ARCTIC/ICE OPERATIONS SESSION. Numerical Simulation of Dynamic Positioning in Ice

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1 Return to Session Menu DYNAMIC POSITIONING CONFERENCE October 9-10, 2012 ARCTIC/ICE OPERATIONS SESSION Numerical Simulation of Dynamic Positioning in Ice Ivan Metrikin and Sveinung Løset Norwegian University of Science and Technology (NTNU) Nils Albert Jenssen Kongsberg Maritime S fi K k i Sofien Kerkeni DCNS Research/Sirehna

2 Numerical Simulation of Dynamic Positioning in Ice Ivan Metrikin and Sveinung Løset Department of Civil and Transport Engineering Norwegian University of Science and Technology Trondheim, Norway Nils Albert Jenssen Kongsberg Maritime Kongsberg, Norway Sofien Kerkeni DCNS Research/Sirehna Nantes, France Arctic/Ice Operations 9-10 Oct 2012 Dynamic Positioning Conference Houston, TX, USA

3 Contents Fields of Application Physical Ice Environment Ice Loads Modeling for Numerical DP Simulations Empirical and Statistical Models Experimental Data Series Methods Physically Based Modeling NTNU Numerical Model Model Description Fully Coupled Numerical DP Simulations, Experimental Validation 10 Oct 2012 Ivan Metrikin et al. 2/31

4 Contents Fields of Application Physical Ice Environment Ice Loads Modeling for Numerical DP Simulations Empirical and Statistical Models Experimental Data Series Methods Physically Based Modeling NTNU Numerical Model Model Description Fully Coupled Numerical DP Simulations, Experimental Validation 10 Oct 2012 Ivan Metrikin et al. 3/31

5 Fields of Application Ice loads on ships DP vessel concepts Screenshots from the DelftShip software, Parent 40 icebreaker model 10 Oct 2012 Ivan Metrikin et al. 4/31

6 Fields of Application DP control schemes Training simulators Oct 2012 Ivan Metrikin et al. 5/31

7 Fields of Application Multi-vessel operations Risk assessment Rohlén, Oct 2012 Ivan Metrikin et al. 6/31

8 Fields of Application Integrated systems Scientific research Illustration: Bjarne Stenberg 10 Oct 2012 Ivan Metrikin et al. 7/31

9 Contents Fields of Application Physical Ice Environment Ice Loads Modeling for Numerical DP Simulations Empirical and Statistical Models Experimental Data Series Methods Physically Based Modeling NTNU Numerical Model Model Description Fully Coupled Numerical DP Simulations, Experimental Validation 10 Oct 2012 Ivan Metrikin et al. 8/31

10 Physical Ice Environment 10 Oct 2012 Ivan Metrikin et al. 9/31

11 Ice Management Moran et al., 2006 Illustration: Joakim Haugen 10 Oct 2012 Ivan Metrikin et al. 10/31

12 Managed Ice Discrete-continuum material 10 Oct 2012 Ivan Metrikin et al. 11/31

13 Contents Fields of Application Physical Ice Environment Ice Loads Modeling for Numerical DP Simulations Empirical and Statistical Models Experimental Data Series Methods Physically Based Modeling NTNU Numerical Model Model Description Fully Coupled Numerical DP Simulations, Experimental Validation 10 Oct 2012 Ivan Metrikin et al. 12/31

14 Empirical Models Ice Shapes and sizes of the ice features Ice and water densities Ice material strength Ice floe size distribution Ice concentration ti Ice confinement Hydrodynamics of the ice pieces (e.g. added mass) Presence of snow cover Fi Friction Vessel Shape and size of the hull Mass and inertia tensor Friction properties of the hull Hydrodynamics d of the vessel Froude number Propulsion Ice loads = F( ) 10 Oct 2012 Ivan Metrikin et al. 13/31

15 Statistical Approach Ice loads = F(ice, vessel) = const Monte Carlo simulation Gauss Poisson Weibull Ice loads = F(ice, vessel) = F(t) 10 Oct 2012 Ivan Metrikin et al. 14/31

16 Contents Fields of Application Physical Ice Environment Ice Loads Modeling for Numerical DP Simulations Empirical and Statistical Models Experimental Data Series Methods Physically Based Modeling NTNU Numerical Model Model Description Fully Coupled Numerical DP Simulations, Experimental Validation 10 Oct 2012 Ivan Metrikin et al. 15/31

17 Experimental Data Series Methods 3 DOF RPM Azimuth Thrust Ice loads Drag Inertia Ice field Dyn. inertia Damping Coriolis Centrifugal 10 Oct 2012 Ivan Metrikin et al. 16/31

18 Open-water DP vs. ice-adapted DP Pos North Pos North [m] 0 [m] 0-10 [m] [deg] [sec] Pos East [sec] Heading [m] [deg] [sec] 0-20 Pos East [sec] Heading [sec] Full-scale values [sec] Recorded Simulated Setpoints 10 Oct 2012 Ivan Metrikin et al. 17/31

19 Contents Fields of Application Physical Ice Environment Ice Loads Modeling for Numerical DP Simulations Empirical and Statistical Models Experimental Data Series Methods Physically Based Modeling NTNU Numerical Model Model Description Fully Coupled Numerical DP Simulations, Experimental Validation 10 Oct 2012 Ivan Metrikin et al. 18/31

20 Physically Based Modeling Fundamental laws of physics High fidelity Real system dynamics Millan and Wang, 2011 Zhan and Molyneux, Oct 2012 Ivan Metrikin et al. 19/31

21 Contents Fields of Application Physical Ice Environment Ice Loads Modeling for Numerical DP Simulations Empirical and Statistical Models Experimental Data Series Methods Physically Based Modeling NTNU Numerical Model Model Description Fully Coupled Numerical DP Simulations, Experimental Validation 10 Oct 2012 Ivan Metrikin et al. 20/31

22 Structure of the Model Wind Waves Vortex physics engine 10 Oct 2012 Ivan Metrikin et al. 21/31

23 The DP Vessel Illustration: Statoil Length between perpendiculars m Breadth, moulded m Design draught m Draught at aft perpendicular m Draught at fwd. perpendicular m Displacement volume m³ Centre of gravity from aft perp m Block coefficient azimuths bow Propulsion: 5.4 MN - 3 azimuths stern CAD model 2956 vertices 5908 faces 10 Oct 2012 Ivan Metrikin et al. 22/31

24 Ice Conditions Assumptions - 6 DOF RBs - Unbreakable - Undeformable - No brash ice - No added mass - No hydrodynamic damping - No ventilation Courtesy HSVA 10 Oct 2012 Ivan Metrikin et al. 23/31

25 Contents Fields of Application Physical Ice Environment Ice Loads Modeling for Numerical DP Simulations Empirical and Statistical Models Experimental Data Series Methods Physically Based Modeling NTNU Numerical Model Model Description Fully Coupled Numerical DP Simulations, Experimental Validation 10 Oct 2012 Ivan Metrikin et al. 24/31

26 DP Simulations Scale factor = 30 Ice drift = 0.5 kts ship moves through the ice The same DP control system and the same tuning as in the ice basin 10 Oct 2012 Ivan Metrikin et al. 25/31

27 Ice Drift Angle = 0 Ice tank Numeric 10 Oct 2012 Ivan Metrikin et al. 26/31

28 Ice Drift Angle = 5 Ice tank Numeric 10 Oct 2012 Ivan Metrikin et al. 27/31

29 Ice Drift Angle = 10 Ice tank Numeric 10 Oct 2012 Ivan Metrikin et al. 28/31

30 Conclusions To the authors knowledge, this is the first publication of a fully coupled numerical simulation of DP in managed ice performed at such fidelity level 10 Oct 2012 Ivan Metrikin et al. 29/31

31 Conclusions Strengths Weaknesses Empirical and statistical models Experimental data series methods Physically based modeling Numerical Reliable for certain High fidelity efficiency conditions Real system dynamics Possible oversimplification Can be difficult to extend Uncoupled icevessel dynamics Recommended usage Initial testing of the DP controllers Tuning the DP systems to a particular set of conditions Computationally demanding Numerical performance assessments Robustness analyses Detailed testing ti of the DP control systems 10 Oct 2012 Ivan Metrikin et al. 30/31

32 Acknowledgements The authors would like to thank the Research Council of Norway (RCN) for the financial support of the MARTEC ERA-NET project DYPIC - Dynamic positioning in ice covered waters (RCN Project No ) and the Arctic DP project (RCN Project No /I40). The authors would also like to thank the Ministry of Ecology, Sustainable Development, Transport and Housing (France) and the Federal Ministry of Economics and Technology (Germany) for their financial support of the MARTEC ERA-NET project DYPIC Dynamic positioning in ice covered waters. Additionally, the authors would like to thank their industry sponsor, Statoil ASA, their project partners, Det Norske Veritas and Hamburg Ship Model Basin, and the authors affiliated companies for the permission to publish this paper. Finally, the authors are thankful to Mr. Dmitry Sapelnikov (NTNU) for his efforts in implementing the NTNU numerical simulator Full reference list can be found in the paper 10 Oct 2012 Ivan Metrikin et al. 31/31