Development of Closed Formula of Wave Load Based Upon Long-Term Prediction \u2013 Heave Acceleration and Pitch Angle

2021 ◽  
Author(s):  
Kyohei Shinomoto ◽  
Sadaoki Matsui ◽  
Kei Sugimoto ◽  
Shinsaku Ashida
Author(s):  
Kyohei Shinomoto ◽  
Sadaoki Matsui ◽  
Kei Sugimoto ◽  
Shinsaku Ashida

Abstract In order to ensure the structural safety of a ship, the most severe sea states she is expected to encounter throughout her service life need to be given consideration. This is the reason why the maximum loads corresponding to such sea states are typically specified in classification society structural rules such as the Common Structural Rules (CSR) of the International Association of Classification Societies (IACS). The maximum loads used for the structural design of a ship can have a significant impact on not only her structural safety, but also her hull construction cost; therefore, it is very important that the loads be accurately estimated. The linear term of the maximum loads typically specified in some classification society rules is equivalent to a long-term predicted value with an exceedance probability of 10−8. Since the maximum loads specified in classification society rules such as the CSR were developed specifically for specific ship types, their effective application to other ship types may be somewhat limited. Aim of our larger study is to develop a closed formula of long-term prediction for maximum loads. The formula has high accuracy and can be applied to any ship size and type. This paper focused on the heave acceleration and pitch angle, which are used for the calculation of internal loads and so on. A formula which takes into account such as the standard deviation of the hull response in irregular waves and the directional distribution of irregular waves was proposed. Main ship parameters such as ship length L, breadth B, draft d, block coefficient Cb, and water line area coefficient Cw were used for formulating the long-term prediction. The accuracy and effectiveness of the proposed formula were confirmed through various numerical calculations using a linear seakeeping analysis code developed by ClassNK. The calculation covers 154 ship models (77 existing ships × 2 loading conditions per ship).


2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Hiroshi Okamura ◽  
Yutaka Osada ◽  
Shota Nishijima ◽  
Shinto Eguchi

AbstractNonlinear phenomena are universal in ecology. However, their inference and prediction are generally difficult because of autocorrelation and outliers. A traditional least squares method for parameter estimation is capable of improving short-term prediction by estimating autocorrelation, whereas it has weakness to outliers and consequently worse long-term prediction. In contrast, a traditional robust regression approach, such as the least absolute deviations method, alleviates the influence of outliers and has potentially better long-term prediction, whereas it makes accurately estimating autocorrelation difficult and possibly leads to worse short-term prediction. We propose a new robust regression approach that estimates autocorrelation accurately and reduces the influence of outliers. We then compare the new method with the conventional least squares and least absolute deviations methods by using simulated data and real ecological data. Simulations and analysis of real data demonstrate that the new method generally has better long-term and short-term prediction ability for nonlinear estimation problems using spawner–recruitment data. The new method provides nearly unbiased autocorrelation even for highly contaminated simulated data with extreme outliers, whereas other methods fail to estimate autocorrelation accurately.


1985 ◽  
Vol 12 ◽  
pp. 176
Author(s):  
H Kurth ◽  
B Anders ◽  
G Lucas

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