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At least 1,153 records · Page 64
All sourcesNASA NTRSDOE OSTI
NASA NTRS2006

Introduction to MODIS Cloud Products

The Earth's radiative energy balance and hydrological cycle are fundamentally coupled with the distribution and properties of clouds. Therefore, the ability to remotely infer cloud properties and their variation in space and time is crucial for establishing climatologies as a reference for validation of present-day climate models and in assessing future climate change. Remote cloud observations also provide data sets useful for testing and improving cloud model physics, and for assimilation into numerical weather prediction models. The MODerate Resolution Imaging Spectroradiometer (MODIS) imagers on the Terra and Aqua Earth Observing System (EOS) platforms provide the capability for globally retrieving these properties using passive solar reflectance and infrared techniques. In addition to providing measurements similar to those offered on a suite of historical operational weather platforms such as the Advanced Very High Resolution Radiometer (AVHRR), the High-resolution Infrared Radiation Sounder (HIRS), and the Geostationary Operational Environmental Satellite (GOES), MODIS provides additional spectral and/or spatial resolution in key atmospheric bands, along with on-board calibration, to expand the capability for global cloud property retrievals. The core MODIS operational cloud products include cloud top pressure, thermodynamic phase, optical thickness, particle size, and water path, and are derived globally at spatial resolutions of either 1- or 5-km (referred to as Level-2 or pixel-level products). In addition, the MODIS atmosphere team (collectively providing cloud, aerosol, and clear sky products) produces a combined gridded product (referred to as Level-3) aggregated to a 1 equal-angle grid, available for daily, eight-day, and monthly time periods. The wealth of information available from these products provides critical information for climate studies as well as the continuation and improved understanding of existing satellite-based cloud climatologies derived from heritage instruments. This chapter provides an overview of the MODIS Level-2 and -3 operational cloud products.

Baum, Bryan A.↗
DOE OSTI2016

Towards an improved understanding of the influence of subpixel vegetation structure on pixel-level spectra: a simulation approach

The planned NASA Hyperspectral Infrared Imager (HyspIRI) mission, equipped with an imaging spectrometer that has the capability of monitoring ecosystems globally, will provide an unprecedented opportunity to address scientific challenges related to ecosystem function and change. However, uncertainty remains around the impact of subpixel vegetation structure, in combination with the point spread function, on pixel-level imaging spectroscopy data. We estimated structural parameters, e.g., leaf area index (LAI), canopy cover, and tree location, from HyspIRI spectral data, with the goal of assessing how subpixel variation in these parameters impact pixel-level imaging spectroscopy data. The fine-scale variability of real vegetation structure makes this a challenging endeavor. Therefore, we utilized a simulation-based approach to counter the time-consuming and often destructive sampling needs of vegetation structural analysis and to simultaneously generate synthetic HyspIRI data pre-launch. Three virtual scenes were constructed, corresponding to the actual vegetation structure in the National Ecological Observatory Network’s (NEON) Pacific Southwest Domain (Fresno, CA). These included an oak savanna, a dense coniferous forest, and a conifer-manzanita-mixed forest. Simulated spectroscopy data for these scenes were then generated using the Digital Imaging and Remote Sensing Image Generation (DIRSIG) model. Simulations first were used to verify the physical model, virtual scene geometrical information, and simulation parameters. This was followed by simulations of HyspIRI data, where within-pixel structural variability was introduced, e.g., by iteratively changing per-pixel canopy cover and tree placement, tree clustering, leaf area index (LAI), etc., between simulation runs for the virtual scenes. Finally, narrow-band vegetation indices (VIs) were extracted from the data in an attempt to describe the variability of the subpixel structural parameters; this was done in order to assess VI robustness to changes in structural “levels”, as well as placement of trees/canopies within the instrument’s instantaneous field-of-view (IFOV). Our ultimate goal is not only to better understand how such subpixel variability influence imaging spectroscopy outputs, but also to better estimate vegetation structural parameters using spectra. We constructed regression models for LAI (R2 = 0.92) and canopy cover (R2 = 0.97) with narrow-band VIs via this simulation approach. Our models ultimately are intended to improve the HyspIRI mission’s ability to monitor global vegetation structure.

Van Aardt, Jan↗
DOE OSTI2012

Implementation of non-condensable gases condensation suppression model into the WCOBRA/TRAC-TF2 LOCA safety evaluation code

The non-condensable gases condensation suppression model is important for a realistic LOCA safety analysis code. A condensation suppression model for direct contact condensation was previously developed by Westinghouse using first principles. The model is believed to be an accurate description of the direct contact condensation process in the presence of non-condensable gases. The Westinghouse condensation suppression model is further revised by applying a more physical model. The revised condensation suppression model is thus implemented into the WCOBRA/TRAC-TF2 LOCA safety evaluation code for both 3-D module (COBRA-TF) and 1-D module (TRAC-PF1). Parametric study using the revised Westinghouse condensation suppression model is conducted. Additionally, the performance of non-condensable gases condensation suppression model is examined in the ACHILLES (ISP-25) separate effects test and LOFT L2-5 (ISP-13) integral effects test. (authors)

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
NASA NTRSDate not supplied

Hybrid Model Based Approaches for Systems Health Management and Prognostics

To facilitate and solve the prediction problem, awareness of the current health state of the system is key, since it is necessary to perform condition-based predictions. To accurately predict the future state of any system, it is required to possess knowledge of its current health state and future operational conditions. Latest achievements of data-driven algorithms in regression of complex nonlinear functions and classification tasks have generated a growing interest in artificial intelligence for industrial applications. Complex multi-physics models as well as digital twins, once purely built on physics and corresponding simplified lumped parameter iterations, can now benefit from machine learning algorithms to mitigate the lack of understanding of some complex behavior. Given models of the current and future system behavior, a general approach of model-based prognostics can solve the prediction problem and further decision making. In principle, data driven approaches can replace expensive experimental test-setups as well as reduce the number of simulations needed to explore, e.g., the parametric space of a multi-parameter model. Nonetheless, the limitations of pure data-driven methods came to light rather quickly, at least for some industries. In many industrial applications, data acquisition is costly, and the volume of data that can be collected does not satisfy the requirements for an effective model training and cross-validation. Therefore, some recent works in the area of machine learning is focusing on blending physics with data-driven algorithms, thus mitigating the drawbacks of the two approaches and emphasizing respective advantages. Partial physical knowledge of the problem can aid the learning process by “guiding” the algorithm towards efficient solutions that satisfy the physics driving the system behavior. The result is a hybrid modeling approach combining physical knowledge as well data driven methods to develop a unified hybrid approach. A hybrid framework for fusing information from physics-based performance models along with deep learning algorithms for prognostics of complex safety critical systems is presented. In this framework, physics-based performance models infer unobservable model parameters related to the system's components health solving a calibration problem in the deep learning approach.

Hybrid Modeling↗
DOE OSTI2010

THE ORIGIN OF THE HOT GAS IN THE GALACTIC HALO: CONFRONTING MODELS WITH XMM-NEWTON OBSERVATIONS

We compare the predictions of three physical models for the origin of the hot halo gas with the observed halo X-ray emission, derived from 26 high-latitude XMM-Newton observations of the soft X-ray background between l = 120{sup 0} and l = 240{sup 0}. These observations were chosen from a much larger set of observations as they are expected to be the least contaminated by solar wind charge exchange emission. We characterize the halo emission in the XMM-Newton band with a single-temperature plasma model. We find that the observed halo temperature is fairly constant across the sky ({approx}(1.8-2.4) x 10{sup 6} K), whereas the halo emission measure varies by an order of magnitude ({approx}0.0005-0.006 cm{sup -6} pc). When we compare our observations with the model predictions, we find that most of the hot gas observed with XMM-Newton does not reside in isolated extraplanar supernova (SN) remnants-this model predicts emission an order of magnitude too faint. A model of an SN-driven interstellar medium, including the flow of hot gas from the disk into the halo in a galactic fountain, gives good agreement with the observed 0.4-2.0 keV surface brightness. This model overpredicts the halo X-ray temperature by a factor of {approx}2, but there are a several possible explanations for this discrepancy. We therefore conclude that a major (possibly dominant) contributor to the halo X-ray emission observed with XMM-Newton is a fountain of hot gas driven into the halo by disk SNe. However, we cannot rule out the possibility that the extended hot halo of accreted material predicted by disk galaxy formation models also contributes to the emission.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2018

Analytic comparison of the dispersion relation of waves present in various MHD models

Ideal magnetohydrodynamics (MHD) has been a widely used theoretical model for studying fusion plasmas. However, as it is well known, MHD is not an entirely accurate physical model and, in some cases, can miss essential physics that is of interest. To remedy this, several improved MHD models have been proposed; these include Hall MHD and a recently developed extended-MHD model. For these models, it is important to understand the predicted plasma responses to infinitesimal perturbations; that is, their relevant wave dynamics. In this work, I derive the wave dispersion relations for ideal, Hall, and extended MHD models and compare them to those obtained using the two-fluid model for plasmas. It is shown that, for waves with frequencies below or close to the ion gyrofrequency, Hall MHD and extended MHD reproduce quite accurately the wave dispersion relations. However, as it is expected, at higher wave frequencies, all MHD models diverge from the results predicted using the two-fluid model.

42 ENGINEERING↗
DOE OSTI2019

Introduction to the Special Section on Fast Physics in Climate Models: Parameterization, Evaluation and Observation

Many physical processes that influence Earth’s climate occur at scales of space and time that are too small to be resolved by typical global climate models (GCMS). These processes – e.g., aerosol/cloud physics, convection, boundary layer processes, turbulence, radiation, and land-atmosphere interactions–must be parameterized in GCMs, and are collectively called fast physics or fast processes for convenience.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS1992

Validation and upgrading of physically based mathematical models

The validation of the results of physically-based mathematical models against experimental results was discussed. Systematic techniques are used for: (1) isolating subsets of the simulator mathematical model and comparing the response of each subset to its experimental response for the same input conditions; (2) evaluating the response error to determine whether it is the result of incorrect parameter values, incorrect structure of the model subset, or unmodeled external effects of cross coupling; and (3) modifying and upgrading the model and its parameter values to determine the most physically appropriate combination of changes.

Duval, Ronald↗
DOE OSTI2021

High-resolution hourly surrogate modeling framework for physics-based large-scale building stock modeling

Surrogate modeling can play a key role in reducing high computational burdens for large-scale physics-based modeling and uncertainty quantification. With the rapid development of large-scale building stock energy modeling, surrogate modeling has also begun to be widely applied in this field; however, most existing surrogate models lack hourly time resolution for regional-scale modeling, which is essential for understanding building demand profiles and grid impacts. Further, there is generally a lack of necessary data and feature engineering frameworks specific to building modeling for efficiently managing large datasets and complex computations. Furthermore, this paper proposes a modeling framework for large-scale (city-/region-scale), high-resolution, high-fidelity surrogate building stock energy models. Our developed framework consists of six modules: (1) building stock energy modeling (ComStock TM and ResStock TM ), (2) data engineering for large simulation data, (3) high performance computing workflow, (4) feature engineering, (5) machine learning model development, and (6) model performance evaluation. Two case studies apply the developed framework in both residential and commercial building stock analysis to demonstrate its computational efficiency and surrogate modeling accuracies. Results show that surrogate models, when efficiently trained using the HPC workflow module, reach a high level of modeling accuracy for two case studies.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2013

Simulations of drift resistive ballooning L-mode turbulence in the edge plasma of the DIII-D tokamak

Results from simulations of electromagnetic drift-resistive ballooning turbulence for tokamak edge turbulence in realistic single-null geometry are reported. The calculations are undertaken with the BOUT three-dimensional fluid code that solves Braginskii-based fluid equations [X. Q. Xu and R. H. Cohen, Contrib. Plasma Phys. 36, 158 (1998)]. The simulation setup models L-mode edge plasma parameters in the actual magnetic geometry of the DIII-D tokamak [J. L. Luxon et al., Fusion Sci. Technol. 48, 807 (2002)]. The computations track the development of drift-resistive ballooning turbulence in the edge region to saturation. Fluctuation amplitudes, fluctuation spectra, and particle and thermal fluxes are compared to experimental data near the outer midplane from Langmuir probe and beam-emission-spectroscopy for a few well-characterized L-mode discharges in DIII-D. The simulations are comprised of a suite of runs in which the physics model is varied to include more fluid fields and physics terms. The simulations yield results for fluctuation amplitudes, correlation lengths, particle and energy fluxes, and diffusivities that agree with measurements within an order of magnitude and within factors of 2 or better for some of the data. The agreement of the simulations with the experimental measurements varies with respect to including more physics in the model equations within the suite of models investigated. The simulations show stabilizing effects of sheared E × B poloidal rotation (imposed zonal flow) and of lower edge electron temperature and density.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2015

THREE-DIMENSIONAL RADIO AND X-RAY MODELING AND DATA ANALYSIS SOFTWARE: REVEALING FLARE COMPLEXITY

Many problems in solar physics require analysis of imaging data obtained in multiple wavelength domains with differing spatial resolution in a framework supplied by advanced three-dimensional (3D) physical models. To facilitate this goal, we have undertaken a major enhancement of our IDL-based simulation tools developed earlier for modeling microwave and X-ray emission. The enhanced software architecture allows the user to (1) import photospheric magnetic field maps and perform magnetic field extrapolations to generate 3D magnetic field models; (2) investigate the magnetic topology by interactively creating field lines and associated flux tubes; (3) populate the flux tubes with user-defined nonuniform thermal plasma and anisotropic, nonuniform, nonthermal electron distributions; (4) investigate the spatial and spectral properties of radio and X-ray emission calculated from the model; and (5) compare the model-derived images and spectra with observational data. The package integrates shared-object libraries containing fast gyrosynchrotron emission codes, IDL-based soft and hard X-ray codes, and potential and linear force-free field extrapolation routines. The package accepts user-defined radiation and magnetic field extrapolation plug-ins. We use this tool to analyze a relatively simple single-loop flare and use the model to constrain the magnetic 3D structure and spatial distribution of the fast electrons inside this loop. We iteratively compute multi-frequency microwave and multi-energy X-ray images from realistic magnetic flux tubes obtained from pre-flare extrapolations, and compare them with imaging data obtained by SDO, NoRH, and RHESSI. We use this event to illustrate the tool's use for the general interpretation of solar flares to address disparate problems in solar physics.

79 ASTRONOMY AND ASTROPHYSICS↗
NASA NTRS1994

High-frequency techniques for RCS prediction of plate geometries and a physical optics/equivalent currents model for the RCS of trihedral corner reflectors, parts 1 and 2

Formulations for scattering from the coated plate and the coated dihedral corner reflector are included. A coated plate model based upon the Uniform Theory of Diffraction (UTD) for impedance wedges was presented in the last report. In order to resolve inaccuracies and discontinuities in the predicted patterns using the UTD-based model, an improved model that uses more accurate diffraction coefficients is presented. A Physical Optics (PO) model for the coated dihedral corner reflector is presented as an intermediary step in developing a high-frequency model for this structure. The PO model is based upon the reflection coefficients for a metal-backed lossy material. Preliminary PO results for the dihedral corner reflector suggest that, in addition to being much faster computationally, this model may be more accurate than existing moment method (MM) models. An improved Physical Optics (PO)/Equivalent Currents model for modeling the Radar Cross Section (RCS) of both square and triangular, perfectly conducting, trihedral corner reflectors is presented. The new model uses the PO approximation at each reflection for the first- and second-order reflection terms. For the third-order reflection terms, a Geometrical Optics (GO) approximation is used for the first reflection; and PO approximations are used for the remaining reflections. The previously reported model used GO for all reflections except the terminating reflection. Using PO for most of the reflections results in a computationally slower model because many integrations must be performed numerically, but the advantage is that the predicted RCS using the new model is much more accurate. Comparisons between the two PO models, Finite-Difference Time-Domain (FDTD) and experimental data are presented for validation of the new model.

Balanis, Constantine A.↗
DOE OSTI2019

Verification of Reduced Order Modeling Based Uncertainty/Sensitivity Estimator (ROMUSE)

This article presents a number of verification case studies for a recently developed sensitivity/uncertainty code package. The code package, ROMUSE (Reduced Order Modeling based Uncertainty/Sensitivity Estimator) is an effort to provide an analysis tool to be used in conjunction with reactor core simulators, in particular the Virtual Environment for Reactor Applications (VERA) core simulator. ROMUSE has been written in C++ and is currently capable of performing various types of parameter perturbations and associated sensitivity analysis, uncertainty quantification, surrogate model construction and subspace analysis. The current version 2.0 has the capability to interface with the Design Analysis Kit for Optimization and Terascale Applications (DAKOTA) code, which gives ROMUSE access to the various algorithms implemented within DAKOTA, most importantly model calibration. The verification study is performed via two basic problems and two reactor physics models. The first problem is used to verify the ROMUSE single physics gradient-based range finding algorithm capability using an abstract quadratic model. The second problem is the Brusselator problem, which is a coupled problem representative of multi-physics problems. This problem is used to test the capability of constructing surrogates via ROMUSE-DAKOTA. Finally, light water reactor pin cell and sodium-cooled fast reactor fuel assembly problems are simulated via SCALE 6.1 to test ROMUSE capability for uncertainty quantification and sensitivity analysis purposes.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2016

Final Report on DTRA Basic Research Project #BRCALL08-Per3-C-2-0006 "High-Z Non-Equilibrium Physics and Bright X-ray Sources with New Laser Targets"

This project had two major goals. Final Goal: obtain spectrally resolved, absolutely calibrated x-ray emission data from uniquely uniform mm-scale near-critical-density high-Z plasmas not in local thermodynamic equilibrium (LTE) to benchmark modern detailed atomic physics models. Scientific significance: advance understanding of non-LTE atomic physics. Intermediate Goal: develop new nano-fabrication techniques to make suitable laser targets that form the required highly uniform non-LTE plasmas when illuminated by high-intensity laser light. Scientific significance: advance understanding of nano-science. The new knowledge will allow us to make x-ray sources that are bright at the photon energies of most interest for testing radiation hardening technologies, the spectral energy range where current x-ray sources are weak. All project goals were met.

74 ATOMIC AND MOLECULAR PHYSICS↗
DOE OSTI2015

Branch-and-Bound algorithm applied to uncertainty quantification of a Boiling Water Reactor Station Blackout

Evaluation of the impacts of uncertainty and sensitivity in modeling presents a significant set of challenges in particular to high fidelity modeling. Computational costs and validation of models creates a need for cost effective decision making with regards to experiment design. Experiments designed to validate computation models can be used to reduce uncertainty in the physical model. In some cases, large uncertainty in a particular aspect of the model may or may not have a large impact on the final results. For example, modeling of a relief valve may result in large uncertainty, however, the actual effects on final peak clad temperature in a reactor transient may be small and the large uncertainty with respect to valve modeling may be considered acceptable. Additionally, the ability to determine the adequacy of a model and the validation supporting it should be considered within a risk informed framework. Low fidelity modeling with large uncertainty may be considered adequate if the uncertainty is considered acceptable with respect to risk. In other words, models that are used to evaluate the probability of failure should be evaluated more rigorously with the intent of increasing safety margin. Probabilistic risk assessment (PRA) techniques have traditionally been used to identify accident conditions and transients. Traditional classical event tree methods utilize analysts’ knowledge and experience to identify the important timing of events in coordination with thermal-hydraulic modeling. These methods lack the capability to evaluate complex dynamic systems. In these systems, time and energy scales associated with transient events may vary as a function of transition times and energies to arrive at a different physical state. Dynamic PRA (DPRA) methods provide a more rigorous analysis of complex dynamic systems. Unfortunately DPRA methods introduce issues associated with combinatorial explosion of states. This study presents a methodology to address combinatorial explosion using a Branch-and-Bound algorithm applied to Dynamic Event Trees (DET), which utilize LENDIT (L – Length, E – Energy, N – Number, D – Distribution, I – Information, and T – Time) as well as a set theory to describe system, state, resource, and response (S2R2) sets to create bounding functions for the DET. The optimization of the DET in identifying high probability failure branches is extended to create a Phenomenological Identification and Ranking Table (PIRT) methodology to evaluate modeling parameters important to safety of those failure branches that have a high probability of failure. The PIRT can then be used as a tool to identify and evaluate the need for experimental validation of models that have the potential to reduce risk. Finally, in order to demonstrate this methodology, a Boiling Water Reactor (BWR) Station Blackout (SBO) case study is presented.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2018

Probing 6D operators at future e – e + colliders

We explore the sensitivities at future e – e + colliders to probe a set of six-dimensional operators which can modify the SM predictions on Higgs physics and electroweak precision measurements. We consider the case in which the operators are turned on simultaneously. Such an analysis yields a “conservative” interpretation on the collider sensitivities, complementary to the “optimistic” scenario where the operators are individually probed. After a detail analysis at CEPC in both “conservative” and “optimistic” scenarios, we also considered the sensitivities for FCC-ee and ILC. As an illustration of the potential of constraining new physics models, we applied sensitivity analysis to two benchmarks: holographic composite Higgs model and littlest Higgs model.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2024

Heterogeneous Cluster Energetics and Nonlinear Thermodynamic Response in Supercritical Fluids

Microstructural heterogeneities arising from molecular clusters directly affect the nonlinear thermodynamic properties of supercritical fluids. We present a physical model to elucidate the relation between energy exchange and heterogeneous cluster dynamics during the transition from liquidlike to gaslike conditions. By analyzing molecular-dynamics data and employing physical principles, the model considers contributions from three key processes, namely, changing cluster density, cluster separation, and transfer of molecules between clusters. We show that the proposed model is consistent with the energetics at subcritical conditions and can be used to explain the nonlinear behavior of thermodynamic response functions, including the peak in the isobaric heat capacity.

42 ENGINEERING↗
NASA NTRS1979

Simplified model of a volumetric direct nuclear pumped He-3-Ar laser

A physical model for the volumetric nuclear pumped He-3-Ar laser is described and the source terms arising from the He-3(n, p)H-3 reaction as well as the rate equations are given. Steady state solutions are derived for the densities of the species vs the fraction of argon. The dominant pumping mechanism is found to be collisional radiative recombination of the argon atomic ions and subsequent cascading into the upper laser level. The reactions following recombination are described and an expression is derived for the difference in densities of the argon 3d and 4p levels. Comparison with experiments shows good agreement.

Harries, W. L.↗