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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 505 records · Page 28

An Analysis of Texture on Lunar Ground Photos

An experiment was performed in an attempt to evaluate autocorrelation as an indicator of texture using five small patches representing varying distances on each of four lunar photos. Each patch was scanned at 50 micron increments on a 64-level gray scale. Several problems were involved in using the ordinary autocorrelation value but a rougher autocorrelation measure, the percentage of neighboring pairs (at a given lag distance) which fell within one graylevel of one another, yielded very encouraging results. As the distance to the feature decreased, initial slope of the graph of percentage against lag increased, and the general level of the graph decreased. When a crestline was present, the graph tended to continue to decrease at higher lags as well, rather than leveling off after the initial steep slope.

Olson, J. M.↗

Heat flow anomaly associated with dike intrusion. II

An investigation reported by Horai (1974) is continued. A special case of the steady state temperature field associated with dike intrusion is studied, taking into account an infinite vertical downward extension of the isotherm of rectangular shape approximating the dike. The considered case represents a problem of two-dimensional steady state thermal conduction. The technique of conformal mapping used is identical to the method employed by Horai (1974). The characteristics of surface heat flow associated with an infinitesimal thin dike of certain temperature with the considered extension are shown in a graph.

Horai, K.-I.↗

Multiple degree of freedom object recognition using optical relational graph decision nets

Multiple-degree-of-freedom object recognition concerns objects with no stable rest position with all scale, rotation, and aspect distortions possible. It is assumed that the objects are in a fairly benign background, so that feature extractors are usable. In-plane distortion invariance is provided by use of a polar-log coordinate transform feature space, and out-of-plane distortion invariance is provided by linear discriminant function design. Relational graph decision nets are considered for multiple-degree-of-freedom pattern recognition. The design of Fisher (1936) linear discriminant functions and synthetic discriminant function for use at the nodes of binary and multidecision nets is discussed. Case studies are detailed for two-class and multiclass problems. Simulation results demonstrate the robustness of the processors to quantization of the filter coefficients and to noise.

Casasent, David P.↗

A Statistical Project Control Tool for Engineering Managers

This slide presentation reviews the use of a Statistical Project Control Tool (SPCT) for managing engineering projects. A literature review pointed to a definition of project success, (i.e., A project is successful when the cost, schedule, technical performance, and quality satisfy the customer.) The literature review also pointed to project success factors, and traditional project control tools, and performance measures that are detailed in the report. The essential problem is that with resources becoming more limited, and an increasing number or projects, project failure is increasing, there is a limitation of existing methods and systematic methods are required. The objective of the work is to provide a new statistical project control tool for project managers. Graphs using the SPCT method plotting results of 3 successful projects and 3 failed projects are reviewed, with success and failure being defined by the owner.

Bauch, Garland T.↗

Array distribution in data-parallel programs

We consider distribution at compile time of the array data in a distributed-memory implementation of a data-parallel program written in a language like Fortran 90. We allow dynamic redistribution of data and define a heuristic algorithmic framework that chooses distribution parameters to minimize an estimate of program completion time. We represent the program as an alignment-distribution graph. We propose a divide-and-conquer algorithm for distribution that initially assigns a common distribution to each node of the graph and successively refines this assignment, taking computation, realignment, and redistribution costs into account. We explain how to estimate the effect of distribution on computation cost and how to choose a candidate set of distributions. We present the results of an implementation of our algorithms on several test problems.

Chatterjee, Siddhartha↗

Transmission Scheduling and Routing Algorithms for Delay Tolerant Networks

The challenges of data processing, transmission scheduling and routing within a space network present a multi-criteria optimization problem. Long delays, intermittent connectivity, asymmetric data rates and potentially high error rates make traditional networking approaches unsuitable. The delay tolerant networking architecture and protocols attempt to mitigate many of these issues, yet transmission scheduling is largely manually configured and routes are determined by a static contact routing graph. A high level of variability exists among the requirements and environmental characteristics of different missions, some of which may allow for the use of more opportunistic routing methods. In all cases, resource allocation and constraints must be balanced with the optimization of data throughput and quality of service. Much work has been done researching routing techniques for terrestrial-based challenged networks in an attempt to optimize contact opportunities and resource usage. This paper examines several popular methods to determine their potential applicability to space networks.

Space Networking↗

Recursive Gaussian Process over graphs for Integrating Multi-timescale Measurements in Low-Observable Distribution Systems

The transition to a smarter grid is empowered by enhanced sensor deployments and smart metering infrastructure in the distribution system. Measurements from these sensors and meters can be used for many applications, including distribution system state estimation (DSSE). However, these measurements are typically sampled at different rates and could be intermittent due to losses during the aggregation process. These multi timescale measurements should be reconciled in real-time to perform accurate grid monitoring. This paper tackles this problem by formulating a recursive multi-task Gaussian process (RGP-G) approach that sequentially aggregates sensor measurements. Specifically, we formulate a recursive multi-task GP with and without network connectivity information to reconcile the multi time-scale measurements in distribution systems. Here, the proposed framework is capable of aggregating the multi-time scale measurements batch-wise or in real-time. Following the aggregation of the multi time-scale measurements, the spatial states of the consistent time-series are estimated using matrix completion based DSSE approach. Simulation results on IEEE 37 and IEEE 123 bus test systems illustrate the efficiency of the proposed methods from the standpoint of both multi time-scale data aggregation and DSSE.

42 ENGINEERING↗

The problem of the man-space data interface during computer processing of data

The necessity is shown for data output at different processing stages to man, taking into account the processing level, the output objective, and the user. The use of the phototelegraph I/O computer device for this purpose is considered in detail, and several examples are given. It is shown that the type of output (shaded of halftone graphs), the scales, the compression, and the mutual position of the data are selected on the basis of the character of the data displayed.

Mamotko, Z. N.↗

Element-by-element and implicit-explicit finite element formulations for computational fluid dynamics

Preconditioner algorithms to reduce the computational effort in FEM analyses of large-scale fluid-dynamics problems are presented. A general model problem is constructed on the basis of the convection-diffusion equation and the two-dimensional vorticity/stream-function formulation of the Navier-Stokes equations; this problem is then analyzed using element-by-element, implicit-explicit, and adaptive implicit-explicit approximation schemes. Numerical results for the two-dimensional advection and rigid-body rotation of a cosine hill, flow past a circular cylinder, and driven cavity flow are presented in extensive graphs and shown to be in good agreement with those obtained using implicit methods.

Tezduyar, T. E.↗

Robust second-order approximation of the compressible Euler equations with an arbitrary equation of state

Here, this paper is concerned with the approximation of the compressible Euler equations supplemented with an arbitrary or tabulated equation of state. The proposed approximation technique is robust, formally second-order accurate in space, invariant-domain preserving, and works for every equation of state, tabulated or analytic, provided the pressure is nonnegative. An entropy surrogate functional that grows across shocks is proposed. The numerical method is verified with novel analytical solutions and then validated with several computational benchmarks seen in the literature including problems with composite waves.

97 MATHEMATICS AND COMPUTING↗

Summer Proceedings 2019

The Computer Science Research Institute (CSRI) brings university faculty and students to Sandia for focused collaborative research on Department of Energy (DOE) computer and computational science problems. The institute provides an opportunity for university researchers to learn about problems in computer and computational science at DOE laboratories. Participants conduct leading-edge research, interact with scientists and engineers at the laboratories, and help transfer results of their research to programs at the labs. Some specific CSRI research interest areas are: scalable solvers, optimization, adaptivity and mesh refinement, graph-based, discrete, and combinatorial algorithms, uncertainty estimation, mesh generation, dynamic load-balancing, virus and other malicious-code defense, visualization, scalable cluster computers and heterogeneous computers, data-intensive computing, environments for scalable computing, parallel input/output, advanced architectures, and theoretical computer science. The CSRI Summer Program includes the organization of a weekly seminar series and the publication of this summer proceedings.

97 MATHEMATICS AND COMPUTING↗

CSRI Summer Proceedings 2020

The Computer Science Research Institute (CSRI) brings university faculty and students to Sandia for focused collaborative research on Department of Energy (DOE) computer and computational science problems. The institute provides an opportunity for university researchers to learn about problems in computer and computational science at DOE laboratories. Participants conduct leading-edge research, interact with scientists and engineers at the laboratories, and help transfer results of their research to programs at the labs. Some specific CSRI research interest areas are: scalable solvers, optimization, adaptivity and mesh refinement, graph-based, discrete, and combinatorial algorithms, uncertainty estimation, mesh generation, dynamic load-balancing, virus and other malicious-code defense, visualization, scalable cluster computers, data-intensive computing, environments for scalable computing, parallel input/output, advanced architectures, and theoretical computer science. The CSRI Summer Program is organized by CSRI and typically includes the organization of a weekly seminar series and the publication of a summer proceedings. In 2020, the CSRI summer program was executed completely virtually; all student interns worked from home, due to the COVID-19 pandemic.

97 MATHEMATICS AND COMPUTING↗

Study of fluid mechanical helium argon ion laser

An approach to an argon ion laser based on gasdynamic techniques is presented. Improvement in efficiency and power output are achieved by eliminating high heat rejection problems and plasma confinement of the seal-off conventional lasers. The process of producing population inversion between the same energy levels, as in the conventional argon ion laser, has been divided into two phases by separating each other from the processes of ionization and subsequent excitation. Line drawings and graphs are included to amplify the theoretical presentation.

Source record↗

Towards automatic Markov reliability modeling of computer architectures

The analysis and evaluation of reliability measures using time-varying Markov models is required for Processor-Memory-Switch (PMS) structures that have competing processes such as standby redundancy and repair, or renewal processes such as transient or intermittent faults. The task of generating these models is tedious and prone to human error due to the large number of states and transitions involved in any reasonable system. Therefore model formulation is a major analysis bottleneck, and model verification is a major validation problem. The general unfamiliarity of computer architects with Markov modeling techniques further increases the necessity of automating the model formulation. This paper presents an overview of the Automated Reliability Modeling (ARM) program, under development at NASA Langley Research Center. ARM will accept as input a description of the PMS interconnection graph, the behavior of the PMS components, the fault-tolerant strategies, and the operational requirements. The output of ARM will be the reliability of availability Markov model formulated for direct use by evaluation programs. The advantages of such an approach are (a) utility to a large class of users, not necessarily expert in reliability analysis, and (b) a lower probability of human error in the computation.

Liceaga, C. A.↗

The Pack Method for Compressive Tests of Thin Specimens of Materials Used in Thin-Wall Structures

The strength of modern lightweight thin-wall structures is generally limited by the strength of the compression members. An adequate design of these members requires a knowledge of the compressive stress-strain graph of the thin-wall material. The "pack" method was developed at the National Bureau of Standards with the support of the National Advisory Committee for Aeronautics to make possible a determination of compressive stress-strain graphs for such material. In the pack test an odd number of specimens are assembled into a relatively stable pack, like a "pack of cards." Additional lateral stability is obtained from lateral supports between the external sheet faces of the pack and outside reactions. The tests seems adequate for many problems in structural research.

Aitchison, C S↗

Becoming Reactive by Concretization

One way to build a reactive system is to construct an action table indexed by the current situation or stimulus. The action table describes what course of action to pursue for each situation or stimulus. This paper describes an incremental approach to constructing the action table through achieving goals with a hierarchical search system. These hierarchies are generated with transformations called concretizations, which add constraints to a problem and which can reduce the search space. The basic idea is that an action for a state is looked up in the action table and executed whenever the action table has an entry for that state; otherwise, a path is found to the nearest (cost-wise in a graph with costweighted arcs) state that has a mappring from a state in the next highest hierarchy. For each state along the solution path, the successor state in the path is cached in the action table entry for that state. Without caching, the hierarchical search system can logarithmically reduce search. When the table is complete the system no longer searches: it simply reacts by proceeding to the state listed in the table for each state. Since the cached information is specific only to the nearest state in the next highest hierarchy and not the goal, inter-goal transfer of reactivity is possible. To illustrate our approach, we show how an implemented hierarchical search system can completely reactive.

Prieditis, Armand↗

Sparse Approximate Multifrontal Factorization with Butterfly Compression for High-Frequency Wave Equations

In this work, we present a fast and approximate multifrontal solver for large-scale sparse linear systems arising from finite-difference, finite-volume or finite-element discretization of high-frequency wave equations. The proposed solver leverages the butterfly algorithm and its hierarchical matrix extension for compressing and factorizing large frontal matrices via graph-distance guided entry evaluation or randomized matrix-vector multiplication-based schemes. Complexity analysis and numerical experiments demonstrate $\mathcal{O}(N\log^2 N)$ computation and $\mathcal{O}(N)$ memory complexity when applied to an $N\times N$ sparse system arising from 3D high-frequency Helmholtz and Maxwell problems.

97 MATHEMATICS AND COMPUTING↗

A Functional All-Hazard Approach to Critical Infrastructure Dependency Analysis

The critical infrastructures protection landscape is a vast and varied pattern of independent, but interconnected infrastructure systems that are essential to the function of our modern society. The U.S. policy on critical infrastructure protection has been continually evolving since the “President’s Commission on Critical Infrastructure Protection” was published in 1997. In response to these policies, federal, state, and local governments, along with research institutions, have invested a substantial amount of time and effort into identifying and analyzing critical infrastructure, their functions, and dependencies/interdependencies to better understand their vulnerabilities. To date, the ability to assess vulnerabilities, resiliency, and priorities for protecting interdependent critical infrastructure systems from an all-hazards perspective remains a difficult problem. In this paper we introduce the All-Hazards Analysis (AHA) methodology, which provides an integrated functional basis across infrastructure systems, through the implementation of a common language and a scalable level of decomposition to effectively evaluate the resilience of interconnected infrastructure systems. AHA models infrastructure systems as directed multidimensional graphs, which enable the evaluation of cross-sector interdependencies prior to, during, and after disruptive events. Finally, and by design, AHA enables the cross linking of data taxonomies to enable more effective data sharing, such as the National Critical Functions (NCF) and Infrastructure Data Taxonomy (IDT).

02 PETROLEUM↗