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DOE OSTI2024

ACE-ENA: Fast Liquid Water Content

These data were collected during the Aerosol and Cloud Experiments in the Eastern North Atlantic field campaign as part of ARM Aerial Facility deployment (ACE-ENA, https://www.arm.gov/research/campaigns/aaf2017ace-ena). The ARM Aerial Facility Gulfstream-1 was deployed at Lajes Air Base (IATA: TER, ICAO: LPLA), on Terceira Island in the Azores, Portugal, for the two Intensive Observation Periods from June 20 through July 22, 2017 (IOP#1) and from January 11 through February 22, 2018 (IOP#2). The G-1 aircraft performed 20+19 research flights over the ARM Eastern North Atlantic (ENA) site and Atlantic Ocean to measure atmospheric turbulence, cloud water content and drop size distributions, aerosol precursor gases, aerosol chemical composition and size distributions. The current data set presents re-processed Particle Volume Monitor PVM-100A (aka Gerber probe) data: Liquid Water Content (LWC), Particle Surface Area (PSA), and the effective droplet radius (re) averaged to 50 Hz, 10 Hz, and 1 Hz.

54 ENVIRONMENTAL SCIENCES↗

NASA NTRS1983

The 1982 control network of Mars

Attention is given to a planet-wide control network of Mars that was computed in September 1982 using a large single-block analytical triangulation with 47,524 measurements of 6853 control points on 1054 Mariner 9 and 757 Viking pictures. In all, 19,139 normal equations were solved, with a resulting standard error of measurement of 18.06 microns. The control points identified by name and letter designation are given, as are the aerographic coordinates of the control points. In addition, the coordinates of the Viking I lander site are given: latitude, 22.480 deg; longitude, 47.962 deg (radius, 3389.32 km). This study expands and updates the previously published network (1978). It is noted that the computation differs in many respects from standard aerial mapping photogrammetric practice. In comparison with aerial mapping photography, the television formats are small and the focal lengths are long; stereo coverage is rare, the scale of the pictures varies greatly, and the residual camera distortions are large.

Davies, M. E.↗

DOE OSTI2020

Machine Learning for Automated Extraction of Building Geometry

As data science comes to buildings, the promise of using machine learning and novel sources of data has received much attention. Advances in machine learning and computer vision algorithms, combined with increased access to unstructured data (e.g., images and text), have created an opportunity for automated extraction of building characteristics – cost-effectively, and at scale. Acquisition of features such as footprint are time consuming and costly to acquire with today’s manual methods, but can be streamlined through intelligent software-based solutions applied to satellite images. When combined with aerial RGB and thermal images, full 3D geometries and thermal maps can be constructed to determine additional characteristics such as window to wall ratio, height, number of stories and envelope thermal characteristics. In this paper we present three contributions to accelerate these high potential opportunities: (1) a methodical analysis of how these features can be integrated into today’s simulation and data driven software tools to enhance efficiency measure identification and owner/operator decision making; (2) development and accuracy testing of open source deep neural network methods to extract building footprints from satellite imagery, including the curation and application of openly available GIS datasets for training and continued development by others; and (3) an open framework for drone-based image capture and creation of 3D building geometries. This work represents an important bridge between high-level studies that span diverse application areas and those that detail point solutions yet cannot be easily replicated or extended.

Touzani, Samir↗

NASA NTRS1970

Computer discrimination procedures applicable to aerial and ERTS multispectral data

Two statistical models are compared in the classification of crops recorded on color aerial photographs. A theory of error ellipses is applied to the pattern recognition problem. An elliptical boundary condition classification model (EBC), useful for recognition of candidate patterns, evolves out of error ellipse theory. The EBC model is compared with the minimum distance to the mean (MDM) classification model in terms of pattern recognition ability. The pattern recognition results of both models are interpreted graphically using scatter diagrams to represent measurement space. Measurement space, for this report, is determined by optical density measurements collected from Kodak Ektachrome Infrared Aero Film 8443 (EIR). The EBC model is shown to be a significant improvement over the MDM model.

Richardson, A. J.↗

NASA NTRS1971

Computer identification of ground pattern from aerial photographs.

Two statistical models are comapared in the classification of crops recorded on color aerial photographs. A theory of error ellipses is applied to the pattern recognition problem. An elliptical boundary condition classification model (EBC), useful for recognition of candidate patterns, evolves out of error ellipse theory. The EBC model is compared with the minimum distance to the mean (MDM) classification model in terms of pattern recognition ability. The pattern recognition results of both models are interpreted graphically using scatter diagrams to represent measurement space. Measurement space, for this report, is determined by optical density measurements collected from Kodak Ektachrome Infrared Aero Film 8443 (EIR). The EBC model is shown to be a significant improvement over the MDM model.

Richardson, A. J.↗

NASA NTRS1974

Application of remote sensing for fishery resource assessment and monitoring

The author has identified the following significant results. A plot was drawn of the dolphin catch and the water discontinuities observed in the aerial photography. This plot was similar in format to the one made earlier on the white marlin catch relative to the water rips. Neither plot substantiates (as far as white marlin and dolphin are concerned) an opinion held by fishermen that better fishing may be found in the vicinity of the rips. Remotely inferred values for sea surface temperature, chlorophyll-a and turbidity were substituted for sea truth measurements in prediction models developed in previous analysis. Model performance, using the new values, was disappointing.

Savastano, K. J.↗

NASA NTRS1988

Uniformity of environmental conditions and plant growth in a hydroponic culture system for use in a growth room with aerial CO2 control

A portable system of hydroponic culture was developed that maintained temperature, pH, and nutrient concentrations of circulating nutrient solutions. The hydroponic system is used within a controlled-environment room (CER) for control of aerial environment. The CER was equipped with an auto-calibrating system for atmospheric CO2 control. The control systems for the hydroponic chambers were able to maintain acidity within +/- 0.2 pH units and the temperature with +/- 0.5 degree C. Mixing time for the 200-liter volume of solution within a hydroponic chamber was less than 12 min. The CO2 control system was able to maintain aerial concentrations within +/- 10 ppm CO2 during the light period. The only gradient found to occur within the hydroponic chambers or CER was a slight gradient in aerial temperature along the length of hydroponic chambers. Growth of soybeans [Glycine max (L.) Merr.] was characterized during a 3-week period of vegetative development by leaf number and area, plant dry weight, total N content of plants, and N depletion from the nutrient solution. The growth characteristics among populations for three hydroponic chambers within the CER were not significantly different, and the percent standard errors of means of the measurements within populations from each chamber were nearly all less than 10%. Thus, the uniformity of plant growth reflected the uniformity of environmental conditions.

NASA Discipline Life Support Systems↗

NASA NTRS2003

UAV Flight Control Using Distributed Actuation and Sensing

An array of effectors and sensors has been designed, tested and implemented on a Blended Wing Body Uninhabited Aerial Vehicle (UAV). This UAV is modified to serve as a flying, controls research, testbed. This effectorhensor array provides for the dynamic vehicle testing of controller designs and the study of decentralized control techniques. Each wing of the UAV is equipped with 12 distributed effectors that comprise a segmented array of independently actuated, contoured control surfaces. A single pressure sensor is installed near the base of each effector to provide a measure of deflections of the effectors. The UAV wings were tested in the North Carolina State University Subsonic Wind Tunnel and the pressure distribution that result from the deflections of the effectors are characterized. The results of the experiments are used to develop a simple, but accurate, prediction method, such that for any arrangement of the effector array the corresponding pressure distribution can be determined. Numerical analysis using the panel code CMARC verifies this prediction method.

Barnwell, William G.↗

NASA NTRS2003

Distributed Actuation and Sensing on an Uninhabited Aerial Vehicle

An array of effectors and sensors has been designed, tested and implemented on a Blended Wing Body Uninhabited Aerial Vehicle (UAV). The UAV is modified to serve as a flying, controls research, testbed. This effector/sensor array provides for the dynamic vehicle testing of controller designs and the study of decentralized control techniques. Each wing of the UAV is equipped with 12 distributed effectors that comprise a segmented array of independently actuated, contoured control surfaces. A single pressure sensor is installed near the base of each effector to provide a measure of deflections of the effectors. The UAV wings were tested in the North Carolina State University Subsonic Wind Tunnel and the pressure distribution that result from the deflections of the effectors are characterized. The results of the experiments are used to develop a simple, but accurate, prediction method, such that for any arrangement of the effector array the corresponding pressure distribution can be determined. Numerical analysis using the panel code CMARC verifies this prediction method.

Barnwell, William Garrard↗

NASA NTRS2016

Using Natural Language to Enable Mission Managers to Control Multiple Heterogeneous UAVs

The availability of highly capable, yet relatively cheap, unmanned aerial vehicles (UAVs) is opening up new areas of use for hobbyists and for commercial activities. This research is developing methods beyond classical control-stick pilot inputs, to allow operators to manage complex missions without in-depth vehicle expertise. These missions may entail several heterogeneous UAVs flying coordinated patterns or flying multiple trajectories deconflicted in time or space to predefined locations. This paper describes the functionality and preliminary usability measures of an interface that allows an operator to define a mission using speech inputs. With a defined and simple vocabulary, operators can input the vast majority of mission parameters using simple, intuitive voice commands. Although the operator interface is simple, it is based upon autonomous algorithms that allow the mission to proceed with minimal input from the operator. This paper also describes these underlying algorithms that allow an operator to manage several UAVs.

Trujillo, Anna C.↗

NASA NTRS2012

NASA Tech Briefs, January 2012

Contents of this issue are: (1) Energy-Based Tetrahedron Sensor for High-Temperature, High-Pressure Environments (2) Handheld Universal Diagnostic Sensor (3) Large-Area Vacuum Ultraviolet Sensors (4) Fiber Bragg Grating Sensor System for Monitoring Smart Composite Aerospace Structures (5) Health-Enabled Smart Sensor Fusion Technology (6) Extended-Range Passive RFID and Sensor Tags (7) Hybrid Collaborative Learning for Classification and Clustering in Sensor Networks (8) Self-Healing, Inflatable, Rigidizable Shelter (9) Improvements in Cold-Plate Fabrication (10) Technique for Radiometer and Antenna Array Calibration - TRAAC (11) Real-Time Cognitive Computing Architecture for Data Fusion in a Dynamic Environment (12) Programmable Digital Controller (13) Use of CCSDS Packets Over SpaceWire to Control Hardware (14) Key Decision Record Creation and Approval Module (15) Enhanced Graphics for Extended Scale Range (16) Debris Examination Using Ballistic and Radar Integrated Software (17) Data Distribution System (DDS) and Solar Dynamic Observatory Ground Station (SDOGS) (18) Integration Manager (19) Eclipse-Free-Time Assessment Tool for IRIS (20) Automated and Manual Rocket Crater Measurement Software (21) MATLAB Stability and Control Toolbox Trim and Static Stability Module (22) Patched Conic Trajectory Code (23) Ring Image Analyzer (24) SureTrak Probability of Impact Display (25) Implementation of a Non-Metallic Barrier in an Electric Motor (26) Multi-Mission Radioisotope Thermoelectric Generator Heat Exchangers for the Mars Science Laboratory Rover (27) Uniform Dust Distributor for Testing Radiative Emittance of Dust-Coated Surfaces (28) MicroProbe Small Unmanned Aerial System (29) Highly Stable and Active Catalyst for Sabatier Reactions (30) Better Proton-Conducting Polymers for Fuel-Cell Membranes (31) CCD Camera Lens Interface for Real-Time Theodolite Alignment (32) Peregrine 100-km Sounding Rocket Project (33) SOFIA Closed- and Open-Door Aerodynamic Analyses (34) Sonic Thermometer for High-Altitude Balloons (35) Near-Infrared Photon-Counting Camera for High-Sensitivity Observations (36) Integrated Optics Achromatic Nuller for Stellar Interferometry (37) High-Speed Digital Interferometry (38) Ultra-Miniature Lidar Scanner for Launch Range Data Collection (39) Shape and Color Features for Object Recognition Search (40) Explanation Capabilities for Behavior-Based Robot Control (41) A DNA-Inspired Encryption Methodology for Secure, Mobile Ad Hoc Networks (42) Quality Control Method for a Micro-Nano-Channel Microfabricated Device (43) Corner-Cube Retroreflector Instrument for Advanced Lunar Laser Ranging (44) Electrospray Collection of Lunar Dust (45) Fabrication of a Kilopixel Array of Superconducting Microcalorimeters with Microstripline Wiring Spacecraft Attitude Tracking and Maneuver Using Combined Magnetic Actuators (46) Coherent Detector for Near-Angle Scattering and Polarization Characterization of Telescope Mirror Coatings

Source record↗

NASA NTRS2018

A Prognostics Framework Development for Swarm Satellite Formations

Prognostics is the science of predicting the failure(s) of a component or a system and understanding how the performance will change in the event of a failure or degradation mechanism. With accurate predictions of possible failures, autonomous mitigative actions can be taken to correct/repair any issues or alert human operators of a failure threshold exceedance requiring condition-based maintenance. Although there is extensive research on failure predictions for a component or a system, there are significantly more opportunities to foray into failure predictions and prognostics for a system of systems such as an airspace consisting of multiple aircraft, a fleet of unmanned aerial vehicles, and a swarm of intelligent satellite systems. Failure prediction and mitigation are particularly important in autonomous systems such as satellite swarm systems that need effective resource management and minimal human interactions. Based on NASA's decadal survey, there is a clear need to prioritize the development of satellite swarm technology for studies of space physics and Earth science. The science community will propose future missions that return in-situ measurements from a 3-D (three-dimensional) volume of space, with relative spacecraft motion and inter-satellite baselines controlled according to the mission objectives. For such multi-spacecraft missions, it is required that ground operations resources do not scale with the number of satellites, thus compromising the swarm or leading to inefficiencies in resource allocation. Swarms of tens or hundreds of small satellites will require autonomy in attitude control, navigation and failure. Although significant research has been conducted in the areas of autonomous formation flying algorithms, less attention has been given to the development of resilient systems robust to failures.The focus of this research paper is the integration of model-based prognostics into the swarm dynamics control and decision-making algorithms. We simulate swarm management strategies for a subsystem failure to demonstrate the importance of failure predictions by comparing two cases: (i) no health information is provided to the system and utilized in the decision-making process and (2) system health information is obtained using prognostics and employed by the control system. One example scenario presented is for the GPS (Global Positioning System) system of an individual satellite to perform off-nominally due to increasing estimated error. In this scenario, the keep-out zone for that satellite would become more conservative, thereby decreasing the risk of collision. This is achieved via tuning the individual artificial repulsive functions assigned to each satellite.This paper is structured as follows. First we provide an overview of current swarm technology development, where we specifically use the term swarm to define multiple satellites flying in formation in similar orbits, with cross-link communication and station-keeping capabilities. Second, we give an introduction to the Swarm Orbital Dynamics Advisor (SODA), a tool that accepts high-level configuration commands and provides the orbital maneuvers required to achieve the prescribed formation configuration. Third, we provide the details of the model-based prognostics algorithm implementation in SODA. Finally, we present different case studies for potential component/subsystem failures and the swarm responses based with and without failure prediction information.

prognostics↗

NASA NTRS2004

Classification of Tropical Oceanic Precipitation Using High Altitude Aircraft Microwave and Electric Field Measurements

A physically intuitive and computationally simple precipitation mapping algorithm has been developed for use with the airborne Advanced Microwave Precipitation Radiometer (AMPR). The algorithm is based on microwave emission and scattering properties of precipitation. Specifically, emission by liquid water allows increasing brightness temperatures at low frequencies to be interpreted as increasing rain rates. Scattering by large hydrometeors (particularly graupel and hail) causes relative minima in the brightness temperatures, with progressively larger hydrometeors scattering progressively longer wavelengths. The vigor of convection is therefore ascertained according to which wavelengths are being significantly scattered. The combination of emission and scattering information from four microwave channels is used to assign a precipitation category, which is related to the liquid rain rate, the vertical extent of precipitation, and the vigor of convection. The qualitative precipitation categories output by the passive microwave algorithm have been verified using coincident radar (ER-2 Doppler Radar - EDOP) and electric field measurements (Lightning Instrument Package - LIP). These coincident measurements can subsequently be used to quantify rain rates, hydrometeor contents, and vertical profiles that are typical for each precipitation category. This algorithm has been developed using an airborne platform. Comparisons are being made with other airborne, satellite, and ground-based radar and radiometer data. This technique shows promise both as a research tool and potentially as a real-time analysis tool, which could be applied to either traditional or uninhabited aerial vehicles.

Cecil, Daniel J.↗

NASA NTRS2004

Classification of Tropical Oceanic Precipitation Using High Altitude Aircraft Microwave and Electric Field Measurements

Cecil, Daniel J.↗

NASA NTRS2018

Onboard Stereo Vision for Drone Pursuit or Sense and Avoid

Wedescribeanew,on-board,shortrangeperceptionsystem that enables micro aerial vehicles (MAVs) to detect, track, and follow or avoid nearby drones (within 2-20 meters) in GPS-denied environments. Each vehicle is able to sense its neighborhood and adapt its motion accordingly without use of centralized reasoning or inter-vehicle communication. To enable a lightweight, low power solution, on-board stereo cameras are used for detection and tracking with depth images, while a downward-looking camera and an inertial measurement unit are used to estimate the position of the observer without use of GPS. We illustrate the robustness and accuracy of this approach through real-time, outdoor leader-follower experiments with three quadrotors. Our experiments show that state-of-art trackers are far less robust in detection against cluttered background. This demonstrates that stereo vision is a highly effective approach to perception for safe navigation of multiple MAVs in close proximity.

Matthies, Larry↗

NASA NTRS2022

Determination of Chlorophyll Content in Selected Grass Communities of Krkonoše Mts. Tundra Based on Laboratory Spectroscopy and Aerial Hyperspectral Data

The study focuses on the determination of chlorophyll content in four prevailing grasses in the relict arctic-alpine tundra located in the Krkonoše Mountains National Park, Czech Republic. We compared two methods for determination of leaf chlorophyll content (LCC) – spectrophotometric determination in the laboratory, and the LCC assessed by fluorescence portable chlorophyll meter CCM-300. Relationships were established between the LCCs and vegetation indices calculated from leaf spectra acquired with contact probe coupled with an ASD FieldSpec4 Wide-Res spectroradiometer. Canopy chlorophyll contents (CCC) were computed from the LCCs and green leaf area index (LAI), and modelled based on the field spectra measured by the spectroradiometer and the hyperspectral images acquired by Headwall Nano-Hyperspec® mounted on the DJI Matrice 600 Pro drone. The calculations are performed on datasets acquired in June, July and August 2020 together and separately for species and months. In general, the correlations based on June datasets work the best at both levels: median R 2 for all indices was 0.52 for all species together at leaf level and median R 2 = 0.47 at the canopy level (vegetation indices computed from field spectra). Canopy chlorophyll content map was created based on the results of stepwise multiple linear regression. The R 2 was 0.42 when using four wavelengths from the red and red edge spectral region. We attribute the weak model performance to a combination of several factors: leaf structure may bias LCC from laboratory measurements, effects of LAI variability on CCC, and the sampling design, probably not covering the whole phenology equally for all studied species.

L. Cervena↗

DOE OSTI2020

Flexible Magnetic Polymer Composite Substrate with Ba 1.5 Sr 1.5 Z Hexaferrite Particles of VHF/Low UHF Patch Antennas for UAVs and Medical Implant Devices

Our goal is to fabricate flexible magnetic polymer composites as antenna substrates for very high frequency (VHF)/low ultra high frequency (UHF) antennas for unmanned aerial vehicles (UAVs) and medical devices. Magnetodielectric materials, which have permeability (μ) similar to permittivity (ε), have attracted great attention, because they facilitate miniaturization of microwave devices while keeping or enhancing electromagnetic characteristics. Mechanically millled Ba 1.5 Sr 1.5 Co 2 Fe 24 O 41 (Ba 1.5 Sr 1.5 Z) hexaferrite particles were used to increase permeability in the interesting frequency band. The microwave properties of Ba 1.5 Sr 1.5 Z composites were predicted and measured. Hansen’s zero-order analysis of antenna bandwidth and electromagnetic field simulation showed that the hexaferrite-based flexible composite could enhance a bandwidth and achieve the miniaturization of antennas as well. The magnetic antenna substrates can be a good solution to integrate antennas into the UAVs whose dimensions are comparable to or larger than communication wavelength.

36 MATERIALS SCIENCE↗

NASA NTRS2016

Design, Development, and Testing of a UAV Hardware-in-the-Loop Testbed for Aviation and Airspace Prognostics Research

The airspace is becoming more and more complicated, and will continue to do so in the future with the integration of Unmanned Aerial Vehicles (UAVs), autonomy, spacecraft, other forms of aviation technology into the airspace. The new technology and complexity increases the importance and difficulty of safety assurance. Additionally, testing new technologies on complex aviation systems & systems of systems can be very difficult, expensive, and sometimes unsafe in real life scenarios. Prognostic methodology provides an estimate of the health and risks of a component, vehicle, or airspace and knowledge of how that will change over time. That measure is especially useful in safety determination, mission planning, and maintenance scheduling. The developed testbed will be used to validate prediction algorithms for the real-time safety monitoring of the National Airspace System (NAS) and the prediction of unsafe events. The framework injects flight related anomalies related to ground systems, routing, airport congestion, etc. to test and verify algorithms for NAS safety. In our research work, we develop a live, distributed, hardware-in-the-loop testbed for aviation and airspace prognostics along with exploring further research possibilities to verify and validate future algorithms for NAS safety. The testbed integrates virtual aircraft using the X-Plane simulator and X-PlaneConnect toolbox, UAVs using onboard sensors and cellular communications, and hardware in the loop components. In addition, the testbed includes an additional research framework to support and simplify future research activities. It enables safe, accurate, and inexpensive experimentation and research into airspace and vehicle prognosis that would not have been possible otherwise. This paper describes the design, development, and testing of this system. Software reliability, safety and latency are some of the critical design considerations in development of the testbed. Integration of HITL elements in the development phases and veri cation/ validation are key elements to this report.

HITL↗