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At least 1,279 records · Page 71

Cytoskeletal mechanics in pressure-overload cardiac hypertrophy

We have shown that the cellular contractile dysfunction characteristic of pressure-overload cardiac hypertrophy results not from an abnormality intrinsic to the myofilament portion of the cardiocyte cytoskeleton but rather from an increased density of the microtubule component of the extramyofilament portion of the cardiocyte cytoskeleton. To determine how, in physical terms, this increased microtubule density mechanically overloads the contractile apparatus at the cellular level, we measured cytoskeletal stiffness and apparent viscosity in isolated cardiocytes via magnetic twisting cytometry, a technique by which magnetically induced force is applied directly to the cytoskeleton through integrin-coupled ferromagnetic beads coated with Arg-Gly-Asp (RGD) peptide. Measurements were made in two groups of cardiocytes from cats with right ventricular (RV) hypertrophy induced by pulmonary artery banding: (1) those from the pressure-overloaded RV and (2) those from the normally loaded same-animal control left ventricle (LV). Cytoskeletal stiffness increased almost twofold, from 8.53 +/- 0.77 dyne/cm2 in the normally loaded LV cardiocytes to 16.46 +/- 1.32 dyne/cm2 in the hypertrophied RV cardiocytes. Cytoskeletal apparent viscosity increased almost fourfold, from 20.97 +/- 1.92 poise in the normally loaded LV cardiocytes to 87.85 +/- 6.95 poise in the hypertrophied RV cardiocytes. In addition to these baseline data showing differing stiffness and, especially, apparent viscosity in the two groups of cardiocytes, microtubule depolymerization by colchicine was found to return both the stiffness and the apparent viscosity of the pressure overload-hypertrophied RV cells fully to normal. Conversely, microtubule hyperpolymerization by taxol increased the stiffness and apparent viscosity values of normally loaded LV cardiocytes to the abnormal values given above for pressure-hypertrophied RV cardiocytes. Thus, increased microtubule density constitutes primarily a viscous load on the cardiocyte contractile apparatus in pressure-overload cardiac hypertrophy.

Non-NASA Center↗

Optical Measurement of Mass Flow of a Two-Phase Fluid

An optoelectronic system utilizes wavelength-dependent scattering of light for measuring the density and mass flow of a two-phase fluid in a pipe. The apparatus was invented for original use in measuring the mass flow of a two-phase cryogenic fluid (e.g., liquid hydrogen containing bubbles of hydrogen gas), but underlying principles of operation can readily be adapted to non-cryogenic two-phase fluids. The system (see figure) includes a laser module, which contains two or more laser diodes, each operating at a different wavelength. The laser module also contains beam splitters that combine the beams at the various wavelengths so as to produce two output beams, each containing all of the wavelengths. One of the multiwavelength output beams is sent, via a multimode fiberoptic cable, to a transmitting optical coupler. The other multiwavelength output beam is sent, via another multimode fiber-optic cable, to a reference detector module, wherein fiber-optic splitters split the light into several multiwavelength beams, each going to a photodiode having a spectral response that is known and that differs from the spectral responses of the other photodiodes. The outputs of these photodiodes are digitized and fed to a processor, which executes an algorithm that utilizes the known spectral responses to convert the photodiode outputs to obtain reference laser-power levels for the various wavelengths. The transmitting optical coupler is mounted in (and sealed to) a hole in the pipe and is oriented at a slant with respect to the axis of the pipe. The transmitting optical coupler contains a collimating lens and a cylindrical lens that form the light emerging from the end of the fiber-optic cable into a fan-shaped beam in a meridional plane of the pipe. Receiving optical couplers similar to the transmitting optical couplers are mounted in the same meridional plane at various longitudinal positions on the opposite side of the pipe, approximately facing the transmitting optical coupler along the same slant. Light collected by each receiving optical coupler is sent, via a multimode fiber-optic cable, to a detector module similar to the reference detector module. The outputs of the photodiodes in each detector module are digitized and processed, similarly to those of the reference detector module, to obtain indications of the amounts of light of each wavelength scattered to the corresponding receiving position. The value for each wavelength at each position is also normalized to the reference laser-power level for that wavelength. From these normalized values, the density and the mass flow rate of the fluid are estimated.

Wiley, John↗

In-medium $\Delta (1232)$ potential, pion production in heavy-ion collisions and the symmetry energy

Using the dcQMD transport model, the isoscalar and isovector in-medium potentials of the Δ (1232) baryon are studied and information regarding their effective strength is obtained from a comparison to experimental pion production data in heavy-ion collisions below 800 MeV/nucleon impact energy. The best description is achieved for an isoscalar potential moderately more attractive than the nucleon optical potential and a rather small isoscalar relative effective mass $m$$^{*}_{Δ}$ ≈ 0.45. For the isovector component only a constraint between the potential’s strength at saturation and the isovector effective mass difference can be extracted, which depends on quantities such as the slope of the symmetry energy and the neutron-proton effective mass difference. These results are incompatible with the usual assumption, in transport models, that the Δ (1232) and nucleon potentials are equal. The density dependence of symmetry energy can be studied using the high transverse momentum tail of pion multiplicity ratio spectra. Results are however correlated with the value of neutron-proton effective mass difference. Furthermore, this region of spectra is shown to be affected by uncertain model ingredients such as the pion potential or in-medium correction to inelastic scattering cross-sections at levels smaller than 10%. Extraction of precise constraints for the density dependence of symmetry energy above saturation will require experimental data for pion production in heavy-ion collisions below 800 MeV/nucleon impact energy and experimental values for the high transverse momentum tail of pion multiplicity ratio spectra accurate to better than 5%.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Yield modeling of acoustic charge transport transversal filters

This paper presents a yield model for acoustic charge transport transversal filters. This model differs from previous IC yield models in that it does not assume that individual failures of the nondestructive sensing taps necessarily cause a device failure. A redundancy in the number of taps included in the design is explained. Poisson statistics are used to describe the tap failures, weighted over a uniform defect density distribution. A representative design example is presented. The minimum number of taps needed to realize the filter is calculated, and tap weights for various numbers of redundant taps are calculated. The critical area for device failure is calculated for each level of redundancy. Yield is predicted for a range of defect densities and redundancies. To verify the model, a Monte Carlo simulation is performed on an equivalent circuit model of the device. The results of the yield model are then compared to the Monte Carlo simulation. Better than 95% agreement was obtained for the Poisson model with redundant taps ranging from 30% to 150% over the minimum.

Kenney, J. S.↗

Grid-responsive hydrogen production: Capital utilization and current density vs. efficiency in variable electricity markets

To achieve low-cost hydrogen production from water electrolyzers, grid tied electrolysis may need to operate dynamically to minimize the cost of supplying energy to the electrolyzer stack and produce hydrogen during low-cost hours and turn off/down during high-cost hours. Operating systems in this way can decrease capital utilization (capacity factor) and electricity costs. This strategy would shift the dominant cost drivers away from electricity (and thus efficiency) to the capital costs of the system, due to the underutilized capital when operating at low-capacity factors. Increasing the operational current density of the system could, in effect, reduce the capital cost of the system while producing hydrogen at a lower efficiency on a per unit energy basis. In the variable electricity cost profiles analyzed in this paper, increasing the current density for liquid alkaline from 0.5 A/cm2 to 1.5 Ac/m2 and proton exchange membrane electrolyzers from 2 A/cm2 to 4 A/cm2 resulted in substantial reductions in the levelized cost of hydrogen. Additionally, as capacity factors and electricity costs decrease, the optimal operating current density of the electrolyzer systems analyzed increases. These findings suggest R&D efforts should focus on increasing the operational current densities, reducing the turn down ratios, and understanding the durability implications of those strategies on low-temperature liquid alkaline and proton exchange membrane electrolyzers.

08 HYDROGEN↗

Heavy ion beam probe for Wendelstein 7-X measurement capabilities as projected through its design

A heavy ion beam probe (HIBP) diagnostic is being developed for studies of plasma equilibrium and turbulence in the optimized Wendelstein 7-X (W7-X) stellarator. Operation of W7-X has experimentally demonstrated that its optimized magnetic field results in improved neoclassical particle confinement and, as a result, turbulence is the predominant cause of energy transport. The HIBP will have the unique ability to provide experimental data needed to complement models of both neoclassical and turbulent transport. It will acquire direct measurements in the W7-X plasma interior of the electric potential (needed for understanding ambipolar particle flux) and fluctuations of electron density and potential (needed for understanding turbulence). The HIBP for W7-X will inject singly charged ion beams with energies of up to 2 MeV and is designed to access the upper cross section of the W7-X plasma. We use trajectory simulations to illustrate the plasma coverage that the diagnostic can achieve in the reference magnetic configurations of W7-X. We calculate beam signal levels, discuss anticipated measurement sensitivity of broadband fluctuations of electron density and plasma potential, and show how they depend on plasma density. We also discuss the diagnostic sensitivity to equilibrium plasma potential.

Instruments & Instrumentation↗

Enabling Airspace Integration for High-Density On-Demand Mobility Operations

Aviation technologies and concepts have reached a level of maturity that may soon enable an era of on-demand mobility (ODM) fueled by quiet, efficient, and largely automated air taxis. However, successfully bringing such a system to fruition will require introducing orders of magnitude more aircraft to a given airspace volume than can be accommodated by the traditional air traffic control system, among other important technical challenges. The airspace integration problem is further compounded by requirements to set aside appropriate ground infrastructure for take-off and landing areas and ensuring these new aircraft types and their operations do not burden traditional airspace users and air traffic control. This airspace integration challenge may be significantly reduced by extending the concepts and technologies developed to manage small unmanned aircraft systems (UAS) at low altitudethe UAS traffic management (UTM) systemto higher altitudes and new aircraft types, or by equipping ODM aircraft with advanced sensors, algorithms, and interfaces. The precedent of operational freedom inherent in visual flight rules and the technologies developed for large UAS and commercial aircraft automation will contribute to the evolution of an ODM system enabled by UTM. This paper describes the set of air traffic services, normally provided by the traditional air traffic system, that an ODM system would implement to achieve the high densities needed for ODMs economic viability. Finally, the paper proposes a framework for integrating, evaluating, and deploying low-, medium-, and high-density ODM concepts that build on each other to ensure operational and economic feasibility at every step.

Mueller, Eric↗

Enabling Airspace Integration for High-Density On-Demand Mobility Operations

Aviation technologies and concepts have reached a level of maturity that may soon enable an era of on-demand mobility (ODM) fueled by quiet, efficient, and largely automated air taxis. However, successfully bringing such a system to fruition will require introducing orders of magnitude more aircraft to a given airspace volume than can be accommodated by the traditional air traffic control system, among other important technical challenges. The airspace integration problem is further compounded by requirements to set aside appropriate ground infrastructure for take-off and landing areas and ensuring these new aircraft types and their operations do not burden traditional airspace users and air traffic control. This airspace integration challenge may be significantly reduced by extending the concepts and technologies developed to manage small unmanned aircraft systems (UAS) at low altitude - the UAS traffic management (UTM) system - to higher altitudes and new aircraft types, or by equipping ODM aircraft with advanced sensors, algorithms, and interfaces. The precedent of operational freedom inherent in visual flight rules and the technologies developed for large UAS and commercial aircraft automation will contribute to the evolution of an ODM system enabled by UTM. This paper describes the set of air traffic services, normally provided by the traditional air traffic system, that an ODM system would implement to achieve the high densities needed for ODM's economic viability. Finally, the paper proposes a framework for integrating, evaluating, and deploying low-, medium-, and high-density ODM concepts that build on each other to ensure operational and economic feasibility at every step.

Mueller, Eric↗

Accelerating multilevel Markov Chain Monte Carlo using machine learning models

Here, this work presents an efficient approach for accelerating multilevel Markov Chain Monte Carlo (MCMC) sampling for large-scale problems using low-fidelity machine learning models. While conventional techniques for large-scale Bayesian inference often substitute computationally expensive high-fidelity models with machine learning models, thereby introducing approximation errors, our approach offers a computationally efficient alternative by augmenting high-fidelity models with low-fidelity ones within a hierarchical framework. The multilevel approach utilizes the low-fidelity machine learning model (MLM) for inexpensive evaluation of proposed samples thereby improving the acceptance of samples by the high-fidelity model. The hierarchy in our multilevel algorithm is derived from geometric multigrid hierarchy. We utilize an MLM to accelerate the coarse level sampling. Training machine learning model for the coarsest level significantly reduces the computational cost associated with generating training data and training the model. We present an MCMC algorithm to accelerate the coarsest level sampling using MLM and account for the approximation error introduced. We provide theoretical proofs of detailed balance and demonstrate that our multilevel approach constitutes a consistent MCMC algorithm. Additionally, we derive the expression for cost reduction due to machine learning model to facilitate cost analysis of the hierarchical sampling algorithm. Our technique is demonstrated on a standard benchmark inference problem in groundwater flow, where we estimate the probability density of a quantity of interest using a four-level MCMC algorithm. Our proposed algorithm accelerates multilevel sampling by a factor of two while achieving similar accuracy compared to sampling using the standard multilevel algorithm.

97 MATHEMATICS AND COMPUTING↗

Development of a machine learning model for polyethylene pyrolysis using a detailed reaction mechanism

Waste plastics have recently received significant attention as the issue of waste generation continues to increase. Thermal conversion processes, such as pyrolysis and gasification, are attractive potential technologies for utilizing waste plastics and reducing overall waste generation. Efficient utilization of plastics requires a detailed understanding of the conversion process such as pyrolysis and gasification. However, a mechanistic understanding of these processes lead to large and complex kinetic schemes that are not suited for large-scale and long-time simulation methods. Currently, most modeling approaches for pyrolysis and gasification rely on globally lumped, simplified kinetic schemes that provide results that are classified by their product type and not individual species, which limit the level of fidelity achieved via modeling. A machine learning (ML) model has been developed for the primary reactions of high-density polyethylene (HDPE) in an attempt to increase computational efficiency while still maintaining a high level of detail and accuracy. The ML model is trained on a detailed reaction mechanism containing 42 total species and 737 chemical reactions. A DeepONet branch and trunk architecture was adopted to train the model using time-steps relevant to computational fluid dynamics simulations. The ML used physics-informed loss functions to ensure mass conservation. The surrogate model has been deployed in simple MFiX CFD simulations, single particle and an experimental drop tube reactor, and has shown promising performance compared to the original scheme.

Houston, Ross↗

Creating a Multifunctional Composite Stator Slot Material System to Enable High Power Density Electric Machines for Electrified Aircraft Applications

Increasing the power density and efficiency of electric machines (motors and generators) is integral to bringing Electrified Aircraft (EA) to commercial realization. However, power density and efficiency are not qualities that can be developed independently. At the heart of any electric machine are the conductors (usually copper) that carry current and generate magnetic fields. Increased power density means increased current density and increased joule heating in a smaller volume. To increase efficiency at the wire level means minimizing electrical resistance and hence power lost to joule heating. There are fundamental challenges with concomitantly increasing both power density and efficiency since the copper resistivity is very temperature sensitive at common electric machine operating conditions. Simple calculations of the linear increase in resistivity of copper as a function of temperature, reveals that a one degree Celsius increase in temperature results in a 0.39% decrease in efficiency. Conversely, a 20 degree Celsius decrease in copper temperature produces a 7.8% increase in efficiency. Therefore, improved thermal management concepts for electric machine building blocks such as stator winding are a priority for improving efficiency and power density. This paper proposing changing the view of component materials in the stator slots from individual components with singular functionality to a composite system where the components take on a multifunctional roles. In the composite framework, achievable material development goals are defined that together have maximum system impact on the thermal environment inside of high power density electric machines for aerospace applications.

thermal management↗

Accumulate Repeat Accumulate Coded Modulation

In this paper we propose an innovative coded modulation scheme called 'Accumulate Repeat Accumulate Coded Modulation' (ARA coded modulation). This class of codes can be viewed as serial turbo-like codes, or as a subclass of Low Density Parity Check (LDPC) codes that are combined with high level modulation. Thus at the decoder belief propagation can be used for iterative decoding of ARA coded modulation on a graph, provided a demapper transforms the received in-phase and quadrature samples to reliability of the bits.

coded modulation↗

Sodium-sulfur batteries for spacecraft energy storage

Power levels for future space missions will be much higher than are presently attainable using nickel-cadmium and nickel-hydrogen batteries. Development of a high energy density rechargeable battery is essential in being able to provide these higher power levels without tremendous weight penalties. Studies conducted by both the Air Force and private industry have identified the sodium-sulfur battery as the best candidate for a next generation battery system. The advantages of the sodium-sulfur battery over the nickel-cadmium battery are discussed.

Dueber, R. E.↗

Dependence of divertor turbulence on plasma density and current in TCV

To reliably predict the distribution of heat and particle fluxes at the target plates of tokamaks, a comprehensive understanding of turbulence throughout the entire Scrape-Off-Layer (SOL) is imperative. This study examines divertor turbulence systematically across a broad parameter range on the TCV tokamak, including variations in magnetic field direction, plasma current I p ∈ [140,320] kA, edge safety factor q 95 ∈ [2.6,4.7] and Greenwald fraction f G ∈ [0.18,0.6]. The TCV X-point Gas Puff Imaging (GPI) system is used to measure 2D filament properties in the inner and outer divertor region. The fluctuation levels in the divertor are found to strongly increase with density (to 80% over most of the SOL) while remaining insensitive to I p . The previously identified divertor-localized filaments (DLF), located on the bad curvature side of the outer divertor leg, are found to be a common feature on TCV, while no filaments are observed in the PFR. DLFs are present over most of the parameter space and in both field directions. However, they are absent, or appear only closer to the target, for sufficiently large Λ div ≳ 10 or q 95 ≳ 3.7. Across both I p and f G scans, some clear trends with Λ div are found for divertor filament sizes and velocities, and with target fall-off lengths of density and heat flux profiles at the outer target. This study provides important experimental insights to turbulent transport in the divertor also for comparison with self-consistent, turbulence simulations and extrapolation to future reactor conditions.

cross-field transport↗

Rapid recovery of invasive wild pig (Sus scrofa) populations following density reduction

Abstract Trapping is an effective strategy for control of invasive wild pig (Sus scrofa), but eradication of populations via trapping alone typically is impractical throughout much of the species’ introduced range. Consequently, recovery of wild pig populations to pre-trapping levels following control is a major impediment to success of long-term control. In this study, we conducted camera-trap surveys to monitor recovery of two wild pig populations immediately following density reductions achieved via trapping on two sites on the Savannah River Site, SC. We used spatial capture-recapture models to estimate wild pig density during seven 3 week periods spanning 12 months to: (1) determine the time required for populations to recover to pre-trapping levels; and (2) evaluate trends in population growth, density, and distribution during recovery. Recovery of both wild pig populations started immediately after trapping ceased, with populations reaching pre-trapping levels in 3 and 5 months. Threeweek population growth rates for each wild pig population during recovery averaged 1.28 (range = 1.11–1.39 on site 1) and 1.24 (range = 0.64–1.92 on site 2), which corresponded to a 345% and 132% increase in abundance (an increase of 141 and 126 individual wild pigs on site 1 and 2, respectively) of each population by the last survey period. Rapid recovery and growth beyond pre-trapping levels of wild pig populations likely were driven by residual wild pigs not removed by trapping and compensatory reproduction and immigration. Our study is one of the first to provide information on how quickly wild pig populations can recover following overall density reductions of 54–68% and indicates practitioners should be prepared to reinitiate trapping efforts in as little as 3 months to prevent recovery of wild pig populations following control.

Biodiversity & Conservation↗

Datasets for Custom-trained Machine-learning Interatomic Potentials: Nitric Acid Aqueous Solution

This dataset was generated using an iterative active learning strategy with the ArcaNN software package (https://github.com/arcann-chem/arcann_training) to train machine-learning interatomic potentials (MLIPs) for aqueous nitric acid. Each active-learning cycle consisted of three stages: (1) training, (2) exploration, and (3) labeling. The initial training set comprised approximately 800 randomly selected configurations from a previous study by Lewis et al. (https://doi.org/10.1021/jp205510q), which investigated nitric acid solutions at 2, 3, 4, and 5 mol/L. For all configurations, single-point calculations of atomic forces and total energies were performed at the quantum density functional theory BLYP-D2 and PBE-D3 levels of theory using the CP2K Quickstep module. Valence electrons were treated explicitly, while core electrons on all atoms were represented by norm-conserving Goedecker–Teter–Hutter (GTH) pseudopotentials. Long-range dispersion interactions were accounted for using Grimme dispersion corrections. Wave functions were expanded in a mixed Gaussian-and-plane-wave scheme using TZV2P-MOLOPT basis sets for all elements and an 800 Ry auxiliary plane-wave cutoff for the electron density. Self-consistent field convergence was accelerated using orbital transformation and Direct Inversion in the Iterative Subspace, with a convergence threshold of 10^{-6}. All single-point calculations were carried out in periodic orthorhombic cells whose dimensions match those of the molecular configurations sampled from earlier trajectories. The CELL_REF keyword in CP2K was used to define a fixed reference cell, ensuring consistency in the reference data used for MLIP training, particularly when cell fluctuations are present in NpT simulations. The resulting high-fidelity energies and forces constitute the ground-truth labels used to train the MLIPs contained in this dataset.

Dinpajooh, Mohammadhasan [Pacific Northwest Nation↗

The circumstellar nature of the metallic features in a hot DA white dwarf

A new co-added IUE echelle spectrum of the bright DA white dwarf CD -38 deg 10980, together with a newly determined radial velocity for this star, indicate that the sharp lined Si and C absorption features seen in the UV are clearly circumstellar in origin. Absorption in both excited and ground state transitions occurs at a velocity displaced by -12.1 +/- 2.0 km.s with respect to the photospheric velocity. Weak features due to the Si IV doublet are seen at a velocity intermediate between that of the circumstellar features and the photosphere. First time estimates of column densities for excited and ground states of C II, Si II, and Si III are derived. These quantities are used with electron density estimates derived from these species to determine the location and physical conditions of the circumstellar gas in the vicinity of CD -38 deg 10980. If collisional excitation alone is responsible for the excited levels of Si III observed in CD -38 deg 10980, then electron densities in the circumstellar gas must exceed 10(exp 9)/cu cm. Substantially lower electron densities are possible if the circumstellar gas is located near enough to the star so that photoexcitation is the dominant process responsible for the excited lines seen in the UV. Strong limits are placed on the photospheric abundance of Si and C in the star itself. These limits are in sharp contrast to the theoretical predictions of radiative levitation in which Si, but not C, is expected in the photosphere of a white dwarf such as CD -38 deg 10980. The interstellar line of sight to CD -38 deg 10980 is also investigated.

Holberg, J. B.↗

CHARGED POINT DEFECTS AND DEFECT COMPLEXES IN PHOSPHORENE AND STRUCTURAL PREDICTION OF TAU-11, A DENSITY FUNCTIONAL THEORY APPROACH

With the advent of powerful computers, first principle calculations have become a robust and reliable tool to complement experiments in the study of materials. First principle calculations such as density functional theory can be used to guide experiments to save time and effort when it comes to new and advanced materials discovery. Study of charge defects in materials and crystal structure prediction are such areas in which density functional theory calculations facilitate the prediction of defect formation energy, charge transition levels and elemental site occupations. Experimentally, studying charge defects requires inferring results from various techniques. Likewise, determining site occupancies for similar elements using experimental techniques is challenging and sometimes impossible. In this work, we study the charged intrinsic and extrinsic defects and defect complexes in phosphorene and determine the site occupancies of Al, Fe and Si in the τ11 phase using density functional theory. In the defect work, we calculate the defect formation energy, charge transition level, binding energies and Stokes shift for vacancy, dopant substitution and dopant-vacancy defect complexes in phosphorene. We found that vacancy defect in phosphorene becomes negatively charged in n-type doping and may passivate the dopants and reduce carrier concentration and mobility. For non-metal dopants in phosphorene, we predict that O, S and Si prefer to form dopant-vacancy complexes removing the vacancy defect states from the band gap. Mn dopant-vacancy defect complex exhibits possibility of switching between two magnetic spin states. Lastly, using density functional theory, we complement the results from neutron powder diffraction to determine the site occupancies of Al and Si in τ11 phase which was used to determine the alloying element to develop a high temperature and low density alloy.

36 MATERIALS SCIENCE↗