Journal of the Society of Naval Architects of Korea (대한조선학회논문집)

The Society of Naval Architects of Korea (대한조선학회)
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Uncertainty Analysis for Speed and Power Performance in Sea Trial using Monte Carlo Simulation

몬테카를로 시뮬레이션을 이용한 시운전 선속-동력 성능에 대한 불확실성 해석

  • Received : 2018.08.08
  • Accepted : 2019.01.04
  • Published : 2019.06.20
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Abstract

The speed and power performance of a ship is not only a guarantee issue between the ship owner and the ship-yard, but also is related with the Energy Efficiency Design Index (EEDI) regulation. Recently, International Organization for Standardization (ISO) published the procedure of the measurement and assessment for ship speed and power at sea trial. The results of speed and power performance measured in actual sea condition must inevitably include various uncertainty factors. In this study, the influence for systematic error of shaft power measurement system was examined using the Monte Carlo simulation. It is found that the expanded uncertainty of speed and power performance is approximately ${\pm}1.2%$ at the 95% confidence level(k=2) and most of the uncertainty factor is attributed to shaft torque measurement system.

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References

  1. Brown, A. & Chen. 2002. Probabilistic method for predicting ship collision damage. Ocean Engineering International Journal, 6(1), pp.55-65.
  2. Coleman, H.W., & Steele, W.G., 2009. Experimentation, validation, and uncertainty analysis for engineers, 3rd Ed., John Wiley & Sons, Inc.
  3. Coraddu, A., Figari, M. & Savio S., 2014. Numerical investigation on ship energy efficiency by Monte Carlo simulation. Journal of Engineering for the Maritime Environment, 228(3), pp.220-234.
  4. Han, M.C., 1994. On the development of speed trial data measurement and processing system. Journal of the Society of Naval Architects of Korea, 31(2), pp.22-28.
  5. Han, B.W., Seo, J.H., Lee, S.,J., Seol, D.M. & Rhee, S.H., 2017. Uncertainty assessment for a towed underwater stereo PIV system by uniform flow measurement. International Journal of Naval Architecture and Ocean Engineering, 10(5), pp.596-608. https://doi.org/10.1016/j.ijnaoe.2017.11.005
  6. Kamal, I.M., Binns, J., Bose, N. & Thomas, G. 2013. Reliability assessment of ship powering performance extrapolations using Monte Carlo methods. Third International Symposium on Marine Propulsor, Tasmaia, Australia, May, 2013.
  7. Kim, H.J., 2011. Uncertainty analysis for a calibration process of fringe projection profilometry by using Monte Carlo method, Master's Thesis, Division of Mechanical Engineering, KAIST.
  8. Kim, J.H., Kim, J.J., Kim, S.M., Kim, J.K., Choi. S.H., Lee, D.H. & Kim, B.K., 2017, A study on full scale application of Samsungs air lubrication system(SAVER Air) for an LNG carrier. The Korean Association of Ocean Science and Technology Societies, Busan, Republic of Korea, 19-20 April 2017.
  9. ISO JCGM 100, 2008a. Evaluation of measurement data - Guide to the expression of uncertainty in measurement.
  10. ISO JCGM 101, 2008b. Evaluation of measurement data - Guide to the expression of uncertainty in measurement - Propagation of distributions using Monte Carlo method.
  11. ISO 15016, 2015. Ships and marine technology - Guidelines for the assessment of speed and power performance by analysis of speed trial data.
  12. ISO 19030, 2016. Ships and marine technology - Measurement of changes in hull and propeller performance.
  13. Insel, M., 2008. Uncertainty in the analysis of speed and powering trials. Ocean Engineering, 35, pp.1183-1193. https://doi.org/10.1016/j.oceaneng.2008.04.009
  14. International Towing Tank Conference (ITTC), 2002. Final report and recommendations to the 23rd ITTC - The Speicialist Committee on Speed and Powering Trials.
  15. International Towing Tank Conference (ITTC), 2005. Recommended procedures and guidelines - Testing and extrapolation methods loads and responses, seakeeping experiments (7.5-02-07-02.1).
  16. Park, D.W., Kim, M.G. & Kang, S.H., 2003. Uncertainty analysis for the resistance and self-propulsion test of ship model. Journal of the Society of Naval Architects of Korea, 40(5), pp.1-9. https://doi.org/10.3744/SNAK.2003.40.5.001
  17. Park, D.M., Kim, T.Y. & Kim, Y., 2012. Study on numerical sensitivity and uncertainty in the analysis of parametric roll. Journal of the Society of Naval Architects of Korea, 49(1), pp.60-67. https://doi.org/10.3744/SNAK.2012.49.1.60
  18. Park, D.M., Lee, J.H., & Kim, Y., 2015. Uncertainty analysis for added resistance experiment of KVLCC2 Ship, Ocean Engineering, 94, pp.143-156. https://doi.org/10.1016/j.oceaneng.2014.12.007
  19. Seo, S., Song, S. & Park, S., 2016. A study on CFD uncertainty analysis and its application to ship resistance performance using open source libraries. Journal of the Society of Naval Architects of Korea, 53(4), pp.329-335. https://doi.org/10.3744/SNAK.2016.53.4.329
  20. Song, M.H., 2008. A Study on the Shaft Power Measurement of Diesel Engine Using Strain Gauge in Marine Vessel, Maters' Thesis, Division of Marine Engineering System Graduate School, Mokpo National Maritime University
  21. Sun, L., Zhang, Q., Ma, G. & Zhang, T. 2017. Analysis of ship collision damage by combining Monte Carlo simulation and the artificial neural network approach. Journal Ships and Offshore Structures, 12, pp.S21-S30. https://doi.org/10.1080/17445302.2016.1258759