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At least 145 records · Page 8

Multi-Scale Hydrometeorological Modeling, Land Data Assimilation and Parameter Estimation with the Land Information System

The Land Information System (LIS; http://lis.gsfc.nasa.gov) is a flexible land surface modeling framework that has been developed with the goal of integrating satellite-and ground-based observational data products and advanced land surface modeling techniques to produce optimal fields of land surface states and fluxes. As such, LIS represents a step towards the next generation land component of an integrated Earth system model. In recognition of LIS object-oriented software design, use and impact in the land surface and hydrometeorological modeling community, the LIS software was selected as a co-winner of NASA?s 2005 Software of the Year award.LIS facilitates the integration of observations from Earth-observing systems and predictions and forecasts from Earth System and Earth science models into the decision-making processes of partnering agency and national organizations. Due to its flexible software design, LIS can serve both as a Problem Solving Environment (PSE) for hydrologic research to enable accurate global water and energy cycle predictions, and as a Decision Support System (DSS) to generate useful information for application areas including disaster management, water resources management, agricultural management, numerical weather prediction, air quality and military mobility assessment. LIS has e volved from two earlier efforts -- North American Land Data Assimilation System (NLDAS) and Global Land Data Assimilation System (GLDAS) that focused primarily on improving numerical weather prediction skills by improving the characterization of the land surface conditions. Both of GLDAS and NLDAS now use specific configurations of the LIS software in their current implementations.In addition, LIS was recently transitioned into operations at the US Air Force Weather Agency (AFWA) to ultimately replace their Agricultural Meteorology (AGRMET) system, and is also used routinely by NOAA's National Centers for Environmental Prediction (NCEP)/Environmental Modeling Center (EMC) for their land data assimilation systems to support weather and climate modeling. LIS not only consolidates the capabilities of these two systems, but also enables a much larger variety of configurations with respect to horizontal spatial resolution, input datasets and choice of land surface model through "plugins". LIS has been coupled to the Weather Research and Forecasting (WRF) model to support studies of land-atmosphere coupling be enabling ensembles of land surface states to be tested against multiple representations of the atmospheric boundary layer. LIS has also been demonstrated for parameter estimation, who showed that the use of sequential remotely sensed soil moisture products can be used to derive soil hydraulic and texture properties given a sufficient dynamic range in the soil moisture retrievals and accurate precipitation inputs.LIS has also recently been demonstrated for multi-model data assimilation using an Ensemble Kalman Filter for sequential assimilation of soil moisture, snow, and temperature.Ongoing work has demonstrated the value of bias correction as part of the filter, and also that of joint calibration and assimilation.Examples and case studies demonstrating the capabilities and impacts of LIS for hydrometeorological modeling, assimilation and parameter estimation will be presented as advancements towards the next generation of integrated observation and modeling systems

Peters-Lidard, Christa D.↗

The Radiation, Interplanetary Shocks, and Coronal Sources (RISCS) Toolset

We outline a plan to develop a physics based predictive toolset RISCS to describe the interplanetary energetic particle and radiation environment throughout the inner heliosphere, including at the Earth. To forecast and "nowcast" the radiation environment requires the fusing of three components: 1) the ability to provide probabilities for incipient solar activity; 2) the use of these probabilities and daily coronal and solar wind observations to model the 3D spatial and temporal heliosphere, including magnetic field structure and transients, within 10 AU; and 3) the ability to model the acceleration and transport of energetic particles based on current and anticipated coronal and heliospheric conditions. We describe how to address 1) - 3) based on our existing, well developed, and validated codes and models. The goal of RISCS toolset is to provide an operational forecast and "nowcast" capability that will a) predict solar energetic particle (SEP) intensities; b) spectra for protons and heavy ions; c) predict maximum energies and their duration; d) SEP composition; e) cosmic ray intensities, and f) plasma parameters, including shock arrival times, strength and obliquity at any given heliospheric location and time. The toolset would have a 72 hour predicative capability, with associated probabilistic bounds, that would be updated hourly thereafter to improve the predicted event(s) and reduce the associated probability bounds. The RISCS toolset would be highly adaptable and portable, capable of running on a variety of platforms to accommodate various operational needs and requirements.

Zank, G. P.↗

Development and Transition of the Radiation, Interplanetary Shocks, and Coronal Sources (RISCS) Toolset

We outline a plan to develop and transition a physics based predictive toolset called The Radiation, Interplanetary Shocks, and Coronal Sources (RISCS) to describe the interplanetary energetic particle and radiation environment throughout the inner heliosphere, including at the Earth. To forecast and "nowcast" the radiation environment requires the fusing of three components: 1) the ability to provide probabilities for incipient solar activity; 2) the use of these probabilities and daily coronal and solar wind observations to model the 3D spatial and temporal heliosphere, including magnetic field structure and transients, within 10 Astronomical Units; and 3) the ability to model the acceleration and transport of energetic particles based on current and anticipated coronal and heliospheric conditions. We describe how to address 1) - 3) based on our existing, well developed, and validated codes and models. The goal of RISCS toolset is to provide an operational forecast and "nowcast" capability that will a) predict solar energetic particle (SEP) intensities; b) spectra for protons and heavy ions; c) predict maximum energies and their duration; d) SEP composition; e) cosmic ray intensities, and f) plasma parameters, including shock arrival times, strength and obliquity at any given heliospheric location and time. The toolset would have a 72 hour predicative capability, with associated probabilistic bounds, that would be updated hourly thereafter to improve the predicted event(s) and reduce the associated probability bounds. The RISCS toolset would be highly adaptable and portable, capable of running on a variety of platforms to accommodate various operational needs and requirements. The described transition plan is based on a well established approach developed in the Earth Science discipline that ensures that the customer has a tool that meets their needs

Spann, James F.↗

Treatment of Electronic Energy Level Transition and Ionization Following the Particle-Based Chemistry Model

A new method of treating electronic energy level transitions as well as linking ionization to electronic energy levels is proposed following the particle-based chemistry model of Bird. Although the use of electronic energy levels and ionization reactions in DSMC are not new ideas, the current method of selecting what level to transition to, how to reproduce transition rates, and the linking of the electronic energy levels to ionization are, to the author s knowledge, novel concepts. The resulting equilibrium temperatures are shown to remain constant, and the electronic energy level distributions are shown to reproduce the Boltzmann distribution. The electronic energy level transition rates and ionization rates due to electron impacts are shown to reproduce theoretical and measured rates. The rates due to heavy particle impacts, while not as favorable as the electron impact rates, compare favorably to values from the literature. Thus, these new extensions to the particle-based chemistry model of Bird provide an accurate method for predicting electronic energy level transition and ionization rates in gases.

Liechty, Derek S.↗

A comparison of observed and forecast energetics over North America

The observed kinetic energy balance is calculated over North America and compared with that computed from forecast fields for the 13-15 January 1979 cyclone. The FGGE upper-air rawinsonde network serves as the observational database while the forecast energetics are derived from a numerical integration with the GLAS fourth-order general circulation model initialized at 00 GMT 13 January. Maps of the observed and predicted kinetic energy and eddy conversion are in good qualitative agreement, although the model eddy conversion tends to be 2 to 3 times stronger than the observed values. Both the forecast and observations exhibit the lower and upper tropospheric maxima in vertical profiles of kinetic energy generation and dissipation typically found in cyclonic disturbances. An interesting time lag is noted in the observational analysis with the maximum observed kinetic energy occurring 12 h later than the maximum eddy conversion over the same region.

Baker, W. E.↗

High-Performance Computing Optimization for Aladyn – Adaptive Neural Network Molecular Dynamics Mini-Application

This report provides a description and performance evaluation of the optimization techniques for high performance computing (HPC) implementation of the open source Computational Materials mini-application Aladyn (https://github.com/nasa/aladyn). Aladyn is a basic molecular dynamics code written in FORTRAN 2003, which is designed to demonstrate the use of adaptive neural networks (ANNs) in atomistic simulations. The role of ANNs is to efficiently reproduce the very complex energy landscape resulting from the atomic interactions in materials with the accuracy of the more expensive quantum mechanics-based calculations. The ANN is trained on a large set of atomic structures calculated using the density functional theory (DFT) method. While achieving orders of magnitude faster computational performance than DFT, the ANN-based approach was still very computationally demanding compared to the conventional approach of using empirically fitted energy functions. After its initial development, Aladyn was evaluated and optimized by experts at the NASA Advanced Supercomputing (NAS) division to exploit modern supercomputer architectures. The code has been optimized for execution on multicore central processing units (CPUs), including Intel® Skylake microarchitecture, and on graphic accelerators, such as Nvidia® V100 graphic processing units (GPUs), using Open Multi-Processing (OpenMP) and Open Accelerators (OpenACC) programming interfaces. The optimization achieved a speedup of 4.7 times the baseline version on CPU performance and an additional 2.4 times on CPU+GPU performance. Atomistic computer simulations are a fundamental tool in materials research to model material properties form physics-based first principles. Atomic interaction, governed by Quantum Mechanics (QM) require sophisticated and highly computationally demanding mathematical models to calculate [1]. Classical methods use approximate functional forms, empirically fitted through a set of variable parameters to emulate atomic energies as direct functions of atomic coordinates [2]. While empirical potentials are computationally much simpler, allowing simulations of large-scale systems of up to a trillion (1012) atoms [3], they are substantially less accurate compared to quantum calculations and applicable only to very specific atomic configurations or predefined crystallographic phases. A recently suggested approach is to use heuristic machine learning methods [4], such as those based on Adaptive Neural Networks (ANNs) to predict atomic energies, after being trained on a sufficiently large database of QM-calculated structures [5,6]. This approach reduces significantly the computational complexity, allowing for simulations of orders of magnitude larger systems compared to QM-based methods without compromising accuracy. Still, compared to classical methods using empirical energy functions, ANN methods remain two- to three orders of magnitude more computationally demanding. Hence, the computational cost of simulations, together with the need for extensive training of ANNs, still makes the practical implementation of ANN-based methods quite challenging. The purpose of the Aladyn mini-application software [7], available as open source at https://github.com/nasa/aladyn, is to be a testbed for exploring possible optimization strategies to develop highly scalable parallel algorithms for ANN-based atomistic simulations. Aladyn is aimed at utilizing the architecture of the high-end modern highperformance computing (HPC) hardware based on multicore central processing units (CPUs) equipped with graphic processing unit (GPU) accelerators. Specifically, the goal is to optimize the performance on a single HPC compute node, before implementing scaling to multi-node parallelization using message passing interface (MPI). At the same time, the open source code of Aladyn can serve as a training model for students and professors in academia.

Yamakov, Vesselin I.↗

NECAP 4.1: NASA's Energy-Cost Analysis Program input manual

The computer program NECAP (NASA's Energy Cost Analysis Program) is described. The program is a versatile building design and energy analysis tool which has embodied within it state of the art techniques for performing thermal load calculations and energy use predictions. With the program, comparisons of building designs and operational alternatives for new or existing buildings can be made. The major feature of the program is the response factor technique for calculating the heat transfer through the building surfaces which accounts for the building's mass. The program expands the response factor technique into a space response factor to account for internal building temperature swings; this is extremely important in determining true building loads and energy consumption when internal temperatures are allowed to swing.

Jensen, R. N.↗

Solar wind heat flow

The ability of a theoretical solar wind model to predict the energy flux density due to heat conduction was investigated. In order to demonstrate this capability, the analysis used simultaneous data from the electron plasma experiment of Ogilvie and Lind, and the vector magnetic field data of Heppner and Sugiura on OGO-5. On the strength of two independent, different, and consistent experimental determinations of the conduction of heat flux by electrons at 149.6 gigameters(1 AU), it was determined that the models for the solar wind must be able to predict a value for the heat conduction in the range 0.007 to 0.008 in order to be in agreement with the observations.

Scudder, J.↗

Energies of backstreaming protons in the foreshock

A predicted pattern of energy vs detector location in the cislunar region is displayed for protons of zero pitch angle traveling upstream away from the quasi-parallel bow shock. The pattern is implied by upstream wave boundary properties. In the solar ecliptic, protons are estimated to have a minimum of 1.1 times the solar wind bulk energy E sub SW when the wave boundary is in the early morning sector and a maximum of 8.2 E sub SW when the boundary is near the predawn flank.

Greenstadt, E. W.↗

NASA POWER: Providing Present and Future Climate Services Based on NASA Data for the Energy, Agricultural, and Sustainable Buildings Communities

NASA’s Prediction of Worldwide Energy Resource (POWER) project facilitates the use of NASA Earth Science data holdings within the renewable energy, agricultural, and building heating/cooling design industries. POWER packages solar and meteorological data at various temporal levels from several NASA projects in a user friendly GIS-enabled web services system (https://power.larc.nasa.gov). Data users can access these data either through an intuitive data viewer, image services fully integrable with GIS analysis, connections in the cloud through an Amazon Web Services S3 Bucket, or fully customizable access through an API. Data provided by POWER has been successfully used by decision makers to support actions that address climate change. For example, POWER data has been used to remotely monitor solar array fields and integrated in a sizing tool for off-grid solar and storage systems. POWER data has also been coupled with key building decision tools to support design and retrofitting of building energy systems for energy efficiency and reduction of greenhouse gases. POWER is now developing climate services to provide time series of the projected future evolution of key quantities that interest our users, such as heating/cooling degree days, temperature, wind speed, and downwelling solar flux. We demonstrate the potential of the new climate services by presenting here a range of possible future changes in these quantities at different NASA centers across the continental United States. These data services are based on downscaled climate model data from the NASA Earth Exchange Global Daily Downscaled Projections (NEX-GDDP) data set. We highlight the important insights that new climate services can provide. Our climate services will help our user communities quantify the impacts of climate change to support their key decisions in planning for the future, both inside and outside the Federal Government, especially for decisions in renewable energy and in building heating and cooling.

Bradley Hegyi↗

High Energy Astrophysics Tests of Lorentz Invariance Violation

Observations of the multi-TeV spectra of the Mkn 501 and other nearby BL Lac objects exhibit the high energy cutoffs predicted to be the result of intergalactic annihilation interactions, primarily with IR photons having a flux level as determined by various astronomical observations. After correcting for such intergalactic absorption, these spectra can be explained within the framework of synchrotron self-Compton emission models. Stecker and Glashow have shown that the existence of this annihilation via electron-positron pair production puts strong constraints on Lorentz invariance violation. Such constraints have important implications for some quantum gravity and large extra dimension models. A much smaller amount of Lorentz invariance violation has potential implications for understanding the spectra of ultrahigh energy cosmic rays.

Stecker, F. W.↗

The Spectrum of Ultrahigh Energy Cosmic Rays and Constraints on Lorentz Invariance Violation

There has been much interest in possible violations of Lorentz invariance, particularly motivated by quantum gravity theories. It has been suggested that a small amount of Lorentz invariance violation (LIV) could turn off photomeson interactions of ultrahigh energy cosmic rays (UHECRs) with photons of the cosmic background radiation and thereby eliminate the resulting sharp steepening in the spectrum of the highest energy CRs predicted by Greisen Zatsepin and Kuzmin (GZK). Recent measurements of the UHECR spectrum reported by the HiRes and Auger collaborations, however, indicate the presence of the GZK effect. We present the results of a detailed calculation of the modification of the UHECR spectrum caused by LIV using the formalism of Coleman and Glashow. We then use a chi-squared analysis to compare our results with the experimental UHECR data and thereby place limits on the amount of LIV. We also discuss how a small amount of LIV that is consistent with the experimental data can still lead to a recovery of the cosmic ray flux at higher energies than presently observed.

Stecker, F. W.↗

High Energy Astrophysics Tests of Lorentz Invariance Violation

Observations of the multi-TeV spectra of the nearby BL Lac objects Mkn 421 and Mkn 501 exhibit the high energy cutoffs predicted to be the result of intergalactic annihilation interactions, primarily with IR photons having a flux level as determined by various astronomical observations. After correcting for such intergalactic absorption, these spectra can be explained within the framework of synchrotron self-Compton emission models. Stecker & Glashow have shown that the existence of this annihilation via electron-positron pair production puts strong constraints on Lorentz violation. We will show that such constraints have important implications for some quantum gravity models and large extra dimension models. We will also discuss the potentially important effects of a smaller Lorentz violation which is consistent with these constraints on the propagation and spectra of ultrahigh energy cosmic rays.

Stecker, Floyd W.↗

Lorentz Invariance Violation and the Observed Spectrum of Ultrahigh Energy Cosmic Rays

There has been much interest in possible violations of Lorentz invariance, particularly motivated by quantum gravity theories. It has been suggested that a small amount of Lorentz invariance violation (LIV) could turn of photomeson interactions of ultrahigh energy cosmic rays (UHECRs) with photons of the cosmic background radiation and thereby eliminate the resulting sharp steepening in the spectrum of the highest energy CRs predicted by Greisen Zatsepin and Kuzmin (GZK). Recent measurements of the UHECR spectrum reported by the HiRes and Auger collaborations, however, indicate the presence of the GZK effect. We present the results of a detailed calculation of the modification of the UHECR spectrum caused by LIV using the formalism of Coleman and Glashow. We then compare these results with the experimental UHECR data from Auger and HiRes. Based on these data, we find a best fit amount of LIV of 4.5+1:5 ..4:5 x 10(exp -23),consistent with an upper limit of 6 x 10(exp -23). This possible amount of LIV can lead to a recovery of the cosmic ray spectrum at higher energies than presently observed. Such an LIV recovery effect can be tested observationally using future detectors.

Scully, S. T.↗

Exploring the Predictability of the High-Energy Tail of MEE Precipitation Based on Solar Wind Properties

Medium Energy Electron (MEE) precipitation (≳30 keV) ionizes the mesosphere and initiates chemical reactions, which ultimately can reduce mesospheric and stratospheric ozone. Currently, there are considerable differences in how existing parameterizations represent flux response, timing, and duration of MEE precipitation, especially considering its high-energy tail (≳300 keV). This study compares the nature of ≳300 to ≳30 keV electron fluxes to better understand differences within MEE precipitation. The MEE fluxes are estimated from measurements by the Medium Energy Proton and Electron Detector (MEPED) onboard the Polar Orbiting Environmental Satellite (POES) from 2004 to 2014. The fluxes are explored in the context of solar wind drivers: corotating high-speed solar wind streams (HSSs) and coronal mass ejections (CMEs) alongside their associated solar wind properties. Three key aspects of ≳300 keV electron fluxes are investigated: maximum response, peak timing, and duration. The results reveal a structure-dependent correlation (0.89) between the peak fluxes of ≳30 and ≳300 keV electrons. The epsilon coupling function correlates well (0.84) with the ≳300 keV peak flux, independent of solar wind structure. The ≳300 keV flux peaks 0–3 days after the ≳30 keV flux peaks. The highest probability (∼42%) occurs for a 1-day delay, while predictive capabilities increase when accounting for solar wind speed. The ≳300 keV flux response has the highest probability of lasting 4 days for both CMEs and HSSs. The results form a base for a stochastic MEE parameterization that goes beyond the average picture, enabling realistic flux variability on both daily and decadal scales.

J A Salice↗

Interface Finite Elements for the Analysis of Fracture Initiation and Progression

Progressive failure analyses (PFA) are important for the prediction of residual strength and damage tolerance of vehicle structures, and to predict the energy absorbing capability of vehicle structures under crash-type loads. Typically continuum damage mechanics (CDM) and fracture mechanics (FM) are the methods used for PFA. The method of interfacial damage mechanics (IDM) is used for PFA in this research. IDM has capabilities intermediate between CDM and FM, and is used to numerically model the initiation, growth, and arrest of cracks. IDM smooths the stress singularity at the crack tip, and is easily adaptable with other nonlinearties such as plasticity and material damage. IDM is implemented by user-defined interface elements in the ABAQUS/ Standard structural analysis software package. The structural components selected to demonstrate the effectiveness PFA using interface elements are, for the most part, those with published test data. These structural components were subjected to quasi-static loading in the tests. Thus, the ABAQUS analyses are used to predict geometrically and materially nonlinear equilibrium states. Impact loading, dynamic fracture, reflected stress waves, inertia, and time dependent material behavior are not considered.

Ambur, Damodar R.↗

Accurate Modeling of Lyα Profiles and their Impact on Photolysis of Terrestrial Planet Atmospheres

Accurately measuring and modeling the Lyα (Lyα; λ1215.67 Å) emission line from low-mass stars is vital for our ability to build predictive high energy stellar spectra, yet interstellar medium (ISM) absorption of this line typically prevents model-measurement comparisons. Lyα also controls the photodissociation of important molecules, like water and methane, in exoplanet atmospheres such that any photochemical models assessing potential biosignatures or atmospheric abundances require accurate Lyα host star flux estimates. Recent observations of three early M and K stars (K3, M0, M1) with exceptionally high radial velocities (>100 km s −1 ) reveal the intrinsic profiles of these types of stars as most of their Lyα flux is shifted away from the geocoronal line core and contamination from the ISM. These observations indicate that previous stellar spectra computed with the PHOENIX atmosphere code have underpredicted the core of Lyα in these types of stars. With these observations, we have been able to better understand the microphysics in the upper atmosphere and improve the predictive capabilities of the PHOENIX atmosphere code. Since these wavelengths drive the photolysis of key molecular species, we also present results analyzing the impact of the resulting changes to the synthetic stellar spectra on observable chemistry in terrestrial planet atmospheres.

Sarah Peacock↗

Load limiting energy absorbing lightweight debris catcher

In the representative embodiment of the invention disclosed, a load limiting, energy absorbing net is arranged to overlay a normally-covered vent opening in the rear bulkhead of the space orbiter vehicle. Spatially-disposed flexible retainer straps are extended from the net and respectively secured to bulkhead brackets spaced around the vent opening. The intermediate portions of the straps are doubled over and stitched together in a pattern enabling the doubled-over portions to progressively separate at a predicable load designed to be well below the tensile capability of the straps as the stitches are successively torn apart by the forces imposed on the retainer members whenever the cover plate is explosively separated from the bulkhead and propelled into the net. By arranging these stitches to be successively torn away at a load below the strap strength in response to forces acting on the retainers that are less than the combined strength of the retainers, this tearing action serves as a predictable compact energy absorber for safely halting the cover plate as the retainers are extended as the net is deployed. The invention further includes a block of an energy-absorbing material positioned in the net for receiving loose debris produced by the explosive release of the cover plate.

Kahn, Jon B.↗