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

Assessing the impact of spatial resolution of UAS-based remote sensing and spectral resolution of proximal sensing on crop nitrogen retrieval accuracy

Foliar nitrogen (N) plays a central role in photosynthetic machinery of plants, regulating their growth rates. However, field-based methods for monitoring plant N concentration are costly and limited in their ability to cover large spatial extents. In this study, we had two objectives: (1) assess the capability of unoccupied aerial system (UAS) and non-imaging spectroscopic data in estimating sorghum and corn N concentration and (2) determine the impact of spatial and spectral resolution of reflectance data on estimating sorghum and corn N concentration. We used a UAS and an ASD spectroradiometer to collect canopy- and leaf-level spectral data from sorghum and corn at experimental plots located in Stillwater, Oklahoma, U.S. We also collected foliage samples in the field and measured foliar N concentration in the lab for model validation. To assess the impact of spectral scale on estimating N concentration, we resampled our leaf-level ASD data to generate datasets with coarser spectral resolutions. To determine the impact of spatial scale on estimating N concentration, we resampled our UAS data to simulate five datasets with varying spatial resolutions ranging from 5 cm to 1 m. Finally, we used a suite of vegetation indices (VIs) and machine learning algorithms (MLAs) to estimate N concentration. Results from leaf-level ASD spectral data showed that the resampled data matching the spectral resolution of our UAS-based data at five spectral bands ranging from 360 to 900 nm provided sufficient spectral information to estimate plot-level sorghum and corn N concentration. Regarding spatial resolution, canopy-level UAS data resampled at multiple pixel sizes, ranging from 1 cm to 1 m were consistently capable of estimating N concentration. Overall, our findings indicate the possibility of developing monitoring instruments with optimal spectral and spatial resolution for estimating N concentration in crops

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

Pilot Visual Detection of Small Unmanned Aircraft Systems (sUAS) Equipped with Strobe Lighting

When operating under Visual Flight Rules, pilots primarily rely on visual scanning to avoid other aircraft and airborne collision threats. Records from the Federal Aviation Administration indicate that near encounters with unmanned aircraft are on the rise, reaching 1,761 reported unmanned aircraft system (UAS) sightings or near-misses in 2016. This study sought to assess the effectiveness of pilot visual detection of UAS platforms that were equipped with strobe lighting. A sample of 10 pilots flew a general aviation aircraft on a scripted series of five intercepts with a small UAS (sUAS) that was equipped with strobe lighting. Participants were asked to indicate when they visually detected the unmanned aircraft. Geolocation information for both the aircraft and sUAS platform was compared to assess visibility distance. Findings were used to evaluate the efficacy of daytime strobe lighting as a method to enhance pilot sUAS detection, visibility, and collision avoidance. Participants detected the unmanned aircraft during 7.7% of the intercepts. Due to a lack of data points, the authors were unable to conclusively determine if strobe lighting improved UAS visual detection. The authors recommend further research to explore the effectiveness of using sUAS-mounted strobe lights for nighttime visual detection