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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 37 records · Page 2
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Higher spin partition functions via the quasinormal mode method in de Sitter quantum gravity

In this note we compute the 1-loop partition function of spin- s s fields on Euclidean de Sitter space S^{2n+1} S 2 n + 1 using the quasinormal mode method. Instead of computing the quasinormal mode frequencies from scratch, we use the analytic continuation prescription L_{\text{AdS}}\to iL_{\text{dS}} L AdS → i L dS , appearing in the dS/CFT correspondence, and Wick rotate the normal mode frequencies of fields on thermal \text{AdS}_{2n+1} AdS 2 n + 1 into the quasinormal mode frequencies of fields on de Sitter space. We compare the quasinormal mode and heat kernel methods of calculating 1-loop determinants, finding exact agreement, and furthermore explicitly relate these methods via a sum over the conformal dimension. We discuss how the Wick rotation of normal modes on thermal \text{AdS}_{2n+1} AdS 2 n + 1 can be generalized to calculating 1-loop partition functions on the thermal spherical quotients S^{2n+1}/\mathbb{Z}_{p} S 2 n + 1 / ℤ p . We further show that the quasinormal mode frequencies encode the group theoretic structure of the spherical spacetimes in question, analogous to the analysis made for thermal AdS in [1-3] .

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2026

An analytic result for the 0 → ggHHH amplitude

We present a fully analytic calculation of the leading-order one-loop amplitude for triple Higgs production via gluon fusion, gg → HHH, retaining full dependence on the mass of the heavy quark circulating in the loop. This amplitude provides a direct probe of the triple and quartic Higgs self-couplings, the measurement of which is a central goal of current and future colliders. The amplitude can be presented in compact form thanks to the use of analytic reconstruction techniques, based on finite-field and p-adic evaluations, multivariate partial fraction decompositions, and primary decompositions to identify common numerator factors. Although full analytic results are given in the text and in the supplementary material, the main thrust of this paper is to further test and illustrate these analytic reconstruction techniques in a concrete physical example. Our results provide a compact and efficient representation of the matrix element for this process, enabling evaluations that are more than an order of magnitude faster than existing numerical alternatives. Full analytic control of the leading-order, loop-induced amplitude is an important step towards handling more complex 2-loop or real-radiation corrections to this and related processes.

Campbell, John M. [Fermilab] (ORCID:00000002136193↗
DOE OSTI2020

Kinetic Simulations of Microstructural Evolution (KSOME)

"Kinetic simulations of microstructural evolution" (KSOME) is an object Kinetic Monte Carlo (OMKC) simulation code. It is developed to simulate microstructural evolution in materials during irradiation. KSOME is developed from ground up with priority given to the flexibility, ease of upgradability, and computation efficiency, in that order. With previously developed simulation codes, various processes (more precisely, the diffusion-reaction processes) that can occur in a system were hardwired into the code. Hence, to perform higher fidelity simulations, a significant coding effort was required every time to incorporate either a more accurate description of existing processes or new processes. With KSOME, the necessity for frequent code upgrades whenever there is a need to perform higher fidelity simulations is either eliminated or reduced significantly. In KSOME, the categories of various diffusion-reaction processes and the data-management system are hardwired, while the execution of the diffusion-reaction processes specific to a system is specified via input files. In the present version of KSOME, the analytical expression required to calculate defect interaction radii are inputted via a text file. However, the ability to parse mathematical expressions from a text file can be extended to input the analytical expression to calculate other defect properties; including the expressions to calculate the change in the migration barriers of mobile defects due to long-range interaction with extended defects

Nandipati, Giridhar [Pacific Northwest National La↗
DOE OSTI2018

Theoretical Expressions for the Ascent Rate of Moist Deep Convective Thermals

An approximate analytic expression is derived for the ratio λ of the ascent rate of moist deep convective thermals and the maximum vertical velocity within them; λ is characterized as a function of two nondimensional buoyancy-dependent parameters y and h and is used to express the thermal ascent rate as a function of the buoyancy field. The parameter y characterizes the vertical distribution of buoyancy within the thermal, and h is the ratio of the vertically integrated buoyancy from the surface to the thermal top and the vertical integral of buoyancy within the thermal. Theoretical λ values are calculated using values of y and h obtained from idealized numerical simulations of ascending moist updrafts and compared to λ computed directly from the simulations. The theoretical values of [Formula: see text] 0.4–0.8 are in reasonable agreement with the simulated λ (correlation coefficient of 0.86). These values are notably larger than the [Formula: see text] from Hill’s (nonbuoyant) analytic spherical vortex, which has been used previously as a framework for understanding the dynamics of moist convective thermals. The relatively large values of λ are a result of net positive buoyancy within the upper part of thermals that opposes the downward-directed dynamic pressure gradient force below the thermal top. These results suggest that nonzero buoyancy within moist convective thermals, relative to their environment, fundamentally alters the relationship between the maximum vertical velocity and the thermal-top ascent rate compared to nonbuoyant vortices. Implications for convection parameterizations and interpretation of the forces contributing to thermal drag are discussed.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS2020

What Can We Learn from One Billion Ground System Log Messages?

Shortage of log-based data in a ground system they have traditionally been the under achievers in a satellite ground system. This is due to several factors: Once log messages scroll out of view on the TTC event console window they are soon forgotten. Application and system log files are scattered across directories within a system, across a multitude of servers, and across one or more databases making access cumbersome. Typical tools to perform log file content searching are generally crude and typically only employed as part of trouble-shooting exercises.As we move towards satellite constellations and fleets and add even more status information, the number of messages keeps growing. One mission now estimates that they could generate 3,000,000 messages per day 1 billion per year - for the life of their mission. What to do with those 1 billion messages? That is the challenge. With the recent technological advances in the management of large data sets, text-based processing, and data analytics, there are now capabilities that we can provide to the ground system engineers and satellite operators to address what we postulate are missed opportunities. Advanced real-time log analysis can allow us to be less reactionary in favor of being more proactive. Analytics goals include the ability to: Identify root cause of unexpected events, failures or error conditions enabled by correlating disparate data. Detect security breaches attempts before they are successful. Help admins ensure IT resources continue running optimally. Identify trends and patterns that may indicate impending failures or error conditions for valuable assets before they happen. Compare satellites in a fleet or constellation in terms of number of alarms, number of command sent to them, etc.. Answer questions like "Are the operations support needs increasing over the past year?" or "Have we seen this combination of alarm conditions before?" But really, once the tools are readily available the users will start realizing what can be done with their new powers. In this presentation we will show the results of analyzing millions of actual mission operations log messages, how the results can be displayed to the user, and how new products now available as open source can be applied to the challenges of large scale time-tagged text-based mission operations messages. Flight operations team members believe that this is a powerful new option for how they assess overall system and space asset health. Technical descriptions of the design, tools, and storage will be provided. One billion messages? Bring'em on!

Orsborne, Sharon↗
DOE OSTI2019

An improved understanding of the roles of atomic processes and power balance in divertor target ion current loss during detachment

The process of divertor detachment, whereby heat and particle fluxes to divertor surfaces are strongly diminished, is required to reduce heat loading and erosion in a magnetic fusion reactor to acceptable levels. In this paper, the physics leading to the decrease of the total divertor ion current ($I_t$), or ‘roll-over’, is experimentally explored on the TCV tokamak through characterization of the location, magnitude and role of the various divertor ion sinks and sources including a complete analysis of particle and power balance. These first measurements of the profiles of divertor ionisation and hydrogenic radiation along the divertor leg are enabled through novel spectroscopic techniques. Over a range in TCV plasma conditions (plasma current and electron density, with/ without impurity-seeding) the $I_t$ roll-over is ascribed to a drop in the divertor ion source; recombination remains small or negligible farther into the detachment process. Further, the ion source reduction is driven by both a reduction in the power available for ionization, $P_{\text{recl}}$, and concurrent increase in the energy required per ionisation, $E_{\text{ion}}$: this effect of power available on the ionization source is often described as ‘power starvation’ (or ‘power limitation’). The detachment threshold is found experimentally (in agreement with analytic model predictions) to be ~$P_{\text{recl}}/I_tE_{\text{ion}}$ ~ 2, corresponding to a target electron temperature, $T_t ~ E_{\text{ion}}/γ$ where $\gamma$ is the sheath transmission coefficient. The target pressure reduction, required to reduce the target ion current, is driven both by volumetric momentum loss as well as upstream pressure loss. The measured evolution through detachment of the divertor profile of various ion sources/ sinks as well as power losses are quantitatively reproduced through full 2D SOLPS modelling through the detachment process as the upstream density is varied.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2021

Large-Scale Trajectory Analysis via Feature Vectors

The explosion of both sensors and GPS-enabled devices has resulted in position/time data being the next big frontier for data analytics. However, many of the problems associated with large numbers of trajectories do not necessarily have an analog with many of the historic big-data applications such as text and image analysis. Modern trajectory analytics exploits much of the cutting-edge research in machine-learning, statistics, computational geometry and other disciplines. We will show that for doing trajectory analytics at scale, it is necessary to fundamentally change the way the information is represented through a feature-vector approach. We then demonstrate the ability to solve large trajectory analytics problems using this representation.

58 GEOSCIENCES↗
NASA NTRS1980

Helicopter theory

A comprehensive presentation is made of the engineering analysis methods used in the design, development and evaluation of helicopters. After an introduction covering the fundamentals of helicopter rotors, configuration and operation, rotary wing history, and the analytical notation used in the text, the following topics are discussed: (1) vertical flight, including momentum, blade element and vortex theories, induced power, vertical drag and ground effect; (2) forward flight, including in addition to momentum and vortex theory for this mode such phenomena as rotor flapping and its higher harmonics, tip loss and root cutout, compressibility and pitch-flap coupling; (3) hover and forward flight performance assessment; (4) helicopter rotor design; (5) rotary wing aerodynamics; (6) rotary wing structural dynamics, including flutter, flap-lag dynamics ground resonance and vibration and loads; (7) helicopter aeroelasticity; (8) stability and control (flying qualities); (9) stall; and (10) noise.

Johnson, W.↗
DOE OSTI2022

Isotherm Model for Moisture-Controlled CO 2 Sorption

Moisture-controlled sorption of CO 2 , the basis for moisture-swing CO 2 capture from air, is a novel phenomenon observed in strong-base anion exchange materials. Prior research has shown that Langmuir isotherms provide an approximate fit to moisture-controlled CO 2 sorption isotherm data. However, this fit still lacks a governing equation derived from an analytic model. As such, in this paper we derive an analytic form for an isotherm equation from a bottom-up approach, starting with a fundamental theory for an alkali liquid. In the range of interest relevant to CO 2 capture from air, an isotherm equation for an alkali liquid reduces to a simple analytic form with a single parameter, $K_{\text{eq}}$. In the limit $K_{\text{eq}} \gg 1$, a 2nd order approximation simplifies to a Langmuir isotherm that, however, deviates from experimental data. The isotherm theory for an alkali liquid has been generalized to a strong-base anion exchange material. In a strong-base anion exchange material, water concentration inside a sorbent, [H 2 O], is not large enough to be regarded as constant, which allows us to extend $K_{\text{eq}}$ to $K_{\text{eq(AEM)eff}} = K_{\text{eq(AEM)}} \times$ [H 2 O]$^{–n}$ according to the law of mass action. The final isotherm formula has been validated by experimental data from the literature. For a moisture-controlled CO 2 sorbent, $K_{\text{eq(AEM)eff}}$ varies significantly with moisture content of the sorbent. Depending on moisture level, the observed $K_{\text{eq(AEM)eff}}$ in a specific sorbent ranges from a few times to a few thousand times the value of $K_{\text{eq}}$ of a 2 mol L –1 alkali liquid.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2019

Method and system for information retrieval and aggregation from inferred user reasoning

The visual analytic system enables information retrieval within large text collections. Typically, users have to directly and explicitly query information to retrieve it. With this system and process, the reasoning of the user is inferred from the user interaction they perform in a visual analytic tool, and the appropriate information to query, process, and visualize is systematically determined.

96 KNOWLEDGE MANAGEMENT AND PRESERVATION↗
DOE OSTI2019

Safety Analytics Forecasting and Evaluation Reporting (SAFER)

The SAFER Sandbox is a web application for testing various types of data visualization tools that analyze safety data across national laboratories. By enabling the user to visualize this data through visual and textual analyses, the SAFER Sandbox helps to facilitate the research and support for the National Nuclear Security Administration (NNSA) Office of Safety, Infrastructure and Operations (NA-50). Safety data across the national laboratory complex is not currently analyzed in one location. This prohibits administrators from viewing safety data trends and making large scale decisions based on a holistic view of the data. By implementing data analytics web services such as representative text summary, noun phrase extraction and graph exploration, users can view and explore safety data based on search queries. The data visualizations in the SAFER Sandbox reveal trends and point to items of concern based on safety data. The SAFER Sandbox is a testing ground for these visualizations.

98 NUCLEAR DISARMAMENT, SAFEGUARDS, AND PHYSICAL P↗
NASA NTRS1972

Revision of the standard reference data for thermocouples.

Revision of the International Practical Temperature Scale requires that there be changes for all accurately tabulated thermophysical values. Revised reference data for thermocouples have been generated in a program carried out by the National Bureau of Standards. The new reference data reflect not only revisions in the temperature scale, but also slight changes in the materials themselves and improvements in data fitting methods. A new NBS monograph that contains tables, analytic expressions, various approximations, and explanatory text has been prepared. A general discussion of the project and some specific examples are given.

Powell, R. L.↗
NASA NTRS2010

Preliminary Geological Findings on the BP-1 Simulant

The following is a summation of information and discussion between Doug Stoeser of the USGS and Doug Rickman of NASA in February and March, 2010 pertaining to the BP-1 simulant. The analytical results and the bulk of the text are from communications from Dr. Stoeser. The BP-1 simulant is made from Black Point Basalt Flow, San Francisco Volcanic Field, northern Arizona. There is an aggregate (road metal) quarry on the northern margin of the flow towards the west end that was used as a Desert Research and Technology Studies (Desert RATS) analog test site. Silty material from this site was also used in laboratory tests and found to have geotechnical properties similar to the LHT-2M and Chenobi regolith simulants and is being proposed as a possible simulant for geotechnical use. It currently has the designation of BP-1 (Black Point 1). Figure

Rickman, D. L.↗
NASA NTRSDate not supplied

Towards Automated Analytics of Research Publications

For readers of scientific publications it remains a big challenge to unambiguously relate the published research with the data used. To a substantial degree it is attributed to authors, journals, editors, and reviewers not prioritizing correct data citation, which impacts traceability, repeatability, and giving credits to published authors and their funding sources. Furthermore, uniform classification of the content of the published research is hampered by journals using journal specific topics and letting authors to assign free text keywords to their papers. We demonstrate automated analytics methods for extracting and relating datasets used and the research application areas by processing 1,300 research papers that referenced the NASA Giovanni service (but probably not the datasets in particular) as supporting their publication process. This presentation was given during the 2022 ESIP January meeting held virtually in January 2022.

Irina Gerasimov↗
DOE OSTI2017

The Impact of Streaming Data on Sensemaking with Mixed-Initative Visual Analytics

Visual data analysis helps people gain insights into data via interactive visualizations. People generate and test hypotheses and questions about data in context of the domain. This process can generally be referred to as sensemaking. Much of the work on studying sensemaking (and creating visual analytic techniques in support of it) has been focused on static datasets. However, how do the cognitive processes of sensemaking change when data are changing? Further, what implication for design does this create for mixed-initiative visual analytics systems? This paper presents the results of a user study analyzing the impact of streaming data on sensemaking. To perform this study, we developed a mixed-initiative visual analytic prototype, the Streaming Canvas, that affords the analysis of streaming text data. We compare the sensemaking process of people using this tool for a static and streaming dataset. We present the results of this study and discuss the implications on future visual analytic systems that combine machine learning and interactive visualization to help people make sense of streaming data.

visualization↗
DOE OSTI2022

Learning Global Proliferation Expertise Evolution Using AI-Driven Analytics and Public Information

Detecting and anticipating global proliferation expertise and capability evolution from unstructured, noisy, and incomplete public data streams is a highly desired, but extremely challenging task. Here, in this article, we present our pioneering data-driven approach to support the non-proliferation mission to detect and explain the evolution of proliferation expertise and capability development globally from terabytes of publicly available information (PAI), focusing on our knowledge extraction pipeline and descriptive analytics. We first discuss how we fuse nine open-source data streams, including multilingual data, to convert 4 TB of unstructured data to structured knowledge and encode dynamically evolving proliferation expertise representations—content and context graphs. For this, we rely on natural language processing (NLP) and deep learning (DL) models to perform information extraction, topic modeling, and distributed text representation (aka embedding) learning. We then present interactive, usable, and explainable descriptive analytics to refine domain knowledge and present it in a human-understandable form. Finally, we introduce future work avenues that will leverage our dynamic knowledge representations and descriptive analytics to enable predictive and prescriptive inferences to achieve real-time domain understanding and contextual reasoning about global proliferation expertise and capability evolution.

98 NUCLEAR DISARMAMENT, SAFEGUARDS, AND PHYSICAL P↗
NASA NTRS1972

System safety engineering analysis handbook

The basic requirements and guidelines for the preparation of System Safety Engineering Analysis are presented. The philosophy of System Safety and the various analytic methods available to the engineering profession are discussed. A text-book description of each of the methods is included.

Ijams, T. E.↗
NASA NTRSDate not supplied

Classification of Notices to Airmen using Natural Language Processing

This paper establishes the feasibility of using Natural Language Processing (NLP) to classify NOTAMs or Notices to Airmen – a pilot messaging framework to gather real-time situational awareness. Present day air mobility operations heavily rely on NOTAMs. However, pilots often have difficulty interpreting NOTAMs due to the sheer volume of inapplicable messages and unclear abbreviations. Using NLP, the presented study analyzes the accuracy of classifying NOTAMs and, thereby, the efficiency of generating actionable interpretations in real time. To this effect, efficacies of four NLP neural network architectures were analyzed, including three Recurrent Neural Networks (RNNs) with GloVe, Word2Vec, and FastText word embeddings, and one trained Bi-Directional Encoder Representations from Transformers (BERT) model. The four neural networks were trained and evaluated on three open-source datasets of varying text lengths, vocabularies, and grammars, taken from e-commerce product descriptions, social media tweets, and unstructured descriptions for data and analytics services on open data marketplaces such as NASA’s Data and Reasoning Fabric (DRF) platform. This provided cross-analysis of each neural network architecture’s performance per text type. The best performing architecture, BERT, was then fine-tuned on a collection of open-source NOTAM data. Post-training, a real-time NOTAM classification service was implemented to draw inference on new NOTAMs using the trained model, which demonstrated close to 99% accuracy in classification. This modular classification service is envisioned to be integrated with a data and analytics delivery platform, such as the DRF, thus availing real-time contextualization of NOTAMs to air mobility clients, humans, and machines for enhanced decision making.

Aiden C. Szeto↗