scholarly journals ISO 15016:2015-Based Method for Estimating the Fuel Oil Consumption of a Ship

2020 ◽  
Vol 8 (10) ◽  
pp. 791
Author(s):  
Ki-Su Kim ◽  
Myung-Il Roh
Keyword(s):  
Statistical Model ◽  
Route Planning ◽  
Fuel Oil ◽  
Accurate Estimation ◽  
Technology Planning ◽  
Optimal Route ◽  
Oil Consumption ◽  
Operating Data ◽  
Model Based ◽  
Calculation Methodology

Recently, interest in the design and construction of smart ships has been widely increasing. Optimal route planning is a widely studied essential aspect of smart ship technology. Planning an optimal route requires an accurate estimation of the fuel oil consumption of a ship. Various studies have suggested methods for theoretically estimating the fuel oil consumption. However, the calculation methodology and accuracy are different for each method. In addition, in commercial software, a statistical model based mainly on operating data has been used. Therefore, in this study, we propose a method based on ISO 15016:2015 for estimating the fuel oil consumption of a ship by improving the ISO 15016:2002 method—which has been predominantly used in existing studies. Moreover, the accuracy of the proposed method is examined by comparing it with a gray box model based on operating data. The results confirm that the proposed method can be used for estimating the fuel oil consumption of a ship.

scholarly journals On the Accuracy of the Sine Power Lomax Model for Data Fitting

Modelling ◽  
2021 ◽  
Vol 2 (1) ◽  
pp. 78-104
Author(s):  
Vasili B. V. Nagarjuna ◽  
R. Vishnu Vardhan ◽  
Christophe Chesneau
Keyword(s):  
Statistical Model ◽  
Simulation Study ◽  
Statistical Models ◽  
Goodness Of Fit ◽  
Data Fitting ◽  
Applied Science ◽  
Survival Distribution ◽  
Lomax Distribution ◽  
Model Based

Every day, new data must be analysed as well as possible in all areas of applied science, which requires the development of attractive statistical models, that is to say adapted to the context, easy to use and efficient. In this article, we innovate in this direction by proposing a new statistical model based on the functionalities of the sinusoidal transformation and power Lomax distribution. We thus introduce a new three-parameter survival distribution called sine power Lomax distribution. In a first approach, we present it theoretically and provide some of its significant properties. Then the practicality, utility and flexibility of the sine power Lomax model are demonstrated through a comprehensive simulation study, and the analysis of nine real datasets mainly from medicine and engineering. Based on relevant goodness of fit criteria, it is shown that the sine power Lomax model has a better fit to some of the existing Lomax-like distributions.

Diffusion-weighted imaging of prostate cancer using a statistical model based on the gamma distribution

2014 ◽  
Vol 42 (1) ◽  
pp. 56-62 ◽  
Author(s):  
Hiroshi Shinmoto ◽  
Koichi Oshio ◽  
Chiharu Tamura ◽  
Shigeyoshi Soga ◽  
Teppei Okamura ◽  
...  
Keyword(s):  
Prostate Cancer ◽  
Statistical Model ◽  
Gamma Distribution ◽  
Diffusion Weighted Imaging ◽  
Model Based ◽  
Diffusion Weighted

Evaluation of Ship Performance Using Operation Records

2018 ◽  
Author(s):  
Kenichi Fukuda ◽  
Yoshihisa Okada ◽  
Akinori Okazaki ◽  
Hiroyuki Adachi ◽  
Yuichiro Hisamuara ◽  
...  
Keyword(s):  
Big Data ◽  
Fuel Oil ◽  
Time Dependent ◽  
Oil Consumption ◽  
Sea Trial ◽  
Before And After ◽  
Report Data ◽  
Unique Approach ◽  
Performance Conditions ◽  
Ship Performance

Recently, the big data can be employed as the economical ship operating or evaluation of ship performance conditions. However, such data cannot be easily obtained and analyzed for every ship. In this case, for example, an evaluation of ship performance during operation is usually dependent on ship owner’s experience. The time-dependent ship performance is an essential topic for ship owners because if they realize their current ship performance, they can implement something such as hull or propeller cleaning for their economical operation. This study is focused on the usage of noon report data rather than the big data due to their obtainability. Usually, such data are considered as references because different ship operational condition and environmental condition obscure current ship performance. However, our unique approach, which is used integrally the noon report data such as BHP, propeller revolution and fuel oil consumption, ship sea trial data and propeller performance, can be evaluated ship performance during ship in service. The analyzed output data can be produced as increasing of ship resistance (delta Rw) versus ship performance efficiency, fuel oil consumption (ton per day) or sea margin. Under this output conditions, it can be comparable at same conditions even though the conditions of operations are different. Therefore, this analyzed data has a potential ability to have a look at ship performance conditions during ship in service. The purpose of this paper is to introduce our unique approach using noon data for time-dependent ship performance and then discuss the verification of this approach. As the case study, the noon report data for Japanese domestic bulker was chosen and the ship performance was evaluated in terms of different points of views. It was done comparing the conditions of before and after dry dock to evaluate our approach. In addition, the potential application of this approach will be discussed in this paper.

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