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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 1,531 records · Page 85
All sourcesNASA NTRSDOE OSTI
DOE OSTI2018

ARIADNE – a program estimating covariances in detail for neutron experiments

The python program ARIADNE is a tool developed for evaluators to estimate detailed uncertainties and covariances for experimental data in a consistent and efficient manner. Currently, it is designed to aid in the uncertainty quantification of prompt fission neutron spectra, and was employed to estimate experimental covariances for CIELO and ENDF/B-VIII.0 evaluations. It provides a streamlined way to estimate detailed covariances by (1) implementing uncertainty quantification algorithms specific to the observables, (2) defining input quantities for typically encountered uncertainty sources and correlation shapes, and (3) automatically generating plots of data, uncertainties and correlations, GND formatted XML and plain text output files. Covariances of the same and between different datasets can be estimated, and tools are provided to assemble a database of experimental data and covariances for an evaluation based on ARIADNE outputs. The underlying IPython notebook files can be easily stored, including all assumptions on uncertainties, leading to more reproducible inputs for nuclear data evaluations. Here, the key inputs and outputs are shown along with a representative example for the current version of ARIADNE to illustrate its usability and to open a discussion on how it could address further needs of the nuclear data evaluation community.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2021

Probabilistic error estimation for non-intrusive reduced models learned from data of systems governed by linear parabolic partial differential equations

This work derives a residual-based a posteriori error estimator for reduced models learned with non-intrusive model reduction from data of high-dimensional systems governed by linear parabolic partial differential equations with control inputs. It is shown that quantities that are necessary for the error estimator can be either obtained exactly as the solutions of least-squares problems in a non-intrusive way from data such as initial conditions, control inputs, and high-dimensional solution trajectories or bounded in a probabilistic sense. Here, the computational procedure follows an offline/online decomposition. In the offline (training) phase, the high-dimensional system is judiciously solved in a black-box fashion to generate data and to set up the error estimator. In the online phase, the estimator is used to bound the error of the reduced-model predictions for new initial conditions and new control inputs without recourse to the high-dimensional system. Numerical results demonstrate the workflow of the proposed approach from data to reduced models to certified predictions.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2014

Estimates of Glacier Mass Loss and Contribution to Streamflow in the Wind River Range in Wyoming: Case Study

The Wind River Range is a continuous mountain range, approximately 160 km in length, in west-central Wyoming. The presence of glaciers results in meltwater contributions to streamflow during the late summer (July, August, and September: JAS) when snowmelt is decreasing; temperatures are high; precipitation is low; evaporation rates are high; and municipal, industrial, and irrigation water are at peak demands. Therefore, the quantification of glacier meltwater (e.g., volume and mass) contributions to late summer/early fall streamflow is important, given that this resource is dwindling owing to glacier recession. The current research expands upon previous research efforts and identifies two glaciated watersheds, one on the east slope (Bull Lake Creek) and one on the west slope (Green River) of the Wind River Range, in which unimpaired streamflow is available from 1966 to 2006. Glaciers were delineated within each watershed and area estimates (with error) were obtained for the years 1966, 1989, and 2006. Glacier volume (mass) loss (with error) was estimated by using empirically based volume-area scaling relationships. For 1966 to 2006, glacier mass contributions to JAS streamflow on the east slope were approximately 8%, whereas those on the west slope were approximately 2%. Furthermore, the volume-area scaling glacier mass estimates compared favorably with measured (stereo pair remote sensed data) estimates of glacier mass change for three glaciers (Teton, Middle Teton, and Teepe) in the nearby Teton Range and one glacier (Dinwoody) in the Wind River Range.

58 GEOSCIENCES↗
DOE OSTI2019

Hurricane Harvey Highlights: Need to Assess the Adequacy of Probable Maximum Precipitation Estimation Methods

Probable maximum precipitation (PMP) is the primary criterion used to design flood protection measures for critical infrastructures such as dams and nuclear power plants. Based on our analysis using the Stage IV (ST4) quantitative precipitation estimates, precipitation associated with Hurricane Harvey near Houston, Texas, represents a PMP-scale storm and partially exceeds the Hydrometeorological Report No. 51 (HMR51) 72-h PMP estimates at 5,000 mi 2 (ST4=805 mm; HMR51=780 mm) and 10,000 mi 2 (ST4=686 mm; HMR51=673 mm). We also find statistically significant increasing trends since 1949 in the annual maximum total precipitable water and dew point temperature observations along the US Gulf Coast region, suggesting that, if the trend continues, the theoretical upper bound of PMP could be even larger. Our analysis of Hurricane Harvey rainfall data demonstrates that an extremely large PMP-scale storm is physically possible and that PMP estimates should not be considered overly conservative. Furthermore, this case study highlights the need for improved PMP estimation methodologies to account for long-term trends and to ensure the safety of our critical infrastructures.

42 ENGINEERING↗
DOE OSTI2020

Estimating Sediment Settling Velocities from a Theoretically Guided Data-Driven Approach

Sediment settling velocities are commonly estimated from analytical or process-based approaches. These approaches have theoretical constraints due to the incompletely resolved settling physics. A parametric data-driven approach was recently proposed without theoretical constraints, but it is limited by its mathematical assumptions. To overcome these limitations, here we apply a machine learning algorithm to an aggregated sediment settling experimental database and develops a nonparametric data-driven model to estimate the noncohesive sediment settling velocity in water. A cross-comparison against five process-based equations and a parametric data-driven equation demonstrates the higher accuracy and better consistency of the new model in estimating sediment settling velocities under various physical regimes. The new model also shows an easily implemented self-update capability by assimilating theoretical data derived from the process-based equations. The updated model, incorporating experimental and theoretical data of sediment settling processes, further improves the accuracy and reduces the uncertainty in estimating sediment settling velocities. This study demonstrates the capability of machine learning in sediment transport study and illustrates an alternative framework for other hydraulic engineering challenges.

42 ENGINEERING↗
DOE OSTI2013

Anisotropic parameter estimation using velocity variation with offset analysis

Seismic anisotropy is defined as velocity dependent upon angle or offset. Knowledge about anisotropy effect on seismic data is important in amplitude analysis, stacking process and time to depth conversion. Due to this anisotropic effect, reflector can not be flattened using single velocity based on hyperbolic moveout equation. Therefore, after normal moveout correction, there will still be residual moveout that relates to velocity information. This research aims to obtain anisotropic parameters, ε and δ, using two proposed methods. The first method is called velocity variation with offset (VVO) which is based on simplification of weak anisotropy equation. In VVO method, velocity at each offset is calculated and plotted to obtain vertical velocity and parameter δ. The second method is inversion method using linear approach where vertical velocity, δ, and ε is estimated simultaneously. Both methods are tested on synthetic models using ray-tracing forward modelling. Results show that δ value can be estimated appropriately using both methods. Meanwhile, inversion based method give better estimation for obtaining ε value. This study shows that estimation on anisotropic parameters rely on the accuracy of normal moveout velocity, residual moveout and offset to angle transformation.

58 GEOSCIENCES↗
DOE OSTI2014

A combined method to estimate parameters of the thalamocortical model from a heavily noise-corrupted time series of action potential

A combined method composing of the unscented Kalman filter (UKF) and the synchronization-based method is proposed for estimating electrophysiological variables and parameters of a thalamocortical (TC) neuron model, which is commonly used for studying Parkinson's disease for its relay role of connecting the basal ganglia and the cortex. In this work, we take into account the condition when only the time series of action potential with heavy noise are available. Numerical results demonstrate that not only this method can estimate model parameters from the extracted time series of action potential successfully but also the effect of its estimation is much better than the only use of the UKF or synchronization-based method, with a higher accuracy and a better robustness against noise, especially under the severe noise conditions. Considering the rather important role of TC neuron in the normal and pathological brain functions, the exploration of the method to estimate the critical parameters could have important implications for the study of its nonlinear dynamics and further treatment of Parkinson's disease.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2014

Explicit approximations to estimate the perturbative diffusivity in the presence of convectivity and damping. III. Cylindrical approximations for heat waves traveling inwards

In this paper, a number of new explicit approximations are introduced to estimate the perturbative diffusivity (χ), convectivity (V), and damping (τ) in cylindrical geometry. For this purpose, the harmonic components of heat waves induced by localized deposition of modulated power are used. The approximations are based on the heat equation in cylindrical geometry using the symmetry (Neumann) boundary condition at the plasma center. This means that the approximations derived here should be used only to estimate transport coefficients between the plasma center and the off-axis perturbative source. If the effect of cylindrical geometry is small, it is also possible to use semi-infinite domain approximations presented in Part I and Part II of this series. A number of new approximations are derived in this part, Part III, based upon continued fractions of the modified Bessel function of the first kind and the confluent hypergeometric function of the first kind. These approximations together with the approximations based on semi-infinite domains are compared for heat waves traveling towards the center. The relative error for the different derived approximations is presented for different values of the frequency, transport coefficients, and dimensionless radius. Moreover, it is shown how combinations of different explicit formulas can be used to estimate the transport coefficients over a large parameter range for cases without convection and damping, cases with damping only, and cases with convection and damping. The relative error between the approximation and its underlying model is below 2% for the case, where only diffusivity and damping are considered. If also convectivity is considered, the diffusivity can be estimated well in a large region, but there is also a large region in which no suitable approximation is found. This paper is the third part (Part III) of a series of three papers. In Part I, the semi-infinite slab approximations have been treated. In Part II, cylindrical approximations are treated for heat waves traveling towards the plasma edge assuming a semi-infinite domain.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2014

Patient dose estimation from CT scans at the Mexican National Neurology and Neurosurgery Institute

In the radiology department of the Mexican National Institute of Neurology and Neurosurgery, a dedicated institute in Mexico City, on average 19.3 computed tomography (CT) examinations are performed daily on hospitalized patients for neurological disease diagnosis, control scans and follow-up imaging. The purpose of this work was to estimate the effective dose received by hospitalized patients who underwent a diagnostic CT scan using typical effective dose values for all CT types and to obtain the estimated effective dose distributions received by surgical and non-surgical patients. Effective patient doses were estimated from values per study type reported in the applications guide provided by the scanner manufacturer. This retrospective study included all hospitalized patients who underwent a diagnostic CT scan between 1 January 2011 and 31 December 2012. A total of 8777 CT scans were performed in this two-year period. Simple brain scan was the CT type performed the most (74.3%) followed by contrasted brain scan (6.1%) and head angiotomography (5.7%). The average number of CT scans per patient was 2.83; the average effective dose per patient was 7.9 mSv; the mean estimated radiation dose was significantly higher for surgical (9.1 mSv) than non-surgical patients (6.0 mSv). Three percent of the patients had 10 or more brain CT scans and exceeded the organ radiation dose threshold set by the International Commission on Radiological Protection for deterministic effects of the eye-lens. Although radiation patient doses from CT scans were in general relatively low, 187 patients received a high effective dose (>20 mSv) and 3% might develop cataract from cumulative doses to the eye lens.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2014

Quantum limits on optical phase estimation accuracy from classical rate-distortion theory

The classical information-theoretic lower bound on the distortion of a random variable upon transmission through a noisy channel is applied to quantum-optical phase estimation. An approach for obtaining Bayesian lower bounds on the phase estimation accuracy is described that employs estimates of the classical capacity of the relevant quantum-optical channels. The Heisenberg limit for lossless phase estimation is derived for arbitrary probe state and prior distributions of the phase, and shot-noise scaling of the phase accuracy is established in the presence of nonzero loss for a parallel entanglement-assisted strategy with a single probe mode.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2015

A tight distance-dependent estimator for screening three-center Coulomb integrals over Gaussian basis functions

A new estimator for three-center two-particle Coulomb integrals is presented. Our estimator is exact for some classes of integrals and is much more efficient than the standard Schwartz counterpart due to the proper account of distance decay. Although it is not a rigorous upper bound, the maximum degree of underestimation can be controlled by two adjustable parameters. We also give numerical evidence of the excellent tightness of the estimator. The use of the estimator will lead to increased efficiency in reduced-scaling one- and many-body electronic structure theories.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2015

Estimation of anisotropy parameters in organic-rich shale: Rock physics forward modeling approach

Anisotropy analysis becomes an important step in processing and interpretation of seismic data. One of the most important things in anisotropy analysis is anisotropy parameter estimation which can be estimated using well data, core data or seismic data. In seismic data, anisotropy parameter calculation is generally based on velocity moveout analysis. However, the accuracy depends on data quality, available offset, and velocity moveout picking. Anisotropy estimation using seismic data is needed to obtain wide coverage of particular layer anisotropy. In anisotropic reservoir, analysis of anisotropy parameters also helps us to better understand the reservoir characteristics. Anisotropy parameters, especially ε, are related to rock property and lithology determination. Current research aims to estimate anisotropy parameter from seismic data and integrate well data with case study in potential shale gas reservoir. Due to complexity in organic-rich shale reservoir, extensive study from different disciplines is needed to understand the reservoir. Shale itself has intrinsic anisotropy caused by lamination of their formed minerals. In order to link rock physic with seismic response, it is necessary to build forward modeling in organic-rich shale. This paper focuses on studying relationship between reservoir properties such as clay content, porosity and total organic content with anisotropy. Organic content which defines prospectivity of shale gas can be considered as solid background or solid inclusion or both. From the forward modeling result, it is shown that organic matter presence increases anisotropy in shale. The relationships between total organic content and other seismic properties such as acoustic impedance and Vp/Vs are also presented.

58 GEOSCIENCES↗
DOE OSTI2016

Neutral gas temperature estimates and metastable resonance energy transfer for argon-nitrogen discharges

Rovibrational spectroscopy band fitting of the nitrogen (N{sub 2}) second positive system is a technique used to estimate the neutral gas temperature of N{sub 2} discharges, or atomic discharges with trace amounts of a N{sub 2} added. For mixtures involving argon and N{sub 2}, resonant energy transfer between argon metastable atoms (Ar*) and N{sub 2} molecules may affect gas temperature estimates made using the second positive system. The effect of Ar* resonance energy transfer is investigated here by analyzing neutral gas temperatures of argon-N{sub 2} mixtures, for N{sub 2} percentages from 1% to 100%. Neutral gas temperature estimates are higher than expected for mixtures involving greater than 5% N{sub 2} addition, but are reasonable for argon with less than 5% N{sub 2} addition when compared with an analytic model for ion-neutral charge exchange collisional heating. Additional spatiotemporal investigations into neutral gas temperature estimates with 10% N{sub 2} addition demonstrate that although absolute temperature values may be affected by Ar* resonant energy transfer, spatiotemporal trends may still be used to accurately diagnose the discharge.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2016

A novel technique for real-time estimation of edge pedestal density gradients via reflectometer time delay data

A new model-based technique for fast estimation of the pedestal electron density gradient has been developed. The technique uses ordinary mode polarization profile reflectometer time delay data and does not require direct profile inversion. Because of its simple data processing, the technique can be readily implemented via a Field-Programmable Gate Array, so as to provide a real-time density gradient estimate, suitable for use in plasma control systems such as envisioned for ITER, and possibly for DIII-D and Experimental Advanced Superconducting Tokamak. The method is based on a simple edge plasma model with a linear pedestal density gradient and low scrape-off-layer density. By measuring reflectometer time delays for three adjacent frequencies, the pedestal density gradient can be estimated analytically via the new approach. Using existing DIII-D profile reflectometer data, the estimated density gradients obtained from the new technique are found to be in good agreement with the actual density gradients for a number of dynamic DIII-D plasma conditions.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2018

A tesselation-based model for intensity estimation and laser plasma interactions calculations in three dimensions

Here, a three-dimensional laser propagation model for computation of laser-plasma interactions is presented. It is focused on indirect drive geometries in inertial confinement fusion and formulated for use at large temporal and spatial scales. A modified tesselation-based estimator and a relaxation scheme are used to estimate the intensity distribution in plasma from geometrical optics rays. Comparisons with reference solutions show that this approach is well-suited to reproduce realistic 3D intensity field distributions of beams smoothed by phase plates. It is shown that the method requires a reduced number of rays compared to traditional rigid-scale intensity estimation. Using this field estimator, we have implemented laser refraction, inverse-bremsstrahlung absorption, and steady-state crossed-beam energy transfer with a linear kinetic model in the numerical code VAMPIRE. Probe beam amplification and laser spot shapes are compared with experimental results and pf3d paraxial simulations. These results are promising for the efficient and accurate computation of laser intensity distributions in holhraums, which is of importance for determining the capsule implosion shape and risks of laser-plasma instabilities such as hot electron generation and backscatter in multi-beam configurations.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2025

Spatially and temporally resolved plasma parameter estimations of laser heated MagLIF relevant gas pipes at NIF

The ability to control laser pre-heat is an integral part of the inertial confinement fusion concept known as Magnetized Liner Inertial Fusion. This process is studied at the National Ignition Facility (NIF) where 4 of the 192 laser beams are propagated through a 1-cm long gas cell where they deposit >20 kJ of energy into the gaseous fuel via inverse bremsstrahlung absorption. This process ionizes the gas, producing a plasma that follows behind the laser front and expands over the radius of the cell. Emission from this plasma, as viewed by a gated x-ray detector, can be used to build spatially and temporally resolved estimations of the pre-heat plasma's density and temperature profiles. This can then be used to estimate the plasma pressure, internal energy, and radiation losses. Estimations show the evolution of the plasma in magnetized and unmagnetized gas cells filled with ambient temperature neopentane (C5H12) +1% Ar, as well as unmagnetized cryogenically cooled (32 K) deuterium +1% Ne filled targets. This analysis shows the effects of initial gas-fill density, composition, and axial magnetization on the time-dependent plasma parameters. Previously, these parameters at the NIF had not been experimentally characterized, and these estimations provided a potential new means of testing radiation magneto-hydrodynamic predictive capability models. Results in unmagnetized targets have strong agreement with simulations. However, in targets with a 19 T applied axial magnetic field, this method yields electron temperatures up to 100% hotter than those predicted by HYDRA codes.

Bremsstrahlung↗
DOE OSTI2020

Accuracy of the duration estimates of ultrashort laser pulses using a single-shot second-order intensity autocorrelator

The accuracy of estimating the duration of single-cycle laser pulses with centre wavelengths of 910 and 780 nm is analysed using a single-shot second-order intensity autocorrelator. It is shown that estimates of the single-cycle pulse duration with an error of less than 5 % require the use of KDP crystals with a thickness of no more than 10 μm for the second harmonic generation. At the same time, to estimate the duration of a transform-limited pulse containing ten optical cycles, the crystal thickness can be up to 1 mm. In this case, at an optimum angle of convergence of the first-harmonic beams, the duration estimation error is less than 2 %. (paper)

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2019

Metalearners for estimating heterogeneous treatment effects using machine learning

There is growing interest in estimating and analyzing heterogeneous treatment effects in experimental and observational studies. We describe a number of metaalgorithms that can take advantage of any supervised learning or regression method in machine learning and statistics to estimate the conditional average treatment effect (CATE) function. Metaalgorithms build on base algorithms—such as random forests (RFs), Bayesian additive regression trees (BARTs), or neural networks—to estimate the CATE, a function that the base algorithms are not designed to estimate directly. We introduce a metaalgorithm, the X-learner, that is provably efficient when the number of units in one treatment group is much larger than in the other and can exploit structural properties of the CATE function. For example, if the CATE function is linear and the response functions in treatment and control are Lipschitz-continuous, the X-learner can still achieve the parametric rate under regularity conditions. We then introduce versions of the X-learner that use RF and BART as base learners. In extensive simulation studies, the X-learner performs favorably, although none of the metalearners is uniformly the best. In two persuasion field experiments from political science, we demonstrate how our X-learner can be used to target treatment regimes and to shed light on underlying mechanisms. A software package is provided that implements our methods.

42 ENGINEERING↗