On the Influence of Environmental Contour Method in Estimating Extreme Structural Response

Author(s):  
Erik Vanem

Environmental contours are often applied in probabilistic structural reliability analysis in order to identify extreme environmental conditions that may give rise to extreme loads and responses. The perhaps most common way of establishing such environmental contours are based on the Rosenblatt transform and the IFORM approximation (Inverse First Order Reliability Method), but recently an alternative approach based on direct Monte Carlo simulations with importance sampling has been proposed. A recent comparison study revealed that there might be rather large differences in certain parts of the contours and for certain joint environmental models. In particular, the alternative contour method yields convex contours by design, whereas the traditional contours may be convex or non-convex. In this paper, comparison studies that include applications on a few structural examples are presented. Comparing the contours with known response surfaces, one may investigate how large the differences between the contour methods may be, and compare this to the correct extreme response estimated by simulation studies. These case studies clearly illustrate the influence of the environmental contour calculation method on the estimated extreme response. Whereas the different methods yield comparable results for some structural problems, they may give very different estimates of the extreme response for other. It is demonstrated that in certain cases, the estimates from some of the contour methods are highly conservative, whereas they in other cases might be very optimistic. The reason for these results are discussed and some requirements on the response functions for obtaining conservative estimates will be stated.

Author(s):  
Yuliang Zhao ◽  
Sheng Dong ◽  
Zihao Yang ◽  
Lance Manuel

Abstract To ensure acceptable operation and/or survival of floating structures in extreme conditions, nonlinear time-domain simulations are often used to predict the structural response at the design stage. An environmental contour (EC) is commonly employed to identify critical sea states that serve as input for numerical simulations to assess the safety and performance of marine structures. In many studies, marginal and conditional distributions are defined to construct bivariate joint probability distributions for variables such as significant wave height and zero-crossing period; then, environmental contours can be constructed using the inverse first-order reliability method (IFORM). This study adopts alternative models to describe the generalized dependence structure between the environmental variables using copulas; the Nataf transformation is also discussed as a special case. Environmental contours are constructed, making use of measured wave data from moored buoys. Derived design loads are applied on a semi-submersible platform to assess possible differences. In addition, the long-term extremes of the tension of the mooring lines are estimated, considering uncertainties in the structural response using a 3D model (that includes response variability, ignored with the EC approach) to help establish more accurate design loads using Monte Carlo simulation. Results offer a clear indication of the extreme response of the floating structure based on the different models.


2006 ◽  
Vol 128 (4) ◽  
pp. 554-561 ◽  
Author(s):  
Korn Saranyasoontorn ◽  
Lance Manuel

When interest is in establishing ultimate design loads for wind turbines such that a service life of, say, 20 years is assured, alternative procedures are available. One class of methods works by employing statistical loads extrapolation techniques following development first of 10-minute load maxima distributions (conditional on inflow parameters such as mean wind speed and turbulence intensity). The parametric conditional load distributions require extensive turbine response simulations over the entire inflow parameter range. We will refer to this first class of methods as the “parametric method.” An alternative method is based on traditional structural reliability concepts and isolates only a subset of interesting inflow parameter combinations that are easily first found by working backward from the target return period of interest. This so-called inverse reliability method can take on various forms depending on the number of variables that are modeled as random. An especially attractive form that separates inflow (environmental) variables from turbine load∕response variables and further neglects variability in the load variables given inflow is referred to as the environmental contour (EC) method. We shall show that the EC method requires considerably smaller amounts of computation than the parametric method. We compare accuracy and efficiency of the two methods in 1- and 20-year design out-of-plane blade bending loads at the root of two 1.5 MW turbines. Simulation models for these two turbines with contrasting features, in that one is stall-regulated and the other pitch-regulated, are used here. Refinements to the EC method that account for the effects of the neglected response variability are proposed to improve the turbine design load estimates.


Author(s):  
Finn-Idar G. Giske ◽  
Bernt Johan Leira ◽  
Ole Øiseth

In this paper the first order reliability method (FORM) found in connection with structural reliability analysis is first used in an inverse manner to efficiently obtain an approximate solution of the full long-term extreme response of marine structures. A new method is then proposed where the second order reliability method (SORM) is used to improve the accuracy of the approximation. This method is compared with exact results obtained using full numerical integration. The new method is seen to achieve improved accuracy for large return periods, yet keep the number of required short-term response analyses within acceptable levels.


Author(s):  
Oleg Gaidai ◽  
Jo̸rgen Krokstad

Paper describes a method for prediction of extreme response statistics of fixed offshore structures subjected to random seas by Monte Carlo simulation. The nonlinear structural response know as “ringing” is studied, 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 inclusive diffraction effects. Structure is modeled as a multi-degree of freedom (MDOF) system and number of Monte Carlo simulations was performed to highlight extreme response in severe random seas. Since MDOF numerical simulation is costly, an efficient statistical technique was adopted, minimizing required computational effort. Environmental contour method was combined with accurate distribution tail extrapolation. 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. Measured response time histories were used to validate numerical results.


2017 ◽  
Vol 08 (03n04) ◽  
pp. 1740001 ◽  
Author(s):  
Llewellyn Morse ◽  
Zahra Sharif Khodaei ◽  
M. H. Aliabadi

In this work, a method for the application of multi-fidelity modeling to the reliability analysis of 2D elastostatic structures using the boundary element method (BEM) is proposed. Reliability analyses were carried out on a rectangular plate with a center circular hole subjected to uniaxial tension using Monte Carlo simulations (MCS), the first-order reliability method (FORM), and the second-order reliability method (SORM). Two BEM models were investigated, a low-fidelity model (LFM) of 20 elements and a high-fidelity model (HFM) of 100 elements. The response of these models at several design points was used to create multi-fidelity models (MFMs) utilizing second-order polynomial response surfaces and their reliability, alongside that of the LFM and the HFM, was evaluated. Results show that the MFMs that directly called the LFM were significantly superior in terms of accuracy to the LFM, achieving very similar levels of accuracy to the HFM, while also being of similar computational cost to the LFM. These direct MFMs were found to provide good substitutes for the HFM for MCS, FORM, and SORM.


Author(s):  
Erik Vanem ◽  
Arne Bang Huseby

Abstract Environmental contours are often applied in probabilistic structural reliability analysis to identify extreme environmental conditions that may give rise to extreme loads and responses. It represents an approximate method for performing long-term extreme response analyses in cases where full long-term analyses are not feasible due to computationally heavy and time-demanding response calculations. There are various methods for deriving environmental contours given a set of metocean data. These relate to different approaches for modelling the joint behaviour of the metocean variables, i.e., a joint distribution function fitted to the data, but also different ways of establishing the environmental contour given a joint distribution for the environmental variables. In light of this, a benchmark exercise was announced at OMAE 2019 [1], asking for contributions from different practitioners involved with environmental contours. Various bivariate datasets are provided and two exercises are specified for which different solutions are elicited. The first part of the exercise concerns the estimation of the actual contours, whereas the second part relates to the uncertainty characterization of the contours in light of sampling variability. This paper is a response to this announcement and provides one contribution to these benchmark exercises; environmental contours based on a direct sampling approach as well as contours based on the IFORM approach will be presented. Both sets of contours are based on the same models for the joint distribution of the environmental variables, i.e., a conditional model where the joint distribution is modelled as a product of a marginal model for one variable and a conditional model for the other. Both the joint modelling of the environmental variables and the different approaches to estimate environmental contours are described in this paper and the results for the provided datasets are shown.


Author(s):  
Finn-Idar Grøtta Giske ◽  
Arnt Fredriksen

Abstract In this paper, long-term extreme response analysis is performed for a straight floating bridge across the Bjørnafjord, using a recently developed inverse first-order reliability method (IFORM) approach. Full integration of the long-term extreme response formulation is also performed for comparison. Two different environmental models are estimated based on a scatter diagram of significant wave height and peak period for the given location. The IFORM method is seen to provide reasonable estimates of the long-term extreme response, at a significantly reduced computational effort.


Author(s):  
Finn-Idar G. Giske ◽  
Bernt Johan Leira ◽  
Ole Øiseth

In this paper, the first-order reliability method (FORM) found in connection with structural reliability analysis is first used in an inverse manner to efficiently obtain an approximate solution of the full long-term extreme response of marine structures. A new method is then proposed where the second-order reliability method (SORM) is used to improve the accuracy of the approximation, resulting in an inverse SORM (ISORM) approach. This method is compared with exact results obtained using full numerical integration. The new method is seen to achieve significantly improved accuracy, yet keep the number of required short-term response analyses within acceptable levels.


Author(s):  
Arne Bang Huseby ◽  
Erik Vanem ◽  
Bent Natvig

The environmental contour concept is often applied in marine structural design in conjunction with the Inverse First Order Reliability Method (IFORM). It allows for the great advantage of considering the environmental loads independently of the structural response. In this way, design sea states may be identified along the contour and time consuming response calculations are only needed for a limited set of design sea states. The traditional way of establishing such environmental contour lines is by applying the Rosenblatt transformation and identify the circle (in two dimensions) with radius equal to the reliability index βr The points along this circle are then transformed back to the original environmental space, specifying the closed contour. In this paper, an alternative approach for establishing the environmental contour lines in the original environmental space is proposed, eliminating the need for any transformations. This approach utilizes Monte Carlo simulations of the joint environmental model and is generally found to perform well. Advantages are that it yields a more precise interpretation and allows for more flexible modelling of the environmental parameters. This makes it easier to modify the environmental models to account for effects such as climate change if this is desired. In addition, possible over- or underestimation of failure probabilities due to the Rosenblatt transformation inherent in the traditional approach can be avoided with the proposed method.


Materials ◽  
2021 ◽  
Vol 14 (8) ◽  
pp. 1820
Author(s):  
Mohamed El Amine Ben Seghier ◽  
Behrooz Keshtegar ◽  
Hussam Mahmoud

Reinforced concrete (RC) beams are basic elements used in the construction of various structures and infrastructural systems. When exposed to harsh environmental conditions, the integrity of RC beams could be compromised as a result of various deterioration mechanisms. One of the most common deterioration mechanisms is the formation of different types of corrosion in the steel reinforcements of the beams, which could impact the overall reliability of the beam. Existing classical reliability analysis methods have shown unstable results when used for the assessment of highly nonlinear problems, such as corroded RC beams. To that end, the main purpose of this paper is to explore the use of a structural reliability method for the multi-state assessment of corroded RC beams. To do so, an improved reliability method, namely the three-term conjugate map (TCM) based on the first order reliability method (FORM), is used. The application of the TCM method to identify the multi-state failure of RC beams is validated against various well-known structural reliability-based FORM formulations. The limit state function (LSF) for corroded RC beams is formulated in accordance with two corrosion types, namely uniform and pitting corrosion, and with consideration of brittle fracture due to the pit-to-crack transition probability. The time-dependent reliability analyses conducted in this study are also used to assess the influence of various parameters on the resulting failure probability of the corroded beams. The results show that the nominal bar diameter, corrosion initiation rate, and the external loads have an important influence on the safety of these structures. In addition, the proposed method is shown to outperform other reliability-based FORM formulations in predicting the level of reliability in RC beams.


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