Bayesian optimization of disruption scenarios with fluid-kinetic models
Paper i proceeding, 2023
loads, mechanical stresses and impact of energetic runaway
electron beams. We use a Bayesian optimization framework to
optimize massive material injection of deuterium and neon in an
ITER-like tokamak set up. The optimization is performed using both
fluid and kinetic plasma models. The fluid model allows the
exploration of a large parameter space. Once promising parameter
regions are located, these are studied in higher physics fidelity using
kinetic simulations. The kinetic model predicts more optimistic results
regarding the success of the disruption mitigation.
kinetic
runaway electron
fluid
disruptions
massive material injection
Författare
Ida Ekmark
Chalmers, Fysik, Subatomär, högenergi- och plasmafysik
Istvan Pusztai
Chalmers, Fysik, Subatomär, högenergi- och plasmafysik
M. Hoppe
Kungliga Tekniska Högskolan (KTH)
Patrik Jansson
Chalmers, Data- och informationsteknik, Funktionell programmering
Tünde-Maria Fülöp
Chalmers, Fysik, Subatomär, högenergi- och plasmafysik
49th EPS Conference on Plasma Physics, EPS 2023
978-171389867-2 (ISBN)
Bordeaux, France,
Ämneskategorier
Fusion, plasma och rymdfysik