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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 973 records · Page 54

All sources NASA NTRS DOE OSTI

DOE OSTI2018

The Improved Thermal Conductivity of a Potting Material for High-Power Fast Warm-Up Cathodes

With higher power, frequency and longer life of microwave tubes, cathode heater assembly is being modified to enhance the warm-up performance and reliability, which are governed by ceramics thermal conductivity, electrical resistivity and shrinkage. In present work, a potting material with a high thermal conductivity of 22.14 W/(m K) and low linear shrinkage of 5.5% was prepared using two kinds of alumina powders with different size and morphology. Aqueous slurries were produced for centrifugal casting. The highest solid loading slurries with 70 vol.% were obtained. Green body with relative density above 70% was easily made from slurries using centrifugal casting. Relative sintered density reached 86.75% maximum without any sintering aids. Rheological behavior of slurries, potting microstructure, sintering shrinkage and thermal conductivity were analyzed. Continuous particle distribution, series and parallel models were used to guide the powders proportion and explain the thermal conductivity. The potting material thermal conductivity experimental data agreed with the series and parallel models when the weight parameter ξ was between 0.3 and 0.5.

36 MATERIALS SCIENCE↗

DOE OSTI2020

Pass-efficient methods for compression of high-dimensional turbulent flow data

The future of high-performance computing, specifically on future Exascale computers, will presumably see memory capacity and bandwidth fail to keep pace with data generated, for instance, from massively parallel partial differential equation (PDE) systems. Current strategies proposed to address this bottleneck entail the omission of large fractions of data, as well as the incorporation of in situ compression algorithms to avoid overuse of memory. To ensure that post-processing operations are successful, this must be done in a way that a sufficiently accurate representation of the solution is stored. Moreover, in situations where the input/output system becomes a bottleneck in analysis, visualization, etc., or the execution of the PDE solver is expensive, the number of passes made over the data must be minimized. In the interest of addressing this problem, this work focuses on the utility of pass-efficient, parallelizable, low-rank, matrix decomposition methods in compressing high-dimensional simulation data from turbulent flows. Additionally, a particular emphasis is placed on using coarse representation of the data – compatible with the PDE discretization grid – to accelerate the construction of the low-rank factorization. This includes the presentation of a novel single-pass matrix decomposition algorithm for computing the so-called interpolative decomposition. The methods are described extensively and numerical experiments on two turbulent channel flow data are performed. In the first (unladen) channel flow case, compression factors exceeding 400 are achieved while maintaining accuracy with respect to first- and second-order flow statistics. In the particle-laden case, compression factors of 100 are achieved and the compressed data is used to recover particle velocities. These results show that these compression methods can enable efficient computation of various quantities of interest in both the carrier and disperse phases.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

DOE OSTI2017

ATLAS (Automatic Tool for Local Assembly Structures) - A Comprehensive Infrastructure for Assembly, Annotation, and Genomic Binning of Metagenomic and Metaranscripomic Data

ATLAS (Automatic Tool for Local Assembly Structures) is a comprehensive multiomics data analysis pipeline that is massively parallel and scalable. ATLAS contains a modular analysis pipeline for assembly, annotation, quantification and genome binning of metagenomics and metatranscriptomics data and a framework for reference metaproteomic database construction. ATLAS transforms raw sequence data into functional and taxonomic data at the microbial population level and provides genome-centric resolution through genome binning. ATLAS provides robust taxonomy based on majority voting of protein coding open reading frames rolled-up at the contig level using modified lowest common ancestor (LCA) analysis. ATLAS provides robust taxonomy based on majority voting of protein coding open reading frames rolled-up at the contig level using modified lowest common ancestor (LCA) analysis. ATLAS is user-friendly, easy install through bioconda maintained as open-source on GitHub, and is implemented in Snakemake for modular customizable workflows.

genome binning↗

NASA NTRS1997

High Performance Morphological Filtering of Cirrus Emission from Infrared Images

The project was designed to explore new morphological filtering, techniques for the removal of foreground Galactic 'Cirrus' emission from NASA Infrared Astronomical Satellite (IRAS) data, especially at 100 microns, using parallel processors as the main engine for achieving this result. The ultimate aim was to provide NASA with completely filtered data by the end of the grant period for the entire IRAS 100 and possibly 60 micron database. If successful, the filtered data would reveal many new sources of IR emission, especially at low galactic latitudes, which had previously been heavily confused with diffuse Galactic 'cirrus'.

Appleton, P. N.↗

NASA NTRSDate not supplied

Nanopore Sequencing-Based Microbial Air Profiling Method for Crewed Spacecraft

Microbial monitoring of the International Space Station (ISS) atmosphere is vital to maintaining the health of the spacecraft and crew. Key to NASA’s microbial risk assessment is the identity of contaminating microorganisms in the environment. Historically, this has been achieved through impaction-based air sampling followed by culture. Identification of the microorganisms present requires sample return to Earth and lab-based analyses. While this culture-based approach has served to provide alerts to anomalies and overall confidence in the controls in place, it is not suitable for exploration missions with no sample return. Recently, significant advancements in molecular-based microbial monitoring via nanopore sequencing have been implemented onboard the ISS. Building on this work, multiple commercially available air samplers, compatible with downstream molecular analysis, were evaluated for use in the spaceflight environment. Through this assessment, the Coriolis Compact (Bertin Technologies), which uses cyclonic technology to collect bioaerosols onto the surface of a sterile cone, was selected for a larger-scale comparison to the current culture-based monitoring method. Using the Coriolis Compact, 1000 L of air was collected from the breakroom of an office building and a fitness center. The buffer used to dissociate the microbial cells from the surface of the cone was split between the NASA Microbiology Laboratory’s standard culture and Sanger sequencing-based method and the culture-independent nanopore sequencing method. The bacteria identified through culture were present in the nanopore data, with Micrococcus, Staphylococcus, and Moraxella being the most common cultured isolates, which is expected based on the media and growth conditions. Not surprisingly, the nanopore data yielded much higher diversity and paralleled that of previous atmospheric microbiome studies of human-occupied built environments. As compared to the culture-based data where the breakroom and fitness center data sets cluster in proximity, the nanopore data depicts the contrast of these atmospheric microbiomes. Moreover, the nanopore data were sufficient to meet NASA’s risk assessment needs and noted the culturable isolates routinely observed. This nanopore-based atmospheric microbial profiling method will enable near real-time environmental monitoring of crewed spacecraft as future missions extend beyond low-Earth orbit.

Brandon Dunbar↗

NASA NTRS1977

Analysis of low altitude atmospheric turbulence data measured in flight

All three components of turbulence were measured simultaneously in flight at each wing tip of a Beech D-18 aircraft. The flights were conducted at low altitude, 30.5 - 61.0 meters (100-200 ft.), over water in the presence of wind driven turbulence. Statistical properties of flight measured turbulence were compared with Gaussian and non-Gaussian turbulence models. Spatial characteristics of the turbulence were analyzed using the data from flight perpendicular and parallel to the wind. The probability density distributions of the vertical gusts show distinctly non-Gaussian characteristics. The distributions of the longitudinal and lateral gusts are generally Gaussian. The power spectra compare in the inertial subrange at some points better with the Dryden spectrum, while at other points the von Karman spectrum is a better approximation. In the low frequency range the data show peaks or dips in the power spectral density. The cross between vertical gusts in the direction of the mean wind were compared with a matched non-Gaussian model. The real component of the cross spectrum is in general close to the non-Gaussian model. The imaginary component, however, indicated a larger phase shift between these two gust components than was found in previous research.

Ganzer, V. M.↗

NASA NTRS1972

Post-analysis report on Chesapeake Bay data processing

The additional processing performed on data collected over the Rhode River Test Site and Forestry Site in November 1970 is reported. The techniques and procedures used to obtain the processed results are described. Thermal data collected over three approximately parallel lines of the site were contoured, and the results color coded, for the purpose of delineating important scene constituents and to identify trees attacked by pine bark beetles. Contouring work and histogram preparation are reviewed and the important conclusions from the spectral analysis and recognition computer (SPARC) signature extension work are summarized. The SPARC setup and processing records are presented and recommendations are made for future data collection over the site.

Thomson, F.↗

DOE OSTI2018

FDTD: Solving 1+1D delay PDE in parallel

We present a proof of concept for solving a 1+1D complex-valued, delay partial differential equation (PDE) that emerges in the study of waveguide quantum electrodynamics (QED) by adapting the finite-difference time-domain (FDTD) method. The delay term is spatially non-local, rendering conventional approaches such as the method of lines inapplicable. Here, we show that by properly designing the grid and by supplying the (partial) exact solution as the boundary condition, the delay PDE can be numerically solved. In addition, we demonstrate that while the delay imposes strong data dependency, multi-thread parallelization can nevertheless be applied to such a problem. Our code provides a numerically exact solution to the time-dependent multi-photon scattering problem in waveguide QED.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

NASA NTRS1997

High Performance Input/Output Systems for High Performance Computing and Four-Dimensional Data Assimilation

The approach of this task was to apply leading parallel computing research to a number of existing techniques for assimilation, and extract parameters indicating where and how input/output limits computational performance. The following was used for detailed knowledge of the application problems: 1. Developing a parallel input/output system specifically for this application 2. Extracting the important input/output characteristics of data assimilation problems; and 3. Building these characteristics s parameters into our runtime library (Fortran D/High Performance Fortran) for parallel input/output support.

Fox, Geoffrey C.↗

DOE OSTI2019

Managing variations among nodes in parallel system frameworks

Systems, apparatuses, and methods for managing variations among nodes in parallel system frameworks. Sensor and performance data associated with the nodes of a multi-node cluster may be monitored to detect variations among the nodes. A variability metric may be calculated for each node of the cluster based on the sensor and performance data associated with the node. The variability metrics may then be used by a mapper to efficiently map tasks of a parallel application to the nodes of the cluster. In one embodiment, the mapper may assign the critical tasks of the parallel application to the nodes with the lowest variability metrics. In another embodiment, the hardware of the nodes may be reconfigured so as to reduce the node-to-node variability.

97 MATHEMATICS AND COMPUTING↗

NASA NTRS1999

Parallelization of the Physical-Space Statistical Analysis System (PSAS)

Atmospheric data assimilation is a method of combining observations with model forecasts to produce a more accurate description of the atmosphere than the observations or forecast alone can provide. Data assimilation plays an increasingly important role in the study of climate and atmospheric chemistry. The NASA Data Assimilation Office (DAO) has developed the Goddard Earth Observing System Data Assimilation System (GEOS DAS) to create assimilated datasets. The core computational components of the GEOS DAS include the GEOS General Circulation Model (GCM) and the Physical-space Statistical Analysis System (PSAS). The need for timely validation of scientific enhancements to the data assimilation system poses computational demands that are best met by distributed parallel software. PSAS is implemented in Fortran 90 using object-based design principles. The analysis portions of the code solve two equations. The first of these is the "innovation" equation, which is solved on the unstructured observation grid using a preconditioned conjugate gradient (CG) method. The "analysis" equation is a transformation from the observation grid back to a structured grid, and is solved by a direct matrix-vector multiplication. Use of a factored-operator formulation reduces the computational complexity of both the CG solver and the matrix-vector multiplication, rendering the matrix-vector multiplications as a successive product of operators on a vector. Sparsity is introduced to these operators by partitioning the observations using an icosahedral decomposition scheme. PSAS builds a large (approx. 128MB) run-time database of parameters used in the calculation of these operators. Implementing a message passing parallel computing paradigm into an existing yet developing computational system as complex as PSAS is nontrivial. One of the technical challenges is balancing the requirements for computational reproducibility with the need for high performance. The problem of computational reproducibility is well known in the parallel computing community. It is a requirement that the parallel code perform calculations in a fashion that will yield identical results on different configurations of processing elements on the same platform. In some cases this problem can be solved by sacrificing performance. Meeting this requirement and still achieving high performance is very difficult. Topics to be discussed include: current PSAS design and parallelization strategy; reproducibility issues; load balance vs. database memory demands, possible solutions to these problems.

Larson, J. W.↗

DOE OSTI2023

In-depth analysis on parallel processing patterns for high-performance Dataframes

The Data Science domain has expanded monumentally in both research and industry communities during the past decade, predominantly owing to the Big Data revolution. Artificial Intelligence (AI) and Machine Learning (ML) are bringing more complexities to data engineering applications, which are now integrated into data processing pipelines to process terabytes of data. Typically, a significant amount of time is spent on data preprocessing in these pipelines, and hence improving its efficiency directly impacts the overall pipeline performance. The community has recently embraced the concept of Dataframes as the de-facto data structure for data representation and manipulation. However, the most widely used serial Dataframes today (R, pandas) experience performance limitations while working on even moderately large data sets. We believe that there is plenty of room for improvement by taking a look at this problem from a high-performance computing point of view. In a prior publication, we presented a set of parallel processing patterns for distributed dataframe operators and the reference runtime implementation, Cylon. In this paper, we are expanding on the initial concept by introducing a cost model for evaluating the said patterns. Furthermore, we evaluate the performance of Cylon on the ORNL Summit supercomputer.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2017

Hierarchical calibration and validation for modeling bench-scale solvent-based carbon capture. Part 1: Non-reactive physical mass transfer across the wetted wall column

A hierarchical model calibration and validation are proposed here for quantifying the confidence level of mass transfer prediction using a computational fluid dynamics (CFD) model, where the solvent-based carbon dioxide (CO 2 ) capture is simulated and the predicted results are compared to the corresponding bench-scale experimental data. Two unit problems with an increasing level of complexity are proposed to break down the complex physical/chemical processes of solvent-based CO 2 capture into relatively simpler problems to separate the effects of physical transport and chemical reaction. This paper focuses on the calibration and validation of the first unit problem, i.e., the CO 2 mass transfer across a falling ethanolamine (MEA) film in the absence of chemical reaction. This problem is investigated both experimentally and numerically using non-reactive nitrous oxide (N 2 O) as a surrogate for CO 2 . To capture motion of the gas-liquid interface, a volume of fluid method is employed with a one-fluid formulation to compute the mass transfer between the two phases. Parallel bench-scale experiments are designed and conducted to validate and calibrate the CFD models using a general Bayesian calibration approach. Two important transport parameters, Henry's constant and gas diffusivity, are calibrated to produce the posterior distributions, which will be used as input for the second unit problem to address the chemical absorption of CO 2 across the MEA falling film, where both mass transfer and chemical reaction are involved. Finally, mass transfer coefficients predicted by CFD are also compared with those predicted by the traditional/empirical correlations under both steady and wavy falling film conditions.

54 ENVIRONMENTAL SCIENCES↗

NASA NTRS1975

Evaluation of ERTS multispectral signatures in relation to ground control signatures using a nested-sampling approach

The author has identified the following significant results. Ground measured spectral signatures of wavelength bands matching ERTS MSS were collected using a radiometer at several Californian and Nevadan sites, and directly compared with similar data from ERTS CCTs. The comparison was tested at the highest possible spatial resolution for ERTS, using deconvoluted MSS data, and contrasted with that of ground measured spectra, originally from 1 meter squares. In the mobile traverses of the grassland sites, these one meter fields of view were integrated into eighty meter transects along the five km track across four major rock/soil types. Suitable software was developed to read the MSS CCT tapes, to shadeprint individual bands with user-determined greyscale stretching. Four new algorithms for unsupervised and supervised, normalized and unnormalized clustering were developed, into a program termed STANSORT. Parallel software allowed the field data to be calibrated, and by using concurrently continuously collected, upward- and downward-viewing, 4 band radiometers, bidirectional reflectances could be calculated.

Lyon, R. J. P.↗

DOE OSTI2024

High-performance data management for whole slide image analysis in digital pathology

When dealing with giga-pixel digital pathology in whole-slide imaging, a notable proportion of data records holds relevance during each analysis operation. For instance, when deploying an image analysis algorithm on whole-slide images (WSI), the computational bottleneck often lies in the input-output (I/O) system. This is particularly notable as patch-level processing introduces a considerable I/O load onto the computer system. However, this data management process could be further paralleled, given the typical independence of patch-level image processes across different patches. This paper details our endeavors in tackling this data access challenge by implementing the Adaptable IO System version 2 (ADIOS2). Our focus has been constructing and releasing a digital pathology-centric pipeline using ADIOS2, which facilitates streamlined data management across WSIs. Additionally, we’ve developed strategies aimed at curtailing data retrieval times. The performance evaluation encompasses two key scenarios: (1) a pure CPU-based image analysis scenario (“CPU scenario”), and (2) a GPU-based deep learning framework scenario (“GPU scenario”). Our findings reveal noteworthy outcomes. Under the CPU scenario, ADIOS2 showcases an impressive two-fold speed-up compared to the brute-force approach. In the GPU scenario, its performance stands on par with the cutting-edge GPU I/O acceleration framework, NVIDIA Magnum IO GPU Direct Storage (GDS). From what we know, this appears to be among the initial instances, if any, of utilizing ADIOS2 within the field of digital pathology. The source code has been made publicly available at https://github.com/hrlblab/adios.

Wang, Xiao↗

NASA NTRS1986

Mountain building processes in the Central Andes

False color composite images of the Thematic Mapper (TM) bands 5, 4, and 2 were examined to make visual interpretations of geological features. The use of the roam mode of image display with the International Imaging Systems (IIS) System 600 image processing package running on the IIS Model 75 was very useful. Several areas in which good comparisons with ground data existed, were examined in detail. Parallel to the visual approach, image processing methods are being developed which allow the complete use of the seven TM bands. The data was organized into easily accessible files and a visual cataloging of the quads (quarter TM scenes) with preliminary registration with the best available charts for the region. The catalog has proved to be a valuable tool for the rapid scanning of quads for a specific investigation. Integration of the data into a complete approach to the problems of uplift, deformation, and magnetism in relation to the Nazca-South American plate interaction is at an initial stage.

Bloom, A. L.↗

NASA NTRS1994

Analysis and Optimization of Parallel Software Pipeline Performance

Pipelining is a common strategy for extracting parallelism from a collection of independent computational tasks, each of which is spread among a number of processors and has an implied data dependence. When implemented on MIMD parallel computers with finite process interrupt times, pipeline algorithms suffer from slowdown--in addition to the expected pipeline fill time--due to a wave-like propagation of delays. This phenomenon, which has been observed experimentally using the performance monitoring system AIMS, is investigated analytically, and an optimal correction is derived to eliminate the wave. Efficiency increase through the correction is verified experimentally.

VanderWijngaart, Rob F.↗

NASA NTRS1995

The Effect of Interrupts on Software Pipeline Execution on Message-Passing Architectures

VanderWijngaart, Rob F.↗