Extreme large cargo ship panel stresses by bivariate ACER method

Gaidai, Oleg; Storhaug, Gaute; Næss, Arvid

doi:10.1016/j.oceaneng.2016.06.048

Cited by 38 publications

(15 citation statements)

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“…It is now assumed that the marginal extreme value distributions (EVD) are represented by the univariate ACER functions, see Naess and Karpa (2015); Karpa and Naess (2015); Gaidai et al (2016) ( ) ≈ exp{−( − + 1) ( )} , ≥ 1 ( ) ≈ exp{−( − + 1) ( )} , ≥ 1 (5) with ( ) = exp{− ( − ) } and similar definition for ( ). The detailed optimization procedure for estimation of parameters , , , , , , , is outlined in Naess and Karpa (2015); Karpa and Naess (2015); Gaidai et al (2016). The choice of copula model is now determined by the accuracy obtained by fitting ( , ) to the empirical ( , ).…”

Section: Discussionmentioning

confidence: 99%

“…Note that both the stochastic processes (heave and pitch in this paper) are required to be synchronous in time, which allows an in-depth look into the long term correlation statistics and coupling effects. The brief decription of the bivariate ACER2D method is given in Appendix, for more details see Naess andKarpa (2015); Karpa and Naess (2015); Gaidai et al (2016).…”

Section: Statistical Approach -The Acer2d Methodsmentioning

confidence: 99%

“…The aim of this paper is to develop a simple and general Monte Carlo (MC) based method, which is able to tackle all nonlinear effects without simplifications, except for those inherent in the hydrodynamic model itself. This goal has been achieved by combining standard MC simulations with a CPU time-saving extrapolation scheme Naess and Karpa (2015); Karpa and Naess (2015); Gaidai et al (2016). As opposed to univariate statistical methods, the ACER2D method takes into account bivariate correlation, which may reflect important coupling effects.…”

Section: Introductionmentioning

confidence: 99%

“…Then, when ≫ , one has ( , ) ≈ exp{ − ( − + 1) ℰ ( , )} ; , → ∞ (4) Estimation of bivariate ACER2D functions ℰ ( , ) for the simulated/observed stationary/non-stationary time series constitutes counting of exceedance events. For the detailed estimation of the bivariate ACER2D functions, see Naess and Karpa (2015); Karpa and Naess (2015); Gaidai et al (2016).…”

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confidence: 99%

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Bivariate statistics of wind farm support vessel motions while docking

Gaidai

Næss

et al. 2020

Ships and Offshore Structures

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Robust prediction of extreme motions during wind farm support vessel (WFSV) operation is an important safety concern. In particular, it is important to study safety of operation in random sea conditions during WFSV docking against the wind tower, while workers are able to get on to the tower. Docking is performed by thrusting the vessel fender against the wind tower (the alternative docking maneuver by hinging is not studied here). In this paper, the finite element software AQWA has been used to analyze the vessel response due to hydrodynamic wave loads, acting on a specific maintenance ship under actual sea conditions. Excessive motions may occur during certain sea conditions, posing a risk to the crew transfer operation. The authors have primarily focused on the statistical analysis rather than the dynamics of the problem. This paper presents a novel method for estimating bivariate statistics, based on Monte Carlo simulations (or measurements if available). The bivariate average conditional exceedance rate (ACER2D) method is briefly outlined. The ACER2D method offers an accurate estimation of bivariate statistics, utilizing the available data efficiently. Two dimensional probability contours, corresponding to large return periods, are obtained by the ACER2D method. Based on the overall performance of the presented method, it is seen that the ACER2D method provides an efficient and accurate prediction of extreme return period contours. The described approach may serve as a useful tool for vessel design, facilitating optimization of boat parameters in order to minimize excessive vessel motions.

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Section: Discussionmentioning

confidence: 99%

Section: Statistical Approach -The Acer2d Methodsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

mentioning

confidence: 99%

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Bivariate statistics of wind farm support vessel motions while docking

Gaidai

Næss

et al. 2020

Ships and Offshore Structures

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“…In recent years, the problem was analysed in the experimental and numerical domain. In the experiments, both model tests (Storhaug et al 2010) and full-scale measurements (Gaidai et al 2016, Mao et al 2015 were carried out. In model testing, the tests are usually quite expensive, and only a limited number of cases could be investigated.…”

Section: Introductionmentioning

confidence: 99%

Modern Trends in Research on Steel, Aluminium and Composite Structures

Giżejowski¹,

Kozłowski²,

Chybiński³

et al. 2021

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involvement in the organisation of the 14th International Conference of Metal Structures is perceived by me as a distinction, but also as a proof of trust in the University. This activity fits perfectly the University mission to educate at all levels of higher education and in lifelong learning programs in close connection with scientific and research development. Nowadays, Poznan University of Technology offers education at 9 fac ulties, covering a total of 33 fields of study. Nearly 16,000 students study here and over 1,300 academic teachers cater to their education. The didactic offer of Poznan University of Tech nology covers the most important fields related to modern technology with a recently launched program in Artificial Intelligence; it is also well adapted to the requirements of both domestic and foreign employers. High-quality scientific research is an integral element of Poznan University of Technology strategy, characterized by scientific achievements of its employees who published more than 2,000 scientific contributions: highly ranked articles, monographs, textbooks and other publications. The total number of PUT Library collections is over 450,000 volumes. Among numerous achievements, the University is proud of the H2020 Marie Sklodowska-Curie Global Fellowships and ERC grants. Furthermore, our sci entists are among the authorities of the Polish Academy of Sciences (9 representatives) and are also members of numerous international scientific societies. According to Shanghai Rank ing 2020 edition in disciplines, PUT was classified among the best 400 universities in the world in Mechanical Engineering. Also, we are ranked by students as the most popular university in Poland according to the Ministry of Science and Higher Education in the 2020/2021 academic year.Owing to EU funding, recent years have introduced the development of research infrastruc ture at the Warta university campus. In 2020 our University also became a leader of European University EUNICEa project funded by the European Commission with a budget of more than 6 million EUR. Our university consortium partners originate from Belgium, Germany, France, Finland, Italy and Spain. EUNICE's main goal is to build a common European Uni versity of the future, and prepare its structure and management design within 3 years. EUNICE is aspiring to provide a high-quality digital learning, offering flexible and multidis ciplinary studies, as well as opportunities for students and staff for international exchange and networking. EUNICE will develop modern and innovative pedagogical methods and provide enhanced student services, in terms of enrolment, recognition, student counselling and guid ance aimed at boosting the employability of all students. Just recently, PUT was also granted by the European Commission a follow-up scientific project REUNICE. This H2020 strategic project for the European University Alliance EUNICE aims at aligning its education, research and innovation strategies through an ambitious and transformative agenda.Therefore, I am ...

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Novel Reliability Method Validation for Floating Wind Turbines

Gaidai

Wang

Xing

et al. 2023

Adv Energy and Sustain Res

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Wind turbines and associated parts are susceptible to cyclic stresses, including torque, bending, and longitudinal stress, and twisting moments. Therefore, research on the resilience of dynamic systems under such high loads is crucial for design and future risk‐free operations. The method described in this study is beneficial for multidimensional structural responses that have undergone sufficient numerical simulation or measurement. In contrast to established dependability methodologies, the unique technique does not need to restart the numerical simulation each time the system fails. Herein, it is demonstrated that it is also possible to accurately predict the probability of a system failure in the event of a measurable structural reaction. In contrast to well‐established bivariate statistical methods, which are known to predict extreme response levels for 2D systems accurately, this study validates a novel structural reliability method that is particularly suitable for multidimensional structural responses. In contrast to conventional methods, the novel reliability approach does not invoke a multidimensional reliability function in the Monte Carlo numerical simulation case. As demonstrated in this study, it is also possible to accurately anticipate the likelihood of a system failure in the case of a measurable structural reaction.

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Extreme large cargo ship panel stresses by bivariate ACER method

Cited by 38 publications

References 11 publications

Bivariate statistics of wind farm support vessel motions while docking

Bivariate statistics of wind farm support vessel motions while docking

Modern Trends in Research on Steel, Aluminium and Composite Structures

Novel Reliability Method Validation for Floating Wind Turbines

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