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NASA NTRS2003

Radiation Belt Electron Dynamics: Modeling Atmospheric Losses

The first year of work on this project has been completed. This report provides a summary of the progress made and the plan for the coming year. Also included with this report is a preprint of an article that was accepted for publication in Journal of Geophysical Research and describes in detail most of the results from the first year of effort. The goal for the first year was to develop a radiation belt electron model for fitting to data from the SAMPEX and Polar satellites that would provide an empirical description of the electron losses into the upper atmosphere. This was largely accomplished according to the original plan (with one exception being that, for reasons described below, the inclusion of the loss cone electrons in the model was deferred). The main concerns at the start were to accurately represent the balance between pitch angle diffusion and eastward drift that determines the dominant features of the low altitude data, and then to accurately convert the model into simulated data based on the characteristics of the particular electron detectors. Considerable effort was devoted to achieving these ends. Once the model was providing accurate results it was applied to data sets selected from appropriate periods in 1997, 1998, and 1999. For each interval of -30 to 60 days, the model parameters were calculated daily, thus providing good short and long term temporal resolution, and for a range of radial locations from L = 2.7 to 3.9. .

Selesnick, R. S.↗

NASA NTRS2008

Friction Stir Weld Restart+Reweld Repair Allowables

A friction stir weld (FSW) repair method has been developed and successfully implemented on Al 2195 plate material for the Space Shuttle External Fuel Tank (ET). The method includes restarting the friction stir weld in the termination hole of the original weld followed by two reweld passes. Room temperature and cryogenic temperature mechanical properties exceeded minimum FSW design strength and compared well with the development data. Simulated service test results also compared closely to historical data for initial FSW, confirming no change to the critical flaw size or inspection requirements for the repaired weld. Testing of VPPA fusion/FSW intersection weld specimens exhibited acceptable strength and exceeded the minimum design value. Porosity, when present at the intersection was on the root side toe of the fusion weld, the "worst case" being 0.7 inch long. While such porosity may be removed by sanding, this "worst case" porosity condition was tested "as is" and demonstrated that porosity did not negatively affect the strength of the intersection weld. Large, 15-inch "wide panels" FSW repair welds were tested to demonstrate strength and evaluate residual stresses using photo stress analysis. All results exceeded design minimums, and photo stress analysis showed no significant stress gradients due to the presence of the restart and multi-pass FSW repair weld.

Clifton, Andrew↗

NASA NTRS2013

Usage of Data-Encoded Web Maps with Client Side Color Rendering for Combined Data Access, Visualization and Modeling Purposes

Current approaches to satellite observation data storage and distribution implement separate visualization and data access methodologies which often leads to the need in time consuming data ordering and coding for applications requiring both visual representation as well as data handling and modeling capabilities. We describe an approach we implemented for a data-encoded web map service based on storing numerical data within server map tiles and subsequent client side data manipulation and map color rendering. The approach relies on storing data using the lossless compression Portable Network Graphics (PNG) image data format which is natively supported by web-browsers allowing on-the-fly browser rendering and modification of the map tiles. The method is easy to implement using existing software libraries and has the advantage of easy client side map color modifications, as well as spatial subsetting with physical parameter range filtering. This method is demonstrated for the ASTER-GDEM elevation model and selected MODIS data products and represents an alternative to the currently used storage and data access methods. One additional benefit includes providing multiple levels of averaging due to the need in generating map tiles at varying resolutions for various map magnification levels. We suggest that such merged data and mapping approach may be a viable alternative to existing static storage and data access methods for a wide array of combined simulation, data access and visualization purposes.

Pliutau, Denis↗

NASA NTRSDate not supplied

TPSAS-NF1676L-21838-DND

Correlation relationships between particle microphysical parameters and optical data are investigated. The results show that surface-area concentrations and extinction coefficients are linearly correlated with a correlation coefficient above 0.99 for arbitrary particle size distribution. The correlation relationships that we obtained can be used as constraints in our inversion of optical lidar data. Simulation studies demonstrate a significant stabilization of aerosol microphysical data products if we apply the gradient correlation method (GCM) in our traditional regularization technique.

Alexei Kolgotin↗

NASA NTRS1993

AVIRIS and TIMS data processing and distribution at the land processes distributed active archive center

The U.S. Government has initiated the Global Change Research program, a systematic study of the Earth as a complete system. NASA's contribution of the Global Change Research Program is the Earth Observing System (EOS), a series of orbital sensor platforms and an associated data processing and distribution system. The EOS Data and Information System (EOSDIS) is the archiving, production, and distribution system for data collected by the EOS space segment and uses a multilayer architecture for processing, archiving, and distributing EOS data. The first layer consists of the spacecraft ground stations and processing facilities that receive the raw data from the orbiting platforms and then separate the data by individual sensors. The second layer consists of Distributed Active Archive Centers (DAAC) that process, distribute, and archive the sensor data. The third layer consists of a user science processing network. The EOSDIS is being developed in a phased implementation. The initial phase, Version 0, is a prototype of the operational system. Version 0 activities are based upon existing systems and are designed to provide an EOSDIS-like capability for information management and distribution. An important science support task is the creation of simulated data sets for EOS instruments from precursor aircraft or satellite data. The Land Processes DAAC, at the EROS Data Center (EDC), is responsible for archiving and processing EOS precursor data from airborne instruments such as the Thermal Infrared Multispectral Scanner (TIMS), the Thematic Mapper Simulator (TMS), and Airborne Visible and Infrared Imaging Spectrometer (AVIRIS). AVIRIS, TIMS, and TMS are flown by the NASA-Ames Research Center ARC) on an ER-2. The ER-2 flies at 65000 feet and can carry up to three sensors simultaneously. Most jointly collected data sets are somewhat boresighted and roughly registered. The instrument data are being used to construct data sets that simulate the spectral and spatial characteristics of the Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) instrument scheduled to be flown on the first EOS-AM spacecraft. The ASTER is designed to acquire 14 channels of land science data in the visible and near-IR (VNIR), shortwave-IR (SWIR), and thermal-IR (TIR) regions from 0.52 micron to 11.65 micron at high spatial resolutions of 15 m to 90 m. Stereo data will also be acquired in the VNIR region in a single band. The AVIRIS and TMS cover the ASTER VNIR and SWIR bands, and the TIMS covers the TIR bands. Simulated ASTER data sets have been generated over Death Valley, California, Cuprite, Nevada, and the Drum Mountains, Utah using a combination of AVIRIS, TIMS, amd TMS data, and existing digital elevation models (DEM) for the topographic information.

Mah, G. R.↗

NASA NTRS2009

Analytic Confusion Matrix Bounds for Fault Detection and Isolation Using a Sum-of-Squared- Residuals Approach

Given a system which can fail in 1 or n different ways, a fault detection and isolation (FDI) algorithm uses sensor data in order to determine which fault is the most likely to have occurred. The effectiveness of an FDI algorithm can be quantified by a confusion matrix, which i ndicates the probability that each fault is isolated given that each fault has occurred. Confusion matrices are often generated with simulation data, particularly for complex systems. In this paper we perform FDI using sums of squares of sensor residuals (SSRs). We assume that the sensor residuals are Gaussian, which gives the SSRs a chi-squared distribution. We then generate analytic lower and upper bounds on the confusion matrix elements. This allows for the generation of optimal sensor sets without numerical simulations. The confusion matrix bound s are verified with simulated aircraft engine data.

Simon, Dan↗

NASA NTRS2002

Piloted Evaluation of a UH-60 Mixer Equivalent Turbulence Simulation Model

A simulation study of a recently developed hover/low speed Mixer Equivalent Turbulence Simulation (METS) model for the UH-60 Black Hawk helicopter was conducted in the NASA Ames Research Center Vertical Motion Simulator (VMS). The experiment was a continuation of previous work to develop a simple, but validated, turbulence model for hovering rotorcraft. To validate the METS model, two experienced test pilots replicated precision hover tasks that had been conducted in an instrumented UH-60 helicopter in turbulence. Objective simulation data were collected for comparison with flight test data, and subjective data were collected that included handling qualities ratings and pilot comments for increasing levels of turbulence. Analyses of the simulation results show good analytic agreement between the METS model and flight test data, with favorable pilot perception of the simulated turbulence. Precision hover tasks were also repeated using the more complex rotating-frame SORBET (Simulation Of Rotor Blade Element Turbulence) model to generate turbulence. Comparisons of the empirically derived METS model with the theoretical SORBET model show good agreement providing validation of the more complex blade element method of simulating turbulence.

Lusardi, Jeff A.↗

NASA NTRS2021

Groundwater Recharge Estimated by Land Surface Models: An Evaluation in the Conterminous U.S.

Estimating diffuse recharge of precipitation is fundamental to assessing groundwater sustainability. Diffuse recharge is also the process through which climate and climate change directly affect groundwater. In this study, we evaluated diffuse recharge over the conterminous U.S. simulated by a suite of land surface models (LSMs) that were forced using a common set of meteorological input data. Simulated annual recharge exhibited spatial patterns that were similar among the LSMs, with the highest values in the eastern U.S. and Pacific Northwest. However, the magnitudes of annual recharge varied significantly among the models and were associated with differences in simulated ET, runoff and snow. Evaluation against two independent datasets did not answer the question of whether the ensemble mean performs the best, due to inconsistency between those datasets. The amplitude and timing of seasonal maximum recharge differed among the models, influenced strongly by model physics governing deep soil moisture drainage rates and, in cold regions, snowmelt. Evaluation using in situ soil moisture observations suggested that true recharge peaks 1-3 months later than simulated recharge, indicating systematic biases in simulating deep soil moisture. However, recharge from lateral flows and through preferential flows cannot be inferred from soil moisture data, and the seasonal cycle of simulated groundwater storage actually compared well with in situ groundwater observations. Long-term trends in recharge were not consistently correlated with either precipitation trends or temperature trends. This study highlights the need to employ dynamic flow models in LSMs, among other improvements, to enable more accurate simulation of recharge.

snowmelt↗

DOE OSTI2020

AFIP6-MkII and RERTR-12 Porosity Data Collection and Analysis for Modeling and Simulation

Gathering data for the improvement of nuclear fuel modeling and simulation efforts is the primary driver for this work. Mechanistic models allow for a better understanding of the material on a micro- and macrostructural level while saving time and money over traditional experiment efforts. Historically, summarized data and correlations are the inputs for empirical material models and model validation. When improving these models for nuclear fuels with experimental results, there is a lack of reliable data readily available. Experiments - RERTR-12 and AFIP6-MkII - were conducted to understand the irradiation behavior of metallic U-10Mo monolithic fuels for use in extreme reactor environments such as research reactors like the Advanced Test Reactor (ATR) or the High Flux Isotope Reactor (HFIR). Microstructural characteristics of fission gas pores (FGP) in each experiment are collected using an automated image analysis technique developed at the University of Florida and presented here. A series of statistical tests are performed to explore the reliability of the results, as well as understand where the data is lacking and what future data collection is necessary to provide sufficient information to assist modeling efforts. The focus is on the porosity, pore size, and eccentricity of FGPs formed during irradiation in three AFIP6-MkII samples and one RERTR-12 sample. From the analysis, it is clear there are substantial impacts of fission density on the pore structure, but there also exist also underlying connections between each sample and the behavior observed in the pores. Further analyses of the pre- and post-irradiation microstructure are needed to improve the understanding of these connections. An early method for microstructural data analysis is presented within and is currently being expanded to include other microstructure data.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

NASA NTRS1993

Autonomic physiological data associated with simulator discomfort

A physiological monitoring capability was developed for the Army's Crew Station Research and Development Facility (CSRDF), a research simulator for advanced rotorcraft. Preliminary physiological data are reported from studies of simulator-induced sickness. Our objective was to demonstrate sensitivity of physiological measures relative to self-reports of simulator sickness severity. The data suggested that heart period, tachygastria, and skin conductance level were more sensitive to simulator sickness than were vagal tone and normal myoelectrical gastric activity.

Miller, James C.↗

DOE OSTI2020

Deep learning of interface structures from simulated 4D STEM data: cation intermixing vs. roughening ∗

Abstract Interface structures in complex oxides remain an active area of condensed matter physics research, largely enabled by recent advances in scanning transmission electron microscopy (STEM). Yet the nature of the STEM contrast in which the structure is projected along the given direction precludes separation of possible structural models. Here, we utilize deep convolutional neural networks (DCNN) trained on simulated 4D STEM datasets to predict structural descriptors of interfaces. We focus on the widely studied interface between LaAlO 3 and SrTiO 3 , using dynamical diffraction theory and leveraging high performance computing to simulate thousands of possible 4D STEM datasets to train the DCNN to learn properties of the underlying structures on which the simulations are based. We test the DCNN on simulated data and show that it is possible (with >95% accuracy) to identify a physically rough from a chemically diffuse interface and create a DCNN regression model to predict step positions. We quantify the applicability of the model to different thicknesses and the transferability of the approach. The method shown here is general and can be applied for any inverse imaging problem where forward models are present.

42 ENGINEERING↗

DOE OSTI2025

Dataset for manuscript "Equipartition and the temperature of maximum density of TIP4P/2005 water"

We simulate TIP4P/2005 water in the temperature range of 257 K to 318 K with time-steps 0.25, 0.50, 1.00, 2.00, and 4.00 fs. The density-temperature behavior obtained using 0.25 or 0.50 fs are in excellent agreement with each other but differ from those obtained using time-steps that have been shown earlier to lead to a breakdown of equipartition. The temperature of maximum density (TMD) is 277.15 K with time-step 0.25 or 0.50 fs, but is shifted to progressively lower values for longer time-steps, a trend that holds for different thermostat/barostat combinations. Enhancing the water-water dispersion interaction, as has been recommended for simulating disordered proteins in TIP4P/2005, degrades the description of the liquid-vapor phase envelope. We present a simple physically transparent reasoning to highlight the separation of the time-scales between translational and rotational motion. We also develop a metric, Chi, that we term the equipartition anomaly, to detect equipartition violations in simulations that include molecules that are treated as rigid objects. Calculating Chi is shown to be straightforward and sensitive to equipartition violations. A key takeaway from this study is that using sufficiently short time-steps (less than or equal to 0.5 fs) to preserve equipartition is essential for obtaining meaningful liquid water properties and for producing reliable simulation data, as correct-ensemble sampling is fundamental to ensure reproducibility across codes and simulation alogrithms. The included dataset provides the raw data used in the preparation of the graphs noted in the manuscript.

36 MATERIALS SCIENCE↗

DOE OSTI2024

CNN-Based Phase Fault Classification in Real and Simulated Power Systems Data

This study proposes a convolutional neural network (CNN)–based two-step phase fault detection and identification method to classify anomalies in the power grid signal. Specifically, the first step checks the fault’s existence and determines the need for the second step. Subsequently, in the case of anomalies in the power grid signal, the second step identifies the type of fault, including line-to-line, single-line-to-ground, double-line-to-ground, and triple-line. Accordingly, the CNN architecture is both designed for the classification layers and trained with simulated data. To provide maximum prediction accuracy with minimum processing time, this study investigates the combinations of various feature extraction (FE) techniques, such as fast Fourier transform (FFT), amplitude and phase (AP), auto-correlation function, power spectral density, and wavelet transform (WT). Consequently, simulated and real-world results demonstrate that the proposed two-step method outperforms conventional one-step techniques, with the best performance obtained by using the combination of AP-AP, AP-WT, FFT-AP, and FFT-WT–based FE methods.

Alaca, Ozgur↗

NASA NTRS1998

Long-Term Global Morphology of Gravity Wave Activity Using UARS Data

This is the first quarter's report on research to extract global gravity-wave data from satellite data and to model those observations synoptically. Preliminary analysis of global maps of extracted middle atmospheric temperature variance from the CRISTA instrument is presented, which appear to contain gravity-wave information. Corresponding simulations of global gravity-wave and mountain-wave activity during this mission period are described using global ray-tracing and mountain-wave models, and interesting similarities among simulated data and CRISTA data are noted. Climatological simulations of mesospheric gravity-wave activity using the HWM-03 wind-temperature climatology are also reported, for comparison with UARS MLS data. Preparatory work on modeling of gravity wave observations from space-based platforms and subsequent interpretation of the MLS gravity-wave product are also described. Preliminary interpretation and relation to the research objectives are provided, and further action for the next quarter's research is recommended.

Eckermann, Stephen D.↗

NASA NTRS2019

Flight Performance Maneuver Planning for NASA’s X-57 “Maxwell” Flight Demonstrator – Part 1: Power-Off Glides

Distributed Electric Propulsion technology is expected to yield up to a fivefold increase in high-speed cruise efficiency for NASA’s X-57 “Maxwell” flight demonstrator when compared to a combustion-powered general aviation baseline. A portion of this increased efficiency is due to beneficial aero-propulsive interaction inherent to the distributed propulsion architecture. The measure of the relative increase in efficiency between a conventional and distributed propulsion wing will be extracted from comparisons between flight test data from the electrically powered X-57 Mod II configuration with a conventional wing, and from the electrically powered X-57 Mod III/IV configuration with a distributed propulsion wing. Flight test maneuvers that accommodate errors in instrumentation and the flight test environment are developed to establish the power-off drag characteristics for all X-57 configurations. Analysis of these maneuvers with typical errors, including pilot-in-the-loop simulation data that incorporates simulated atmospheric turbulence effects, shows that the proposed power-off flight maneuvers can generate accurate power-off drag predictions for the X-57. These predictions show that the power-off differences in aerodynamic performance between the conventional and distributed propulsion configurations can be accurately measured from flight test data in the presence of typical data error sources.

Borer, Nicholas K.↗

NASA NTRS1989

Advancements in turbulence modeling

Direct simulation data are used to test newly proposed nonlinear models in the Reynolds stress anisotropy for the rapid pressure-strain terms. It is found that the nonlinear models will perform better than the linear models. In addition to testing the rapid pressure-strain models, a new k-epsilon model is proposed for near-wall flow simulation. The model is proposed for near-wall flow simulation. The model was developed by fitting low-Reynolds number data from a direct simulation of a channel flow. A new wall-correction for the eddy-viscosity as well as wall-corrections for the epsilon-equation are proposed. The model will give better predictions of the turbulent kinetic profile in the near-wall region than existing models.

Mansour, N. N.↗

NASA NTRS2002

High-Resolution Simulation of Hurricane Bonnie (1998): Microphysics Validation using TRMM Data

A simulation of Hurricane Bonnie (1998) has been performed using multiple grid nesting to 2 km grid spacing. The simulation is initialized with large-scale analysis fields from the European Center for Medium Range Forecasts and with a bogus vortex inserted via four-dimensional variational data assimilation. The simulation reproduces well the storm intensity, the wavenumber 1 asymmetry of the precipitation field, the occurrence of deep convective towers within the eyewall, and the presence of broad stratiform precipitation regions. Radar and microwave observations from TRMM are used to validate the simulation. Result show excessive graupel production and, to some extent, excessive precipitation production in general by the model. Additional simulations are conducted (and validated by TRMM data) to test parameters and assumptions within the microphysics parameterizations including particle size distributions, particle densities, and assumptions that impact the partitioning of precipitation mass between graupel and snow.

Starr, David OC.↗

DOE OSTI2021

Direct evaluation of the phase diagrams of dense multicomponent plasmas by integration of the Clapeyron equations

Accurate phase diagrams of multicomponent plasmas are required for the modeling of dense stellar plasmas, such as those found in the cores of white dwarf stars and the crusts of neutron stars. Those phase diagrams have been computed using a variety of standard techniques, which suffer from physical and computational limitations. Here we present an efficient and accurate method that overcomes the drawbacks of previously used approaches. In particular, finite-size effects are avoided as each phase is calculated separately; the plasma electrons and volume changes are explicitly taken into account; and arbitrary analytic fits to simulation data as well as particle insertions are avoided. Furthermore, no simulations at “uninteresting” state conditions, i.e., away from the phase coexistence curves, are required, which improves the efficiency of the technique. The method consists of an adaptation of the so-called Gibbs-Duhem integration approach to electron-ion plasmas, where the coexistence curve is determined by direct numerical integration of its underlying Clapeyron equation. The thermodynamics properties of the coexisting phases are evaluated separately using Monte Carlo simulations in the isobaric semigrand canonical ensemble (NPT Δ μ ). We describe this Monte Carlo-based Clapeyron integration method, including its basic physical and numerical principles, our extension to electron-ion plasmas, and our numerical implementation. We illustrate its applicability and benefits with the calculation of the melting curve of dense carbon-oxygen plasmas under conditions relevant for the cores of white dwarf stars and provide analytic fits to implement this new melting curve in white dwarf models. While this work focuses on the liquid-solid phase boundary of dense two-component plasmas, a wider range of physical systems and phase boundaries are within the scope of the Clapeyron integration method, which had until now only been applied to simple model systems of neutral particles.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗