Robust avoidance of edge localized modes alongside pedestal formation in negative triangularity plasmas
ORAL · Invited
Abstract
High performance plasmas without edge-localized modes (ELMs) are obtained over a wide range of magnetic field, current, pressure, and density in DIII-D plasmas featuring strong negative triangularity (NT) shaping. Detailed magnetohydrodynamic modeling of over 300 NT discharges is consistent with the edge pressure gradient being ultimately limited by high-n ballooning modes, confirming previous predictions [1]. As a result, plasmas with strong enough NT (triangularities δ < δcrit, where δcrit ~ -0.18 on DIII-D) remain completely ELM-free, even in high power diverted operation. The formation of an electron temperature pedestal in NT contributes to edge pressure gradients that exceed typical L-mode levels, enabling these ELM-free plasmas to routinely achieve higher normalized performance (simultaneous access to H98y2 ≳ 1, βN ≳ 2.5 and fGW ≳ 1). Detailed fluctuation data from magnetics and turbulence diagnostics reveal a wealth of complex behavior in the NT edge that is associated with both ELM suppression and performance enhancement. NT plasmas on DIII-D are further compared to other established ELM-suppression strategies, showing that NT compares favorably in terms of access criteria, normalized performance and scrape-off-layer collisionality. Finally, since ELM suppression in NT results directly from geometry-induced changes of the magnetic shear, predictive calculations find that an ELM-free edge is sustained even in burning plasma regimes characteristic of reactor operation. This implies that it may be possible to eliminate critical integration issues raised by ELMs and exhaust power handling without compromising reactor performance by exploiting strong NT shaping in fusion power plant designs.
[1] A.O. NELSON, et. al., Nucl. Fusion 62 096020 (2022)
[1] A.O. NELSON, et. al., Nucl. Fusion 62 096020 (2022)
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Presenters
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Andrew O Nelson
Columbia University
Authors
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Andrew O Nelson
Columbia University