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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 1,261 records · Page 70
All sourcesNASA NTRSDOE OSTI
DOE OSTI2017

Estimation of d- 2 H Breakup Neutron Energy Distributions From d- 3 He

A method is described to estimate deuteron-on-deuteron breakup neutron distributions at 0° using deuterium bombardment of 3 He. Break-up neutron distributions are modeled with the product of a Fermi-Dirac distribution and a cumulative logistic distribution function. Four measured break-up neutron distributions from 6.15- to 12.0-MeV deuterons on 3 He are compared with thirteen measured distributions from 6.83- to 11.03-MeV deuterons on deuterium. Model pararmeters that describe d -3 He neutron distributions are used to estimate neutron distributions from 6- to 12-MeV deuterons on deuterium.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2021

Shock-ramp analysis test problem

Quasi-isentropic (ramp) compression is now a well-established experimental method and so are the analysis techniques to give Lagrangian sound speed, pressure, and density along the sample material's isentrope. A shock followed by ramp compression is a natural extension to investigate, for example, shock melt and refreeze on compression, or isentropes of states off the Hugoniot or principal isentrope. In practice, graded-density impactors produce initial shocks, compression by shaped laser pulses may be unable to produce a smooth pressure increase from zero, and incidental perturbations on the drive pulse may also give rise to shocks, so robust shock-ramp analysis methods will be needed. Appropriate analysis methods are needed for shock-ramp experiments, based on those for quasi-isentropic compression, and these require validation. This paper describes three different analyses of a shock-ramp test problem, including an assessment of their estimated errors. The methods tested were based on hydrodynamic characteristics or integration backward in space. All methods gave the known Lagrangian sound speed to within ~1%, and pressure and volume to within less than 2% and 1%, demonstrating that the analysis methods of isentropic compression experiments can be confidently extended to the analysis of shock and ramp compression.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2019

A Multi-Model Adaptive Kalman Filtering Approach to Power System Dynamic State Estimation

Accurate information about dynamic states (such as rotor angle and speed of a synchronous machine) is important for monitoring and controlling power system rotor-angle stability. In this paper, a multi-model adaptive Kalman filtering (MMAKF) approach is proposed to accurately and robustly estimate power system dynamic states. This approach consists of three major steps: (i) multiple Kalman filtering approaches, i.e., the extended Kalman filter (EKF), unscented Kalman filter (UKF), ensemble Kalman filter (EnKF), and cubature Kalman filter (CKF), are run concurrently in parallel to estimate the dynamic states of a synchronous generator using phasor measurement unit data; (ii) probability indexes, which quantify the likelihood of each estimation model, are determined at each time step using hypothesis testing based on the measurement innovation; (iii) the a posteriori estimate of states is obtained using the best-fix approach. The two-area four-machine system is used to evaluate the effectiveness of the proposed MMAKF approach. It is shown through the Monte-Carlo method that the estimation accuracy and robustness of the proposed approach is better than those from any individual filtering algorithm.

multi-model adaptive Kalman Filtering, Power Syste↗
DOE OSTI2015

Laboratory testing options for FUSRAP projects - 15462

Remediation projects within the Formerly Used Sites Remedial Action Program (FUSRAP) have many options to consider when evaluating their analytical testing needs. Factors that should be considered in determination of a project's analytical testing needs include which parameter results are considered time-critical, the potential savings in reduction of construction-related delays when time-critical samples are analyzed onsite (including screening) instead of offsite, control of data quality for onsite versus offsite data, and the value of additional knowledge gained by programs such as FUSRAP by employing onsite laboratories. The most important factor turned out to be reduction in construction-related delays. We considered development of an optimum combination of onsite lab/offsite lab capability. This depends on: i. Time critical parameters and the methods required; ii. Estimated Cost for onsite lab construction or facility rental, maintenance, labor, chemicals (reagents and standards), and certification (if desired and deemed necessary) iii. Ability, flexibility, and cost of offsite lab sample testing using project-desired TATs and methods that will meet project action levels iv. Willingness of stakeholders, in particular regulators, in accepting some combination of onsite and offsite testing (for example, onsite screening followed by offsite confirmatory testing for certain parameters) Due to the significant costs in construction of an onsite lab and development of sample testing capability and all which that entails, the recommendations made in this paper will aid other FUSRAP projects in finding an acceptable combination of onsite and offsite testing that is acceptable to all stakeholders. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2023

Shedding light on the economic costs of long-duration power outages: A review of resilience assessment methods and strategies

Here this paper provides a literature review of methods and modeling techniques to estimate the cost of power system outages, along with the value of outage mitigation or system resilience. Regulators, policymakers, and infrastructure owners have a growing need to understand the methods for estimating the benefits of resilience improvements of electric infrastructure against natural and man-made disasters. There is a broad literature that estimates the cost of short-duration outages and a small but developing literature on estimating the cost of long-duration outages. This article reviews the models used to estimate the cost of outages and discusses their relative strengths. Additionally, this paper identifies key questions from stakeholders regarding resilience investment and maps them to the relevant models that would help answer them. We include recommendations for future work to include recent advances in regional economic modeling that can estimate region and demographic-specific costs and the distributional consequences of potential resilience projects.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2015

Development of a dual phantom technique for measuring the fast neutron component of dose in boron neutron capture therapy

Purpose: Research and development of various accelerator-based irradiation systems for boron neutron capture therapy (BNCT) is underway throughout the world. Many of these systems are nearing or have started clinical trials. Before the start of treatment with BNCT, the relative biological effectiveness (RBE) for the fast neutrons (over 10 keV) incident to the irradiation field must be estimated. Measurements of RBE are typically performed by biological experiments with a phantom. Although the dose deposition due to secondary gamma rays is dominant, the relative contributions of thermal neutrons (below 0.5 eV) and fast neutrons are virtually equivalent under typical irradiation conditions in a water and/or acrylic phantom. Uniform contributions to the dose deposited from thermal and fast neutrons are based in part on relatively inaccurate dose information for fast neutrons. This study sought to improve the accuracy in the dose estimation for fast neutrons by using two phantoms made of different materials in which the dose components can be separated according to differences in the interaction cross sections. The development of a “dual phantom technique” for measuring the fast neutron component of dose is reported. Methods: One phantom was filled with pure water. The other phantom was filled with a water solution of lithium hydroxide (LiOH) capitalizing on the absorbing characteristics of lithium-6 (Li-6) for thermal neutrons. Monte Carlo simulations were used to determine the ideal mixing ratio of Li-6 in LiOH solution. Changes in the depth dose distributions for each respective dose component along the central beam axis were used to assess the LiOH concentration at the 0, 0.001, 0.01, 0.1, 1, and 10 wt. % levels. Simulations were also performed with the phantom filled with 10 wt. % {sup 6}LiOH solution for 95%-enriched Li-6. A phantom was constructed containing 10 wt. % {sup 6}LiOH solution based on the simulation results. Experimental characterization of the depth dose distributions of the neutron and gamma-ray components along the central axis was performed at Heavy Water Neutron Irradiation Facility installed at Kyoto University Reactor using activation foils and thermoluminescent dosimeters, respectively. Results: Simulation results demonstrated that the absorbing effect for thermal neutrons occurred when the LiOH concentration was over 1%. The most effective Li-6 concentration was determined to be enriched {sup 6}LiOH with a solubility approaching its upper limit. Experiments confirmed that the thermal neutron flux and secondary gamma-ray dose rate decreased substantially; however, the fast neutron flux and primary gamma-ray dose rate were hardly affected in the 10%-{sup 6}LiOH phantom. It was confirmed that the dose contribution of fast neutrons is improved from approximately 10% in the pure water phantom to approximately 50% in the 10%-{sup 6}LiOH phantom. Conclusions: The dual phantom technique using the combination of a pure water phantom and a 10%-{sup 6}LiOH phantom developed in this work provides an effective method for dose estimation of the fast neutron component in BNCT. Improvement in the accuracy achieved with the proposed technique results in improved RBE estimation for biological experiments and clinical practice.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2022

General Relativistic Implicit Monte Carlo Radiation-hydrodynamics

Abstract We report on a new capability added to our general relativistic radiation-magnetohydrodynamics code, Cosmos++ : an implicit Monte Carlo (IMC) treatment for radiation transport. The method is based on a Fleck-type implicit discretization of the radiation-hydrodynamics equations, but generalized for both Newtonian and relativistic regimes. A multiple reference frame approach is used to geodesically transport photon packets (and solve the hydrodynamics equations) in the coordinate frame, while radiation–matter interactions are handled either in the fluid or electron frames then communicated via Lorentz boosts and orthonormal tetrad bases attached to the fluid. We describe a method for constructing estimators of radiation moments using path-weighting that generalizes to arbitrary coordinate systems in flat or curved spacetime. Absorption, emission, scattering, and relativistic Comptonization are among the matter interactions considered in this report. We discuss our formulations and numerical methods, and validate our models against a suite of radiation and coupled radiation-hydrodynamics test problems in both flat and curved spacetimes.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2026

Quantifying mean, variability, and uncertainty in indoor radon exposure in Pennsylvania using random forest and quantile regression forest models

Radon is a naturally occurring radioactive gas that poses a serious health risk as the primary cause of lung cancer in non-smokers. Despite the well-known adverse association with health outcomes, current radon exposure assessments are limited to county-level or average-level estimates, which fail to capture regional variability. This study uses Machine Learning models, including Random Forest (RF) and Quantile Regression Forest (QRF), to estimate the indoor radon concentrations at the ZCTA (Zip code tabulation area)-level and characterize uncertainties in model estimates. Incorporating geological, meteorological, and building-specific data, the models aim to improve radon risk assessment by capturing mean exposure, variability, and extreme concentration levels. Processed radon test data (n = 718,111) were analyzed using average, variability, and quantile prediction methods. Models that estimate the average radon exposure at the ZCTA-level can yield promising model-fit results, but they do not capture the underlying variability of indoor radon exposure within a ZCTA. We utilize volatility analyses to identify characteristics indicative of high variability of indoor radon exposure. We also show that a QRF model can be used to estimate upper quantiles of residential radon exposure, thereby uncovering localized areas of elevated exposure that were not apparent in mean estimates. The results highlighted the need for a deep characterization of exposure risk and show that regions with moderate average exposure levels could still harbor extreme outliers with implications for evaluating health risks. Utilizing multiple radon exposure models allows for a deeper characterization of radon risk within a geographic area and can better identify high-risk areas. The results from this study provide a foundation for developing mitigation strategies and examining associations between radon exposure and health outcomes at fine scales. Future research should extend the geographic scope and incorporate additional environmental risk factors to establish a comprehensive framework for risk assessment.

Lee, Heechan [ORNL]↗
DOE OSTI2017

8760-Based Method for Representing Variable Generation Capacity Value in Capacity Expansion Models: Preprint

Capacity expansion models (CEMs) are widely used to evaluate the least-cost portfolio of electricity generators, transmission, and storage needed to reliably serve demand over the evolution of many years or decades. Various CEM formulations are used to evaluate systems ranging in scale from states or utility service territories to national or multi-national systems. CEMs can be computationally complex, and to achieve acceptable solve times, key parameters are often estimated using simplified methods. In this paper, we focus on two of these key parameters associated with the integration of variable generation (VG) resources: capacity value and curtailment. We first discuss common modeling simplifications used in CEMs to estimate capacity value and curtailment, many of which are based on a representative subset of hours that can miss important tail events or which require assumptions about the load and resource distributions that may not match actual distributions. We then present an alternate approach that captures key elements of chronological operation over all hours of the year without the computationally intensive economic dispatch optimization typically employed within more detailed operational models. The updated methodology characterizes the (1) contribution of VG to system capacity during high load and net load hours, (2) the curtailment level of VG, and (3) the potential reductions in curtailments enabled through deployment of storage and more flexible operation of select thermal generators. We apply this alternate methodology to an existing CEM, the Regional Energy Deployment System (ReEDS). Results demonstrate that this alternate approach provides more accurate estimates of capacity value and curtailments by explicitly capturing system interactions across all hours of the year. This approach could be applied more broadly to CEMs at many different scales where hourly resource and load data is available, greatly improving the representation of challenges associate with integration of variable generation resources.

14 SOLAR ENERGY↗
DOE OSTI2016

The Casualidad method for uncertainty evaluation of best-estimate system thermal-hydraulics calculations

The present paper deals with the description of the salient features of three independent approaches for estimating uncertainties associated with predictions of complex system codes. The first approach is the 'standard' one and the most used at the industrial level: it is based upon the selection of input uncertain parameters, on assigning related ranges of variations and, possibly, PDF (Probability Density Functions) and on performing a suitable number of code runs to get the combined effect of variation on the results. In the second approach the uncertainty derives from the comparison between relevant measured data and results of corresponding code calculations. The third approach is based on the Bayesian inference technique and on the availability of experimental data by which computer model predictions can be improved and the ranges of variation of (in theory) 'all' input parameters can be characterized. More details are provided in respect with the third approach that has been named CASUALIDAD (Code with the capability of Adjoint Sensitivity and Uncertainty Analysis by Internal Data Adjustment and assimilation). (authors)

42 ENGINEERING↗
DOE OSTI2023

Inferring Viral Transmission Time from Phylogenies for Known Transmission Pairs

When the time of an HIV transmission event is unknown, methods to identify it from virus genetic data can reveal the circumstances that enable transmission. We developed a single-parameter Markov model to infer transmission time from an HIV phylogeny constructed of multiple virus sequences from people in a transmission pair. Our method finds the statistical support for transmission occurring in different possible time slices. We compared our time-slice model results to previously described methods: a tree-based logical transmission interval, a simple parsimony-like rules-based method, and a more complex coalescent model. Across simulations with multiple transmitted lineages, different transmission times relative to the source’s infection, and different sampling times relative to transmission, we found that overall our time-slice model provided accurate and narrower estimates of the time of transmission. We also identified situations when transmission time or direction was difficult to estimate by any method, particularly when transmission occurred long after the source was infected and when sampling occurred long after transmission. Applying our model to real HIV transmission pairs showed some agreement with facts known from the case investigations. We also found, however, that uncertainty on the inferred transmission time was driven more by uncertainty from time calibration of the phylogeny than from the model inference itself. Encouragingly, comparable performance of the Markov time-slice model and the coalescent model—which make use of different information within a tree—suggests that a new method remains to be described that will make full use of the topology and node times for improved transmission time inference.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2016

Advanced Methods for Modeling Water-Levels and Estimating Drawdowns with SeriesSEE, an Excel Add-In

Water-level modeling is used for multiple-well aquifer tests to reliably differentiate pumping responses from natural water-level changes in wells, or environmental fluctuations. Synthetic water levels are created during water-level modeling and represent the summation of multiple component fluctuations, including those caused by environmental forcing and pumping. Pumping signals are modeled by transforming step-wise pumping records into water-level changes by using superimposed Theis functions. Water-levels can be modeled robustly with this Theis-transform approach because environmental fluctuations and pumping signals are simulated simultaneously. Water-level modeling with Theis transforms has been implemented in the program SeriesSEE, which is a Microsoft® Excel add-in. Moving average, Theis, pneumatic-lag, and gamma functions transform time series of measured values into water-level model components in SeriesSEE. Earth tides and step transforms are additional computed water-level model components. Water-level models are calibrated by minimizing a sum-of-squares objective function where singular value decomposition and Tikhonov regularization stabilize results. Drawdown estimates from a water-level model are the summation of all Theis transforms minus residual differences between synthetic and measured water levels. The accuracy of drawdown estimates is limited primarily by noise in the data sets, not the Theis-transform approach. Drawdowns much smaller than environmental fluctuations have been detected across major fault structures, at distances of more than 1 mile from the pumping well, and with limited pre-pumping and recovery data at sites across the United States. In addition to water-level modeling, utilities exist in SeriesSEE for viewing, cleaning, manipulating, and analyzing time-series data.

58 GEOSCIENCES↗
DOE OSTI2020

Probabilistic predictions and uncertainty estimation for radiological and nuclear effects modeling

Better characterization of meteorological uncertainty is needed to predict the effects of radiological and nuclear releases in the atmosphere. Multi-physics ensembles of atmospheric simulations can estimate uncertainty of physical processes, but they are often limited for computational reasons. Because weather uncertainty is important for emergency response applications, but the conventional way of running multi-physics ensembles is infeasible, we have developed new machine learning-based methods that quickly estimate and identify key sources of meteorological uncertainty. Machine learning accelerates the analysis of weather uncertainty by iteratively learning about model physics options that affect plume predictions. We have demonstrated the power of machine learning by creating a large multi-physics weather and dispersion ensemble dataset containing 1,200 simulations for two hypothetical radiological release scenarios. By training on less than 10% of the ensemble, we can quickly and accurately predict different outcomes, including the mass of radiological material deposited and spatial distribution and extent of contaminated areas.

54 ENVIRONMENTAL SCIENCES↗