6 research outputs found
Preliminary Design of a Mid-Range Superconducting Wireless Power Transfer System for Magnetic Levitation Vehicles:Application to the MagLev-Cobra
This work presents a mid-range wireless power transfer (WPT) system that uses a high-temperature superconducting coil in the transmitter circuit to increase the efficiency of the system. The presented system is foreseen to provide energy to superconducting magnetic levitation vehicles and is intended to be implemented in the Brazilian MagLev-Cobra. The developed concept is based on an Inductive Power Transfer (IPT) system, using magnetic core reactors (MCR) to tune the resonant frequency under load variations, which arise in the charging process of the vehicle. Based on this architecture, the proof of concept was demonstrated in a laboratory-scale system, namely by assessing the performance as a function of the distance between the receiver and the transmitter coils, as well as its misalignment.</p
tLOSS: a collaborative machine learning platform for predicting AC losses in HTS devices
International audienc
A methodology for assessing the impact of the interannual variability of wave energy resource on electrical energy conversion
This paper presents a methodology to assess the wave energy potential and the impact of inter-annual variability of the resource in overall energy production. This methodology was developed in the scope of a running H2020 project named Big-DataOcean, which aims to create a data repository and service marketplace for the maritime sector. The methodology is applied considering data from two different locations in the Portuguese coast for the years of2016 and 2017. Additionally, two wave energy converters are also used to verify the impact of inter-annual variability in the energy production through well-established KPI's.proofpublishe
Validation and Application of Sand Pile Modeling of Multiseeded HTS Bulk Superconductors
This work was supported by national funds through FCT Fundacao para a Ciencia e a Tecnologia, under project PEst-OE/EEI/UI0066/2011Sand pile and Bean models have already been applied to describe single grain HTS bulks. An extension to that approach was used to model multiseed bulks, needed for several practical applications as electric motors or flywheels with superconducting bearings. The use of genetic algorithms was then proposed to determine intra- and intergrain current densities, and application to two and three seeds samples using trapped flux experimental measurements was exemplified. However, this model assumed some simplifications, as equal properties in grain boundaries between neighboring grains. In this paper an extension to this methodology is proposed and evaluated by analyzing measurements performed in plans at different distances from surfaces of samples with three seeds. Discussion of its influence on a practical application is also explored.authorsversionpublishe
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Roadmap on artificial intelligence and big data techniques for superconductivity
This paper presents a roadmap to the application of AI techniques and big data (BD) for different modelling, design, monitoring, manufacturing and operation purposes of different superconducting applications. To help superconductivity researchers, engineers, and manufacturers understand the viability of using AI and BD techniques as future solutions for challenges in superconductivity, a series of short articles are presented to outline some of the potential applications and solutions. These potential futuristic routes and their materials/technologies are considered for a 10–20 yr time-frame