Search NASA⌕ Search

SEARCH · Search NASA

Results for “Relative Navigation”

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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 19 records

Terrain-Relative Navigation with Neuro-Inspired Elevation Encoding

Terrain-relative navigation (TRN) encompasses a wide variety of algorithms that perform localization with respect to the terrain below a flying vehicle. In traditional approaches, measurements of the terrain are matched to a map carried onboard. This work presents a terrain-relative navigation filter with a position measurement inspired by neural activity associated with positioning in nature. Here, the filter is shown to produce accurate position measurements that outperform popular optimization and template matching methods given poor prior knowledge of the position. The proposed method is also better-suited to distributed implementation than optimization-based methods.

33 ADVANCED PROPULSION SYSTEMS↗

High-Resolution Sampling of a River Plume Front with Uncrewed Underwater and Aerial Vehicles

Sampling fast-propagating oceanic features is inherently challenging and demands versatile instrumentation and innovative strategies. This paper introduces a novel sampling strategy designed to capture such phenomena, exemplified by a river plume front. Our method revolves around modifying the preprogrammed pathway of an uncrewed underwater vehicle (UUV) to dynamically track and three-dimensionally sample the evolution of the front. To enable the UUV to follow the feature, we adapt the use of a drifting gateway buoy to be positioned and trapped at the front’s convergence zone, allowing underway navigation relative to the buoy. In our demonstration, we showcase the effectiveness of this strategy by successfully conducting over 30 crossings of a river plume front within a 6-h window. The UUV sensors allowed a comprehensive assessment of key front characteristics, including density, velocity, and turbulence. Supplemental drone footage contributed to the overall picture and facilitated the transformation of the dataset into a front-following reference frame. This article provides an in-depth description of the deployment strategy and required postcollection data processing, including frontal crossing detection, the assessment of the frontal orientation from drone footage, and defining the plume bottom boundaries using backscatter intensity contours.

autonomous observations↗

Polimaster PM1401K-3 Test Report

Extensive testing, including measurements on large quantities of special nuclear material, were taken to assess the functionality of the Polimaster PM1401K-3 to other detectors used in the field. The Polimaster can detect alpha, beta, gamma, and neutron radiation. However, efficiency and accuracy has been sacrificed to accomplish this. Compared to the IdentiFINDER 2, SRM, and FH-40 alpha probe, the Polimaster underperforms in almost all categories regarding radiation detection. The Helium-3 neutron detector in the Polimaster, due to a larger volume, outperformed the IdentiFINDER 2 for neutron measurements. The alpha search mode showed higher efficiency than the FH-40 alpha probe, but uses a more complicated process. The user interface is relatively easy to navigate, clear, and comparable to other detectors. However, the detector has added complications when trying to detect alpha or beta radiation or save a spectrum.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Navigating high-dimensional process-structure–property relations in nanocrystalline Pt-Au alloys with machine learning

For decades, materials scientists have relied on the process-structure–property paradigm to guide investigations into material behaviors. Traditional studies often examine a limited number of process-structure–property variables, striving to elucidate mechanisms governing material response. However, this approach is time consuming and can limit exploration, as well as the discovery of process-structure–property relations in novel materials. In this paper, we combined combinatorial sputter deposition and multi-modal high-throughput materials characterization with feedforward neural networks to establish high-dimensional process-structure–property relations in Pt-Au alloys, yielding nanocrystalline alloys with high hardness and low resistivity relevant to electrical contact switch applications. We mapped three indicators of process conditions (composition and two atomic deposition characteristics) onto four indicators of material structure (X-ray diffraction, film thickness, density, and surface roughness) and two indicators of material properties (hardness and resistivity), resulting in 784 unique combinations evaluated over a 13-dimensional space. The neural networks predicted Pt-Au alloys with 18–24 at.% Au, when deposited at specific conditions, to have a nanoindentation hardness up to 7.2 GPa. This high hardness value, comparable to some steels, represents a 3-fold improvement in hardness over “hard gold”, a commonly used electrical contact alloy, while maintaining requisite electrical conductivity. The neural network models provide an avenue to identify expected process windows capable of maximizing material performance.

Electrical contact materials↗

An Assessment of Technical Hydropower Potential at Non-Powered Dams in the United States

Historically, dams have been constructed for a variety of purposes, such as providing a more secure and reliable water supply, mitigating impacts from variations in river flow, allowing continuous navigability, and harnessing mechanical power. A relatively small portion of dams have been designed to store or regulate flows for the purpose of generating electricity (roughly 3% of nationally inventoried dams in the US and 17% of the dams included in the World Register of Dams). The remaining population of existing non-powered dams (NPDs) presents both an opportunity to generate renewable energy and a need to modernize aging infrastructure. This report describes an assessment of more than 2,600 NPDs in the US that have a collective potential of nearly 4 GW in new power capacity. Previous national-scale assessments were aimed at evaluating the theoretical maximum power potential at existing dams in the United States. These estimates were based on the best available information at the time for water availability, hydraulic head, and representative regional capacity factors. This study revisits a subset of 3,299 dams identified in the most recent theoretical resource assessment and uses more detailed and updated hydrologic data to produce estimates of technical potential. These improvements in data enable estimates that more realistically reflect what is physically possible given simple assumptions about the existing structure and constraints on flow and head (Figure 1).

13 HYDRO ENERGY↗

Barriers to Balcony Solar and Plug-In Distributed Energy Resources in the United States

Plug-in distributed energy resources (DERs), such as balcony solar, backfeed power to the home through a standard plug. These systems may represent the future of residential solar and storage, particularly as recent net metering policies have reduced the economic appeal of rooftop solar. While plug-in DERs have seen widespread success in Europe, their U.S. market is stagnant. This paper reviews the technical, interconnection, and regulatory barriers hindering the adoption of plug-in DERs. We first discuss the technical barriers, which include touch safety, breaker masking, and bidirectional ground-fault circuit interrupters. We then examine utility perspectives on plug-in DERs and strategies for navigating interconnection challenges. Finally, we discuss regulatory hurdles related to UL standards and the National Electrical Code.

Gerber, Daniel L. (ORCID:0000000219720679)↗

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↗

Magnetic Navigation for GPS-Denied Airborne Applications

Most current flight systems are dependent on GPS for navigation. Recently, however, navigation in GPS-denied environments has become an area of intensive research. Additional navigation sensor data can be obtained from visual observations (stars or terrain), inertial measurement units, radar, measurements of the local magnetic field, or perhaps even gravity. Absolute and relative positioning via magnetic field measurements have been shown to be viable in many applications including ground navigation, low altitude aircraft flight, and spaceflight. There is greater variability in the magnetic field over shorter distances when flying at low altitude and in ground applications, leading to more accurate positioning. However, ground-based magnetic navigation is often heavily influenced by man-made structures, especially in urban environments. This is not the case for airborne magnetic navigation since the influence of buildings, roads, etc. is negligible for typical aircraft altitudes. For absolute magnetic navigation, the positioning accuracy decreases as altitude increases for a given vehicle velocity, but the observed time variability in the field can be reclaimed by traveling faster through the field. Thus, navigation accuracy becomes a balance of speed and altitude since the higher altitude can be counterbalanced by higher velocity. To understand these effects quantitatively, we explored various techniques to aid a simulated inertial measurement unit with magnetic information. Using a technique known as two-dimensional magnetic map matching, we simulated the performance of airborne magnetic navigation at fixed speed while varying the altitude, flight direction, magnetometer data collection time, reference magnetic map bias error, and type of trajectory (over land or over ocean).

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

WPTO Navigator

Protecting hydroelectric plants from incidents that adversely impact their cyber-physical systems presents unique challenges due to the plants’ widely dispersed geographic locations and varied configurations as well as the relative nascent nature of the cyberattacks targeting these facilities. To help hydroelectric plants better respond to and mitigate cybersecurity incidents, this Department of Energy Water Power Technologies Office Navigator aligns the processes within the National Institute of Standards 800-61r2 Computer Security Incident Handling Guide with the emergency actions within the FEMA 64 Emergency Action Plan Framework. This work is to be used at a hydroelectric plant to quickly understand how the plant responds to a cyber incident in relationship to the actions involved in an emergency action plan involving a hydroelectric plant. In addition to this product, there are three other products meant to be distributed to a hydroelectric plant to assist in their cyber incident response and recovery. The first, a report on the processes of building a R&R flip book based on a large set of existing guidance. The second, a handy flip book meant to be distributed to hydroelectric plants to assist them during a cybersecurity incident occurring on a hydroelectic plant. And the third is a comprehensive set of resources to assist an operator in locating appropriate guidance during the recovery process.

13 HYDRO ENERGY↗

Detection and Perception of Sound by Eagles and Surrogate Raptors

One overarching objective of this program of study was the accumulation of objective, scientifically valid information relating to auditory performance of bald and golden eagles that may be used to guide the development of acoustic alerting/deterrence technologies intended to discourage encroachment into wind energy air spaces. To that end, analyses aimed at the characterization of sensitivity to sound in bald and golden eagles, along with findings in the supra-threshold, dynamic frequency spaces related to response latencies and amplitudes, leads us to conclude that bald, and golden eagles navigate the same basic working auditory space, as in other known and thus far characterized members of the diurnal raptor family. Specifically, bald and golden eagles, along with other raptor species within the group, operate in an auditory space characterized by a frequency band at least four octaves wide and centered on 2 kHz, with an upper frequency limit between 6 and 10 kHz at 80 dB SPL and a lower frequency limit that almost certainly extends below 0.2 kHz. Consequently, we recommend that signal designers use these data as a guideline in efforts to design effective and efficient acoustic alerting/deterrent systems. It is important to note that signal energy broadcast outside of this frequency band at moderate levels will not contribute to the efficacy of a deterrent but will add an unnecessary fraction to the overall acoustic pollution budget. The importance of this consideration is heightened by contemporaneous concerns related to the transmission of noise broadcast by wind energy farms. In addition, based on analyses of data acquired from red-tailed hawks using the same experimental paradigm and data acquisition system, we conclude that auditory function in the red-tailed hawk is sufficiently like that observed in bald and golden eagles to permit its use as a surrogate species. Response waveforms, threshold-frequency curves, and input-output characteristics match those of eagles closely. It should be noted however, that differences in sensitivity and slightly extended high-frequency limits of hearing should be taken into account when extrapolating findings from one species to the others. Although the inclusion of behavioral tests of red-tailed hawks to acoustic stimuli was beyond the scope of this investigation, future efforts to assess response parameters like signal-type preference and habituation rate will further elucidate their suitability to serve as eagle surrogates in behavioral studies; nonetheless, the species in question are well matched with respect to basic auditory performance. A second essential objective of this program of study was the acoustic characterization of a subset of calls comprising the vocal repertoires of bald and golden eagles that may be used to supplement auditory performance findings in the effort to guide the development of acoustic alerting signals. With regard to that objective, the vocal repertoires of both bald and golden eagle species are rich and varied. While similar in spectrographic structure, distinctive differences are also clear. Generally, golden eagles produce some calls with shorter durations, and similar “sounding” calls exhibit distinctively different spectrographic patterns than those of bald eagles. Both species produce calls that contain a wide variety of nonlinear elements that operate to enhance the rich and varied nature of commonly observed vocal products. Comparison of the average power spectra of commonly observed bald and golden eagle calls with threshold-frequency curves leads to the conclusion that call energies fall within the frequency bounds of hearing. Further, the acoustic energy of calls considered in this report tend to fall into overlapping, but different frequency ranges of the acoustic sensitivity curve. This condition may encourage signal designers to vary the frequency content of acoustic deterrence signals in the field. Finally, preliminary observations relating to the tendencies and proclivities of bald eagles to attend to the acoustic landscape lead to the conclusion that eagles monitor their immediate sound environment assiduously. Individuals respond to a variety of natural and synthetic sound signals reliably and, perhaps most relevant in the context of the engineering of acoustic alerting/deterrence technologies, habituation to most sounds considered in this effort was minimal. These preliminary results, while calling for extended behavioral testing, are promising and set the stage for the exportation of behavioral studies into real world scenarios.

17 WIND ENERGY↗

Rapidly Deployable Acoustic Monitoring and Localization System Based on a Low-Cost Wave Buoy Platform

The primary objective of this project is to develop a cost-effective, fit-for-purpose environmental monitoring system, “NoiseSpotter®,” that characterizes, classifies, and provides accurate location information for anthropogenic and natural sounds in near real-time. NoiseSpotter was developed to support the evaluation of potential acoustic effects of marine energy (ME) projects. By utilizing a compact array of three acoustic particle motion sensors, NoiseSpotter triangulates individual bearings to provide sound source localization to within 5% accuracy, allowing the ability to discern ME device sounds relative to other confounding sounds in the environment, while providing location estimates to nearby marine mammals for environmental mitigation purposes. The ME industry needs proven solutions to meet environmental impact assessment needs. The NoiseSpotter® includes off-the-shelf, modular components that are easy to assemble and disassemble. Its acoustic particle motion sensors are commercially available and the data logger and real-time telemetry system is designed to be plug-and-play. The entire system is relatively compact and can be deployed from small vessels. NoiseSpotter’s near real-time capability enables operational monitoring of ME sounds, particularly during early stages of technology adoption to facilitate mitigation of potential noise effects. Widespread adoption of the technology for acoustic monitoring of ME devices requires that it be cost effective; hence the anticipated commercial cost of system hardware is $35,000. This project contributes to reducing barriers to ME testing through support of scientific research focused on reducing or mitigating environmental risks and lowering costs and complexity of environmental monitoring. This project has developed an acoustic monitoring system, NoiseSpotter® (U.S. Patent No. 11,156,734 and U.S. Registered Trademark No. 6,442,313), to detect and characterize baseline noise and sounds from ME operations and support geolocation of detected sounds. The intended outcome of the project is to mitigate concerns about the potential for ME device noise to alter marine mammal or fish behavior. NoiseSpotter® enables cost-effective, near real-time acoustic monitoring of an operational ME device relative to ambient environmental noise and provides a technical basis for ME developers seeking to navigate the permitting process in an efficient manner.

16 TIDAL AND WAVE POWER↗

The US Naval Observatory VLBI Spectroscopic Catalog

Despite their importance for astrometry and navigation, the active galactic nuclei (AGNs) that comprise the International Celestial Reference Frame (ICRF) are relatively poorly understood, with key information such as their spectroscopic redshifts, AGN spectral type, and emission-/absorption-line properties generally missing from the literature. Using an updated, publicly available, state-of-the-art spectroscopic fitting code optimized for the spectra of AGNs from low to high redshift, we present a catalog of emission-line and spectral continuum parameters for 1014 unique ICRF3 objects with single-fiber spectra from the Sloan Digital Sky Survey DR16. We additionally present black hole virial mass scaling relationships that use Hα-, Hβ-, Mg II -, and C IV -based line widths, all consistent with each other, which can be used in studies of radio-loud objects across a wide range of redshifts, and we use these scaling relationships to provide derived properties such as black hole masses and bolometric luminosities for the catalog. We briefly comment on these properties for the ICRF objects, as well as their overall spectroscopic characteristics.

79 ASTRONOMY AND ASTROPHYSICS↗

Photoproduction of K 0 S Pairs at GlueX

We present an study of the ¿¿ ¿ ¿0 ¿¿0 ¿¿ channel measured by the GlueX experiment. This channel selects for resonances with ¿¿¿ = even++ quantum numbers (the ¿0, ¿2, ¿0, and ¿2 light, flavorless mesons) and potentially contains contributions from the lightest scalar glueball (¿0). Data from the 2017, 2018, and 2020 run periods are used to perform a mass independent (binned) partial-wave analysis to distinguish spin states. Due to the polarized photon beam at GlueX, we are also able to extract reflectivity amplitudes for the first time in this channel. Additionally, we perform mass-dependent partial-wave analyses using a fixed ¿-matrixparameterization to attempt a determination of the relative contribution of each res onance, and we present a guided initialization method which facilitates navigation through a parameter space with many local minima. These mass-dependent fits are a proof-of-concept in using fixed ¿-matrix models constrained by other experiments to measure photoproduc tion amplitudes for overlapping states which may only differ by isospin, a property which cannot be distinguished in this channel.

Hoffman, Nathaniel [Carnegie Mellon University]↗