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At least 253 records · Page 14

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DOE OSTI2018

Lévy-stable two-pion Bose-Einstein correlations in s NN = 200 GeV Au + Au collisions

Here, we present a detailed measurement of charged two-pion correlation functions in 0–30% centrality √ s NN = 200 GeV Au + Au collisions by the PHENIX experiment at the Relativistic Heavy Ion Collider. The data are well described by Bose-Einstein correlation functions stemming from Lévy-stable source distributions. Using a fine transverse momentum binning, we extract the correlation strength parameter λ, the Lévy index of stability α, and the Lévy length scale parameter R as a function of average transverse mass of the pair m T . We find that the positively and the negatively charged pion pairs yield consistent results, and their correlation functions are represented, within uncertainties, by the same Lévy-stable source functions. The λ(m T ) measurements indicate a decrease of the strength of the correlations at low m T . The Lévy length scale parameter R(m T ) decreases with increasing m T , following a hydrodynamically predicted type of scaling behavior. The values of the Lévy index of stability α are found to be significantly lower than the Gaussian case of α = 2, but also significantly larger than the conjectured value that may characterize the critical point of a second-order quark-hadron phase transition.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

DOE OSTI2019

A Review on Binder Jet Additive Manufacturing of 316L Stainless Steel

Binder jet additive manufacturing enables the production of complex components for numerous applications. Binder jetting is the only powder bed additive manufacturing process that is not fusion-based, thus manufactured parts have no residual stresses as opposed to laser-based additive manufacturing processes. Binder jet technology can be adopted for the production of various small and large metallic parts for specific applications, including in the biomedical and energy sectors, at a lower cost and shorter lead time. One of the most well-known types of stainless steels for various industries is 316L, which has been extensively manufactured using binder jet technology. Binder jet manufactured 316L parts have obtained near full density and, in some cases, similar mechanical properties compared to conventionally manufactured parts. This article introduces methods, principles, and applications of binder jetting of SS 316L. Details of binder jetting processes, including powder characteristics (shape and size), binder properties (binder chemistry and droplet formation mechanism), printing process parameters (such as layer thickness, binder saturation, drying time), and post-processing sintering mechanism and densification processes, are carefully reviewed. Furthermore, critical factors in the selection of feedstock, printing parameters, sintering temperature, time, atmosphere, and heating rate of 316L binder jet manufactured parts are highlighted and summarized. Finally, the above-mentioned processing parameters are correlated with final density and mechanical properties of 316L components to establish a guideline on feedstock selection and process parameters optimization to achieve desired density, structure and properties for various applications.

36 MATERIALS SCIENCE↗

DOE OSTI2022

Standardizing Platinum Dainotti-correlated gamma-ray bursts, and using them with standardized Amati-correlated gamma-ray bursts to constrain cosmological model parameters

ABSTRACT We show that the Platinum gamma-ray burst (GRB) data compilation, probing the redshift range 0.553 ≤ z ≤ 5.0, obeys a cosmological-model-independent three-parameter Fundamental Plane (Dainotti) correlation and so is standardizable. While they probe the largely unexplored z ∼ 2.3–5 part of cosmological redshift space, the GRB cosmological parameter constraints are consistent with, but less precise than, those from a combination of baryon acoustic oscillation (BAO) and Hubble parameter [H(z)] data. In order to increase the precision of GRB-only cosmological constraints, we exclude common GRBs from the larger Amati-correlated A118 data set composed of 118 GRBs and jointly analyse the remaining 101 Amati-correlated GRBs with the 50 Platinum GRBs. This joint 151 GRB data set probes the largely unexplored z ∼ 2.3–8.2 region; the resulting GRB-only cosmological constraints are more restrictive, and consistent with, but less precise than, those from H(z) + BAO data.

79 ASTRONOMY AND ASTROPHYSICS↗

NASA NTRS1975

Are climatological correlations with the Hale double sunspot cycle meaningful?

A sunspot cycle which may have been subject to a predicted phase reversal between 1800 and 1880 A. D is discussed. Several climatological parameters normally correlated with this cycle are examined and do not exhibit a corresponding phase reversal during this period. It is proposed that this apparent discrepancy can be resolved by suitable observations during the upcoming half decade.

Goldberg, R. A.↗

DOE OSTI2018

The Correlation between Characteristics of Macrolocalized Plastic Deformation and Parameters of the Electronic Structure of Metals

The correlation between lattice characteristics of a deformed medium and parameters of autowaves of a localized plastic flow in metals at the stage of linear strain hardening is considered. Such correlation testifies for the existence of a close connection between elastic and plastic deformations of the medium and, more generally, between characteristics of plasticity and electronic structure of elements.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

DOE OSTI2018

Confocal Raman Microscopy for In-situ Measurement of Phospholipid-Water Partitioning into Model Phospholipid Bilayers within Individual Chromatographic Particles

The phospholipid-water partition coefficient is a commonly measured parameter that correlates with drug efficacy, small-molecule toxicity, and accumulation of molecules in biological systems in the environment. Despite the utility of this parameter, methods for measuring phospholipid-water partition coefficients are limited. This is due to the difficulty of making quantitative measurements in vesicle membranes or supported phospholipid bilayers, both of which are small-volume phases that challenge the sensitivity of many analytical techniques. In this paper, we employ in-situ confocal Raman microscopy to probe the partitioning of a model membrane-active compound, 2-(4-isobutylphenyl) propionic acid or ibuprofen, into both hybrid- and supported-phospholipid bilayers deposited on the pore walls of individual chromatographic particles. The large surface-area-to-volume ratio of chromatographic silica allows interrogation of a significant lipid bilayer area within a very small volume. The local phospholipid concentration within a confocal probe volume inside the particle can be as high as 0.5 M, which overcomes the sensitivity limitations of making measurements in the limited membrane areas of single vesicles or planar supported bilayers. Quantitative determination of ibuprofen partitioning is achieved by using the phospholipid acyl-chains of the within-particle bilayer as an internal standard. This approach is tested for measurements of pH-dependent partitioning of ibuprofen into both hybrid-lipid and supported-lipid bilayers within silica particles, and the results are compared with octanol-water partitioning and with partitioning into individual optically-trapped phospholipid vesicle membranes. Finally and additionally, the impact of ibuprofen partitioning on bilayer structure is evaluated for both within-particle model membranes and compared with the structural impacts of partitioning into vesicle lipid bilayers.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2018

Laser-Hardened and Ultrasonically Peened Surface Layers on Tool Steel AISI D2: Correlation of the Bearing Curves’ Parameters, Hardness and Wear

This paper is focused on the effects of the separately applied laser heat treatment (LHT) and ultrasonic impact treatment (UIT) and the combined LHT + UIT process on the wear and friction behaviors of the hardened surface layers of the tool steel AISI D2. In comparison with the initial state, wear losses of the treated specimens after long-term wear tests were decreased by 68, 41, and 77% at the LHT, UIT, and combined LHT + UIT processes, respectively. The Abbott–Firestone bearing curves were used to analyze the material ratio and functional characterization (bearing capacity and oil capacitance) of the studied surface specimens. The wear losses registered after short (15 min) tests correlate well with the changes in experimental surface roughness Ra, and the predictive Rpk, and bearing capacity B{sub C} parameters, respectively, evaluated using the Abbott–Firestone curves and Kragelsky–Kombalov formula. The wear losses after the long-term (45 min) tests are in good correlation with the reciprocal surface microhardness HV and with the W{sub L} and W{sub P} wear parameters, respectively, estimated using Archard–Rabinowicz formula and complex roughness-and-strength approach. The observed HV increase is supported by nanotwins (LHT), by dense dislocation nets (UIT), and by dislocation cells/nanograins fixed with fine carbides (LHT + UIT) formed in the surface layers of the steel.

36 MATERIALS SCIENCE↗

NASA NTRS1995

A simulation to study the feasibility of improving the temporal resolution of LAGEOS geodynamic solutions by using a sequential process noise filter

A key drawback to estimating geodetic and geodynamic parameters over time based on satellite laser ranging (SLR) observations is the inability to accurately model all the forces acting on the satellite. Errors associated with the observations and the measurement model can detract from the estimates as well. These 'model errors' corrupt the solutions obtained from the satellite orbit determination process. Dynamical models for satellite motion utilize known geophysical parameters to mathematically detail the forces acting on the satellite. However, these parameters, while estimated as constants, vary over time. These temporal variations must be accounted for in some fashion to maintain meaningful solutions. The primary goal of this study is to analyze the feasibility of using a sequential process noise filter for estimating geodynamic parameters over time from the Laser Geodynamics Satellite (LAGEOS) SLR data. This evaluation is achieved by first simulating a sequence of realistic LAGEOS laser ranging observations. These observations are generated using models with known temporal variations in several geodynamic parameters (along track drag and the J(sub 2), J(sub 3), J(sub 4), and J(sub 5) geopotential coefficients). A standard (non-stochastic) filter and a stochastic process noise filter are then utilized to estimate the model parameters from the simulated observations. The standard non-stochastic filter estimates these parameters as constants over consecutive fixed time intervals. Thus, the resulting solutions contain constant estimates of parameters that vary in time which limits the temporal resolution and accuracy of the solution. The stochastic process noise filter estimates these parameters as correlated process noise variables. As a result, the stochastic process noise filter has the potential to estimate the temporal variations more accurately since the constraint of estimating the parameters as constants is eliminated. A comparison of the temporal resolution of solutions obtained from standard sequential filtering methods and process noise sequential filtering methods shows that the accuracy is significantly improved using process noise. The results show that the positional accuracy of the orbit is improved as well. The temporal resolution of the resulting solutions are detailed, and conclusions drawn about the results. Benefits and drawbacks of using process noise filtering in this type of scenario are also identified.

Hartman, Brian Davis↗

DOE OSTI2019

Feasibility of using computed tomography texture analysis parameters as imaging biomarkers for predicting risk grade of gastrointestinal stromal tumors: comparison with visual inspection

Purpose: To evaluate the feasibility of using computed tomography texture analysis (CTTA) parameters for predicting malignant risk grade and mitosis index of gastrointestinal stromal tumors (GISTs), compared with visual inspection. Method and materials: CTTA was performed on portal phase CT images of 145 surgically confirmed GISTs (mean size: 42.9 ± 37.5 mm), using TexRAD software. Mean, standard deviation, entropy, mean of positive pixels (MPP), skewness, and kurtosis of CTTA parameters, on spatial scaling factor (SSF), 2–6 were compared by risk grade, mitosis rate, and the presence or absence of necrosis on visual inspection. CTTA parameters were correlated with risk grade. Diagnostic performance was evaluated with receiver operating characteristic curve analysis. Enhancement pattern, necrosis, heterogeneity, calcification, growth pattern, and mucosal ulceration were subjectively evaluated by two observers. Results: Three to four parameters at different scales were significantly different according to the risk grade, mitosis rate, and the presence or absence of necrosis (p < 0.041). MPP at fine or medium scale (r = − 0.547 to − 393) and kurtosis at coarse scale (r = 0.424–0.454) correlated significantly with risk grade (p < 0.001). HG-GIST was best differentiated from LG-GIST by MPP at SSF 2 (AUC, 0.782), and kurtosis at SSF 4 (AUC, 0.779) (all p < 0.001). CT features predictive of HG-GIST were density lower than or equal to that of the erector spinae muscles on enhanced images (OR 2.1; p = 0.037; AUC, 0.59), necrosis (OR, 6.1; p < 0.001; AUC, 0.70), heterogeneity (OR, 4.3; p < 0.001; AUC, 0.67), and mucosal ulceration (OR, 3.3; p = 0.002; AUC, 0.62). Conclusion: Using TexRAD, MPP and kurtosis are feasible in predicting risk grade and mitosis index of GISTs. CTTA demonstrated meaningful accuracy in preoperative risk stratification of GISTs.

62 RADIOLOGY AND NUCLEAR MEDICINE↗

NASA NTRS2011

Can Functional Cardiac Age be Predicted from ECG in a Normal Healthy Population

In a normal healthy population, we desired to determine the most age-dependent conventional and advanced ECG parameters. We hypothesized that changes in several ECG parameters might correlate with age and together reliably characterize the functional age of the heart. Methods: An initial study population of 313 apparently healthy subjects was ultimately reduced to 148 subjects (74 men, 84 women, in the range from 10 to 75 years of age) after exclusion criteria. In all subjects, ECG recordings (resting 5-minute 12-lead high frequency ECG) were evaluated via custom software programs to calculate up to 85 different conventional and advanced ECG parameters including beat-to-beat QT and RR variability, waveform complexity, and signal-averaged, high-frequency and spatial/spatiotemporal ECG parameters. The prediction of functional age was evaluated by multiple linear regression analysis using the best 5 univariate predictors. Results: Ignoring what were ultimately small differences between males and females, the functional age was found to be predicted (R2= 0.69, P < 0.001) from a linear combination of 5 independent variables: QRS elevation in the frontal plane (p<0.001), a new repolarization parameter QTcorr (p<0.001), mean high frequency QRS amplitude (p=0.009), the variability parameter % VLF of RRV (p=0.021) and the P-wave width (p=0.10). Here, QTcorr represents the correlation between the calculated QT and the measured QT signal. Conclusions: In apparently healthy subjects with normal conventional ECGs, functional cardiac age can be estimated by multiple linear regression analysis of mostly advanced ECG results. Because some parameters in the regression formula, such as QTcorr, high frequency QRS amplitude and P-wave width also change with disease in the same direction as with increased age, increased functional age of the heart may reflect subtle age-related pathologies in cardiac electrical function that are usually hidden on conventional ECG.

Schlegel, Todd↗

DOE OSTI2025

A Scientist-in-the-Loop Data Analytics Framework for Intelligent Simulation Model Tuning and Validation

This project developed a scientist-in-the-loop data analytics framework for intelligent simulation model tuning and validation, targeting the Weather Research and Forecasting (WRF) model and its solar energy variant, WRF-Solar-BNL. Domain experts, such as climate scientists, depend on large-scale numerical simulations for knowledge discovery and decision-making, yet the complexity of parameter tuning and the disconnect between automated optimization and domain expertise pose significant challenges. We extended an interactive visual analytics framework that enables domain experts to observe and intervene in the computational steering process by identifying disagreements between the simulation model, surrogate model, and the expert’s domain knowledge. Using Bayesian Optimization with Gaussian Process Regression as the surrogate model, our system allows users to probe parameter relationships, analyze correlation patterns, and adjust tuning parameters in real time. We developed use cases for solar irradiance forecasting through sustained collaboration with Brookhaven National Laboratory, resolving critical model configuration challenges and achieving meaningful reductions in prediction error. The project supported one PhD student, one MS student, and eight undergraduate students across three Data Science Capstone projects, resulting in one master’s thesis.

Dasgupta, Aritra [New Jersey Institute of Technolo↗

DOE OSTI2026

A Bayesian approach to the long-baseline neutrino oscillation sensitivity of DUNE

The sensitivity of the Deep Underground Neutrino Experiment (DUNE) to neutrino oscillation is evaluated using a Bayesian Markov Chain Monte Carlo (MCMC) approach. This analysis uses the same underlying sensitivity inputs as previous DUNE studies [Eur. Phys. J. C 80, 978 (2020)], and therefore does not present updated DUNE sensitivities, but instead explores the additional inferences accessible using a Bayesian approach. We present four-dimensional posterior probability distributions of the oscillation parameters, highlighting the breadth of correlation in the parameter space of interest, especially between $\sin^2 θ_{23}$ and $\sin^2 θ_{13}$. We exploit the flexibility of the Bayesian framework to incorporate parameter constraints post hoc and assess the impact of applying a reactor short-baseline $θ_{13}$ constraint. A significant increase in the sensitivity to the $θ_{23}$ octant is found when including the constraint. Posterior distributions of derived quantities can be easily constructed from MCMC results. This work presents the first study of DUNE's sensitivity to the Jarlskog invariant, $J$, a quantity that provides a parametrisation-independent measure of charge-parity violation in the leptonic sector.

Abbaslu, Saeed [IPM, Tehran] (ORCID:00000003356771↗

NASA NTRS1976

A scaling law for energy transfer by inelastic electron-molecule collisions in mixtures

The equation governing the electron energy distribution in the presence of a spatially uniform electric field in a weakly ionized gas was reformulated into an integral equation for the logarithmic slope of the distribution function. For gas mixtures in which the dominant electron energy loss mechanism is by vibrational excitation of the molecules, this equation is suitable for approximate analysis and exact numerical solution by iteration. Superelastic collisions are easily included in this formulation, and do not seriously effect the convergence of the numerical scheme. The approximate analytical results are only qualitatively correct, but suggest appropriate parameters which correlate the exact numerical results very well. The distribution function as well as certain gross properties such as net energy transfer into vibration, mean energy, and drift velocity depend primarily on a single nondimensional parameter involving only E/N and the cross sections.

Bienkowski, G. K.↗

NASA NTRS1972

Propellant sidefeed-short pulse discharge thruster studies

The technique of feeding a solid propellant into the discharge from the sides of the discharge was evaluated. The thrust/power ratio could be significantly effected by the included angle of V-shaped propellants and by the electrode length. This result implies that when results are compared at the same specific impulse it is possible to obtain higher thrust efficiencies. In particular, it was found that for a given discharge energy the thrust/power ratio correlated with propellant mass. Increasing the integral simultaneously increases both the gas dynamic and electromagnetic thrust. An analytic expression was formulated for ablated mass which comprehensively describes experimental data in terms of geometry and electrical parameters. The correlation of the product impulse x specific impulse with discharge energy was also described. It is suggested that the reliability of dry energy storage capacitors does not equal the reliability of liquid impregnated units when the comparison is made at the same joules/Kg rating.

Palumbo, D. J.↗

NASA NTRSDate not supplied

Probabilistic Modeling of a Three-Stage Human Landing System Architecture

Unmitigated uncertainties are known to have previously led to failed development programs; in order to combat these uncertainties, risks and their impacts must be understood and handled to ensure program success. In this paper, a probabilistic methodology to handle uncertainties is demonstrated on a three-element Human Landing System (HLS) concept, which allows tracking of current best estimates of the vehicle’s performance and assessment of its robustness against uncertainties. This methodology has two key parts: ﬁrst, the creation of a dynamic architecture model of a three-element HLS concept; and second, its use with surrogate modeling and range estimating techniques to capture and propagate uncertainties. The DYnamic Rocket EQuation Tool (DYREQT), a space systems synthesis and sizing framework used by NASA, was used as to model the HLS architecture. For the probabilistic analysis, uncertainties of interest within the HLS concept were enumerated and represented as parameters within the DYREQT model as inputs for vehicle stages or mission proﬁle events. Range estimating — a probabilistic method that combines Monte Carlo sampling, focus on critical parameters, and heuristics to assess risk and opportunities — is then adapted with operational parameters as well as vehicle parameters in the DYREQT model to capture mission uncertainty alongside vehicle uncertainty. To perform the range estimation portion of this methodology, the DYREQT model was sampled using a Design of Experiments (DoE) to eﬃciently explore the architecture design space with respect to the set of uncertainty parameters. Then, the results were used to create surrogate models, multivariate regressions that can visualize hypercube trends in the design space, of the architecture with respect to the uncertainty parameters. Using a correlation matrix constructed for the uncertainty parameters, previously independent samples were transformed to perform a Correlated Monte Carlo on the surrogate models. This probabilistic methodology was proved to provide insight into the underlying uncertainties of the three-element HLS architecture.

Stephanie Y Zhu↗

NASA NTRSDate not supplied

Probabilistic Modeling of a Three-Stage Human Landing System Architecture

Stephanie Y. Zhu↗

DOE OSTI2019

A data-driven approach to construct a quantitative relationship between microstructural features of fatigue cracks and contact acoustic nonlinearity

This study demonstrates the feasibility of a data-driven approach to construct a quantitative relationship between nonlinear acoustic parameters and microstructural features of contact interfaces. The near-surface nonlinearity is measured using dynamic acousto-elastic testing (DAET) with a surface wave probe, while the microstructural features are extracted from scanning electron microscopy (SEM) images of fatigue cracks. Four aluminum alloy samples, each having a fatigue crack are prepared. Six local nonlinearity parameters are measured at different locations along the crack propagation direction. A total of 40 local measurements are acquired. A principal component analysis (PCA) reveals that all six nonlinearity parameters are correlated and hence can be replaced by one principal component (PC). Fifteen crack micro-geometrical features at each measurement point were extracted from the SEM images. Regression analysis is used to relate the PC of the nonlinearity parameters to the microstructural features at the crack interface. We compare three regression models that take variable selection into account: stepwise multiple linear regression (MLR), stepwise principal component regression (PCR), and least absolute shrinkage and selection operator (LASSO). Despite having different principles, the three predictive models identify two features as the most significant in predicting the interface nonlinearity: the crack aperture (opening) distribution and the distance to the crack tip. The differences between the three models and the physical interpretation of the data-driven predictions are discussed.

36 MATERIALS SCIENCE↗

NASA NTRS1984

Structure-activity correlations for organophosphorus ester anticholinesterases. Part 2: CNDO/2 calculations applied to ester hydrolysis rates

Quantitative structure-activity relationships are presented for the hydrolysis of organophosphorus esters, RR'P(O)X, where R and R' are alkyl and/or alkoxy groups and X is fluorine, chlorine or a phenoxy group. CNDO/2 calculations provide values for molecular parameters that correlate with alkaline hydrolysis rates. For each subset of esters with the same leaving group, X, the CNDO-derived net atomic charge at the central phosphorus atom correlates well with the alkaline hydrolysis rate constants. For the whole set of esters with different leaving groups, equations are derived that relate charge, orbital energy and bond order to the hydrolysis rate constants.

Johnson, H.↗