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Statistical Reliability Analysis of Numerical Simulation for Prediction of Model-Ship Resistance

선체 저항에 대한 수치 해석의 통계적 신뢰도 분석

  • Lee, Sang Bong (Maritime Research Institute, Hyundai Heavy Industries Co. Ltd.) ;
  • Lee, Youn Mo (Maritime Research Institute, Hyundai Heavy Industries Co. Ltd.)
  • Received : 2013.12.20
  • Accepted : 2014.05.26
  • Published : 2014.08.20

Abstract

A wide scope of numerical simulations was performed to predict model-ship resistances by using STAR-CCM+ and OpenFOAM. The numerical results were compared with experimental measurements in towing tank to analyze statistical reliability of the present simulations. Based on the normal distribution of resistance errors in 113 cases of container carriers, tankers and very large crude-oil carriers, the confidence intervals of numerical error were estimated as [-2.64%,+2.32%] and [-1.82%, +1.87%] with 95% confidence in STAR-CCM+ and OpenFOAM, respectively. The resistance errors of liquefied natural gas carriers with single- and twin-skeg were confident in the ranges of [-2.51%,+2.64%] and [-2.29%, +1.46%], respectively. The grid uncertainty of resistance coefficients for KCS was also quantitatively analyzed by using a grid verification procedure. The grid uncertainty of OpenFOAM (5.1%) was larger than 4.4% uncertainty of STAR-CCM+ although OpenFOAM provided statistically more confident results than those of STAR-CCM+. It means that a grid system verified under a specific condition does not automatically lead to statistical reliability in general cases.

Keywords

References

  1. Choi, J.E. Kim, J.H. Lee, S.B. & Lee, H.G., 2009. Computational Prediction of Speed Performance for a Ship with Vortex Generator. Journal of the Society of Naval Architect of Korea, 46(2), pp.136-147. https://doi.org/10.3744/SNAK.2009.46.2.136
  2. Lee, S.B., 2013. Application of OpenFOAM to prediction of hull resistance. 8th International OpenFOAM Workshop, Jeju, Korea, 11-14 June 2013.
  3. Lee, S.B. Han, B.W. Park, D.W. Ahn Y.W. Go, S.C. & Seo, H.W., 2012. Proper Orthogonal Decomposition of Pressure Fluctuations in Moonpool. Journal of the Society of Naval Architect of Korea, 49(6), pp.484-490. https://doi.org/10.3744/SNAK.2012.49.6.484
  4. Park, S. Park, S.W. Rhee, S.H. Lee, S.B. Choi, J.-E. & Kang, S.H., 2013. Investigation on the Wall Function Implementation for the Prediction of Ship Resistance. International Journal of Naval Architecture and Ocean Engineering, 5, pp.33-46. https://doi.org/10.3744/JNAOE.2013.5.1.033
  5. Roache, P., 2003. Errors bars for CFD. AIAA 2003-408 41st Aerospace Scuebces Meeting, Reno, Nevada, 6-9 January 2003.
  6. Stern, F. Wilson, R.V. Coleman, H.W. & Paterson E.G., 2001. Comprehensive Approach to Verification and Validation of CFD Simulations-Part 1: Methodology and Procedures. Journal of Fluids Engineering, 123, pp.793-802. https://doi.org/10.1115/1.1412235
  7. Stern, F. Wilson, R.V. & Shao J., 2006. Quantitative V&V of CFD Simulations and Certification of CFD codes. International Journal for Numerical Methods in Fluids, 50, pp.1335-1355. https://doi.org/10.1002/fld.1090
  8. Wilson, R.V. Stern, F. Coleman, H.W. & Paterson E.G., 2001. Comprehensive Approach to Verification and Validation of CFD Simulations-Part 2: Application for Rans Simulation of a Cargo/Container Ship. Journal of Fluids Engineering, 123, pp.803-810. https://doi.org/10.1115/1.1412236
  9. Xing, T. & Stern F., 2008. Factors of Safety for Richardson Extrapolation for Industrial Applications. IIHR Technical Report No. 466. Iwowa: The university of Iwowa

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