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Results for “topological gradient”

Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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95 records · Page 6
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

A cryogenically cooled 200 kV DC photoemission electron gun for ultralow emittance photocathodes

Novel photocathode materials like ordered surfaces of single crystal metals, epitaxially grown high quantum efficiency thin films, and topologically non-trivial materials with dirac cones show great promise for generating brighter electron beams for various accelerator and ultrafast electron scattering applications. Despite several materials being identified as brighter photocathodes, none of them have been tested in electron guns to extract electron beams due to technical and logistical challenges. In this paper, we present the design and commissioning of a cryocooled 200 kV DC electron gun that is capable of testing a wide variety of novel photocathode materials over a broad range of temperatures from 298 to 35 K for bright electron beam generation. This gun is designed to enable easy transfer of the photocathode to various standard ultra-high-vacuum surface diagnostics and preparation techniques, allowing a full characterization of the dependence of beam brightness on the photocathode material and surface properties. We demonstrate the development of such a high-voltage, high-gradient gun using materials and equipment that are easily available in any standard university lab, making the development of such 200 kV electron guns more accessible.

Instruments & Instrumentation↗
DOE OSTI2023

An adaptive sampling augmented Lagrangian method for stochastic optimization with deterministic constraints

The primary goal of this paper is to provide an efficient solution algorithm based on the augmented Lagrangian framework for optimization problems with a stochastic objective function and deterministic constraints. Our main contribution is combining the augmented Lagrangian framework with adaptive sampling, resulting in an efficient optimization methodology validated with practical examples. To achieve the presented efficiency, here we consider inexact solutions for the augmented Lagrangian subproblems, and through an adaptive sampling mechanism, we control the variance in the gradient estimates. Furthermore, we analyze the theoretical performance of the proposed scheme by showing equivalence to a gradient descent algorithm on a Moreau envelope function, and we prove sublinear convergence for convex objectives and linear convergence for strongly convex objectives with affine equality constraints. The worst-case sample complexity of the resulting algorithm, for an arbitrary choice of penalty parameter in the augmented Lagrangian function, is $\mathscr{O}$(ϵ -3-δ ) , where ϵ > 0 is the expected error of the solution and δ > 0 is a user-defined parameter. If the penalty parameter is chosen to be $\mathscr{O}$(ϵ -1 ), we demonstrate that the result can be improved to $\mathscr{O}$(ϵ -2 ) , which is competitive with the other methods employed in the literature. Moreover, if the objective function is strongly convex with affine equality constraints, we obtain $\mathscr{O}$(ϵ -1 log(1/ϵ)) complexity. Finally, we empirically verify the performance of our adaptive sampling augmented Lagrangian framework in machine learning optimization and engineering design problems, including topology optimization of a heat sink with environmental uncertainty.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2022

A shift from inorganic to organic nitrogen-dominance shapes soil microbiome composition and co-occurrence networks

Soil microbiomes are characterized by their composition and networks, which are linked to soil nitrogen (N) availability. In nature, inorganic N dominates at one end and organic N dominates at the other end along soil N gradients; however, little is known about how this shift influences soil microbiome composition and co-occurrence networks, as well as their controls. To this end, we conducted an experiment with the host plant Solidago canadensis , which was subject to three N regimes: inorganic N-dominated, co-dominated by inorganic and organic N (CIO), and organic N-dominated. Organic N dominance exhibited stronger effects on the composition and co-occurrence networks of soil microbiomes than inorganic N dominance. The predominant control was plant traits for bacterial and fungal richness, and soil pH for keystone species. Relative to the CIO regime, inorganic N dominance did not affect fungal richness and increased keystone species; organic N dominance decreased fungal richness and keystone species. Pathogenic fungi and arbuscular mycorrhizal fungi were suppressed by organic N dominance but not by inorganic N dominance. These findings suggest that the shift from soil inorganic N-dominance to soil organic N-dominance could strongly shape soil microbiome composition and co-occurrence networks by altering species diversity and topological properties.

Xin, Yue↗
DOE OSTI2022

Exploring the Basic Physical Mechanisms of Cathode- and Anode-Initiated High-Voltage Surface Flashover

Surface flashover in vacuum imposes a substantial physical limit on modern, large-scale pulsed power. One of the ramifications is a minimum size requirement for new machines, which in itself becomes a hard barrier to the modernization and improvement of existing infrastructure. Pulsed power topologies require the physical mechanisms of both anode- and cathode-initiated flashover to be considered. Originally, the geometrical implications of field emission at the cathode triple junction (CTJ) motivated the usage of configurations that avoid electrons impinging on the insulating material. This will largely suppress the cathode-initiated flashover, which is best described by the secondary electron avalanche mechanism, gas desorption, and final breakdown in the desorbed gas. It depends on the cascade growth of a conducting plasma along the length of the insulator from the cathode. Mitigating the cathode-initiated flashover typically comes at the cost of a significant field enhancement at the anode triple junction (ATJ). In a typical implementation, the anode field may be three times higher than the cathode field for a given voltage, making the corresponding anode-initiated flashover much more common than otherwise. In the case of pulsed, anode-initiated flashover, experimental evidence suggests that charge is directly extracted from the insulator resulting in the insulator taking on a net positive charge advancing the anode potential. Furthermore, along with accompanying gas desorption from the surface, the potential will then propagate from the anode toward the cathode until the effective length of the gap is sufficiently reduced to support flashover. The underlying physical mechanisms of cathode- and anode-directed flashover are discussed in light of previously gathered experimental data and recent experiments with pulsed, high-gradient, anode-initiated flashover.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2025

Differentiable lagrangian shock hydrodynamics with application to stable shock acceleration of density interfaces

We develop a gradient based optimization approach for the equations of compressible, Lagrangian hydrodynamics and demonstrate how it can be employed to automatically uncover strategies to control hydrodynamic instabilities arising from shock acceleration of density interfaces. Strategies for controlling the Richtmyer-Meshkov instability (RMI) are of great benefit for inertial confinement fusion (ICF) where shock interactions with many small imperfections in the density interface lead to instabilities which rapidly grow over time. These instabilities lead to mixing which, in the case of laser driven ICF, quenches the runaway fusion process ruining the potential for positive energy return. Here, we demonstrate that control of these instabilities can be achieved by optimization of initial conditions with ( > 100) parameters. Optimizing over a large parameter space like this is not possible with gradient-free optimization strategies. This requires computation of the gradient of the outputs of a numerical solution to the equations of Lagrangian hydrodynamics with respect to the inputs. We show that the efficient computation of these gradients is made possible via a judicious application of (i) adjoint methods, the exact formal representation of sensitivities involving partial differential equations, and (ii) automatic differentiation (AD), the algorithmic calculation of derivatives of functions. Careful regularization of multiple operators including artificial viscosity and timestep control is required. We perform design optimization of > 100 parameter energy field driving the Richtmyer Meshkov instability showing significant suppression while simultaneously enhancing the acceleration of the interface relative to a nominal baseline case.

Hydrophysics↗