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At least 1,657 records · Page 92
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

UQpy: A general purpose Python package and development environment for uncertainty quantification

In this paper, we present the UQpy software toolbox, an open-source Python package for general uncertainty quantification (UQ) in mathematical and physical systems. The software serves as both a user-ready toolbox that includes many of the latest methods for UQ in computational modeling and a convenient development environment for Python programmers advancing the field of UQ. The paper presents an introduction to the software's architecture and existing capabilities, divided in the code in a set of modules centered around different UQ tasks such as sampling methods, generation of random processes and random fields, probabilistic inverse modeling, reliability analysis, surrogate modeling, and active learning. The paper also highlights the importance of the RunModel module, which is used to drive simulations in the uncertainty analyses performed in UQpy. This module conveniently allows the user to define computational models directly in Python, or to run simulations from a third-party software in serial or in parallel. To illustrate the various capabilities, two examples are tracked throughout the paper and analyzed repeatedly for various UQ tasks. The first is a Python model solving a nonlinear structural dynamics problem, used to illustrate UQpy's capabilities in sampling and forward propagation of high dimensional random vectors (stochastic processes), and probabilistic inference. The second model is a third-party Abaqus finite element model solving the thermomechanical response of a beam structure. This example is used to illustrate UQpy's capabilities in variance reduction sampling techniques, reliability analysis, surrogate modeling and active learning techniques.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2018

Real homotopy theory and supersymmetric quantum mechanics

In the context of observing string backgrounds, much work has been devoted to the question of how similar a general quantum field theory (specifically, a two-dimensional superconformal field theory) is to a sigma model. Put differently, one would like to know how well or poorly one can understand the physics of string backgrounds in terms of concepts of classical geometry. Much attention has also been given of late to the question of how geometry can be encoded in a microscopic physical description that makes no explicit reference to space and time. We revisit the first question and review both well-known and less well-known results about geometry and sigma models from the perspective of dimensional reduction to supersymmetric quantum mechanics. The consequences of arising as the dimensional reduction of a d -dimensional theory for the resulting quantum mechanics are explored. In this context, we reinterpret the minimal models of rational (more precisely, complex) homotopy theory as certain supersymmetric Fock spaces, with unusual actions of the supercharges. The data of the Massey products appear naturally as supersymmetric vacuum states that are entangled between different degrees of freedom. This connection between entanglement and geometry is, as far as we know, not well known to physicists. In addition, we take note of an intriguing numerical coincidence in the context of string compactification on hyper-Kähler eight-manifolds.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2014

Modeling In-stream Tidal Energy Extraction and Its Potential Environmental Impacts

In recent years, there has been growing interest in harnessing in-stream tidal energy in response to concerns of increasing energy demand and to mitigate climate change impacts. While many studies have been conducted to assess and map tidal energy resources, efforts for quantifying the associated potential environmental impacts have been limited. This paper presents the development of a tidal turbine module within a three-dimensional unstructured-grid coastal ocean model and its application for assessing the potential environmental impacts associated with tidal energy extraction. The model is used to investigate in-stream tidal energy extraction and associated impacts on estuarine hydrodynamic and biological processes in a tidally dominant estuary. A series of numerical experiments with varying numbers and configurations of turbines installed in an idealized estuary were carried out to assess the changes in the hydrodynamics and biological processes due to tidal energy extraction. Model results indicated that a large number of turbines are required to extract the maximum tidal energy and cause significant reduction of the volume flux. Preliminary model results also indicate that extraction of tidal energy increases vertical mixing and decreases flushing rate in a stratified estuary. The tidal turbine model was applied to simulate tidal energy extraction in Puget Sound, a large fjord-like estuary in the Pacific Northwest coast.

Yang, Zhaoqing↗
NASA NTRS1973

High tip speed fan inlet noise reduction using treated inlet splitters and accelerating inlets (quiet engine program fan C scale model)

A series of inlet suppression tests were run on a supersonic tip speed fan which employed an acoustically treated cowl wall, treated splitters and elevated average throat Mach numbers in various combinations. Results show appreciable fan noise reductions at high fan speeds; 15-18 PNdB. On the basis of inlet total pressure recovery loss per PNdb of noise reduction, an inlet with no splitters produced the most efficient design. However, greater reduction in noise was achieved with one splitter in the inlet. It was also noted that moderate increases in inlet Mach number increased noise in the acoustically treated inlets and that Mach numbers in excess of 0.65 were required before net noise reduction was realized.

Kazin, S. B.↗
DOE OSTI2019

Simulating International Drought Experiment field observations using the Community Land Model

Anthropogenic climate change will alter regional hydrologic cycles around the world, in part by increasing the frequency or duration of droughts in some areas. The International Drought Experiment (IDE) is investigating the impact of severe drought on terrestrial vegetation by experimentally reducing precipitation at dozens of sites. Here, in this study, we implement the IDE precipitation reduction protocol using the Community Land Model (CLM). Though many model results suggest that carbon fertilization will outpace drought-caused reduction of terrestrial carbon uptake, uncertainty is large. We therefore configure CLM to consider carbon cycling impacts of reduced moisture availability without intertwining the effects of carbon fertilization or phenological changes. California hosts a number of IDE sites and a wide range of topography, climate, and biomes. CMIP5 predictions suggest 21st century California will experience droughts in excess of the 1000-year climatological record for both frequency and magnitude. CLM suggests that some regions, including much of Northern California, may experience a steeper decline in gross primary productivity (GPP) during 21st century severe droughts than during 20th century severe droughts. Vegetation in Northern California experiences virtually all of this GPP reduction during the dry season, with little wet season GPP reduction even during severe drought. Southern California vegetation experiences soil moisture GPP limitation at virtually all times, increasing substantially with drought severity. Southern California should experience a more pronounced shift in GPP seasonality and decline in magnitude relative to Northern California during droughts. Some parts of every vegetated continent see changes to drought response and seasonality similar to Southern California. Our CLM results provide drought impacts that forthcoming IDE field observations may test, can help to spatially upscale site-based IDE observations of drought impact, and provide CLM's prediction of reduced precipitation impacts per unit leaf area index.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

An Overview of Wind Energy Production Prediction Bias, Losses, and Uncertainties

The financing of a wind farm directly relates to the preconstruction energy yield assessments which estimate the annual energy production for the farm. The accuracy and the precision of the preconstruction energy estimates can dictate the profitability of the wind project. Historically, the wind industry tended to overpredict the annual energy production of wind farms. Experts have been dedicated to eliminating such prediction errors in the past decade, and recently the industry is recording near-zero average energy prediction bias. Herein, we present an overview of the energy yield assessment errors across the global wind energy industry. We identify a long-term trend of reduction in the overprediction bias, whereas the uncertainty associated with the prediction error is prominent. We also summarize the recent advancements of the wind resource assessment process that justify the bias reduction, including the improvements in modeling and measurement techniques. Additionally, because the energy losses and uncertainties substantially influence the prediction error, we document and examine the estimated and observed loss and uncertainty values from the literature, according to the proposed framework in the International Electrotechnical Commission 61400-15 wind resource assessment standard. From our findings, we highlight the opportunities for the industry to move forward, such as the validation and reduction of prediction uncertainty, and the prevention of energy losses caused by wake effect and environmental events. Overall, this study provides a summary on how the wind energy industry has been quantifying and reducing prediction errors, energy losses, and production uncertainties. Finally, for this work to be as reproducible as possible, we include all of the data used in the analysis in appendices to the manuscript.

literature review↗
NASA NTRS1981

Large ozone perturbations caused by the 1908 Tunguska meteor fall - Were there related weather effects

The magnitude of the ozone depletion due to the 1908 Tunguska meteor fall is estimated and observational evidence of such a depletion is presented. Calculated stratospheric ozone and NO(x) perturbations caused by the meteor are shown, with the hemispherically averaged model giving total stratospheric ozone reductions as large as 45 percent in the first year, with significant reductions persisting for at least three more years. Ozone depletion above 10 km altitude is found to be about 85 percent for several months, and higher yet at 20, 30, and 40 km. Data from the early 1900s to calculate the variability of the solar constant is used to calculate the ozone column concentration for 1909-11. The results are in close agreement with the model prediction. Weather records of the early 1900s show a cooling trend in the Northern Hemisphere for almost a decade after Tunguska.

Turco, R. P.↗
DOE OSTI2024

Simplification of the Grid Model and its Impact on the Analysis of Electrical Power Systems

Here, this paper analyzes the impact of the use of Kron reduction on the state variables of a three-phase electrical system, even when it does not meet the necessary conditions for its application. Reduction is applied to a power line model to eliminate the equation corresponding to the neutral conductor of the line. The ATP program is used to model and simulate the behavior of an electrical system considering different degrees of disequilibrium as a reference for the comparison of results. The results show that under certain conditions of disequilibrium the Kron reduction can lead to significant errors in the state variables of the system.

Electric Power Systems↗
DOE OSTI2016

Further Investigation of Employing Binomial Small-Sample Estimator in M-LROM

Reduced Order Modeling (ROM) is essential to enable the identification of the so-called active parameter subspace for high-fidelity models that are employed in computationally intensive analyses such as uncertainty characterization and data assimilation. Given the complexity of models for real-world application, brute force methods to identify the active subspace may not be computationally efficient to realize the value of reduction, since in realistic problems, the full scale model must be executed few hundred times, which may be computationally taxing. Earlier work has introduced a new approach, which represents a further development of our previous work on ROM, referred to as multi-level ROM (M-LROM). In M-LROM, approximate models are employed to identify the active subspace instead of the full scale model. In this summary, we present our recent results on M-LROM, specifically in regard to the construction of reliable error metrics that can bound the errors resulting from the reduction. The idea is to employ a lower fidelity model, i.e., an approximation of the full scale or high fidelity model, to build the active subspace, and via the proposed error bound, the quality of the active subspace can be determined by calculating an upper bound on the errors resulting from the reduction. For this approach to be practical, the error bound must be realistic, implying that it should be close to the actual errors expected, and not much higher. Therefore, an important goal of this summary is to compare different error bounds in terms of the relation between their estimated bounds to the actual errors. In particular, we compare the proposed error bound which numerically construct an estimator using binomial distribution to the widely used small-sample norm estimators. Unlike most probabilistic error estimation methods, the proposed bound employs a binomial distribution to construct the estimator whereas in other conventional methods, the distribution employed is typically the standard Gaussian, normalized over a unit hypersphere as initially proposed by the seminal paper of J. Dixon on random matrix theory. Previous publications provided evidence that the binomial distribution calculates more realistic bounds as compared to the Gaussian distribution, which tends to be conservative, implying that the bound is much bigger than the actual errors, which diminishes the value of the reduction, as now must increase the size of the active subspace to reach the desired upper bound on the reduction errors. This work has provided a rigorous approach by which error bounds on the reduction errors can be established without having to execute the high fidelity model during the construction of the active subspace. The high fidelity model is only need to test the error bound using small number of executions. This methodology paves the way for a more efficient application of ROM to complex engineering models, where standard ROM techniques may be too taxing to optimally realize their value in practical situations. (authors)

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
NASA NTRS1994

Evaluation of SSME test data reduction methods

Accurate prediction of hardware and flow characteristics within the Space Shuttle Main Engine (SSME) during transient and main-stage operation requires a significant integration of ground test data, flight experience, and computational models. The process of integrating SSME test measurements with physical model predictions is commonly referred to as data reduction. Uncertainties within both test measurements and simplified models of the SSME flow environment compound the data integration problem. The first objective of this effort was to establish an acceptability criterion for data reduction solutions. The second objective of this effort was to investigate the data reduction potential of the ROCETS (Rocket Engine Transient Simulation) simulation platform. A simplified ROCETS model of the SSME was obtained from the MSFC Performance Analysis Branch . This model was examined and tested for physical consistency. Two modules were constructed and added to the ROCETS library to independently check the mass and energy balances of selected engine subsystems including the low pressure fuel turbopump, the high pressure fuel turbopump, the low pressure oxidizer turbopump, the high pressure oxidizer turbopump, the fuel preburner, the oxidizer preburner, the main combustion chamber coolant circuit, and the nozzle coolant circuit. A sensitivity study was then conducted to determine the individual influences of forty-two hardware characteristics on fourteen high pressure region prediction variables as returned by the SSME ROCETS model.

Santi, L. Michael↗
DOE OSTI2015

Understanding the contribution of non-carbon dioxide gases in deep mitigation scenarios

The combined 2010 emissions of methane (CH4), nitrous oxide (N2O) and the fluorinated gasses (F-gas) account for about 20-30% of total emissions and about 30% of radiative forcing. At the moment, most studies looking at reaching ambitious climate targets project the emission of carbon dioxide (CO2) to be reduced to zero (or less) by the end of the century. As for non-CO2 gases, the mitigation potential seem to be more constrained, we find that by the end of the century in the current deep mitigation scenarios non-CO2 emissions could form the lion’s share of remaining greenhouse gas emissions. In order to support effective climate policy strategies, in this paper we provide a more in-depth look at the role of non-CO2¬ emission sources (CH4, N2O and F-gases) in achieving deep mitigation targets (radiative forcing target of 2.8 W/m2 in 2100). Specifically, we look at the sectorial mitigation potential and the remaining non-CO2 emissions. By including a set of different models, we provide some insights into the associated uncertainty. Most of the remaining methane emissions in 2100 in the climate mitigation scenario come from the livestock sector. Strong reductions are seen in the energy supply sector across all models. For N2O, less reduction potential is seen compared to methane and the sectoral differences are larger between the models. The paper shows that the assumptions on remaining non-CO2 emissions are critical for the feasibility of reaching ambitious climate targets and the associated costs.

Gernaat, David↗
DOE OSTI2018

Emergent orbitals in the cluster Mott insulator on a breathing kagome lattice

Motivated by the recent developments on cluster Mott insulating materials such as the cluster magnet LiZn 2 Mo 3 O 8 , we consider the strong plaquette charge ordered regime of the extended Hubbard model on a breathing kagome lattice and reveal the properties of the cluster Mottness. The plaquette charge order arises from the intersite charge interaction and the collective motion of three localized electrons on the hexagon plaquettes. This model leads naturally to a reduction of the local moments by 2/3, as observed in LiZn 2 Mo 3 O 8 . Furthermore, at low temperatures, each hexagon plaquette contains an extra orbital-like degree of freedom in addition to the remaining spin 1/2. We explore the consequence of this emergent orbital degree of freedom. We point out the interaction between the local moments is naturally described by a Kugel-Khomskii spin-orbital model. We develop a parton approach and suggest a spin-liquid ground state with spinon Fermi surfaces for this model. Here, we further predict an emergent orbital order when the system is under a strong magnetic field. Various experimental consequences for LiZn 2 Mo 3 O 8 are discussed, including an argument that the charge ordering must be short ranged if the charge per Mo is slightly off stoichiometric.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2014

BEAMS3D Neutral Beam Injection Model

With the advent of applied 3D fields in Tokamaks and modern high performance stellarators, a need has arisen to address non-axisymmetric effects on neutral beam heating and fueling. We report on the development of a fully 3D neutral beam injection (NBI) model, BEAMS3D, which addresses this need by coupling 3D equilibria to a guiding center code capable of modeling neutral and charged particle trajectories across the separatrix and into the plasma core. Ionization, neutralization, charge-exchange, viscous velocity reduction, and pitch angle scattering are modeled with the ADAS atomic physics database. Benchmark calculations are presented to validate the collisionless particle orbits, neutral beam injection model, frictional drag, and pitch angle scattering effects. A calculation of neutral beam heating in the NCSX device is performed, highlighting the capability of the code to handle 3D magnetic fields.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2024

Growth of Well-Defined Model Catalysts for Electrochemistry: From Surface Science Studies to Electrocatalytic CO2 Conversion

We combined ultrahigh vacuum (UHV) surface science techniques, electrochemical measurements, and computational modeling to investigate electrocatalytic systems that are crucial components of the carbon management effort, including oxygen evolution reactions (OER) and CO2 reduction reactions (CO2RR). Well-defined Model catalysts were grown on substrates in the UHV chamber and characterized with X-ray photoelectron spectroscopy (XPS) and scanning tunneling microscopy (STM). Selected model electrocatalysts were then tested in electrochemical cells to establish the structure-property relationships in OER and CO2RR. Our results showed that the edge sites of Fe2O3 grown on Au(111) were the most active toward OER and incorporation of Ni at the edge sites (NiFeOx) further boosted their OER activity. We also resolved the size-dependent electrocatalytic CO2-to-CO conversion of the Ag nanoparticle electrocatalysts with average particle diameter between 2 to 6 nm: smaller diameter (< 3 nm) particles favored H2 evolution reaction (HER) due to a high population of Ag edge sites, whereas larger diameter particles favored CO2RR as the population of Ag(100) surface sites grew. We further discovered that electronic interactions between small diameter Ag particles and highly defective carbon supports could break the size-dependent CO2RR selectivity, resulting in highly selective (CO Faradaic Efficiency > 90%) and active Ag nanoparticle electrocatalysts with sizes < 2 nm diameter.

Deng, Xingyi↗
NASA NTRS1980

Real-time data reduction capabilities at the Langley 7 by 10 foot high speed tunnel

The 7 by 10 foot high speed tunnel performs a wide range of tests employing a variety of model installation methods. To support the reduction of static data from this facility, a generalized wind tunnel data reduction program had been developed for use on the Langley central computer complex. The capabilities of a version of this generalized program adapted for real time use on a dedicated on-site computer are discussed. The input specifications, instructions for the console operator, and full descriptions of the algorithms are included.

Fox, C. H., Jr.↗
DOE OSTI2017

Computational Flame Diagnostics for Direct Numerical Simulations with Detailed Chemistry of Transportation Fuels

The goal of the proposed research is to create computational flame diagnostics (CFLD) that are rigorous numerical algorithms for systematic detection of critical flame features, such as ignition, extinction, and premixed and non-premixed flamelets, and to understand the underlying physicochemical processes controlling limit flame phenomena, flame stabilization, turbulence-chemistry interactions and pollutant emissions etc. The goal has been accomplished through an integrated effort on mechanism reduction, direct numerical simulations (DNS) of flames at engine conditions and a variety of turbulent flames with transport fuels, computational diagnostics, turbulence modeling, and DNS data mining and data reduction. The computational diagnostics are primarily based on the chemical explosive mode analysis (CEMA) and a recently developed bifurcation analysis using datasets from first-principle simulations of 0-D reactors, 1-D laminar flames, and 2-D and 3-D DNS (collaboration with J.H. Chen and S. Som at Argonne, and C.S. Yoo at UNIST). Non-stiff reduced mechanisms for transportation fuels amenable for 3-D DNS are developed through graph-based methods and timescale analysis. The flame structures, stabilization mechanisms, local ignition and extinction etc., and the rate controlling chemical processes are unambiguously identified through CFLD. CEMA is further employed to segment complex turbulent flames based on the critical flame features, such as premixed reaction fronts, and to enable zone-adaptive turbulent combustion modeling.

42 ENGINEERING↗
NASA NTRS2019

The Effects of an Improved Dynamic Vegetation Phenology Representation in a Global Land Surface Model

Evapotranspiration (ET) is a major driver of the interaction between the land surface and the atmosphere through its component mechanisms, including plant transpiration (T) and soil evaporation. To accurately capture land-atmosphere interactions in global Earth System Models, it is thus critical that the underlying land surface models accurately model both the land hydrology as well as the dynamic response of vegetation to environmental drivers. In an effort to introduce a more realistic vegetation representation, the NASA Catchment land surface model, which is part of the Goddard Earth Observing System (GEOS), has previously been merged with the carbon and nitrogen physics modules of the Community Land Model version 4, resulting in the new Catchment-CN model. Catchment-CN has inherited the advanced treatment of land surface hydrology of Catchment, but is additionally able to dynamically model the response of vegetation to environmental drivers, in contrast to the fixed vegetation climatology that was prescribed in Catchment. Recently, the parameterization of Catchment-CN vegetation has been augmented to better account for variability of vegetation responses to external forcings within existing plant functional types, and vegetation parameters have been calibrated against Moderate Resolution Imaging Spectrometer observations of the fraction of absorbed photosynthetically radiation. These efforts have led to a significant reduction in the RMSE of modeled photosynthetic activity with respect to observations.This presentation investigates the effect of the improved vegetation representation on the partitioning of ET within Catchment-CN. Specifically, we compare global maps of the T:ET ratio across different temporal scales in (1) the original Catchment model, (2) the original Catchment-CN model, and (3) the augmented and calibrated Catchment-CN model. The modeled T and ET estimates are compared against a comprehensive set of ground observations from various field studies, as well as independent global T:ET estimates from different ET algorithms provided in the context of the Water Cycle Observation Multi-mission Strategy ? Evapotranspiration (WACMOS-ET) initiative.

Kolassa, J.↗
NASA NTRS1982

Reliability model for planetary gear

A reliability model is presented for planetary gear trains in which the ring gear is fixed, the Sun gear is the input, and the planet arm is the output. The input and output shafts are coaxial and the input and output torques are assumed to be coaxial with these shafts. Thrust and side loading are neglected. This type of gear train is commonly used in main rotor transmissions for helicopters and in other applications which require high reductions in speed. The reliability model is based on the Weibull distribution of the individual reliabilities of the transmission components. The transmission's basic dynamic capacity is defined as the input torque which may be applied for one million input rotations of the Sun gear. Load and life are related by a power law. The load life exponent and basic dynamic capacity are developed as functions of the component capacities.

Savage, M.↗