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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 487 records · Page 27
All sourcesNASA NTRSDOE OSTI
DOE OSTI2018

Effective Demagnetizing Factors of Diamagnetic Samples of Various Shapes

Effective demagnetizing factors that connect the sample magnetic moment with the applied magnetic field are calculated numerically for perfectly diamagnetic samples of various nonellipsoidal shapes. The procedure is based on calculating the total magnetic moment by integrating the magnetic induction obtained from a full three-dimensional (3D) solution of the Maxwell equations using an adaptive mesh. The results are relevant for superconductors (and conductors in ac fields) when the London penetration depth (or the skin depth) is much smaller than the sample size. In conclusion, simple but reasonably accurate approximate formulas are given for practical shapes including rectangular cuboids, finite cylinders in axial and transverse fields, as well as infinite rectangular and elliptical cross-section strips.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2018

Marine Corps Base Camp Lejeune Water Quality Dataflow Viewer

Critical military training and testing on lands along the nation’s coastal and estuarine shorelines are increasingly placed at risk because of encroachment pressures in surrounding areas, impairments due to other anthropogenic disturbances, and changes in climate and sea level. The U.S. Department of Defense (DoD) intends to enhance and sustain its training and testing assets and also optimize its stewardship of natural resources through the development and application of an ecosystem-based management approach on DoD installations. To accomplish this goal, particularly for installations in estuarine/coastal environments, the Strategic Environmental Research and Development Program (SERDP) launched the Defense Coastal/Estuarine Research Program (DCERP) as a 10-year effort at Marine Corps Base Camp Lejeune (MCBCL) in North Carolina. The results of the second 5 years of the program (DCERP2) are presented in the DCERP2 Final Report.There were four overarching objectives of DCERP2. The first objective was to understand the effects of climate change impacts, including warming temperatures, variability in the hydrological cycle, storm events, and sea level rise on the coastal ecosystems at MCBCL from observations and measurements made over the 10-year program. The second objective was to understand the carbon cycle of the coastal and terrestrial ecosystems at MCBCL through a highly integrated sampling program. The third objective was to develop models, tools, and indicators to evaluate current and projected future ecosystem state changes and translate scientific findings into actionable information for installation managers. The last objective was to recommend adaptive management strategies to sustain ecosystem natural resources within the context of an active military installation.GIS was used to create point layers from the coordinates representing samples taken along the mainstem and shallow portions of the New River Estuary. The point layers were transformed into linear features and datasets were created for each parameter (salinity, chlorophyll, and turbidity). The line representing each sample collection point was symbolized based on the value of each parameter in the Water Quality Explorer for the dawn samples only. The date and time collected for each sample was used to visualize the sample collection at dawn in the map viewer. Each GIS layer was time enabled with a daily time step interval so that changes in concentrations of salinity, chlorophyll, and turbidity could be observed on a daily basis. In the geodatabase, the layers used for the dawn samples end with “_AM”. The ones without AM at the end include all samples (AM and PM); note that the PM samples are not visualized in the Water Quality Explorer.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2012

PROFILES OF DARK MATTER VELOCITY ANISOTROPY IN SIMULATED CLUSTERS

We report statistical results for dark matter (DM) velocity anisotropy, {beta}, from a sample of some 6000 cluster-size halos (at redshift zero) identified in a {Lambda}CDM hydrodynamical adaptive mesh refinement simulation performed with the ENZO code. These include profiles of {beta} in clusters with different masses, relaxation states, and at several redshifts, modeled both as spherical and triaxial DM configurations. Specifically, although we find a large scatter in the DM velocity anisotropy profiles of different halos (across elliptical shells extending to at least {approx}1.5r{sub vir}), universal patterns are found when these are averaged over halo mass, redshift, and relaxation stage. These are characterized by a very small velocity anisotropy at the halo center, increasing outward to {approx}0.27 and leveling off at {approx}0.2r{sub vir}. Indirect measurements of the DM velocity anisotropy fall on the upper end of the theoretically expected range. Though measured indirectly, the estimations are derived by using two different surrogate measurements-X-ray and galaxy dynamics. Current estimates of the DM velocity anisotropy are based on a very small cluster sample. Increasing this sample will allow theoretical predictions to be tested, including the speculation that the decay of DM particles results in a large velocity boost. We also find, in accord with previous works, that halos are triaxial and likely to be more prolate when unrelaxed, whereas relaxed halos are more likely to be oblate. Our analysis does not indicate that there is significant correlation (found in some previous studies) between the radial density slope, {gamma}, and {beta} at large radii, 0.3 r{sub vir} < r < r{sub vir}.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2015

Rapid fusion method for the determination of Pu, Np, and Am in large soil samples

A new rapid sodium hydroxide fusion method for the preparation of 10-20 g soil samples has been developed by the Savannah River National Laboratory (SRNL). The method enables lower detection limits for plutonium, neptunium, and americium in environmental soil samples. The method also significantly reduces sample processing time and acid fume generation compared to traditional soil digestion techniques using hydrofluoric acid. Ten gram soil aliquots can be ashed and fused using the new method in 1-2 hours, completely dissolving samples, including refractory particles. Pu, Np and Am are separated using stacked 2mL cartridges of TEVA and DGA Resin and measured using alpha spectrometry. The method can be adapted for measurement by inductively-coupled plasma mass spectrometry (ICP-MS). Two 10 g soil aliquots of fused soil may be combined prior to chromatographic separations to further improve detection limits. Total sample preparation time, including chromatographic separations and alpha spectrometry source preparation, is less than 8 hours.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2014

Adaptive OFDM Radar Waveform Design for Improved Micro-Doppler Estimation

Here we analyze the performance of a wideband orthogonal frequency division multiplexing (OFDM) signal in estimating the micro-Doppler frequency of a rotating target having multiple scattering centers. The use of a frequency-diverse OFDM signal enables us to independently analyze the micro-Doppler characteristics with respect to a set of orthogonal subcarrier frequencies. We characterize the accuracy of micro-Doppler frequency estimation by computing the Cramer-Rao bound (CRB) on the angular-velocity estimate of the target. Additionally, to improve the accuracy of the estimation procedure, we formulate and solve an optimization problem by minimizing the CRB on the angular-velocity estimate with respect to the OFDM spectral coefficients. We present several numerical examples to demonstrate the CRB variations with respect to the signal-to-noise ratios, number of temporal samples, and number of OFDM subcarriers. We also analysed numerically the improvement in estimation accuracy due to the adaptive waveform design. A grid-based maximum likelihood estimation technique is applied to evaluate the corresponding mean-squared error performance.

47 OTHER INSTRUMENTATION↗
DOE OSTI2020

Mercury Speciation of Hanford 241-AP-107 Tank Waste Samples - 20384

The concentration of key mercury species in the Hanford tank waste has not been previously measured. Based on process knowledge, an estimated inventory of 2,100 kg of mercury is assumed and was distributed in varied amounts across 149 single-shell tanks (SSTs) and 28 double-shell tanks (DSTs). Limited analyses of individual SSTs and DSTs for total mercury were all below detection, yielding upper limits in concentration estimates based solely on instrument detection limits, resulting in an uncertain mercury inventory for Hanford tanks. Accurate and reliable chemical speciation and quantification is desired to anticipate, predict, and abate the mass movements of various mercury species through the Hanford waste processing flowsheet. Highly sensitive separation and quantification methods for total, elemental, and monomethyl mercury species, in tank waste, have been developed at the Pacific Northwest National Laboratory's (PNNL) Radiochemical Processing Laboratory (RPL). A non-radiological environmental method to quantify mercury species has been adapted for application to Hanford tank 241-AP-107 raw supernatant feed, filtered feed, and cesium-decontaminated samples. These samples represent feed inventory and pretreatment process effluents prior to immobilization by vitrification. This method separates and preconcentrates total, elemental, and monomethyl mercury onto selective solid substrates with little-to-no radioactive background. The solid samples can then be released from strict radiological control, allowing for analytical work to be conducted in low-level radiological facilities. Separation of mercury species was demonstrated at PNNL's RPL in Richland, Washington before transport and analytical quantification using cold vapor atomic fluorescence spectrometry (CVAFS) at PNNL's Marine Science Laboratory (MSL) in Sequim, Washington. Additional studies were conducted to assess the stability of monomethyl mercury in distilled matrices and preconcentrated onto the Carbotrap{sup R} solid substrate to assess sample degradation over time during transport. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2017

A two-stage adaptive stochastic collocation method on nested sparse grids for multiphase flow in randomly heterogeneous porous media

A new computational method is proposed for efficient uncertainty quantification of multiphase flow in porous media with stochastic permeability. For pressure estimation, it combines the dimension-adaptive stochastic collocation method on Smolyak sparse grids and the Kronrod–Patterson–Hermite nested quadrature formulas. For saturation estimation, an additional stage is developed, in which the pressure and velocity samples are first generated by the sparse grid interpolation and then substituted into the transport equation to solve for the saturation samples, to address the low regularity problem of the saturation. Numerical examples are presented for multiphase flow with stochastic permeability fields to demonstrate accuracy and efficiency of the proposed two-stage adaptive stochastic collocation method on nested sparse grids.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2012

An Adaptive Sparse-Grid High-Order Stochastic Collocation Method for Bayesian Inference in Groundwater Reactive Transport Modeling

Although Bayesian analysis has become vital to the quantification of prediction uncertainty in groundwater modeling, its application has been hindered due to the computational cost associated with numerous model executions needed for exploring the posterior probability density function (PPDF) of model parameters. This is particularly the case when the PPDF is estimated using Markov Chain Monte Carlo (MCMC) sampling. In this study, we develop a new approach that improves computational efficiency of Bayesian inference by constructing a surrogate system based on an adaptive sparse-grid high-order stochastic collocation (aSG-hSC) method. Unlike previous works using first-order hierarchical basis, we utilize a compactly supported higher-order hierar- chical basis to construct the surrogate system, resulting in a significant reduction in the number of computational simulations required. In addition, we use hierarchical surplus as an error indi- cator to determine adaptive sparse grids. This allows local refinement in the uncertain domain and/or anisotropic detection with respect to the random model parameters, which further improves computational efficiency. Finally, we incorporate a global optimization technique and propose an iterative algorithm for building the surrogate system for the PPDF with multiple significant modes. Once the surrogate system is determined, the PPDF can be evaluated by sampling the surrogate system directly with very little computational cost. The developed method is evaluated first using a simple analytical density function with multiple modes and then using two synthetic groundwater reactive transport models. The groundwater models represent different levels of complexity; the first example involves coupled linear reactions and the second example simulates nonlinear ura- nium surface complexation. The results show that the aSG-hSC is an effective and efficient tool for Bayesian inference in groundwater modeling in comparison with conventional MCMC sim- ulations. The computational efficiency is expected to be more beneficial to more computational expensive groundwater problems.

Zhang, Guannan↗
DOE OSTI2015

Pathosphere.org: pathogen detection and characterization through a web-based, open source informatics platform

The detection of pathogens in complex sample backgrounds has been revolutionized by wide access to next-generation sequencing (NGS) platforms. However, analytical methods to support NGS platforms are not as uniformly available. Pathosphere (found at Pathosphere.org) is a cloud - based open - sourced community tool that allows for communication, collaboration and sharing of NGS analytical tools and data amongst scientists working in academia, industry and government. The architecture allows for users to upload data and run available bioinformatics pipelines without the need for onsite processing hardware or technical support. The pathogen detection capabilities hosted on Pathosphere were tested by analyzing pathogen-containing samples sequenced by NGS with both spiked human samples as well as human and zoonotic host backgrounds. Pathosphere analytical pipelines developed by Edgewood Chemical Biological Center (ECBC) identified spiked pathogens within a common sample analyzed by 454, Ion Torrent, and Illumina sequencing platforms. ECBC pipelines also correctly identified pathogens in human samples containing arenavirus in addition to animal samples containing flavivirus and coronavirus. These analytical methods were limited in the detection of sequences with limited homology to previous annotations within NCBI databases, such as parvovirus. Utilizing the pipeline-hosting adaptability of Pathosphere, the analytical suite was supplemented by analytical pipelines designed by the United States Army Medical Research Institute of Infectious Diseases and Walter Reed Army Institute of Research (USAMRIID-WRAIR). These pipelines were implemented and detected parvovirus sequence in the sample that the ECBC iterative analysis previously failed to identify. By accurately detecting pathogens in a variety of samples, this work demonstrates the utility of Pathosphere and provides a platform for utilizing, modifying and creating pipelines for a variety of NGS technologies developed to detect pathogens in complex sample backgrounds. These results serve as an exhibition for the existing pipelines and web-based interface of Pathosphere as well as the plug-in adaptability that allows for integration of newer NGS analytical software as it becomes available.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2019

Large Circular Plasmids from Groundwater Plasmidomes Span Multiple Incompatibility Groups and Are Enriched in Multimetal Resistance Genes

ABSTRACT Naturally occurring plasmids constitute a major category of mobile genetic elements responsible for harboring and transferring genes important in survival and fitness. A targeted evaluation of plasmidomes can reveal unique adaptations required by microbial communities. We developed a model system to optimize plasmid DNA isolation procedures targeted to groundwater samples which are typically characterized by low cell density (and likely variations in the plasmid size and copy numbers). The optimized method resulted in successful identification of several hundred circular plasmids, including some large plasmids (11 plasmids more than 50 kb in size, with the largest being 1.7 Mb in size). Several interesting observations were made from the analysis of plasmid DNA isolated in this study. The plasmid pool (plasmidome) was more conserved than the corresponding microbiome distribution (16S rRNA based). The circular plasmids were diverse as represented by the presence of seven plasmid incompatibility groups. The genes carried on these groundwater plasmids were highly enriched in metal resistance. Results from this study confirmed that traits such as metal, antibiotic, and phage resistance along with toxin-antitoxin systems are encoded on abundant circular plasmids, all of which could confer novel and advantageous traits to their hosts. This study confirms the ecological role of the plasmidome in maintaining the latent capacity of a microbiome, enabling rapid adaptation to environmental stresses. IMPORTANCE Plasmidomes have been typically studied in environments abundant in bacteria, and this is the first study to explore plasmids from an environment characterized by low cell density. We specifically target groundwater, a significant source of water for human/agriculture use. We used samples from a well-studied site and identified hundreds of circular plasmids, including one of the largest sizes reported in plasmidome studies. The striking similarity of the plasmid-borne ORFs in terms of taxonomical and functional classifications across several samples suggests a conserved plasmid pool, in contrast to the observed variability in the 16S rRNA-based microbiome distribution. Additionally, the stress response to environmental factors has stronger conservation via plasmid-borne genes as marked by abundance of metal resistance genes. Last, identification of novel and diverse plasmids enriches the existing plasmid database(s) and serves as a paradigm to increase the repertoire of biological parts that are available for modifying novel environmental strains.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2013

Adaptive polynomial chaos techniques for uncertainty quantification of a gas cooled fast reactor transient

Uncertainty quantification plays an increasingly important role in the nuclear community, especially with the rise of Best Estimate Plus Uncertainty methodologies. Sensitivity analysis, surrogate models, Monte Carlo sampling and several other techniques can be used to propagate input uncertainties. In recent years however polynomial chaos expansion has become a popular alternative providing high accuracy at affordable computational cost. This paper presents such polynomial chaos (PC) methods using adaptive sparse grids and adaptive basis set construction, together with an application to a Gas Cooled Fast Reactor transient. Comparison is made between a new sparse grid algorithm and the traditionally used technique proposed by Gerstner. An adaptive basis construction method is also introduced and is proved to be advantageous both from an accuracy and a computational point of view. As a demonstration the uncertainty quantification of a 50% loss of flow transient in the GFR2400 Gas Cooled Fast Reactor design was performed using the CATHARE code system. The results are compared to direct Monte Carlo sampling and show the superior convergence and high accuracy of the polynomial chaos expansion. Since PC techniques are easy to implement, they can offer an attractive alternative to traditional techniques for the uncertainty quantification of large scale problems. (authors)

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2016

In Situ Sample Environment for Studying Corrosion of Nuclear Materials

Currently there is lack of fundamental understanding of kinetics and reaction mechanisms that occur at nuclear cladding-steam interface under extreme environments in the nuclear reactors. Such understanding is vital to design and develop advanced cladding materials for more economical and safer nuclear power. We present advanced in situ sample environment for probing solid-fluid interfaces using high resolution synchrotron methods for studying early stages of corrosion including development of oxide layer as corrosion proceeds. Both X-ray diffraction and X-ray fluorescence methods will be discussed to probe structural and elemental composition changes under steam environment using corrosion resistant cell at high temperatures. High intensity and brightness of synchrotron coupled with advanced in situ sample environment developed, presents an opportunity to understand the fundamental interfacial processes involved in degradation of materials. The in situ sample environment is optimized for XRD and XRF data collection at NSLS-II and will be available to all users through the proposal process. The in situ sample environment is built to study the interfacial interactions at temperatures and pressures up to 400 deg. C and 1500 psi. It consists of three main parts; the distribution manifold, the pressure vessel, and the reaction cell as shown in Figure 1. Water is allowed to heat up to 350 deg. C inside the pressure vessel to produce steam which is delivered to reaction cell using insulated delivery system. The cell design is adapted from J. Diefenbacher, et. al. However, it is modified for corrosion applications in steam environments. The reaction cell and sample holder are made from hastelloy due to its high corrosion resistance. The reaction cell is surrounded by copper heating block to control its temperature independently from the rest of the system. Lab view based platform is developed for remote monitoring of pressure and temperature. The sample environment was commissioned at 6-IDD beamline in the Advanced Photon Source, for grazing incidence XRD corrosion studies. Metallic Zr sample (200 μm thickness) was used due to its faster oxidation kinetics as compared to Zircaloy. Sample was exposed to steam at 350 deg. C and 50 psi for a total time of 64 hours. Results showed the presence of α-Zr as the dominant phase. After 32 hours of exposure to steam, three oxide peaks in the low diffraction angle side started to develop with time. These peaks are attributed to the growth of substoichiometric zirconium oxide phases (Zr{sub 3}O and Zr{sub 3}O{sub 1-x}). (authors)

36 MATERIALS SCIENCE↗
DOE OSTI2015

Limitations of polynomial chaos expansions in the Bayesian solution of inverse problems

Polynomial chaos expansions are used to reduce the computational cost in the Bayesian solutions of inverse problems by creating a surrogate posterior that can be evaluated inexpensively. We show, by analysis and example, that when the data contain significant information beyond what is assumed in the prior, the surrogate posterior can be very different from the posterior, and the resulting estimates become inaccurate. One can improve the accuracy by adaptively increasing the order of the polynomial chaos, but the cost may increase too fast for this to be cost effective compared to Monte Carlo sampling without a surrogate posterior.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2023

HBMax: Optimizing Memory Efficiency for Parallel Influence Maximization on Multicore Architectures

The goal of influence maximization is to select k most-influential vertices or seeds in a network, where influence is defined by a given diffusion process. The problem has a number of important applications such as viral marketing, information spread, and epidemic control. Although computing optimal seed set is NP-Hard, due to the submodular nature of the problem efficient approximation algorithms exist. However, even state-of-the-art parallel implementations are limited by a sampling step that incurs large memory footprints. This in turn limits the problem size reach and approximation quality. In this work, we study the memory footprint of the sampling process collecting reverse reachability information in the IMM algorithm over large real-world social networks. We present an adaptive and memory-efficient optimization approach for a state-of-the-art multi-threaded parallel influence maximization algorithm. Our approach,HuffMax, uses a portion of the reverse reachable (RR) sets collected by the algorithm to learn the characteristics of the graph. Then, it compresses the intermediate reverse reachability information with Huffman coding, and queries directly on the compressed data to preserve the memory savings obtained through compression. We also propose an efficient sampling strategy based on the distribution of RR sets, which can further reduce the computation time for typical social networks with long-tail distributions. Considering a NUMA architecture, we scale up our solution on 128-core CPUs and reduce the memory footprint by up to 45.7% with negligible time overhead (or even faster) and without perceivable loss of accuracy.

Chen, Xinyu↗
DOE OSTI2019

Using geochemical indicators to distinguish high biogeochemical activity in floodplain soils and sediments, Science of the Total Environment: Dataset

Data associated with analysis of sediment samples collected in the East River watershed and Rifle floodplain sites, CO. Samples were collected and analyzed as part of two student MS theses at Colorado School of Mines (Kenwell and Prugue) over a time period ranging from 2012 to 2015. Analyses include total organic carbon, leachable Fe and Mn, and total microbial DNA; all analyses performed at Colorado School of Mines. Methods: Samples were collected from core during a drilling campaign at the Rifle Site. Samples were collected every 1.5 m. At the East River site soil and sediment samples were collected using hand-augered bulk density sampler. Collected samples were stored at -20C until analysis. Samples were thawed in an anaerobic chamber and subsampled for extractions and DNA analysis. Samples for DNA analysis were freeze-dried, the remaining sample was oven dried and ground to 0.991 cm for TOC and leaching analysis. TOC analysis was performed on duplicate samples using a CM 5014 Coulometer (UIC, Joliet, IL, USA). Two chemical extractions were performed: hydroxylamine (HA) extraction of Fe and Mn adapted from Lovley et al., 1987 and synthetic precipitation (ppt) leaching adapted from EPA method 1312 (EPA, 1994) . For theHA extraction 3g of wet sediment was mixed with 150 mL of 0.5 N HCl in one bottle and another 3 g of sediment was mixed with 150 mL of 0.25 N hydroxylamine hydrochloride in 0.5 N HCl. Extraction were performed for 24 hours at room temperature after which samples of the liquid were removed and filtered to 0.45 micron and analyzed by ICP-AES. HA-reducible iron and manganese concentrations were determined by difference between the two extractions. For ppt leaches, a 60:40 sulfuric:nitric acid mixture was added to Milliq water to a pH of 4.2 and combined with sediment in a 20:1 mass ratio of acid to sediment. The extraction was performed for 18 hours at room temperature after which the samples of the liquid were removed and filtered to 0.45 micron and analyzed by ICP-AES. DNA was sampled from sediment using a PowerSoil DNA Isolation Kit and extractions were performed according to manufactured instuctions with one adjustment, a 1 minute bead beating replaced the 10 minute vortexing step. Extracted DNA was stored at -20C. Quantitative PCR was performed in triplicate on a Roche LightCycler 480 system and working curves were created by amplifying environmental samples with primers and bead purifying them with Agencourt AMPure XP. Analysis was performed with a Qubit 2.0 Fluorometer and Qubit dsDNA High Sensitivity Assay Kit with results converted to copies using the URI Genomics and Sequencing Center converter (Staroscik, 2004). Additional method details can be found in Kenwell et al., 2016. Lovley, D.R., Phillips, E.J.P. (1987). Rapid assay for microbially reducible ferric iron in aquatic sediments. Applied and Environmental Microbiology, 53(7), 1536-1540. Staroscik, A. (2004). Calculator for determining the number of copies of a template. URI Genomics & Sequencing Center. <http://cels.uri.edu/gsc/cndna.html>. EPA. (1994). Method 1312: Synthetic precipitation leaching procedure.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Initial assessment of second generation of large-area picosecond photodetectors with multi-channel systems-on-a-chip readout

Here, we first briefly describe the history and motivation behind Cherenkov and scintillation light detection. We then discuss the instrumentation needed to detect these photons as it applies to both photodetectors and readout electronics. One of the motivations is future large neutrino detectors that could, in principle, differentiate between Cherenkov and scintillation light if using novel water-based scintillators. In this paper, we present the first measurements utilizing the second generation of Large Area Picosecond Photodetectors (LAPPDs) in conjunction with commercial system-on-a-chip readouts from Nalu Scientific—in particular, the High Density System on Chip (HDSoC) and Advanced ASoC Rapid Digitizer, Variable Adaptive Readout Chip (AARDVARC) platforms. These state-of-the-art full-waveform digitizers feature sampling rates on the order of 1 and 10 samples per nanosecond, respectively. Using a picosecond laser, we measured the timing jitter between a pair of LAPPD channels, demonstrating the potential of this setup for precise timing applications.

Li, V. A. [Lawrence Livermore National Laboratory ↗
DOE OSTI2014

M-dwarf rapid rotators and the detection of relatively young multiple M-star systems

We have searched the Kepler light curves of ∼3900 M-star targets for evidence of periodicities that indicate, by means of the effects of starspots, rapid stellar rotation. Several analysis techniques, including Fourier transforms, inspection of folded light curves, 'sonograms', and phase tracking of individual modulation cycles, were applied in order to distinguish the periodicities due to rapid rotation from those due to stellar pulsations, eclipsing binaries, or transiting planets. We find 178 Kepler M-star targets with rotation periods, P {sub rot}, of <2 days, and 110 with P {sub rot} < 1 day. Some 30 of the 178 systems exhibit two or more independent short periods within the same Kepler photometric aperture, while several have 3 or more short periods. Adaptive optics imaging and modeling of the Kepler pixel response function for a subset of our sample support the conclusion that the targets with multiple periods are highly likely to be relatively young physical binary, triple, and even quadruple M star systems. We explore in detail the one object with four incommensurate periods all less than 1.2 days, and show that two of the periods arise from one of a close pair of stars, while the other two arise from the second star, which itself is probably a visual binary. If most of these M-star systems with multiple periods turn out to be bound M stars, this could prove a valuable way discovering young hierarchical M-star systems; the same approach may also be applicable to G and K stars. The ∼5% occurrence rate of rapid rotation among the ∼3900 M star targets is consistent with spin evolution models that include an initial contraction phase followed by magnetic braking, wherein a typical M star can spend several hundred Myr before spinning down to periods longer than 2 days.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2015

Approximating the Generalized Voronoi Diagram of Closely Spaced Objects

We present an algorithm to compute an approximation of the generalized Voronoi diagram (GVD) on arbitrary collections of 2D or 3D geometric objects. In particular, we focus on datasets with closely spaced objects; GVD approximation is expensive and sometimes intractable on these datasets using previous algorithms. With our approach, the GVD can be computed using commodity hardware even on datasets with many, extremely tightly packed objects. Our approach is to subdivide the space with an octree that is represented with an adjacency structure. We then use a novel adaptive distance transform to compute the distance function on octree vertices. The computed distance field is sampled more densely in areas of close object spacing, enabling robust and parallelizable GVD surface generation. We demonstrate our method on a variety of data and show example applications of the GVD in 2D and 3D.

97 MATHEMATICS AND COMPUTING↗