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At least 1,549 records · Page 86

Atomic data and spectral model for Fe II

We present extensive calculations of radiative transition rates and electron impact collision strengths for Fe ii. The data sets involve 52 levels from the 3d{sup 7}, 3d{sup 6}4s, and 3d{sup 5}4s{sup 2} configurations. Computations of A-values are carried out with a combination of state-of-the-art multiconfiguration approaches, namely the relativistic Hartree–Fock, Thomas–Fermi–Dirac potential, and Dirac–Fock methods, while the R-matrix plus intermediate coupling frame transformation, Breit–Pauli R-matrix, and Dirac R-matrix packages are used to obtain collision strengths. We examine the advantages and shortcomings of each of these methods, and estimate rate uncertainties from the resulting data dispersion. We proceed to construct excitation balance spectral models, and compare the predictions from each data set with observed spectra from various astronomical objects. We are thus able to establish benchmarks in the spectral modeling of [Fe ii] emission in the IR and optical regions as well as in the UV Fe ii absorption spectra. Finally, we provide diagnostic line ratios and line emissivities for emission spectroscopy as well as column densities for absorption spectroscopy. All atomic data and models are available online and through the AtomPy atomic data curation environment.

79 ASTRONOMY AND ASTROPHYSICS↗

Quantitative Proteomic Profiling of Low Dose Ionizing Radiation Effects in a Human Skin Model

To assess molecular responses to low doses of radiation that may be encountered during medical diagnostic procedures, nuclear accidents, or terrorist acts, a quantitative global proteomic approach was used to identify protein alterations in a reconstituted human skin tissue treated with 10 cGy of ionizing radiation. Subcellular fractionation was employed to remove highly abundant structural proteins and provide insight on radiation induced alterations in protein abundance and localization. In addition, peptides were post-fractionated using high resolution 2-dimensional liquid chromatography to increase the dynamic range of detection of protein abundance and translocation changes. Quantitative data was obtained by labeling peptides with 8-plex isobaric iTRAQ tags. A total of 207 proteins were detected with statistically significant alterations in abundance and/or subcellular localization compared to sham irradiated tissues. Bioinformatics analysis of the data indicated that the top canonical pathways affected by low dose radiation are related to cellular metabolism. Among the proteins showing alterations in abundance, localization and proteolytic processing was the skin barrier protein filaggrin which is consistent with our previous observation that ionizing radiation alters profilaggrin processing with potential effects on skin barrier functions. In addition, a large number of proteases and protease regulators were affected by low dose radiation exposure indicating that altered proteolytic activity may be a hallmark of low dose radiation exposure. While several studies have demonstrated altered transcriptional regulation occurs following low dose radiation exposures, the data presented here indicates post-transcriptional regulation of protein abundance, localization, and proteolytic processing play an important role in regulating radiation responses in complex human tissues.

Environmental Molecular Sciences Laboratory↗

Metadata Schemas and Ontologies for Building Energy Applications: A Critical Review and Use Case Analysis

With the increasing digitalization of processes throughout the lifecycle of buildings, data exchanged between stakeholders and between building systems has grown significantly. However, a lack of semantic interoperability between data in different systems is still prevalent, hindering the development of applications that can be reused across buildings and limiting the scalability of innovative solutions. Semantics refers to the description of the meaning of the data in a way that can be consistently understood by applications. Recently, several competing initiatives have been developing metadata schemas and ontologies to express this semantic information for different applications in the building domain. This paper systematically reviews these schemas and conducts an analysis of five of them to evaluate their applicability to three high-value use cases for building operations: energy audits, automated fault detection and diagnostics and optimal control. The survey finds 40 schemas published in the last 10 years but but their actual use in industry is difficult to estimate. Among the five selected ontologies, several gaps are highlighted in relation to the three use cases. Recommendations for the future include better harmonization of these initiatives, more centralized repositories and search engines for these schemas as well as better industry engagement to facilitate their adoption.

Smart Building, Sematic, Metadata, Ontology, Data ↗

Radioimaging for real-time tracking of high-voltage breakdown

Development of a radioimaging diagnostic for high-voltage component reliability testing and electrical breakdown computational model validation is described. Radioimaging has its roots in radio astronomy, where aperture synthesis (also known as synthesis imaging) has been utilized for decades to image radio sources far from Earth. Radioimaging as described herein, in contrast, seeks to image radio sources in close proximity to its receivers (i.e., in a laboratory environment). Here it is shown that corona discharge, a non-destructive precursor to catastrophic (thermal) arc discharge, electromagnetically radiates strongly within a 250 kHz – 2.5 GHz bandwidth, and is readily detected and located by postprocessing the received radio signals. The ability of radioimaging to detect both corona and arc discharge (grouped together herein as high voltage breakdown or HVB) makes it a valuable tool for 100% HVB detection in materials, components, and devices, and has the ability to indicate electrical weakness (via corona detection) prior to a destructive arc discharge event. Radioimaging enables HVB to be located both internal and external to dielectric components under test in near-real-time, with multiple and/or extended HVB events located simultaneously. In contrast, existing non-destructive diagnostics (at the time of this writing) either indicate electrical breakdown without resolving failure locations (e.g., current, voltage, and chemical measurements), locate external HVB (e.g., high-speed optical and ultraviolet (UV) measurements or photography), or locate both external and internal HVB but with low fidelity (e.g., a single HVB source can be located by existing time-of-arrival (TOA) UHF or acoustic emissions). Radioimaging instead creates a sequence of high-fidelity images similar to an optical high-speed camera but at radiofrequencies (RF), and is not limited to two-dimensions. Moreover, radioimaging has already served one internal and two external industry customers, the results of which are detailed in this report. The radioimaging results described herein were part of a three-year effort funded by the Sandia Lab Directed Research and Development (LDRD) program within the Radiation, Electromagnetic, High Energy Density Science (REHEDS) investment area.

47 OTHER INSTRUMENTATION↗

Local-Level Prognostics Health Management Systems Framework for Passive AdvSMR Components. Interim Report

This report describes research results to date in support of the integration and demonstration of diagnostics technologies for prototypical AdvSMR passive components (to establish condition indices for monitoring) with model-based prognostics methods. The focus of the PHM methodology and algorithm development in this study is at the localized scale. Multiple localized measurements of material condition (using advanced nondestructive measurement methods), along with available measurements of the stressor environment, enhance the performance of localized diagnostics and prognostics of passive AdvSMR components and systems.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

Revisiting impacts of nuclear burning for reviving weak shocks in neutrino-driven supernovae

We revisit potential impacts of nuclear burning on the onset of the neutrino-driven explosions of core-collapse supernovae. By changing the neutrino luminosity and its decay time to obtain parametric explosions in one- and two-dimensional (1D and 2D, respectively) models with or without a 13 isotope α network, we study how the inclusion of nuclear burning could affect the postbounce dynamics for 4 progenitor models; 3 for 15.0 M {sub ☉} stars and 1 for an 11.2 M {sub ☉} star. We find that the energy supply due to the nuclear burning of infalling material behind the shock can energize the shock expansion, especially for models that produce only marginal explosions in the absence of nuclear burning. These models are energized by nuclear energy deposition when the shock front passes through the silicon-rich layer and/or later as it touches the oxygen-rich layer. Depending on the neutrino luminosity and its decay time, the diagnostic energy of the explosion increases up to a few times 10{sup 50} erg for models with nuclear burning compared to the corresponding models without. We point out that these features are most remarkable for the Limongi-Chieffi progenitor in both 1D and 2D because the progenitor model possesses a massive oxygen layer, with an inner-edge radius that is smallest among the employed progenitors, which means that the shock can touch the rich fuel on a shorter timescale after bounce. The energy difference is generally smaller (∼0.1-0.2 × 10{sup 51} erg) in 2D than in 1D (at most ∼0.6 × 10{sup 51} erg). This is because neutrino-driven convection and the shock instability in 2D models enhance the neutrino heating efficiency, which makes the contribution of nuclear burning relatively smaller compared to 1D models. Considering uncertainties in progenitor models, our results indicate that nuclear burning should remain one of the important ingredients to foster the onset of neutrino-driven explosions.

79 ASTRONOMY AND ASTROPHYSICS↗

Combining Model-Based and Feature-Driven Diagnosis Approaches - A Case Study on Electromechanical Actuators

Model-based diagnosis typically uses analytical redundancy to compare predictions from a model against observations from the system being diagnosed. However this approach does not work very well when it is not feasible to create analytic relations describing all the observed data, e.g., for vibration data which is usually sampled at very high rates and requires very detailed finite element models to describe its behavior. In such cases, features (in time and frequency domains) that contain diagnostic information are extracted from the data. Since this is a computationally intensive process, it is not efficient to extract all the features all the time. In this paper we present an approach that combines the analytic model-based and feature-driven diagnosis approaches. The analytic approach is used to reduce the set of possible faults and then features are chosen to best distinguish among the remaining faults. We describe an implementation of this approach on the Flyable Electro-mechanical Actuator (FLEA) test bed.

Narasimhan, Sriram↗

Development of an Information Fusion System for Engine Diagnostics and Health Management

Aircraft gas-turbine engine data are available from a variety of sources including on-board sensor measurements, maintenance histories, and component models. An ultimate goal of Propulsion Health Management (PHM) is to maximize the amount of meaningful information that can be extracted from disparate data sources to obtain comprehensive diagnostic and prognostic knowledge regarding the health of the engine. Data Fusion is the integration of data or information from multiple sources, to achieve improved accuracy and more specific inferences than can be obtained from the use of a single sensor alone. The basic tenet underlying the data/information fusion concept is to leverage all available information to enhance diagnostic visibility, increase diagnostic reliability and reduce the number of diagnostic false alarms. This paper describes a basic PHM Data Fusion architecture being developed in alignment with the NASA C17 Propulsion Health Management (PHM) Flight Test program. The challenge of how to maximize the meaningful information extracted from disparate data sources to obtain enhanced diagnostic and prognostic information regarding the health and condition of the engine is the primary goal of this endeavor. To address this challenge, NASA Glenn Research Center (GRC), NASA Dryden Flight Research Center (DFRC) and Pratt & Whitney (P&W) have formed a team with several small innovative technology companies to plan and conduct a research project in the area of data fusion as applied to PHM. Methodologies being developed and evaluated have been drawn from a wide range of areas including artificial intelligence, pattern recognition, statistical estimation, and fuzzy logic. This paper will provide a broad overview of this work, discuss some of the methodologies employed and give some illustrative examples.

Volponi, Allan J.↗

An Analytical Model for Capturing the Decline of Fracture Conductivity in the Tuscaloosa Marine Shale Trend from Production Data

Fracture conductivity decline is a concern in the Tuscaloosa Marine Shale (TMS) wells due to the high content of clay in the shale. An analytical well productivity model was developed in this study considering the pressure-dependent conductivity of hydraulic fractures. The log-log diagnostic approach was used to identify the boundary-dominated flow regime rather than the linear flow regime. Case studies of seven TMS wells indicated that the proposed model allows approximation of the field data with good accuracy. Production data analyses with the model revealed that the pressure-dependent fracture conductivity in the TMS in the Mississippi section declines following a logarithmic mode, with dimensionless coefficient χ varying between 0.116 and 0.130. The pressure-dependent decline of fracture conductivity in the transient flow period is more significant than that in the boundary-dominated flow period.

58 GEOSCIENCES↗

The Effect of Bypass Nozzle Exit Area on Fan Aerodynamic Performance and Noise in a Model Turbofan Simulator

The design of effective new technologies to reduce aircraft propulsion noise is dependent on identifying and understanding the noise sources and noise generation mechanisms in the modern turbofan engine, as well as determining their contribution to the overall aircraft noise signature. Therefore, a comprehensive aeroacoustic wind tunnel test program was conducted called the Fan Broadband Source Diagnostic Test as part of the NASA Quiet Aircraft Technology program. The test was performed in the anechoic NASA Glenn 9- by 15-Foot Low Speed Wind Tunnel using a 1/5 scale model turbofan simulator which represented a current generation, medium pressure ratio, high bypass turbofan aircraft engine. The investigation focused on simulating in model scale only the bypass section of the turbofan engine. The test objectives were to: identify the noise sources within the model and determine their noise level; investigate several component design technologies by determining their impact on the aerodynamic and acoustic performance of the fan stage; and conduct detailed flow diagnostics within the fan flow field to characterize the physics of the noise generation mechanisms in a turbofan model. This report discusses results obtained for one aspect of the Source Diagnostic Test that investigated the effect of the bypass or fan nozzle exit area on the bypass stage aerodynamic performance, specifically the fan and outlet guide vanes or stators, as well as the farfield acoustic noise level. The aerodynamic performance, farfield acoustics, and Laser Doppler Velocimeter flow diagnostic results are presented for the fan and four different fixed-area bypass nozzle configurations. The nozzles simulated fixed engine operating lines and encompassed the fan stage operating envelope from near stall to cruise. One nozzle was selected as a baseline reference, representing the nozzle area which would achieve the design point operating conditions and fan stage performance. The total area change from the smallest to the largest nozzle was 12.9 percent of the baseline nozzle area. The results will show that there are significant changes in aerodynamic performance and farfield acoustics as the fan nozzle area is increased. The weight flow through the fan model increased between 7 and 9 percent, the fan and stage pressure dropped between 8 and 10 percent, and the adiabatic efficiency increased between 2 and 3 percent--the magnitude of the change dependent on the fan speed. Results from force balance measurements of fan and outlet guide vane thrust will show that as the nozzle exit area is increased the combined thrust of the fan and outlet guide vanes together also increases, between 2 and 3.5 percent, mainly due to the increase in lift from the outlet guide vanes. In terms of farfield acoustics, the overall sound power level produced by the fan stage dropped nearly linearly between 1 dB at takeoff condition and 3.5 dB at approach condition, mainly due to a decrease in the broadband noise levels. Finally, fan swirl angle survey and Laser Doppler Velocimeter mean velocity and turbulence data obtained in the fan wake will show that the swirl angles and turbulence levels within the wake decrease as the fan nozzle area increases, which helps to explain the drop in the fan broadband noise at all fan speeds.

Hughes, Christopher E.↗

High resolution magnetic field measurements in hydrogen and helium plasmas using active laser spectroscopy

Passive spectroscopic measurements of Zeeman splitting have been used reliably to measure magnetic fields in plasmas for decades. However, a requirement is that the field magnitude must be sufficiently strong to be resolved over Doppler and instrument broadening (typically >10 000 G). A diagnostic for measuring magnetic fields spectroscopically well below this limit (>20 G) with high sensitivity has been developed at the Oak Ridge National Laboratory. The diagnostic relies on measuring a high resolution spectral profile using Doppler-free saturation spectroscopy (DFSS) and then fitting the spectrum to a quantum mechanical model. DFSS is an active, laser based technique that greatly reduces the influence of Doppler broadening and eliminates instrument broadening. To date, the diagnostic has been successfully employed to measure the magnetic field in magnetized (550-900 G), low-temperature (5-10 eV), low-density (10 10 –10 12 cm –3 ), hydrogen and helium plasmas in the 5-200 mTorr pressure range using a low power (25 mW) diode laser. Implementing an approximate crossover resonance model, the measurements are shown to be accurate within 5 G for helium and 83 G for hydrogen. The accuracy in hydrogen can be improved to 39 G if the crossover resonances are neglected. As a result, a more robust crossover model can decrease this error to <1 G.

47 OTHER INSTRUMENTATION↗

MJO Teleconnections over the PNA Region in Climate Models. Part II: Impacts of the MJO and Basic State

In an assessment of 29 global climate models (GCMs), Part I of this study identified biases in boreal winter MJO teleconnections in anomalous 500-hPa geopotential height over the Pacific–North America (PNA) region that are common to many models: an eastward shift, a longer persistence, and a larger amplitude. In Part II, we explore the relationships of the teleconnection metrics developed in Part I with several existing and newly developed MJO and basic state (the mean subtropical westerly jet) metrics. The MJO and basic state diagnostics indicate that the MJO is generally weaker and less coherent and propagates faster in models compared to observations. The mean subtropical jet also exhibits notable biases such as too strong amplitude, excessive eastward extension, or southward shift. The following relationships are found to be robust among the models: 1) models with a faster MJO propagation tend to produce weaker teleconnections; 2) models with a less coherent eastward MJO propagation tend to simulate more persistent MJO teleconnections; 3) models with a stronger westerly jet produce stronger and eastward shifted MJO teleconnections; 4) models with an eastward extended jet produce an eastward shift in MJO teleconnections; and 5) models with a southward shifted jet produce stronger MJO teleconnections. The results are supported by linear baroclinic model experiments. Our results suggest that the larger amplitude and eastward shift biases in GCM MJO teleconnections can be attributed to the biases in the westerly jet, and that the longer persistence bias is likely due to the lack of coherent eastward MJO propagation.

59 BASIC BIOLOGICAL SCIENCES↗

Numerical models of star formation in X-ray cluster cooling flows

A grid of numerical models is used here to study how accretion flows are affected by star formation. The observables associated with these models are investigated, presenting their X-ray surface brightness profiles. An X-ray diagnostic is searched for that, in the absence of spatially resolved X-ray spectral data, can be an unambiguous indicator for ongoing star formation in cooling flows. The spatial distributions of newly formed stars are presented and compared to profiles of the accreting galaxy in each model. Whether the accretion population can form the luminous parts of the accreting galaxy or whether it forms a dark component is considered.

White, Raymond E., III↗

Measurement of helicon waves with phase contrast imaging on DIII-D – A theoretical feasibility study

A DIII-D high-beta H-mode discharge, with I p = 850 kA, B t = 2.1 T n e = 4 10 19 m –3 , has been designed to validate full wave modeling of helicon waves by optimizing the expected response of the Phase Contrast Imaging diagnostic. Helicon waves have been predicted to have high current drive efficiency off-axis without facing the accessibility issues of lower-hybrid waves. To test these predictions experimentally, DIII-D has recently commissioned a high-power helicon antenna. To confidently predict the behavior of helicon waves in future devices, measurements of their fundamental properties and validation against models will be essential. Phase contrast imaging (PCI) is an absolutely calibrated internal reference interferometer able to measure density fluctuations with radial wavenumbers k R between 1.5 cm –1 and 20 cm –1 . For helicon waves 2 cm –1 < k R < 10 cm –1 is expected, allowing PCI to measure their envelope and wavenumber spectrum. This makes PCI a powerful tool for the validation of state-of-the-art models, like the AORSA full wave code. AORSA is used to compute the density perturbations measured by the PCI with 2D calculations corresponding to 11 different toroidal mode numbers combined to resolve the trajectory of the helicon wave in 3D. This is necessary because the waves travel 120 degrees toroidally from the antenna to the PCI. Here, a cold plasma finite element model (CPFEM) [4] is used to predict propagation through the scrape-off layer. The result of the CPFEM model is connected to AORSA by creating an artificial Gaussian antenna on the last closed flux surface. PCI shows best results for waves with small vertical wavenumbers k z . Modeling the helicon waves for several past DIII-D experiments shows that k z is minimized if the intersection of the helicon and the PCI laser beams occurs in the midplane. For such an optimized scenario the predicted signal level is two orders of magnitude larger than the background density fluctuations arising from broadband turbulence.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

How Aqueous Solvation Impacts the Frequencies and Intensities of Infrared Absorption Bands in Flavin: The Quest for a Suitable Solvent Model

FTIR spectroscopy accompanied by quantum chemical simulations can reveal important information about molecular structure and intermolecular interactions in the condensed phase. Simulations typically account for the solvent either through cluster quantum mechanical (QM) models, polarizable continuum models (PCM), or hybrid quantum mechanical/molecular mechanical (QM/MM) models. Recently, we studied the effect of aqueous solvent interactions on the vibrational frequencies of lumiflavin, a minimal flavin model, using cluster QM and PCM models. Those models successfully reproduced the relative frequencies of four prominent stretching modes of flavin’s isoalloxazine ring in the diagnostic 1450–1750 cm−1 range but poorly reproduced the relative band intensities. Here, we extend our studies on this system and account for solvation through a series of increasingly sophisticated models. Only by combining elements of QM clusters, QM/MM, and PCM approaches do we obtain an improved agreement with the experiment. The study sheds light more generally on factors that can impact the computed frequencies and intensities of IR bands in solution.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

An advanced hypervelocity aerophysics facility - A ground-based flight-test range

The paper discusses a concept for a ground-based flight-test facility, a large aeroballistic range capable of launching models large enough to permit the installation of significant amounts of onboard instrumentation. The large model size would also provide thick shock/boundary layers, thus providing the opportunity to measure flow-field properties via advanced offboard diagnostics. Current fabrication technology should permit the construction of a two-stage light-gas gun capable of accelerating 20 to 25 cm diameter models to velocities on the order of 6 km/sec. An electromagnetic launcher or a ram accelerator is considered as a potential means for achieving larger model sizes and/or greater launch velocities. Possible methods for obtaining and recording data are discussed as are the test chamber and model deceleration section requirements.

Witcofski, R. D.↗

The Livingstone Model of a Main Propulsion System

Livingstone is a discrete, propositional logic-based inference engine that has been used for diagnosis of physical systems. We present a component-based model of a Main Propulsion System (MPS) and say how it is used with Livingstone (L2) in order to implement a diagnostic system for integrated vehicle health management (IVHM) for the Propulsion IVHM Technology Experiment (PITEX). We start by discussing the process of conceptualizing such a model. We describe graphical tools that facilitated the generation of the model. The model is composed of components (which map onto physical components), connections between components and constraints. A component is specified by variables, with a set of discrete, qualitative values for each variable in its local nominal and failure modes. For each mode, the model specifies the component's behavior and transitions. We describe the MPS components' nominal and fault modes and associated Livingstone variables and data structures. Given this model, and observed external commands and observations from the system, Livingstone tracks the state of the MPS over discrete time-steps by choosing trajectories that are consistent with observations. We briefly discuss how the compiled model fits into the overall PITEX architecture. Finally we summarize our modeling experience, discuss advantages and disadvantages of our approach, and suggest enhancements to the modeling process.

Bajwa, Anupa↗

Kinetic corrections from analytic non-Maxwellian distribution functions in magnetized plasmas

In magnetized plasma physics, almost all developed analytic theories assume a Maxwellian distribution function (MDF) and in some cases small deviations are described using the perturbation theory. The deviations with respect to the Maxwellian equilibrium, called kinetic effects, are required to be taken into account especially for fusion reactor plasmas. Generally, because the perturbation theory is not consistent with observed steady-state non-Maxwellians, these kinetic effects are numerically evaluated by very central processing unit (CPU)-expensive codes, avoiding the analytic complexity of velocity phase space integrals. We develop here a new method based on analytic non-Maxwellian distribution functions constructed from non-orthogonal basis sets in order to (i) use as few parameters as possible, (ii) increase the efficiency to model numerical and experimental non-Maxwellians, (iii) help to understand unsolved problems such as diagnostics discrepancies from the physical interpretation of the parameters, and (iv) obtain analytic corrections due to kinetic effects given by a small number of terms and removing the numerical error of the evaluation of velocity phase space integrals. This work does not attempt to derive new physical effects even if it could be possible to discover one from the better understandings of some unsolved problems, but here we focus on the analytic prediction of kinetic corrections from analytic non-Maxwellians. As applications, examples of analytic kinetic corrections are shown for the secondary electron emission, the Langmuir probe characteristic curve, and the entropy. This is done by using three analytic representations of the distribution function: the Kappa distribution function, the bi-modal or a new interpreted non-Maxwellian distribution function (INMDF). The existence of INMDFs is proved by new understandings of the experimental discrepancy of the measured electron temperature between two diagnostics in JET. As main results, it is shown that (i) the empirical formula for the secondary electron emission is not consistent with a MDF due to the presence of super-thermal particles, (ii) the super-thermal particles can replace a diffusion parameter in the Langmuir probe current formula, and (iii) the entropy can explicitly decrease in presence of sources only for the introduced INMDF without violating the second law of thermodynamics. Moreover, the first order entropy of an infinite number of super-thermal tails stays the same as the entropy of a MDF. The latter demystifies the Maxwell's demon by statistically describing non-isolated systems.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗