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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 109 records · Page 6
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Validation of the two-region Rossi-alpha model for reflected assemblies

Nuclear criticality safety, nonproliferation and safeguards, emergency response, and stockpile stewardship utilize estimates of the k eff multiplication factor. The value of k eff cannot be directly measured, but it can be inferred from the prompt neutron period. One modality of measuring the prompt neutron period is the Rossi-alpha method, which is predicated on fitting a histogram of detection time differences due to the nonrandom temporal distribution of same-fission-chain neutrons. Recent works have developed the motivation and theory to expand traditional one-region point kinetic models resulting in one-exponential histogram fits to two-region models that result in two-exponential fits. This paper validates the new two-region model using organic scintillator measurements of copper-reflected weapons-grade plutonium (0:83 ≤ k eff ≤ 0:94) and high-density- polyethylene-reflected highly enriched uranium (0:73 ≤ k eff ≤ 0:95). Furthermore, the results show that more thermal systems have shorter prompt neutron periods in the core region due to increased induced-fission probabilities for moderated neutrons. Here, a new parameter introduced by the two- region model is also shown to be correlated to the amount of reflection, and may be used to infer assembly properties such as type and amount of reflector.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2017

A STUDY OF CHANGES IN DEFORMATION AND METABOLISM IN LEFT VENTRICLE AS A FUNCTION OF HYPERTROPHY IN SPONTANEOUS HYPERTENSIVE RATS USING MICROPET TECHNOLOGY

Problem: In the case of hypertrophy caused by pressure overload (hypertension) there is an increase in cardiac mass and modification cardiac metabolism. Aim: This study was designed to study the changes in glucose metabolism, ejection fraction, and deformation in the left ventricle with the progression of hypertrophy in spontaneous hypertensive rats (SHR). Methods: Dynamic PET data were acquired using the microPET II at UC Davis. Two rats were imaged at 10-week intervals for 18 months. Each time a dose of approximately 1- 1.5 mCi of F-18-FDG was injected into a normotensive Wistar Kyoto (WKY) rat and the same dose was injected into a SHR rat. Each rat was imaged using a gated dynamic acquisition for 80 minutes acquiring list mode data with cardiac gating of approximately 600-900 million total counts. For the analysis of glucose of metabolism, the list mode data were histogrammed into a dynamic sequence (42 frames over 80 mins). For each time frame, projection data of 1203 140x210 sinograms of 0.582 mm bins were formed by summing the last three gates before and one after the R-wave trigger to correspond to the diastolic phase of the cardiac cycle. Dynamic sequences of 128x128x83 matrices of 0.4x0.4x0.582 mm3 voxels in x, y, and z were reconstructed using an iterative MAP reconstruction which used a prior that penalized the high frequency components of the reconstruction using appropriate weighting between 26 nearest neighboring voxels. Time activity curves were generated from the dynamic reconstructed sequence for the blood and left ventricular tissue regions of interest which were fit to a 2-compartment model to obtain a least squares fit for the kinetic parameters. For the analysis of deformation, the list mode data were histogrammed into 8 gates of the cardiac cycle, each gate was the total sum of the later 60 mins of the 80 min acquisition. Images of 128x128x83 matrices for each gate were reconstructed using the same iterative MAP reconstruction used to reconstruct the dynamic sequence. The in-plane image dimensions were doubled to 256x256x83 in order to increase the resolution for the Warping analyses. These image data sets were then cropped to 128x128x83. The end-systolic image data sets were designated as the template images and the end-diastole image data sets were designated as the target images, thus providing an analysis of the diastolic relaxation and filling phases of the cardiac cycle. The template images were manually segmented to create surface definitions representing the epi- and endocardial surfaces. Finite element models of the left ventricles were created using the segmented surfaces and defining a transversely isotropic material with fiber angles varying from the epicardial surface to the endocardial surface. A Warping analyses was performed to obtain the LV strain tensor and fiber stretch distributions. Results: In one study, the average first principal Green-Lagrange strain, fiber stretch, ejection fraction, and metabolic rate of F-18-FDG was 0.22, 1.08, 80%, 0.1 for the WKY rat and 0.16, 1.06, 50%, 0.25 for the SHR rat, respectively. These same rats studied a year later presented with a metabolic rate of F-18-FDG of 0.11 and 0.25 for the WKY and SHR, respectively. A follow-up study the average strain (n=10) and ejection fraction (n=18) was 0.21, 72.7% for WKY and 0.17, 69.8% for the SHR, respectively. Conclusion: In the case of pressure overload there is an increased reliance on carbohydrate oxidation in an attempt to maintain contractile function.

Sitek, Arkadiusz↗
DOE OSTI2024

On the instrument-dependent appearance of ion dissociation events in atom probe tomography mass spectra

The successful application of atom probe tomography (APT) relies on the accurate interpretation of the mass spectrum (i.e. m/z histogram) from a sample. Some materials yield mass spectra that are amenable to a straightforward peak assignment/ranging, however, there are many materials that produce mass spectra with features that defy simple interpretation. One such example is Ga 2 O 3 which yields mass spectra containing several broad and difficult to interpret features. Herein, we study the GaO 2+ → O 1+ + Ga 1+ dissociation and we explain how this dissociation process gives rise to broad and previously unassigned features in the mass spectrum. Trajectory simulations are performed for the dissociation reaction utilizing realistic electrostatic models and compared to experiments using commercially available straight flight and reflectron based local electrode (LE) APT instruments. It is shown that the appearance of these features is strongly dependent on the specific design of the time-of-flight (ToF) mass analyzer. Additionally, we explore how various experimental parameters can affect the appearance of the dissociation process in the one-dimensional (1D) mass spectrum and in the two-dimensional (2D) correlation histogram. While the focus of this work is on a particular dissociation process related to Ga 2 O 3 , the understanding gained in the course of these simulations and experiments should be applicable to the interpretation of dissociation processes in other materials.

47 OTHER INSTRUMENTATION↗
DOE OSTI2016

Planck intermediate results: XLIV. Structure of the Galactic magnetic field from dust polarization maps of the southern Galactic cap

Using data from the Planck satellite, we study in this paper the statistical properties of interstellar dust polarization at high Galactic latitudes around the south pole (b < -60°). Our aim is to advance the understanding of the magnetized interstellar medium (ISM), and to provide a modelling framework of the polarized dust foreground for use in cosmic microwave background (CMB) component-separation procedures. We examine the Stokes I, Q, and U maps at 353 GHz, and particularly the statistical distribution of the polarization fraction (p) and angle (ψ), in order to characterize the ordered and turbulent components of the Galactic magnetic field (GMF) in the solar neighbourhood. The Q and U maps show patterns at large angular scales, which we relate to the mean orientation of the GMF towards Galactic coordinates (l 0 ,b 0 ) = (70° ± 5°,24° ± 5°). The histogram of the observed p values shows a wide dispersion up to 25%. The histogram of ψ has a standard deviation of 12° about the regular pattern expected from the ordered GMF. We build a phenomenological model that connects the distributions of p and ψ to a statistical description of the turbulent component of the GMF, assuming a uniform effective polarization fraction (p 0 ) of dust emission. To compute the Stokes parameters, we approximate the integration along the line of sight (LOS) as a sum over a set of N independent polarization layers, in each of which the turbulent component of the GMF is obtained from Gaussian realizations of a power-law power spectrum. We are able to reproduce the observed p and ψ distributions using a p 0 value of 26%, a ratio of 0.9 between the strengths of the turbulent and mean components of the GMF, and a small value of N. The mean value of p (inferred from the fit of the large-scale patterns in the Stokes maps) is 12 ± 1%. We relate the polarization layers to the density structure and to the correlation length of the GMF along the LOS. We emphasize the simplicity of our model (involving only a few parameters), which can be easily computed on the celestial sphere to produce simulated maps of dust polarization. Finally, our work is an important step towards a model that can be used to assess the accuracy of component-separation methods in present and future CMB experiments designed to search the B mode CMB polarization from primordial gravity waves.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2023

Fast correlation function calculator: A high-performance pair-counting toolkit

A novel high-performance exact pair-counting toolkit called fast correlation function calculator (FCFC) is presented. With the rapid growth of modern cosmological datasets, the evaluation of correlation functions with observational and simulation catalogues has become a challenge. High-efficiency pair-counting codes are thus in great demand. We introduce different data structures and algorithms that can be used for pair-counting problems, and perform comprehensive benchmarks to identify the most efficient algorithms for real-world cosmological applications. We then describe the three levels of parallelisms used by FCFC, SIMD, OpenMP, and MPI, and run extensive tests to investigate the scalabilities. Finally, we compare the efficiency of FCFC with alternative pair-counting codes. The data structures and histogram update algorithms implemented in FCFC are shown to outperform alternative methods. FCFC does not benefit greatly from SIMD because the bottleneck of our histogram update algorithm is mainly cache latency. Nevertheless, the efficiency of FCFC scales well with the numbers of OpenMP threads and MPI processes, even though speedups may be degraded with over a few thousand threads in total. FCFC is found to be faster than most (if not all) other public pair-counting codes for modern cosmological pair-counting applications.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2016

Free energy landscape and molecular pathways of gas hydrate nucleation

Despite the significance of gas hydrates in diverse areas, a quantitative knowledge of hydrate formation at a molecular level is missing. The impediment to acquiring this understanding is primarily attributed to the stochastic nature and ultra-fine scales of nucleation events, posing a great challenge for both experiment and simulation to explore hydrate nucleation. Here we employ advanced molecular simulation methods, including forward flux sampling (FFS), p{sub B} histogram analysis, and backward flux sampling, to overcome the limit of direct molecular simulation for exploring both the free energy landscape and molecular pathways of hydrate nucleation. First we test the half-cage order parameter (H-COP) which we developed for driving FFS, through conducting the p{sub B} histogram analysis. Our results indeed show that H-COP describes well the reaction coordinates of hydrate nucleation. Through the verified order parameter, we then directly compute the free energy landscape for hydrate nucleation by combining both forward and backward flux sampling. The calculated stationary distribution density, which is obtained independently of nucleation theory, is found to fit well against the classical nucleation theory (CNT). Subsequent analysis of the obtained large ensemble of hydrate nucleation trajectories show that although on average, hydrate formation is facilitated by a two-step like mechanism involving a gradual transition from an amorphous to a crystalline structure, there also exist nucleation pathways where hydrate crystallizes directly, without going through the amorphous stage. The CNT-like free energy profile and the structural diversity suggest the existence of multiple active transition pathways for hydrate nucleation, and possibly also imply the near degeneracy in their free energy profiles among different pathways. Our results thus bring a new perspective to the long standing question of how hydrates crystallize.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2018

Time filtering of event based neutron scattering data: A pathway to study the dynamic structural responses of materials

Time-resolved diffraction has become a vital tool for probing dynamic responses to an applied stimulus. Such experiments traditionally use hardware solutions to histogram measured data into their respective bin. We will show that a major advantage of event-based data acquisition, which time-stamps measured diffraction data with 100 ns accuracy, is much preferred over hardware histogramming of the data by enabling postprocessing for advanced custom binning using a software solution. This approach is made even more powerful by coupling measured diffraction data with metadata about the applied stimuli and material response. In this work, we present a time-filter approach that leverages the power of event-based diffraction collection to reduce stroboscopic data measured over many hours into equally weighted segments that represent subsets of the response to a single cycle of the applied stimulus. We demonstrate this approach by observing ferroelectric/ferroelastic domain wall motion during electric field cycling of BaTiO 3 . Furthermore, the developed approach can readily be expanded to investigate other dynamic phenomena using complex sample environments.

47 OTHER INSTRUMENTATION↗
DOE OSTI2025

An implementation of neural simulation-based inference for parameter estimation in ATLAS

Neural simulation-based inference (NSBI) is a powerful class of machine-learning-based methods for statistical inference that naturally handles high-dimensional parameter estimation without the need to bin data into low-dimensional summary histograms. Such methods are promising for a range of measurements, including at the Large Hadron Collider, where no single observable may be optimal to scan over the entire theoretical phase space under consideration, or where binning data into histograms could result in a loss of sensitivity. This work develops a NSBI framework for statistical inference, using neural networks to estimate probability density ratios, which enables the application to a full-scale analysis. It incorporates a large number of systematic uncertainties, quantifies the uncertainty due to the finite number of events in training samples, develops a method to construct confidence intervals, and demonstrates a series of intermediate diagnostic checks that can be performed to validate the robustness of the method. As an example, the power and feasibility of the method are assessed on simulated data for a simplified version of an off-shell Higgs boson couplings measurement in the four-lepton final states. This approach represents an extension to the standard statistical methodology used by the experiments at the Large Hadron Collider, and can benefit many physics analyses.

frequentist statistics↗
DOE OSTI2025

Discriminative versus generative approaches to simulation-based inference

Most of the fundamental, emergent, and phenomenological parameters of particle and nuclear physics are determined through parametric template fits. Simulations are used to populate histograms which are then matched to data. This approach is inherently lossy, since histograms are binned and low-dimensional. Deep learning has enabled unbinned and high-dimensional parameter estimation through neural likelihood(-ratio) estimation. We compare two approaches for neural simulation-based inference (NSBI): one based on discriminative learning (classification) and one based on generative modeling. These two approaches are directly evaluated on the same datasets, with a similar level of hyperparameter optimization in both cases. In addition to a Gaussian dataset, we study NSBI using a Higgs boson dataset from the FAIR Universe Challenge. We find that both the direct likelihood and likelihood ratio estimation are able to effectively extract parameters with reasonable uncertainties. For the numerical examples and within the set of hyperparameters studied, we found that the likelihood ratio method is more accurate and/or precise. Both methods have a significant spread from the network training and would require ensembling or other mitigation strategies in practice.

high energy physics↗
DOE OSTI2023

High-energy synchrotron flares powered by strongly radiative relativistic magnetic reconnection: 2D and 3D PIC simulations

ABSTRACT The time evolution of high-energy synchrotron radiation generated in a relativistic pair plasma energized by reconnection of strong magnetic fields is investigated with 2D and 3D particle-in-cell (PIC) simulations. The simulations in this 2D/3D comparison study are conducted with the radiative PIC code OSIRIS, which self-consistently accounts for the synchrotron radiation reaction on the emitting particles, and enables us to explore the effects of synchrotron cooling. Magnetic reconnection causes compression of the plasma and magnetic field deep inside magnetic islands (plasmoids), leading to an enhancement of the flaring emission, which may help explain some astrophysical gamma-ray flare observations. Although radiative cooling weakens the emission from plasmoid cores, it facilitates additional compression there, further amplifying the magnetic field B and plasma density n, and thus partially mitigating this effect. Novel simulation diagnostics utilizing 2D histograms in the n-B space are developed and used to visualize and quantify the effects of compression. The n-B histograms are observed to be bounded by relatively sharp power-law boundaries marking clear limits on compression. Theoretical explanations for some of these compression limits are developed, rooted in radiative resistivity or 3D kinking instabilities. Systematic parameter-space studies with respect to guide magnetic field, system size, and upstream magnetization are conducted and suggest that stronger compression, brighter high-energy radiation, and perhaps significant quantum electrodynamic effects such as pair production, may occur in environments with larger reconnection-region sizes and higher magnetization, particularly when magnetic field strengths approach the critical (Schwinger) field, as found in magnetar magnetospheres.

Schoeffler, K. M. (ORCID:0000000276447381)↗
DOE OSTI2021

Geometrical-Based Generative Adversarial Network to Enhance Digital Rock Image Quality

X-ray microcomputed tomography (micro-CT) is a common tool for the study of porous media structures and properties. High-quality micro-CT data are required to accurately capture pore structures. Acquiring high-quality micro-CT data, however, is not always possible, owing to application limitations and experimental constraints. Therefore, we propose a geometrical-based generative adversarial network (GAN) to rapidly restore noisy micro-CT images to their clean counterparts. The training data and related ground-truth (GT) data are scanned for 7 min and 9.5 h, respectively. To evaluate the performance of the geometrical-based GAN, a 6003 voxel image that has never been used for training is reconstructed and compared with the corresponding GT image. Histogram matching and linear normalization are implemented to adjust the histogram of the reconstructed image to that of the GT image. A watershed-based segmentation method is then applied to delineate pore and solid phases. Lastly, we measure the Minkowski functionals and petrophysical properties, including absolute permeability, pore size distribution, drainage capillary pressure-saturation curve, and imbibition relative permeability, to estimate the physical accuracy of the denoised image. The results show that the proposed geometrical-based GAN can accurately restore noisy micro-CT data. By reducing the scanning time from 9.5 h to 7 min, the expenditure of collecting micro-CT can be decreased significantly. This is particularly important for applications where time-lapse images of a dynamic process are required, high-throughput imaging is necessary for real-time data analysis, or where the quantification of large sample volumes is required.

58 GEOSCIENCES↗
DOE OSTI2023

MILK : a Python scripting interface to MAUD for automation of Rietveld analysis

Modern diffraction experiments ( e.g. in situ parametric studies) present scientists with many diffraction patterns to analyze. Interactive analyses via graphical user interfaces tend to slow down obtaining quantitative results such as lattice parameters and phase fractions. Furthermore, Rietveld refinement strategies ( i.e. the parameter turn-on-off sequences) tend to be instrument specific or even specific to a given dataset, such that selection of strategies can become a bottleneck for efficient data analysis. Managing multi-histogram datasets such as from multi-bank neutron diffractometers or caked 2D synchrotron data presents additional challenges due to the large number of histogram-specific parameters. To overcome these challenges in the Rietveld software Material Analysis Using Diffraction ( MAUD ), the MAUD Interface Language Kit ( MILK ) is developed along with an updated text batch interface for MAUD . The open-source software MILK is computer-platform independent and is packaged as a Python library that interfaces with MAUD . Using MILK , model selection ( e.g. various texture or peak-broadening models), Rietveld parameter manipulation and distributed parallel batch computing can be performed through a high-level Python interface. A high-level interface enables analysis workflows to be easily programmed, shared and applied to large datasets, and external tools to be integrated with MAUD . Through modification to the MAUD batch interface, plot and data exports have been improved. The resulting hierarchical folders from Rietveld refinements with MILK are compatible with Cinema: Debye–Scherrer , a tool for visualizing and inspecting the results of multi-parameter analyses of large quantities of diffraction data. In this manuscript, the combined Python scripting and visualization capability of MILK is demonstrated with a quantitative texture and phase analysis of data collected at the HIPPO neutron diffractometer.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2025

Bimodal Visualization of Industrial X-Ray and Neutron Computed Tomography Data

Advanced manufacturing creates increasingly complex objects with material compositions that are often difficult to characterize by a single modality. Our collaborating domain scientists are going beyond traditional methods by employing both X-ray and neutron computed tomography to obtain complementary representations expected to better resolve material boundaries. However, the use of two modalities creates its own challenges for visualization, requiring either complex adjustments of bimodal transfer functions or the need for multiple views. Together with experts in nondestructive evaluation, we designed a novel interactive bimodal visualization approach to create a combined view of the co-registered X-ray and neutron acquisitions of industrial objects. Using an automatic topological segmentation of the bivariate histogram of X-ray and neutron values as a starting point, the system provides a simple yet effective interface to easily create, explore, and adjust a bimodal visualization. Here, we propose a widget with simple brushing interactions that enables the user to quickly correct the segmented histogram results. Our semiautomated system enables domain experts to intuitively explore large bimodal datasets without the need for either advanced segmentation algorithms or knowledge of visualization techniques. We demonstrate our approach using synthetic examples, industrial phantom objects created to stress bimodal scanning techniques, and real-world objects, and we discuss expert feedback.

image segmentation↗
DOE OSTI2024

An Entropy-Based Test and Development Framework for Uncertainty Modeling in Level-Set Visualizations

We present a simple comparative framework for testing and developing uncertainty modeling in uncertain marching cubes implementations. The selection of a model to represent the probability distribution of uncertain values directly influences the memory use, run time, and accuracy of an uncertainty visualization algorithm. We use an entropy calculation directly on ensemble data to establish an expected result and then compare the entropy from various probability models, including uniform, Gaussian, histogram, and quantile models. Our results verify that models matching the distribution of the ensemble indeed match the entropy. We further show that fewer bins in nonparametric histogram models are more effective whereas large numbers of bins in quantile models approach data accuracy.

Sisneros, Robert↗
DOE OSTI2017

Multicanonical sampling of the space of states of ℋ(2, n)-vector models

Problems of temperature behavior of specific heat are solved by the entropy simulation method for Ising models on a simple square lattice and a square spin ice (SSI) lattice with nearest neighbor interaction, models of hexagonal lattices with short-range (SR) dipole interaction, as well as with long-range (LR) dipole interaction and free boundary conditions, and models of spin quasilattices with finite interaction radius. It is established that systems of a finite number of Ising spins with LR dipole interaction can have unusual thermodynamic properties characterized by several specific-heat peaks in the absence of an external magnetic field. For a parallel multicanonical sampling method, optimal schemes are found empirically for partitioning the space of states into energy bands for Ising and SSI models, methods of concatenation and renormalization of histograms are discussed, and a flatness criterion of histograms is proposed. It is established that there is no phase transition in a model with nearest neighbor interaction on a hexagonal lattice, while the temperature behavior of specific heat exhibits singularity in the same model, in case of LR interaction. A spin quasilattice is found that exhibits a nonzero value of residual entropy.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2017

Simulation of polarized optical radiation transport in time and frequency representations

Monte Carlo simulation of backward scattering of polarized optical radiation has been performed in the time and frequency representations based on the description of radiation transport in terms of the Bethe–Salpeter equation. The histograms of an ultrashort pulse of linearly or circularly polarized radiation have been calculated in the time representation; it is found that for distances between the source and detector on the order of the transport length, the histograms exhibit a strong dependence on the polarization type; in the case of circular polarization, the direction of the polarization plane rotation changes upon an increase in the scattering anisotropy.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2018

Formation of Radiation Defects by Proton Braking in Lightly Doped n- and p-SiC Layers

Mathematical simulation of the cascade of displacements in SiC is used to consider the specific features of Frenkel-pair generation upon the scattering of 8- and 15-MeV protons. The distribution histograms of energies acquired not only by primary knocked-out atoms, but also by recoil atoms generated in displacement cascades, are calculated. An analysis of the histograms considers two energy ranges. In the first range of “low” energies, the spontaneous recombination of genetically related Frenkel pairs is dominant. Recoil atoms in the second range have a higher energy, which enables these atoms to leave the spontaneousrecombination zone and dissociate into isolated components. The compensation of lightly doped n- and p-4H-SiC samples grown by gas-phase epitaxy is experimentally studied under irradiation with 8- and 15-MeV protons. The carrier removal rates are measured. The calculated and experimental data are compared and estimates are obtained for the size of the spontaneous-recombination zone.

36 MATERIALS SCIENCE↗
DOE OSTI2019

pnnl/rhizo_phosph

Python package to be used when working with the DDAO method of visualizing phosphatase activity in the rhizosphere. Includes a module with functions that generate figures for analysis of phosphatase levels in images of soil and root based on pixel intensity. These functions can be used on images with a single root or multiple roots. Figures include distance maps to show how phosphatase levels change as you move away from the root and along the roots themselves, line plots to show average phosphatase levels moving down the root and the soil surrounding the root, 2D histograms to show how phosphatase levels change moving away from the root, and 1D histograms to show overall differences in phosphatase distribution depending on whether a root was grown next to a phosphorus source or not.

McGrady, Monee↗