Global Performance and Mooring Analysis Using Long Term Analysis Methodology

2016 ◽  
Author(s):  
Mubing Xu ◽  
Anil Sablok ◽  
Oddgeir Dalane
Keyword(s):  
High Speed ◽  
Line Tension ◽  
Mooring Line ◽  
Return Periods ◽  
Short Term ◽  
Analysis Methodology ◽  
Extreme Response ◽  
Global Performance ◽  
Term Analysis

The long term analysis is performed to predict the hull global motion and mooring strength of a Spar platform and the results from long term analysis are compared with the predictions from the short term analysis. The long term motions are also used to investigate the long term riser strength response in Ref. [5]. The results includes the lateral offset, heel angle, heave motion and the mooring line tension at the fairleads. In the short term analysis, the environment events with various return periods and various realizations are considered for each environment load. The Gumbel fitting is used to predict the extreme response. In the long term analysis methodology, the prediction of the global performance and the mooring tension are based on 56-year hindcast wind and wave data with 3-hour intervals. Weibull fitting is used to predict the extreme response for various return periods. The comparison between the long term and the short term predictions indicate that the short term predictions are generally conservative compared to the more accurate, but computationally expensive long term analysis method. The long term methodology is not widely adopted currently due to the computation inefficiency. However, it is expected that this long term methodology could provide a better option in the future with the consideration of its accuracy and the application of high speed computer.

Strength Performance of Steel Catenary Riser Using Short Term and Long Term Analysis Methodologies

2016 ◽  
Author(s):  
Feng Wang ◽  
Roger Burke ◽  
Anil Sablok ◽  
Kristoffer H. Aronsen ◽  
Oddgeir Dalane
Keyword(s):  
Bending Moment ◽  
Current Profile ◽  
Short Term ◽  
Sea State ◽  
Strength Performance ◽  
Steel Catenary Riser ◽  
Analysis Methodology ◽  
Riser Design ◽  
Term Analysis

Strength performance of a steel catenary riser tied back to a Spar is presented based on long term and short term analysis methodologies. The focus of the study is on response in the riser touch down zone, which is found to be the critical region based on short term analysis results. Short term riser response in design storms is computed based on multiple realizations of computed vessel motions with various return periods. Long term riser response is based on vessel motions for a set of 45,000 sea states, each lasting three hours. The metocean criteria for each sea state is computed based on fifty six years of hindcast wind and wave data. A randomly selected current profile is used in the long term riser analysis for each sea state. Weibull fitting is used to compute the extreme riser response from the response of the 45,000 sea states. Long term analysis results in the touch down zone, including maximum bending moment, minimum effective tension, and maximum utilization using DNV-OS-F201, are compared against those from the short term analysis. The comparison indicates that the short term analysis methodology normally followed in riser design is conservative compared to the more accurate, but computationally more expensive, long term analysis methods. The study also investigates the important role that current plays in the strength performance of the riser in the touch down zone.

Long Term Analysis of Steep and Breaking Wave Properties by Event Matching

2018 ◽  
Author(s):  
Thomas B. Johannessen ◽  
Øystein Lande
Keyword(s):  
Wave Breaking ◽  
Offshore Structures ◽  
Return Periods ◽  
Short Term ◽  
Nonlinear Load ◽  
Load Effect ◽  
Strongly Nonlinear ◽  
Load Effects ◽  
Term Analysis

Offshore structures are typically required to withstand extreme and abnormal load effects with annual probabilities of occurrence of 10−2 and 10−4 respectively. For linear or weakly nonlinear problems, the load effects with the prescribed annual probabilities of occurrence are typically estimated as a relatively rare occurrence in the short term distribution of 100 year and 10 000 year seastates. For strongly nonlinear load effects, it is not given that an extreme seastate can be used reliably to estimate the characteristic load effect. The governing load may occur as an extremely rare event in a much lower seastate. In attempting to model the load effect in an extreme seastate, the relevant short term probability level is not known nor is it known whether the physics of the wave loading is captured correctly in an extreme seastate. Examples of such strongly nonlinear load effects are slamming loads on large volume offshore structures or wave in deck loads on jacket structures subject to seabed subsidence. The present paper is concerned with the long term distribution of strongly nonlinear load effects and a methodology is proposed which incorporates CFD analysis in a long term Monte Carlo analysis of crest elevations and wave kinematics. Based on a long term time domain simulation of a linear surface elevation, a selection of events is run in CFD in order to obtain a database of linear and corresponding fully nonlinear wave fields with the possibility of wave breaking included. In the subsequent long term analysis, a large linear event is then replaced by the closest matching event in the database. A technique is developed to Froude scale the database results and shift the origin in time and plane so that the database of typically only 100 events give a close match to all the events in the simulation. The method is applied to the simple case of drag loading on a cylinder which is truncated above the still water level such that only the largest waves impact with the structure. It is observed that whereas the Event Matching method agree well with a second order model for return periods lower than 100 years, the loading on the cylinder is significantly larger for longer return periods. The deviation is caused by the increasing dominance of wave braking in the largest crest and illustrates the importance of incorporating wave breaking in the analysis of wave in deck loading problems.

Long-term extreme response analysis for semi-submersible platform mooring systems

2020 ◽  
pp. 147509022097651
Author(s):  
Yuliang Zhao ◽  
Sheng Dong
Keyword(s):  
Environmental Data ◽  
Distribution Model ◽  
Response Analysis ◽  
Accurate Assessment ◽  
Response Distribution ◽  
Short Term ◽  
Floating Structure ◽  
Extreme Response ◽  
Term Analysis

The accurate assessment of long-term extreme responses of floating-structure mooring system designs is important because of small failure probabilities caused by long-term and complex ocean conditions. The most accurate assessment would involve considering all conceivable sea states in which each sea state is regarded as a stochastic process and performing nonlinear time-domain numerical simulations of mooring systems to estimate the extreme response from a long-term analysis. This procedure would be computationally intensive because of the numerous short-term sea states involved. Here, a more feasible approach to evaluate the long-term extreme response is presented through immediate integration combined with Monte Carlo simulations. A parameter fitting procedure of the short-term extreme response distribution under irregular wave conditions is employed to solve the long-term response integration. Case studies were conducted on a semi-submersible platform using environmental data measurements of the Gulf of Mexico and a joint distribution model of the environmental parameters was considered. This approach was observed to be effective and the results were compared with those of traditional methodologies (univariate extreme value design and environmental contour methods). The differences were reflected using a reliability analysis of mooring lines, which indicated that the design standards must be stricter when using long-term analysis.

Long-Term Analysis Applied to Mooring Systems Design

2020 ◽  
Author(s):  
Pedro Seabra ◽  
Luis Volnei Sudati Sagrilo ◽  
Paulo Esperança
Keyword(s):  
Time Domain ◽  
Environmental Conditions ◽  
Systems Design ◽  
Environmental Data ◽  
Coupled Analysis ◽  
Offshore Structure ◽  
Short Term ◽  
Extreme Response ◽  
Term Analysis

Abstract Nowadays, the most used methodology to predict line tensions is the short-term coupled analysis, where the mooring system responses are obtained by a time-domain analysis for only some specific design combinations of extreme environmental conditions. This mooring analysis demands certain considerations and it is not the best way to obtain the offshore structure responses. The advances in both quantity and quality of collected environmental data and the increase of the computers processing power has enabled to consider the approach of more accurate long-term methodologies for mooring systems design. This paper proposes a numerical/computational procedure to obtain the extreme loads (ULS) acting on offshore platforms’ mooring lines. The work is based on the methodology of long-term analysis, employing a 10-yr long short-term environmental dataset of 3-h sea-states, where each short-term environmental condition is composed of the simultaneously observed environmental parameters of wave (sea and swell), wind and current. The methodology is applied to the analysis of three different mooring systems: a) spread-moored FPSO, b) Semi-Submersible platform and c) turret-moored FPSO. The Bootstrap approach is employed in order to take into account the statistical uncertainty associated to the estimated long-term most probable extreme response due to the limited number of short-term environmental conditions. The work was carried out using Dynasim software [1] to generate the time domain tension time series, which were later post-processed by using computational codes developed with Python software. Longer short-term numerical simulations lengths than the short-term period (3-h) have been investigated in order to understand the influence of this parameter on the final extreme long-term top tensions.

LOCA analysis of BWR-4/Mark-I nuclear power plant with TRACE

Kerntechnik ◽  
2021 ◽  
Vol 86 (2) ◽  
pp. 128-142
Author(s):  
J.-J. Huang ◽  
S.-W. Chen ◽  
J.-R. Wang ◽  
C. Shih ◽  
H.-T. Lin
Keyword(s):  
Nuclear Power ◽  
Coupled Model ◽  
Short Term ◽  
Containment System ◽  
Loss Of Coolant Accident ◽  
Main Steam Line ◽  
Main Steam ◽  
Temperature Responses ◽  
Term Analysis

Abstract This study established an RCS-Containment coupled model that integrates the reactor coolant system (RCS) and the containment system by using the TRACE code. The coupled model was used in both short-term and long-term loss of coolant accident (LOCA) analyses. Besides, the RELAP5/CONTAN model that only contains the containment system was also developed for comparison. For short-term analysis, three kinds of LOCA scenarios were investigated: the recirculation line break (RCLB), the main steam line break (MSLB), and the feedwater line break (FWLB). For long-term analysis, the dry-well and suppression pool temperature responses of the RCLB were studied. The analysis results of RELAP5/CONTAN and TRACE models are benchmarked with those of FSAR and RELAP5/GOTHIC models, and it appears that the results of the above four models are consistent in general trends.

On the Probability Distribution of Mooring Line Tensions in a Directional Environment

2011 ◽  
Author(s):  
Jan Mathisen ◽  
Siril Okkenhaug ◽  
Kjell Larsen
Keyword(s):  
Time Series ◽  
Probability Distributions ◽  
Extreme Value Distribution ◽  
Line Tension ◽  
Extreme Value ◽  
Mooring Line ◽  
Large Set ◽  
Short Term ◽  
Reliability Method ◽  
Line Design

A joint probabilistic model of the metocean environment is assembled, taking account of wind, wave and current and their respective heading angles. Mooring line tensions are computed in the time domain, for a large set of short-term stationary conditions, intended to span the domain of metocean conditions that contribute significantly to the probabilities of high tensions. Weibull probability distributions are fitted to local tension maxima extracted from each time series. Long time series of 30 hours duration are used to reduce statistical uncertainty. Short-term, Gumbel extreme value distributions of line tension are derived from the maxima distributions. A response surface is fitted to the distribution parameters for line tension, to allow interpolation between the metocean conditions that have been explicitly analysed. A second order reliability method is applied to integrate the short-term tension distributions over the probability of the metocean conditions and obtain the annual extreme value distribution of line tension. Results are given for the most heavily loaded mooring line in two mooring systems: a mobile drilling unit and a production platform. The effects of different assumptions concerning the distribution of wave heading angles in simplified analysis for mooring line design are quantified by comparison with the detailed calculations.

A dynamic and robust image processing based method for measuring the yarn diameter and its variation

2014 ◽  
Vol 84 (18) ◽  
pp. 1948-1960 ◽  
Author(s):  
Mohamed Eldessouki ◽  
Sayed Ibrahim ◽  
Jiři Militky
Keyword(s):  
High Speed ◽  
Dynamic Change ◽  
Effective Property ◽  
Periodic Variation ◽  
Short Term ◽  
Reasonable Time ◽  
Yarn Diameter ◽  
Fabric Structure ◽  
Robust Image

The yarn diameter is an effective property in determining fabric structure and processing settings. There are different systems of measuring the yarn diameter; among them is the image analysis of the yarn’s microscopic images. This method is considered to be more precise than other methods, but it is “static” in nature as it measures the property at scattered intervals and does not reflect the continuous variation of the yarn diameter. The goal of the current work is to measure the yarn diameter and its variation over a long length of yarn at fixed intervals to consider the “dynamic” change in the property. To achieve this goal, a high-speed camera (HSC) with a proper magnification was used to capture the images of the yarn and a new robust algorithm was developed to analyze the massive amount of yarn pictures in a reasonable time. The collected data for the yarn diameter were analyzed and compared to the results of the commercial Uster Evenness Tester IV. The results of the HSC were very comparable to the results of Uster and they were able to detect the short-term, the long-term, and the periodic variation of the yarn diameter.

Long-term and short-term analysis of the natural rubber market

1989 ◽  
Vol 125 (4) ◽  
pp. 718-747 ◽  
Author(s):  
Kees Burger ◽  
Hidde P. Smit
Keyword(s):  
Natural Rubber ◽  
Short Term ◽  
Rubber Market ◽  
Term Analysis

Estimation of Extreme Ship Response

2012 ◽  
Vol 56 (01) ◽  
pp. 23-34
Author(s):  
Wengang Mao ◽  
Igor Rychlik
Keyword(s):  
Gaussian Model ◽  
Container Ship ◽  
Short Term ◽  
Sea State ◽  
High Quantiles ◽  
Alternative Approach ◽  
Extreme Response ◽  
Heading Angle ◽  
Ship Speed

In practice the severity of ship response is measured by high quantiles of long-term distribution of the response. The distribution is estimated by combining the short-term distribution of the response with a long-term probability distribution of encountered sea states. The paper describes an alternative approach, the so-called Rice's method, based on estimation of expected number of upcrossings of high levels by stress during 1 year. The method requires description of long-term variability of the standard deviation, skewness, kurtosis, and zero upcrossing frequency of ship response. It is assumed that the parameters are functions of encountered significant wave height, heading angle, and ship speed. The relation can be estimated from the measured stresses or computed by dedicated software assuming rigid ship hull model. Then Winterstein's transformed Gaussian model is used to estimate the upcrossing rates of response during a sea state. The proposed method is validated using the full-scale measurements of a 2,800 TEU container ship during the first 6 months of 2008. Numerical estimation of 4,400 TEU container ship extreme of the extreme response for a 4400 TEU container ship illustrates the approach when no measurements are available.

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