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At least 145 records · Page 8

Sunspots, Starspots, and Elemental Abundances

Element abundances in the solar photosphere, chromosphere, transition region, and corona are key parameters for investigating sources of the solar wind and for estimating radiative losses in the quiet corona and in dynamical events such as solar flares. Abundances in the solar corona and photosphere differ from each other depending on the first ionization potential (FIP) of the element. Normally, abundances with FIP values less than about 10 eV are about 3–4 times more abundant in the corona than in the photosphere. However, recently, an inverse FIP effect was found in small regions near sunspots where elements with FIP less than 10 eV are less abundant relative to high FIP elements (⩾10 eV) than they are in the photosphere. This is similar to fully convective stars with large starspots. The inverse FIP effect is predicted to occur in the vicinity of sunspots/starspots. Up to now, the solar anomalous abundances have only been found in very spatially small areas. In this paper, we show that in the vicinity of sunspots there can be substantially larger areas with abundances that are between coronal and photospheric abundances and sometimes just photospheric abundances. In some cases, the FIP effect tends to shut down near sunspots. We examine several active regions with relatively large sunspots that were observed with the Extreme-ultraviolet Imaging Spectrometer on the Hinode spacecraft in cycle 24.

79 ASTRONOMY AND ASTROPHYSICS↗

Impact of Inverter-Interfaced Renewable Generation on Transient Stability at Varying Levels of Penetration: Preprint

The transient dynamics of conventional power systems are dominated by synchronous generators, and low-inertia inverters serve as the primary interface between power systems and renewable energy resources. Increasing penetration levels of inverter-interfaced generation are impacting the transient dynamics of power systems. In this paper, we attempt to quantify these impacts at different penetration levels. An elementary system including one inverter, one synchronous generator, and one load is studied under different parameter variations to assess the transient dynamics of the system. To quantify transient stability, the post-fault regions of attraction of the system are estimated by the sample-based basin stability approach with parallel computing technology. The simulation results suggest that different inverter penetration levels, inertias of the generator, inverter controller gains, and phase-locked loop controller gains have a clear impact on the regions of attraction as well as on the transient dynamics of proposed systems.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Cost Implications of Uncertainty in CO{sub 2} Storage Resource Estimates: A Review

Carbon capture from stationary sources and geologic storage of carbon dioxide (CO{sub 2}) is an important option to include in strategies to mitigate greenhouse gas emissions. However, the potential costs of commercial-scale CO{sub 2} storage are not well constrained, stemming from the inherent uncertainty in storage resource estimates coupled with a lack of detailed estimates of the infrastructure needed to access those resources. Storage resource estimates are highly dependent on storage efficiency values or storage coefficients, which are calculated based on ranges of uncertain geological and physical reservoir parameters. If dynamic factors (such as variability in storage efficiencies, pressure interference, and acceptable injection rates over time), reservoir pressure limitations, boundaries on migration of CO{sub 2}, consideration of closed or semi-closed saline reservoir systems, and other possible constraints on the technically accessible CO{sub 2} storage resource (TASR) are accounted for, it is likely that only a fraction of the TASR could be available without incurring significant additional costs. Although storage resource estimates typically assume that any issues with pressure buildup due to CO{sub 2} injection will be mitigated by reservoir pressure management, estimates of the costs of CO{sub 2} storage generally do not include the costs of active pressure management. Production of saline waters (brines) could be essential to increasing the dynamic storage capacity of most reservoirs, but including the costs of this critical method of reservoir pressure management could increase current estimates of the costs of CO{sub 2} storage by two times, or more. Even without considering the implications for reservoir pressure management, geologic uncertainty can significantly impact CO{sub 2} storage capacities and costs, and contribute to uncertainty in carbon capture and storage (CCS) systems. Given the current state of available information and the scarcity of (data from) long-term commercial-scale CO{sub 2} storage projects, decision makers may experience considerable difficulty in ascertaining the realistic potential, the likely costs, and the most beneficial pattern of deployment of CCS as an option to reduce CO{sub 2} concentrations in the atmosphere.

54 ENVIRONMENTAL SCIENCES↗

Are camera surveys useful for assessing recruitment in white-tailed deer?

Camera surveys commonly are used by managers and hunters to estimate white-tailed deer Odocoileus virginianus density and demographic rates. Though studies have documented biases and inaccuracies in the camera survey methodology, camera traps remain popular due to ease of use, cost-effectiveness, and ability to survey large areas. Because recruitment is a key parameter in ungulate population dynamics, there is a growing need to test the effectiveness of camera surveys for assessing fawn recruitment. At Savannah River Site, South Carolina, we used six years of camera-based recruitment estimates (i.e. fawn:doe ratio) to predict concurrently collected annual radiotag-based survival estimates. The coefficient of determination (R) was 0.445, indicating some support for the viability of cameras to reflect recruitment. Here, we added two years of data from Fort Bragg Military Installation, North Carolina, which improved R to 0.621 without accounting for site-specific variability. Also, we evaluated the correlation between year-to-year changes in recruitment and survival using the Savannah River Site data; R was 0.758, suggesting that camera-based recruitment could be useful as an indicator of the trend in survival. Because so few researchers concurrently estimate survival and camera-based recruitment, examining this relationship at larger spatial scales while controlling for numerous confounding variables remains difficult. We believe that future research should test the validity of our results from other areas with varying deer and camera densities, as site (e.g. presence of feral pigs Sus scrofa) and demographic (e.g. fawn age at time of camera survey) parameters may have a large influence on detectability. Until such biases are fully quantified, we urge researchers and managers to use caution when advocating the use of camera-based recruitment estimates.

59 BASIC BIOLOGICAL SCIENCES↗

Calibrating Physical Parameters in House Models Using Aggregate AC Power Demand

For residential houses, the air conditioning (AC) units are one of the major resources that can provide significant flexibility in energy use for the purpose of demand response. To quantify the flexibility, the characteristics of all the houses need to be accurately estimated, so that certain house models can be used to predict the dynamics of the house temperatures in order to adjust the setpoints accordingly to provide demand response while maintaining the same comfort levels. In this paper, we propose an approach using the Reverse Monte Carlo modeling method and aggregate house models to calibrate the distribution parameters of the house models for a population of residential houses. Given the aggregate AC power demand for the population, the approach can successfully estimate the distribution parameters for the sensitive physical parameters based on our previous uncertainty quantification study, such as the mean of the floor areas of the houses.

Sun, Yannan↗

Characterizing vortex tangle properties in steady-state He II counterflow using particle tracking velocimetry

Historically, there has been little faith in particle tracking velocimetry (PTV) as a tool to make quantitative measurements of thermal counterflow in He II, since tracer particle motion is complicated by influences from the normal fluid, superfluid, and quantized vortex lines, or a combination thereof. Recently, we introduced a scheme for differentiating particles trapped on vortices (G1) from particles entrained by the normal fluid (G2). In this paper, we apply this scheme to demonstrate the utility of PTV for quantitative measurements of vortex dynamics in He II counterflow.We estimate Ι, the mean vortex line spacing, using G2 velocity data, and c 2 , a parameter related to the mean curvature radius of vortices and energy dissipation in quantum turbulence, using G1 velocity data. We find that both estimations show good agreement with existing measurements that were obtained using traditional experimental methods. This is of particular consequence since these parameters likely vary in space, and PTV offers the advantage of spatial resolution. Furthermore, we also show a direct link between power-law tails in transverse particle velocity probability density functions (PDFs) and reconnection of vortex lines on which G1 particles are trapped.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

A Multivariate Space‐Time Dynamic Model for Characterizing the Atmospheric Impacts Following the Mt. Pinatubo Eruption

The June 1991 Mt. Pinatubo eruption resulted in a massive increase of sulfate aerosols in the atmosphere, absorbing radiation and leading to global changes in surface and stratospheric temperatures. A volcanic eruption of this magnitude serves as a natural analog for stratospheric aerosol injection, a proposed solar radiation modification method to combat a warming climate. The impacts of such an event are multifaceted and region-specific. Our goal is to characterize the multivariate and dynamic nature of the atmospheric impacts following the Mt. Pinatubo eruption. We developed a multivariate space-time dynamic linear model to understand the full extent of the spatially- and temporally-varying impacts. Specifically, spatial variation is modeled using a flexible set of basis functions for which the basis coefficients are allowed to vary in time through a vector autoregressive (VAR) structure. This novel model is cast in a Dynamic Linear Model (DLM) framework and estimated via a customized MCMC approach. We demonstrate how the model quantifies the relationships between key atmospheric parameters prior to and following the Mt. Pinatubo eruption with reanalysis data from MERRA-2 and highlight when such a model is advantageous over univariate models.

Dynamic Linear Model↗

Effect of K + Force Fields on Ionic Conductivity and Charge Dynamics of KOH in Ethylene Glycol

Predicting ionic conductivity is crucial for developing efficient electrolytes for energy storage and conversion and other electrochemical applications. An accurate estimate of ionic conductivity requires understanding complex ion–ion and ion–solvent interactions governing the charge transport at the molecular level. Molecular simulations can provide key insights into the spatial and temporal behavior of electrolyte constituents. However, such insights depend on the ability of force fields to describe the underlying phenomena. In this work, molecular dynamics simulations were leveraged to delineate the impact of force field parameters on ionic conductivity predictions of potassium hydroxide (KOH) in ethylene glycol (EG). Four different force fields were used to represent the K + ion. Diffusion-based Nernst–Einstein and correlation-based Einstein approaches were implemented to estimate the ionic conductivity, and the predicted values were compared with experimental measurements. The physical aspects, including ion-aggregation, charge distribution, cluster correlation, and cluster dynamics, were also examined. A force field was identified that provides reasonably accurate Einstein conductivity values and a physically coherent representation of the electrolyte at the molecular level.

25 ENERGY STORAGE↗

Filtering adaptive output feedback control for multivariable nonlinear systems with mismatched uncertainties and unmodeled dynamics

This article synthesizes a filtering adaptive output feedback controller for multivariable nonlinear systems with mismatched uncertainties and unmodeled dynamics. The multivariable nonlinear systems under consideration have both matched and mismatched uncertainties, which satisfy the semiglobal Lipschitz condition. The unmodeled dynamics are bounded-input bounded-output stable. By adopting an estimation/cancellation strategy, a piecewise constant adaptive law drives the estimation error to zero at every time instant, which yields the adaptive parameters; a disturbance rejection control law is designed to compensate the nonlinear uncertainties within the bandwidth of low-pass filters. The matched uncertainties are cancelled directly by adopting their opposite in the control signal, while a dynamic inversion of the system is required to eliminate the effect of the mismatched uncertainties on the output. A feedforward control law is designed to track a given command. Since the virtual reference system defines the best performance that can be achieved by the closed-loop system, the uniform performance bounds are derived for the states and control signals via comparison. Both numerical and practical examples are provided to illustrate the effectiveness of the proposed filtering adaptive output feedback control architecture, comparisons with the model reference adaptive control demonstrates the superiority of the proposed control method.

filtering adaptive control, mismatched uncertainit↗

Rapid data-driven model reduction of nonlinear dynamical systems including chemical reaction networks using ℓ 1 -regularization

We develop a new data-driven paradigm for efficient model reduction of a broad class of nonlinear dynamical systems. Our model reduction method directly enables the interpretation of key components of the dynamical system, unlike traditional projection-based model reduction methods that focus on reducing computational complexity more than interpretability. Our method is not application specific and is simple to implement on nonlinear dynamical systems arising from a variety of different fields. It requires minimal parameterization using a single parameter to trade-off between model complexity and estimation error. We use a data-driven paradigm to formulate model reduction as an efficient convex optimization problem that scales polynomially in the original size of the complex system, enabling systems with as many as thousands of components to be reduced in a matter of minutes.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Dynamically morphing microchannels in liquid crystal elastomer coatings containing disclinations

Liquid crystal elastomers (LCEs) hold a major promise as a versatile material platform for smart soft coatings, since their orientational order can be predesigned to program a desired dynamic profile. In this work, we introduce temperature-responsive dynamic coatings based on LCEs with arrays of singular defects-disclinations that run parallel to the surface. The disclinations form in response to antagonistic patterns of the molecular orientation at the top and bottom surfaces, imposed by the plasmonic mask photoalignment. Upon heating, an initially flat LCE coating develops linear microchannels located above each disclination. The stimulus that causes a non-flat profile of LCE coatings upon heating is the activation force induced by the gradients of molecular orientation around disclinations. To describe the formation of microchannels and their thermal response, we adopt a Frank-Oseen model of disclinations in patterned director field and propose a linear elasticity theory to connect the complex spatially-varying molecular orientation to the displacements of the LCE. The thermo-responsive surface profiles predicted by the theory and by the finite element modeling are in good agreement with the experimental data; in particular, higher gradients of molecular orientation produce a stronger modulation of the coating profile. The elastic theory and the finite element simulations allow us to estimate the material parameter that characterizes the elastomer coating’s response to the thermal activation. The disclinations containing LCEs show potential as soft dynamic coatings with a predesigned responsive surface profile.

36 MATERIALS SCIENCE↗

Detecting outbreaks using a spatial latent field

In this paper, we present a method for estimating the infection-rate of a disease as a spatial-temporal field. Our data comprises time-series case-counts of symptomatic patients in various areal units of a region. We extend an epidemiological model, originally designed for a single areal unit, to accommodate multiple units. The field estimation is framed within a Bayesian context, utilizing a parameterized Gaussian random field as a spatial prior. We apply an adaptive Markov chain Monte Carlo method to sample the posterior distribution of the model parameters condition on COVID-19 case-count data from three adjacent counties in New Mexico, USA. Our results suggest that the correlation between epidemiological dynamics in neighboring regions helps regularize estimations in areas with high variance (i.e., poor quality) data. Using the calibrated epidemic model, we forecast the infection-rate over each areal unit and develop a simple anomaly detector to signal new epidemic waves. Our findings show that anomaly detector based on estimated infection-rates outperforms a conventional algorithm that relies solely on case-counts.

Safta, Cosmin [Sandia National Laboratories (SNL-C↗

Data-driven discovery of dynamics from time-resolved coherent scattering

Coherent X-ray scattering (CXS) techniques are capable of interrogating dynamics of nano- to mesoscale materials systems at time scales spanning several orders of magnitude. However, obtaining accurate theoretical descriptions of complex dynamics is often limited by one or more factors—the ability to visualize dynamics in real space, computational cost of high-fidelity simulations, and effectiveness of approximate or phenomenological models. In this work, we develop a data-driven framework to uncover mechanistic models of dynamics directly from time-resolved CXS measurements without solving the phase reconstruction problem for the entire time series of diffraction patterns. Our approach uses neural differential equations to parameterize unknown real-space dynamics and implements a computational scattering forward model to relate real-space predictions to reciprocal-space observations. This method is shown to recover the dynamics of several computational model systems under various simulated conditions of measurement resolution and noise. Moreover, the trained model enables estimation of long-term dynamics well beyond the maximum observation time, which can be used to inform and refine experimental parameters in practice. Finally, we demonstrate an experimental proof-of-concept by applying our framework to recover the probe trajectory from a ptychographic scan. Our proposed framework bridges the wide existing gap between approximate models and complex data.

36 MATERIALS SCIENCE↗

CO OBSERVATIONS AND INVESTIGATION OF TRIGGERED STAR FORMATION TOWARD THE N10 INFRARED BUBBLE AND SURROUNDINGS

We studied the environment of the dust bubble N10 in molecular emission. Infrared bubbles, first detected by the GLIMPSE survey at 8.0 μ m, are ideal regions to investigate the effect of the expansion of the H ii region on its surroundings and the eventual triggering of star formation at its borders. In this work, we present a multi-wavelength study of N10. This bubble is especially interesting because infrared studies of the young stellar content suggest a scenario of ongoing star formation, possibly triggered on the edge of the H ii region. We carried out observations of {sup 12}CO(1-0) and {sup 13}CO(1-0) emission at PMO 13.7 m toward N10. We also analyzed the IR and sub-millimeter emission on this region and compare those different tracers to obtain a detailed view of the interaction between the expanding H ii region and the molecular gas. We also estimated the parameters of the denser cold dust condensation and the ionized gas inside the shell. Bright CO emission was detected and two molecular clumps were identified from which we have derived physical parameters. We also estimate the parameters for the densest cold dust condensation and for the ionized gas inside the shell. The comparison between the dynamical age of this region and the fragmentation timescale favors the “Radiation-Driven Implosion” mechanism of star formation. N10 is a case of particular interest with gas structures in a narrow frontier between the H ii region and surrounding molecular material, and with a range of ages of YSOs situated in the region, indicating triggered star formation.

79 ASTRONOMY AND ASTROPHYSICS↗

A DATA-DRIVEN ANALYTIC MODEL FOR PROTON ACCELERATION BY LARGE-SCALE SOLAR CORONAL SHOCKS

We have recently studied the development of an eruptive filament-driven, large-scale off-limb coronal bright front (OCBF) in the low solar corona, using remote observations from the Solar Dynamics Observatory ’s Advanced Imaging Assembly EUV telescopes. In that study, we obtained high-temporal resolution estimates of the OCBF parameters regulating the efficiency of charged particle acceleration within the theoretical framework of diffusive shock acceleration (DSA). These parameters include the time-dependent front size, speed, and strength, as well as the upstream coronal magnetic field orientations with respect to the front’s surface normal direction. Here we present an analytical particle acceleration model, specifically developed to incorporate the coronal shock/compressive front properties described above, derived from remote observations. We verify the model’s performance through a grid of idealized case runs using input parameters typical for large-scale coronal shocks, and demonstrate that the results approach the expected DSA steady-state behavior. We then apply the model to the event of 2011 May 11 using the OCBF time-dependent parameters derived by Kozarev et al. We find that the compressive front likely produced energetic particles as low as 1.3 solar radii in the corona. Comparing the modeled and observed fluences near Earth, we also find that the bulk of the acceleration during this event must have occurred above 1.5 solar radii. With this study we have taken a first step in using direct observations of shocks and compressions in the innermost corona to predict the onsets and intensities of solar energetic particle events.

79 ASTRONOMY AND ASTROPHYSICS↗

Membrane interactions of the globular domain and the hypervariable region of KRAS4b define its unique diffusion behavior

The RAS proteins are GTP-dependent switches that regulate signaling pathways and are frequently mutated in cancer. RAS proteins concentrate in the plasma membrane via lipid-tethers and hypervariable region side-chain interactions in distinct nano-domains. However, little is known about RAS membrane dynamics and the details of RAS activation of downstream signaling. Here, we characterize RAS in live human and mouse cells using single-molecule-tracking methods and estimate RAS mobility parameters. KRAS4b exhibits confined mobility with three diffusive states distinct from the other RAS isoforms (KRAS4a, NRAS, and HRAS); and although most of the amino acid differences between RAS isoforms lie within the hypervariable region, the additional confinement of KRAS4b is largely determined by the protein’s globular domain. To understand the altered mobility of an oncogenic KRAS4b, we used complementary experimental and molecular dynamics simulation approaches to reveal a detailed mechanism.

59 BASIC BIOLOGICAL SCIENCES↗

Dynamics of filaments during the edge-localized mode crash on NSTX

Edge localized modes (ELMs) are routinely observed in H-mode plasma regimes of the National Spherical Torus Experiment (NSTX). Due to the explosive nature of the instability, only diagnostics with high temporal and spatial resolution could provide a detailed insight into the dynamics associated with the ELMs. Gas-puff imaging at NSTX provides 2D measurements of the magnetic field aligned fluctuations (e.g., ELM filaments) in the scrape-off layer and at the plasma edge with 2.5 μs temporal and 10 mm optical resolution. A novel analysis technique was developed to estimate the frame-by-frame velocities and the spatial parameters of the dominant structures associated with the ELMs. The analysis was applied to single ELM events to characterize the ELM crash dynamics and then extended to a database of 159 ELM events. Statistical analysis was performed in order to find the characterizing dynamics of the ELM crash. The results show that on average, an ELM crash consists of a filament with a circular cross section, which is propelled outward with a characterizing peak radial velocity of ~3.3 km/s. The radial velocity was found to be linearly dependent on the distance of the filament from the separatrix, which has never been seen before. The ELM filament is characterized by propagation in the ion-diamagnetic direction poloidally with a peak velocity of 11.4 km/s. The ELM crash lasts for approximately 100 μs until the radial propulsion settles back to the pre-ELM level. Furthermore, the experimental findings were compared with analytical theory. Two possible mechanisms were identified for explaining the observations: the curvature interchange model and the current–filament interaction model.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Dynamics of filaments during the edge-localized mode crash on NSTX

Edge localized modes (ELMs) are routinely observed in H-mode plasma regimes of the National Spherical Torus Experiment (NSTX). Due to the explosive nature of the instability, only diagnostics with high temporal and spatial resolution could provide a detailed insight into the dynamics associated with the ELMs. Gas-puff imaging (GPI) at NSTX provides 2D measurements of the magnetic field aligned fluctuations (e.g. ELM filaments) in the scrape-off layer and the at the plasma edge with 2.5 us temporal and 10 mm optical resolution.A novel analysis technique was developed to estimate the frame-by-frame velocities and the spatial parameters of the dominant structures associated with the ELMs. The analysis was applied to single ELM events to characterize the ELM crash dynamics, and then extended to a database of 169 ELM events.Statistical analysis was performed in order to find the characterizing dynamics of the ELM crash. The results show that on average an ELM crash consists of a filament with a circular cross-section which is propelled outwards with a characterizing peak radial velocity of ~3.3 km/s. The radial velocity was found to be linearly dependent on the distance of the filament from the separatrix, which has never been seen before. The ELM filament is characterized by propagation in the ion-diamagnetic direction poloidally with a peak velocity of 11.4 km/s. The ELM crash lasts for approximately 100us until the radial propulsion settles back to the pre-ELM level. The experimental findings were compared with analytical theory. Two possible mechanisms were identified for explaining the observations: the curvature interchange model and the current-filament interaction model.

correlation↗