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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 1,477 records · Page 82
All sourcesNASA NTRSDOE OSTI
DOE OSTI2017

Indirect Validation of Probe Speed Data on Arterial Corridors

This study aimed to estimate the accuracy of probe speed data on arterial corridors on the basis of roadway geometric attributes and functional classification. It was assumed that functional class (medium and low) along with other road characteristics (such as weighted average of the annual average daily traffic, average signal density, average access point density, and average speed) were available as correlation factors to estimate the accuracy of probe traffic data. This study tested these factors as predictors of the fidelity of probe traffic data by using the results of an extensive validation exercise. This study showed strong correlations between these geometric attributes and the accuracy of probe data when they were assessed by using average absolute speed error. Linear models were regressed to existing data to estimate appropriate models for medium- and low-type arterial corridors. The proposed models for medium- and low-type arterials were validated further on the basis of the results of a slowdown analysis. These models can be used to predict the accuracy of probe data indirectly in medium and low types of arterial corridors.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2024

Crystal Engineering of Hydrogen Bonding for Direct Air Capture of CO2: A Quantum Crystallography Perspective

Rising atmospheric CO2 levels demand efficient and sustainable carbon capture solutions. Direct air capture (DAC) via crystallizing hydrogen-bonded frameworks such as carbonate salts has emerged as a promising approach. This review explores the potential of crystal engineering, in tandem with advanced quantum crystallography techniques and computational modeling, to unlock the full potential of DAC materials. We examine the critical role of hydrogen bonding and other noncovalent interactions within a family of bis-guanidines that governs the formation of carbonate salts with high CO2 capture capacity and low regeneration energies for utilization. Quantum crystallography and charge density analysis prove instrumental in elucidating these interactions. A case study of a highly insoluble carbonate salt of a 2,6-pyridine-bis-(iminoguanidine) exemplifies the effectiveness of these approaches. However, challenges remain in the systematic and precise determination of hydrogen atom positions and atomic displacement parameters within DAC materials using quantum crystallography, and limitations persist in the accuracy of current energy estimation models for hydrogen bonding interactions. Future directions lie in exploring diverse functional groups, designing advanced hydrogen-bonded frameworks, and seamlessly integrating experimental and computational modeling with machine learning. This synergistic approach promises to propel the design and optimization of DAC materials, paving the way for a more sustainable future.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Self-Cleaning Highly Porous TiO 2 Coating Designed by Swelling-Assisted Sequential Infiltration Synthesis (SIS) of a Block Copolymer Template

Photocatalytic self-cleaning coatings with a high surface area are important for a wide range of applications, including optical coatings, solar panels, mirrors, etc. Here, we designed a highly porous TiO 2 coating with photoinduced self-cleaning characteristics and very high hydrophilicity. This was achieved using the swelling-assisted sequential infiltration synthesis (SIS) of a block copolymer (BCP) template, which was followed by polymer removal via oxidative thermal annealing. The quartz crystal microbalance (QCM) was employed to optimize the infiltration process by estimating the mass of material infiltrated into the polymer template as a function of the number of SIS cycles. This adopted swelling-assisted SIS approach resulted in a smooth uniform TiO 2 film with an interconnected network of pores. The synthesized film exhibited good crystallinity in the anatase phase. The resulting nanoporous TiO 2 coatings were tested for their functional characteristics. Exposure to UV irradiation for 1 h induced an improvement in the hydrophilicity of coatings with wetting angle reducing to unmeasurable values upon contact with water droplets. Furthermore, their self-cleaning characteristics were tested by measuring the photocatalytic degradation of methylene blue (MB). The synthesized porous TiO 2 nanostructures displayed promising photocatalytic activity, demonstrating the degradation of approximately 92% of MB after 180 min under ultraviolet (UV) light irradiation. Thus, the level of performance was comparable to the photoactivity of commercial anatase TiO 2 nanoparticles of the same quantity. Our results highlight a new robust approach for designing hydrophilic self-cleaning coatings with controlled porosity and composition.

36 MATERIALS SCIENCE↗
DOE OSTI2017

EmpiriciSN: Re-sampling Observed Supernova/Host Galaxy Populations Using an XD Gaussian Mixture Model

We describe two new open-source tools written in Python for performing extreme deconvolution Gaussian mixture modeling (XDGMM) and using a conditioned model to re-sample observed supernova and host galaxy populations. XDGMM is new program that uses Gaussian mixtures to perform density estimation of noisy data using extreme deconvolution (XD) algorithms. Additionally, it has functionality not available in other XD tools. It allows the user to select between the AstroML and Bovy et al. fitting methods and is compatible with scikit-learn machine learning algorithms. Most crucially, it allows the user to condition a model based on the known values of a subset of parameters. This gives the user the ability to produce a tool that can predict unknown parameters based on a model that is conditioned on known values of other parameters. EmpiriciSN is an exemplary application of this functionality, which can be used to fit an XDGMM model to observed supernova/host data sets and predict likely supernova parameters using a model conditioned on observed host properties. It is primarily intended to simulate realistic supernovae for LSST data simulations based on empirical galaxy properties.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2017

A revised planetary nebula luminosity function distance to NGC 628 using MUSE

Distance uncertainties plague our understanding of the physical scales relevant to the physics of star formation in extragalactic studies. The planetary nebulae luminosity function (PNLF) is one of very few techniques that can provide distance estimates to within ∼10%; however, it requires a planetary nebula (PN) sample that is uncontaminated by other ionizing sources. We employ optical integral field unit spectroscopy using the Multi-Unit Spectroscopic Explorer on the Very Large Telescope to measure [O iii] line fluxes for sources unresolved on 50 pc scales within the central star-forming galaxy disk of NGC 628. We use diagnostic line ratios to identify 62 PNe, 30 supernova remnants, and 87 H ii regions within our fields. Using the 36 brightest PNe, we determine a new PNLF distance modulus of 29.91{sub −0.13}{sup +0.08} mag (9.59{sub −0.57}{sup +0.35} Mpc), which is in good agreement with literature values, but significantly larger than the previously reported PNLF distance. We are able to explain the discrepancy and recover the previous result when we reintroduce SNR contaminants to our sample. This demonstrates the power of full spectral information over narrowband imaging in isolating PNe. Given our limited spatial coverage within the Galaxy, we show that this technique can be used to refine distance estimates, even when IFU observations cover only a fraction of a galaxy disk.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2020

Relaxation time estimation in surface NMR

Technologies including NMR relaxation time estimation methods and corresponding apparatus are disclosed. Example techniques may include performing at least one single-pulse acquisition sequence, the single-pulse acquisition sequence comprising transmitting a single modulated pulse with a surface coil, wherein the phase, frequency, or amplitude of the single modulated pulse is varied during the single modulated pulse, and wherein the single modulated pulse excites a transverse magnetization component within a subsurface fluid. The resulting NMR signal may be recorded on at least one receiving device, including recording the NMR signal associated with the transverse magnetization component excited by the single modulated pulse. Processing techniques may be applied in which recorded NMR response data are used to estimate NMR properties and the relaxation times T1 and T2* as a function of position as well as one-dimensional and two-dimension distributions of T1 versus T2* as a function of subsurface position.

58 GEOSCIENCES↗
DOE OSTI2016

Assessment of Multi-Step CADIS Parameter Sensitivity to Neutron Flux Spectrum in Shutdown Dose Rate Calculations

Shutdown dose rate (SDDR) analysis requires (a) a neutron transport calculation to estimate neutron flux fields, (b) an activation calculation to compute radionuclide inventories and associated photon sources, and (c) a photon transport calculation to estimate final dose rate. In some applications, accurate full-scale Monte Carlo (MC) SDDR simulations are needed for very large systems with massive amounts of shielding materials. For example, SDDR assessments are required throughout the biological shield (bio-shield) of the ITER experimental facility to evaluate the required waiting period after the shutdown of ITER and to identify the locations where human accessibility should be prohibited. The bio-shield is a large cylindrical concrete structure (30 m tall and 34 m in diameter) surrounding the very complex tokamak machine. Determining the effects on SDDR of important factors, such as the cross talk (interactions) between the different ports of ITER, is possible only through full-scale simulations that involve all the complex inner details of the ITER tokamak machine. These simulations are impractical because calculation of space- and energy-dependent neutron fluxes throughout the structural materials is needed to estimate the distribution of radioisotopes causing the SDDR. Determining a good importance function that can be used in biasing a neutron MC calculation for SDDR is complicated because it is difficult to explicitly express the SDDR response function, which depends on subsequent computational steps. The Multi-Step Consistent Adjoint Driven Importance Sampling (MS-CADIS) hybrid MC/deterministic method was developed to speed up the SDDR MC neutron transport calculation using an importance function that represents the neutron importance to the final SDDR. The MS-CADIS method uses the CADIS method, which has been Notice: This manuscript has been authored by UT-Battelle, LLC, under Contract No. DE-AC0500OR22725 with the U.S. Department of Energy. The United States Government retains and the publisher, by accepting the article for publication, acknowledges that the United States Government retains a non-exclusive, paid-up, irrevocable, world-wide license to publish or reproduce the published form of this manuscript, or allow others to do so, for the United States Government purposes. The Department of Energy will provide public access to these results of federally sponsored research in accordance with the DOE Public Access Plan (http://energy.gov/downloads/doe-public-access-plan). successfully used for more than a decade in radiation shielding applications to generate consistent source biasing and weight window (WW) variance reduction parameters to accelerate continuous-energy MC simulations. However, because MS-CADIS focuses on multi-step shielding calculations such as SDDR calculations, it develops an importance function for the initial radiation transport calculation (e.g., the neutron calculations in SDDR simulations) that represents the importance of particles to the final response of the overall simulation. To develop this importance function, the MS-CADIS method uses an adjoint calculation with a specific neutron adjoint source that represents the neutron's contribution to the final SDDR. Brute force calculation of the MS-CADIS neutron adjoint source requires a deterministic neutron transport calculation coupled with activation calculations in each element of the deterministic mesh. These calculations are needed to determine the MS-CADIS parameter for the neutron interactions that produce radioisotopes contributing to the SDDR. The MS-CADIS parameter is the microscopic cross section of the radioisotope-producing interaction, multiplied by the mass of this radioisotope existing at the end of the irradiation and decay scenario, and divided by the steady-state rate of the interaction. Because the activation calculations are performed for each radionuclide in each mesh element, implementation of the MS-CADIS method can be computationally expensive. However, these neutron transport and activation calculations are not needed if we assume that the radioisotopes are created due to single neutron interactions and their concentrations do not change as a result of burnup by neutron irradiation. The use of this approximation, which renders the MS-CADIS parameter independent of the neutron flux, seems reasonable in calculating the MS-CADIS importance function because this function is needed only to speed up the MC calculation, not to calculate the final SDDR. In this work, we investigate the validity of this approximation by investigating the behavior of the MS-CADIS parameter as a function of the neutron flux spectra in the Fusion Evaluated Nuclear Data Library (FENDL) Neutronics and Shielding Benchmark problem that contains representative isotopes and flux environments of fusion energy systems. (authors)

61 RADIATION PROTECTION AND DOSIMETRY↗
DOE OSTI2019

Semi-inclusive deep-inelastic scattering, parton distributions, and fragmentation functions at a future electron-ion collider

We present a quantitative assessment of the impact a future electron-ion collider would have in the determination of parton distribution functions in the proton and parton-to-hadron fragmentation functions through semi-inclusive deep-inelastic electron-proton scattering data. Specifically, we estimate the kinematic regions for which the forthcoming data are expected to have the most significant impact in the precision of these distributions, computing the respective correlation and sensitivity coefficients. Using a reweighting technique for the sets of simulated data with their realistic uncertainties for two different center-of-mass energies, we analyze the resulting new sets of parton distribution functions and fragmentation functions, which have significantly reduced uncertainties.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2014

Planck 2013 results. XX. Cosmology from Sunyaev–Zeldovich cluster counts

We present constraints on cosmological parameters using number counts as a function of redshift for a sub-sample of 189 galaxy clusters from the Planck SZ (PSZ) catalogue. The PSZ is selected through the signature of the Sunyaev-Zeldovich (SZ) effect, and the sub-sample used here has a signal-to-noise threshold of seven, with each object confirmed as a cluster and all but one with a redshift estimate. We discuss the completeness of the sample and our construction of a likelihood analysis. Using a relation between mass M and SZ signal Y calibrated to X-ray measurements, we derive constraints on the power spectrum amplitude σ8 and matter density parameter Ω m in a flat ΛCDM model. We test the robustness of our estimates and find that possible biases in the Y–M relation and the halo mass function are larger than the statistical uncertainties from the cluster sample. Assuming the X-ray determined mass to be biased low relative to the true mass by between zero and 30%, motivated by comparison of the observed mass scaling relations to those from a set of numerical simulations, we find that σ 8 = 0.75 ± 0.03, Ω m = 0.29 ± 0.02, and σ 8 (Ω m /0.27) 0.3 = 0.764 ± 0.025. The value of σ 8 is degenerate with the mass bias; if the latter is fixed to a value of 20% (the central value from numerical simulations) we find σ 8 (Ω m /0.27) 0.3 = 0.78 ± 0.01 and a tighter one-dimensional range σ 8 = 0.77 ± 0.02. We find that the larger values of σ 8 and Ω m preferred by Planck's measurements of the primary CMB anisotropies can be accommodated by a mass bias of about 40%. Alternatively, consistency with the primary CMB constraints can be achieved by inclusion of processes that suppress power on small scales relative to the ΛCDM model, such as a component of massive neutrinos. We place our results in the context of other determinations of cosmological parameters, and discuss issues that need to be resolved in order to make further progress in this field.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2014

The structure of PX{sub 3} (X = Cl, Br, I) molecular liquids from X-ray diffraction, molecular dynamics simulations, and reverse Monte Carlo modeling

Synchrotron X-ray diffraction measurements have been conducted on liquid phosphorus trichloride, tribromide, and triiodide. Molecular Dynamics simulations for these molecular liquids were performed with a dual purpose: (1) to establish whether existing intermolecular potential functions can provide a picture that is consistent with diffraction data and (2) to generate reliable starting configurations for subsequent Reverse Monte Carlo modelling. Structural models (i.e., sets of coordinates of thousands of atoms) that were fully consistent with experimental diffraction information, within errors, have been prepared by means of the Reverse Monte Carlo method. Comparison with reference systems, generated by hard sphere-like Monte Carlo simulations, was also carried out to demonstrate the extent to which simple space filling effects determine the structure of the liquids (and thus, also estimating the information content of measured data). Total scattering structure factors, partial radial distribution functions and orientational correlations as a function of distances between the molecular centres have been calculated from the models. In general, more or less antiparallel arrangements of the primary molecular axes that are found to be the most favourable orientation of two neighbouring molecules. In liquid PBr{sub 3} electrostatic interactions seem to play a more important role in determining intermolecular correlations than in the other two liquids; molecular arrangements in both PCl{sub 3} and PI{sub 3} are largely driven by steric effects.

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

How to Obtain the Redshift Distribution from Probabilistic Redshift Estimates

Abstract A reliable estimate of the redshift distribution n ( z ) is crucial for using weak gravitational lensing and large-scale structures of galaxy catalogs to study cosmology. Spectroscopic redshifts for the dim and numerous galaxies of next-generation weak-lensing surveys are expected to be unavailable, making photometric redshift (photo- z ) probability density functions (PDFs) the next best alternative for comprehensively encapsulating the nontrivial systematics affecting photo- z point estimation. The established stacked estimator of n ( z ) avoids reducing photo- z PDFs to point estimates but yields a systematically biased estimate of n ( z ) that worsens with a decreasing signal-to-noise ratio, the very regime where photo- z PDFs are most necessary. We introduce Cosmological Hierarchical Inference with Probabilistic Photometric Redshifts ( CHIPPR ), a statistically rigorous probabilistic graphical model of redshift-dependent photometry that correctly propagates the redshift uncertainty information beyond the best-fit estimator of n ( z ) produced by traditional procedures and is provably the only self-consistent way to recover n ( z ) from photo- z PDFs. We present the chippr prototype code, noting that the mathematically justifiable approach incurs computational cost. The CHIPPR approach is applicable to any one-point statistic of any random variable, provided the prior probability density used to produce the posteriors is explicitly known; if the prior is implicit, as may be the case for popular photo- z techniques, then the resulting posterior PDFs cannot be used for scientific inference. We therefore recommend that the photo- z community focus on developing methodologies that enable the recovery of photo- z likelihoods with support over all redshifts, either directly or via a known prior probability density.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2019

Volume Flow Rate Estimation for Small Explosions at Mt. Etna, Italy, From Acoustic Waveform Inversion

Rapid assessment of the volume and the rate at which gas and pyroclasts are injected into the atmosphere during volcanic explosions is key to effective eruption hazard mitigation. Here, we use data from a dense infrasound network deployed in 2017 on Mt. Etna, Italy, to estimate eruptive volume flow rates (VFRs) during small gas-and-ash explosions. We use a finite-difference time-domain approximation to compute the acoustic Green's functions and perform a full waveform inversion for a multipole source, combining monopole and horizontal dipole terms. The inversion produces realistic estimates of VFR, on the order of 4 × 10 4 m 3 /s and well-defined patterns of source directivity. This is the first application of acoustic waveform inversion at Mt. Etna. Our results demonstrate that acoustic waveform inversion is a mature and robust tool for assessment of source parameters and holds potential as a tool to provide rapid estimates of VFR in near real time.

58 GEOSCIENCES↗
DOE OSTI2015

Accounting for partiality in serial crystallography using ray-tracing principles

Serial crystallography generates partial reflections from still diffraction images. Partialities are estimated with EVAL ray-tracing simulations, thereby improving merged reflection data to a similar quality as conventional rotation data. Serial crystallography generates ‘still’ diffraction data sets that are composed of single diffraction images obtained from a large number of crystals arbitrarily oriented in the X-ray beam. Estimation of the reflection partialities, which accounts for the expected observed fractions of diffraction intensities, has so far been problematic. In this paper, a method is derived for modelling the partialities by making use of the ray-tracing diffraction-integration method EVAL. The method estimates partialities based on crystal mosaicity, beam divergence, wavelength dispersion, crystal size and the interference function, accounting for crystallite size. It is shown that modelling of each reflection by a distribution of interference-function weighted rays yields a ‘still’ Lorentz factor. Still data are compared with a conventional rotation data set collected from a single lysozyme crystal. Overall, the presented still integration method improves the data quality markedly. The R factor of the still data compared with the rotation data decreases from 26% using a Monte Carlo approach to 12% after applying the Lorentz correction, to 5.3% when estimating partialities by EVAL and finally to 4.7% after post-refinement. The merging R{sub int} factor of the still data improves from 105 to 56% but remains high. This suggests that the accuracy of the model parameters could be further improved. However, with a multiplicity of around 40 and an R{sub int} of ∼50% the merged still data approximate the quality of the rotation data. The presented integration method suitably accounts for the partiality of the observed intensities in still diffraction data, which is a critical step to improve data quality in serial crystallography.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2022

Advanced Finite-Volume Numerics and Source Term Assumptions for Kernel and G-Equation Modelling of Propane/Air Flames

Here G-Equation models represent propagating flame fronts with an implicit two-dimensional surface representation (level-set). Level-set methods are fast, as transport source terms for the implicit surface can be solved with finite-volume operators on the finite-volume domain, without having to build the actual surface. However, they include approximations whose practical effects are not properly understood. In this study, we improved the numerics of the FRESCO CFD code’s G-Equation solver and developed a new method to simulate kernel growth using signed distance functions and the analytical sphere-mesh overlap. We analyzed their role for simulating propane/air flames, using three well-established constant-volume configurations: a one-dimensional, freely propagating laminar flame; a disc-shaped, constant-volume swirl combustor; and torch-jet flame development through an orifice from a two-chamber device. We tested the explicit (sub-cycled) vs. implicit formulation for the standard transport operators (advection, diffusion, compressibility). In addition to the accurate flame swept-volume method for chemistry and species source term, we developed a more accurate estimator for the burnt/unburnt split cell composition. Then, we developed a signed-distance-function (SDF) based method which provides a more stable reinitialization of the level-set field at every time-step. We found that simplifying assumptions common to several G-Equation implementations, for straightforward terms such as compressibility and advection, lead to large errors in predicting the propagation of even laminar flames, with deviations up to ~300% in simulated vs. formulated flame speed. Conversely, the enhanced numerics enabled through the SDF field reinitialization and improved chemistry source term improve simulation stability and smooth flame propagation even with significantly larger solver time-steps.

42 ENGINEERING↗
DOE OSTI2017

Girsanov's transformation based variance reduced Monte Carlo simulation schemes for reliability estimation in nonlinear stochastic dynamics

The study considers the problem of simulation based time variant reliability analysis of nonlinear randomly excited dynamical systems. Attention is focused on importance sampling strategies based on the application of Girsanov's transformation method. Controls which minimize the distance function, as in the first order reliability method (FORM), are shown to minimize a bound on the sampling variance of the estimator for the probability of failure. Two schemes based on the application of calculus of variations for selecting control signals are proposed: the first obtains the control force as the solution of a two-point nonlinear boundary value problem, and, the second explores the application of the Volterra series in characterizing the controls. The relative merits of these schemes, vis-à-vis the method based on ideas from the FORM, are discussed. Illustrative examples, involving archetypal single degree of freedom (dof) nonlinear oscillators, and a multi-degree of freedom nonlinear dynamical system, are presented. The credentials of the proposed procedures are established by comparing the solutions with pertinent results from direct Monte Carlo simulations. - Highlights: • The distance minimizing control forces minimize a bound on the sampling variance. • Establishing Girsanov controls via solution of a two-point boundary value problem. • Girsanov controls via Volterra's series representation for the transfer functions.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2014

SU-E-QI-08: Fourier Properties of Cone Beam CT Projection

Purpose: To explore the Fourier properties of cone beam CT (CBCT) projections and apply the property to directly estimate noise level of CBCT projections without any prior information. Methods: By utilizing the property of Bessel function, we derivate the Fourier properties of the CBCT projections for an arbitrary point object. It is found that there exists a double-wedge shaped region in the Fourier space where the intensity is approximately zero. We further derivate the Fourier properties of independent noise added to CBCT projections. The expectation of the square of the module in any point of the Fourier space is constant and the value approximately equals to noise energy. We further validate the theory in numerical simulations for both a delta function object and a NCAT phantom with different levels of noise added. Results: Our simulation confirmed the existence of the double-wedge shaped region in Fourier domain for the x-ray projection image. The boundary locations of this region agree well with theoretical predictions. In the experiments of estimating noise level, the mean relative error between the theory estimation and the ground truth values is 2.697%. Conclusion: A novel theory on the Fourier properties of CBCT projections has been discovered. Accurate noise level estimation can be achieved by applying this theory directly to the measured CBCT projections. This work was supported in part by NIH(1R01CA154747-01), NSFC((No. 61172163), Research Fund for the Doctoral Program of Higher Education of China (No. 20110201110011) and China Scholarship Council.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2014

Turbulence-induced relative velocity of dust particles. III. The probability distribution

Motivated by its important role in the collisional growth of dust particles in protoplanetary disks, we investigate the probability distribution function (PDF) of the relative velocity of inertial particles suspended in turbulent flows. Using the simulation from our previous work, we compute the relative velocity PDF as a function of the friction timescales, τ{sub p1} and τ{sub p2}, of two particles of arbitrary sizes. The friction time of the particles included in the simulation ranges from 0.1τ{sub η} to 54T {sub L}, where τ{sub η} and T {sub L} are the Kolmogorov time and the Lagrangian correlation time of the flow, respectively. The relative velocity PDF is generically non-Gaussian, exhibiting fat tails. For a fixed value of τ{sub p1}, the PDF shape is the fattest for equal-size particles (τ{sub p2} = τ{sub p1}), and becomes thinner at both τ{sub p2} < τ{sub p1} and τ{sub p2} > τ{sub p1}. Defining f as the friction time ratio of the smaller particle to the larger one, we find that, at a given f in (1/2) ≲ f ≲ 1, the PDF fatness first increases with the friction time τ{sub p,h} of the larger particle, peaks at τ{sub p,h} ≅ τ{sub η}, and then decreases as τ{sub p,h} increases further. For 0 ≤ f ≲ (1/4), the PDF becomes continuously thinner with increasing τ{sub p,h}. The PDF is nearly Gaussian only if τ{sub p,h} is sufficiently large (>>T {sub L}). These features are successfully explained by the Pan and Padoan model. Using our simulation data and some simplifying assumptions, we estimated the fractions of collisions resulting in sticking, bouncing, and fragmentation as a function of the dust size in protoplanetary disks, and argued that accounting for non-Gaussianity of the collision velocity may help further alleviate the bouncing barrier problem.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2019

Methodology to estimate vapor quality of refrigerant leaks

The US Department of Energy (DOE) Building Technology Office (BTO) and the Air-conditioning, Heating & Refrigeration Technology Institute (AHRTI) are sponsoring an experimental study of refrigerant leak characteristics. The objectives are to conduct refrigerant leak tests on several heating, ventilating, air conditioning and refrigeration (HVAC&R) systems under operating conditions representative of actual applications to document the pressure decay rate and the mass flow rate of leaked refrigerant as a function of time. Another aspect of the study was to formulate and document a procedure for estimating the quality (vapor versus liquid) of the leaking refrigerant and oil escaping from the high- and low-pressure sides with the unit energized and with the unit turned off. Refrigerant quality was estimated by tracking total system weight of a packaged air-conditioning (A/C) unit and the total weight of a large container used to capture the refrigerant leakage escaping the packaged unit.

Miller, William A.↗