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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 811 records · Page 45
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

2D k -th nearest neighbour statistics: a highly informative probe of galaxy clustering

ABSTRACT Beyond standard summary statistics are necessary to summarize the rich information on non-linear scales in the era of precision galaxy clustering measurements. For the first time, we introduce the 2D k-th nearest neighbour (kNN) statistics as a summary statistic for discrete galaxy fields. This is a direct generalization of the standard 1D kNN by disentangling the projected galaxy distribution from the redshift-space distortion signature along the line-of-sight. We further introduce two different flavours of 2D kNNs that trace different aspects of the galaxy field: the standard flavour which tabulates the distances between galaxies and random query points, and a ‘DD’ flavour that tabulates the distances between galaxies and galaxies. We showcase the 2D kNNs’ strong constraining power both through theoretical arguments and by testing on realistic galaxy mocks. Theoretically, we show that 2D kNNs are computationally efficient and directly generate other statistics such as the popular two-point correlation function (2PCF), voids probability function, and counts-in-cell statistics. In a more practical test, we apply the 2D kNN statistics to simulated galaxy mocks that fold in a large range of observational realism and recover parameters of the underlying extended halo occupation distribution (HOD) model that includes velocity bias and galaxy assembly bias. We find unbiased and significantly tighter constraints on all aspects of the HOD model with the 2D kNNs, both compared to the standard 1D kNN, and the classical redshift-space 2PCF.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2013

Effects of dilute aqueous NaCl solution on caffeine aggregation

The effect of salt concentration on association properties of caffeine molecule was investigated by employing molecular dynamics simulations in isothermal-isobaric ensemble of eight caffeine molecules in pure water and three different salt (NaCl) concentrations, at 300 K temperature and 1 atm pressure. The concentration of caffeine was taken almost at the solubility limit. With increasing salt concentration, we observe enhancement of first peak height and appearance of a second peak in the caffeine-caffeine distribution function. Furthermore, our calculated solvent accessible area values and cluster structure analyses suggest formation of higher order caffeine cluster on addition of salt. The calculated hydrogen bond properties reveal that there is a modest decrease in the average number of water-caffeine hydrogen bonds on addition of NaCl salt. Also observed are: (i) decrease in probability of salt contact ion pair as well as decrease in the solvent separated ion pair formation with increasing salt concentration, (ii) a modest second shell collapse in the water structure, and (iii) dehydration of hydrophobic atomic sites of caffeine on addition of NaCl.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2012

PLANET OCCURRENCE WITHIN 0.25 AU OF SOLAR-TYPE STARS FROM KEPLER

We report the distribution of planets as a function of planet radius, orbital period, and stellar effective temperature for orbital periods less than 50 days around solar-type (GK) stars. These results are based on the 1235 planets (formally 'planet candidates') from the Kepler mission that include a nearly complete set of detected planets as small as 2 R{sub Circled-Plus }. For each of the 156,000 target stars, we assess the detectability of planets as a function of planet radius, R{sub p}, and orbital period, P, using a measure of the detection efficiency for each star. We also correct for the geometric probability of transit, R{sub *}/a. We consider first Kepler target stars within the 'solar subset' having T{sub eff} = 4100-6100 K, log g 4.0-4.9, and Kepler magnitude Kp < 15 mag, i.e., bright, main-sequence GK stars. We include only those stars having photometric noise low enough to permit detection of planets down to 2 R{sub Circled-Plus }. We count planets in small domains of R{sub p} and P and divide by the included target stars to calculate planet occurrence in each domain. The resulting occurrence of planets varies by more than three orders of magnitude in the radius-orbital period plane and increases substantially down to the smallest radius (2 R{sub Circled-Plus }) and out to the longest orbital period (50 days, {approx}0.25 AU) in our study. For P < 50 days, the distribution of planet radii is given by a power law, df/dlog R = k{sub R}R{sup {alpha}} with k{sub R} = 2.9{sup +0.5}{sub -0.4}, {alpha} = -1.92 {+-} 0.11, and R {identical_to} R{sub p}/R{sub Circled-Plus }. This rapid increase in planet occurrence with decreasing planet size agrees with the prediction of core-accretion formation but disagrees with population synthesis models that predict a desert at super-Earth and Neptune sizes for close-in orbits. Planets with orbital periods shorter than 2 days are extremely rare; for R{sub p} > 2 R{sub Circled-Plus} we measure an occurrence of less than 0.001 planets per star. For all planets with orbital periods less than 50 days, we measure occurrence of 0.130 {+-} 0.008, 0.023 {+-} 0.003, and 0.013 {+-} 0.002 planets per star for planets with radii 2-4, 4-8, and 8-32 R{sub Circled-Plus }, in agreement with Doppler surveys. We fit occurrence as a function of P to a power-law model with an exponential cutoff below a critical period P{sub 0}. For smaller planets, P{sub 0} has larger values, suggesting that the 'parking distance' for migrating planets moves outward with decreasing planet size. We also measured planet occurrence over a broader stellar T{sub eff} range of 3600-7100 K, spanning M0 to F2 dwarfs. Over this range, the occurrence of 2-4 R{sub Circled-Plus} planets in the Kepler field increases with decreasing T{sub eff}, with these small planets being seven times more abundant around cool stars (3600-4100 K) than the hottest stars in our sample (6600-7100 K).

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2011

Time operators in stroboscopic wave-packet basis and the time scales in tunneling

We demonstrate that the time operator that measures the time of arrival of a quantum particle into a chosen state can be defined as a self-adjoint quantum-mechanical operator using periodic boundary conditions and applied to wave functions in energy representation. The time becomes quantized into discrete eigenvalues; and the eigenstates of the time operator, i.e., the stroboscopic wave packets introduced recently [Phys. Rev. Lett. 101, 046402 (2008)], form an orthogonal system of states. The formalism provides simple physical interpretation of the time-measurement process and direct construction of normalized, positive definite probability distribution for the quantized values of the arrival time. The average value of the time is equal to the phase time but in general depends on the choice of zero time eigenstate, whereas the uncertainty of the average is related to the traversal time and is independent of this choice. The general formalism is applied to a particle tunneling through a resonant tunneling barrier in one dimension.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2022

Game-Theoretic Strategies for Cyber-Physical Infrastructures Under Component Disruptions

In this work, networked infrastructures of recursively defined systems composed of discrete cyber and physical components are considered. The components of basic systems at the finest levels can be disrupted by cyber or physical means, and can be reinforced to survive at certain costs. A problem of ensuring the infrastructure performance is formulated as a game between a provider and an attacker, who probabilistically choose components to reinforce and attack, respectively. The disruptions of this infrastructure are characterized using the aggregate failure correlation function that specifies the conditional failure probability of the infrastructure given the failure of an individual system at that level. The survival probabilities of basic systems satisfy simple product-form, first-order differential equations expressed in terms of the multiplier functions. The utility functions of the provider and attacker are composed of the reward and cost terms, both expressed in terms of the component reinforcement and attack probabilities. The Nash equilibrium of this game is characterized, along with the sensitivity functions of the survival probabilities of basic systems that highlight their dependence individually on the cost-benefit terms, the correlation functions, and the multiplier functions. These results are illustrated using simplified models of a distributed cloud servers infrastructure, a 5G data network infrastructure, a high performance computing federation, and a smart energy grid infrastructure.

42 ENGINEERING↗
DOE OSTI2018

New approaches for understanding the statistics of daily weather extremes in a changing climate. SARDESHMUKH_Final_Technical_Report_Extremes_DE-SC0006965

This project quantified the changes in the mean climate and climate variability over the last 140 years, with emphasis on the changes in the tails of the probability distributions of daily variations, i.e. changes in extreme weather statistics. We were interested in not just the mean shifts of the distributions under climate change but also changes in the variance and higher statistical moments such as skewness and kurtosis. The project focused on two important aspects of the probability density functions (pdfs) of daily anomalies and their estimations from observational records of limited length. The first is that the pdfs are not Gaussian but are distinctively skewed and heavy tailed. This has large implications for the probabilities of extreme values and for estimating those probabilities from limited records. It also motivated our second focus, to estimate the pdfs from the longest available global datasets based on instrumental observations.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2015

Dependence in probabilistic modeling Dempster-Shafer theory and probability bounds analysis

This report summarizes methods to incorporate information (or lack of information) about inter-variable dependence into risk assessments that use Dempster-Shafer theory or probability bounds analysis to address epistemic and aleatory uncertainty. The report reviews techniques for simulating correlated variates for a given correlation measure and dependence model, computation of bounds on distribution functions under a specified dependence model, formulation of parametric and empirical dependence models, and bounding approaches that can be used when information about the intervariable dependence is incomplete. The report also reviews several of the most pervasive and dangerous myths among risk analysts about dependence in probabilistic models.

Ferson, Scott↗
DOE OSTI2014

Momentum conserving Brownian dynamics propagator for complex soft matter fluids

We present a Galilean invariant, momentum conserving first order Brownian dynamics scheme for coarse-grained simulations of highly frictional soft matter systems. Friction forces are taken to be with respect to moving background material. The motion of the background material is described by locally averaged velocities in the neighborhood of the dissolved coarse coordinates. The velocity variables are updated by a momentum conserving scheme. The properties of the stochastic updates are derived through the Chapman-Kolmogorov and Fokker-Planck equations for the evolution of the probability distribution of coarse-grained position and velocity variables, by requiring the equilibrium distribution to be a stationary solution. We test our new scheme on concentrated star polymer solutions and find that the transverse current and velocity time auto-correlation functions behave as expected from hydrodynamics. In particular, the velocity auto-correlation functions display a long time tail in complete agreement with hydrodynamics.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2016

Sampling Polymorphs of Ionic Solids using Random Superlattices

Polymorphism offers rich and virtually unexplored space for discovering novel functional materials. To harness this potential approaches capable of both exploring the space of polymorphs and assessing their realizability are needed. Here, one such approach devised for partially ionic solids is presented. The structure prediction part is carried out by performing local density functional theory relaxations on a large set of random supperlattices (RSLs) with atoms distributed randomly over different planes in a way that favors cation-anion coordination. Applying the RSL sampling on MgO, ZnO, and SnO 2 reveals that the resulting probability of occurrence of a given structure offers a measure of its realizability explaining fully the experimentally observed, metastable polymorphs in these three systems.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2015

POPULATION EFFECTS ON THE METALLICITY DISTRIBUTION FUNCTION DERIVED FROM THE RED GIANT BRANCH

We have tested the reliability of the red giant branch (RGB) as a metallicity indicator accounting for observational errors as well as the complexity of star formation histories and chemical evolution histories observed in various stellar systems. We generate model color–magnitude diagrams (CMDs) produced with a variety of evolutionary histories and compare the resultant metallicity estimates from the colors and magnitudes of RGB stars to the true input metallicities. We include realistic models for photometric errors and completeness in our synthetic CMDs. As expected, for simple simple stellar populations dominated by old stars, the RGB provides a very accurate estimate of the modular metallicity value for a population. An error in the age of a system targeted for this type of study may produce metallicity errors of a few tenths of a dex. The size of this metallicity error depends linearly on the age error, and we find this dependence to be stronger with more precise photometry. If the population has experienced any significant star formation within the last ∼6 Gyr, the metallicity estimates, [M/H], derived from the RGB may be in error by up to ∼0.5 dex. Perhaps the most important consideration for this technique is an accurate, independent estimate of the average age for the target stellar system, especially if it is probable that a significant fraction of the population formed less than ∼6 Gyr ago.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2011

Universal Relations for Identical Bosons from Three-Body Physics

Systems consisting of identical bosons with a large scattering length satisfy universal relations determined by 2-body physics that are similar to those for fermions with two spin states. They require the momentum distribution to have a large-momentum 1/k{sup 4} tail and the radio-frequency transition rate to have a high-frequency 1/{omega}{sup 3/2} tail, both of which are proportional to the 2-body contact. Identical bosons also satisfy additional universal relations that are determined by 3-body physics and involve the 3-body contact, which measures the probability of 3 particles being very close together. The coefficients of the 3-body contact in the 1/k{sup 5} tail of the momentum distribution and in the 1/{omega}{sup 2} tail of the radio-frequency transition rate are log-periodic functions of k and {omega} that depend on the Efimov parameter.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2013

Improving experimental phases for strong reflections prior to density modification

A genetic algorithm has been developed to optimize the phases of the strongest reflections in SIR/SAD data. This is shown to facilitate density modification and model building in several test cases. Experimental phasing of diffraction data from macromolecular crystals involves deriving phase probability distributions. These distributions are often bimodal, making their weighted average, the centroid phase, improbable, so that electron-density maps computed using centroid phases are often non-interpretable. Density modification brings in information about the characteristics of electron density in protein crystals. In successful cases, this allows a choice between the modes in the phase probability distributions, and the maps can cross the borderline between non-interpretable and interpretable. Based on the suggestions by Vekhter [Vekhter (2005 ▶), Acta Cryst. D61, 899–902], the impact of identifying optimized phases for a small number of strong reflections prior to the density-modification process was investigated while using the centroid phase as a starting point for the remaining reflections. A genetic algorithm was developed that optimizes the quality of such phases using the skewness of the density map as a target function. Phases optimized in this way are then used in density modification. In most of the tests, the resulting maps were of higher quality than maps generated from the original centroid phases. In one of the test cases, the new method sufficiently improved a marginal set of experimental SAD phases to enable successful map interpretation. A computer program, SISA, has been developed to apply this method for phase improvement in macromolecular crystallography.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2021

Lessons Learned in Employing Data Analytics to Predict Oxidation Kinetics and Spallation Behavior of High-Temperature NiCr-Based Alloys

Machine learning (ML) can offer many advantages in predicting material properties over traditional materials development methods based solely on limited experimental investigations or physical-based simulations with the capability to reduce development cost, risk, and time. However, so far, limited efforts have been made to predict alloy oxidation kinetics and spallation behavior via ML due to the lack of consistently measured and sufficient experimental data and the inherent complexity in oxidation behavior of multicomponent high-temperature alloys. A previous study reported the ability of ML to predict oxidation kinetics of NiCr-based alloys as a function of alloy composition and operating conditions. Here, the performance of a ML model in predicting rate constants and spallation probability was evaluated in light of the roles of the data distribution of the experimental dataset (data analytics), the alloy composition, the exposure environment and the chosen oxidation approach to extracting kinetic values from the measured mass changes (but using either a simple parabolic law or a statistical cyclic oxidation model). Potential strategies to improve the predictions and enhance the extrapolative capability of the previously trained model will be discussed.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Unified, Geometric Framework for Nonequilibrium Protocol Optimization

Controlling thermodynamic cycles to minimize the dissipated heat is a long-standing goal in thermodynamics, and more recently, a central challenge in stochastic thermodynamics for nanoscale systems. Here, we introduce a theoretical and computational framework for optimizing nonequilibrium control protocols that can transform a system between two distributions in a minimally dissipative fashion. These protocols optimally transport a system along paths through the space of probability distributions that minimize the dissipative cost of a transformation. Furthermore, we show that the thermodynamic metric—determined via a linear response approach—can be directly derived from the same objective function that is optimized in the optimal transport problem, thus providing a unified perspective on thermodynamic geometries. As a result, we investigate this unified geometric framework in two model systems and observe that our procedure for optimizing control protocols is robust beyond linear response.

36 MATERIALS SCIENCE↗
DOE OSTI2011

Fine structure of strength functions for beta decays of atomic nuclei

The β transition strength function S{sub β}(E) is the nuclear excitation energy distribution of moduli squared of the β-decay-type matrix elements. The function S{sub β}(E) determines the characteristics of β decay, the spectra of accompanying radiation, and the probabilities of delayed processes following the β decay. Until recently, tools widely used for experimental investigation of the S{sub β}(E) structure have been total absorption gamma spectrometers and total absorption gamma-ray spectroscopy (TAGS) which could not provide high energy resolution. Development of experimental techniques allows nuclear spectroscopy methods with high energy resolution to be used for studying the fine structure of S{sub β}(E). A thorough investigation of this kind has been carried out for a number of nuclei produced at the YASNAPP-2 facility in Dubna. In this review, studies involving works on measuring the fine structure of S{sub β}(E) in spherical and deformed nuclei are analyzed. Modern nuclear spectroscopy methods made it possible to identify the splitting of peaks from nuclear deformation in S{sub β}(E) for Gamow-Teller (GT) transitions. The resonance nature of S{sub β}(E) for first-forbidden (FF) transitions in both spherical and deformed nuclei is experimentally proven. It is shown that for some nuclear excitation energies, FF transitions can be comparable in intensity with GT transitions. Criteria for verifying the completeness of nuclear decay schemes are considered. The S{sub β}(E) functions obtained by TAGS and by the high-resolution spectroscopy are compared.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2013

Evaluating and Constraining Ice Cloud Parameterizations in CAM5 using Aircraft Measurements from the SPARTICUS Campaign

This study uses aircraft measurements of relative humidity and ice crystal size distribution collected in synoptic cirrus during the SPARTICUS (Small PARTicles In CirrUS) field campaign to evaluate and constrain ice cloud parameterizations in the Community Atmosphere Model version 5. The probability density function (PDF) of ice crystal number concentration (Ni) derived from high frequency (1 Hz) measurements features a strong dependence on ambient temperature. As temperature decreases from -35°C to -62°C, the peak in the PDF shifts from 10-20 L-1 to 200-1000 L-1, while the ice crystal number concentration shows a factor of 6-7 increase. Model simulations are performed with two different insitu ice nucleation schemes. One of the schemes can reproduce a clear increase of Ni with decreasing temperature, by using either an observation based ice nuclei spectrum or a classical theory based spectrum with a relatively low (5%-10%) maximum freezing ratio for dust aerosols. The simulation with the other scheme, which assumes a high maximum freezing ratio (100%), shows much weaker temperature dependence of Ni. Simulations are also performed to test empirical parameters related to water vapor deposition and the auto-conversion of ice crystals to snow. Results show that a value between 0.05 and 0.1 for the water vapor deposition coefficient and 250 um for the critical ice crystal size can produce good agreements between model simulation and the SPARTICUS measurements in terms of ice crystal number concentration and effective radius. The climate impact of perturbing these parameters is also discussed.

AIRCRAFT↗