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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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All sourcesNASA NTRSDOE OSTI
NASA NTRS2012

Water Detection Based on Color Variation

This software has been designed to detect water bodies that are out in the open on cross-country terrain at close range (out to 30 meters), using imagery acquired from a stereo pair of color cameras mounted on a terrestrial, unmanned ground vehicle (UGV). This detector exploits the fact that the color variation across water bodies is generally larger and more uniform than that of other naturally occurring types of terrain, such as soil and vegetation. Non-traversable water bodies, such as large puddles, ponds, and lakes, are detected based on color variation, image intensity variance, image intensity gradient, size, and shape. At ranges beyond 20 meters, water bodies out in the open can be indirectly detected by detecting reflections of the sky below the horizon in color imagery. But at closer range, the color coming out of a water body dominates sky reflections, and the water cue from sky reflections is of marginal use. Since there may be times during UGV autonomous navigation when a water body does not come into a perception system s field of view until it is at close range, the ability to detect water bodies at close range is critical. Factors that influence the perceived color of a water body at close range are the amount and type of sediment in the water, the water s depth, and the angle of incidence to the water body. Developing a single model of the mixture ratio of light reflected off the water surface (to the camera) to light coming out of the water body (to the camera) for all water bodies would be fairly difficult. Instead, this software detects close water bodies based on local terrain features and the natural, uniform change in color that occurs across the surface from the leading edge to the trailing edge.

Rankin, Arturo L.↗
NASA NTRS2015

NASA CYGNSS Mission Applications Workshop

NASA's Cyclone Global Navigation Satellite System, (CYGNSS), mission is a constellation of eight microsatellites that will measure surface winds in and near the inner cores of hurricanes, including regions beneath the eyewall and intense inner rainbands that could not previously be measured from space. The CYGNSS-measured wind fields, when combined with precipitation fields (e.g., produced by the Global Precipitation Measurement [GPM] core satellite and its constellation of precipitation imagers), will provide coupled observations of moist atmospheric thermodynamics and ocean surface response, enabling new insights into hurricane inner core dynamics and energetics. The outcomes of this workshop, which are detailed in this report, comprise two primary elements: (1) A report of workshop proceedings, and; (2) Detailed Applications Traceability Matrices with requirements and operational considerations to serve broadly for development of value-added tools, applications, and products.

Amin, Aimee V.↗
NASA NTRSDate not supplied

Venus Global Reference Atmospheric Model (Venus-GRAM) Upgrades

Introduction: The Venus Global Reference Atmospheric Model (Venus-GRAM) is one of the most widely used engineering models of Venus’ atmosphere. The Venus-GRAM upgrades are being developed by NASA Marshall Space Flight Center (MSFC) and NASA Langley Research Center (LaRC). This presentation will provide details regarding the upgrades that have been made to Venus-GRAM and the ongoing objectives, tasks, and milestones related to the GRAM upgrades funded by the NASA Science Mission Directorate (SMD). Venus-GRAM: Venus-GRAM is an engineering-oriented atmospheric model that estimates mean values and statistical variations of the atmospheric properties of Venus. Venus-GRAM provides mean values and variability for any point in the atmosphere as well as seasonal, geographic, and altitude variations. Venus-GRAM outputs include atmospheric density, temperature, pressure, winds, and chemical composition along a user-defined path. It is extensively used by the engineering community because of its ability to create realistic dispersions. GRAMs have been integrated into high fidelity flight dynamic simulations of launch, entry, descent and landing (EDL), aerobraking and aerocapture. GRAMs are currently available for Earth, Mars, Venus, Neptune, Titan, and Uranus. The lower atmosphere model in Venus-GRAM (up to 250 km) is based on the Venus International Reference Atmosphere (VIRA) [1]. The Venus-GRAM thermosphere (250 to 1000 km) is based on a MSFC-developed model [2] which assumes an isothermal temperature profile initialized using VIRA conditions at 250 km [3]. The VIRA version included in Venus-GRAM includes Pioneer Venus Orbiter and Probe data as well as Venera probe data, but it does not include a solid planet model or a high-resolution gravity model [4]. Venus-GRAM Upgrade Status: Code Modernization. Venus-GRAM has been rearchitected from Fortran to a common object-oriented C++ framework called the GRAM Suite. This new architecture creates a common GRAM library of data models and utilities. The first C++ release of the rearchitected Venus-GRAM is a straight conversion from the latest Fortran version. Model Upgrades. The focus of the model upgrade task is to improve the atmosphere models in the existing GRAMs and to establish a foundation for developing GRAMs for additional destinations. The GRAM ephemeris has been upgraded to the NASA Navigation and Ancillary Information Facility (NAIF) SPICE toolkit (version N0066). The calculation of the speed of sound has also been improved in the GRAMs. In FY20, the GRAM project established contracts to improve the model data within Venus-GRAM. Hampton University is developing an empirical global model for Venus. The University of Wisconsin is reanalyzing the Venus Express radio occultation observations and analyzing the Akatsuki thermal imaging data. Upgraded Venus-GRAM Release. GRAM Suite Version 1.3 will be released in September 2021 and will contain the rearchitected Venus-GRAM, including the common GRAM framework and planet–specific code. A User Guide and Programmer’s Manual are released with all GRAMs. Conclusions: GRAMs are frequently used toolsets and vital in assessing effects of atmospheres on interplanetary spacecraft during the program life cycle process. Releases of the GRAM Suite, upgrades of the existing planetary GRAMs, and development of new planetary GRAMs are ongoing. Venus-GRAM atmosphere model upgrades will be included in the next phase of GRAM tasks. References: [1] Kliore, A. J. et al. (1985) ASR, 5, 11, 1-304. [2] Justh, H. L. et al. (2006) AIAA/AAS Astrodynamics Specialist Conference & Exhibit, Abstract AIAA-2006-6394. [3] Guide to Reference and Standard Atmosphere Models, BSR/AIAA G-003-2010. [4] Limaye, S. S. (2012), LPSC VEXAG Townhall Meeting. Acknowledgments: The authors gratefully acknowledge support from the NASA SMD.

atmospheric models↗
NASA NTRS2007

Commercial Flight Crew Decision-Making during Low-Visibility Approach Operations Using Fused Synthetic/Enhanced Vision Systems

NASA is investigating revolutionary crew-vehicle interface technologies that strive to proactively overcome aircraft safety barriers that would otherwise constrain the full realization of the next-generation air transportation system. A fixed-based piloted simulation experiment was conducted to evaluate the complementary use of Synthetic and Enhanced Vision technologies. Specific focus was placed on new techniques for integration and/or fusion of Enhanced and Synthetic Vision and its impact within a two-crew flight deck on the crew's decision-making process during low-visibility approach and landing operations. Overall, the experimental data showed that significant improvements in situation awareness, without concomitant increases in workload and display clutter, could be provided by the integration and/or fusion of synthetic and enhanced vision technologies for the pilot-flying and the pilot-not-flying. During non-normal operations, the ability of the crew to handle substantial navigational errors and runway incursions were neither improved nor adversely impacted by the display concepts. The addition of Enhanced Vision may not, unto itself, provide an improvement in runway incursion detection without being specifically tailored for this application. Existing enhanced vision system procedures were effectively used in the crew decision-making process during approach and missed approach operations but having to forcibly transition from an excellent FLIR image to natural vision by 100 ft above field level was awkward for the pilot-flying.

Kramer, Lynda J.↗
DOE OSTI2011

Mobile C-arm cone-beam CT for guidance of spine surgery: Image quality, radiation dose, and integration with interventional guidance

Purpose: A flat-panel detector based mobile isocentric C-arm for cone-beam CT (CBCT) has been developed to allow intraoperative 3D imaging with sub-millimeter spatial resolution and soft-tissue visibility. Image quality and radiation dose were evaluated in spinal surgery, commonly relying on lower-performance image intensifier based mobile C-arms. Scan protocols were developed for task-specific imaging at minimum dose, in-room exposure was evaluated, and integration of the imaging system with a surgical guidance system was demonstrated in preclinical studies of minimally invasive spine surgery. Methods: Radiation dose was assessed as a function of kilovolt (peak) (80-120 kVp) and milliampere second using thoracic and lumbar spine dosimetry phantoms. In-room radiation exposure was measured throughout the operating room for various CBCT scan protocols. Image quality was assessed using tissue-equivalent inserts in chest and abdomen phantoms to evaluate bone and soft-tissue contrast-to-noise ratio as a function of dose, and task-specific protocols (i.e., visualization of bone or soft-tissues) were defined. Results were applied in preclinical studies using a cadaveric torso simulating minimally invasive, transpedicular surgery. Results: Task-specific CBCT protocols identified include: thoracic bone visualization (100 kVp; 60 mAs; 1.8 mGy); lumbar bone visualization (100 kVp; 130 mAs; 3.2 mGy); thoracic soft-tissue visualization (100 kVp; 230 mAs; 4.3 mGy); and lumbar soft-tissue visualization (120 kVp; 460 mAs; 10.6 mGy) - each at (0.3 x 0.3 x 0.9 mm{sup 3}) voxel size. Alternative lower-dose, lower-resolution soft-tissue visualization protocols were identified (100 kVp; 230 mAs; 5.1 mGy) for the lumbar region at (0.3 x 0.3 x 1.5 mm{sup 3}) voxel size. Half-scan orbit of the C-arm (x-ray tube traversing under the table) was dosimetrically advantageous (prepatient attenuation) with a nonuniform dose distribution ({approx}2 x higher at the entrance side than at isocenter, and {approx}3-4 lower at the exit side). The in-room dose (microsievert) per unit scan dose (milligray) ranged from {approx}21 {mu}Sv/mGy on average at tableside to {approx}0.1 {mu}Sv/mGy at 2.0 m distance to isocenter. All protocols involve surgical staff stepping behind a shield wall for each CBCT scan, therefore imparting {approx}zero dose to staff. Protocol implementation in preclinical cadaveric studies demonstrate integration of the C-arm with a navigation system for spine surgery guidance-specifically, minimally invasive vertebroplasty in which the system provided accurate guidance and visualization of needle placement and bone cement distribution. Cumulative dose including multiple intraoperative scans was {approx}11.5 mGy for CBCT-guided thoracic vertebroplasty and {approx}23.2 mGy for lumbar vertebroplasty, with dose to staff at tableside reduced to {approx}1 min of fluoroscopy time ({approx}40-60 {mu}Sv), compared to 5-11 min for the conventional approach. Conclusions: Intraoperative CBCT using a high-performance mobile C-arm prototype demonstrates image quality suitable to guidance of spine surgery, with task-specific protocols providing an important basis for minimizing radiation dose, while maintaining image quality sufficient for surgical guidance. Images demonstrate a significant advance in spatial resolution and soft-tissue visibility, and CBCT guidance offers the potential to reduce fluoroscopy reliance, reducing cumulative dose to patient and staff. Integration with a surgical guidance system demonstrates precise tracking and visualization in up-to-date images (alleviating reliance on preoperative images only), including detection of errors or suboptimal surgical outcomes in the operating room.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
NASA NTRS1992

A land-surface testbed for EOSDIS

We propose to develop an on-line data distribution and interactive display system for the collection, archival, distribution and analysis of operational weather satellite data for applications in land surface studies. A 1,000 sq km scene of the western U.S. (centered on the Colorado Rockies) will be extracted from Advanced Very High Resolution Radiometer (AVHRR) imagery collected from morning and afternoon passes of the NOAA polar-orbiters at the direct readout stations operated by CU/CCAR. All five channels of these AVHRR data will be navigated and map registered at CU/CCAR and then be transferred to NCAR for storage in an on-line data system. Software will also be available at NCAR to process and navigate the raw AVHRR data as needed. A display workstation software, based on a Macintosh II computer, will be developed that will display and further process the AVHRR data for studies of vegetation monitoring and snowpack assessment. Various options of presently used techniques for both vegetation and snowpack monitoring will be implemented in the workstation software to provide the individual investigator with the freedom to interact with the satellite image data. The display software will be freely distributed online to interested investigators and the AVHRR data will be made available on-line to anyone interested. In addition, potential users will be sought out and connected to the on-line data archive. This experiment with an active on-line archive and interactive analysis systems will provide experience with a small scale EOSDIS.

Emery, William↗
NASA NTRS1993

A land-surface testbed for EOSDIS

We propose to develop an on-line data distribution and interactive display system for the collection, archival, distribution and analysis of operational weather satellite data for applications in land surface studies. A 1,000 square km scene of the western U.S. (centered on the Colorado Rockies) will be extracted from Advanced Very High Resolution Radiometer (AVHRR) imagery collected from morning and afternoon passes of the NOAA polar-orbiters at the direct readout stations operated by CU/CCAR. All five channels of these AVHRR data will be navigated and map registered at CU/CCAR and then be transferred to NCAR for storage in an on-line data system. Software will also be available at NCAR to process and navigate the raw AVHRR data as needed. A display workstation software, based on a Macintosh II computer, will be developed that will display and further process the AVHRR data for studies of vegetation monitoring and snowpack assessment. Various options of presently used techniques for both vegetation and snowpack monitoring will be implemented in the workstation software to provide the individual investigator with the freedom to interact with the satellite image data. The display software will be freely distrributed online to interested investigators, and the AVHRR data will be made available on-line to anyone interested. In addition, potential users will be sought out and connected to the on-line data archive. This experiment with an active on-line archive and interactive analysis systems will provide experience with a small scale EOSDIS.

Emery, William↗
NASA NTRS2003

Software for a GPS-Reflection Remote-Sensing System

A special-purpose software Global Positioning System (GPS) receiver designed for remote sensing with reflected GPS signals is described in Delay/Doppler-Mapping GPS-Reflection Remote-Sensing System (NPO-30385), which appears elsewhere in this issue of NASA Tech Briefs. The input accepted by this program comprises raw (open-loop) digitized GPS signals sampled at a rate of about 20 MHz. The program processes the data samples to perform the following functions: detection of signals; tracking of phases and delays; mapping of delay, Doppler, and delay/Doppler waveforms; dual-frequency processing; coherent integrations as short as 125 s; decoding of navigation messages; and precise time tagging of observable quantities. The software can perform these functions on all detectable satellite signals without dead time. Open-loop data collected over water, land, or ice and processed by this software can be further processed to extract geophysical information. Possible examples include mean sea height, wind speed and direction, and significant wave height (for observations over the ocean); bistatic-radar terrain images and measures of soil moisture and biomass (for observations over land); and estimates of ice age, thickness, and surface density (for observations over ice).

Lowe, Stephen↗
NASA NTRS2021

Tonlé Sap Food Security and Agriculture: Evaluating the Effects of Land Use and Hydrological Change on Ecosystem Vitality using Remotely-Sensed Data in the Tonlé Sap Lake Basin

Tonlé Sap Lake, the largest lake in Southeast Asia, is a critical source of fish and freshwater resources for the region. The health of this freshwater system is under pressure from accelerating dam construction, intensifying agriculture, deforestation, and changing climate patterns, forcing tradeoffs between immediate food security and the long-term vitality and productivity of the ecosystem. Efficient freshwater system monitoring is crucial to navigating these challenges. In collaboration with Conservation International, the Cambodian Ministry of Water Resources and Meteorology, and the Tonlé Sap Authority, we developed and tested remotely-sensed proxies for sub-indicators of the Freshwater Health Index (FHI), which is typically calculated using in situ datasets. We used landcover datasets derived from Landsat 5 Thematic Mapper (TM), Landsat 7 Enhanced Thematic Mapper Plus (ETM+), Landsat 8 Operational Land Imager (OLI), PROBA-V Vegetation sensor (VGT), Sentinel-2 Multispectral Imager (MSI), Advanced Very High Resolution Radiometer (AVHRR), and Envisat Medium Resolution Imaging Spectrometer (MERIS) as inputs to calculate land cover naturalness and bank modification. Additionally, we created a lake-level time series using a collection of altimetry data sources to estimate deviation from natural flow. We observed a decrease in landcover naturalness and a breakdown in the volume and regularity of annual lake levels from 2000-2020, reflecting increased pressure on water supply and agricultural productivity. At least 8% of forested areas in the basin were lost and rice harvest intensity increased over the course of the study period. These results will help our partners make informed decisions regarding freshwater management. Furthermore, our remotely-sensed FHI analysis can be replicated in other regions, providing decision makers with a snapshot of freshwater health in data-scarce environments.

Marco Vallejos↗
NASA NTRS1979

A Mars airplane

An airplane specifically designed for Mars flight is described, emphasizing its conceivable role as an aerial surveyor for visual imaging, gamma-ray and IR reflectance spectroscopy, studies of atmospheric composition and dynamics, and gravity-field, magnetic-field, and electromagnetic sounding. Possible imaging systems and surveying tasks are considered, along with a plausible mission scenario for a fleet of 12 airplanes, which would be taken to Mars in squadrons of four by three Shuttle/IUS Twin Stage/spacecraft carriers. A basic configuration closely resembling that of a competition glider is examined, and four types of airplane are discussed: hydrazine-powered cruisers and landers and electrically powered cruisers and landers. Attention is given to navigation, guidance, and control avionics, vehicle weight, the use of composite materials for the wing, and flight testing on earth.

Clarke, V. C.↗
NASA NTRS2021

Assateague Island National Seashore Ecological Forecasting: Characterizing Nearshore Suspended Sediments and Landcover Change Relative to Sediment Bypassing and Catastrophic Events

Assateague Island is located off the coast of Maryland and Virginia and serves as a home to sensitive species and habitats. However, infrastructure development disrupted the natural sediment transport processes of the barrier island, which accelerated erosion of the island’s shoreline. To counteract this, the United States Army Corps of Engineers (USACE) initiated semiannual sediment bypassing operations in 2004. Over time, financial constraints limited the amount of sediment deposition possible, leading to concerns over navigational issues in nearby channels and the possibility of the operations not providing their intended benefits. To address these issues, NASA DEVELOP partnered with the National Park Service NPS and USACE. The team performed time series analyses of nearshore suspended sediment from 2004-2020 and landcover change from 2006-2018 with satellite imagery from Landsat 5 Thematic Mapper (TM), Landsat 7 Enhanced Thematic Mapper Plus (ETM+), Landsat 8 Operational Land Imager (OLI), and Sentinel-2 MultiSpectral Instrument (MSI). The sediment transport analyses showed that suspended sediment levels are seasonally dependent. Meanwhile, historical land cover trends included a net increase in unconsolidated shore and a net decrease in open water. Land cover change was then forecast to 2021, 2031, and 2046 using the IDRISI TerrSet Land Change Modeler. The model predicted the most drastic land cover changes in the southern portion and the least on the eastern foreshore of the island. As a result, this project allows our partners to understand the impact of sediment bypassing operations more fully and make better-informed decisions regarding the island’s management.

M Colin Marvin↗
DOE OSTI2019

Integration and operation of a sUAS-based multi-modal imaging payload equipped with a novel communication system enabling autonomous platform control

Oak Ridge National Laboratory presents a new UAS-mounted multi-modal imaging payload containing five sensors. We have integrated several distinct commercially available sensors onto a large Class-1 autonomous quadcopter aircraft: a LIDAR (Light Detection and Ranging) scanner, a hyperspectral pushbroom sensor, a multispectral camera, a longwave infrared thermal camera, and an RGB camera. The system integrates our proprietary Multi-modal Autonomous Vehicle Network (MAVNet) and communication system, allowing autonomous control via multiple communication networks. Using one common Global Navigation Satellite System (GNSS) and inertial navigation system (INS/GPS), imagery from all sensors are accurately and precisely geolocated and co-registered.

Duncan, Andrew↗
NASA NTRS2012

Vehicle Detection for RCTA/ANS (Autonomous Navigation System)

Using a stereo camera pair, imagery is acquired and processed through the JPLV stereo processing pipeline. From this stereo data, large 3D blobs are found. These blobs are then described and classified by their shape to determine which are vehicles and which are not. Prior vehicle detection algorithms are either targeted to specific domains, such as following lead cars, or are intensity- based methods that involve learning typical vehicle appearances from a large corpus of training data. In order to detect vehicles, the JPL Vehicle Detection (JVD) algorithm goes through the following steps: 1. Take as input a left disparity image and left rectified image from JPLV stereo. 2. Project the disparity data onto a two-dimensional Cartesian map. 3. Perform some post-processing of the map built in the previous step in order to clean it up. 4. Take the processed map and find peaks. For each peak, grow it out into a map blob. These map blobs represent large, roughly vehicle-sized objects in the scene. 5. Take these map blobs and reject those that do not meet certain criteria. Build descriptors for the ones that remain. Pass these descriptors onto a classifier, which determines if the blob is a vehicle or not. The probability of detection is the probability that if a vehicle is present in the image, is visible, and un-occluded, then it will be detected by the JVD algorithm. In order to estimate this probability, eight sequences were ground-truthed from the RCTA (Robotics Collaborative Technology Alliances) program, totaling over 4,000 frames with 15 unique vehicles. Since these vehicles were observed at varying ranges, one is able to find the probability of detection as a function of range. At the time of this reporting, the JVD algorithm was tuned to perform best at cars seen from the front, rear, or either side, and perform poorly on vehicles seen from oblique angles.

Brennan, Shane↗
DOE OSTI2022

Intelligent Process Visualization through Nuclear Operation Process Modeling, Reasoning, and Object Detection from Field Videos (Final Report)

This report is a deliverable for the “Final Report” task of DOE NEET Project 19-16790, "Context-Aware Safety Information Display for Nuclear Field Workers." This project's overall goal is to test the hypothesis that integrating computer vision and process reasoning methods will enable proactive visualization of the safe operation and maintenance processes of Nuclear Power Plants (NPP) for field workers. Augmented Reality (AR) glasses adopting such proactive safety information visualization techniques can significantly increase personnel safety and reduce the NPP’s operating costs. The current practice of monitoring NPPs requires workers to switch between digital models, data, and physical workspaces in identifying relevant but potentially occluded objects and in assessing the risks of operation and maintenance processes. On the other hand, frequently changed field conditions require field workers to report to supervisors for real-time guidance. Such guidance is essential to ensure that changing conditions will not invalidate or endanger the work order and other ongoing processes that may jeopardize NPP operations. Additionally, incorrect recognition of equipment objects can result in communication errors and safety problems. AR techniques can assist engineers in viewing the physical workspaces with objects labeled with detailed operation procedures and safety reminders during field operations. The project team developed an “Intelligent Context-Aware Safety Information Display” (ICAD) for supporting Nuclear Power Plant (NPP) field workers in achieving safe and efficient execution of a series of operational tasks in uncertain and changing workspaces of an NPP. Before designing the ICAD-AR prototype, the project team synthesized NPP operational knowledge models through literature review studies, surveys, interviews with domain experts, and knowledge modeling. The project team conducted an extensive study of the operational procedures of various NPPs, and digital technologies that can support the safe and efficient execution of those procedures in different NPP operational contexts. This literature review helped the project team conduct surveys and interviews with nuclear engineers and field workers to identify three categories of information. The NPP knowledge modeling efforts reveal that the three categories of information identified have different levels of importance in a typical procedure of carrying out a series of tasks to achieve a specific NPP operation goal (e.g., shutdown, mode changes). These three categories of information include 1) Workspace dynamics – the changing spatial arrangements of workspaces, tools, protection equipment, and supporting materials, 2) Workflow prognostics – the dynamic dependencies between different parts of an NPP that functionally support and influence each other in terms of safety and efficiency, and 3) Hazards – objects and spaces that contain hazardous materials or physical conditions that can pose risks to workers or mechanical systems. The project team has profiled the importance levels of these categories of information into a knowledge model. This knowledge model specifies what types of information are more critical for a given task in a given workspace so that computers can automatically identify critical objects and sensors in a scene for delivering context-ware safety information to field workers through AR devices. Significant research development of this project results in technical research outcomes and a prototyping system that illustrates the technical feasibility of establishing an ICAD-AR system supporting the proactive safety information display for nuclear field workers. This final report summarizes the project team’s technological achievements in the past three years. Overall, the project team completed the development and integration of five techniques into a prototype ICAD Augmented Reality (ICAD-AR) system and demonstrated the developed system’s real-time execution in a mechanical room. The project team completed the analysis of using this prototype in other types of workspaces based on 3D image data and digital design models collected from two additional workspaces (a water treatment plant and a flow loop training facility). The integrated techniques include 1) Natural Language Processing (NLP) algorithms supporting the generation and updates of nuclear fieldwork process models based on text analysis of work packages and operation manuals; 2) sensor log analysis for predicting control actions in given sensor reading contexts; 3) computer vision algorithms for automatic localization and navigation of workers; 4) object detection algorithms for identifying task-related objects and correlated sensors for safety checking; 5) AR technique as a platform for supporting the integration. The testing results of these five techniques have shown that 1) the sensor log analysis model can predict the next control action with an accuracy of 0.883; 2) the trained natural language processing model can extract more than 80% of the critical information from paper-based procedures (PBPs); 3) the navigation algorithm with the integration of Visual Inertial Odometry (VIO) and Non-Recursive Bayesian Filter methods make operator’s trajectory estimation resilient to drift error; 4) the computer vision algorithm can detect task-specific and safety-critical objects with an average accuracy of 95.3%. The project team used work procedures collected from a flow loop training facility and two datasets collected from two mechanical rooms simulating the workspaces of NPPs to demonstrate the technical capabilities of the developed ICAD-AR prototype. The demonstration validated the technical feasibility of establishing the ICAD-AR system for nuclear field workers and identified the challenges in 1) automatic text analysis of work packages; 2) use of limited samples of sensor logs for predicting the proper timings of control actions; 3) reliably tracking workers and their task progress in mechanical rooms with many similar objects.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
NASA NTRS1984

Geometry Software Common to All Experiments

All imaging, remote sensing, and in situ experiments require information about the geometry and location of observations. An alterntive to collecting geometry data with a supplementary experiment data record is proposed. The new method involves identifying the fundamental information, that is, the geometric state upon which geometry calculations are based, and maintaining or delivering these calculations in separate packages which are easily replaced when improved information is available. Implementation of this method in spacecraft navigation is discussed along with software system requirements.

Source record↗
NASA NTRS2022

Velocimeter LIDAR Based Bulk Velocity Estimation for Terrain Relative Navigation Applications

A novel batch state estimation approach to estimate the translational and angular velocity states of a vehicle using a state-of-the-art velocimeter Light Detection and Ranging (LIDAR) sensor for use in Terrain and Hazard Relative Navigation (TRN/HRN) applications is presented in this paper. The velocimeter LIDAR is capable of measuring three dimensional position and line-of-sight (LOS) velocity associated with every pixel in the field-of-view (FOV). This new batch state estimation methodology is shown to provide accurate and statistically consistent velocity estimates with no a priori information. In contrast to traditional computer vision approaches for TRN, the proposed technique is not dependent on image features. This feature alleviates the need for accurate feature detection and correspondence to a predefined map making it suitable for unknown operating environments. Following a detailed development of the mathematical details associated with the batch state estimation methodology, the efficacy and utility of the proposed algorithms are evaluated through emulation robotics experiments performed at Texas A&M’s Land, Air, and Space Robotics (LASR) laboratory.

Skulsky, Eli↗
NASA NTRS1983

Simultaneous dual baseline differential VLBI

Attention is drawn to the benefits of simultaneous dual baseline radio interferometric measurements for low altitude planetary orbiter navigation. The radio interferometric data types constitute a valuable addition to conventional tracking data in the establishment of orbit-plane orientation, thanks to their measurement of inertial reference cross-track velocity. The present results show that only a few Delta-VLBI measurements, taken at either end of a conventional tracking arc, suffice for the realization of a positional accuracy of better than 1 km for the case of a Venus Orbiting Imaging Radar-type planetary orbiter. This is comparable to Deep Space Net accuracies, despite the use of a shorter baseline.

Mohan, S. N.↗
NASA NTRS2001

Optimal Orbit Design for the Magnetospheric Imaging Constellation

The Magnetospheric Imaging Constellation (MagIC) is a NASA space science concept to study the Earth's Magnetosphere. The concept proposes to apply tomography techniques using an array of spacecraft to obtain three dimensional images of the Earth's magnetosphere. This paper presents an optimal orbit design to ensure that the constellation is in the desired region of the magnetosphere for maximum time. The solution is found using a steepest descent optimization algorithm that takes into account perturbations from the non-spherical Earth, drag, Sun, Moon and other significant bodies. The solution also satisfies constraints on maximum eclipse duration and geometry constraints to allow an adequate GPS navigation solution. We present three solutions depending upon the epoch of the primary science: vernal equinox, summer solstice, and a third midway between the vernal equinox and summer solstice. Orbit insertion is also considered. All spacecraft are assumed to be launched on a single vehicle into a nominal orbit and the (Delta)V's to achieve the nominal orbit are presented. After insertion into the nominal orbit, each spacecraft undergoes a phasing maneuver to place it in the appropriate position with respect to the rest of the constellation. We present a minimum fuel approach to maneuver each spacecraft from the nominal orbit into the desired final orbit.

Hughes, Steven P.↗