Modified Inverse First Order Reliability Method (I-FORM) for Predicting Extreme Sea States.

Eckert-Gallup, Aubrey Celia

doi:10.2172/1157595

Cited by 7 publications

(4 citation statements)

References 23 publications

(33 reference statements)

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“…To characterise both the sites of interest and representative design load metrics, the WEC Design Response Toolbox (WDRT) [10] was used. For the former, the WDRT includes a routine for creating environmental contours of extreme sea states based on the principle components analysis (PCA) methodology [11], allowing the characterization of the joint probability distribution of sea state variables of interest. The resulting samples can be used for numerical or physical model simulations analysing the design response of WECs characterized through complementary cumulative distribution functions [12].…”

Section: Wec Design Loadsmentioning

confidence: 99%

Classification systems for wave energy resources and WEC technologies

Neary¹,

Coe²,

Cruz³

et al. 2018

Int. J. Mar. Ene.

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Classification systems for wave energy resources and wave energy converter (WEC) technologies could provide similar benefits to those for the wind energy industry: resource classification facilitating reconnaissance studies and project planning at both regional and national scales; and WEC classification streamlining and reducing costs of WEC device design and manufacturing. In the present study, a classification system for U.S. wave resources is used to investigate the feasibility of WEC classification. Wave spectra inputs from three wave energy resource classes delineated in this system are used to derive distributions of optimized WEC design scaling factors, as well as WEC design responses. Preliminary results indicate that a single standard WEC design class could serve within a given resource class, and corresponding regional wave climate, due to distinct wave energy distributions and concentrations of energy within partitioned period bands for each resource class. The WEC response to extreme loads was found to vary considerably within the most energetic of the resource classes examined, suggesting the need for these standard design classes to meet structural design requirements based on the upper limits of load response within a given resource class. However, the observed load metric variation is lower than the inter-region resource variations.

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Section: Wec Design Loadsmentioning

confidence: 99%

Classification systems for wave energy resources and WEC technologies

Neary¹,

Coe²,

Cruz³

et al. 2018

Int. J. Mar. Ene.

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“…Industry standards for offshore structures such as those published by API [4] and IEC [25] prescribe methods for determining wind and wave conditions from independent distributions. However, many papers have studied the effect of wind and wave correlation through FORM (First Order Reliability Method) [26] and IFORM (Inverse First Order Reliability Method) [27][28][29] and have highlighted that the assumption of independence is conservative and unrealistic under actual offshore conditions. The IWWA framework includes another approach, referred to as the IWWA2 procedure [22], which uses joint probability models to estimate wind speed and wave height at design return periods.…”

Section: General Configurations and Assumptionsmentioning

confidence: 99%

“…The MRP is then used as a single parameter characterization of the aligned wind and wave loading. It should be noted that in principle other methods for parameterizing the loading intensity, such as the inverse first order reliability method (IFORM) [27][28][29], could be used within the directional IWWA context, and that independent models for the wind and wave intensity are used here to simplify the analysis and presentation of directional effects and keep the paper focused on the directionality. direction and intensity, the following procedure is performed to complete the directional IWWA analysis.…”

Section: Directional Iwwa Analysismentioning

confidence: 99%

Directional effects on the reliability of non-axisymmetric support structures for offshore wind turbines under extreme wind and wave loadings

Wei

Arwade

Myers

et al. 2016

Engineering Structures

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In comparison with monopile support structures commonly used for offshore wind turbines (OWTs) in shallow water, fixed bottom support structures for deeper water such as jackets tend to lack axisymmetry and have different capacities when loaded in different directions. Design of such a structure may therefore benefit from consideration of the directional characteristics of loading. This paper focuses on a rational and efficient approach to assess the structural safety of jacket type OWTs under directionally dependent extreme environmental loads. The Incremental Wind-Wave Analysis (IWWA) framework is reviewed and used to assess capacity of jacket-type OWTs under directional environmental wind-wave conditions. The approach uses static pushover analysis of OWT jackets subject to combined wind and wave load patterns corresponding to increasing mean return periods (MRPs). The wind and wave conditions are calculated independently and assumed to occur simultaneously. The loading direction and jacket orientation are both included in the analysis. To illustrate the approach, metocean conditions at different sites along the U.S. Atlantic coast are obtained from the historical database of the National Oceanic and Atmospheric Administration (NOAA) Data Buoy Center. Two models are introduced for estimating the occurrence probability of wave direction, one of which directly uses the frequency of wave directions and the other uses a Gaussian kernel to represent the range of wave directions represented by given directional spectra. For each combination of wind-wave direction and structural orientation, an IWWA analysis gives the capacity in terms of the MRP conditions leading to formation of a fully developed plastic mechanism in the jacket. Those capacities, convolved with MRP models for loading intensity, yield direction-dependent structural reliabilities, and when those reliabilities are convolved with the probability density function for loading direction, a total failure probability is obtained that accounts for wave directionality. Example analyses are conducted for an OWT supported by a four-leg jacket adapted from a design published as part of the European Union UpWind Project. Effects of extreme loading directionality, structural orientation, structural geometry and site specification on the ultimate capacity of the jacket are carefully discussed.

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“…It provides developers, not only with an estimate of the largest significant wave height, but also extreme sea states at other significant wave heights with energy periods that could compromise the survival of a marine structure or service vessel. The modified IFORM used in this study (Eckert-Gallup et al 2014) improves the original fitting method by implementing principal components analysis.…”

Section: Cumulative Distributions Ofmentioning

confidence: 99%

Characterization of U.S. Wave Energy Converter (WEC) Test Sites: A Catalogue of Met-Ocean Data.

Dallman¹,

Neary²

2014

Self Cite

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This report presents met-ocean data and wave energy characteristics at three U.S. wave energy converter (WEC) test and potential deployment sites. Its purpose is to enable the comparison of wave resource characteristics among sites as well as the selection of test sites that are most suitable for a developer's device and that best meet their testing needs and objectives. It also provides essential inputs for the design of WEC test devices and planning WEC tests, including the planning of deployment and operations and maintenance. For each site, this report catalogues wave statistics recommended in the (draft) International Electrotechnical Commission Technical Specification (IEC 62600-101 TS) on Wave Energy Characterization, as well as the frequency of occurrence of weather windows and extreme sea states, and statistics on wind and ocean currents. It also provides useful information on test site infrastructure and services.

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Modified Inverse First Order Reliability Method (I-FORM) for Predicting Extreme Sea States.

Cited by 7 publications

References 23 publications

Classification systems for wave energy resources and WEC technologies

Classification systems for wave energy resources and WEC technologies

Directional effects on the reliability of non-axisymmetric support structures for offshore wind turbines under extreme wind and wave loadings

Characterization of U.S. Wave Energy Converter (WEC) Test Sites: A Catalogue of Met-Ocean Data.

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