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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 775 records · Page 43
All sourcesNASA NTRSDOE OSTI
DOE OSTI2010

Sea quark flavor asymmetry of hadrons in statistical balance model

We suggested a Monte Carlo approach to simulate a kinetic equilibrium ensemble, and proved the equivalence to the linear equations method on equilibrium. With the convenience of the numerical method, we introduced variable splitting rates representing the details of the dynamics as model parameters which were not considered in previous works. The dependence on model parameters was studied, and it was found that the sea quark flavor asymmetry weakly depends on model parameters. It reflects the statistics principle, contributes the dominant part of the asymmetry, and the effect caused by details of the dynamics is small. We also applied the Monte Carlo approach of the statistical model to predict the theoretical sea quark asymmetries in kaons, octet baryons {Sigma}, {Xi}, and {Delta} baryons, even in exotic pentaquark states.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2011

Statistical properties of cosmological billiards

Belinski, Khalatnikov, and Lifshitz pioneered the study of the statistical properties of the never-ending oscillatory behavior (among successive Kasner epochs) of the geometry near a spacelike singularity. We show how the use of a 'cosmological billiard' description allows one to refine and deepen the understanding of these statistical properties. Contrary to previous treatments, we do not quotient the dynamics by its discrete symmetry group (of order 6), thereby uncovering new phenomena, such as correlations between the successive billiard corners in which the oscillations take place. Starting from the general integral invariants of Hamiltonian systems, we show how to construct invariant measures for various projections of the cosmological-billiard dynamics. In particular, we exhibit, for the first time, a (non-normalizable) invariant measure on the 'Kasner circle' which parametrizes the exponents of successive Kasner epochs. Finally, we discuss the relation between: (i) the unquotiented dynamics of the Bianchi-IX (a, b, c or mixmaster) model; (ii) its quotienting by the group of permutations of (a, b, c); and (iii) the billiard dynamics that arose in recent studies suggesting the hidden presence of Kac-Moody symmetries in cosmological billiards.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2011

Coherent combination of baryon acoustic oscillation statistics and peculiar velocity measurements from redshift surveys

A new statistical method is proposed to coherently combine baryon acoustic oscillation statistics (BAO) and peculiar velocity measurements exploiting decomposed density-density and velocity-velocity spectra in real space from the observed redshift distortions in redshift space, 1) to achieve stronger dark energy constraints, {sigma}(w)=0.06 and {sigma}(w{sub a})=0.20, which are enhanced from BAO or velocity measurements alone, and 2) to cross-check consistency of dark energy constraints from two different approaches; BAO as geometrical measurements and peculiar velocity as large-scale structure formation observables. In addition to those advantages, as power spectra decomposition procedure is free from uncertainty of galaxy bias, this simultaneous fitting is an optimal method to extract cosmological parameters without any preassumption about galaxy bias.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2011

Statistical validation of event predictors: A comparative study based on the field of seizure prediction

The prediction of events is of substantial interest in many research areas. To evaluate the performance of prediction methods, the statistical validation of these methods is of utmost importance. Here, we compare an analytical validation method to numerical approaches that are based on Monte Carlo simulations. The comparison is performed in the field of the prediction of epileptic seizures. In contrast to the analytical validation method, we found that for numerical validation methods insufficient but realistic sample sizes can lead to invalid high rates of false positive conclusions. Hence we outline necessary preconditions for sound statistical tests on above chance predictions.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2015

Physics-based statistical learning approach to mesoscopic model selection

In materials science and many other research areas, models are frequently inferred without considering their generalization to unseen data. Here, we apply statistical learning using cross-validation to obtain an optimally predictive coarse-grained description of a two-dimensional kinetic nearest-neighbor Ising model with Glauber dynamics (GD) based on the stochastic Ginzburg-Landau equation (sGLE). The latter is learned from GD “training” data using a log-likelihood analysis, and its predictive ability for various complexities of the model is tested on GD “test” data independent of the data used to train the model on. Using two different error metrics, we perform a detailed analysis of the error between magnetization time trajectories simulated using the learned sGLE coarse-grained description and those obtained using the GD model. We show that both for equilibrium and out-of-equilibrium GD training trajectories, the standard phenomenological description using a quartic free energy does not always yield the most predictive coarse-grained model. Moreover, increasing the amount of training data can shift the optimal model complexity to higher values. Our results are promising in that they pave the way for the use of statistical learning as a general tool for materials modeling and discovery.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Full Counting Statistics of Charge in Chaotic Many-Body Quantum Systems

We investigate the full counting statistics of charge transport in U(1)-symmetric random unitary circuits. We consider an initial mixed state prepared with a chemical potential imbalance between the left and right halves of the system and study the fluctuations of the charge transferred across the central bond in typical circuits. Using an effective replica statistical mechanics model and a mapping onto an emergent classical stochastic process valid at large on-site Hilbert space dimension, we show that charge transfer fluctuations approach those of the symmetric exclusion process at long times, with subleading t –1/2 quantum corrections. Here, we discuss our results in the context of fluctuating hydrodynamics and macroscopic fluctuation theory of classical nonequilibrium systems and check our predictions against direct matrix-product state calculations.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2011

Statistical Characterization and Segmentation of Drusen in Fundus Images

Age related Macular Degeneration (AMD) is a disease of the retina associated with aging. AMD progression in patients is characterized by drusen, pigmentation changes, and geographic atrophy, which can be seen using fundus imagery. The level of AMD is characterized by standard scaling methods, which can be somewhat subjective in practice. In this work we propose a statistical image processing approach to segment drusen with the ultimate goal of characterizing the AMD progression in a data set of longitudinal images. The method characterizes retinal structures with a statistical model of the colors in the retina image. When comparing the segmentation results of the method between longitudinal images with known AMD progression and those without, the method detects progression in our longitudinal data set with an area under the receiver operating characteristics curve of 0.99.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

Extracting Resilience Metrics From Distribution Utility Data Using Outage and Restore Process Statistics

Resilience curves track the accumulation and restoration of outages during an event on an electric distribution grid. We show that a resilience curve generated from utility data can always be decomposed into an outage process and a restore process and that these processes generally overlap in time. We use many events in real utility data to characterize the statistics of these processes, and derive formulas based on these statistics for resilience metrics such as restore duration, customer hours not served, and outage and restore rates. The formulas express the mean value of these metrics as a function of the number of outages in the event. We also give a formula for the variability of restore duration, which allows us to predict a maximum restore duration with 95% confidence. Overall, we give a simple and general way to decompose resilience curves into outage and restore processes and then show how to use these processes to extract resilience metrics from standard distribution system data.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2025

The Statistical Spread of Transmission Outages on a Fast Protection Time Scale Based on Utility Data

When there is a fault, the protection system automatically removes one or more transmission lines on a fast time scale of less than one minute. The outaged lines form a pattern in the transmission network. We extract these patterns from utility outage data, determine some key statistics of these patterns, and then show how to generate new patterns consistent with these statistics. The generated patterns provide a new and easily feasible way to model the overall effect of the protection system at the scale of a large transmission system. This new data-driven generative modeling of protection is expected to contribute to simulations of disturbances in large grids so that they can better quantify the risk of blackouts. Analysis of the pattern sizes suggests an index that describes how much outages spread in the transmission network at the fast timescale.

Transmission↗
DOE OSTI2016

Blade Load Unsteadiness and Turbulence Statistics in an Actuator-Line Computed Turbine–Turbine Interaction Problem

The objective of this study is to investigate how different volumetric projection techniques used in actuator-line modeling affect the unsteady blade loads and wake turbulence statistics. The two techniques for the body-force projection radius are based on either (i) the grid spacing or (ii) the combination of grid spacing and an equivalent elliptic blade planform. An array of two National Renewable Energy Laboratory 5-MW turbines separated by seven rotor diameters is simulated for 2000s (about rotor 300 revolutions) within a large-eddy simulation (LES) solver of the neutral and moderately convective atmospheric boundary layer (ABL). The statistics of sectional angle of attack (AOA), blade loads, and turbine power histories are quantified. Moreover, the degree of unsteadiness of sectional blade loads in response to atmospheric and wake turbulence is computed via a reduced frequency based on the rate-of-change in sectional AOA. Finally, the goal of this work is to make the wind energy community aware of the uncertainties associated with actuator-line modeling approaches.

17 WIND ENERGY↗
DOE OSTI2015

SU-E-T-659: Quantitative Evaluation of Patient Setup Accuracy of Stereotactic Radiotherapy with the Frameless 6D-ExacTrac System Using Statistical Modeling

Purpose: To evaluate patient setup accuracy and quantify individual and cumulative positioning uncertainties associated with different hardware and software components of the stereotactic radiotherapy (SRS/SRT) with the frameless-6D-ExacTrac system. Methods: A statistical model was used to evaluate positioning uncertainties of the different components of SRS/SRT treatment with the BrainLAB 6D-ExacTrac system using the positioning shifts of 35 patients having cranial lesions (49 total lesions treated in 1, 3, 5 fractions). All these patients were immobilized with rigid head-and-neck masks, simulated with BrainLAB-localizer and planned with iPlan treatment planning system. Infrared imaging (IR) was used initially to setup patients. Then, stereoscopic x-ray images (XC) were acquired and registered to corresponding digitally-reconstructed-radiographs using bony-anatomy matching to calculate 6D-translational and rotational shifts. When the shifts were within tolerance (0.7mm and 1°), treatment was initiated. Otherwise corrections were applied and additional x-rays were acquired (XV) to verify that patient position was within tolerance. Results: The uncertainties from the mask, localizer, IR-frame, x-ray imaging, MV and kV isocentricity were quantified individually. Mask uncertainty (Translational: Lateral, Longitudinal, Vertical; Rotational: Pitch, Roll, Yaw) was the largest and varied with patients in the range (−1.05−1.50mm, −5.06–3.57mm, −5.51−3.49mm; −1.40−2.40°, −1.24−1.74°, and −2.43−1.90°) obtained from mean of XC shifts for each patient. Setup uncertainty in IR positioning (0.88,2.12,1.40mm, and 0.64,0.83,0.96°) was extracted from standard-deviation of XC. Systematic uncertainties of the localizer (−0.03,−0.01,0.03mm, and −0.03,0.00,−0.01°) and frame (0.18,0.25,−1.27mm,−0.32,0.18, and 0.47°) were extracted from means of all XV setups and mean of all XC distributions, respectively. Uncertainties in isocentricity of the MV radiotherapy machine were (0.27,0.24,0.34mm) and kV-imager (0.15,−0.4,0.21mm). Conclusion: A statistical model was developed to evaluate the individual and cumulative systematic and random uncertainties induced by the different hardware and software components of the 6D-ExacTrac-system. The immobilization mask was associated with the largest positioning uncertainty.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2016

An efficient computational approach to model statistical correlations in photon counting x-ray detectors

Purpose: To introduce and evaluate an increment matrix approach (IMA) describing the signal statistics of energy-selective photon counting detectors including spatial–spectral correlations between energy bins of neighboring detector pixels. The importance of the occurring correlations for image-based material decomposition is studied. Methods: An IMA describing the counter increase patterns in a photon counting detector is proposed. This IMA has the potential to decrease the number of required random numbers compared to Monte Carlo simulations by pursuing an approach based on convolutions. To validate and demonstrate the IMA, an approximate semirealistic detector model is provided, simulating a photon counting detector in a simplified manner, e.g., by neglecting count rate-dependent effects. In this way, the spatial–spectral correlations on the detector level are obtained and fed into the IMA. The importance of these correlations in reconstructed energy bin images and the corresponding detector performance in image-based material decomposition is evaluated using a statistically optimal decomposition algorithm. Results: The results of IMA together with the semirealistic detector model were compared to other models and measurements using the spectral response and the energy bin sensitivity, finding a good agreement. Correlations between the different reconstructed energy bin images could be observed, and turned out to be of weak nature. These correlations were found to be not relevant in image-based material decomposition. An even simpler simulation procedure based on the energy bin sensitivity was tested instead and yielded similar results for the image-based material decomposition task, as long as the fact that one incident photon can increase multiple counters across neighboring detector pixels is taken into account. Conclusions: The IMA is computationally efficient as it required about 10{sup 2} random numbers per ray incident on a detector pixel instead of an estimated 10{sup 8} random numbers per ray as Monte Carlo approaches would need. The spatial–spectral correlations as described by IMA are not important for the studied image-based material decomposition task. Respecting the absolute photon counts and thus the multiple counter increases by a single x-ray photon, the same material decomposition performance could be obtained with a simpler detector description using the energy bin sensitivity.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2016

WE-AB-202-04: Statistical Evaluation of Lung Function Using 4DCT Ventilation Imaging: Proton Therapy VS IMRT

Purpose: Variation in function of different lung regions has been ignored so far for conventional lung cancer treatment planning, which may lead to higher risk of radiation induced lung disease. 4DCT based lung ventilation imaging provides a novel yet convenient approach for lung functional imaging as 4DCT is taken as routine for lung cancer treatment. Our work aims to evaluate the impact of accounting for spatial heterogeneity in lung function using 4DCT based lung ventilation imaging for proton and IMRT plans. Methods: Six patients with advanced stage lung cancer of various tumor locations were retrospectively evaluated for the study. Proton and IMRT plans were designed following identical planning objective and constrains for each patient. Ventilation images were calculated from patients’ 4DCT using deformable image registration implemented by Velocity AI software based on Jacobian-metrics. Lung was delineated into two function level regions based on ventilation (low and high functional area). High functional region was defined as lung ventilation greater than 30%. Dose distribution and statistics in different lung function area was calculated for patients. Results: Variation in dosimetric statistics of different function lung region was observed between proton and IMRT plans. In all proton plans, high function lung regions receive lower maximum dose (100.2%–108.9%), compared with IMRT plans (106.4%–119.7%). Interestingly, three out of six proton plans gave higher mean dose by up to 2.2% than IMRT to high function lung region. Lower mean dose (lower by up to 14.1%) and maximum dose (lower by up to 9%) were observed in low function lung for proton plans. Conclusion: A systematic approach was developed to generate function lung ventilation imaging and use it to evaluate plans. This method hold great promise in function analysis of lung during planning. We are currently studying more subjects to evaluate this tool.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2016

Statistical theory of diffusion in concentrated bcc and fcc alloys and concentration dependencies of diffusion coefficients in bcc alloys FeCu, FeMn, FeNi, and FeCr

The statistical theory of diffusion in concentrated bcc and fcc alloys with arbitrary pairwise interatomic interactions based on the master equation approach is developed. Vacancy–atom correlations are described using both the second-shell-jump and the nearest-neighbor-jump approximations which are shown to be usually sufficiently accurate. General expressions for Onsager coefficients in terms of microscopic interatomic interactions and some statistical averages are given. Both the analytical kinetic mean-field and the Monte Carlo methods for finding these averages are described. The theory developed is used to describe sharp concentration dependencies of diffusion coefficients in several iron-based alloy systems. For the bcc alloys FeCu, FeMn, and FeNi, we predict the notable increase of the iron self-diffusion coefficient with solute concentration c, up to several times, even though values of c possible for these alloys do not exceed some percent. For the bcc alloys FeCr at high temperatures T ≳ 1400 K, we show that the very strong and peculiar concentration dependencies of both tracer and chemical diffusion coefficients observed in these alloys can be naturally explained by the theory, without invoking exotic models discussed earlier.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2012

Statistical properties of excited nuclei in the mass range 47 Less-Than-Or-Slanted-Equal-To A Less-Than-Or-Slanted-Equal-To 59

Level densities and their energy dependences for nuclei in the mass range of 47 {<=} A {<=} 59 were determined from the results obtained by measuring neutron-evaporation spectra in respective (p, n) reactions. The spectra of neutrons originating from the (p, n) reactions on {sup 47}Ti, {sup 48}Ti, {sup 49}Ti, {sup 53}Cr, {sup 54}Cr, {sup 57}Fe, and {sup 59}Co nuclei were measured in the proton-energy range of 7-11 MeV. These measurements were performed with the aid of a fast-neutron spectrometer by the time-of-flight method over the base of the EGP-15 pulsed tandem accelerator installed at the Institute for Physics and Power Engineering (Obninsk, Russia). A high resolution of the spectrometer and its stability in the time of flight made it possible to identify reliably discrete low-lying levels along with the continuum part of neutron spectra. Our measured data were analyzed within the statistical equilibrium and preequilibrium models of nuclear reactions. The respective calculations were performed with the aid of the Hauser-Feshbach formalismof statistical theory supplemented with the generalized model of a superfluid nucleus, the back-shifted Fermi gas model, and the Gilbert-Cameron composite formula for nuclear level densities. Nuclear level densities for {sup 47}V, {sup 48}V, {sup 49}V, {sup 53}Mn, {sup 54}Mn, {sup 57}Co, and {sup 59}Ni and their energy dependences were determined. The results are discussed and compared with available experimental data and with recommendations of model-based systematics.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2012

Statistical Simulation of the Performance and Degradation of a PEMFC Membrane Electrode Assembly

A 1-D MEA Performance model was developed that considered transport of liquid water, agglomerate catalyst structure, and the statistical variation of the MEA characteristic parameters. The model was validated against a low surface area carbon supported catalyst across various platinum loadings and operational conditions. The statistical variation was found to play a significant role in creating noise in the validation data and that there was a coupling effect between movement in material properties with liquid water transport. Further, in studying the low platinum loaded catalyst layers it was found that liquid water played a significant role in the increasing the overall transport losses. The model was then further applied to study platinum dissolution via potential cycling accelerated stress tests, in which the platinum was found to dissolve nearest the membrane effectively resulting in reaction distribution shifts within the layer.

08 HYDROGEN↗
DOE OSTI2021

Challenging Practices of Algebraic Battery Life Models through Statistical Validation and Model Identification via Machine-Learning

Various modeling techniques are used to predict the capacity fade of Li-ion batteries. Algebraic reduced-order models, which are inherently interpretable and computationally fast, are ideal for use in battery controllers, technoeconomic models, and multi-objective optimizations. For Li-ion batteries with graphite anodes, solid-electrolyte-interphase (SEI) growth on the graphite surface dominates fade. This fade is often modeled using physically informed equations, such as square-root of time for predicting solvent-diffusion limited SEI growth, and Arrhenius and Tafel-like equations predicting the temperature and state-of-charge rate dependencies. In some cases, completely empirical relationships are proposed. However, statistical validation is rarely conducted to evaluate model optimality, and only a handful of possible models are usually investigated. This article demonstrates a novel procedure for automatically identifying reduced-order degradation models from millions of algorithmically generated equations via bi-level optimization and symbolic regression. Identified models are statistically validated using cross-validation, sensitivity analysis, and uncertainty quantification via bootstrapping. On a LiFePO 4 /Graphite cell calendar aging data set, automatically identified models utilizing square-root, power law, stretched exponential, and sigmoidal functions result in greater accuracy and lower uncertainty than models identified by human experts, and demonstrate that previously known physical relationships can be empirically "rediscovered" using machine learning.

25 ENERGY STORAGE↗
DOE OSTI2026

Object-Based Evaluation of Dynamical and Statistical Downscaled Precipitation Products over CONUS

High-resolution precipitation data, generated through dynamical downscaling (DD) or statistical downscaling (SD) of global climate model output, provide critical information for regional climate assessment and adaptation planning. Most downscaling development and validation have focused on accurate gridscale precipitation construction and ignored the spatial structure of precipitation across model grids and at the event scale. However, many applications, e.g., hydrologic modeling and the analysis using the downscaled precipitation, require a reasonable representation of the spatial structure of precipitation within watersheds. Therefore, a set of standard metrics to evaluate the representation of the spatial structure of individual storms across diverse downscaled precipitation products is desired. To address this need, we conducted an object-based evaluation of precipitation in decades-long DD and SD products over the contiguous United States (CONUS). Specifically, we evaluate their ability to reproduce various features of precipitation objects in the observations: total volume, precipitation area, peak intensity, and spatial structure. Multiple metrics (bias, Perkins score, and nonparametric statistical tests) are used to quantify model performance. Our evaluation reveals notable variations in performance among individual products across different climate zones and seasons, as well as between extreme and nonextreme events. In general, most DD products exhibit balanced performance across the four precipitation object features, while SD products vary more significantly in their performance across products. Based on this comprehensive evaluation, we provide guidance on choosing downscaled products for specific regions, seasons, and precipitation object features. These findings and recommendations can inform precipitation-relevant modeling and analysis over CONUS, guide future downscaling technique developments, and provide actionable information for climate impact assessment and adaptation.

Downscaling↗