Special Issue "Measurement, Analysis, Modeling and Prediction of Strong Winds in Atmospheric Boundary Layer"

A special issue of Atmosphere (ISSN 2073-4433). This special issue belongs to the section "Meteorology".

Deadline for manuscript submissions: closed (10 February 2022) | Viewed by 7183

Special Issue Editors

Department of Civil, Structural and Environmental Engineering, University at Buffalo, Buffalo, NY 14260, USA
Interests: wind engineering; bridge engineering; structural engineering; hurricane resilience; machine learning; climate change
Special Issues, Collections and Topics in MDPI journals
Department of Construction Engineering, École de Technologie Supérieure, University of Quebec, Montreal, QC H3C 1K3, Canada
Interests: wind engineering; tropical cyclone; extra typical cyclones; machine learning
Department of Civil and Environmental Engineering, Lehigh University, Bethlehem, PA 18015, USA
Interests: wind engineering; performance-based design; stochastic process; machine learning; computer vision

Special Issue Information

Dear Colleagues,

Strong winds in the atmospheric boundary layer (e.g., tropical cyclones, extratropical cyclones, downbursts and tornados) can cause significant casualty, property damage, and economic loss. The strong wind-induced structure and infrastructure damage and loss will become more severe in the context of climate change, where both the frequency and intensity of strong wind events are expected to increase. A deep understanding of strong winds will greatly benefit the wind engineering field, especially for the design and retrofit of structures and infrastructures. This Special Issue calls for papers that can shed light onto the measurement, analysis, modeling and prediction of strong winds in the atmospheric boundary layer. The topics of interest for this Special Issue include, but are not limited to, the following:

  • The wind measurement from conventional and novel sensors (e.g., anemometer, scanning Lidar, Radar, dropsonde, satellite and optical fiber);
  • The analysis of wind data with advanced signal processing techniques and statistics;
  • The characterization of strong winds with consideration of climate change;
  • The modeling of strong wind events with data-driven, physics-based or hybrid approaches;
  • The short-term and/or long-term forecasting of strong winds;
  • The uncertainty quantification and propagation in the predictability of strong winds;
  •  The simulation of strong winds in conventional and novel wind tunnels.

Prof. Dr. Teng Wu
Dr. Reda Snaiki
Dr. Haifeng Wang
Guest Editors

Manuscript Submission Information

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Keywords

  • wind engineering
  • hurricane
  • tornado
  • downburst
  • extra-tropical cyclone
  • wind forecasting
  • wind tunnel
  • machine learning
  • field measurement
  • climate change

Published Papers (4 papers)

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Research

14 pages, 4930 KiB  
Article
Knowledge-Enhanced Deep Learning for Simulation of Extratropical Cyclone Wind Risk
Atmosphere 2022, 13(5), 757; https://doi.org/10.3390/atmos13050757 - 08 May 2022
Cited by 1 | Viewed by 1396
Abstract
Boundary-layer wind associated with extratropical cyclones (ETCs) is an essential element for posing serious threats to the urban centers of eastern North America. Using a similar methodology for tropical cyclone (TC) wind risk (i.e., hurricane tracking approach), the ETC wind risk can be [...] Read more.
Boundary-layer wind associated with extratropical cyclones (ETCs) is an essential element for posing serious threats to the urban centers of eastern North America. Using a similar methodology for tropical cyclone (TC) wind risk (i.e., hurricane tracking approach), the ETC wind risk can be accordingly simulated. However, accurate and efficient assessment of the wind field inside the ETC is currently not available. To this end, a knowledge-enhanced deep learning (KEDL) is developed in this study to estimate the ETC boundary-layer winds over eastern North America. Both physics-based equations and semi-empirical formulas are integrated as part of the system loss function to regularize the neural network. More specifically, the scale-analysis-based reduced-order Navier–Stokes equations that govern the ETC wind field and the European Centre for Medium-Range Weather Forecasts (ECMWF) Re-Analysis (ERA) ERA-interim data-based two-dimensional (2D) parametric formula (with respect to radial and azimuthal coordinates) that prescribes an asymmetric ETC pressure field are respectively employed as rationalism-based and empiricism-based knowledge to enhance the deep neural network. The developed KEDL, using the standard storm parameters (i.e., spatial coordinates, central pressure difference, translational speed, approach angle, latitude of ETC center, and surface roughness) as the network inputs, can provide the three-dimensional (3D) boundary-layer wind field of an arbitrary ETC with high computational efficiency and accuracy. Finally, the KEDL-based wind model is coupled with a large ETC synthetic track database (SynthETC), where 6-hourly ETC center location and pressure deficit are included to effectively assess the wind risk along the US northeast coast in terms of annual exceedance probability. Full article
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28 pages, 8213 KiB  
Article
Experimental Investigation of the Near-Surface Flow Dynamics in Downburst-like Impinging Jets Immersed in ABL-like Winds
Atmosphere 2022, 13(4), 621; https://doi.org/10.3390/atmos13040621 - 13 Apr 2022
Cited by 2 | Viewed by 1405
Abstract
Downburst winds are strong downdrafts of cold air that embed into the atmospheric boundary layer (ABL) and produce intense horizontal outflow upon impingement on the ground. They are highly transient and three-dimensional extreme wind phenomena with a limited spatiotemporal structure that often makes [...] Read more.
Downburst winds are strong downdrafts of cold air that embed into the atmospheric boundary layer (ABL) and produce intense horizontal outflow upon impingement on the ground. They are highly transient and three-dimensional extreme wind phenomena with a limited spatiotemporal structure that often makes the anemometric measurements in nature inadequate for reconstructing their complex flow fields. In the framework of the project THUNDERR, an experimental campaign on downburst outflows has been carried out at the WindEEE Dome at Western University, Canada. The present study analyzes the three-dimensional interaction between downburst (DB) outflows produced as large-scale impinging jets and ABL winds. Most experimental, numerical and analytical models in the literature neglect this flow interplay or treat it in an oversimplistic manner through a vector superposition. We found that the generated near-surface outflow is asymmetric, and a high-intensity wind zone develops at the interface between DB and ABL winds. The time variability of the leading edge of the outflow was investigated by synchronizing all wind measurements across the testing chamber. The three-dimensional flow structure was studied using a refined grid of Cobra probes that sampled the flow at high frequencies. The passage of the primary vortex produced a significant decrease in the height of maximum radial wind speed, predominantly in the ABL-streamwise direction. The turbulence intensity was the highest in the region where DB propagates into oppositely directed ABL winds. Full article
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19 pages, 38729 KiB  
Article
The Effect of Continuous Trapezoidal Straight Spoiler Plates on the Vortex-Induced Vibration of Wind Turbine Towers
Atmosphere 2022, 13(3), 447; https://doi.org/10.3390/atmos13030447 - 09 Mar 2022
Cited by 3 | Viewed by 1805
Abstract
This paper proposes a method of controlling the vortex-induced vibration (VIV) of wind turbine towers by adding continuous trapezoidal straight spoiler plates (TS) onto their outer surface: a fluid–solid coupling model was constructed to simulate the processes of Karman vortex generation and shedding [...] Read more.
This paper proposes a method of controlling the vortex-induced vibration (VIV) of wind turbine towers by adding continuous trapezoidal straight spoiler plates (TS) onto their outer surface: a fluid–solid coupling model was constructed to simulate the processes of Karman vortex generation and shedding on the different surfaces of an original tower (O–tower) and a tower with TS (TS–tower) with assumed and actual Re, while the VIV frequencies were also calculated and compared; the effects of the TS geometry parameters on the VIV frequency of towers were studied to investigate the recommended size; a modal analysis was carried out to research the effects of TS on the vortex-induced resonance risk of towers; and the simulation results as well as relevant research conclusions were validated by an analogical wind tunnel test. Full article
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22 pages, 4234 KiB  
Article
Study on Flow Field Characteristics in Sandstorm Conditions Using Wind Tunnel Test
Atmosphere 2022, 13(3), 446; https://doi.org/10.3390/atmos13030446 - 09 Mar 2022
Cited by 3 | Viewed by 1645
Abstract
To study the sandstorm resistance design of civil structures and transportation infrastructures, the sandstorm flow fields with various grain concentrations were simulated by the windblown sand tunnel. The results show that the grain concentration profile presents an exponential decay form before the critical [...] Read more.
To study the sandstorm resistance design of civil structures and transportation infrastructures, the sandstorm flow fields with various grain concentrations were simulated by the windblown sand tunnel. The results show that the grain concentration profile presents an exponential decay form before the critical wind speed; as the test speed increases, the grain concentration decreases initially and increases afterwards with height, and the characteristic height of moving grain increases while the creep percentage decreases. Moving sand grains reduce wind speed and increase turbulence intensity, and the whole process is affected by grain concentration. The moving grain and the turbulence of the sandstorm flow field form a mutual feedback mechanism, which affects the wind-induced response and impact response to structures. The variation of kinetic energy with height is similar to that of total energy with height in the sandstorm flow fields. Specifically, the grain energy increases with increasing concentration and wind speed, but decreases initially and increases afterwards with height. Furthermore, the critical heights of the grain energy and concentration profile are both about 0.2 m, which has little impact on structures. Full article
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