Decrease of Ship Speed in Actual Seas of a Bulk Carrier in Full Load and Ballast Conditions

Ichinose, Yasuo; Tsujimoto, Masaru; Shiraishi, Kimio; Sogihara, Naoto

doi:10.2534/jjasnaoe.15.37

Cited by 5 publications

(4 citation statements)

References 6 publications

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“…The method has been validated by onboard measurements with the cooperation of the Ministry of Land, Infrastructure, Transport and Tourism, Japan, the Ministry of Environment, Japan and the relevant shipping and shipbuilding companies. The results of onboard measurements for the pure car carriers, the tanker, and the bulk carrier have been reported 2),3), 4) , and it has been confirmed that the calculated decrease of ship speed in actual seas by the method well agree with data by the onboard measurement.…”

Section: Introductionsupporting

confidence: 69%

Onboard Measurement for a Container Ship in view of Container Load Condition

2012

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SummaryFor the estimation of ship speed in actual seas, it is important to calculate external forces acted on a ship hull with accuracy. In National Maritime Research Institute, a calculation method for ship speed in actual seas on a constant engine output has been developed and validated by onboard measurements with the cooperation of the Ministry of Land, Infrastructure, Transport and Tourism, Japan, the Ministry of Environment, Japan and the relevant shipping and ship building companies. The results of onboard measurements for the pure car carriers, the tanker, and the bulk carrier have been reported.In this paper, the results of onboard measurements for the container ship of about 280 meter long are reported in terms of the verification of the calculation method of ship speed in actual seas. Moreover the influence of container load condition related to ship performance in actual seas is studied by the calculation and the onboard measurement.

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Section: Introductionsupporting

confidence: 69%

Onboard Measurement for a Container Ship in view of Container Load Condition

2012

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“…Since the draught or trim values change continuously due to the movement of the ship through the water, especially in rough weather, it can be difficult to obtain the exact operating conditions of the ship in a specific moment [28,29]. Therefore, when using such values for analysis, due consideration of the collection interval and quality of the data is critical.…”

Section: Data Smoothing Using a Median Filtermentioning

confidence: 99%

Development of a Fuel Consumption Prediction Model Based on Machine Learning Using Ship In-Service Data

Kim

Jung

Park

2021

JMSE

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As interest in eco-friendly ships increases, methods for status monitoring and forecasting using in-service data from ships are being developed. Models for predicting the energy efficiency of a ship in real time need to effectively process the operational data and be optimized for such an application. This paper presents models that can predict fuel consumption using in-service data collected from a 13,000 TEU class container ship, along with statistical and domain-knowledge methods to select the proper input variables for the models. These methods prevent overfitting and multicollinearity while providing practical applicability. To implement the prediction model, either an artificial neural network (ANN) or multiple linear regression (MLR) were applied, where the ANN-based models showed the best prediction accuracy for both variable selection methods. The goodness of fit of the models based on ANN ranged from 0.9709 to 0.9936. Furthermore, sensitivity analysis of the draught under normal operating conditions indicated an optimal draught of 14.79 m, which was very close to the design draught of the target ship, and provides the optimal fuel consumption efficiency. These models could provide valuable information for ship operators to support decision making to maintain efficient operating conditions.

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“…Kashiwagi and Ikeda 6 studied the effects of variation of draft on the added resistance of a modified Wigley hull in Waves. Ichinose et al 7,8 studied two bulk carriers at full load and ballast conditions and investigated the effect of trim on the added resistance. Valanto and Hong 3 carried out an experimental investigation on the added resistance of a cruise ship (of small draft) in waves of various headings.…”

Section: Introductionmentioning

confidence: 99%

Approximation of the added resistance of ships with small draft or in ballast condition by empirical formula

Liu

Papanikolaou

2017

Proceedings of the Institution of Mechanical Engineers, Part M:

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An attempt was made to extend and further tune the existing formula for approximating the added resistance in head seas to cover a wider range of speed and to account the impact of loading conditions; a new parameter based on B/T was introduced after conducting extensive parametric study to capture the influence of draft on the added resistance; the trim effect has also been investigated; Furthermore, the draft effect on the added resistance due to diffraction is further tuned and simplified. The derived formula uses only a few input, including only some ship dimensions to yield an estimation of the added resistance of ships in regular waves. Numerical results show that the added resistance of various ships in head seas at low speeds, as well as the added resistance of tankers in ballast condition and cruise ships, can be properly captured by the new formula. Hence, it meets the demand of fast examination of the minimum power; it can also be used in the early design stage of a ship for power estimation.

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Decrease of Ship Speed in Actual Seas of a Bulk Carrier in Full Load and Ballast Conditions

Cited by 5 publications

References 6 publications

Onboard Measurement for a Container Ship in view of Container Load Condition

Onboard Measurement for a Container Ship in view of Container Load Condition

Development of a Fuel Consumption Prediction Model Based on Machine Learning Using Ship In-Service Data

Approximation of the added resistance of ships with small draft or in ballast condition by empirical formula

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