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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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NASA NTRS1988

A parallel expert system for the control of a robotic air vehicle

Expert systems can be used to govern the intelligent control of vehicles, for example the Robotic Air Vehicle (RAV). Due to the nature of the RAV system the associated expert system needs to perform in a demanding real-time environment. The use of a parallel processing capability to support the associated expert system's computational requirement is critical in this application. Thus, algorithms for parallel real-time expert systems must be designed, analyzed, and synthesized. The design process incorporates a consideration of the rule-set/face-set size along with representation issues. These issues are looked at in reference to information movement and various inference mechanisms. Also examined is the process involved with transporting the RAV expert system functions from the TI Explorer, where they are implemented in the Automated Reasoning Tool (ART), to the iPSC Hypercube, where the system is synthesized using Concurrent Common LISP (CCLISP). The transformation process for the ART to CCLISP conversion is described. The performance characteristics of the parallel implementation of these expert systems on the iPSC Hypercube are compared to the TI Explorer implementation.

Shakley, Donald↗
NASA NTRS2019

Analysis Ready Data in Analytics Optimized Data Stores for Analysis of Big Earth Data in the Cloud

Cloud computing offers the possibility of making the analysis of Big Data approachable for a wider community due to affordable access to computing power, an ecosystem of usable tools for parallel processing, and migration of many large datasets to archives in the cloud, allowing data-proximal computing. Generally, data analysis acceleration in the cloud comes from running multiple nodes in a split-combine-apply strategy. Data systems such as the Earth Observing System Data and Information System are in a position to "pre-split" the data by storing them in a data store that is optimized for data parallel computing, i.e., an Analytics-Optimized Data Store (AODS). A variety of approaches to AODS are possible, from highly scalable databases to scalable filesystems to data formats optimized for cloud access (e.g., zarr and cloud-optimized datasets), with the optimal choice dependent on both the types of analysis and the geospatial structure of the data. A key question is how much preprocessing of the data to do, both before splitting and as the first part of the apply step. Again, the geospatial structure of the data and the analysis type influence the decision, with the added complexity of the user type. Trans-disciplinary users who are not well-versed in the nuances of quality-filtering and georeferencing of remote sensing orbit/swath/scene data tend to ask for more highly processed data, relying on the data provider to make sensible decisions on preprocessing parameters. (This accounts for the popularity of "Level 3" gridded data, despite the lower spatial resolution it provides.) In this case, data can be preprocessed before the split, resulting in higher performance in the rest of the "apply" step, which can be transformative for use cases such as interactive data exploration at scale. Discipline researchers who are experienced with remote sensing data often prefer more flexibility in customizing the preprocessing data into Analysis Ready Data, resulting in more need for on-the-fly preprocessing.

Lynnes, Christopher↗
NASA NTRS1996

Aerodynamic Influence Coefficient Computations Using Euler/Navier-Stokes Equations on Parallel Computers

Modem design requirements for an aircraft push current technologies used in the design process to their limit or sometimes require more advanced technologies to meet the requirement. New design requirements always demand to improve the operational performance. Accurate prediction of aerodynamic coefficients is essential to improve the performance. For example, in the design of an advanced subsonic civil transport, since the fluid flow at transonic regime shows strong nonlinearities, high fidelity equations, such as the Euler or Navier-Stokes equations predict flow characteristics more accurately than the linear aerodynamics, which are widely used in the current design process However, high fidelity flow equations are computationally expensive and require an order of magnitude longer time to obtain aerodynamic coefficients required in the design. Parallel computing is one possibility to cut down the computational turn-around time in using high fidelity equations so that high fidelity equations would be incorporated into the design process. By doing so, high fidelity equations would be used in the routine design process. This work will demonstrate the feasibility of using high fidelity flow equations in a design process by computing aerodynamic influence coefficients of a wing-body-empennage configuration on a multiple-instruction, multiple-data parallel computer.

Byun, Chansup↗
NASA NTRS2003

Monte Carlo Methodology Serves Up a Software Success

Widely used for the modeling of gas flows through the computation of the motion and collisions of representative molecules, the Direct Simulation Monte Carlo method has become the gold standard for producing research and engineering predictions in the field of rarefied gas dynamics. Direct Simulation Monte Carlo was first introduced in the early 1960s by Dr. Graeme Bird, a professor at the University of Sydney, Australia. It has since proved to be a valuable tool to the aerospace and defense industries in providing design and operational support data, as well as flight data analysis. In 2002, NASA brought to the forefront a software product that maintains the same basic physics formulation of Dr. Bird's method, but provides effective modeling of complex, three-dimensional, real vehicle simulations and parallel processing capabilities to handle additional computational requirements, especially in areas where computational fluid dynamics (CFD) is not applicable. NASA's Direct Simulation Monte Carlo Analysis Code (DAC) software package is now considered the Agency s premier high-fidelity simulation tool for predicting vehicle aerodynamics and aerothermodynamic environments in rarified, or low-density, gas flows.

Source record↗
NASA NTRS2005

Forecasting of Storm Surge Floods Using ADCIRC and Optimized DEMs

Increasing the accuracy of storm surge flood forecasts is essential for improving preparedness for hurricanes and other severe storms and, in particular, for optimizing evacuation scenarios. An interactive database, developed by WorldWinds, Inc., contains atlases of storm surge flood levels for the Louisiana/Mississippi gulf coast region. These atlases were developed to improve forecasting of flooding along the coastline and estuaries and in adjacent inland areas. Storm surge heights depend on a complex interaction of several factors, including: storm size, central minimum pressure, forward speed of motion, bottom topography near the point of landfall, astronomical tides, and most importantly, maximum wind speed. The information in the atlases was generated in over 100 computational simulations, partly by use of a parallel-processing version of the ADvanced CIRCulation (ADCIRC) model. ADCIRC is a nonlinear computational model of hydrodynamics, developed by the U.S. Army Corps of Engineers and the US Navy, as a family of two- and three-dimensional finite element based codes. It affords a capability for simulating tidal circulation and storm surge propagation over very large computational domains, while simultaneously providing high-resolution output in areas of complex shoreline and bathymetry. The ADCIRC finite-element grid for this project covered the Gulf of Mexico and contiguous basins, extending into the deep Atlantic Ocean with progressively higher resolution approaching the study area. The advantage of using ADCIRC over other storm surge models, such as SLOSH, is that input conditions can include all or part of wind stress, tides, wave stress, and river discharge, which serve to make the model output more accurate.

Valenti, Elizabeth↗
NASA NTRS2006

Forecasting of Storm-Surge Floods Using ADCIRC and Optimized DEMs

Increasing the accuracy of storm-surge flood forecasts is essential for improving preparedness for hurricanes and other severe storms and, in particular, for optimizing evacuation scenarios. An interactive database, developed by WorldWinds, Inc., contains atlases of storm-surge flood levels for the Louisiana/Mississippi gulf coast region. These atlases were developed to improve forecasting of flooding along the coastline and estuaries and in adjacent inland areas. Storm-surge heights depend on a complex interaction of several factors, including: storm size, central minimum pressure, forward speed of motion, bottom topography near the point of landfall, astronomical tides, and, most importantly, maximum wind speed. The information in the atlases was generated in over 100 computational simulations, partly by use of a parallel-processing version of the ADvanced CIRCulation (ADCIRC) model. ADCIRC is a nonlinear computational model of hydrodynamics, developed by the U.S. Army Corps of Engineers and the US Navy, as a family of two- and three-dimensional finite-element-based codes. It affords a capability for simulating tidal circulation and storm-surge propagation over very large computational domains, while simultaneously providing high-resolution output in areas of complex shoreline and bathymetry. The ADCIRC finite-element grid for this project covered the Gulf of Mexico and contiguous basins, extending into the deep Atlantic Ocean with progressively higher resolution approaching the study area. The advantage of using ADCIRC over other storm-surge models, such as SLOSH, is that input conditions can include all or part of wind stress, tides, wave stress, and river discharge, which serve to make the model output more accurate. To keep the computational load manageable, this work was conducted using only the wind stress, calculated by using historical data from Hurricane Camille, as the input condition for the model. Hurricane storm-surge simulations were performed on an eight-node Linux computer cluster. Each node contained dual 2-GHz processors, 2GB of memory, and a 40GB hard drive. The digital elevation model (DEM) for this region was specified using a combination of Navy data (over water), NOAA data (for the coastline), and optimized Interferometric Synthetic Aperture Radar data (over land). This high-resolution topographical data of the Mississippi coastal region provided the ADCIRC model with improved input with which to calculate improved storm-surge forecasts.

Valenti, Elizabeth↗
NASA NTRS1993

A comparison of queueing, cluster and distributed computing systems

Using workstation clusters for distributed computing has become popular with the proliferation of inexpensive, powerful workstations. Workstation clusters offer both a cost effective alternative to batch processing and an easy entry into parallel computing. However, a number of workstations on a network does not constitute a cluster. Cluster management software is necessary to harness the collective computing power. A variety of cluster management and queuing systems are compared: Distributed Queueing Systems (DQS), Condor, Load Leveler, Load Balancer, Load Sharing Facility (LSF - formerly Utopia), Distributed Job Manager (DJM), Computing in Distributed Networked Environments (CODINE), and NQS/Exec. The systems differ in their design philosophy and implementation. Based on published reports on the different systems and conversations with the system's developers and vendors, a comparison of the systems are made on the integral issues of clustered computing.

Kaplan, Joseph A.↗
NASA NTRS1979

Optical memories in digital computing

High capacity optical memories with relatively-high data-transfer rate and multiport simultaneous access capability may serve as basis for new computer architectures. Several computer structures that might profitably use memories are: a) simultaneous record-access system, b) simultaneously-shared memory computer system, and c) parallel digital processing structure.

Alford, C. O.↗
NASA NTRS1990

Order (n) DISCOS for multibody systems with gear reduction

Recent developments in O(n) algorithms (where n is the number of bodies in the system) and parallel processing have drastically reduced the computer time needed to simulate systems involving many bodies. This paper presents a gear-reduction model for the O(n) version of DISCOS, a standard software package for simulation and analysis of flexible multibody systems. The gear-reduction model allows the accurate modeling of harmonic drives, which are commonly used in robot joints. The formulation has been implemented and validated with known results. The gear model can also be used for gear-train, rack-and-pinion, and screw joints.

Chun, Hon M.↗
NASA NTRS1994

High Performance Parallel Analysis of Coupled Problems for Aircraft Propulsion

In order to predict the dynamic response of a flexible structure in a fluid flow, the equations of motion of the structure and the fluid must be solved simultaneously. In this paper, we present several partitioned procedures for time-integrating this focus coupled problem and discuss their merits in terms of accuracy, stability, heterogeneous computing, I/O transfers, subcycling, and parallel processing. All theoretical results are derived for a one-dimensional piston model problem with a compressible flow, because the complete three-dimensional aeroelastic problem is difficult to analyze mathematically. However, the insight gained from the analysis of the coupled piston problem and the conclusions drawn from its numerical investigation are confirmed with the numerical simulation of the two-dimensional transient aeroelastic response of a flexible panel in a transonic nonlinear Euler flow regime.

Felippa, C. A.↗
NASA NTRS2000

Highly Parallel Computing Architectures by using Arrays of Quantum-dot Cellular Automata (QCA): Opportunities, Challenges, and Recent Results

There has been significant improvement in the performance of VLSI devices, in terms of size, power consumption, and speed, in recent years and this trend may also continue for some near future. However, it is a well known fact that there are major obstacles, i.e., physical limitation of feature size reduction and ever increasing cost of foundry, that would prevent the long term continuation of this trend. This has motivated the exploration of some fundamentally new technologies that are not dependent on the conventional feature size approach. Such technologies are expected to enable scaling to continue to the ultimate level, i.e., molecular and atomistic size. Quantum computing, quantum dot-based computing, DNA based computing, biologically inspired computing, etc., are examples of such new technologies. In particular, quantum-dots based computing by using Quantum-dot Cellular Automata (QCA) has recently been intensely investigated as a promising new technology capable of offering significant improvement over conventional VLSI in terms of reduction of feature size (and hence increase in integration level), reduction of power consumption, and increase of switching speed. Quantum dot-based computing and memory in general and QCA specifically, are intriguing to NASA due to their high packing density (10(exp 11) - 10(exp 12) per square cm ) and low power consumption (no transfer of current) and potentially higher radiation tolerant. Under Revolutionary Computing Technology (RTC) Program at the NASA/JPL Center for Integrated Space Microelectronics (CISM), we have been investigating the potential applications of QCA for the space program. To this end, exploiting the intrinsic features of QCA, we have designed novel QCA-based circuits for co-planner (i.e., single layer) and compact implementation of a class of data permutation matrices, a class of interconnection networks, and a bit-serial processor. Building upon these circuits, we have developed novel algorithms and QCA-based architectures for highly parallel and systolic computation of signal/image processing applications, such as FFT and Wavelet and Wlash-Hadamard Transforms.

Fijany, Amir↗
NASA NTRS2002

Parametric Study of a YAV-8B Harrier in Ground Effect using Time-Dependent Navier-Stokes Computations

A process is described which enables the generation of 35 time-dependent viscous solutions for a YAV-8B Harrier in ground effect in one week. Overset grids are used to model the complex geometry of the Harrier aircraft and the interaction of its jets with the ground plane and low-speed ambient flow. The time required to complete this parametric study is drastically reduced through the use of process automation, modern computational platforms, and parallel computing. Moreover, a dual-time-stepping algorithm is described which improves solution robustness. Unsteady flow visualization and a frequency domain analysis are also used to identify and correlated key flow structures with the time variation of lift.

Pandya, Shishir↗
NASA NTRS2004

On the Hilbert-Huang Transform Theoretical Foundation

The Hilbert-Huang Transform [HHT] is a novel empirical method for spectrum analysis of non-linear and non-stationary signals. The HHT is a recent development and much remains to be done to establish the theoretical foundation of the HHT algorithms. This paper develops the theoretical foundation for the convergence of the HHT sifting algorithm and it proves that the finest spectrum scale will always be the first generated by the HHT Empirical Mode Decomposition (EMD) algorithm. The theoretical foundation for cutting an extrema data points set into two parts is also developed. This then allows parallel signal processing for the HHT computationally complex sifting algorithm and its optimization in hardware.

Kizhner, Semion↗
NASA NTRS2001

Arthropod phylogeny based on eight molecular loci and morphology

The interrelationships of major clades within the Arthropoda remain one of the most contentious issues in systematics, which has traditionally been the domain of morphologists. A growing body of DNA sequences and other types of molecular data has revitalized study of arthropod phylogeny and has inspired new considerations of character evolution. Novel hypotheses such as a crustacean-hexapod affinity were based on analyses of single or few genes and limited taxon sampling, but have received recent support from mitochondrial gene order, and eye and brain ultrastructure and neurogenesis. Here we assess relationships within Arthropoda based on a synthesis of all well sampled molecular loci together with a comprehensive data set of morphological, developmental, ultrastructural and gene-order characters. The molecular data include sequences of three nuclear ribosomal genes, three nuclear protein-coding genes, and two mitochondrial genes (one protein coding, one ribosomal). We devised new optimization procedures and constructed a parallel computer cluster with 256 central processing units to analyse molecular data on a scale not previously possible. The optimal 'total evidence' cladogram supports the crustacean-hexapod clade, recognizes pycnogonids as sister to other euarthropods, and indicates monophyly of Myriapoda and Mandibulata.

Non-NASA Center↗
NASA NTRS2006

Satellite Image Mosaic Engine

A computer program automatically builds large, full-resolution mosaics of multispectral images of Earth landmasses from images acquired by Landsat 7, complete with matching of colors and blending between adjacent scenes. While the code has been used extensively for Landsat, it could also be used for other data sources. A single mosaic of as many as 8,000 scenes, represented by more than 5 terabytes of data and the largest set produced in this work, demonstrated what the code could do to provide global coverage. The program first statistically analyzes input images to determine areas of coverage and data-value distributions. It then transforms the input images from their original universal transverse Mercator coordinates to other geographical coordinates, with scaling. It applies a first-order polynomial brightness correction to each band in each scene. It uses a data-mask image for selecting data and blending of input scenes. Under control by a user, the program can be made to operate on small parts of the output image space, with check-point and restart capabilities. The program runs on SGI IRIX computers. It is capable of parallel processing using shared-memory code, large memories, and tens of central processing units. It can retrieve input data and store output data at locations remote from the processors on which it is executed.

Plesea, Lucian↗
NASA NTRS1993

Development of iterative techniques for the solution of unsteady compressible viscous flows

During the past two decades, there has been significant progress in the field of numerical simulation of unsteady compressible viscous flows. At present, a variety of solution techniques exist such as the transonic small disturbance analyses (TSD), transonic full potential equation-based methods, unsteady Euler solvers, and unsteady Navier-Stokes solvers. These advances have been made possible by developments in three areas: (1) improved numerical algorithms; (2) automation of body-fitted grid generation schemes; and (3) advanced computer architectures with vector processing and massively parallel processing features. In this work, the GMRES scheme has been considered as a candidate for acceleration of a Newton iteration time marching scheme for unsteady 2-D and 3-D compressible viscous flow calculation; from preliminary calculations, this will provide up to a 65 percent reduction in the computer time requirements over the existing class of explicit and implicit time marching schemes. The proposed method has ben tested on structured grids, but is flexible enough for extension to unstructured grids. The described scheme has been tested only on the current generation of vector processor architecture of the Cray Y/MP class, but should be suitable for adaptation to massively parallel machines.

Hixon, Duane↗
NASA NTRS1987

The use of transputers in processing telemetry data

Parallelism will be an essential ingredient of high performance systems of the future. The Inmos transputer is a high performance single-chip computer whose architecture facilitates the construction of parallel processing systems. Occam is a high level language developed for use with the Inmos transputer. This paper describes a project to evaluate the feasibility of using the transputer to implement real time processing of telemetry data.

Delgado, Hugo M., Jr.↗