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EN
This paper deals with the results of studying the effect of trim on the performance of series cargo ship 12500DWT in full scale at two operating conditions by using the RANSE method. The Body Force Propeller method is used to simulate a rotating propeller behind the ship. The numerical predicted results at the ballast condition were verified and validated with sea trial data. The ship’s engine power curves for different trim conditions at two operating conditions were carried out to produce a data source to evaluate the effect of trim on the performance of the 12500DWT cargo ship. The results indicate that if the ship operates under optimum trim conditions, this can decrease the ship’s engine power in a range from 2.5 to 4.5% depending on different loading conditions and ship speeds. Finally, the paper also provides detailed differences in flow around the ship due to trim variation to explain the physical phenomenon of changing ship performance.
EN
The paper presents the results of computational evaluation of the hull-propeller interaction coefficients, also referred to propulsive coefficients, based on the unsteady RANS flow model. To obtain the propulsive coefficients, the ship resistance, the open-water characteristics of the propeller, and the flow past the hull with working propeller were computed. For numerical evaluation of propeller open-water characteristics, the rotating reference frame approach was used, while for self-propulsion simulation, the rigid body motion method was applied. The rotating propeller was modelled with the sliding mesh technique. The dynamic sinkage and trim of the vessel were considered. The free surface effects were included by employing the volume of fluid method (VOF) for multi-phase flows. The self-propulsion point was obtained by performing two runs at constant speed with different revolutions. The well-known Japan Bulk Carrier (JBC) test cases were used to verify and validate the accuracy of the case studies. The solver used in the study was the commercial package Star-CCM+ from SIEMENS.
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