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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 55 records · Page 3
All sourcesNASA NTRSDOE OSTI
NASA NTRS2011

The VIIRS Ocean Data Simulator Enhancements and Results

The VIIRS Ocean Science Team (VOST) has been developing an Ocean Data Simulator to create realistic VIIRS SDR datasets based on MODIS water-leaving radiances. The simulator is helping to assess instrument performance and scientific processing algorithms. Several changes were made in the last two years to complete the simulator and broaden its usefulness. The simulator is now fully functional and includes all sensor characteristics measured during prelaunch testing, including electronic and optical crosstalk influences, polarization sensitivity, and relative spectral response. Also included is the simulation of cloud and land radiances to make more realistic data sets and to understand their important influence on nearby ocean color data. The atmospheric tables used in the processing, including aerosol and Rayleigh reflectance coefficients, have been modeled using VIIRS relative spectral responses. The capabilities of the simulator were expanded to work in an unaggregated sample mode and to produce scans with additional samples beyond the standard scan. These features improve the capability to realistically add artifacts which act upon individual instrument samples prior to aggregation and which may originate from beyond the actual scan boundaries. The simulator was expanded to simulate all 16 M-bands and the EDR processing was improved to use these bands to make an SST product. The simulator is being used to generate global VIIRS data from and in parallel with the MODIS Aqua data stream. Studies have been conducted using the simulator to investigate the impact of instrument artifacts. This paper discusses the simulator improvements and results from the artifact impact studies.

Robinson, Wayne D.↗
NASA NTRS1984

Landsat-4 thematic mapper and thematic mapper simulator data for a porphyry copper deposit

Aircraft thematic mapper (TM) data were analyzed to evaluate the potential utility of the Landsat-4 thematic mapper for geologic mapping and detection of hydrothermal alteration zones in the Silver Bell porphyry copper deposit in southern Arizona. The data allow a comparison between aircraft TV simulator data and the Landsat-4 TM satellite data which possess similar spectral bands. A color rationcomposite of 30-m pixels was resampled, in order to clearly define a number of hydroxyl bearing minerals, (kaolinite, sericite, white mica), pyrite and iron oxide/hydroxide minerals. The iron oxide minerals have diagnostic absorption bands in the 0.45 and 0.85 micron regions of the spectrum, and the hydrous minerals are characterized by an absorption in the 2.2 micron region. The position of the spectral bands allow the TM to identify regions of hydrothermal alteration without resorting to a data processing algorithm. The comparison of the aircraft and Landsat-4 TM data showed considerable agreement, and confirmed the utility of TM data for identifying hydrothermal alteration zones. Samples of some color TM images are provided.

Abrams, M. J.↗
NASA NTRS1992

Modeling the dissipation-rate equation with the aid of direct simulation data

The epsilon-budget was computed from the direct simulation data (DNS) of Kim (1990) for developed channel flow at Re(tau) = 395. The relative magnitude of the terms in the epsilon-equation is shown with the aid of scaling arguments, and the parameter governing this magnitude is established. The modeling of the terms in the equation is then addressed in the context of eddy-viscosity k-epsilon models. Some existing models for the sum of all source and sink terms in the epsilon-equation are tested against DNS data, and an improved model is proposed on the basis of these data.

Rodi, W.↗
DOE OSTI2024

Spatially Local Surrogate Modeling of Subgrid-Scale Effects in Idealized Atmospheric Flows: A Deep Learned Approach Using High-Resolution Simulation Data

Abstract We introduce a machine learned surrogate model from high-resolution simulation data to capture the subgrid-scale effects in dry, stratified atmospheric flows. We use deep neural networks (NNs) to model the spatially local state differences between a coarse-resolution simulation and a high-resolution simulation. The setup enables the capture of both dissipative and antidissipative effects in the state differences. The NN model is able to accurately capture the state differences in offline tests outside the training regime. In online tests intended for production use, the NN-coupled coarse simulation has higher accuracy over a significant period of time compared to the coarse-resolution simulation without any correction. We provide evidence of the capability of the NN model to accurately capture high-gradient regions in the flow field. With the accumulation of the errors, the NN-coupled simulation becomes computationally unstable after approximately 90 coarse simulation time steps. Insights gained from these surrogate models further pave the way for formulating stable, complex, physics-based spatially local NN models which are driven by traditional subgrid-scale turbulence closure models. Significance Statement Flows in the atmosphere are highly chaotic and turbulent, comprising flow structures of broad scales. For effective computational modeling of atmospheric flows, the effects of the small- and large-scale structures need to be captured by the simulations. Capturing the small-scale structures requires fine-resolution simulations. Even with the current state-of-the-art supercomputers, it can be prohibitively expensive to simulate these flows when computed for the entire earth over climate time scales. Thus, it is necessary to focus on the larger-scale structures using a coarse-resolution simulation while capturing the effects of the smaller-scale structures using some parameterization (approximation) scheme and incorporating it into the coarse-resolution simulation. We use machine learning to model the effects of the small-scale structures (subgrid-scale effects) in atmospheric flows. Data from a fine-resolution simulation is used to compute the missing subgrid-scale effects in coarse-resolution simulations. We then use machine learning models to approximate these differences between the coarse- and fine-resolution simulations. We see improved accuracy for the coarse-resolution simulations when corrected using these machine learned models.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Fast and Invertible Simplicial Approximation of Magnetic‐Following Interpolation for Visualizing Fusion Plasma Simulation Data

We introduce a fast and invertible approximation for fusion plasma simulation data represented as 2D planar meshes with connectivities approximating magnetic field lines along the toroidal dimension in deformed 3D toroidal spaces. Scientific variables (e.g., density and temperature) in these fusion data are interpolated following a complex magnetic-field-line-following scheme in the toroidal space represented by a cylindrical coordinate system. This deformation in the 3D space poses challenges for root-finding and interpolation. To this end, we propose a novel paradigm for visualizing and analyzing such data based on a newly developed algorithm for constructing a 3D simplicial mesh within the deformed 3D space. Our algorithm generates a tetrahedral mesh that connects the 2D meshes using tetrahedra while adhering to the constraints on node connectivities imposed by the magnetic field-line scheme. Specifically, we first divide the space into smaller partitions to reduce complexity based on the input geometries and constraints on connectivities. Then, we independently search for a feasible tetrahedralization of each partition, considering nonconvexity. We demonstrate our method with two X-Point Gyrokinetic Code (XGC) simulation datasets on the International Thermonuclear Experimental Reactor (ITER) and Wendelstein 7-X (W7-X), and use an ocean simulation dataset to substantiate broader applicability of our method. An open source implementation of our algorithm is available at https://github.com/rcrcarissa/DeformedSpaceTet.

Ren, Congrong [The Ohio State Univ., Columbus, OH ↗
DOE OSTI2016

Impact disruption of gravity-dominated bodies: New simulation data and scaling

We present results from a suite of 169 hydrocode simulations of collisions between planetary bodies with radii from 100 to 1000 km. The simulation data are used to derive a simple scaling law for the threshold for catastrophic disruption, defined as a collision that leads to half the total colliding mass escaping the system post impact. For a target radius 100 ≤ R T ≤ 1000km and a mass M T and a projectile radius r p ≤ R T and mass mp we find that a head-on impact with velocity magnitude v is catastrophic if the kinetic energy of the system in the center of mass frame, K=0.5 M T m p v 2 /(M T +m p ) exceeds a threshold value K* that is a few times U= (3/5) GM$2\atop{T}$/RT+ (3/5) Gm$2\atop{p}$/r p + GM T m p /(R T +r p ), the gravitational binding energy of the system at the moment of impact; G is the gravitational constant. In all head-on collision runs we find K* = (5.5 ± 2.9) U. Oblique impacts are catastrophic when the fraction of kinetic energy contained in the volume of the projectile intersecting the target during impact exceeds ~2 K* for 30° impacts and ~3.5 K* for 45° impacts. We compare predictions made with this scaling to those made with existing scaling laws in the literature extrapolated from numerical studies on smaller targets. We find significant divergence between predictions where in general our results suggest a lower threshold for disruption except for highly oblique impacts with rp << RT. Lastly, this has implications for the efficiency of collisional grinding in the asteroid belt (Morbidelli et al., [2009] Icarus, 204, 558–573), Kuiper belt (Greenstreet et al., [2015] Icarus, 258, 267–288), and early Solar System accretion (Chambers [2013], Icarus, 224, 43–56).

58 GEOSCIENCES↗
DOE OSTI2022

2-D Surface Temperature Simulation Data and Matlab Scripts

SAND2023-07249O The 2-D Surface Temperature Simulation Data and Matlab software can estimate 2D temperature fields from electrical measurements along the edge of the 2D domain. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy’s National Nuclear Security Administration under contract DE-NA0003525.

Sjoberg, Carl Magnus↗
NASA NTRS1978

Aircraft simulation data management - A prototype system

Piloted flight simulations are used throughout the aircraft development process to evaluate design concepts, handling qualities and operational procedures. Simulation project managers are often inundated with data but without a convenient and efficient way to make the correlations and analyses necessary to evaluate system performance. A computer-based Simulation Management System (SIMS) is under development. SIMS will permit simulation project engineers to quickly acquire, access, display, edit, analyze, and document the information necessary to more efficiently manage the research program. SIMS features interactive, associative access to simulation data. This paper describes SIMDEM, a prototype system designed to demonstrate these concepts and procedures in order to obtain feedback from simulator users to guide system design.

Crane, D. F.↗
NASA NTRS1981

A statistical analysis of simulated data from potential stratospheric satellite missions

A simplified one-dimensional model is used to analyze simulated data from typical proposed satellite measurements of trace species in the stratosphere. Uncertainties are introduced in simulated species concentration measurements and applied to the basic physical and chemical model data. The results of the calculations are then used to predict uncertainties in the species concentrations computed by the model. Candidate satellite missions can be evaluated for net information acquired by applying the error analysis. An abbreviated depiction of the computational procedure is given, and sample histograms based on an accumulation of 200 calculations are shown for H2O2 and ClNO3, demonstrating that emergent species distributions are roughly Gaussian in the logarithm of number density. Calculated vertical concentration profiles for these two species are presented.

Nealy, J. E.↗
NASA NTRS1986

Analysis of forest structure using thematic mapper simulator data

The potential of Thematic Mapper Simulator (TMS) data for sensing forest structure information has been explored by principal components and feature selection techniques. In a survey of forest structural properties conducted for 123 field sites of the Sequoia National Park, the canopy closure could be well estimated (r = 0.62 to 0.69) by a variety of channel bands and band ratios, without reference to the forest type. Estimation of the basal area was less successful (r = 0.51 or less) on the average, but could be improved for certain forest types when data were stratified by floristic composition. To achieve such a stratification, individual sites were ordinated by a detrended correspondence analysis based on the canopy of dominant species. The analysis of forest structure in the Sequoia data suggests that total basal area can be best predicted in stands of lower density, and in younger even-aged managed stands.

Peterson, D. L.↗
NASA NTRS1997

SimGraph: A Flight Simulation Data Visualization Workstation

Today's modern flight simulation research produces vast amounts of time sensitive data, making a qualitative analysis of the data difficult while it remains in a numerical representation. Therefore, a method of merging related data together and presenting it to the user in a more comprehensible format is necessary. Simulation Graphics (SimGraph) is an object-oriented data visualization software package that presents simulation data in animated graphical displays for easy interpretation. Data produced from a flight simulation is presented by SimGraph in several different formats, including: 3-Dimensional Views, Cockpit Control Views, Heads-Up Displays, Strip Charts, and Status Indicators. SimGraph can accommodate the addition of new graphical displays to allow the software to be customized to each user s particular environment. A new display can be developed and added to SimGraph without having to design a new application, allowing the graphics programmer to focus on the development of the graphical display. The SimGraph framework can be reused for a wide variety of visualization tasks. Although it was created for the flight simulation facilities at NASA Langley Research Center, SimGraph can be reconfigured to almost any data visualization environment. This paper describes the capabilities and operations of SimGraph.

Kaplan, Joseph A.↗
DOE OSTI2022

Identifications of RR Lyrae Stars and Quasars from the Simulated Data of Mephisto-W Survey

We have investigated the feasibilities and accuracies of the identifications of RR Lyrae stars and quasars from the simulated data of the Multi-channel Photometric Survey Telescope (Mephisto) W Survey. Based on the variable sources light curve libraries from the Sloan Digital Sky Survey (SDSS) Stripe 82 data and the observation history simulation from the Mephisto-W Survey Scheduler, we have simulated the uvgriz multi-band light curves of RR Lyrae stars, quasars and other variable sources for the first-year observation of Mephisto W Survey. We have applied the ensemble machine learning algorithm Random Forest Classifier (RFC) to identify RR Lyrae stars and quasars, respectively. We build training and test samples and extract ~150 features from the simulated light curves and train two RFCs respectively for the RR Lyrae star and quasar classification. We find that, our RFCs are able to select the RR Lyrae stars and quasars with remarkably high precision and completeness, with purity = 95.4% and completeness = 96.9% for the RR Lyrae RFC and purity = 91.4% and completeness = 90.2% for the quasar RFC. In conclusion, we have also derived relative importances of the extracted features utilized to classify RR Lyrae stars and quasars.

(galaxies:) quasars: general↗
NASA NTRSDate not supplied

GMAO Simulated Data

Updates on GMAO simulated observations for PACE OCI.

Patricia Castellanos↗
NASA NTRS1996

Development of a Flight Simulation Data Visualization Workstation

Today's moderm flight simulation research produces vast amounts of time sensitive data. The meaning of this data can be difficult to assess while in its raw format . Therefore, a method of breaking the data down and presenting it to the user in a graphical format is necessary. Simulation Graphics (SimGraph) is intended as a data visualization software package that will incorporate simulation data into a variety of animated graphical displays for easy interpretation by the simulation researcher. Although it was created for the flight simulation facilities at NASA Langley Research Center, SimGraph can be reconfigured to almost any data visualization environment. This paper traces the design, development and implementation of the SimGraph program, and is intended to be a programmer's reference guide.

Kaplan, Joseph A.↗
NASA NTRS1991

The use of direct numerical simulation data in turbulence modeling

Direct numerical simulations (DNS) of turbulent flows provide a complete data base to develop and to test turbulence models. In this article, the progress made in developing models for the dissipation rate equation is reviewed. New scaling arguments for the various terms in the dissipation rate equation were tested using data from DNS of homogeneous shear flows. Modifications to the epsilon-equation model that take into account near-wall effects were developed using DNS of turbulent channel flows. Testing of new models for flows under mean compression was carried out using data from DNS of isotropically compressed turbulence. In all of these studies the data from the simulations was essential in guiding the model development. The next generation of DNS will be at higher Reynolds numbers, and will undoubtedly lead to improved models for computations of flows of practical interest.

Mansour, N. N.↗
NASA NTRS1996

User's Guide for Flight Simulation Data Visualization Workstation

Today's modern flight simulation research produces vast amounts of time sensitive data. The meaning of this data can be difficult to assess while in its raw format. Therefore, a method of breaking the data down and presenting it to the user in a graphical format is necessary. Simulation Graphics (SimGraph) is intended as a data visualization software package that will incorporate simulation data into a variety of animated graphical displays for easy interpretation by the simulation researcher. This document is intended as an end user's guide.

Kaplan, Joseph A.↗
NASA NTRS1983

The utility of calibration - Landsat 4 TM simulator data, Patrick Draw, Wyoming

A novel calibration approach was used for Landsat 4 TM simulator data acquired at the Patrick Draw test site, Wyoming, where the 'true' reflectance spectrum for any pixel area cannot be practically determined because of mixing of spectral components. An empirically derived function was first applied to the scanner data to remove the brightness gradient due to directional scattering and surface geometry. Based on the observation that the distribution of scanner brightness values (DN) were Gaussian, the minimum, mean, and maximum DN for each band were extracted and plotted versus the similar percent reflectance values determined from a large representative collection of field reflectance data for the area. These plots provided linear transformations relating DN value to reflectance in each band.

Lang, H. R.↗
NASA NTRS2016

Prospects of the ICESat-2 Laser Altimetry Mission for Savanna Ecosystem Structural Studies Based on Airborne Simulation Data

The next planned spaceborne lidar mission is the Ice, Cloud and land Elevation Satellite 2 (ICESat-2), which will use the Advanced Topographic Laser Altimeter System (ATLAS) sensor, a photon counting technique. To pre-validate the capability of this mission for studying three dimensional vegetation structure in savannas, we assessed the potential of the measurement approach to estimate canopy height in an oak savanna landscape. We used data from the Multiple Altimeter Beam Experimental Lidar (MABEL), an airborne photon counting lidar sensor developed by NASA's Goddard Space Flight Center. ATLAS-like data was generated using the MATLAS simulator, which adjusts MABEL data's detected number of signal and noise photons to that expected from the ATLAS instrument. Transects flown over the Tejon ranch conservancy in Kern County, California, USA were used for this work. For each transect we chose to use data from the near infrared channel that had the highest number of photons. We segmented each transect into 50 m, 25 m and 14 m long blocks and aggregated the photons in each block into a histogram based on their elevation values. We then used an automated algorithm to identify cut off points where the cumulative density of photons from the highest elevation indicates the presence of the canopy top and likewise where such cumulative density from the lowest elevation indicates the mean terrain elevation. MABEL derived height metrics were moderately correlated to discrete return lidar (DRL) derived height metrics r(sub 2) and RMSE values ranging from 0.60 to 0.73 and 2.9 m to 4.4 m respectively) but MATLAS simulation resulted in more modest correlations with DRL indices r(sub 2) ranging from 0.5 to 0.64 and RMSE from 3.6 m to 4.6 m). Simulations also indicated that the expected number of signal photons from ATLAS will be substantially lower, a situation that reduces canopy height estimation precision especially in areas of low density vegetation cover. On the basis of the simulated data, there is reason to believe that the ability of ICESat-2 to estimate height in savannas will be comparable to the original ICESat mission although the respective sensors have different measurement principles.

Gwenzi, David↗