Offshore Monitoring of Snorre A TLP TTR Jumpers

2015 ◽  
Author(s):  
Phelim Rooney ◽  
Christoffer Nilsen-Aas ◽  
Haavard Skjerve ◽  
Kristin Nedrelid ◽  
Nils Gunnar Viko
Keyword(s):  
Data Base ◽  
Significant Wave Height ◽  
Environmental Data ◽  
Life Extension ◽  
Data Sets ◽  
Analysis Model ◽  
Peak Period ◽  
Wave Measurement ◽  
Motion Responses ◽  
Flexible Jumper

Four sensors were installed on the Snorre A TLP (Tension Leg Platform) on 16th April 2014 and retrieved on 10th May 2014, to document motions of the vessel, top tensioned riser (TTR) and flexible jumper connecting the TTR (Top Tensioned Riser) with the topside piping. The data recorded represents 3828 data sets. Associated significant wave height and peak period is synchronous data extracted from the Miros wave measurement radar and stored in the environmental data base. The SmartMotion riser sensors are certified for service in the Wellbay. The sensors are modelled into the OrcaFlex (1) “calibration” analysis model in order to simulate the motion responses in the same format as recorded offshore (accelerations and rates of rotation), and to carry out verification of the OrcaFlex model by comparing both raw data and filtered/integrated derivatives. This work provides a basis for life extension of the Jumpers and provides valuable feedback to design and analysis of TLP and Spar Jumpers between TTRs and topside Headers.

A Joint Probability Model for Environmental Parameters

2011 ◽  
Vol 133 (3) ◽  
Author(s):  
Luís Volnei Sudati Sagrilo ◽  
Edison Castro Prates de Lima ◽  
Arnaldo Papaleo
Keyword(s):  
Wave Height ◽  
Significant Wave Height ◽  
Environmental Parameters ◽  
Offshore Structures ◽  
Environmental Data ◽  
Statistical Dependence ◽  
Response Analysis ◽  
Peak Period ◽  
Significant Wave ◽  
Nataf Transformation

Joint probabilistic models (JPMs) for the environmental parameters such as wave, wind, and current are nowadays of paramount importance in order to perform the reliability analysis of marine structures. These JPMs are also essential for long-term statistics-based design of offshore structures and to perform dynamic response analysis of floating units that are strongly dependent on the directionality of the environmental actions such as turret-moored floating, production, storage, and offloading vessels (FPSOs). Recently, some JPMs have been proposed in literature to represent the joint statistics of a reduced number of environmental parameters. However, it is a difficult task to obtain practical and reliable models to express the complete statistical dependence among the environmental parameters intensities and their correspondent directions. This paper presents a methodology, based on the Nataf transformation, to create a JPM of wave, wind, and current environmental parameters taking into account, also, the statistical correlation between intensities and directions. The proposed model considers ten short-term environmental variables: the significant wave height, peak period, and direction of the sea waves, the significant wave height, peak period, and direction of the swell waves, the amplitude and direction of the 1 h wind velocity, and, finally, the amplitude and direction of the surface current velocity. The statistical dependence between them is modeled using concepts of linear-linear, linear-circular, and circular-circular variables correlation. Some results of the proposed JPM methodology are presented based on simultaneous environmental data gathered in an offshore Brazil location.

A Joint Probability Model for Environmental Parameters

2008 ◽  
Author(s):  
Lui´s Volnei Sudati Sagrilo ◽  
Edison Castro Prates de Lima ◽  
Arnaldo Papaleo
Keyword(s):  
Wave Height ◽  
Significant Wave Height ◽  
Environmental Parameters ◽  
Offshore Structures ◽  
Environmental Data ◽  
Statistical Dependence ◽  
Response Analysis ◽  
Peak Period ◽  
Significant Wave ◽  
Nataf Transformation

The joint probabilistic models (JPM) of the environmental parameters of wave, wind and current are nowadays extremely needed in order to perform reliability analyses of offshore structures. These JPM are also essential steps for the design of offshore structures based on long-term statistics and to perform dynamic response analysis of floating units that are strongly dependent on the directionality of the environmental actions, such as turret-moored FPSOs. Recently, some JPM have been proposed in the literature to represent the joint statistics of a reduced number of environmental parameters. However, it is difficult to find a practical and fully operational model taking into account the complete statistical dependence among all the environmental parameters intensities and their correspondent directions. In this paper, it is presented a straightforward methodology, based on the Nataf transformation, to create a JPM of the environmental parameters taking into account the dependence between the intensity and direction of all variables. The proposed model considers the statistical dependence of ten short-term variables: the significant wave height, peak period and direction of the sea waves, the significant wave height, peak period and direction of the swell waves, the amplitude and direction of the 1-h wind velocity and, finally, the amplitude and direction of the surface current velocity. The statistical dependence between them is evaluated using concepts of linear-linear, linear-circular and circular-circular variables correlation. Some results of the proposed JPM methodology are presented based on simultaneous environmental data gathered in a location offshore Brazil.

scholarly journals Data base and erosion risk map creation at Trichonida lake using fuzzy sets and G.I.S.

2001 ◽  
Vol 34 (1) ◽  
pp. 443
Author(s):  
Β. ΣΑΜΠΩ ◽  
Θ. ΓΚΟΥΡΝΕΛΟΣ ◽  
Ν. ΕΥΕΛΠΙΔΟΥ ◽  
Α. ΒΑΣΙΛΟΠΟΥΛΟΣ
Keyword(s):  
Data Base ◽  
Drainage Basin ◽  
Environmental Data ◽  
Primary Data ◽  
Data Sets ◽  
Risk Map ◽  
Thematic Maps ◽  
Thematic Map ◽  
Erosion Risk ◽  
Input Variables

Trichonida lake has an area of 96,17Km2 and is situated at Etoloakarnania prefecture. In this study a data base has been developed, on geological, geomorphological and environmental data, concerning the wider zone around Trichonida lake. Different thematic maps have been created, using as input variables, the GIS database fields and the statistical analysis output from the MathLab software. Using MathLab software, the primary data has been transformed into fuzzy data sets and for each drainage basin an erodibility value was calculated. The final thematic map, present the erodibility values of each drainage basin. Such geographical GIS databases may be used in local or regional level for the study of erodibility problems, the development of thematic maps and moreover to decision support systems.

PWA OF πN SCATTERING WITH FIXED-t DISPERSION RELATIONS

2005 ◽  
Vol 20 (08n09) ◽  
pp. 1810-1813
Author(s):  
PEKKO PIIROLA ◽  
M. E. SAINIO
Keyword(s):  
Data Base ◽  
Forward Direction ◽  
Dispersion Relations ◽  
Data Sets ◽  
Coupling Constant ◽  
Partial Waves ◽  
Scattering Measurements ◽  
Pion Nucleon ◽  
Good Agreement

The πN scattering measurements from last couple of decades are not in very good agreement with each other. In fact, using the different data sets one finds different values for the pion-nucleon coupling constant. An analysis with theoretical constraints is the only way to produce accurate partial waves. In this analysis, the fixed-t dispersion relations are used to ensure analyticity in the invariant amplitudes and to decrease the effects of inaccuracies in the data base. Pietarinen's expansion is the method used to enforce the dispersion constraints. The strength of the analyticity constraints is illustrated with C± amplitudes in the forward direction.

Semi-Empirical Crest Distributions of Long-Crest Nonlinear Waves of Three-Hour Duration

2017 ◽  
Author(s):  
Zhenjia (Jerry) Huang ◽  
Qiuchen Guo
Keyword(s):  
Nonlinear Wave ◽  
Wave Height ◽  
Model Test ◽  
Significant Wave Height ◽  
Spectral Peak ◽  
Wave Crest ◽  
Empirical Formulas ◽  
Peak Period ◽  
Significant Wave ◽  
Semi Empirical

In wave basin model test of an offshore structure, waves that represent the given sea states have to be generated, qualified and accepted for the model test. For seakeeping and stationkeeping model tests, we normally accept waves in wave calibration tests if the significant wave height, spectral peak period and spectrum match the specified target values. However, for model tests where the responses depend highly on the local wave motions (wave elevation and kinematics) such as wave impact, green water impact on deck and air gap tests, additional qualification checks may be required. For instance, we may need to check wave crest probability distributions to avoid unrealistic wave crest in the test. To date, acceptance criteria of wave crest distribution calibration tests of large and steep waves of three-hour duration (full scale) have not been established. The purpose of the work presented in the paper is to provide a semi-empirical nonlinear wave crest distribution of three-hour duration for practical use, i.e. as an acceptance criterion for wave calibration tests. The semi-empirical formulas proposed in this paper were developed through regression analysis of a large number of fully nonlinear wave crest distributions. Wave time series from potential flow simulations, computational fluid dynamics (CFD) simulations and model test results were used to establish the probability distribution. The wave simulations were performed for three-hour duration assuming that they were long-crested. The sea states are assumed to be represented by JONSWAP spectrum, where a wide range of significant wave height, peak period, spectral peak parameter, and water depth were considered. Coefficients of the proposed semi-empirical formulas, comparisons among crest distributions from wave calibration tests, numerical simulations and the semi-empirical formulas are presented in this paper.

Statistical Uncertainty in Long-Term Distributions of Significant Wave Height

1996 ◽  
Vol 118 (4) ◽  
pp. 284-291 ◽  
Author(s):  
C. Guedes Soares ◽  
A. C. Henriques
Keyword(s):  
Probability Distribution ◽  
Wave Height ◽  
Significant Wave Height ◽  
Data Sets ◽  
Monthly Basis ◽  
Significant Wave ◽  
Fitting Procedure ◽  
The One ◽  
Homogeneous Data

This work examines some aspects involved in the estimation of the parameters of the probability distribution of significant wave height, in particular the homogeneity of the data sets and the statistical methods of fitting a distribution to data. More homogeneous data sets are organized by collecting the data on a monthly basis and by separating the simple sea states from the combined ones. A three-parameter Weibull distribution is fitted to the data. The parameters of the fitted distribution are estimated by the methods of maximum likelihood, of regression, and of the moments. The uncertainty involved in estimating the probability distribution with the three methods is compared with the one that results from using more homogeneous data sets, and it is concluded that the uncertainty involved in the fitting procedure can be more significant unless the method of moments is not considered.

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.

scholarly journals An Environmental GIS-based Variable Analysis of SARS-CoV-2 in the City of Recife, Brazil

2020 ◽  
Author(s):  
Arthur Souza ◽  
Caroline Mota ◽  
Amanda Rosa ◽  
Ciro Figueiredo ◽  
Ana Lucia Candeias
Keyword(s):  
Low Income ◽  
Public Services ◽  
Spatial Regression ◽  
Case Fatality ◽  
Global Scale ◽  
Environmental Data ◽  
Data Sets ◽  
Spatial Regression Analysis ◽  
Effective Drugs ◽  
The City

Abstract Background: Given the increasing rates at which cases of people infected by Covid-19 have been evolving to case-fatality rates on a global scale and the context of there being a world-wide socio-economic crisis, decision-making must be undertaken based on prioritizing effective measures to control and combat the disease since there is a lack of effective drugs and as yet no vaccine. Method: This paper explores the determinant factors of the COVID-19 pandemic and its impacts on Recife, Pernambuco-Brazil by performing both local and global spatial regression analysis on two types of environmental data-sets. Data were obtained from ten specific days between late April and early July 2020, comprehending the ascending, peak and descending behaviours of the curve of infections.Results: This study highlights the importance of identifying and mapping clusters of the most affected neighbourhoods and their determinant effects. We have identified that it is increasingly common for there to be a phase in which hotspots of confirmed cases appear in a well-developed and heavily densely-populated neighbourhood of the city of Recife. From there, the disease is carried to areas characterised by having a precarious provision of public services and a low-income population and this quickly creates hotspots of case-fatality rates. The results also help to understand the influence of the age, income, level of education of the population and, additionally, of the extent to which they can access public services, on the behaviour of the virus across neighbourhoods.Conclusion: This study supports government measures against the spread of Covid-19 in heterogeneous cities, evidencing social inequality as a driver for a high incidence of fatal cases of the disease. Understanding the variables which influence the local dynamics of the virus spread becomes vital for identifying the most vulnerable regions for which prevention actions need to be developed.

Comparison of Bivariate Models of the Distribution of Significant Wave Height and Peak Wave Period

2007 ◽  
Author(s):  
Catarina S. Soares ◽  
C. Guedes Soares
Keyword(s):  
Wave Height ◽  
Significant Wave Height ◽  
Bivariate Normal Distribution ◽  
Wave Period ◽  
Peak Period ◽  
Data Set ◽  
Significant Wave ◽  
The North ◽  
Bivariate Models ◽  
The North Sea

This paper presents the results of a comparison of the fit of three bivariate models to a set of 14 years of significant wave height and peak wave period data from the North Sea. One of the methods defines the joint distribution from a marginal distribution of significant wave height and a set of distributions of peak period conditional on significant wave height. Other method applies the Plackett model to the data and the third one applies the Box-Cox transformation to the data in order to make it approximately normal and then fits a bivariate normal distribution to the transformed data set. It is shown that all methods provide a good fit but each one have its own strengths and weaknesses, being the choice dependent on the data available and applications in mind.

Sign in / Sign up

Export Citation Format

Share Document