The Role of Extreme Wind Events in the Structural Design of Tall- and Super-tall Buildings

Stefano Cammelli Head of Wind Engineering BMT Fluid Mechanics Teddington, UK scammelli@bmtfm.com Stefano received his civil engineering degree from the University of Genoa. He is currently Head of Wind Engineering at BMT Fluid Mechanics.

Leighton Aurelius Line Manager BMT Fluid Mechanics Teddington, UK laurelius@bmtfm.com Leighton received his aeronautical engineering degree From the University of Sydney. He is currently a Line Manager within the Wind Engineering Group of BMT Fluid Mechanics.

Summary As highlighted by the Council on Tall Buildings and Urban Habitat (CTBUH) [1], at the turn of the millennium there were approximately 250 tall buildings with height in the excess of 200 m across the globe: the projections for the end of 2015 indicate there will likely be more than 1000. Similarly, the number of ‘super-tall’ buildings (taller than 300 m) has more than tripled during the course of the last decade and ‘mega-tall’ buildings (taller than 600 m) are appearing on the map. The dynamic response of such tall structures to external natural forces such as the ones generated by gusty winds and – perhaps even more importantly – the ones generated by aerodynamic features such as vortex shedding, has the potential to strongly influence the choice as well as the design of the structure’s lateral-stability systems: it is within this context that an accurate understanding of the nature, strength and directionality of the extreme wind events within the region of interest is particularly vital in assisting designers to deliver commercially and financially viable schemes. This technical paper will examine the challenges and inherent limitations which wind engineers are often confronted with during the analysis of wind records; uncertainties in the prediction of site-specific design wind speeds as well as their impact on the assessment of key wind-induced load effects such as accelerations and base overturning moments will be discussed through a detailed case study.

Keywords: Wind engineering; climatology; wind loading; vortex shedding; wind tunnel testing; tall buildings.

1. Introduction Wind tunnel technology is nowadays widely utilised in the evaluation of the structural performance of tall and super-tall buildings under wind loading excitation. In this process wind tunnel data – which can be obtained employing different techniques (e.g. high-frequency force balance (HFFB, see also [2]); simultaneous pressure integration (SPI); or aeroelastic technique) – need to be appropriately combined with information about the wind climate specific for the project site. This information is in some cases fully provided by codes of practice (e.g. Eurocode 1 [3] and related National Annexes) but, when it is not, it needs to be determined by the wind specialists through a thorough extreme value analysis of long-term wind records, often obtained from an airfield or a weather station within the region of interest. It cannot be denied that this particular process of accurately estimating design wind speeds (that is strength and directionality of the extreme wind events) is probably one of the biggest challenge for wind engineers: quality of surface data coming from multiple weather stations is key and supplementary information coming from weather balloons and / or more sophisticated mesoscale numerical modelling techniques often need to be utilised.

Let’s assume for instance that a structural engineering firm is working on a tall building scheme and, as a result of their preliminary estimates, for the most critical direction for stability they are expecting a peak wind-induced bending moment at foundation level of the order of 200 MNm. Now, if the outcome of the wind tunnel study is for instance 220 MNm then the design has the potential to almost go back to the drawing board; if, instead, the result is 180 MNm the design could easily

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go through a value-engineering process. This may sound rather extreme but, in the experience of the authors of this technical paper, this scenario is not that untypical – the key question here is: is this at all sensible? How accurate are the design wind speeds that are used in the post-processing of the acquired wind tunnel data? How does any uncertainty in the actual wind records propagates through the Alan G. Davenport Wind Loading Chain [4]? It is the aim of the next sections of this technical paper to try to answer these questions and shed some light on the role of extreme wind events in the structural design of tall buildings.

2. Wind climate

2.1 General There are different types of storm mechanisms that can develop near the surface of our planet; the most relevant ones for the structural design of the lateral-stability system of tall & super-tall buildings are: monsoons, tropical cyclones (typhoon and hurricanes) and extra-tropical depressions (gales and fronts). Amongst these, tropical cyclones have the potential to generate some of the strongest winds experienced on Earth: these types of storms typically form over large masses of warm water at latitudes approximately ranging between 10° to 30° (e.g. South China Sea, south coast of Japan, Gulf of Thailand, Coral Sea, north coast of Australia, Bay of Bengal, Gulf of Mexico, Caribbean Sea and west coast of Mexico).

2.2 Extreme Value Analysis

2.2.1 Background

The prediction of design wind speeds from long-term wind records is a subset of “wind engineering” that has a long history. Early approaches to this typically drew on the work of Gumbel [5], and it has not been until recent times that the wind engineering industry has moved away from these more simple methods into more sophisticated approaches that consider in greater detail the meteorological phenomena behind the different types of storm mechanisms. In recent years, in fact, developments of these analysis methods (most notably by Gomes and Vickery [6], Cook [7] and Harris [8]) have led to improvements in the accuracy of estimates, and more importantly – especially with regard to the work of Gomes and Vickery [6] and Cook et al. [9] – the ability to take into account the specific nature of the storm types at the location of interest.

2.2.2 Typical approach to design wind speed prediction

As a first step one must acquire long-term wind records from weather stations within the region (ideally in excess of 30-years). In recent years this is a relatively straightforward procedure as the US Government (via the National Oceanic and Atmospheric Administration (NOAA) [10]) now provides (free of charge) wind records for over 100,000 stations (see Figure 1).

Fig. 1: Location of NOAA stations worldwide

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In an ideal situation one would consider multiple stations for the analysis, which would allow for an easy identification of any unreliable / spurious data that may exist at one of the stations. This is a rather important exercise as the analysis of different weather stations within the same region of interest can significantly improve the robustness of the statistical dispersion (1/a) of the local wind climate.

An analysis of the local terrain (including topographical features) / building morphology surrounding the anemometer site is subsequently undertaken to “transpose” the wind records to some common reference point (such as open terrain at 10 m above sea level, as it is typically specified in design codes [3]). This of course requires the accurate identification of the anemometer location, which, depending on the country of interest may prove challenging (see Figure 2).

Fig. 2: WMO compliant (left) and non-compliant anemometer (right)

The specific geographic location of the station may lead itself to experiencing more than one type of storm mechanism (e.g. Hong Kong, where extreme wind speeds are driven by large-scale typhoon events, yet the more “day-to-day” winds are driven by monsoonal weather patterns). In these cases the storms associated to these different meteorological events must be separately identified, analysed and combined [6] such that the true probability of exceedance of both storm types can be derived.

Fig. 3: Example of the graphical output of a mixed climate extreme value analysis

Following these steps one would then arrive at transposed time-traces of storm events which represent the main input of the subsequent detailed extreme value analysis.

2.3 Uncertainties in the extreme wind speed analysis process In each of the above steps there is of course the potential for uncertainties, whether from: the nature

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of the sampling of the wind records; the actual anemometer location (nature of the surface roughness around the weather station as well as the height of the instrument itself); the specific type of extreme value analysis adopted.

In the experience of the authors in dealing with numerous meteorological agencies worldwide, it is not that uncommon for storm-traces to be sampled not in a continuous and rigorous manner (e.g. the average wind speed and wind direction of the first / last 2 minutes / 10 minutes of each hour as opposed to true 10-min. mean or true mean-hourly speeds). Non-continuous sampling is particularly concerning especially when operating in regions where the wind climate is dominated by non-stationary events such as thunderstorms. Confusing a true 10-min. mean wind record with a mean-hourly one could lead to over-estimations of the order of approximately +5%. Also, large gaps in the wind speed records (e.g. Gulf War in Kuwait in the 90s or the Cultural revolution in China in the 60s and 70s) as well as rounding in the data reported by the NOAA (the NOAA in fact exclusively deals in miles per hour converted to integers, alluding to some rounding of the actual recorded values) can make the statistical analysis of such data extremely challenging. In the authors’ experience the level of uncertainty associated with the rounding process of the wind records could lead to uncertainties in the design wind speed predictions of the order of approximately ±2-3%.

Incorrect assumptions made about the surrounding terrain can also have an influence on the use of the wind records. For example, if a weather station was located within an area that over time has seen a significant amount of development (i.e. rapidly urbanised areas of China), then the average wind speeds recorded at the weather station are very likely to have reduced in strength with time. As such, it is important to consider the evolution of the urbanisation in any terrain categorisation that is done for the purpose of transposing wind records to a common reference for further analysis. Also, conducting sensitivity analyses to ascertain the impact of uncertainties in the surface roughness classification on the transposition factors is rather important. Uncertainties in the assumptions made for the nature of the surface roughness around the anemometer site could lead to uncertainties of the order of approximately ±8-10%. It should be noted that it is not that uncommon to see anemometers installed on the roof of a meteorological station (see Figure 2), without meeting the WMO standards. This is obviously far from ideal: localised wind speed-ups generated by the close proximity of the instrumentation with the edge of the actual roof can easily lead to over-estimation of the order of approximately +10%.

Lack of proper treatment of different storm mechanisms via an appropriate mixed climate analysis could lead to final uncertainties in design wind speeds of the order of approximately ±5-10%. Finally one can examine the variation between different extreme value analysis methods (see for example Figure 4 which shows the predicted 50-year return period design wind speed for a particular station based on two methods – Method of Independent Storms (MIS) [7] and Lieblein BLUE [11] – showing discrepancies of the order of approximately ±5%).

Fig. 4: Design wind speed prediction via two different analysis methods

Most of the above uncertainties can, in principle, be mitigated: the most critical ones an experienced

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wind engineer is very often left with are those associated with terrain roughness and analysis method. It is therefore fair to say that the overall uncertainty level in the estimation of the basic design wind speeds when starting from wind records at surface level is likely to be in the region of ±10-12%.

3. A case study The building here taken in examination is a prismatic tower approximately 120 m tall with a diamond-shaped cross-section approximately 20 m x 40 m in size.

The lateral stability of the tower is provided by a central reinforced concrete core. The numerically predicted structural frequencies of the three fundamental modes of vibration of the building are: 0.25 Hz, 0.29 Hz and 0.37 Hz, with the first two describing almost pure sway of the structure along the principal axes of the central core (exponent of these mode shapes ~ 1.5) and the third one being torsional.

The surface roughness characterising the area in the immediate vicinity of the structure is z0 ~ 0.3 m. For the purpose of this example, the wind data presented in Figure 4 will be used. The characteristics product (being the ratio of the statistical mode, U, to the statistical dispersion, 1/a) for this specific set of wind records is approximately in the range of 4-5, which is very typical for weather systems driven by monsoonal / synoptic front weather patterns. The result of the MIS method [7] will be used (Vb ~ 21 m/s in z0 = 0.03 m). The transposition factor from 10 m (z0 = 0.03 m) to 120 m / z0 = 0.3 m is approximately 1.3, making the site-specific design wind speed at the top of the building ~ 27 m/s (directionality associated with the extreme wind events will be ignore in this case study).

Figure 5 illustrates the peak static and peak dynamic (1% structural damping) wind base moment acting on the tall building (for the most critical direction for stability) as a function of the mean wind speed at the top of the structure.

Fig. 5: Peak wind base moment vs. mean-hourly wind speed at the top of the building

The results presented in Figure 5 show a relatively high dynamic load augmentation at the 50-yr speed (driven by the vortex-shedding excitation) and a variation of the peak dynamic response with wind speed much steeper than what prescribed in [3] (the yellow dot represents the load at the 50-yr speed multiplied by ‘1.5’, a figure which is approximately 25% lower than the load at the 1700-yr return period speed). Uncertainties in the basic wind speed of the order of say ±10% could in this

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case lead to under- / over-predictions of the peak dynamic cross-wind moments of approximately 35-40%, with rather obvious implications on the actual reliability of the design.

4. Conclusions With designers more and more frequently relying on the output of wind climate analyses for the structural design of tall buildings and, with high-rises becoming taller, lighter and more slender, it is increasingly important to understand the effects that items such as: i) the nature of the sampling of the wind records; ii) the nature of the surface roughness around the weather station; iii) the location, height and type of anemometer; and iv) the specific type of extreme value analysis adopted can have on design wind speed predictions.

Particularly when it comes to dynamically-sensitive structures, even small uncertainties in the prediction of design wind speeds can lead to large differences in design wind loads / wind-induced accelerations, with potentially significant financial / safety implications for the project.

In order to better manage the risk associated with the different uncertainties presented within this technical paper, the following is recommended:

When possible, time-traces of continuous 3-s gust wind speeds should be sourced;

When possible, wind records from different weather stations should be sourced;

The source of wind records should always be thoroughly checked;

In mixed climates, wind records associated with different storm mechanisms should always be separated;

The statistical dispersion of the extreme value analysis predictions should always be checked against regional expectations;

5. References [1] http://www.ctbuh.org/Home/FactsData/TallBuildingsover200m/tabid/2777/language/en-

US/Default.aspx

[2] TSCHANZ T., and DAVENPORT A. G., “The base balance technique for the determination of dynamic wind loads”, Journal of Wind Engineering & Industrial Aerodynamics, Vol. 13, 1983.

[3] EN1991-1-4: Eurocode 1: Actions on Structures – Part 1-4: General actions – Wind Actions.

[4] http://www.iawe.org/about/Wind_Loading_Chain.pdf

[5] GUMBEL E. J., “Statistics of Extremes”, Columbia University Press, New York, 1958.

[6] GOMES L., and VICKERY B.J., “Extreme wind speeds in mixed climates”, Journal of Wind Engineering & Industrial Aerodynamics, Vol. 2, 1978.

[7] COOK N. J., “Towards better estimation of extreme winds”, Journal of Wind Engineering & Industrial Aerodynamics, Vol. 9, 1982.

[8] HARRIS, R. I., “Improvements to the `Method of Independent Storms`”, Journal of Wind Engineering & Industrial Aerodynamics, Vol. 80, 1999.

[9] COOK N. J., HARRIS, R. I., WHITING R., “Extreme wind speeds in mixed climates revisited”, Journal of Wind Engineering & Industrial Aerodynamics, Vol. 91, 2003.

[10] www.noaa.gov

[11] LIEBLEIN J., “Efficient methods of extreme-value methodology”, Report NBSIR 74-602, National Bureau of Standards, Washington, 1974.

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