Better analysis of defect data at NASA
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The Elastic Analysis Facility (EAF) hosted at Fermi National Accelerator Laboratory (Fermilab) is a platform being developed with the goal of providing a fast and efficient facility for physics analysis. As high-energy physics moves towards collecting larger datasets, such as those from the High-Luminosity LHC, the EAF strives to provide a powerful and adaptable framework for future colliders and multi-experiment institutions. Currently, the EAF supports several experiments including CMS, NOvA, and DUNE as well as serving accelerator physicists and beam line operations through integrated software and secure connections to Fermilab's computing resources. In addition, the EAF was designed with a user-friendly interface, intended to be more intuitive for emerging generations of physicists, that is still accessible for established styles of analysis. The EAF can also achieve better analysis efficiency due to the modernization of software and tools that can better utilize Fermilab's computing power. Furthermore, its design incorporates industry standards whenever possible, enhancing its sustainability and making it a possible template for other national or international laboratories and research facilities. Overall, the EAF is a forward-looking solution that will meet the evolving needs of particle physics, ensuring readiness for future colliders and multi-experiment research institutions.
Canonical forms and canonical variables for inviscid flow problems are derived. In these forms the components of the system governed by different types of operators (elliptic and hyperbolic) are separated. Both the incompressible and compressible cases are analyzed, and their similarities and differences are discussed. The canonical forms obtained are block upper triangular operator form in which the elliptic and non-elliptic parts reside in different blocks. The full nonlinear equations are treated without using any linearization process. This form enables a better analysis of the equations as well as better numerical treatment. These forms are the analog of the decomposition of the one dimensional Euler equations into characteristic directions and Riemann invariants.
We explore statistical properties of Bogomol’nyi-Prasad-Sommerfield q-series for strongly coupled supersymmetric theories that correspond to a particular family of three-manifolds. We discover that gaps between exponents in the -series are statistically more significant at the beginning of the -series compared to gaps that appear in higher powers of. Our observations are obtained by calculating saliencies of -series features used as input data for principal component analysis, which is a standard example of an explainable machine learning technique that allows for a direct calculation and a better analysis of feature saliencies.
The effect of rotor blade dynamics on aerodynamic and structural loads is examined for a conventional, main- rotor helicopter using both a comprehensive rotorcraft analysis (CAMRAD) and night test data. The impact of blade dynamics on blade section lift-coefficient time histories is studied by comparing predictions from both a rigid blade analysis and an elastic blade analysis with helicopter flight test data. The elastic blade analysis better predicts high-frequency behavior of section lift. In addition, components of the blade angle of attack, such as elastic blade twist, blade nap rate, blade slope velocity, and inflow, are examined as a function of blade mode. Elastic blade motion affects the blade angle of attack by a few tenths of a degree, and up to the sixth rotor harmonic. A similar study of the influence of blade dynamics on bending and torsion moments was also conducted. The modal analysis of the predicted blade structural loads suggested that five elastic bending deg of freedom (four flap and one lag) and three elastic torsion deg of freedom contributed to calculations of the blade structural loads. However, when structural bending load predictions from several elastic blade analyses were compared with flight test data, an elastic blade model consisting of only three elastic bending modes (first and second flap, and first lag), and two elastic torsion modes was found to be sufficient for maximum correlation.
Although the study of the Urban Heat Island (UHI) effect dates back to the early 1800's when Luke Howard discovered London s heat island, it has only been with the advent of thermal remote sensing systems that the extent, characteristics, and impacts of the UHI have become to be understood. Analysis of the UHI effect is important because above all, this phenomenon can directly influence the health and welfare of urban residents. For example, in 1995, over 700 people died in Chicago due to heat-related causes. UHI s are characterized by increased temperature in comparison to rural areas and mortality rates during a heat wave increase exponentially with the maximum temperature, an effect that is exacerbated by the UHI. Aside from the direct impacts of the UHI on temperature, UHI s can produce secondary effects on local meteorology, including altering local wind patterns, increased development of clouds and fog, and increasing rates of precipitation either over, or downwind, of cities. Because of the extreme heterogeneity of the urban surface, in combination with the sprawl associated with urban growth, thermal infrared (TIR) remote sensing data have become of significant importance in understanding how land cover and land use characteristics affect the development and intensification of the UHI. TIR satellite data have been used extensively to analyze the surface temperature regimes of cities to help observe and measure the impacts of surface temperatures across the urban landscape. However, the spatial scales at which satellite TIR data are collected are for the most part, coarse, with the finest readily available TIR data collected by the Landsat ETM+ sensor at 60m spatial resolution. For many years, we have collected high spatial resolution (10m) data using an airborne multispectral TIR sensor over a number of cities across the United States. These high resolution data have been used to develop an understanding of how discrete surfaces across the urban environment (e.g., rooftops, pavements) interact from a surface-lower atmosphere energy flux perspective, to force the development of the UHI. Moreover, the airborne TIR sensor we used in our UHI studies was a multispectral sensor that had six channels in the 8-12pm range. The advantages of collecting multispectral TIR data became readily evident as a valuable tool for better calculation of unique surface thermal energy responses for urban materials over the 8-12 micrometer region, and also for getting a better handle on surface emissivity characteristics for these discrete surfaces. In this presentation, we will provide evidence on the virtues of how high spatial resolution multispectral TIR data can provide for better analysis of the UHI that cannot now be attained via TIR data obtained from satellites. Furthermore, we wish to provide compelling evidence on why future TIR satellite sensors should collect data at fine spatial resolutions (e.g. less than or equal to 30m) to better allow for measurement of surface thermal energy fluxes from discrete urban surfaces, and to better understand how surface fluxes from different urban materials in cities around the world in different climatic regimes, affect development of the UHI characteristics.
A roving vehicle capable of autonomously exploring the surface of an alien world is under development and an advanced terrain modeler to characterize the possible paths of the rover as hazardous or safe is presented. This advanced terrain modeler has several improvements over the Troiani modeler that include: a crosspath analysis, better determination of hazards on slopes, and methods for dealing with missing returns at the extremities of the sensor field. The results from a package of programs to simulate the roving vehicle are then examined and compared to results from the Troiani modeler.
The effect of rotor blade dynamics on aerodynamic and structural loads is examined for a conventional, main-rotor helicopter using a comprehensive rotorcraft analysis (CAMRAD) and flight-test data. The impact of blade dynamics on blade section lift-coefficient time histories is studied by comparing predictions from a rigid-blade analysis and an elastic-blade analysis with helicopter flight test data. The elastic blade analysis better predicts high-frequency behavior of section lift. In addition, components of the blade angle of attack such as elastic blade twist, blade flap rate, blade slope velocity, and inflow are examined as a function of blade mode. Elastic blade motion changed blade angle of attack by a few tenths of a degree, and up to the sixth rotor harmonic. A similar study of the influence of blade dynamics on bending and torsion moments was also conducted. A correlation study comparing predictions from several elastic-blade analyses with flight-test data revealed that an elastic-blade model consisting of only three elastic bending modes (first and second flap and first lag), and two elastic torsion modes was sufficient for good correlation.
The Mobile Exploration System Project (MEX) at NASA Ames Research Center has been conducting studies into hybrid communication networks for future planetary missions. These networks consist of space-based communication assets connected to ground-based Internets and planetary surface-based mobile wireless networks. These hybrid mobile networks have been deployed in rugged field locations in the American desert and the Canadian arctic for support of science and simulation activities on at least six occasions. This work has been conducted over the past five years resulting in evolving architectural complexity, improved component characteristics and better analysis and test methods. A rich set of data and techniques have resulted from the development and field testing of the communication network during field expeditions such as the Haughton Mars Project and NASA Mobile Agents Project.
The Standard Energy Efficiency Data (SEED) and Building Efficiency Targeting Tool for Energy Retrofits (BETTER) platforms are both developed by the Department of Energy and work better together. SEED is a database to manage building characteristics and performance data from a variety of sources. BETTER provides simple energy efficiency measure analyses based on high level data about the building or portfolio of buildings. A demonstration of each platform and their integration will be provided. The inputs for BETTER are building type, floor area, location, utility data, and whether PV shall be included in the analysis. The BETTER analysis can be manually set up through the web application or data can be uploaded with a BuildingSync XML file either directly or through the API. SEED can be the source of this data and the data can be sent to BETTER through the SEED application after the BETTER API token has been entered. The benefit of utilizing SEED is that it has connections to many other sources of data such as ENERGY STAR Portfolio Manager, Audit Template, and Salesforce. Therefore, it is likely that a user of SEED will already have the required inputs for BETTER in SEED already and can create BETTER analyses across their whole portfolio in a couple mouse clicks. This is a major time savings and enables decision makers an easy path to identify buildings that should undergo more detailed audits or retrofit pathways.
Little theory exists in the field of software system measurement. Concepts such as complexity, coupling, cohesion or even size are very often subject to interpretation and appear to have inconsistent definitions in the literature. As a consequence, there is little guidance provided to the analyst attempting to define proper measures for specific problems. Many controversies in the literature are simply misunderstandings and stem from the fact that some people talk about different measurement concepts under the same label (complexity is the most common case). There is a need to define unambiguously the most important measurement concepts used in the measurement of software products. One way of doing so is to define precisely what mathematical properties characterize these concepts regardless of the specific software artifacts to which these concepts are applied. Such a mathematical framework could generate a consensus in the software engineering community and provide a means for better communication among researchers, better guidelines for analysis, and better evaluation methods for commercial static analyzers for practitioners. In this paper, we propose a mathematical framework which is generic, because it is not specific to any particular software artifact, and rigorous, because it is based on precise mathematical concepts. This framework defines several important measurement concepts (size, length, complexity, cohesion, coupling). It is not intended to be complete or fully objective; other frameworks could have been proposed and different choices could have been made. However, we believe that the formalism and properties we introduce are convenient and intuitive. In addition, we have reviewed the literature on this subject and compared it with our work. This framework contributes constructively to a firmer theoretical ground of software measurement.
A computer program implements a finite-element-based method of predicting the deformations of thin aerospace structures made of isotropic materials or anisotropic fiber-reinforced composite materials. The technique and corresponding software are applicable to thin shell structures in general and are particularly useful for analysis of thin beamlike members having open cross-sections (e.g. I-beams and C-channels) in which significant warping can occur.
The United States National Aeronautics and Space Administration (NASA) is in the midst of a space exploration program called Constellation to send crew and cargo to the international Space Station, to the moon, and beyond. As part of the Constellation program, a new launch vehicle, Ares I, is being developed by NASA Marshall Space Flight Center. Designing a launch vehicle with high reliability and increased safety requires a significant effort in understanding design variability and design uncertainty at the various levels of the design (system, element, subsystem, component, etc.) and throughout the various design phases (conceptual, preliminary design, etc.). In a previous paper [1] we discussed a probabilistic functional failure analysis approach intended mainly to support system requirements definition, system design, and element design during the early design phases. This paper provides an overview of the application of probabilistic engineering methods to support the detailed subsystem/component design and development as part of the "Design for Reliability and Safety" approach for the new Ares I Launch Vehicle. Specifically, the paper discusses probabilistic engineering design analysis cases that had major impact on the design and manufacturing of the Space Shuttle hardware. The cases represent important lessons learned from the Space Shuttle Program and clearly demonstrate the significance of probabilistic engineering analysis in better understanding design deficiencies and identifying potential design improvement for Ares I. The paper also discusses the probabilistic functional failure analysis approach applied during the early design phases of Ares I and the forward plans for probabilistic design analysis in the detailed design and development phases.
Using public data from the NEWFIRM Medium-Band Survey (NMBS) and the Cosmic Assembly Near-Infrared Deep Extragalactic Legacy Survey (CANDELS), we investigate the population of massive galaxies at z > 3. The main aim of this work is to identify the potential progenitors of z ∼ 2 compact, massive, quiescent galaxies (CMQGs), furthering our understanding of the onset and evolution of massive galaxies. Our work is enabled by high-resolution images from CANDELS data and accurate photometric redshifts, stellar masses, and star formation rates (SFRs) from 37-band NMBS photometry. The total number of massive galaxies at z > 3 is consistent with the number of massive, quiescent galaxies (MQGs) at z ∼ 2, implying that the SFRs for all of these galaxies must be much lower by z ∼ 2. We discover four CMQGs at z > 3, pushing back the time for which such galaxies have been observed. However, the volume density for these galaxies is significantly less than that of galaxies at z < 2 with similar masses, SFRs, and sizes, implying that additional CMQGs must be created in the intervening ∼1 Gyr between z = 3 and z = 2. We find five star-forming galaxies at z ∼ 3 that are compact (Re < 1.4 kpc) and have stellar mass M∗ > 1010.6M; these galaxies are likely to become members of the massive, quiescent, compact galaxy population at z ∼ 2. We evolve the stellar masses and SFRs of each individual z > 3 galaxy adopting five different star formation histories (SFHs) and studying the resulting population of massive galaxies at z = 2.3. We find that declining or truncated SFHs are necessary to match the observed number density of MQGs at z ∼ 2, whereas a constant delayed-exponential SFH would result in a number density significantly smaller than observed. All of our assumed SFHs imply number densities of CMQGs at z ∼ 2 that are consistent with the observed number density. Better agreement with the observed number density of CMQGs at z ∼ 2 is obtained if merging is included in the analysis and better still if star formation quenching is assumed to shortly follow the merging event, as implied by recent models of the formation of MQGs.
Remote observations of Mars have led scientists to believe that its early climate was similar to that of the early Earth, having had abundant liquid water and a dense atmosphere. One of the most fascinating questions of recent times is whether simple bacterial life developed on Mars (as it did on the Earth) during this early element period. Analyses of SNC meteorites have broadened considerably our knowledge of the chemistry of certain types of Martian rocks, underscoring the tantalizing possibility of early hydrothermal systems and even of ancient bacterial life. Detailed analyses of SNC meteorites in Terrestrial laboratories utilize the most sophisticated organic, isotopic and microscopic techniques in existence. Indeed; it is unlikely that the key biogenic indicators used in McKay et al (ibid) could be identified by a remote instrument on the surface of Mars. As a result, it is probable that any robotic search for evidence of an ancient Martian biosphere will have as its focus the identification of key minerals in likely host rocks rather than the direct detection of organic or isotopic biomarkers. Even on a sample return mission, mineralogical screening will be utilized to choose the most likely candidate rocks. X-ray diffraction (XRD) is the only technique that can provide a direct determination of the crystal structures of the phases present within a sample. When many different crystalline phases are present, quantitative analysis is better constrained if used in conjunction with a determination of elemental composition, obtainable by X-ray fluorescence (XRF) using the same X-ray source as for XRD. For planetary surface analysis, a remote instrument combining XRD and XRF could be used for mineralogical characterization of both soils and rocks. We are designing a remote XRD/XRF instrument with this objective in mind. The instrument concept pays specific attention to constraints in sample preparation, weight, volume, power, etc. Based on the geometry of a pinhole camera (transmission geometry, flat two-dimensional detector perpendicular to the direct beam), the instrument (which we call CHEMIN, for Chemistry and Mineralogy) uses an X-ray sensitive CCD detector which will allow concurrent positional and energy-dispersive analysis of collected photons. Thus XRF (energy) and XRD (geometry) analysis of transmitted X-rays will be performed at the same time. Tests performed with single minerals and simple mixtures give promising results. Refinements of the prototype promise interpretable results on complex samples.
As national investments in EV charging infrastructure accelerate, this project advances the state-of-the-art in infrastructure analysis to better inform deployment strategies. It enhances NLR's EVI-X Suite, a set of tools supporting national network planning, local site design, and financial evaluation. These capabilities will position VTO to provide timely analysis to the DOT/DOE Joint Office, and to guide the strategic buildout of the national charging network. EVI-X development is closely coordinated with other VTO-funded efforts to ensure consistent, integrated use of key inputs and outputs, including EV adoption scenarios from TEMPO and infrastructure designs developed through EVs@Scale.
This project advances the state-of-the-art in infrastructure analysis to better inform deployment strategies. It enhances NLR's EVI-X Suite, a set of tools supporting national network planning, local site design, and financial evaluation. These capabilities will position DOE to provide timely analysis and inform the strategic buildout of the national charging network. EVI-X development is closely coordinated with other DOE-funded efforts to ensure consistent, integrated use of key inputs and outputs, including EV adoption scenarios from NLR's TEMPO model.