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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 55 records · Page 3
All sourcesNASA NTRSDOE OSTI
NASA NTRS1973

General aviation air traffic pattern safety analysis

A concept is described for evaluating the general aviation mid-air collision hazard in uncontrolled terminal airspace. Three-dimensional traffic pattern measurements were conducted at uncontrolled and controlled airports. Computer programs for data reduction, storage retrieval and statistical analysis have been developed. Initial general aviation air traffic pattern characteristics are presented. These preliminary results indicate that patterns are highly divergent from the expected standard pattern, and that pattern procedures observed can affect the ability of pilots to see and avoid each other.

Parker, L. C.↗
NASA NTRS1990

Neural net diagnostics for VLSI test

This paper discusses the application of neural network pattern analysis algorithms to the IC fault diagnosis problem. A fault diagnostic is a decision rule combining what is known about an ideal circuit test response with information about how it is distorted by fabrication variations and measurement noise. The rule is used to detect fault existence in fabricated circuits using real test equipment. Traditional statistical techniques may be used to achieve this goal, but they can employ unrealistic a priori assumptions about measurement data. Our approach to this problem employs an adaptive pattern analysis technique based on feedforward neural networks. During training, a feedforward network automatically captures unknown sample distributions. This is important because distributions arising from the nonlinear effects of process variation can be more complex than is typically assumed. A feedforward network is also able to extract measurement features which contribute significantly to making a correct decision. Traditional feature extraction techniques employ matrix manipulations which can be particularly costly for large measurement vectors. In this paper we discuss a software system which we are developing that uses this approach. We also provide a simple example illustrating the use of the technique for fault detection in an operational amplifier.

Lin, T.↗
NASA NTRS1980

SPS large array simulation

The computer programming efforts were directed primarily to beam pattern analysis. The computer programs used for simulation provide: verification of the reference design; definition of feasible departures such as quantized distributions; the study of far-out sidelobe roll-off characteristics; the analysis of errors and failures; illumination function analysis to develop beam patterns for efficient collection; and beam shaping synthesis to meet environmental constraints.

Rathjen, S.↗
NASA NTRS1986

Pattern recognition analysis of satellite data for tropical cyclone motion and intensity forecasts

An objective empirical analysis technique is employed to investigate the extent to which satellite-obtained measurements (GOES IR and TOVS data) of a tropical cyclone and its environment can be used to predict cyclone motion. The paper describes the procedure used to process the satellite derived data in order to optimize their possible predictive value, the technique used in developing the regression algorithms, and the results of testing these algorithms using the Lachenbrach and Mickey (1968) procedure. The data were examined alone and in conjunction with available nonsatellite climatological and persistence variables for each storm. These predictors are similar to those used in the National Hurricane Center (NHC) CLIPPER model. The performances obtained using the Nichols Research Corporation CLIPPER model and the NHC CLIPPER model are compared, using homogeneous data sets for the comparisons. Major differences in results were found to be related to differences in the models.

Hunter, Herbert↗
NASA NTRS2002

Program Instrumentation and Trace Analysis

Several attempts have been made recently to apply techniques such as model checking and theorem proving to the analysis of programs. This shall be seen as a current trend to analyze real software systems instead of just their designs. This includes our own effort to develop a model checker for Java, the Java PathFinder 1, one of the very first of its kind in 1998. However, model checking cannot handle very large programs without some kind of abstraction of the program. This paper describes a complementary scalable technique to handle such large programs. Our interest is turned on the observation part of the equation: How much information can be extracted about a program from observing a single execution trace? It is our intention to develop a technology that can be applied automatically and to large full-size applications, with minimal modification to the code. We present a tool, Java PathExplorer (JPaX), for exploring execution traces of Java programs. The tool prioritizes scalability for completeness, and is directed towards detecting errors in programs, not to prove correctness. One core element in JPaX is an instrumentation package that allows to instrument Java byte code files to log various events when executed. The instrumentation is driven by a user provided script that specifies what information to log. Examples of instructions that such a script can contain are: 'report name and arguments of all called methods defined in class C, together with a timestamp'; 'report all updates to all variables'; and 'report all acquisitions and releases of locks'. In more complex instructions one can specify that certain expressions should be evaluated and even that certain code should be executed under various conditions. The instrumentation package can hence be seen as implementing Aspect Oriented Programming for Java in the sense that one can add functionality to a Java program without explicitly changing the code of the original program, but one rather writes an aspect and compiles it into the original program using the instrumentation. Another core element of JPaX is an observation package that supports the analysis of the generated event stream. Two kinds of analysis are currently supported. In temporal analysis the execution trace is evaluated against formulae written in temporal logic. We have implemented a temporal logic evaluator on finite traces using the Maude rewriting system from SRI International, USA. Temporal logic is defined in Maude by giving its syntax as a signature and its semantics as rewrite equations. The resulting semantics is extremely efficient and can handle event streams of hundreds of millions events in few minutes. Furthermore, the implementation is very succinct. The second form of even stream analysis supported is error pattern analysis where an execution trace is analyzed using various error detection algorithms that can identify error-prone programming practices that may potentially lead to errors in some different executions. Two such algorithms focusing on concurrency errors have been implemented in JPaX, one for deadlocks and the other for data races. It is important to note, that a deadlock or data race potential does not need to occur in order for its potential to be detected with these algorithms. This is what makes them very scalable in practice. The data race algorithm implemented is the Eraser algorithm from Compaq, however adopted to Java. The tool is currently being applied to a code base for controlling a spacecraft by the developers of that software in order to evaluate its applicability.

Havelund, Klaus↗
DOE OSTI2020

Analysis of Electric Vehicle Charging Behavior Patterns with Function Principal Component Analysis Approach

This manuscript focused on analyzing electric vehicles’ (EV) charging behavior patterns with a functional data analysis (FDA) approach, with the goal of providing theoretical support to the EV infrastructure planning and regulation, as well as the power grid load management. 5-year real-world charging log data from a total of 455 charging stations in Kansas City, Missouri, was used. The focuses were placed on analyzing the daily usage occupancy variability, daily energy consumption variability, and station-level usage variability. Compared with the traditional discrete-based analysis models, the proposed FDA modeling approach had unique advantages in preserving the smooth function behavior of the data, bringing more flexibility in the modeling process with little required assumptions or background knowledge on independent variables, as well as the capability of handling time series data with different lengths or sizes. In addition to the patterns revealed in the EV charging station’s occupancy and energy consumption, the differences between EV driver’s charging time and parking time were analyzed and called for the needs for parking regulation and enforcement. The different usage patterns observed at charging stations located on different land-use types were also analyzed.

Engineering↗
DOE OSTI2026

Data for Spatial Analysis of Cell Patterning to Aid Genetic and Phenotypic Understanding of Grass Stomatal Density: A Case Study in Maize

Biological processes involve complex hierarchies where composite traits result from multiple component traits. However, holistically understanding of how sets of component traits interact to underpin genotype-to-phenotype relationships is generally lacking. Stomatal density (SD) is a tractable model system for exploring how high-throughput phenotyping (HTP) data could be exploited by a new spatial analysis approach to better understand a developmentally and functionally important trait. SD is a composite trait, resulting from various components related to cell identity and size, which are themselves governed by a series of spatio-developmental processes. Data from 192 recombinant inbred lines of maize [Zea mays (L.)] were analyzed by a new stomatal patterning phenotype (SPP) to (1) describe the average spatial probability distribution of the nearest neighboring stomata; (2) derive a core set of component traits related to cell size, cell packing, and positional probabilities; (3) build a structural equation model of component traits underlying SD; and (4) identify stomatal patterning quantitative trait loci (QTL). The core set of SPP-derived traits explained 74% of the variation in SD. Analyzing SPP component traits allowed some loci previously identified as generic SD QTL to be recognized as specific to lateral versus longitudinal elements of stomatal patterning. Therefore, this study highlights how novel insights can be gained by decomposing a composite trait (e.g., SD) into a set of component traits that were present in HTP data but not previously exploited.

AI/ML↗
DOE OSTI2023

ESnet Requirements Review Program Through the IRI Lens: A Meta-Analysis of Workflow Patterns Across DOE Office of Science Programs (Final Report)

The Department of Energy (DOE) ensures America’s security and prosperity by addressing its energy, environmental, and nuclear challenges through transformative science and technology solutions. The DOE’s Office of Science (SC) delivers groundbreaking scientific discoveries and major scientific tools that transform our understanding of nature and advance the energy, economic, and national security of the United States. The SC’s programs advance DOE mission science across a wide range of disciplines and have developed the research infrastructure needed to remain at the forefront of scientific discovery. The DOE SC’s world-class research infrastructure — exemplified by the 28 SC scientific user facilities — provides the research community with premier observational, experimental, computational, and network capabilities. Each user facility is designed to provide unique capabilities to advance core DOE mission science for its sponsor SC program and to stimulate a rich discovery and innovation ecosystem. Research communities gather and flourish around each user facility, bringing together diverse perspectives. A hallmark of many facilities is the large population of students, postdoctoral researchers, and early-career scientists who contribute as full-fledged users. These facility staff and users collaborate over years to devise new approaches to utilizing the user facility’s core capabilities. The history of the SC user facilities has many examples of wildly inventive researchers challenging operational orthodoxy to pioneer new vistas of discovery; for example, the use of the synchrotron X-ray light sources for study of proteins and other large biological molecules. This continual reinvention of the practice of science — as users and staff forge novel approaches expressed in research workflows — unlocks new discoveries and propels scientific progress. Within this research ecosystem, the high-performance computing (HPC) and networking user facilities stewarded by SC’s Advanced Scientific Computing Research (ASCR) program play a dynamic cross-cutting role, enabling complex workflows demanding high performance data, networking, and computing solutions. The DOE SC’s three HPC user facilities and the Energy Sciences Network (ESnet) high-performance research network serve all of the SC’s programs as well as the global research community. Argonne Leadership Computing Facility (ALCF), the National Energy Research Scientific Computing Center (NERSC), and Oak Ridge Leadership Computing Facility (OLCF) conceive, build, and provide access to a range of supercomputing, advanced computing, and large-scale data-infrastructure platforms, while ESnet interconnects DOE SC research infrastructure and enables seamless exchange of scientific data. All four facilities operate testbeds to expand the frontiers of computing and networking research. Together, the ASCR facilities enterprise seeks to understand and meet the needs and requirements across SC and DOE domain science programs and priority efforts, highlighted by the formal requirements reviews (RRs) methodology. In recent years, the research communities around the SC user facilities have begun experimenting with and demanding solutions integrated with HPC and data infrastructure. This rise of integrated-science approaches is documented in many community and high-level government reports. At the dawn of the era of exascale science and the acceleration of artificial intelligence (AI) innovation, there is a broad need for integrated computational, data, and networking solutions. In response to these drivers, DOE has developed a vision for an Integrated Research Infrastructure (IRI): To empower researchers to meld DOE’s world-class research tools, infrastructure, and user facilities seamlessly and securely in novel ways to radically accelerate discovery and innovation.

42 ENGINEERING↗
NASA NTRS2016

High-Temperature, Perhaps Silicic, Volcanism on Mars Evidenced by Tridymite Detection in High-SiO2 Sedimentary Rock at Gale Crater, Mars

The Mars Science Laboratory (MSL) rover, Curiosity, has been exploring sedimentary rocks within Gale crater since landing in August, 2012. On the lower slopes of Aeolis Mons (a.k.a. Mount Sharp), drill powder was collected from a high-silica (74 wt% SiO2) outcrop named Buckskin (BK). It was a surprise to find that the Buckskin sample contained significant amounts of the relatively rare silica polymorph tridymite. We describe the setting of the Buckskin sample, the detection of tridymite by the MSL Chemistry and Mineralogy (CheMin) X-ray diffraction instrument, and detection implications. Geologic setting: The Buckskin outcrop is part of the Murray formation exposed in the Marias Pass area. The formation was previously studied by CheMin in the Pahrump Hills member [1] where three samples of drill fines were analyzed (Confidence Hills (CH), Mojave2 (MJ) and Telegraph Peak (TP) [2]). Assuming approximately horizontal bedding, the Buckskin outcrop is approx.15 m stratigraphically above the bottom of the Pahrump Hills member. Mudstone, generally characterized by fine lamination, is the dominant depositional facies [1]. Buckskin Mineralogical and Chemical Composition: The CheMin instrument and XRD pattern analysis procedures have been previously discussed [3-6]. The diffraction pattern used for quantitative XRD analysis (Fig. 1) is the sum of the first 4 of 45 diffraction images. The remaining images are all characterized by both on-ring and off-ring diffraction spots that we attributed to poor grain motion and particle clumping. Coincident with particle clumping was a significant decrease in the intensity of the tridymite diffraction peaks (Fig. 2a). The derived mineralogical composition of the crystalline component (derived from the first 4 diffraction images) is given in Table 1. The tridymite is well-crystalline and its pattern is refined as monoclinic tridymite (Fig 1). Mineral chemical compositions were derived from XRD unit cell parameters or obtained from stoichiometry. The XRD-calculated amorphous component was 50 +/- 15 wt%. We constrained the value to 60 wt% because it is the minimum value necessary to give a positive Al2O3 concentration for the amorphous component using APXS data for the post-sieve dump pile (Table 2). The amorphous component has high SiO2 (approx.77 wt%) and high anion (SO3+P2O5+Cl ~10 wt%) concentrations. Calculation shows that a cation-anion balance is achieved if the cations in the amorphous component except SiO2 and TiO2, which do not readily form salts, are assumed to be present as amorphous mixed-cation sulfates, phosphates, and chlorides (or perchlorates/ chlorates).

Morris, R. V.↗
NASA NTRS1989

Jacobi-Bessel Analysis Of Antennas With Elliptical Apertures.

Coordinate transformation improves convergence pattern analysis of elliptical-aperture antennas. Modified version of Jacobi-Bessel expansion for vector diffraction analysis of reflector antennas uses coordinate transformation to improve convergence with elliptical apertures. Expansion converges rapidly for antennas with circular apertures, but less rapidly for elliptical apertures. Difference in convergence behavior between circular and elliptical Jacobi-Bessel algorithms indicated by highest values of indices m, n, and p required to achieve same accuracy in computed radiation pattern of offset paraboloidal antenna with elliptical aperture.

Rahmat-Samii, Y.↗
DOE OSTI2025

Neutron Total Scattering Analysis of Materials for the Nuclear Fuel Cycle

Here, this paper reviews recent experimental efforts at the University of Tennessee and Oak Ridge National Laboratory to comprehensively characterize the structural details of materials relevant for the nuclear fuel cycle by employing advanced neutron scattering techniques. For the study of nuclear ceramics, neutron scattering offers distinct advantages over traditional laboratory or synchrotron X-ray diffraction, including enhanced sensitivity to elements with a low atomic mass, such as oxygen, nitrogen, and carbon. The key to these efforts is the recent advancement in the neutron scattering infrastructure at the high-flux diffractometers at the Spallation Neutron Source. The high neutron flux at these instruments enables neutron total scattering, a nondestructive bulk technique that simultaneously captures both short-range structural effects through pair distribution function analysis and long-range order through diffraction pattern analysis. This approach is particularly important for a comprehensive description of defective, disordered, or amorphous nuclear materials. The case studies presented here include analyses of the local defect structure in hyperstoichiometric uranium oxides and short-range order of ion-irradiated ceramics. This advanced analytical methodology will improve our understanding of the behavior of materials in extreme environments and contribute to the development of more resilient nuclear materials.

Neutron scattering↗
NASA NTRS2000

Thermoelastic Stress Analysis: An NDE Tool for the Residual Stress Assessment of Metallic Alloys

During manufacturing, certain propulsion components that will be used in a cyclic fatigue environment are fabricated to contain compressive residual stresses on their surfaces because these stresses inhibit the nucleation of cracks. Overloads and elevated temperature excursions cause the induced residual stresses to dissipate while the component is still in service, lowering its resistance to crack initiation. Research at the NASA Glenn Research Center at Lewis Field has focused on employing the Thermoelastic Stress Analysis technique (TSA, also recognized as SPATE: Stress Pattern Analysis by Thermal Emission) as a tool for monitoring the residual stress state of propulsion components. TSA is based on the fact that materials experience small temperature changes when they are compressed or expanded. When a structure is cyclically loaded (i.e., cyclically compressed and expanded), the resulting surface-temperature profile correlates to the stress state of the structure s surface. The surface-temperature variations resulting from a cyclic load are measured with an infrared camera. Traditionally, the temperature amplitude of a TSA signal has been theoretically defined to be linearly dependent on the cyclic stress amplitude. As a result, the temperature amplitude resulting from an applied cyclic stress was assumed to be independent of the cyclic mean stress.

Gyekenyesi, Andrew L.↗
NASA NTRS1979

Analysis of aperture antenna radiation pattern

Report presents analysis of radiation pattern produced by aperture antenna transmitting through layered dielectric material. Report also describes computer program developed to compute radiation patterns on basis of analysis.

Herskind, R.↗