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At least 343 records · Page 19
All sourcesNASA NTRSDOE OSTI
NASA NTRS1994

Assessment of the SFC database for analysis and modeling

SFC is one of the four clusters that make up the Integrated Work Control System (IWCS), which will integrate the shuttle processing databases at Kennedy Space Center (KSC). The IWCS framework will enable communication among the four clusters and add new data collection protocols. The Shop Floor Control (SFC) module has been operational for two and a half years; however, at this stage, automatic links to the other 3 modules have not been implemented yet, except for a partial link to IOS (CASPR). SFC revolves around a DB/2 database with PFORMS acting as the database management system (DBMS). PFORMS is an off-the-shelf DB/2 application that provides a set of data entry screens and query forms. The main dynamic entity in the SFC and IOS database is a task; thus, the physical storage location and update privileges are driven by the status of the WAD. As we explored the SFC values, we realized that there was much to do before actually engaging in continuous analysis of the SFC data. Half way into this effort, it was realized that full scale analysis would have to be a future third phase of this effort. So, we concentrated on getting to know the contents of the database, and in establishing an initial set of tools to start the continuous analysis process. Specifically, we set out to: (1) provide specific procedures for statistical models, so as to enhance the TP-OAO office analysis and modeling capabilities; (2) design a data exchange interface; (3) prototype the interface to provide inputs to SCRAM; and (4) design a modeling database. These objectives were set with the expectation that, if met, they would provide former TP-OAO engineers with tools that would help them demonstrate the importance of process-based analyses. The latter, in return, will help them obtain the cooperation of various organizations in charting out their individual processes.

Centeno, Martha A.↗
DOE OSTI2023

Hydrostatic and Non‐Hydrostatic Baroclinic Instability in the Dynamical Core of the DOE Global Climate Model

Abstract The dynamical core of the Department of Energy global climate model is used to understand the role of non‐hydrostatic dynamics in the simulation of dry and moist baroclinic waves. To reduce computational cost, the Diabatic Acceleration and REscaling approach is adopted. Scale analysis and numerical simulations suggest that the model solution is not distorted by the change of spherical metric terms due to the change of Earth radius, neither are the inter‐scale interactions strongly altered as indicated by the analysis of spectral flux. Compared with hydrostatic simulations, the onset of baroclinic instability is delayed under non‐hydrostatic dynamics as the associated weaker vertical motions tend to increase the critical wavelength and narrow the range of waves that can be baroclinically unstable. During the development of baroclinic waves, non‐hydrostatic dynamics tends to induce vertical motions in the upper troposphere, accelerating the eastward propagation of upper‐level ridges through their impact on local vorticity tendency. These processes reduce the westward tilt of the vertical ridge axes and suppress the conversion of mean flow available potential energy to eddy kinetic energy, leading to weaker baroclinic eddies than in hydrostatic simulations. The contrasts between hydrostatic and non‐hydrostatic settings hold in supplemental experiments that vary the background flow Rossby number, the amount of water vapor content and vertical resolution. We also find that mesoscale and smaller‐scale activities can be considerably under‐represented when the vertical resolution is limited to that typically used in global climate models.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2015

Molecular-dynamics analysis of mobile helium cluster reactions near surfaces of plasma-exposed tungsten

We report the results of a systematic atomic-scale analysis of the reactions of small mobile helium clusters (He{sub n}, 4 ≤ n ≤ 7) near low-Miller-index tungsten (W) surfaces, aiming at a fundamental understanding of the near-surface dynamics of helium-carrying species in plasma-exposed tungsten. These small mobile helium clusters are attracted to the surface and migrate to the surface by Fickian diffusion and drift due to the thermodynamic driving force for surface segregation. As the clusters migrate toward the surface, trap mutation (TM) and cluster dissociation reactions are activated at rates higher than in the bulk. TM produces W adatoms and immobile complexes of helium clusters surrounding W vacancies located within the lattice planes at a short distance from the surface. These reactions are identified and characterized in detail based on the analysis of a large number of molecular-dynamics trajectories for each such mobile cluster near W(100), W(110), and W(111) surfaces. TM is found to be the dominant cluster reaction for all cluster and surface combinations, except for the He{sub 4} and He{sub 5} clusters near W(100) where cluster partial dissociation following TM dominates. We find that there exists a critical cluster size, n = 4 near W(100) and W(111) and n = 5 near W(110), beyond which the formation of multiple W adatoms and vacancies in the TM reactions is observed. The identified cluster reactions are responsible for important structural, morphological, and compositional features in the plasma-exposed tungsten, including surface adatom populations, near-surface immobile helium-vacancy complexes, and retained helium content, which are expected to influence the amount of hydrogen re-cycling and tritium retention in fusion tokamaks.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2017

Fuel pin zoning to improve the accuracy of the palisades spent fuel pool criticality analysis

Most PWR spent fuel pool criticality analyses assume that the burnup is uniformly distributed among the fuel pins in the assembly. This assumption is accurate for PWR cores that have the typical small inter-assembly gap. The Palisades reactor core, however, is different in that it uses cruciform control rods in between fuel assemblies. Every interior assembly has two sides having a wide water gap and two sides having a narrow water gap. After depleting under these conditions, the pins near the wide water gap will have a higher burnup than the pins in the center. If the burnup is distributed uniformly among the pins, the resulting k calculation will be conservative but excessively so. The excess conservatism was found to be on the order of 1% in k. For this analysis, SCALE 6.1 depletion with TRITON is used followed by the CSAS5 module for the Palisades pool analysis. Several burnup zoning arrangements (uniform enrichment) were investigated ranging from 3 zones to as many as 19 zones. The 19 zone analysis agreed well with a CASMO analysis where every pin was its own depletion zone. It was found that 8 fuel zones gave essentially the same result as 19 zones with less complexity. The depletion calculation using 8 fuel zones instead of a single zone is more complicated but the resulting k calculation no longer has the excessive conservatism seen in a one zone model. (authors)

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2023

Automated Energy-Dispersive X-ray Spectroscopy Analysis for Multi-Modal Few-Shot Learning

Scanning transmission electron microscopy (STEM) is a powerful tool that allows for the atomic-scale analysis of a materials’ structure, chemistry, and defect domains (Akers et al. 2021). The current generation of microscopes generate vast amounts of data, surpassing the limits of effective manual analysis traditionally performed by domain experts (Spurgeon et al. 2021). While recent strides in machine learning have significantly enhanced the processing of large and intricate datasets acquired through electron microscopy, the prevalent use of proprietary software packages for initial data collection poses a challenge. In many cases, these software packages act as a ‘black box’, constraining user functionality and hindering the output of data in a format that is conducive to seamless integration into machine learning models. This work addresses these challenges by adapting HyperSpy, an open-source Python library, for the analysis and quantification of raw energy dispersive spectroscopy (EDS) data acquired through STEM. The modified HyperSpy code successfully facilitates user-defined segmentation of the data, enabling the integration of atomic %, weight %, and raw EDS spectra for each segmented region into an existing few-shot machine learning model. While initial results reveal discrepancies in quantified atomic and weight percentages when compared to proprietary software, ongoing efforts aim to rectify this issue by refining the fit of the HyperSpy model to the EDS spectra. Overall, this research underscores the potential of open-source tools like HyperSpy to enhance the accessibility of analytical tools, fostering a transparent and user-friendly environment for seamlessly incorporating electron microscopy data into machine learning models.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Change Detection Applications in the Earth Sciences Using UAS-Based Sensing: A Review and Future Opportunities

Over the past decade, advancements in collection platforms such as unoccupied aerial systems (UAS), survey-grade GNSS, sensor packages, processing software, and spatial analytical tools have facilitated change detection analyses at an unprecedented resolution over broader spatial and temporal extents and in environments where such investigations present challenges. These technological improvements, coupled with the accessibility and versatility of UAS technology, have pushed the boundaries of spatial and temporal scales in geomorphic change detection. As a result, the cm-scale analysis of topographic signatures can detect and quantify surface anomalies during geomorphic evolution. This review focuses on the use of UAS photogrammetry for fine spatial (cm) and temporal (hours to days) scale geomorphic analyses, and it highlights analytical approaches to detect and quantify surface processes that were previously elusive. The review provides insight into topographic change characterization with precise spatial validations applied to landscape processes in various fields, such as the cryosphere and geosphere, as well as anthropogenic earth processes and national security applications. This work sheds light on previously unexplored aspects of both natural and human-engineered environments, demonstrating the potential of UAS observations in change detection. Our discussion examines the emerging horizons of UAS-based change detection, including machine learning and LIDAR systems. In addition, our meta-analysis of spatial and temporal UAS-based observations highlights the new fine-scale niche of UAS-photogrammetry. This scale advancement sets a new frontier in change detection, offering exciting possibilities for the future of land surface analysis and environmental monitoring in the field of Earth Science.

Andresen, Christian G.↗
DOE OSTI2013

Observation of spin-glass behavior in nickel adsorbed few layer graphene

Nickel-adsorbed graphene was prepared by first synthesizing graphite oxide (GO) by modified Hummers' method and then reducing a solution containing both GO and Ni{sup 2+}. Energy dispersive X-ray spectroscopy analysis showed 31 at. % nickel was present. Magnetization measurements under both dc and ac magnetic fields were carried out in the temperature range 2 K to 300 K. The zero field cooled and field cooled magnetization data showed a pronounced irreversibility at a temperature around 20 K. The analysis of the ac susceptibility data was carried out by both Vogel-Fulcher as well as power law. From dynamic scaling analysis, the microscopic flipping time {tau}{sub 0}{approx}10{sup -13}s and critical exponent z{nu}=5.9{+-}0.1 were found, indicating the presence of conventional spin glass in the system. The spin glass transition temperature was estimated as 19.5 K. Decay of thermoremanent magnetization was explained by stretched exponential function with a value of the exponent as 0.6. From the results, it is concluded that nickel adsorbed graphene behaves like a spin-glass.

77 NANOSCIENCE AND NANOTECHNOLOGY↗
DOE OSTI2018

The effect of chain stiffness and salt on the elastic response of a polyelectrolyte

Here, We present simulations of the force-extension curves of strong polyelectrolytes with varying intrinsic stiffness as well as specifically treating hyaluronic acid, a polyelectrolyte of intermediate stiffness. Whereas fully flexible polyelectrolytes show a high-force regime where extension increases nearly logarithmically with force, we find that the addition of even a small amount of stiffness alters the short-range structure and removes this logarithmic elastic regime. This further confirms that the logarithmic regime is a consequence of the short-ranged “wrinkles” in the flexible chain. As the stiffness increases, the force-extension curves tend toward and reach the wormlike chain behavior. Using the screened Coulomb potential and a simple bead-spring model, the simulations are able to reproduce the hyaluronic acid experimental force-extension curves for salt concentrations ranging from 1 to 500 mM. Furthermore, the simulation data can be scaled to a universal curve like the experimental data. The scaling analysis is consistent with the interpretation that, in the low-salt limit, the hyaluronic acid chain stiffness scales with salt with an exponent of –0.7, rather than either of the two main theoretical predictions of –0.5 and –1. Furthermore, given the conditions of the simulation, we conclude that this exponent value is not due to counterion condensation effects, as had previously been suggested.

36 MATERIALS SCIENCE↗
NASA NTRS1984

Data engineering systems: Computerized modeling and data bank capabilities for engineering analysis

The Data Engineering System (DES) is a computer-based system that organizes technical data and provides automated mechanisms for storage, retrieval, and engineering analysis. The DES combines the benefits of a structured data base system with automated links to large-scale analysis codes. While the DES provides the user with many of the capabilities of a computer-aided design (CAD) system, the systems are actually quite different in several respects. A typical CAD system emphasizes interactive graphics capabilities and organizes data in a manner that optimizes these graphics. On the other hand, the DES is a computer-aided engineering system intended for the engineer who must operationally understand an existing or planned design or who desires to carry out additional technical analysis based on a particular design. The DES emphasizes data retrieval in a form that not only provides the engineer access to search and display the data but also links the data automatically with the computer analysis codes.

Kopp, H.↗
DOE OSTI2018

Plasma Surface Interactions: Bridging from the Surface to the Micron Frontier through Leadership Class Computing (Final Technical Progress Report)

The performance demands on plasma-facing components (PFCs) in future fusion power plants are beyond the capability of current materials. In defining the plasma-surface interaction (PSI), it is evident that three coupled spatial regions influence PFC materials evolution and performance. These regions consist of (1) the edge and scrape-off layer region of the plasma, (2) the near-surface material response to extreme thermal and particle fluxes under the influence of, and feedback to, the plasma sheath, and (3) the structural material’s response to an intense, 14 MeV peaked neutron spectrum, which produces very high concentrations of transmuted elements through (n,p) and (n,α) reactions and structural material property degradation. The objective of this project is to develop and deploy validated, high-performance simulation tools capable of predicting the performance of tungsten-based plasma-facing components (PFCs) in a burning fusion plasma environment, which includes modeling surface morphology evolution in either erosion or re-deposition regimes, and the recycling of hydrogen species. This requires the development of a leadership-scale computational code to predict PFC behavior that is well integrated to a suite of multiscale modeling techniques to bridge the scales needed to address complex physical and computational issues at the plasma surface interface and the transition region below the surface where neutron damage processes in the bulk dominate material behavior. Successful completion of this project will provide PFC simulation tools to evaluate steady-state performance of tungsten-based PFC and divertor components in burning plasma environments. This will enable the identification of critical experiments to confirm whether practical PFC solutions exist for magnetic fusion energy beyond ITER. More specifically, the research activities within this project focus on two broadly defined research thrusts: 1) Developing a new simulation code, Xolotl-PSI to predict PFC operating lifetime and performance, that is specifically designed to take advantage of leadership class computing facilities; and 2) Integrating and applying discrete particle-based, as well as continuum-based, multiscale modeling techniques to provide scientific discovery of the mechanisms controlling PFC and bulk materials evolution under fusion plasma and 14-MeV neutron exposure; in this thrust, the challenge of scale-bridging between atomistic/microstructural modeling and the continuum-scale of PFC device performance is achieved through multiscale modeling techniques. Throughout the grant period, research at UMass Amherst focused on the atomic-scale analysis of the dynamics and kinetics (transport and reactions) of small mobile helium clusters near surfaces and grain boundaries in plasma-exposed tungsten, as well as the proper parameterization and incorporation of these processes into our SciDAC team’s continuum-level cluster dynamics code (Xolotl). Our work also included characterization of large-scale molecular-dynamics (MD) simulation results of helium implantation into tungsten based on the findings of our analysis and comparisons of Xolotl simulation predictions with the large-scale MD simulation results for Xolotl validation purposes; emphasis was placed on the impact of helium cluster dynamics/kinetics on tungsten surface morphology, near-surface tungsten structure, and helium retention. Furthermore, our work included initiation of a research program on evaluating the impact of structural defects in tungsten due to plasma exposure (such as helium nanobubbles) on tungsten’s thermophysical properties, focusing on lattice thermal conductivity. Our studies contributed to a fundamental understanding of the effects of plasma-surface interactions on the dynamical response of plasma-facing materials in nuclear fusion devices and the development of predictive hierarchical multiscale computational tools for the quantitative description of the material’s dynamical response to plasma exposure.

36 MATERIALS SCIENCE↗
NASA NTRS2015

Projection-Based Reduced Order Modeling for Spacecraft Thermal Analysis

This paper presents a mathematically rigorous, subspace projection-based reduced order modeling (ROM) methodology and an integrated framework to automatically generate reduced order models for spacecraft thermal analysis. Two key steps in the reduced order modeling procedure are described: (1) the acquisition of a full-scale spacecraft model in the ordinary differential equation (ODE) and differential algebraic equation (DAE) form to resolve its dynamic thermal behavior; and (2) the ROM to markedly reduce the dimension of the full-scale model. Specifically, proper orthogonal decomposition (POD) in conjunction with discrete empirical interpolation method (DEIM) and trajectory piece-wise linear (TPWL) methods are developed to address the strong nonlinear thermal effects due to coupled conductive and radiative heat transfer in the spacecraft environment. Case studies using NASA-relevant satellite models are undertaken to verify the capability and to assess the computational performance of the ROM technique in terms of speed-up and error relative to the full-scale model. ROM exhibits excellent agreement in spatiotemporal thermal profiles (<0.5% relative error in pertinent time scales) along with salient computational acceleration (up to two orders of magnitude speed-up) over the full-scale analysis. These findings establish the feasibility of ROM to perform rational and computationally affordable thermal analysis, develop reliable thermal control strategies for spacecraft, and greatly reduce the development cycle times and costs.

0000↗
DOE OSTI2024

Mechanical and Thermal Forcing for Upslope Flows and Cumulus Convection over the Sierras de Córdoba

Abstract The upslope flow processes affecting the vertical extent of orographic cumulus convection are examined using observations from the Cloud, Aerosol, and Complex Terrain Interactions (CACTI) field campaign. Specifically, clear air returns from the U.S. Department of Energy (DOE) second-generation C-band scanning Atmospheric Radiation Measurement (ARM) precipitation radar (CSAPR2) are used to characterize the structure and variability of the ridge-normal (i.e., up/downslope) flow components, which transport mass to the crest of Argentina’s Sierras de Córdoba and contribute to convective initiation. Data are compiled for the entire CACTI period (October–April), including days with clear skies, shallow cumuli, cumulus congestus, and deep convection. To examine shared variability among >70 000 radar scans, we use (i) a principal component analysis (PCA) to isolate modes of variability in the upslope flow and (ii) composite analysis based on convective outcomes, determined from GOES-16 satellite observations. These data are contextualized with observed surface sensible heat fluxes, thermodynamic profiles, and synoptic-scale analysis. Results indicate distinct thermally and mechanically forced upslope flow modes, modulated by diurnal heating and synoptic-scale variations, respectively. In some instances, there is a superposition of thermal and mechanical forcing, yielding either deeper or shallower upslope flow. The composite analyses based on satellite data show that successively deeper convective outcomes are associated with successively deeper upslope flow layers that more readily transport mass to the ridge crest in conjunction with lower lifting condensation levels, facilitating convective initiation. These results help to isolate the forcing mechanisms for orographic convection and thus provide a foundation for parameterizing orographic convective processes in coarse resolution models.

Meteorology & Atmospheric Sciences↗
DOE OSTI2024

Intracore Natural Circulation Study in the High Temperature Test Facility

The development of the Modular High-Temperature Gas-Cooled Reactor is a significant milestone in advanced nuclear reactor technology. One of the concerns for the reactor’s safe operation is the effects of a loss-of-flow accident (LOFA) where the coolant circulators are tripped, and forced coolant flow through the core is lost. Depending on the steam generator placement, loop or intracore natural circulation develops to help transfer heat from the core to the reactor cavity, cooling system. This paper investigates the fundamental physical phenomena associated with intracore coolant natural circulation flow in a one-sixth Computational Fluid Dynamics (CFD) model of the Oregon State University High Temperature Test Facility (OSU HTTF) following a loss-of-flow accident transient. This study employs conjugate heat transfer and steady-state flow along with an SST k-ω turbulence model to characterize the phenomenon of core channel-to-channel natural convection. Previous studies have revealed the importance of complex flow distribution in the inlet and outlet plenums with the potential to generate hot coolant jets. For this reason, complete upper and lower plenum volumes are included in the analyzed computational domain. CFD results also include parametric studies performed for a mesh sensitivity analysis, generated using the STAR-CCM+ software. The resulting channel axial velocities and flow directions support the test facility scaling analysis and similarity group distortions calculation.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
NASA NTRS2020

Improving Quantitative Laboratory Analysis of Phycobiliproteins to Provide High Quality Validation Data for Ocean Color Remote Sensing Algorithm

Identification and characterization of phytoplankton communities and their physiology is a primary aim of NASA's PACE satellite mission. The concentration and composition of phytoplankton pigments modulate the spectral distribution of light emanating from the ocean, which is measured by ocean color satellites, and thus provide critical information on phytoplankton community composition and physiological parameters. One diagnostic class of pigments not routinely well-characterized is the phycobiliproteins (PBPs), and NASA has a requirement to collect and distribute high quality in situ data in support of data product validation activities for ocean color missions. Phycobiliproteins are light-harvesting proteins that are the predominant photosynthetic pigments in some classes of phytoplankton including cyanobacteria, such as Synechococcus, Trichodesmium, and Microcystis. With the advance of hyperspectral ocean color sensors such as on PACE (expected to launch in late 2022), it is essential that we implement routine analysis of PBPs that satisfies several considerations: reproducible, high extraction efficiency for a variety of environments, and Suitable for large scale analysis. Published techniques for PBP analysis vary in recommendations for: collection, extraction, disruption mode, and analysis; evidence suggests the variation in results may depend at least in part on the species and even strain(s) of interest. Experiments that tested variations in these parameters have drawn very different conclusions regarding extraction efficiency and reproducibility. Cyanobacteria are more difficult to extract than other PBP-containing algae such as cryptophytes, but can be important primary producers. We used a cryptophyte (Rhodomonas salina) and cyanobacterium (Synechococcus sp.) to compare extraction efficiencies of water samples concentrated via centrifugation to filtered samples using two different extraction buffers (phosphate and asolectin-CHAPS). Samples were analyzed on a fluorometer configured for PC and PE detection. The results have important implications for collection and storage of samples for routine analysis; some previous studies (although not all) have suggested that filtered samples have a much lower extraction efficiency than whole water samples.

Kenemer, Christopher↗
DOE OSTI2021

Validation of Scale-Derived Ages in Wild Juvenile and Adult Steelhead Using Parental-Based Tagging

Abstract Accurate age information is a critical component in fisheries monitoring, management, and research. The ability to assign accurate ages to fish by using nonlethal structures is vital in calculating cohort productivity for fish species with low abundances and variable life histories. A common nonlethal method to assign ages is by interpretation of patterns in scales. Validation of ages is not easily obtained for free-ranging fishes; however, the development of genetic “tags” has expanded age validation opportunities. In this study, we used parental-based genetic tagging to validate ages determined from scales collected from juvenile and adult steelhead Oncorhynchus mykiss in two streams within the Snake River basin. Juvenile scale ages were in agreement with 93% of the known ages. Adult scale ages were in agreement with 89% of the known ages. Although overall bias in juvenile ages was very low, we saw a slight positive bias in younger fish (young of the year and age 1) and a small negative bias in older juveniles (ages 2–4). A small negative bias in ages of adults was a consequence of errors in freshwater age. The errors observed did not significantly bias age compositions because the 90% confidence intervals about the age proportions based on scales contained the known proportions; therefore, scale analysis is an acceptable method for assigning ages to Snake River steelhead. We discuss the value of validated known-age scales as a reference collection, and as an illustrative use, we constructed a circulus count guide to aid technicians in identifying missing annuli and distinguishing true from false annuli. To demonstrate the use of the circulus guidelines, we reanalyzed samples with age discrepancies, applying the circulus count data and the known age to identify mistakes.

Reinhardt, Leslie↗
DOE OSTI2023

Exact hopfion vortices in a 3D Heisenberg ferromagnet

Here, we find exact static soliton solutions for the unit spin vector field of an inhomogeneous, anisotropic three-dimensional Heisenberg ferromagnet. Each soliton is labeled by two integers n and m. It is a (modified) skyrmion in the z = 0 plane with winding number n, which twists out of the plane m times in the z-direction to become a 3D soliton. Here m arises due to the periodic boundary condition at the z-boundaries. We use Whitehead’s integral expression to find that the Hopf invariant of the soliton is an integer H = nm. It represents a hopfion vortex. Plots of the preimages of this topological soliton show that they are either unknots or nontrivial knots, depending on n and m. Any pair of preimage curves links H times, corroborating the interpretation of H as a linking number. We also calculate the exact energy of the hopfion vortex, and show that its topological lower bound has a sublinear dependence on H. Using Derrick’s scaling analysis, we demonstrate that the presence of a spatial inhomogeneity in the anisotropic interaction, which in turn introduces a characteristic length scale in the system, leads to the stability of the hopfion vortex.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Ion versus Electron Heating in Compressively Driven Astrophysical Gyrokinetic Turbulence

The partition of irreversible heating between ions and electrons in compressively driven (but subsonic) collisionless turbulence is investigated by means of nonlinear hybrid gyrokinetic simulations. We derive a prescription for the ion-to-electron heating ratio Q i /Q e as a function of the compressive-to-Alfvénic driving power ratio P compr /P AW , of the ratio of ion thermal pressure to magnetic pressure β i , and of the ratio of ion-to-electron background temperatures T i /T e . It is shown that Q i /Q e is an increasing function of P compr /P AW . When the compressive driving is sufficiently large, Q i /Q e approaches ≃P compr /P AW . This indicates that, in turbulence with large compressive fluctuations, the partition of heating is decided at the injection scales, rather than at kinetic scales. Analysis of phase-space spectra shows that the energy transfer from inertial-range compressive fluctuations to sub-Larmor-scale kinetic Alfvén waves is absent for both low and high β i , meaning that the compressive driving is directly connected to the ion-entropy fluctuations, which are converted into ion thermal energy. This result suggests that preferential electron heating is a very special case requiring low βi and no, or weak, compressive driving. Our heating prescription has wide-ranging applications, including to the solar wind and to hot accretion disks such as M87 and Sgr A*.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2016

Mini-apps for high performance data analysis

Scaling-up scientific data analysis and machine learning algorithms for data-driven discovery is a grand challenge that we face today. Despite the growing need for analysis from science domains that are generating `Big Data' from instruments and simulations, building high-performance analytical workflows of data-intensive algorithms have been daunting because: (i) the `Big Data' hardware and software architecture landscape is constantly evolving, (ii) newer architectures impose new programming models, and (iii) data-parallel kernels of analysis algorithms and their performance facets on different architectures are poorly understood. To address these problems, we have: (i) identified scalable data-parallel kernels of popular data analysis algorithms, (ii) implemented `Mini-Apps' of those kernels using different programming models (e.g. Map Reduce, MPI, etc.), (iii) benchmarked and validated the performance of the kernels in diverse architectures. In this paper, we discuss two of those Mini-Apps and show the execution of principal component analysis built as a workflow of the Mini-Apps. We show that Mini-Apps enable scientists to (i) write domain-specific data analysis code that scales on most HPC hardware and (ii) and offers the ability (most times with over a 10x speed-up) to analyze data sizes 100 times the size of what off-the-shelf desktop/workstations of today can handle.

Sukumar, Sreenivas R.↗