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At least 1,423 records · Page 79

Inheritance of magma ocean differentiation during lunar origin by giant impact

The giant impact model for the Moon has won widespread support. It seems to satisfactorily explain the high angular momentum of the Earth-Moon system, and the strong depletion of FeNi in the Moon. This model is usually assumed to entail no significant fractionation of nonvolatile lithophile elements relative to a simple binary mixture of impactor silicates plus protoearth silicates. Although the Earth may have been hot enough before the impact to be completely molten, analysis of the likely number and timing of major impacts in the prehistory of the impactor indicates that a fully molten, undifferentiated condition for that relatively small body is unlikely. Given selective sampling by the giant impact, any significant vertical differentiation within the noncore portion of the impactor would have been largely inherited by the Moon.

Warren, Paul H.↗

Extinction of a Free Methanol Droplet in Microgravity

The combustion of isolated, unsupported methanol droplets under microgravity conditions has been studied in the NASA-Lewis 2.2-sec drop tower. The substitution of O2/He mixtures for O2/N2 mixtures results in a substantial increase in the oxygen index required for ignition, the rate of gasification, and the diameter at extinction. As a result, droplets with initial size larger than 1 mm can be produced, deployed, ignited, and burned to extinction, all under microgravity conditions in this facility. A comprehensive time dependent numerical model incorporating detailed multicomponent molecular transport mechanisms and complex elementary chemical kinetics was developed and applied to simulate the entire transient droplet combustion processes (ignition/quasi-steady burning/extinction). Model outputs show good agreement with the experimental measurements, without parameter adjustment. Analysis of modeling results shows that the thermal conductivity of the gas phase under combustion environments increased by a factor of two when the 50-percent O2/50 percent He mixture is used instead of air. The increased thermal conductivity accelerates the heat transfer from the flame front to the droplet surface, resulting in a factor of two increase in the burning rate.

Cho, S. Y.↗

A comparative analysis of two land surface heterogeneity representations

Two contrasting representations of land surface variability used in general circulation models (GCMs) are compared through an analysis of their corresponding surface energy balance equations. In one representation (the 'mixture' approach), different vegetation types are assumed to be homogeneously mixed over a grid square, so that the GCM atmosphere sees near-surface conditions pertaining to the mixture only. In the second representation (the 'mosaic' approach), different vegetation types are viewed as separate 'tiles' of a grid-square 'mosaic', and each tile interacts with the atmosphere independently. The mosaic approach is computationally simpler and in many ways more flexible than the mixture approach. Analytical solutions to the linearized energy balance equations and numerical solutions to the nonlinear equations both demonstrate that the mixture strategy, when applied to two coexisting vegetation types that differ only in canopy transpiration resistance, promotes both total turbulent flux and latent heat flux relative to the mosaic strategy. The effective differences between the strategies, however, are small over a wide range of conditions. In particular, the strategies are effectively equivalent when the transpiration resistances of the different vegetation types are of the same order of magnitude.

Koster, Randal D.↗

Growing Three-Dimensional Cocultures Of Cells

Laboratory process provides environmental conditions favoring simultaneous growth of cocultures of mammalian cells of more than one type. Cultures become three-dimensional tissuelike assemblies serving as organoid models of differentiation of cells. Process used, for example, to study growth of human colon cancers, starting from mixtures of normal colonic fibroblasts and partially differentiated colon adenocarcinoma cells.

Wolf, David A.↗

The Influence of Thermodynamic Phase on the Retrieval of Mixed-Phase Cloud Microphysical and Optical Properties in the Visible and Near Infrared Region

Cloud microphysical and optical properties are inferred from the bidirectional reflectances simulated for a single-layered cloud consisting of an external mixture of ice particles and liquid droplets. The reflectances are calculated with a rigorous discrete ordinates radiative transfer model and are functions of the cloud effective particle size, the cloud optical thickness, and the values of the ice fraction in the cloud (i.e., the ratio of ice water content to total water content). In the present light scattering and radiative transfer simulations, the ice fraction is assumed to be vertically homogeneous; the habit (shape) percentage as a function of ice particle size is consistent with that used for the Moderate Resolution Imaging Spectroradiometer (MODIS) operational (Collection 4 and earlier) cloud products; and the surface is assumed to be Lambertian with an albedo of 0.03. Furthermore, error analyses pertaining to the inference of the effective particle sizes and optical thicknesses of mixed-phase clouds are performed. Errors are calculated with respect to the assumption of a cloud containing solely liquid or ice phase particles. The analyses suggest that the effective particle size inferred for a mixed-phase cloud can be underestimated (or overestimated) if pure liquid phase (or pure ice phase) is assumed for the cloud, whereas the corresponding cloud optical thickness can be overestimated (or underestimated).

Lee, Joonsuk↗

Mapping and monitoring changes in vegetation communities of Jasper Ridge, CA, using spectral fractions derived from AVIRIS images

An important application of remote sensing is to map and monitor changes over large areas of the land surface. This is particularly significant with the current interest in monitoring vegetation communities. Most of traditional methods for mapping different types of plant communities are based upon statistical classification techniques (i.e., parallel piped, nearest-neighbor, etc.) applied to uncalibrated multispectral data. Classes from these techniques are typically difficult to interpret (particularly to a field ecologist/botanist). Also, classes derived for one image can be very different from those derived from another image of the same area, making interpretation of observed temporal changes nearly impossible. More recently, neural networks have been applied to classification. Neural network classification, based upon spectral matching, is weak in dealing with spectral mixtures (a condition prevalent in images of natural surfaces). Another approach to mapping vegetation communities is based on spectral mixture analysis, which can provide a consistent framework for image interpretation. Roberts et al. (1990) mapped vegetation using the band residuals from a simple mixing model (the same spectral endmembers applied to all image pixels). Sabol et al. (1992b) and Roberts et al. (1992) used different methods to apply the most appropriate spectral endmembers to each image pixel, thereby allowing mapping of vegetation based upon the the different endmember spectra. In this paper, we describe a new approach to classification of vegetation communities based upon the spectra fractions derived from spectral mixture analysis. This approach was applied to three 1992 AVIRIS images of Jasper Ridge, California to observe seasonal changes in surface composition.

Sabol, Donald E., Jr.↗

Prediction of an axisymmetric combusting flow

A numerical model for turbulent, recirculating combusting flow is developed and applied to a research combustor. The model is based on the time-averaged Navier-Stokes equations with k-epsilon turbulence closure and the compositional fluctuations at each point are given probabilistically in terms of the mixture fraction. The probability density function is derived from transport equations for its first two moments along with an assumption regarding its shape. The resulting equations are solved using a standard line relaxation algorithm. It is found that the predictions of the model are in good agreement with data from an axisymmetric, bluff-body stabilized research combustor, while the major discrepancies are similar to those found in isothermal flow comparisons. The peculiar features of this flow which contribute to the errors are examined. The agreement between the theory and data deteriorates as the central jet velocity is increased which indicates an enhanced role for unsteady effects.

Correa, S. M.↗

Experimental basis for a Titan probe organic analysis

The recent Voyager flyby of Titan produced evidence for at least nine organic compounds in that atmosphere that are heavier than methane. Several models of Titan's atmosphere, as well as laboratory simulations, suggest the presence of organics considerably more complex that those observed. To ensure that the in situ measurements are definitive with respect to Titan's atmosphere, experiment concepts, and the related instrumentation, must be carefully developed specifically for such a mission. To this end, the possible composition of the environment to be analyzed must be bracketed and model samples must be provided for instrumentation development studies. Laboratory studies to define the optimum flight experiment and sampling strategy for a Titan entry probe are currently being conducted. Titan mixtures are being subjected to a variety of energy sources including high voltage electron from a DC discharge, high current electric shock, and laser detonation. Gaseous and solid products are produced which are then analyzed. Samples from these experiements are also provided to candidate flight experiments as models for instrument development studies. Preliminary results show that existing theoretical models for chemistry in Titan's atmosphere cannot adequetely explain the presence and abundance of all trace gases observed in these experiments.

Mckay, C. P.↗

Performance Evaluation Modeling of Network Sensors

Substantial benefits are promised by operating many spatially separated sensors collectively. Such systems are envisioned to consist of sensor nodes that are connected by a communications network. A simulation tool is being developed to evaluate the performance of networked sensor systems, incorporating such metrics as target detection probabilities, false alarms rates, and classification confusion probabilities. The tool will be used to determine configuration impacts associated with such aspects as spatial laydown, and mixture of different types of sensors (acoustic, seismic, imaging, magnetic, RF, etc.), and fusion architecture. The QualNet discrete-event simulation environment serves as the underlying basis for model development and execution. This platform is recognized for its capabilities in efficiently simulating networking among mobile entities that communicate via wireless media. We are extending QualNet's communications modeling constructs to capture the sensing aspects of multi-target sensing (analogous to multiple access communications), unimodal multi-sensing (broadcast), and multi-modal sensing (multiple channels and correlated transmissions). Methods are also being developed for modeling the sensor signal sources (transmitters), signal propagation through the media, and sensors (receivers) that are consistent with the discrete event paradigm needed for performance determination of sensor network systems. This work is supported under the Microsensors Technical Area of the Army Research Laboratory (ARL) Advanced Sensors Collaborative Technology Alliance.

probability of detection↗

Using a Chromatographic Pseudophase Model To Elucidate the Mechanism of Olefin Separation by Silver(I) Ions in Ionic Liquids

Silver(I) ions undergo selective olefin complexation and have been utilized in various olefin/paraffin separation techniques such as argentation chromatography and facilitated transport membranes. Ionic liquids (ILs) are solvents known for their low vapor pressure, high thermal stability, low melting points, and ability to promote a favorable solvation environment for silver(I) ion–olefin interactions. To develop highly selective separation systems, a fundamental understanding of analyte partitioning to the stationary phase and the thermodynamic driving forces behind solvation is required. In this study, a chromatographic model treating silver(I) ions as a pseudophase is constructed and employed for the first time to investigate the olefin separation mechanism in silver(I) salt/IL mixtures. Stationary phases containing varying amounts of noncoordinated silver(I) salt ([Ag + ][NTf 2 – ]) dissolved in the 1-decyl-3-methylimidazolium bis[(trifluoromethyl)sulfonyl]imide ([C 10 MIM + ][NTf 2 – ]) IL are utilized to determine the partition coefficients of various analytes including alkanes, alkenes, alkynes, aromatics, aldehyde, esters, and ketones. As ligand coordination to silver(I) ions is known to lower its olefin complexation capability, this study also examines two different types of coordinated silver(I) ion pseudophases, namely, monocoordinated silver(I) salt ([Ag + (1-decyl-2-methylimidazole, DMIM)][NTf 2 – ]) and dicoordinated silver(I) salt ([Ag + (1-methylimidazole, MIM)(DMIM)][NTf 2 – ]). The extent of olefin partitioning to the coordinated silver(I) ion pseudophases over the carrier gas and IL decreased by up to two orders of magnitude. Values for enthalpy, entropy, and free energy of solvation were determined for the three silver(I) ion-containing systems. Olefin retention was observed to be enthalpically dominated, while ligand coordination to the silver(I) ion pseudophase resulted in variations for both enthalpic and entropic contributions to the free energy of solvation. Furthermore, the developed model can be used to study chemical changes that occur in silver(I) ions over time as well as identify optimal silver(I) salt/IL mixtures that yield high olefin selectivity.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Hierarchical transfer learning: an agile and equitable strategy for machine-learning interatomic models

Machine-learned interatomic models are growing in popularity due to their ability to afford near quantum-accurate predictions for complex phenomena with orders-of-magnitude greater computational efficiency. However, these models struggle when applied to systems of many element types due to the approximately exponential increase in number of parameters that must be determined. To mitigate this challenge, we present a new hierarchical transfer learning approach that allows the fitting problem to be decomposed into smaller independent and reusable parameter blocks that enable development of explicitly chemically extensible ML-IAM. Application of this strategy is demonstrated for C and N mixtures under conditions ranging from nominally ambient to ~10,000 K and 200 GPa for compositions from 0 to 100% N. Ultimately, this strategy makes model generation for chemically complex systems more tractable and efficient, facilitates comprehensive model validation, and makes ML-IAM development for problems of this nature more accessible to users with limited access to extreme computing infrastructure.

Lindsey, Rebecca K. [Univ. of Michigan, Ann Arbor,↗

Tritium Breeding Ratio Evaluation of Solid Breeder Concepts for the FESS-FNSF

This paper presents a parametric study of the Fusion Energy System Studies-Fusion Nuclear Science Facility’s (FNSF’s) tritium breeding performance for several solid breeder concepts, neutron multiplying materials, and blanket materials, assuming volume fractions based on the most recent FNSF design as a realistically representative fusion facility. In this study, we initially surveyed the tritium breeding ratio (TBR) of several solid breeder concepts by employing a simplified but efficient one-dimensional (1-D) infinite cylinder reduced-order model (ROM). Parametric studies were performed with the ROMs for the full range of breeder-to-multiplier ratios to identify the optimum mixture compositions for each breeder type that would lead to a maximum TBR. These optimized breeder-multiplier combinations were then homogenized with FNSF blanket component materials to estimate their impacts on the TBR. Subsequently, as a validation step for the optimal designs, TBR calculations were performed using a more realistic modified 1-D ROM with inner and outer breeding regions, as well as with a fully detailed 22.5-deg three-dimensional (3-D) sector of the FNSF to assess the impact of geometry details on the TBR. The differences between the two 1-D models were negligible, while the ROMs were able to correctly predict trends and identify the maximum and minimum TBR cases, as well as show consistent biases relative to the results produced by the full 3-D, 22.5-deg sector for specific breeder/multiplier combinations. Solid breeder concepts such as Li 2 O, Li 4 SiO 4 , and Li 8 ZrO 6 outperformed all others in this study in terms of TBR performance when combined with all the neutron multiplier materials selected. Here, an underlying goal of this study was to develop and improve rapid and reliable ROMs to aid designers during parametric optimizations of highly complex and computationally expensive fusion models.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

On the applicability of the Redlich-Kister framework for viscosity estimation of molten halide salt mixtures

For molten halide salt mixtures already being utilized or under consideration for carbon-free energy production systems, it is crucial that their viscosity is well understood so that system thermal hydraulics can be reliably assessed. Because of the difficulty in accurately measuring molten halide viscosity and the sheer size of the matrix of possible higher order salt mixtures that may be of interest to the energy industry, there are several gaps in the quantified understanding of molten halide viscosity across this matrix. As such, both first-principles and semi-empirical modeling techniques may be crucial for rapidly assessing this broad, complex compositional domain. Herein, the Redlich-Kister framework is applied to assess the feasibility of broadly interpolating and estimating the viscosity of several pseudobinary and pseudoternary molten halide salt systems that may be of key interest to the energy industry. The framework is based on the assumption that an ideal component and a nonideal component collectively describe the viscosity as a function of composition and temperature for a given molten halide system. Three different ideal models were considered for the ideal component, including Grunburg-Nissan, Katti-Chaudhri, and Gambill methods. Regarding the pseudobinary interpolations, the Redlich-Kister models with either the Grunburg-Nissan or Katti-Chaudhri models as the ideal component resulted in either highly (average error less than 5%) or reasonably (average error less than 15%) accurate interpolations of pseudobinary halide viscosity; BeF 2 - or UF 4 -bearing salts tended to result in reasonably accurate interpolations, whereas other pseudobinary mixtures tended to show high accuracy. Regarding the pseudoternary extrapolations, the Redlich-Kister framework shows reasonable success at estimating the extent to which a pseudoternary system may indicate deviations from ideal Grunburg-Nissan mixing, where discrepancies with comparative experimental data generally stay within 30%. Finally, the primary reasons identified for such discrepancies are (1) inaccuracy in the underlying experimental data, (2) different complexation behavior in the higher order systems compared to the pseudobinary subsystems, and (3) extrapolation into temperatures too far out of the domain, which is valid for the underlying experimental data feeding the Redlich-Kister model.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Recent Developments in the Assimilation of Microwave and Radar Observations Into NWP Models

Microwave observations play a very important role in improving the weather forecasts. Although these observations are routinely assimilated into NWP models in clear-sky conditions, assimilation of all-sky microwave observations is very limited. Two main factors contributing to this limitation are inaccuracy in the input cloud and hydrometeor profiles used as input to the radiative transfer model and also error in scattering calculations performed by the radiative transfer model itself. The Mie theory is used by many fast RT models to estimate the optical properties of single particles. The Mie theory assumes spherical shapes for ice or snow particles with mixture of air and ice. However, hydrometeors scattering radiation at microwave frequencies have different shapes, sizes, and orientations. Therefore, using Mie theory to determine their optical properties leads to large uncertainties in all-sky radiative transfer calculations. The discrete dipole approximation (DDA) which approximates the optical properties of large objects in terms of discrete dipoles has shown promise in calculating the scattering properties of particles with different shapes in the microwave frequencies. This presentation focuses on recent advancements in the CRTM scattering calculations for frozen hydrometeors in the microwave frequencies using the DDA technique. In addition to using stand-alone CRTM calculations using collocated ATMS and reanalysis profiles, the data assimilation experiments conducted using the NOAA FV3GFS forecast system are used to evaluate the scattering improvements. Additionally, the backscattering information from the DDA database was used to implement a radar simulator into CRTM. The radar operator takes advantage of CRTM different modules to calculate clouds absorption and scattering properties. In addition to the forward model both adjoint and tangent linear of the radar simulator are implemented and evaluated as well. The radar simulator is currently being tested within the JEDI/GEOS data assimilation framework to facilitate the assimilation of radar measurements such as CloudSat CPR and GPM DPR into the NASA GEOS model.

Isaac Moradi↗

Enhancing CRTM All-Sky Simulations and Implementation of A New Active Sensor Module

Microwave observations play a very important role in improving the weather forecasts. Although these observations are routinely assimilated into NWP models in clear-sky conditions, assimilation of all-sky microwave observations is very limited. Two main factors contributing to this limitation are inaccuracy in the input cloud and hydrometeor profiles used as input to the radiative transfer model and also error in scattering calculations performed by the radiative transfer model itself. The Mie theory is used by many fast RT models to estimate the optical properties of single particles. The Mie theory assumes spherical shapes for ice or snow particles with mixture of air and ice. However, hydrometeors scattering radiation at microwave frequencies have different shapes, sizes, and orientations. Therefore, using Mie theory to determine their optical properties leads to large uncertainties in all-sky radiative transfer calculations. The discrete dipole approximation (DDA) which approximates the optical properties of large objects in terms of discrete dipoles has shown promise in calculating the scattering properties of particles with different shapes in the microwave frequencies. This presentation focuses on recent advancements in the CRTM scattering calculations for frozen hydrometeors in the microwave frequencies using the DDA technique. In addition to using stand-alone CRTM calculations using collocated ATMS and reanalysis profiles, the data assimilation experiments conducted using the NOAA FV3GFS forecast system are used to evaluate the scattering improvements. Additionally, the backscattering information from the DDA database was used to implement a radar simulator into CRTM. The radar operator takes advantage of CRTM different modules to calculate clouds absorption and scattering properties. In addition to the forward model both adjoint and tangent linear of the radar simulator are implemented and evaluated as well. The radar simulator is currently being tested within the JEDI/GEOS data assimilation framework to facilitate the assimilation of radar measurements such as CloudSat CPR and GPM DPR into the NASA GEOS model.

Isaac Moradi↗

CRTM Microwave Cloud Scattering Lookup Tables and Radar Simulator

Microwave observations play a very important role in improving the weather forecasts. Although these observations are routinely assimilated into NWP models in clear-sky conditions, assimilation of all-sky microwave observations is very limited. Two main factors contributing to this limitation are inaccuracy in the input cloud and hydrometeor profiles used as input to the radiative transfer model and also error in scattering calculations performed by the radiative transfer model itself. The Mie theory is used by many fast RT models to estimate the optical properties of single particles. The Mie theory assumes spherical shapes for ice or snow particles with mixture of air and ice. However, hydrometeors scattering radiation at microwave frequencies have different shapes, sizes, and orientations. Therefore, using Mie theory to determine their optical properties leads to large uncertainties in all-sky radiative transfer calculations. The discrete dipole approximation (DDA) which approximates the optical properties of large objects in terms of discrete dipoles has shown promise in calculating the scattering properties of particles with different shapes in the microwave frequencies. This presentation focuses on recent advancements in the CRTM scattering calculations for frozen hydrometeors in the microwave frequencies using the DDA technique. In addition to using stand-alone CRTM calculations using collocated ATMS and reanalysis profiles, the data assimilation experiments conducted using the NOAA FV3GFS forecast system are used to evaluate the scattering improvements. Additionally, the backscattering information from the DDA database was used to implement a radar simulator into CRTM. The radar operator takes advantage of CRTM different modules to calculate clouds absorption and scattering properties. In addition to the forward model both adjoint and tangent linear of the radar simulator are implemented and evaluated as well. The radar simulator is currently being tested within the JEDI/GEOS data assimilation framework to facilitate the assimilation of radar measurements such as CloudSat CPR and GPM DPR into the NASA GEOS model.

Isaac Moradi↗

Experimental Constraints on a Vesta Magma Ocean

A magma ocean model was devised to relate eucrites (basalts) and diogenites (orthopyroxenites), which are found mixed together as clasts in a suite of polymict breccias known as howardites. The intimate association of eucritic and diogenitic clasts in howardites argues strongly that these three classes of achondritic meteorites all originated from the same planetoid. Reflectance spectral evidence (including that from the DAWN mission) has long suggested that Vesta is indeed the Eucrite Parent Body. Specifically, the magma ocean model was generated as follows: (i) the bulk Vesta composition was taken to be 0.3 CV chondrite + 0.7 L chondrite but using only 10% of the Na2O from this mixture; (ii) this composition is allowed to crystallize at 500 bar until approx. 80% of the system is solid olivine + low-Ca pyroxene; (iii) the remaining 20% liquid crystallizes at one bar from 1250C to 1110C, a temperature slightly above the eucrite solidus. All crystallization calculations were performed using MELTS. In this model, diogenites are produced by cocrystallization of olivine and pyroxene in the >1250C temperature regime, with Main Group eucrite liquids being generated in the 1300-1250C temperature interval. Low-Ca pyroxene reappears at 1210C in the one-bar calculations and fractionates the residual liquid to produce evolved eucrite compositions (Stannern Trend). We have attempted to experimentally reproduce the <1250C portion of the MELTS Vesta magma ocean. In the MELTS calculation, the change from 500 bar to one bar results in a shift of the olivine:low-Ca pyroxene boundary so that the 1250C liquid is now in the olivine field and, consequently, olivine should be the first-crystallizing phase, followed by low-Ca pyroxene at 1210C, and plagioclase at 1170C. Because at one bar the olivine:low-Ca pyroxene boundary is a peritectic, fractional crystallization of the 1210C liquid proceeds with only pyroxene crystallization until plagioclase appears. Thus, the predictions of the MELTS calculation are clear and straightforward.

Hoff, C.↗