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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 NTRS2000

Computational Nanotechnology of Materials, Devices, and Machines: Carbon Nanotubes

The mechanics and chemistry of carbon nanotubes have relevance for their numerous electronic applications. Mechanical deformations such as bending and twisting affect the nanotube's conductive properties, and at the same time they possess high strength and elasticity. Two principal techniques were utilized including the analysis of large scale classical molecular dynamics on a shared memory architecture machine and a quantum molecular dynamics methodology. In carbon based electronics, nanotubes are used as molecular wires with topological defects which are mediated through various means. Nanotubes can be connected to form junctions.

Srivastava, Deepak↗
NASA NTRS1993

Infrared Cirrus and Discrete Sources in the Outer Galaxy

Studies of Galactic infrared cirrus have been based on observations of individual high latitude clouds, analysis of large scale emission at high latitudes in the Solar Neighborhood and complete linear decomposition of the global emission from IRAS and other observations over the entire Galaxy.

IRAS infrared cirrus linear decomposition Point So↗
NASA NTRS2009

Cloud Imagers Offer New Details on Earth's Health

A stunning red sunset or purple sunrise is an aesthetic treat with a scientific explanation: The colors are a direct result of the absorption or reflectance of solar radiation by atmospheric aerosols, minute particles (either solid or liquid) in the Earth s atmosphere that occur both naturally and because of human activity. At the beginning or end of the day, the Sun s rays travel farther through the atmosphere to reach an observer s eyes and more green and yellow light is scattered, making the Sun appear red. Sunset and sunrise are especially colorful when the concentration of atmospheric particles is high. This ability of aerosols to absorb and reflect sunlight is not just pretty; it also determines the amount of radiation and heat that reaches the Earth s surface, and can profoundly affect climate. In the atmosphere, aerosols are also important as nuclei for the condensation of water droplets and ice crystals. Clouds with fewer aerosols cannot form as many water droplets (called cloud particles), and consequently, do not scatter light well. In this case, more sunlight reaches the Earth s surface. When aerosol levels in clouds are high, however, more nucleation points can form small liquid water droplets. These smaller cloud particles can reflect up to 90 percent of visible radiation to space, keeping the heat from ever reaching Earth s surface. The tendency for these particles to absorb or reflect the Sun s energy - called extinction by astronomers - depends on a number of factors, including chemical composition and the humidity and temperature in the surrounding air; because cloud particles are so small, they are affected quickly by minute changes in the atmosphere. Because of this sensitivity, atmospheric scientists study cloud particles to anticipate patterns and shifts in climate. Until recently, NASA s study of atmospheric aerosols and cloud particles has been focused primarily on satellite images, which, while granting large-scale atmospheric analysis, limited scientists ability to acquire detailed information about individual particles. Now, experiments with specialized equipment can be flown on standard jets, making it possible for researchers to monitor and more accurately anticipate changes in Earth s atmosphere and weather patterns.

Source record↗
NASA NTRS2017

Mapping the Iron Oxidation State in Martian Meteorites

Several types of Martian igneous meteorites have been identified: clinopyroxenites (nakhlites), basaltic shergottites, peridotitic shergottites, dunites (chassignites) and orthopyroxenites [1,2]. In order to constrain the heterogeneity of the Martian mantle and crust, and their evolution through time, numerous studies have been performed on the iron oxidation state of these meteorites [3,4,5,6,7,8,9]. The calculated fO2 values all lie within the FMQ-5 to FMQ+0.5 range (FMQ representing the Fayalite = Magnetite + Quartz buffer); however, discrepancies appear between the various studies, which are either attributed to the choice of the minerals/melts used, or to the precision of the analytical/calculation method. The redox record in volcanic samples is primarily related to the oxidation state in the mantle source(s). However, it is also influenced by several deep processes: melting, crystallization, magma mixing [10], assimilation and degassing [11]. In addition, the oxidation state in Martian meteorites is potentially affected by several surface processes: assimilation of sediment/ crust during lava flowing at Mars' surface, low temperature micro-crystallization [10], weathering at the surface of Mars and low temperature reequilibration, impact processes (i.e. high pressure phase transitions, mechanical mixing, shock degassing and melting), space weathering, and weathering on Earth (at atmospheric conditions different from Mars). Decoding the redox record of Martian meteorites, therefore, requires large-scale quantitative analysis methods, as well as a perfect understanding of oxidation processes.

Martin, A. M.↗
NASA NTRS2017

Three-Dimensional High Fidelity Progressive Failure Damage Modeling of NCF Composites

Performance prediction of off-axis laminates is of significant interest in designing composite structures for energy absorption. Phenomenological models available in most of the commercial programs, where the fiber and resin properties are smeared, are very efficient for large scale structural analysis, but lack the ability to model the complex nonlinear behavior of the resin and fail to capture the complex load transfer mechanisms between the fiber and the resin matrix. On the other hand, high fidelity mesoscale models, where the fiber tows and matrix regions are explicitly modeled, have the ability to account for the complex behavior in each of the constituents of the composite. However, creating a finite element model of a larger scale composite component could be very time consuming and computationally very expensive. In the present study, a three-dimensional mesoscale model of non-crimp composite laminates was developed for various laminate schemes. The resin material was modeled as an elastic-plastic material with nonlinear hardening. The fiber tows were modeled with an orthotropic material model with brittle failure. In parallel, new stress based failure criteria combined with several damage evolution laws for matrix stresses were proposed for a phenomenological model. The results from both the mesoscale and phenomenological models were compared with the experiments for a variety of off-axis laminates.

Aitharaju, Venkat↗
DOE OSTI2020

TriC: Distributed-memory Triangle Counting by Exploiting the Graph Structure

Graph analytics has emerged as an important tool in the analysis of large scale data from diverse application domains such as social networks, cyber security and bioinformatics. Counting the number of triangles in a graph is a fundamental kernel with several applications such as detecting the community structure of a graph or in identifying important vertices in a graph. The ubiquity of massive datasets is driving the need to scale graph analytics on parallel systems. However, numerous challenges exist in efficiently parallelizing graph algorithms, especially on distributed-memory systems. Irregular memory accesses and communication patterns, low computation to communication ratios, and the need for frequent synchronization are some of the leading challenges. In this paper, we present TriC, our distributed-memory implementation of triangle counting in graphs using the Message Passing Interface (MPI), as a submission to the 2020 GraphChallenge competition. Using a set of synthetic and real-world inputs from the challenge, we demonstrate a speedup of up to 90x relative to previous work on 32 processor-cores of a NERSC Cori node. We also provide details from distributed runs with up to8192 processes along with strong scaling results. The observations presented in this work provide an understanding of the system-level bottlenecks at scale that specifically impact sparse-irregular workloads and will therefore benefit other efforts to parallelize graph algorithms.

Halappanavar, Mahantesh↗
DOE OSTI2022

Precision QCD, Hadronic Structure & Forward QCD, Heavy Ions: Report of Energy Frontier Topical Groups 5, 6, 7 submitted to Snowmass 2021

This report was prepared on behalf of three Energy Frontier Topical Groups of the Snowmass 2021 Community Planning Exercise. It summarizes the status and implications of studies of strong interactions in high-energy experiments and QCD theory. We emphasize the rich landscape and broad impact of these studies in the decade ahead. Hadronic interactions play a central role in the high-luminosity Large Hadron Collider (LHC) physics program, and strong synergies exist between the (HL-)LHC and planned or proposed experiments at the U.S. Electron-Ion Collider, CERN forward physics experiments, high-intensity facilities, and future TeV-range lepton and hadron colliders. Prospects for precision determinations of the strong coupling and a variety of nonperturbative distribution and fragmentation functions are examined. We also review the potential of envisioned tests of new dynamical regimes of QCD in high-energy and high-density scattering processes with nucleon, ion, and photon initial states. The important role of the high-energy heavy-ion program in studies of nuclear structure and the nuclear medium, and its connections with QCD involving nucleons are summarized. We address ongoing and future theoretical advancements in multi-loop QCD computations, lattice QCD, jet substructure, and event generators. Cross-cutting connections between experimental measurements, theoretical predictions, large-scale data analysis, and high-performance computing are emphasized.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2023

Consideration of Non-Ideal Detonation Regimes Influenced by Wave Modes in a Water-Cooled Rotating Detonation Engine Using OH Chemiluminescence

Within this study, the presence and proportion of ideal and non-ideal combustion regimes is compared across a variety of process conditions and wave modes. Large-scale data analysis seeks to summarize proportional heat release associated with commensal, parasitic, and detonative combustion averaged across individual traces of OH* chemiluminescent data acquired at the detonation plane. Means of regime partitioning based on the anatomy of the time-resolved OH* signal are proposed to ensure consistent analysis throughout the current and future studies concerning combustion regimes.

Johnson, Kristyn↗
DOE OSTI2026

Dark Energy Survey Year 6 Results: Cosmological Constraints from Galaxy Clustering and Weak Lensing

We present cosmology results combining galaxy clustering and weak gravitational lensing measured in the full six years (Y6) of observations by the Dark Energy Survey (DES) covering $\sim$5000 deg$^2$. We perform a large-scale structure analysis using three two-point correlation functions (3$\times$2pt): (i) cosmic shear from 140 million source galaxy shapes, (ii) galaxy clustering of 9 million lens galaxy positions, and (iii) galaxy-galaxy lensing from their cross-correlation. We model the data in flat $Λ$CDM and $w$CDM cosmologies. The combined analysis yields $S_8\equiv σ_8 (Ω_{\rm m}/0.3)^{0.5} = 0.789^{+0.012}_{-0.012}$ and matter density $Ω_{\rm m} = 0.333^{+0.023}_{-0.028}$ in $Λ$CDM (68% CL), where $σ_8$ is the clustering amplitude. These constraints show a (full-space) parameter difference of 1.8$σ$ from a combination of cosmic microwave background (CMB) primary anisotropy datasets from Planck 2018, ACT-DR6, and SPT-3G DR1. Projected only into $S_8$ the difference is $2.6σ$. In $w$CDM the Y6 3$\times$2pt results yield $S_8 = 0.782^{+0.021}_{-0.020}$, $Ω_{\rm m} = 0.325^{+0.032}_{-0.035}$, and dark energy equation-of-state parameter $w = -1.12^{+0.26}_{-0.20}$. For the first time, we combine all DES dark-energy probes: 3$\times$2pt, SNe Ia, BAO and Clusters. In $Λ$CDM this combination yields a $2.8σ$ parameter difference from the CMB. When combining DES 3$\times$2pt with other low-redshift datasets (DESI DR2 BAO, DES SNe Ia, SPT clusters), we find a 2.3$σ$ parameter difference with CMB. A joint fit of Y6 3$\times$2pt, CMB, and those low-redshift datasets produces the tightest $Λ$CDM constraints to date: $S_8 = 0.806^{+0.006}_{-0.007}$, $Ω_{\rm m} = 0.302^{+0.003}_{-0.003}$, $h = 0.683^{+0.003}_{-0.002}$, and $\sum m_ν< 0.14$ eV (95% CL). In $w$CDM, this combination yields $w = -0.981^{+0.021}_{-0.022}$.

Abbott, T. M.C. [Cerro-Tololo InterAmerican Obs.]↗
DOE OSTI2026

Measurement-informed Dynamic Aggregation of Distribution Systems

This paper proposes a measurement-informed dynamic aggregation methodology in order to create equivalent representations of distribution systems that are compatible with large-scale transmission analysis. By optimizing an equivalent feeder parameters using time-series measurements of active power, reactive power, and voltage at the Point of Interconnection (POI), the approach yields simplified yet dynamically accurate equivalents. Implemented in PSCAD with models of photovoltaic–battery systems, three-phase motors, and static loads, the method employs hybrid differential evolution and bounded least-squares optimization laying the foundation for for real-time state estimation and optimized sensor placement in distribution networks.

Ahmed, Kazi Ishrak [University of Tennessee, Knoxv↗
DOE OSTI2025

ARCH: Large-scale knowledge graph via aggregated narrative codified health records analysis

Objective: Electronic health record (EHR) systems contain a wealth of clinical data stored as both codified data and free-text narrative notes (NLP). The complexity of EHR presents challenges in feature representation, information extraction, and uncertainty quantification. Here, to address these challenges, we proposed an efficient Aggregated naRrative Codified Health (ARCH) records analysis to generate a large-scale knowledge graph (KG) for a comprehensive set of EHR codified and narrative features. Methods: Using data from 12.5 million Veterans Affairs patients, ARCH first derives embedding vectors and generates similarities along with associated p-values to measure the strength of relatedness between clinical features with statistical certainty quantification. Next, ARCH performs a sparse embedding regression to remove indirect linkage between features to build a sparse KG. Finally, ARCH was validated on various clinical tasks, including detecting known relationships between entity pairs, predicting drug side effects, disease phenotyping, as well as sub-typing Alzheimer’s disease patients. Results: ARCH produces high-quality clinical embeddings and KG for over 60,000 codified and narrative EHR concepts. The KG and embeddings are visualized in the R-shiny powered web-API.3 ARCH achieved high accuracy in detecting EHR concept relationships, with AUCs of 0.926 (codified) and 0.861 (NLP) for similar EHR concepts, and 0.810 (codified) and 0.843 (NLP) for related pairs. It detected drug side effects with a 0.723 AUC, which improved to 0.826 after fine-tuning. Using both codified and NLP features, the detection power increased significantly. Compared to other methods, ARCH has superior accuracy and enhances weakly supervised phenotyping algorithms’ performance. Notably, it successfully categorized Alzheimer’s patients into two subgroups with varying mortality rates. Conclusion: The proposed ARCH algorithm generates large-scale high-quality semantic representations and knowledge graph for both codified and NLP EHR features, useful for a wide range of predictive modeling tasks.

Electronic health records↗
DOE OSTI2026

Scalable Computation of Topological Abstractions for Scalar Data

Topological data analysis has become an important tool for large scale scalar data analysis and visualization, efficiently extracting the inherent structure and features of interest of the data. However, with growing dataset sizes and complexity, it is increasingly becoming infeasible to compute topological abstractions of interest in serial and on single machines. This paper presents the state of the art in the scalable computation of topological abstractions on scalar data, in shared memory parallel on single machines, and in distributed memory parallel on multiple machines. We highlight results for set‐based, graph‐based and complex‐based abstractions and organize the state of the art based on this taxonomy. The paper identifies parallelization and distribution techniques common in topological algorithms and highlights further areas of interest with underdeveloped efforts.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS1994

Termination shock response to large-scale solar wind fluctuations

The analysis of data recorded by the Voyager 2 spacecraft indicates the presence of large-scale fluctuations in the solar wind ram pressure on the time scale of tens of days. The amplitude of the fluctuations is highly variable but often lies within a factor of 5 to 10 change from an average or mean value of the ram pressure. Since the spacecraft has presumably not encountered the termination shock yet, these fluctuations should eventually interact with the shock and thereby play a role in determining the shock location. Numerical solutions of the time-dependent gasdynamic equations are used to simulate the response of the termination shock to fluctuations in the solar wind ram pressure comparable to those observed. The primary result of this study is that the maximum shock excursion due to the fluctuations is of the order of 1 AU, which is much smaller than that predicted by other studies. Additional simulations show that the limited movement is due to the fact that the time scale for the termination shock response is substantially larger than the time scale of the fluctuations. It is also shown that the heliopause acts as a barrier for the fluctuations and confines them to the heliosphere.

Steinolfson, R. S.↗
NASA NTRS1994

Termination shock response to large-scale solar wind fluctuations

The analysis of data recorded by the Voyager 2 spacecraft indicates the presence of large-scale fluctuations in the solar wind ram pressure on the time scale of tens of days. The amplitude of the fluctuations is highly variable but often lies within a factor of 5 to 10 change from an average or mean value of the ram pressure. Since the spacecraft has presumably not encountered the termination shock yet, these fluctuations should eventually interact with the shock and thereby play a role in determining the shock location. Numerical solutions of the time-dependent gas dynamic equations are used to simulate the response of the termination shock to fluctuations in the solar wind ram pressure comparable to those observed. The primary result of this study is that the maximum shock excursion due to the fluctuations is of the order of 1 AU, which is much smaller than that predicted by other studies. Additional simulations show that the limited movement is due to the fact that the time scale for the termination shock response is substantially larger than the time scale of the fluctuations. It is also shown that the heliopause acts as a barrier for the fluctuations and confines them to the heliosphere.

Steinolfson, R. S.↗
NASA NTRS1985

Large-scale spectral structure with a gap in the stably stratified atmosphere

The analysis of the large-scale structure of turbulence in a stratified atmosphere is important for the prediction and modelling of turbulence. The Monin-Obukhov similarity consideration is well suited for the modelling of small-scale turbulence. But the large-scale turbulence possesses new features and parameters, as connected with the appearance of a spectral gap in the stably stratified atmosphere, for the understanding of which an analytical investigation is needed. By a group-kinetic method, the anisotropic form of the transfer function and its governing eddy viscosity are derived. On this basis, the spectral laws k to the -5/3rd, k to the -1st, k to the -3rd are obtained for the subranges of inertia, shear, and buoyancy, respectively. A gap connects the last two subranges by the variable anisotropy, as a result of the fall of the spectrum of the vertical velocity fluctuations. The variable anisotropy causes the deviations from the spectral laws k to the -1st and k to the -3rd. An experiment supports the analytical prediction.

Larsen, S. E.↗
NASA NTRS2005

A Priori Analysis of Subgrid-Scale Models for Large Eddy Simulations of Supercritical Binary-Species Mixing Layers

Models for large eddy simulation (LES) are assessed on a database obtained from direct numerical simulations (DNS) of supercritical binary-species temporal mixing layers. The analysis is performed at the DNS transitional states for heptane/nitrogen, oxygen/hydrogen and oxygen/helium mixing layers. The incorporation of simplifying assumptions that are validated on the DNS database leads to a set of LES equations that requires only models for the subgrid scale (SGS) fluxes, which arise from filtering the convective terms in the DNS equations. Constant-coefficient versions of three different models for the SGS fluxes are assessed and calibrated. The Smagorinsky SGS-flux model shows poor correlations with the SGS fluxes, while the Gradient and Similarity models have high correlations, as well as good quantitative agreement with the SGS fluxes when the calibrated coefficients are used.

turbulence↗
DOE OSTI2020

Description of the Three-Dimensional Large-Scale Forcing Data from the 3D Constrained Variational Analysis (VARANAL3D)

This technical report introduces a Three-Dimensional Constrained Variational Analysis (3DCVA) (Tang and Zhang 2015) and its product of three-dimensional large-scale forcing data to drive single-column models (SCM), cloud-resolving models (CRM), and large-eddy simulation (LES) models, and to evaluate model results. The 3DCVA algorithm is an extension of the original 1D constrained variational analysis (1DCVA) (Zhang and Lin 1997, Zhang et al. 2001). The three-dimensional structure of the forcing data allows studies of spatial variation of the large-scale forcing fields and tests of physical parameterizations across scales. In the U.S. Department of Energy Atmospheric Radiation Measurement (ARM) user facility, the 3D forcing data are assigned the datastream name varanal3d. In this technical report, 3DCVA will be used to refer to the algorithm, while VARANAL3D will be used to refer to the data product.

54 ENVIRONMENTAL SCIENCES↗