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

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At least 73 records · Page 4
All sourcesNASA NTRSDOE OSTI
NASA NTRS2008

Renewed Mapping of the Nepthys Mons Quadrangle (V-54), Venus

After a long hiatus due to competing tasks with the PI, mapping of Venus' Nepthys Mons Quadrangle (V-54, 300-330degE, 25-50degS) has been resumed, with planned submission late in 2008 or early 2009. Major goals are to determine the style of volcanism and tectonism over time, the evolution of shield volcanoes, the evolution of coronae, the characteristics of plains volcanism, and what these observations tell us about the general geologic history of Venus. This abstract largely repeats earlier progress reports, with some updates to show GEMS that the PI intends to complete this task in the near future. Methods: Geologic units and structures have been mapped onto hardcopy FMAPs and then transferred to the 1:5 million-scale map base (Figure 1). Pseudostereo anaglyphs have proved an indispensable tool and have resulted in a virtual complete revision of previously mapped areas [1,2]. At FMAP scale, structural trends and inferred ages are broken out using different symbols and colors. These are in the process of being transferred to a 1:5 million-scale structure map separate from the geologic map. The geologic units, structures, impact craters, coronae, and volcanoes are being arranged in time-stratigraphic sequences as the mapping progresses.

Bridges, Nathan T.↗
NASA NTRS1993

Navigational demands of low-level helicopter flight

The present study was designed to assess the verbal references to map, terrain, direction, and position, that navigators and pilots communicate during a simulated low-level flight. Two-person crews were asked to communicate normally while negotiating six short flight missions that varied widely in regard to map-terrain characteristics. Half of the crews performed the exercises with fixed, north-up maps and the other half used movable maps that were adjusted to maintain a track-up correspondence to the flight route. An analysis was performed to compare differences in crew communication patterns between map orientations, characteristics, and navigation tasks. The results showed differences in the frequency of communication across categories for map characteristics but not for map orientations or tasks. A difference in the proportion of communications between pilot and navigator occurred when crew were lost. Pilots communicated more than navigators when crews were lost and the reverse was true when crews were not lost. The results support and extend findings from a distance error performance analysis performed on the same flight missions.

Delzell, Susanne↗
NASA NTRS1987

Computer architecture for efficient algorithmic executions in real-time systems: New technology for avionics systems and advanced space vehicles

Improvements and advances in the development of computer architecture now provide innovative technology for the recasting of traditional sequential solutions into high-performance, low-cost, parallel system to increase system performance. Research conducted in development of specialized computer architecture for the algorithmic execution of an avionics system, guidance and control problem in real time is described. A comprehensive treatment of both the hardware and software structures of a customized computer which performs real-time computation of guidance commands with updated estimates of target motion and time-to-go is presented. An optimal, real-time allocation algorithm was developed which maps the algorithmic tasks onto the processing elements. This allocation is based on the critical path analysis. The final stage is the design and development of the hardware structures suitable for the efficient execution of the allocated task graph. The processing element is designed for rapid execution of the allocated tasks. Fault tolerance is a key feature of the overall architecture. Parallel numerical integration techniques, tasks definitions, and allocation algorithms are discussed. The parallel implementation is analytically verified and the experimental results are presented. The design of the data-driven computer architecture, customized for the execution of the particular algorithm, is discussed.

Carroll, Chester C.↗
NASA NTRS1989

Eigensolution of finite element problems in a completely connected parallel architecture

A parallel algorithm for the solution of the generalized eigenproblem in linear elastic finite element analysis, (K)(phi)=(M)(phi)(omega), where (K) and (M) are of order N, and (omega) is of order q is presented. The parallel algorithm is based on a completely connected parallel architecture in which each processor is allowed to communicate with all other processors. The algorithm has been successfully implemented on a tightly coupled multiple-instruction-multiple-data (MIMD) parallel processing computer, Cray X-MP. A finite element model is divided into m domains each of which is assumed to process n elements. Each domain is then assigned to a processor, or to a logical processor (task) if the number of domains exceeds the number of physical processors. The macro-tasking library routines are used in mapping each domain to a user task. Computational speed-up and efficiency are used to determine the effectiveness of the algorithm. The effect of the number of domains, the number of degrees-of-freedom located along the global fronts and the dimension of the subspace on the performance of the algorithm are investigated. For a 64-element rectangular plate, speed-ups of 1.86, 3.13, 3.18 and 3.61 are achieved on two, four, six and eight processors, respectively.

Akl, Fred A.↗
NASA NTRS2020

Investigating Relationships Between Geochemistry and Physical Grain Characteristics Along a Glacio-Fluvial-Aeolian Sediment Transport Pathway Using µXRF

Iceland’s basaltic volcanic rocks and glacial, fluvial, and aeolian landscapes resemble those studied on Mars, which makes it an ideal location to study the evolution of basaltic landscapes, the weathering and alteration of basaltic sediments in cold and wet environments, and the generation of a basaltic sedimentary record. The SAND-E: Semi-Autonomous Navigation for Detrital Environments project examines physical and chemical changes in sediments transported through basaltic fluvial and aeolian environments, and tests operational scenarios, which include a drone and a robotic rover instrumented with autonomous terrain analysis software. As part of the SAND-E project, we examined a glacial outwash plain at Skjaldbreiðauhraun, in SW Iceland. This study uses micro X-ray fluorescence (μXRF) to examine the chemical and physical properties of unconsolidated sediment-size fractions from 710 μm to < 63 μm along a downstream transect from a glacial sourced watershed. μXRF is ideally suited for this task because it maps elemental distributions at sub-grain scales thereby allowing a direct correlation between grainsize, grain shape, and chemistry. It is also a good analog technique for the Mars 2020 mission equipped with the PIXL (Planetary Instrument for X-ray Lithochemistry) that will be deployed at Jezero Crater, Mars.

Champion, E.↗
NASA NTRSDate not supplied

What Went Wrong: A Survey of Wildfire UAS Mishaps through Named Entity Recognition

Increasingly, unmanned aircraft systems (UAS) are being applied to wildfire incidents for tasks such as mapping, aerial ignition, and delivery. As a result, incident reporting systems for wildfires are beginning to accumulate data related to UAS mishaps in wildfire response. In this research, we apply state-of-the-art natural language processing (NLP) techniques to develop a custom Named Entity Recognition (NER) model which extracts a Failure Modes and Effects Analysis (FMEA)-style survey of wildfire UAS mishaps reported in SAFECOM. The custom NER model is built by fine-tuning an existing (BERT) model, resulting in a generalizable NER model that can extract engineering relevant entities including failure modes, causes, effects, control processes, and recommendations from any failure-relevant text. Similar mishaps are clustered and reported as single rows within the FMEA. For each cluster, frequency, severity, and overall risk are computed. The methodology can be applied as part of a broader safety management system to track trends in mishaps and discover knowledge that can be utilized to improve safety outcomes and system performance.

Machine Learning↗
NASA NTRSDate not supplied

What Went Wrong: A Survey of Wildfire UAS Mishaps through Named Entity Recognition

Increasingly, unmanned aircraft systems (UAS) are being applied to wildfire incidents for tasks such as mapping, aerial ignition, and delivery. As a result, aviation incident reporting systems for wildfires are beginning to accumulate data related to UAS mishaps in wildfire response. In this research, we apply state-of-the-art natural language processing (NLP) techniques to develop a custom Named Entity Recognition (NER) model which extracts entities relevant to safety analysts. The custom NER model is built by fine-tuning an existing Bidirectional Encoder Representations from Transformers (BERT) model, resulting in a generalizable NER model that can extract engineering relevant entities including failure modes, causes, effects, control processes, and recommendations from failure-relevant text. This model performs passably, with a weighted average f1 score of 0.33 across entity types, indicating more labeled training data is needed. Extracted entities are used to form a Failure Modes and Effects Analysis (FMEA)-style survey of wildfire UAS mishaps reported using the SAFECOM system. Similar mishaps are manually clustered and reported as single rows within an FMEA. Foreach cluster, we compute frequency, severity, and overall riskin accordance with FAA standards. This methodology can beapplied as part of a broader safety management system totrack trends in mishaps (e.g., likelihood, severity) and discoverknowledge (e.g., causes, effects) that can be utilized to improvesafety outcomes and system performance.

Machine Learning↗
NASA NTRSDate not supplied

What Went Wrong: A Survey of Wildfire UAS Mishaps through Named Entity Recognition

Increasingly, unmanned aircraft systems (UAS) are being applied to wildfire incidents for tasks such as mapping, aerial ignition, and delivery. As a result, incident reporting systems for wildfires are beginning to accumulate data related to UAS mishaps in wildfire response. In this research, we apply state-of-the-art natural language processing (NLP) techniques to develop a custom Named Entity Recognition (NER) model which extracts a Failure Modes and Effects Analysis (FMEA)-style survey of wildfire UAS mishaps reported in SAFECOM. The custom NER model is built by fine-tuning an existing (BERT) model, resulting in a generalizable NER model that can extract engineering relevant entities including failure modes, causes, effects, control processes, and recommendations from any failure-relevant text. Similar mishaps are clustered and reported as single rows within the FMEA. For each cluster, frequency, severity, and overall risk are computed. The methodology can be applied as part of a broader safety management system to track trends in mishaps and discover knowledge that can be utilized to improve safety outcomes and system performance.

Machine Learning↗
NASA NTRS2011

Classification

A supervised learning task involves constructing a mapping from input data (normally described by several features) to the appropriate outputs. Within supervised learning, one type of task is a classification learning task, in which each output is one or more classes to which the input belongs. In supervised learning, a set of training examples---examples with known output values---is used by a learning algorithm to generate a model. This model is intended to approximate the mapping between the inputs and outputs. This model can be used to generate predicted outputs for inputs that have not been seen before. For example, we may have data consisting of observations of sunspots. In a classification learning task, our goal may be to learn to classify sunspots into one of several types. Each example may correspond to one candidate sunspot with various measurements or just an image. A learning algorithm would use the supplied examples to generate a model that approximates the mapping between each supplied set of measurements and the type of sunspot. This model can then be used to classify previously unseen sunspots based on the candidate's measurements. This chapter discusses methods to perform machine learning, with examples involving astronomy.

Oza, Nikunj C.↗
NASA NTRS1992

Locus of the single-channel bottleneck in dual-task interference

Two experiments used the locus-of-cognitive-slack method to determine whether dual-task interference occurs before or after the response selection stage. The experiments used the overlapping tasks paradigm, in which two signals, each requiring a different speeded choice response, are presented in rapid succession. In Experiment 1, stimulus-response (S-R) compatibility was manipulated by varying whether Task 2 stimuli were mapped onto their responses by a rule or arbitrarily. Compatibility effects were additive with the effects of degree of task overlap, manipulated by varying the stimulus onset asynchrony between the signals. Experiment 2 examined 2 additional forms of S-R compatibility: symbolic compatability (arrows vs. letters) and spatial compatibility (the 'Simon' effect). Effects of symbolic compatibility were additive with effects of degree of task overlap, whereas the effects of spatial compatibility and degree of task overlap were underadditive. It is argued that only a central-bottleneck model provides a consistent account of these results. The nature of the central bottleneck is considered.

Mccann, Robert S.↗
NASA NTRS2011

The Functional Task Test (FTT): An Interdisciplinary Testing Protocol to Investigate the Factors Underlying Changes in Astronaut Functional Performance

Exposure to space flight causes adaptations in multiple physiological systems including changes in sensorimotor, cardiovascular, and neuromuscular systems. These changes may affect a crewmember s ability to perform critical mission tasks immediately after landing on a planetary surface. The overall goal of this project is to determine the effects of space flight on functional tests that are representative of high priority exploration mission tasks and to identify the key underlying physiological factors that contribute to decrements in performance. To achieve this goal we developed an interdisciplinary testing protocol (Functional Task Test, FTT) that evaluates both astronaut functional performance and related physiological changes. Functional tests include ladder climbing, hatch opening, jump down, manual manipulation of objects and tool use, seat egress and obstacle avoidance, recovery from a fall and object translation tasks. Physiological measures include assessments of postural and gait control, dynamic visual acuity, fine motor control, plasma volume, orthostatic intolerance, upper- and lower-body muscle strength, power, endurance, control, and neuromuscular drive. Crewmembers perform this integrated test protocol before and after short (Shuttle) and long-duration (ISS) space flight. Data are collected on two sessions before flight, on landing day (Shuttle only) and 1, 6 and 30 days after landing. Preliminary results from both Shuttle and ISS crewmembers indicate decrement in performance of the functional tasks after both short and long-duration space flight. On-going data collection continues to improve the statistical power required to map changes in functional task performance to alterations in physiological systems. The information obtained from this study will be used to design and implement countermeasures that specifically target the physiological systems most responsible for the altered functional performance associated with space flight.

Bloomberg, J. J.↗
NASA NTRS1995

The PRP Effect Following Callosotomy: Residual Interference Despite Uncoupling of Lateralized Response Codes

A callosotomy patient was tested in two dual-task experiments requiring successive speeded responses to lateralized stimuli. In accord with the recent findings of Pashler, O'Brien, Luck, Hillyard, Mangun, and Gazzaniga (in press), the patient showed a robust psychological refractory period effect (PRP) responses on Task 2 were inversely related to the stimulus-onset asynchrony (SOA). However, three aspects of our data indicated that the processing limitations for the patient were different than those observed with control subjects. First, the split-brain patient did not show an increase in reaction time when the two tasks required responses from a common output system (i.e., both manual responses) in comparison to when different output systems were used (i.e., manual-vocal). Second, inconsistent stimulus-response mappings for the two tasks greatly inflated response latencies for the control subjects, but had minimal effect on the performance of the split-brain patient. Third, the consistency manipulation was underadditive with SOA for only the patient, suggesting a later bottleneck in processing following callosotomy than was observed for the control subjects. It is proposed that sectioning the corpus callosum eliminates interference resulting from competing stimulus response codes. Nonetheless, dual-task interference persists for the split-brain subject because a subcortical gate constrains when selected responses can be implemented.

Ivry, Richard B.↗
NASA NTRS1992

Mapping unstructured grid computations to massively parallel computers

Investigated here is this mapping problem: assign the tasks of a parallel program to the processors of a parallel computer such that the execution time is minimized. First, a taxonomy of objective functions and heuristics used to solve the mapping problem is presented. Next, we develop a highly parallel heuristic mapping algorithm, called Cyclic Pairwise Exchange (CPE), and discuss its place in the taxonomy. CPE uses local pairwise exchanges of processor assignments to iteratively improve an initial mapping. A variety of initial mapping schemes are tested and recursive spectral bipartitioning (RSB) followed by CPE is shown to result in the best mappings. For the test cases studied here, problems arising in computational fluid dynamics and structural mechanics on unstructured triangular and tetrahedral meshes, RSB and CPE outperform methods based on simulated annealing. Much less time is required to do the mapping and the results obtained are better. Compared with random and naive mappings, RSB and CPE reduce the communication time two fold for the test problems used. Finally, we use CPE in two applications on a CM-2. The first application is a data parallel mesh-vertex upwind finite volume scheme for solving the Euler equations on 2-D triangular unstructured meshes. CPE is used to map grid points to processors. The performance of this code is compared with a similar code on a Cray-YMP and an Intel iPSC/860. The second application is parallel sparse matrix-vector multiplication used in the iterative solution of large sparse linear systems of equations. We map rows of the matrix to processors and use an inner-product based matrix-vector multiplication. We demonstrate that this method is an order of magnitude faster than methods based on scan operations for our test cases.

Hammond, Steven Warren↗
NASA NTRSDate not supplied

SafeMAP: Safe Multi-Agent Planning Framework Based on Dynamic Probabilistic Risk Assessment

This paper proposes a risk-aware framework for Safe Multi-Agent Planning (SafeMAP) that unifies disparate models for multi-agent systems in a Markovian process that allows for simultaneous system health monitoring, decision making under uncertainty, and multi-agent system collaboration. As operations beyond low earth orbit mature, there is an increased need for autonomous cyber-physical systems with onboard decision making capabilities. Multi-agent cyber-physical systems in particular offer the potential of increased efficiency, resiliency, and mission capabilities for future applications such as multi-rover terrain operations, distributed satellite operations, and management of smart lunar habitats. SafeMAP utilizes physics-based models of each agent and the relevant components, probability models of the environment and component operational states, and reward models for mission-specific objectives such as scientific task completion or resource consumption. The output of SafeMAP is a set of mission plans that satisfy the mission objective under specified risk/reward constraints. A readable interpretation of each of these generated mission plans is provided as an additional output. SafeMAP has been demonstrated on a simulated case study involving a four-rover system performing surface mapping operations and science tasks. Results of this paper demonstrate SafeMAP’s ability to generate explainable mission plans that satisfy the mission objective while minimizing risk under nominal and off-nominal conditions.

Mohammad Hejase↗
NASA NTRSDate not supplied

SafeMAP: Safe Multi-Agent Planning framework based on Dynamic Probabilistic Risk Assessment

This paper proposes a risk-aware framework for Safe Multi-Agent Planning (SafeMAP) that unifies disparate models for multi-agent systems in a Markovian process that allows for simultaneous system health monitoring, decision making under uncertainty, and multi-agent system collaboration. As operations beyond low earth orbit mature, there is an increased need for autonomous cyber-physical systems with onboard decision making capabilities. Multi-agent cyber-physical systems in particular offer the potential of increased efficiency, resiliency, and mission capabilities for future applications such as multi-rover terrain operations, distributed satellite operations, and management of smart lunar habitats. SafeMAP utilizes physics-based models of each agent and the relevant components, probability models of the environment and component operational states, and reward models for mission-specific objectives such as scientific task completion or resource consumption. The output of SafeMAP is a set of mission plans that satisfy the mission objective under specified risk/reward constraints. A readable interpretation of each of these generated mission plans is provided as an additional output. SafeMAP has been demonstrated on a simulated case study involving a four-rover system performing surface mapping operations and science tasks. Results of this paper demonstrate SafeMAP’s ability to generate explainable mission plans that satisfy the mission objective while minimizing risk under nominal and off-nominal conditions.

Mohammad Hejase↗
NASA NTRS2008

The Moon is a Planet Too: Lunar Science and Robotic Exploration

The first decades of the 21st century will be marked by major lunar science and exploration activities. The Moon is a witness to 4.5 billion years of solar system history, recording that history more completely and more clearly than any other planetary body. Lunar science encompasses early planetary evolution and differentiation, lava eruptions and fire fountains, impact scars throughout time, and billions of years of volatile input. I will cover the main outstanding issues in lunar science today and the most intriguing scientific opportunities made possible by renewed robotic and human lunar exploration. Barbara is a planetary scientist at NASA s Marshall Space Flight Center. She studies meteorites from the Moon, Mars and asteroids and has been to Antarctica twice to hunt for them. Barbara also works on the Mars Exploration Rovers Spirit and Opportunity and has an asteroid named after her. She is currently helping the Lunar Precursor Robotics Program on the Lunar Mapping and Modeling Project, a project tasked by the Exploration System Mission Directorate (ESMD) to develop maps and tools of the Moon to benefit the Constellation Program lunar planning. She is also supporting the Science Mission Directorate s (SMD) lunar flight projects line at Marshall as the co-chair of the Science Definition Team for NASA s next robotic landers, which will be nodes of the International Lunar Network, providing geophysical information about the Moon s interior structure and composition.

Cohen, Barbara↗
NASA NTRS1989

Cognitive perspectives on map displays for helicopter flight

Currently accessible technologies are providing entirely new display concepts for enhancing helicopter navigation. Yet the effectiveness of such displays depends on the extent to which they are configured according to principles from research on human performance. Computer generated map displays in the present study were configured according to previous research on maps, navigational problem solving, and spatial cognition in large scale environments. Interest centered on the representation of different spatial relationships that would best support helicopter navigational problem solving. One map display emphasized the global relationships between objects in the environment. The other map showed the pilot's relationship to objects as he traveled through the environment. Twenty skilled pilots used the maps to complete several navigational tasks that occurred within a realistic simulation program tailored for helicopter navigation. Findings indicate that the type of task and mode of flight (low level or Nap of the Earth (NOE)) are important determinants of map display effectiveness.

Harwood, Kelly↗
NASA NTRS1991

The performance evaluation of a new neural network based traffic management scheme for a satellite communication network

A neural-network-based traffic management scheme for a satellite communication network is described. The scheme consists of two levels of management. The front end of the scheme is a derivation of Kohonen's self-organization model to configure maps for the satellite communication network dynamically. The model consists of three stages. The first stage is the pattern recognition task, in which an exemplar map that best meets the current network requirements is selected. The second stage is the analysis of the discrepancy between the chosen exemplar map and the state of the network, and the adaptive modification of the chosen exemplar map to conform closely to the network requirement (input data pattern) by means of Kohonen's self-organization. On the basis of certain performance criteria, whether a new map is generated to replace the original chosen map is decided in the third stage. A state-dependent routing algorithm, which arranges the incoming call to some proper path, is used to make the network more efficient and to lower the call block rate. Simulation results demonstrate that the scheme, which combines self-organization and the state-dependent routing mechanism, provides better performance in terms of call block rate than schemes that only have either the self-organization mechanism or the routing mechanism.

Ansari, Nirwan↗