Civil Engineering Reference
In-Depth Information
Thus, if the annual maximum is being considered, then the return period is measured in
years. Thus, a 50-year return period wind speed has a probability of exceedence of 0.02
(1/50) in any 1 year. It should not be interpreted as recurring regularly every 50 years.
The probability of a wind speed, of given return period, being exceeded in a lifetime of a
structure is discussed in Section 2.5.3.
2.2.3
Separation by storm type
In Chapter 1, the various types of wind storm that are capable of generating winds strong
enough to be important for structural design were discussed. These different event types
will have different probability distributions and therefore should be statistically analysed
separately; however, this is usually quite a difficult task as weather bureaus or
meteorological offices do not normally record the necessary information. If anemograph
records such as those shown in Figures 1.5 and 1.7 are available, these can be used for
identification purposes—although this is a time-consuming and painstaking task!
The relationship between the combined return period,
R
c
for a given extreme wind
speed due to winds of either type and for those calculated separately for storm types 1
and 2 (
R
1
and
R
2
) is:
(2.3)
Equation (2.3) relies on the assumption that exceedence of wind speeds from the two
different storm types is an independent event.
2.2.4
Simulation methods for tropical cyclone wind speeds
The winds produced by severe tropical cyclones also known as 'hurricanes' and
'typhoons' are the most severe on earth (apart from those produced by tornadoes which
affect very small areas). However, their infrequent occurrence at particular locations
often makes the historical record of recorded wind speeds an unreliable predictor for
design wind speeds. An alternative approach, which gained popularity in the 1970s and
early 1980s, was the simulation or 'Monte Carlo' approach, introduced originally for
offshore engineering by Russell (1971). In this procedure, satellite and other information
on storm size, intensity and tracks are made use of to enable a computer-based simulation
of wind speed (and in some cases direction) at particular sites. Usually, established
probability distributions are used for parameters such as central pressure and radius to
maximum winds. A recent use of these models is for damage prediction for insurance
companies. The disadvantage of this approach is the subjective aspect resulting from the
complexity of the problem. Significantly varying predictions could be obtained by
adopting different assumptions. Clearly whatever recorded data that are available should
be used to calibrate these models.
