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

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At least 883 records · Page 49
All sourcesNASA NTRSDOE OSTI
NASA NTRS2000

Uncertainty Analysis of Decomposing Polyurethane Foam

Sensitivity/uncertainty analyses are necessary to determine where to allocate resources for improved predictions in support of our nation's nuclear safety mission. Yet, sensitivity/uncertainty analyses are not commonly performed on complex combustion models because the calculations are time consuming, CPU intensive, nontrivial exercises that can lead to deceptive results. To illustrate these ideas, a variety of sensitivity/uncertainty analyses were used to determine the uncertainty associated with thermal decomposition of polyurethane foam exposed to high radiative flux boundary conditions. The polyurethane used in this study is a rigid closed-cell foam used as an encapsulant. Related polyurethane binders such as Estane are used in many energetic materials of interest to the JANNAF community. The complex, finite element foam decomposition model used in this study has 25 input parameters that include chemistry, polymer structure, and thermophysical properties. The response variable was selected as the steady-state decomposition front velocity calculated as the derivative of the decomposition front location versus time. An analytical mean value sensitivity/uncertainty (MV) analysis was used to determine the standard deviation by taking numerical derivatives of the response variable with respect to each of the 25 input parameters. Since the response variable is also a derivative, the standard deviation was essentially determined from a second derivative that was extremely sensitive to numerical noise. To minimize the numerical noise, 50-micrometer element dimensions and approximately 1-msec time steps were required to obtain stable uncertainty results. As an alternative method to determine the uncertainty and sensitivity in the decomposition front velocity, surrogate response surfaces were generated for use with a constrained Latin Hypercube Sampling (LHS) technique. Two surrogate response surfaces were investigated: 1) a linear surrogate response surface (LIN) and 2) a quadratic response surface (QUAD). The LHS techniques do not require derivatives of the response variable and are subsequently relatively insensitive to numerical noise. To compare the LIN and QUAD methods to the MV method, a direct LHS analysis (DLHS) was performed using the full grid and timestep resolved finite element model. The surrogate response models (LIN and QUAD) are shown to give acceptable values of the mean and standard deviation when compared to the fully converged DLHS model.

Hobbs, Michael L.↗
DOE OSTI2025

Re-evaluating the prompt fission neutron spectrum of spontaneously fissioning 252 Cf

The prompt fission neutron spectrum (PFNS) of spontaneously fissioning 252 Cf is a Neutron Data Standards observable. Nearly all fission spectra of actinides were measured relative to it, using efficiencies derived from it, or analyzed with simulations validated by it. The current Standards evaluation was published by W. Mannhart in 1987. It could not be updated because the evaluation input, experimental mean values and covariances, were lost. First, we attempt to reproduce it. However, Mannhart’s evaluation can only be reproduced within its one-σ uncertainties as some of its aspects (e.g., experimental covariances, rejected data points) remain unknown. Therefore, a new evaluation is presented: We revisit all existing experimental 252 Cf(sf) PFNS data, including those published after the release of the current Standards evaluation, and re-estimate associated covariances. The newly evaluated 252 Cf(sf) PFNS differs distinctly from Mannhart’s below 300 keV and extends it to lower and higher outgoing neutron energies (500 eV–25 MeV). The new evaluated uncertainties are larger from 3–9 MeV and smaller otherwise. Spectrum averaged cross sections of importance to the International Reactor Dosimetry and Fusion File community calculated with the new spectrum are close to those calculated with Mannhart’s evaluation and agree with experimental values well within their uncertainties.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2023

Considering the Variability of Soiling in Long-Term PV Performance Forecasting

This study presents the development of a methodology for evaluating the variability associated with soiling on long-term photovoltaic (PV) forecasting. Independent engineering firms typically build forecasts for large PV plants through the use of the PVsyst software, where monthly soiling losses are one of many inputs to the P50 model. Subsequently, long-term performance distributions are constructed through a Monte Carlo analysis that includes various factors, such as satellite irradiance modeling uncertainty, uncertainty in the PVsyst model, and long-term irradiance variability. Often the PVsyst model uncertainty is increased to account for sites with significant soiling concerns but no systematic method has been presented in the literature to specifically include soiling variability within long-term performance uncertainty. In this work soiling information from 16 sites in the U.S. Southwest are combined with 24 years of rainfall data to generate 24 years of energy production with soiling losses and then subsequently generate probability of exceedance values (e.g., P50, P90, P95…). The results show that the size of the 90% confidence interval (P5–P95) can increase from –0.7% to 10.1% when interannual soiling variability and soiling rate uncertainty is included.

14 SOLAR ENERGY↗
DOE OSTI2021

Metallic Fuel Performance Code Requirements for the Versatile Test Reactor Project

Metallic nuclear fuels have been proposed for use in several emerging nuclear reactor designs, and a number of codes have been developed to model these fuels and assess their performance. Qualification of these metallic nuclear fuels will ultimately require monitored irradiation of lead test assemblies, but the use of fuel performance codes can reduce the uncertainty associated with these efforts by quantifying uncertainties and estimating margins to failure ahead of time. In this work, metallic fuel performance code requirements are defined for the Versatile Test Reactor (VTR) project using input from the Experimental Breeder Reactor II functional requirements, operational requirements, and design criteria. This work focuses on the thermomechanical responses and irradiation behaviors of metallic fuel elements that are representative of the proposed VTR driver fuel design concepts. As such, many of the code requirements and physics/modeling discussions in this work are expected to be broadly applicable to metallic fuel applications outside of the VTR project.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2022

U.S. Efforts in Support of Examinations at Fukushima Daiichi (November 2021 Meeting Notes with Updated Information Requests)

Information obtained from Fukushima Daiichi Nuclear Power Station (Daiichi) is required to inform future Decontamination and Decommissioning (D&D) activities, improving the ability of the Tokyo Electric Power Company Holdings, Incorporated (TEPCO Holdings) to characterize potential hazards and to ensure the safety of workers involved with cleanup activities. This information also has important implications for the safety and operation of U.S. commercial nuclear power plants. This document summarizes results from the Fiscal Year 2022 (FY2022) U.S. effort to review Daiichi information and extract insights to enhance the safety of existing and future nuclear power plant designs. This U.S. effort, which was initiated in 2014 by the Department of Energy Office of Nuclear Energy, is completed by a group of experts in reactor safety and plant operations that identify examination needs and evaluate recent Daiichi examination data to address these needs. Fukushima-related information and associated discussions during forensics meetings benefit operating, new, and advanced reactors. Significant safety insights are being obtained in several areas: system and component performance, radionuclide surveys and sampling, debris end-state location, combustible gas effects, and plant operations and maintenance. In addition to reducing uncertainties related to severe accident modeling progression, these insights have and continue to be used to update guidance for severe accident prevention, mitigation, and emergency planning. As discussed in this document, revised operator guidance was successfully used to improve operator response during a loss of off-site power event at the Duane Arnold Energy Center plant. Reduced uncertainties in modeling the events at Daiichi improve the realism of reactor safety evaluations that inform future D&D activities. U.S. evaluations of information from Fukushima and input regarding future examinations are of interest to several organizations within Japan. Meeting presentations by Japan describe how comments and recommendations documented in prior U.S. forensics effort reports, including consensus information requests developed by forensics effort participants, are considered in future Fukushima D&D activities. As discussed in this report, TEPCO Holdings considered these information requests in their D&D planning activities. An updated list of consensus information requests is included in this FY2022 report.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
NASA NTRS1994

Feedback control laws for highly maneuverable aircraft

During the first half of the year, the investigators concentrated their efforts on completing the design of control laws for the longitudinal axis of the HARV. During the second half of the year they concentrated on the synthesis of control laws for the lateral-directional axes. The longitudinal control law design efforts can be briefly summarized as follows. Longitudinal control laws were developed for the HARV using mu synthesis design techniques coupled with dynamic inversion. An inner loop dynamic inversion controller was used to simplify the system dynamics by eliminating the aerodynamic nonlinearities and inertial cross coupling. Models of the errors resulting from uncertainties in the principal longitudinal aerodynamic terms were developed and included in the model of the HARV with the inner loop dynamic inversion controller. This resulted in an inner loop transfer function model which was an integrator with the modeling errors characterized as uncertainties in gain and phase. Outer loop controllers were then designed using mu synthesis to provide robustness to these modeling errors and give desired response to pilot inputs. Both pitch rate and angle of attack command following systems were designed. The following tasks have been accomplished for the lateral-directional controllers: inner and outer loop dynamic inversion controllers have been designed; an error model based on a linearized perturbation model of the inner loop system was derived; controllers for the inner loop system have been designed, using classical techniques, that control roll rate and Dutch roll response; the inner loop dynamic inversion and classical controllers have been implemented on the six degree of freedom simulation; and lateral-directional control allocation scheme has been developed based on minimizing required control effort.

Garrard, William L.↗
NASA NTRS1994

Microgravity isolation system design: A case study

Many acceleration-sensitive, microgravity science experiments will require active vibration isolation from manned orbiters on which they will be mounted. The isolation problem, especially in the case of a tethered payload, is a complex three-dimensional one that is best suited to modern-control design methods. In this paper, extended H(sub 2) synthesis is used to design an active isolator (i.e., controller) for a realistic single-input-multiple-output (SIMO) microgravity vibration isolation problem. Complex mu-analysis methods are used to analyze the isolation system with respect to sensor, actuator, and umbilical uncertainties. The paper fully discusses the design process employed and the insights gained. This design case study provides a practical approach for isolation problems of greater complexity. Issues addressed include a physically intuitive state-space description of the system, disturbance and noise filters, filters for frequency weighting, and uncertainty models. The controlled system satisfies all the performance specifications and is robust with respect to model uncertainties.

Hampton, R. D.↗
NASA NTRS2004

On the Measurement of Elemental Abundance Ratios in Inner Galaxy H II Regions

Although abundance gradients in the Milky Way Galaxy certainly exist, details remain uncertain, particularly in the inner Galaxy, where stars and H II regions in the Galactic plane are obscured optically. In this paper we revisit two previously studied, inner Galaxy H II regions: G333.6-0.2 and W43. We observed three new positions in G333.6-0.2 with the Kuiper Airborne Observatory and reobserved the central position with the Infrared Space Observatory's Long Wavelength Spectrometer in far-infrared lines of S++, N++, N+, and O++. We also added the N+ lines at 122 and 205 microns to the suite of lines measured in W43 by Simpson et al.. The measured electron densities range from approx. 40 to over 4000 per cu cm in a single HII region, indicating that abundance analyses must consider density variations, since the critical densities of the observed lines range from 40 to 9000 per cu cm. We propose a method to handle density variations and make new estimates of the S/H and N/H abundance ratios. We find that our sulfur abundance estimates for G333.6-0.2 and W43 agree with the S/H abundance ratios expected for the gradient previously reported by Simpson et al., with the S/H values revised to be smaller owing to changes in collisional excitation cross sections. The estimated N/H, S/H, and N/S ratios are the most reliable because of their small corrections for unseen ionization states (< or approx. 10%). The estimated N/S ratios for the two sources are smaller than what would be calculated from the N/H and S/H ratios in our previous paper. If all low excitation H II regions had similar changes to their N/S ratios as a result of adding measurements of N+ to previous measurements of N++, there would be no or only a very small gradient in N/S. This is interesting because nitrogen is considered to be a secondary element and sulfur is a primary element in galactic chemical evolution calculations. We compute models of the two H II regions to estimate corrections for the other unseen ionization states. We find, with large uncertainties, that oxygen does not, have a high abundance, with the result that the N/O ratio is as high (approx. 0.35) as previously reported. The reasons for the uncertainty in the ionization corrections for oxygen are both the non-uniqueness of the H II region models and the sensitivity of these models to different input atomic data and stellar atmosphere models. We discuss these predictions and conclude that only a few of the latest models adequately reproduce H II region observations, including the well-known, relatively-large observed Ne++/O++ ratios in low- and moderate-excitation H II regions.

Simpson, Janet P.↗
NASA NTRS2004

Application of Non-Deterministic Methods to Assess Modeling Uncertainties for Reinforced Carbon-Carbon Debris Impacts

The Space Shuttle Columbia Accident Investigation Board (CAIB) made several recommendations for improving the NASA Space Shuttle Program. An extensive experimental and analytical program has been developed to address two recommendations related to structural impact analysis. The objective of the present work is to demonstrate the application of probabilistic analysis to assess the effect of uncertainties on debris impacts on Space Shuttle Reinforced Carbon-Carbon (RCC) panels. The probabilistic analysis is used to identify the material modeling parameters controlling the uncertainty. A comparison of the finite element results with limited experimental data provided confidence that the simulations were adequately representing the global response of the material. Five input parameters were identified as significantly controlling the response.

Lyle, Karen H.↗
NASA NTRS2004

Assessment of Clear Sky Radiative Forcing in the Caribbean Region Using an Aerosol Dispersion Model and Ground Radiometry During Puerto Rico Dust Experiment

This study investigates the surface and top of the atmosphere solar radiative forcing by long-range transport of Saharan dust. The calculations of radiative forcing are based on measurements collected in the Puerto Rico Dust Experiment (PRIDE) carried out during July, 2000. The purpose of the experiment was the characterization of the Saharan dust plume, which frequently reaches the Caribbean region during the summer. The experiment involved the use of three approaches to study the plume: space and ground based remote sensing, airborne and ground based in-situ measurements and aerosol dispersion modeling. The diversity of measuring platforms provides an excellent opportunity for determination of the direct effect of dust on the clear sky radiative forcing. Specifically, comparisons of heating rates, surface and TOA fluxes derived from the Navy global aerosol dispersion model NAAPS (NRL Aerosol Analysis and Prediction System) and actual measurements of fluxes from ground and space based platforms are shown. In addition, the direct effect of dust on the clear sky radiative forcing is modeled. The extent and time of evolution of the radiative properties of the plume are computed with the aerosol concentrations modeled by NAAPS. Standard aerosol parameterizations, as well as in-situ composition and size distributions measured during PRIDE, are utilized to compute the aerosol optical depth, single scattering albedo and asymmetry factor. Radiative transfer computations are done with an in-house modified spectral radiative transfer code (Fu-Liou). The code includes gas absorption and cloud particles (ice and liquid phase) and it allows the input of meteorological data. The code was modified to include modules for the aerosols contribution to the calculated fluxes. This comparison study helps to narrow the current uncertainty in the dust direct radiative forcing, as recently reported in the 2001 IPCC assessment.

Gasso, Santiago↗
NASA NTRS2009

Using LIDAR and Quickbird Data to Model Plant Production and Quantify Uncertainties Associated with Wetland Detection and Land Cover Generalizations

Spatiotemporal data from satellite remote sensing and surface meteorology networks have made it possible to continuously monitor global plant production, and to identify global trends associated with land cover/use and climate change. Gross primary production (GPP) and net primary production (NPP) are routinely derived from the MOderate Resolution Imaging Spectroradiometer (MODIS) onboard satellites Terra and Aqua, and estimates generally agree with independent measurements at validation sites across the globe. However, the accuracy of GPP and NPP estimates in some regions may be limited by the quality of model input variables and heterogeneity at fine spatial scales. We developed new methods for deriving model inputs (i.e., land cover, leaf area, and photosynthetically active radiation absorbed by plant canopies) from airborne laser altimetry (LiDAR) and Quickbird multispectral data at resolutions ranging from about 30 m to 1 km. In addition, LiDAR-derived biomass was used as a means for computing carbon-use efficiency. Spatial variables were used with temporal data from ground-based monitoring stations to compute a six-year GPP and NPP time series for a 3600 ha study site in the Great Lakes region of North America. Model results compared favorably with independent observations from a 400 m flux tower and a process-based ecosystem model (BIOME-BGC), but only after removing vapor pressure deficit as a constraint on photosynthesis from the MODIS global algorithm. Fine resolution inputs captured more of the spatial variability, but estimates were similar to coarse-resolution data when integrated across the entire vegetation structure, composition, and conversion efficiencies were similar to upland plant communities. Plant productivity estimates were noticeably improved using LiDAR-derived variables, while uncertainties associated with land cover generalizations and wetlands in this largely forested landscape were considered less important.

Cook, Bruce D.↗
DOE OSTI2020

A Novel Modeling Framework for Computationally Efficient and Accurate Real-Time Ensemble Flood Forecasting With Uncertainty Quantification

A novel modeling framework that simultaneously improves accuracy, predictability, and computational efficiency is presented. It embraces the benefits of three modeling techniques integrated together for the first time: surrogate modeling, parameter inference, and data assimilation. The use of polynomial chaos expansion (PCE) surrogates significantly decreases computational time. Parameter inference allows for model faster convergence, reduced uncertainty, and superior accuracy of simulated results. Ensemble Kalman filters assimilate errors that occur during forecasting. To examine the applicability and effectiveness of the integrated framework, we developed 18 approaches according to how surrogate models are constructed, what type of parameter distributions are used as model inputs, and whether model parameters are updated during the data assimilation procedure. We conclude that (1) PCE must be built over various forcing and flow conditions, and in contrast to previous studies, it does not need to be rebuilt at each time step; (2) model parameter specification that relies on constrained, posterior information of parameters (so-called Selected specification) can significantly improve forecasting performance and reduce uncertainty bounds compared to Random specification using prior information of parameters; and (3) no substantial differences in results exist between single and dual ensemble Kalman filters, but the latter better simulates flood peaks. The use of PCE effectively compensates for the computational load added by the parameter inference and data assimilation (up to ~80 times faster). Therefore, the presented approach contributes to a shift in modeling paradigm arguing that complex, high-fidelity hydrologic and hydraulic models should be increasingly adopted for real-time and ensemble flood forecasting.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Identifying atmospheric rivers and their poleward latent heat transport with generalizable neural networks: ARCNNv1

Abstract. Atmospheric rivers (ARs) are extreme weather events that can alleviate drought or cause billions of US dollars in flood damage. By transporting significant amounts of latent energy towards the poles, they are crucial to maintaining the climate system's energy balance. Since there is no first-principle definition of an AR grounded in geophysical fluid mechanics, AR identification is currently performed by a multitude of expert-defined, threshold-based algorithms. The variety of AR detection algorithms has introduced uncertainty into the study of ARs, and the thresholds of the algorithms may not generalize to new climate datasets and resolutions. We train convolutional neural networks (CNNs) to detect ARs while representing this uncertainty; we name these models ARCNNs. To detect ARs without requiring new labeled data and labor-intensive AR detection campaigns, we present a semi-supervised learning framework based on image style transfer. This framework generalizes ARCNNs across climate datasets and input fields. Using idealized and realistic numerical models, together with observations, we assess the performance of the ARCNNs. We test the ARCNNs in an idealized simulation of a shallow-water fluid in which nearly all the tracer transport can be attributed to AR-like filamentary structures. In reanalysis and a high-resolution climate model, we use ARCNNs to calculate the contribution of ARs to meridional latent heat transport, and we demonstrate that this quantity varies considerably due to AR detection uncertainty.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS2020

Ensemble PM2.5 Forecasting during the 2018 Camp Fire Event Using the HYSPLIT Transport and Dispersion Model

Biomass burning releases a vast amount of aerosols into the atmosphere, often leading to severe air quality and health problems. Prediction of the air quality effects from biomass burning emissions is challenging due to uncertainties in fire emission, plume rise calculation, and other model inputs/processes. Ensemble forecasting is increasingly used to represent model uncertainties. In this paper, an ensemble forecast was conducted to predict surface PM2.5 during the 2018 California Camp Fire event using the NOAA HYSPLIT dispersion model at 0.1- degree horizontal resolution. Different combinations of four satellite-based fire emission datasets (FEER, FLAMBE, GBBEPx and GFAS), two plume rise schemes (Briggs and Sofiev), various meteorology inputs and model setup options were used to create the forecast ensemble, for a total of 112 experiments. The performance of each ensemble member and the ensemble mean were evaluated using ground-based observations, with four statistical metrics and an overall rank. The ensemble spread of the 112 members reached 1000 μg/m3, highlighting the large uncertainty in wildfire forecast. The ensemble mean displayed the best performance. Each fire emission product contributed to one or more members among the top ten performers, revealing the forecasting dependence on both the quality of fire emissions data and model representation of emission, transport and removal processes. In addition, an ensemble size reduction technique was introduced. With the help of this technique, the ensemble size was reduced from 112 to 28 members and still produced an ensemble mean that yielded comparable or even better performance to that of the full ensemble.

Biomass Burning↗
DOE OSTI2020

State-of-the-Art Reactor Consequence Analysis Project: Sensitivity Analysis Using Dakota

The State-of-the-Art Reactor Consequence Analyses (SOARCA) project has focused on best estimate analyses and uncertainty analysis for postulated accidents at specific nuclear power plants. The consequences of these accidents are estimated using the simulation tools MELCOR and MACCS. To understand which uncertain input variables are important to determining these consequences, analysts have performed sensitivity analyses. The tool used to perform these sensitivity analyses in previous SOARCA work, CompModSA, is no longer supported. Therefore, the current work focuses on migrating these analyses to another tool and evaluating its performance. Dakota, which is a tool developed at Sandia National Laboratories, is used in this work. Sensitivity results are created for three analyses from the SOARCA Surry UA. Though CompModSA and Dakota vary slightly in their algorithms and implementation, their sensitivity results generally agree, which gives confidence in the Dakota approach and increases confidence in the original analyses. It is likely that this methodology is extendable to the rest of SOARCA analyses.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
NASA NTRS1992

Monte Carlo exploration of Mikheyev-Smirnov-Wolfenstein solutions to the solar neutrino problem

The paper explores the impact of astrophysical uncertainties on the Mikheyev-Smirnov-Wolfenstein (MSW) solution by calculating the allowed MSW solutions for 1000 different solar models with a Monte Carlo selection of solar model input parameters, assuming a full three-family MSW mixing. Applications are made to the chlorine, gallium, Kamiokande, and Borexino experiments. The initial GALLEX result limits the mixing parameters to the upper diagonal and the vertical regions of the MSW triangle. The expected event rates in the Borexino experiment are also calculated, assuming the MSW solutions implied by GALLEX.

Shi, X.↗