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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 775 records · Page 43
All sourcesNASA NTRSDOE OSTI
NASA NTRS1992

Internal Shock Interactions in Propulsion/Airframe Integrated Three-Dimensional Sidewall Compression Scramjet Inlets

The advantages and design requirements of propulsion/airframe integration for high Mach number flight have led to extensive study of the three-dimensional sidewall compression scramjet inlet in recent years. Recent research publications have indicated testing over a broad range of Mach number (2 to 18) in a variety of test gases, such as air, helium, and tetrafluoromethane. Multiple experimental techniques have been employed to obtain detailed internal shock interaction data, performance data, and inlet starting limits. Computational fluid dynamics has been effectively used for preliminary parametric studies as well as in parallel with experiments to aid in the explanation of unusual or unexpected flow phenomena. Inlets of this genre afford a relatively simple, generic geometry while producing a highly complex, three-dimensional flow field dominated by shock/shock and shock/boundary layer interactions. While the importance of the viscous effects in high speed inlet interactions is recognized, the present work addresses in a parametric fashion the inviscid effects of leading edge sweep, sidewall compression, and inflow Mach number on the internal shock structure in terms of inlet compression and mass capture. In the process, the source of the of the Mach number invariance with leading edge sweep for a constant sidewall compression class of inlet is identified, and a previously undocumented spillage phenomenon in a constant effective wedge angle class of inlets is discussed.

Holland, Scott D.↗
NASA NTRSDate not supplied

High Performance Access to Archival Data Stored in HDF4 and HDF5 on Cloud Object Stores Without Reformatting the Files

Cloud computing offers numerous advantages for users of extensive Earth science data collections. These benefits encompass direct online access to data files and granules from any location, scalable access supporting parallel computing workflows, and flexible computing tools enabling innovative experimentation with processing techniques. However, older archival file formats designed for distinct computing systems hinder efficient access to decade-long time-series data when compared to data stored in modern cloud-optimized formats like Web Object Stores (WOS), exemplified by Amazon Web Services’ Simple Storage Service (S3). We describe DMR++ (Dataset Metadata Response plus plus), a technology facilitating efficient access to HDF5 (Hierarchical Data Format, version 5) and HDF4 files stored on WOS systems without requiring data reformatting. DMR++ achieves performance comparable to technologies like Zarr while preserving the original file structure, a substantial benefit considering the vast quantity of archival files held by organizations such as NASA. Moreover, DMR++ typically outperforms cloud-optimized versions of HDF5. Essentially an XML (Extensible Markup Language) document usually stored alongside the described data, DMR++ can also be generated on-the-fly but is generally created during data staging to the WOS. Archival files that use HDF4/5 often store large arrays of numerical data. The data in these files is often compressed, typically reducing their size by a factor of four or more. To achieve efficient access to portions of those arrays, they are 'chunked' into smaller sub-arrays, each individually compressed. The chunk size is a compromise, where spinning disks can efficiently access data in smaller chunks while S3 favors larger chunks. A simple optimization of aggregating smaller chunks that are stored adjacently, transferring them in a single access and then individually decompressing them will improve performance. NASA data pose an additional challenge: special Application Programmer Interface (API) libraries are often needed to compute some variables. These libraries are incompatible with WOS environments. Our solution involves storing computed values in the DMR++ document or a companion file, making them accessible like other variables and eliminating the need for specialized APIs. We outline specific optimizations for both satellite grid and swath data stored in HDF4-EOS2 (Earth Observing System).

James Gallagher↗
NASA NTRS1984

Structure and Growth of the Marine Boundary Layer

LANDSAT visible imagery and a one-dimensional Lagrangian boundary layer model were used to hypothesize the nature and the development of the marine boundary layer during a winter episode of strong seaward cold air advection. Over-water heating and moistening of the cold, dry continental air is estimable from linear relations involving horizontal gradients of the near-surface air temperature and humidity. A line of enhanced convection paralleling the Atlantic U.S. coast from south of New York Bay to the vicinity of Virginia Beach, VA was attributed to stronger convergence at low levels. This feature was characterized as a mesoscale front. With the assistance of a three-dimensional mesoscale boundary layer model, initialized with data obtained from the MASEX, the marine boundary layer can be mapped over the entire Atlantic coastal domain and the evolution of the boundary layer can be studied as a function of different characteristics of important surface level forcings. The effects on boundary layer growth due to the magnitude and pattern of sea surface temperature, to the shape of the coastline, and to atmospheric conditions, such as the orientation of the prevailing wind are examined.

Mccumber, M.↗
NASA NTRS2007

Evaluation of a Highly Anticlastic Panel with Tow Overlaps

A rectangular, variable-stiffness panel with tow overlaps was manufactured using an advanced tow placement machine. The cured panel had large anticlastic imperfections, with measured amplitudes of over two times the average panel thickness. These imperfections were not due to the overall steered-fiber layup or the tow overlaps, but instead resulted from local asymmetries in the laminate that were caused by a manufacturing oversight. In the nominal panel layup, fiber angles vary linearly from 60 degrees on the panel axial centerline to 30 degrees on the parallel edges. A geometrically nonlinear analysis was performed with a -280 degree Fahrenheit thermal load to simulate the postcure cooldown to room temperature. The predicted geometric imperfections correlated well with the measured panel shape. Unique structural test fixtures were then developed which greatly reduced these imperfections, but they also caused prestresses in the panel. Surface imperfections measured after the panel was installed in the test fixtures were used with nonlinear finite element analyses to predict these fixturing-induced prestresses. These prestresses were also included in structural analyses of panel end compression to failure, and the analytical results compared well with test data when both geometric and material nonlinearities were included.

Wu, K. Chauncey↗
DOE OSTI2025

Altermagnetic behavior in OsO 2 : Parallels with RuO 2

We investigate and compare the electronic structure of OsO 2 with the extensively studied RuO 2 . Calculations show that OsO 2 exhibits antiferromagnetism and spin splitting driven by crystal symmetry, a characteristic of altermagnetism and similar to RuO 2 . Examination of the Fermi surface, with and without spin-orbit coupling, reveals that OsO 2 has lower Fermi group velocities compared to RuO 2 , suggesting limited charge carrier mobility in OsO 2 . While this characteristic may constrain its performance in high-speed electronic transport applications, it may also enhance stability for spin-based information storage in spintronics. Additionally, comparison of the vibrational properties of these rutile oxide systems demonstrates dynamical stability, typical mass dependent behaviors, and favorable agreement with measured Raman data. The calculated phonon density of states for RuO 2 also agrees with our neutron scattering data. These observations substantiate the implications of the electronic and vibrational behaviors in OsO 2 and RuO 2 , encouraging further investigation of their potential for emerging technological applications.

36 MATERIALS SCIENCE↗
NASA NTRS1980

Modification in drag of turbulent boundary layers resulting from manipulation of large-scale structures

The effects of placing a parallel-plate turbulence manipulator in a boundary layer are investigated by means of flow visualization and hot-wire measurements. The manipulator was found to be effective in inhibiting the intermittent large scale structure of the boundary layer, and the effect persists for at least 70 boundary-layer thicknesses downstream of the manipulator. With the removal of the large scale, there was an observed reduction in the streamwise turbulence intensity levels near the wall. The downstream distribution of the skin friction coefficient, determined from the stream wise change in fluid momentum, was also altered by the introduction of the manipulator. The data from both the visualization and hot wire studies are provided.

Corke, T. C.↗
DOE OSTI2017

Glass-like energy and property landscape of Pt nanoclusters

Pt nanoclusters play an important role in catalysis-related applications. Essential to their activities are their geometries and energy landscapes. In this work, we studied the energy landscapes of Pt clusters using a parallel differential evolution optimization algorithm and an accelerated ab initio atomic relaxation method, which allowed us to explore unprecedentedly large numbers of geometry local minima at ab initio level. We found many lower-energy isomers with low symmetry in their geometry. The energy landscapes were demonstrated to be glass-like with a large number of local minimum structures close to the global minimum. The electronic and magnetic properties of most glass-like local minima were dramatically different from the global minimum, and they should be observed in the experimental measurements. The connections between these local minima were further analyzed using data mining techniques.

Chen, Zhanghui↗
NASA NTRS1994

Contributions of cretaceus quiet zone natural remanent magnetization to Magsat anomalies in the Southwest Indian Ocean

The Magsat magnetic anomalies over the Southwest Indian Ocean are modeled using a combination of induced plus viscous remanent magnetization (IM/VRM) and natural remanent magnetization (NRM). Two broad, roughly parallel, SW to NE trending triple-peaked positive anomalies dominate the region, one lying south of Africa and the other north of Antarctica. Although these anomaly peaks generally correspond with the Agulhas Plateau/Maud Rise, Mozambique Plateau/Astrid Ridge, and Madagascar Ridge/Conrad Rise conjugate pairs, the IM/VRM contribution from structural characteristics (i.e., crustal thickness) accounts for only about 20% of the anomaly amplitudes. A spatially variable but observationally constrained NRM contribution in Cretaceous Quiet Zone (KQZ) crust is required to account for the location, shape, and amplitude contrast of these anomalies. Many crustal features in the Southwest Indian Ocean near Antarctica have little geophysical data to constrain their structure but do hagve tectonic conjugates near Africa for which much more geophysical data are generally available. Using geophysical and geological constraints from one member to model the magnetization structure of its conjugate reproduces the observed Magsat reduced-to-pole anomalies over both structures very well. This suggests that no significant alteration in their magnetization structure has occurred since the features split. Models of these conjugate structures show that IM/VRM reproduces the Magsat anomalies associated with non-KQZ crust but that both IM/VRM and a dominant NRM component are required to explain the anomalies associated with KQZ crust.

Fullerton, Lawrence G.↗
NASA NTRS1995

High Temperature Superconductivity in Praseodymium Doped (0%, 2%, 4%) in Melt-Textured Y(1-x)Pr(x)Ba2Cu3O(7-delta) Systems

A study of the magnetic and structural properties of the alloy Y(1-x)Pr(x)Ba2Cu3O(7-delta) of 0%, 2%, and 4% doping of praseodymium is presented. The resulting oxides of the alloy series are a high-temperature superconductor Y-Ba-Cu-O, which has an orthorhombic superconducting crystal-lattice. Magnetic relaxation studies have been performed on the Y-Pr-Ba-CuO bulk samples for field orientation parallel to the c-axis, using a vibrating sample magnetometer. Relaxation was measured at several temperatures to obtain the irreversible magnetization curves used for the Bean model. Magnetization current densities were derived from the relaxation data. Field and temperature dependence of the logarithmic flux-creep relaxation was measured in critical state. The data indicates that the effective activation energy U(eff) increases with increasing T between 77 K and 86 K. Also, the data shows that U(eff)(T) and superconducting transition temperature, Tc, decreased as the lattice parameters increased with increasing Pr ion concentration, x, for the corresponding Y(1-x)Pr(x)Ba(x)Cu3O(7-delta) oxides. One contribution to Tc decrease in this sampling is suspected to be due to the larger ionic radius of the Pr(3+) ion. The upper critical field (H(sub c2)) was measured in the presence of magnetic field parallel to the c axis. A linear temperature dependence with H(sub c2) was obtained.

James, Claudell↗
NASA NTRS2010

Characterization of Orbital Debris Photometric Properties Derived from Laboratory-Based Measurements

Capitalizing on optical data products and applying them to generate a more complete understanding of orbital space objects, is a key objective of NASA's Optical Measurement Program, and a primary objective for the creation of the Optical Measurements Center(OMC). The OMC attempts to emulate space-based illumination conditions using equipment and techniques that parallel telescopic observations and source-target-sensor orientations. The data acquired in the OMC are a function of known shape, size, and material. These three physical parameters are key to understanding the orbital debris environment in more depth. For optical observations, one must rely on spectroscopic or photometric measurements to ascertain an object's material type. Determination of an object s shape using remote observations is more complicated due to the various light scattering properties each object present and is a subject that requires more study. It is much easier to look at the periodicity of the light curve and analyze its structure for rotation. In order to best simulate the orbital debris population, three main sources were used as test fragments for optical measurements: flight-ready materials, destructive hypervelocity testing (simulating on-orbit collisions) and destructive pressure testing (simulating on-orbit explosions). Laboratory optical characteristics of fragments were measured, including light curve shape, phase angle dependence, and photometric and spectroscopic color indices. These characteristics were then compared with similar optical measurements acquired from telescopic observations in order to correlate remote and laboratory properties with the intent of ascertaining the intrinsic properties of the observed orbital debris

Cowardin, Heather↗
DOE OSTI2017

Exploring performance and energy tradeoffs for irregular applications: A case study on the Tilera many-core architecture

High performance, parallel applications with irregular data accesses are becoming a critical workload class for modern systems. In particular, the execution of such workloads on emerging many-core systems is expected to be a significant component of applications in data mining, machine learning, scientific computing and graph analytics. However, power and energy constraints limit the capabilities of individual cores, memory hierarchy and on-chip interconnect of such systems, thus leading to architectural and software trade-os that must be understood in the context of the intended application’s behavior. Irregular applications are notoriously hard to optimize given their data-dependent access patterns, lack of structured locality and complex data structures and code patterns. We have ported two irregular applications, graph community detection using the Louvain method (Grappolo) and high-performance conjugate gradient (HPCCG), to the Tilera many-core system and have conducted a detailed study of platform-independent and platform-specific optimizations that improve their performance as well as reduce their overall energy consumption. To conduct this study, we employ an auto-tuning based approach that explores the optimization design space along three dimensions - memory layout schemes, GCC compiler flag choices and OpenMP loop scheduling options. We leverage MIT’s OpenTuner auto-tuning framework to explore and recommend energy optimal choices for different combinations of parameters. We then conduct an in-depth architectural characterization to understand the memory behavior of the selected workloads. Finally, we perform a correlation study to demonstrate the interplay between the hardware behavior and application characteristics. Using auto-tuning, we demonstrate whole-node energy savings and performance improvements of up to 49:6% and 60% relative to a baseline instantiation, and up to 31% and 45:4% relative to manually optimized variants.

auto tuning↗
DOE OSTI2020

How good are polarizable and flexible models for water: Insights from a many-body perspective

We present a systematic analysis of state-of-the-art polarizable and flexible water models from a many-body perspective, with a specific focus on their ability to represent the Born–Oppenheimer potential energy surface of water from the gas to the liquid phase. Using coupled cluster data in the completed basis set limit as a reference, we examine the accuracy of the polarizable models in reproducing individual many-body contributions to interaction energies and harmonic frequencies of water clusters and compare their performance with that of MB-pol, an explicit many-body model that has been shown to correctly predict the properties of water across the entire phase diagram. Based on these comparisons, we use MB-pol as a reference to analyze the ability of the polarizable models to reproduce the energy landscape of liquid water under ambient conditions. We find that, while correctly reproducing the energetics of minimum-energy structures, the polarizable models examined in this study suffer from inadequate representations of many-body effects for distorted configurations. To investigate the role played by geometry-dependent representations of 1-body charge distributions in reproducing coupled cluster data for both interaction and many-body energies, we introduce a simplified version of MB-pol that adopts fixed atomic charges and demonstrate that the new model retains the same accuracy as the original MB-pol model. Based on the analyses presented in this study, we believe that future developments of both polarizable and explicit many-body models should continue in parallel and would benefit from synergistic efforts aimed at integrating the best aspects of the two theoretical/computational frameworks.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

Geometric GNNs for charged particle tracking at GlueX

Nuclear physics experiments are aimed at uncovering the fundamental building blocks of matter. The experiments involve high-energy collisions that produce complex events with many particle trajectories. Tracking charged particles resulting from collisions in the presence of a strong magnetic field is critical to enable the reconstruction of particle trajectories and precise determination of interactions. It is traditionally achieved through combinatorial approaches that scale worse than linearly as the number of hits grows. Since particle hit data naturally form a point cloud and can be structured as graphs, graph neural networks (GNNs) emerge as an intuitive and effective choice for this task. In this study, we evaluate the GNN model for track finding on the data from the GlueX experiment at Jefferson Lab. We use simulation data to train the model and test on both simulation and real GlueX measurements. We demonstrate that GNN-based track finding outperforms the currently used traditional method at GlueX in terms of segment-based efficiency at a fixed purity while providing faster inferences. We show that the GNN model can achieve significant speedup by processing multiple events in batches, which exploits the parallel computation capability of graphical processing units (GPUs). Finally, we compare the GNN implementation on GPU and field-programmable gate array and describe the trade-off.

batched GNN pipeline↗
NASA NTRS1992

Electrostatic waves due to field-aligned electron beams in the low-latitude boundary layer

Mass-resolved ion, electron, and plasma wave data obtained from several low-latitude boundary layer (LLBL) crossings by the AMPTE CCE satellite are analyzed. The data clearly separate the LLBL from the adjacent magnetosheath and magnetosphere. Attention was focused on wave-particle interactions involving electrons. Electron beams were found to be present in the LLBL during the southward interplanetary magnetic field, along with a simultaneous enhancement of electrostatic waves with parallel polarization. Linear theory analysis shows that for plasma conditions in the LLBL, electron beams are unstable to electrostatic waves that propagate parallel to the local magnetic field, in agreement with observations. A numerical simulation study of the beam-plasma interaction in the LLBL shows that the instability saturates by thermalization of the beam but that a beamlike structure can still remain in the electron distribution for certain initial parameters. It is suggested that peaks in the electron velocity distribution function may be found in the LLBL away from the beam source region.

Peroomian, V.↗
DOE OSTI2017

Energy-efficient mapping of large-scale workflows under deadline constraints in big data computing systems

Large-scale workflows for big data analytics have become a main consumer of energy in data centers where moldable parallel computing models such as MapReduce are widely applied to meet high computational demands with time-varying computing resources. The granularity of task partitioning in each moldable job of such big data workflows has a significant impact on energy efficiency, which remains largely unexplored. In this paper, we analyze the properties of moldable jobs and formulate a workflow mapping problem to minimize the dynamic energy consumption of a given workflow request under a deadline constraint in big data systems. Since this problem is strongly NP-hard, we design a fully polynomial-time approximation scheme (FPTAS) for a special case with a pipeline-structured workflow on a homogeneous cluster and a heuristic for the generalized problem with an arbitrary workflow on a heterogeneous cluster. The performance superiority of the proposed solution in terms of dynamic energy saving and deadline missing rate is illustrated by extensive simulation results in comparison with existing algorithms, and further validated by real-life workflow implementation and experimental results in Hadoop/YARN systems.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2024

Custom Accessors: Enabling Scalable Data Ingestion, (Re-)Organization, and Analysis on Distributed Systems

The emerging class of high velocity and high volume data analytic workflows comprise interwoven data ingestion, organization, and processing stages, with ingestion and organization steps often contributing comparable or even higher computational costs than actual processing steps. Since complex workflows consist of a variety of phases that view and use data differently, being able to construct efficient, scalable, distributed data structures (arrays, vectors, sets, maps, and multi-maps) is essential and requires custom methods to extend and shrink containers, analyze and position data, and, maintain globallyconsistent meta-data. In this paper, we propose a novel datastructure access paradigm based on the concept of Accessors. At a high level, accessors are customizable callable objects that can modify the behavior of insert, read, update, and delete operations for distributed containers while preserving atomicity guarantees. Accessors provide a very clean and natural way to implement a variety of programming patterns, e.g., conditional insertion/deletion and cascading computations, which would be otherwise hard (or even impossible) to express in parallel and distributed settings without using locks. We demonstrate the practicality and usefulness of our approach with two representative use cases and study the performance of these applications on a distributed High-Performance Computing system. Our analysis highlights that our proposed abstraction allows for an effective overlapping and concurrent execution of different workflow steps (e.g., data ingestion and analysis), which in a conventional analytics pipeline would execute sequentially, contributing cumulatively to the overall latency.

Castellana, Vito G. [BATTELLE (PACIFIC NW LAB)] (O↗
DOE OSTI2022

Scalable training of graph convolutional neural networks for fast and accurate predictions of HOMO-LUMO gap in molecules

Abstract Graph Convolutional Neural Network (GCNN) is a popular class of deep learning (DL) models in material science to predict material properties from the graph representation of molecular structures. Training an accurate and comprehensive GCNN surrogate for molecular design requires large-scale graph datasets and is usually a time-consuming process. Recent advances in GPUs and distributed computing open a path to reduce the computational cost for GCNN training effectively. However, efficient utilization of high performance computing (HPC) resources for training requires simultaneously optimizing large-scale data management and scalable stochastic batched optimization techniques. In this work, we focus on building GCNN models on HPC systems to predict material properties of millions of molecules. We use HydraGNN, our in-house library for large-scale GCNN training, leveraging distributed data parallelism in PyTorch. We use ADIOS, a high-performance data management framework for efficient storage and reading of large molecular graph data. We perform parallel training on two open-source large-scale graph datasets to build a GCNN predictor for an important quantum property known as the HOMO-LUMO gap. We measure the scalability, accuracy, and convergence of our approach on two DOE supercomputers: the Summit supercomputer at the Oak Ridge Leadership Computing Facility (OLCF) and the Perlmutter system at the National Energy Research Scientific Computing Center (NERSC). We present our experimental results with HydraGNN showing (i) reduction of data loading time up to 4.2 times compared with a conventional method and (ii) linear scaling performance for training up to 1024 GPUs on both Summit and Perlmutter.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
NASA NTRS1976

Magnetic anomaly map of North America south of 50 degrees north from Pogo data

A magnetic anomaly map produced from Pogo data for North America and adjacent ocean areas is presented. At satellite elevations anomalies have wavelengths measured in hundreds of kilometers, and reflect regional structures on a large scale. Prominent features of the map are: (1) a large east-west high through the mid-continent, breached at the Mississippi Embayment; (2) a broad low over the Gulf of Mexico; (3) a strong gradient separating these features, which follows the Southern Appalachian-Ouachita curvature; and (4) a high over the Antilles-Bahamas Platform which extends to northern Florida. A possible relationship between the high of the mid-continent and the 38th parallel lineament is noted.

Mayhew, M. A.↗