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At least 1,423 records · Page 79

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NASA NTRS1925

Pressure Distribution on Joukowski Wings and Graphic Construction of Joukowski Wings

In the first article, in connection with a lecture on the hydrodynamic basis of flight and the potential flow about a Joukowski wing, the pressure distribution on several wings is computed and plotted. The diagrams of the pressure distributions are presented accompanied with a qualitative discussion of the pressure distribution. In the second article, the the cross-sectional outline (or profile) a Joukowski wing are plotted.

PRESSURE DISTRIBUTION - AIRFOILS - JOUKOWSKI↗

NASA NTRS1996

An MPI-IO Interface to HPSS

This paper describes an implementation of the proposed MPI-IO standard for parallel I/O. Our system uses third-party transfer to move data over an external network between the processors where it is used and the I/O devices where it resides. Data travels directly from source to destination, without the need for shuffling it among processors or funneling it through a central node. Our distributed server model lets multiple compute nodes share the burden of coordinating data transfers. The system is built on the High Performance Storage System (HPSS), and a prototype version runs on a Meiko CS-2 parallel computer.

Parallel Processing↗

NASA NTRS1994

Wing-Body Aeroelasticity Using Finite-Difference Fluid/Finite-Element Structural Equations on Parallel Computers

In recent years significant advances have been made for parallel computers in both hardware and software. Now parallel computers have become viable tools in computational mechanics. Many application codes developed on conventional computers have been modified to benefit from parallel computers. Significant speedups in some areas have been achieved by parallel computations. For single-discipline use of both fluid dynamics and structural dynamics, computations have been made on wing-body configurations using parallel computers. However, only a limited amount of work has been completed in combining these two disciplines for multidisciplinary applications. The prime reason is the increased level of complication associated with a multidisciplinary approach. In this work, procedures to compute aeroelasticity on parallel computers using direct coupling of fluid and structural equations will be investigated for wing-body configurations. The parallel computer selected for computations is an Intel iPSC/860 computer which is a distributed-memory, multiple-instruction, multiple data (MIMD) computer with 128 processors. In this study, the computational efficiency issues of parallel integration of both fluid and structural equations will be investigated in detail. The fluid and structural domains will be modeled using finite-difference and finite-element approaches, respectively. Results from the parallel computer will be compared with those from the conventional computers using a single processor. This study will provide an efficient computational tool for the aeroelastic analysis of wing-body structures on MIMD type parallel computers.

Byun, Chansup↗

NASA NTRS1977

Computer programs for the interpretation of low resolution mass spectra: Program for calculation of molecular isotopic distribution and program for assignment of molecular formulas

Two FORTRAN computer programs for the interpretation of low resolution mass spectra were prepared and tested. One is for the calculation of the molecular isotopic distribution of any species from stored elemental distributions. The program requires only the input of the molecular formula and was designed for compatability with any computer system. The other program is for the determination of all possible combinations of atoms (and radicals) which may form an ion having a particular integer mass. It also uses a simplified input scheme and was designed for compatability with any system.

Miller, R. A.↗

DOE OSTI2024

The reproduction number and its probability distribution for stochastic viral dynamics

We consider stochastic models of individual infected cells. The reproduction number, R, is understood as a random variable representing the number of new cells infected by one initial infected cell in an otherwise susceptible (target cell) population. Variability in R results partly from heterogeneity in the viral burst size (the number of viral progeny generated from an infected cell during its lifetime), which depends on the distribution of cellular lifetimes and on the mechanism of virion release. We analyse viral dynamics models with an eclipse phase: the period of time after a cell is infected but before it is capable of releasing virions. The duration of the eclipse, or the subsequent infectious, phase is non-exponential, but composed of stages. We derive the probability distribution of the reproduction number for these viral dynamics models, and show it is a negative binomial distribution in the case of constant viral release from infectious cells, and under the assumption of an excess of target cells. In a deterministic model, the ultimate in-host establishment or extinction of the viral infection depends entirely on whether the mean reproduction number is greater than, or less than, one, respectively. Here, the probability of extinction is determined by the probability distribution of R, not simply its mean value. In particular, we show that in some cases the probability of infection is not an increasing function of the mean reproduction number.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2021

HTR-1.3 solver: Predicting electrified combustion using the hypersonic task-based research solver

Here this manuscript presents an updated open-source version of the Hypersonics Task-based Research (HTR) solver. The solver, whose main features are presented in Di Renzo et al. (2020) and Di Renzo & Pirozzoli (2021), is designed for direct numerical simulation of reacting flows at high Reynolds numbers. This new version extends the applications of the HTR solver to turbulent combustion in the presence of external electric fields. In particular, a new distributed Poisson solver compatible with heterogeneous architectures has been incorporated in the algorithm to compute the electric potential distribution in bi-periodic configurations. The drift fluxes of the electrically charged species are now included in the transport equations using a targeted essentially non-oscillatory scheme. A verification of these new features of the solver is provided using one-dimensional burner stabilized flames, whereas a three dimensional turbulent flame is utilized to discuss the scalability of the proposed numerical tool.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

DOE OSTI2024

A Review of Edge Computing Technology and Its Applications in Power Systems

Recent advancements in network-connected devices have led to a rapid increase in the deployment of smart devices and enhanced grid connectivity, resulting in a surge in data generation and expanded deployment to the edge of systems. Classic cloud computing infrastructures are increasingly challenged by the demands for large bandwidth, low latency, fast response speed, and strong security. Therefore, edge computing has emerged as a critical technology to address these challenges, gaining widespread adoption across various sectors. This paper introduces the advent and capabilities of edge computing, reviews its state-of-the-art architectural advancements, and explores its communication techniques. A comprehensive analysis of edge computing technologies is also presented. Furthermore, this paper highlights the transformative role of edge computing in various areas, particularly emphasizing its role in power systems. It summarizes edge computing applications in power systems that are oriented from the architectures, such as power system monitoring, smart meter management, data collection and analysis, resource management, etc. Additionally, the paper discusses the future opportunities of edge computing in enhancing power system applications.

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2021

Recommendations for Distributed Energy Resource Patching

While computer systems, software applications, and operational technology (OT)/Industrial Control System (ICS) devices are regularly updated through automated and manual processes, there are several unique challenges associated with distributed energy resource (DER) patching. Millions of DER devices from dozens of vendors have been deployed in home, corporate, and utility network environments that may or may not be internet-connected. These devices make up a growing portion of the electric power critical infrastructure system and are expected to operate for decades. During that operational period, it is anticipated that critical and noncritical firmware patches will be regularly created to improve DER functional capabilities or repair security deficiencies in the equipment. The SunSpec/Sandia DER Cybersecurity Workgroup created a Patching Subgroup to investigate appropriate recommendations for the DER patching, holding fortnightly meetings for more than nine months. The group focused on DER equipment, but the observations and recommendations contained in this report also apply to DERMS tools and other OT equipment used in the end-to-end DER communication environment. The group found there were many standards and guides that discuss firmware lifecycles, patch and asset management, and code-signing implementations, but did not singularly cover the needs of the DER industry. This report collates best practices from these standards organizations and establishes a set of best practices that may be used as a basis for future national or international patching guides or standards.

97 MATHEMATICS AND COMPUTING↗

NASA NTRS1993

Probability of lensing magnification by cosmologically distributed galaxies

We present the analytical formulae for computing the magnification probability caused by cosmologically distributed galaxies. The galaxies are assumed to be singular, truncated-isothermal spheres without both evolution and clustering in redshift. We find that, for a fixed total mass, extended galaxies produce a broader shape in the magnification probability distribution and hence are less efficient as gravitational lenses than compact galaxies. The high-magnification tail caused by large galaxies is well approximated by an A exp -3 form, while the tail by small galaxies is slightly shallower. The mean magnification as a function of redshift is, however, found to be independent of the size of the lensing galaxies. In terms of the flux conservation, our formulae for the isothermal galaxy model predict a mean magnification to within a few percent with the Dyer-Roeder model of a clumpy universe.

Pei, Yichuan C.↗

NASA NTRS2004

Plasma Dispersion Function for the Kappa Distribution

The plasma dispersion function is computed for a homogeneous isotropic plasma in which the particle velocities are distributed according to a Kappa distribution. An ordinary differential equation is derived for the plasma dispersion function and it is shown that the solution can be written in terms of Gauss' hypergeometric function. Using the extensive theory of the hypergeometric function, various mathematical properties of the plasma dispersion function are derived including symmetry relations, series expansions, integral representations, and closed form expressions for integer and half-integer values of K.

Podesta, John J.↗

NASA NTRS1991

The chemical composition of the dust-free Martian atmosphere - Preliminary results of a two-dimensional model

This paper describes a two-dimensional model of the Martian atmosphere, in which chemical, radiative and dynamical processes are treated interactively. The model is developed for a carbon dioxide-hydrogen-oxygen-nitrogen atmosphere and provides estimates of concentrations for 19 chemical species. The dynamical equations are expressed in the transformed Eulerian coordinates. The wave driving and eddy mixing coefficients resulting from gravity and Rossby wave absorption are computed consistently with the evolving distribution of the mean zonal wind. The net diabatic heating/cooling rate is derived from a detailed radiative scheme including the contributions of CO2, O3, H2O and O2, and is computed consistently with the calculated distribution of temperature and trace species quantities. The computed temperature field as well as the meridional and seasonal variations of ozone column abundance are in good agreement with the distributions observed by Mariner 9 and Viking spacecrafts and the results obtained by previous studies. The present version of the model does not include the effects of dust, clouds and polar hood and only the chemistry in a dust-free atmosphere is considered.

Moreau, D.↗

NASA NTRS1950

Analysis of spanwise temperature distribution in three types of air-cooled turbine blade

Methods for computing spanwise blade-temperature distributions are derived for air-cooled hollow blades, air-cooled hollow blades with inserts, and air-cooled blades containing internal cooling fins. Individual and combined effects on spanwise blade-temperature distributions of cooling-air and radial heat conduction are determined. In general, the effects of radiation and radial heat conduction were found to be small and the omission of these variations permitted the construction of nondimensional charts for use in determining spanwise temperature distribution through air-cooled turbine blades. An approximate method for determining the allowable stress-limited blade-temperature distribution is included, with brief accounts of a method for determining the maximum allowable effective gas temperatures and the cooling-air requirements. Numerical examples that illustrate the use of the various temperature-distribution equations and of the nondimensional charts are also included.

Livingood, John N B↗

DOE OSTI2024

Distributed-Memory Sparse Deep Neural Network Inference Using Global Arrays

Partitioned Global Address Space (PGAS) models exhibit tremendous promise in developing efficient and productive distributed-memory parallel applications. They have been used extensively in scientific computations due to conveniently offering a ``shared-memory''-like model and convenient interfaces that separate communication with synchronization. Traditionally, PGAS communication models have been applied to dense/contiguously distributed data, but most modern applications depict varied levels of sparsity. Existing PGAS models require certain adaptations to support distributed sparse computations, since associated computations often require matrix arithmetic, in addition to data movement. The Global Arrays toolkit from Pacific Northwest National Laboratory (PNNL) is one of the earliest PGAS models to combine one-sided data communication and distributed matrix operations and is still used in the popular NWChem quantum chemistry suite. Recently, we have expanded the Global Arrays toolkit to support common sparse operations, like sparse matrix-dense matrix multiplies (SpMM), sparse matrix-sparse matrix multiplication (SpGEMM) and Sampled Dense-Dense Matrix Multiplication (SDDMM). As it turns out, these operations are the bedrock of sparse Deep Learning (DL); sparse deep neural networks and Graph Neural Networks (GNNs) have gained increasing attention recently in achieving speedups on training and inference with reduced memory footprints. Unlike scientific applications in High Performance Computing (HPC), modern (distributed-memory capable) DL toolkits often rely on non-standardized and closed-source vendor software optimizations, creating challenges in software-hardware co-design at scale. Our goal is to support a variety of distributed-memory sparse matrix operations and helper functions in the newly created Sparse Global Arrays (SGA), such that it is possible to build portable and productive Machine Learning scenarios for algorithm/software and hardware codesign purposes. Contemporary data-parallel schemes for training/inference are undergoing a major overhaul since model replication limits scalability and causes resource inefficiencies. As such, we have adopted tensor parallelism in decomposing the model and inputs, to mitigate memory issues. Current implementation is built on top of MPI and uses CPUs to maximize the portability across the platforms.

Distributed computing, machine learning↗

NASA NTRS1987

Performance issues for domain-oriented time-driven distributed simulations

It has long been recognized that simulations form an interesting and important class of computations that may benefit from distributed or parallel processing. Since the point of parallel processing is improved performance, the recent proliferation of multiprocessors requires that we consider the performance issues that naturally arise when attempting to implement a distributed simulation. Three such issues are: (1) the problem of mapping the simulation onto the architecture, (2) the possibilities for performing redundant computation in order to reduce communication, and (3) the avoidance of deadlock due to distributed contention for message-buffer space. These issues are discussed in the context of a battlefield simulation implemented on a medium-scale multiprocessor message-passing architecture.

Nicol, David M.↗

DOE OSTI2024

Solving differential‐algebraic equations in power system dynamic analysis with quantum computing

Abstract Power system dynamics are generally modeled by high dimensional non‐linear differential‐algebraic equations (DAEs) given a large number of components forming the network. These DAEs' complexity can grow exponentially due to the increasing penetration of distributed energy resources, whereas their computation time becomes sensitive due to the increasing interconnection of the power grid with other energy systems. This paper demonstrates the use of quantum computing algorithms to solve DAEs for power system dynamic analysis. We leverage a symbolic programming framework to equivalently convert the power system's DAEs into ordinary differential equations (ODEs) using index reduction methods and then encode their data into qubits using amplitude encoding. The system non‐linearity is captured by Hamiltonian simulation with truncated Taylor expansion so that state variables can be updated by a quantum linear equation solver. Our results show that quantum computing can solve the power system's DAEs accurately with a computational complexity polynomial in the logarithm of the system dimension. We also illustrate the use of recent advanced tools in scientific machine learning for implementing complex computing concepts, that is, Taylor expansion, DAEs/ODEs transformation, and quantum computing solver with abstract representation for power engineering applications.

computational complexity↗

NASA NTRSDate not supplied

Flight Test Design and Implementation for Airspace Independent Surveillance Through a Distributed Ground Based Sensor Network

The paper presents a system architecture for distributed sensing, networking and computing, its hardware implementation, and execution of initial flight experiments to validate theoretical findings. It induces development of distributed sensing requirements, framework, and architecture, development of distributed ground node hardware prototypes, integration of all nodes and testing of baseline functionalities, integration of in-house developed perception, migration and tracking software packages, establishing flight scenario and flyable path for a selected UAS, flying the air vehicle along the path, recording sensors measurements, pre-processing them and transferring the resulting data to an optimal computing center. It also addresses the challenges related to pre-flight hardware calibration, clock synchronization, sensor registration and establishing a communication network. Sensors data processing results demonstrate the functionality of the presented distributed architecture and satisfactory performance of the applied technologies.

Target tracking↗

NASA NTRSDate not supplied

Flight Test Design and Implementation for Independent Surveillance of an Airspace Through a Distributed Ground Sensing Network

Distributed sensing↗

NASA NTRS1987

Comparing the Performance of Two Dynamic Load Distribution Methods

Parallel processing of symbolic computations on a message-passing multi-processor presents one challenge: To effectively utilize the available processors, the load must be distributed uniformly to all the processors. However, the structure of these computations cannot be predicted in advance. go, static scheduling methods are not applicable. In this paper, we compare the performance of two dynamic, distributed load balancing methods with extensive simulation studies. The two schemes are: the Contracting Within a Neighborhood (CWN) scheme proposed by us, and the Gradient Model proposed by Lin and Keller. We conclude that although simpler, the CWN is significantly more effective at distributing the work than the Gradient model.

Kale, L. V.↗