Oleg Gaidai

Estimation of Extreme Values by the Average Conditional Exceedance Rate Method

This paper details a method for extreme value prediction on the basis of a sampled time series. The method is specifically designed to account for statistical dependence between the sampled data points in a precise manner. In fact, if properly used, the new method will provide statistical estimates of the exact extreme value distribution provided by the data in most cases of practical interest. It avoids the problem of having to decluster the data to ensure independence, which is a requisite component in the application of, for example, the standard peaks-over-threshold method. The proposed method also targets the use of subasymptotic data to improve prediction accuracy. The method will be demonstrated by application to both synthetic and real data. From a practical point of view, it seems to perform better than the POT and block extremes methods, and, with an appropriate modification, it is directly applicable to nonstationary time series.

Statistics of Extreme Events in Airgap Measurements

The paper presents a study of the extreme value statistics related to airgap measurements on a scale model of a semisubmersible platform subjected to random waves in a wave basin. Relative wave elevation records corresponding to totally 24 h storm duratiou are considered, made up by 8 × 3 h realizations. The focus is on a comparison of two alternative methods for the prediction of extreme values from finite recordings at two different locations at the platform. One is a standard method used in the wave basin, making use of a Weibull-tail fitting procedure. The other is a novel method based on the level up-crossing function combined with an optimization procedure that allows prediction at extreme response levels. Similar results are obtained in the mean values by the two methods, while the latter shows less variability in the predictions from single 3 h records.

Numerical investigation of infragravity wave amplifications during harbor oscillations influenced by variable offshore topography

The infragravity (IG) period oscillations inside an elongated rectangular harbor near the offshore fringing reef induced by normal-incident bichromatic short wave groups are simulated using a fully nonlinear Boussinesq model, FUNWAVE 2.0. Based on an IG wave separation procedure, this article presents a systematical investigation on how the maximum IG period component amplitude, the bound and free IG waves, and their relative components inside the harbor change with respect to the plane reef-face slope and the incident short wave amplitude under the condition of the 2nd to the 5th modes. For the given harbor and the ranges of the reef-face slope and the incident short wave amplitude studied in this paper, it is shown that both the maximum IG period component amplitude and the free IG wave component amplitude inside the harbor fluctuate widely with the reef-face slope, and their changing trends with the reef-face slope are almost identical with each other, while the bound IG waves inside the harbor seem insensitive to it. Both the maximum IG period component amplitude and those of the bound and free IG standing waves inside the harbor change cubically with the incident short wave amplitude.

Random Vibrations with Inelastic Impacts

The paper presents a study of single-degree-of-freedom stochastic vibroimpact problems using numerical path integration (PI). This is a challenging problem due to discontinuities in the state space paths of displacement and velocity response. It is shown that by introducing a suitable transformation of the state space variables, PI can be much simplified, and very accurate numerical results can be obtained. This is verified by comparison with extensive Monte Carlo simulation results.

Numerical study on transient harbor oscillations induced by successive solitary waves

Tsunamis are traveling waves which are characterized by long wavelengths and large amplitudes close to the shore. Due to the transformation of tsunamis, undular bores have been frequently observed in the coastal zone and can be viewed as a sequence of solitary waves with different wave heights and different separation distances among them. In this article, transient harbor oscillations induced by incident successive solitary waves are first investigated. The transient oscillations are simulated by a fully nonlinear Boussinesq model, FUNWAVE-TVD. The incident successive solitary waves include double solitary waves and triple solitary waves. This paper mainly focuses on the effects of different waveform parameters of the incident successive solitary waves on the relative wave energy distribution inside the harbor. These wave parameters include the incident wave height, the relative separation distance between adjacent crests, and the number of elementary solitary waves in the incident wave train. The relative separation distance between adjacent crests is defined as the ratio of the distance between adjacent crests in the incident wave train to the effective wavelength of the single solitary wave. Maximum oscillations inside the harbor excited by various incident waves are also discussed. For comparison, the transient oscillation excited by the single solitary wave is also considered. The harbor used in this paper is assumed to be long and narrow and has constant depth; the free surface movement inside the harbor is essentially one-dimensional. This study reveals that, for the given harbor and for the variation ranges of all the waveform parameters of the incident successive solitary waves studied in this paper, the larger incident wave heights and the smaller number of elementary solitary waves in the incident tsunami lead to a more uniform relative wave energy distribution inside the harbor. For the successive solitary waves, the larger relative separation distance between adjacent crests can cause more obvious fluctuations of the relative wave energy distribution over different resonant modes. When the wave height of the elementary solitary wave in the successive solitary waves equals to that of the single solitary wave and the relative separation distance between adjacent crests is equal to or greater than 0.6, the maximum oscillation inside the harbor induced by the successive solitary waves is almost identical to that excited by the single solitary wave.

Extreme Value Statistics of Large Container Ship Roll

The paper describes a method for prediction of large container ship extreme roll angles occurring during sailing in harsh weather. Rolling is coupled with other ship motions and exhibits highly nonlinear behavior. Risk of losing containers due to a large roll is primary concern for ship transport. Because of nonstationarity and complicated nonlinearities of both waves and ship motions, it is a considerable challenge to model such a phenomenon. In case of extreme motions, the role of nonlinearities dramatically increases, activating effects of second and higher order. Moreover, laboratory tests may also be questioned because of the scaling and the sea state choice. Therefore, data measured on actual ships during their voyages in harsh weather provide a unique insight into statistics of ship motions. The aim of this work is to benchmark state of art method, which makes it possible to extract the necessary information about the extreme response from onboard measured time histories. The method proposed in this paper opens up the possibility to predict simply and efficiently both short- and long-term extreme response statistics.

Extreme Response Statistics of Fixed Offshore Structures Subjected to Ringing Loads

This paper describes an efficient Monte Carlo based method for prediction of extreme response statistics of fixed offshore structures subjected to random seas. The nonlinear structural response known as “ringing” is studied, which is caused by the wave impact force on structural support units. Common challenge for design of such structures is a sound estimate of the hydrodynamic load including diffraction effects. The aim of the work was to develop specific methods which make it possible to extract the necessary information about the extreme response from relatively short time histories. The method proposed in this paper opens up the possibility to predict simply and efficiently both short-term and long-term extreme response statistics. The results presented are based on extensive simulation results for the large fixed platform operating on the Norwegian continental shelf. Structural response time histories, measured in MARINTEK (MT) wave basin lab, were used to validate numerical results.

A Monte Carlo Approach to Prediction of Extreme Response Statistics of Drag Dominated Offshore Structures

The focus of the present paper is the extreme response statistics of drag dominated offshore structures subjected to harsh weather conditions. More specifically, severe sea states both with and without strong current are considered. The nature of the hydrodynamic forces acting on the structure becomes highly nonlinear. In addition to the drag forces, the so called inundation effect due to the wave elevation, corrected to include second order waves, is also taken into account. In the present paper, the Monte Carlo method along with a special extrapolation technique is applied. The proposed method opens up for the possibility to predict simply and efficiently long-term extreme response statistics, which is an important issue for the design of offshore structures.

Long-term offshore Bohai bay Jacket strength assessment based on satellite wave data

ABSTRACT This paper presents generic Monte Carlo-based approach, based on satellite wave data, for extreme response prediction of offshore structures, particularly Jacket type. An operating Jacket in Bohai bay was taken as an example to demonstrate proposed methodology. Satellite-based global wave statistics was used to obtain wave scatter diagram in the area of interest. Effects of second-order waves and sea current were taken into account. The detailed finite element Analysis System (ANSYS) model was employed to study non-linear Jacket dynamics, subject to hydrodynamic wave loads. Stresses in the most critical structural members were extracted and extreme value study was carried out. Proper extrapolation technique was applied to predict stresses with 10–50 year return periods, which is of practical interest for the design and operation of offshore structures.

Prediction of Airgap Statistics for Fixed Offshore Platforms

Air gap statistics for offshore platforms is directly related to the extreme value statistics of the random ocean wave field. The present paper describes a new method for predicting the extreme values of a random wave field in both space and time. The method relies on the use of data provided by measurements or Monte Carlo simulation combined with a technique for estimating the extreme value distribution of a recorded time series. The time series in question represents the spatial extremes of the random field at each point in time. The time series is constructed by sampling the available realization of the random field over a suitable grid defining the domain in question and extracting the extreme value. This is done for each time point of a suitable time grid. Thus, a time series of spatial extremes is produced. This time series provides the basis for estimating the extreme value distribution using recently developed techniques for time series, which results in an accurate practical procedure for solving a very difficult problem. This procedure is applied to the prediction of air gap statistics for a jacket structure.Copyright