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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 1,189 records · Page 66
All sourcesNASA NTRSDOE OSTI
DOE OSTI2019

A Parallel Graph Environment for Real-World Data Analytics Workflows

Economic competitiveness and national security depend increasingly on the insightful analysis of large data sets. The diversity of real-world data sources and analytic workflows impose challenging hardware and software requirements for parallel graph platforms. The irregular nature of graph methods is not supported well by the deep memory hierarchies of conventional distributed systems, requiring new processor and runtime system designs to tolerate memory and synchronization latencies. Moreover, the efficiency of relational table operations and matrix computations are not attainable when data is stored in common graph data structures. In this paper, we present HAGGLE, a high-performance, scalable data analytics platform. The platform’s hybrid data model supports a variety of distributed, thread-safe data structures, parallel programming constructs, and persistent and streaming data. An abstract runtime layer enables us to map the stack to conventional, distributed computer systems with accelerators. The runtime uses multithreading, active messages, and data aggregation to hide memory and synchronization latencies on large-scale systems.

Graph Analytics↗
DOE OSTI2022

Machine learning the metastable phase diagram of covalently bonded carbon

Abstract Conventional phase diagram generation involves experimentation to provide an initial estimate of the set of thermodynamically accessible phases and their boundaries, followed by use of phenomenological models to interpolate between the available experimental data points and extrapolate to experimentally inaccessible regions. Such an approach, combined with high throughput first-principles calculations and data-mining techniques, has led to exhaustive thermodynamic databases (e.g. compatible with the CALPHAD method), albeit focused on the reduced set of phases observed at distinct thermodynamic equilibria. In contrast, materials during their synthesis, operation, or processing, may not reach their thermodynamic equilibrium state but, instead, remain trapped in a local (metastable) free energy minimum, which may exhibit desirable properties. Here, we introduce an automated workflow that integrates first-principles physics and atomistic simulations with machine learning (ML), and high-performance computing to allow rapid exploration of the metastable phases to construct “metastable” phase diagrams for materials far-from-equilibrium. Using carbon as a prototypical system, we demonstrate automated metastable phase diagram construction to map hundreds of metastable states ranging from near equilibrium to far-from-equilibrium (400 meV/atom). We incorporate the free energy calculations into a neural-network-based learning of the equations of state that allows for efficient construction of metastable phase diagrams. We use the metastable phase diagram and identify domains of relative stability and synthesizability of metastable materials. High temperature high pressure experiments using a diamond anvil cell on graphite sample coupled with high-resolution transmission electron microscopy (HRTEM) confirm our metastable phase predictions. In particular, we identify the previously ambiguous structure of n -diamond as a cubic-analog of diaphite-like lonsdaelite phase.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
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↗
NASA NTRS1994

Nonlinear structural response using adaptive dynamic relaxation on a massively-parallel-processing system

A parallel adaptive dynamic relaxation (ADR) algorithm has been developed for nonlinear structural analysis. This algorithm has minimal memory requirements, is easily parallelizable and scalable to many processors, and is generally very reliable and efficient for highly nonlinear problems. Performance evaluations on single-processor computers have shown that the ADR algorithm is reliable and highly vectorizable, and that it is competitive with direct solution methods for the highly nonlinear problems considered. The present algorithm is implemented on the 512-processor Intel Touchstone DELTA system at Caltech, and it is designed to minimize the extent and frequency of interprocessor communication. The algorithm has been used to solve for the nonlinear static response of two and three dimensional hyperelastic systems involving contact. Impressive relative speedups have been achieved and demonstrate the high scalability of the ADR algorithm. For the class of problems addressed, the ADR algorithm represents a very promising approach for parallel-vector processing.

Oakley, David R.↗
NASA NTRS1977

Experimental measurement and computer analysis of stray radiation in a telescope

A description is presented of an experimental measurement system for the study of the stray radiation performance of a 50-cm aperture astronomical telescope model. The model incorporates a very high performance baffle system. To simulate the space environment of the actual orbiting telescope, the telescope model was placed in a vacuum chamber. The stray radiation source for the experiment was a ruby laser system. A photomultiplier tube was used for the detector. A minicomputer system was used to control the experiment and to gather and process the data. A computer program was used to model the telescope baffle system. Experimentally and analytically determined stray radiation attenuation data are compared.

Hunt, G. H.↗
NASA NTRS1992

Description of a prototype emission-transmission computed tomography imaging system

We have developed a prototype imaging system that can perform simultaneous x-ray transmission CT and SPECT phantom studies. This system employs a 23-element high-purity-germanium detector array. The detector array is coupled to a collimator with septa angled toward the focal spot of an x-ray tube. During image acquisition, the x-ray fan beam and the detector array move synchronously along an arc pivoted at the x-ray source. Multiple projections are obtained by rotating the object, which is mounted at the center of rotation of the system. The detector array and electronics can count up to 10(6) cps/element with sufficient energy-resolution to discriminate between x-rays at 100-120 kVp and gamma rays from 99mTc. We have used this device to acquire x-ray CT and SPECT images of a three-dimensional Hoffman brain phantom. The emission and transmission images may be superimposed in order to localize the emission image on the transmission map.

NASA Discipline Musculoskeletal↗
NASA NTRS2016

Utilizing Commercial Hardware and Open Source Computer Vision Software to Perform Motion Capture for Reduced Gravity Flight

Long duration space travel to Mars or to an asteroid will expose astronauts to extended periods of reduced gravity. Since gravity is not present to aid loading, astronauts will use resistive and aerobic exercise regimes for the duration of the space flight to minimize the loss of bone density, muscle mass and aerobic capacity that occurs during exposure to a reduced gravity environment. Unlike the International Space Station (ISS), the area available for an exercise device in the next generation of spacecraft is limited. Therefore, compact resistance exercise device prototypes are being developed. The NASA Digital Astronaut Project (DAP) is supporting the Advanced Exercise Concepts (AEC) Project, Exercise Physiology and Countermeasures (ExPC) project and the National Space Biomedical Research Institute (NSBRI) funded researchers by developing computational models of exercising with these new advanced exercise device concepts. To perform validation of these models and to support the Advanced Exercise Concepts Project, several candidate devices have been flown onboard NASAs Reduced Gravity Aircraft. In terrestrial laboratories, researchers typically have available to them motion capture systems for the measurement of subject kinematics. Onboard the parabolic flight aircraft it is not practical to utilize the traditional motion capture systems due to the large working volume they require and their relatively high replacement cost if damaged. To support measuring kinematics on board parabolic aircraft, a motion capture system is being developed utilizing open source computer vision code with commercial off the shelf (COTS) video camera hardware. While the systems accuracy is lower than lab setups, it provides a means to produce quantitative comparison motion capture kinematic data. Additionally, data such as required exercise volume for small spaces such as the Orion capsule can be determined. METHODS: OpenCV is an open source computer vision library that provides the ability to perform multi-camera 3 dimensional reconstruction. Utilizing OpenCV, via the Python programming language, a set of tools has been developed to perform motion capture in confined spaces using commercial cameras. Four Sony Video Cameras were intrinsically calibrated prior to flight. Intrinsic calibration provides a set of camera specific parameters to remove geometric distortion of the lens and sensor (specific to each individual camera). A set of high contrast markers were placed on the exercising subject (safety also necessitated that they be soft in case they become detached during parabolic flight); small yarn balls were used. Extrinsic calibration, the determination of camera location and orientation parameters, is performed using fixed landmark markers shared by the camera scenes. Additionally a wand calibration, the sweeping of the camera scenes simultaneously, was also performed. Techniques have been developed to perform intrinsic calibration, extrinsic calibration, isolation of the markers in the scene, calculation of marker 2D centroids, and 3D reconstruction from multiple cameras. These methods have been tested in the laboratory side-by-side comparison to a traditional motion capture system and also on a parabolic flight.

Biodynamics↗
DOE OSTI2026

Ultra-thick three-dimensional interpenetrating graphene electrode architectures for high volumetric density energy storage

For electrochemical energy storage, increasing the electrode thickness is an effective approach to achieving higher energy density from a given material. However, this often compromises ion transport, leading to diminished performance. Here, in this study, we present a novel platform for fabricating complex 3D interpenetrating electrode structures via photo-polymerization 3D printing, integrated with computational structural optimization for energy storage. The platform employs an acrylate resin system infused with graphene oxide (GO), enabling high-fidelity printing of optimized porous structures and facilitating efficient electron and ion transport in ultra-thick electrodes. The optimized 3D layouts substantially enhance energy and power densities compared to conventional configurations, ensuring superior material utilization and minimal ohmic losses. Supercapacitors fabricated using this approach achieved an exceptional energy density of 4.7 Wh L−1 at a power density of 1689.0 W L−1, surpassing traditional designs. This work underscores the transformative role of structural optimization in advancing electrochemical performance and establishes a versatile pathway for developing next-generation energy storage systems with exceptional efficiency and functionality.

Wang, Zhen [University of California, Berkeley, CA↗
DOE OSTI2018

Runtime Scheduling Policies for Distributed Graph Algorithms

In this paper we explore scheduling and runtime system support for unordered distributed graph computations that rely on optimistic (speculative) execution. Performance of such algorithms is impacted by two competing trends: the higher degree of parallelism enabled by optimistic execution in turn requires substantial runtime support. To address the potentially high overhead and scheduling complexity introduced by the runtime, we investigate customizable scheduling policies that augment the scheduler of the underlying runtime to adapt it to a specific graph application. We present several implementations of Distributed Control (DC), a data-driven unordered approach with work prioritization and demonstrate that customizable scheduling policies result in the most efficient implementation, outperforming the well-known -stepping Single-Source Shortest Paths (SSSP) and Jones-Plassmann vertex-coloring algorithms. We apply two scheduling techniques, flow control and adaptive frequency of network progress, which allow application-level control over the balance of domain work and the runtime work. Experimental results show the benefit of such application-aware scheduling for irregular distributed graph algorithms.

Firoz, Jesun S.↗
DOE OSTI2018

Advancing graph-based algorithms for predicting flow and transport in fractured rock

Discrete fracture network (DFN) models are a powerful alternative to continuum models for subsurface flow and transport simulations because they explicitly include fracture geometry and network topology, thereby allowing for better characterization of the latter's influence on flow and transport through fractured media. Recent advances in high performance computing have opened the door for flow and transport simulations in large explicit three-dimensional DFN, but this increase in model fidelity and system size comes at a huge computational cost because of the large number of mesh elements required to represent thousands of fractures (with sizes that can range several orders of magnitude, from mm to km). In most subsurface applications, fracture characteristics are only known statistically and numerous realizations are needed to bound uncertainty in flow and transport in the system, thereby exacerbating the computational burden. blackGraphs provide a simple and elegant way to characterize, query, and interrogate fracture network connectivity. We propose a DFN model reduction framework where various graph-representations are used in conjunction with high-fidelity DFN simulations to increase computational efficiency while retaining accuracy of key quantities of interest. The appropriate choice of a graph-representation, namely, which attributes of the DFN are to be represented as nodes and which ones as edges connecting those nodes, depends on the relevant scientific questions. We demonstrate that the proposed DFN model reduction framework provides an efficient means for DFN modeling through both system reduction of the DFN using graph-based properties and combining DFN and graph-based flow and transport simulations.

58 GEOSCIENCES↗
DOE OSTI2022

Newton trust-region methods with primary variable switching for simulating high temperature multiphase porous media flow

Coupling multiphase flow with energy transport due to high temperature heat sources introduces significant new challenges since boiling and condensation processes can lead to dry-out conditions with subsequent re-wetting. The transition between two-phase and single-phase behavior can require changes to the primary dependent variables adding discontinuities as well as extending constitutive nonlinear relations to extreme physical conditions. Practical simulations of large-scale engineered domains lead to Jacobian systems with a very large number of unknowns that must be solved efficiently using iterative methods in parallel on high-performance computers. Performance assessment of potential nuclear repositories, carbon sequestration sites and geothermal reservoirs can require numerous Monte-Carlo simulations to explore uncertainty in material properties, boundary conditions, and failure scenarios. Due to the numerical challenges, standard NR iteration may not converge over the range of required simulations and require more sophisticated optimization method like trust-region. In this study, we use the open-source simulator PFLOTRAN for the important practical problem of the safety assessment of future nuclear waste repositories in the U.S. DOE geologic disposal safety assessment Framework. The simulator applies the PETSc parallel framework and a backward Euler, finite volume discretization. We demonstrate failure of the conventional NR method and the success of trust-region modifications to Newton’s method for a series of test problems of increasing complexity. Trust-region methods essentially modify the Newton step size and direction under some circumstances where the standard NR iteration can cause the solution to diverge or oscillate. Furthermore, we show how the Newton Trust-Region method can be adapted for Primary Variable Switching (PVS) when the multiphase state changes due to boiling or condensation. The simulations with high-temperature heat sources which led to extreme nonlinear processes with many state changes in the domain did not converge with NR, but they do complete successfully with the trust-region methods modified for PVS. This implementation effectively decreased weeks of simulation time needing manual adjustments to complete a simulation down to a day. Finally, we show the strong scalability of the methods on a single node and multiple nodes in an HPC cluster.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2017

Three-Dimensional Dosimetric Validation of a Magnetic Resonance Guided Intensity Modulated Radiation Therapy System

Purpose: To validate the dosimetric accuracy of a commercially available magnetic resonance guided intensity modulated radiation therapy (MRgIMRT) system using a hybrid approach: 3-dimensional (3D) measurements and Monte Carlo calculations. Methods and Materials: We used PRESAGE radiochromic plastic dosimeters with remote optical computed tomography readout to perform 3D high-resolution measurements, following a novel remote dosimetry protocol. We followed the intensity modulated radiation therapy commissioning recommendations of American Association of Physicists in Medicine Task Group 119, adapted to incorporate 3D data. Preliminary tests (“AP” and “3D-Bands”) were delivered to 9.5-cm usable diameter cylindrical PRESAGE dosimeters to validate the treatment planning system (TPS) for nonmodulated deliveries; assess the sensitivity, uniformity, and rotational symmetry of the PRESAGE dosimeters; and test the robustness of the remote dosimetry protocol. Following this, 4 clinical MRgIMRT plans (“MultiTarget,” “Prostate,” “Head/Neck,” and “C-Shape”) were measured using 13-cm usable diameter PRESAGE dosimeters. For all plans, 3D-γ (3% or 3 mm global, 10% threshold) passing rates were calculated and 3D-γ maps were examined. Point doses were measured with an IBA-CC01 ionization chamber for validation of absolute dose. Finally, by use of an in-house-developed, GPU-accelerated Monte Carlo algorithm (gPENELOPE), we independently calculated dose for all 6 Task Group 119 plans and compared against the TPS. Results: For PRESAGE measurements, 3D-γ analysis yielded passing rates of 98.7%, 99.2%, 98.5%, 98.0%, 99.2%, and 90.7% for AP, 3D-Bands, MultiTarget, Prostate, Head/Neck, and C-Shape, respectively. Ion chamber measurements were within an average of 0.5% (±1.1%) from the TPS dose. Monte Carlo calculations demonstrated good agreement with the TPS, with a mean 3D-γ passing rate of 98.5% ± 1.9% using a stricter 2%/2-mm criterion. Conclusions: We have validated the dosimetric accuracy of a commercial MRgIMRT system using high-resolution 3D techniques. We have demonstrated for the first time that hybrid 3D remote dosimetry is a comprehensive and feasible approach to commissioning MRgIMRT. This may provide better sensitivity in error detection compared with standard 2-dimensional measurements and could be used when implementing complex new magnetic resonance guided radiation therapy technologies.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2024

Photoinduced Electron–Nuclear Dynamics of Fullerene and Its Monolayer Networks in Solvated Environments

The recently synthesized monolayer fullerene network in a quasi-hexagonal phase (qHP-C 60 ) exhibits superior electron mobility and optoelectronic properties compared to molecular fullerene (C 60 ), making it highly promising for a variety of applications. However, the microscopic carrier dynamics of qHP-C 60 remain unclear, particularly in realistic environments, which are of significant importance for applications in optoelectronic devices. Unfortunately, traditional ab initio methods are prohibitive for capturing the real-time carrier dynamics of such large systems due to their high computational cost. In this work, we present the first real-time electron–nuclear dynamics study of qHP-C 60 using velocity-gauge density functional tight binding, which enables us to perform several picoseconds of excited-state electron–nuclear dynamics simulations for nanoscale systems with periodic boundary conditions. When applied to C 60 , qHP-C 60 , and their solvated counterparts, we demonstrate that water/moisture significantly increases the electron–hole recombination time in C 60 but has little impact on qHP-C 60 . Our excited-state electron–nuclear dynamics calculations show that qHP-C 60 is extremely unique and enable exploration of time-resolved dynamics for understanding excited-state processes of large systems in complex, solvated environments.

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

Scidac-Data: Enabling Data Driven Modeling of Exascale Computing

Here, the SciDAC-Data project is a DOE-funded initiative to analyze and exploit two decades of information and analytics that have been collected by the Fermilab data center on the organization, movement, and consumption of high energy physics (HEP) data. The project analyzes the analysis patterns and data organization that have been used by NOvA, MicroBooNE, MINERvA, CDF, D0, and other experiments to develop realistic models of HEP analysis workflows and data processing. The SciDAC-Data project aims to provide both realistic input vectors and corresponding output data that can be used to optimize and validate simulations of HEP analysis. These simulations are designed to address questions of data handling, cache optimization, and workflow structures that are the prerequisites for modern HEP analysis chains to be mapped and optimized to run on the next generation of leadership-class exascale computing facilities. We present the use of a subset of the SciDAC-Data distributions, acquired from analysis of approximately 71,000 HEP workflows run on the Fermilab data center and corresponding to over 9 million individual analysis jobs, as the input to detailed queuing simulations that model the expected data consumption and caching behaviors of the work running in high performance computing (HPC) and high throughput computing (HTC) environments. In particular we describe how the Sequential Access via Metadata (SAM) data-handling system in combination with the dCache/Enstore-based data archive facilities has been used to develop radically different models for analyzing the HEP data. We also show how the simulations may be used to assess the impact of design choices in archive facilities.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2022

Bridging Python to Silicon: The SODA Toolchain

Systems performing scientific computing, data analysis, and machine learning tasks have a growing demand for application-specific accelerators that can provide high computational performance while meeting strict size and power requirements. However, the algorithms and applications that need to be accelerated are evolving at a rate that is incompatible with manual design processes based on hardware description languages. Agile hardware design tools based on compiler techniques can help by quickly producing an application-specific integrated circuit (ASIC) accelerator starting from a high-level algorithmic description. Here, we present the software-defined accelerator (SODA) synthesizer, a modular and open-source hardware compiler that provides automated end-to-end synthesis from high-level software frameworks to ASIC implementation, relying on multilevel representations to progressively lower and optimize the input code. Our approach does not require the application developer to write any register-transfer level code, and it is able to reach up to 364 giga floating point operations per second (GFLOPS)/W efficiency (32-bit precision) on typical convolutional neural network operators.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS1975

Analytical evaluation of ILM sensors. Volume 2: Appendices

The applicability of various sensing concepts to independent landing monitor systems was analyzed. Microwave landing system MLS accuracy requirements are presented along with a description of MLS airborne equipment. Computer programs developed during the analysis are described and include: a mathematical computer model for use in the performance assessment of reconnaissance sensor systems; a theoretical formulation of electromagnetic scattering to generate data at high incidence angles; atmospheric attenuation of microwaves; and microwave radiometry, programs

Kirk, R. J.↗
NASA NTRS1982

Conceptual design and cost analysis of hydraulic output unit for 15 kW free-piston Stirling engine

A long-life hydraulic converter with unique features was conceptually designed to interface with a specified 15 kW(e) free-piston Stirling engine in a solar thermal dish application. Hydraulic fluid at 34.5 MPa (5000 psi) is produced to drive a conventional hydraulic motor and rotary alternator. Efficiency of the low-maintenance converter design was calculated at 93.5% for a counterbalanced version and 97.0% without the counterbalance feature. If the converter were coupled to a Stirling engine with design parameters more typcial of high-technology Stirling engines, counterbalanced converter efficiency could be increased to 99.6%. Dynamic computer simulation studies were conducted to evaluate performance and system sensitivities. Production costs of the complete Stirling hydraulic/electric power system were evaluated at $6506 which compared with $8746 for an alternative Stirling engine/linear alternator system.

White, M. A.↗
NASA NTRS1990

Data quality analysis at the National Transonic Facility

The data quality analysis program that was developed at Langley Research Center's National Transonic Facility is described. The program provides a computer driven systematic analysis of data taken during calibrations of the high speed digital data acquisition system. Five distinct checks that are performed on the calibration data are outlined. The five checks are for non-linearity, noise, short term drift, long term drift, and the proper functioning of the calibrator. The program has established a standard set of evaluation guidelines.

Stewart, Pamela N.↗