Global load determination of high-speed wave-piercing catamarans using finite element method and linear least squares applied to sea trial strain measurements

Almallah, I; Lavroff, J; Holloway, DS; Shabani, B; Davis, W. Rhett

doi:10.1007/s00773-019-00688-3

Cited by 7 publications

(2 citation statements)

References 22 publications

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“…The Hull Response Monitoring System (HRMS) is a system that measures and displays ship structure stress, ship structure strain, and ship motion data. Many scholars have established a real-time prediction method for hull girder loads based on real-time strain monitoring data by utilizing the mechanical relationship between hull girder loads and structural strain [3][4][5][6][7][8]. Strain sensors on the hull structure may experience data drift and other issues during long-term use, which can lead to incorrect reporting of the hull girder loads.…”

Section: Introductionmentioning

confidence: 99%

Research on a Real-Time Prediction Method of Hull Girder Loads Based on Different Recurrent Neural Network Models

Wang,

Wu,

et al. 2024

JMSE

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Real-time prediction of hull girder loads is of great significance for the safety of ship structures. Some scholars have used neural network technology to investigate hull girder load real-time prediction methods based on motion monitoring data. With the development of deep learning technology, a variety of recurrent neural networks have been proposed; however, there is still a lack of systematic comparative analysis on the prediction performance of different networks. In addition, the real motion monitoring data inevitably contains noise, and the effect of data noise has not been fully considered in previous studies. In this paper, four different recurrent neural network models are comparatively investigated, and the effect of different levels of noise on the prediction accuracy of various load components is systematically analyzed. It is found that the GRU network is suitable for predicting the torsional moment and horizontal bending moment, and the LSTM network is suitable for predicting the vertical bending moment. Although filtering has been applied to the original noise data, the prediction accuracy still decreased as the noise level increased. The prediction accuracy of the vertical bending moment and horizontal bending moment is higher than that of the torsional moment.

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Section: Introductionmentioning

confidence: 99%

Research on a Real-Time Prediction Method of Hull Girder Loads Based on Different Recurrent Neural Network Models

Wang,

Wu,

et al. 2024

JMSE

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“…For example, Gahlinger 26 determined a motion sickness score based on the questionnaires collected from 260 cruises passengers. Almallah et al 27 studied wave response in the sea trial of the vessel HSV-2 Swift (Figure 1), but only to determine the motions and structural loads. In contrast, the present study aims to improve the understanding of vessel motion in random seas and their impact on motion sickness incidence (MSI), based on sea trials data.…”

Section: Introductionmentioning

confidence: 99%

Influence of an active T-foil on motions and passenger comfort of a wave-piercing catamaran based on sea trials in oblique seas

Lau

Ali-Lavroff

Holloway

et al. 2022

Proceedings of the Institution of Mechanical Engineers, Part M:

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In this paper the influence of a Ride-Control System (RCS) on the Response Amplitude Operator (RAO) of a full-scale high-speed catamaran was investigated using sea trials data. A T-foil and stern tabs were installed on a Wave-Piercing Catamaran (Incat Tasmania Hull 061) to improve ship motions and passenger comfort. More than 40 total effective hours of sea trials were conducted by the US Navy in 2004, encountering sea states 4–5 in the Atlantic Ocean near the United Kingdom. The reduction in Motion Sickness Incidence (MSI) was estimated in order to examine the effectiveness of the RCS in improving passenger comfort. By comparing the case of active RCS (T-foil plus stern tabs) with the case of active stern tabs only, it was found that the T-foil plays a vital role in the passenger comfort enhancement. Based on ISO recommended MSI calculation of a 2-h seaway, the percentage reduction in MSI was estimated, and hence the effectiveness of the T-foil deployment, along with the influence of speeds, headings, location on board and encountered wave height were analysed. A notable improvement in passenger comfort was observed in the real world bow quartering sea by deploying the RCS. An MSI reduction of 21% in high speeds (30–35 knots, [Formula: see text] 0.6) was observed, which was almost twice the MSI reduction (11%) in low speeds (15–20 knots, [Formula: see text] 0.3). However, in terms of MSI percentage reduction, the ability of T-foil in vessel motion control in oblique seas was found to be limited compared to the results in head seas.

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Real-time prediction of wave-induced hull girder loads for a large container ship based on the recurrent neural network model and error correction strategy

Wang,

Yu,

et al. 2024

International Journal of Naval Architecture and Ocean Engineeri

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Global load determination of high-speed wave-piercing catamarans using finite element method and linear least squares applied to sea trial strain measurements

Cited by 7 publications

References 22 publications

Research on a Real-Time Prediction Method of Hull Girder Loads Based on Different Recurrent Neural Network Models

Research on a Real-Time Prediction Method of Hull Girder Loads Based on Different Recurrent Neural Network Models

Influence of an active T-foil on motions and passenger comfort of a wave-piercing catamaran based on sea trials in oblique seas

Real-time prediction of wave-induced hull girder loads for a large container ship based on the recurrent neural network model and error correction strategy

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