structural DESIGN Ground Snow Loads for ASCE 7-22 What Has Changed and Why?
By Marc Maguire, Ph.D., Brennan Bean, Ph.D., James Harris, P.E., Ph.D., NAE, Abbie Liel, Ph.D., P.E., and Scott Russell, S.E., P.E., P.Eng
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he new ASCE 7-22, Minimum Design Loads for Buildings and Other Structures, ground snow load maps target uniform reliability rather than a uniform hazard (Bean et al., 2021). Previously, the ASCE 7 snow loads used a uniform-hazard 50-year mean recurrence interval (MRI) with a 1.6 load factor. These loads resulted in non-uniform reliability for structures across the country. The site-specific ground snow load determination is no longer tied to a uniform hazard (i.e., X-year recurrence interval) but to the safety or reliability levels stipulated in Chapter 1 of ASCE 7. The new strength level loads are used with a load factor of 1.0, as shown in Equation 1, and were selected to create uniform reliability across the country. These loads are mapped in the new ASCE 7-22 Chapter 7 in the online Hazard Tool and additionally reduced the number of case study regions by 90%. φRn = 1.2Dn + 1.0Sn (Eqn. 1) In Equation 1, φ is the resistance factor; Rn is the nominal resistance; Dn is the nominal dead load; and Sn is the nominal roof snow load. Snow loading has significant site-to-site variability, both in mean, coefficient of variation, and shape of the statistical distribution of measurements. The earlier 1.6 safety factor, introduced by Ellingwood et al. (1980), bridged the gap between the largest expected snow load during the service life of the structure (i.e., 50-years) and loads that achieve safety objectives. The factor was derived by considering the average behavior of ground snow load probability distributions at eight locations across the country. This is a rational and computationally feasible approach for estimating design snow loads but averaging necessarily overestimates design snow loads in some regions and underestimates them in others. Fortunately, modern computational power and contemporary weather station data can estimate site-specific, reliability-targeted design snow loads.
Figure 1. Histograms, fitted distributions, and factored loads for select cities.
16 STRUCTURE magazine
Reliability Targeted Loads ASCE 7-22 Chapter 1 expresses safety as a reliability index of 3.0 for ductile limit states in Risk Category II structures, corresponding to an annual probability of failure of 3 × 10-5, which results in an approximate mean failure interval of 30,000 years. Such a low probability of failure is difficult to contextualize for any single building and outside the range of personal experiences. A different perspective on the 30,000-year interval is that, out of perhaps 10,000 communities in the U.S., one would not want to see failures due to snow overload in more than about one of those 10,000 communities every three years. This low failure rate requires the extrapolation of the statistical distributions describing all ASCE 7 considered hazards (snow, wind, etc.) to events that exceed those observed in the period of record (which is well under 150 years and, in many cases, under 50 years). The resistance factor and the inherent conservatism in design procedures deliver part of the safety. Still, most of the margin must be based on the source with the highest statistical variability, which in this case is the snow load. Bean et al. (2021) conducted a site-specific reliability analysis to determine ground snow loads, considering both the uncertainty in the snow load and the structural resistance. The targeted resistance member was the flexural yielding (0.9ZxFy) of a steel W-shape using new A992 steel statistical models (Bartlett et al., 2003). This resistance was combined with a flat roof condition and a nominal dead load of 15 psf to be consistent with common roof construction. The authors also developed a unified depth-to-weight conversion (effective density) that converts ground snow depth to load, based on winter temperature, winter precipitation, and distance to coastlines, allowing data from stations that measure
