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At least 1,081 records · Page 60

Linking Plasma Conditions in the Magnetosphere with Ionospheric Signatures

Modeling of the full magnetosphere, ring current and ionosphere system has become an indispensable tool in analyzing the series of events that occur during geomagnetic storms. The CCMC has a full model suite available for the magnetosphere, together with visualization tools that allow a user to perform a large variety of analyses. The January, 21, 2005 storm was a moderate-size storm that has been found to feature a large penetration electric field and unusually large polar caps (low-latitude precipitation patterns) that are otherwise found in super storms. Based on simulations runs at CCMC we can outline the likely causes of this behavior. Using visualization tools available to the online user we compare results from different magnetosphere models and present connections found between features in the magnetosphere and the ionosphere that are connected magnetically. The range of magnetic mappings found with different models can be compared with statistical models (Tsyganenko) and the model's fidelity can be verified with observations from low earth orbiting satellites such as DMSP and TIMED.

Rastaetter, Lutz↗

Landform Evolution Modeling of Sedimentary Processes on Icy Worlds: the Cases of Hyperion and Helene

Sedimentary activity (erosion, transportation and deposition) is a major landscape-shaping process on many icy worlds of the outer solar system for which an understanding of this process is central to their geologic characterizations. Several recent studies, lead by the authors, have identified the effects of sedimentary activity on icy satellite landforms and recognized the role of mass wasting and volatile loss and redistribution in the evolution of these features. We apply state of the art, physics based, landform evolution modeling to icy satellite sedimentary landforms in order to fully quantitatively characterize how their morphologies change with time, and what their present appearances imply for the initial abundance and distribution of loose material, volatiles, and refractories in original pristine landforms. We will present results of our landform evolution modeling to the development of the landscapes of the Saturnian moons of Hyperion and Helene. Our current conclusions for Hyperion are that its unique appearance can be explained in part by the loss to space of ballistic ejecta during impact events. In order to create the smooth surfaces and the reticulate, honeycomb pattern of narrow divides between old craters, appreciable subsequent modification of crater morphology must occur through mass-wasting processes accompanied by sublimation, probably facilitated by the loss of CO2 as a component of the relief-supporting matrix of the bedrock. This mass wasting effectively destroys small craters, at least in part accounting for the paucity of sub-kilometer craters on Hyperion. Helene’s unusual morphology consists of broad depressions (modified large craters) and a generally smooth surface patterned with streaks and grooves. The streaks appear to be oriented down-gradient, as are the grooves. This pattern suggests intensive mass-wasting as a dominant process. Our initial modeling of this surface suggests a Bingham-like rheological behavior for the loose down-slope moving material. Interestingly, as a Bingham flow, the models indicate that aperiodic "intermittent" behavior to be present, suggesting that periods of quiet steady landform evolution are punctuated short periods of active surface readjustment.

Saturnian moons↗

Assessment of Extremes in Global Precipitation Products: How Reliable Are They?

Global gridded precipitation products have proven essential for many applications ranging from hydrological modeling and climate model validation to natural hazard risk assessment. They provide a global picture of how precipitation varies across time and space, specifically in regions where ground-based observations are scarce. While the application of global precipitation products has become widespread, there is limited knowledge on how well these products represent the magnitude and frequency of extreme precipitation—the key features in triggering flood hazards. Here, five global precipitation datasets (MSWEP, CFSR, CPC, PERSIANN-CDR, and WFDEI) are compared to each other and to surface observations. The spatial variability of relatively high precipitation events (tail heaviness) and the resulting discrepancy among datasets in the predicted precipitation return levels were evaluated for the time period 1979–2017. The analysis shows that 1) these products do not provide a consistent representation of the behavior of extremes as quantified by the tail heaviness, 2) there is strong spatial variability in the tail index, 3) the spatial patterns of the tail heaviness generally match the Köppen–Geiger climate classification, and 4) the predicted return levels for 100 and 1000 years differ significantly among the gridded products. More generally, our findings reveal shortcomings of global precipitation products in representing extremes and highlight that there is no single global product that performs best for all regions and climates.

Risk assessment↗

Electrifying Road Trips to and from National Parks in the Western United States

We evaluate charging infrastructure requirement for electrified long-distance travels to/from national parks in the Western U.S. We conduct a high-resolution spatial and temporal analysis of road trips in the region, accounting for detailed travel volume and pattern, the type of electric vehicles, heterogeneous energy consumption rates depending on driving conditions, charging technology (e.g., power and speed), and charging behavior. The scope includes on-route (or way-point) charging as well as destination charging (in national parks). We estimate the locations and sizes of required charging stations in the entire Western U.S. to enable electrified road trips to/from national parks. We also examine environmental justice and energy equity aspects of projected charging infrastructure (for national parks) in the context of the overall vehicle electrification and charging infrastructure build-out.

ADVANCED PROPULSION SYSTEMS,ENERGY PLANNING, POLIC↗

New principles of self‐organization created through the interplay of DNA condensates, microtubules, and motors

Bioinspired design—which holds great promise for a new generation of materials that are robust to defects, scalable under green manufacture, environmentally responsive, and programmably reconfigurable—requires mastery over molecular self-organization. Yet, from its specific mechanisms to most general architectures, the principles governing self-organization remain poorly understood and not even fully enumerated. For living systems, one obvious architectural principle is the modular reuse of a few simple molecular components in myriad combinations to achieve more complex phenomena. For example, the mechanical tasks of a cell are driven by the nonequilibrium dynamics of cytoskeletal filaments and molecular motors—the same filaments and motors, reprogrammed by a variety of modulators, perform tasks ranging from cell movement to division. Similarly, many compartmentalization tasks are performed by liquid-like condensates of simple components, which act as membraneless organelles to localize particular molecules in space and time (e.g. for gene regulation or RNA processing). In a few cases, condensates combine and interact with the cytoskeleton to create still more complex phenomena, e.g. the nucleation of microtubule asters from the centrosome (a protein condensate) to form the mitotic spindle during cell division. Very little is known about the fundamental mechanisms of such filament-plus-condensate phenomena. Despite few examples, the landscape of behaviors that can be achieved through the combination of condensates, filaments, and motors appears vast. However, exploration has been hindered by a lack of systems that have sufficiently programmable and dynamically tunable interactions between component condensates, filaments, and motors. We proposed to combine programmable DNA condensates, filamentous microtubules, and light-controlled motors into self-organizing systems whose principles go beyond those that have been observed in nature. In one limit, our systems will use microtubules and motors to create the molecular analog of a network of roads, which will organize droplets of DNA condensates capable of carrying molecular cargo. DNA condensates coupled to motors will flow from one microtubule aster hub to another, with their direction and timing controlled by DNA circuits. In another limit, microtubules will swim through bulk DNA condensates and exhibit strong interactions with boundaries between different types of condensates. Microtubule swimmers will reflect, get trapped, or refract at boundaries, under a mechanical analog of the classical optical index of refraction. DNA condensates having different mechanical indexes of refraction will be used to construct the analog of optical lenses, so that microtubule swimmers can be manipulated like light—collimated, diffracted, focused, and sorted based on properties analogous to wavelength. These two limits define two new architectures, within which multiple new mechanistic principles for self-organization will be discovered and explored. To explore these architectures, the motor-based coupling between DNA condensates and filaments will be controlled in time and space through the use of opto-proteins that create reversible links between DNA condensates and motors upon illumination. For each principle of interest, patterns of light will create virtual experiments by defining patterns of activity where DNA condensates walk along filaments, or filaments swim through condensates, and patterns of inactivity which will serve either as controls, or as boundary conditions vital to create the desired phenomena. This research serves the goals of Basic Energy Sciences Biomolecular Material Program by elucidating the principles by which the emergent, nonequilibrium behavior of collections of DNA condensates, motors, and microtubules can be programmed by environmental light patterns to create complex motion and materials transport. Because DNA condensates can be readily coupled to virtually any high performance nanomaterial, from carbon nanotubes, to metal nanoparticles, to light harvesting systems, this work provides a path to the construction, self-maintenance and reconfiguration of materials relevant to the Department of Energy.

60 APPLIED LIFE SCIENCES↗

Surfactant-like peptide gels are based on cross-β amyloid fibrils

Surfactant-like peptides, in which hydrophilic and hydrophobic residues are encoded within different domains in the peptide sequence, undergo facile self-assembly in aqueous solution to form supramolecular hydrogels. These peptides have been explored extensively as substrates for the creation of functional materials since a wide variety of amphipathic sequences can be prepared from commonly available amino acid precursors. The self-assembly behavior of surfactant-like peptides has been compared to that observed for small molecule amphiphiles in which nanoscale phase separation of the hydrophobic domains drives the self-assembly of supramolecular structures. Here, we investigate the relationship between sequence and supramolecular structure for a pair of bola-amphiphilic peptides, Ac-KLIIIK-NH 2 (L2) and Ac-KIIILK-NH 2 (L5). Despite similar length, composition, and polar sequence pattern, L2 and L5 form morphologically distinct assemblies, nanosheets and nanotubes, respectively. Cryo-EM helical reconstruction was employed to determine the structure of the L5 nanotube at near-atomic resolution. Rather than displaying self-assembly behavior analogous to conventional amphiphiles, the packing arrangement of peptides in the L5 nanotube displayed steric zipper interfaces that resembled those observed in the structures of β-amyloid fibrils. Like amyloids, the supramolecular structures of the L2 and L5 assemblies were sensitive to conservative amino acid substitutions within an otherwise identical amphipathic sequence pattern. This study highlights the need to better understand the relationship between sequence and supramolecular structure to facilitate the development of functional peptide-based materials for biomaterials applications.

Das, Abhinaba [Emory University, Atlanta, GA (Unit↗

Flow studies in close-coupled ventral nozzles for STOVL aircraft

Flow in a generic ventral nozzle system was studied experimentally and analytically with the PARC3D computational fluid dynamics program (a full Navier-Stokes equations solver) in order to evaluate the program's ability to predict system performance and internal flow patterns. A generic model of a tailpipe with a rectangular ventral nozzle, about one-third of full size, was tested with unheated air at steady-state pressure ratios up to 4.0. Measurements showed about 5.5 percent flow-turning loss and reasonable nozzle performance coefficients. The flow turned more than the designed 90 deg, causing an aftward axial component in the total thrust. Flow behavior into and through the ventral duct is discussed and illustrated with paint streak flow visualization photographs. PARC3D graphic images are shown for comparison with the experiment photographs. The program successfully predicted internal flow patterns; it also computed thrust and discharge coefficients within 1 percent of measured values.

Mcardle, Jack G.↗

Traffic Prediction for Uncommunicative Aircraft in Terminal Airspace: Development Framework and Performance Evaluations

This paper presents an air traffic prediction algorithm that takes observations of an aircraft and classifies aircraft type, estimates the aircraft's intent to and method of joining an airport traffic pattern, and predicts the aircaft's future trajectory. To develop algorithms that enable autonomous aircraft to safely insert into un-towered traffic patterns, several challenges need to be addressed. These challenges range from traffic detection to sensor fusion to own-ship trajectory replanning. Critical to a trajectory replanning algorithm is information regarding the future behavior of all traffic aircraft in the operational environment. The presented traffic prediction algorithm generates this information using regular measurements of traffic aircraft position and velocity to classify the aircraft by speed-class, estimate how the aircraft will approach the runway, and construct a predicted trajectory to the runway including future positions and velocities at specific times. The predictions of the presented algorithm are the necessary inputs for any downstream traffic pattern sequencing and own-ship trajectory planning routines. The presented algorithm is benchmarked using approximately 300 randomized traffic trajectories, spanning four vehicle weight classes and eight traffic entry types. While the algorithm can process multiple traffic vehicles in the terminal area, there is no prediction of traffic-on-traffic interaction. Each traffic vehicle is processed separately.

John D McMinn↗

Formation of Ligand Clusters on Multimodal Chromatographic Surfaces

Multimodal chromatography is a powerful tool which uses multiple modes of interaction, such as charge and hydrophobicity, to purify protein-based therapeutics. In this work, we performed molecular dynamics simulations of a series of multimodal cation-exchange ligands immobilized on a hydrophilic self-assembled monolayer surface at the commercially relevant surface density (1 ligand/nm2). We found that ligands that were flexible and terminated in a hydrophobic group had a propensity to aggregate on the surface, while less flexible ligands containing a hydrophobic group closer to the surface did not aggregate. For aggregating ligands, we report this resulted in the formation of a surface pattern that contained relatively large patches of hydrophobicity and charge whose sizes exceeded the length scale of the individual ligands. On the other hand, lowering the surface density to 1 ligand/3 nm 2 reduced or eliminated this aggregation behavior. In addition, the introduction of a flexible linker (corresponding to the commercially available ligand) enhanced cluster formation and allowed aggregation to occur at lower surface densities. Further, the use of flexible linkers enabled hydrophobic groups to collapse to the surface, reducing their accessibility. Finally, we developed an approach for quantifying differences in the observed surface patterns by calculating distributions of the patch size and patch length. This clustering phenomenon is likely to play a key role in governing protein–surface interactions in multimodal chromatography. This new understanding of multimodal surfaces has important implications for developing improved predictive models and designing new classes of multimodal separation materials.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

QUIC-fire: A fast-running simulation tool for prescribed fire planning

Coupled fire-atmospheric modeling tools are increasingly used to understand the complex and dynamic behavior of wildland fires. Multiple research tools linking combustion to fluid flow use Navier-Stokes numerical solutions coupled to a thermodynamic model to understand fire-atmospheric feedbacks, but these computational fluid dynamics approaches require high-performance computing resources. We present a new simulation tool called QUIC-Fire to rapidly solve these feedbacks by coupling the mature 3-D rapid wind solver QUIC-URB to a physics-based cellular automata fire spread model Fire-CA. QUIC-Fire uses 3-D fuels inputs similar to the CFD model FIRETEC, allowing this tool to simulate effects of fuel structure on local winds and fire behavior. Results comparing fire behavior metrics to the computational fluid dynamic model FIRETEC show strong agreement. As a result, QUIC-Fire is the first tool intended to provide an opportunity for prescribed fire planners to compare, evaluate and design burn plans, including complex ignition patterns and coupled fire atmospheric feedbacks.

54 ENVIRONMENTAL SCIENCES↗

Multiaxial ratcheting of 20 carbon steel: Macroscopic experiments and microscopic observations

The multiaxial ratcheting behaviors of polycrystalline 20 ordinary carbon steel were investigated at room temperature. The macroscopic experimental results showed that the studied multiaxial ratcheting depends greatly on the mean stress, stress amplitude and loading path. The axial ratcheting strain increased with the increase of applied mean stress and stress amplitude. Apparent additional hardening was observed in the non-proportionally multiaxial cyclic loading. The multiaxial ratcheting of 20 carbon steel was lower than the corresponding uniaxial one and varies with different loading paths. Dislocation patterns and their evolutions of the multiaxial ratcheting of different loading paths were then investigated using transmission electron microscopy. The obtained images showed that, with the increasing number of loading cycles, the dislocation patterns evolved from dislocation lines and networks to dislocation tangles, walls and cells. After certain cycles, sub-grains were formed because of the re-arrangement of dislocations in the walls of cells and inside the cells since the cross slip of dislocations can be easily activated for the 20 carbon steel, a kind of body-centered cubic metal. The dislocation evolution of the multiaxial ratcheting is much quicker than that of the uniaxial one. With the reference to the uniaxial one of 20 carbon steel, the macroscopic multiaxial ratcheting behaviors can be qualitatively correlated with the microscopic observation of the dislocation patterns and their evolution. - Highlights: • Multiaxial loading hardly changes the cyclic stable feature of 20 carbon steel. • Multiaxial ratcheting of 20 carbon steel depends greatly on the load path. • Dislocation patterns evolve quicker in the multiaxial case. • The stabilized dislocation pattern is sub-grain, rather than the dislocation cell. • Sub-grains formed after certain cycles make the stable ratcheting strain rate large.

36 MATERIALS SCIENCE↗

Nanoscale kinetics and dynamics during Ar + patterning of SiO 2

Broad-beam low-energy ion bombardment can lead to the spontaneous formation of nanoscale surface structures, but the dominant mechanisms driving evolution remain controversial. Using coherent x-ray scattering to examine the classic case of ion-beam rippling of SiO 2 surfaces, we study the relationship between the average kinetics of ripple formation and the underlying fluctuation dynamics. The early stage growth of fluctuations is well fit with a linear theory formalism employing a viscous relaxation term with full wave-number dependence. In this regime, the x-ray photon correlation spectroscopy two-time correlation function shows distinctive behavior with memory stretching back to the beginning of the bombardment. For a given length scale, correlation times do not grow significantly beyond the characteristic time associated with the early-stage ripple growth. In the late stages of patterning, when the average surface structure on a given length scale is no longer evolving, dynamical processes continue on the surface. Nonlinear processes dominate at long length scales, leading to compressed exponential decay of the speckle correlation functions, while at short length scales the dynamics appears to approach a linear behavior consistent with viscous flow relaxation. This behavior is found to be consistent with simulations of a recent nonlinear growth model. In addition, it is shown that the surface ripple velocity, an important parameter of the ion-driven surface evolution, can be measured with coherent x-ray scattering in conjunction with use of an inhomogeneous ion beam. The change in viewpoint exemplified by this study, from a focus on only average surface kinetics to one incorporating the underlying nanoscale dynamics, is rapidly becoming more widely applicable as new and upgraded x-ray sources with higher coherent flux come online.

36 MATERIALS SCIENCE↗

Dimensionality-Dependent Electronic Properties of the Highly Conducting n-Type Polymer, Poly(benzodifurandione)

Poly(benzodifurandione) (n-PBDF) has garnered significant interest as it displays the highest reported n-type electrical conductivity among π-conjugated polymers. Earlier theoretical studies of n-PBDF could not rationalize this high conductivity. Here, we explore the geometric and electronic properties of two-dimensional (2D) and three-dimensional (3D) n-PBDF networks using first-principles calculations and tight-binding models. In 2D networks, a metallic electronic configuration occurs when considering a coplanar geometry with BDF moieties bounded to protons on the same side; however, backbone torsions disrupt the metallic behavior. In contrast, all 3D architectures consistently lead to a metallic nature, which is not impacted by variations in proton positions and stacking patterns. Tight-binding models allowed us to evaluate the respective strengths of intra- and interchain electronic couplings in n-PBDF. Altogether, our investigations provide a comprehensive picture into the electronic properties of n-PBDF and shed light on how they are affected by system dimensionality, proton positions, and stacking patterns.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Effects of Fault Roughness on Coseismic Slip and Earthquake Locations

We report that fault zone structure is well known to exert strong controls on earthquake properties including coseismic slip distribution, rupture propagation direction, and hypocenter location. It has also been well established that the principal slip surface, which accommodates the majority of earthquake displacement, exhibits roughness at all scales following self-affine fractal distributions. Here we explore the relationship between fault roughness and specific earthquake properties including coseismic slip distribution and hypocenter location based on long-term simulations of earthquake catalogs on fractally rough faults. We begin by using the von Kármán autocorrelation function to procedurally generate single faults with different fractal roughness properties, which we place in a homogeneous elastic solid and apply pure right-lateral shear at a constant back slip rate with the earthquake simulator RSQSim. Running the simulations for 10,000 years each, we generate millions of earthquakes including thousands of events with Mw > 6.0, which rupture the surface. We show that the patterns of surface rupture in these large events follow self-affine fractal distributions with consistent fractal dimension related distinctly to the fractal dimension of the fault. In addition, the hypocenters of these large events occur in very specific predictable locations where the longest wavelength structure produces a stress asperity (i.e., restraining bend). The resulting patterns can explain many features observed on real fault systems, including clustered hypocenter locations, spatially variable coseismic slip distributions, and characteristic slip recurrence behavior. Lastly, these results demonstrate a quantitative link between a directly measurable fault property—roughness—and the properties of future earthquakes.

58 GEOSCIENCES↗

Phase-operation for conduction electron by atomic-scale scattering via single point-defect

In order to propose a phase-operation technique for conduction electrons in solid, we have investigated, using scanning tunneling microscopy, an atomic-scale electron-scattering phenomenon on a 2D subband state formed in Si. Particularly, we have noticed a single surface point-defect around which a standing-wave pattern created, and a dispersion of scattering phase-shifts by the defect-potential against electron-energy has been measured. The behavior is well-explained with appropriate scattering parameters: the potential height and radius. This result experimentally proves that the atomic-scale potential scattering via the point defect enables phase-operation for conduction electrons.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗