Enthalpy and entropy of para-hydrogen.
Enthalpy and entropy of parahydrogen from PVT DATA and from limited amount of thermal data
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Enthalpy and entropy of parahydrogen from PVT DATA and from limited amount of thermal data
It is shown that pseudo-range measurements to four GPS satellites based on correlation of the pseudo random code transmissions from the satellites can be used to determine the relative position of ground stations which are separated by several hundred kilometers to a precision at the centimeter level. Carrier signal measurements during the course of passage of satellites over a pair of stations also yield centimeter precision in the relative position, but oscillator instabilities limit the accuracy. The accuracy of solutions based on either type of data is limited by unmodeled tropospheric refraction effects which would reach 5 centimeters at low elevation angles for widely separated stations.
A user's manual is provided for program PARACH, a FORTRAN digital computer program operational on the Univac 1108. A description of the program and operating instructions for it are included. Program PARACH is used to study the interaction dynamics of a parachute and its payload during terminal descent. Operating instructions, required input data, program options and limitations, and output data are described. Subroutines used in this program are also listed and explained.
The current state of knowledge of the variations of the Alfvenic fluctuations with heliocentric disturbance is reviewed, and results are considered in the context of the waves-turbulence dialogue. Direct information with regard to the outer corona has been limited, and most available data has been limited to near the ecliptic plane. Determination of the possible variation of intensity and the nature of the interplanetary fluctuations with heliocentric latitude, to characterize the role of fluctuations in accelerating the solar wind, may be provided by the Ulysses mission. It is noted that application of the results of incompressible turbulence theory to the Alfvenic fluctuation problem will be problematic due to the neglect of compressibility.
A manned flight research program using a modified sailplane was conducted to very high angles of attack at the NASA-Ames. Piloting techniques were established that enabled the pilot to attain and stabilize on an angle of attack in the 30 to 72 deg range. Aerodynamic derivatives were estimated from the flight data for both low and very high angles of attack and are compared to wind tunnel data. In addition, limited performance and trim data are presented.
Advanced Microwave Scanning Radiometer (AMSR) will be flown on-board of the Japanese Advanced Earth Observing Satellite-II (ADEOS-II) and United States Earth Observation System (EOS) PM-1 satellite. AMSR is a passive microwave radiometer with frequency ranges from 6.9 GHz to 89 GHz. It scans conically with a constant incidence angle of 55 deg at the Earth's surface. The swath width is about 1600 km. With a large antenna, AMSR will provide the best spatial resolution of multi-frequency radiometer from space. This provides us an opportunity to improve the snow parameter retrieval. Accurate determination of snow parameters from space is a challenging effort. Over the years, many different techniques have been used to account for the complicated snow parameters such as the density, stratigraphy, snow grain size, temperature variation of the snow-pack. Forest type, fractional forest cover and land use type also need to be considered in developing an improved retrieval algorithm. However, snow is such a dynamic variable, snow-pack parameter keeps changing once the snow is deposited on the earth surface. Currently, NASDA and NASA are developing AMSR snow retrieval algorithms. These algorithms are now being carefully tested and evaluated using the SSM/I data. Due to limited snow-pack data available for comparison, this activity is progressing slowly. However, it is clear that in order to improve the snow retrieval algorithm, it is necessary to model the metamorphism history of the snow-pack.
A very high-momentum resolution particle spectrometer called the Alpha Magnetic Spectrometer (AMS) was flown in the payload bay of the Space Shuttle in a 51.65 degrees x 380-km orbit during the last solar minimum. This spectrometer has provided the first high statistics data set for galactic cosmic radiation protons, and helium, as well as limited spectral data on carbon and oxygen nuclei in the International Space Station orbit. First measurements of the albedo protons at this inclination were also made. Because of the high-momentum resolution and high statistics, the data can be separated as a function of magnetic latitude. A related investigation, the balloon borne experiment with a superconducting solenoid spectrometer (BESS), has been flown from Lynn Lake, Canada and has also provided excellent high-resolution data on protons and helium. These two data sets have been used here to study the validity of two galactic cosmic ray models and the geomagnetic transmission function developed from the 1990 geomagnetic reference field model. The predictions of both the CREME96 and NASA/JSC models are in good agreement with the AMS data. The shape of the AMS measured albedo proton spectrum, up to 2 GeV, is in excellent agreement with the previous balloon and satellite observations. A new LIS spectrum was developed that is consistent with both previous and new BESS 3He observations. Because the astronaut radiation exposures onboard ISS will be highest around the time of the solar minimum, these AMS measurements and these models provide important benchmarks for future radiation studies. AMS-02 slated for launch in September 2003, will provide even better momentum resolution and higher statistics data. Published by Elsevier Science Ltd.
Probing radars have been widely recognized by the science community to be an efficient tool to explore lunar subsurface providing a unique capability to address several scientific and operational issues. A wideband (200 to 1200 MHz) Ground Penetrating Radar (GPR) mounted on a surface rover can provide high vertical resolution and probing depth from few tens of centimeters to few tens of meters depending on the sounding frequency and the ground conductivity. This in term can provide a better understand regolith thickness, elemental iron concentration (including ilmenite), volatile presence, structural anomalies and fracturing. All those objectives are of important significance for understanding the local geology and potential sustainable resources for future landing sites in particular exploring the thickness, structural heterogeneity and potential volatiles presence in the lunar regolith. While the operation and data collection of GPR is a straightforward case for most terrestrial surveys, it is a challenging task for remote planetary study especially on robotic platforms due to the complexity of remote operation in rough terrains and the data collection constrains imposed by the mechanical motion of the rover and limitation in data transfer. Nevertheless, Rover mounted GPR can be of great support to perform systematic subsurface surveys for a given landing site as it can provide scientific and operational support in exploring subsurface resources and sample collections which can increase the efficiency of the EVA activities for potential human crews as part of the NASA Constellation Program. In this study we attempt to explore the operational challenges and their impact on the EVA scientific return for operating a rover mounted GPR in support of potential human activity on the moon. In this first field study, we mainly focused on the ability of GPR to support subsurface sample collection and explore shallow subsurface volatiles.
With the launch of the European Space Agency's Aeolus Mission in 2013, direct spaceborne measurements of vertical wind profiles are imminent via Doppler wind lidar technology. Part of the preparedness for such missions is the development of the proper data assimilation methodology for handling such observations. Since no heritage measurements exist in space, the Joint Observing System Simulation Experiment (Joint OSSE) framework has been utilized to generate a realistic proxy dataset as a precursor to flight. These data are being used for the development of the Gridpoint Statistical Interpolation (GSI) data assimilation system utilized at a number of centers through the United States including the Global Modeling and Assimilation Office (GMAO) at NASA/Goddard Space Flight Center and at the National Centers for Environmental Prediction (NOAA/NWS/NCEP) as an activity through the Joint Center for Satellite Data Assimilation. An update of this ongoing effort will be presented, including the methodology of proxy data generation, the limitations of the proxy data, the handling of line-of-sight wind measurements within the GSI, and the impact on both analyses and forecasts with the addition of the new data type.
Past efforts to synthesize and quantify the magnitude and change in carbon dioxide (CO 2 ) fluxes in terrestrial ecosystems across the rapidly warming Arctic–boreal zone (ABZ) have provided valuable information but were limited in their geographical and temporal coverage. Furthermore, these efforts have been based on data aggregated over varying time periods, often with only minimal site ancillary data, thus limiting their potential to be used in large-scale carbon budget assessments. To bridge these gaps, we developed a standardized monthly database of Arctic–boreal CO 2 fluxes (ABCflux) that aggregates in situ measurements of terrestrial net ecosystem CO 2 exchange and its derived partitioned component fluxes: gross primary productivity and ecosystem respiration. The data span from 1989 to 2020 with over 70 supporting variables that describe key site conditions (e.g., vegetation and disturbance type), micrometeorological and environmental measurements (e.g., air and soil temperatures), and flux measurement techniques. Here, we describe these variables, the spatial and temporal distribution of observations, the main strengths and limitations of the database, and the potential research opportunities it enables. In total, ABCflux includes 244 sites and 6309 monthly observations; 136 sites and 2217 monthly observations represent tundra, and 108 sites and 4092 observations represent the boreal biome. The database includes fluxes estimated with chamber (19 % of the monthly observations), snow diffusion (3 %) and eddy covariance (78 %) techniques. The largest number of observations were collected during the climatological summer (June–August; 32 %), and fewer observations were available for autumn (September–October; 25 %), winter (December–February; 18 %), and spring (March–May; 25 %). ABCflux can be used in a wide array of empirical, remote sensing and modeling studies to improve understanding of the regional and temporal variability in CO 2 fluxes and to better estimate the terrestrial ABZ CO 2 budget.
BACKGROUND The Privacy Act of 1974 regulates the use a nd disclosure of personally identifiable information by US Federal agencies. The Act applies to biographical, financial, a nd other identity-linked information, a s well a s personal health information (PHI). As such, the use of astronaut PHI is limited to authorized personnel for preapproved uses, with data reporting often limited to aggregated information about groups. These limitations on the use a nd reporting of astronaut PHI complicates surveillance efforts, wherein epidemiologists a t the National Aeronautics and Space Administration (NASA)monitor the incidence of targeted health conditions in the astronaut population, or to discover emerging trends of aging and disease. Stratification on one or more covariates –particularly time-period, sex, a nd mission participation –can lead to extremely small datasets such that the reporting of results is potentially attributable to individuals. An additional challenge is the small size of the astronaut population, both in terms of numbers of individuals a s well a s in terms of density of exposure time. Such small datasets yield volatile rate estimates that are difficult to interpret. To a id the epidemiological surveillance efforts, a surveillance tool is required that can (a) satisfy the need for rapid computation of condition-specific incidence and mortality rates; (b) improve the statistical estimates of these estimated rates; and (c) maintain astronaut privacy. Here we describe a nd demonstrate such a tool. METHODS We devised a system that models incidence a nd mortality rates rather than calculating them directly. This ha s the advantage of using all the available data to derive the estimates, lea ding to rates that a re not attributable to any one individual, a nd a re a s numerically stable a s they can be given the extremely limited data. The system models disease endpoints using a Poisson regression model with exposure density (measured in person-years) a s a n offset term. By doing so the model is estimating event counts per person-year, equivalent to modeling the rates directly. It uses a standard (pre-specified)set of covariates; the system does not engage in “model-building” as model parsimony is not the goa l. Instead, it is explicitly recognized that if a covariate is not statistically significant a nd not a confounder then it will likely have very little effect on the estimate of the incidence a nd mortality rates. Users are able to specify the disease endpoint of interest and the covariates over which they would like to stratify. The system then uses the resulting model to compute the estimated rates for the user-chosen configuration of variables as visualizes those either over an age range within a specified time-period, or over time for astronauts with a specified age range. RESULTS The first iteration of the tool computes incidence a nd mortality rates for cardiovascular conditions and cancers. Code ha s been developed to retrieve the appropriate data from the IMPALA analysis platform, compute the models for incidence a nd mortality, a nd then use those models to generate the corresponding rate curves. A companion graphical user interface allows the user to specify the curves and visualize the results. CONCLUSIONS It is important to note that the rapid surveillance tool described here is neither meant to be a definitive assessment of the incidence or mortality of any particular disease or condition in the astronaut population, nor is it meant to be used for research purposes. Rather, it is meant as an early indicator that in-depth investigation may be warranted. By automating a repetitive process and leveraging carefully curated astronaut health outcomes, the tool makes possible a rapid “first look” into known areas of concern, and, if used judiciously, may surface new areas of concern for long-term astronaut health. This work is supported in part by the Translational Research Institute for Space Health (TRISH) through NASA Cooperative Agreement NNX16AO69A.
We report that reliable experimental diffusion coefficients of 10 key alloying elements in Mg obtained by the present authors together with experimental data in the literature enabled us to perform a systematic test of the reliability of diffusion coefficients obtained from DFT calculations. The computed activation energy values were found to be quite accurate (mostly within 0.2 eV) but the computed pre-factors were less reliable. Such insights allowed us to develop a practical and yet robust strategy to perform diffusion mobility assessments by adopting the computed activation energy while fitting only the pre-factor when available experimental data are limited to a narrow temperature range. The overall good agreement between the DFT data and experimental data also gave us the confidence to employ the computed data for those that were still missing or inaccessible from experimental measurements. A systematic assessment of both the measured and computed diffusion data in hcp Mg was performed using the above holistic approach to yield the most comprehensive open Mg mobility database to date, comprising 23 elements (Mg, Ag, Al, Be, Ca, Cd, Ce, Cu, Fe, Ga, Gd, In, La, Li, Mn, Nd, Ni, Pu, Sb, Sn, U, Y, Zn). This more reliable mobility database will contribute to future development of advanced Mg alloys. The holistic approach developed in this study will be very beneficial to the future establishment of reliable mobility databases for other alloy systems as well.
X-ray photon correlation spectroscopy (XPCS) is a versatile tool to measure dynamics on the nanometer to micrometer scale in bulk samples. XPCS has also been applied in grazing incidence (GI) geometry to examine the dynamics of surface layers. However, considering GI scattering experiments more universally, the GI geometry leads to a superposition of signals due to reflection and refraction effects, also known from the distorted-wave Born approximation (DWBA). In this paper, the impact of these reflection and refraction effects on the correlation analysis is determined experimentally by measuring grazing incidence transmission XPCS (GT-XPCS) and grazing incidence XPCS (GI-XPCS) simultaneously for a thin film sample, showing non-equilibrium dynamics. Here the results of the GI and GT geometry comparisons are combined within the framework of the standardly applied, simplified DWBA. These calculations allow identifying the main contributions of the detected signal from the leading scattering terms along the out-of-plane direction q z , which dominate the measured intensity pattern on the detector. In combination with the calculation of the non-linear effect of refraction in GTSAXS and GISAXS, it is possible to identify experimental conditions that can be chosen to run experiments and data analysis as close as possible to transmission XPCS and to explain which limitations for data interpretations are observed. Consequently, the beam exposure can be significantly reduced by using GI geometry only. Calculations of experimental settings prior to experiments are detailed to determine suitable q z regions for a variety of material systems measured in bulk-sensitive GI-XPCS experiments, allowing us to determine the scaling behavior of typical decay times as a function of q that is comparable to the scaling behavior obtained in distortion-free GT-XPCS or transmission XPCS experiments.
The rapidly decreasing cost of gene sequencing has resulted in a deluge of genomic data from across the tree of life; however, outside a few model organism databases, genomic data are limited in their scientific impact because they are not accompanied by computable phenomic data. The majority of phenomic data are contained in countless small, heterogeneous phenotypic data sets that are very difficult or impossible to integrate at scale because of variable formats, lack of digitization, and linguistic problems. One powerful solution is to represent phenotypic data using data models with precise, computable semantics, but adoption of semantic standards for representing phenotypic data has been slow, especially in biodiversity and ecology. Some phenotypic and trait data are available in a semantic language from knowledge bases, but these are often not interoperable. In this review, we will compare and contrast existing ontology and data models, focusing on nonhuman phenotypes and traits. We discuss barriers to integration of phenotypic data and make recommendations for developing an operationally useful, semantically interoperable phenotypic data ecosystem.
Alloy 244 is a potential material of interest for molten salt reactor (MSR) developers employing molten chloride as fuel and coolant salts because of its improved mechanical properties compared to the austenitic stainless steel 316H and the Ni-base alloy Hastelloy-N. However, data are limited on the corrosion behavior of alloy 244 in molten chloride salts. Experimental data on the corrosion behavior of 244 in chloride salts will provide valuable data to MSR developers while simultaneously aiding in improving mechanistic understanding of the role of salt chemistry, alloying constituents and microstructure of 244. This task evaluated the compatibility of alloy 244 in two different eutectic NaCl–MgCl 2 salt mixtures. Similar corrosion behavior in terms of depths of attack and compositional changes in the alloy subsurface was observed after exposure in both salts for 500 h at 750°C. However, severe corrosion attack was observed after 500 h at 850°C in one of the chloride salt mixture. This was most likely due to the combined effects of the differences in the two salt chemistries, distinct microstructure of 244 at 850°C compared to 750°C, and the temperature dependence of the chemical interactions (thermodynamic and kinetic) between the alloying constituents.
In light water reactors, fuel vendors are investigating the use of dopants to modify the properties of UO 2 pellets, with the goal of improving pellet-cladding mechanical interactions during operation. Dopants are expected to ‘soften’ the pellets; that is, the doped pellets have higher plastic deformation than conventional UO 2 . This leads to a reduction in the severity of mechanical pellet-cladding interactions, helping to reduce the hoop strain on the cladding. By minimizing the strain exerted by the pellet on the cladding, it is anticipated that cladding performance under accident conditions can be enhanced (i.e., lowering the risk of burst during a LOCA). Dopants such as chromium (Cr) promote grain growth during pellet fabrication, leading to larger grains; therefore, understanding the link between chemistry, microstructure and mechanical deformation (enhanced creep rates) behavior of UO 2 is critical to helping operators further substantiate the benefits of doping UO 2 . Historically, the nuclear energy industry has relied on empirical models to make assessments of performance. Compared to empirical models, mechanistic physics-based models provide benefits, such as, fewer data points for validation and better extrapolation where experimental data is scarce or non-existent. In this report, Bayesian inference techniques have been applied to a previously developed lower length-scale-informed diffusional creep model. The objective is to i) infer lower-length-scale parameter distributions from available experiment and then ii) determine the uncertainties in the measurable quantity (in this case creep rates) after propagating the inferred lower length scale parameter uncertainties. The approach requires many evaluations of the model, which becomes computationally insurmountable; therefore, a neural-network model is trained to data obtained by sampling the full model over the most important parameters. This neural-network is then used in the Bayesian inference approach to determine probability distributions in the parameter values that represent the uncertainty in the model given what is known from the experiments (posterior). A significant reduction compared to conservative initial (prior) uncertainties is achieved through inference against the experimental data, demonstrating the efficacy of this approach. Furthermore, by accounting for uncertainties in the experimental conditions and sample non-stoichiometry, it is possible to resolve apparent discrepancies in experimental measurements within a self-consistent grain boundary (Coble) creep model that is sensitive to chemistry. This work has been written up and submitted to Nuclear Technology for a special issue on accelerated fuel qualification (AFQ). This uncertainty quantification (UQ) work not only improves the diffusional model, while accounting for uncertainty, but also establishes a framework which can readily be applied to the mechanistic models of dislocation deformation developed in this study. The most likely values from the Bayesian analysis are incorporated into our UO 2 diffusional creep model and a lower length scale-informed irradiation UO 2 creep mechanistic model to generate a dataset. This dataset has been provided to our INL collaborators for training an artificial neural network surrogate model, which will be implemented in the BISON fuel performance code to assess how the results differ from those currently obtained using a fully empirical model and that of using the nominal (uncalibrated) atomic scale parameters in our mechanistic model. Plastic deformation (creep and glide) in UO 2 is a complex phenomenon, governed by multiple underlying processes such as local defect concentrations, applied stresses, and microstructural characteristics. Consequently, there is a need for a meso-scale model with polycrystalline resolution capable of extrapolating to large grain sizes applicable to doped UO 2 , where data is limited and the model can help bridge the knowledge gap. By integrating atomistic data into the polycrystal LApx code, it becomes possible to predict dislocation climb and glide plasticity that simple analytical models cannot accurately represent. The application of atomic-scale data within LApx demonstrated the importance of climb and glide mechanisms in reproducing high-stress UO 2 behavior. Behaviors such as this are crucial to capture and implement in BISON, as parts of the fuel pellet can reach temperatures where glide can occur before pellet cracking. This model which captures dislocation based mechanisms for UO 2 is then used to stand up the doped model accounting for larger grain sizes. It was found that larger grain sizes can lead to enhanced deformation rates in the glide regime, and therefore can help with the pellet cladding mechanical interaction. Therefore if the fuel pellet reaches conditions (stress/temperature) where glide is active, the enhanced creep rates for larger grains in the glide regime (doped UO 2 ) can help with pellet cladding mechanical interactions. Plastic deformation in UO 2 involves multiple mechanisms, including diffusional creep, dislocation climb, and glide. This milestone contains two parts: (1) UQ of a pre-existing lower length scale informed mechanistic diffusional creep model, and (2) development of a new LApx based model for dislocation-mediated creep mechanisms in UO 2 , with application to large-grain doped UO 2 .
Under certain conditions, inlets with a sharp edge or geometric corner were shown to exhibit sufficiently strong separation effects to permit the working fluid to flow through the duct as if it were a free jet. Mass limiting flow data and associated pressure profiles for tubes of 53, 64, 73, and 105 length/diameter with a 90 deg sharp edge or orifice type inlet were taken and compared to Borda type inlet data to determine bounds of the free jet phenomena. For smooth tubes the limits appear to be one dimensional and dependent only on inlet stagnation conditions. Similar free jet effects were found for fluid hydrogen indicating that fluid jetting may common to all fluids flowing through 90 deg sharp edge inlet geometries.
The suggestion that primordial undifferentiated material may exist in the earth's mantle has recently been revived on the strength of Nd isotope data for two types of young continental rocks - flood basalts and kimberlites. The limited published data show a clustering of Nd isotopic compositions close to those for meteorites with chondritic relative rare-earth (REE) abundance. In contrast, data are presented for samples from the Columbia flood basalt province of the northwestern United States which show large isotopic variability suggestive of mixing processes acting after the separation of the primary magmas from their mantle source.