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At least 1,711 records · Page 95

Relativistic mean-field theories for neutron-star physics based on chiral effective field theory

We describe and implement a procedure for determining the couplings of a relativistic mean-field theory (RMFT) that is optimized for application to neutron star phenomenology. In the standard RMFT approach, the couplings are constrained by comparing the theory's predictions for symmetric matter at saturation density with measured nuclear properties. The theory is then applied to neutron stars which consist of neutron-rich matter at densities ranging up to several times saturation density, which allows for additional astrophysical constraints. In our approach, rather than using the RMFT to extrapolate from symmetric to neutron-rich matter and from finite-sized nuclei to uniform matter, we fit the RMFT to properties of uniform pure neutron matter obtained from chiral effective field theory. Chiral effective field theory incorporates the experimental data for nuclei in the framework of a controlled expansion for nuclear forces valid at nuclear densities and enables us to account for theoretical uncertainties when fitting the RMFT. We construct four simple RMFTs that span the uncertainties provided by chiral effective field theory for neutron matter, and are consistent with current astrophysical constraints on the equation of state. Lastly, our RMFTs can be used to model the properties of neutron-rich matter across the vast range of densities and temperatures encountered in neutron stars and their mergers.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

GridMan: A grid manipulation system

GridMan is an interactive grid manipulation system. It operates on grids to produce new grids which conform to user demands. The input grids are not constrained to come from any particular source. They may be generated by algebraic methods, elliptic methods, hyperbolic methods, parabolic methods, or some combination of methods. The methods are included in the various available structured grid generation codes. These codes perform the basic assembly function for the various elements of the initial grid. For block structured grids, the assembly can be quite complex due to a large number of clock corners, edges, and faces for which various connections and orientations must be properly identified. The grid generation codes are distinguished among themselves by their balance between interactive and automatic actions and by their modest variations in control. The basic form of GridMan provides a much more substantial level of grid control and will take its input from any of the structured grid generation codes. The communication link to the outside codes is a data file which contains the grid or section of grid.

Eiseman, Peter R.↗

The role of sea ice in 2 x CO2 climate model sensitivity. Part 1: The total influence of sea ice thickness and extent

As a first step in investigating the effects of sea ice changes on the climate sensitivity to doubled atmospheric CO2, the authors use a standard simple sea ice model while varying the sea ice distributions and thicknesses in the control run. Thinner ice amplifies the atmospheric temperature senstivity in these experiments by about 15% (to a warming of 4.8 C), because it is easier for the thinner ice to be removed as the climate warms. Thus, its impact on sensitivity is similar to that of greater sea ice extent in the control run, which provides more opportunity for sea ice reduction. An experiment with sea ice not allowed to change between the control and doubled CO2 simulations illustrates that the total effect of sea ice on surface air temperature changes, including cloud cover and water vapor feedbacks that arise in response to sea ice variations, amounts to 37% of the temperature sensitivity to the CO2 doubling, accounting for 1.56 C of the 4.17 C global warming. This is about four times larger than the sea ice impact when no feedbacks are allowed. The different experiments produce a range of results for southern high latitudes with the hydrologic budget over Antarctica implying sea level increases of varying magnitude or no change. These results highlight the importance of properly constraining the sea ice response to climate perturbations, necessitating the use of more realistic sea ice and ocean models.

Rind, D.↗

NASA Tech Briefs, March 2014

Topics include: Data Fusion for Global Estimation of Forest Characteristics From Sparse Lidar Data; Debris and Ice Mapping Analysis Tool - Database; Data Acquisition and Processing Software - DAPS; Metal-Assisted Fabrication of Biodegradable Porous Silicon Nanostructures; Post-Growth, In Situ Adhesion of Carbon Nanotubes to a Substrate for Robust CNT Cathodes; Integrated PEMFC Flow Field Design for Gravity-Independent Passive Water Removal; Thermal Mechanical Preparation of Glass Spheres; Mechanistic-Based Multiaxial-Stochastic-Strength Model for Transversely-Isotropic Brittle Materials; Methods for Mitigating Space Radiation Effects, Fault Detection and Correction, and Processing Sensor Data; Compact Ka-Band Antenna Feed with Double Circularly Polarized Capability; Dual-Leadframe Transient Liquid Phase Bonded Power Semiconductor Module Assembly and Bonding Process; Quad First Stage Processor: A Four-Channel Digitizer and Digital Beam-Forming Processor; Protective Sleeve for a Pyrotechnic Reefing Line Cutter; Metabolic Heat Regenerated Temperature Swing Adsorption; CubeSat Deployable Log Periodic Dipole Array; Re-entry Vehicle Shape for Enhanced Performance; NanoRacks-Scale MEMS Gas Chromatograph System; Variable Camber Aerodynamic Control Surfaces and Active Wing Shaping Control; Spacecraft Line-of-Sight Stabilization Using LWIR Earth Signature; Technique for Finding Retro-Reflectors in Flash LIDAR Imagery; Novel Hemispherical Dynamic Camera for EVAs; 360 deg Visual Detection and Object Tracking on an Autonomous Surface Vehicle; Simulation of Charge Carrier Mobility in Conducting Polymers; Observational Data Formatter Using CMOR for CMIP5; Propellant Loading Physics Model for Fault Detection Isolation and Recovery; Probabilistic Guidance for Swarms of Autonomous Agents; Reducing Drift in Stereo Visual Odometry; Future Air-Traffic Management Concepts Evaluation Tool; Examination and A Priori Analysis of a Direct Numerical Simulation Database for High-Pressure Turbulent Flows; and Resource-Constrained Application of Support Vector Machines to Imagery.

Source record↗

The impact of depth-dependent water content on steady state weathering and eroding systems

Models for weathering and regolith formation are normally built on the assumption of constant rates of water advection in the zone of water-saturated pores, and constant water content of those pores, but it is common that weathering occurs in the water-unsaturated zone where lateral flow occurs. Hence, water content in pores varies with depth. Here we model mineral weathering profiles while accounting for depth-dependent water content. Like previous models, a mineral equilibrates with water over a length ξ that depends on dissolution and advection rates, but a new lengthscale λ is introduced to describe the decrease of water content with depth. Steady states of the regolith thickness can be attained for any finite λ and non-zero velocity v E of erosion at the land surface. The type of mineral depletion profile developed over geological timescales depends on coupling between weathering and erosion: for slow erosion, a completely developed profile (CDP) is observed, in which the mineral-depleted zone at the top of the regolith has thickness of order λ ; as v E increases, there is a transition to an incompletely developed profile (IDP), in which partial mineral depletion at the land surface is constrained to a narrow range of velocities; when v E exceeds the advance rate of weathering under far from equilibrium conditions, the profile transitions to an unstable regime that exposes bedrock. In general, the reaction front (RF) thickness and the velocity where CPD transitions to IDP depend on the interplay of both water infiltration and chemical equilibration over the timescale of water residence in regolith. The RF thickness roughly equals a correlation length χ defined as half the harmonic average of ξ and λ . In cases of limited water infiltration, water-mineral equilibration is achieved within the length λ , so that the RF thickness is controlled by hydrological properties and is independent of dissolution and advection rates. In the opposite endmember, water infiltrates to large depths and the effects of physical and chemical parameters on RF thickness are the same as in previous geochemical models. The relaxation time for reaching a steady state is shown to be ~ χ / v E . We discuss the effects of physical and chemical parameters in CDPs and IDPs in those endmembers and show an application to a CDP in granitic regolith.

54 ENVIRONMENTAL SCIENCES↗

Tuning domain size and crystallinity in isoindigo/PCBM organic solar cells via solution shearing

Despite having achieved the long sought-after performance of 10% power conversion efficiency, high performance organic photovoltaics (OPVs) are still mostly constrained to lab scale devices fabricated by spin coating. Efforts to produce printed OPVs lag considerably behind, and the sensitivity to different fabrication methods highlights the need to develop a comprehensive understanding of the processing-morphology relationship in printing methods. Here we present a systematic experimental investigation of a model low bandgap polymer/fullerene system, poly-isoindigo thienothiophene/PC 61 BM, using a lab-scale analogue to roll-to-roll coating as the fabrication tool in order to understand the impact of processing parameters on morphological evolution. We report that domain size and polymer crystallinity can be tuned by a factor of two by controlling the temperature and coating speed. Lower fabrication temperature simultaneously decreased the phase separation domain size and increased the relative degree of crystallinity in those domains, leading to improved photocurrent. We conclude that domain size in isoindigo/PCBM is dictated by spontaneous phase separation rather than crystal nucleation and growth. Moreover we present a model to describe the temperature dependence of domain size formation in our system, which demonstrates that morphology is not necessarily strictly dependent on the evaporation rate, but rather on the interplay between evaporation and diffusion during the printing process.

14 SOLAR ENERGY↗

Axon-like active signal transmission

Any electrical signal propagating in a metallic conductor loses amplitude due to the natural resistance of the metal. Compensating for such losses presently requires repeatedly breaking the conductor and interposing amplifiers that consume and regenerate the signal. This century-old primitive severely constrains the design and performance of modern interconnect-dense chips. Here we present a fundamentally different primitive based on semi-stable edge of chaos (EOC), a long-theorized but experimentally elusive regime that underlies active (self-amplifying) transmission in biological axons. By electrically accessing the spin crossover in LaCoO 3 , we isolate semi-stable EOC, characterized by small-signal negative resistance and amplification of perturbations. In a metallic line atop a medium biased at EOC, a signal input at one end exits the other end amplified, without passing through a separate amplifying component. While superficially resembling superconductivity, active transmission offers controllably amplified time-varying small-signal propagation at normal temperature and pressure, but requires an electrically energized EOC medium. Operando thermal mapping reveals the mechanism of amplification—bias energy of the EOC medium, instead of fully dissipating as heat, is partly used to amplify signals in the metallic line, thereby enabling spatially continuous active transmission, which could transform the design and performance of complex electronic chips.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Hyper-Differential Sensitivity Analysis of Uncertain Parameters in PDE-Constrained Optimization

Many problems in engineering and sciences require the solution of large scale optimization constrained by partial differential equations (PDEs). Though PDE-constrained optimization is itself challenging, most applications pose additional complexity, namely, uncertain parameters in the PDEs. Uncertainty quantification (UQ) is necessary to characterize, prioritize, and study the influence of these uncertain parameters. Sensitivity analysis, a classical tool in UQ, is frequently used to study the sensitivity of a model to uncertain parameters. In this article, we introduce "hyper-differential sensitivity analysis" which considers the sensitivity of the solution of a PDE-constrained optimization problem to uncertain parameters. Our approach is a goal-oriented analysis which may be viewed as a tool to complement other UQ methods in the service of decision making and robust design. We formally define hyper-differential sensitivity indices and highlight their relationship to the existing optimization and sensitivity analysis literatures. Assuming the presence of low rank structure in the parameter space, computational efficiency is achieved by leveraging a generalized singular value decomposition in conjunction with a randomized solver which converts the computational bottleneck of the algorithm into an embarrassingly parallel loop. Two multi-physics examples, consisting of nonlinear steady state control and transient linear inversion, demonstrate efficient identification of the uncertain parameters which have the greatest influence on the optimal solution.

97 MATHEMATICS AND COMPUTING↗

A synthesis dataset of permafrost-affected soil thermal conditions for Alaska, USA

Recent observations of near-surface soil temperatures over the circumpolar Arctic show accelerated warming of permafrost-affected soils. The availability of a comprehensive near-surface permafrost and active layer dataset is critical to better understanding climate impacts and to constraining permafrost thermal conditions and its spatial distribution in land system models. We compiled a soil temperature dataset from 72 monitoring stations in Alaska using data collected by the U.S. Geological Survey, the National Park Service, and the University of Alaska Fairbanks permafrost monitoring networks. The array of monitoring stations spans a large range of latitudes from 60.9 to 71.3°N and elevations from near sea level to ~1300 m, comprising tundra and boreal forest regions. This dataset consists of monthly ground temperatures at depths up to 1 m, volumetric soil water content, snow depth, and air temperature during 1997–2016. These data have been quality controlled in collection and processing. Meanwhile, we implemented data harmonization evaluation for the processed dataset. The final product (PF-AK, v0.1) is available at the Arctic Data Center (https://doi.org/10.18739/A2KG55).

58 GEOSCIENCES↗

The Aura Mission and Its Application to Climate and Air Quality

NASA's Aura satellite is scheduled to launch in the second quarter of 2004 into a polar orbit. The Aura mission is designed to collect data to address three high priority environmental science questions: (1) Is the ozone layer recovering as expected? (2) What are the sources and processes that control tropospheric pollutants? And (3) what is the quantitative impact of constituents on climate change? Aura will answer these questions by globally measuring a comprehensive set of trace gases and aerosols in the troposphere and stratosphere. Aura data will also have applications for monitoring and predicting climate and air quality parameters. Aura s observations will continue the TOMS ozone trend record and provide an assessment as to whether the Montreal Protocol is achieving its objective. Aura will measure gases and aerosols in the upper troposphere and lower stratosphere that contribute to climate forcing. These data will be of sufficient coverage, vertical resolution, and accuracy to help constrain climate models. In addition, Aura observations of tropospheric ozone and its precursors will have regional as well as intercontinental coverage, which could improve emission inventories. Near real time data will tested for local air quality forecasts in collaboration with the US's Environmental Protection UV-B forecasts from Aura ozone and cloud cover data. An overview of Aura s instruments, data products, validation, and examples of data applications will be presented.

Hilsenrath, Ernest↗

Internal Structure and Mineralogy of Differentiated Asteroids Assuming Chondritic Bulk Composition: The Case of Vesta

Bulk composition (including oxygen content) is a primary control on the internal structure and mineralogy of differentiated asteroids. For example, oxidation state will affect core size, as well as Mg# and pyroxene content of the silicate mantle. The Howardite-Eucrite-Diogenite class of meteorites (HED) provide an interesting test-case of this idea, in particular in light of results of the Dawn mission which provide information on the size, density and differentiation state of Vesta, the parent body of the HED's. In this work we explore plausible bulk compositions of Vesta and use mass-balance and geochemical modelling to predict possible internal structures and crust/mantle compositions and mineralogies. Models are constrained to be consistent with known HED samples, but the approach has the potential to extend predictions to thermodynamically plausible rock types that are not necessarily present in the HED collection. Nine chondritic bulk compositions are considered (CI, CV, CO, CM, H, L, LL, EH, EL). For each, relative proportions and densities of the core, mantle, and crust are quantified. Considering that the basaltic crust has the composition of the primitive eucrite Juvinas and assuming that this crust is in thermodynamic equilibrium with the residual mantle, it is possible to calculate how much iron is in metallic form (in the core) and how much in oxidized form (in the mantle and crust) for a given bulk composition. Of the nine bulk compositions tested, solutions corresponding to CI and LL groups predicted a negative metal fraction and were not considered further. Solutions for enstatite chondrites imply significant oxidation relative to the starting materials and these solutions too are considered unlikely. For the remaining bulk compositions, the relative proportion of crust to bulk silicate is typically in the range 15 to 20% corresponding to crustal thicknesses of 15 to 20 km for a porosity-free Vesta-sized body. The mantle is predicted to be largely dominated by olivine (>85%) for carbonaceous chondrites, but to be a roughly equal mixture of olivine and pyroxene for ordinary chondrite precursors. All bulk compositions have a significant core, but the relative proportions of metal and sulphide can be widely different. Using these data, total core size (metal+ sulphide) and average core densities can be calculated, providing a useful reference frame within which to consider geophysical/gravity data of the Dawn mission.

Toplis, M. J.↗

Constraining Systematics at SBND to Reduce Uncertainties in SBN Oscillation Analyses

The Short Baseline Near Detector (SBND) is a crucial component of the Short Baseline Neutrino (SBN) Program, situated 110 meters from the Booster Neutrino Beam (BNB) target. This 112-ton Liquid Argon Time Projection Chamber (LArTPC) Near Detector is optimally positioned to investigate the potential existence of an additional flavor of neutrino through neutrino oscillation. Due to its proximity to the BNB target, SBND is uniquely positioned to receive a high rate of un-oscillated neutrino events. This setup offers a valuable opportunity to examine exclusive channels, thereby enhancing our understanding of various neutrino interaction modes, aiding in the understanding and mitigation of various sources of uncertainties. By fully utilizing the detector's capabilities, we aim to mitigate significant uncertainties in neutrino oscillation studies, primarily those related to neutrino interactions and flux. Achieving a deeper understanding of these uncertainties and controlling them with near detector data is essential. In this poster I will present an SBND event selection to control these uncertainties for the SBN oscillation analyses.

Yadav, Shweta [Texas U., Arlington]↗

Chelation-directed interface engineering of in-place self-cleaning membranes

Water–energy sustainability will depend upon the rapid development of advanced pressure-driven separation membranes. Although energy-efficient, water-treatment membranes are constrained by ubiquitous fouling, which may be alleviated by engineering self-cleaning membrane interfaces. In this study, a metal-polyphenol network was designed to direct the armorization of catalytic nanofilms (ca. 18 nm) on inert polymeric membranes. The chelation-directed mineralized coating exhibits high polarity, superhydrophilicity, and ultralow adhesion to crude oil, enabling cyclable crude oil-in-water emulsion separation. The in-place flux recovery rate exceeded 99.9%, alleviating the need for traditional ex situ cleaning. The chelation-directed nanoarmored membrane exhibited 48-fold and 6.8-fold figures of merit for in-place self-cleaning regeneration compared to the control membrane and simple hydraulic cleaning, respectively. Precursor interaction mechanisms were identified by density functional theory calculations. Here, chelation-directed armorization offers promise for sustainable applications in catalysis, biomedicine, environmental remediation, and beyond.

42 ENGINEERING↗

Measurement and analysis of critical crack tip processes during fatigue crack growth

The mechanics of fatigue crack growth under constant-amplitudes and variable-amplitude loading were examined. Critical loading histories involving relatively simple overload and overload/underload cycles were studied to provide a basic understanding of the underlying physical processes controlling crack growth. The material used for this study was 7091-T7E69, a powder metallurgy aluminum alloy. Local crack-tip parameters were measured at various times before, during, and after the overloads, these include crack-tip opening loads and displacements, and crack-tip strain fields. The latter were useed, in combination with the materials cyclic and monotonic stress-strain properties, to compute crack-tip residual stresses. The experimental results are also compared with analytical predictions obtained using the FAST-2 computer code. The sensitivity of the analytical model to constant-amplitude fatigue crack growth rate properties and to through-thickness constrain are studied.

Davidson, D. L.↗

A Rover Deployed Ground Penetrating Radar on Mars

Radar is a fundamental tool capable of addressing a variety of geological problems on Mars via collection of data suitable for interpreting variations in surface morphology and reflectivity. Surface-deployed ground penetrating radar (GPR) can help further constrain the geology and structure of the near surface of Mars by directly measuring the range and character of in situ radar properties. In recognition of this potential, a miniaturized, easily modified GPR is being developed for possible deployment on a future Mars rover and will enable definition of radar stratigraphy at high spatial resolution to depths of 10-20 meters. Ongoing development of a Mars impulse GPR with industry partners at Geophysical Survey Systems, Inc., focuses on design and testing of a prototype transducer array (with both high frequency bistatic and low frequency monostatic components) in parallel with fabrication of a low power, mass, and volume control unit. The operational depth of 10-20 meters is geared towards definition of stratigraphy, subsurface blocks, and structure at the decimeter to meter scale that is critical for establishing the geologic setting of the rover. GPR data can also be used to infer the degree of any post-depositional pedogenic alteration or weathering that has subsequently taken place, thereby enabling assessment of pristine versus secondary morphology at the landing site. As is the case for most remote sensing instruments, a GPR may not detect water unambiguously. Nevertheless, any local, near-surface occurrence of liquid water will lead to large, easily detected dielectric contrasts. Moreover, definition of stratigraphy and setting will help in evaluating the history of aqueous activity and where any water might occur and be accessible. Most importantly perhaps, GPR can provide critical context for other rover and orbital instruments/data sets. Hence, GPR deployment along well positioned transects in the vicinity of a lander should enable 3-D mapping of stratigraphy and could serve to guide direct subsurface sampling. Additional information is contained in the original extended abstract.

Grant, J. A.↗

Vegetation controls on surface heat flux partitioning, and land-atmosphere coupling

Here, we provide observational evidence that land-atmosphere coupling is underestimated by a conventional metric defined by the correlation between soil moisture and surface evaporative fraction (latent heat flux normalized by the sum of sensible and latent heat flux). Land-atmosphere coupling is 3 times stronger when using leaf area index as a correlate of evaporative fraction instead of soil moisture, in the Southern Great Plains. The role of vegetation was confirmed using adjacent flux measurement sites having identical atmospheric forcing but different vegetation phenology. Transpiration makes the relationship between evaporative fraction and soil moisture nonlinear and gives the appearance of weak coupling when using linear soil moisture metrics. Regions of substantial coupling extend to semiarid and humid continental climates across the United States, in terms of correlations between vegetation metrics and evaporative fraction. The hydrological cycle is more tightly constrained by the land surface than previously inferred from soil moisture.

58 GEOSCIENCES↗

Parallel derivative-free optimization for simulation-based design of behind-the-meter energy systems

In this work, the integrated design and dispatch of behind-the-meter or distributed resources (e.g. stationary battery storage and solar PV generation) is considered. A simulation-based framework is employed, generating high-fidelity results with closed-loop predictive control at a fine resolution, at the expense of high computational cost (several minutes to a few hours per design point). To address this challenge, parallel derivative-free design methods are considered. Four methods are compared, including state-of-the-art surrogate-based methods (Radial-Basis Functions and Gaussian processes) and sampling strategies, an evolutionary-based method, and a simple sequential grid refinement method. As a case study, two types of design problem with increasing complexity are considered, namely, the design of behind-the-meter resources (three design variables) and the inclusion of grid capacity (four design variables). The second yields a constrained design problem for which violations can only be determined after solving the computationally expensive simulation. For the three-dimensional case, all methods present a good performance, achieving a solution within 1% of the optimum after the first iteration, with the sequential grid refinement exhibiting the fastest convergence and achieving the best final objective value. This indicates that the parallel evaluation of multiple sampling points may be more important than the choice of method for small decision spaces. For the four-dimensional constrained case, the Genetic Algorithm presents the best tradeoff between performance and computational effort, while the rough objective function terrain generated by constraint violation penalties reduces the performance of surrogate-based methods. Contour plots with flat regions indicate flexibility in the optimal design and highlight the importance of characterizing the solution space.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Analog-to-digital converter based on voltage-controlled superconducting devices

The increasing demand for cryogenic electronics in superconducting and quantum computing systems calls for ultra-energy-efficient data conversion architectures that remain functional at deep cryogenic temperatures. Here, in this work, we present the first design of a voltage-controlled superconducting flash analog-to-digital converter (ADC) based on a voltage-controlled quantum-enhanced Josephson junction field-effect transistor (JJFET). Exploiting its strong gate tunability and transistor-like behavior, the JJFET offers a scalable alternative to conventional current-controlled superconducting devices while aligning naturally with CMOS-style design methodologies. Building on our previously developed Verilog-A compact model calibrated to experimental data, we design and simulate a three-bit JJFET-based flash ADC targeted for integration within cryogenic control and readout circuitry in quantum computing. The core comparator block is realized through careful bias current selection and augmented with a three-terminal nanocryotron to precisely define reference voltages. Cascaded JJFET comparators ensure robust voltage gain, cascadability, and logic-level restoration across stages. Simulation results demonstrate accurate quantization behavior with ultra-low power dissipation, underscoring the feasibility of voltage-driven superconducting mixed-signal circuits. This work establishes a critical step toward unifying superconducting logic and data conversion, paving the way for scalable cryogenic architectures in quantum–classical co-processors, low-power artificial intelligence accelerators, and next-generation energy-constrained computing platforms.

Analog-to-digital converter↗