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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 1,279 records · Page 71
All sourcesNASA NTRSDOE OSTI
NASA NTRS1994

Parallel Computational Fluid Dynamics: Current Status and Future Requirements

One or the key objectives of the Applied Research Branch in the Numerical Aerodynamic Simulation (NAS) Systems Division at NASA Allies Research Center is the accelerated introduction of highly parallel machines into a full operational environment. In this report we discuss the performance results obtained from the implementation of some computational fluid dynamics (CFD) applications on the Connection Machine CM-2 and the Intel iPSC/860. We summarize some of the experiences made so far with the parallel testbed machines at the NAS Applied Research Branch. Then we discuss the long term computational requirements for accomplishing some of the grand challenge problems in computational aerosciences. We argue that only massively parallel machines will be able to meet these grand challenge requirements, and we outline the computer science and algorithm research challenges ahead.

Simon, Horst D.↗
DOE OSTI2015

SU-E-T-756: Tissue Inhomogeneity Corrections in Intra-Operative Radiotherapy

Purpose: Investigate the impact of tissue inhomogeneities on dose distributions produced by low-energy X-rays in intra-operative radiotherapy (IORT). Methods: A 50-kV INTRABEAM X-ray device with superficial (Flat and Surface) applicators was commissioned at our institution. For each applicator, percent depth-dose (PDD), dose-profiles (DP) and output factors (OF) were obtained. Calibrated GaFchromic (EBT3) films were used to measure dose distributions in solid water phantom at various depths (2, 5, 10, and 15 mm). All recommended precautions for film-handling, film-exposure and scanning were observed. The effects of tissue inhomogeneities on dose distributions were examined by placing air-cavities and bone and tissue equivalent materials of different density (ρ), atomic number (Z), and thickness (t = 0–4mm) between applicator and film detector. All inhomogeneities were modeled as a cylindrical cavity (diameter 25 mm). Treatment times were calculated to deliver 1Gy dose at 5mm depth. Film results were verified by repeat measurements with a thin-window parallel plate ion-chamber (PTW 34013A) in a water tank. Results: For a Flat-4cm applicator, the measured dose rate at 5mm depth in solid water was 0.35 Gy/min. Introduction of a cylindrical air-cavity resulted in an increased dose past the inhomogeneity. Compared to tissue equivalent medium, dose enhancement due to 1mm, 2mm, 3mm and 4mm air cavities was 10%, 16%, 24%, and 35% respectively. X-ray attenuation by 2mm thick cortical bone resulted in a significantly large (58%) dose decrease. Conclusion: IORT dose calculations assume homogeneous tissue equivalent medium. However, soft X-rays are easily affected by non-tissue equivalent materials. The results of this study may be used to estimate and correct IORT dose delivered in the presence of tissue inhomogeneities.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2019

Reverse-Mode Algorithmic Differentiation of an OpenMP-Parallel Compressible Flow Solver

y Reverse-mode algorithmic differentiation (AD) is an established method for obtaining adjoint derivatives of computer simulation applications. In computational fluid dynamics (CFD), adjoint derivatives of a cost function output such as drag or lift with respect to design parameters such as surface coordinates or geometry control points are a key ingredient for shape optimization, uncertainty quantification and flow control. The computational cost of CFD applications and their derivatives makes it essential to use high-performance computing hardware efficiently, including multi- and many-core architectures. Nevertheless, OpenMP is not supported in most AD tools, and previously shown methods achieve poor scalability of the derivative code. We present the AD of an OpenMP-parallelized finite volume compressible flow solver for unstructured meshes. Our approach enables us to reuse the parallelization of the original code in the computation of adjoint derivatives. The method works by identifying code segments that can be differentiated in reverse-mode without changing their memory access pattern. The OpenMP parallelization is integrated into the derivative code during the build process in a way that is robust to modifications of the original code and independent of the OpenMP support of the differentiation tool. We show the scalability of our adjoint CFD solver on test cases ranging from thousands to millions of finite volume mesh cells on CPUs with up to 16 threads as well as on an Intel XeonPhi card with 236 threads. We demonstrate that our approach is more practical to implement for production-sized CFD codes and produces more efficient adjoint derivative code than previously shown AD methods.

Huckelheim, Jan↗
NASA NTRS2023

Cloud Computing Option for Modeling the Debris Environment

NASA’s Digital Transformation Initiative aims to promote the agency’s adoption of current and evolving digital technologies. Through agency-wide collaboration with other NASA teams, the Office of Safety and Mission Assurance (OSMA) has directed the Orbital Debris Program Office and the Meteoroid Environment Office to integrate cloud computing technologies into their publicly released software models: the Orbital Debris Engineering Model (ORDEM) and the Meteoroid Engineering Model (MEM). Decoupling the user interface from the backend processor was key for the software packages to run on a cloud computing framework. Benefits to this design include horizontal scaling of computing resources, user authentication and authorization, and automated deployment. Both models are hosted on a cloud computing platform supported by the NASA authorized IT security and compliance framework. This paper focuses on the new ORDEM web application, which includes the current features of the publicly released ORDEM software with an upgraded frontend design, although parallels between ORDEM and MEM are also discussed. The underlying ORDEM processor is run on a cloud container, allowing the user to run multiple spacecraft and telescope/radar mode simulations. Features exclusive to the ORDEM web application, such as importing multiple TLEs, auto-generated plotting, and the ability to check runtime progress are discussed. Comparisons between the current ORDEM software and the web application are summarized.

Andrew Vavrin↗
DOE OSTI2022

Spectral quadrature for the first principles study of crystal defects: Application to magnesium

In this work, we present an accurate and efficient finite-difference formulation and parallel implementation of Kohn-Sham Density (Operator) Functional Theory (DFT) for non periodic systems embedded in a bulk environment. Specifically, employing non-local pseudopotentials, local reformulation of electrostatics, and truncation of the spatial Kohn-Sham Hamiltonian, and the Linear Scaling Spectral Quadrature method to solve for the pointwise electronic fields in real-space and the non-local component of the atomic force, we develop a parallel finite difference framework suitable for distributed memory computing architectures to simulate non-periodic systems embedded in a bulk environment. Choosing examples from magnesium-aluminum alloys, we first demonstrate the convergence of energies and forces with respect to spectral quadrature polynomial order, and the width of the spatially truncated Hamiltonian. Next, we demonstrate the parallel scaling of our framework, and show that the computation time and memory scale linearly with respect to the number of atoms. Next, we use the developed framework to simulate isolated point defects and their interactions in magnesium-aluminum alloys. Our findings conclude that the binding energies of divacancies, Al solute-vacancy and two Al solute atoms are anisotropic and are dependent on cell size. Furthermore, the binding is favorable in all three cases.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2016

Fenix, A Fault Tolerant Programming Framework for MPI Applications

Fenix provides APIs to allow the users to add fault tolerance capability to MPI-based parallel programs in a transparent manner. Fenix-enabled programs can run through process failures during program execution using a pool of spare processes accommodated by Fenix.

Gamel, Marc↗
NASA NTRS1985

Parallel VLSI Architecture

Fermat number transformation convolutes two digital data sequences. Very-large-scale integration (VLSI) applications, such as image and radar signal processing, X-ray reconstruction, and spectrum shaping, linear convolution of two digital data sequences of arbitrary lenghts accomplished using Fermat number transform (ENT).

Truong, T. K.↗
DOE OSTI2018

Exploiting Hierarchical Parallelism in an Astrophysical Equation of State Using OpenACC and OpenMP

Modeling thermonuclear supernovae is a premier application for leadership-class supercomputers and requires multi-physics simulation codes to capture hydrodynamics, nuclear burning, gravitational forces, etc. As a nuclear detonation burns through the stellar material, it also increases the temperature. An equation of state (EOS) is then required to determine, for example, the new pressure associated with this temperature increase. In fact, an EOS is needed after thermodynamic conditions are changed by any physics routines. This means it is called many times throughout a simulation, requiring the need for a fast EOS implementation. Fortunately, these calculations can be performed independently during each time step, so the work can be offloaded to GPUs. Using results from the IBM/NVIDIA early test system (Summitdev, a precursor to the upcoming Summit supercomputer) at Oak Ridge National Laboratory, we describe a hybrid OpenMP implementation with offloaded work to GPUs. We compare performance results between the two implementations, with a discussion of some of the currently available features of OpenACC and OpenMP 4.5.

Messer, Bronson↗
DOE OSTI2017

A Pervasive Parallel Processing Framework for Data Visualization and Analysis at Extreme Scale

Most of today’s visualization libraries and applications are based off of what is known today as the visualization pipeline. In the visualization pipeline model, algorithms are encapsulated as “filtering” components with inputs and outputs. These components can be combined by connecting the outputs of one filter to the inputs of another filter. The visualization pipeline model is popular because it provides a convenient abstraction that allows users to combine algorithms in powerful ways. Unfortunately, the visualization pipeline cannot run effectively on exascale computers. Experts agree that the exascale machine will comprise processors that contain many cores. Furthermore, physical limitations will prevent data movement in and out of the chip (that is, between main memory and the processing cores) from keeping pace with improvements in overall compute performance. To use these processors to their fullest capability, it is essential to carefully consider memory access. This is where the visualization pipeline fails. Each filtering component in the visualization library is expected to take a data set in its entirety, perform some computation across all of the elements, and output the complete results. The process of iterating over all elements must be repeated in each filter, which is one of the worst possible ways to traverse memory when trying to maximize the number of executions per memory access. This project investigates a new type of visualization framework that exhibits a pervasive parallelism necessary to run on exascale machines. Our framework achieves this by defining algorithms in terms of functors, which are localized, stateless operations. Functors can be composited in much the same way as filters in the visualization pipeline. But, functors’ design allows them to be concurrently running on massive amounts of lightweight threads. Only with such fine-grained parallelism can we hope to fill the billions of threads we expect will be necessary for efficient computation on an exascale computer. This project concludes with a functional prototype containing pervasively parallel algorithms that perform demonstratively well on many-core processors. These algorithms are fundamental for performing data analysis and visualization at extreme scale.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS2013

NASA Tech Briefs, June 2013

Topics include: Cloud Absorption Radiometer Autonomous Navigation System - CANS, Software Method for Computed Tomography Cylinder Data Unwrapping, Re-slicing, and Analysis, Discrete Data Qualification System and Method Comprising Noise Series Fault Detection, Simple Laser Communications Terminal for Downlink from Earth Orbit at Rates Exceeding 10 Gb/s, Application Program Interface for the Orion Aerodynamics Database, Hyperspectral Imager-Tracker, Web Application Software for Ground Operations Planning Database (GOPDb) Management, Software Defined Radio with Parallelized Software Architecture, Compact Radar Transceiver with Included Calibration, Software Defined Radio with Parallelized Software Architecture, Phase Change Material Thermal Power Generator, The Thermal Hogan - A Means of Surviving the Lunar Night, Micromachined Active Magnetic Regenerator for Low-Temperature Magnetic Coolers, Nano-Ceramic Coated Plastics, Preparation of a Bimetal Using Mechanical Alloying for Environmental or Industrial Use, Phase Change Material for Temperature Control of Imager or Sounder on GOES Type Satellites in GEO, Dual-Compartment Inflatable Suitlock, Modular Connector Keying Concept, Genesis Ultrapure Water Megasonic Wafer Spin Cleaner, Piezoelectrically Initiated Pyrotechnic Igniter, Folding Elastic Thermal Surface - FETS, Multi-Pass Quadrupole Mass Analyzer, Lunar Sulfur Capture System, Environmental Qualification of a Single-Crystal Silicon Mirror for Spaceflight Use, Planar Superconducting Millimeter-Wave/Terahertz Channelizing Filter, Qualification of UHF Antenna for Extreme Martian Thermal Environments, Ensemble Eclipse: A Process for Prefab Development Environment for the Ensemble Project, ISS Live!, Space Operations Learning Center (SOLC) iPhone/iPad Application, Software to Compare NPP HDF5 Data Files, Planetary Data Systems (PDS) Imaging Node Atlas II, Automatic Calibration of an Airborne Imaging System to an Inertial Navigation Unit, Translating MAPGEN to ASPEN for MER, Support Routines for In Situ Image Processing, and Semi-Supervised Eigenbasis Novelty Detection.

Source record↗
DOE OSTI2015

Influence of Domain Width on Vortex Nucleation in Superconductor/Ferromagnet Hybrid Structures.

We have investigated the effect of spatially inhomogenous magnetic fields on vortex nucleation in magnetically coupled superconductor/ferromagnet hybrid structures. Using low-temperature scanning tunneling microscopy and spectroscopy (LT-STM/STS) we have studied Pb/[Co-Pd] systems with slightly inhomogeneous magnetic domain width throughout the sample. Visualization of the underlying magnetic template structure is achieved through field dependent conductance maps. In the case of zero applied fields, these maps reveal the absence of vortices below a threshold domain width. At those locations with insufficient domain width to support generation of vortices in zero applied fields, nucleation can be restored through the application of an external magnetic field, with vortices nucleating above the domain parallel to the external field. For the magnetic domain width studied in this work, local tunneling spectroscopy reveals uniform superconducting critical temperature as a function of location, despite of local differences in the stray field experienced by the superconductor.

Low Temperature Superconductors↗
DOE OSTI2022

SPACE: 3D parallel solvers for Vlasov-Maxwell and Vlasov-Poisson equations for relativistic plasmas with atomic transformations

A parallel, relativistic, three-dimensional particle-in-cell code SPACE has been developed for the simulation of electromagnetic fields, relativistic particle beams, and plasmas. In addition to the standard second-order Particle-in-Cell (PIC) algorithm, SPACE includes efficient novel algorithms to resolve atomic physics processes such as multi-level ionization of plasma atoms, recombination, and electron attachment to dopants in dense neutral gases. SPACE also contains a highly adaptive particle-based method, called Adaptive Particle-in-Cloud (AP-Cloud), for solving the Vlasov-Poisson problems. It eliminates the traditional Cartesian mesh of PIC and replaces it with an adaptive octree data structure. The code's algorithms, structure, capabilities, parallelization strategy, and performance have been discussed. Additionally, typical examples of SPACE applications to accelerator science and engineering problems are described.

43 PARTICLE ACCELERATORS↗
DOE OSTI2015

Oxygen transport properties estimation by classical trajectory–direct simulation Monte Carlo

Coupling direct simulation Monte Carlo (DSMC) simulations with classical trajectory calculations is a powerful tool to improve predictive capabilities of computational dilute gas dynamics. The considerable increase in computational effort outlined in early applications of the method can be compensated by running simulations on massively parallel computers. In particular, Graphics Processing Unit acceleration has been found quite effective in reducing computing time of classical trajectory (CT)-DSMC simulations. The aim of the present work is to study dilute molecular oxygen flows by modeling binary collisions, in the rigid rotor approximation, through an accurate Potential Energy Surface (PES), obtained by molecular beams scattering. The PES accuracy is assessed by calculating molecular oxygen transport properties by different equilibrium and non-equilibrium CT-DSMC based simulations that provide close values of the transport properties. Comparisons with available experimental data are presented and discussed in the temperature range 300–900 K, where vibrational degrees of freedom are expected to play a limited (but not always negligible) role.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2016

Molecular dynamics study of mechanical properties of carbon nanotube reinforced aluminum composites

Atomistic simulations were conducted to estimate the effect of the carbon nanotube (CNT) reinforcement on the mechanical behavior of CNT-reinforced aluminum (Al) nanocomposite. The periodic system of CNT-Al nanocomposite was built and simulated using molecular dynamics (MD) software LAMMPS (Large-scale Atomic/Molecular Massively Parallel Simulator). The mechanical properties of the nanocomposite were investigated by the application of uniaxial load on one end of the representative volume element (RVE) and fixing the other end. The interactions between the atoms of Al were modeled using embedded atom method (EAM) potentials, whereas Adaptive Intermolecular Reactive Empirical Bond Order (AIREBO) potential was used for the interactions among carbon atoms and these pair potentials are coupled with the Lennard-Jones (LJ) potential. The results show that the incorporation of CNT into the Al matrix can increase the Young’s modulus of the nanocomposite substantially. In the present case, i.e. for approximately 9 with % reinforcement of CNT can increase the axial Young’s modulus of the Al matrix up to 77 % as compared to pure Al.

77 NANOSCIENCE AND NANOTECHNOLOGY↗
DOE OSTI2021

Optimizing Error-Bounded Lossy Compression for Scientific Data on GPUs

Error-bounded lossy compression is a critical technique for significantly reducing scientific data volumes. With ever-emerging heterogeneous high-performance computing (HPC) architecture, GPU-accelerated error-bounded compressors (such as CUSZ and cuZFP) have been developed. However, they suffer from either low performance or low compression ratios. To this end, we propose CUSZ+ to target both high compression ratios and throughputs. We identify that data sparsity and data smoothness are key factors for high compression throughputs. Our key contributions in this work are fourfold: (1) We propose an efficient compression workflow to adaptively perform run-length encoding and/or variable-length encoding. (2) We derive Lorenzo reconstruction in decompression as multidimensional partial-sum computation and propose a fine-grained Lorenzo reconstruction algorithm for GPU architectures. (3) We carefully optimize each of CUSZ kernels by leveraging state-of-the-art CUDA parallel primitives. (4) We evaluate CUSZ+ using seven real-world HPC application datasets on V100 and A100 GPUs. Experiments show CUSZ+ improves the compression throughputs and ratios by up to 18.4x and 5.3x, respectively, over CUSZ on the tested datasets.

Tian, Jiannan↗
DOE OSTI2015

Porting Ordinary Applications to Blue Gene/Q Supercomputers

Efficiently porting ordinary applications to Blue Gene/Q supercomputers is a significant challenge. Codes are often originally developed without considering advanced architectures and related tool chains. Science needs frequently lead users to want to run large numbers of relatively small jobs (often called many-task computing, an ensemble, or a workflow), which can conflict with supercomputer configurations. In this paper, we discuss techniques developed to execute ordinary applications over leadership class supercomputers. We use the high-performance Swift parallel scripting framework and build two workflow execution techniques-sub-jobs and main-wrap. The sub-jobs technique, built on top of the IBM Blue Gene/Q resource manager Cobalt's sub-block jobs, lets users submit multiple, independent, repeated smaller jobs within a single larger resource block. The main-wrap technique is a scheme that enables C/C++ programs to be defined as functions that are wrapped by a high-performance Swift wrapper and that are invoked as a Swift script. We discuss the needs, benefits, technicalities, and current limitations of these techniques. We further discuss the real-world science enabled by these techniques and the results obtained.

Maheshwari, Ketan C.↗
DOE OSTI2016

IMPACC: A Tightly Integrated MPI+OpenACC Framework Exploiting Shared Memory Parallelism

We propose IMPACC, an MPI+OpenACC framework for heterogeneous accelerator clusters. IMPACC tightly integrates MPI and OpenACC, while exploiting the shared memory parallelism in the target system. IMPACC dynamically adapts the input MPI+OpenACC applications on the target heterogeneous accelerator clusters to fully exploit target system-specific features. IMPACC provides the programmers with the unified virtual address space, automatic NUMA-friendly task-device mapping, efficient integrated communication routines, seamless streamlining of asynchronous executions, and transparent memory sharing. We have implemented IMPACC and evaluated its performance using three heterogeneous accelerator systems, including Titan supercomputer. Results show that IMPACC can achieve easier programming, higher performance, and better scalability than the current MPI+OpenACC model.

Kim, Jungwon↗
DOE OSTI2017

Supplemental Information for New York State Standardized Interconnection Requirements

This document is intended to aid in the understanding and application of the New York State Standardized Interconnection Requirements (SIR) and Application Process for New Distributed Generators 5 MW or Less Connected in Parallel with Utility Distribution Systems, and it aims to provide supplemental information and discussion on selected topics relevant to the SIR. This guide focuses on technical issues that have to date resulted in the majority of utility findings within the context of interconnecting photovoltaic (PV) inverters. This guide provides background on the overall issue and related mitigation measures for selected topics, including substation backfeeding, anti-islanding and considerations for monitoring and controlling distributed energy resources (DER).

24 POWER TRANSMISSION AND DISTRIBUTION↗