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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 811 records · Page 45
All sourcesNASA NTRSDOE OSTI
NASA NTRS2004

Software for Preprocessing Data from Rocket-Engine Tests

Three computer programs have been written to preprocess digitized outputs of sensors during rocket-engine tests at Stennis Space Center (SSC). The programs apply exclusively to the SSC E test-stand complex and utilize the SSC file format. The programs are the following: Engineering Units Generator (EUGEN) converts sensor-output-measurement data to engineering units. The inputs to EUGEN are raw binary test-data files, which include the voltage data, a list identifying the data channels, and time codes. EUGEN effects conversion by use of a file that contains calibration coefficients for each channel. QUICKLOOK enables immediate viewing of a few selected channels of data, in contradistinction to viewing only after post-test processing (which can take 30 minutes to several hours depending on the number of channels and other test parameters) of data from all channels. QUICKLOOK converts the selected data into a form in which they can be plotted in engineering units by use of Winplot (a free graphing program written by Rick Paris). EUPLOT provides a quick means for looking at data files generated by EUGEN without the necessity of relying on the PV-WAVE based plotting software.

Cheng, Chiu-Fu↗
NASA NTRS2005

Analysis of Wallops Flight Test Data Through an Automated COTS System

During the summer of 2004 NASA Langley Research Center flight tested a Synthetic Vision System (SVS) at the Reno/Tahoe International Airport (RNO) and the Wallops Flight Facility (WAL). The SVS included a Runway Incursion Prevention System (RIPS) to improve pilot situational awareness while operating near and on the airport surface. The flight tests consisted of air and ground operations to evaluate and validate the performance of the system. This paper describes the flight test and emphasizes how positioning data was collected, post processed and analyzed through the use of a COTS-derived software system. The system that was developed to analyze the data was constructed within the MATLAB(TM) environment. The software was modified to read the data, perform several if-then scenarios and produce the relevant graphs, figures and tables.

Blackstock, Dexter Lee↗
NASA NTRS2006

Spotlight-8 Image Analysis Software

Spotlight is a cross-platform GUI-based software package designed to perform image analysis on sequences of images generated by combustion and fluid physics experiments run in a microgravity environment. Spotlight can perform analysis on a single image in an interactive mode or perform analysis on a sequence of images in an automated fashion. Image processing operations can be employed to enhance the image before various statistics and measurement operations are performed. An arbitrarily large number of objects can be analyzed simultaneously with independent areas of interest. Spotlight saves results in a text file that can be imported into other programs for graphing or further analysis. Spotlight can be run on Microsoft Windows, Linux, and Apple OS X platforms.

Klimek, Robert↗
DOE OSTI2025

Harnessing distributed GPU computing for generalizable graph convolutional networks in power grid reliability assessments

Although machine learning (ML) has emerged as a powerful tool for rapidly assessing grid contingencies, prior studies have largely considered a static grid topology in their analyses. This limits their application, since they need to be re-trained for every new topology. Here, this paper explores the development of generalizable graph convolutional network (GCN) models by pre-training them across a range of grid topologies and contingency types. We found that a GCN model with auto-regressive moving average (ARMA) layers with a line graph representation of the grid offered the best predictive performance in predicting voltage magnitudes (VM) and voltage angles (VA). We introduced the concept of phantom nodes to consider disparate grid topologies with a varying number of nodes and lines. For pre-training the GCN ARMA model across a variety of topologies, distributed graphics processing unit (GPU) computing afforded us significant training scalability. The predictive performance of this model on grid topologies that were part of the training data is substantially better than the direct current (DC) approximation. Although direct application of the pre-trained model to topologies that are not part of the grid is not particularly satisfactory, fine-tuning with small amounts of data from a specific topology of interest significantly improves predictive performance. In general, this paper highlights the feasibility of training large-scale GNN models to assess the reliability of power grids by considering a wide variety of grid topologies and contingency types. With the advent of foundational models in ML and the exponential increase in GPU computing clusters, generalizable ML models will significantly enhance how utilities manage power systems and make decisions in real-time or near-real-time.

24 - POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2017

Capturing the two-way hydromechanical coupling effect on fluid-driven fracture in a dual-graph lattice beam model

Fluid-driven fractures of brittle rock is simulated via a dual-graph lattice model. The new discrete hydromechanical model incorporates a two-way coupling mechanism between the discrete element model and the flow network. Through adopting an operator-split algorithm, the coupling model is able to replicate the transient poroelasticity coupling mechanism and the resultant Mandel-Cryer hydromechanical coupling effect in a discrete mechanics framework. As crack propagation, coalescence and branching are all path-dependent and irreversible processes, capturing this transient coupling effect is important for capturing the essence of the fluid-driven fracture in simulations. Injection simulations suggest that the onset and propagation of fractures is highly sensitive to the ratio between the injection rate and the effective permeability. Moreover, we show that in a permeable rock, the borehole breakdown pressure, the pressure at which fractures start to grow from the borehole, depends on both the given ratio between injection rate and permeability and the Biot coefficient.

58 GEOSCIENCES↗
DOE OSTI2023

Ensuring thermodynamic consistency with invertible coarse-graining

Coarse-grained models are a core computational tool in theoretical chemistry and biophysics. A judicious choice of a coarse-grained model can yield physical insights by isolating the essential degrees of freedom that dictate the thermodynamic properties of a complex, condensed-phase system. The reduced complexity of the model typically leads to lower computational costs and more efficient sampling compared with atomistic models. Designing “good” coarse-grained models is an art. Generally, the mapping from fine-grained configurations to coarse-grained configurations itself is not optimized in any way; instead, the energy function associated with the mapped configurations is. In this work, we explore the consequences of optimizing the coarse-grained representation alongside its potential energy function. We use a graph machine learning framework to embed atomic configurations into a low-dimensional space to produce efficient representations of the original molecular system. Because the representation we obtain is no longer directly interpretable as a real-space representation of the atomic coordinates, we also introduce an inversion process and an associated thermodynamic consistency relation that allows us to rigorously sample fine-grained configurations conditioned on the coarse-grained sampling. We illustrate that this technique is robust, recovering the first two moments of the distribution of several observables in proteins such as chignolin and alanine dipeptide.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

An Intelligent Garbage Sorting System Based on Edge Computing and Visual Understanding of Social Internet of Vehicles

In order to enable Social Internet of Vehicles devices to achieve the purpose of intelligent and autonomous garbage classification in a public environment, while avoiding network congestion caused by a large amount of data accessing the cloud at the same time, it is therefore considered to combine mobile edge computing with Social Internet of Vehicles to give full play to mobile edge computing features of high bandwidth and low latency. At the same time, based on cutting-edge technologies such as deep learning, knowledge graph, and 5G transmission, the paper builds an intelligent garbage sorting system based on edge computing and visual understanding of Social Internet of Vehicles. First of all, for the massive multisource heterogeneous Social Internet of Vehicles big data in the public environment, different item modal data adopts different processing methods, aiming to obtain a visual understanding model. Secondly, using the 5G network, the model is deployed on the edge device and the cloud for cloud-side collaborative management, aiming to avoid the waste of edge node resources, while ensuring the data privacy of the edge node. Finally, the Social Internet of Vehicles devices is used to make intelligent decision-making on the big data of the items. First, the items are judged as garbage, and then the category is judged, and finally the task of grabbing and sorting is realized. The experimental results show that the system proposed in this paper can efficiently process the big data of Social Internet of Vehicles and make valuable intelligent decisions. At the same time, it also has a certain role in promoting the promotion of Social Internet of Vehicles devices.

Shen, Xuehao↗
DOE OSTI2015

PANTHER. Pattern ANalytics To support High-performance Exploitation and Reasoning.

Sandia has approached the analysis of big datasets with an integrated methodology that uses computer science, image processing, and human factors to exploit critical patterns and relationships in large datasets despite the variety and rapidity of information. The work is part of a three-year LDRD Grand Challenge called PANTHER (Pattern ANalytics To support High-performance Exploitation and Reasoning). To maximize data analysis capability, Sandia pursued scientific advances across three key technical domains: (1) geospatial-temporal feature extraction via image segmentation and classification; (2) geospatial-temporal analysis capabilities tailored to identify and process new signatures more efficiently; and (3) domain- relevant models of human perception and cognition informing the design of analytic systems. Our integrated results include advances in geographical information systems (GIS) in which we discover activity patterns in noisy, spatial-temporal datasets using geospatial-temporal semantic graphs. We employed computational geometry and machine learning to allow us to extract and predict spatial-temporal patterns and outliers from large aircraft and maritime trajectory datasets. We automatically extracted static and ephemeral features from real, noisy synthetic aperture radar imagery for ingestion into a geospatial-temporal semantic graph. We worked with analysts and investigated analytic workflows to (1) determine how experiential knowledge evolves and is deployed in high-demand, high-throughput visual search workflows, and (2) better understand visual search performance and attention. Through PANTHER, Sandia's fundamental rethinking of key aspects of geospatial data analysis permits the extraction of much richer information from large amounts of data. The project results enable analysts to examine mountains of historical and current data that would otherwise go untouched, while also gaining meaningful, measurable, and defensible insights into overlooked relationships and patterns. The capability is directly relevant to the nation's nonproliferation remote-sensing activities and has broad national security applications for military and intelligence- gathering organizations.

58 GEOSCIENCES↗
NASA NTRS1972

Kinematic distributions for electron pair production by muons

Cross sections and kinematic distributions for the trident production process plus or negative muon plus charge yields plus or minus muon plus electron plus positron plus charge (with charge = dipion moment and Fe) are given for beam energies of 100 to 300 GeV at fixed (electron positron) masses from 5 to 15 GeV. This process is interesting as a test of quantum electrodynamics at high energies, and in particular as a test of the form of the photon propagator at large timelike (four-momentum) squared. For this purpose, it is desirable to impose kinematic cuts that favor those Bethe-Heitler graphs which contain a timelike photon propagator. It is found that there are substantial differences between the kinematic distributions for the full Bethe-Heitler matrix element and the distributions for the two timelike-photon graphs alone; these differences can be exploited in the selection of appropriate kinematic cuts.

Linsker, R.↗
NASA NTRS1991

Representations of mechanical assembly sequences

Five types of representations for assembly sequences are reviewed: the directed graph of feasible assembly sequences, the AND/OR graph of feasible assembly sequences, the set of establishment conditions, and two types of sets of precedence relationships. (precedence relationships between the establishment of one connection between parts and the establishment of another connection, and precedence relationships between the establishment of one connection and states of the assembly process). The mappings of one representation into the others are established. The correctness and completeness of these representations are established. The results presented are needed in the proof of correctness and completeness of algorithms for the generation of mechanical assembly sequences.

Homem De Mello, Luiz S.↗
NASA NTRS1989

Impact cratering: A geologic process

The mechanisms involved in the formation of impact craters are examined theoretically, reviewing the results of recent investigations. Topics addressed include crater morphology, stress waves in solids, the contact and compression stage, the excavation stage, and ejecta deposits. Consideration is given to the scaling of crater dimensions, the crater modification stage, multiring basins, cratered landscapes, atmospheric interactions, and the implications of impact cratering for planetary evolution. Extensive diagrams, graphs, tables, and images of typical craters are provided.

Melosh, H. J.↗
NASA NTRS2000

Analysis of Complexity Evolution Management and Human Performance Issues in Commercial Aircraft Automation Systems

Autoflight systems in the current generation of aircraft have been implicated in several recent incidents and accidents. A contributory aspect to these incidents may be the manner in which aircraft transition between differing behaviours or 'modes.' The current state of aircraft automation was investigated and the incremental development of the autoflight system was tracked through a set of aircraft to gain insight into how these systems developed. This process appears to have resulted in a system without a consistent global representation. In order to evaluate and examine autoflight systems, a 'Hybrid Automation Representation' (HAR) was developed. This representation was used to examine several specific problems known to exist in aircraft systems. Cyclomatic complexity is an analysis tool from computer science which counts the number of linearly independent paths through a program graph. This approach was extended to examine autoflight mode transitions modelled with the HAR. A survey was conducted of pilots to identify those autoflight mode transitions which airline pilots find difficult. The transitions identified in this survey were analyzed using cyclomatic complexity to gain insight into the apparent complexity of the autoflight system from the perspective of the pilot. Mode transitions which had been identified as complex by pilots were found to have a high cyclomatic complexity. Further examination was made into a set of specific problems identified in aircraft: the lack of a consistent representation of automation, concern regarding appropriate feedback from the automation, and the implications of physical limitations on the autoflight systems. Mode transitions involved in changing to and leveling at a new altitude were identified across multiple aircraft by numerous pilots. Where possible, evaluation and verification of the behaviour of these autoflight mode transitions was investigated via aircraft-specific high fidelity simulators. Three solution approaches to concerns regarding autoflight systems, and mode transitions in particular, are presented in this thesis. The first is to use training to modify pilot behaviours, or procedures to work around known problems. The second approach is to mitigate problems by enhancing feedback. The third approach is to modify the process by which automation is designed. The Operator Directed Process forces the consideration and creation of an automation model early in the design process for use as the basis of the software specification and training.

Vakil, Sanjay S.↗
DOE OSTI2018

Human attitude analysis based on fuzzy soft differential equations with Bonferroni mean

In this paper, we model a system of fuzzy soft differential equations to analyze the behavior over the time of an individual depending on their companion’s actions under any particular situation against some decision. The Bonferroni mean (BM) is a very useful tool for group decision-making problems when arguments are interrelated to each other as Bonferroni mean can capture the interrelationship of the individual arguments. Using this ability of BM, we define Bonferroni fuzzy soft matrix (BFSM) and weighted Bonferroni fuzzy soft matrix (WBFSM) for data representation. WBFSM is a decision matrix and provide the optimum fuzzy soft constant (OFSC) which is the key element of fuzzy soft differential equation. By utilizing the OFSC, we develop a system of fuzzy soft differential equations to study a dynamical process with nonlinear uncertain and vague data. Second, we present a novel efficient technique for analyzing the future attitude of people due to their present decisions. To illustrate the practicality and feasibility of proposed technique an illustrative example is also discussed with the help of phase portrait and line graphs.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2023

A Data Processing Pipeline for Socio-Technical Network Analysis [Slides]

With the rapid adoption of emerging technologies, there is a need to catalog and model sociotechnical interdependencies that have been historically used to influence the operation of Critical Infrastructure networks including the impacts of mergers and acquisitions, hostile takeovers, and foreign investment. Our research intends to address this need with two primary contributions. First, we have developed a data curation and processing pipeline to generate sociotechnical networks extracted from a variety of data sources including SEC filings and infrastructure asset databases. The pipeline, implemented in Apache Airflow, extracts and normalizes the representation of entities and relations, specified within ontologies. Second, networks produced by our pipeline enable the development of graph-theoretic metrics that consider the properties of network components in addition to its topology. Measures of network complexity, such as degree distribution, reachability analyses, temporal analysis, and community detection may be adapted to indicate adversarial organizational influence. Our intent is to provide an extensible, machine-actionable approach to quickly communicate such models, reproduce previous results, and adapt them to new, unanticipated situations.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS1977

Spontaneous emission from ScF in a supersonic mixing flame

An investigation was conducted of the two reactions: Sc + F2 yields ScF(asterisk) + F and Y + Cl2 yields YCl(asterisk) + Cl. Experiments were designed for studying the reactions under the relatively high pressure conditions (5-20 torr) appropriate for chemical laser operation. A shock tube was used to provide a short duration flow through a supersonic nozzle array. Shock wave heating is used to dissociate the ScCl3 or YCl3 at temperatures of about 6000 K, before the gases are accelerated and expanded through the supersonic nozzle array. The expanded primary flow is then mixed with a secondary flow of F2 introduced through slots at the trailing edge of each nozzle blade. Graphs show the temporal behavior of the visible spontaneous emission over the range from 3000 to 9000 A for a typical test condition, a microdensitometer tracing of the visible emission over the range from 4000 to 7000 A, and the spontaneous emission from ScF(asterisk) obtained by computer image processing of intensity data.

Fischell, D. R.↗
DOE OSTI2016

Data Validation Package November 2015 Groundwater and Surface Water Sampling at the Old and New Rifle, Colorado, Processing Sites February 2016

Water samples were collected from 36 locations at New Rifle and Old Rifle, Colorado, Processing Sites. Duplicate samples were collected from New Rifle locations 0659 and 0855, and Old Rifle location 0304. One equipment blank was collected after decontamination of non-dedicated equipment used to collect one surface water sample. Sampling and analyses were conducted as specified in the Sampling and Analysis Plan for U.S. Department of Energy Office of Legacy Management Sites (LMS/PRO/S04351, continually updated). New Rifle Site Samples were collected at the New Rifle site from 16 monitoring wells and 7 surface locations in compliance with the December 2008 Groundwater Compliance Action Plan [GCAP] for the New Rifle, Colorado, Processing Site (LMS/RFN/S01920), with one exception: New Rifle location 0635 could not be sampled because it was inaccessible; a fence installed by the Colorado Department of Transportation prevents access to this location. DOE is currently negotiating access with the Colorado Department of Transportation. Analytes measured at the New Rifle site included contaminants of concern (COCs) (arsenic, molybdenum, nitrate + nitrite as nitrogen, selenium, uranium, and vanadium) ammonia as nitrogen, major cations, and major anions. Field measurements of total alkalinity, oxidation- reduction potential, pH, specific conductance, turbidity, and temperature were made at each location, and the water level was measured at each sampled well. A proposed alternate concentration limit (ACL) for vanadium of 50 milligrams per liter (mg/L), specific to the compliance (POC) wells (RFN-0217, -0659, -0664, and -0669) is included in the New Rifle GCAP. Vanadium concentrations in the POC wells were below the proposed ACL as shown in the time-concentration graphs in the Data Presentation section (Attachment 2). Time-concentration graphs from all other locations sampled are also included in Attachment 2. Sampling location RFN-0195 was misidentified for the June/August 2014 and November 2014 sampling events. (Well RFN-0609 was inadvertently sampled instead of RFN-0195 in 2014.) The results for RFN-0195 have been corrected, and are included in associated time-concentration graphs for this location. Recent results for RFN-0195 are consistent with established trends with the possible exception of vanadium. The most recent result for vanadium showed an increase over recent values. Vanadium concentrations at RFN-0195 and other locations will continue to be evaluated in the future to determine the potential for deviations from established trends. The surface water locations were sampled to monitor the impact of groundwater discharge. COC concentrations at Colorado River surface water locations RFN-0324 and RFN-0326, downgradient of the site, remained low and were consistent with historical results, as shown in the time-concentration graphs. COC concentrations did not indicate there are any impacts related to groundwater discharge to the river. In many cases, elevated COC concentrations at the New Rifle site pond locations were observed, as shown in the time-versus concentration graphs. As noted in the GCAP, this indicates impacts from groundwater discharge to the ponds. Old Rifle Site Samples were collected at the Old Rifle site from eight monitoring wells and five surface locations in compliance with the December 2001 Groundwater Compliance Action Plan for the Old Rifle, Colorado, UMTRA Project Site (GJ0-2000-177-TAR). Analytes measured at the Old Rifle site included COCs (selenium, uranium, and vanadium), major cations, and major anions. Field measurements of total alkalinity, oxidation-reduction potential, pH, specific conductance, turbidity, temperature, were made at each location, and the water level was measured at each sampled well. The monitoring strategy described in the GCAP is designed to determine progress of the natural flushing process in meeting compliance standards for site COCs. Standards for selenium and vanadium are the proposed ACLs of0.05 mg/L and 1.0 mg/L, respectively. For uranium the cleanup goal is the UMTRA standard of 0.044 mg/L or background, whichever is higher. As shown in the time concentration graphs, the uranium concentration exceeds the cleanup goal at groundwater monitoring locations RF0-0304, -0305, -0310, -0655, and -0656. The surface water locations were sampled to monitor the impact of groundwater discharge at Colorado River surface water locations adjacent to (RF0-0396) and downgradient of the site (RF0-0741). COC concentrations remain low and consistent with historical concentrations as shown in the time-concentration graphs (Attachment 2), which indicate no impacts from groundwater discharge to the river.

2015 Old and New Rifle↗
DOE OSTI2013

Effect of DC voltage pulses on memristor behavior.

Current knowledge of memristor behavior is limited to a few physical models of which little comprehensive data collection has taken place. The purpose of this research is to collect data in search of exploitable memristor behavior by designing and implementing tests on a HP Labs Rev2 Memristor Test Board. The results are then graphed in their optimal format for conceptualizing behavioral patterns. This series of experiments has concluded the existence of an additional memristor state affecting the behavior of memristors when pulsed with positively polarized DC voltages. This effect has been observed across multiple memristors and data sets. The following pages outline the process that led to the hypothetical existence and eventual proof of this additional state of memristor behavior.

Evans, Brian R.↗
DOE OSTI2016

Stationary stability for evolutionary dynamics in finite populations

Here, we demonstrate a vast expansion of the theory of evolutionary stability to finite populations with mutation, connecting the theory of the stationary distribution of the Moran process with the Lyapunov theory of evolutionary stability. We define the notion of stationary stability for the Moran process with mutation and generalizations, as well as a generalized notion of evolutionary stability that includes mutation called an incentive stable state (ISS) candidate. For sufficiently large populations, extrema of the stationary distribution are ISS candidates and we give a family of Lyapunov quantities that are locally minimized at the stationary extrema and at ISS candidates. In various examples, including for the Moran andWright–Fisher processes, we show that the local maxima of the stationary distribution capture the traditionally-defined evolutionarily stable states. The classical stability theory of the replicator dynamic is recovered in the large population limit. Finally we include descriptions of possible extensions to populations of variable size and populations evolving on graphs.

60 APPLIED LIFE SCIENCES↗