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Characterizing the Chemical Stability of High Temperature Materials for Application in Extreme Environments
The chemical stability of high temperature materials must be known for use in the extreme environments of combustion applications. The characterization techniques available at NASA Glenn Research Center vary from fundamental thermodynamic property determination to material durability testing in actual engine environments. In this paper some of the unique techniques and facilities available at NASA Glenn will be reviewed. Multiple cell Knudsen effusion mass spectrometry is used to determine thermodynamic data by sampling gas species formed by reaction or equilibration in a Knudsen cell held in a vacuum. The transpiration technique can also be used to determine thermodynamic data of volatile species but at atmospheric pressures. Thermodynamic data in the Si-O-H(g) system were determined with this technique. Free Jet Sampling Mass Spectrometry can be used to study gas-solid interactions at a pressure of one atmosphere. Volatile Si(OH)4(g) was identified by this mass spectrometry technique. A High Pressure Burner Rig is used to expose high temperature materials in hydrocarbon-fueled combustion environments. Silicon carbide (SiC) volatility rates were measured in the burner rig as a function of total pressure, gas velocity and temperature. Finally, the Research Combustion Lab Rocket Test Cell is used to expose high temperature materials in hydrogen/oxygen rocket engine environments to assess material durability. SiC recession due to rocket engine exposures was measured as a function of oxidant/fuel ratio, temperature, and total pressure. The emphasis of the discussion for all techniques will be placed on experimental factors that must be controlled for accurate acquisition of results and reliable prediction of high temperature material chemical stability.
Characterization and identification of HPC applications at leadership computing facility
High Performance Computing (HPC) is an important method for scientific discovery via large-scale simulation, data analysis, or artificial intelligence. Leadership-class supercomputers are expensive, but essential to run large HPC applications. The Petascale era of supercomputers began in 2008, with the first machines achieving performance in excess of one petaflops, and with the advent of new supercomputers in 2021 (e.g., Aurora, Frontier), the Exascale era will soon begin. However, the high theoretical computing capability (i.e., peak FLOPS) of a machine is not the only meaningful target when designing a supercomputer, as the resources demand of applications varies. A deep understanding of the characterization of applications that run on a leadership supercomputer is one of the most important ways for planning its design, development and operation. In order to improve our understanding of HPC applications, user demands and resource usage characteristics, we perform correlative analysis of various logs for different subsystems of a leadership supercomputer. This analysis reveals surprising, sometimes counter-intuitive patterns, which, in some cases, conflicts with existing assumptions, and have important implications for future system designs as well as supercomputer operations. For example, our analysis shows that while the applications spend significant time on MPI, most applications spend very little time on file I/O. Combined analysis of hardware event logs and task failure logs show that the probability of a hardware FATAL event causing task failure is low. Combined analysis of control system logs and file I/O logs reveals that pure POSIX I/O is used more widely than higher level parallel I/O. Based on holistic insights of the application gained through combined and co-analysis of multiple logs from different perspectives and general intuition, we engineer features to "fingerprint" HPC applications. We use t-SNE (a machine learning technique for dimensionality reduction) to validate the explainability of our features and finally train machine learning models to identify HPC applications or group those with similar characteristic. To the best of our knowledge, this is the first work that combines logs on file I/O, computing, and inter-node communication for insightful analysis of HPC applications in production.
Data used in “Enguehard et al. 2022, Machine-Learning Functional Zonation Approach for Characterizing Terrestrial–Aquatic Interfaces: Application to Lake Erie”
The package contains the data layers used in “Enguehard et al. 2022, Machine-Learning Functional Zonation Approach for Characterizing Terrestrial–Aquatic Interfaces: Application to Lake Erie”. Spatial data layers include: topography, wetland vegetation cover, time series of Landsat’s enhanced vegetation index (EVI) between 1990 and 2020. The study aims to characterize coastal wetlands with particular focus on the co-variability between plant dynamics, topography, soil, and other environmental factors. We proposed a functional zonation approach based on machine learning clustering to identify the spatial regions, i.e., zones that capture these co-varied properties. This approach was applied to publicly available datasets along Lake Erie, in the Great Lakes Region
Neutron Resonance Spectroscopy Applications for Nuclear Fuel Characterization
Neutron absorption resonance spectroscopy (NRS) is a unique tool with various potential applications that could play an important role in advanced nuclear fuel characterization by providing advanced characterization techniques.
Cloud properties inferred from 8-12 micron data
A trispectral combination of observations at 8-, 11-, and 12-micron bands is suggested for detecting cloud and cloud properties in the infrared. Atmospheric ice and water vapor absorption peak in opposite halves of the window region so that positive 8-minus-11-micron brightness temperature differences indicate cloud, while near-zero or negative differences indicate clear regions. The absorption coefficient for water increases more between 11 and 12 microns than between 8 and 11 microns, while for ice, the reverse is true. Cloud phases is determined by a scatter diagram of 8-minus-11-micron versus 11-minus-12-micron brightness temperature differences; ice cloud shows a slope greater than 1 and water cloud less than 1. The trispectral brightness temperature method was tested upon high-resolution interferometer data resulting in clear-cloud and cloud-phase delineation. Simulations using differing 8-micron bandwidths revealed no significant degradation of cloud property detection. Thus, the 8-micron bandwidth for future satellites can be selected based on the requirements of other applications, such as surface characterization studies. Application of the technique to current polar-orbiting High-Resolution Infrared Sounder (HIRS)-Advanced Very High Resolution Radiometer (AVHRR) datasets is constrained by the nonuniformity of the cloud scenes sensed within the large HIRS field of view. Analysis of MAS (MODIS Airborne Simulator) high-spatial resolution (500 m) data with all three 8-, 11-, and 12-micron bands revealed sharp delineation of differing cloud and background scenes, from which a simple automated threshold technique was developed. Cloud phase, clear-sky, and qualitative differences in cloud emissivity and cloud height were identified on a case study segment from 24 November 1991, consistent with the scene. More rigorous techniques would allow further cloud parameter clarification. The opportunities for global cloud delineation with the Moderate-Resolution Imaging Spectrometer (MODIS) appear excellent. The spectral selection, the spatial resolution, and the global coverage are all well suited for significant advances.
Stochastic Characterization of Communication Network Latency for Wide Area Grid Control Applications.
This report characterizes communications network latency under various network topologies and qualities of service (QoS). The characterizations are probabilistic in nature, allowing deeper analysis of stability for Internet Protocol (IP) based feedback control systems used in grid applications. The work involves the use of Raspberry Pi computers as a proxy for a controlled resource, and an ns-3 network simulator on a Linux server to create an experimental platform (testbed) that can be used to model wide-area grid control network communications in smart grid. Modbus protocol is used for information transport, and Routing Information Protocol is used for dynamic route selection within the simulated network.
Characterization of iron-doped lithium niobate for holographic storage applications
A comprehensive characterization of chemical and holographic properties of eight systematically chosen Fe:LiNbO3 crystals is performed in order to determine optimum performance of the crystals in holographic storage and display applications. The discussion covers determination of Fe(2+) and Fe(3+) ion concentrations in Fe:LiNbO3 system from optical absorption and EPR measurements; establishment of the relation between the photorefractive sensitivity of Fe(2+) and Fe(3+) concentrations; study of the spectral dependence, the effect of oxygen annealing, and of other impurities on the photorefractive sensitivity; analysis of the diffraction efficiency curves for different crystals and corresponding sensitivities with the dynamic theory of hologram formation; and determination of the bulk photovoltaic fields as a function of Fe(2+) concentrations. In addition to the absolute Fe(2+) concentration, the relative concentrations of Fe(2+) and Fe(3+) ions are also important in determining the photorefractive sensitivity. There exists an optimal set of crystal characteristics for which the photorefractive sensitivity is most favorable.
Study on spectral/radiometric characteristics of the Thematic Mapper for land use applications
Previous characterization of scan-related low-frequency noise was extended and refined through detailed analysis of shutter calibration data on CCT-ADDS tapes and reflective-band data from nighttime acquisitions. A recommended correction procedure was identified that uses calibration shutter data both as a diagnostic and to obtain correction values. Through comparison of coincident TM and MSS data, illustrations of the added information content of TM data for agricultural applications were developed. The capability of improved spatial resolution to better define boundaries and to resolve spatial details is shown. Spectral analysis of tasseled-cap transformations of TM and MSS data shows high correlation between greenness features, greater signal range for TM, and indications that a subset of TM bands could accurately simulate MSS data, if required.
Perspectives and progress on wurtzite ferroelectrics: Synthesis, characterization, theory, and device applications
Wurtzite ferroelectrics are an emerging material class that expands the functionality and application space of wide bandgap semiconductors. Promising physical properties of binary wurtzite semiconductors include a large, reorientable spontaneous polarization, direct band gaps that span from the infrared to ultraviolet, large thermal conductivities and acoustic wave velocities, high mobility electron and hole channels, and low optical losses. The ability to reverse the polarization in ternary wurtzite semiconductors at room temperature enables memory and analog type functionality and quasi-phase matching in optical devices and boosts the ecosystem of wurtzite semiconductors, provided the appropriate combination of properties can be achieved for any given application. In this article, advances in the design, synthesis, and characterization of wurtzite ferroelectric materials and devices are discussed. Highlights include: the direct and quantitative observation of polarization reversal of ~135 μC/cm 2 charge in Al 1-x B x N via electron microscopy, Al 1-x B x N ferroelectric domain patterns poled down to 400 nm in width via scanning probe microscopy, and full polarization retention after over 1000 h of 200 °C baking and a 2× enhancement relative to ZnO in the nonlinear optical response of Zn 1-x Mg x O. In conclusion, the main tradeoffs, challenges, and opportunities in thin film deposition, heterostructure design and characterization, and device fabrication are overviewed.
Efficient Third Harmonic Generation for Wind Lidar Applications
The characterization of atmospheric winds on a global basis is a key parameter required for accurate weather prediction. The use of a space based lidar system for remote measurement of wind speed would provide detailed and highly accurate data for future weather prediction models. This paper reports the demonstration of efficient third harmonic conversion of a 1 micrometer laser to provide an ultraviolet (UV) source suitable for a wind lidar system based on atmospheric molecular scattering. Although infrared based lidars using aerosol scattering have been demonstrated to provide accurate wind measurement, a UV based system using molecular or Rayleigh scattering will provide accurate global wind measurements, even in those areas of the atmosphere where the aerosol density is too low to yield good infrared backscatter signals. The overall objective of this work is to demonstrate the maturity of the laser technology and its suitability for a near term flight aboard the space shuttle. The laser source is based on diode-pumped solid-state laser technology which has been extensively demonstrated at TRW in a variety of programs and internal development efforts. The pump laser used for the third harmonic demonstration is a breadboard system, designated the Laser for Risk Reduction Experiments (LARRE), which has been operating regularly for over 5 years. The laser technology has been further refined in an engineering model designated as the Compact Advanced Pulsed Solid-State Laser (CAPSSL), in which the laser head was packaged into an 8 x 8 x 18 inch volume with a weight of approximately 61 pounds. The CAPSSL system is a ruggedized configuration suitable for typical military applications. The LARRE and CAPSSL systems are based on Nd:YAG with an output wavelength of 1064 nm. The current work proves the viability of converting the Nd:YAG fundamental to the third harmonic wavelength at 355 nm for use in a direct detection wind lidar based on atmospheric Rayleigh scattering.
Trace Theorem and Applications
We characterize three-dimensional vector fields on the basis of the trace of a certain combination of normal derivatives, curl, and divergence. We clarify an unconditional connection between the values of a vector-valued function and the values of gradient, curl, and divergence on the boundary, which makes it possible to consider boundary value problems with boundary conditions that involve the basic first order differential operations of field theory.
Decay heat analysis for advanced reactor spent fuel transportation and storage applications
Accurate characterization of nuclide inventories and decay heat in spent nuclear fuel is critical for ensuring its safe handling, storage, transportation, and disposal. Although extensive research has been conducted on light-water reactor fuel, advanced reactors present unique challenges due to their diverse core configurations, fuel characteristics, neutron energy spectra, and burnup levels. Building upon previous efforts that developed representative reactor core models for various advanced reactor types and fuels, this study evaluates reactor-specific decay heat characteristics. The results highlight significant variations across advanced reactor types as well as across reactor designs within the same reactor type, and they provide comparison to typical commercial light-water reactor fuel. For example, thermal-spectrum reactor fuels were observed to have an approximately 100-fold decrease in decay heat over the first decade of cooling, whereas the reduction was 10-fold for fast-spectrum reactor fuels. Mass-specific decay heat at discharge can differ by three orders of magnitude among the fast and thermal reactor systems considered. Overall, for the analyzed advanced reactor fuel, fewer than 17 nuclides account for over 99% of total decay heat at 0.5 years, and that number drops to fewer than 7 nuclides at 100 years of cooling. By quantifying reactor-specific decay heat trends and nuclide contributions, this work provides a technical basis to support the development of spent fuel management strategies for advanced reactor fuels as well as safety evaluations for storage, transportation, and long-term waste disposal.
Dynamics of a 4x6-Meter Thin Film Elliptical Inflated Membrane for Space Applications
Dynamic characterization of a thin film inflatable elliptical structure is described in detail. A two-step finite element modeling approach in MSC/NASTRAN is utilized, consisting of (1) a nonlinear static pressurization procedure used to obtain the updated stiffness matrix, and (2) a modal "restart" eigen solution that uses the modified stiffness matrix. Unique problems encountered in modeling of this large Hexameter lightweight inflatable arc identified, including considerable difficulty in obtaining convergence in the nonlinear finite element pressurization solution. It was found that the extremely thin polyimide film material (.001 in or 1 mil) presents tremendous problems in obtaining a converged solution when internal pressure loading is applied. Approaches utilized to overcome these difficulties are described. Comparison of finite element predictions for frequency and mode shapes of the inflated structure with closed-form solutions for a flat pre-tensioned membrane indicate reasonable agreement.
Machine-Learning Functional Zonation Approach for Characterizing Terrestrial–Aquatic Interfaces: Application to Lake Erie
Ecosystems at coastal terrestrial–aquatic interfaces play a significant role in global biogeochemical cycles. In this study, we aimed to characterize coastal wetlands with particular focus on the co-variability between plant dynamics, topography, soil, and other environmental factors. We proposed a functional zonation approach based on machine learning clustering to identify the spatial regions, i.e., zones that capture these co-varied properties. This approach was applied to publicly available datasets along Lake Erie, in the Great Lakes Region. We investigated the heterogeneity of coastal ecosystem structures as a function of along-shore distance and transverse distance, based on the spatial data layers, including topography, wetland vegetation cover, and the time series of Landsat’s enhanced vegetation index (EVI) between 1990 and 2020. Results showed that the topographic metrics (elevation and slope), soil texture, and plant productivity influence the spatial distribution of wetland land-covers (emergent and phragmites). These results highlight a natural organization along the transverse axis, where the elevation and the EVI increase further away from the coastline. In addition, the clustering analysis allowed us to identify regions with distinct environmental characteristics, as well as the ones that are more sensitive to interannual lake-level variations.
Materials & Engineering: Propelling Innovation MRS Bulletin Special Issue Session
Materials enable engineering; and, engineering in turn depends on materials to transform design concepts and equations into physical entities. This relationship continues to grow with expanding societal demand for new products and processes. MRS Bulletin, a publication of the Materials Research Society (MRS) and Cambridge University Press, planned a special issue for December 2015 on Materials and Engineering: Propelling Innovation. This special issue of MRS Bulletin captured the unique relationship between materials and engineering, which are closely intertwined. A special half day session at the 2015 MRS Fall Meeting in Boston captured this discussion through presentations by high level experts followed by a panel discussion on what it takes to translate materials discoveries into products to benefit society. The Special Session included presentations by experts who are practitioners in materials as well as engineering applications, followed by a panel discussion. Participants discussed state-of-the-art in materials applications in engineering, as well as how engineering needs have pushed materials developments, as also reflected in the 20 or so articles published in the special issue of MRS Bulletin. As expected, the discussions spanned the broad spectrum of materials and provided very strong interdisciplinary interactions and discussions by participants and presenters.
Results of MODIS Band-to-Band Registration Characterization Using On-Orbit Lunar Observations
Since launch, lunar observations have been made regularly by both Terra and Aqua MODIS and used for a number of sensor calibration and characterization related applications, including radiometric stability monitoring, spatial characterization, optical leak and electronic cross-talk characterization, and calibration inter-comparison. MODIS has 36 spectral bands with a total of 490 individual detectors. They are located on four focal plane assemblies (FPA). This paper focuses on the use of MODIS lunar observations to characterize its band-to-band registration (BBR). In addition to BBR, the approach developed by the MODIS Characterization Support Team (MCST) can be used to characterize MODIS detector-to-detector registration (DDR). Long-term BBR results developed from this approach are presented and compared with that derived from a unique on-board calibrator (OBC). Results show that on-orbit changes of BBR have been very small for both Terra and Aqua MODIS and this approach can be applied to other remote sensing instruments.