Journal of Marine Science and Technology

Journal of Marine Science and Technology

Power estimation of container carriers at early stage of design by multiple linear regression method

Document Type : Original Manuscript

Authors
Mohsen Shojaie
Mostafa Jafarzadeh Khatibani
Etemad ODin Rabei Gholami
Department of Naval Architecture - Faculty of Marine Engineering - Khorramshahr University of Marine Science and Technology, Khorramshahr, Iran.
10.22113/jmst.2020.199000.2306
Abstract
Estimating the required propulsive power of a vessel at early stage of design is important from two aspects, which are estimating the weight of the machinery as a function of required power and estimating the amount of fuel needed to determine the initial capacity of the vessel. This approximation can be based on empirical formulas, data of similar ships or diagrams deduced from statistical data for various types and sizes of ships. Current empirical formulas for estimating ship power are only limited to very few general equations and are inaccurate for specific type of vessels. In this study, by using 90 container ship data and multiple linear regression method, several statistical models were prepared and statistically analyzed considering the influence of the main parameters of the vessels on the required amount of power, and finally a suitable formula extracted. Evaluation of the extracted formula indicates acceptable accuracy for the container ships which can be used to estimate the required power of container ships within the range of this formula.
Keywords
Multiple linear regression
Early stage of design
Power prediction
Container carrier

Subjects

Boulougouris, E.K, Papanikolaou, A.D. and Pavlou, 2011. A. Energy efficiency parametric design tool in the framework of holistic ship design optimization. Proceedings of the Institution of Mechanical Engineers, Part M. Journal of Engineering for the Maritime Environment.;225(3), pp.242-260. DOI: 10.1 177/1475090211409997.
Cassella, P. and Krauss, G.R., 1983. Hydrostatic data for cargo ships obtained with regression analysis. Ocean Engineering, 10(3), pp.145-155. DOI: 10.1016/0029-8018(83)90023-9.
Ghasemi, H. and Jafarzadeh Khatibani, M., 2004, determining the stability of commercial ships in the initial stage of design using regression analysis, the 12th annual conference and the 8th international conference on mechanical engineering - Tarbiat Modares University (in Persian).
Heichel, S., Pape, J. and Tosun, J., 2014. Regulation of industrial discharges into surface water. Understanding Environmental Policy Convergence: The Power of Words, Rules and Money, p.64.
Papanikolaou, A., 2014. Ship design: methodologies of preliminary design. Springer. DOI: 10.1007/978-94-017-8751-2.
Papanikolaou, A.D., 2002. Developments and potential of advanced marine vehicles concepts. Bulletin of the KANSAI Society of Naval Architects, Japan, 55, pp.50-54. DOI: doi.org/10.14856/ran.55.0_50.
Rencher, A.C. and Schaalje, G.B., 2008. Linear models in statistics. John Wiley & Sons.
Schneekluth, H. and Bertram, V., 1998. Ship Design for Efficiency and Economy. Butterworth-Heinemann. DOI: 10.1016/B9 78-0-7506-4133-3.X5000-2.
Veritas, B., 2017. Available at: World Wide Web, https://www.veristar.com/portal/veristarinfo/generalinfo/registers/seaGoingShips.
Yilmaz, H. and Giiner, M., 2001. An approximate method for cross curves of cargo vessels. Marine technology and SNAME news, 38(02), pp.92-94. DOI: 10.5957/mt1.2001.38.2.92.
Journal of Marine Science and Technology
Volume 22, Issue 4
Autumn 2023
Pages 1-12

  • Receive Date 23 August 2019
  • Revise Date 02 January 2020
  • Accept Date 11 January 2020
  • Publish Date 22 November 2023