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At least 1,639 records · Page 91

Self-consistent Non-LTE Model of Infrared Molecular Emissions and Oxygen Dayglows in the Mesosphere and Lower Thermosphere

We present the new version of the ALI-ARMS (for Accelerated Lambda Iterations for Atmospheric Radiation and Molecular Spectra) model. The model allows simultaneous self-consistent calculating the non-LTE populations of the electronic-vibrational levels of the O3 and O2 photolysis products and vibrational level populations of CO2, N2,O2, O3, H2O, CO and other molecules with detailed accounting for the variety of the electronic-vibrational, vibrational-vibrational and vibrational-translational energy exchange processes. The model was used as the reference one for modeling the O2 dayglows and infrared molecular emissions for self-consistent diagnostics of the multi-channel space observations of MLT in the SABER experiment It also allows reevaluating the thermalization efficiency of the absorbed solar ultraviolet energy and infrared radiative cooling/heating of MLT by detailed accounting of the electronic-vibrational relaxation of excited photolysis products via the complex chain of collisional energy conversion processes down to the vibrational energy of optically active trace gas molecules.

Feofilov, Artem G.↗

GEMS

The prime scientific objectives of the Gravity and Extreme Magnetism SMEX, GEMS, are to determine the effects of the spin of black holes, the configurations of the magnetic fields of magnetars, and the structure of the supernova shocks which accelerate cosmic rays. In the cases of both stellar black holes and supermassive black holes, sensitivity to 1% polarization is needed to make diagnostic measurements of the net polarizations predicted for probable disk and corona models. GEMS can reach this goal for several Seyferts and quasars and measure the polarizations of representatives of a variety of other classes of X-ray sources, such as rotation-powered and accretion-powered pulsars. GEMS uses foil mirrors to maximize the collecting area achievable within the SMEX constraints. The polarimeters at the mirror foci are Time Projection Chambers which use the photoelectic effect to measure the polarization of the incident photon. We have built laboratory models with good efficiency and modulation in the 2-10 keV range. An attached small student experiment would add 0.5 keV sensitivity for bright soft sources. The instrument has a point spread function which allows measurement of structures in the brighter nearby supernova remnants. GEMS' Orbital Sciences spacecraft will rotate at a rate of 0.1 revolutions per minute during observations, so that systematic errors due to the detector can be detected and corrected. A program of 35 sources can be observed in 9 months. GEMS is designed for a two year lifetime which will allow a General Observer program that would more than double the number of sources measured. For subsets of black holes, neutron stars and supernova remnants, GEMS will measure the polarization of several sources, solving important questions while establishing the sensitivity required for future missions.

Swank, Jean↗

NASA SPoRT GOES-R Proving Ground Activities

The NASA Short-term Prediction Research and Transition (SPoRT) program is a partner with the GOES-R Proving Ground (PG) helping prepare forecasters understand the unique products to come from the GOES-R instrument suite. SPoRT is working collaboratively with other members of the GOES-R PG team and Algorithm Working Group (AWG) scientists to develop and disseminate a suite of proxy products that address specific forecast problems for the WFOs, Regional and National Support Centers, and other NOAA users. These products draw on SPoRT s expertise with the transition and evaluation of products into operations from the MODIS instrument and the North Alabama Lightning Mapping Array (NALMA). The MODIS instrument serves as an excellent proxy for the Advanced Baseline Imager (ABI) that will be aboard GOES-R. SPoRT has transitioned and evaluated several multi-channel MODIS products. The true and false color products are being used in natural hazard detection by several SPoRT partners to provide better observation of land features, such as fires, smoke plumes, and snow cover. Additionally, many of SPoRT s partners are coastal offices and already benefit from the MODIS sea surface temperature composite. This, along with other surface feature observations will be developed into ABI proxy products for diagnostic use in the forecast process as well as assimilation into forecast models. In addition to the MODIS instrument, the NALMA has proven very valuable to WFOs with access to these total lightning data. These data provide situational awareness and enhanced warning decision making to improve lead times for severe thunderstorm and tornado warnings. One effort by SPoRT scientists includes a lightning threat product to create short-term model forecasts of lightning activity. Additionally, SPoRT is working with the AWG to create GLM proxy data from several of the ground based total lightning networks, such as the NALMA. The evaluation will focus on the vastly improved spatial coverage of the GLM, but with the trade-off of lower resolution compared to the NALMA. In addition to the above tasks, SPoRT will make these data available in the NWS next generation display software, AWIPS II. This has already been successfully completed for the two basic GLM proxies. SPoRT will use these products to train forecasters on the capabilities of GOES-R and foster feedback to develop additional products, visualizations, and requirements beneficial to end users needs. These developments and feedback will be made available to the GOES-R Proving Ground for the upcoming 2010 Spring Program in Norman, Oklahoma.

Stano, Geoffrey T.↗

Vehicle Integrated Prognostic Reasoner (VIPR) 2010 Annual Final Report

Honeywell's Central Maintenance Computer Function (CMCF) and Aircraft Condition Monitoring Function (ACMF) represent the state-of-the art in integrated vehicle health management (IVHM). Underlying these technologies is a fault propagation modeling system that provides nose-to-tail coverage and root cause diagnostics. The Vehicle Integrated Prognostic Reasoner (VIPR) extends this technology to interpret evidence generated by advanced diagnostic and prognostic monitors provided by component suppliers to detect, isolate, and predict adverse events that affect flight safety. This report describes year one work that included defining the architecture and communication protocols and establishing the user requirements for such a system. Based on these and a set of ConOps scenarios, we designed and implemented a demonstration of communication pathways and associated three-tiered health management architecture. A series of scripted scenarios showed how VIPR would detect adverse events before they escalate as safety incidents through a combination of advanced reasoning and additional aircraft data collected from an aircraft condition monitoring system. Demonstrating VIPR capability for cases recorded in the ASIAS database and cross linking them with historical aircraft data is planned for year two.

Hadden, George D.↗

Performance Evaluation of the T6 Ion Engine

The T6 ion engine is a 22-cm diameter, 4.5-kW Kaufman-type ion thruster produced by QinetiQ, Ltd., and is baselined for the European Space Agency BepiColombo mission to Mercury and is being qualified under ESA sponsorship for the extended range AlphaBus communications satellite platform. The heritage of the T6 includes the T5 ion thruster now successfully operating on the ESA GOCE spacecraft. As a part of the T6 development program, an engineering model thruster was subjected to a suite of performance tests and plume diagnostics at the Jet Propulsion Laboratory. The engine was mounted on a thrust stand and operated over its nominal throttle range of 2.5 to 4.5 kW. In addition to the typical electrical and flow measurements, an E x B mass analyzer, scanning Faraday probe, thrust vector probe, and several near-field probes were utilized. Thrust, beam divergence, double ion content, and thrust vector movement were all measured at four separate throttle points. The engine performance agreed well with published data on this thruster. At full power the T6 produced 143 mN of thrust at a specific impulse of 4120 seconds and an efficiency of 64%; optimization of the neutralizer for lower flow rates increased the specific impulse to 4300 seconds and the efficiency to nearly 66%. Measured beam divergence was less than, and double ion content was greater than, the ring-cusp-design NSTAR thruster that has flown on NASA missions. The measured thrust vector offset depended slightly on throttle level and was found to increase with time as the thruster approached thermal equilibrium.

Snyder, John Steven↗

Probing the Sun with Imaging Spectrographs

EUV and X-ray images of the Sun have revolutionized our understanding of our closest star. With them, we can probe the morphology and temperature structure of the solar atmosphere and see how they evolve as a function of space and time. However, image data cannot be used to determine line-of-sight velocities, abundances, or densities. This information is required to calculate the energy budget of eruptive events, provide boundary conditions for global solar models, and explore fundamental processes occurring in the solar atmosphere. For those diagnostics, we require spectroscopy. Because the structures on the Sun are extended sources, most modern-day spectrographs observe the Sun through long narrow slits. Two-dimensional, spectrally pure solar images with velocity, abundance, and density information are built up by stepping the slit over regions of interest. This mode of operation implies that two-dimensional information is highly limited by cadence and the temporal evolution and spatial structure of these parameters can never be truly separated. Both spatial and spectral information can be obtained in a single snapshot with slitless spectrographs, which were often used in the 1950-1970s, but were abandoned due to the difficulty of unfolding the overlapping spatial and spectral information. Thanks to advances in computer processing speeds and machine learning algorithms, there have been several techniques developed to complete the spatial/spectral unfolding, unlocking the full capability of slitless spectrographs for solar observations. The goal of this talk is to give a broad overview of the capability of such instruments and demonstrate their usefulness in the next decade of solar observatories and beyond.

Amy Winebarger↗

Probing the Sun with Imaging Spectrographs

EUV and X-ray images of the Sun have revolutionized our understanding of our closest star. With them, we can probe the morphology and temperature structure of the solar atmosphere and see how they evolve as a function of space and time. However, image data cannot be used to determine line-of-sight velocities, abundances, or densities. This information is required to calculate the energy budget of eruptive events, provide boundary conditions for global solar models, and explore fundamental processes occurring in the solar atmosphere. For those diagnostics, we require spectroscopy. Because the structures on the Sun are extended sources, most modern-day spectrometers observe the Sun through long narrow slits. Two-dimensional, spectrally pure solar images with velocity, abundance, and density information are built up by stepping the slit over regions of interest. This method implies that two-dimensional information is highly limited by cadence and the temporal evolution and spatial structure of these parameters can never be truly separated. Both spatial and spectral information can be obtained in a single snapshot with slitless spectrometers, which were often used in the 1950-1970s, but were abandoned due to the difficulty of unfolding the overlapping spatial and spectral information. Thanks to advances in computer processing speeds and machine learning algorithms, there have been several techniques developed to complete the spatial/spectral unfolding, unlocking the full capability of slitless spectrometers for solar observations. The goal of this talk is to give an overview of the capability of such instruments, including recent results from a sounding rocket flight, and demonstrate their usefulness in the next decade of solar observatories and beyond.

Amy Winebarger↗

Probing the Sun with Imaging Spectrographs

EUV and X-ray images of the Sun have revolutionized our understanding of our closest star. With them, we can probe the morphology and temperature structure of the solar atmosphere and see how they evolve as a function of space and time. However, image data cannot be used to determine line-of-sight velocities, abundances, or densities. This information is required to calculate the energy budget of eruptive events, provide boundary conditions for global solar models, and explore fundamental processes occurring in the solar atmosphere. For those diagnostics, we require spectroscopy. Because the structures on the Sun are extended sources, most modern-day spectrometers observe the Sun through long narrow slits. Two-dimensional, spectrally pure solar images with velocity, abundance, and density information are built up by stepping the slit over regions of interest. This method implies that two-dimensional information is highly limited by cadence and the temporal evolution and spatial structure of these parameters can never be truly separated. Both spatial and spectral information can be obtained in a single snapshot with slitless spectrometers, which were often used in the 1950-1970s, but were abandoned due to the difficulty of unfolding the overlapping spatial and spectral information. Thanks to advances in computer processing speeds and machine learning algorithms, there have been several techniques developed to complete the spatial/spectral unfolding, unlocking the full capability of slitless spectrometers for solar observations. The goal of this talk is to give an overview of the capability of such instruments, including recent results from a sounding rocket flight, and demonstrate their usefulness in the next decade of solar observatories and beyond.

Amy Winebarger↗

Probing the Sun with Imaging Spectrographs

EUV and X-ray images of the Sun have revolutionized our understanding of our closest star. With them, we can probe the structure of the solar atmosphere and see how they evolve as a function of space and time. However, image data cannot be used to determine line-of-sight velocities, abundances, or densities. This information is required to calculate the energy budget of eruptive events, provide boundary conditions for global solar models, and explore fundamental processes occurring in the solar atmosphere. For those diagnostics, we require spectroscopy. Because the structures on the Sun are extended sources, most modern-day spectrometers observe the Sun through long narrow slits. Two-dimensional, spectrally pure solar images with velocity, abundance, and density information are built up by stepping the slit over regions of interest. This method implies that two-dimensional information is highly limited by cadence and the temporal evolution and spatial structure of these parameters can never be truly separated. Both spatial and spectral information can be obtained in a single snapshot with slitless spectrometers, which were often used in the 1950-1970s, but were abandoned due to the difficulty of unfolding the overlapping spatial and spectral information. Thanks to advances in computer processing speeds and machine learning algorithms, there have been several techniques developed to complete the spatial/spectral unfolding, unlocking the full capability of slitless spectrometers for solar observations. The goal of this talk is to give an overview of the capability of such instruments and demonstrate their usefulness in the next decade of solar observatories and beyond.

Amy Winebarger↗

Year 2 Final Report - Protein Function Prediction Platform (v.0.5)

Upon completion of our second year of development in a 3-year development cycle, we have completed a prototype protein structure-function annotation and function prediction system: Protein Function Prediction (PFP) platform (v.0.5). We have met our milestones for Years 1 and 2 and are positioned to continue development in completion of our original statement of work, or a reasonable modification thereof, in service to DTRA Programs involved in diagnostics and medical countermeasures research and development. The PFP platform is a multi-scale computational modeling system for protein structure-function annotation and function prediction. As of this writing, PFP is the only existing fully automated, high-throughput, multi-scale modeling, whole-proteome annotation platform, and represents a significant advance in the field of genome annotation (Fig. 1). PFP modules perform protein functional annotations at the sequence, systems biology, protein structure, and atomistic levels of biological complexity (Fig. 2). Because these approaches provide orthogonal means of characterizing proteins and suggesting protein function, PFP processing maximizes the protein functional information that can currently be gained by computational means. Comprehensive annotation of pathogen genomes is essential for bio-defense applications in pathogen characterization, threat assessment, and medical countermeasure design and development in that it can short-cut the time and effort required to select and characterize protein biomarkers.

59 BASIC BIOLOGICAL SCIENCES↗

SPECTRAL AND PHOTOMETRIC DIAGNOSTICS OF GIANT PLANET FORMATION SCENARIOS

Gas-giant planets that form via core accretion might have very different characteristics from those that form via disk instability. Disk-instability objects are typically thought to have higher entropies, larger radii, and (generally) higher effective temperatures than core-accretion objects. In this paper, we provide a large set of models exploring the observational consequences of high-entropy (hot) and low-entropy (cold) initial conditions, in the hope that this will ultimately help to distinguish between different physical mechanisms of planet formation. However, the exact entropies and radii of newly formed planets due to these two modes of formation cannot, at present, be precisely predicted. It is possible that the distribution of properties of core-accretion-formed planets and the distribution of properties of disk-instability-formed planets overlap. We, therefore, introduce a broad range of 'warm-start' gas-giant planet models. Between the hottest and the coldest models that we consider, differences in radii, temperatures, luminosities, and spectra persist for only a few million to a few tens of millions of years for planets that are a few times Jupiter's mass or less. For planets that are {approx}five times Jupiter's mass or more, significant differences between hottest-start and coldest-start models persist for on the order of 100 Myr. We find that out of the standard infrared bands (J, H, K, L', M, N) the K and H bands are the most diagnostic of the initial conditions. A hottest-start model can be from {approx}4.5 mag brighter (at Jupiter's mass) to {approx}9 mag brighter (at 10 times Jupiter's mass) than a coldest-start model in the first few million years. In more massive objects, these large differences in luminosity and spectrum persist for much longer than in less massive objects. Finally, we consider the influence of atmospheric conditions on spectra, and find that the presence or absence of clouds, and the metallicity of an atmosphere, can affect an object's apparent brightness in different bands by up to several magnitudes.

79 ASTRONOMY AND ASTROPHYSICS↗

Evaluating nonlocal heat transport in directly driven chromium spheres using x-ray spectroscopy

We report on experiments investigating heat transport in laser-generated plasmas using directly driven chromium spheres. The spheres are fielded at the OMEGA laser facility and are driven with laser intensities of 5×10 14 Wcm −2 . Plasma conditions in the corona and scattered light are measured experimentally and compared against predictions from two-dimensional (2D) radiation-hydrodynamic simulations using different heat transport models. Spectroscopic analysis of x-ray self-emission is used as an additional diagnostic. X-ray emission is integrated over a large region of the plasma, probing regions that are not observed by localized optical Thomson scattering. In particular, x-ray emission peaks near the plasma critical density, so emission from optically thin lines provides information on plasma conditions where nonlocal transport is most likely to be significant. Three common heat transport models are considered: local transport with flux limiters f = 0.15 and f = 0.03, and the nonlocal Schurtz–Nicolai–Busquet (SNB) model. Consistent with previous work, both the high-flux (f = 0.15) and SNB models show good agreement with experimentally measured plasma conditions in the corona despite overpredicting laser absorption, whereas the low-flux (f = 0.03) model fails to match any experimental data. Conditions inferred from x-ray self-emission line ratios support this conclusion during the period of laser peak power, although synthetic spectra for all models fail to match the experiment during the transient portions of the pulse. For these reasons, the low-flux model is again rejected.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Line profiles variations from atmospheric eclipses: Constraints on the wind structure in Wolf-Rayet stars

Binary systems in which one of the components has a stellar wind may present a phenomenon known as 'wind' or 'atmospheric eclipse', in which that wind occults the luminous disk of the companion. The enhanced absorption profile, relative to the spectrum at uneclipsed orbital phases, can be be modeled to yield constraints on the spatial structure of the eclipsing wind. A new, very efficient approach to the radiative transfer problem, which makes no requirements with respect to monotonicity of the velocity gradient or size of that gradient, is presented. The technique recovers both the comoving frame calculation and the Sobolev approximation in the appropiate limits. Sample computer simulations of the line profile variations induced by wind eclipses are presented. It is shown that the location of the wind absorption features in frequency is a diagnostic tool for identifying the size of the wind acceleration region. Comparison of the model profile variations with the observed variations in the Wolf-Rayet (W-R)+6 binary system V444 Cyg illustrate how the method can be used to derive information on the structure of the wind of the W-R star constrain the size of the W-R core radius.

Auer, L. H.↗

Hidden-strangeness tetraquarks in the dynamical diquark model

The dynamical diquark model describes multiquark exotic hadrons in terms of diquark components nucleated by heavy quarks and successfully explains multiple features of hidden-charm and hidden-bottom exotics. Here, we apply the model to the marginally heavy case of hidden-strange states to probe whether mesons near 2 GeV with peculiar properties, such as 𝜙⁡(2170), 𝑓 2 ⁡(2340), and 𝑋⁡(2370), are possible tetraquark candidates. We calculate spin-multiplet average masses using potentials obtained through lattice simulations and quark models, and we also describe the detailed spectra of the expected multiplets as a diagnostic to discern the nature of future hadrons likely to be discovered in this mass region by experiments at facilities such as BESIII, JLab, and the EIC.

Bound states↗

The Aerosol Model Benchmarking Repository: A toolkit for model intercomparison

The Aerosol Model Benchmarking Repository and Standards (AMBRS) project was initiated to provide tools and to establish community standards for benchmarking aerosol models. This report describes a set of open-source tools for building, running, and analyzing aerosol box model simulations in a standardized framework. The framework consists of three core components: AMBuilder, a CMake-based build system that compiles supported models consistently; AMBRS, a Python module that defines unified numerical experiments and executes them with aligned inputs; and PyParticle, an aerosol analysis package that standardizes output, computes diagnostics, and visualizes simulation results. Together, these tools enable reproducible intercomparison of aerosol schemes and support process-level evaluation of how model simplifications affect predictions of size distributions, cloud condensation nuclei activity, and other relevant properties relevant for the Earth-Energy system. Beyond its role in benchmarking, AMBRS provides a platform for studying aerosol processes across scales and can be used to generate training data for AI/ML applications in support of a broader hierarchical aerosol modeling strategy.

54 ENVIRONMENTAL SCIENCES↗

Progress in the development and understanding of a high poloidal-beta tokamak operating scenario for an attractive fusion pilot plant

Abstract The high poloidal-beta ( $$\beta _{\textrm{P}}$$ β P ) regime was first proposed as a high bootstrap current scenario for a steady-state fusion pilot plant (FPP) in the 1990s (Kikuchi in Nucl Fusion 30:265, 1990). Since then, there have been many theoretical, modeling, and experimental research activities on this topic. A joint DIII-D/EAST research team began exploring the high- $$\beta _{\textrm{P}}$$ β P regime in 2013, focusing on addressing the needs of attractive FPP design by taking advantage of the extensive diagnostic set and sophisticated plasma control system on DIII-D and the well-developed integrated modeling capability at General Atomics. The ultimate goal is to demonstrate such a scenario on EAST with truly long pulse and metal wall compatibility. This paper summarizes the highlights of the research results on DIII-D by the joint team in the past decade. Experimental evidence and modeling analysis show the high- $$\beta _{\textrm{P}}$$ β P scenario has great advantages in addressing key needs for an attractive FPP design, such as high-energy confinement quality at low rotation, excellent core-edge integration, high line-averaged density above the Greenwald limit, low disruption risk, and high bootstrap current fraction for steady-state operation. This provides a relatively safe and economical option to base an FPP design on that will lead to commercial fusion energy.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Deep learning with plasma plume image sequences for anomaly detection and prediction of growth kinetics during pulsed laser deposition

Abstract Materials synthesis platforms that are designed for autonomous experimentation are capable of collecting multimodal diagnostic data that can be utilized for feedback to optimize material properties. Pulsed laser deposition (PLD) is emerging as a viable autonomous synthesis tool, and so the need arises to develop machine learning (ML) techniques that are capable of extracting information from in situ diagnostics. Here, we demonstrate that intensified-CCD image sequences of the plasma plume generated during PLD can be used for anomaly detection and the prediction of thin film growth kinetics. We develop multi-output (2 + 1)D convolutional neural network regression models that extract deep features from plume dynamics that not only correlate with the measured chamber pressure and incident laser energy, but more importantly, predict parameters of an auto-catalytic film growth model derived from in situ laser reflectivity experiments. Our results demonstrate how ML with in situ plume diagnostics data in PLD can be utilized to maintain deposition conditions in an optimal regime. Further, the predictive capabilities of plume dynamics on the kinetics of film growth or other film properties prior to deposition provides a means for rapid pre-screening of growth conditions for the non-expert, which promises to accelerate materials optimization with PLD.

36 MATERIALS SCIENCE↗

Analyzing Martian winds and tracer concentrations using Mars Observer data

During the courses of a day, the Mars Observer spacecraft will acquire globally distributed profiles of the martian atmosphere. It is highly desirable that this data be assembled into synoptic weather maps (complete specifications of the atmospheric pressure, temperature, and winds at a given time), which can in turn be used as starting points in the study of many meteorological phenomena. Unfortunately, the special nature of the Mars Observer data presents several challenges above and beyond the usual difficult problem of data initialization. Mars Observer atmospheric data will consist almost exclusively of asynoptic vertical profiles of temperatures (or radiances) and pressures, whereas winds are generally in balance with horizontal gradients of these quantities (which will not be observed). It will therefore be necessary to resort to dynamical models to analyze the wind fields. As a rule, data assimilation into atmospheric models can result in the generation of spurious gravity waves, so special steps must be taken to suppress these. In addition, the asynoptic nature of the data will require a four-dimensional (space and time) data assimilation scheme. The problem is to find a full set of meteorological fields (winds and temperatures) such that, when marched forward in time in the model, they achieve a best fit (in the weighted least-squares sense) to the data. The proposed solution is to develop a model especially for the Mars Observer data assimilation problem. Gravity waves are filtered from the model by eliminating all divergence terms from the prognostic divergence equation. This leaves a diagnostic gradient wind relation between the rotational wind and the temperature field. The divergent wind is diagnosed as the wind required to maintain the gradient wind balance in the presence of the diabatic heating. The primitive equations of atmospheric dynamics (with three principal dependent variables) are thus reduced to a simpler system with a single prognostic equation for temperature - the variable that will be best observed. (This balance system was apparently first derived by Charney as a first-order Rossby number expansion of the equations of motion). Experience with a full primitive equation model of the martian atmosphere indicates that a further simplification is possible: at least for short-term integrations, the model can be linearized about the zonally symmetric basic state.

Houben, Howard C.↗