Macroscopic trends of neoclassical tearing stability in high-field H-mode tokamak pilot plants

Abstract The neoclassical tearing mode (NTM) stability metric—minimum marginally stable island width <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" overflow="scroll"> <mml:mrow> <mml:msubsup> <mml:mi>w</mml:mi> <mml:mi>m</mml:mi> <mml:mo>∗</mml:mo> </mml:msubsup> </mml:mrow> </mml:math> —was compared across 14651 inductive high-field tokamak pilot plant equilibria. Larger devices with reduced elongation and/or increased minor radius demonstrated an order-of-magnitude increase in <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" overflow="scroll"> <mml:mrow> <mml:msubsup> <mml:mi>w</mml:mi> <mml:mi>m</mml:mi> <mml:mo>∗</mml:mo> </mml:msubsup> </mml:mrow> </mml:math> , primarily due to a reduction in bootstrap drive. This work is part of an ongoing effort to ensure passive NTM-stability in the ARC tokamak, in which the technology to achieve active tearing-suppression with localised electron cyclotron current drive does not yet exist. The equilibrium scenarios in the database were Monte Carlo generated and normalised to the same <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" overflow="scroll"> <mml:mrow> <mml:mo>&gt;</mml:mo> </mml:mrow> </mml:math> 400MW fusion power, minimum pressure scenario at a range of plasma currents, before tearing analysis using the modified Rutherford equation was applied for all resonant poloidal and toroidal m , n modes up to n = 4. Single-helicity toroidal <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" overflow="scroll"> <mml:mrow> <mml:msup> <mml:mi mathvariant="normal">Δ</mml:mi> <mml:mrow> <mml:mi>′</mml:mi> </mml:mrow> </mml:msup> </mml:mrow> </mml:math> calculations in resistive DCON set the minimum marginally stable island width, and a simple modal scaling proportional to <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" overflow="scroll"> <mml:mrow> <mml:mo>−</mml:mo> <mml:msup> <mml:mi>m</mml:mi> <mml:mn>2</mml:mn> </mml:msup> <mml:msup> <mml:mi>n</mml:mi> <mml:mrow> <mml:mo>−</mml:mo> <mml:mn>1</mml:mn> </mml:mrow> </mml:msup> </mml:mrow> </mml:math> was identified for high- m <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" overflow="scroll"> <mml:mrow> <mml:msup> <mml:mi mathvariant="normal">Δ</mml:mi> <mml:mrow> <mml:mi>′</mml:mi> </mml:mrow> </mml:msup> </mml:mrow> </mml:math> values. The dominant correlates of <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" overflow="scroll"> <mml:mrow> <mml:msubsup> <mml:mi>w</mml:mi> <mml:mi>m</mml:mi> <mml:mo>∗</mml:mo> </mml:msubsup> </mml:mrow> </mml:math> and <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" overflow="scroll"> <mml:mrow> <mml:msup> <mml:mi mathvariant="normal">Δ</mml:mi> <mml:mrow> <mml:mi>′</mml:mi> </mml:mrow> </mml:msup> </mml:mrow> </mml:math> across the database were analysed using interpretable machine learning techniques.