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All sourcesNASA NTRSDOE OSTI
NASA NTRS2000

Karst Groundwater Hydrologic Analyses Based on Aerial Thermography

On February 23, 1999, thermal imagery of Marshall Space Flight Center, Alabama was collected using an airborne thermal camera. Ground resolution was I in. Approximately 40 km 2 of thermal imagery in and around Marshall Space Flight Center (MSFC) was analyzed to determine the location of springs for groundwater monitoring. Subsequently, forty-five springs were located ranging in flow from a few ml/sec to approximately 280 liter/sec. Groundwater temperatures are usually near the mean annual surface air temperature. On thermography collected during the winter, springs show up as very warm spots. Many of the new springs were submerged in lakes, streams, or swamps; consequently, flow measurements were difficult. Without estimates of discharge, the impacts of contaminated discharge on surface streams would be difficult to evaluate. An approach to obtaining an estimate was developed using the Environmental Protection Agency (EPA) Cornell Mixing Zone Expert System (CORMIX). The thermography was queried to obtain a temperature profile down the center of the surface plume. The spring discharge was modeled with CORMIX, and the flow adjusted until the surface temperature profile was matched. The presence of volatile compounds in some of the new springs also allowed MSFC to unravel the natural system of solution cavities of the karst aquifer. Sampling results also showed that two springs on either side of a large creek had the same water source so that groundwater was able to pass beneath the creek.

Campbell, C. Warren↗
NASA NTRS2007

NASA Tech Briefs, February 2007

Topics covered include: Calibration Test Set for a Phase-Comparison Digital Tracker; Wireless Acoustic Measurement System; Spiral Orbit Tribometer; Arrays of Miniature Microphones for Aeroacoustic Testing; Predicting Rocket or Jet Noise in Real Time; Computational Workbench for Multibody Dynamics; High-Power, High-Efficiency Ka-Band Space Traveling-Wave Tube; Gratings and Random Reflectors for Near-Infrared PIN Diodes; Optically Transparent Split-Ring Antennas for 1 to 10 GHz; Ice-Penetrating Robot for Scientific Exploration; Power-Amplifier Module for 145 to 165 GHz; Aerial Videography From Locally Launched Rockets; SiC Multi-Chip Power Modules as Power-System Building Blocks; Automated Design of Restraint Layer of an Inflatable Vessel; TMS for Instantiating a Knowledge Base With Incomplete Data; Simulating Flights of Future Launch Vehicles and Spacecraft; Control Code for Bearingless Switched- Reluctance Motor; Machine Aided Indexing and the NASA Thesaurus; Arbitrating Control of Control and Display Units; Web-Based Software for Managing Research; Driver Code for Adaptive Optics; Ceramic Paste for Patching High-Temperature Insulation; Fabrication of Polyimide-Matrix/Carbon and Boron-Fiber Tape; Protective Skins for Aerogel Monoliths; Code Assesses Risks Posed by Meteoroids and Orbital Debris; Asymmetric Bulkheads for Cylindrical Pressure Vessels; Self-Regulating Water-Separator System for Fuel Cells; Self-Advancing Step-Tap Drills; Array of Bolometers for Submillimeter- Wavelength Operation; Delta-Doped CCDs as Detector Arrays in Mass Spectrometers; Arrays of Bundles of Carbon Nanotubes as Field Emitters; Staggering Inflation To Stabilize Attitude of a Solar Sail; and Bare Conductive Tether for Decelerating a Spacecraft.

Source record↗
NASA NTRS2024

Quantification of Uncertainty and Risk Sensitivity for Safety of Emerging Operations

The growing need to develop and deploy small unmanned aerial vehicles (sUAVs) for various applications in the airspace necessitates reliable tools to accurately predict the flight trajectories of the sUAVs. The knowledge of the predicted trajectories help decision makers anticipate potential conflict, assess the risk, and take appropriate risk mitigation actions. In addition, uncertainties in vehicle models, weather, and controller action further highlights the need for reliable prediction tools. In this project, the application of mixed sparse grid-based quadrature and generalized polynomial chaos(gPC) expansion method for uncertainty quantification and collision assessment in air traffic consisting of fixed-wing small unmanned aerial vehicles (sUAV) was studied. From the results obtained, it can be concluded that this provides a reliable framework to carry out quantitative conflict assessment in an unmanned air traffic, which when employed, can improve the functionalities of the unmanned traffic management system. It was observed that the results from the gPC expansion framework developed in the project can be utilized to conduct rapid probabilistic collision assessment for near real-time unmanned traffic management in the airspace. From the vehicle models, position updates, and wind-field data, a priori gPC based 3-σcon-fidence ellipses can provide estimates of potential conflict at some future instants. The computational costs scaled linearly when the uncertain inputs were fewer. Further, the largest allowable distribution of para-metric uncertainties that leads to the smallest risk of collision in traffic of small unmanned aerial vehicles could be calculated. The time of closest approach between two sUAVs can be established paving way for development of proactive mitigation strategies. The separation between the sUAVs was found to be most significantly affected by uncertainties in the maximum available thrusts, zero-lift drag coefficients, and wing planform areas of the sUAVs. The study of uncertain wind-fields indicated that a heterogeneous traffic mix resulted in an increased probability of conflict. Increased measurement update rate reduced the uncertain-ties in the trajectories of the vehicles, further reducing the probability of conflict but rapid updates of all vehicles in the airspace poses a stringent communication limitation. The gPC framework also provided the means to analyze vehicle impact (crash region) due to loss of control resulting from actuator failure in sUAS traffic, essentially to predict impact and crash zones for representative vehicles. The predicted regions when compared with non-participant density, provides a means to develop an early mitigation strategy, should the sUAV detect an imminent actuator failure.

Rajnish Bhusal↗
NASA NTRS2019

Health Management and Prognostics for Electric Aircraft Powertrain

W and c Any air borne vehicle needs incorporating safety as key parameter of measure, and inclusion of autonomy raises the critical need for safety under autonomous operations. Management of faults and component degradation is key as complexity in autonomous operations grow over the period of time. Therefore, in addition to basic operational requirements, an autonomous electric vehicle should be able to make accurate estimates of its current system health and take the correct decisions to complete its mission successfully. Real-time safety and state-awareness tools are therefore essential for the vehicle to be able to reach its destination in a safe and successful manner. The need for safety assurance and health management capabilities is particularly relevant for aircraft electric propulsion systems, which are relatively new and with limited historical to learn. They are critical systems requiring high power density along with reliability, resilience, efficient management of weight, and operational costs. A model- based fault diagnosis and prognostics approach of complex critical systems can successfully accomplish the safety and state awareness goal for such electric propulsion systems, enabling autonomous decision making capability for safe and efficient operation. To identify critical components in the system a Qualitative Bayesian approach using FMECA is implemented. This requires the assessment of some quantities representing the state of the electric unmanned aerial systems (e-UAS), as well as look-ahead forecasts of such states during the entire flight, presented in form of safety metrics (SM). In-service data and performance data gathered from degraded components sup- ports diagnostic and prognostic methods for these systems, but this data can be difficult to obtain as weight and packaging restrictions reduce redundancy and instrumentation on-board the vehicle. Therefore, an model-based framework should be capable or operating with limited data. In addition to data scarcity, the variability of such complex critical systems re- quires the model-based framework to reason in the presence of uncertainty, such as sensor noise, and modeling imperfections. Quantification of errors and uncertainties in the measured states and quantities is therefore a fundamental step for a precise estimation of such SMs; un-modeled uncertainty may result in erroneous state assessment and un- reliable predictions of future states of e-UAVs. Typical, centralized model-based schemes suffer from inherent disadvantages such as computational complexity, single point of failure, and scalability issues, and therefore may fail in such a complex scenario. This paper presents a methodology for developing a system level diagnostics and prognostics approach using a Qualitative Bayesian FMECA approach along with a formal uncertainty management framework for an e-UAS. In this work we demonstrate the efficacy of the framework to predict effects of sub-system level degradation on vehicle operation incorporating uncertainty management to predict future behavior under different operating conditions.

Kulkarni, Chetan↗
DOE OSTI2021

Multi-sensor agent devices

Apparatus, methods, and systems implementing multi-sensor agent devices are described herein. The agent devices can each include a plurality of sensors for measuring parameters of interest to an entity such as an electric power utility. The sensors can be organized in individually-IP-addressable sensor clusters, with each sensor cluster including an associated microcontroller. The agent devices can be controlled by a control center of the entity to operate in a coordinated manner, such as to gather and transmit data regarding parameters of interest. The agent devices can be transported to desired areas for data collection by unmanned aerial systems such as drones, and the collected data can be stored in a distributed blockchain ledger.

Fuhr, Peter L.↗
DOE OSTI2020

Coupling Remote Sensing and Sonar Measurements to Estimate Availability of Suitable Backwater Nursery Habitat for Colorado Pikeminnow

Low-velocity channel-margin habitats serve as important nursery habitats for the endangered Colorado pikeminnow (Ptychocheilus lucius) in the middle Green River between Jensen and Ouray, Utah. These habitats, known as backwaters, are associated with emergent sandbars and are shaped and reformed annually by peak flows. Recent knowledge about backwater characteristics and dynamics was summarized in a synthesis report (Grippo et al. 2015) that was based on detailed annual survey data collected from a relatively small sample of backwaters between 2003 to 2014 and reach-wide evaluations of backwater surface area based on manual interpretation of aerial and satellite imagery. Methods that bridge the gap between the detailed surveys from a small number of backwaters and reach-wide assessments of their surface area would enable an improved assessment of the availability of backwater habitats that provide suitable depths for young-of-the-year (YOY) Colorado pikeminnow.

13 HYDRO ENERGY↗
NASA NTRS1977

The remote sensing of algae

State agencies need rapid, synoptic and inexpensive methods for lake assessment to comply with the 1972 Amendments to the Federal Water Pollution Control Act. Low altitude aerial photography may be useful in providing information on algal type and quantity. Photography must be calibrated properly to remove sources of error including airlight, surface reflectance and scene-to-scene illumination differences. A 550-nm narrow wavelength band black and white photographic exposure provided a better correlation to algal biomass than either red or infrared photographic exposure. Of all the biomass parameters tested, depth-integrated chlorophyll a concentration correlated best to remote sensing data. Laboratory-measured reflectance of selected algae indicate that different taxonomic classes of algae may be discriminated on the basis of their reflectance spectra.

Thorne, J. F.↗
NASA NTRS2001

Use of the Aerosonde Unihabited Aerial Vehicle (UAV) in the Fourth Convection and Moisture Experiment (CAMEX 4)

The Fourth Convection and Moisture Experiment (CAMEX 4) was a scientific field experiment based in Florida in summer 2001 focused on the study of hurricanes off the east coast of the United States. Sponsored by the National Aeronautics and Space Administration's Office of Earth Science, and conducted in collaboration with the National Oceanic and Atmospheric Administration's annual hurricane research program, CAMEX 4 utilized aircraft, ground-based and satellite instrumentation to obtain unprecedented, three dimensional characterizations of these important storms. The Aerosonde UAV was selected by NASA to participate in CAMEX 4 because it provided a unique capability to obtain measurements in the atmospheric boundary layer in and around the storms, unattainable by other platforms or measurement capabilities. This talk focuses on the NASA review process that was followed to coordinate the UAV activity with the conventional aircraft operations, as well as with the other participating agencies and the FAA. We will discuss how Aerosonde addressed the issues of safety, coordination and communication and summarize the lessons learned.

Hipskind, R. Stephen↗
NASA NTRS1983

Beaufort/Bering 1979 microwave remote sensing data catalog report, 14-24 March 1979

The airborne microwave remote sending measurements obtained by the Langley Research Center in support of the 1979 Sea-Ice Radar Experiment (SIRE) in the Beaufort and Bering Seas are discussed. The remote sensing objective of SIRE was to define correlations between both active and passive microwave signatures and ice phenomena assocated with practical applications in the Arctic. The instruments used by Langley during SIRE include the stepped frequency microwave radiometer (SFMR), the airborne microwave scatterometer (AMSCAT), the precision radiation thermometer (PRT-5), and metric aerial photography. Remote sensing data are inventoried and cataloged in a user-friendly format. The data catalog is presented as time-history plots when and where data were obtained as well as the sensor configuration.

Hirstein, W. S.↗
NASA NTRS2014

Spectroscopic Measurement Techniques for Aerospace Flows

The conditions that characterize aerospace flows are so varied, that a single diagnostic technique is not sufficient for its measurement. Fluid dynamists use knowledge of similarity to help categorize and focus on different flow conditions. For example, the Reynolds number represents the ratio of inertial to viscous forces in a flow. When the velocity scales, length scales, and gas density are large and the magnitude of the molecular viscosity is low, the Reynolds number becomes large. This corresponds to large scale vehicles (e.g Airbus A380), fast moving objects (e.g. artillery projectiles), vehicles in dense fluids (e.g. submarine in water), or flows with low dynamic viscosity (e.g. skydiver in air). In each of these cases, the inertial forces dominate viscous forces, and unsteady turbulent fluctuations in the flow variables are observed. In contrast, flows with small length scales (e.g. dispersion of micro-particles in a solid rocket nozzle), slow moving objects (e.g. micro aerial vehicles), flows with low density gases (e.g. atmospheric re-entry), or fluids with a large magnitude of viscosity (e.g. engine coolant flow), all have low Reynolds numbers. In these cases, viscous forces become very important and often the flows can be steady and laminar. The Mach number, which is the ratio of the velocity to the speed of sound in the medium, also helps to differentiate types of flows. At very low Mach numbers, acoustic waves travel much faster than the object, and the flow can be assumed to be incompressible (e.g. Cessna 172 aircraft). As the object speed approaches the speed of sound, the gas density can become variable (e.g. flow over wing of Learjet 85). When the object speed is higher than the speed of sound (Ma > 1), the presences of shock waves and other gas dynamic features can become important to the vehicle performance (e.g. SR-71 Blackbird). In the hypersonic flow regime (Ma > 5), large changes in temperature begin to affect flow properties, causing real-gas effects to occur (e.g. X-43 Scramjet). At even higher Mach numbers, chemistry and nonequilibrium effects come into play (e.g. Startdust re-entry capsule), further complicating the measurement. These limits can be predicted by calculating the ratio of chemical and thermal relaxation time to the flow time scales. Other non-dimensional numbers can be used to further differentiate types of aerospace flows.

Danehy, Paul M.↗
DOE OSTI2026

The U.S. DOE ARM User Facility Establishes a New Site for Studies of Land–Aerosol–Cloud Interactions in the Southeastern United States

The U.S. Department of Energy (DOE) Atmospheric Radiation Measurement (ARM) user facility has established a new site in the Bankhead National Forest (BNF) in northern Alabama that will gather data on how clouds, the land surface, and aerosols interact at a hierarchy of scales important to understanding and simulating the Earth system. Starting its operations in October 2024, the BNF site provides a multi-year opportunity for scientists to unravel complex land-atmosphere interactions. A suite of ground-based sensors, elevated tower-based instrumentation, and aerial facilities will enable scientists to investigate those interactions from within the canopy to the clouds. The Southeastern United States was recommended by the DOE ARM and its collaborators in the broader community as an important region to address their common scientific questions given the region’s abundant surface-forced convective clouds and mesoscale convective systems that pose ongoing challenges in Earth system models. The region is also home to significant terrain complexity and land-use heterogeneity that will unleash new understanding of anthropogenic and biogenic aerosol processes, boundary-layer aerosol-cloud interactions, and the interactions between the terrestrial ecosystem and coupled aerosol-cloud-radiation processes.

Aerosols↗
NASA NTRS1985

Mega-geomorphology and neotectonics

For several decades, subtle neotectonic effects involving several square kilometers have been studied in detail using remote sensing, primarily various types of stereo-aerial photographs at scales of 1:10,000 to 1:80,000. These subtle effects, especially local uplifts associated with growing structures of differential compaction, have been detected by the effect on drainage patterns, changes in hydraulic geometry of individuals channels or groups of channels, tonal halos (soil) and fracture patterns. The studies were extended with the advent of thermal IR imagery particularly in tonal analysis, and SLAR primarily in fracture pattern studies. Lately, quantitative efforts have begun attempting to link measured uplift over known structures with measured changes in hydraulic geometry and alluvial deposition. Thus, efforts are now underway attempting to quantify the relationship between neo- (micro-) tectonic changes and geomorphic parameters of drainage systems.

Lattman, L. H.↗
NASA NTRS2011

NASA's Internal Space Weather Working Group

Measurements from many of NASA's scientific spacecraft are used routinely by space weather forecasters, both in the U.S. and internationally. ACE, SOHO (an ESA/NASA collaboration), STEREO, and SDO provide images and in situ measurements that are assimilated into models and cited in alerts and warnings. A number of years ago, the Space Weather laboratory was established at NASA-Goddard, along with the Community Coordinated Modeling Center. Within that organization, a space weather service center has begun issuing alerts for NASA's operational users. NASA's operational user community includes flight operations for human and robotic explorers; atmospheric drag concerns for low-Earth orbit; interplanetary navigation and communication; and the fleet of unmanned aerial vehicles, high altitude aircraft, and launch vehicles. Over the past three years we have identified internal stakeholders within NASA and formed a Working Group to better coordinate their expertise and their needs. In this presentation we will describe this activity and some of the challenges in forming a diverse working group.

St. Cyr, O. C.↗
NASA NTRS1973

Analysis of remotely sensed data for detecting soil limitations

During 1971 and 1972 a detailed study was conducted on a fallow field in the proposed Oahe Irrigation Project to determine the relationship between the tonal variation observed on aerial photographs and the properties of eroded soil. Correlation and regression analysis of digitized, multiemulsion, color infrared film (2443) data and detailed field data revealed a highly significant correlation between film transmittance and several soil properties indicative of the erosion limitation. Computer classification of the multiemulsion film data resulted in maps portraying the eroded soil and the normal soil. Both correlation and computer classification results were best using the reflectance data from the red spectral band. The results showed film transmittance was actually measuring the reflectivity of the soil surface which was increased by the incorporation of the light colored, calcareous parent material exposed by erosion or tillage on soils with thin surface horizons.

Benson, L. A.↗
NASA NTRS1973

The use of aerial photography to quantitatively delineate mixing zones - A progress report

Aerial photography has been used to characterize and model the mixing zones which result from waste effluent discharges at seven river sites throughout the state of Wisconsin. The mixing zone is defined as the portion of the river where the waste effluent is totally mixed with the ambient receiving water. An integrated program of field sampling, mathematical modeling, laboratory modeling, and remote sensing was conducted to develop a quantitative relationship for the volumetric configuration of the mixing zone as a function of the measurable characteristics of various effluents, outfalls, and receiving water bodies. Analysis of scanning microdensitometer data extracted from 9-in. color IR transparencies has confirmed the utility of employing image density measurements to quantitatively delineate surficial concentration patterns within the mixing zone.

Lillesand, T. M.↗
NASA NTRS2019

Scenario Complexity for Unmanned Aircraft System Traffic

This work introduces an approach to estimate the complexity of a low-altitude air traffic scenario involving multiple UASs using mathematical programming. Given a set of multi-point UAS flight trajectories, vehicle dynamics, and a conflict resolution algorithm, an abstract model is developed such that it can be solved quickly using a mathematical programming optimization software without running high-fidelity simulations that can be computationally expensive and may not suit real-time apA quick and accurate assessment of complexity for a given traffic scenario can help plan and schedule flights to alleviate traffic bottleneck and mitigate operation risks, especially for unmanned aerial system traffic management where high traffic density or complexity is expected. This work introduces a traffic scenario complexity metric that was constructed based on the number of potential conflicts weighted by the conflict resolution cost associated. The cost associated with a conflict is calculated based on the corresponding conflict resolution maneuvers. To obtain the conflict resolution maneuvers, a MILP-based optimization was formulated with the vehicle model and conflict management parameters incorporated. To evaluate the complexity metrics, an approach of using measurements from high-fidelity simulations was proposed. The scenario complexity measurements for 920 random-generated scenarios were obtained through high-fidelity simulations and treated as the ground truth. Two statistics methods: Pearson and Alternative Conditional Expectations were applied for analysis. The results showed that the number of flights has low correlation with the scenario complexity according to the correlation coefficients calculated by both methods. The Alternative Conditional Expectations method shows that the proposed scenario complexity metric has better correlation with the ground truth than the number of potential conflicts.plications. In the abstract model, each vehicle is represented by a time-varied vector associated with position, speed, and heading information. The total extra distance that aircraft need to divert from their original routes to avoid collisions is computed and used to setup a quadratic programming formula. The metrics including the number of conflicts and extra distances travelled by all vehicles are then utilized to estimate the complexity of a given UAS flight scenario. Results and verification against high-fidelity simulations will be provided in the final draft.

traffic complexity↗
NASA NTRS2011

Algorithm for Autonomous Landing

Because of their small size, high maneuverability, and easy deployment, micro aerial vehicles (MAVs) are used for a wide variety of both civilian and military missions. One of their current drawbacks is the vast array of sensors (such as GPS, altimeter, radar, and the like) required to make a landing. Due to the MAV s small payload size, this is a major concern. Replacing the imaging sensors with a single monocular camera is sufficient to land a MAV. By applying optical flow algorithms to images obtained from the camera, time-to-collision can be measured. This is a measurement of position and velocity (but not of absolute distance), and can avoid obstacles as well as facilitate a landing on a flat surface given a set of initial conditions. The key to this approach is to calculate time-to-collision based on some image on the ground. By holding the angular velocity constant, horizontal speed decreases linearly with the height, resulting in a smooth landing. Mathematical proofs show that even with actuator saturation or modeling/ measurement uncertainties, MAVs can land safely. Landings of this nature may have a higher velocity than is desirable, but this can be compensated for by a cushioning or dampening system, or by using a system of legs to grab onto a surface. Such a monocular camera system can increase vehicle payload size (or correspondingly reduce vehicle size), increase speed of descent, and guarantee a safe landing by directly correlating speed to height from the ground.

Kuwata, Yoshiaki↗
NASA NTRS1975

Study to develop improved spacecraft snow survey methods using Skylab/EREP data

The author has identified the following significant results. Of the four black and white S190A camera stations, snowcover is best defined in the two visible spectral bands, due in part to their better resolution. The overall extent of the snow can be mapped more precisely, and the snow within shadow areas is better defined in the visible bands. Of the two S190A color products, the aerial color photography is the better. Because of the contrast in color between snow and snow-free terrain and the better resolution, this product is concluded to be the best overall of the six camera stations for detecting and mapping snow. Overlapping frames permit stereo viewing, which aids in distinguishing clouds from the underlying snow. Because of the greater spatial resolution of the S190B earth terrain camera, areal snow extent can be mapped in greater detail than from the S190A photographs. The snow line elevation measured from the S190A and S190B photographs is reasonable compared to the meager ground truth data available.

Barnes, J. C.↗