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At least 1,207 records · Page 67

3D Structure of Oil Droplets in Hardened Geopolymer Emulsions: Impact of Various Commercial Liquid Oils - 20184

Cement-based solidification/stabilization (S/S) is a widely applied technique for the immobilization of inorganic hazardous constituents. However, S/S is considered less compatible for organic liquid waste (OLW) because organic compounds may inhibit binder hydration. Geopolymers (i.e. alumino-silicate materials) are an alternative for applications in which Portland cements are inappropriate. In a previous work, we proposed a direct immobilization of organic liquid waste in a geopolymer binder (GEOIL composite). We demonstrated the feasibility for producing various composites on model system (hexadecane) and on a hydraulic oil, which are dispersed in the geopolymer binder as droplets (10-50 μm typical size). In nuclear facilities, legacy waste based on organic liquids are currently stored. Many of them have been used for various applications in the nuclear industry (lubrication, cutting, analysis, liquid/liquid extraction..) with very wide chemical compositions. In this study, we study the influence of various commercial organic oils immobilized in hardened geopolymer emulsions by X-ray micro-tomography. Image analysis make it possible to determine the 3D spatial and size distributions of oil droplets in geopolymer emulsions. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

MOOSE Optimization Module Overview: Application to Residual Stress Inversion in Nuclear Fuel Plates

Manufacturing methods, material selections and unique plate geometries used in low enriched uranium plate fuels for the High Performance Research Reactor (HPRR) have led to concerns about the residual stresses effect on bond strength of the fuel/cladding interfaces and overall fuel performance under irradiation. The current HPRR plate fuel test program performed residual stress calculations using the contour method with experimental displacement data obtained by incrementally cutting the plate fuel. In this work, we use a gradient based inverse optimization module developed within the MOOSE framework to estimate normal and shear residual stresses within the plate fuels using displacement data taken from a cut placed in the HPRR fuel plate. These results are verified against residual stress calculations obtained from the contour method. The inversion protocol used in this work utilizes two meshes to separately discretize the physics and parameter space. This allows a fine mesh to be used to fully resolve the physics and geometry of the forward problem. A coarser mesh is used to resolve the parameter space with spatially varying mesh density determined from a sensitivity analysis. The adaptive resolution of the parameter space essentially has the effect of regularization as it is designed to achieve the bias-variance tradeoff.

42 ENGINEERING↗

Automatic Assessment and Reduction of Noise using Edge Pattern Analysis in Non-Linear Image Enhancement

Noise is the primary visibility limit in the process of non-linear image enhancement, and is no longer a statistically stable additive noise in the post-enhancement image. Therefore novel approaches are needed to both assess and reduce spatially variable noise at this stage in overall image processing. Here we will examine the use of edge pattern analysis both for automatic assessment of spatially variable noise and as a foundation for new noise reduction methods.

Jobson, Daniel J.↗

The effect of a transducer’s spatial averaging on an elastodynamic guided wave’s wavenumber spectrum

Elastodynamic guided waves propagate in an elastic solid which makes it difficult, if not impractical, to place a receiving transducer in the direct path of the propagating wave (as one would for an acoustic wave in a fluid medium). Thus, to account for this, receiving transducers are often placed on the surface of the solid waveguide such that the transducer surface is parallel to the wave propagation direction. This transducer orientation introduces spatial averaging, which causes the received signal to have an altered signal amplitude and mode bias. We investigate both of these effects and present a simple model from which we derive a scaling-ratio expression that describes the effects of spatial averaging. Furthermore, we then test its performance using finite-element simulations that incorporate “real-world” assumptions (e.g., transient waves, piezoelectric effects, etc.). The results from the simulations demonstrate that the scaling-ratio can characterize the effects resulting from spatial averaging. The scaling-ratio expression will be particularly useful when designing experiments involving high frequency (small wavelength) guided waves. Lastly, the proposed scaling-ratio expression could be applied to other sensing methods, like Laser Doppler Vibrometry (LDV) or piezoelectric waveguides with inter-digitated transducers, because of its generality. However, the authors are careful to note that the scaling-ratio expression is not intended as a replacement of multi-physics analysis or good experimental design, and the effects of spatial averaging should be avoided whenever possible.

2DFFT↗

An Integrated Assessment of a G3 GMD Event on Large-Scale Power Grids: From Magnetometer Data to Geomagnetically Induced Current Analysis

Solar activities can cause geomagnetic disturbances (GMDs) that give rise to geomagnetically induced currents (GICs) which may compromise the reliability of the power system. In order to build more reliable models representing GMD interactions with the power grid, the power system’s detailed electrical model must be considered along with fluctuations in the earth’s magnetic and induced surface electric fields. Here, this study investigates the impact of incorporating spatially varying magnetic fields into surface electric field models on GMD risk metrics. A spatially independent magnetic field model and a spatially varying model are compared through simulations. To perform this analysis, the earth’s magnetic field disturbances are transformed into surface electric fields using respective one-dimensional earth conductivity models. Then, the modeling impact of these electric fields is studied using a 2,000-bus grid for Texas and a 25,000-bus grid for the northeast and mid- Atlantic regions of the United States. Simulation results reveal that the inclusion of spatially varying magnetic fields results in considerable differences in GMD risk metrics, highlighting the importance of accounting for spatial variability when assessing GMD risks in the power system.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Remote sensing inputs to landscape models which predict future spatial land use patterns for hydrologic models

A tropical forest area of Northern Thailand provided a test case of the application of the approach in more natural surroundings. Remote sensing imagery subjected to proper computer analysis has been shown to be a very useful means of collecting spatial data for the science of hydrology. Remote sensing products provide direct input to hydrologic models and practical data bases for planning large and small-scale hydrologic developments. Combining the available remote sensing imagery together with available map information in the landscape model provides a basis for substantial improvements in these applications.

Miller, L. D.↗

Cometary atmospheres: Modeling the spatial distribution of observed neutral radicals

An algorithm for the random walk problem of multiple elastic collisions between newly formed non-thermal neutral cometary radicals and the outflowing cometary molecules was incorporated into the Monte Carlo particle-trajectory model. Preliminary model analysis has shown that the effects of collision on the observed spatial distribution of cometary radicals becomes important for the larger bright comets, especially at smaller values of the helicocentric distance. The model and early results are discussed herein.

Combi, M. R.↗

Global Energy and Water Budgets in MERRA

Reanalyses, retrospectively analyzing observations over climatological time scales, represent a merger between satellite observations and models to provide globally continuous data and have improved over several generations. Balancing the Earth s global water and energy budgets has been a focus of research for more than two decades. Models tend to their own climate while remotely sensed observations have had varying degrees of uncertainty. This study evaluates the latest NASA reanalysis, called the Modern Era Retrospective-analysis for Research and Applications (MERRA), from a global water and energy cycles perspective. MERRA was configured to provide complete budgets in its output diagnostics, including the Incremental Analysis Update (IAU), the term that represents the observations influence on the analyzed states, alongside the physical flux terms. Precipitation in reanalyses is typically sensitive to the observational analysis. For MERRA, the global mean precipitation bias and spatial variability are more comparable to merged satellite observations (GPCP and CMAP) than previous generations of reanalyses. Ocean evaporation also has a much lower value which is comparable to observed data sets. The global energy budget shows that MERRA cloud effects may be generally weak, leading to excess shortwave radiation reaching the ocean surface. Evaluating the MERRA time series of budget terms, a significant change occurs, which does not appear to be represented in observations. In 1999, the global analysis increments of water vapor changes sign from negative to positive, and primarily lead to more oceanic precipitation. This change is coincident with the beginning of AMSU radiance assimilation. Previous and current reanalyses all exhibit some sensitivity to perturbations in the observation record, and this remains a significant research topic for reanalysis development. The effect of the changing observing system is evaluated for MERRA water and energy budget terms.

Bosilovich, Michael G.↗

Estimating Spatially-distributed Surface Fluxes in a Semi-arid Great Basin Desert Using Landsat TM Thermal Data

The research described in this chapter demonstrates a method for using Landsat Thematic Mapper data to estimate instantaneous regional-scale energy fluxes over an arid valley in eastern Nevada, U.S.A. Here point-based models of surface energy and water balance fluxes were applied to individual pixels of a Landsat Thematic Mapper scene over the study area. Although the method used to estimate these instantaneous fluxes requires certain assumptions be made about the spatial distribution of several physical parameters, the results from this analysis and modeling suggest that it is possible to scale from point measurements of environmental state variables (i.e., net radiation flux, surface heat flux, sensible heat flux, and latent heat flux) to regional estimates of energy exchange to obtain an understanding of the spatial relationship between these fluxes and landscape variables.

Quattrochi, Dale A.↗

The use of Doppler radar to help forecast the development of thunderstorms

The role of Doppler radars in forecasting the location and timing of the initiation of thunderstorms both over Kennedy Space Center and central Florida is analyzed. The data used in this analysis was collected with two Doppler radars with high temporal and spatial resolution throughout the troposphere. Previous studies of thunderstorm initiation in the vicinity of Kennedy Space Center, including synoptic and site-specific observations are outlined. As a result of the analysis of nine cases of thunderstorm initiation, it is concluded that an expert system could be developed that would take input data from the existing field mill network, instrumented tower network, lightning detection system, from sounding, and from Doppler-radar-based algorithms. Such a system would be able to determine a probability of thunderstorm development in the next 10, 20, and 30 minutes for the area of interest.

Eilts, Michael D.↗

Griffin: A MOOSE-based reactor physics application for multiphysics simulation of advanced nuclear reactors

Griffin is a Multiphysics Object-Oriented Simulation Environment (MOOSE) based reactor physics application for multiphysics simulations of advanced reactor designs jointly developed by Idaho National Laboratory and Argonne National Laboratory. This paper summarizes the motivation, significance, architecture, design, and features of Griffin. Griffin offers flexible and extensible features to address the challenges associated with advanced reactor designs. These features range from fundamental particle transport to specific reactor physics tasks. The features cover a wide range including on-the-fly and traditional two-step cross-section generation methods, steady-state and transient transport solvers suitable for both heterogeneous and homogeneous models, high-fidelity depletion where thousands of isotopes can be tracked and low-fidelity depletion characterized by burnup, etc. The most fundamental aspect that sets Griffin apart from other reactor analysis codes is that it is developed based on the MOOSE framework. A modular development approach is strongly enforced, with multiphysics being an essential element considered since the beginning of Griffin’s development. Griffin links various MOOSE physics modules and couples to other MOOSE-based applications and non-MOOSE-based applications for multiphyiscs simulations. Griffin includes three modules: ISOXML for preparing and managing multigroup cross sections, radiation transport for solving the neutron transport equation, and reactor analysis for user-oriented reactor physics analysis functionalities. Griffin uses various finite element methods for spatial discretization, multigroup approximation for energy discretization and discrete ordinates method, spherical harmonics expansion method, and diffusion approximation for streaming direction discretization to solve the neutron transport equation. Griffin’s flexibility is evidenced through Griffin’s various applications to fast reactor, high-temperature reactor, pebble bed reactor, molten salt reactor, and microreactor designs. Griffin development follows the software quality assurance procedure for MOOSE-based applications and with software requirements consistent with the ASME NQA-1 standard. Griffin has been adopted into the reactor analysis system for the U.S. NRC and is in use at U.S. companies, universities and national laboratories.

97 MATHEMATICS AND COMPUTING↗

Analysis of Interpretable Data Representations for 4D-STEM Using Unsupervised Learning

Abstract Understanding the structure of materials is crucial for engineering devices and materials with enhanced performance. Four-dimensional scanning transmission electron microscopy (4D-STEM) is capable of mapping nanometer-scale local crystallographic structure over micron-scale field of views. However, 4D-STEM datasets can contain tens of thousands of images from a wide variety of material structures, making it difficult to automate detection and classification of structures. Traditional automated analysis pipelines for 4D-STEM focus on supervised approaches, which require prior knowledge of the material structure and cannot describe anomalous or deviant structures. In this article, a pipeline for engineering 4D-STEM feature representations for unsupervised clustering using non-negative matrix factorization (NMF) is introduced. Each feature is evaluated using NMF and results are presented for both simulated and experimental data. It is shown that some data representations more reliably identify overlapping grains. Additionally, real space refinement is applied to identify spatially distinct sample regions, allowing for size and shape analysis to be performed. This work lays the foundation for improved analysis of nanoscale structural features in materials that deviate from expected crystallographic arrangement using 4D-STEM.

Bruefach, Alexandra (ORCID:0000000209323477)↗

A Method to Retrieve Rainfall Rate over Land from TRMM Observations

Tropical Rainfall Measuring Mission (TRMM) Precipitation Radar (PR) observations over mesoscale convective systems (MCSs) reveal that there are localized maxima in the rain rate with a scale of about 10 to 20 km that represent thunderstorms (Cbs). Some of these Cbs are developing or intense, while others are decaying or weak. These Cbs constitute only about 20 % of the rain area of a given MCS. Outside of Cbs, the average rain rate is much weaker than that within Cbs. From an analysis of the PR data, we find that the spatial distribution of rain and its character, convective or stratiform, is highly inhomogeneous. This complex nature of rain exists on a scale comparable to that of a Cb. The 85 GHz brightness temperature, T85, observations of the TRMM Microwave Imager (TMI) radiometer taken over an MCS reflect closely the PR rain rate pattern over land. Local maxima in rain rate shown by PR are observed as local minima in T85. Where there are no minima in T85, PR observations indicate there is light rain. However, the TMI brightness temperature measurements (Tbs) have poor ability to discriminate convective rain from stratiform rain. For this reason, a TMI rain retrieval procedure that depends primarily on the magnitude of Tbs performs poorly. In order to retrieve rain rate from TMI data on land one has to include the spatial distribution information deduced from the T85 data in the retrieval method. Then, quantitative estimation of rain rate can be accomplished. A TMI rain retrieval method developed along these lines can yield estimates of rain rate and its frequency distribution which agree closely with that given by PR. We find the current TRMM project TMI (Version 5) rain retrieval algorithm on land could be improved with the retrieval scheme developed here. To support the conceptual frame work of the rain retrieval method developed here, a theoretical analysis of the TMI brightness temperatures in convective and stratiform regions is presented.

Prabhakara, C.↗

Modeling Variable Renewable Energy and Storage in the Power Sector

The emergence of variable renewable energy and battery storage technologies have fundamentally transformed the electric power sector and generated demand for analysis to understand their roles in future energy systems. Although unique characteristics of these resources are well-recognized and require more sophisticated methodologies to capture effectively, guidance is limited on best practices and research gaps. This paper selectively reviews recent literature and draws upon our collective modeling experience to offer recommendations to analysts and consumers of model outputs on approaches for modeling variable renewable energy and storage in long-term electric sector models. We focus on regional- and national-scale models with technological, temporal, and spatial detail given their prevalence in planning and policy analysis, though insights are applicable in other settings. The review highlights how the research frontier has advanced in representing renewables and energy storage over the past decade; however, given the many considerations involved with appropriately capturing salient economic and operational characteristics of renewables, there is a gap between commonly used models and state-of-the-art methods. Model simplifications can materially impact policy analysis associated with power sector decarbonization and high renewables deployment, and improving model representations of variable renewables can enhance insights for policymakers and other stakeholders. This review can point the way for improved methods for established models and designs for emerging ones.

energy and environmental policy↗

Influence of spatial filtering on possible anisotropies in solar oscillations

Full disk Doppler observations of solar oscillations were used to compare the amplitudes of sectoral modes propagating along the equator with those of similar modes propagating along a great circle aligned with the poles. It is found that the amplitudes are generally not equal for the two classes of modes, but the results are sensitive to analysis procedures attempting to isolate the different modes of oscillation. Spatial filtering of the data using spherical harmonics suggests that greater amplitudes are associated with 'polar' sectoral modes than with 'equatorial' sectoral modes.

Hill, Frank↗

Synthetic aperture radar imaging of moving ocean waves

A theory for the radar imaging of ocean waves is presented under the assumptions that a swell propagates through an ensemble of Bragg scatterers and that the integration time of the synthetic aperture radar (SAR) is small compared to the angular velocity of the swell. Results are presented which show image development and distortions caused by the radial velocities and accelerations of the swell. Neglecting small wave bunching and tilts due to the longer underlying waves, and considering only one-dimensional geometries, the mechanism of wave motions are considered and their efforts on the production of the usual intensity pattern representing the wave image are studied. The analysis shows that in certain situations a processed image can appear which has twice the spatial period of the actual long wave on the ocean, which can confuse the interpretation of ocean wave analysis.

Swift, C. T.↗

Using NASA Environmental Data to Enhance Public Health Decision Making

The Universities Space Research Association at the NASA Marshall Space Flight Center is collaborating with the University of Alabama at Birmingham (UAB) School of Public Health and the Centers for Disease Control and Prevention (CDC) to address issues of environmental health and enhance public health decision making by utilizing NASA remotely sensed data and products. The objectives of this collaboration are to develop high-quality spatial data sets of environmental variables, and deliver the data sets and associated analyses to local, state and federal end-user groups. These data can be linked spatially and temporally to public health data, such as mortality and disease morbidity, for further analysis and decision making. Three daily environmental data sets have been developed for the conterminous U.S. on different spatial resolutions for the time period 2003-2008: (1) spatial surfaces of estimated fine particulate matter (PM2.5) exposures on a 10-km grid utilizing the US Environmental Protection Agency (EPA) ground observations and NASA s MODerate-resolution Imaging Spectroradiometer (MODIS) data; (2) a 1-km grid of Land Surface Temperature (LST) using MODIS data; and (3) a 12-km grid of daily Solar Insolation (SI) and maximum and minimum air temperature using the North American Land Data Assimilation System (NLDAS) forcing data. These environmental data sets will be linked with public health data from the UAB REasons for Geographic And Racial Differences in Stroke (REGARDS) national cohort study to determine whether exposures to these environmental risk factors are related to cognitive decline and other health outcomes. These environmental datasets and public health linkage analyses will be made available to public health professionals, researchers and the general public through the CDC Wide-ranging Online Data for Epidemiologic Research (WONDER) system and through peer reviewed publications. To date, two of the data sets have been released to the public in CDC WONDER, Daily Air Temperature and Heat Index for years 1979-2010, and Daily Fine Particulate Matter (PM2.5) air quality measures for years 2003-2008. These data in CDC WONDER can be aggregated to the county-level, state-level, or regional-level as per users need and downloaded in tabular, graphical, and map formats. The summary statistical output are available to web and app developers via the WONDER Application Programming Interface (API). The linkage of these data with the CDC WONDER system provides a significant addition to CDC WONDER, allowing public health researchers and policy makers to better include environmental exposure data in the context of other health data available in CDC WONDER online system. It also substantially expands public access to NASA environmental data, making their use by a wide range of decision makers feasible.

Al-Hamdan, Mohammad↗

Real time thermal imaging for analysis and control of crystal growth by the Czochralski technique

A real time thermal imaging system with temperature resolution better than +/- 0.5 C and spatial resolution of better than 0.5 mm has been developed. It has been applied to the analysis of melt surface thermal field distributions in both Czochralski and liquid encapsulated Czochralski growth configurations. The sensor can provide single/multiple point thermal information; a multi-pixel averaging algorithm has been developed which permits localized, low noise sensing and display of optical intensity variations at any location in the hot zone as a function of time. Temperature distributions are measured by extraction of data along a user selectable linear pixel array and are simultaneously displayed, as a graphic overlay, on the thermal image.

Wargo, M. J.↗