This paper presents a polynomial dimensional decomposition (PDD) method for global sensitivity analysis of stochastic systems subject to independent random input following arbitrary probability distributions. The method involves Fourier-polynomial expansions of lower-variate component functions of a stochastic response by measure-consistent orthonormal polynomial bases, analytical formulae for calculating the global sensitivity indices in terms of the expansion coefficients, and dimension-reduction integration for estimating the expansion coefficients. Due to identical dimensional structures of PDD and analysis-of-variance decomposition, the proposed method facilitates simple and direct calculation of the global sensitivity indices. Numerical results of the global sensitivity indices computed for smooth systems reveal significantly higher convergence rates of the PDD approximation than those from existing methods, including polynomial chaos expansion, random balance design, state-dependent parameter, improved Sobol’s method, and sampling-based methods. However, for non-smooth functions, the convergence properties of the PDD solution deteriorate to a great extent, warranting further improvements. The computational complexity of the PDD method is polynomial, as opposed to exponential, thereby alleviating the curse of dimensionality to some extent. Mathematical modeling of complex systems often requires sensitivity analysis to determine how an output variable of interest is influenced by individual or subsets of input variables. A traditional local sensitivity analysis entails gradients or derivatives, often invoked in design optimization, describing changes in the model response due to the local variation of input. Depending on the model output, obtaining gradients or derivatives, if they exist, can be simple or difficult. In contrast, a global sensitivity analysis (GSA), increasingly becoming mainstream, characterizes how the global variation of input, due to its uncertainty, impacts the overall uncertain behavior of the model. In other words, GSA constitutes the study of how the output uncertainty from a mathematical model is divvied up, qualitatively or quantitatively, to distinct sources of input variation in the model [1].

Reliability Engineering and System Safety

A tendency to erect ever more wind turbines can be observed in order to reduce the environmental consequences of electric power generation. As a result of this, in the near future, wind turbines may start to influence the behavior of electric power systems by interacting with conventional generation and loads. Therefore, wind turbine models that can be integrated into power system simulation software are needed. In this contribution, a model that can be used to represent all types of variable speed wind turbines in power system dynamics simulations is presented. First, the modeling approach is commented upon and models of the subsystems of which a variable speed wind turbine consists are discussed. Then, some results obtained after incorporation of the model in PSS/E, a widely used power system dynamics simulation software package, are presented and compared with measurements.

/pdf/general-model-for-representing-variable-speed-wind-turbines-2905aqc505.pdf

General model for representing variable speed wind turbines in power system dynamics simulations

Recently, there has been considerable interest in new tiered network cellular architectures, which would likely use many more cell sites than found today. Two major challenges will be i) providing backhaul to all of these cells and ii) finding efficient techniques to leverage higher frequency bands for mobile access and backhaul. This paper proposes the use of outdoor millimeter wave communications for backhaul networking between cells and mobile access within a cell. To overcome the outdoor impairments found in millimeter wave propagation, this paper studies beamforming using large arrays. However, such systems will require narrow beams, increasing sensitivity to movement caused by pole sway and other environmental concerns. To overcome this, we propose an efficient beam alignment technique using adaptive subspace sampling and hierarchical beam codebooks. A wind sway analysis is presented to establish a notion of beam coherence time. This highlights a previously unexplored tradeoff between array size and wind-induced movement. Generally, it is not possible to use larger arrays without risking a corresponding performance loss from wind-induced beam misalignment. The performance of the proposed alignment technique is analyzed and compared with other search and alignment methods. The results show significant performance improvement with reduced search time.

Millimeter Wave Beamforming for Wireless Backhaul and Access in Small Cell Networks

Minimum Design Loads for Buildings and Other Structures provides requirements for general structural design and includes means for determining dead, live, soil, flood, wind, snow, rain, atmospheric ice, and earthquake loads, as well as their combinations, which are suitable for inclusion in building codes and other documents. This Standard, a revision of ASCE/SEI 7-05, offers a complete update and reorganization of the wind load provisions, expanding them from one chapter into six. The Standard contains new ultimate event wind maps with corresponding reductions in load factors, so that the loads are not affected, and updates the seismic loads with new risk-targeted seismic maps. The snow, live, and atmospheric icing provisions are updated as well. In addition, the Standard includes a detailed Commentary with explanatory and supplementary information designed to assist building code committees and regulatory authorities. Standard ASCE/SEI 7 is an integral part of building codes in the United States. Many of the load provisions are substantially adopted by reference in the International Building Code and the NFPA 5000 Building Construction and Safety Code. Structural engineers, architects, and those engaged in preparing and administering local building codes will find this Standard an essential reference in their practice. Note: New orders are fulfilled from the second printing, which incorporates the errata to the first printing.

Minimum Design Loads for Buildings and Other Structures

On generalise l'estimateur bien connu de Hill de l'indice d'une fonction de reparatition avec queue de variation reguliere a une estimation de l'indice d'une loi de valeurs extremes. On demontre la convergence et la normalite asymptotique. On utilise l'estimateur pour certaines estimations comme celle d'une quantile elevee et d'un point d'extremite

A moment estimator for the index of an extreme-value distribution

Wind Effects on Structures: Modern Structural Design for Wind

This book provides detailed information on the design of wind resistant structures. It includes material on building code provisions for wind loads on low rise buildings. It provides engineers with up-to-date methods and standards for the construction of wind-resistant structures and reflects the increased use of instrumentation and computers to predict structural loading and the creation of more stringent building codes.

Wind effects on structures : fundamentals and applications to design

THE ATMOSPHERE Atmospheric Circulations The Atmospheric Boundary Layer Extreme Wind Climatology WIND LOADS AND THEIR EFFECTS ON STRUCTURES Fundamentals Bluff-Body Aerodynamics Structural Dynamics Aereolastic Phenomena Wind Tunnels Wind Directionality Effects Applications to Design Tall Buildings: Structural Response and Cladding Design Slender Towers and Stacks with Circular Cross Section Hyperbolic Cooling Towers Trussed Frameworks and Plate Girders Suspended-Span Bridges, Tension Structures, and Power Lines Offshore Structures Wind-Induced Discomfort In and Around Buildings Tornado Effects Appendixes Index.

Wind effects on structures: An introduction to wind engineering

We seek to ascertain whether the reverse Weibull distribution is an appropriate extreme wind-speed model by performing statistical analyses based on the “peaks over threshold” approach. We use the de Haan method, which was found in previous studies to perform about as well or better than the Pickands and cumulative mean exceedance methods, and has the advantage of providing estimates of confidence bounds. The data are taken principally from records of the largest daily wind speeds obtained over periods of 15 to 26 years at 44 U.S. weather stations in areas not subjected to mature hurricane winds. From these records we create samples with reduced mutual correlation among the data. In our opinion, the analyses provide persuasive evidence that extreme wind speeds are described predominantly by reverse Weibull distributions, which unlike the Gumbel distribution have a finite upper tail and lead to reasonable estimates of wind load factors. Instructions are provided for accessing the data and attendant programs.

Extreme Wind Distribution Tails: A “Peaks over Threshold” Approach

Current procedures for estimating the peaks of the stochastic response of tall buildings to wind are based on the assumption that the response is Gaussian. Those procedures are therefore inapplicable to low-rise buildings, in which time histories of wind-induced internal forces are generally non-Gaussian. In this paper, an automated procedure is developed for obtaining from such time histories sample statistics of internal force peaks for low-rise building design and codification. The procedure is designed for use in software for calculating internal force time series by the database-assisted design approach. A preliminary step in the development of the procedure is the identification of the appropriate marginal probability distribution of the time series using the probability plot correlation coefficient method. The result obtained is that the gamma distribution and a normal distribution are appropriate for estimating the peaks correspond- ing, respectively, to the longer and shorter tail of the time series' histograms. The distribution of the peaks is then estimated by using the standard translation processes approach. It is found that the peak distribution can be represented by the Extreme Value Type I ~Gumbel! distribution. Because estimates obtained from this approach are based on the entire information contained in the time series, they are more stable than estimates based on observed peaks. The procedure can be used to establish minimum acceptable requirements with respect to the duration and sampling rate of the time series of interest, so that the software used for database-assisted design will be both efficient and accurate.

/pdf/peak-non-gaussian-wind-effects-for-database-assisted-low-to5jakbuol.pdf

Emil Simiu

Papers

Wind Effects on Structures: Modern Structural Design for Wind

Wind effects on structures : fundamentals and applications to design

Wind effects on structures: An introduction to wind engineering

Extreme Wind Distribution Tails: A “Peaks over Threshold” Approach

Peak Non-Gaussian Wind Effects for Database-Assisted Low-Rise Building Design