Pattern recognition in probability spaces for the analysis of edge-localized instabilities in tokamak plasmas

06 November 2015 → 18 August 2017
Regional and community funding: Special Research Fund
Research disciplines
  • Natural sciences
    • Applied mathematics in specific fields
    • Geometry
    • Statistics and numerical methods
    • Computer architecture and networks
    • Distributed computing
    • Information sciences
    • Information systems
    • Programming languages
    • Scientific computing
    • Theoretical computer science
    • Visual computing
    • Other information and computing sciences
    • Classical physics
    • Physics of gases, plasmas and electric discharges
geodesic distance nuclear fusion ELM control edge-localized modes (ELMs) pattern recognition probability theory
Project description

Stochasticity of edge-localized instabilities (ELMs) in nuclear fusion plasmas is modelled with specialized probability distributions (PDFs). Pattern recognition methods are developed in geometric PDF spaces to classify various ELM regimes and to characterize the dependence of ELM distributions on plasma conditions. This work contributes to the physical understanding of ELMs and optimization of ELM control and mitigation schemes in ITER.