Reliability of Offshore Foundations—State of the Art

Wu, Tien H.; Tang, Wilson H.; Sangrey, Dwight A.; Baecher, Gregory B.

doi:10.1061/(asce)0733-9410(1989)115:2(157)

Cited by 46 publications

(9 citation statements)

References 26 publications

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“…The laboratory testing and field measurements are used to estimate the inputs for the model. In this estimation process, different sources of uncertainty of unknown magnitude are introduced (Wu et al, 1989). These parameters then have to be modelled as stochastic variables with a certain statistical distribution.…”

Section: Input Uncertainties For the Scd Modelmentioning

confidence: 99%

Reliability analysis of offshore wind turbine foundations under lateral cyclic loading

Zorzi¹,

Mankar

Velarde

et al. 2020

Wind Energ. Sci.

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Abstract. The design of foundations for offshore wind turbines (OWTs) requires the assessment of long-term performance of the soil–structure interaction (SSI), which is subjected to many cyclic loadings. In terms of serviceability limit state (SLS), it has to be ensured that the load on the foundation does not exceed the operational tolerance prescribed by the wind turbine manufacturer throughout its lifetime. This work aims at developing a probabilistic approach along with a reliability framework with emphasis on verifying the SLS criterion in terms of maximum allowable rotation during an extreme cyclic loading event. This reliability framework allows the quantification of uncertainties in soil properties and the constitutive soil model for cyclic loadings and extreme environmental conditions and verifies that the foundation design meets a specific target reliability level. A 3D finite-element (FE) model is used to predict the long-term response of the SSI, accounting for the accumulation of permanent cyclic strain experienced by the soil. The proposed framework was employed for the design of a large-diameter monopile supporting a 10 MW offshore wind turbine.

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Section: Input Uncertainties For the Scd Modelmentioning

confidence: 99%

Reliability analysis of offshore wind turbine foundations under lateral cyclic loading

Zorzi¹,

Mankar

Velarde

et al. 2020

Wind Energ. Sci.

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“…The theoretical application of a random field in geotechnical engineering was popularised in an earlier paper by Vanmarcke (1977). Other seminal contributions were also made by pioneers such as Wilson Tang (Tang 1984;Lacasse, Liu, and Nadim 2017), Tien H Wu (Wu et al 1989(Wu et al , 1996; Baecher and Christian 2019), Harr (1987), Lacasse and Nadim (1996), Gregory Baecher and John Christian (Baecher 1987;Baecher and Christian 2003), Herbert Einstein (Einstein and Baecher 1983;Einstein et al 1996), and many others. The author is unable to do even partial justice in this cursory overview of more than five decades of work in trying to coax data that are 100% accurate (within measurement limits) to say something useful about the unknown state of the ground between measured locations.…”

Section: Generic Databasesmentioning

confidence: 99%

The story of statistics in geotechnical engineering

Phoon

2019

Georisk: Assessment and Management of Risk for Engineered Syste

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The story of statistics in geotechnical engineering can be traced to Lumb's classical Canadian Geotechnical Journal paper on "The Variability of Natural Soils" published in 1966. In parallel, the story of risk management in geotechnical engineering has progressed from design by prescriptive measures that do not require site-specific data, to more refined estimation of site-specific response using limited data from site investigation as inputs to physical models, to quantitative risk assessment (QRA) requiring considerable data at regional/national scales. In an era where data is recognised as the "new oil", it makes sense for us to lean towards decision making strategies that are more responsive to data, particularly if we have zettabytes coming our way. In fact, we already have a lot of data, but the vast majority is shelved after a project is completed ("dark data"). It does not make sense to reduce one zettabyte to a few bytes describing a single cautious value. It does not make sense to expect big data to be precise and to fit a particular favourite physical model as demanded by the classical deterministic world view. This paper advocates the position that there is value in data of any kind (good or not so good quality, or right or wrong fit to a physical model) and the challenge is for the new generation of researchers to uncover this value by hearing what data have to say for themselves, be it using probabilistic, machine learning, or other data-driven methods including those informed by physics and human experience, and to re-imagine the role of the geotechnical engineer in an immersive environment likely to be imbued by machine intelligence.

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“…Laboratory testing and field measurements are used in order to estimate the inputs for the model. In this estimation process different sources of uncertainty of unknown magnitude are introduced (Wu et al, 1989). These parameters then have to be modelled as stochastic variables with a certain statistical distribution.…”

Section: Input Uncertainties For the Scd Modelmentioning

confidence: 99%

Reliability analysis of offshore wind turbine foundations under lateral cyclic loading

Zorzi¹,

Mankar²,

Velarde³

et al. 2019

Preprint

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Abstract. The design of foundations for offshore wind turbines (OWT) requires the assessment of the long-term performance of the soil–structure-interaction (SSI) which is subjected to a large number of cyclic loadings. In terms of serviceability limit state (SLS), it has to be ensured that the foundation does not exceed the operational tolerance prescribed by the wind turbine manufacturer throughout its lifetime. This work aims at developing a probabilistic approach along with a reliability framework with emphasis on verifying the SLS criteria in terms of maximum allowable rotation during an extreme cyclic loading event. This reliability framework allows the quantification of uncertainties in soil properties, in the constitutive soil model for cyclic loadings and extreme environmental conditions and verifies that the foundation design meets a specific target reliability level. A 3D finite element (FE) model is used to predict the long-term response of the SSI accounting for the accumulation of permanent cyclic strain experienced by the soil. The proposed framework is employed for the design of a large diameter monopile supporting a 10 MW offshore wind turbine.

show abstract

Reliability of Offshore Foundations—State of the Art

Cited by 46 publications

References 26 publications

Reliability analysis of offshore wind turbine foundations under lateral cyclic loading

Reliability analysis of offshore wind turbine foundations under lateral cyclic loading

The story of statistics in geotechnical engineering

Reliability analysis of offshore wind turbine foundations under lateral cyclic loading

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