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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 217 records · Page 12

Cosmic Voids in the SDSS DR12 BOSS Galaxy Sample: the Alcock–Paczyński test

We apply the Alcock–Paczyński (AP) test to stacked voids identified using the final data release (DR12) of the Baryon Oscillation Spectroscopic Survey (BOSS). We also use 1000 mock galaxy catalogs that match the geometry, density, and clustering properties of the BOSS sample in order to characterize the statistical uncertainties of our measurements and take into account systematic errors such as redshift space distortions. For both BOSS data and mock catalogs, we use the ZOBOV algorithm to identify voids, we stack together all voids with effective radii of 30--100 h{sup −1} Mpc in the redshift range of 0.43–0.7, and we accurately measure the shape of the stacked voids. Our tests with the mock catalogs show that we measure the stacked void ellipticity with a statistical precision of 2.6%. The stacked voids in redshift space are slightly squashed along the line of sight, consistent with previous studies. We repeat this measurement of stacked void shape in the BOSS data, assuming several values of Ω{sub m} within the flat ΛCDM model, and we compare this to the mock catalogs in redshift space to perform the AP test. We obtain a constraint of Ω{sub m}=0.38{sub −0.15}{sup +0.18} at the 68% confidence level from the AP test. We discuss the sources of statistical and systematic noise that affect the constraining power of this method. In particular, we find that the measured ellipticity of stacked voids changes more weakly with cosmology than the standard AP prediction, leading to significantly weaker constraints. We discuss how constraints will improve in future surveys with larger volumes and densities.

79 ASTRONOMY AND ASTROPHYSICS↗

NGEE Arctic Soil Pit and Core Inventory for Samples Collected Between 2016-2019: Locations, Sampling Characteristics, Collection, and Contacts, Seward Peninsula, Alaska, USA

This dataset includes associated information about individual pit and core samples (e.g., location, contact, date, data collected) sampled between 2016 and 2019 from NGEE Arctic sites at Teller (MM 27 and MM47), Kougarok (MM47 and MM56, Hillslope, and vegetation plot areas), and Council (MM71). The inventory is qualitative and excludes those datasets on soil pit cores that included time-series information. The package includes one each *.csv data file, *.kml and *.pdf. All quantitative data is available in the related datasets https://doi.org/10.5440/1417652, https://doi.org/10.5440/1423892, https://doi.org/10.5440/1342956, https://doi.org/10.5440/1854940, https://doi.org/10.5440/1544760, https://doi.org/10.5440/1346200, and https://doi.org/10.5440/1856042. The goal of this dataset is to help modelers understand when, where, and what data was collected with respect to physical soil properties on the Seward Peninsula, AK, USA over the course of NGEE Arctic’s campaigns in the region from 2016-2019. The Next-Generation Ecosystem Experiments: Arctic (NGEE Arctic), was a research effort to reduce uncertainty in Earth System Models by developing a predictive understanding of carbon-rich Arctic ecosystems and feedbacks to climate. NGEE Arctic was supported by the Department of Energy's Office of Biological and Environmental Research. The NGEE Arctic project had two field research sites: 1) located within the Arctic polygonal tundra coastal region on the Barrow Environmental Observatory (BEO) and the North Slope near Utqiagvik (Barrow), Alaska and 2) multiple areas on the discontinuous permafrost region of the Seward Peninsula north of Nome, Alaska. Through observations, experiments, and synthesis with existing datasets, NGEE Arctic provided an enhanced knowledge base for multi-scale modeling and contributed to improved process representation at global pan-Arctic scales within the Department of Energy's Earth system Model (the Energy Exascale Earth System Model, or E3SM), and specifically within the E3SM Land Model component (ELM).

54 ENVIRONMENTAL SCIENCES↗

Control of the positional relationship between a sample collection instrument and a surface to be analyzed during a sampling procedure using a laser sensor

A system and method utilizes distance-measuring equipment including a laser sensor for controlling the collection instrument-to-surface distance during a sample collection process for use, for example, with mass spectrometric detection. The laser sensor is arranged in a fixed positional relationship with the collection instrument, and a signal is generated by way of the laser sensor which corresponds to the actual distance between the laser sensor and the surface. The actual distance between the laser sensor and the surface is compared to a target distance between the laser sensor and the surface when the collection instrument is arranged at a desired distance from the surface for sample collecting purposes, and adjustments are made, if necessary, so that the actual distance approaches the target distance.

47 OTHER INSTRUMENTATION↗

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↗

Toward Automated Sampling of Polymorph Nucleation and Free Energies with the SGOOP and Metadynamics

Understanding the driving forces behind the nucleation of different polymorphs is of great importance for material sciences and the pharmaceutical industry. This includes understanding the reaction coordinate that governs the nucleation process and correctly calculating the relative free energies of different polymorphs. Here, we demonstrate, for the prototypical case of urea nucleation from the melt, how one can learn such a one-dimensional reaction coordinate as a function of prespecified order parameters and use it to perform efficient biased all-atom molecular dynamics simulations. The reaction coordinate is learnt as a function of the generic thermodynamic and structural order parameters using the “spectral gap optimization of order parameters (SGOOP)” approach [Tiwary, P. and Berne, B. J. Proc. Natl. Acad. Sci. U.S.A. (2016)] and is biased using well-tempered metadynamics simulations. The reaction coordinate gives insights into the role played by different structural and thermodynamics order parameters, and the biased simulations obtain accurate relative free energies for different polymorphs. This includes an accurate prediction of the approximate pressure at which urea undergoes a phase transition and one of the metastable polymorphs becomes the most stable conformation. Here, we believe the ideas demonstrated in this work will facilitate efficient sampling of nucleation in complex, generic systems.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Synchrotron X-ray measurement techniques for thermal barrier coated cylindrical samples under thermal gradients

Measurement techniques to obtain accurate in situ synchrotron strain measurements of thermal barrier coating systems (TBCs) applied to hollow cylindrical specimens are presented in this work. The Electron Beam Physical Vapor Deposition coated specimens with internal cooling were designed to achieve realistic temperature gradients over the TBC coated material such as that occurring in the turbine blades of aeroengines. Effects of the circular cross section on the x-ray diffraction (XRD) measurements in the various layers, including the thermally grown oxide, are investigated using high-energy synchrotron x-rays. Multiple approaches for beam penetration including collection, tangential, and normal to the layers, along with variations in collection parameters are compared for their ability to attain high-resolution XRD data from the internal layers. This study displays the ability to monitor in situ, the response of the internal layers within the TBC, while implementing a thermal gradient across the thickness of the coated sample. The thermal setup maintained coating surface temperatures in the range of operating conditions, while monitoring the substrate cooling, for a controlled thermal gradient. Through variation in measurement location and beam parameters, sufficient intensities are obtained from the internal layers which can be used for depth resolved strain measurements. Results are used to establish the various techniques for obtaining XRD measurements through multi-layered coating systems and their outcomes will pave the way towards goals in achieving realistic in situ testing of these coatings.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Capsule implosions for continuum x-ray backlighting of opacity samples at the National Ignition Facility

Direct drive implosions of plastic capsules have been performed at the National Ignition Facility to provide a broad-spectrum (500–2000 eV) X-ray continuum source for X-ray transmission spectroscopy. The source was developed for the high-temperature plasma opacity experimental platform. Initial experiments using 2.0 mm diameter polyalpha-methyl styrene capsules with ~20 μm thickness have been performed. X-ray yields of up to ~1 kJ/sr have been measured using the Dante multichannel diode array. The backlighter source size was measured to be ~100 μm FWHM, with ~350 ps pulse duration during the peak emission stage. Lastly, these results are used to simulate transmission spectra for a hypothetical iron opacity sample at 150 eV, enabling the derivation of photometrics requirements for future opacity experiments.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Contour forward flux sampling: Sampling rare events along multiple collective variables

Many rare event transitions involve multiple collective variables (CVs), and the most appropriate combination of CVs is generally unknown a priori. As such, we introduce a new method, contour forward flux sampling (cFFS), to study rare events with multiple CVs simultaneously. cFFS places nonlinear interfaces on-the-fly from the collective progress of the simulations, without any prior knowledge of the energy landscape or appropriate combination of CVs. We demonstrate cFFS on analytical potential energy surfaces and a conformational change in alanine dipeptide.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Quasiclassical sampling and Wigner sampling of initial vibrational coordinates and momenta for polyatomic molecules in Monte Carlo molecular dynamics simulations

In a quasiclassical trajectory simulation, the vibrational modes are initialised with quantised vibrational energies, but vibrational phases are sampled by Monte Carlo. This requires an algorithm to assign coordinates and momenta to the various atoms. In this work, we present two methods for implementing this for nonrotating polyatomic molecules, namely, fixed-energy vibrational-state-selected initial conditions and thermal initial conditions. We also present a method for initiating classical trajectories with a ground-state Wigner distribution. These vibrational treatments are sufficient to initialise trajectories for unimolecular processes, and we also show how they can be applied to simulate bimolecular collision processes. The treatments of unimolecular and bimolecular collision processes are available in two Python codes called wigner_state_selected.py and bimolecular_collision.py, respectively, which will generate initial condition files that are recognisable by the SHARC and SHARC-MN computer programs for dynamics calculations. Both codes are available as standalone programs, as well as being included in SHARC-MN, and they will be included in future versions of SHARC. Here, the methods implemented in these codes are mostly also available in the ANT computer program, and those that are not available in ANT will be incorporated in future versions of ANT.

Wigner distribution↗

Genome Sequences of Industrially Relevant Saccharomyces cerevisiae Strain M3707, Isolated from a Sample of Distillers Yeast and Four Haploid Derivatives

Saccharomyces cerevisiae strain M3707 was isolated from a sample of commercial distillers yeast, and its genome sequence together with the genome sequences for the four derived haploid strains M3836, M3837, M3838, and M3839 has been determined. Yeasts have potential for consolidated bioprocessing (CBP) for biofuel production, and access to these genome sequences will facilitate their development.

09 BIOMASS FUELS↗

Compressive Sensing with Cross-Validation and Stop-Sampling for Sparse Polynomial Chaos Expansions

Here, compressive sensing is a powerful technique for recovering sparse solutions of underdetermined linear systems, which is often encountered in uncertainty quantification analysis of expensive and high-dimensional physical models. We perform numerical investigations employing several compressive sensing solvers that target the unconstrained LASSO formulation, with a focus on linear systems that arise in the construction of polynomial chaos expansions. With core solvers l1_ls, SpaRSA, CGIST, FPC_AS, and ADMM, we develop techniques to mitigate overfitting through an automated selection of regularization constant based on cross-validation, and a heuristic strategy to guide the stop-sampling decision. Practical recommendations on parameter settings for these techniques are provided and discussed. The overall method is applied to a series of numerical examples of increasing complexity, including large eddy simulations of supersonic turbulent jet-in-crossflow involving a 24-dimensional input. Through empirical phase-transition diagrams and convergence plots, we illustrate sparse recovery performance under structures induced by polynomial chaos, accuracy, and computational trade-offs between polynomial bases of different degrees, and practicability of conducting compressive sensing for a realistic, high-dimensional physical application. Across test cases studied in this paper, we find ADMM to have demonstrated empirical advantages through consistent lower errors and faster computational times.

97 MATHEMATICS AND COMPUTING↗