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At least 739 records · Page 41
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Dark Matter halo parameters from overheated exoplanets via Bayesian hierarchical inference

Dark Matter (DM) can become captured, deposit annihilation energy, and hence increase the heat flow in exoplanets and brown dwarfs. Detecting such a DM-induced heating in a population of exoplanets in the inner kpc of the Milky Way thus provides potential sensitivity to the galactic DM halo parameters. We develop a Bayesian Hierarchical Model to investigate the feasibility of DM discovery with exoplanets and examine future prospects to recover the spatial distribution of DM in the Milky Way. We reconstruct from mock exoplanet datasets observable parameters such as exoplanet age, temperature, mass, and location, together with DM halo parameters, for representative choices of measurement uncertainty and the number of exoplanets detected. We find that detection of O(100) exoplanets in the inner Galaxy can yield quantitative information on the galactic DM density profile, under the assumption of 10% measurement uncertainty. Even as few as O(10) exoplanets can deliver meaningful sensitivities if the DM density and inner slope are sufficiently large.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2021

Sensitive parameter identification and uncertainty quantification for the stability of pipeline conveying fluid

In this study, several uncertainty quantification and sensitivity analysis methods are used to determine the most sensitive geometric and material input parameters of a cantilevered pipeline conveying fluid when uncertainty is introduced to the system at the onset of instability. The full nonlinear equations of motion are modeled using the extended Hamilton’s principle and then discretized using Galerkin’s method. A parametric study is first performed, and the Morris elementary effects are calculated to obtain a preliminary understanding of how the onset speed changes when each parameter is introduced to a ± 5% uncertainty. Then, four different input uncertainty distributions, mainly, uniform and Gaussian distribution, are chosen to investigate how input distributions affect uncertainty in the output. A convergence analysis is used to determine the number of samples needed to maintain simulation accuracy while saving the most computational time. Then, Monte Carlo simulations are run, and the output distributions for each input distribution at ± 1%, ± 3% and ± 5% input uncertainty range are found and discussed. Additionally, the Pearson correlation coefficients are evaluated for different uncertainty ranges. A final Monte Carlo study is performed in which single parameters are held constant while all others still have uncertainty. Overall, the flow speed at the onset of instability is the most sensitive to changes in the outer diameter of the pipe.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Relative permeability of gas and water flow in hydrate-bearing porous media: A micro-scale study by lattice Boltzmann simulation

The water-gas relative permeability is an important parameter to characterize multiphase flow in sediments. To study the water-gas relative permeability of hydrate-bearing porous media, multiphase flow simulations were carried out at the pore scale using the lattice Boltzmann method. In this work, the effects of hydrate saturation and hydrate-growth habits on the water-gas relative permeability, which is scaled by the relative permeability considering the hydrate only, were evaluated in a two-dimensional porous medium. Results show that the increase of hydrate saturation causes the decrease of water-gas effective permeability as expected. However, the effect of hydrate saturation on the water-gas relative permeability is different from that of hydrate saturation on the water-gas effective permeability. The water-gas relative permeability increases with the increase of hydrate saturation in the pore-filling case. The water-gas relative permeability decreases with the increase of hydrate saturation in the grain-coating case. The wettability of solid phase has a different effect on the relative permeability of wetting phase and nonwetting phase. The Jamin effect (phase blocking) was observed and may exist in the production of gas from natural gas hydrate reservoirs. This seriously affects the multiphase flow characteristics. The changes of microscale fluid distribution effect the changes of water-gas relative permeability. The relationship between the water-gas relative permeability and the characterization parameters of microscale fluid distribution was analyzed.

58 GEOSCIENCES↗
DOE OSTI2022

The stellar parameters and elemental abundances from low-resolution spectra – I. 1.2 million giants from LAMOST DR8

As a typical data-driven method, deep learning becomes a natural choice for analysing astronomical data. In this study, we built a deep convolutional neural network (NN) to estimate basic stellar parameters $T\rm {_{eff}}$, log g , metallicity ([M/H] and [Fe/H]) and [α/M] along with nine individual elemental abundances ([C/Fe], [N/Fe], [O/Fe], [Mg/Fe], [Al/Fe], [Si/Fe], [Ca/Fe], [Mn/Fe], and [Ni/Fe]). The NN is trained using common stars between the APOGEE survey and the LAMOST survey. We used low-resolution spectra from LAMOST survey as input, and measurements from APOGEE as labels. For stellar spectra with the signal-to-noise ratio in g band larger than 10 in the test set, the mean absolute error (MAE) is 29 K for $T\rm {_{eff}}$, 0.07 dex for log g , 0.03 dex for both [Fe/H] and [M/H], and 0.02 dex for [α/M]. The MAE of most elements is between 0.02 and 0.04 dex. The trained NN was applied to 1210 145 giants, including sub-giants, from LAMOST DR8 within the range of stellar parameters 3500 K < $T\rm {_{eff}}$ < 5500 K, 0.0 dex < log g < 4.0 dex, −2.5 dex < [Fe/H] < 0.5 dex. The distribution of our results in the chemical spaces is highly consistent with APOGEE labels and stellar parameters show consistency with external high-resolution measurements from GALAH. The results in this study allow us to further studies based on LAMOST data and deepen our understanding of the accretion and evolution history of the Milky Way. The electronic version of the value added catalog is available at http://www.lamost.org/dr8/v1.1/doc/vac.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2025

Turbulent Parameters by airborne measurements over BNF in March 2025

The original data were collected during the AAF Engineering Flights (AEF2025) in the vicinity of the ARM Bankhead National Forest (BNF) Atmospheric Observatory (https://www.arm.gov/capabilities/observatories/bnf ) in northwestern Alabama in March 2025. The ARM Aerial Facility ArcticShark uncrewed aerial system (UAS, https://www.arm.gov/capabilities/observatories/aaf/uas) was based at the public-use airport of Posey Field, Alabama (FAA LID: 1M4, 34.28027778° N, 87.60055556° W, 283m MSL) from March 10 through March 24, 2025. The ArcticShark UAS performed nine flights, including eight research flights over the AMF3 (BNF Main Site) and Supplemental Facilities to measure atmospheric state, turbulence, surface IR temperature and imagery, and aerosol number concentration and size distribution. The current data set presents a collection of turbulent parameters in the atmospheric boundary layer or lower free troposphere based on airborne measurement throughout the field campaign. The primary instruments used to create the current data set were the Aircraft Integrated Meteorological Measurement System (AIMMS-30) and the fine-wire thermocouple probe.

Atmosphere↗
DOE OSTI2025

CHELAX-BNF: Turbulent Parameters by airborne measurements

The original data were collected on board the ARM Aerial Facility ArcticShark uncrewed aerial system (UAS; https://www.arm.gov/capabilities/observatories/aaf/uas ) during the “Characterizing HEterogeneous Land-Atmosphere eXchanges at BNF” field campaign (CHEAX-BNF; https://arm.gov/research/campaigns/aaf2025CHELAX-BNF ). The ARM Aerial Facility ArcticShark UAS was based at the public-use airport of Posey Field, AL (FAA LID: 1M4, 34.28027778° N, 87.60055556° W, 283m MSL) from May 28 through June 23, 2025. The ArcticShark UAS performed 5 flights, including 4 research flights over the BNF Main Site (ARM Mobile Facility 3, https://arm.gov/capabilities/observatories/amf ) and Supplemental Facilities to measure atmospheric state, turbulence, surface IR temperature and imagery, aerosol number concentration, and aerosol size distribution. The current data set presents a collection of turbulent parameters in the atmospheric boundary layer or lower free troposphere based on airborne measurement throughout the field campaign. The primary instruments used to create the current data set were the Aircraft Integrated Meteorological Measurement System (AIMMS-30) and the fine-wire thermocouple probe.

Aircraft Integrated Meteorological Measurement Sys↗
DOE OSTI2020

Observation of X(2370) and search for X(2120) in $J/\psi \rightarrow \gamma K{\bar{K}} \eta '$: BESIII Collaboration

Using a sample of 1.31 × 10 9 J/ψ events collected with the BESIII detector, we perform a study of J/ψ → γKK¯η'. X(2370) is observed in the KK¯η' invariant-mass distribution with a statistical significance of 8.3σ. Its resonance parameters are measured to be M = 2341.6 ± 6.5(stat.) ± 5.7(syst.) MeV/c 2 and Γ = 117 ± 10(stat.) ± 8(syst.) MeV. The product branching fractions for J/ψ → γX(2370), X(2370) → K + K – η' and J/ψ → γX(2370), X(2370) → $K$ $^{0}_{S}$ $K$ $^{0}_{S}$η' are determined to be (1.79 ± 0.23(stat.) ± 0.65(syst.)) × 10 –5 and (1.18 ± 0.32(stat.) ± 0.39(syst.)) × 10 –5 , respectively. No evident signal for X(2120) is observed in the KK¯η' invariant-mass distribution. The upper limits for the product branching fractions of B(J/ψ → γX(2120) → γK + K – η') and B(J/ψ → γX(2120) → $K$ $^{0}_{S}$ $K$ $^{0}_{S}$η') are determined to be 1.49 × 10 –5 and 6.38 × 10 –6 at the 90% confidence level, respectively.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2025

Versatile system for ion energy measurements generated by pulsed laser ionization: Insights into electron-ion dynamics

Ion energy distributions generated by pulsed laser interactions with materials are essential for applications ranging from materials science to oncology. Ion energy characterization is particularly important for an emerging mass spectrometry technique called virtual-slit cycloidal mass spectrometry (VS-CMS). The ion energy distribution influences the design and performance of VS-CMS instruments, as well as the efficacy of laser-driven ionization methods in various fields. Several established techniques, including the retarding potential method, time-of-flight (TOF) analysis, and electrostatic energy analyzers, have been employed to measure ion energy distributions. The wide range of ion energies reported highlights the strong dependence of ion energy on laser parameters, target materials, and experimental conditions, as well as the necessity of making independent measurements of the ion energy distribution for specific laser systems and materials. This paper presents the design and characterization of a simple TOF-based apparatus for measuring ion energy distributions from pulsed laser ionization without external fields. This approach minimizes perturbation of electron-ion dynamics and enables simultaneous energy measurements at multiple spatial positions. Here, the apparatus was tested using a nanosecond pulsed Nd:YAG laser operating at 1064 nm, 532 nm, and 266 nm on solid copper sheets at various laser fluences. Simultaneous measurements at different distances provide new insights into ion-electron interactions post-ionization and demonstrate the influence of laser wavelength and fluence on ion energy distributions.

Ion energy↗
DOE OSTI2020

Forecasting cosmological constraints from the weak lensing magnification of type Ia supernovae measured by the Nancy Grace Roman Space Telescope

We report that the weak lensing magnification of type Ia supernovae (SNe Ia) is sensitive to the clustering of matter and provides an independent cosmological probe complementary to SN Ia distance measurements. The Nancy Grace Roman Space Telescope is uniquely sensitive to this measurement as it can discover high redshift SNe Ia and measure them with high precision. We present a methodology for reconstructing the probability distribution of the weak lensing magnification μ of SNe Ia, p(μ), from observational data, and using it to constrain cosmological parameters. We find that the reconstructed p(μ) can be fitted accurately by a stretched Gaussian distribution and used to measure the variance of μ, ξ μ , which can be compared to theoretical predictions in a likelihood analysis. Applying our methodology to a set of realistically simulated SNe Ia expected from the Roman Space Telescope, we find that using the weak lensing magnification of the SNe Ia constrains a combination of matter density Ω m and matter clustering amplitude σ 8 . SN Ia distances alone lead to a better than 1% measurement of Ωm. The combination of SN Ia weak lensing magnification and distance measurements result in a ~10 % measurement on σ 8 . The SNe Ia from Roman will be powerful in constraining the cosmological model.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2021

Forecasting Multi-Wave Epidemics Through Bayesian Inference

We present a simple, near-real-time Bayesian method to infer and forecast a multiwave outbreak, and demonstrate it on the COVID-19 pandemic. The approach uses timely epidemiological data that has been widely available for COVID-19. It provides short-term forecasts of the outbreak’s evolution, which can then be used for medical resource planning. The method postulates one- and multiwave infection models, which are convolved with the incubation-period distribution to yield competing disease models. The disease models’ parameters are estimated via Markov chain Monte Carlo sampling and information-theoretic criteria are used to select between them for use in forecasting. The method is demonstrated on two- and three-wave COVID-19 outbreaks in California, New Mexico and Florida, as observed during Summer-Winter 2020. We find that the method is robust to noise, provides useful forecasts (along with uncertainty bounds) and that it reliably detected when the initial single-wave COVID-19 outbreaks transformed into successive surges as containment efforts in these states failed by the end of Spring 2020.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

Implementing contact angle boundary conditions for second-order Phase-Field models of wall-bounded multiphase flows

In the present work, a general formulation is proposed to implement the contact angle boundary conditions for the second-order Phase-Field models, which is applicable to N-phase (N ≥ 2) moving contact line problems. To remedy the issue of mass change due to the contact angle boundary condition, a source term or Lagrange multiplier is added to the original second-order Phase-Field models, which is determined by the consistent and conservative volume distribution algorithm so that the summation of the order parameters and the consistency of reduction are not influenced. To physically couple the proposed formulation to the hydrodynamics, especially for large-density-ratio problems, the consistent formulation is employed. The reduction-consistent conservative Allen-Cahn models are chosen as examples to illustrate the application of the proposed formulation. The numerical scheme that preserves the consistency and conservation of the proposed formulation is employed to demonstrate its effectiveness. Results produced by the proposed formulation are in good agreement with the exact and/or asymptotic solutions. The proposed method captures complex dynamics of moving contact line problems having large density ratios.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2023

TGA Study of the Reaction Kinetics of a CuFeMnAlO 4+δ Oxygen Carrier for Methane Chemical Looping Combustion under High Pressure and Atmospheric Pressure Conditions

Reduction and oxidation kinetics of a CuFeMnAlO 4+δ oxygen carrier for methane were studied using an atmospheric thermogravimetric analyzer (TGA) and a pressurized TGA. Important parameters such as temperature (500–900 °C), particle size distribution (150–650 μm), and partial pressures of reactants (methane and oxygen) were evaluated. Results showed that the reduction of the oxygen carrier was not affected by particle size distribution studied in this work, and that above 750 °C, the effect of the temperature on oxygen carrier reduction started to diminish. The reaction time approaches an asymptotic limit as methane partial pressure increases. For oxygen carrier oxidation, it was found that the rate of oxidation increased with increasing oxygen concentration. The effect of the oxygen concentration was more noticeable when the oxygen concentration was below 7.5%. Because of the inherent feature of the oxygen carrier, its chemical looping with oxygen uncoupling property was also assessed. A phase boundary-controlled shrinking sphere model was used to model the test data from the TGAs. Modeling results showed that the oxygen carrier reduction had a reaction order of 1 with an activation energy of ∼46 kJ/mol. Oxygen carrier oxidation demonstrated a reaction order of 1.1 with an activation energy of ∼55 kJ/mol. Additionally, the differences of the experimental results between the atmospheric pressure TGA and the pressurized TGA were discussed in detail and the limitations of the pressurized TGA were highlighted.

Hydrocarbons↗
DOE OSTI2023

Influence of Pore Length on Hydrogenolysis of Polyethylene within a Mesoporous Support Architecture

Due to the plastic waste crisis, selective chemical upcycling of polyolefins into value-added products is a topic of intense interest, demanding polymer deconstruction processes that afford control over the product chain lengths. Recently, a catalytic architecture was synthesized in which a polyolefin melt infiltrates a porous support, and its chains are cleaved by a metal nanoparticle catalyst at the bottom of the pores, yielding a narrow distribution of alkane products. Although the influence of various parameters of these catalytic materials, including the effects of the nanoparticle size and pore diameter on product chain length, has been examined before, here, we investigate the role of the pore length in the cleavage process through the first study that combines catalytic hydrogenolysis and coarse-grained modeling to gain insights not available by experiment alone. We show that the pore length can permit control over the average product length with qualitative agreement between experiment and simulation. In conclusion, we go beyond this observation to uncover the dynamic phenomenon responsible for the pore-length dependence of the cleavage products.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

Computational investigation of incident ion angles and material erosion at rough graphite and silicon carbide divertor surfaces

We present a computational investigation of the dependence of material erosion on the incident ion angle at rough graphite and silicon carbide divertor surfaces. Ion angle distributions (IADs) for D plasmas at NSTX-U and DIII-D divertors were calculated by an equation-of-motion model that traces the ion trajectories in the sheath. Then, the effective sputtering yields and ion shadowed area fractions were calculated by a Monte Carlo micro-patterning and roughness code that applied the calculated IADs to surface topographic data that were obtained from optical confocal microscopy of rough graphite and SiC divertor surfaces from NSTX-U and DIII-D experiments. The calculations found that the effective sputtering yields, the sputtering pattern, and the shadowed area are determined by the detailed surface topology rather than the root mean square roughness R RMS , which represents deviations from a flat surface. The suppression of the effective sputtering yields for rough surfaces compared to the yield for a smooth surface was accounted for by the change of the mean local incident ion angle (LIIA) (θ'). The mean surface inclination angle distribution (SIAD) (δ) was found to be a useful parameter to estimate the LIIA from the calculated IADs. We report global empirical formulas for the mean LIIA and fraction of the area shadowed from the main ions for D plasmas for rough surfaces with B-field incident angles α = 85°–89° as a function of the mean SIAD (δ). We propose the use of the mean LIIA (θ') to estimate the sputtering yield for rough surfaces from the angular dependence of the sputtering yield.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2024

Proton rings from late-forming ballistic sheath fields

Many laser-driven ion experiments have seen ring-like patterns in the proton angular distribution across a wide array of laser and target parameters. These rings can impede measurement due to the small acceptance angle of detectors and often inhibit potential applications. A myriad of explanations for their formation have been proposed, yet most studies attribute them to some aspect of the laser–plasma interaction. Using 3D particle-in-cell simulations, we show that late-forming strong radial electric fields can arise due to charge separation while the beam is in flight, long after the laser–plasma interaction. These fields can accelerate ions to significant divergences (≈ 10°) as they propagate away from the target. We compare our results to a recent experiment where a high intensity, short pulse laser (I 0 ≈ 10 21 W/cm 2 , τ ≈ 30 fs) was incident upon thin (≈ 1 μm) liquid crystal targets. Our simulations capture all the main features of the experimental results—namely, robust ring formation and larger rings for higher energy protons. In addition, we show that rings do not form for sufficiently short preplasma scale lengths. Finally, we develop a phenomenological model to describe the spatiotemporal structure of the radial electric field and use this to explain the proton rings' energy and preplasma dependencies.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2022

Mesoscale structural gradients in human tooth enamel

The outstanding mechanical and chemical properties of dental enamel emerge from its complex hierarchical architecture. An accurate, detailed multiscale model of the structure and composition of enamel is important for understanding lesion formation in tooth decay (dental caries), enamel development (amelogenesis) and associated pathologies (e.g., amelogenesis imperfecta or molar hypomineralization), and minimally invasive dentistry. Although features at length scales smaller than 100 nm (individual crystallites) and greater than 50 µm (multiple rods) are well understood, competing field of view and sampling considerations have hindered exploration of mesoscale features, i.e., at the level of single enamel rods and the interrod enamel (1 to 10 µm). Here, we combine synchrotron X-ray diffraction at submicrometer resolution, analysis of crystallite orientation distribution, and unsupervised machine learning to show that crystallographic parameters differ between rod head and rod tail/interrod enamel. This variation strongly suggests that crystallites in different microarchitectural domains also differ in their composition. Thus, we use a dilute linear model to predict the concentrations of minority ions in hydroxylapatite (Mg 2+ and CO 3 2- /Na + ) that plausibly explain the observed lattice parameter variations. While differences within samples are highly significant and of similar magnitude, absolute values and the sign of the effect for some crystallographic parameters show interindividual variation that warrants further investigation. In conclusion, by revealing additional complexity at the rod/interrod level of human enamel and leaving open the possibility of modulation across larger length scales, these results inform future investigations into mechanisms governing amelogenesis and introduce another feature to consider when modeling the mechanical and chemical performance of enamel.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2024

Bayesian mixture model approach to quantifying the empirical nuclear saturation point

The equation of state (EOS) in the limit of infinite symmetric nuclear matter exhibits an equilibrium density, $n_0 \approx 0.16 \, \mathrm{fm}^{-3}$, at which the pressure vanishes and the energy per particle attains its minimum, $E_0 \approx -16 \, \mathrm{MeV}$. Although not directly measurable, the nuclear saturation point $(n_0,E_0)$ can be extrapolated by density functional theory (DFT), providing tight constraints for microscopic interactions derived from chiral effective field theory (EFT). However, when considering several DFT predictions for $(n_0,E_0)$ from Skyrme and Relativistic Mean Field (RMF) models together, a discrepancy between these model classes emerges at high confidence levels that each model prediction's uncertainty cannot explain. How can we leverage these DFT constraints to rigorously benchmark nuclear saturation properties of chiral interactions? To address this question, we present a Bayesian mixture model that combines multiple DFT predictions for $(n_0,E_0)$ using an efficient conjugate prior approach. The inferred posterior distribution for the saturation point's mean and covariance matrix follows a Normal-inverse-Wishart class, resulting in posterior predictives in the form of correlated, bivariate $t$-distributions. The DFT uncertainty reports are then used to mix these posteriors using an ordinary Monte Carlo approach. At the 95\% credibility level, we estimate $n_0 \approx 0.157 \pm 0.010 \, \mathrm{fm}^{-3}$ and $E_0 \approx -15.97 \pm 0.40 \, \mathrm{MeV}$ for the marginal (univariate) $t$-distributions. Combined with chiral EFT calculations of the pure neutron matter EOS, we obtain bivariate normal distributions for the nuclear symmetry energy and its slope parameter evaluated at $n_0$: $S_v \approx 32.0 \pm 1.1 \, \mathrm{MeV}$ and $L\approx 52.6\pm 8.1 \, \mathrm{MeV}$ (95\%), respectively. Furthermore, our Bayesian framework is publicly available, so practitioners can readily use and extend our results.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2023

Beyond Fisher forecasting for cosmology

The planning and design of future experiments rely heavily on forecasting to assess the potential scientific value provided by a hypothetical set of measurements. The Fisher information matrix, due to its convenient properties and low computational cost, provides an especially useful forecasting tool. However, the Fisher matrix only provides a reasonable approximation to the true likelihood when data are nearly Gaussian distributed and observables have nearly linear dependence on the parameters of interest. Also, Fisher forecasting techniques alone cannot be used to assess their own validity. Thorough sampling of the exact or mock likelihood can definitively determine whether a Fisher forecast is valid, though such sampling is often prohibitively expensive. Here we propose a simple test, based on the Derivative Approximation for likelihoods (DALI) technique, to determine whether the Fisher matrix provides a good approximation to the exact likelihood. We show that the Fisher matrix becomes a poor approximation to the true likelihood in regions where two-dimensional slices of level surfaces of the DALI approximation to the likelihood differ from two-dimensional slices of level surfaces of the Fisher approximation to the likelihood. We demonstrate that our method accurately predicts situations in which the Fisher approximation deviates from the true likelihood for various cosmological models and several data combinations, with only a modest increase in computational cost compared to standard Fisher forecasts.

79 ASTRONOMY AND ASTROPHYSICS↗