Plasma Actuator

An actuator including a first and second conductor on a dielectric, wherein application of a voltage to the first conductor creates a plasma, thereby modifying a fluid flow in communication with the actuator. Related systems and methods are also provided

Calm before the storm: Comparing the initial stages of tornadic vs. non-tornadic supercells

Supercells are one of the most dramatic displays of weather in Oklahoma, and it is from this type of storm that the majority of tornadoes are produced. But while most tornados are produced by supercells, not every supercell storm produces tornadoes. Many supercells form and dissipate with processes almost identical to those that produce tornadoes but either the tornado does not form or it never reaches the ground. While these storms still pose threats to life and property, it is important to be able to better predict which supercells will produce tornadoes and which ones will not. Therefore, the question to be addressed by this project is which parameters differ between tornadic supercells and tornadic supercells and how those parameters might affect whether or not a tornado will form.In order to better understand what conditions might influence the formation of tornadoes I studied both tornadic and non-tornadic supercells. This work was done primarily through the use of computational models using the Cloud Model (CM1) code and the high performance computing system at Oklahoma State University. CM1 is a program that was designed to model small-scale atmospheric processes and can be customized to simulate many instances of severe weather. For this project I used CM1 to model a nontornadic supercell and a tornadic supercell thunderstorm using a combination of preconfigured code and soundings collected by the National Weather Service in Norman, Oklahoma during a storm that took place El Reno on May 31, 2013.The next step was to compare the simulated storms to data collected directly from storms. Using the WeatherScope software available through the Mesonet website I generated graphs displaying atmospheric pressure and wind speeds for a nontornadic supercell and a tornadic supercell. From this comparison I saw that the pressure was almost 10 millibars higher throughout for the nontornadic supercell when compared to the tornadic supercell. These results indicate that very low pressure prior to the formation of a supercell means that tornados may be more likely to form.Lew Wentz FoundationMechanical and Aerospace Engineerin

Seeing the Threat: Pilot Visual Detection of Small Unmanned Aircraft Systems in Visual Meteorological Conditions

One key challenge of integrating Unmanned Aircraft Systems (UAS) platforms into the National Airspace System (NAS) is the potential for midair collisions between manned aircraft and the unmanned system. The lack of an established UAS benchmark for Detect, Sense & Avoid Systems put the preponderance of avoidance efforts on manned aircraft pilots to visually see and avoid potential collision threats. The small size, unusual configurations, and diverse operational applications of unmanned systems make UAS platforms difficult to visually identify. This paper sought to determine the mean visibility distance of small UAS systems (sUAS) to an alerted pilot flying a general aviation aircraft in visual meteorological conditions (VMC). The study evaluated mean visibility distance to various sUAS platforms based on a scripted set of UAS convergence conditions. The study utilized a mixed method design in which a general aviation aircraft was flown into a UAS operations area. Study pilots were instructed to locate a flying UAS aircraft without bearing assistance. Both the UAS and manned aircraft were assigned vertically de-conflicted altitudes with the UAS aircraft executing a series of converging and crossing courses relative to the manned aircraft. The distance at which the pilot visually located the UAS platform was timestamped and electronically recorded via a GPS tracking device. The various conditions were analyzed to determine significant visibility differences among the various convergence conditions. Qualitative data was collected from participant comments and observations recorded by an in-flight safety observer

Considerations for Atmospheric Measurements with Small Unmanned Aircraft Systems

This paper discusses results of the CLOUD-MAP(Collaboration Leading Operational UAS Development for Meteorology and Atmospheric Physics) project dedicated to developing, fielding, and evaluating integrated small unmanned aircraft systems (sUAS) for enhanced atmospheric physics measurements. The project team includes atmospheric scientists, meteorologists, engineers, computer scientists, geographers, and chemists necessary to evaluate the needs and develop the advanced sensing and imaging, robust autonomous navigation, enhanced data communication, and data management capabilities required to use sUAS in atmospheric physics. Annual integrated evaluation of the systems in coordinated field tests are being used to validate sensor performance while integrated into various sUAS platforms. This paper focuses on aspects related to atmospheric sampling of thermodynamic parameters with sUAS, specifically sensor integration and calibration/validation, particularly as it relates to boundary layer profiling. Validation of sensor output is performed by comparing measurements with known values, including instrumented towers, radiosondes, and other validated sUAS platforms. Experiments to determine the impact of sensor location and vehicle operation have been performed, with sensor aspiration a major factor. Measurements are robust provided that instrument packages are properly mounted in locations that provide adequate air flow and proper solar shielding

Unmanned aerial vehicle-to-wearables (UAV2W) indoor radio propagation channel measurements and modeling

In this paper, off-body ultra-wide band (UWB) channel characterization and modeling are presented between an unmanned aerial vehicle (UAV) and a human subject. The wearable antenna was patched at nine different body locations on a human subject during the experiment campaign. The prime objective of this work was to study and evaluate the distance and frequency dependent path loss factors for different bandwidths corresponding to various carrier frequencies, and also look into the time dispersion properties of such unmanned aerial vehicle-to-wearables (UAV2W) system. The environment under consideration was an indoor warehouse with highly conductive metallic walls and roof. Best fit statistical analysis using Akaike Information Criteria revealed that the Log-normal distribution is the best fit distribution to model the UWB fading statistics. The study in this paper will set up a road map for future UAV2W studies to develop enhanced retail and remote health-care monitoring/diagnostic systems

Air Exchange Rate in a Horse Trailer During Road Transport

Horses traveling by road commonly experience heat stress conditions and poor air quality, which may be caused by insufficient ventilation; however, there are few estimates of air exchange in a horse trailer during transport. Air exchange rate was measured at ten locations within a four-horse trailer (internal volume 18.5 m3) using tracer gas decay measurement to assess the adequacy of ventilation. Three vehicle speeds (13, 48, and 97 km h-1) and three window configurations (all windows and roof vents closed, all windows open, all windows open and roof vents open forward) were tested with and without animals present in the trailer. External air temperature ranged from 22.3°C to 28.3°C with an average of 25.3°C, and internal air temperature ranged from 29.9°C to 34.8°C with an average of 31.3°C with animals present. Air exchange rate increased with vehicle speed and open window and vent area. The average air exchange rate over all vehicle speeds and ventilation configurations was 0.52 min-1 with animals present and 0.76 min-1 without animals. Without animals present, the maximum mean exchange rate was 1.42 min-1 at 97 km h-1 at the rear left window with all windows and vents open; the lowest mean exchange rate was 0.12 min-1 at 13 km h-1 with all windows and vents closed at the lower position of the rearmost stall divider. With animals present, the maximum air exchange rate observed was 0.84 min-1 with all windows and vents open and traveling at 97 km h-1. Ventilation in the trailer was not adequate when compared to recommendations for stabled horses for any combination of vehicle speed or ventilation configuration. Increasing open vent area, either by increasing the number and size of roof vents or the size of windows in the sidewall, would be the most cost-effective means of increasing air exchange in a horse trailer

Detecting and Assessing Collision Potential of Aircraft and Small Unmanned Aircraft Systems (sUAS) by Visual Observers

Visual observers are used to assist the Remote Pilot with maintaining sight of the unmanned aircraft as well as scanning the surrounding airspace for potential collision hazards. The purpose of this study was to examine the effectiveness of visual observers in detecting an intruding general aviation aircraft approaching the small unmanned aircraft system (sUAS) operations area. The study sought to determine the effectiveness of sUAS visual observers in detecting a general aviation aircraft collision hazard with a sUAS. Ten participants were asked to perform visual observer duties in support of a sUAS operation. Participants were asked to indicate when they were able to hear and see an aircraft that conducted a scripted series of close intercepts with a sUAS. Additionally, researchers assessed each visual observer’s ability to accurately judge the closure rate of the aircraft, by estimating the duration from initial sighting until the aircraft would intercept the airborne sUAS platform. Geolocation data from both the aircraft and sUAS were time correlated and compared to determine estimation accuracy. Findings were used to formulate operational recommendations to improve visual observer performance in detecting and assessing intruder aircraft collision potential

Data Generated during the 2018 LAPSE-RATE Campaign: An Introduction and Overview

Unmanned aircraft systems (UASs) offer innovative capabilities for providing new perspectives on the atmosphere, and therefore atmospheric scientists are rapidly expanding their use, particularly for studying the planetary boundary layer. In support of this expansion, from 14 to 20 July 2018 the International Society for Atmospheric Research using Remotely piloted Aircraft (ISARRA) hosted a community flight week, dubbed the Lower Atmospheric Profiling Studies at Elevation – a Remotely-piloted Aircraft Team Experiment (LAPSE-RATE; de Boer et al., 2020a). This field campaign spanned a 1-week deployment to Colorado\u27s San Luis Valley, involving over 100 students, scientists, engineers, pilots, and outreach coordinators. These groups conducted intensive field operations using unmanned aircraft and ground-based assets to develop comprehensive datasets spanning a variety of scientific objectives, including a total of nearly 1300 research flights totaling over 250 flight hours. This article introduces this campaign and lays the groundwork for a special issue on the LAPSE-RATE project. The remainder of the special issue provides detailed overviews of the datasets collected and the platforms used to collect them. All of the datasets covered by this special issue have been uploaded to a LAPSE-RATE community set up at the Zenodo data archive (https://zenodo.org/communities/lapse-rate/, last access: 3 December 2020)

Intercomparison of Small Unmanned Aircraft System (sUAS) Measurements for Atmospheric Science During the LAPSE-RATE Campaign

Small unmanned aircraft systems (sUAS) are rapidly transforming atmospheric research. With the advancement of the development and application of these systems, improving knowledge of best practices for accurate measurement is critical for achieving scientific goals. We present results from an intercomparison of atmospheric measurement data from the Lower Atmospheric Process Studies at Elevation—a Remotely piloted Aircraft Team Experiment (LAPSE-RATE) field campaign. We evaluate a total of 38 individual sUAS with 23 unique sensor and platform configurations using a meteorological tower for reference measurements. We assess precision, bias, and time response of sUAS measurements of temperature, humidity, pressure, wind speed, and wind direction. Most sUAS measurements show broad agreement with the reference, particularly temperature and wind speed, with mean value differences of 1.6 ± 2.6 °C and 0.22 ± 0.59 m/s for all sUAS, respectively. sUAS platform and sensor configurations were found to contribute significantly to measurement accuracy. Sensor configurations, which included proper aspiration and radiation shielding of sensors, were found to provide the most accurate thermodynamic measurements (temperature and relative humidity), whereas sonic anemometers on multirotor platforms provided the most accurate wind measurements (horizontal speed and direction). We contribute both a characterization and assessment of sUAS for measuring atmospheric parameters, and identify important challenges and opportunities for improving scientific measurements with sUAS