scholarly journals Extreme Value Estimation of Mooring Loads Based on Station-Keeping Trials in Ice

2020 ◽  
Author(s):  
Chana Sinsabvarodom ◽  
Bernt J. Leira ◽  
Wei Chai ◽  
Arvid Naess
Keyword(s):  
Field Experiments ◽  
Time Window ◽  
Extreme Value ◽  
International Standards ◽  
Management Systems ◽  
Station Keeping ◽  
Threshold Method ◽  
Mooring Lines ◽  
Peak Over Threshold ◽  
Value Estimation

Abstract The purpose of this work is to perform an extreme value estimation of the mooring loads associated with station-keeping of a ship operating in ice. In general, the design of mooring lines is based on estimation of the extreme loading caused by environmental conditions within the relevant area. In March 2017, station-keeping trials (SKT) in drifting ice were performed as part of a project headed by Statoil in the Bay of Bothnia. The objective was to investigate the characteristics of the mooring loads for the supply vessel Magne Viking for different types of physical ice management schemes. Tor Viking was employed as an ice breaker as part of the physical ice management systems. The ice conditions (i.e. the ice drift velocity and the ice thickness) during the trials were monitored by using Ice Profiling Sensors (IPSs). Different patterns of ice-breaking manoeuvers were investigated as part of the physical ice management systems, such as square updrift, round circle, circle updrift and linear updrift pattern were studied as part of the field experiments. The peak values of the mooring loads for the supply vessel are determined by using the min peak prominence method. For the purpose of extreme value prediction, the peak over threshold method and block maxima method for a specific time window are applied to estimate the mooring loads that correspond to specific probabilities of exceedance (or equivalently: return periods). These loads can then be compared to the design loads that are being specified by relevant international standards.

Extreme value statistics for river quality simulations

2010 ◽  
Vol 61 (2) ◽  
pp. 397-406 ◽  
Author(s):  
N. Schindler ◽  
J. Tränckner ◽  
P. Krebs
Keyword(s):  
Urban Areas ◽  
Concentration Level ◽  
Extreme Value ◽  
Extreme Value Statistics ◽  
Threshold Method ◽  
Peak Over Threshold ◽  
Peak Over Threshold Method ◽  
The Impact ◽  
Posteriori Estimation

Various methods have been proposed to assess intermittent pollution loads and impacts on rivers in urban areas. Although the variables to describe the impact are mainly the same, the standards show significant differences in the assessment of permitted concentration level, duration and return period. The probability of an event is derived using either frequencies of occurrence or predefined extreme value distributions. Both methods have drawbacks. To bypass these, an a posteriori estimation of the statistical distribution of data based on the peak-over-threshold method is proposed. The method is exemplarily demonstrated using a semi-virtual case study.

scholarly journals Extreme Value Estimation of Mooring Loads Based on Station-Keeping Trials in Ice

2021 ◽  
Author(s):  
CHANA SINSABVARODOM ◽  
Bernt Leira ◽  
Wei Chai ◽  
Arvid Naess
Keyword(s):  
Extreme Value ◽  
Station Keeping ◽  
Value Estimation

New approaches to improving enterprise management systems using international models and standards in a digital transformation environment

2020 ◽  
pp. 24-29
Author(s):  
V.V. Silaeva ◽  
◽  
V.P. Semenov ◽  
Keyword(s):  
Management System ◽  
Integrated Management ◽  
Digital Transformation ◽  
International Standards ◽  
System Model ◽  
Management Systems ◽  
Enterprise Management ◽  
Integrated Management System ◽  
New Approaches ◽  
Iso 31000

The relevance of creating integrated management systems for enterprises in a digital transformation environment is proved. New approaches to improving the management system in accordance with the new European excellence model (EFQM 2020) and international standards for achieving sustainable success and risk management are described. Approach to the development of integrated management system model based on the new EFQM 2020 model and international standards such as ISO 9004:2018 and ISO 31000:2018 is offered.

Hermite Extreme Value Estimation of Non-Gaussian Wind Load Process on a Long-Span Roof Structure

2014 ◽  
Vol 140 (9) ◽  
pp. 04014061 ◽  
Author(s):  
M. F. Huang ◽  
Wenjuan Lou ◽  
Xiaotao Pan ◽  
C. M. Chan ◽  
Q. S. Li
Keyword(s):  
Wind Load ◽  
Extreme Value ◽  
Long Span ◽  
Roof Structure ◽  
Value Estimation ◽  
Non Gaussian

Damage Detection of Offshore Platform Mooring Line Using Artificial Neural Network

2018 ◽  
Author(s):  
Djoni E. Sidarta ◽  
Jim O’Sullivan ◽  
Ho-Joon Lim
Keyword(s):  
Neural Network ◽  
Artificial Neural Network ◽  
Damage Detection ◽  
Total Mass ◽  
Offshore Platform ◽  
Mooring Line ◽  
Ann Model ◽  
Station Keeping ◽  
Mooring Lines ◽  
Artificial Neural

Station-keeping using mooring lines is an important part of the design of floating offshore platforms, and has been used on most types of floating platforms, such as Spar, Semi-submersible, and FPSO. It is of great interest to monitor the integrity of the mooring lines to detect any damaged and/or failures. This paper presents a method to train an Artificial Neural Network (ANN) model for damage detection of mooring lines based on a patented methodology that uses detection of subtle shifts in the long drift period of a moored floating vessel as an indicator of mooring line failure, using only GPS monitoring. In case of an FPSO, the total mass or weight of the vessel is also used as a variable. The training of the ANN model employs a back-propagation learning algorithm and an automatic method for determination of ANN architecture. The input variables of the ANN model can be derived from the monitored motion of the platform by GPS (plus vessel’s total mass in case of an FPSO), and the output of the model is the identification of a specific damaged mooring line. The training and testing of the ANN model use the results of numerical analyses for a semi-submersible offshore platform with twenty mooring lines for a range of metocean conditions. The training data cover the cases of intact mooring lines and a damaged line for two selected adjacent lines. As an illustration, the evolution of the model at various training stages is presented in terms of its accuracy to detect and identify a damaged mooring line. After successful training, the trained model can detect with great fidelity and speed the damaged mooring line. In addition, it can detect accurately the damaged mooring line for sea states that are not included in the training. This demonstrates that the model can recognize and classify patterns associated with a damaged mooring line and separate them from patterns of intact mooring lines for sea states that are and are not included in the training. This study demonstrates a great potential for the use of a more general and comprehensive ANN model to help monitor the station keeping integrity of a floating offshore platform and the dynamic behavior of floating systems in order to forecast problems before they occur by detecting deviations in historical patterns.

scholarly journals ANALYSIS OF THE TECHNICAL REGULATION STATE OF COSMETIC PRODUCTS TURNOVER IN UKRAINE

ScienceRise ◽  
2020 ◽  
Vol 2 ◽  
pp. 39-46
Author(s):  
Iryna Kazakova ◽  
Viacheslav Lebedynets
Keyword(s):  
Life Cycle ◽  
Quality Management ◽  
State Regulation ◽  
The State ◽  
International Standards ◽  
Management Systems ◽  
Cosmetic Products ◽  
Technical Regulation ◽  
Quality Management Systems ◽  
Technological Product

The object of research is the state regulation of the turnover of cosmetic products and some aspects of their implementation in Ukraine. Investigated problem. The issue of import substitution of Ukrainian cosmetic products and the increase in their production and sales in the Ukrainian and foreign markets is an urgent reason for the dynamic development of the cosmetic industry and the diversification of its traditional forms and directions of application. The solution to these problems mainly depends on the level of technical regulation by the state and requires proper legislative support in accordance with the requirements of international standards and EU directives. The main scientific results. The foreign experience of regulatory support and state regulation of the turnover of cosmetic products (CP) is summarized. The problems of technical regulation of cosmetic and medicinal cosmetics in Ukraine are identified. An addition to the draft national technical regulation for cosmetic products is proposed and recommendations for its rational use are given. The prospects of introducing quality management systems at enterprises engaged in activities at all stages of the CP life cycle are determined. Innovative technological product. A model has been developed to improve the current regulatory and technical framework governing the CP turnover in Ukraine, and an algorithm for its implementation is presented. The relevance of methods and means of ensuring the quality, safety and effectiveness of CP by introducing quality management systems at all stages of its life cycle is determined. The scope of the innovative technological product. The developed proposals are recommended for implementation in the system of state regulation of the CP turnover in order to ensure its quality, effectiveness and safety for the health of consumers.

Consideration of Epistemic Uncertainty in Extreme Wave Height Estimation

2014 ◽  
Author(s):  
Ryota Wada ◽  
Takuji Waseda
Keyword(s):  
Gulf Of Mexico ◽  
Observational Data ◽  
Wave Height ◽  
Extreme Values ◽  
Epistemic Uncertainty ◽  
Extreme Value Distribution ◽  
Predictive Distribution ◽  
Extreme Value ◽  
Posterior Predictive Distribution ◽  
Value Estimation

Extreme value estimation of significant wave height is essential for designing robust and economically efficient ocean structures. But in most cases, the duration of observational wave data is not efficient to make a precise estimation of the extreme value for the desired period. When we focus on hurricane dominated oceans, the situation gets worse. The uncertainty of the extreme value estimation is the main topic of this paper. We use Likelihood-Weighted Method (LWM), a method that can quantify the uncertainty of extreme value estimation in terms of aleatory and epistemic uncertainty. We considered the extreme values of hurricane-dominated regions such as Japan and Gulf of Mexico. Though observational data is available for more than 30 years in Gulf of Mexico, the epistemic uncertainty for 100-year return period value is notably large. Extreme value estimation from 10-year duration of observational data, which is a typical case in Japan, gave a Coefficient of Variance of 43%. This may have impact on the design rules of ocean structures. Also, the consideration of epistemic uncertainty gives rational explanation for the past extreme events, which were considered as abnormal. Expected Extreme Value distribution (EEV), which is the posterior predictive distribution, defined better extreme values considering the epistemic uncertainty.

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