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Collection and analysis of wind data...
~
Espina, Chad Edward Obedoza.
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Collection and analysis of wind data for the evaluation of Wildland-Urban Interface Fire Dynamics Simulator.
紀錄類型:
書目-電子資源 : Monograph/item
正題名/作者:
Collection and analysis of wind data for the evaluation of Wildland-Urban Interface Fire Dynamics Simulator./
作者:
Espina, Chad Edward Obedoza.
面頁冊數:
106 p.
附註:
Source: Masters Abstracts International, Volume: 53-05.
Contained By:
Masters Abstracts International53-05(E).
標題:
Electrical engineering. -
電子資源:
http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=1563369
ISBN:
9781321123500
Collection and analysis of wind data for the evaluation of Wildland-Urban Interface Fire Dynamics Simulator.
Espina, Chad Edward Obedoza.
Collection and analysis of wind data for the evaluation of Wildland-Urban Interface Fire Dynamics Simulator.
- 106 p.
Source: Masters Abstracts International, Volume: 53-05.
Thesis (M.S.)--San Diego State University, 2014.
The Wildland Urban-Interface Fire Dynamics Simulator (WFDS) is a computer code that is currently being developed by the National Institute of Standards and Technology (NIST). WFDS has the capability of simulating wildland fire behavior with prescribed elements such vegetative and structural fuel, topography, and weather conditions.
ISBN: 9781321123500Subjects--Topical Terms:
649834
Electrical engineering.
Collection and analysis of wind data for the evaluation of Wildland-Urban Interface Fire Dynamics Simulator.
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The Wildland Urban-Interface Fire Dynamics Simulator (WFDS) is a computer code that is currently being developed by the National Institute of Standards and Technology (NIST). WFDS has the capability of simulating wildland fire behavior with prescribed elements such vegetative and structural fuel, topography, and weather conditions.
520
$a
In this initial stage of the research, support for the development of WFDS focuses on the evaluation of a wind flow simulation on a very complex, outdoor terrain. This effort is preceded by the fabrication, installation and testing of wind-sensing equipment. Foremost, wind data gathered from different sites using various instruments are compared and evaluated. The data gathered in the Trails community of Rancho Bernardo is then presented and compared to select WFDS simulations.
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Systems consisting of a wind vane and anemometer are currently installed in the Trails community of Rancho Bernardo. They were installed by Professor Fletcher J. Miller and me using a lift that is attached to a telescoping crane. These instruments will gather the wind data needed to show the behavioral patterns of winds influenced by the topography and obstructions such as trees and houses. They are currently installed on top of light posts. These light posts were picked based on the path of the fire influenced by the Santa Ana winds that ravaged the community in 2007. The data from these instruments were graphically represented using a Matlab code that was developed specifically for the data sets. The Matlab graphing utility plots wind speed and wind direction along with matching polar plots. Other main features also include the ability to set a time range and compare two sites in one plot.
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There are other wind instruments currently being tested and being analyzed to ensure correct data is being recorded. These instruments will also expand to a wider range the wind data-gathering capabilities vertically. A Sound Detecting and Ranging (SoDAR) unit gathers wind speed and direction from the sound waves, initially emitted by the SoDAR to the atmosphere, that are reflected by the air flow above the unit. Wind data has been compared to the SoDAR unit with data from instruments installed on a meteorological tower operated by the National Oceanic and Atmospheric Administration (NOAA) located in northern California. Two more SoDARs are currently in Texas where initially they were deployed 400 meters apart of each other at an airfield. Also in the same airfield, the wind instrument of an Unmanned Aerial Vehicle (UAV) SuperBat was tested and compared to the SoDARs. Lastly, a self-contained wind instrument (Wind Dart) on a UAV that was developed by the University of Colorado was tested. The instrument was used while attached to the UAV Spectra. A static test was also done in San Diego State University's low speed wind tunnel.
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The wind data comparison from the SoDAR and meteorological tower in Lodi, California showed close tracking to each other both in wind speed and direction. The comparison of the wind data gathered by the two SoDARs in Texas also showed close tracking to each other. As for the Wind Dart, the data gathered from the instrument and UAV Spectra are not conclusive enough to validate the abilities of the Wind Dart. The experimental procedure in testing the Wind Dart on a moving platform must be further developed. Before the aerial test of the Wind Dart, it was first tested at San Diego State University's low speed tunnel. The detected wind speed by the Wind Dart closely matches the prescribed wind speed of the wind tunnel. The data between the UAV SuperBat and SoDARs showed close tracking. Data collected by the Rancho Bernardo wind instruments shows cyclical wind patterns in the neighborhood. Initial evaluation of select WFDS simulations show data that mimics data gathered from the field.
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