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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 271 records · Page 15
All sourcesNASA NTRSDOE OSTI
DOE OSTI2018

Portable Data-Parallel Surface Reconstruction on a Uniform Rectilinear Grid

With the increasing heterogeneity and on-node parallelism of high-performance computing hardware, a major challenge is to develop portable and efficient algorithms and software. In this work, we present our implementation of a portable code to perform surface reconstruction using NVIDIA's Thrust library. Surface reconstruction is a technique commonly used in volume tracking methods for simulations of multimaterial flow with interfaces. Here, we have designed a 3D mesh data structure that is easily mapped to the 1D vectors used by Thrust and at the same time is simple to use and uses familiar data structure terminology (such as cells, faces, vertices, and edges). With this new data structure in place, we have implemented a piecewise linear interface reconstruction algorithm in 3 dimensions that effectively exploits the symmetry present in a uniform rectilinear computational cell. Finally, we report performance results, which show that a single implementation of these algorithms can be compiled to multiple backends (specifically, multi-core CPUs, NVIDIA GPUs, and Intel Xeon Phi processors), making efficient use of the available parallelism on each. We also compare performance of our implementation to a legacy FORTRAN implementation in Message Passing Interface (MPI) and show performance parity on single and multi-core CPU and achieved good parallel speed-ups on GPU. In conclusion, our research demonstrates the advantage of performance portability of the underlying data-parallel programming model.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS2003

Cloud-Resolving Model and GPM

Over the past twenty years, rainfall retrieval algorithms have been developed to retrieve rainfall and vertical hydrometeor structures from passive microwave observations by making use of the fact that weighting functions for various frequencies peak at different levels within a rainy atmosphere. GPROF is one of two TMI rainfall algorithms. It is physically based retrieval that finds the vertical hydrometeor profile that best fits the brightness temperatures in the available passive radiometer channels. Matching is achieved using a library of hydrometeor profiles generated by cloud-resolving models (CRMs). The hydrometeor profiles have a corresponding surface precipitation rate. The algorithm retrieves the hydrometeor profiles and associated surface rainfall using a Bayesian approach that gives the estimated expected values. The ability of CRMs to produce cloud structures that are reliable and representative of observed storms is crucial for the success of GPROF. The cloud mycrophysics are one of the keys to achieving this. In addition, CRMs have been a very useful tool for GPM-algorithm developers through Cloud-Radiation Simulations (CRS), one of the nine GPM disciplinary research themes. This paper will discuss how to generate consistent and comprehensive 4D cloud datasets from an improved (i.e., in regard to bulk and multi-moment microphysics) CRM for TRMM and GPM rainfall retrieval algorithm developers. These cloud datasets include CRM-simulated clouds and cloud systems from different geographic locations in the tropics and midlatitudes. By linking the CRM with a passive microwave radiative-transfer model and using satellite and airborne data, the performance of the "cloud physics" can be assessed and in turn modified and improved. This paper will also address how to assess and improve the performance of various latent and diabatic heating algorithms and develop an algorithm to retrieve the vertical structure of apparent moistening (Q2). Considering that the GPM will produce high (temporal and spatial) resolution heating and rainfall data, these algorithms will be used to obtain the temporal and spatial distributions of surface rainfall and the associated vertical heating and moistening profiles throughout the subtropical and midlatitudes.

Tao, Wei-Kuo↗
DOE OSTI2019

Relaxation algorithms for matrix completion, with applications to seismic travel-time data interpolation

Travel time tomography is used to infer the underlying three-dimensional wavespeed structure of the Earth by fitting seismic travel time data collected at surface stations. Data interpolation and denoising techniques are important pre-processing steps that use prior knowledge about the data, including parsimony in the frequency and wavelet domains, low-rank structure of matricizations, and local smoothness. In this work, we show how local smoothness structure can be combined with low rank constraints using level-set optimization formulations, and develop a new relaxation algorithm that can efficiently solve these joint problems. In the seismology setting, we use the approach to interpolate missing stations and de-noise observed stations. The new approach is competitive with alternative algorithms, and offers new functionality to interpolate observed data using both smoothness and low rank structure in the presence of data fitting constraints.

constrained optimization↗
DOE OSTI2023

Ume: Unstructured Mesh Explorations

Ume is an open-source collection of data structures for unstructured computational meshes and some simple algorithms that operate on them. These algorithms mimic the memory access patterns of a common class of operations found in several of the computational physics simulation codes developed at Los Alamos National Laboratory. The intent is that Ume can be used by hardware vendors to understand the memory traffic created by complex codes in a simplified environment, and to explore new means of optimization for that traffic. Ume is provided as a source-code C++ library and includes several applications that demonstrate the use of that library.

Henning, Paul↗
DOE OSTI2015

Structure Learning and Statistical Estimation in Distribution Networks - Part II

Limited placement of real-time monitoring devices in the distribution grid, recent trends notwithstanding, has prevented the easy implementation of demand-response and other smart grid applications. Part I of this paper discusses the problem of learning the operational structure of the grid from nodal voltage measurements. In this work (Part II), the learning of the operational radial structure is coupled with the problem of estimating nodal consumption statistics and inferring the line parameters in the grid. Based on a Linear-Coupled(LC) approximation of AC power flows equations, polynomial time algorithms are designed to identify the structure and estimate nodal load characteristics and/or line parameters in the grid using the available nodal voltage measurements. Then the structure learning algorithm is extended to cases with missing data, where available observations are limited to a fraction of the grid nodes. The efficacy of the presented algorithms are demonstrated through simulations on several distribution test cases.

24 POWER TRANSMISSION AND DISTRIBUTION↗
NASA NTRS1983

Three-dimensional flow over a conical afterbody containing a centered propulsive jet - A numerical simulation

The supersonic flow field over a body of revolution incident to the free stream is simulated numerically on a large, array processor (the CDC Cyber 205). The configuration is composed of a cone-cylinder forebody followed by a conical afterbody from which emanates a centered, supersonic propulsive jet. The free-stream Mach number is 2, the jet-exit Mach number is 2.5, and the jet-to-free-stream static pressure ratio is 3. Both the external flow and the exhaust are ideal air at a common total temperature. The thin-layer approximation to the time-dependent, compressible, Reynolds-averaged Navier-Stokes equations are solved using an implicit finite-difference algorithm. The data base, of 5 million words, is structured in a 'pencil' format so that efficient use of the array processor can be realized. The computer code is completely vectorized to take advantage of the data structure. Turbulence closure is achieved using an empirical algebraic eddy-viscosity model. The configuration and flow conditions correspond to published experimental tests and the computed solutions are consistent with the experimental data.

Deiwert, G. S.↗
NASA NTRS1991

Querying databases of trajectories of differential equations 2: Index functions

Suppose that a large number of parameterized trajectories (gamma) of a dynamical system evolving in R sup N are stored in a database. Let eta is contained R sup N denote a parameterized path in Euclidean space, and let parallel to center dot parallel to denote a norm on the space of paths. A data structures and indices for trajectories are defined and algorithms are given to answer queries of the following forms: Query 1. Given a path eta, determine whether eta occurs as a subtrajectory of any trajectory gamma from the database. If so, return the trajectory; otherwise, return null. Query 2. Given a path eta, return the trajectory gamma from the database which minimizes the norm parallel to eta - gamma parallel.

Grossman, Robert↗
NASA NTRS1992

Efficient use of high performance computers for integrated controls and structures design

Simply transporting design codes from sequential-scalar computers to parallel-vector computers does not fully utilize the computational benefits offered by high performance computers. By performing integrated controls and structures design on an experimental truss platform with both sequential-scalar and parallel-vector design codes, conclusive results are presented to substantiate this claim. The efficiency of a Cholesky factorization scheme in conjunction with a variable-band row data structure is presented. In addition, the Lanczos eigensolution algorithm has been incorporated in the design code for both parallel and vector computations. Comparisons of computational efficiency between the initial design code and the parallel-vector design code are presented. It is shown that the Lanczos algorithm with the Cholesky factorization scheme is far superior to the sub-space iteration method of eigensolution when substantial numbers of eigenvectors are required for control design and/or performance optimization. Integrated design results show the need for continued efficiency studies in the area of element computations and matrix assembly.

Belvin, W. K.↗
NASA NTRS1993

Designing reduced-order linear multivariable controllers using experimentally derived plant data

An iterative numerical algorithm for simultaneously improving multiple performance and stability robustness criteria for multivariable feedback systems is developed. The unsatisfied design criteria are improved by updating the free parameters of an initial, stabilizing controller's state-space matrices. Analytical expressions for the gradients of the design criteria are employed to determine a parameter correction that improves all of the feasible, unsatisfied design criteria at each iteration. A controller design is performed using the algorithm with experimentally derived data from a large space structure test facility. Experimental results of the controller's performance at the facility are presented.

Frazier, W. G.↗
NASA NTRS2015

Explore GPM IMERG and Other Global Precipitation Products with GES DISC GIOVANNI

New features and capabilities in the newly released GIOVANNI allow exploring GPM IMERG (Integrated Multi-satelliE Retrievals for GPM) Early, Late and Final Run global half-hourly and monthly precipitation products as well as other precipitation products distributed by the GES DISC such as TRMM Multi-Satellite Precipitation Analysis (TMPA), MERRA (Modern Era Retrospective-Analysis for Research and Applications), NLDAS (North American Land Data Assimilation Systems), GLDAS (Global Land Data Assimilation Systems), etc. GIOVANNI is a web-based tool developed by the GES DISC (Goddard Earth Sciences and Data Information Services Center) to visualize and analyze Earth science data without having to download data and software. The new interface in GIOVANNI allows searching and filtering precipitation products from different NASA missions and projects and expands the capabilities to inter-compare different precipitation products in one interface. Knowing differences in precipitation products is important to identify issues in retrieval algorithms, biases, uncertainties, etc. Due to different formats, data structures, units and so on, it is not easy to inter-compare precipitation products. Newly added features and capabilities (unit conversion, regridding, etc.) in GIOVANNI make inter-comparisons possible. In this presentation, we will describe these new features and capabilities along with examples.

Giovanni↗
DOE OSTI2019

Linear optimal power flow system and method

An electric power system or power grid is optimized using a computer-implemented tool the represents in computer memory the optimization function and at least one constraint, which the processor operates upon using a linear programming solver algorithm. The constraints are represented in memory as data structures that include both real and reactive power terms, corresponding to at least one of a power flow model and a transmission line model. The transmission line model is represented using a piecewise linear representation. The power flow model may also include for each node in the power system a real power loss term representing transmission line loss allocated to that node.

24 POWER TRANSMISSION AND DISTRIBUTION↗
NASA NTRS1993

A new procedure for dynamic adaption of three-dimensional unstructured grids

A new procedure is presented for the simultaneous coarsening and refinement of three-dimensional unstructured tetrahedral meshes. This algorithm allows for localized grid adaption that is used to capture aerodynamic flow features such as vortices and shock waves in helicopter flowfield simulations. The mesh-adaption algorithm is implemented in the C programming language and uses a data structure consisting of a series of dynamically-allocated linked lists. These lists allow the mesh connectivity to be rapidly reconstructed when individual mesh points are added and/or deleted. The algorithm allows the mesh to change in an anisotropic manner in order to efficiently resolve directional flow features. The procedure has been successfully implemented on a single processor of a Cray Y-MP computer. Two sample cases are presented involving three-dimensional transonic flow. Computed results show good agreement with conventional structured-grid solutions for the Euler equations.

Biswas, Rupak↗
NASA NTRS2005

Self-Organizing-Map Program for Analyzing Multivariate Data

SOM_VIS is a computer program for analysis and display of multidimensional sets of Earth-image data typified by the data acquired by the Multi-angle Imaging Spectro-Radiometer [MISR (a spaceborne instrument)]. In SOM_VIS, an enhanced self-organizing-map (SOM) algorithm is first used to project a multidimensional set of data into a nonuniform three-dimensional lattice structure. The lattice structure is mapped to a color space to obtain a color map for an image. The Voronoi cell-refinement algorithm is used to map the SOM lattice structure to various levels of color resolution. The final result is a false-color image in which similar colors represent similar characteristics across all its data dimensions. SOM_VIS provides a control panel for selection of a subset of suitably preprocessed MISR radiance data, and a control panel for choosing parameters to run SOM training. SOM_VIS also includes a component for displaying the false-color SOM image, a color map for the trained SOM lattice, a plot showing an original input vector in 36 dimensions of a selected pixel from the SOM image, the SOM vector that represents the input vector, and the Euclidean distance between the two vectors.

Li, P. Peggy↗
DOE OSTI2021

Materials Fingerprinting Classification

Significant progress in many classes of materials could be made with the availability of experimentally-derived large datasets composed of atomic identities and three-dimensional coordinates. Methods for visualizing the local atomic structure, such as atom probe tomography (APT), which routinely generate datasets comprised of millions of atoms, are an important step in realizing this goal. However, state-of-the-art APT instruments generate noisy and sparse datasets that provide information about elemental type, but obscure atomic structures, thus limiting their subsequent value for materials discovery. The application of a materials fingerprinting process, a machine learning algorithm coupled with topological data analysis, provides an avenue by which here-to-fore unprecedented structural information can be extracted from an APT dataset. As a proof of concept, the material fingerprint is applied to high-entropy alloy APT datasets containing body-centered cubic (BCC) and face-centered cubic (FCC) crystal structures. A local atomic configuration centered on an arbitrary atom is assigned a topological descriptor, with which it can be characterized as a BCC or FCC lattice with near perfect accuracy, despite the inherent noise in the dataset. Finally, this successful identification of a fingerprint is a crucial first step in the development of algorithms which can extract more nuanced information, such as chemical ordering, from existing datasets of complex materials.

36 MATERIALS SCIENCE↗
NASA NTRS1987

Reverse time migration: A seismic processing application on the connection machine

The implementation of a reverse time migration algorithm on the Connection Machine, a massively parallel computer is described. Essential architectural features of this machine as well as programming concepts are presented. The data structures and parallel operations for the implementation of the reverse time migration algorithm are described. The algorithm matches the Connection Machine architecture closely and executes almost at the peak performance of this machine.

Fiebrich, Rolf-Dieter↗
DOE OSTI2020

Compiler and Runtime Approaches to Enable Large-Scale Irregular Programs. Final report, July 2013 - July 2019

While regular algorithms, characterized by operations on dense matrices and arrays, have long been the mainstay of scientific, high-performance computing, irregular algorithms, which feature unpredictable accesses to pointer-based data structures, are becoming increasingly common in high performance computing, arising in graph analysis, data mining and visualization, among other domains. Unfortunately, the defining characteristics of irregular applications, their dynamic, unpredictable, data-dependent access patterns and data layouts, make achieving high performance on large scale systems difficult. Scaling applications to peta- and exa-scale requires carefully controlling communication and data movement and placement, an inherently difficult task when access patterns and data layouts are unpredictable! Most irregular applications that attain high performance must be painstakingly hand-written and hand-tuned, with few common principles or paradigms uniting various implementations and easing future development. Despite the increasing importance of irregular applications, there is little programmer knowledge, and even less compiler ability, devoted to optimizing them. This project aims to solve these problems. By allowing programmers to write irregular applications in high level forms, with at most a few annotations highlighting key structural properties, programmers can focus on developing their algorithms and methods. The compiler and run-time system can take on the tedious task of optimizing the application for execution at large scales, and can automatically provide efficient implementations. This will provide portability and ease maintenance for existing irregular applications, but, more importantly, open up whole new domains of computational science to large-scale, high-performance simulation codes.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS2005

A Constraint-Based Planner for Data Production

This paper presents a graph-based backtracking algorithm designed to support constrain-tbased planning in data production domains. This algorithm performs backtracking at two nested levels: the outer- backtracking following the structure of the planning graph to select planner subgoals and actions to achieve them and the inner-backtracking inside a subproblem associated with a selected action to find action parameter values. We show this algorithm works well in a planner applied to automating data production in an ecological forecasting system. We also discuss how the idea of multi-level backtracking may improve efficiency of solving semi-structured constraint problems.

Pang, Wanlin↗
NASA NTRS2018

Applications of the Dynamic N-Dimensional K-Vector

The n-dimensional k-vector (NDKV) is an appealing alternative to binary tress for resolving complex queries in large relational databases. The method has excelled in several applications involving static databases. The present paper extends the theory supporting the NDKV to handle dynamic databases, where the data is updated frequently. This includes deleting records, adding new entries, or editing existing elements. The merit of this new version of the NDKV, the dynamic n-dimensional k-vector (DNDKV), is that it is no longer necessary to recompute the entire k-vector (the main structure that indexes the data) every time a record changes. The algorithm updates the four constituents of the standard NDKV on the fly: the database, sorted database, index, and k-vector tables. As a result, the DNDKV becomes comparable in terms of capabilities and flexibility to stateof-the-art storage engines relying on structured query languages (SQL). The performance of the DNDKV is assessed by running typical read/write operations on a database that contains millions of pre-computed missions to celestial bodies. This database requires frequent updates whenever an orbit solution is refined or new bodies are discovered. The DNDKV is faster than rebuilding the k-vector tables completely, provided that the number of elements being added or removed is not excessively large. Direct runtime comparisons with MySQL suggest that the DNDKV is several times faster for reading but might be slower for writing and updating the database. One limit of the technique is the elements being added must be within the range of the current k-vector tables. If this is not the case, the technique cannot be used and the k-vector tables must be rebuilt from scratch.

Mortari, Daniele↗