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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 289 records · Page 16
All sourcesNASA NTRSDOE OSTI
NASA NTRS1988

Characteristics of satellite breakups from radar cross section and plane change angle

A problem of considerable interest in orbital debris research is the determination of the cause of the fragmentation of a satellite from the observed radar cross section and orbital element data. In this paper, analytic representations of the observed distribution functions of the radar cross section and the orbital plane change angle are derived. This then allows for the extraction of a small number of features that describe the observed data. Based on the known cause of fragmentation of a subset of satellites, a linear classifier is trained on these derived features. The discriminant function derived from this training is used to determine the previously unknown cause of the satellite breakup. the technique developed is objective and has been applied to the study of the cause of a number of unknown satellite breakup events.

Badhwar, Gautam D.↗
NASA NTRS2014

Propulsion Electric Grid Simulator (PEGS) for Future Turboelectric Distributed Propulsion Aircraft

NASA Glenn Research Center, in collaboration with the aerospace industry and academia, has begun the development of technology for a future hybrid-wing body electric airplane with a turboelectric distributed propulsion (TeDP) system. It is essential to design a subscale system to emulate the TeDP power grid, which would enable rapid analysis and demonstration of the proof-of-concept of the TeDP electrical system. This paper describes how small electrical machines with their controllers can emulate all the components in a TeDP power train. The whole system model in Matlab/Simulink was first developed and tested in simulation, and the simulation results showed that system dynamic characteristics could be implemented by using the closed-loop control of the electric motor drive systems. Then we designed a subscale experimental system to emulate the entire power system from the turbine engine to the propulsive fans. Firstly, we built a system to emulate a gas turbine engine driving a generator, consisting of two permanent magnet (PM) motors with brushless motor drives, coupled by a shaft. We programmed the first motor and its drive to mimic the speed-torque characteristic of the gas turbine engine, while the second motor and drive act as a generator and produce a torque load on the first motor. Secondly, we built another system of two PM motors and drives to emulate a motor driving a propulsive fan. We programmed the first motor and drive to emulate a wound-rotor synchronous motor. The propulsive fan was emulated by implementing fan maps and flight conditions into the fourth motor and drive, which produce a torque load on the driving motor. The stator of each PM motor is designed to travel axially to change the coupling between rotor and stator. This feature allows the PM motor to more closely emulate a wound-rotor synchronous machine. These techniques can convert the plain motor system into a unique TeDP power grid emulator that enables real-time simulation performance using hardware-in-the-loop (HIL).

electric power grid emulator↗
NASA NTRS1999

NASA Langley Teacher Resource Center at the Virginia Air and Space Center

Nation's education goals through expanding and enhancing the scientific an technological competence of students and educators. To help disseminate NASA instructional materials and educational information, NASA's Education Division has established the Educator Resource Center Network. Through this network (ERCN), educators are provided the opportunity to receive free instructional information, materials, consultation, and training workshops on NASA educational products. The Office of Education at NASA Langley Research Center offers an extension of its Precollege Education program by supporting the NASA LARC Educator Resource Center at the Virginia Air & Space Center, the official visitor center for NASA LARC. This facility is the principal distribution point for educators in the five state service region that includes Virginia, West Virginia, Kentucky, North Carolina and South Carolina. The primary goal, to provide expertise and facilities to help educators access and utilize science, mathematics, and technology instructional products aligned with national standards and appropriate state frameworks and based on NASA's unique mission and results, has been accomplished. This ERC had 15,200 contacts and disseminated over 190,000 instructional items during the period of performance. In addition the manager attended 35 conferences, workshops, and educational meetings as an GR, presenter, or participant. The objective to demonstrate and facilitate the use of educational technologies has been accomplished through the following: The ERC's web page has been developed as a cyber-gateway to a multitude of NASA and other educational resources as well as to Our own database of current resource materials. NASA CORE CD-ROM technology is regularly demonstrated and promoted using the center's computers. NASA TV is available, demonstrated to educators, and used to facilitate the downlinking of NASA educational programming.

Maher, Kim L.↗
NASA NTRS2021

Loss of Control Detection for Commercial Transports Using Conditional Variational Autoencoders

This work describes a detector for the loss of control of a commercial transport in flight. The detector has a belief state defined by the latent variable stochastic modeling of a conditional variational autoencoder (CVAE) constructed with bidirectional recurrent layers. In 2000, the Boeing Company and the NASA Langley Research Center jointly developed a quantitative set of metrics for defining loss-of-control (LOC) for a commercial transport. We use the thresholds for these quantitative metrics to define a condition vector for training the CVAE. We demonstrate through experimentation that reconstruction probability is an accurate indicator that the vehicle has shifted to an LOC state. Second, we introduce a technique for inferring that the vehicle is experiencing a flight state change is approaching by measuring a shift in the sampling Gaussian distributions of the latent space. We provide an analysis of its applicability to flight data from a NASA generic commercial transport-type aircraft.

Newton H Campbell↗
NASA NTRS1975

Coastal Zone Classification from Satellite Imagery

The author has identified the following significant results. Studies of cover distribution along Delaware's coast, especially in tidal wetlands, were made utilizing semi-automated analysis of LANDSAT-1 MSS digital data. Cover maps with eleven vegetation and other cover categories were produced with accuracy of identification above 80% in all categories. Recent studies have tested a new technique for training automated analysis which uses ground measured reflectance and atmospheric correction techniques to derive signatures for specific categories in preference to the relative radiance signatures derived from training sets within the LANDSAT data itself. Initial tests using a four category scheme indicate that training data based on absolute measured reflectance and atmospheric correction of LANDSAT data can produce comparable accuracy of categorization to that achieved using more conventional relative radiance training.

Klemas, V.↗
NASA NTRS1976

Coastal zone classification from satellite imagery

The author has identified the following significant results. Studies of cover distribution along Delaware's coast, especially in tidal wetlands, were made, utilizing semi-automated analysis of LANDSAT-1 MSS digital data. Cover maps with eleven vegetation and other cover categories were produced with accuracy of identification above 80% in all categories. Recent studies have tested a new technique for training automated analysis which uses ground measured reflectance and atmospheric correction techniques to derive signatures for specific categories in preference to the relative radiance signatures derived from training sets within LANDSAT data itself. Initial tests using a four category scheme indicate that training data based on absolute measured reflectance and atmospheric correction of LANDSAT data can produce comparable accuracy of categorization to that achieved using more conventional relative radiance training. The analysis of the same four categories produced average categorization accuracies of 82.1% by conventional reflative radiance training and 81.9% by use of absolute reflectance signatures.

Klemas, V.↗
NASA NTRS2010

NATO Human View Architecture and Human Networks

The NATO Human View is a system architectural viewpoint that focuses on the human as part of a system. Its purpose is to capture the human requirements and to inform on how the human impacts the system design. The viewpoint contains seven static models that include different aspects of the human element, such as roles, tasks, constraints, training and metrics. It also includes a Human Dynamics component to perform simulations of the human system under design. One of the static models, termed Human Networks, focuses on the human-to-human communication patterns that occur as a result of ad hoc or deliberate team formation, especially teams distributed across space and time. Parameters of human teams that effect system performance can be captured in this model. Human centered aspects of networks, such as differences in operational tempo (sense of urgency), priorities (common goal), and team history (knowledge of the other team members), can be incorporated. The information captured in the Human Network static model can then be included in the Human Dynamics component so that the impact of distributed teams is represented in the simulation. As the NATO militaries transform to a more networked force, the Human View architecture is an important tool that can be used to make recommendations on the proper mix of technological innovations and human interactions.

Handley, Holly A. H.↗
NASA NTRS2016

Ultraviolet Satellite Measurements of Volcanic Ash

Ultraviolet (UV) remote sensing of volcanic ash and other absorbing aerosols from space began with the launch of the first Total Ozone Mapping Spectrometer (TOMS) instrument in 1978. Subsequent UV satellite missions (TOMS, GOME, SCIAMACHY, OMI, GOME-2, OMPS) have extended UV ash measurements to the present, generating a unique multidecadal record. A UV Aerosol Index (UVAI) based on two near-UV wavelengths, equally applicable to multispectral (TOMS, DSCOVR) or hyperspectral (GOME, SCIAMACHY, OMI, GOME-2, OMPS) instruments, has been used to derive a unique absorbing aerosol climatology across multiple UV satellite missions. Advantages of UV ash measurements relative to infrared (IR) techniques include the ability to detect ash at any altitude (assuming no clouds), above clouds, and over bright surfaces, where visible and IR techniques may fail. Disadvantages include the daytime-only restriction and nonspecificity to silicate ash, since UV measurements are sensitive to any UV-absorbing aerosol, including smoke, desert dust, and pollution. However, simultaneous retrieval of sulfur dioxide (SO2) abundance and UVAI provides robust discrimination of volcanic clouds. Although the UVAI is only semiquantitative, it has proved successful at detecting and tracking volcanic ash clouds from many volcanic eruptions since 1978. NASA A-Train measurements since 2006 (eg, CALIOP) have provided much improved constraints on volcanic ash altitude, and also permit identification of aerosol type through sensor synergy. Quantitative UV retrievals of ash optical depth, effective particle size, and ash column mass are possible and require assumptions of ash refractive index, particle size distribution, and ash layer altitude. The lack of extensive ash refractive index data in the UV-visible and the effects of ash particle shape on retrievals introduce significant uncertainty in the retrieved parameters, although limited validation against IR ash retrievals has been successful. In this contribution, we review UV ash detection and retrieval techniques and provide examples of volcanic eruptions detected in the approx. 37 year data record.

Multidecadal record↗
NASA NTRS1961

Applications of Power Spectral Analysis Methods to Maneuver Loads Obtained on Jet Fighter Airplanes During Service Operations

Power spectral densities of normal load factor have been obtained for two service operational training flights of a Republic F-84G airplane and three service operational training flights of a North American F-86A airplane in order to indicate the load-factor frequency content and possible uses of power spectral methods in analyzing maneuver load data. It was determined that the maneuvering load-factor time histories appeared to be described by a truncated normal distribution. The power spectral densities obtained were relatively level at frequencies below 0.03 cycle per second and varied inversely with approximately the cube of the frequency at the higher frequencies. In general, the frequency content was very low above 0.2 cycle per second. The load-factor peak distributions were estimated fairly well from the spectrum analysis. In addition, peak load data obtained during service operations of fighter-type airplanes with flight time totaling about 24,000 hours were examined and appeared to agree reasonably well with the type of equations obtained from spectrum peak-load distributions.

Mayer, John P.↗
NASA NTRSDate not supplied

Eleven Countries, an Integrated Spacecraft: the Story of International Collaboration that Built the Orion Spacecraft and Powered the Success of the Artemis I Mission

The quest to return humans to the Moon in the next step towards humanity's exploration of space is more alive than ever. After a great deal of achievements, failures, and lessons learned, the Artemis I mission set o to the Moon on November 16, 2022, with the goal of testing a new rocket, the Space Launch System, and a new spacecraft, Orion: designed, assembled, and tested across two continents, and 11 countries. Behind this mission, decades of experience with the International Space Station, Autonomous Transfer Vehicle operations, and many other program collaborations built the know-how on how to succeed together in the toughest environment | deep space. The Artemis I mission proved to be an incredible success, meeting 161 total mission objectives, including 21 developed during the flight based on outperforming spacecraft. It was also a case-study in international collaboration, given that ESA, NASA, and industry partners Airbus and Lockheed Martin for the first time had to design, build, test, and fly a fully integrated human-rated spacecraft, with most critical functions dependent and interconnected across U.S. and European systems. The U.S.-built Orion Crew Module and Crew Module Adapter and European-built European Service Module (ESM) shared critical interfaces and commodities, from propulsion, avionics, active/passive thermal, electrical power generation, storage and distribution to the software that managed it all. In this paper, we will describe relevant aspects of the integrated spacecraft design, providing context for the challenges that the team faced in all phases required to get Orion ready to fly, and provide a direct account of how the joint team formed, trained, and supported the operations of the successful Artemis I mission. We will also explore the evolution of the partnerships, given that these allow a multi-national e ort to sustain the program production, share costs, leverage a broader base of engineering expertise, and build more diverse capabilities over the long haul to support the Artemis goals and objectives. Lastly, we will cover critical lessons learned and how the Orion Program has implemented these in preparation of the next Artemis missions to repeat the success of Artemis I. The purpose of this paper is to document knowledge we gained and lessons we learned through the development of an integrated Orion spacecraft, since it is imperative we build on this now, at the dawn of the Artemis Program, an international endeavor to push human space exploration.

Deep Space Exploration↗
NASA NTRS1973

Estimation of proportions of objects and determination of training sample-size in a remote sensing application

A multichannel scanning device may fail to observe objects because of obstructions blocking the view, or different categories of objects may make up a resolution element giving rise to a single observation. Ground truth will be required on any such categories of objects in order to estimate their expected proportions associated with various classes represented in the remote sensing data. Considering the classes to be distributed as multivariate normal with different mean vectors and common covariance, maximum likelihood estimates are given for the expected proportions of objects associated with different classes, using the Bayes procedure for classification of individuals obtained from these classes. An approximate solution for simultaneous confidence intervals on these proportions is given, and thereby a sample-size needed to achieve a desired amount of accuracy for the estimates is determined.

Chhikara, R. S.↗
NASA NTRS2017

One Giant Leap to Protect All Mankind: An Overview of the Lunar Receiving Laboratory

Motivation. In 1961, President John F. Kennedy charged the nation "to land a man on the moon and return him safely to Earth." Eight years later, the Apollo 11 astronauts splashed down in the Pacific Ocean after this first 8-day journey to the moon. As humans had never ventured to another extraterrestrial body, the U.S. government noted the great uncertainty associated with the unknown exposures related to this historic mission. Overview. With this uncertainty in mind, a newly formed Interagency Committee on Back Contamination (ICBC) was established to review the potential for lunar contaminants and establish the prevention of their escape into the biosphere during crew and sample recovery operations from the floating command module to the mobile quarantine facility on the recovery ship and return to the Johnson Space Center. Significance. As a result of the ICBC recommendations, in 1966 NASA planned and built the Lunar Receiving Laboratory (LRL) at the Johnson Space Center in Houston, Texas. The LRL served a great role in service of human space exploration to quarantine Apollo crewmembers, their space vehicles, and the lunar samples collected. Almost an afterthought in the space race to the Moon, the 83,000-square-foot LRL was designed and completed in 1967 for $7.8 million. The core purpose of the LRL was "to protect the public's health, agriculture, and other living resources; to provide lunar sample distribution to approved scientific investigators; and to preserve the scientific integrity of the lunar samples at all times." Its layout was comprised of three major zones: a quarantined Crew Area, a separate but also quarantined Sample Operations Area, and a Support and Administration Area outside the controlled biological barrier. This facility required trained personnel to live and perform within it for several weeks post-flight, to include astronaut crewmembers, flight surgeons, scientists, and vehicle recovery engineers. The LRL holds memories of these historic events but has since been repurposed for NASA's medical and environmental sciences activities, in what is now known as Building 37. As we approach its 50th anniversary, the LRL story will end in demolition as NASA advances its facilities for the next steps in human exploration of space. Learning Objectives: 1. To capture the historical relevance of the NASA Lunar Receiving Laboratory 2. To understand the requirements of receiving crew and samples from the moon for the first time 3. To describe the facility capabilities in protection of public health.

Hayes, Judith↗
NASA NTRS2016

A Multi-Sensor Water Vapor, Temperature and Cloud Climate Data Record: Status of Our MEaSUREs 2012 Project

- Our primary objectives: Incorporate all A-Train water vapor, including small-scale, horizontal and vertical water vapor structure from MODIS (Moderate Resolution Imaging Spectroradiometer) and GPS (Global Positioning System); Use MODIS cloud classification that is collocated at the pixel-scale over the full AIRS/AMSU (Atmospheric Infrared Sounder/Advanced Microwave Sounding Unit) swath; Extend summaries to PDFs (Probability Distribution Functions)/higher order moments of water vapor sorted by cloud classes; Establish robust, scale-dependent statistical relationships between cloud, temperature, and water vapor PDFs for the climate modeling community. - We will also: Update our current data record to new CloudSat/CALIPSO (Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation) cloud classification; Provide merged AIRS and MLS (Microwave Limb Sounder) water vapor profiles using averaging kernels; Include temperature and water vapor from models (ECMWF - European Centre for Medium-Range Weather Forecasts) and re-analyses (MERRA - Modern Era-Retrospective Analysis for Research and Applications); Classify METOP-A (Meteorological Operational Satellite-A) and NOAA (National Oceanic and Atmospheric Administration) satellite water vapor with AVHRR (Advanced Very High Resolution Radiometer) during SNOs (Solar Neutrino Oscillations); Compare with the NVAP-M (re-analysis and extension of the NASA Water Vapor Project (NVAP)) water vapor climatologies; Use existing data sources and mature algorithms, and document processing algorithms.

Fetzer, Eric↗
NASA NTRS2017

Flow and Noise From Septa Nozzles

This investigation pertains to distributed propulsion system. Basically, the jet exhaust is divided and channeled through multiple compartments or septa. In one version of the concept each septum is to be driven by an electric fan, the power being supplied by engines suitably mounted on the airframe. In the latter hybrid case the need for heavy power trains is eliminated and system studies indicate a net benefit in efficiency. From aeroacoustics point of view, however, there are concerns. An immediate question is whether the noise from the multiple jets would be equal to or greater than that from an equivalent single jet. When multiple jets are placed side by side sometimes they resonate and produce more noise. In order to address these issues a fundamental model-scale experiment is being carried out at NASA Glenn Research Center (GRC). Preliminary results from this study have been presented recently. One of the key findings is that the noise from the septa nozzle can actually be less than that from the equivalent single nozzle. Continued studies make it clear that the flow from the septa nozzle may be quite sensitive to upstream passage geometry in each septum. This can have a profound impact on the evolution of the flow downstream as well as noise. These issues are currently being researched. The proposed paper is to summarize the results from the mainly experimental study that is to be aided by limited numerical simulation.

nozzle flow↗
NASA NTRS2017

TPSAS-NF1676L-26965-DND

A comprehensive understanding of the spatial and temporal distributions of clouds on a global scale can be best achieved when the vertical distributions and multi-layer occurrence frequencies obtained from active remote sensors are fully integrated with the horizontal distributions currently provided by passive sensors. The Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) satellite lidar onboard the Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO) spacecraft was specially designed to acquire aerosol and cloud profiles with unprecedented high vertical resolution and accuracy. As a part of the A-Train satellite constellation, CALIPSO has been operating routinely for more than 10 years and continues to provide a wealth of cloud observations to describe the mean state and inter-annual variability. Recently a suite of level 3 (L3) cloud products has been under development by the CALIPSO lidar science working group at the NASA Langley Research Center. These products describe 3-dimensional (3D) cloud occurrence and 3D ice cloud extinction coefficients and ice water content. Future evolution of the products will add observations from the Imaging Infrared Radiometer onboard CALIPSO. Here we present a brief introduction and provide results from a product prototype. We will characterize the inter-annual vertical variability of zonal cloud occurrence and ice water content during the last 10 years. Suggestions and comments are welcome to help us design and provide better cloud climatology products using CALIOP observations for our cloud community.

Xia Cai↗
NASA NTRS1980

Development of alternative data analysis techniques for improving the accuracy and specificity of natural resource inventories made with digital remote sensing data

An investigation was conducted into ways to improve the involvement of state and local user personnel in the digital image analysis process by isolating those elements of the analysis process which require extensive involvement by field personnel and providing means for performing those activities apart from a computer facility. In this way, the analysis procedure can be converted from a centralized activity focused on a computer facility to a distributed activity in which users can interact with the data at the field office level or in the field itself. A general image processing software was developed on the University of Minnesota computer system (Control Data Cyber models 172 and 74). The use of color hardcopy image data as a primary medium in supervised training procedures was investigated and digital display equipment and a coordinate digitizer were procured.

Lillesand, T. M.↗
NASA NTRS2019

Automatically Finding Ship-Tracks to Enable Large-Scale Analysis of Aerosol-Cloud Interactions

Ship tracks appear as long winding linear features in satellite images and are produced by aerosols from ship exhausts changing low cloud properties. They are one of the best examples of aerosol‐cloud interaction experiments. However, manually finding ship tracks from satellite data on a large scale is prohibitively costly while a large number of samples are required to improve our understanding. Here we train a deep neural network to automate finding ship tracks. The neural network model generalizes well as it not only finds ship tracks labeled by human experts but also detects those that are occasionally missed by humans. It finds more ship tracks than all previous studies combined and produces a map of ship track distributions off the California coast that matches well with known shipping traffic. Our technique will enable studying aerosol effects on low clouds using ship tracks on a large scale, which will potentially narrow the uncertainty of the aerosol‐cloud interactions.

aerosol cloud interactions↗
NASA NTRS1981

Comparison of wheat classification accuracy using different classifiers of the image-100 system

Classification results using single-cell and multi-cell signature acquisition options, a point-by-point Gaussian maximum-likelihood classifier, and K-means clustering of the Image-100 system are presented. Conclusions reached are that: a better indication of correct classification can be provided by using a test area which contains various cover types of the study area; classification accuracy should be evaluated considering both the percentages of correct classification and error of commission; supervised classification approaches are better than K-means clustering; Gaussian distribution maximum likelihood classifier is better than Single-cell and Multi-cell Signature Acquisition Options of the Image-100 system; and in order to obtain a high classification accuracy in a large and heterogeneous crop area, using Gaussian maximum-likelihood classifier, homogeneous spectral subclasses of the study crop should be created to derive training statistics.

Dejesusparada, N.↗