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The Splitting of Double-component Active Asteroid P/2016 J1 (PANSTARRS)
We present deep imaging observations, orbital dynamics, and dust-tail model analyses of the double-component asteroid P/2016 J1 (J1-A and J1-B). The observations were acquired at the Gran Telescopio Canarias (GTC) and the Canada–France–Hawaii Telescope (CFHT) from mid-March to late July of 2016. A statistical analysis of backward-in-time integrations of the orbits of a large sample of clone objects of P/2016 J1-A and J1-B shows that the minimum separation between them occurred most likely ∼2300 days prior to the current perihelion passage, i.e., during the previous orbit near perihelion. This closest approach was probably linked to a fragmentation event of their parent body. Monte Carlo dust-tail models show that those two components became active simultaneously ∼250 days before the current perihelion, with comparable maximum loss rates of ∼0.7 and ∼0.5 kg s{sup −1}, and total ejected masses of 8 × 10{sup 6} and 6 × 10{sup 6} kg for fragments J1-A and J1-B, respectively. Consequently, the fragmentation event and the present dust activity are unrelated. The simultaneous activation times of the two components and the fact that the activity lasted 6–9 months or longer, strongly indicate ice sublimation as the most likely mechanism involved in the dust emission process.
Optimal control of wave energy converters
A wave energy converter and method for extracting energy from water waves maximizes the energy extraction per cycle by estimating an excitation force of heave wave motion on the buoy, computing a control force from the estimated excitation force using a dynamic model, and applying the computed control force to the buoy to extract energy from the heave wave motion. Analysis and numerical simulations demonstrate that the optimal control of a heave wave energy converter is, in general, in the form of a bang-singular-bang control; in which the optimal control at a given time can be either in the singular arc mode or in the bang-bang mode. The excitation force and its derivatives at the current time can be obtained through an estimator, for example, using measurements of pressures on the surface of the buoy in addition to measurements of the buoy position. A main advantage of this approximation method is the ease of obtaining accurate measurements for pressure on the buoy surface and for buoy position, compared to wave elevation measurements.
Uncertainty Quantification of Calculated Temperatures for the AGR 5/6/7 Experiment
This report documents the quantification of uncertainty of the calculated temperature data for the Advanced Gas Reactor (AGR) 5/6/7 fuel irradiation experiment conducted in the Advanced Test Reactor at Idaho National Laboratory in support of the Advanced Reactor Technologies? research and development program. Recognizing uncertainties inherent in physics and thermal simulations of the AGR 5/6/7 capsules, the results of the numerical simulations are used in combination with statistical analysis methods to improve qualification of measured data. The calculated fuel temperatures for AGR tests are also used for validation of the fission product transport and fuel performance simulation models. These crucial roles of the calculated fuel temperatures in ensuring achievement of the AGR experimental program objectives require accurate determination of the model temperature uncertainties. This report covers temperature uncertainty results for each of the five AGR 5/6/7 capsules. To quantify the uncertainty of calculated temperatures determined using the ABAQUS finite element heat transfer code, this study identifies and analyzes model parameters of potential importance to the calculated temperatures of fuel compacts and thermocouples. The selection of input parameters for uncertainty quantification is based on the ranking of their influences upon temperature predictions. Thus, selected input parameters include those with high sensitivity and those with the largest uncertainty. Propagation of model parameter uncertainty and sensitivity is then used to quantify the overall uncertainty of calculated temperatures. Measurement uncertainty, analysis of modeling assumptions, and expert judgment are used as the basis to quantify the uncertainty range for selected input parameters. The input uncertainties are dynamic, accounting for the effect of unplanned events and changes in thermal properties of capsule components over extended exposure to high temperatures and fast neutron irradiation. The sensitivity analysis performed in this work went beyond the traditional local sensitivity. Using experimental design, analysis of pairwise interactions of model parameters was performed to establish sufficiency of the time dependent first order (linear) expansion terms in constructing the temperature response surface. To achieve completeness, uncertainty propagation made use of pairwise noise correlations of model parameters. Furthermore, using an interpolation scheme over the input parameter domain, the analysis obtains time dependent sensitivity over the test campaign duration. This allows computation of uncertainty for the calculated fuel temperatures and the calculated graphite temperatures at thermocouple locations during the entire irradiation period.
Autocorrelation and Multifractal Detrended Fluctuation Analyses Reveal Superdiffusive Mass Transport in Solvent-Filled Nanoporous Media
Fluorescence fluctuation spectroscopy experiments were conducted to better understand the complex mass transport dynamics of organic molecules in liquid-filled nanoporous media. Anodic aluminum oxide (AAO) membranes incorporating 10 and 20 nm diameter cylindrical pores were employed as model materials. Nile red (NR) dye was used as a fluorescent tracer. The dye was dissolved separately in ethanol and toluene at a concentration of 20 nM and used to fill the membrane nanopores. Confocal fluorescence microscopy was employed to capture photon intensity time series data reflecting apparent diffusion of the dye within the pores. Autocorrelation of these data revealed that NR diffusion within the membranes occurred over a broad range of time scales. The autocorrelation decays were fit to a model for one-dimensional diffusion incorporating both fast and slow components having apparent diffusion coefficients, D f and D s , differing by a factor of ∼100. The fast mechanism was attributed to hindered bulk-like diffusion in the central pore cavity, while slow diffusion likely involved absorption of the dye to the pore surfaces. Unfortunately, important evidence of diffusion anomalies is lost in the broad autocorrelation decays obtained. The method of multifractal detrended fluctuation analysis (MF-DFA) was applied to the same data as a means to overcome this limitation. MF-DFA revealed that time series acquired from within the nanopores were multifractal and exhibited evidence of anomalous superdiffusion, likely resulting from the participation of a desorption-mediated diffusion mechanism. Monte Carlo simulations of time series modeling desorption-mediated diffusion in cylindrical nanopores provided support for this assignment. Here, the new knowledge gained affords an improved understanding of hydrocarbon dynamics within nanoporous oil and gas shales.
Observation of mode splitting in artificial spin ice: A comparative ferromagnetic resonance and Brillouin light scattering study
We report the dependence of the magnetization dynamics in a square artificial spin-ice lattice on the in-plane magnetic field angle. Using two complementary measurement techniques—broadband ferromagnetic resonance and micro-focused Brillouin light scattering spectroscopy—we systematically study the evolution of the lattice dynamics, for both a coherent radio frequency excitation and an incoherent thermal excitation of spin dynamics. We observe a splitting of modes facilitated by inter-element interactions that can be controlled by the external field angle and magnitude. Detailed time-dependent micromagnetic simulations reveal that the split modes are localized in different regions of the square network. Furthermore, this observation suggests that it is possible to disentangle modes with different spatial profiles by tuning the external field configuration.
Noise analysis of genome-scale protein synthesis using a discrete computational model of translation
Noise in genetic networks has been the subject of extensive experimental and computational studies. However, very few of these studies have considered noise properties using mechanistic models that account for the discrete movement of ribosomes and RNA polymerases along their corresponding templates (messenger RNA (mRNA) and DNA). The large size of these systems, which scales with the number of genes, mRNA copies, codons per mRNA, and ribosomes, is responsible for some of the challenges. Additionally, one should be able to describe the dynamics of ribosome exchange between the free ribosome pool and those bound to mRNAs, as well as how mRNA species compete for ribosomes. We developed an efficient algorithm for stochastic simulations that addresses these issues and used it to study the contribution and trade-offs of noise to translation properties (rates, time delays, and rate-limiting steps). The algorithm scales linearly with the number of mRNA copies, which allowed us to study the importance of genome-scale competition between mRNAs for the same ribosomes. We determined that noise is minimized under conditions maximizing the specific synthesis rate. Moreover, sensitivity analysis of the stochastic system revealed the importance of the elongation rate in the resultant noise, whereas the translation initiation rate constant was more closely related to the average protein synthesis rate. We observed significant differences between our results and the noise properties of the most commonly used translation models. Overall, our studies demonstrate that the use of full mechanistic models is essential for the study of noise in translation and transcription.
Tracking the Light-Induced Excited-State Dynamics and Structural Configurations of an Extraordinarily Long-Lived Metastable State at Room Temperature
Time-resolved X-ray (Tr-XAS) and optical transient absorption (OTA) spectroscopy in the pico-microsecond time scale coupled with Density Functional theory calculations are applied to study the light-induced spin crossover processes of a Fe-based macrocyclic complex in solution. Tr-XAS analysis after light illumination shows the formation of a seven-coordinated high spin quintet metastable state which relaxes to a six-coordinated high spin configuration before decaying to ground state. Kinetic analysis of the macrocyclic complex reveals an unprecedented long-lived decay lifetime of ~42.6 µs. Comparative studies with a non-macrocyclic counterpart illustrate a significantly shortened ~568-old decay lifetime of ~75 ns, and highlight the importance of the ligand arrangement in stabilizing the reactivity of the excited state. Lastly, OTA analysis shows the seven-coordinated high spin state to be formed within ~6.2 ps. Finally, these findings provide a complete understanding of the spin crossover reaction and relaxation pathways of the macrocyclic complex, and reveal the importance of a flexible coordination environment for their rational design.
Enhanced window breakdown dynamics in a nanosecond microwave tail pulse
The mechanisms of nanosecond microwave-driven discharges near a dielectric/vacuum interface were studied by measuring the time- and space-dependent optical emissions and pulse waveforms. The experimental observations indicate multipactor and plasma developing in a thin layer of several millimeters above interface. The emission brightness increases significantly after main pulse, but emission region widens little. The mechanisms are studied by analysis and simulation, revealing intense ionization concentrated in a desorbed high-pressure layer, leading to a bright light layer above surface; the lower-voltage tail after main pulse contributes to heat electron energy tails closer to excitation cross section peaks, resulting in brighter emission.
Field Dynamics of Coherent Synchrotron Radiation Using a Direct Numerical Solution of Maxwell's Equations
We present and discuss the properties of the coherent electromagnetic fields of a very short, ultrarelativistic bunch in a rectangular vacuum chamber inside a bending magnet. The analysis is based on the results of a direct numerical solution of Maxwell's equations together with Newton's equations. We use a new dispersion-free time-domain algorithm which employs a more efficient use of finite element mesh techniques and, hence, produces self-consistent and stable solutions for very short bunches. We investigate the fine structure of the coherent synchrotron radiation fields. We also discuss coherent edge radiation. We present a clear picture of the field using the electric field lines constructed from the numerical solutions. This method should be useful in the study of existing and future concepts of particle accelerators and ultrafast coherent light sources, where high peak currents and very short bunches are envisioned.
Use of Interrupted Helium Flow in the Analysis of Vapor Samples with Flowing Atmospheric-Pressure Afterglow-Mass Spectrometry
The flowing atmospheric-pressure afterglow (FAPA) source was used for the mass-spectrometric analysis of vapor samples introduced between the source and mass spectrometer inlet. Through interrupted operation of the plasma-supporting helium flow, helium consumption is greatly reduced and dynamic gas behavior occurs that was characterized by schlieren imaging. Moreover, mass spectra acquired immediately after the onset of helium flow exhibit a signal spike before declining and ultimately reaching a steady level. This initial signal appears to be due to greater interaction of sample vapor with the afterglow of the source when helium flow resumes. In part, the initial spike in signal can be attributed to a pooling of analyte vapor in the absence of helium flow from the source. Finally, time-resolved schlieren imaging of the helium flow during on and off cycles provided insight into gas-flow patterns between the FAPA source and the MS inlet that were correlated with mass-spectral data.
Synthesis of high intrinsic loss power aqueous ferrofluids of iron oxide nanoparticles by citric acid-assisted hydrothermal-reduction route
Monodispersed aqueous ferrofluids of iron oxide nanoparticle were synthesized by hydrothermal-reduction route. They were characterized by X-ray diffraction analysis, Fourier transform infrared spectroscopy, scanning and transmission electron microscopy and dynamic light scattering. The results showed that certain concentrations of citric acid (CA) are required to obtain only magnetic iron oxides with mean particle sizes around 8 nm. CA acts as a modulator and reducing agent in iron oxide formation which controls nanoparticle size. The XRD, magnetic and heating measurements showed that the temperature and time of hydrothermal reaction can affect the magnetic properties of obtained ferrofluids. The synthesized ferrofluids were stable at pH 7. Their mean hydrodynamic size was around 80 nm with polydispersity index (PDI) of 0.158. The calculated intrinsic loss power (ILP) was 9.4 nHm{sup 2}/kg. So this clean and cheap route is an efficient way to synthesize high ILP aqueous ferrofluids applicable in magnetic hyperthermia. - Graphical abstract: Monodispersed aqueous ferrofluids of iron oxide nanoparticles were synthesized by hydrothermal-reduction method with citric acid as reductant which is an efficient way to synthesize aqueous ferrofluids applicable in magnetic hyperthermia. Highlights: Black-Right-Pointing-Pointer Aqueous iron oxide ferrofluids were synthesized by hydrothermal-reduction route. Black-Right-Pointing-Pointer Citric acid acted as reducing agent and surfactant in the route. Black-Right-Pointing-Pointer This is a facile, low energy and environmental friendly route. Black-Right-Pointing-Pointer The aqueous iron oxide ferrofluids were monodispersed and stable at pH of 7. Black-Right-Pointing-Pointer The calculated intrinsic loss power of the synthesized ferrofluids was very high.
Cyber-Infrastructure for Data-Intensive Geospatial Computing
With the recent advent of heterogeneous High-performance Computing (HPC) to handle EO “Big Data” workloads, there is a need for a unified Cyber-infrastructure (CI) platform that can bridge the best of many HPC worlds. In this chapter, we discuss such a CI platform being developed at Geographic Information Science and Technology (GIST) group using novel and innovative techniques, and emerging technologies that are scalable to large-scale supercomputers. The CI platform utilizes a wide variety of computing such as GPGPU, distributed, real-time and cluster computing, which are being brought together architecturally to enable data-driven analysis, scientific understanding of earth system models, and research collaboration. This development addresses the need for close integration of EO and other geospatial information in the face of growing volumes of the data, and facilitates spatio-temporal analysis of disparate and dynamic data streams. Horizontal scalability and linear throughput are supported in the heart of the platform itself. It is being used to support very broad application areas, ranging from high-resolution settlement mapping, national bioenergy infrastructure to urban information and mobility systems. The platform provides spatio-temporal decision support capabilities in planning, policy and operational missions for US federal agencies. Also, the platform is designed to be functionally and technologically sustainable for continued support of the US energy and environment mission for the coming decades.
Polymer coatings on zirconia microspheres via rotating flow fluid dynamics
Conventional tristructural isotropic (TRISO) coatings for nuclear fuels require multi-step and expensive formation processes; any breakage of the coatings may lead to fission species release. Polymer derived ceramic (PDC) coatings can be a suitable alternative to address these issues. In this study, allylhydridopolycarbosilane (SMP-10) coatings were created on yttria stabilized zirconia (YSZ) microspheres using a Rotating Flow Fluid Dynamics (RFFD) coating method. The effects of curing temperature, rotation speed, and coating cycle/time on the coating were analyzed. Surface functionalization of YSZ microspheres with NaOH resulted in good adhesion between the polymer precursor and the YSZ kernel particles. Spectroscopy analysis revealed complete curing of SMP-10 coated YSZ at 160 °C. Rotation speed and coating time significantly affect the coating characteristics. After 3 cycles at lower rotation speed (50 rpm) for 10 min each, the coating obtained was uniform and homogeneous. In comparison, the coating showed almost 10 times less eccentricity at a high rotation speed of 300 rpm. Compared with the coatings prepared at 300 rpm condition, the coatings have higher sphericity and lower eccentricity at 50 rpm. Overall, this study provides a novel and effective route for fabricating and curing SMP-10 precursor coatings on YSZ microspheres.
Modelling and analysis of salt-convection effect on oxide reduction process for uranium oxides using smoothed particle hydrodynamics
Oxygen ion transport via molten salt continuum is a key kinetic feature of electrochemical reduction process for uranium oxides in molten salt. During the electrolysis, the evolution of oxygen ion concentration field in molten salt continuum appears from porous metallic layer to open bulk salt. Despite the important role affecting process throughput, its effect coupled with controlled salt movement was not adequately investigated. To capture the reactive oxygen ion transport phenomena, a multidimensional reduction model based on smoothed particle hydrodynamics (SPH) was combined with the advection-diffusion model. A pelletized oxide fuel bed capturing interconnected salt continuum is considered as a reactant material geometry, which allows forced convective delivery of molten salt through the reactant materials with a relatively low pressure head. Here, in this study, reduction time of a pelletized-fuel bed was quantified with respect to key design parameters of the reactant material configuration. The simulation results demonstrated the advantage of salt convection which effectively removes oxygen ion products from the reactant materials and consequently accelerates the reduction process. Moreover, the reduction-time correlation of a single pelletized fuel was developed as a function of relevant dimensionless parameters and was extended to the application for a pelletized-fuel bed. Finally, several insights and implications in the use of a pelletized oxide fuel were presented. The developed SPH-based framework enabled multi-physics analysis of governing dynamics in appreciating and screening candidate reactant material configurations in a cost-effective manner.
Mechanism of conductivity relaxation in liquid and polymeric electrolytes: Direct link between conductivity and diffusivity
Combining broadband impedance spectroscopy, differential scanning calorimetry, and nuclear magnetic resonance we analyzed charge and mass transport in two polymerized ionic liquids and one of their monomeric precursors. In order to establish a general procedure for extracting single-particle diffusivity from their conductivity spectra, we critically assessed several approaches previously employed to describe the onset of diffusive charge dynamics and of the electrode polarization in ion conducting materials. Based on the analysis of the permittivity spectra, we demonstrate that the conductivity relaxation process provides information on ion diffusion and the magnitude of cross-correlation effects between ionic motions. A new approach is introduced which is able to estimate ionic diffusivities from the characteristic times of conductivity relaxation and ion concentration without any adjustable parameters. Furthermore, this opens the venue for a deeper understanding of charge transport in concentrated and diluted electrolyte solutions.
Matrix Approach to Land Carbon Cycle Modeling
Land ecosystems contribute to climate change mitigation by taking up approximately 30% of anthropogenically emitted carbon. However, estimates of the amount and distribution of carbon uptake across the world's ecosystems or biomes display great uncertainty. The latter hinders a full understanding of the mechanisms and drivers of land carbon uptake, and predictions of the future fate of the land carbon sink. The latter is needed as evidence to inform climate mitigation strategies such as afforestation schemes. To advance land carbon cycle modeling, we have developed a matrix approach. Land carbon cycle models use carbon balance equations to represent carbon exchanges among pools. Our approach organizes this set of equations into a single matrix equation without altering any processes of the original model. The matrix equation enables the development of a theoretical framework for understanding the general, transient behavior of the land carbon cycle. While carbon input and residence time are used to quantify carbon storage capacity at steady state, a third quantity, carbon storage potential, integrates fluxes with time to define dynamic disequilibrium of the carbon cycle under global change. The matrix approach can help address critical contemporary issues in modeling, including pinpointing sources of model uncertainty and accelerating spin-up of land carbon cycle models by tens of times. The accelerated spin-up liberates models from the computational burden that hinders comprehensive parameter sensitivity analysis and assimilation of observational data to improve model accuracy. Such computational efficiency offered by the matrix approach enables substantial improvement of model predictions using ever-increasing data availability. Overall, the matrix approach offers a step change forward for understanding and modeling the land carbon cycle.