Numerical simulation of ice-induced loads on ships and comparison with field measurements. Biao Su Department of Marine Technology, NTNU May 28, 2013

Transcription

1 Numerical simulation of ice-induced loads on ships and comparison with field measurements Biao Su Department of Marine Technology, NTNU May 28, 2013

2 Motivation Ice hull interaction Local ice load Global ice load Ship s performance Local ice load Global ice load Ship s performance

3 Outline Introduction Numerical modeling Spatial distribution of local ice load Probabilistic distribution of local ice load Discussions

4 Sea ice Complexity Simplification: level ice Randomization: ice thickness and strength properties

5 Ice hull interaction Crushing Bending Ice breaking Crushing Bending Rotating Sliding Ice displacing Sliding Rotating Source: Riska, 2010

6 Numerical modeling Valanto, 2001 Liu et al., 2006 Martio, 2007 Nguyen et al., 2009 Sawamura et al., 2010 Lubbad & Løset, 2011 Source: Valanto, 2007 Source: Lubbad & Løset, 2011

7 Numerical modeling Izumiyama et al., 1992 Su et al., 2010 A A Crushing Bending Rotating Sliding Section A A B T T B 1 1 v R ghb T L T s i 0.7 cos cos B 2T tan 4tan sin tan gl (Lindqvist,1989)

8 Numerical modeling Local ice load Global ice load Ship s motion Interation

9 Numerical modeling F( t ) F( t ) F( t ) k1 k1, 0 k 1 F( tk1) F( tk1 ) 6 3, i1 x( tk 1) 2 M+A BC F( tk 1) M+Aak Bbk Solve equations of motion Update hull nodes t t No Detect the contact zones between ice and hull Update the forces F( t ) F( t ) k1 k1, i1 Acceptable? F( t ) F( t ) F( t ) k1, i1 k1, i k1, i Yes Update ice nodes Next time step

10 Numerical modeling Convergence test - Global ice load - Discretization size of ice nodes: 1600, 800, 400, 200, 100, 50, 25 mm - Time step length: 0.032, 0.016, 0.008, 0.004, 0.002, 0.001, s

11 Numerical modeling Computation time - A 30-min icebreaking run - Discretization size of ice nodes: 1600, 800, 400, 200, 100, 50, 25 mm - Time step length: 0.032, 0.016, 0.008, 0.004, 0.002, 0.001, s - Real-time simulation can be achieved by using a discretization size of 100 mm and a time step length of 0.01 s.

12 Numerical modeling Convergence test - Local ice load - Discretization size of ice nodes: 1600, 800, 400, 200, 100, 50, 25 mm - Time step length: 0.032, 0.016, 0.008, 0.004, 0.002, 0.001, s

13 Case studies MT Uikku MS Kemira S.A. Agulhas II Tor Viking II CIVArctic vessel Local ice load Global ice load and ship s performance

14 Local ice load Ice-induced frame load Icebreaking tanker, MT Uikku

15 Spatial distribution of local ice load 30 frames on different hull areas of MT Uikku are selected to investigate the spatial distribution of local ice loads in both straight going and turning operations: Peak value Mean value

16 Spatial distribution of local ice load Simulated peak loads with a non-exceedance probability of 99% (in a period of 30 minutes simulated in 0.34 m thick ice ) on different frames around the hull: This result suggests that it is possible that when a ship turns in ice, the aftshoulder area is equally or even more vulnerable to ice damage, as compared with the bow area. Similar results have been obtained by Izumiyama et al. (2005) and Valanto (2007) based on their experimental and numerical works.

17 Spatial distribution of local ice load Simulated mean loads (inaperiodof30minutessimulatedin0.34m thick ice ) on different frames around the hull: Aft Time average: 129 kn/m This result suggests that when a ship turns in ice, the aft shoulder area may encounter much heavier turning resistance as compared with the bow area. Bow Time average: 7.28 kn/m

18 Probabilistic distribution of local ice load Statistical variation of the ice: - Ice thickness - Crushing strength - Bending strength

19 Probabilistic distribution of local ice load Statistical variation of the ice: - Ice thickness - Crushing strength - Bending strength

20 Short-term distribution of local ice load A 10-min time history of simulated ice loads on frame in randomly varying ice conditions (average ice thickness: m, average ship speed: 5.43 m/s): Field measurements: (Kotisalo & Kujala, 1999)

21 Short-term distribution of local ice load Distribution of the load peaks: Data from Hänninen, 2003

22 Short-term distribution of local ice load Fitted probability distributions of the peak loads (in 12 hours) on frame by using the Weibull model: Suggested by Kujala et al., (2009), based on field measurements

23 Short-term distribution of local ice load Variation in the contact and icebreaking patterns:

24 Short-term distribution of local ice load Probabilistic distribution of the simulated peak loads (in 12 hours) on frame with varying or full contact:

25 Long-term distribution of local ice load Estimated long-term extremes based on the short-term distributions Chemical tanker MS Kemira The distribution of 12-hour load maxima measured on board MS Kemira and the estimated long-term extremes (Hänninen, 2003)

26 Long-term distribution of local ice load Distributions of simulated 10-min load maxima, w, in in the ice where the thickness, h i, is assumed to be normally distributed with a mean value, m h, and standard deviation, σ h. 12 hour Fitted Gumbel I asymptotic extreme value distribution: 1 F ( w hi) exp exp WH wu ci i

27 Long-term distribution of local ice load Correlation between the distribution of simulated load maxima and the ice thickness: F ( w hi) exp exp i exp exp WH wu wku,1 hi ku,2h i c i kch i F w w k h k h f h h hmax 1 2 W( ) exp exp u,1 i u,2 i H ( ) d i i i 0 kh c i

28 Summary Numerical modeling of ice hull interaction (based on emprical data) Spatial distribution of local ice loads around the hull (comparison) Short-term distribution of local ice load (comparison) Long-term distribution of local ice load (no comparison) Global ice load and ship s performance

29 References [1] Hänninen, S., Ship based observations on board MT Uikku during the winter Report for Deliverable D8 of IRIS Project, November [2] Izumiyama, K., Kitagawa, H., Koyama, K. and Uto, S., A numerical simulation of ice-cone interaction. Proceedings of 11 st International Symposium on Ice (IAHR), Banff, Alberta, Canada. [3] Izumiyama, K., Wako, D., Shimoda, H. and Uto, S., Ice load measurement on a model ship hull. Proceedings of 18 th International Conference on Port and Ocean Engineering under Arctic Conditions (POAC), New York, USA. [4] Kotisalo, K. and Kujala, P., Ice load measurements onboard MT Uikku during the ARCDEV voyage. Proceedings of 15th International Conference on Port and Ocean Engineering under Arctic Conditions (POAC), Espoo, Finland. [5] Kujala, P., Results of long-term measurements on board chemical tanker Kemira in the Baltic Sea during the winters 1985 to Research Report No. 47, Winter Navigation Research Board, Finland and Sweden, [6] Kujala, P., Suominen, M. and Riska, K., Statistics of ice loads measured on MT Uikku in the Baltic. Proceedings of 20 th International Conference on Port and Ocean Engineering under Arctic Conditions (POAC), Lulea, Sweden. [7] Lindqvist, G., A straightforward method for calculation of ice resistance of ships. Proceedings of 10 th International Conference on Port and Ocean Engineering under Arctic Conditions (POAC), Lulea, Sweden. [8] Liu, J.C., Lau, M. and Williams, F.M., Mathematical modeling of ice hull interaction for ship maneuvering in ice simulations. Proceedings of 7 th International Conference and Exhibition on Performance of Ships and Structures in Ice (ICETECH), Banff, Alberta, Canada. [9] Lubbad, R. and Løset, S., A numerical model for real-time simulation of ship-ice interaction. Cold Regions Science and Technology Vol. 65, pp [10] Martio, J., Numerical simulation of vessel s maneuvering performance in uniform ice. Report No. M-301, Ship Laboratory, Helsinki University of Technology, Finland.

30 References [11] Nguyen, D.T., Sørbø, A.H. and Sørensen, A.J., Modeling and control for dynamic positioned vessels in level ice. Proceedings of 8 th Conference on Manoeuvring and Control of Marine Craft, Guarujá, Brazil. [12] Riska, K., Design of ice breaking ships. Encyclopedia of Life Support Systems (EOLSS), Developed under the Auspices of the UNESCO, Eolss Publishers, Oxford, UK, [ [13] Sawamura, J., Tsuchiya, H., Tachibana, T. and Osawa, N., Numerical modeling for ship maneuvering in level ice. Proceedings of 20 th International Symposium on Ice (IAHR), Lahti, Finland. [14] Su, B., Riska, K. and Moan, T., A numerical method for the prediction of ship performance in level ice. Cold Regions Science and Technology, Vol. 60, pp [15] Su, B., Riska, K. and Moan, T., 2011a. Numerical simulation of local ice loads in uniform and randomly varying ice conditions. Cold Regions Science and Technology, Vol. 65, pp [16] Su, B., Riska, K. and Moan, T., 2011b. Numerical study of ice-induced loads on ship hulls. Marine Structures, Vol. 24, pp [17] Su, B., Riska, K. and Moan, T., 2011c. Numerical simulation of ships operating in level ice. Proceedings of 21 st International Conference on Port and Ocean Engineering under Arctic Conditions (POAC), Montreal, Canada. [18] Valanto, P., The resistance of ships in level ice. Transactions of Society of Naval Architects and Marine Engineers (SNAME), Vol. 109, pp [19] Valanto, P., Spatial distribution of numerically predicted ice loads on ship hulls in level ice. Report for Deliverable D6-3 of SAFEICE Project, May 2007.

31 Thank you for your attention!