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This paper considers the trajectories of compact and rod-type wind-borne debris in horizontal winds, using a combination of experimental and numerical studies. These types are representative of the roof gravel and timber members currently used for testing building facades and storm shutters. These studies indicate that the ratio of horizontal debris speed to wind gust speed is primarily a function of the horizontal distance traveled by the debris as it accelerates toward the wind speed. Empirical expressions to approximate the horizontal speed of these debris as a function of travel distance and time are developed, and may be used to establish rational debris impact criteria. CE Database subject headings: Debris; Hurricanes; Wind tunnels; Damage; Numerical analysis.

By observing that the optimal basis for the proper orthogonal decomposition (POD) can be obtained from the cross power spectral density (XPSD) matrix of a multivariate stationary Gaussian stochastic process, the computational efficiency, in both time and memory consumption, of simulations of this process is improved by using a hybrid spectral representation and POD approach with negligible loss of accuracy. This hybrid approach actually simulates another multivariate process with many fewer variables in an optimal subspace obtained by the POD. This approach is straightforward, effective, and does not place any conditions on the XPSD matrices. Furthermore, the error induced by the reduction of variables is predictable and controllable prior to the simulation procedure. The spectral representation method (SRM) is discussed in a heuristic way. In this paper, a specific POD theorem is formally stated, proved, and related to XPSD matrices. A numerical example is given to demonstrate the effectiveness of this hybrid approach. This approach may also have potential applications for simulations of nonstationary non-Gaussian processes. DOI: 10.1061/(ASCE)0733-9399(2005)131:8(801) CE Database subject headings: Simulation; Gaussian process; Stationary process; Spectral density function; Decomposition.

Reliability-based design of infrastructure requires the probabilistic assessment of jointly occurring natural hazards. As infrastructure design practices evolve, it is important that multiple hazards be considered--for example, wind and storm surge in a hurricane, an earthquake generating a tsunami, or strong winds and high temperatures leading to wildfires. These jointly occurring hazards in some cases can be more devastating than a single hazard. This paper describes the assessment of two jointly occurring hazards: wind and ice. For locations in the United States, wind and ice [e.g., freezing rain (FR)] are hazards whose properties are of interest for the design of transmission lines and other energy infrastructure (e.g., wind turbines). Using archived meteorological data from measurement stations in the Midwest, occurrences of icing conditions and the wind speeds that accompany them were identified and input into a simple ice accretion model. Observations from wind speed and ice thickness were fit to probability distributions, and simulations using these distributions were constructed. These simulations were then compared with the observed data and with existing prescribed treatments of these two hazards in design loading guidelines, such as ASCE 7. It is shown that the ASCE 7 method is overly conservative when considering joint hazards. [ABSTRACT FROM AUTHOR]

By observing that the optimal basis for the proper orthogonal decomposition (POD) can be obtained from the cross power spectral density (XPSD) matrix of a multivariate stationary Gaussian stochastic process, the computational efficiency, in both time and memory consumption, of simulations of this process is improved by using a hybrid spectral representation and POD approach with negligible loss of accuracy. This hybrid approach actually simulates another multivariate process with many fewer variables in an optimal subspace obtained by the POD. This approach is straightforward, effective, and does not place any conditions on the XPSD matrices. Furthermore, the error induced by the reduction of variables is predictable and controllable prior to the simulation procedure. The spectral representation method (SRM) is discussed in a heuristic way. In this paper, a specific POD theorem is formally stated, proved, and related to XPSD matrices. A numerical example is given to demonstrate the effectiveness of this hybrid approach. This approach may also have potential applications for simulations of nonstationary non-Gaussian processes. [ABSTRACT FROM AUTHOR]