough quantification of the differences in wake fraction due to the inlet shape changes and differences in velocity profile with open and closed inlets using CFD will be beneficial American Society of Naval Engineers 223

8 Including the effects of the waterjet induced sinkage and trim using the CFD waterjet model captures some of the waterjet system- bare hull system interaction effects, and indicates an increase in resistance by 4%. This accounts for some of the interaction effects which contribute to the thrust deduction, but does not account for the effect of the boundary layer ingestion on thrust which is one of the most dominant jet-hull interaction as addressed by Van Terwisga (1995) and Hoyt et al. (1999). In addition to the thrust deduction, which accounts for the effects of waterjet hull interaction, the propulsive efficiency is an important parameter needed for accurate assessment of delivered powering requirements. Calculation of the overall propulsive efficiency requires accurate estimation of the pump efficiency which necessitates modeling of the shaft, hub, rotor and stator (Bulten and Van Esch, 2007) which is out of scope of the present work and needs to be addressed in future work. The present work demonstrates the feasibility of using URANS for performance analysis of hull-integrated waterjet propelled ship with free surface and dynamic motions and work paves way for waterjet inlet optimization studies with main objective of decreasing powering requirements by increasing the inlet efficiency through modification of intake duct shape (Kandasamy et al., 2011). REFERENCES Balay, S., Buschelman, K., Gropp, W., Kaushik, D., Knepley, M., Curfman, L., Smith, B. and Zhang, H., (2002) PETSc User Manual, ANL-95/11-Revision 2.1.5, Argonne National Laboratory Boger, D.A. & Dreyer, J.J. (2006) Prediction of Hydrodynamic Forces and Moments for Underwater Vehicles Using Overset Grids, AIAA paper , 44th AIAA -Aerospace Sciences Meeting, Reno, Nevada, 2006 Bulten, N.W.H. (2006). Numerical Analysis of Waterjet Propulsion System, PhD thesis, Technical University of Eindhoven, ISBN-10: Library Eindhoven University of Technology Bulten, N.W.H. & Van Esch, B.P.M. (2007) Fully transient CFD analyses of waterjet pumps, Marine Technology, 44(3), pp Carrica, P. M., Wilson, R. V., and Stern, F. (2007) An unsteady single-phase level set method for viscous free surface flows International Journal for Numerical Methods in Fluids, Vol. 53, pp Delaney, K., Donnely, M., Elbert, M., and Fry, D. (2009) Use of RANS for Waterjet Analysis of a High-Speed Sealift Concept Vessel, 1 st International Symposium on Marine Propulsors, Trondheim, Norway Hino, T.., Ohashi, K. (2009) Numerical Simulation of Flow around a Waterjet Propelled Ship 1 st International Symposium on Marine Propulsors, Trondheim, Norway Hoyt III, J.G. (Chairman), 1999, Report of thespecialist Committee on Waterjet, 22ndITTC, Seoul/Shanhai. Jang, J.H., Park, W.G., Boo, J.S., Chun, H.H., & Kim, M.C. (2004) Numerical Simulations of Waterjet with Rotor- Stator Interaction, 10 th international symposium on transport phenomenon and dynamics of rotating machinery, Hawaii Jessup, S., Donnelly, M., Fry, D., Cusanelli, D., & Wilson, M. (2008) Performance Analysis of a Four Waterjet Propulsion System for a Large Sealift Ship, 27 th symposium on Naval hydrodynamics, Seoul, Korea Kandasamy, M., Ooi, S.K., Carrica, P., & Stern, F. (2010) Integral force/moment water-jet model for CFD simulations, Journal of Fluids Engineering, Vol. 132, Kandasamy, M., He, W., Tahara, Y., Peri, D., Campana, E., Wilson, W., & Stern, F. (2011) 'Optimization of waterjet propelled high speed ships - JHSS and Delft catamaran', submitted to FAST 2011, Hawaii Kim, M-C., Chun, H-H., Kim, H. Y., Park, W. K., Jung, U. H. (2009) Comparison of waterjet performance in tracked vehicles by impeller diameter, Ocean Engineering, Vol. 36, pp Noack, R. (2005) SUGGAR: a General Capability for Moving Body Overset Grid Assembly, AIAA paper , 17 th AIAA Computational Fluid Dynamics Conference, Toronto, Ontario, Canada Paterson, E. G., Wilson, R. V., and Stern, F. (2003) General-Purpose Parallel Unsteady RANS Ship Hydrodynamics Code: CFDSHIP-IOWA, IIHR Technical Report, #432, The University of Iowa Roberts, J.L., and Walker, G.J., 1998, Boundary layer ingestion effects in flushwaterjet intakes, International conferenceon Waterjet Propulsion II, RINA, Amsterdam,The Netherlands. Takai, T., Kandasamy, M., & Stern, F., (2011). 'Verification and validation study of URANS simulations for axial waterjet propelled large high speed ship', submitted to Journal of Marine Science and Technology. Van Terwisga, T. et al. (2005) Report of the Specialist Committee on Validation of Waterjet Test Procedures, Proceedings 24 th Int. Towing Tank Conference; II: ACKNOWLEDGEMENTS This work is sponsored by the US Office of Naval Research through research grants N , under the administration of Dr. Ki-Han Kim. The simulations were performed on 4.7GHz IBM Power 6 machine DaVinci at the DoD NAVO center American Society of Naval Engineers