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At least 1,369 records · Page 76

Measurement of target and double-spin asymmetries for the $\vec e\vec p\to e\pi^+ (n)$ reaction in the nucleon resonance region at low $Q^2$

We report measurements of target- and double-spin asymmetries for the exclusive channel $\vec e\vec p\to e\pi^+ (n)$ in the nucleon resonance region at Jefferson Lab using the CEBAF Large Acceptance Spectrometer (CLAS). These asymmetries were extracted from data obtained using a longitudinally polarized NH$_3$ target and a longitudinally polarized electron beam with energies 1.1, 1.3, 2.0, 2.3 and 3.0 GeV. The new results are consistent with previous CLAS publications but are extended to a low $Q^2$ range from $0.0065$ to $0.35$ (GeV$/c$)$^2$. The $Q^2$ access was made possible by a custom-built Cherenkov detector that allowed the detection of electrons for scattering angles as low as $6^\circ$. These results are compared with the unitary isobar models JANR and MAID, the partial-wave analysis prediction from SAID and the dynamic model DMT. In many kinematic regions our results, in particular results on the target asymmetry, help to constrain the polarization-dependent components of these models.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Quasi-Dynamic Electromagnetic Field Safety Analysis and Mitigation for High-Power Dynamic Wireless Charging of Electric Vehicles

Dynamic wireless charging of electric vehicles (EV) is an emerging charging technology to enable non-contact wireless charging while the vehicle is moving. Compared to stationary wireless charging, in-motion wireless charging involves dynamic processes in which an EV is passing over the charging pads (transmitters). This in motion process makes the dynamic electromagnetic (EM) environment more complicated, and EM safety needs to be ensured under all circumstances. This is due to the fact that the entire vehicle body may be exposed to magnetic fields while the vehicle moves over the energized transmitter. This paper investigates several typical charging scenarios when EVs approach, pass over, and move away from the charging pads. Quasi-dynamic models, which are preliminarily verified by coils’ inductance measurements, are developed to analyze the dynamic process. Based on the quasi-dynamic analysis, shielding solutions are also studied to ensure EM safety for the dynamic wireless charging processes.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Modeling and Dynamic Analysis of Paralleled dc/dc Converters With Master-Slave Current Sharing Control

A simple, application-oriented, transfer function model of paralleled converters employing Master-Slave Current-sharing (MSC) control is developed. Dynamically, the Master converter retains its original design characteristics; all the Slave converters are forced to depart significantly from their original design characteristics into current-controlled current sources. Five distinct loop gains to assess system stability and performance are identified and their physical significance is described. A design methodology for the current share compensator is presented. The effect of this current sharing scheme on 'system output impedance' is analyzed.

Rajagopalan, J.↗

Experimental Validation of FE/BEM Dynamic Strain Model Under Diffuse Acoustic Field Loading

Structural finite element (FE) models naturally output displacement or acceleration response data. However, they can also be used to compute stress, internal forces, and strain response. When coupled with a boundary element model (BEM) of the fluid surrounding the structure, a fully coupled analysis can be performed. Modeling a diffuse acoustic field in the BEM fluid provides an excitation like that found when the structure is placed in a reverberation chamber. Fully coupling the structural FE model to the acoustic BEM model provides a means to predict not only the acceleration response of the panel to diffuse field loading, but also the ability to predict the dynamic stress and strain response. This type of model has been available with current predictive tools, but experimental validation of the prediction of dynamic stress or strain is difficult to find. An aluminum panel was instrumented with accelerometers and strain gages and hung in a reverberation room and subjected to a diffuse acoustic field. This paper presents the comparison of the experimental and predicted results.

Tsoi, W. Ben↗

Overview of Coupon Testing of an IM7/8552 Composite Required to Characterize High-Energy Impact Dynamic Material Models

As part of NASA’s Advanced Composites Project (ACP), a significant research effort was established to develop and mature analysis methods for composite materials particularly applicable to high-energy dynamic impact applications. An overall goal was to develop and advance analysis methods that can be characterized using fundamental coupon level tests. Based on this fundamental characterization, simulations at the higher levels of a building block approach can be purely predictive. The tests described in this report were performed on a unidirectional carbon fiber polymer matrix composite, IM7/8552 tape, as this material system is representative of a modern aerospace grade carbon fiber tape system. These tests were chosen to provide fundamental material characterization data for three representative progressive damage and failure analysis material models available within the LS-DYNA commercial transient dynamic finite element code for use in the simulation of the dynamic and impact response of composite materials. Two of the material models, MAT162 and MAT261, are well established material models within LS-DYNA. The third material model, MAT213, is under active development. Testing consisted primarily of ASTM-type standard tests, and the tests that were performed were consistent with the needs of all three models. Additionally, coupon level tests were performed that can be used to characterize a delamination model (e.g., cohesive zone or tie-break contact). While, the tests described in this report provide fundamental material characterization data for all three of the material models mentioned above, the data is applicable to additional material models not discussed.

Justusson, Brian P.↗

Effects of Deployment Investment on the Growth of the Biofuels Industry

In support of the national goals for biofuel use in the United States, numerous technologies have been developed that convert biomass to biofuels. Some of these biomass to biofuel conversion technology pathways are operating at commercial scales, while others are in earlier stages of development. The advancement of a new pathway toward commercialization involves various types of progress, including yield improvements, process engineering, and financial performance. Actions of private investors and public programs can accelerate the demonstration and deployment of new conversion technology pathways. These investors (both private and public) will pursue a range of pilot, demonstration, and pioneer scale biorefinery investments; the most cost-effective set of investments for advancing the maturity of any given biomass to biofuel conversion technology pathway is unknown. In some cases, whether or not the pathway itself will ultimately be technically and financially successful is also unknown. This report presents results from the Biomass Scenario Model -- a system dynamics model of the biomass to biofuels system -- that estimate effects of investments in biorefineries at different maturity levels and operational scales. The report discusses challenges in estimating effects of such investments and explores the interaction between this deployment investment and a volumetric production incentive. Model results show that investments in demonstration and deployment have a substantial positive effect on the development of the biofuels industry. Results also show that other conditions, such as supportive policies, have major impacts on the effectiveness of such investments.

09 BIOMASS FUELS↗

Machine-learning force-field models for dynamical simulations of metallic magnets

We review recent advances in machine-learning (ML) force-field methods for Landau–Lifshitz–Gilbert simulations of itinerant electron magnets, focusing on their scalability and transferability. Built on the principle of locality, a deep neural-network model is developed to efficiently and accurately predict electron-mediated forces governing spin dynamics. Symmetry-aware descriptors constructed through a group-theoretical approach ensure rigorous incorporation of both lattice and spin-rotation symmetries. The framework is demonstrated using the prototypical s-d exchange model widely employed in spintronics. ML-enabled large-scale simulations reveal novel nonequilibrium phenomena, including anomalous coarsening of tetrahedral spin order on the triangular lattice and the freezing of phase-separation dynamics in lightly hole-doped, strong-coupling square-lattice systems. These results establish ML force-field frameworks as scalable, accurate, and versatile tools for modeling nonequilibrium spin dynamics in itinerant magnets.

Artificial neural networks↗

Modeling the Dynamics of the Middle Atmosphere and Lower Thermosphere Under the Influence of Gravity Waves

Our Numerical Spectral Model (NSM), which extends from the ground up into the thermosphere, is non-linear, time-dependent and has been employed for 2D and 3D applications. The standard version of the NSM incorporates Hines' Doppler Spread Parameterization for small scale gravity waves (GW), but planetary waves generated in the troposphere have also been incorporated. The NSM has been applied to describe: (1) the anomalous seasonal variations of the zonal circulation and temperature in the upper mesosphere, (2) the equatorial oscillations (quasi-biennial and semi-annual oscillations (QBO and SAO)) extending from the stratosphere into the upper mesosphere, (3) the diurnal and semi-diurnal tides, and (4) the planetary waves that are excited in the mesosphere. With the emphasis to provide understanding, we present here results from numerical experiments with the NSM that shed light on the GW processes that are of central importance in the mesosphere and lower thermosphere. These are our conclusions: (1) The large semiannual variations in the diurnal tide (DT), with peak amplitudes observed around equinox, are produced primarily by GW interactions that involve, in part, planetary waves. The DT, like planetary waves, tends to be amplified by GW momentum deposition, which reduces also the vertical wavelength, but variations in eddy viscosity associated with GW interactions are also important. (2) The semidiurnal tide (SDT) and its phase in particular, is strongly influenced by the mean zonal circulation. The SDT, individually, is also amplified by GW. But the DT filters out GW such that the GW interaction effectively reduces the amplitude of the SDT, producing a strong nonlinear interaction between the DT and SDT. (3) Without external time dependent energy or momentum sources, planetary waves (PW) are generated in the model for zonal wavenumbers 1 to 4, which have amplitudes in the mesosphere above 50 km as large as 40 m/s and periods between 50 and 2 days. The waves are generated primarily during solstice conditions, which indicates that the baroclinic instability (associated with the GW induced reversal in the latitudinal temperature gradient) is playing an important role. Numerical experiment show that GW, directly, also greatly amplify the PW. A common feature of the PW generated in summer and winter is that their vertical wavelengths throughout the mesosphere are large, which indicates that the waves are not propagating freely but are generated throughout the region. Another common feature is that the PW propagate preferentially westward in summer and eastward in winter, being launched from the westward and eastward zonal winds that prevail respectively in summer and winter at altitudes below 80 km. (4) Planetary waves generated internally by baroclinic instability and GW interaction produce large amplitude modulations of the DT and SDT. In summary we conclude that GW play major roles in generating and amplifying the dynamical components in the MLT region and, acting principally through wave filtering, produce important non-linear interactions between the components.

Mayr, H. G.↗

Effects of Deployment Investment on the Growth of the Biofuels Industry. 2016 Update

This report updates the 2013 report of the same title. Some text originally published in that report is retained and indicated in gray. In support of the national goals for biofuel use in the United States, numerous technologies have been developed that convert biomass to biofuels. Some of these biomass to biofuel conversion technology pathways are operating at commercial scales, while others are in earlier stages of development. The advancement of a new pathway toward commercialization involves various types of progress, including yield improvements, process engineering, and financial performance. Actions of private investors and public programs can accelerate the demonstration and deployment of new conversion technology pathways. These investors (both private and public) will pursue a range of pilot, demonstration, and pioneer scale biorefinery investments; the most cost-effective set of investments for advancing the maturity of any given biomass to biofuel conversion technology pathway is unknown. In some cases, whether or not the pathway itself will ultimately be technically and financially successful is also unknown. This report presents results from the Biomass Scenario Model--a system dynamics model of the biomass to biofuels system--that estimate effects of investments in biorefineries at different maturity levels and operational scales. The report discusses challenges in estimating effects of such investments and explores the interaction between this deployment investment and a volumetric production incentive. Model results show that investments in demonstration and deployment have a substantial growth impact on the development of the biofuels industry. Results also show that other conditions, such as accompanying incentives, have major impacts on the effectiveness of such investments. Results from the 2013 report are compared to new results. This report does not advocate for or against investments, incentives, or policies, but analyzes simulations of their hypothetical effects.

09 BIOMASS FUELS↗

Modeling and Optimal Design of Absorbent Enhanced Ammonia Synthesis

Synthetic ammonia produced from fossil fuels is essential for agriculture. However, the emissions-intensive nature of the Haber–Bosch process, as well as a depleting supply of these fossil fuels have motivated the production of ammonia using renewable sources of energy. Small-scale, distributed processes may better enable the use of renewables, but also result in a loss of economies of scale, so the high capital cost of the Haber–Bosch process may inhibit this paradigm shift. A process that operates at lower pressure and uses absorption rather than condensation to remove ammonia from unreacted nitrogen and hydrogen has been proposed as an alternative. In this work, a dynamic model of this absorbent-enhanced process is proposed and implemented in gPROMS ModelBuilder. This dynamic model is used to determine optimal designs of this process that minimize the 20-year net present cost at small scales of 100 kg/h to 10,000 kg/h when powered by wind energy. The capital cost of this process scales with a 0.77 capacity exponent, and at production scales below 6075 kg/h, it is less expensive than the conventional Haber–Bosch process.

10 SYNTHETIC FUELS↗

Modeling and Dynamic Analysis of Paralleled of dc/dc Converters with Master-Slave Current Sharing Control

A simple, application-oriented, transfer function model of paralleled converters employing Master-Slave Current-sharing (MSC) control is developed. Dynamically, the Master converter retains its original design characteristics; all the Slave converters are forced to depart significantly from their original design characteristics into current-controlled current sources. Five distinct loop gains to assess system stability and performance are identified and their physical significance is described. A design methodology for the current share compensator is presented. The effect of this current sharing scheme on 'system output impedance' is analyzed.

Rajagopalan, J.↗

An Object Model for a Rocket Engine Numerical Simulator

Rocket Engine Numerical Simulator (RENS) is a packet of software which numerically simulates the behavior of a rocket engine. Different parameters of the components of an engine is the input to these programs. Depending on these given parameters the programs output the behaviors of those components. These behavioral values are then used to guide the design of or to diagnose a model of a rocket engine "built" by a composition of these programs simulating different components of the engine system. In order to use this software package effectively one needs to have a flexible model of a rocket engine. These programs simulating different components then should be plugged into this modular representation. Our project is to develop an object based model of such an engine system. We are following an iterative and incremental approach in developing the model, as is the standard practice in the area of object oriented design and analysis of softwares. This process involves three stages: object modeling to represent the components and sub-components of a rocket engine, dynamic modeling to capture the temporal and behavioral aspects of the system, and functional modeling to represent the transformational aspects. This article reports on the first phase of our activity under a grant (RENS) from the NASA Lewis Research center. We have utilized Rambaugh's object modeling technique and the tool UML for this purpose. The classes of a rocket engine propulsion system are developed and some of them are presented in this report. The next step, developing a dynamic model for RENS, is also touched upon here. In this paper we will also discuss the advantages of using object-based modeling for developing this type of an integrated simulator over other tools like an expert systems shell or a procedural language, e.g., FORTRAN. Attempts have been made in the past to use such techniques.

Mitra, D.↗

Modeling Snow Dynamics and Stable Water Isotopes Across Mountain Landscapes

Abstract A coupled hydrologic and snowpack stable water isotope model assesses controls on isotopic inputs across a mountainous basin. Annually, the most depleted isotope conditions occur in the upper subalpine where snow accumulation is high, and rainfall is low. Snowmelt isotopic evolution over time indicates fractionation processes account for <25% snowmelt enrichment. Meltwater isotopic inputs are largely determined by controls on the amount, phase and isotopic mass of precipitation coincident with the ablation period. Effect of vapor loss from the snowpack on d‐excess in snowmelt is a balance between energy and snow‐availability. It is highest above treeline, and in the grass and aspen‐dominated portions of the upper montane where vegetation shading is low. Deep snowpack in conifer forests limit the influence of vapor loss in the subalpine. Wet years reduce the effects of vapor loss on snowmelt across the basin, except in the lower montane where added snowfall bolsters snow‐limited conditions.

58 GEOSCIENCES↗

A Dynamic Failure Model for Predicting the Impact that a Program Location has on the Program

This paper presents a dynamic technique for predicting the effect that a "location" of a program will have on the program's computational behavior. The technique is based on the three necessary and sufficient conditions for software failure to occur: (1) a fault must be executed, (2) the fault must adversely affect the data state, and (3) the adverse effect in a data state must affect program output. In order to predict the effect that a location of a program will have on the program's computational behavior, the following characteristics of each program location are estimated: (1) the probability that a location of the program is executed, (2) the probability that a location of the program noticeably affects the program state created by the location, and (3) the probability that the data states created by a location affect the program's output. With estimates of these characteristics for each location in a program, we can predict those locations where a fault can more easily remain undetected during testing, as well as predict the degree of testing necessary to be convinced that a fault is not remaining undetected in a particular location.

Voas, Jeffrey↗

Dynamic tooth loads and stressing for high contact ratio spur gears

A time history, closed form solution is presented for a dynamic model of spur gear systems for all practical contact ratios. The analysis determines the dynamic response of the gear system and the associated tooth loads and stressing. The dynamic model assumes the two gears act as a rigid inertia and the teeth act as a variable spring of a dynamic system excited by the meshing action of the teeth. Included in the analysis are the effects of the nonlinearity of the tooth pair stiffness during mesh, the tooth errors, and the tooth profile modifications. Besides reviewing the features, solution, and program of this analysis, preliminary results from applying the analysis are presented, which show that tooth profile modification, system inertia and damping, and system critical speeds can affect the dynamic gear tooth loads and stressing significantly.

Cornell, R. W.↗

Solar Models with Dynamic Screening and Early Mass Loss Tested by Helioseismic, Astrophysical, and Planetary Constraints

The faint young Sun paradox remains an open question. Presented here is one possible solution to this apparent inconsistency, a more massive early Sun. Based on the conditions on early Earth and Mars, a luminosity constraint is set as a function of mass. For this, we examine helioseismic constraints of these alternative mass-losing models. Additionally, we explore a dynamic electron screening correction in an effort to improve helioseismic agreement in the core of the early mass-losing model.

79 ASTRONOMY AND ASTROPHYSICS↗

A Real-Time Big Data Control-Theoretical Framework for Cyber-Physical-Human Systems [Book Chapter]

It is known that cyber-physical-human systems naturally arise from interdependent infrastructure systems and smart connected communities. Such applications require ubiquitous information sensing and processing, intelligent machine-to-machine communication for a seamless coordination, as well as intelligent interactions between humans and machines. This chapter presents a control-theoretical framework to model heterogeneous physical dynamic systems, information and communication, as well as cooperative controls and/or distributed optimization of such interconnected systems. It is shown that efficient analytical and computational algorithms can be modularly designed and hierarchically implemented to operate and optimize cyber-physical-human systems, first to quantify individually the input–output relationship of nonlinear dynamic behaviors of every physical subsystem, then to coordinate locally both cyber-physical interactions of neighboring agents as well as physical-human interactions, and finally to dynamically model and optimize the overall networked system. The hierarchical structure makes the overall optimization and control problem scalable and solvable. Moreover, the three levels integrate individual designs and optimization, distributed cooperative optimization, and decision-making through real-time, data-driven, model-based learning and control. Specifically, one of the contributions of the chapter is to demonstrate how the combination of dissipativity theory and cooperative control serves as a natural framework and promising tools to analyze, optimize, and control such large-scale system. Application to digital grid is investigated as an illustrative example.

97 MATHEMATICS AND COMPUTING↗