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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 1,135 records · Page 63
All sourcesNASA NTRSDOE OSTI
DOE OSTI2017

Quantum behavior of water nano-confined in beryl

The proton mean kinetic energy, Ke(H), of water confined in nanocavities of beryl (Be 3 Al 2 Si 6 O 18 ) at 5 K was obtained by simulating the partial vibrational density of states from density functional theory based first-principles calculations. The result, Ke(H) = 104.4 meV, is in remarkable agreement with the 5 K deep inelastic neutron scattering (DINS) measured value of 105 meV. This is in fact the first successful calculation that reproduces an anomalous DINS value regarding Ke(H) in nano-confined water. The calculation indicates that the vibrational states of the proton of the nano-confined water molecule distribute much differently than in ordinary H 2 O phases, most probably due to coupling with lattice modes of the hosting beryl nano-cage. These findings may be viewed as a promising step towards the resolution of the DINS controversial measurements on other H 2 O nano-confining systems, e.g., H 2 O confined in single and double walled carbon nanotubes.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2019

Ignition thresholds of aluminized HMX-based polymer-bonded explosives

Here, the ignition of aluminized HMX-based polymer-bonded explosives (PBXs) under shock loading is studied via mesoscale simulations. The conditions analyzed concern loading pulses of 20 nanoseconds to 0.8 microseconds in duration and impact piston velocities on the order of 400-1000 m/s or loading stresses on the order of 3-14 GPa. The sets of samples studied have stochastically similar microstructures consisting of a bimodal distribution of HMX grains, an Estane binder, and aluminum particles 50-100 µm in diameter. The computational model accounts for constituent elasto-viscoplasticity, viscoelasticity, bulk compressibility, fracture, interfacial debonding, internal contact, bulk and frictional heating, and heat conduction. The analysis focuses on the development of hotspots under different material settings and loading conditions. In particular, the ignition thresholds in the forms of the James relation and the Walker-Wasley relation and the corresponding ignition probability are calculated and expressed as functions of the aluminum volume fraction for the PBXs analyzed. Lastly, it is found that the addition of aluminum raises the ignition thresholds, causing the materials to be less sensitive. Dissipation and heating mechanism changes responsible for this trend are delineated.

36 MATERIALS SCIENCE↗
DOE OSTI2016

Diffusion of energetic electrons in turbulent plasmas of the solar wind

A method of calculation of the diffusion coefficients D(v) of particles in velocity space, based on the statistical analysis of the motion of a great number of test electrons, is proposed. In the case of Langmuir turbulence developing in plasmas with fluctuating density inhomogeneities such as the solar wind, simulations provide coefficients D(v) which mainly depend on the Langmuir wave spectra and agree well with the analytical predictions D{sub th}(v) of the quasilinear theory of weak turbulence. Nevertheless, some noticeable differences exist with this theory: in the range of phase velocity of the short waves where the main part of the wave energy is concentrated, D(v) is noticeably smaller than D{sub th}(v), due to the scattering, the reflection, and the focusing effects encountered by the Langmuir waves when they interact with the plasma density inhomogeneities. Moreover, the probability of large velocity jumps in the particles’ trajectories essentially exceeds the probability of a Gaussian distribution. These large jumps, which are connected with the waves’ transformation processes, modify the nature of the particle diffusion, which is no more classical. These higher order effects cause the discrepancies observed with the quasilinear theory, which does not take them into account in its perturbative approach. The solar wind plasmas, which present fluctuating density inhomogeneities of noticeable average levels, are a very good laboratory to study such diffusion processes, which can eventually influence significantly on the development of essential physical phenomena, as electromagnetic radio emissions by type III solar radio bursts, for example.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2014

The AstraLux multiplicity survey: Extension to late M-dwarfs

The distribution of multiplicity among low-mass stars is a key issue to understanding the formation of stars and brown dwarfs, and recent surveys have yielded large enough samples of nearby low-mass stars to study this issue statistically to good accuracy. Previously, we have presented a multiplicity study of ∼700 early/mid M-type stars observed with the AstraLux high-resolution Lucky Imaging cameras. Here, we extend the study of multiplicity in M-type stars through studying 286 nearby mid/late M-type stars, bridging the gap between our previous study and multiplicity studies of brown dwarfs. Most of the targets have been observed more than once, allowing us to assess common proper motion to confirm companionship. We detect 68 confirmed or probable companions in 66 systems, of which 41 were previously undiscovered. Detections are made down to the resolution limit of ∼100 mas of the instrument. The raw multiplicity in the AstraLux sensitivity range is 17.9%, leading to a total multiplicity fraction of 21%-27% depending on the mass ratio distribution, which is consistent with being flat down to mass ratios of ∼0.4, but cannot be stringently constrained below this value. The semi-major axis distribution is well represented by a log-normal function with μ{sub a} = 0.78 and σ{sub a} = 0.47, which is narrower and peaked at smaller separations than for a Sun-like sample. This is consistent with a steady decrease in average semi-major axis from the highest-mass binary stars to the brown dwarf binaries.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2025

Learning error distribution kernel‐enhanced neural network methodology for multi‐intersection signal control optimization

Traffic congestion has substantially induced significant mobility and energy inefficiency. Many research challenges are identified in traffic signal control and management associated with artificial intelligence (AI)-based models. For example, developing AI-driven dynamic traffic system models that accurately capture high-resolution traffic attributes and formulate robust control algorithms for traffic signal optimization is difficult. Additionally, uncertainties in traffic system modeling and control processes can further complicate traffic signal system controllability. To partially address these challenges, this study presents a novel, hybrid neural network model enhanced with a probability density function kernel shaping technique to formulate traffic system dynamics better and improve comprehensive traffic network modeling and control. The numerical experimental tests were conducted, and the results demonstrate that the proposed control approach outperforms the baseline control strategies and reduces overall average delays by 11.64% on average. By leveraging the capabilities of this innovative model, this study aims to address major challenges related to traffic congestion and energy inefficiency toward more effective and adaptable AI-based traffic control systems.

Wang, Hong [Oak Ridge National Laboratory (ORNL), ↗
DOE OSTI2011

On a wave-particle in closed and open isotropic universes

The Klein-Gordon equation satisfied by the wave function in general relativity is solved for the metric of the closed and open universe corresponding to Einstein-De Sitter-Friedmann isotropic cosmological model. The angular dependences are specified by spherical harmonics for the longitude and latitude, and for the hyperlatitude by modified spherical harmonics having as variable circular functions for the closed universe and hyperbolic functions for the open universes. The time dependence of the probabilistic wave function is similar for the closed and open universes and is obtained in the following three cases: (I) constant Hubble parameter, (II) constant decceleration parameter, and (III) uniform matter and energy distribution, which corresponds to the Hubble parameter a linear function of time. Thus six solutions are obtained, namely, the three cases I-III each for closed and open isotropic universes. For each of these six solutions is considered: (i) the existence of singularities in space-time including asymptotic time in the future or past, (ii) the square integrability of the wave function over the full extent of the four-dimensional space-time, and (iii) the existence or otherwise of a positive probability density associated with the wave function.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2011

Stochastic Eulerian Lagrangian methods for fluid-structure interactions with thermal fluctuations

We present approaches for the study of fluid-structure interactions subject to thermal fluctuations. A mixed mechanical description is utilized combining Eulerian and Lagrangian reference frames. We establish general conditions for operators coupling these descriptions. Stochastic driving fields for the formalism are derived using principles from statistical mechanics. The stochastic differential equations of the formalism are found to exhibit significant stiffness in some physical regimes. To cope with this issue, we derive reduced stochastic differential equations for several physical regimes. We also present stochastic numerical methods for each regime to approximate the fluid-structure dynamics and to generate efficiently the required stochastic driving fields. To validate the methodology in each regime, we perform analysis of the invariant probability distribution of the stochastic dynamics of the fluid-structure formalism. We compare this analysis with results from statistical mechanics. To further demonstrate the applicability of the methodology, we perform computational studies for spherical particles having translational and rotational degrees of freedom. We compare these studies with results from fluid mechanics. The presented approach provides for fluid-structure systems a set of rather general computational methods for treating consistently structure mechanics, hydrodynamic coupling, and thermal fluctuations.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2018

Structure of Copper–Cobalt Surface Alloys in Equilibrium with Carbon Monoxide Gas

Here, we studied the structure of the copper–cobalt (CuCo) surface alloy, formed by Co deposition on Cu(110), in dynamic equilibrium with CO. Using scanning tunneling microscopy (STM), we found that, in vacuum at room temperature and at low Co coverage, clusters of a few Co atoms substituting Cu atoms form at the surface. At CO pressures in the Torr range, we found that up to 2.5 CO molecules can bind on a single Co atom, in carbonyl-like configurations. Based on high-resolution STM images, together with density functional theory calculations, we determined the most stable CuCo cluster structures formed with bound CO. Such carbonyl-like formation manifests in shifts in the binding energy of the Co core-level peaks in X-ray photoelectron spectra, as well as shifts in the vibrational modes of adsorbed CO in infrared reflection absorption spectra. The multiple CO adsorption on a Co site weakens the Co–CO bond and thus reduces the C–O bond scission probability. Our results may explain the different product distribution, including higher selectivity toward alcohol formation, when bimetallic CuCo catalysts are used compared to pure Co.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2014

Star-cluster mass and age distributions of two fields in M83 based on HST/WFC3 observations

We study star clusters in two fields in the nearby spiral galaxy M83 using broadband and narrowband optical imaging taken with the Wide Field Camera 3 onboard the Hubble Space Telescope. We present results on the basis of several different catalogs of star clusters in inner and outer fields, and we conclude that different methods of selection do not strongly affect the results, particularly for clusters older than ≈10 Myr. The age distributions can be described by a power law, dN/dτ∝τ{sup γ}, with γ ≈ –0.84 ± 0.12 in the inner field, and γ ≈ –0.48 ± 0.12 in the outer field for τ ≳ 10 Myr. We bracket the difference, Δγ, between the two fields to be in the 0.18 to 0.36 range, based on estimates of the relative star-formation histories. The mass functions can also be described by a power law, dN/dM∝M {sup β}, with β ≈ –1.98 ± 0.14 and β ≈ –2.34 ± 0.26 in the inner and outer fields, respectively. We conclude that the shapes of the mass and age distributions of the clusters in the two fields are similar, as predicted by the quasi-universal model. Any differences between the two fields are at the ≈2σ-3σ (≈1σ-2σ) level for the age (mass) distributions. Therefore, any dependence of these distributions on the local environment is probably weak. We compare the shapes of the distributions with those predicted by two popular cluster disruption models. We find that both show evidence that the clusters are disrupted at a rate that is approximately independent of their mass. We compare the shapes of the distributions with those predicted by two popular cluster disruption models, and find that both show evidence that the clusters are disrupted at a rate that is approximately independent of their mass, and that observational results do not support the earlier disruption of lower-mass clusters relative to their higher-mass counterparts.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2017

Soot and Spectral Radiation Modeling for a High-Pressure Turbulent Spray Flame

Simulations are performed of a transient high-pressure turbulent n-dodecane spray flame under engine-relevant conditions. An unsteady RANS formulation is used, with detailed chemistry, a semi-empirical two-equation soot model, and a particle-based transported composition probability density function (PDF) method to account for unresolved turbulent fluctuations in composition and temperature. Results from the PDF model are compared with those from a locally well-stirred reactor (WSR) model to quantify the effects of turbulence-chemistry-soot interactions. Computed liquid and vapor penetration versus time, ignition delay, and flame lift-off height are in good agreement with experiment, and relatively small differences are seen between the WSR and PDF models for these global quantities. Computed soot levels and spatial soot distributions from the WSR and PDF models show large differences, with PDF results being in better agreement with experimental measurements. An uncoupled photon Monte Carlo method with line-by-line spectral resolution is used to compute the spectral intensity distribution of the radiation leaving the flame. This provides new insight into the relative importance of molecular gas radiation versus soot radiation, and the importance of turbulent fluctuations on radiative heat transfer.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2022

Hot and dense matter equation of state probability distributions for astrophysical simulations

We add an ensemble of nuclei to the equation of state for homogeneous nucleonic matter to generate a new set of models suitable for astrophysical simulations of core-collapse supernovae and neutron star mergers. We implement empirical constraints from (i) nuclear mass measurements, (ii) proton-proton scattering phase shifts, and (iii) neutron star observations. Our model is also guided by microscopic many-body theory calculations based on realistic nuclear forces, including the zero-temperature neutron matter equation of state from quantum Monte Carlo simulations and thermal contributions to the free energy from finite-temperature many-body perturbation theory. We ensure that the parameters of our model can be varied while preserving thermodynamic consistency and the connection to experimental or observational data, thus providing a probability distribution of the astrophysical hot and dense matter equation of state. Furthermore, we compare our results with those obtained from other available equations of state. While our probability distributions indeed represent a large number of possible equations of state, we cannot yet claim to have fully explored all of the uncertainties, especially with regard to the structure of nuclei in the hot and dense medium.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2023

Detecting low-mass perturbers in cluster lenses using curved arc bases

ABSTRACT Strong gravitationally lensed arcs produced by galaxy clusters have been observationally detected for several decades now. These strong lensing constraints provided high-fidelity mass models for cluster lenses that include substructure down to $10^{9{-}10}\, \mathrm{M}_\odot$. Optimizing lens models, where the cluster mass distribution is modelled by a smooth component and subhaloes associated with the locations of individual cluster galaxies, has enabled deriving the subhalo mass function, providing important constraints on the nature and granularity of dark matter. In this work, we explore and present a novel method to detect and measure individual perturbers (subhaloes, line-of-sight haloes, and wandering supermassive black holes) by exploiting their proximity to highly distorted lensed arcs in galaxy clusters, and by modelling the local lensing distortions with curved arc bases. This method offers the possibility of detecting individual low-mass perturber subhaloes in clusters and haloes along the line of sight down to a mass resolution of $10^8\, \mathrm{M}_\odot$. We quantify our sensitivity to low-mass perturbers ($M\sim 10^{7{-}9}\, \mathrm{M}_\odot$) in clusters (M ∼ 1014–15 M⊙), by creating realistic mock data. Using three lensed images of a background galaxy in the cluster SMACS J0723, taken by JWST, we study the retrieval of the properties of potential perturbers with masses $M=10^{7{-}9}\, \mathrm{M}_\odot$. From the derived posterior probability distributions for the perturber, we constrain its concentration, redshift, and ellipticity. By allowing us to probe lower mass substructures, the use of curved arc bases can lead to powerful constraints on the nature of dark matter as discrimination between dark matter models appears on smaller scales.

Astronomy & Astrophysics↗
DOE OSTI2024

Deep Learning-Based Weather-Related Power Outage Prediction with Socio-Economic and Power Infrastructure Data

This paper presents a deep learning-based approach for hourly power outage probability prediction within census tracts encompassing a utility company's service territory. Two distinct deep learning models, conditional Multi-Layer Perceptron (MLP) and unconditional MLP, were developed to forecast power outage probabilities, leveraging a rich array of input features gathered from publicly available sources including weather data, weather station locations, power infrastructure maps, socio-economic and demographic statistics, and power outage records. Given a one-hour-ahead weather forecast, the models predict the power outage probability for each census tract, taking into account both the weather prediction and the location's characteristics. The deep learning models employed different loss functions to optimize prediction performance. Our experimental results underscore the significance of socio-economic factors in enhancing the accuracy of power outage predictions at the census tract level.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2021

Correlated Response of Protein Side-Chain Fluctuations and Conformational Entropy to Ligand Binding

The heterogeneous fast side-chain dynamics of proteins plays crucial roles in molecular recognition and binding. Site-specific NMR experiments quantify these motions by measuring the model-free order parameter (O axis 2 ) on a scale of 0 (most flexible) to 1 (least flexible) for each methyl-containing residue of proteins. In this work, we have examined ligand-induced variations in the fast side-chain dynamics and conformational entropy of calmodulin (CaM) using five different CaM–peptide complexes. O axis 2 of CaM in the ligand-free (O axis,U 2 ) and ligand-bound (O axis,B 2 ) states are calculated from molecular dynamics trajectories and conformational energy surfaces obtained using the adaptive biasing force (ABF) method. ΔO axis 2 = O axis,B 2 – O axis,U 2 follows a Gaussian-like unimodal distribution whose second moment is a potential indicator of the binding affinity of these complexes. The probability for the binding-induced O axis,U 2 → O axis,B 2 transition decreases with increasing magnitude of ΔO axis 2 , indicating that large flexibility changes are improbable for side chains of CaM after ligand binding. A linear correlation established between ΔOaxis2 and the conformational entropy change of the protein makes possible the determination of the conformational entropy of binding of protein–ligand complexes. The results not only underscore the functional importance of fast side-chain fluctuations but also highlight key motional and thermodynamic correlates of protein–ligand binding.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

On the Stochastic Stability of Deep Markov Models

Deep Markov models (DMM) are generative models which are scalable and expressive generalization of Markov models for representation, learning, and inference problems. DMMs using deep neural networks to parametrize the transition of Markov probability distributions have recently been shown to provide more expressiveness in modeling sequential data and dynamical system responses. However, the fundamental stochastic stability guarantees of such models have not been thoroughly investigated. In this paper, we present a rigorous analytical method to prove the necessary and sufficient conditions of DMM's stochastic stability. This task is achieved by spectral analysis of the efficiently computed Jacobians of probabilistic maps modeled by deep neural networks. We make theoretical connections between the eigenvalues of neural network's weights and the different activation function types used on the stability and overall dynamic behavior of DMMs with Gaussian distributions. We empirically substantiate our theoretical results on stochastic stability and eigenvalue spectra via several numerical experiments. Formal stability guarantees of DMMs can substantially improve their robustness and trustworthiness, necessary for reliable use in safety-critical real-world applications.

Drgona, Jan↗
DOE OSTI2011

Sensitivity of postplanning target and OAR coverage estimates to dosimetric margin distribution sampling parameters

Purpose: A dosimetric margin (DM) is the margin in a specified direction between a structure and a specified isodose surface, corresponding to a prescription or tolerance dose. The dosimetric margin distribution (DMD) is the distribution of DMs over all directions. Given a geometric uncertainty model, representing inter- or intrafraction setup uncertainties or internal organ motion, the DMD can be used to calculate coverage Q, which is the probability that a realized target or organ-at-risk (OAR) dose metric D{sub v} exceeds the corresponding prescription or tolerance dose. Postplanning coverage evaluation quantifies the percentage of uncertainties for which target and OAR structures meet their intended dose constraints. The goal of the present work is to evaluate coverage probabilities for 28 prostate treatment plans to determine DMD sampling parameters that ensure adequate accuracy for postplanning coverage estimates. Methods: Normally distributed interfraction setup uncertainties were applied to 28 plans for localized prostate cancer, with prescribed dose of 79.2 Gy and 10 mm clinical target volume to planning target volume (CTV-to-PTV) margins. Using angular or isotropic sampling techniques, dosimetric margins were determined for the CTV, bladder and rectum, assuming shift invariance of the dose distribution. For angular sampling, DMDs were sampled at fixed angular intervals {omega} (e.g., {omega}=1 deg., 2 deg., 5 deg., 10 deg., 20 deg.). Isotropic samples were uniformly distributed on the unit sphere resulting in variable angular increments, but were calculated for the same number of sampling directions as angular DMDs, and accordingly characterized by the effective angular increment {omega}{sub eff}. In each direction, the DM was calculated by moving the structure in radial steps of size {delta}(=0.1,0.2,0.5,1 mm) until the specified isodose was crossed. Coverage estimation accuracy {Delta}Q was quantified as a function of the sampling parameters {omega} or {omega}{sub eff} and {delta}. Results: The accuracy of coverage estimates depends on angular and radial DMD sampling parameters {omega} or {omega}{sub eff} and {delta}, as well as the employed sampling technique. Target |{Delta}Q|<1% and OAR |{Delta}Q|<3% can be achieved with sampling parameters {omega} or {omega}{sub eff}=20 deg., {delta}=1 mm. Better accuracy (target |{Delta}Q|<0.5% and OAR |{Delta}Q|<{approx}1%) can be achieved with {omega} or {omega}{sub eff}=10 deg., {delta}=0.5 mm. As the number of sampling points decreases, the isotropic sampling method maintains better accuracy than fixed angular sampling. Conclusions: Coverage estimates for post-planning evaluation are essential since coverage values of targets and OARs often differ from the values implied by the static margin-based plans. Finer sampling of the DMD enables more accurate assessment of the effect of geometric uncertainties on coverage estimates prior to treatment. DMD sampling with {omega} or {omega}{sub eff}=10 deg. and {delta}=0.5 mm should be adequate for planning purposes.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2021

Potential of hotspot solar‐induced chlorophyll fluorescence for better tracking terrestrial photosynthesis

Abstract Remote sensing of solar‐induced fluorescence (SIF) opens a new window for quantifying a key ecological variable, the terrestrial ecosystem gross primary production (GPP), because of the revealed strong SIF–GPP correlation. However, similar to many other remotely sensed metrics, SIF observations suffer from the sun‐sensor geometry effects, which may have important impacts on the SIF–GPP relationship but remain poorly understood. Here we used remotely sensed SIF, globally distributed tower GPP data, and a mechanistic model to provide a systematic analysis. Our results reveal that leaf physiology, canopy structure, and sun‐sensor geometries all affect the SIF–GPP relationship. In particular, we found that SIF observations in the sun‐tracking hotspot direction can be a better proxy of GPP due to the similar responses of light use efficiency and SIF escaping probability in the hotspot direction to the increasing incoming solar radiation. Such conclusions are supported by a variety of modeling simulations and satellite observations over various plant function types, at different time scales and with satellite observational modes. This study demonstrates the potential and advantage of normalizing SIF observations to the hotspot direction for better global GPP estimations. This study also demonstrates the great potentials of current and future spaceborne sun‐tracking satellite missions for a significant improvement in measuring and monitoring, at a wide range of spatial and temporal scales, the changes in terrestrial ecosystem GPP in response to anticipated changes in the Earth's environmental conditions.

Hao, Dalei↗
DOE OSTI2017

Langmuir probe study of an inductively coupled magnetic-pole-enhanced helium plasma

This study reports the effects of RF power and filling gas pressure variation on the plasma parameters, including the electron number density n{sub e}, electron temperature T{sub e}, plasma potential V{sub p}, skin depth δ, and electron energy probability functions (EEPFs) in a low-pressure inductively coupled helium plasma source with magnetic pole enhancement. An RF compensated Langmuir probe is used to measure these plasma parameters. It is observed that the electron number density increases with both the RF power and the filling gas pressure. Conversely, the electron temperature decreases with increasing RF power and gas pressure. It is also noted that, at low RF powers and gas pressures, the EEPFs are non-Maxwellian, while at RF powers of ≥50 W, they evolve into a Maxwellian distribution. The dependences of the skin depth and plasma potential on the RF power are also studied and show a decreasing trend.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗