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NASA NTRS1987

Synthetic estimation filters for a control system

Hybrid optical correlators, which use spatial light modulators and solid state imagers to interface computers and optical Fourier correlators, will allow the rapid changing of filters and digital pre- or post-correlation processing in vision systems. However, optical correlation (particulary with phase-only filtration) is notoriously sensitive to mismatches of rotation and magnification between the reference image and the input image. Such sharpness is not always desirable if the correlation pattern is to be used in a control system. Two methods of conforming the response of an inherently sharp-response optical correlation to an in plane rotation between reference and object images are discussed. The objective is to condition the correlation for better suitability to a vision-controlled system. The first method is controlled convolutional blurring of a reference image followed by construction of a matched filter (perhaps implemented as a phase-only filter). An alternative is discussed in more detail: it is a synthesis from sharp filters, so weighted as to produce a specified off-center behavior.

Juday, Richard D.↗

NASA NTRS1990

Orthogonal subspaces for correlation masking

A digital correlation mask that induces orthogonality among a prescribed set of reference imagery is described. In this particular implementation, the resulting correlation is undersampled and shift-variant, though if it is applied to optical correlators, those limitations are removed. A method of introducing orthogonality among the weights among the training set from which filter values are obtained is derived, so that the correlation value from a given filter is representative of the unique nature of the reference object as compared against the other objects in the training class.

Juday, Richard D.↗

NASA NTRS2004

Metadata and Buckets in the Smart Object, Dumb Archive (SODA) Model

We present the Smart Object, Dumb Archive (SODA) model for digital libraries (DLs), and discuss the role of metadata in SODA. The premise of the SODA model is to "push down" many of the functionalities generally associated with archives into the data objects themselves. Thus the data objects become "smarter", and the archives "dumber". In the SODA model, archives become primarily set managers, and the objects themselves negotiate and handle presentation, enforce terms and conditions, and perform data content management. Buckets are our implementation of smart objects, and da is our reference implementation for dumb archives. We also present our approach to metadata translation for buckets.

Nelson, Michael L.↗

NASA NTRS1991

Advanced Photovoltaic Experiment, S0014: Preliminary Flight Results and Post-Flight Findings

The Advanced Photovoltaic Experiment (APEX) is an LDEF experiment designed to provide reference solar cell standards for laboratory measurements as well as to investigate the solar spectrum and the effects of long term exposure of solar cells to the LEO environment. Silicon and gallium arsenide solar cells were flown with the appropriate instrumentation to periodically measure cell performance and temperature. The experimental objectives, the design employed to realize these objectives and the solar cells and instrumentation selected for the flight are presented. A discussion of the flight data returned are included. Preliminary results from the post flight analysis of the absolute cavity radiometer, the digital solar angle sensor, and the Barr Associates narrow bandpass optical filters are also presented. The initial findings of work to determine the chemical nature of contamination layers on APEX are also presented.

Brinker, David J.↗

NASA NTRS1981

SEM analysis of ionizing radiation effects in an analog to digital converter /AD571/

The considered investigation is concerned with the study of the total-dose degradation mechanisms in an IIL analog to digital (A/D) converter. The A/D converter is a 10 digit device having nine separate functional units on the chip which encompass several hundred transistors and circuit elements. It was the objective of the described research to find the radiation sensitive elements by a systematic search of the devices on the LSI chip. The employed technique using a scanning electron microscope to determine the functional blocks of an integrated circuit which are sensitive to ionizing radiation and then progressively zeroing in on the soft components within those blocks, proved extremely successful on the AD571. Four functional blocks were found to be sensitive to radiation, including the Voltage Reference, DAC, IIL Clock, and IIL SAR.

Gauthier, M. K.↗

NASA NTRS1975

The 4D area navigation system description and flight test results

A 4D area navigation system was designed to guide aircraft along a prespecified flight path (reference path) such that the aircraft would arrive at the approach gate at a time specified by the ATC controller. Key components to achieve this requirement were: (1) stored reference trajectories; (2) a continuously recomputed capture trajectory to a selected waypoint on the reference trajectory so as to achieve the desired time of arrival; (3) electronic situation displays; and (4) a control system to follow the overall trajectory in space and time. The system was implemented in a digital integrated avionics system (STOLAND) installed on a CV-340 airplane. Although the 4D system was designed primarily for automatic operation, it was flight tested in a flight director mode (the pilot follows the flight director commands), because the CV-340 autopilot servos were not tied to the avionics system. The flight test showed that, even in the flight director mode, the pilot did achieve the objectives of path tracking and time of arrival control with only moderate workload. The system also permitted controlled delay of the time of arrival by path stretching, which takes advantage of the continuously changing capture trajectory to predict the time of arrival. Simulations in the automatic and manual modes were used to complement the flight data.

Lee, H. Q.↗

NASA NTRS1989

CSM research: Methods and application studies

Computational mechanics is that discipline of applied science and engineering devoted to the study of physical phenomena by means of computational methods based on mathematical modeling and simulation, utilizing digital computers. The discipline combines theoretical and applied mechanics, approximation theory, numerical analysis, and computer science. Computational mechanics has had a major impact on engineering analysis and design. When applied to structural mechanics, the discipline is referred to herein as computational structural mechanics. Complex structures being considered by NASA for the 1990's include composite primary aircraft structures and the space station. These structures will be much more difficult to analyze than today's structures and necessitate a major upgrade in computerized structural analysis technology. NASA has initiated a research activity in structural analysis called Computational Structural Mechanics (CSM). The broad objective of the CSM activity is to develop advanced structural analysis technology that will exploit modern and emerging computers, such as those with vector and/or parallel processing capabilities. Here, the current research directions for the Methods and Application Studies Team of the Langley CSM activity are described.

Knight, Norman F., Jr.↗

NASA NTRSDate not supplied

Real World Applications of AI/ML in Optimizing Airspace Operations

As National Airspace System (NAS) is going through the Digital Transformation journey, data science and analytics methods can significantly contribute to improving the traditional physics-based decision-making tools. The adoption of AI/ML methods will not only help accelerate Federal Aviation Administration (FAA)’s vision of Info-centric NAS but also contribute to the overall objective of sustainable aviation. AI/ML can improve the ground and airspace operations by enhancing the accuracy of current decision-making tools used by the airlines and the FAA to manage traffic on the ground and in the air. Huge amount of data that gets collected during a flight. AI/ML methods can extract information from this data and provide valuable insights to make better operational decisions. NASA has partnered with the FAA and commercial airlines such as American and Southwest Airlines on this effort and has successfully demonstrated the benefits of using ML in real world environment by reducing delays and optimizing ground operations at the US airports. In 2022 itself, NASA demonstrated real-world benefits (over 24K lbs. of fuel savings, over 76.6K lbs. CO2 emission savings, and several hours of delay savings) by deploying ML based prediction models to optimize ground operations at Dallas/Fort Worth International and Dallas Love Field Airports in Texas. These tools are being deployed on the cloud for broader deployment, adaptability, and scalability. NASA is developed a reference implementation of the cloud-based platform to significantly lower the bar to development and distribution of these digital services for aviation. In this talk, I will share information about the Digital Information Platform project, the novel AI/ML based approaches used for optimizing ground operations and the opportunities to partner with NASA on these demonstrations.

air traffic management↗

NASA NTRS1979

New techniques in television to provide research in three-dimensional real-time or near real-time imagery and reduced cost systems for teleconferencing and educational uses, part 1

The results are presented of a continuing research and development program the objective of which is to develop a reduced bandwidth television system and a technique for television transmission of holograms. The result of the former is a variable frame rate television system, the operation of which was demonstrated for both black-and-white and color signals. This system employs a novel combination of the inexpensive mass storage capacity of a magnetic disc with the reliability of a digital system for time expansion and compression. Also reported are the results of a theoretical analysis and preliminary feasibility experiment of an innovative system for television transmission of holograms using relatively conventional TV equipment along with a phase modulated reference wave for production of the original interference pattern.

Pao, Y. H.↗

NASA NTRS1979

Digital adaptive controllers for VTOL vehicles. Volume 1: Concept evaluation

A digital self-adaptive flight control system was developed for flight test in the VTOL approach and landing technology (VALT) research aircraft (a modified CH-47 helicopter). The control laws accept commands from an automatic on-board guidance system. The primary objective of the control laws is to provide good command-following with a minimum cross-axis response. Three attitudes and vertical velocity are separately commanded. Adaptation of the control laws is based on information from rate and attitude gyros and a vertical velocity measurement. The final design resulted from a comparison of two different adaptive concepts--one based on explicit parameter estimates from a real-time maximum-likelihood estimation algorithm, the other based on an implicit model reference adaptive system. The two designs were compared on the basis of performance and complexity.

Hartmann, G. L.↗

NASA NTRS1980

In-flight calibration of the fine pointing Sun sensor on the solar maximum mission

The attitude control objectives of solar maximum mission are to point the boresight of the payload fine pointing sun sensor (FPSS) to any point within 30 arc-minutes of the Sun's center with an accuracy of 5 arc-seconds (3 sigma, pitch and yaw) and a jitter of less than 3 arc-seconds (3 sigma). To meet these stringent accuracy requirements, a procedure was developed for in-flight calibration of the FPSS. The spacecraft was maneuvered using FPSS offset commands to position the Sun at different points within the FPSS field of view. The coefficients of the FPSS digital to analog nonlinear transfer function were determined by minimizing the residuals between the pitch and yaw angles computed from the FPSS measurements and the corresponding reference angles obtained from inertial reference unit measurements. The actual in-flight calibration and the calibration algorithm are discussed.

Gambardella, P. J.↗

NASA NTRSDate not supplied

Application of ML/AI for Identifying Earth Science Datasets in Research Publications

NASA Data Active Archive Centers, or DAACs, ingest, store and distribute data acquired from satellites, ground systems as well as modelling data. These data are organized by the datasets, each presenting collection of files usually associated with the certain mission, instrument, processing level, parameter(s), algorithm and/or model. The number of datasets offered by a single DAAC to the public varies. GES DISC, for example, currently offers for public use approximately ~1,300 datasets. While each publicly offered dataset comes with supporting documentation, it is challenging for novice and even experienced scientists to navigate among the datasets that offer similar parameters to find the datasets for their particular research application. Supplying dataset documentation with the scientific paper citations that refer to that dataset provides means for the dataset users to educate themselves with the application research that dataset is being used in. Collecting citations of the papers that use the datasets for their research yield valuable insights into application areas of those datasets, information about usage of the dataset groups for specific applications and those application topics. It also gives insights into the “deep metrics” of the dataset usage, as opposed to the common metrics of the dataset usage such as number of users who downloaded the dataset files and volumes of downloaded data. Association of a certain scientific paper with the dataset(s) presents a challenge because most of the paper authors do not properly cite the datasets, datasets usually have cryptic names and Digital Object Identifiers (DOIs) that are used for dataset identification were assigned to the datasets only few years ago. Simple Google or online library search do not provide even meaningful fraction of the results when performed by the dataset name or DOI, however they provide too many results when the search is done by more broader terms such as mission and instrument names. Attempts to create an AI system capable to identify dataset in the scientific papers have already been made using neural networks classifiers on the basis of the dataset mission, instrument and variable name. This method was applied to NASA SEDAC, which has 41 datasets in total. In GES DISC there can be as many as ~100 datasets per mission/instrument with some of the datasets consisting of multiple variables so there is a need for more differentiating parameters for dataset identification in the paper. The approach we are currently investigating is creating AI classifiers that are based on multiple dataset features, or keywords, extracted from the NASA Earthdata Common Dataset Repository (CMR). The features are weighted based on how precisely they can identify a dataset. The classifier uses preprocessed paper text as input and searches for the CMR datasets whose feature sets are the closest to the feature sets contained in the paper. The challenges of dataset identification include variety of ways the paper authors describe the datasets in their papers and incomplete tagging of the CMR dataset description (DIFs).

Irina Gerasimov↗

NASA NTRS2009

Land-Use and Land-Cover Change around Mobile Bay, Alabama from 1974-2008

This document summarizes the major findings of a Gulf of Mexico Application Pilot project led by NASA Stennis Space Center (SSC) in conjunction with a regional collaboration network of the Gulf of Mexico Alliance (GOMA). NASA researchers processed and analyzed multi-temporal Landsat data to assess land-use and land-cover (LULC) changes in the coastal counties of Mobile and Baldwin, AL between 1974 and 2008. Our goal was to create satellite-based LULC data products using methods that could be transferable to other coastal areas of concern within the Gulf of Mexico. The Mobile Bay National Estuary Program (MBNEP) is the primary end-user, however, several other state and local groups may benefit from the project s data products that will be available through NOAA-NCDDC s Regional Ecosystem Data Management program. Mobile Bay is a critical ecologic and economic region in the Gulf of Mexico and to the entire country. Mobile Bay was designated as an estuary of national significance in 1996. This estuary receives the fourth largest freshwater inflow in the United States. It provides vital nursery habitat for commercially and recreationally important fish species. It has exceptional aquatic and terrestrial bio-diversity, however, its estuary health is influenced by changing LULC patterns, such as urbanization. Mobile and Baldwin counties have experienced a population growth of 1.1% and 20.5% from 2000-2006. Urban expansion and population growth are likely to accelerate with the construction and operation of the ThyssenKrupp steel mill in the northeast portion of Mobile County. Land-use and land-cover change can negatively impact Gulf coast water quality and ecological resources. The conversion of forest to urban cover types impacts the carbon cycle and increases the freshwater and sediment in coastal waters. Increased freshwater runoff decreases salinity and increases the turbidity of coastal waters, thus impacting the growth potential of submerged aquatic vegetation (SAV), which is critical nursing ground for many Gulf fish species. A survey of Mobile Bay SAV showed widespread decreases since the 1940s. Prior to our project, coastal environmental managers in Baldwin and Mobile counties needed more understanding of the historical LULC for properly assessing the impacts of urbanization. In particular, more information on the location and extent of changing urbanization LULC patterns was needed to aid LULC planning and to assess predictions of future LULC patterns. Our products will assist the coastal environmental managers and land-use planners in making better community growth planning decisions. Our project also will help to establish a historical baseline of LULC distributions, which is a fundamental need in any stewardship plan. The primary research objective of our project was to produce historic and current geospatial LULC change products across a 34-year time frame. A multi-decadal coastal LULC change product was the major project deliverable. The geographic extent and nature of change was quantified and assessed for the upland herbaceous, barren, open water, urban, upland forest, woody wetland, and non-woody wetlanddominated land cover types. We focused on regional analyses of decadal-scale urban expansion and watershed-scaled analyses of LULC change for multiple areas of concern to the Mobile Bay NEP (Figure A). We used the following dates to derive LULC classification products from Landsat data: 1974, 1979, 1984, 1988, 1991, 1996, 2001, 2005, and 2008. We assessed the accuracy of our products using randomly sampled locations and digital geospatial reference data including field survey data, high resolution orthorectified aerial photography, high resolution multispectral and panchromatic satellite data displays (from QuickBird and Corona sensors), digital elevation model data, and National Wetlands Inventory wetland cover type data. NOAA s Coastal Change Assessment Program s (C-CAP) and National Land Cover Database (NLCD) procts were used for qualitative comparison in assessing map accuracy. We calculated an average overall classification accuracy of 87% with similar overall accuracies for the older (MSS) and newer (TM and ETM) Landsat LULC products.

Ellis, Jean↗

NASA NTRS1973

Airborne Laser Polar Nephelometer

A polar nephelometer has been developed at NCAR to measure the angular variation of the intensity of light scattered by air molecules and particles. The system has been designed for airborne measurements using outside air ducted through a 5-cm diameter airflow tube; the sample volume is that which is common to the intersection of a collimated source beam and the detector field of view within the airflow tube. The source is a linearly polarized helium-neon laser beam. The optical system defines a collimated field-of-view (0.5deg half-angle) through a series of diaphragms located behind a I72-mm focal length objective lens. A photomultiplier tube is located immediately behind an aperture in the focal plane of the objective lens. The laser beam is mechanically chopped (on-off) at a rate of 5 Hz; a two-channel pulse counter, synchronized to the laser output, measures the photomultiplier pulse rate with the light beam both on and off. The difference in these measured pulse rates is directly proportional to the intensity of the scattered light from the volume common to the intersection of the laser beam and the detector field-of-view. Measurements can be made at scattering angles from 15deg to 165deg with reference to the direction of propagation of the light beam. Intermediate angles are obtained by selecting the angular increments desired between these extreme angles (any multiple of 0.1deg can be selected for the angular increment; 5deg is used in normal operation). Pulses provided by digital circuits control a stepping motor which sequentially rotates the detector by pre-selected angular increments. The synchronous photon-counting system automatically begins measurement of the scattered-light intensity immediately after the rotation to a new angle has been completed. The instrument has been flown on the NASA Convair 990 airborne laboratory to obtain data on the complex index of refraction of atmospheric aerosols. A particle impaction device is operated simultaneously to collect particles from the same airflow tube used to make the scattered-light measurements. A size distribution function is obtained by analysis of the particles collected by the impaction device. Calculated values of the angular variation of the scattered-light intensity are obtained by applying Mie scattering theory to the observed size distribution function and assuming different values of the complex index of refraction of the particles. The calculated values are then compared with data on the actual variation of the scattered-light intensity obtained with the polar nephelometer. The most probable value of the complex refractive index is that which provides the best fit between the experimental light scattering data and the parameters calculated from the observed size distribution function.

Grams, Gerald W.↗

NASA NTRS1990

Hybrid vision activities at NASA Johnson Space Center

NASA's Johnson Space Center in Houston, Texas, is active in several aspects of hybrid image processing. (The term hybrid image processing refers to a system that combines digital and photonic processing). The major thrusts are autonomous space operations such as planetary landing, servicing, and rendezvous and docking. By processing images in non-Cartesian geometries to achieve shift invariance to canonical distortions, researchers use certain aspects of the human visual system for machine vision. That technology flow is bidirectional; researchers are investigating the possible utility of video-rate coordinate transformations for human low-vision patients. Man-in-the-loop teleoperations are also supported by the use of video-rate image-coordinate transformations, as researchers plan to use bandwidth compression tailored to the varying spatial acuity of the human operator. Technological elements being developed in the program include upgraded spatial light modulators, real-time coordinate transformations in video imagery, synthetic filters that robustly allow estimation of object pose parameters, convolutionally blurred filters that have continuously selectable invariance to such image changes as magnification and rotation, and optimization of optical correlation done with spatial light modulators that have limited range and couple both phase and amplitude in their response.

Juday, Richard D.↗

NASA NTRS1997

Optical Sensors for Use in Propulsion Control Systems

This final technical report describes the results of a cooperative effort which was originally established between John Carroll University and the Instrumentation and Control Technology Division at NASA Lewis Research Center on November, 1982, and then continued with the Engine Sensor Technology Branch at NASA Lewis until March, 1995. All work at John Carroll University was directed by the principal investigator of this grant, Klaus Fritsch, Ph.D. For the first two years of this grant this effort was supervised at NASA by Mr. Robert J. Baumbick and for the remainder of the grant by Dr. Glenn M. Beheim. All research was carried out in close cooperation with Dr. Beheim. Electrically passive optical sensors for measurands such as pressure, temperature, position, and rotational speed are required for aircraft engine control in fly-by-light digital aircraft control systems. Fiberoptic data links and optical multiplexing techniques should be used for combining and processing the outputs from several sensors, sharing as many optical end electronic parts as possible. The overall objective of this grant was to explore techniques for designing and constructing such electrically passive optical sensors for measuring physical parameters in jet aircraft engines and for use in aircraft control systems. We have concentrated our efforts on pressure, temperature, and position sensors employing techniques which are relatively immune to transmissivity variations of the fiber links and to variations in intensity of the light source. Infrared light-emitting diodes are employed because of their longevity and immunity to vibration. We have also studied a number of multiplexing techniques. On the following pages I will give thumbnail sketches of the projects carried out under this grant and provide references to publications and John Carroll M.S. theses which resulted directly from this work and which describe these projects in greater detail.

Fritsch, Klaus↗

NASA NTRS2023

Spacesuit Fit and Mobility Assessments by Digital Human Modeling

Spacesuit Fit and Mobility Assessments by Digital Human Modeling K. Han Kim (Leidos, Inc.) Elizabeth A. Benson (KBR, Inc.) Sudhakar L. Rajulu (NASA Johnson Space Center) Spacesuits are required to accommodate safe operations for astronauts across gender and a wide variety of body shapes and sizes. This goal has been of particular importance given the increasing diversity of NASA crewmembers for upcoming Missions. While testing with design prototypes is a critical step for spacesuit development, iterative mockup design, fabrication, and human subject tests can be extremely costly and time consuming. Moreover, testing with a limited subject pool has often raised questions for validity, as test subjects need to represent the entire astronaut population, not only of the past or current, but also the future. This study is aimed at demonstrating how digital human modeling (DHM) tools have been built and directly supported NASA spacesuit developments. With DHM, the computer aided design (CAD) model of a spacesuit was integrated with human body models. Two use scenarios are presented in this paper, namely fit and mobility. For fit assessments, the suit-to-body contact and compression patterns were estimated using 3D human body scan models virtually wearing a spacesuit model. A statistical fit classifier was made from the contact patterns and applied against a large database of body scans (N=2,500). With this technique, the NASA reference design spacesuit Exploration EVA Mobility Unit (xEMU)was verified to accommodate 90% of the astronaut-like population, with the critical dimensions covering 1stto 99thpercentiles of the target body measurements. A similar technique assessed XEMU mobility. The maximum reach envelopes were considered, within which the work objects and critical hardware interfaces should be located for safe and ergonomic operations. While the reach envelope geometry varies significantly with the suit wearer’s body size and strength, the existing test data did not include the subjects critically required to define suit mobility requirements, such as very small females or large males. Using the xEMU virtual model kinematically simulated and permuted for a hypothetical wearer, however, the existing data were statistically transformed and scaled. This method enabled for a parametric estimation of the reach envelopes from the 1stpercentile female or 99thpercentile male. The outcome was successfully incorporated for requirement developments. With the new DHM tools, human integration of the spacesuit was structurally simulated and predictively assessed, which would have been otherwise impossible. Also, the needs for iterative mockup and subject tests were significantly reduced, which resulted in time and cost saving. Additional work is in progress to integrate additional vehicles, tools, and hardware with DHM framework.

K Han Kim↗

NASA NTRSDate not supplied

Transcribing Air Traffic Control System Command Center Planning Telecons Using Cloud-Based Automatic Speech Recognition

This paper addresses the challenge of using Automatic Speech Recognition (ASR) technology to transcribe regular teleconferences that happen between FAA Air Traffic Control System Command Center (ATCSCC) planners, stakeholders and air users. These planning teleconferences (aka telecons or planning webinars) are an integral part of managing air traffic in the U.S. National Airspace System (NAS). In particular, the meetings facilitate the creation and modification of various traffic management initiatives (TMIs), that are used to regulate the flow of air traffic. This is typically a human intensive process, requiring specialists to listen to the entire meeting audio (10-20 minutes duration) and inferring the state of the NAS (e.g., weather phenomenon) that was discussed. It would be advantageous to have digital transcripts of the audio and have useful information (e.g., related to TMIs) automatically extracted from the transcripts. In this regard, we are exploring the adoption of state-of-the-art speech to text and Natural Language Processing (NLP) tools that will achieve our objective of digitizing the webinar audio. Unfortunately, the highly technical phraseology present in the audio and limited data availability for model building make ASR difficult. To overcome this challenge, we have taken the critical first step in creating a human transcription dataset from ~20 hours of speech in the ATCSCC audio with the help of subject matter experts. A novelty of our work is the creation of a ground truth transcription dataset for ATCSCC teleconference webinars, which is particularly important for Aviation domain-specific NLP tasks. Using Microsoft Speech Studio, a cloud-based ASR platform, we have fine-tuned the English pre-trained ASR models (available in speech studio) and achieved an average word error rate (WER) of 6.81%. The baseline ASR also provides a digital version of each planning webinar, making it accessible and text-searchable for future references. Additionally, the transcriptions can serve as a bridge between raw audio data and a range of text-based NLP tasks, such as named entity recognition (NER) and intent classification, potentially enhancing the digital footprint of the webinars and other connected data sources. Our work has several potential applications. Firstly, the transcriptions can be analyzed to understand the complex decision process of creating, implementing and modifying TMIs and may also contribute to TMI prediction services. Secondly, our dataset and model can be used to develop more accurate ASR systems for aviation-specific language, which can bring about digital communication in the aviation industry (and aid current “voice only” communications, which are inherently error-prone). Lastly, the transcriptions themselves can be used as a valuable resource for training other NLP models.

Stephen S. B. Clarke↗