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where Tp = period at peak frequency in seconds; and H s = signi cant wave height in meters. in .NET Integration qr codes in .NET where Tp = period at peak frequency in seconds; and H s = signi cant wave height in meters.

where Tp = period at peak frequency in seconds; and H s = signi cant wave height in meters. use visual .net qr code iso/iec18004 maker tocompose qr code 2d barcode for .net ISO/IEC 18004:2000 0.99999 0.99995 0.

9999. Environmental Phenomena and Application to Design 100 10 1. Cumulative probability - Weibull scale 0.9995 0.99 visual .

net qr codes 9 0.995 0.99 0.

98 0.95 0.9 0.

8 0.7 0.6 0.

5 0.4 0.3 0.

2 0.1 0.05.

Mean during a year During June August During November January 4 5 6 7 8 910. 30 40 5060. Wind speed (m/sec). Figure 4.2. QR Code ISO/IEC18004 for .

NET Cumulative distribution function for hourly mean wind speed at 10m above mean sea level for the northern North Sea, following Faltinsen (1990).. It is inter esting to note that the highest crest elevation is approximately equal to the signi cant wave height (H s ) for an irregular short-term stationary sea state in visual observations, and the highest individual crest to trough wave height is approximately equal to 1.8H s . The DNV Classi cation Notes 30.

5 also provides much useful information for estimating the long-term wave statistics considering geographical location and storm duration.. 4.4 Winds W .net vs 2010 qr codes ind is a primary metocean parameter that is important to the design of offshore units, for example, during normal operations.

The structure must withstand the forces exerted by the wind, and this depends not only on the structural characteristics such as windage area but also on the speed and direction of the wind. For design, extreme wind speeds for speci ed return periods must be obtained and are speci ed with averaging times ranging from 3 seconds (i.e.

, an extreme gust value) to 24 hours, for example. The speeds are usually estimated at a standard height of 10m above mean sea level, with corrections to more speci c values at other heights. In addition, the spectra of uctuating wind gusts are necessary because wind gusts can excite resonant oscillations of offshore structures (Faltinsen 1990).

For example, slow-drift horizontal motions of moored structures can be caused by wind gust. Also, wind can lead to phenomena such as vortex shedding, together with associated vibrations in some instances, including are tower. Figure 4.

2 shows the cumulative distribution function for hourly mean wind speed at 10m above mean sea level for wind data from the northern North Sea (Faltinsen. 4.4 Winds Table 4.2. visual .

net qr barcode Relationship between 50-year return period wind speed and extreme wind speeds at other return periods (HSE 1989a). N (years) VN /V50 2 0.75 5 0.83 10 0.88 20 0.93 50 1.00 100 1.05 200 1.11 500 1.17 1000 1.23 Notes: (1) .net framework qr-codes N = return period; (2) VN = N year return speed; (3) V50 = 50-year return speed; and (4) these values were obtained from VN = 0.71(1 + 0.

106 ln N)V50 .. 1990). Figu re 4.2 shows that the extreme wind speed with the 100-year return period is about 41m/s.

Table 4.2 shows the relationship between the extreme 50-year return period wind speed used for design in some cases, and the extreme wind speeds at other return periods. Table 4.

3 indicates 100-year return period design wind speeds for UK waters. In the absence of speci c wind data, the UKOOA FPSO design guidelines applicable in UK waters recommend certain design wind speeds depending on the areas involved; see Table 4.4.

Wind speeds for the 10,000-year return period are approximately 16 percent greater than the speed for the 100-year return period indicated in Table 4.4. The UKOOA guidelines suggest the use of NORSOK Standard N003 (NORSOK 1999) formulations to describe the wind-speed variation with the height above sea level.

In determining the design-wind and design-wave actions, it is necessary to know the information on the variation of winds with height above sea level, the direction that the wind blows, and the joint probability between waves and winds. In this regard, Table 4.4 indicates a simpli ed picture representing the relationship among signi cant wave height, wave period, and wind speed for open seas in the North Atlantic and North Paci c (Lee et al.

1985). The wind force on each part of the FPSO may be estimated from the following: F = 0.0625AV2 Cs , (4.

5). where F = w QR-Code for .NET ind surface force in kgf; A= projected area in m2 ; V = wind speed in m/s; and Cs = shape coef cient as de ned in Table 4.5.

In API RP 2FP1 (API 1991), two methods are suggested to evaluate the wind effects: (a) as a constant applied value where the wind speed is taken as the extreme 1-minute mean wind speed; or (b) as a uctuating force based on the extreme 1-hour average velocity together with a time-variant component calculated from a suitable wind-gust spectrum. Formulae are also provided to estimate the wind forces. The DNV Classi cation Notes 30.

5 (DNV 1991) suggests taking the reference averaging period of wind as 10 minutes and the reference height as 10m above sea level. The average wind speed and its pro le with height may then be estimated using a closed-form formula..

Table 4.3. Illustrative 100-year return period design wind speeds for UK waters (UKOOA 2002).

Wind speed Visual Studio .NET QR-Code 1-hour average 10-min. average Central North Sea 37 m/s 40 m/s Northern North Sea 38 m/s 41 m/s West of Shetlands 40 m/s 43 m/s.

North Atlan tic Sustained wind speed (knots)(a) Range 0 6 7 10 11 16 17 21 22 27 28 47 48 55 56 63 >63 3 8.5 13.5 19 24.

5 37.5 51.5 59.

5 >63 0.70 6.80 23.

70 27.80 20.64 13.

15 6.05 1.11 0.

05 3.3 12.8 5.

0 14.8 6.1 15.

2 8.3 15.5 9.

8 16.2 11.8 18.

5 14.2 18.6 18.

0 23.7 7.5 7.

5 8.8 9.7 12.

4 15.0 16.4 20.

0 1.30 6.40 15.

50 31.60 20.94 15.

03 7.00 1.56 0.

07 Mean Percentage probability of sea state Range(b) Most probable(c) Percentage probability of sea state Modal wave period(s) North Paci c Modal wave period(s) Range(b) 5.1 14.9 5.

3 16.1 6.1 17.

2 7.7 17.8 10.

0 18.7 11.7 19.

8 14.5 21.5 16.

4 22.5 Most probable(c) 6.3 7.

5 8.8 9.7 12.

4 15.0 16.4 20.

0. Table 4.4. .

net framework qr bidimensional barcode Annual sea-state occurrences in the North Atlantic and North Paci c (Lee et al. 1985).
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