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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 217 records · Page 12
All sourcesNASA NTRSDOE OSTI
NASA NTRS1985

Performance evaluation of a simulated data-flow computer with low-resolution actors

Basic problems related to the exploitation of parallelism in a program include sequencing of the instructions and communication of the data. It is pointed out that the data-flow approach offers an elegant solution to the sequencing problem, since all data dependencies are automatically handled and only instructions with ready input sets are activated. It is shown that a change in the level of subcomputations (actors) affects communications costs. The concept of variable resolution is discussed, and the testbed environment is examined. Attention is given to the architecture of the processing elements, the communication network, and the simulators. A description of the analytical model is also provided. Simulation and results are discussed, taking into account test programs and allocation, the variation of the number of processing elements, the variation of the resolution in directed acyclic graphs, performance in processing loops, and array handling.

Gaudiot, J. L.↗
NASA NTRS1986

Rapid torque-limited line-of-sight pointing of SCOLE (Spacecraft Control Laboratory Experiment) configuration

The design concept of a control for rapid torque-limited slewing of a rigid-mast version of the NASA SCOLE configuration is presented and demonstrated by means of numerical simulation. The time-optimal control problem for the system is decomposed into separate single-axis problems, expanding analytically the implicit nonlinear transcendental expression for the SCOLE line-of-sight error, and the final Euler attitude angles and slew angles are determined. The simulation results are presented in tables and graphs, and it is found that bang-bang or bang-pause-bang slew maneuvers with control moment applied to the Shuttle and control force applied to the reflector, and with a 5-deg/s slew-rate limit, produce the best pointing accuracy and the shortest slew times, although the specified line-of-sight error of 0.02 deg cannot be achieved using such open-loop single-axis maneuvers.

Lin, J. G.↗
DOE OSTI2022

Graph-based featurization methods for classifying small molecule compounds

For over a decade, drug-induced liver injury (DILI) has posed significant drawbacks in the synthesis and development of drugs and remains a consequential concern. With finite success within the existing preclinical models, DILI is one of the main causes of drug withdrawal or termination from the market. Particularly, this withdrawal occurs during the late stages of drug development (Kullak-Ublick, 2017). Since DILI is difficult to diagnose and treat, it has become an obstacle in the drug production market that in turn affects clinicians, pharmaceutical companies, and consumers. We propose a method for learning features of DILI-positive drugs based on the graphical relationships and patterns they possess within a network of biological databases. We also train various statistical and machine learning models on these learned features in order to classify the drugs as DILI-positive or negative. Our methods include Random Forest, Neural networks, and logistic regression classification. We utilize labeled DILI-positive and DILI-negative datasets, which were developed by the FDA and the National center for toxicological research, as well as additional literature datasets (Thakkar, 2020) in order to validate our results and assess our featurization and model accuracy.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

Post-Disaster Microgrid Formation for Enhanced Distribution System Resilience

This paper proposes a deep reinforcement learning (DRL) based approach for post-disaster critical load restoration in active distribution systems to form microgrids through network reconfiguration to minimize critical load curtailments. Distribution networks are represented as graph networks, and optimal network configurations with microgrids are obtained by searching for the optimal spanning forest. The constraints to the research question being explored are the radial topology and power balance. Unlike existing analytical and population-based approaches, which necessitate the repetition of entire analyses and computation for each outage scenario to find the optimal spanning forest, the proposed approach, once properly trained, can quickly determine the optimal, or near-optimal, spanning forest even when outage scenarios change. When multiple lines fail in the system, the proposed approach forms microgrids with distributed energy resources in active distribution systems to reduce critical load curtailment. The proposed DRL-based model learns the action-value function using the REINFORCE algorithm, which is a model-free reinforcement learning technique based on stochastic policy gradients. A case study was conducted on a 33-node distribution test system, demonstrating the effectiveness of the proposed approach for post-disaster critical load restoration.

active distribution systems↗
DOE OSTI2019

Dynamic Nested Tracking Graphs

This work describes an approach for the interactive visual analysis of large-scale simulations, where numerous superlevel set components and their evolution are of primary interest. The approach first derives, at simulation runtime, a specialized Cinema database that consists of images of component groups, and topological abstractions. This database is processed by a novel graph operation-based nested tracking graph algorithm (GO-NTG) that dynamically computes NTGs for component groups based on size, overlap, persistence, and level thresholds. Finally, the resulting NTGs are in turn used in a feature-centered visual analytics framework to query specific database elements and update feature parameters, facilitating flexible post hoc analysis.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS1980

A microprocessor based high speed space-borne packet switch

The design and performance evaluation of a single microprocessor based packet switch for use on-board a satellite are presented. The primary design criterion is to maximize the system throughput. A number of protocols and their impact on the switch design are discussed. Stem and processor hardware architectures are described. The flow charts of the software required to accomplish the essential functions are presented and modification needed for use in a multisatellite network are also indicated. Maximum throughput attainable is calculated, desirable characteristics of microprocessors for this application are pointed out. A queue theoretic model of the packet switch has been developed. Analytical relationships of the average waiting times and the queue sizes at the queues and the overall average response time with the various design parameters of the switch have been obtained. A number of graphs showing the effect of variation in the number of input and output lines, data rates, destination functions, speed of output lines and some other design parameters on the performance of the switch are presented and discussed.

Arozullah, M.↗
DOE OSTI2024

Theoretical guarantees for permutation-equivariant quantum neural networks

Despite the great promise of quantum machine learning models, there are several challenges one must overcome before unlocking their full potential. For instance, models based on quantum neural networks (QNNs) can suffer from excessive local minima and barren plateaus in their training landscapes. Recently, the nascent field of geometric quantum machine learning (GQML) has emerged as a potential solution to some of those issues. The key insight of GQML is that one should design architectures, such as equivariant QNNs, encoding the symmetries of the problem at hand. Here, we focus on problems with permutation symmetry (i.e., symmetry group $S_n$), and show how to build $S_n$-equivariant QNNs We provide an analytical study of their performance, proving that they do not suffer from barren plateaus, quickly reach overparametrization, and generalize well from small amounts of data. To verify our results, we perform numerical simulations for a graph state classification task. Our work provides theoretical guarantees for equivariant QNNs, thus indicating the power and potential of GQML.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
NASA NTRS1984

Development of acceptance criteria for batches of silane primer for external tank thermal protection system bonding applications

Silane primers for use as thermal protection on external tanks were subjected to various analytic techniques to determine the most effective testing method for silane lot evaluation. The analytic methods included high performance liquid chromatography, gas chromatography, thermogravimetry (TGA), and fourier transform infrared spectroscopy (FTIR). It is suggested that FTIR be used as the method for silane lot evaluation. Chromatograms, TGA profiles, bar graphs showing IR absorbances, and FTIR spectra are presented.

Mikes, F.↗
NASA NTRS1988

Simplified Drag Analysis For Nozzles

Measurements, graphs and calculations combined to give realistic and convenient estimates. Pitot-tube measurements made at various distances from wall to obtain pressure distribution in viscous boundary layer. Pressure readings converted to mach numbers, and analytical expressions for mach-number profile of boundary layer fitted to mach numbers derived from pressure by adjusting shape factor. Applied to jet-expansion devices in turbines, compressors, and variety of other equipment.

Wagner, W. R.↗
DOE OSTI2023

Accelerating network layouts using graph neural networks

Graph layout algorithms used in network visualization represent the first and the most widely used tool to unveil the inner structure and the behavior of complex networks. Current network visualization software relies on the force-directed layout (FDL) algorithm, whose high computational complexity makes the visualization of large real networks computationally prohibitive and traps large graphs into high energy configurations, resulting in hard-to-interpret “hairball” layouts. Here we use Graph Neural Networks (GNN) to accelerate FDL, showing that deep learning can address both limitations of FDL: it offers a 10 to 100 fold improvement in speed while also yielding layouts which are more informative. We analytically derive the speedup offered by GNN, relating it to the number of outliers in the eigenspectrum of the adjacency matrix, predicting that GNNs are particularly effective for networks with communities and local regularities. Finally, we use GNN to generate a three-dimensional layout of the Internet, and introduce additional measures to assess the layout quality and its interpretability, exploring the algorithm’s ability to separate communities and the link-length distribution. The novel use of deep neural networks can help accelerate other network-based optimization problems as well, with applications from reaction-diffusion systems to epidemics.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS1977

Genesis of howardites, diogenites, and eucrites

The reported investigation was mainly concerned with the precise determinations of major-, minor-, and trace-element abundances, especially the REE abundances in the bulk howardites in order to establish the bulk rock composition for the future chemical-mineralogical, petrographic studies of different rock types on the chemically unique howardites and diogenites if they exist. From the chemical data for the major-element abundances and the REE patterns of the howardites analyzed, it is evident that these howardites are predominantly composed of eucritic and diogenitic components. The analytical results for howardites and diogenites are shown in two tables together with the results for CRB-1. The chondritic normalized K, Sr, Ba, REE, Hf, and Sc abundances of these howardites are plotted in two graphs.

Fukuoka, T.↗
NASA NTRS1996

Computer-Based Mathematics Instructions for Engineering Students

Almost every engineering course involves mathematics in one form or another. The analytical process of developing mathematical models is very important for engineering students. However, the computational process involved in the solution of some mathematical problems may be very tedious and time consuming. There is a significant amount of mathematical software such as Mathematica, Mathcad, and Maple designed to aid in the solution of these instructional problems. The use of these packages in classroom teaching can greatly enhance understanding, and save time. Integration of computer technology in mathematics classes, without de-emphasizing the traditional analytical aspects of teaching, has proven very successful and is becoming almost essential. Sample computer laboratory modules are developed for presentation in the classroom setting. This is accomplished through the use of overhead projectors linked to graphing calculators and computers. Model problems are carefully selected from different areas.

Khan, Mustaq A.↗
NASA NTRS1987

Incompressible magnetohydrodynamic surface waves - Nonlinear aspects

The nonlinear properties of MHD surface waves in the solar atmosphere are investigated analytically, assuming that the fluid is incompressible and that the waves are confined to a single surface, with semiinfinite regions on both sides. The governing equations are derived in detail, and qualitative results are presented in a graph. For propagating waves, second-order terms in the wave amplitude are found to lead to wave steepening at leading or trailing edges, the steepening rate becoming very large as the threshold for the linear Kelvin-Helmholtz instability is approached. Second-order effects on standing waves include crest and trough sharpening (increasing with time), a current independent of distance on the surface but decreasing exponentially with distance from the surface, and pressure-field fluctuations of infinite extent. It is suggested that these effects could account for a large fraction of solar-atmosphere heating.

Hollweg, Joseph V.↗
NASA NTRS1988

Primitive numerical simulation of circular Couette flow - Carrousel wind tunnel nonturbulent solutions

The azimuthal-invariant, three-dimensional cylindrical, incompressible Navier-Stokes equations are solved to steady state for a finite-length, physically realistic model. The numerical method relies on an alternating-direction implicit scheme that is formally second-order accurate in space and first-order accurate in time. The equations are linearized and uncoupled by evaluating variable coefficients at the previous time iteration. Wall grid clustering is provided by a Roberts transformation in radial and axial directions. A vorticity-velocity formulation is found to be preferable to a vorticity-streamfunction approach. Subject to no-slip, Dirichlet boundary conditions, except for the inner cylinder rotation velocity (impulsive start-up) and zero-flow initial conditions, nonturbulent solutions are obtained for sub- and supercritical Reynolds numbers of 100 to 400 for a finite geometry where R(outer)/R(inner) = 1.5, H/R(inner) = 0.73, and H/Delta-R = 1.5. An axially-stretched model solution is shown to asymptotically approach the one-dimensional analytic Couette solution at the cylinder midheight. Flowfield change from laminar to Taylor-vortex flow is discussed as a function of Reynolds number. Three-dimensional velocities, vorticity, and streamfunction are presented via two-dimensional graphs and three-dimensional surface and contour plots.

Hasiuk, Jan↗
NASA NTRS1989

Adaptive structures

The fundamental principles of the adaptive structures concept and its applications to current and planned space missions are reviewed and illustrated with diagrams, drawings, graphs, and photographs. An adaptive structure is defined as one which can be modified to meet mission requirements, either by remote commands or automatically in response to external stimuli. Topics addressed include the need for adaptive structures, analytical models, ground testing, sensor/actuator-structure interactions, structural concepts, active damping, wave propagation in large structures, the selection of active member locations, and on-orbit system identification. Particular attention is given to adaptive structures being developed for the NASA Large Deployable Reflector and Optical Interferometer projects.

Wada, Ben K.↗
NASA NTRS1994

ATAMM enhancement and multiprocessing performance evaluation

The algorithm to architecture mapping model (ATAAM) is a Petri net based model which provides a strategy for periodic execution of a class of real-time algorithms on multicomputer dataflow architecture. The execution of large-grained, decision-free algorithms on homogeneous processing elements is studied. The ATAAM provides an analytical basis for calculating performance bounds on throughput characteristics. Extension of the ATAMM as a strategy for cyclo-static scheduling provides for a truly distributed ATAMM multicomputer operating system. An ATAAM testbed consisting of a centralized graph manager and three processors is described using embedded firmware on 68HC11 microcontrollers.

Stoughton, John W.↗
NASA NTRS2016

A New Paradigm for Quality Metrics

SMA metrics have been traditionally represented as either leading and lagging indicators. Traditional ways of viewing these metrics and trending the data is via graphs which reflect one attribute in each graph. The KSC Independent Assessment Team developed a non-traditional method for expressing variation as a ratio (the deviation between the Expected and Actual). This method allows different measures to be plotted on the same graph for trending and comparison to provide a holistic view across a particular theme or discipline. Since all measurements are a ratio of variation and dimensionless, this variation-based metrics approach can be used a new analytical tool which is complimentary to existing value-added metrics tools.

Dimensionless↗
NASA NTRSDate not supplied

Improvements on Low-Density Parity-Check (LDPC) Codes and High-Performance Neuromorphic Engineering for Communication Systems

Belief propagation (BP) on LDPC codes is an iterative decoding algorithm that performs information transfer on the Tanner graph, which represents the code. In each iteration, the algorithm exchanges information (LLR) between variable nodes and check nodes through the edges of the graph. LLR values represent the probability that a given bit in a transmitted codeword equals 0 or 1, given a received word. In the hardware part, recent advancements in intelligent technologies, such as artificial intelligence, big data analytics, autonomous vehicles, and speech/image recognition, have heightened the demand for faster calculations and reduced energy consumption.

Danilo Barrionuevo↗