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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 253 records · Page 14
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Realizability-preserving discontinuous Galerkin method for spectral two-moment radiation transport in special relativity

Here we present a realizability-preserving numerical method for solving a spectral two-moment model to simulate the transport of massless, neutral particles interacting with a steady background material moving with relativistic velocities. The model is obtained as the special relativistic limit of a four-momentum-conservative general relativistic two-moment model. Using a maximum-entropy closure, we solve for the Eulerian-frame energy and momentum. The proposed numerical method is designed to preserve moment realizability, which corresponds to moments defined by a nonnegative phase-space density. The realizability-preserving method is achieved with the following key components: (i) a discontinuous Galerkin phase-space discretization with specially constructed numerical fluxes in the spatial and energy dimensions; (ii) a strong stability-preserving implicit-explicit time-integration method; (iii) a realizability-preserving conserved to primitive moment solver; (iv) a realizability-preserving implicit collision solver; and (v) a realizability-enforcing limiter. Component (iii) is necessitated by the closure procedure, which closes higher order moments nonlinearly in terms of primitive moments. The nonlinear conserved to primitive and the implicit collision solves are formulated as fixed-point problems, which are solved with custom iterative solvers designed to preserve the realizability of each iterate. With a series of numerical tests, we demonstrate the accuracy and robustness of this discontinuous-Galerkin-implicit-explicit method.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2011

Charmonium spectral functions with the variational method in zero and finite temperature lattice QCD

We propose a method to evaluate spectral functions on the lattice based on a variational method. On a lattice with a finite spatial extent, spectral functions consist of discrete spectra only. Adopting a variational method, we calculate the locations and the heights of spectral functions at low-lying discrete spectra. We first test the method in the case of analytically solvable free Wilson quarks at zero and finite temperatures and confirm that the method well reproduces the analytic results for low-lying spectra. We find that we can systematically improve the results by increasing the number of trial states. We then apply the method to calculate the charmonium spectral functions for S and P-wave states at zero-temperature in quenched QCD and compare the results with those obtained using the conventional maximum entropy method (MEM). The results for the ground state are consistent with the location and the area of the first peak in spectral functions from the MEM, while the variational method leads to a mass which is closer to the experimental value for the first excited state. We also investigate the temperature dependence of the spectral functions for S-wave states below and above T{sub c}. We obtain no clear evidences for dissociation of J/{psi} and {eta}{sub c} up to 1.4T{sub c}.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2014

Zero Mode in a Strongly Coupled Quark Gluon Plasma

In connection with massless two-flavor QCD, we analyze the chiral symmetry restoring phase transition using three distinct gluon-quark vertices and two different assumptions about the long-range part of the quark-quark interaction. In each case, we solve the gap equation, locate the transition temperature T-c, and use the maximum entropy method to extract the dressed-quark spectral function at T>T-c. Our best estimate for the chiral transition temperature is T-c=147 +/- 8 MeV, and the deconfinement transition is coincident. For temperatures markedly above Tc, we find a spectral density that is consistent with those produced using a hard thermal loop expansion, exhibiting both a normal and plasmino mode. On a domain T is an element of[T-c, T-s] , with T-s approximate to 1.5T(c), however, with each of the six kernels we considered, the spectral function contains a significant additional feature. Namely, it displays a third peak, associated with a zero mode, which is essentially nonperturbative in origin and dominates the spectral function at T=Tc. We suggest that the existence of this mode is a signal for the formation of a strongly coupled quark-gluon plasma and that this strongly interacting state of matter is likely a distinctive feature of the QCD phase transition.

Gao, Fei↗
DOE OSTI2018

Stochastic reconstructions of spectral functions: Application to lattice QCD

Here, we present a detailed study of the applications of two stochastic approaches, stochastic optimization method (SOM) and stochastic analytical inference (SAI), to extract spectral functions from Euclidean correlation functions. SOM has the advantage that it does not require prior information. On the other hand, SAI is a more generalized method based on Bayesian inference. Under mean field approximation SAI reduces to the often-used maximum entropy method (MEM), and for a specific choice of the prior SAI becomes equivalent to SOM. To test the applicability of these two stochastic methods to lattice QCD, Firstly, we apply these methods to various reasonably chosen model correlation functions, and present detailed comparisons of the reconstructed spectral functions obtained from SOM, SAI and MEM. Next, we present similar studies for charmonia correlation functions obtained from lattice QCD computations using clover-improved Wilson fermions on large, fine, isotropic lattices at 0:75 and 1:5 T c , T c being the deconfinement transition temperature of a pure gluon plasma. We find that SAI and SOM give consistent results to MEM at these two temperatures.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2017

An in situ USAXS–SAXS–WAXS study of precipitate size distribution evolution in a model Ni-based alloy

Intermetallic γ' precipitates typically strengthen nickel-based superalloys. The shape, size and spatial distribution of strengthening precipitates critically influence alloy strength, while their temporal evolution characteristics determine the high-temperature alloy stability. Combined ultra-small-, small- and wide-angle X-ray scattering (USAXS–SAXS–WAXS) analysis can be used to evaluate the temporal evolution of an alloy's precipitate size distribution (PSD) and phase structure during in situ heat treatment. Analysis of PSDs from USAXS–SAXS data employs either least-squares fitting of a preordained PSD model or a maximum entropy (MaxEnt) approach, the latter avoiding a priori definition of a functional form of the PSD. However, strong low- q scattering from grain boundaries and/or structure factor effects inhibit MaxEnt analysis of typical alloys. Lastly, this work describes the extension of Bayesian–MaxEnt analysis methods to data exhibiting structure factor effects and low- q power law slopes and demonstrates their use in an in situ study of precipitate size evolution during heat treatment of a model Ni–Al–Si alloy.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Bayesian optimized collection strategies for fatigue strength testing

Abstract A statistical framework is presented enabling optimal sampling and analysis of constant life fatigue data. Protocols using Bayesian maximum entropy sampling are built based on conventional staircase and stress step methods, reducing the requirement of prior knowledge for data collection. The Bayesian Staircase method shows improved parameter estimation efficiency, and the Bayesian Stress Step method shows equal accuracy to the standard method at larger step size allowing experimentalists to lessen concerns of loading history. Statistical methods for determining model suitability are shown, highlighting the influence of protocol. Experimental validation is performed, showing the applicability of the methods in laboratory testing.

36 MATERIALS SCIENCE↗
DOE OSTI2015

WE-D-204-07: Development of An ImageJ Plugin for Renal Function Quantification: RenalQuant

Purpose: Commercial workstations usually have their own software to calculate dynamic renal functions. However, usually they have low flexibility and subjectivity on delimiting kidney and background areas. The aim of this paper is to present a public domain software, called RenalQuant, capable to semi-automatically draw regions of interest on dynamic renal scintigraphies, extracting data and generating renal function quantification parameters. Methods: The software was developed in Java and written as an ImageJ-based plugin. The preprocessing and segmentation steps include the user’s selection of one time frame with higher activity in kidney’s region, compared with background, and low activity in the liver. Next, the chosen time frame is smoothed using a Gaussian low pass spatial filter (σ = 3) for noise reduction and better delimitation of kidneys. The maximum entropy thresholding method is used for segmentation. A background area is automatically placed below each kidney, and the user confirms if these regions are correctly segmented and positioned. Quantitative data are extracted and each renogram and relative renal function (RRF) value is calculated and displayed. Results: RenalQuant plugin was validated using retrospective 20 patients’ 99mTc-DTPA exams, and compared with results produced by commercial workstation software, referred as reference. The renograms intraclass correlation coefficients (ICC) were calculated and false-negative and false-positive RRF values were analyzed. The results showed that ICC values between RenalQuant plugin and reference software for both kidneys’ renograms were higher than 0.75, showing excellent reliability. Conclusion: Our results indicated RenalQuant plugin can be trustingly used to generate renograms, using DICOM dynamic renal scintigraphy exams as input. It is user friendly and user’s interaction occurs at a minimum level. Further studies have to investigate how to increase RRF accuracy and explore how to solve limitations in the segmentation step, mainly when background region has higher activity compared to kidneys. Financial support by CAPES.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2012

Comparison of electronic structure of as grown and solar grade silicon samples

A comparison of the electronic structure of two different types of silicon materials viz., (i) as grown silicon and (ii) solar silicon has been carried out utilizing maximum entropy method and pair distribution function using powder X-ray data sets. The precise electron density maps have been elucidated for the two samples. The covalent nature of the bonding between atoms in both the samples is found to be well pronounced and clearly seen from the electron density maps. The electron densities at the middle of the Si-Si bond are found to be 0.47 and 0.45 e/A{sup 3} for as grown silicon and solar silicon respectively. In this work, the local structural information has also been obtained by analyzing the atomic pair distribution functions of these two samples.

36 MATERIALS SCIENCE↗
DOE OSTI2018

Oscillations and Waves in a Nonlinear System with the 1/f Spectrum

Numerical methods are used to study a spatially distributed system of two nonlinear stochastic equations that simulate interacting phase transitions. Conditions for self-oscillations and waves are determined. The 1/f and 1/k spectra of extreme fluctuations are formed when waves emerge and move under the action of white noise. The distribution of the extreme fluctuations corresponds to the maximum entropy, which is proven by the stability of the 1/f and 1/k spectra. The formation and motion of waves under external periodic perturbation are accompanied by spatiotemporal chaotic resonance in which the domain of periodic pulsations is extended under the action of white noise.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2025

Intelligent Sampling of Extreme-Scale Turbulence Datasets for Accurate and Efficient Spatiotemporal Model Training

With the end of Moore’s law and Dennard scaling, efficient training increasingly requires rethinking data volume. Can we train better models with significantly less data via intelligent subsampling? To explore this, we develop SICKLE, a sparse intelligent curation framework for efficient learning, featuring a novel maximum entropy (MaxEnt) sampling approach, scalable training, and energy benchmarking. We compare MaxEnt with random and phase-space sampling on large direct numerical simulation (DNS) datasets of turbulence. Evaluating SICKLE at scale on Frontier, we show that subsampling as a preprocessing step can, in many cases, improve model accuracy and substantially lower energy consumption, with observed reductions of up to 38×.

Brewer, Wes [ORNL] (ORCID:0000000236393956)↗
DOE OSTI2022

Correlating Crystallography, Magnetism, and Electronic Structure Across Anhysteretic First-Order Phase Transition in Pr 2 In

Here, temperature-dependent powder X-ray diffraction and magnetization measurements of Pr 2 In conclusively prove that the unusual anhysteretic first-order paramagnetic-ferromagnetic phase transition in the compound is related to concurrent changes in both the magnetic and crystallographic lattices. At the same time, the hexagonal Ni 2 In-type structure is stable at least between 6 and 298 K, including at T C = ~57 K. From the density functional theory calculations, the electronic structure of the compound is extraordinarily sensitive to minor changes in lattice parameters that occur across the phase transition, revealing the origin of strong magnetoelastic coupling. In the vicinity of T C , the maximum entropy change, ΔS Max = -16 J Kg -1 K -1 induced by a moderate magnetic field change of 20 kOe (ΔS Max = -20 J Kg -1 K -1 for 50 kOe magnetic field change) is comparable to other known potentially functional materials demonstrating large cryogenic magnetocaloric effect.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

PNNL-CompBio/BoltzmannMFX

BoltzmannMFX is a biological simulation code that solves chemical reaction networks using maximum entropy methods. It uses modules from MFiX-Exa and is based on the AMReX framework for massively parallel block-structured adaptive mesh applications.

Palmer, Bruce↗
DOE OSTI2026

Boundary-induced classical generalized Gibbs ensemble with angular momentum

We investigate how confinement geometry leads to the emergence of a Generalized Gibbs Ensemble (GGE) in classical systems. Unlike the standard Gibbs ensemble, the GGE includes additional conserved quantities, such as angular momentum, that arise from boundary-induced symmetries. Using analytical arguments based on the maximum entropy principle, we show that circular boundaries preserve angular momentum and drive the system toward a chiral, non-ergodic GGE that violates time-reversal symmetry. This ensemble differs fundamentally from the Gibbs case, producing near-boundary condensation and revealing how geometry alone can alter thermal equilibration. To quantify these effects, we introduce an order parameter measuring deviations from Gibbs behavior and demonstrate that conventional Monte Carlo methods must incorporate angular momentum conservation under such conditions. Our study highlights how geometric constraints shape non-equilibrium statistical ensembles and lead to subtle departures from the Bohr-van Leeuwen theorem. These predictions are validated through detailed simulations of confined classical hard-disk gases.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2022

An ecological niche model to predict the geographic distribution of Haemagogus janthinomys, Dyar, 1921 a yellow fever and Mayaro virus vector, in South America

Yellow fever virus (YFV) has a long history of impacting human health in South America. Mayaro virus (MAYV) is an emerging arbovirus of public health concern in the Neotropics and its full impact is yet unknown. Both YFV and MAYV are primarily maintained via a sylvatic transmission cycle but can be opportunistically transmitted to humans by the bites of infected forest dwelling Haemagogus janthinomys Dyar, 1921. To better understand the potential risk of YFV and MAYV transmission to humans, a more detailed understanding of this vector species’ distribution is critical. This study compiled a comprehensive database of 177 unique Hg . janthinomys collection sites retrieved from the published literature, digitized museum specimens and publicly accessible mosquito surveillance data. Covariate analysis was performed to optimize a selection of environmental (topographic and bioclimatic) variables associated with predicting habitat suitability, and species distributions modelled across South America using a maximum entropy (MaxEnt) approach. Our results indicate that suitable habitat for Hg . janthinomys can be found across forested regions of South America including the Atlantic forests and interior Amazon.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2013

Unveiling Current Guanaco Distribution in Chile Based upon Niche Structure of Phylogeographic Lineages: Andean Puna to Subpolar Forests

Niche description and differentiation at broad geographic scales have been recent major topics in ecology and evolution. Describing the environmental niche structure of sister taxa with known evolutionary trajectories stands out as a useful exercise in understanding niche requirements. Here we model the environmental niche structure and distribution of the recently resolved phylogeography of guanaco (Lama guanicoe) lineages on the western slope of the southern Andes. Using a maximum entropy framework, field data, and information on climate, topography, human density, and vegetation cover, we identify differences between the two subspecies (L.g.cacsilensis, L.g.guanicoe) and their intermediate-hybrid lineage, that most likely determine the distribution of this species. While aridity seems to be a major factor influencing the distribution at the species-level (annual precipitation ,900 mm), we also document important differences in niche specificity for each subspecies, where distribution of Northern lineage is explained mainly by elevation (mean = 3,413 m) and precipitation seasonality (mean = 161 mm), hybrid lineage by annual precipitation (mean = 139 mm), and Southern subspecies by annual precipitation (mean = 553 mm), precipitation seasonality (mean = 21 mm) and grass cover (mean = 8.2%). Among lineages, we detected low levels of niche overlap: I (Similarity Index) = 0.06 and D (Schoener’s Similarity Index) = 0.01; and higher levels when comparing Northern and Southern subspecies with hybrids lineage (I = 0.32-0.10 and D = 0.12-0.03, respectively). This suggests that important ecological and/or evolutionary processes are shaping the niche of guanacos in Chile, producing discrepancies when comparing range distribution at the species-level (81,756 km 2 ) with lineages-level (65,321 km 2 ). The subspecies-specific description of niche structure is provided here based upon detailed spatial distribution of the lineages of guanacos in Chile. Such description provides a scientific tool to further develop large scale plans for habitat conservation and preservation of intraspecific genetic variability for this far ranging South American camelid, which inhabits a diversity of ecoregion types from Andean puna to subpolar forests.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2015

Implications of Climate Change for Bird Conservation in the Southwestern U.S. under Three Alternative Futures

Future expected changes in climate and human activity threaten many riparian habitats, particularly in the southwestern U.S. Using Maximum Entropy (MaxEnt3.3.3) modeling, we characterized habitat relationships and generated spatial predictions of habitat suitability for the Lucy’s warbler (Oreothlypis luciae), the Southwestern willow flycatcher (Empidonax traillii extimus) and the Western yellow-billed cuckoo (Coccyzus americanus). Our goal was to provide site- and species-specific information that can be used by managers to identify areas for habitat conservation and/or restoration along the Rio Grande in New Mexico. We created models of suitable habitat for each species based on collection and survey samples and climate, biophysical, and vegetation data. We projected habitat suitability under future climates by applying these models to conditions generated from three climate models for 2030, 2060 and 2090. By comparing current and future distributions, we identified how habitats are likely to change as a result of changing climate and the consequences of those changes for these bird species. We also examined whether land ownership of high value sites shifts under changing climate conditions. Habitat suitability models performed well. Biophysical characteristics were more important that climate conditions for predicting habitat suitability with distance to water being the single most important predictor. Climate, though less important, was still influential and led to declines of suitable habitat of more than 60% by 2090. For all species, suitable habitat tended to shrink over time within the study area leaving a few core areas of high importance. Overall, climate changes will increase habitat fragmentation and reduce breeding habitat patch size. The best strategy for conserving bird species within the Rio Grande will include measures to maintain and restore critical habitat refugia. This study provides an example of a presence-only habitat model that can be used to inform the management of species at intermediate scales.

54 ENVIRONMENTAL SCIENCES↗