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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 NTRS2017

Understanding the International Space Station Crew Perspective following Long-Duration Missions through Data Analytics & Visualization of Crew Feedback

The International Space Station (ISS) first became a home and research laboratory for NASA and International Partner crewmembers over 16 years ago. Each ISS mission lasts approximately 6 months and consists of three to six crewmembers. After returning to Earth, most crewmembers participate in an extensive series of 30+ debriefs intended to further understand life onboard ISS and allow crews to reflect on their experiences. Examples of debrief data collected include ISS crew feedback about sleep, dining, payload science, scheduling and time planning, health & safety, and maintenance. The Flight Crew Integration (FCI) Operational Habitability (OpsHab) team, based at Johnson Space Center (JSC), is a small group of Human Factors engineers and one stenographer that has worked collaboratively with the NASA Astronaut office and ISS Program to collect, maintain, disseminate and analyze this data. The database provides an exceptional and unique resource for understanding the "crew perspective" on long duration space missions. Data is formatted and categorized to allow for ease of search, reporting, and ultimately trending, in order to understand lessons learned, recurring issues and efficiencies gained over time. Recently, the FCI OpsHab team began collaborating with the NASA JSC Knowledge Management team to provide analytical analysis and visualization of these over 75,000 crew comments in order to better ascertain the crew's perspective on long duration spaceflight and gain insight on changes over time. In this initial phase of study, a text mining framework was used to cluster similar comments and develop measures of similarity useful for identifying relevant topics affecting crew health or performance, locating similar comments when a particular issue or item of operational interest is identified, and providing search capabilities to identify information pertinent to future spaceflight systems and processes for things like procedure development and training. In addition, the comments were scored for sentiment using a polarity scoring algorithm to identify both positive and negative comments for particular groups and clusters, allowing the team to make analytically informed decisions regarding future hardware and operating procedures. The use of polarity scoring with time series analysis was used to provide insight into how crew health and habitability is changing throughout various spaceflight increments or the station lifecycle as a whole. Finally, a visualization framework was developed to address the needs of the end users to search for and analyze comments by user, category or mission. This paper will discuss how the use of an analytical framework in conjunction with the current human interface, improved the understanding of crew perspective and shortened the time for analysis allowing for more informed decisions and rapid development of improvements. These methods are significantly optimizing the way that this valuable data can be assessed and applied to current and future spaceflight design and development. This collaboration allows the FCI OpsHab team to effectively analyze and share data in a more automated and timely fashion. Trends are no longer derived manually and can be illustrated effectively and accurately with these evolving techniques to an ever growing group of human spaceflight end users.

Bryant, Cody↗
DOE OSTI2013

Large High Resolution Displays for Co-Located Collaborative Sensemaking: Display Usage and Territoriality

Large, high-resolution vertical displays carry the potential to increase the accuracy of collaborative sensemaking, given correctly designed visual analytics tools. From an exploratory user study using a fictional textual intelligence analysis task, we investigated how users interact with the display to construct spatial schemas and externalize information, as well as how they establish shared and private territories. We investigated the space management strategies of users partitioned by type of tool philosophy followed (visualization- or text-centric). We classified the types of territorial behavior exhibited in terms of how the users interacted with information on the display (integrated or independent workspaces). Next, we examined how territorial behavior impacted the common ground between the pairs of users. Finally, we offer design suggestions for building future co-located collaborative visual analytics tools specifically for use on large, high-resolution vertical displays.

co-located collaborative sensemaking↗
DOE OSTI2021

COVID19 Disease Map, a computational knowledge repository of virus–host interaction mechanisms

We need to effectively combine the knowledge from surging literature with complex datasets to propose mechanistic models of SARS-CoV-2 infection, improving data interpretation and predicting key targets of intervention. Here, we describe a large-scale community effort to build an open access, interoperable and computable repository of COVID-19 molecular mechanisms. The COVID-19 Disease Map (C19DMap) is a graphical, interactive representation of disease-relevant molecular mechanisms linking many knowledge sources. Notably, it is a computational resource for graph-based analyses and disease modelling. To this end, we established a framework of tools, platforms and guidelines necessary for a multifaceted community of biocurators, domain experts, bioinformaticians and computational biologists. The diagrams of the C19DMap, curated from the literature, are integrated with relevant interaction and text mining databases. We demonstrate the application of network analysis and modelling approaches by concrete examples to highlight new testable hypotheses. This framework helps to find signatures of SARS-CoV-2 predisposition, treatment response or prioritisation of drug candidates. Such an approach may help deal with new waves of COVID-19 or similar pandemics in the long-term perspective.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

Rotational symmetry protected edge and corner states in Abelian topological phases

Spatial symmetries can enrich the topological classification of interacting quantum matter and endow systems with non-trivial strong topological invariants (protected by internal symmetries) with additional "weak" topological indices. In this paper, we study the edge physics of systems with a non-trivial shift invariant, which is protected by either a continuous $\text{U}(1)_r$ or discrete $\text{C}_n$ rotation symmetry, along with internal $\text{U}(1)_c$ charge conservation. Specifically, we construct an interface between two systems which have the same Chern number but are distinguished by their Wen-Zee shift and, through analytic arguments supported by numerics, show that the interface hosts counter-propagating gapless edge modes which cannot be gapped by arbitrary local symmetry-preserving perturbations. Using the Chern-Simons field theory description of two-dimensional Abelian topological orders, we then prove sufficient conditions for continuous rotation symmetry protected gapless edge states using two complementary approaches. One relies on the algebraic Lagrangian sub-algebra framework for gapped boundaries while the other uses a more physical flux insertion argument. For the case of discrete rotation symmetries, we extend the field theory approach to show the presence of fractional corner charges for Abelian topological orders with gappable edges, and compute them in the case where the Abelian topological order is placed on the two-dimensional surface of a Platonic solid. Finally, our work paves the way for studying the edge physics associated with spatial symmetries in symmetry enriched topological phases.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
NASA NTRS1979

ATLAS, an integrated structural analysis and design system. Volume 3: User's manual, input and execution data

The input data and execution control statements for the ATLAS integrated structural analysis and design system are described. It is operational on the Control Data Corporation (CDC) 6600/CYBER computers in a batch mode or in a time-shared mode via interactive graphic or text terminals. ATLAS is a modular system of computer codes with common executive and data base management components. The system provides an extensive set of general-purpose technical programs with analytical capabilities including stiffness, stress, loads, mass, substructuring, strength design, unsteady aerodynamics, vibration, and flutter analyses. The sequence and mode of execution of selected program modules are controlled via a common user-oriented language.

Dreisbach, R. L.↗
DOE OSTI2013

Knowledge Discovery from Massive Healthcare Claims Data

The role of big data in addressing the needs of the present healthcare system in US and rest of the world has been echoed by government, private, and academic sectors. There has been a growing emphasis to explore the promise of big data analytics in tapping the potential of the massive healthcare data emanating from private and government health insurance providers. While the domain implications of such collaboration are well known, this type of data has been explored to a limited extent in the data mining community. The objective of this paper is two fold: first, we introduce the emerging domain of big"healthcare claims data to the KDD community, and second, we describe the success and challenges that we encountered in analyzing this data using state of art analytics for massive data. Specically, we translate the problem of analyzing healthcare data into some of the most well-known analysis problems in the data mining community, social network analysis, text mining, and temporal analysis and higher order feature construction, and describe how advances within each of these areas can be leveraged to understand the domain of healthcare. Each case study illustrates a unique intersection of data mining and healthcare with a common objective of improving the cost-care ratio by mining for opportunities to improve healthcare operations and reducing hat seems to fall under fraud, waste,and abuse.

healthcare fraud↗
DOE OSTI2023

Automated Construction of a Photocatalysis Dataset for Water-Splitting Applications

We present an automatically generated dataset of 15,755 records that were extracted from 47,357 papers. These records contain water-splitting activity in the presence of certain photocatalysts, along with additional information about the chemical reaction conditions under which this activity was recorded. These conditions include any co-catalysts and additives that were present during water splitting, the length of time for which the photocatalytic experiment was conducted, and the type of light source used, including its wavelength. Despite the text extraction of such a wide range of chemical reaction attributes, the dataset afforded good precision (71.2%) and recall (36.3%). These figures-of-merit were calculated based on a random sample of open-access papers from the corpus. Mining such a complex set of attributes required the development of novel techniques in knowledge extraction and interdependency resolution, leveraging inter- and intra-sentence relations, which are also described in this paper. We present a new version (version 2.2) of the chemistry-aware text-mining toolkit ChemDataExtractor, in which these new techniques are included.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

Influence of mass ablation on ignition and burn propagation in layered fusion capsules

After decades of research, recent laser-driven inertial fusion experiments have demonstrated rapid progress toward achieving thermonuclear ignition using capsule designs with cryogenic fuel layers. The ignition physics for these layered capsules involves a complex interplay between the dynamically forming hot spot and the dense surrounding fuel. Using analytic theory and numerical simulations, we demonstrate that the mass ablation rate into the hot spot depends sensitively upon the temperature of the dense fuel, resulting in ablative inflows up to [Formula: see text] faster than previous estimates. This produces an enthalpy flux into the hot spot that plays a critical role in controlling the hot spot temperature, the ignition threshold, and the subsequent burn propagation. The net influence of mass ablation on the ignition threshold is regulated by a dimensionless parameter that depends upon the temperature of the dense fuel. As a consequence, the ignition threshold is sensitive to any mechanism that heats the dense fuel, such as neutrons or radiation emitted from the hot spot. These predictions are confirmed using radiation-hydrodynamic simulations for a series of capsules near ignition conditions. This analysis may have relevance for understanding the variable performance of recent experiments and for guiding new capsule designs toward higher fusion yields.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2022

Exploring 2 + 2 answers to 3 + 1 questions

We explore potential uses of physics formulated in Kleinian (i.e. 2 + 2) signature spacetimes as a tool for understanding properties of physics in Lorentzian (i.e. 3 + 1) signature. Much as Euclidean (i.e. 4 + 0) signature quantities can be used to formally construct the ground state wavefunction of a Lorentzian signature quantum field theory, a similar analytic continuation to Kleinian signature constructs a state of low particle flux in the direction of analytic continuation. There is also a natural supersymmetry algebra available in 2 + 2 signature, which serves to constrain the structure of correlation functions. Spontaneous breaking of Lorentz symmetry can produce various [Formula: see text] supersymmetry algebras that in 3 + 1 signature correspond to nonsupersymmetric systems. We speculate on the possible role of these structures in addressing the cosmological constant problem.

Physics↗
DOE OSTI2022

Exaflops Biomedical Knowledge Graph Analytics

We are motivated by newly proposed methods for mining large-scale corpora of scholarly publications (e.g., full biomedical literature), which consists of tens of millions of papers spanning decades of research. In this setting, analysts seek to discover relationships among concepts. They construct graph representations from annotated text databases and then formulate the relationship-mining problem as an all-pairs shortest paths (APSP) and validate connective paths against curated biomedical knowledge graphs (e.g., Spoke). In this context, we present Coast (Exascale Communication-Optimized All-Pairs Shortest Path) and demonstrate 1.004 EF/s on 9,200 Frontier nodes (73,600 GCDs). We develop hyperbolic performance models (HYPERMOD), which guide optimizations and parametric tuning. The proposed Coast algorithm achieved the memory constant parallel efficiency of 99% in the single-precision tropical semiring. Looking forward, Coast will enable the integration of scholarly corpora like PubMed into the Spoke biomedical knowledge graph.

Kannan, Ramakrishnan {ramki}↗
DOE OSTI2016

Vibronic coupling in the excited-states of carotenoids

The ultrafast femtochemistry of carotenoids is governed by the interaction between electronic excited states, which has been explained by the relaxation dynamics within a few hundred femtoseconds from the lowest optically allowed excited state S 2 to the optically dark state S 1 . Extending this picture, some additional dark states (3A$^–_\text{g}$ and 1B$^–_\text{u}$) and their interaction with the S 2 state have also been suggested to play a major role in the ultrafast deactivation of carotenoids and their properties. In this work, we investigate the interaction between such dark and bright electronic excited states of open chain carotenoids, particularly its dependence on the number of conjugated double bonds (N). We focus on the ultrafast wave packet motion on the excited potential surface, which is modified by the interaction between bright and dark electronic states. Such a coupling between electronic states leads to a shift of the vibrational frequency during the excited-state evolution. In this regard, pump-degenerate four-wave mixing (pump-DFWM) is applied to a series of carotenoids with different numbers of conjugated double bonds N = 9, 10, 11 and 13 (neurosporene, spheroidene, lycopene and spirilloxanthin, respectively). Moreover, we demonstrate in a closed-chain carotenoid (lutein) that the coupling strength and therefore the vibrational shift can be tailored by changing the energy degeneracy between the 1B$^+_\text{u}$ and 1B$^–_\text{u}$ states via solvent interaction.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2017

Applying Graph Analytics to Understand Compute Core Usage and Publication Trends in a Petascale Supercomputing Facility

The Oak Ridge Leadership Computing Facility (OLCF) runs Titan, the No. 4 supercomputer in the world, to deliver over four billion compute core hours every year to several scientific domains, in their pursuit of leadership science. In this paper, we analyze four years worth of heterogeneous log data sources from the OLCF resource fabric, capturing metadata on entities such as users (2,546), scientific project allocations (674), jobs (1,352,402) and publications (1,146), to derive insights into the trends in core hour usage and publications, across 35 science domains. We have constructed a scalable graph to represent the OLCF entities and apply rich graph analytics for our analysis. Based on this, we have analyzed the metadata across five dimensions, namely (1) quantitative analysis of Titan system usage, (2) quantitative analysis of OLCF publications, (3) correlation analysis between system usage and publications, (4) text analysis to derive OLCF research trends, and (5) utilization of graph mining for association analysis. To the best of our knowledge, our work is the first of its kind to apply graph- based big data techniques to provide comprehensive insights on an HPC center's core hour usage and users' publication trends. Our results provide valuable details into an HPC center's core allocation program, measuring the productivity of scientific domains, the interplay between core usage and research output, accelerating collaboration, and in predicting new connections between resource entities.

Lee, Sangkeun (Matt)↗
DOE OSTI2026

Charged loops at the cosmological collider with chemical potential

Cosmological collider physics allows the detection of heavy particles at inflationary scales through their imprints on primordial non-Gaussianities. We study the chemical potential mechanism applied to a pair of charged scalars. We analytically evaluate the resulting one-loop contribution to the bispectrum, using the spectral decomposition. In this way we are able to determine the parametric dependencies for both the signal and the background. We show that a signal strength ${f}_{\text{NL}}\sim \mathcal{O}(0.01)$ can be obtained within theoretical control, potentially reachable by 21 cm tomography. As an application we consider the colored Higgs bosons in SU(5) supersymmetric orbifold grand unification with masses M ≲ 10$^{15}$ GeV.

Bodas, Arushi [Chicago U., EFI; Fermilab] (ORCID:0↗
DOE OSTI2016

Stability of exact solutions of the nonlinear Schrödinger equation in an external potential having supersymmetry and parity-time symmetry

We discuss the stability properties of the solutions of the general nonlinear Schrödinger equation (NLSE) in 1+1 dimensions in an external potential derivable from a parity-time (${ \mathcal P }{ \mathcal T }$) symmetric superpotential $W(x)$ that we considered earlier, Kevrekidis et al (2015 Phys. Rev. E 92 042901). In particular we consider the nonlinear partial differential equation $\{{\rm{i}}\,{\partial }_{t}+{\partial }_{x}^{2}-{V}^{-}(x)+| \psi (x,t){| }^{2\kappa }\}\,\psi (x,t)=0,$ for arbitrary nonlinearity parameter κ. We study the bound state solutions when ${V}^{-}(x)\,=(1/4-{b}^{2}){\text{sech}}^{2}(x)$, which can be derived from two different superpotentials $W(x)$, one of which is complex and ${ \mathcal P }{ \mathcal T }$ symmetric. Using Derrick's theorem, as well as a time dependent variational approximation, we derive exact analytic results for the domain of stability of the trapped solution as a function of the depth b 2 of the external potential. We compare the regime of stability found from these analytic approaches with a numerical linear stability analysis using a variant of the Vakhitov–Kolokolov (V–K) stability criterion. The numerical results of applying the V–K condition give the same answer for the domain of stability as the analytic result obtained from applying Derrick's theorem. Our main result is that for $\kappa \gt 2$ a new regime of stability for the exact solutions appears as long as $b\gt {b}_{{\rm{crit}}}$, where ${b}_{{\rm{crit}}}$ is a function of the nonlinearity parameter κ. In the absence of the potential the related solitary wave solutions of the NLSE are unstable for $\kappa \gt 2$.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2017

Truth of Varying Shades: Analyzing Language in Fake News and Political Fact-Checking

We present an analytic study on the language of news media in the context of political fact-checking and fake news detection. We compare the language of real news with that of satire, hoax, and propaganda to find linguistic cues for untruthful text. To probe the feasibility of automatic political fact-checking, we present a case study based on PolitiFact.com using their factuality judgments on a 6-point scale. Experimental results show that while media fact-checking remains to be an open research question, stylistic cues can help determine the truthfulness of text.

fact-checking↗
DOE OSTI2020

Scalable Knowledge Graph Analytics at 136 Petaflop/s

We are motivated by newly proposed methods for data mining large-scale corpora of scholarly publications, such as the full biomedical literature, which may consist of tens of millions of papers spanning decades of research. In this setting, analysts seek to discover how concepts relate to one another. They construct graph representations from annotated text databases and then formulate the relationship-mining problem as one of computing all-pairs shortest paths (APSP), which becomes a significant bottleneck. In this context, we present a new high-performance algorithm and implementation of the Floyd-Warshall algorithm for distributed-memory parallel computers accelerated by GPUs, which we call DSNAPSHOT (Distributed Accelerated Semiring All-Pairs Shortest Path). For our largest experiments, we ran DSNAPSHOT on a connected input graph with millions of vertices using 4, 096nodes (24,576GPUs) of the Oak Ridge National Laboratory's Summit supercomputer system. We find DSNAPSHOT achieves a sustained performance of 136×1015 floating-point operations per second (136petaflop/s) at a parallel efficiency of 90% under weak scaling and, in absolute speed, 70% of the best possible performance given our computation (in the single-precision tropical semiring or “min-plus” algebra). Looking forward, we believe this novel capability will enable the mining of scholarly knowledge corpora when embedded and integrated into artificial intelligence-driven natural language processing workflows at scale.

Kannan, Ramakrishnan {ramki}↗
DOE OSTI2022

Natural Language Processing-Enhanced Nuclear Industry Operating Experience Data Analysis to Support Risk Model Parameter Estimations

This set of slides has been prepared for a talk at the INL AI/ML Symposium held on September 8, 2022. Presentation outline: Background - Nuclear power plant operating experience data sources • Research focus and motivation - Analyzing free-text operating experience data: present and future • Research method - Input - Methodological steps - Output • Conclusions and next steps

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2025

Neural network-based model of galaxy power spectrum: fast full-shape galaxy power spectrum analysis

ABSTRACT We present a neural network-based emulator for the galaxy redshift-space power spectrum that enables several orders of magnitude acceleration in the galaxy clustering parameter inference, while preserving 3$\sigma$ accuracy better than 0.5 per cent up to $k_{\mathrm{max}}$ = 0.25 $\, h\text{Mpc}^{-1}$ within Lambda-cold dark matter ($\Lambda$CDM) and around 0.5 per cent $w_0$–$w_a$CDM. Our surrogate model only emulates the galaxy bias-invariant terms of one-loop perturbation theory predictions, these terms are then combined analytically with galaxy bias terms, counter-terms, and stochastic terms in order to obtain the non-linear redshift-space galaxy power spectrum. This allows us to avoid any galaxy bias prescription in the training of the emulator, which makes it more flexible. Moreover, we include the redshift $z \in [0,1.4]$ in the training which further avoids the need for re-training the emulator. We showcase the performance of the emulator in recovering the cosmological parameters of $\Lambda$CDM by analysing the suite of 25 AbacusSummit simulations that mimic the Dark Energy Spectroscopic Instrument luminous red galaxies at $z=0.5$ and 0.8, together as the emission line galaxies at $z=0.8$. We obtain similar performance in all cases, demonstrating the reliability of the emulator for any galaxy sample at any redshift in $0 \lt z \lt 1.4$. We will make our emulator public at github repository.

Trusov, Svyatoslav (ORCID:0000000224146720)↗