The Frøya database and maritime boundary layer wind description

Andersen, Odd Jan; Løvseth, Jørgen

doi:10.1016/j.marstruc.2006.07.003

Cited by 45 publications

(24 citation statements)

References 7 publications

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“…It should be noted that the coefficient C y u = 12.5 given in Table 5 for the study of Toriumi et al [40] is the value estimated by fitting the Davenport Model to the data provided in their research article. The coherence measured by Andersen and Løvseth [32] is well approximated by Davenport coherence model but is considerably lower than in any other studies found in the literature with a decay parameter C y u equal to 64. If Equation (15) is applied to the data point provided in Andersen and Løvseth [32], then c 1 = 60 and c 2 = 0.17.…”

Section: Lateral Coherence Of the Longitudinal Wind Fluctuationscontrasting

confidence: 52%

“…The coherence measured by Andersen and Løvseth [32] is well approximated by Davenport coherence model but is considerably lower than in any other studies found in the literature with a decay parameter C y u equal to 64. If Equation (15) is applied to the data point provided in Andersen and Løvseth [32], then c 1 = 60 and c 2 = 0.17. The reason for such a low coherence estimate remains unclear.…”

Section: Lateral Coherence Of the Longitudinal Wind Fluctuationscontrasting

confidence: 52%

“…The equation used by Andersen and Løvseth [32] to estimate the turbulence intensity from the Frøya database is:…”

Section: The Frøya Wind Spectrummentioning

confidence: 99%

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Measurements of Surface-Layer Turbulence in a Wide Norwegian Fjord Using Synchronized Long-Range Doppler Wind Lidars

et al. 2017

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Three synchronized pulsed Doppler wind lidars were deployed from May 2016 to June 2016 on the shores of a wide Norwegian fjord called Bjørnafjord to study the wind characteristics at the proposed location of a planned bridge. The purpose was to investigate the potential of using lidars to gather information on turbulence characteristics in the middle of a wide fjord. The study includes the analysis of the single-point and two-point statistics of wind turbulence, which are of major interest to estimate dynamic wind loads on structures. The horizontal wind components were measured by the intersecting scanning beams, along a line located 25 m above the sea surface, at scanning distances up to 4.6 km. For a mean wind velocity above 8 m·s −1 , the recorded turbulence intensity was below 0.06 on average. Even though the along-beam spatial averaging leads to an underestimated turbulence intensity, such a value indicates a roughness length much lower than provided in the European standard EN 1991-1-4:2005. The normalized spectrum of the along-wind component was compared to the one provided by the Norwegian Petroleum Industry Standard and the Norwegian Handbook for bridge design N400. A good overall agreement was observed for wave-numbers below 0.02 m −1 . The along-beam spatial averaging in the adopted set-up prevented a more detailed comparison at larger wave-numbers, which challenges the study of wind turbulence at scanning distances of several kilometres. The results presented illustrate the need to complement lidar data with point-measurement to reduce the uncertainties linked to the atmospheric stability and the spatial averaging of the lidar probe volume. The measured lateral coherence was associated with a decay coefficient larger than expected for the along-wind component, with a value around 21 for a mean wind velocity bounded between 10 m·s −1 and 14 m·s −1 , which may be related to a stable atmospheric stratification.

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Section: Lateral Coherence Of the Longitudinal Wind Fluctuationscontrasting

confidence: 52%

Section: Lateral Coherence Of the Longitudinal Wind Fluctuationscontrasting

confidence: 52%

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Measurements of Surface-Layer Turbulence in a Wide Norwegian Fjord Using Synchronized Long-Range Doppler Wind Lidars

et al. 2017

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“…The 3P frequency results from shadowing effects of the blade on the tower caused by a drop in the upstream wind velocity in the vicinity of the tower as each of the three blades passes in front of the tower. An example of the dynamic wind loading is also shown in Figure 1, utilising the Frøya wind spectrum (Andersen and Løvseth, 2006). In addition, the dynamic wave loads are modelled using the Pierson and Moskowitz (1964) spectrum, which is considered appropriate for UK North Sea locations.…”

Section: Dynamic Considerations For Designing Offshore Wind Turbinesmentioning

confidence: 99%

Dynamics of offshore wind turbines supported on two foundations

Bhattacharya

Cox

Lombardi

et al. 2013

Proceedings of the Institution of Civil Engineers - Geotechnica

105

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Offshore wind turbines are currently considered as a reliable source of renewable energy in the UK. These structures, owing to their slender nature, are dynamically sensitive at low frequencies, the first modal frequency of the system (less than 1 Hz) being very close to that of the excitation frequencies. The majority of operational offshore wind turbines situated in UK waters are founded on monopiles in water depths up to 30 m. For future development rounds where water depths are up to 70 m, alternative foundation arrangements are needed. To date there have been no long-term observations of the performance of these relatively novel structures. Monitoring of a limited number of offshore wind turbines has indicated a departure of the system dynamics from the design requirements. This paper summarises the results from a series of 1:100 scale tests of a V120 Vestas turbine supported on two types of foundation: monopiles and tetrapod suction caissons. The test bed used consisted of kaolin clay and sand. Up to 1 . 25 million loading cycles were applied to the scaled model, and the dynamic properties of the system were monitored. The results provide an insight into the long-term performance. Some interesting dynamic soil-structure interaction issues are identified and discussed.

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“…Thus, they are mainly dependent on the size of the wind eddies and surface roughness, but are also influenced by any upstream objects. In this study, the Frøya coherence spectrum (Andersen and Løvseth 2006) Coh( , ω n ) is used for calculating both along-and across-wind components between any two points (x1, y1, z1) and (x2, y2, z2) as…”

Section: Calculating the Turbulence Wind Componentsmentioning

confidence: 99%

Investigations of a practical wind-induced fatigue calculation based on nonlinear time domain dynamic analysis and a full wind-directional scatter diagram

Jia¹

2013

Ships and Offshore Structures

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To cite this article: Junbo Jia (2014) Investigations of a practical wind-induced fatigue calculation based on nonlinear time domain dynamic analysis and a full wind-directional scatter diagram, Ships and Offshore Structures, 9:3, 272-296, DOI: 10.1080/17445302.2013 Ships and Offshore Structures, 2014 Vol. 9, No. 3, 272-296, http://dx.doi.org/10.1080/17445302.2013 Investigations By performing the nonlinear time domain dynamic analysis, and calculating the wind-induced fatigue using the procedure presented by this author, this paper investigates the influences from different drag coefficient specification systems. The study shows that the drag coefficient specified by Norsok is more conservative than that of the DnV system, mainly due to Norsok's rough categories of the drag coefficient values varying with the Reynolds number. Furthermore, the effects of time increment step length, time duration for simulation as well as the flexibility of wind strut-main flare boom connections are also investigated. By comparing the fatigue life from dynamic analysis with its static counterpart (without taking into account the inertia effects of the structural and non-structural installations), the significance of the contribution from the structure's dynamic response can be identified. It is suggested that the modelling of secondary structures such as a flare and vent line must be carefully considered, as this may significantly influence fatigue damage calculation. In addition, the effects of gravity on the structure's fatigue damage are also studied and the conclusion challenges traditional engineering practice.Finally, non-Gaussian responses are discussed through the statistical investigation of the local responses. The wind fatigue calculation procedure presented can be widely adopted for the similar study on high-rise tubular structures.

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The Frøya database and maritime boundary layer wind description

Cited by 45 publications

References 7 publications

Measurements of Surface-Layer Turbulence in a Wide Norwegian Fjord Using Synchronized Long-Range Doppler Wind Lidars

Measurements of Surface-Layer Turbulence in a Wide Norwegian Fjord Using Synchronized Long-Range Doppler Wind Lidars

Dynamics of offshore wind turbines supported on two foundations

Investigations of a practical wind-induced fatigue calculation based on nonlinear time domain dynamic analysis and a full wind-directional scatter diagram

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