Using a flux-driven simulation to capture marginality in plasma turbulence
On the path towards energy breakeven in nuclear fusion reactors, great amounts of research have also been invested in computational physics to create simulations that allow for the simulation of the plasma conditions within a tokamak; but there is still much more work to be done to create a reduc...
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2024
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sg-ntu-dr.10356-1756842024-05-06T15:36:52Z Using a flux-driven simulation to capture marginality in plasma turbulence Khoo, Le Han Xavier Garbet Zhisong Qu School of Physical and Mathematical Sciences xavier.garbet@ntu.edu.sg, zhisong.qu@ntu.edu.sg Computer and Information Science Physics Plasma Simulation Physics Fusion Nuclear GYSELA ASPIRE-2A Tokamak Turbulent Transport Reduced element model On the path towards energy breakeven in nuclear fusion reactors, great amounts of research have also been invested in computational physics to create simulations that allow for the simulation of the plasma conditions within a tokamak; but there is still much more work to be done to create a reduced element model that can run within reason- able computational resources and timeframes. We will describe one such program - GYSELA, a flux-based global gyrokinetic code. Additionally, we will characterize the difference between its flux-driven model and gradient-driven models, the evolution of turbulent transport barriers in plasma and the ongoing research to synergize both mod- els. We also present our results in GYSELA that describe the near-marginal conditions that allow for turbulent transport barrier formation, demonstrate the formation of E x B staircases and suppression of turbulence. Bachelor's degree 2024-05-03T02:41:11Z 2024-05-03T02:41:11Z 2023 Final Year Project (FYP) Khoo, L. H. (2023). Using a flux-driven simulation to capture marginality in plasma turbulence. Final Year Project (FYP), Nanyang Technological University, Singapore. https://hdl.handle.net/10356/175684 https://hdl.handle.net/10356/175684 en application/pdf Nanyang Technological University |
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Computer and Information Science Physics Plasma Simulation Physics Fusion Nuclear GYSELA ASPIRE-2A Tokamak Turbulent Transport Reduced element model |
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Computer and Information Science Physics Plasma Simulation Physics Fusion Nuclear GYSELA ASPIRE-2A Tokamak Turbulent Transport Reduced element model Khoo, Le Han Using a flux-driven simulation to capture marginality in plasma turbulence |
description |
On the path towards energy breakeven in nuclear fusion reactors, great amounts of
research have also been invested in computational physics to create simulations that
allow for the simulation of the plasma conditions within a tokamak; but there is still much
more work to be done to create a reduced element model that can run within reason-
able computational resources and timeframes. We will describe one such program -
GYSELA, a flux-based global gyrokinetic code. Additionally, we will characterize the
difference between its flux-driven model and gradient-driven models, the evolution of
turbulent transport barriers in plasma and the ongoing research to synergize both mod-
els. We also present our results in GYSELA that describe the near-marginal conditions
that allow for turbulent transport barrier formation, demonstrate the formation of E x
B staircases and suppression of turbulence. |
author2 |
Xavier Garbet |
author_facet |
Xavier Garbet Khoo, Le Han |
format |
Final Year Project |
author |
Khoo, Le Han |
author_sort |
Khoo, Le Han |
title |
Using a flux-driven simulation to capture marginality in plasma turbulence |
title_short |
Using a flux-driven simulation to capture marginality in plasma turbulence |
title_full |
Using a flux-driven simulation to capture marginality in plasma turbulence |
title_fullStr |
Using a flux-driven simulation to capture marginality in plasma turbulence |
title_full_unstemmed |
Using a flux-driven simulation to capture marginality in plasma turbulence |
title_sort |
using a flux-driven simulation to capture marginality in plasma turbulence |
publisher |
Nanyang Technological University |
publishDate |
2024 |
url |
https://hdl.handle.net/10356/175684 |
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1800916263359217664 |