The Analysis of the Joint Limitation Condition of Wave Height-Period on the Floating Crane Lifting Operation

2019 ◽  
Author(s):  
Xue-gang Wang ◽  
Zong-quan Ying ◽  
Ze-cong Chen
Keyword(s):  
Wave Height ◽  
Time Window ◽  
Operation Condition ◽  
Full Account ◽  
Coupling System ◽  
Acceleration Amplitude ◽  
Wave Heights ◽  
Floating Crane ◽  
Sea Area ◽  
Joint Limitation

Abstract Considering the influence of wave period on the motion of ship, the hydrodynamic model of the floating crane-lifting objects coupling system is built. This model can calculate the motion response of floating crane and lifting object under wave conditions with different wave heights and periods. And it takes stability and sea-keeping of ship, personnel comfort as well as safety of equipment into full account. By comparing swing amplitude and acceleration amplitude of the floating crane and the lifting object, the limit working condition including both wave height and period for hoisting operation of the floating crane is determined. The method for limitation operation condition analysis of the floating crane not only offers calculating foundation for the construction operating adaptability of the engineering ship and the allowable working time window of the construction sea area, but also provides a new technical approach to the arrangement for the construction plan.

scholarly journals Estimation of Significant Wave Heights from ASCAT Scatterometer Data via Deep Learning Network

2021 ◽  
Vol 13 (2) ◽  
pp. 195
Author(s):  
He Wang ◽  
Jingsong Yang ◽  
Jianhua Zhu ◽  
Lin Ren ◽  
Yahao Liu ◽  
...  
Keyword(s):  
Deep Learning ◽  
Wave Height ◽  
Significant Wave Height ◽  
Incidence Angle ◽  
Ocean Waves ◽  
Global Scale ◽  
Learning Technology ◽  
Sea State ◽  
Significant Wave ◽  
Wave Heights

Sea state estimation from wide-swath and frequent-revisit scatterometers, which are providing ocean winds in the routine, is an attractive challenge. In this study, state-of-the-art deep learning technology is successfully adopted to develop an algorithm for deriving significant wave height from Advanced Scatterometer (ASCAT) aboard MetOp-A. By collocating three years (2016–2018) of ASCAT measurements and WaveWatch III sea state hindcasts at a global scale, huge amount data points (>8 million) were employed to train the multi-hidden-layer deep learning model, which has been established to map the inputs of thirteen sea state related ASCAT observables into the wave heights. The ASCAT significant wave height estimates were validated against hindcast dataset independent on training, showing good consistency in terms of root mean square error of 0.5 m under moderate sea condition (1.0–5.0 m). Additionally, reasonable agreement is also found between ASCAT derived wave heights and buoy observations from National Data Buoy Center for the proposed algorithm. Results are further discussed with respect to sea state maturity, radar incidence angle along with the limitations of the model. Our work demonstrates the capability of scatterometers for monitoring sea state, thus would advance the use of scatterometers, which were originally designed for winds, in studies of ocean waves.

scholarly journals Wave Height Distributions and Rogue Waves in the Eastern Mediterranean

2021 ◽  
Vol 9 (6) ◽  
pp. 660
Author(s):  
Sagi Knobler ◽  
Daniel Bar ◽  
Rotem Cohen ◽  
Dan Liberzon
Keyword(s):  
Wave Height ◽  
Eastern Mediterranean ◽  
Rogue Waves ◽  
Distribution Model ◽  
Storm Events ◽  
Order Model ◽  
Deep Seawater ◽  
Wave Heights ◽  
Storm Characteristics ◽  
Buoy Data

There is a lack of scientific knowledge about the physical sea characteristics of the eastern part of the Mediterranean Sea. The current work offers a comprehensive view of wave fields in southern Israel waters covering a period between January 2017 and June 2018. The analyzed data were collected by a meteorological buoy providing wind and waves parameters. As expected for this area, the strongest storm events occurred throughout October–April. In this paper, we analyze the buoy data following two main objectives—identifying the most appropriate statistical distribution model and examining wave data in search of rogue wave presence. The objectives were accomplished by comparing a number of models suitable for deep seawater waves. The Tayfun—Fedele 3rd order model showed the best agreement with the tail of the empirical wave heights distribution. Examination of different statistical thresholds for the identification of rogue waves resulted in the detection of 99 unique waves, all of relatively low height, except for one wave that reached 12.2 m in height which was detected during a powerful January 2018 storm. Characteristics of the detected rogue waves were examined, revealing the majority of them presenting crest to trough symmetry. This finding calls for a reevaluation of the crest amplitude being equal to or above 1.25 the significant wave height threshold which assumes rogue waves carry most of their energy in the crest.

Development of Operational Limit Diagrams for Offshore Lifting Procedures

2015 ◽  
Author(s):  
Leonardo Roncetti ◽  
Fabrício Nogueira Corrêa ◽  
Carl Horst Albrecht ◽  
Breno Pinheiro Jacob
Keyword(s):  
Wave Height ◽  
Significant Wave Height ◽  
Technological Development ◽  
Automatic Generation ◽  
Dynamic Responses ◽  
Offshore Platforms ◽  
Peak Period ◽  
Significant Wave ◽  
Wave Heights ◽  
Offshore Crane

Lifting operations with offshore cranes are fundamental for proper functioning of a platform. Despite the great technological development, offshore cranes load charts only consider the significant wave height as parameter of environmental load, neglecting wave period, which may lead to unsafe or overestimated lifting operations. This paper aims to develop a method to design offshore crane operational limit diagrams for lifting of personnel and usual loads, in function of significant wave height and wave peak period, using time domain dynamic analysis, for a crane installed on a floating unit. The lifting of personnel with crane to transfer between a floating unit and a support vessel is a very used option in offshore operations, and this is in many cases, the only alternative beyond the helicopter. Due to recent fatal accidents with lifting operations in offshore platforms, it is essential the study about this subject, contributing to the increase of safety. The sea states for analysis were chosen covering usual significant wave heights and peak periods limits for lifting operations. The methodology used the SITUA / Prosim software to obtain the dynamic responses of the personnel transfer basket lifting and container loads on a typical FPSO. Through program developed by the author, it was implemented the automatic generation of diagrams as a function of operational limits. It is concluded that using this methodology, it is possible to achieve greater efficiency in the design and execution of personnel and routine load lifting, increasing safety and a wider weather window available.

A Method to Implement the Random Signals for Time Varying Offshore Wave Height During Storm Condition in an Intra-Wave Period Wave Model

2006 ◽  
Author(s):  
Yuliang Zhu ◽  
Shunqi Pan ◽  
Premanandan T. Fernando ◽  
Xiaoyan Zhou
Keyword(s):  
Wave Height ◽  
Wave Model ◽  
Peak Frequency ◽  
Wave Period ◽  
Storm Event ◽  
Time Varying ◽  
Wave Heights ◽  
Offshore Wave ◽  
Storm Condition ◽  
Period Wave

In this paper, a method to implement the surface elevation at the offshore boundary during storm conditions is presented in the intra-wave period wave model. At storm condition, the offshore incident significant wave height is time varying. In the case of time varying incident wave height, the JONSWAP energy spectrum can be manipulated as follows: H1/32s(f). s(f) is the energy density function for a unit wave height. During a storm event not only the offshore boundary significant wave heights but also the peak frequency varies. If we choose a mean peak frequency during a storm event, s(f) can be calculated for the mean peak frequency for the storm event. The amplitudes of the component waves for the random signals are calculated from the unit energy density function s(f), and the phase angle of the component wave, So we can numerically generate surface elevation time series for the time varying offshore wave heights. The method was verified in the intra-wave period wave model using field measurements at Sea Palling site Norfolk UK.

scholarly journals ANALISA TITIK KRITIS GERAKAN ROLL KAPAL TRIMARAN UNTUK DIAPLIKASI PADA KAPAL IKAN PURSE SEINE

2021 ◽  
Vol 4 ◽  
pp. 44-50
Author(s):  
Fella Gaspersz ◽  
Richard B. Luhulima
Keyword(s):  
Critical Point ◽  
Wave Height ◽  
Inclination Angle ◽  
Weather Conditions ◽  
Extreme Weather ◽  
Roll Motion ◽  
Fishing Vessel ◽  
Fishing Vessels ◽  
Wave Heights ◽  
Wave Angle

The marine fisheries catching and processing industry are considered vulnerable to the effects of extreme weather at sea. Global warming effects and El Nino and La Nina have a significant impact on the upwelling process, which impacts the lifestyle and environment of marine biota, including pelagic fish, which is one of the most important contributors to the shipping industry. Extreme weather conditions, with wave heights ranging from 1 to 5 meters, dominate the waters of Maluku. In extreme sea conditions, most fishers choose not to go fishing, not because there are no fish at the fishing grounds, but to avoid mishaps at sea. This research aimed to analyze the critical point of ship roll motion and ship stability. The hull shape employed in this study was a monohull fishing vessel and a trimaran fishing vessel with the same displacement of 21,1 tons. In extreme weather conditions, the Maxsurf software was used to analyze the ship's response, especially the critical point of the ship's roll motion. The I.M.O. Standard was utilized to calculate the ship's stability. The operational speed of the ship was v = 3 knots, with fluctuations in wave angle of incidence between 00 - 1800. Wave heights of 1,0; 2,0; 3,0, and 0,4 meters represent extreme weather conditions in Maluku waters' fishing grounds. The findings revealed that the trimaran hull type had better stability where the inclination angle of trimaran vessel stability was 480 while the monohull was 410. The trimaran fishing vessel was able to withstand a wave height of 3 meters with an inclination angle of 32,560. In comparison, the monohull fishing vessel was able to survive at a wave height of 2 meters with an inclination angle of 24,690. Monohull fishing vessel had a maximum limit of roll motion at wave directions 82 and 99 with a wave height of 3 m, and it reached at the critical point at angles of 43 and 138, at the height of 4 m. Meanwhile, the trimaran fishing vessel had a critical point at a wave angle of 760 and 1000 with a wave height of 4 meters. In the area between those two angles, monohull and trimaran fishing vessels will lose the balance (stability) of the roll motion, resulting in capsize.

scholarly journals MACH-REFLECTION AS A DIFFRACTION PROBLEM

1976 ◽  
Vol 1 (15) ◽  
pp. 45 ◽  
Author(s):  
Udo Berger ◽  
Soren Kohlhase
Keyword(s):  
Wave Height ◽  
Incident Wave ◽  
Water Waves ◽  
Gas Dynamics ◽  
Mach Reflection ◽  
Diffraction Problem ◽  
Vertical Wall ◽  
Oblique Wave ◽  
Wave Heights ◽  
The Waves

As under oblique wave approach water waves are reflected by a vertical wall, a wave branching effect (stem) develops normal to the reflecting wall. The waves progressing along the wall will steep up. The wave heights increase up to more than twice the incident wave height. The £jtudy has pointed out that this effect, which is usually called MACH-REFLECTION, is not to be taken as an analogy to gas dynamics, but should be interpreted as a diffraction problem.

scholarly journals Probabilistic Tsunami Hazard Analysis For Tuzla Test Site Using Monte Carlo Simulations

2019 ◽  
Author(s):  
H. Basak Bayraktar ◽  
Ceren Ozer Sozdinler
Keyword(s):  
Monte Carlo ◽  
Wave Height ◽  
Tsunami Wave ◽  
Hazard Analysis ◽  
Test Site ◽  
Tsunami Hazard ◽  
Earthquake Catalogue ◽  
M Wave ◽  
Wave Heights ◽  
Probabilistic Tsunami Hazard Analysis

Abstract. In this study, time-dependent probabilistic tsunami hazard analysis (PTHA) is performed for Tuzla, Istanbul in the Sea of Marmara, Turkey, using various earthquake scenarios of Prince Island Fault within next 50 and 100 years. Monte Carlo (MC) simulation technique is used to generate a synthetic earthquake catalogue which includes earthquakes having magnitudes between Mw 6.5 and 7.1. This interval defines the minimum and maximum magnitudes for the fault in the case of entire fault rupture which depends on the characteristic fault model. Based on this catalogue, probability of occurrence and associated tsunami wave heights are calculated for each event. The study associates the probabilistic approach with tsunami numerical modelling. Tsunami numerical code NAMI DANCE was used for tsunami simulations. According to the results of the analysis, distribution of probability of occurrence corresponding to tsunami hydrodynamic parameters are represented. Maximum positive and negative wave amplitudes show that tsunami wave heights up to 1 m have 65 % probability of exceedance for next 50 years and this value increases by 85 % in Tuzla region for next 100 years. Inundation depth also exceeds 1 m in the region with probabilities of occurrence of 60 % and 80 % for next 50 and 100 years, respectively. Moreover, Probabilistic inundations maps are generated to investigate inundated zones and the amount of water penetrated inland. Probability of exceedance of 0.3 m wave height, ranges between 10 % and 75 % according to these probabilistic inundation maps and the maximum inundation distance calculated among entire earthquake catalogue is 60 m in this test site. Furthermore, at synthetic gauge points which are selected along the western coast of the Istanbul by including Tuzla coasts. Tuzla is one of the area that shows high probability exceedance of 0.3 m wave height, which is around 90 %, for the next 50 years while this probability reaches up to more than 95 % for the next 100 years.

Extrapolation of Historical Storm Data for Estimating Design-Wave Heights

1971 ◽  
Vol 11 (01) ◽  
pp. 23-37 ◽  
Author(s):  
C. Petrauskas ◽  
P.M. Aagaard
Keyword(s):  
Wave Height ◽  
Distribution Functions ◽  
Extreme Value Statistics ◽  
Return Periods ◽  
Improved Method ◽  
Design Wave Height ◽  
Straight Line ◽  
Wave Heights ◽  
Computerized Procedures ◽  
Selection Of

Abstract An improved method is presented for selecting offshore structure design waves by extrapolating historical storm data to obtain extreme value statistics. The method permits flexibility in choice of distribution functions through use of computerized procedures, estimates extrapolated wave-height procedures, estimates extrapolated wave-height uncertainty due to small sample size, and includes criteria for judging whether or not given wave-height values can be represented by one or more of the distributions implemented in the method. The relevance of uncertainty to selection of design-wave heights is discussed and illustrated. Introduction The problem of selecting design-wave heights for offshore platforms has many facets, ranging from the development of oceanographic data to the selection of the prudent level of engineering risk for a particular installation. This paper deals only with part of the problem; it describes an improved method for using the small available amount of wave-height information to estimate the extreme value statistics and associated uncertainties for the large storm waves that have a very low probability of occurrence. probability of occurrence. Hindcast wave-height information for design-wave studies usually covers a period of historical record that is shorter than the return period selected for acceptable engineering risk. Return periods commonly used for selection design waves are 100 years or more, but good meteorological data, on Which the calculated wave heights are based, can rarely be obtained for periods covering more than 50 to 60 years. As a consequence, extrapolations to longer return periods are necessary. Present methods for making the extrapolation employ probablistic models through the use of special probability graph papers on which a family of distribution functions plot as straight lines. The wave heights are plotted vs their "plotting-position" return period, and a straight line fitted to the plotted data is extended beyond the data to estimate extreme wave heights for return periods of interest. The methods are described in periods of interest. The methods are described in numerous technical papers and books; Refs. 1 through 5 are examples. The shortcomings of the present commonly used methods are:the straight line drawn through the data is in most cases visually fit to the data, thus is subject to error; andno information is available on the uncertainty of the resulting extrapolation. These shortcomings have been discussed by many authors and many of their concepts influenced this study. The improved method presented in this paper offers:greater flexibility in the choice of distributions through computerized procedures,guidelines for picking the "best" distribution from several implemented in the method, andprocedures for estimating the uncertainty of procedures for estimating the uncertainty of extrapolated wave heights. CONDENSED CONCLUSIONS Procedures described in this paper for extrapolating hindcast storm-wave heights and estimating uncertainty intervals to the extrapolated values are recommended as aids in selecting the design-wave height. The results of the extrapolating procedure and related uncertainty considerations procedure and related uncertainty considerations are only aids to help the engineer assess the risks associated with his design. The actual selection of the design-wave height is a matter of engineering judgment. The choice is subjective and will vary according to the risk chosen for the design. Further consideration of ways to decrease the span of be uncertainty intervals is warranted. Increasing the number of years represented in the sample along with the number of storms is a direct way to decrease the span. In the areas of the world having poor weather records the sample size will be marginal for many years to come. SPEJ P. 23

Neural Networks Based Simulation of Significant Wave Height

2007 ◽  
Author(s):  
H. Bazargan ◽  
H. Bahai ◽  
A. Aminzadeh-Gohari ◽  
A. Bazargan
Keyword(s):  
Neural Networks ◽  
Wave Height ◽  
Significant Wave Height ◽  
Optimization Technique ◽  
Conditional Probability Density ◽  
Significant Wave ◽  
The Pacific ◽  
Wave Heights ◽  
Significant Wave Heights ◽  
Long Term Forecasting

A large number of ocean activities call for real time or on-line forecasting of wind wave characteristics including significant wave height (Hs). The work reported in this paper uses statistics, and artificial neural networks trained with an optimization technique called simulated annealing to estimate the parameters of a probability distribution called hepta-parameter spline for the conditional probability density functions (pdf’s) of significant wave heights given their eight immediate preceding 3-hourly observed Hs’s. These pdf’s are used in the simulation of significant wave heights related to a location in the Pacific. The paper also deals with short and long term forecasting of Hs for the region through generating random variates from the spline distribution.

scholarly journals Wave climate in the Arkona Basin, the Baltic Sea

Ocean Science ◽  
2012 ◽  
Vol 8 (2) ◽  
pp. 287-300 ◽  
Author(s):  
T. Soomere ◽  
R. Weisse ◽  
A. Behrens
Keyword(s):  
Baltic Sea ◽  
Wave Height ◽  
Wave Model ◽  
Wave Climate ◽  
Wind Fields ◽  
The Baltic Sea ◽  
Wave Heights ◽  
The Baltic ◽  
Basic Features

Abstract. The basic features of the wave climate in the Southwestern Baltic Sea (such as the average and typical wave conditions, frequency of occurrence of different wave parameters, variations in wave heights from weekly to decadal scales) are established based on waverider measurements at the Darss Sill in 1991–2010. The measured climate is compared with two numerical simulations with the WAM wave model driven by downscaled reanalysis of wind fields for 1958–2002 and by adjusted geostrophic winds for 1970–2007. The wave climate in this region is typical for semi-enclosed basins of the Baltic Sea. The maximum wave heights are about half of those in the Baltic Proper. The maximum recorded significant wave height HS =4.46 m occurred on 3 November 1995. The wave height exhibits no long-term trend but reveals modest interannual (about 12 % of the long-term mean of 0.76 m) and substantial seasonal variation. The wave periods are mostly concentrated in a narrow range of 2.6–4 s. Their distribution is almost constant over decades. The role of remote swell is very small.

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