STAR Global Conference 2017 Parametric modelling and optimization of a marine propulsive system using STAR-CCM+,OPTIMATE+ and CAESES Rolla SP Propellers SA Claudio Ghirlanda

Rolla SP Propellers SA Twin Disc Group Leadership in marine technology. Since 1963 in Switzerland Submerged and surface piercing marine propellers Custom propellers for every application

CFD at Rolla More than 20 years CFD experience Propellers CFD Rudders and other hull appendages Resistance prediction of planing and displacement hulls Always with CD-Adapco (Comet / STAR-CCM+)

Using CD-Adapco Optimate+ on marine field Complex flow defined by propeller diameter, pitch, skew, camber, rake, thickness Limitations (cavitation, hull obstructions and dimensions, etc) Change propeller shape to optimize the efficiency Propeller parametric model

Propeller parametric model Friendship Systems CAESES software to generate a parametric CAD model

Software workflow Friendship Systems CAESES software - generate a parametric model STAR-CCM+ - Run simulation Optimate+ - Optimise the solution

Propeller characteristics curves Adimensional parameters to understand the behaviour and goodness of a propeller J=Va/n*D KT= T/(D^4*n^2*ρ) 10KQ= Q/(D^5*n^2*ρ) η=(KT*J)/(10KQ*2π)

Propeller case characteristics Fully submerged propeller 5 blades Submerged propeller Z [-] 5 D [mm] 1450 Nominal rotational speed [RPM] 693 Nominal water speed [Kn] 32.0 Nominal J [-] 0.9891

Parametric model variables Using Friendship Systems CAESES - define variables Optimate+ - manage to submit values 9 variables Changes in chord, tip and camber Submerged propeller Min Value Baseline Max Value Chord tip 0.4 0.45 0.65 Pitch tip 0.8 1.15 1.27 Chord mid 1.066 1.4 Pitch mid1 1 1.3 Pitch mid2 Chord hub 0.6 0.689 0.7 Pitch hub 0.9 Camber hub 0.0 0.01 Camber tip 0.037 0.006

Simulation physics and models RANS K-ε turbulence model One fifth of the geometry with periodic interfaces Newtonian constant density fluid (seawater) Rotating reference frame approach 0 degrees inclination No cavitation will be simulated Not considering the wake effect of a hull upstream Hub extended until the end of the computational domain

Calculation setup 20 minutes per case 40 runs 256 cores linux cluster 9 milions cells Result = Mean value of last 500 iterations

Optimate+ results Optimization of the geometry with efficiency as design target Constrain on KT knowing the application for the propeller Best efficiency after 30 deigns

Best case description Design 30 30 0.6803 1.0606 0.4417 1.1678 0.9800 Design Id eta_0_mean performance chordtip pitchtip chordmid pitchmid1 pitchmid2 chordhub pitchhub 30 0.6803 1.0606 0.4417 1.1678 0.9800 1.0400 1.3000 0.6400 1.1200 28 0.6800 1.0602 0.5458 1.2700 0.9400 1.0600 0.6000 1.2400 35 0.6786 1.0580 0.4000 1.0861 1.0200 15 1.0579 1.0657 1.0000 34 0.6785 1.0578 1.1270 41 0.6774 1.0562 0.5042 0.6200 29 0.6761 1.0542 1.0452 40 0.6753 1.0529 0.6600 39 0.6749 1.0522 1.0248 0.8200 26 0.6743 1.0512

Results – Targets, comparison and limits of the model Baseline case validated by open water tests Efficiency Lower limit on thrust to ensure hull propulsion No parameters to control important propeller geometrical characteristics – eg: expanded area that is related to cavitation phenomena

Conclusions 6.1 % efficiency gain Torque 3.5% lower Thrust 1.5% higher Changes bigger than 10% in values of chord at hub, chord and Pitch at mid blade section

Conclusions – Advantages In the marine field Fuel consumption Less open water tests In general Powerful combination of tools to improve the product New type of geometry

Future development Adding hull appendages Adding cavitation model to the simulations More variables to describe the propeller profile Different advance coefficient J Cavitation tunnel tests

Thank you