Sand Pile Modeling of Multiseeded HTS Bulk Superconductors: Current Densities Identification by Genetic Algorithms

João Miguel Murta Pina, Pedro Miguel Ribeiro Pereira, Jose Maria Ceballos, Alfredo Alvarez

Research output: Contribution to journalArticle

5 Citations (Scopus)

Abstract

Sand pile model, in conjunction with Bean model, is often applied to describe single grain bulksuperconductors. However, in several applications as electric motors, multiseeded bulks are needed, due to the need to increase samples dimensions. In this paper an extension of sand pile model is presented in order to manage this type of materials. Multiseeded HTS bulk superconductors, produced e.g. by the top-seeded melt growth process, are characterized by intra- and intergrain currents, and these are reflected in the model. However, identifying these currents from flux density measurements is not straightforward, when considering more than one grain. In fact, the number of currents increases with the number of grainsand these have to be identified from the measured field surface. A method to identify these currents based on genetic algorithms is validated with artificial data and then used in real measurements.
Original languageEnglish
Article number8000804
JournalIEEE Transactions on Applied Superconductivity
Volume23
Issue number3
DOIs
Publication statusPublished - 1 Jan 2013

Keywords

  • Genetic algorithms
  • multiseeded superconductor
  • sand pile mode
  • trapped flux

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