32,079 research outputs found

    A maximum spreading speed for magnetopause reconnection

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    Past observations and numerical modeling find magnetic reconnection to initiate at a localized region and then spread along a current sheet. The rate of spreading has been proposed to be controlled by a number of mechanisms based on the properties within the boundary. At the Earth's magnetopause the spreading speed is also limited by the speed at which a shocked solar wind front can move along the magnetopause boundary. The speed at which a purely north to south rotational discontinuity propagates through the magnetosheath and contacts the magnetopause is measured here using the Block‐Adaptive‐Tree Solar Wind Roe‐Type Upwind Scheme global magnetohydrodynamics model. The propagation speed along the magnetopause is fastest near the nose of the magnetopause and decreases with distance from the subsolar point. The average propagation speed along the dayside magnetopause is 847 km/s. This is significantly larger than observed rates of reconnection spreading at the magnetopause of 30–40 km/s indicating that, for the observed conditions, the speed of front propagation along the magnetopause does not limit or control the spreading rate of reconnection.Published versio

    Scaling Configuration of Energy Harvesting Sensors with Reinforcement Learning

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    With the advent of the Internet of Things (IoT), an increasing number of energy harvesting methods are being used to supplement or supplant battery based sensors. Energy harvesting sensors need to be configured according to the application, hardware, and environmental conditions to maximize their usefulness. As of today, the configuration of sensors is either manual or heuristics based, requiring valuable domain expertise. Reinforcement learning (RL) is a promising approach to automate configuration and efficiently scale IoT deployments, but it is not yet adopted in practice. We propose solutions to bridge this gap: reduce the training phase of RL so that nodes are operational within a short time after deployment and reduce the computational requirements to scale to large deployments. We focus on configuration of the sampling rate of indoor solar panel based energy harvesting sensors. We created a simulator based on 3 months of data collected from 5 sensor nodes subject to different lighting conditions. Our simulation results show that RL can effectively learn energy availability patterns and configure the sampling rate of the sensor nodes to maximize the sensing data while ensuring that energy storage is not depleted. The nodes can be operational within the first day by using our methods. We show that it is possible to reduce the number of RL policies by using a single policy for nodes that share similar lighting conditions.Comment: 7 pages, 5 figure

    Dynamic modeling and adaptive control for space stations

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    Of all large space structural systems, space stations present a unique challenge and requirement to advanced control technology. Their operations require control system stability over an extremely broad range of parameter changes and high level of disturbances. During shuttle docking the system mass may suddenly increase by more than 100% and during station assembly the mass may vary even more drastically. These coupled with the inherent dynamic model uncertainties associated with large space structural systems require highly sophisticated control systems that can grow as the stations evolve and cope with the uncertainties and time-varying elements to maintain the stability and pointing of the space stations. The aspects of space station operational properties are first examined, including configurations, dynamic models, shuttle docking contact dynamics, solar panel interaction, and load reduction to yield a set of system models and conditions. A model reference adaptive control algorithm along with the inner-loop plant augmentation design for controlling the space stations under severe operational conditions of shuttle docking, excessive model parameter errors, and model truncation are then investigated. The instability problem caused by the zero-frequency rigid body modes and a proposed solution using plant augmentation are addressed. Two sets of sufficient conditions which guarantee the globablly asymptotic stability for the space station systems are obtained

    The local dayside reconnection rate for oblique interplanetary magnetic fields

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    We present an analysis of local properties of magnetic reconnection at the dayside magnetopause for various interplanetary magnetic field (IMF) orientations in global magnetospheric simulations. This has heretofore not been practical because it is difficult to locate where reconnection occurs for oblique IMF, but new techniques make this possible. The approach is to identify magnetic separators, the curves separating four regions of differing magnetic topology, which map the reconnection X-line. The electric field parallel to the X-line is the local reconnection rate. We compare results to a simple model of local two-dimensional asymmetric reconnection. To do so, we find the plasma parameters that locally drive reconnection in the magnetosheath and magnetosphere in planes perpendicular to the X-line at a large number of points along the X-line. The global magnetohydrodynamic simulations are from the three-dimensional Block-Adaptive, Tree Solarwind Roe-type Upwind Scheme (BATS-R-US) code with a uniform resistivity, although the techniques described here are extensible to any global magnetospheric simulation model. We find that the predicted local reconnection rates scale well with the measured values for all simulations, being nearly exact for due southward IMF. However, the absolute predictions differ by an undetermined constant of proportionality, whose magnitude increases as the IMF clock angle changes from southward to northward. We also show similar scaling agreement in a simulation with oblique southward IMF and a dipole tilt. The present results will be an important component of a full understanding of the local and global properties of dayside reconnection.Comment: 12 pages, 7 figures, 1 table, Submitted to Journal Geophysical Research Space Physics February 12, 2016; Revised April 28, 201

    Achieving Extreme Resolution in Numerical Cosmology Using Adaptive Mesh Refinement: Resolving Primordial Star Formation

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    As an entry for the 2001 Gordon Bell Award in the "special" category, we describe our 3-d, hybrid, adaptive mesh refinement (AMR) code, Enzo, designed for high-resolution, multiphysics, cosmological structure formation simulations. Our parallel implementation places no limit on the depth or complexity of the adaptive grid hierarchy, allowing us to achieve unprecedented spatial and temporal dynamic range. We report on a simulation of primordial star formation which develops over 8000 subgrids at 34 levels of refinement to achieve a local refinement of a factor of 10^12 in space and time. This allows us to resolve the properties of the first stars which form in the universe assuming standard physics and a standard cosmological model. Achieving extreme resolution requires the use of 128-bit extended precision arithmetic (EPA) to accurately specify the subgrid positions. We describe our EPA AMR implementation on the IBM SP2 Blue Horizon system at the San Diego Supercomputer Center.Comment: 23 pages, 5 figures. Peer reviewed technical paper accepted to the proceedings of Supercomputing 2001. This entry was a Gordon Bell Prize finalist. For more information visit http://www.TomAbel.com/GB
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