Short-time FORM analysis for extreme roll motion prediction in beam seas

2022 ◽  
Vol 82 ◽  
pp. 103160
Author(s):  
Tomoki Takami ◽  
Jørgen Juncher Jensen ◽  
Ulrik Dam Nielsen
Keyword(s):  
Motion Prediction ◽  
Roll Motion ◽  
Form Analysis ◽  
Beam Seas ◽  
Short Time ◽  
Time Form

scholarly journals Ship roll motion prediction based on ℓ1 regularized extreme learning machine

PLoS ONE ◽  
2018 ◽  
Vol 13 (10) ◽  
pp. e0206476 ◽  
Author(s):  
Binglei Guan ◽  
Wei Yang ◽  
Zhibin Wang ◽  
Yinggan Tang
Keyword(s):  
Extreme Learning Machine ◽  
Motion Prediction ◽  
Roll Motion ◽  
Ship Roll ◽  
Learning Machine ◽  
Ship Roll Motion

scholarly journals Studies of the Milky Way 1850–1930: some highlights

1985 ◽  
Vol 106 ◽  
pp. 43-58
Author(s):  
Robert W. Smith
Keyword(s):  
Milky Way ◽  
History Of Astronomy ◽  
Galactic System ◽  
Widespread Acceptance ◽  
The Galaxy ◽  
History Of ◽  
Entire History ◽  
Short Time ◽  
Time Form ◽  
Size And Structure

“The Copernicus of the sidereal system is not to be expected for many generations”. So wrote R.A. Proctor1 in his Essays in Astronomy in 1872. Indeed things did look bleak at this time for those who hoped for a good understanding of the size and structure of the Galaxy. Why was this so, and why was there to be such an astonishing transformation of this situation between 1918 and 1930? Certainly these twelve years saw the widespread acceptance of no less than six fundamentally new ways of viewing the Galactic System. These profound shifts, occurring in such a short time, form, I would suggest, one of the most exciting chapters in the entire history of astronomy. And in this paper I shall attempt to describe and analyze what these changes were, what led up to them, as well as to examine the events surrounding them.

scholarly journals Roll motion prediction using a hybrid deep learning and ARIMA model

2018 ◽  
Vol 144 ◽  
pp. 251-258 ◽  
Author(s):  
Novri Suhermi ◽  
Suhartono ◽  
Dedy Dwi Prastyo ◽  
Baharuddin Ali
Keyword(s):  
Deep Learning ◽  
Arima Model ◽  
Motion Prediction ◽  
Roll Motion

Long-Term Extreme Response of a Vessel Rolling in Random Seas

2016 ◽  
Author(s):  
Wei Chai ◽  
Arvid Naess ◽  
Bernt J. Leira
Keyword(s):  
Nonlinear Effects ◽  
Roll Motion ◽  
Response Analysis ◽  
Linear Filter ◽  
Beam Seas ◽  
Random Seas ◽  
Extreme Response ◽  
High Level ◽  
Nonlinear Roll Motion

In this paper, the long-term extreme response of a vessel rolling in random beam seas is addressed. The long-term response analysis is based on the upcrossing rates of the roll motion under different sea states. However, the nonlinear effects associated with the restoring and damping terms have a significant influence on the high-level response, assessing the corresponding statistics, such as the upcrossing rate, with low probability levels is difficult and time-consuming. In this work, the Markov theory is introduced in order to tackle this problem. Specifically, the random roll excitation moment is approximated as a filtered white noise process by applying a linear filter technique and an efficient four-dimensional (4D) path integration (PI) procedure is applied in order to calculate the response statistics. The long-term analysis of nonlinear roll motion in random seas that takes into considerations of the response statistics obtained by the 4D PI method as well as the variation of the sea states could be a valuable reference for ship stability research.

scholarly journals Prediction of Short-Time Cloud Motion Using a Deep-Learning Model

Atmosphere ◽  
2020 ◽  
Vol 11 (11) ◽  
pp. 1151
Author(s):  
Xinyue Su ◽  
Tiejian Li ◽  
Chenge An ◽  
Guangqian Wang
Keyword(s):  
Deep Learning ◽  
Learning Model ◽  
Block Matching ◽  
Solar Irradiation ◽  
Motion Prediction ◽  
Significant Information ◽  
Cloud Motion ◽  
Short Time ◽  
Gated Recurrent Unit ◽  
Deep Learning Model

A cloud image can provide significant information, such as precipitation and solar irradiation. Predicting short-time cloud motion from images is the primary means of making intra-hour irradiation forecasts for solar-energy production and is also important for precipitation forecasts. However, it is very challenging to predict cloud motion (especially nonlinear motion) accurately. Traditional methods of cloud-motion prediction are based on block matching and the linear extrapolation of cloud features; they largely ignore nonstationary processes, such as inversion and deformation, and the boundary conditions of the prediction region. In this paper, the prediction of cloud motion is regarded as a spatiotemporal sequence-forecasting problem, for which an end-to-end deep-learning model is established; both the input and output are spatiotemporal sequences. The model is based on gated recurrent unit (GRU)- recurrent convolutional network (RCN), a variant of the gated recurrent unit (GRU), which has convolutional structures to deal with spatiotemporal features. We further introduce surrounding context into the prediction task. We apply our proposed Multi-GRU-RCN model to FengYun-2G satellite infrared data and compare the results to those of the state-of-the-art method of cloud-motion prediction, the variational optical flow (VOF) method, and two well-known deep-learning models, namely, the convolutional long short-term memory (ConvLSTM) and GRU. The Multi-GRU-RCN model predicts intra-hour cloud motion better than the other methods, with the largest peak signal-to-noise ratio and structural similarity index. The results prove the applicability of the GRU-RCN method for solving the spatiotemporal data prediction problem and indicate the advantages of our model for further applications.

A Comparison of Time Domain Methods for Asymmetric Roll Predictions

2014 ◽  
Author(s):  
Robert Seah ◽  
Fabien Bigot ◽  
Nathan Tom ◽  
Dominique Roddier
Keyword(s):  
Time Domain ◽  
Hydrodynamic Model ◽  
The Other ◽  
Motion Prediction ◽  
Roll Motion ◽  
Analysis Tool ◽  
Dynamics Analysis ◽  
Prediction Tool ◽  
Environmental Condition ◽  
Asymmetric Configuration

Unlike ocean going vessels, FPSOs often have appendages, such as bilge keels or riser porches, at or below the waterline in an asymmetric configuration. In addition, the riser and mooring systems impose asymmetric loads on the hull. As a result, the expected roll motion response to a wave environment is asymmetric and traditional methodologies cannot be used to predict it. Morison drag elements can be incorporated to represent the asymmetric condition and are easily implemented in time domain simulations. The limitation to this engineering approach is that the drag coefficient can only be calibrated to produce accurate motions or accurate appendage loads but not both. In this paper we compare the response using two time domain approaches, the first being adapted from a commercial marine dynamics analysis tool [9] and the other being a specialized hydrodynamics motion prediction tool [4]. Here, the commercial tool utilizes constant coefficient drag elements in conjunction with traditional linear equivalent roll damping to model the effect of unequal port and starboard bilge keels as is typical when a riser balcony are present. In contrast, the newly developed hydrodynamic model relies solely on a Keulegan-Carpenter (KC) number dependent drag relation to represent the asymmetric drag contributions. The different calibration procedures will be discussed and a comparison for a design environmental condition between the two methodologies will be presented.

The Effect of a Dual Draft Hull on the Motion Behaviour of a Pipelay/Heavy-Lift Vessel

2008 ◽  
Author(s):  
J. L. F. van Kessel ◽  
W. J. van der Velde
Keyword(s):  
Wave Height ◽  
Model Tests ◽  
Response Amplitude ◽  
Roll Motion ◽  
Ship Motions ◽  
Beam Seas ◽  
Non Linear ◽  
Heavy Lift ◽  
Linear Damping

The motion behaviour of a Dual Draft vessel was calculated and experimentaly validated by means of model tests. Both the tests and computations showed that the roll behaviour of a Dual Draft vessel in pipelay / transit mode does not correspond to the usual observed response amplitude operator (RAO), where the roll RAO decreases with increasing wave height due to non-linear damping. When the wider top section of the Dual Draft vessel enters the water due to a roll motion, the buoyancy increases at that side and results in an increase of the excitation moment and roll RAO. Non-linear damping is of significant importance on the ship motions and is particulary noticeable in roll motions. This paper describes the effect of a Dual Draft hull on the motion behaviour of a pipelay / heavy-lift vessel in beam seas. The non-linear damping of a Dual Draft vessel will be discussed and calculations of the motion behaviour will be presented and compared with results of model tests.

Long-Term Extreme Response and Reliability of a Vessel Rolling in Random Beam Seas

2017 ◽  
Vol 140 (1) ◽  
Author(s):  
Wei Chai ◽  
Arvid Naess ◽  
Bernt J. Leira
Keyword(s):  
Nonlinear Effects ◽  
Reliability Evaluation ◽  
Roll Motion ◽  
Response Analysis ◽  
Linear Filter ◽  
Beam Seas ◽  
Random Seas ◽  
Extreme Response ◽  
Nonlinear Roll Motion

In this paper, the long-term extreme response of a vessel rolling in random beam seas and the associated reliability evaluation are addressed. The long-term response analysis is based on the upcrossing rates of the roll motion under different sea states. Generally, for nonlinear roll motion in random seas, the high-level roll response is sensitive and closely related to the nonlinear effects associated with the restoring and damping terms. Therefore, assessing the corresponding statistics of the random roll motion with low probability levels is difficult and time-consuming. In this work, the Markov theory is introduced in order to tackle this problem. Specifically, for the dead ship condition, the random roll excitation moment is approximated as a filtered white noise process by applying a second-order linear filter and an efficient four-dimensional (4D) path integration (PI) technique is applied in order to calculate the response statistics. Furthermore, the reliability evaluation is based on the well-known Poisson estimate as well as on the upcrossing rate calculated by the 4D PI method. The long-term analysis and reliability evaluation of the nonlinear roll motion in random seas, which consider the variation of the sea states could be a valuable reference for ship stability research.

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