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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 NTRS2009

Mars Exploration Rover Flight Operations Technical Consultation

The Mars Exploration Rover (MER) Project at the Jet Propulsion Laboratory developed two golf-cart size robotic vehicles, Spirit and Opportunity, for geological exploration of designated target areas on the surface of Mars. The primary scientific objective of these missions was the search for evidence of the presence of water on or near the surface of the planet during its history. Spirit and Opportunity were launched on June 10 and July 7, 2003, with their respective landings scheduled for January 4 and January 25, 2004 (UTC). NASA views the MER missions as particularly critical because of their scientific importance in the ongoing search for conditions under which life might have existed elsewhere in the solar system, because of their high level of public interest and because more than half of all prior missions launched to Mars internationally have failed. This report summarizes the findings and recommendations of the NASA Engineering and Safety Center review of the project.

Leckrone, Dave S.↗
NASA NTRS1984

Design oriented identification of critical times in transient response

Two techniques are presented for reducing the computational effort in identifying the critical time points. One approach is an adaptive search technique, well suited for the case where the response is exactly known. The other technique, useful for noisy response, is based on a least-squares spline approximation of the response. The possibility of grouping several closely spaced local peaks to identify a single super peak from each group is also investigated. The computational efficiency of the techniques proposed here is illustrated by two examples.

Haftka, R. T.↗
NASA NTRS1989

Dynamics of Pluto

The present study of the Pluto orbit yielded by the LONGSTOP 1B, 100-Myr numerical integration of the outer planets has given attention to the 3:2 resonance in mean motion with Neptune up to degree 2 in eccentricities and inclinations. Confirmations are obtained for both the 19,900-year period longitudinal libration and the 3.78-Myr period libration of the Pluto pericenter argument. Because chaos originates with small divisors, possible resonances have been searched for among the frequencies associated with the critical arguments. The macroscopic stability of the orbit of Pluto is explainable in terms of the association of high-order resonances with small chaotic regions.

Milani, A.↗
NASA NTRS1996

NASA Space Missions to Asteroids: Protecting the Earth from NEO Impacts

There is now a general recognition of the hazard of impacts on Earth by comets and asteroids, but there is yet no consensus concerning international actions that should be taken to protect the planet from such impacts. An essential step in the analysis of the situation involves estimating the relative hazard posed by comets and asteroids of different sizes and orbits. All recent studies agree that the larger impacts pose the greater danger, and that our primary concern from the perspective of total risk should be on impacts that are large enough to cause global ecological catastrophe. These global catastrophes are also of special interest, since they (alone among natural disasters) have the potential to destroy civilization. Studies of the sensitivity of the Earth's environment suggest that the energy threshold energy for causing a global catastrophe is at about 1 million megatons, corresponding to impactor diameters of 1.5 to 2 km. This information leads naturally to a strategy of concentrating on the larger NEOs, say those 1 km or more in diameter. This is the rationale for the Spaceguard Survey, which must be the highest priority in mitigation efforts. The second question concerns the value of developing standing defensive systems that could deflect or destroy an incoming NEO. In the case of the asteroids larger than 1 km in diameter, no such system is needed, since there will be ample time (at least several decades) between the discovery of the threatening object by Spaceguard and the requirement to take action against it. In the case of objects smaller than 1 km diameter, development of defensive systems is not cost-effective; there are many greater dangers to persons and property that are much more urgent. Only in the case of large long-period comets is there a rationale for standing defense systems. The question is also raised whether the risks inherent in developing and maintaining a defense system might be greater than the impact risks it is intended to guard against. These and related issues are the focus of much current international debate on defense of the planet against NEO impacts. Meanwhile, the most critical issue remains the expansion of the telescopic search for NEOs.

Morrison, David↗
NASA NTRS2011

Share the Sky: Concepts and Technologies That Will Shape Future Airspace Use

The airspace challenge for the United States is to protect national sovereignty and ensure the safety and security of those on the ground and in the air, while at the same time ensuring the efficiency of flight, reducing the costs involved, protecting the environment, and protecting the freedom of access to the airspace. Many visions of the future NAS hold a relatively near-term perspective, focusing on existing uses of the airspace and assuming that new uses will make up a small fraction of total use. In the longer term, the skies will be filled with diverse and amazing new air vehicles filling our societal needs. Anticipated new vehicles include autonomous air vehicles acting both independently and in coordinated groups, unpiloted cargo carriers, and large numbers of personal air vehicles and small-scale point-to-point transports. These vehicles will enable new capabilities that have the potential to increase societal mobility, transport freight at lower cost and with lower environmental impact, improve the study of the Earth s atmosphere and ecosystem, and increase societal safety and security by improving or drastically lowering the cost of critical services such as firefighting, emergency medical evacuation, search and rescue, border and neighborhood surveillance, and the inspection of our infrastructure. To ensure that uses of the airspace can continue to grow for the benefit of all, a new paradigm for operations is needed: equitably and safely sharing the airspace. This paper is an examination of such a vision, concentrating on the operations of all types of air vehicles and future uses of the National Airspace. Attributes of a long-term future airspace system are provided, emerging operations technologies are described, and initial steps in research and development are recommended.

Ballin, Mark G.↗
NASA NTRS2011

Auto-Gopher: A Wire-Line Rotary-Hammer Ultrasonic Drill

Developing technologies that would enable NASA to sample rock, soil, and ice by coring, drilling or abrading at a significant depth is of great importance for a large number of in-situ exploration missions as well as for earth applications. Proven techniques to sample Mars subsurface will be critical for future NASA astrobiology missions that will search for records of past and present life on the planet, as well as, the search for water and other resources. A deep corer, called Auto-Gopher, is currently being developed as a joint effort of the JPL's NDEAA laboratory and Honeybee Robotics Corp. The Auto-Gopher is a wire-line rotary-hammer drill that combines rock breaking by hammering using an ultrasonic actuator and cuttings removal by rotating a fluted bit. The hammering mechanism is based on the Ultrasonic/Sonic Drill/Corer (USDC) that has been developed as an adaptable tool for many of drilling and coring applications. The USDC uses an intermediate free-flying mass to transform the high frequency vibrations of the horn tip into a sonic hammering of a drill bit. The USDC concept was used in a previous task to develop an Ultrasonic/Sonic Ice Gopher. The lessons learned from testing the ice gopher were implemented into the design of the Auto-Gopher by inducing a rotary motion onto the fluted coring bit. A wire-line version of such a system would allow penetration of significant depth without a large increase in mass. A laboratory version of the corer was developed in the NDEAA lab to determine the design and drive parameters of the integrated system. The design configuration lab version of the design and fabrication and preliminary testing results are presented in this paper

life dectection↗
NASA NTRS2018

Data Mining for Vortices on the Earth's Magnetosphere - Algorithm Application for Detection and Analysis

Unsteady processes in the solar wind– magnetosphere interaction, such as vortices developed at the magnetopause boundary by the Kelvin–Helmholtz instability, may contribute to the process of mass, momentum and energy transfer into the Earth’s magnetosphere. The research described in this paper validates an algorithm to automatically detect and characterize vortices based on velocity data from simulations. The vortex identification algorithm (VIA) systematically searches the 3-D velocity fields to identify critical points where the magnitude of the velocity vector vanishes. The velocity gradient tensor is computed and its invariants are used to assess vortex structure in the flow field. We use the Community Coordinated Modeling Center (CCMC) Runs on Request capability to create a series of model runs initialized from the conditions observed by the Cluster mission in the Hwang et al. (2011) analysis of Kelvin–Helmholtz vortices observed during southward interplanetary magnetic field (IMF) conditions. We analyze further the properties of the vortices found in the runs, including the velocity changes within their motion across the magnetosheath. We also demonstrate the potential of our tool to identify and characterize other transient features (e.g., flux transfer events, FTEs) with vortical internal structures. We find that the vortices are associated with flows on the magnetosheath side of the magnetopause that reach speeds greater than the solar wind speed at the bow shock.

Collado-Vega, Yaireska M.↗
NASA NTRSDate not supplied

Semantic Search with Sentence-BERT for Design Information Retrieval

Managing and referencing design knowledge is a critical activity in the design process. However, reliably retrieving useful knowledge can be a frustrating experience for users of knowledge management systems due to inherent limitations of standard keyword-based searches. In this research, we consider the task of retrieving relevant lessons learned from the NASA Lessons Learned Information System (LLIS). To this end, we apply a state-of-the-art natural language processing (NLP) technique for information retrieval (IR): semantic search with sentence-BERT, which is a modification of a Bidirectional Encoder Representations from Transformers (BERT) model that uses siamese and triplet network architectures to obtain semantically meaningful sentence embeddings. While the pre-trained sBERT model performs well out-of-the-box, we further fine-tune the model on data from the LLIS so that it learns on design engineering-relevant vocabulary. We quantify the improvement in query results using both standard sBERT and fine-tuned sBERT over a keyword search. Our use case throughout the paper is to use queries related to specific requirements from a NASA project. Fine tuning the sBERT model on LLIS data yields a mean average precision (MAP) of 0.807 on queries based on information needs from a real NASA project. Results indicate that applying state-of-the-art natural language processing techniques, especially when finetuned using engineering data, to design information retrieval tasks shows significant promise in modernizing design knowledge management systems.

Hannah S. Walsh↗
NASA NTRSDate not supplied

Semantic Search with Sentence-BERT for Design Information Retrieval

Managing and referencing design knowledge is a critical activity in the design process. However, reliably retrieving useful knowledge can be a frustrating experience for users of knowledge management systems due to inherent limitations of standard keyword-based searches. In this research, we consider the task of retrieving relevant lessons learned from the NASA Lessons Learned Information System (LLIS). To this end, we apply a state-of-the-art natural language processing (NLP) technique for information retrieval: semantic search with sentence-BERT, which is a modification of a Bidirectional Encoder Representations from Transformers (BERT) model that uses siamese and triplet network architectures to obtain semantically meaningful sentence embeddings. While the pretrained sBERT model shows excellent out-of-the-box performance, we further fine-tune the model on data from the LLIS so that it learns on design engineering-relevant vocabulary. We quantify the improvement in query results using both standard sBERT and fine-tuned sBERT over the LLIS’s built-in keyword search. Additionally, we demonstrate a use case for the query system by searching for lessons learned relevant to specific requirements from a NASA project as part of a broader knowledge management and retrieval system. Results indicate that applying state-of-the-art natural language processing techniques, especially when fine-tuned using engineering data, to design information retrieval tasks shows significant promise in modernizing design knowledge management systems.

Hannah S. Walsh↗
NASA NTRS1981

Superconductivity, cohesive energy density, and electron-atom ratio in metals

It is shown that superconductivity above 8 K occurs in alloys and metallic compounds within relatively narrow regions of cohesive energy density with a sharp peak which includes Nb3Ge, SiV3, Nb3Ga, and NbN. When cross-correlated with the electron-atom ratio, high-temperature superconductivity can be observed in only a few regions. This suggests a search for superconductors with high-transition temperatures and critical fields within these regions.

England, C.↗
NASA NTRS1991

Intelligent perturbation algorithms to space scheduling optimization

The limited availability and high cost of crew time and scarce resources make optimization of space operations critical. Advances in computer technology coupled with new iterative search techniques permit the near optimization of complex scheduling problems that were previously considered computationally intractable. Described here is a class of search techniques called Intelligent Perturbation Algorithms. Several scheduling systems which use these algorithms to optimize the scheduling of space crew, payload, and resource operations are also discussed.

Kurtzman, Clifford R.↗
NASA NTRS1992

ULF waves in the outer magnetosphere of Uranus

ULF waves are ubiquitous in the terrestrial magnetosphere, and play a critical role in the physics of the magnetosphere. A search for similar waves in the Uranian magnetosphere using Voyager 2 magnetometer data reveals ULF waves in the outer magnetosphere near the magnetopause. These waves decrease in amplitude with distance from the magnetopause. In the interior of the magnetosphere the wave level is at or below the noise level of the instrument.

Russell, C. T.↗
NASA NTRS1992

The MICRO-BOSS scheduling system: Current status and future efforts

In this paper, a micro-opportunistic approach to factory scheduling was described that closely monitors the evolution of bottlenecks during the construction of the schedule and continuously redirects search towards the bottleneck that appears to be most critical. This approach differs from earlier opportunistic approaches, as it does not require scheduling large resource subproblems or large job subproblems before revising the current scheduling strategy. This micro-opportunistic approach was implemented in the context of the MICRO-BOSS factory scheduling system. A study comparing MICRO-BOSS against a macro-opportunistic scheduler suggests that the additional flexibility of the micro-opportunistic approach to scheduling generally yields important reductions in both tardiness and inventory. Current research efforts include: adaptation of MICRO-BOSS to deal with sequence-dependent setups and development of micro-opportunistic reactive scheduling techniques that will enable the system to patch the schedule in the presence of contingencies such as machine breakdowns, raw materials arriving late, job cancellations, etc.

Sadeh, Norman M.↗
NASA NTRS1993

The MICRO-BOSS scheduling system: Current status and future efforts

In this paper, a micro-opportunistic approach to factory scheduling was described that closely monitors the evolution of bottlenecks during the construction of the schedule, and continuously redirects search towards the bottleneck that appears to be most critical. This approach differs from earlier opportunistic approaches, as it does not require scheduling large resource subproblems or large job subproblems before revising the current scheduling strategy. This micro-opportunistic approach was implemented in the context of the MICRO-BOSS factory scheduling system. A study comparing MICRO-BOSS against a macro-opportunistic scheduler suggests that the additional flexibility of the micro-opportunistic approach to scheduling generally yields important reductions in both tardiness and inventory.

Sadeh, Norman M.↗
NASA NTRS2011

Pattern Recognition for a Flight Dynamics Monte Carlo Simulation

The design, analysis, and verification and validation of a spacecraft relies heavily on Monte Carlo simulations. Modern computational techniques are able to generate large amounts of Monte Carlo data but flight dynamics engineers lack the time and resources to analyze it all. The growing amounts of data combined with the diminished available time of engineers motivates the need to automate the analysis process. Pattern recognition algorithms are an innovative way of analyzing flight dynamics data efficiently. They can search large data sets for specific patterns and highlight critical variables so analysts can focus their analysis efforts. This work combines a few tractable pattern recognition algorithms with basic flight dynamics concepts to build a practical analysis tool for Monte Carlo simulations. Current results show that this tool can quickly and automatically identify individual design parameters, and most importantly, specific combinations of parameters that should be avoided in order to prevent specific system failures. The current version uses a kernel density estimation algorithm and a sequential feature selection algorithm combined with a k-nearest neighbor classifier to find and rank important design parameters. This provides an increased level of confidence in the analysis and saves a significant amount of time.

Restrepo, Carolina↗
NASA NTRSDate not supplied

Enhancing Air Traffic Control Planning with Automatic Speech Recognition

The decisions made during the Federal Aviation Administration Air Traffic Control System Command Center's planning teleconferences hold significant sway over the National Airspace System. Held every two hours, these teleconferences convene air traffic managers and stakeholders from across the nation to discuss airspace conditions, weather, and constraints, leading to the formulation and adjustment of traffic management initiatives. Given the critical nature of these decisions, the need for accurate and efficient record-keeping is paramount. In recent years, the application of automatic speech recognition has gained popularity across diverse industries, including aviation. While traditional applications focus on transcribing air traffic control communication, this paper explores a unique application of automatic speech recognition by converting the audio from planning teleconferences into text transcriptions. This innovative approach addresses key challenges in the field, presenting potential benefits for quality assurance, real-time participation, and downstream natural language processing tasks. A notable breakthrough in the machine learning community, namely the transformer neural network architecture, forms the backbone of the proposed solution in this paper. The transformer architecture's role in this research represents a paradigm shift in the efficiency of automatic speech recognition models. By reducing the amount of in-domain training data required, this architecture allows for the fine-tuning of such models like Whisper, originally pretrained on vast English speech datasets. The adaptability of the transformer architecture proves invaluable in capturing the nuances of aviation terminology and specific language used in planning teleconferences. Leveraging the Whisper model as a baseline, our research details the fine-tuning and validation using a dataset comprising 20 hours of meticulously transcribed planning teleconferences. Notably, the baseline pretrained Whisper model exhibited a word error rate of 18.77%. Through the fine-tuning process, the model achieved a substantial improvement, demonstrating an impressive performance with a reduced word error rate of 6.82%. This substantial decrease in WER not only highlights the effectiveness of the transformer architecture but also emphasizes the practical advancements achieved through the application of automatic speech recognition in this specific domain. The utilization of automatic speech recognition in planning teleconferences in this work introduces several novelties. Firstly, the creation of text transcriptions offers a valuable tool for quality assurance and facilitates the efficient review of teleconferences. This is an important aspect of the proposed solution, given the time-sensitive and high-stakes nature of decisions made during these meetings. Furthermore, text-searchable transcriptions provide a streamlined approach for locating and validating critical information, potentially saving hours of manual effort in searching through audio recordings. Moreover, our research identifies a key use case for external facilities and stakeholders. In situations where attendance at the planning teleconference is not feasible, having access to text transcriptions in real-time or shortly after the teleconference ends, proves to be a time-saving and informative resource. This feature enhances collaboration and ensures that stakeholders can stay abreast of important discussions and decisions even in their absence. Despite the efficiency gains facilitated by the transformer architecture in automatic speech recognition technology, it is essential to acknowledge the human factors in data creation. Subject matter experts play a crucial role in accurately transcribing planning teleconferences due to the specificity and complexity of the information discussed. The research dataset, consisting of 20 hours of transcribed planning teleconferences, forms the foundation for fine-tuning and validating the Whisper model. The achieved word error rate of 6.82% demonstrates promising advancements, particularly in recognizing essential aviation terminology within the teleconferences. In conclusion, this paper presents a comprehensive exploration of the application of automatic speech recognition in Air Traffic Control System Command Center planning teleconferences, leveraging the transformer architecture for enhanced efficiency. The novel contributions lie in the improved accessibility of decision-making records, real-time participation opportunities for external stakeholders, and the potential for downstream natural language processing advancements. As the aviation industry continues to evolve, the integration of automatic speech recognition technologies holds the promise of revolutionizing decision-making processes and contributing to the overall safety and efficiency of air traffic management.

ATM↗
NASA NTRS2016

A Large-Scale Search for Evidence of Quasi-Periodic Pulsations in Solar Flares

The nature of quasi-periodic pulsations (QPP) in solar flares is poorly constrained, and critically the general prevalence of such signals in solar flares is unknown. Therefore, we perform a large-scale search for evidence of signals consistent with QPP in solar flares, focusing on the 1300 s timescale. We analyze 675 M- and X-class flares observed by the Geostationary Operational Environmental Satellite (GOES) series in 18 soft X-rays between 2011 February 1 and 2015 December 31. Additionally, over the same era we analyze Fermi/Gamma-ray Burst Monitor (GBM) 1525 keV X-ray data for each of these flares associated with a Fermi/GBM solar flare trigger, a total of 261 events. Using a model comparison method, we determine whether there is evidence for a substantial enhancement in the Fourier power spectrum that may be consistent with a QPP signature, based on three tested models; a power-law plus a constant, a broken power-law plus constant, and a power-law-plus-constant with an additional QPP signature component. From this, we determine that approx. 30% of GOES events and approx. 8% of Fermi/GBM events show strong signatures consistent with classical interpretations of QPP. For the remaining events either two or more tested models cannot be strongly distinguished from each other, or the events are well-described by single power-law or broken power-law Fourier power spectra. For both instruments, a preferred characteristic time-scale of approx. 5-30 s was found in the QPP-like events, with no dependence on flare magnitude in either GOES or GBM data. We also show that individual events in the sample show similar characteristic time-scales in both GBM and GOES data sets. We discuss the implications of these results for our understanding of solar flares and possible QPP mechanisms.

Inglis, A. R.↗