Research Papers: CFD and VIV

An Integrated Probability-Based Propulsor-Hull Matching Methodology

[+] Author and Article Information
Matthew R. Kramer

e-mail: mattkram@umich.edu

Michael R. Motley

e-mail: mmotley@umich.edu

Yin L. Young

Associate Professor
e-mail: ylyoung@umich.edu
Department of Naval Architecture and Marine Engineering,
University of Michigan,
Ann Arbor, MI 48109

1Corresponding author.

Contributed by the Ocean Offshore and Arctic Engineering Division of ASME for publication in the JOURNAL OF OFFSHORE MECHANICS AND ARCTIC ENGINEERING. Manuscript received December 30, 2010; final manuscript received January 31, 2012; published online February 22, 2013. Assoc. Editor: Thomas Fu.

J. Offshore Mech. Arct. Eng 135(1), 011801 (Feb 22, 2013) (8 pages) Paper No: OMAE-10-1122; doi: 10.1115/1.4007813 History: Received December 30, 2010; Revised January 31, 2012

Traditionally, designers of marine propulsors select a discrete number of critical design points for which to optimize the propulsor geometry. The design procedure carefully weighs the needs to be fuel efficient, to minimize cavitation, to maintain structural integrity, and to provide enough thrust to reach the desired speed, including the need to overcome any resistance humps. The current work proposes a new, alternative propulsor-hull matching methodology that is able to systematically consider the full range of expected operating conditions. A joint probability density function is used to represent the probabilistic operational space as a function of ship speed and sea state, and is used as a weighting function to select the propulsor that will minimize the annual fuel consumption while satisfying a set of constraints. The new probabilistic design approach is able to automatically locate the globally optimal solution by considering the probability of occurrence along with system performance characteristics. Hence, it is able to avoid the inherent ambiguity of selecting the proper design points. The proposed methodology is general to the design of marine propulsors for any type of vessel and engine system. It is applied in the current study for the sizing of waterjets for a surface effect ship.

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Fig. 1

Drawing of experimental setup with terminology defined (not to scale)

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Fig. 2

Model-scale test results for total resistance, trim, draft, and cushion pressure for one model configuration

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Fig. 3

Contours of assumed percentage increase in resistance due to speed and sea state variations

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Fig. 4

Estimated full-scale total resistance for various sea states

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Fig. 5

Velocity distribution representing different operational profiles

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Fig. 6

Sea state distribution

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Fig. 7

Probabilistic design space

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Fig. 8

Characteristic velocities of a waterjet propulsion system

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Fig. 9

Specific fuel consumption for General Electric LM2500 gas turbine (from [7])

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Fig. 10

Penalty function, α = 3, and β = 2.5

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Fig. 11

Results of optimization showing objective and constraint functions, and three different optimum solutions

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Fig. 12

Powering prediction for notional SES design with optimized waterjets




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