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At least 703 records · Page 39
All sourcesNASA NTRSDOE OSTI
NASA NTRS1998

Evaluation of the 29-km Eta Model: Objective Verification at Three Selected Stations - Part 1

This paper describes an objective verification of the National Centers for Environmental Prediction (NCEP) 29-km eta model from May 1996 through January 1998. The evaluation was designed to assess the model's surface and upper-air point forecast accuracy at three selected locations during separate warm (May - August) and cool (October - January) season periods. In order to enhance sample sizes available for statistical calculations, the objective verification includes two consecutive warm and cool season periods. Systematic model deficiencies comprise the larger portion of the total error in most of the surface forecast variables that were evaluated. The error characteristics for both surface and upper-air forecasts vary widely by parameter, season, and station location. At upper levels, a few characteristic biases are identified. Overall however, the upper-level errors are more nonsystematic in nature and could be explained partly by observational measurement uncertainty. With a few exceptions, the upper-air results also indicate that 24-h model error growth is not statistically significant. In February and August 1997, NCEP implemented upgrades to the eta model's physical parameterizations that were designed to change some of the model's error characteristics near the surface. The results shown in this paper indicate that these upgrades led to identifiable and statistically significant changes in forecast accuracy for selected surface parameters. While some of the changes were expected, others were not consistent with the intent of the model updates and further emphasize the need for ongoing sensitivity studies and localized statistical verification efforts. Objective verification of point forecasts is a stringent measure of model performance, but when used alone, is not enough to quantify the overall value that model guidance may add to the forecast process. Therefore, results from a subjective verification of the meso-eta model over the Florida peninsula are discussed in the companion paper by Manobianco and Nutter. Overall verification results presented here and in part two should establish a reasonable benchmark from which model users and developers may pursue the ongoing eta model verification strategies in the future.

Nutter, Paul A.↗
DOE OSTI2024

Predicting turbulent wake flow of marine hydrokinetic turbine arrays in large-scale waterways via physics-enhanced convolutional neural networks

We present a physics-enhanced convolutional neural network (PECNN) algorithm for reconstructing the mean flow and turbulence statistics in the wake of marine hydrokinetic (MHK) turbine arrays installed in large-scale meandering rivers. The algorithm embeds the mass and momentum conservation equations into the loss function of the PECNN algorithm to improve the physical realism of the reconstructed flow fields. The PECNN is trained using large eddy simulation (LES) results of the wake flow of a single row of turbines in a virtual meandering river. Subsequently, the trained PECNN is applied to predict the wake flow of MHK turbines with arrangements and positionings different than those considered during the training process. The PECNN predictions are validated using the results of separately performed LES. The results show that the PECNN algorithm can accurately predict the wake flow of MHK turbine farms at a small fraction of the cost of LES. The PECNN can improve the accuracy by around 1% and reduce the physical constraint indices by around 50% compared to the CNN without physical constraints. This work underscores the potential of PECNN to develop reduced-order models for control co-design and optimization of MHK turbine arrays in natural riverine environments.

Mechanics↗
NASA NTRS1993

Generic results of the space physics community survey

This report summarizes the results of a survey of the members of the space physics research community conducted in 1990-1991 to ascertain demographic information on the respondents and information on their views on a number of facets of their space physics research. The survey was conducted by questionnaire and the information received was compiled in a database and analyzed statistically. The statistical results are presented for the respondent population as a whole and by four different respondent cross sections: individual disciplines of space physics, type of employers, age groups, and research techniques employed. Data from a brief corresponding survey of the graduate students of respondents are also included.

Sharma, Rikhi R.↗
DOE OSTI2023

Surface coverage dynamics for reversible dissociative adsorption on finite linear lattices

Dissociative adsorption onto a surface introduces dynamic correlations between neighboring sites not found in non-dissociative absorption. We study surface coverage dynamics where reversible dissociative adsorption of dimers occurs on a finite linear lattice. We derive analytic expressions for the equilibrium surface coverage as a function of the number of reactive sites, N, and the ratio of the adsorption and desorption rates. Using these results, we characterize the finite size effect on the equilibrium surface coverage. For comparable N’s, the finite size effect is significantly larger when N is even than when N is odd. Moreover, as N increases, the size effect decays more slowly in the even case than in the odd case. The finite-size effect becomes significant when adsorption and desorption rates are considerably different. These finite-size effects are related to the number of accessible configurations in a finite system where the odd-even dependence arises from the limited number of accessible configurations in the even case. We confirm our analytical results with kinetic Monte Carlo simulations. We also analyze the surface-diffusion case where adsorbed atoms can hop into neighboring sites. As expected, the odd-even dependence disappears because more configurations are accessible in the even case due to surface diffusion.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2026

Review of Particle Physics

The Review summarizes much of particle physics and cosmology. Using data from previous editions, plus 3,200 new measurements from 903 papers, we list, evaluate, and average measured properties of gauge bosons and the recently discovered Higgs boson, leptons, quarks, mesons, and baryons. We summarize searches for hypothetical particles such as supersymmetric particles, heavy bosons, axions, dark photons, etc. Particle properties and search limits are listed in Summary Tables. We give numerous tables, figures, formulae, and reviews of topics such as Higgs Boson Physics, Supersymmetry, Grand Unified Theories, Neutrino Mixing, Dark Energy, Dark Matter, Cosmology, Particle Detectors, Colliders, Probability and Statistics. Most of the 118 reviews are updated, including many that are heavily revised.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2020

Understanding Differences in California Climate Projections Produced by Dynamical and Statistical Downscaling

Abstract We compare historical and end‐of‐century temperature and precipitation patterns over California from one dynamically downscaled simulation using the Weather Research and Forecast (WRF) model and two simulations statistically downscaled using Localized Constructed Analogs (LOCA). We uniquely separate causes of differences between dynamically and statistically based future climate projections into differences in historical climate (gridded observations versus regional climate model output) and differences in how these downscaling techniques explicitly handle future climate changes (numerical modeling versus analogs). In these methods, solutions between different downscaling techniques differ more in the future compared to the historical period. Changes projected by LOCA are insensitive to the choice of driving data. Only through dynamical downscaling can we simulate physically consistent regional springtime warming patterns across the Sierra Nevada, while the statistical simulations inherit an unphysical signal from their parent Global Climate Model (GCM) or gridded data. The results of our study clarify why these different techniques produce different outcomes and may also provide guidance on which downscaled products to use for certain impact analyses in California and perhaps other Mediterranean regimes.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

DCTRGAN: improving the precision of generative models with reweighting

Significant advances in deep learning have led to more widely used and precise neural network-based generative models such as Generative Adversarial Networks (Gans). We introduce a post-hoc correction to deep generative models to further improve their fidelity, based on the Deep neural networks using the Classification for Tuning and Reweighting (Dctr) protocol. The correction takes the form of a reweighting function that can be applied to generated examples when making predictions from the simulation. We illustrate this approach using Gans trained on standard multimodal probability densities as well as calorimeter simulations from high energy physics. We show that the weighted Gan examples significantly improve the accuracy of the generated samples without a large loss in statistical power. This approach could be applied to any generative model and is a promising refinement method for high energy physics applications and beyond.

47 OTHER INSTRUMENTATION↗
DOE OSTI2025

DeepBench: A simulation package for physical benchmarking data

We introduce **DeepBench**, a python library that generates simple simulated image data from first principles, such as basic geometric shapes and astronomical objects. These data are highly valuable for developing (calibration, testing, and benchmarking) statistical and machine learning models because they make it possible to connect the final data product to physically interpretable inputs. This software includes tools to curate and store the datasets to maximize reproducibility.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
NASA NTRS2006

The Strings of Eta Carina: The HST/STIS Spectra and [Ca II]

Long linear, filamentary ejecta, are found to move at very high velocity external to the Homunculus, the circumstellar hourglass-shaped ejecta surrounding Eta Carinae. The origin of the strings is a puzzle. As an example, the Weigelt Blobs have N at 10X solar and C, O at 0.01X solar abundance, along with He/H significantly enhanced. This abundance pattern is evidence for extreme CNO-processing. Similarly, the Strontium Filament has Ti/Ni at 100X solar, presumably due to the lack of oxygen to form Ti-oxide precipitates onto dust grains. We have obtained 2-D spectra with the HST/STIS of the Strontium Filament and a portion of a string. These deep spectral exposures, at moderate dispersion, span much of the near red spectral region from 5000 to 9000A. We have identified twelve emission lines in these spectra with proper velocities and spatial structure of this string and obtained line ratios for [Ca II] (7293/7325A) and [Fe Ill (7157/8619A) which are useful for determining physical conditions in this nebulosity. In an attempt to use the [Ca II] ratio to determine the physical parameters, and ultimately the abundances in the strings, we have constructed a statistical equilibrium model for Ca II , including radiative and collisional rates. These results incorporate our newly calculated atomic data for levels n = 3,4,5 and 6 configurations of Ca II. The aim is to compute the [Ca II] line ratios and use them as a diagnostic of the physical parameters. Using the [Fe II] ratio we find that for Te=10,000 K, the electron density is Ne approx.10(exp 6)/cu cm. We plan to use the [Ca II] ratio to confirm this result. Then, we will extend the use of this multilevel model Ca II atom to study the physical conditions of the Strontium filament where eight lines of Ca II, both allowed and forbidden, had been identified. With the physical conditions determined, we will be able to derive reliable estimates for the gas phase abundances in the strings.

Melendez, M. B.↗
DOE OSTI2021

Multiphenomenology explosion monitoring (MultiPEM): a general framework for data interpretation and yield estimation

SUMMARY An underground nuclear explosion (UNE) couples mechanical energy into crustal rock, which propagates as seismic and acoustic waves. These different physical phenomena transport, by different pathways, to standoff detectors at varying distances. The transport pathways attenuate the original signal but in different ways. Enabled by correct statistical weighting, signal attenuation models can be used to combine these disparate sensor data to estimate the yield of an UNE. Contemporaneous statistical models, used in yield estimation, can be improved with an advanced partition of error for these physical signal propagation models. We present an advanced multivariate approach to error modelling of multiphenomenology physical signatures. In addition to measurement error, our error model represents physical model biases as random with a physics-based covariance structure. To illustrate this proposed framework, we demonstrate the estimation of explosion yield using openly available seismic and acoustic data from chemical single-point explosions.

Williams, Brian J.↗
NASA NTRS1993

Mapping of the Ronda peridotite massif (Spain) from AVIRIS spectro-imaging survey: A first attempt

In both AVIRIS and ISM data, through the use of mixing models, geological boundaries of the Ronda massif are identified with respect to the surrounding rocks. We can also yield first-order vegetation maps. ISM and AVIRIS instruments give consistent results. On the basis of endmember fraction images, it is then possible to discard areas highly vegetated or not belonging to the peridotite massif. Within the remaining part of the mosaic, spectro-mixing analysis reveals spectral variations in the peridotite massif between the well-exposed areas. Spatially organized units are depicted, related to differences in the relative depth of the absorption band at 1 micron, and it may be due to a different pyroxene content. At this stage, it is worth noting that, although mineralogical variations observed in the rocks are at a sub-pixel scale for the airborne analysis, we see an emerging spatial pattern in the distribution of spectral variations across the massif which might be prevailingly related to mineralogy. Although it is known from fieldwork that the Ronda peridotite massif exhibits mineralogical variations at local scale in the content of pyroxene, and at regional scale in different mineral facies, ranging from garnet-, to spinel- to plagioclase-lherzolites, no attempt has been done yet to produce a synoptic map relating the two scales of analysis. The present work is a first attempt to reach this objective, though a lot more work is still required. In particular, for the purpose of mineralogical interpretation, it is critical to relate the airborne observation to field work and laboratory spectra of Ronda rocks already obtained, with the use of image endmembers and associated reference endmembers. Also, the pretty rough linear mixing model used here is taken as a 'black-box' process which does not necessarily apply correctly to the physical situation at the sub-pixel level. One may think of using the ground-truth observations bearing on the sub-pixel statistical characteristics (texture, structural pattern, surface distribution and vegetation contribution (grass,..)) to produce a more advanced mixing model, physically appropriate to the geologic and environmental contexts.

Pinet, P. C.↗
DOE OSTI2021

Stochastic thermodynamic cycles of a mesoscopic thermoelectric engine

Here, we analyze a steady-state thermoelectric engine, whose working substance consists of two capacitively coupled quantum dots. One dot is tunnel-coupled to a hot reservoir serving as a heat source, the other one to two electrically biased reservoirs at a colder temperature, such that work is extracted under the form of a steady-state current against the bias. In single realizations of the dynamics of this steady-state engine autonomous, four-stroke cycles can be identified. The cycles are purely stochastic, in contrast to mechanical autonomous engines which exhibit self-oscillations. In particular, these cycles fluctuate in direction and duration and occur in competition with other spurious cycles. Using a stochastic thermodynamic approach, we quantify the cycle fluctuations and relate them to the entropy produced during individual cycles. We identify the cycle mainly responsible for the engine performance and quantify its statistics with tools from graph theory. We show that such stochastic cycles are made possible because the work extraction mechanism is itself stochastic instead of the periodic time dependence in the working-substance Hamiltonian which can be found in conventional mechanical engines. Our investigation brings new perspectives about the connection between cyclic and steady-state engines.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
NASA NTRS1999

Turbulent Diffusivities for Momentum, Heat, Salt and Passive Scalars

A program began ten years ago to build a turbulence model to describe high Reynolds numbers flows. Specifically, the aim was to devise a model that would satisfy two basic conditions: reproduce available turbulence data (laboratory, numerical simulations, etc.) concerning shear driven flows, buoyancy driven flows, 2D turbulence, freely decaying turbulence etc., and yet be manageable so as to be used, for example, in GCM'S. The model was presented in a series of papers that have appeared in Physics of Fluids since 1996. A total of about 80 turbulence statistics were reproduced. The model has no adjustable parameters. The next step was to apply the model to construct the vertical diffusities K for moment K(sub m), temperature K(sub h), salt K(sub s), and passive scalars K(sub c). First, we took K(sub c) = K(sub h) and tested the model using the GFDL ocean model. The results for the profiles of T and S vs. depth are indistinguishable from those derided using the latest model, the KPP model by the NCAR group. Presently, we are running the same GFDL code relaxing the assumptive K(sub c) = K(sub h). Indeed, the turbulence model yelds a salt diffusivity that depends on R(sub i) and R(sub rho) = ((beta)(delta)S/(alpha)(delta)T/(delta)z) in such a way that K(sub s) may be quite different from K(sub h). Salt fingers and double diffusivity laboratory data are reproduced. Results from the ocean model will be available shortly. Finally, we are trying to derive the horizontal diffusivities with the goal of providing a physically acceptable representation of mesoscale eddies. The recently suggested GMW parameterization has improved several O-GCM results and the goal here is to try to derive/justify it from a turbulence model and/or propose improvements/modifications. Theoretical work is in progress.

Canuto, V. M.↗
NASA NTRS1999

Turbulent Diffusivities for Momentum, Heat, Salt and Passive Scalars

A program began ten years ago to build a turbulence model to describe high Reynolds numbers flows. Specifically, the aim was to devise a model that would satisfy two basic conditions: reproduce available turbulence data (laboratory, numerical simulations, etc.) concerning shear driven flows, buoyancy driven flows, 2D turbulence, freely decaying turbulence etc., and yet be manageable so as to be used, for example, in General Circulation Models (GCM'S). The model was presented in a series of papers that have appeared in Physics of Fluids since 1996. A total of about 80 turbulence statistics were reproduced. The model has no adjustable parameters. The next step was to apply the model to construct the vertical diffusities K for moment K(sub m), temperature K(sub h), salt K(sub s). and passive scalars K(sub c). First, we took K(sub s) = K(sub h) and tested the model using the GFDL ocean model. The results for the profiles of T and S vs. depth are indistinguishable from those derived using the latest model, the KPP model by the NCAR group. Presently, we are running the same Geophysical Fluid Dynamics Laboratory (GFDL) code relaxing the assumptive K(sub s) = K(sub h). Indeed, the turbulence model yields a salt diffusivity that depends on Ri and R rho (= Beta delta S/delta z/alpha delta T/delta z) in such a way that K(sub s) may be quite different from K(sub h). Salt fingers and double diffusivity laboratory data are reproduced. Results from the ocean model will be available shortly. Finally, we are trying to derive the horizontal diffusivities with the goal of providing a physically acceptable representation of mesoscale eddies. The recently suggested GMW parameterization has improved several O-GCM results and the goal here is to try to derive/justify it from a turbulence model and/or propose improvements/modifications. Theoretical work is in progress.

Canuto, V. M.↗
NASA NTRS1999

Turbulent Diffusivities for Momentum, Heat, Salt and Passive Scalars

A program began ten years ago to build a turbulence model to describe high Reynolds numbers flows. Specifically, the aim was to devise a model that would satisfy two basic conditions: reproduce available turbulence data (laboratory, numerical simulations, etc.) concerning shear driven flows, buoyancy driven flows, 2D turbulence, freely decaying turbulence etc., and yet be manageable so as to be used, for example, in GCM'S. The model was presented in a series of papers that have appeared in Physics of FLuids since 1996. A total of about 80 turbulence statistics were reproduced. The model has no adjustable parameters. The next step was to apply the model to construct the vertical diffusivities K for moment K(sub m), temperature K(sub h), salt K(sub g) and passive scalars K(sub c). First, we took K(sub g) = K(sub h) and tested the model using the Geophysical Fluid Dynamics Laboratory (GFDL) ocean model. The results for the profiles of T and S vs. depth are indistinguishable from those derided using the latest model, the KPP model by the NCAR group. Presently, we are running the same GFDL code relaxing the assumptive K(sub g) = K(sub h). Indeed, the turbulence model yields a salt diffusivity that depends on Ri and R Rho (= Beta Sigma S/Sigma z/Alpha Sigma T/Sigma z) in such a way that K(sub g) may be quite different from K(sub h). Salt fingers and double diffusivity laboratory data are reproduced. Results from the ocean model will be available shortly. Finally, we are trying to derive the horizontal diffusivities with the goal of providing a physically acceptable representation of mesoscale eddies. The recently suggested GMW parameterization has improved several O-GCM results and the goal here is to try to derive/justify it from a turbulence model and/or propose improvements/modifications. Theoretical work is in progress.

Canuto, Vittorio↗
DOE OSTI2022

Sea Ice Rheology Experiment (SIREx): 1. Scaling and Statistical Properties of Sea-Ice Deformation Fields

As the sea-ice modeling community is shifting to advanced numerical frameworks, developing new sea-ice rheologies, and increasing model spatial resolution, ubiquitous deformation features in the Arctic sea ice are now being resolved by sea-ice models. Initiated at the Forum for Arctic Modeling and Observational Synthesis, the Sea Ice Rheology Experiment (SIREx) aims at evaluating state-of-the-art sea-ice models using existing and new metrics to understand how the simulated deformation fields are affected by different representations of sea-ice physics (rheology) and by model configuration. Part 1 of the SIREx analysis is concerned with evaluation of the statistical distribution and scaling properties of sea-ice deformation fields from 35 different simulations against those from the RADARSAT Geophysical Processor System (RGPS). For the first time, the viscous-plastic (and the elastic-viscous-plastic variant), elastic-anisotropic-plastic, and Maxwell-elasto-brittle rheologies are compared in a single study. We find that both plastic and brittle sea-ice rheologies have the potential to reproduce the observed RGPS deformation statistics, including multi-fractality. Model configuration (e.g., numerical convergence, atmospheric representation, spatial resolution) and physical parameterizations (e.g., ice strength parameters and ice thickness distribution) both have effects as important as the choice of sea-ice rheology on the deformation statistics. It is therefore not straightforward to attribute model performance to a specific rheological framework using current deformation metrics. In light of these results, we further evaluate the statistical properties of simulated Linear Kinematic Features in a SIREx Part 2 companion paper.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Simulating Z 2 lattice gauge theory on a quantum computer

The utility of quantum computers for simulating lattice gauge theories is currently limited by the noisiness of the physical hardware. Various quantum error mitigation strategies exist to reduce the statistical and systematic uncertainties in quantum simulations via improved algorithms and analysis strategies. We perform quantum simulations of Z 2 gauge theory with matter to study the efficacy and interplay of different error mitigation methods: readout error mitigation, randomized compiling, rescaling, and dynamical decoupling. We compute Minkowski correlation functions in this confining gauge theory and extract the mass of the lightest spin-1 state from fits to their time dependence. Quantum error mitigation extends the range of times over which our correlation function calculations are accurate by a factor of 6 and is therefore essential for obtaining reliable masses.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
NASA NTRS2003

The Statistical Mechanics of Ideal MHD Turbulence

Turbulence is a universal, nonlinear phenomenon found in all energetic fluid and plasma motion. In particular. understanding magneto hydrodynamic (MHD) turbulence and incorporating its effects in the computation and prediction of the flow of ionized gases in space, for example, are great challenges that must be met if such computations and predictions are to be meaningful. Although a general solution to the "problem of turbulence" does not exist in closed form, numerical integrations allow us to explore the phase space of solutions for both ideal and dissipative flows. For homogeneous, incompressible turbulence, Fourier methods are appropriate, and phase space is defined by the Fourier coefficients of the physical fields. In the case of ideal MHD flows, a fairly robust statistical mechanics has been developed, in which the symmetry and ergodic properties of phase space is understood. A discussion of these properties will illuminate our principal discovery: Coherent structure and randomness co-exist in ideal MHD turbulence. For dissipative flows, as opposed to ideal flows, progress beyond the dimensional analysis of Kolmogorov has been difficult. Here, some possible future directions that draw on the ideal results will also be discussed. Our conclusion will be that while ideal turbulence is now well understood, real turbulence still presents great challenges.

Shebalin, John V.↗