Academic literature on the topic 'Spatial wind gust'
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Journal articles on the topic "Spatial wind gust"
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Smith, Bryan T., Tomas E. Castellanos, Andrew C. Winters, Corey M. Mead, Andrew R. Dean, and Richard L. Thompson. "Measured Severe Convective Wind Climatology and Associated Convective Modes of Thunderstorms in the Contiguous United States, 2003–09." Weather and Forecasting 28, no. 1 (February 1, 2013): 229–36. http://dx.doi.org/10.1175/waf-d-12-00096.1.
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Abstract A severe thunderstorm wind gust climatology spanning 2003–09 for the contiguous United States is developed using measured Automated Surface Observing System (ASOS) and Automated Weather Observing System (AWOS) wind gusts. Archived severe report information from the National Climatic Data Center publication Storm Data and single-site volumetric radar data are used to identify severe wind gust observations [≥50 kt (25.7 m s−1)] associated with thunderstorms and to classify the convective mode of the storms. The measured severe wind gust distribution, comprising only 2% of all severe gusts, is examined with respect to radar-based convective modes. The convective mode scheme presented herein focuses on three primary radar-based storm categories: supercell, quasi-linear convective systems (QLCSs), and disorganized. Measured severe gust frequency revealed distinct spatial patterns, where the high plains received the greatest number of gusts and occurred most often in the late spring and summer months. Severe wind gusts produced by supercells were most frequent over the plains, while those from QLCS gusts were most frequent in the plains and Midwest. Meanwhile, disorganized storms produced most of their severe gusts in the plains and Intermountain West. A reverse spatial distribution signal exists in the location between the maximum measured severe wind gust corridor located over the high plains and the maximum in all severe thunderstorm wind reports from Storm Data, located near and west of the southern Appalachians.
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Miller, Paul W., Alan W. Black, Castle A. Williams, and John A. Knox. "Quantitative Assessment of Human Wind Speed Overestimation." Journal of Applied Meteorology and Climatology 55, no. 4 (April 2016): 1009–20. http://dx.doi.org/10.1175/jamc-d-15-0259.1.
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AbstractHuman wind reports are a vital supplement to the relatively sparse network of automated weather stations in the United States, especially for localized convective winds. In this study, human wind estimates recorded in Storm Data between 1996 and 2013 were compared with instrumentally observed wind speeds from the Global Historical Climatology Network (GHCN). Nonconvective wind events in areas of flat terrain within the continental United States served as the basis for this analysis because of the relative spatial homogeneity of wind fields in these meteorological and geographic settings. The distribution of 6801 GHCN-measured gust factors (GF), defined here as the ratio of the daily maximum gust to the daily average wind, provided the reference upon which human gust reports were judged. GFs were also calculated for each human estimate by dividing the estimated gust by the GHCN average wind speed on that day. Human-reported GFs were disproportionately located in the upper tail of the observed GF distribution, suggesting that humans demonstrate a tendency to report statistically improbable wind gusts. As a general rule of thumb, humans overestimated nonconvective wind GFs by approximately one-third.
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Mitsuta, Yasushi, and Osamu Tsukamoto. "Studies on Spatial Structure of Wind Gust." Journal of Applied Meteorology 28, no. 11 (November 1989): 1155–60. http://dx.doi.org/10.1175/1520-0450(1989)028<1155:sossow>2.0.co;2.
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Mohr, Susanna, Michael Kunz, Alexandra Richter, and Bodo Ruck. "Statistical characteristics of convective wind gusts in Germany." Natural Hazards and Earth System Sciences 17, no. 6 (June 23, 2017): 957–69. http://dx.doi.org/10.5194/nhess-17-957-2017.
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Abstract. Due to the small-scale and non-stationary nature of the convective wind gusts usually associated with thunderstorms, there is a considerable lack of knowledge regarding their characteristics and statistics. In an effort to remedy this situation, we investigated in this study a set of 110 climate stations of the German Weather Service between 1992 and 2014 to analyze the temporal and spatial distribution, intensity, and occurrence probability of convective gusts. Similar to thunderstorm activity, the frequency of convective gusts decreases gradually from southern to northern Germany. No further spatial structures, such as a relation to orography or climate conditions, can be identified regarding their strength or likelihood. Rather, high wind speeds of above 30 m s−1 can be expected everywhere in Germany with almost similar occurrence probabilities. A comparison of the 20-year return values of convective gusts with those of turbulent gusts demonstrates that the latter have higher frequencies, especially in northern Germany. However, for higher return periods, this effect can be reversed at some stations. The values of the convective gust factors are mainly in a range between 1 and 4 but can even reach values up to 10. Besides the dependency from the averaging time period of the mean wind, the values of the gust factors additionally depend on the event duration and the storm type, respectively.
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Brown, Andrew, and Andrew Dowdy. "Severe convection-related winds in Australia and their associated environments." Journal of Southern Hemisphere Earth Systems Science 71, no. 1 (2021): 30. http://dx.doi.org/10.1071/es19052.
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Severe surface wind gusts produced by thunderstorms have the potential to damage infrastructure and are a major hazard for society. Wind gust data are examined from 35 observing stations around Australia, with lightning observations used to indicate the occurrence of deep convective processes in the vicinity of the observed wind gusts. A collation of severe thunderstorm reports is also used to complement the station wind gust data. Atmospheric reanalysis data are used to systematically examine large-scale environmental measures associated with severe convective winds. We find that methods based on environmental measures provide a better indication of the observed severe convective winds than the simulated model wind gusts from the reanalysis data, noting that the spatial scales on which these events occur are typically smaller than the reanalysis grid cells. Consistent with previous studies in other regions and idealised modelling, the majority of severe convective wind events are found to occur in environments with steep mid-level tropospheric lapse rates, moderate convective instability and strong background wind speeds. A large proportion of events from measured station data occur with relatively dry environmental air at low levels, although it is unknown to what extent this type of environment is representative of other severe wind-producing convective modes in Australia. The occurrence of severe convective winds is found to be well represented by a number of indices used previously for forecasting applications, such as the weighted product of convective available potential energy (CAPE) and vertical wind shear, the derecho composite parameter and the total totals index, as well as by logistic regression methods applied to environmental variables. Based on the systematic approach used in this study, our findings provide new insight on spatio-temporal variations in the risk of damaging winds occurring, including the environmental factors associated with their occurrence.
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Lee, Sung Su, and Jun Yeong Kim. "Spatial and Temporal Analysis of Thunderstorm Wind Gust." Journal of Korea Spatial Information Society 21, no. 4 (August 31, 2013): 1–6. http://dx.doi.org/10.12672/ksis.2013.21.4.001.
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Pryor, S. C., R. Conrick, C. Miller, J. Tytell, and R. J. Barthelmie. "Intense and Extreme Wind Speeds Observed by Anemometer and Seismic Networks: An Eastern U.S. Case Study." Journal of Applied Meteorology and Climatology 53, no. 11 (November 2014): 2417–29. http://dx.doi.org/10.1175/jamc-d-14-0091.1.
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AbstractThe scale and intensity of extreme wind events have tremendous relevance to determining the impact on infrastructure and natural and managed ecosystems. Analyses presented herein show the following. 1) Wind speeds in excess of the station-specific 95th percentile are coherent over distances of up to 1000 km over the eastern United States, which implies that the drivers of high wind speeds are manifest at the synoptic scale. 2) Although cold fronts associated with extratropical cyclones are a major cause of high–wind speed events, maximum sustained and gust wind speeds are only weakly dependent on the near-surface horizontal temperature gradient across the front. 3) Gust factors (GF) over the eastern United States have a mean value of 1.57 and conform to a lognormal probability distribution, and the relationship between maximum observed GF and sustained wind speed conforms to a power law with coefficients of 5.91 and −0.499. Even though there is coherence in the occurrence of intense wind speeds at the synoptic scale, the intensity and spatial extent of extreme wind events are not fully characterized even by the dense meteorological networks deployed by the National Weather Service. Seismic data from the USArray, a program within the Earthscope initiative, may be suitable for use in mapping high-wind and gust events, however. It is shown that the seismic channels exhibit well-defined spectral signatures under conditions of high wind, with a variance peak at frequencies of ~0.04 s−1 and an amplitude that appears to scale with the magnitude of observed wind gusts.
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Youngman, Benjamin D., and David B. Stephenson. "A geostatistical extreme-value framework for fast simulation of natural hazard events." Proceedings of the Royal Society A: Mathematical, Physical and Engineering Sciences 472, no. 2189 (May 2016): 20150855. http://dx.doi.org/10.1098/rspa.2015.0855.
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We develop a statistical framework for simulating natural hazard events that combines extreme value theory and geostatistics. Robust generalized additive model forms represent generalized Pareto marginal distribution parameters while a Student’s t -process captures spatial dependence and gives a continuous-space framework for natural hazard event simulations. Efficiency of the simulation method allows many years of data (typically over 10 000) to be obtained at relatively little computational cost. This makes the model viable for forming the hazard module of a catastrophe model. We illustrate the framework by simulating maximum wind gusts for European windstorms, which are found to have realistic marginal and spatial properties, and validate well against wind gust measurements.
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Liu, Cheng, Qinglan Li, Wei Zhao, Yuqing Wang, Riaz Ali, Dian Huang, Xiaoxiong Lu, Hui Zheng, and Xiaolin Wei. "Spatiotemporal Characteristics of Near-Surface Wind in Shenzhen." Sustainability 12, no. 2 (January 20, 2020): 739. http://dx.doi.org/10.3390/su12020739.
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The spatiotemporal characteristics of near-surface wind in Shenzhen were investigated in this study by using hourly observations at 92 automatic weather stations (AWSs) from 2009 to 2018. The results show that during the past 10 years, most of the stations showed a decreasing trend in the annual mean of the 10 min average wind speed (avg-wind) and the mean of the 3 s average wind speed (gust wind). Over half of the decreasing trends at the stations were statistically significant (p < 0.05). Seasonally, the decrease in wind speed was the most severe in spring, followed by autumn, winter, and summer. The distribution of wind speed tends to be greater in the east and coastal areas for both avg-wind and gust wind. From September to March of the following year, the prevailing wind direction in Shenzhen was northerly, and from April to August, the prevailing wind direction was southerly. The seasonal wind speed distribution exhibited two different types, spring–summer type and autumn–winter type, which may be induced by their different prevailing wind directions. The analysis by the empirical orthogonal function (EOF) method confirmed the previous findings that the mean wind speed was decreasing in Shenzhen and that two different seasonal wind speed spatial distribution patterns existed. Such a study could provide references for wind forecasting and risk assessment in the study area.
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Vrancken, Patrick, and Jonas Herbst. "Development and Test of a Fringe-Imaging Direct-Detection Doppler Wind Lidar for Aeronautics." EPJ Web of Conferences 237 (2020): 07008. http://dx.doi.org/10.1051/epjconf/202023707008.
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DLR currently investigates the use of Doppler wind lidar as sensor within feedforward gust alleviation control loops on fast-flying fixed-wing aircraft. Such a scheme imposes strong requirements on the lidar system such as sub-m/s precision, high rate, high spatial resolution, close measurement ranges and sensitivity to mixed and pure molecular backscatter. We report on the development of a novel direct-detection Doppler wind lidar (DD-DWL) within these requirements. This DD-DWL is based on fringe-imaging of the Doppler-shifted backscatter of UV laser pulses in a field-widened Michelson interferometer using a fast linear photodetector. A prototype for airborne operation has been ground-tested in early 2018 against a commercial coherent DWL, demonstrating its ability of measuring close-range wind speeds with a precision of 0.5 m/s, independent of the actual wind speed.
Dissertations / Theses on the topic "Spatial wind gust"
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"Physics-Based Lidar Simulation and Wind Gust Detection and Impact Prediction for Wind Turbines." Doctoral diss., 2019. http://hdl.handle.net/2286/R.I.53921.
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abstract: Lidar has demonstrated its utility in meteorological studies, wind resource assessment, and wind farm control. More recently, lidar has gained widespread attention for autonomous vehicles.
The first part of the dissertation begins with an application of a coherent Doppler lidar to wind gust characterization for wind farm control. This application focuses on wind gusts on a scale from 100 m to 1000 m. A detecting and tracking algorithm is proposed to extract gusts from a wind field and track their movement. The algorithm was implemented for a three-hour, two-dimensional wind field retrieved from the measurements of a coherent Doppler lidar. The Gaussian distribution of the gust spanwise deviation from the streamline was demonstrated. Size dependency of gust deviations is discussed. A prediction model estimating the impact of gusts with respect to arrival time and the probability of arrival locations is introduced. The prediction model was applied to a virtual wind turbine array, and estimates are given for which wind turbines would be impacted.
The second part of this dissertation describes a Time-of-Flight lidar simulation. The lidar simulation includes a laser source module, a propagation module, a receiver module, and a timing module. A two-dimensional pulse model is introduced in the laser source module. The sampling rate for the pulse model is explored. The propagation module takes accounts of beam divergence, target characteristics, atmosphere, and optics. The receiver module contains models of noise and analog filters in a lidar receiver. The effect of analog filters on the signal behavior was investigated. The timing module includes a Time-to-Digital Converter (TDC) module and an Analog-to-Digital converter (ADC) module. In the TDC module, several walk-error compensation methods for leading-edge detection and multiple timing algorithms were modeled and tested on simulated signals. In the ADC module, a benchmark (BM) timing algorithm is proposed. A Neyman-Pearson (NP) detector was implemented in the time domain and frequency domain (fast Fourier transform (FFT) approach). The FFT approach with frequency-domain zero-paddings improves the timing resolution. The BM algorithm was tested on simulated signals, and the NP detector was evaluated on both simulated signals and measurements from a prototype lidar (Bhaskaran, 2018).Dissertation/Thesis
Doctoral Dissertation Mechanical Engineering 2019
Conference papers on the topic "Spatial wind gust"
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Bartholomay, Sirko, Wolf-Leonard Fruck, George Pechlivanoglou, Christian Navid Nayeri, and Christian Oliver Paschereit. "Reproducible Inflow Modifications for a Wind Tunnel Mounted Research Hawt." In ASME Turbo Expo 2017: Turbomachinery Technical Conference and Exposition. American Society of Mechanical Engineers, 2017. http://dx.doi.org/10.1115/gt2017-64364.
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This paper describes a method of creating inhomogeneous inflow conditions to a horizontal axis wind turbine installed in the settling chamber of the large wind tunnel of the TU Berlin. Thereby, a steady gust (i.e. spatial velocity gradient, constant over time) is created which covers half of the swept area of the turbine. For purposes of analysis, a hotwire traversing system was used and measurements were correlated to on-blade angle of attack, velocity and blade root bending moment measurements. Moreover, the paper presents wake measurements at one downstream plane behind the turbine.
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Tamarozzi, Tommaso, Bart Blockmans, and Wim Desmet. "Efficient Transient Analysis of the High-Speed Stage of a Wind Turbine Gearbox by Advanced Model Reduction Techniques and Memory-Effective Discretization." In ASME 2015 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference. American Society of Mechanical Engineers, 2015. http://dx.doi.org/10.1115/detc2015-47093.
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Modern wind turbines are designed to cope with their increased size and capacity. One of the most expensive components of these machines is the gearbox. Its design is more complex than a mere upscaling exercise from predecessors. The stress levels experienced by the different gear stages, the dynamic effects induced by their size and the unparalleled loads transmitted are some of the challenges that design engineers face. Moreover, unexpected events that load the wind turbines such as voltage dips, wind gusts or emergency breaking are expected to be major contributors to the premature failure of these gearboxes. The lack of engineering experience at this scale calls for accurate and efficient simulation tools thereby enabling reliable gearbox design. Standard lumped-parameters models or rigid multibody approaches do not provide a sufficient level of details to study the dynamic effects induced by e.g. gear design modifications (micro-geometry) or to analyze local stress concentrations. More advanced numerical tools are available such as flexible multibody or non-linear FE and allow to model complex contact interactions including all the relevant dynamic effects. Unfortunately the level of mesh refinement needed for an accurate analysis causes these simulations to be computationally expensive with time scales of several weeks to perform a single full rotation of a gear pair. This work introduces a novel efficient simulation tool for dynamic analysis of transmissions. This tool adopts a flexible multibody paradigm but incorporates several advanced features that allows to run simulations up to two orders of magnitudes faster as compared to non-linear FE with the same level of accuracy. A unique non-linear parametric model order reduction technique is used to develop a simulation strategy that is quasi mesh-independent allowing the usage of very fine FE meshes. Finally, in order to limit the memory consumption, a technique is developed to be able to finely mesh only a few of the gears teeth while the remaining gears are coarsely meshed. The main novelty of this approach lies in the possibility to perform full gear rotations without losing spatial resolution as compared to a finely meshed gear. After an accuracy check performed with a sample pair of helical gears, the framework is used to simulate the high speed stage of a three-stage wind turbine gearbox. The combined efficiency and accuracy of the approach is demonstrated by performing a dynamic stress analysis of the high-speed stage with and without a tip-relief modification. Accuracy of the results, simulation time, and memory usage are assessed.
Reports on the topic "Spatial wind gust"
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Downing, W. Logan, Howell Li, William T. Morgan, Cassandra McKee, and Darcy M. Bullock. Using Probe Data Analytics for Assessing Freeway Speed Reductions during Rain Events. Purdue University, 2021. http://dx.doi.org/10.5703/1288284317350.
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Rain impacts roadways such as wet pavement, standing water, decreased visibility, and wind gusts and can lead to hazardous driving conditions. This study investigates the use of high fidelity Doppler data at 1 km spatial and 2-minute temporal resolution in combination with commercial probe speed data on freeways. Segment-based space-mean speeds were used and drops in speeds during rainfall events of 5.5 mm/hour or greater over a one-month period on a section of four to six-lane interstate were assessed. Speed reductions were evaluated as a time series over a 1-hour window with the rain data. Three interpolation methods for estimating rainfall rates were tested and seven metrics were developed for the analysis. The study found sharp drops in speed of more than 40 mph occurred at estimated rainfall rates of 30 mm/hour or greater, but the drops did not become more severe beyond this threshold. The average time of first detected rainfall to impacting speeds was 17 minutes. The bilinear method detected the greatest number of events during the 1-month period, with the most conservative rate of predicted rainfall. The range of rainfall intensities were estimated between 7.5 to 106 mm/hour for the 39 events. This range was much greater than the heavy rainfall categorization at 16 mm/hour in previous studies reported in the literature. The bilinear interpolation method for Doppler data is recommended because it detected the greatest number of events and had the longest rain duration and lowest estimated maximum rainfall out of three methods tested, suggesting the method balanced awareness of the weather conditions around the roadway with isolated, localized rain intensities.