By Zoheb Nasir | November 19, 2018

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How can insurers assess the vulnerability of complex and non-conventional structures and quantify a risk for which— unlike regular buildings—insurance claims are scarce? The more complex and unconventional a structure is, the more difficult it is to evaluate risk because there is so little claims data or event experience to validate estimates. And conventional building codes and damage surveys don’t help, as severe physical damage is not common.

Computational Fluid Dynamics (CFD) is a handy tool for solving problems like this. It is not a feature of AIR’s models, but a tool that we find increasingly useful for specific tasks. In recent years, rapid advancements in computational technology such as multicore processing and large data storage—along with decreasing costs—have enabled computational modeling efforts to flourish alongside traditional physical simulation techniques.

What Is CFD?

CFD employs algebraic equations to simulate the flow of fluids (gases or liquids) and their interaction with structures or surfaces. Fluid flows can be many things, such as meteorological phenomena, environmental hazards, processes in the human body, or—of particular interest to us—the interaction of structures with the air or water surrounding them. Civil engineers, for example, can use CFD to study the flow of air around buildings without having to use costly wind tunnels. In addition to this, one big advantage of CFD over wind tunnel testing is the full-scale analysis. For example, if someone has adequate information about a particular tornado scenario (wind speed, Enhanced Fujita scale rating, core radius, etc.) and the city/cities it affected on its pathway, one can easily mimic the exact scenario and compute the damage from the CFD runs.

Whenever practical analysis involving site-specific engineering is required, CFD has become an indispensable tool. It can be efficiently deployed to develop a database of wind load and pressure distribution for portfolio-specific risks. The insights gleaned from these representative risks can be used to augment vendor models.

Complex Structures

With the more widespread construction of tall buildings with complex exterior shapes, it becomes necessary to understand the wind/structure interaction as well as the building response under the influence of high intensity wind speeds. If a design results in too much top-floor acceleration, for example, and upper level suites exceed occupant comfort level and become unusable, there will be indirect losses in terms of business interruption (BI). With the proper knowledge of CFD and adequate experience in designing tall buildings, one can easily analyze the wind impact over the structure using either aerodynamic or aeroelastic analysis. Once the building response is obtained, it can be easily converted to occupant comfort, as the two are correlated and are in turn directly related to BI.

Figure 1
Figure 1. Wind vortices and pressure distribution associated with the Empire State Building in New York City and wind streamlines and pressure distribution at the Willis Tower in Chicago. (Source: AIR)

The key to satisfying the design requirements for skyscrapers such as this is employing shape modification features to break the correlation of cross-wind vortices. For example, a combination of tapering and rotating forms has been found to be an effective mitigation feature in reducing the wind-induced motion. Similar mitigation strategies such as softened corners, set-backs, varied cross-sections, and bleed slots at edges have historically been adopted in tall buildings around the world, among them iconic structures such as the Empire State Building in New York City and the Willis Tower in Chicago.

Understanding features such as these and analyzing their relative impact upon the overall performance of a building helps to better quantify the underlying risk. For example, insight into the relative vulnerabilities of different components can be obtained by performing CFD simulation of a structure, obtaining the surface pressure coefficient distribution of the localized hazard, and making a comparison with typical box-type structures where data are available.

Other Applications

CFD is also useful for studying the aerodynamics of large and non-conventional facilities, including sports stadiums and other wide-span roofs, manufacturing facilities, oil and gas refineries, turbines, towers, and so forth. AIR used CFD in a study that looked into how the size of a home impacts its vulnerability to hurricane winds, for example. It was also employed for a study of warehouses with large square footage and complex roof geometries, which showed that as warehouse size increases, the relative pressure coefficient decreases—reducing the roof’s vulnerability.

Figure 2
Figure 2. The mean pressure distribution for a small industrial building with a complex roof. (Source: AIR)

Other applications of CFD include assessing the impact of explosions in densely populated metropolitan areas, site-specific surface roughness analysis, and assessing the impact of adjacent building height. CFD may be just what you need to assess the vulnerability of complex and non-conventional structures and quantify risk.

This is an area where catastrophe models generally fail to capture vulnerability sufficiently accurately. This limitation is even more pronounced when a facility is complex and composed of independent units with various degrees of vulnerability. In such a scenario, site-specific CFD analysis can be used to identify vulnerable units.

CFD can also be used to compare the impact of different types of natural hazards. For example, both tornado and hurricane have high intensity wind speeds, but the nature of their flows is quite different. Although both the flows are rotational in nature, the radius of rotation impacting a city (or part of a city) is much smaller for tornado than for hurricane. As a result, the impact of the flow field would be different for tornado and hurricane over a structure; CFD can be used to obtain this variation.


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Categories: Best Practices

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