This paper evaluates the feasibility of magnetic field energy harvesting (MFEH) near electrified railway tracks, for the purpose of increasing the lifetime of distributed condition monitoring systems. Since MFEH is a novel concept for railway applications, relevant previous work from a power grid context is employed. Using a theoretical model along with simulations, it is estimated that the power output of a solenoid placed near the return current may be sufficient for a monitoring system designed for low-power operation and low-duty-cycle wireless communication. The magnetic induction is estimated to be at least 25 µT at a distance of 0.5 m from the closest rail, and it is argued that an efficient induction energy harvester placed in this magnetic field could potentially increase the lifetime of condition monitoring systems indefinitely.
Magnetic field energy harvesting (MFEH) is a method by which a system can harness an ambient, alternating magnetic field in order to scavenge energy. Presented in this article is a novel application of the concept aimed at the magnetic fields surrounding the rail current in electrified railway. Due to its non-invasive nature, the approach has the potential to be widely deployed as part of low-cost trackside condition monitoring systems in order to increase lifetime and reduce maintenance requirements. In this work, the viability of MFEH in railway is substantiated experimentally-two different configurations are assessed both in a controlled laboratory environment, as well as in situ along Norwegian railway. When placed near an emulated section of railway carrying 200 A in the laboratory, the power output of the system is up to 40.5 mW at 50 Hz and 4.15 mW at 16 2 ⁄3 Hz. In the field, the prototype system harvests 109 mJ from a single freight train passing by, rendering an estimated daily energy output of 1.14 J in a moderately-trafficked location. It is argued that the approach could indeed eliminate the need for battery replacements, and potentially increase the lifetime of an energy-efficient, battery-powered condition monitoring system indefinitely.
Using communicating sequential processes (CSP), this paper presents a model for wireless sensor networks (WSNs) to be used for formal verification of communication reliability in mesh networks. Process models are derived for sensor nodes and communication links, introducing nondeterminism in order to capture the unreliability inherent in wireless communication. It is shown that a guarantee may be issued concerning the CSP model's worst-case performance in terms of packet corruption. This guarantee is substantiated by transformation of the model, employing a series of operations introduced to simplify the network while preserving worst-case performance. The end result is a formal proof of the entire network's worst-case reliability. As long as the nondeterminism of the communication links is modelled with care, the packet corruption rate through the network will be equal to or better than the worst-case performance of its most deterministic path.
A considerable limitation of employing sparse voxels octrees (SVOs) as a model format for ray tracing has been that the octree data structure is inherently static. Due to traversal algorithms' dependence on the strict hierarchical structure of octrees, it has been challenging to achieve real-time performance of SVO model animation in ray tracing since the octree data structure would typically have to be regenerated every frame. Presented in this article is a novel method for animation of models specified on the SVO format. The method distinguishes itself by permitting model transformations such as rotation, translation, and anisotropic scaling, while preserving the hierarchical structure of SVO models so that they may be efficiently traversed. Due to its modest memory footprint and straightforward arithmetic operations, the method is well-suited for implementation in hardware. A software ray tracing implementation of animated SVO models demonstrates real-time performance on current-generation desktop GPUs, and shows that the animation method does not substantially slow down the rendering procedure compared to rendering static SVOs.
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