Design and development of an off-normal warning system for SPARC

Abstract The SPARC tokamak is a compact, high-field, and high-current device that will rely on disruption mitigation and prevention strategies to address the risks associated with its high stored energy densities. In order to implement these strategies, a system will be in place to both predict the onset of disruptive instabilities and inform their avoidance. This paper details the design of an off-normal warning system that accommodates many of the needs that a similar system on SPARC may need for triggering disruption alarms. One of the more novel accommodations is the introduction of a control-oriented metric for optimizing the sensitivity of warning alarms, the ‘damage’ metric, which acts to minimize the accumulated damage to the machine associated with disruptions. Another includes the extension of the points-based stability model (Gerhardt et al 2013 Nucl. Fusion 53 063021) to accommodate ease of use in day-to-day operation, improving both its interpretability and tunability through reduced input-space complexity and flexible point-assignment mappings. The benefits of these designs are demonstrated through the development and testing of alarms for detecting radiative collapses and vertical displacement events on Alcator C-Mod. Their compatibility with triggering the disruption mitigation system based on their distribution of warning times is investigated, and found to be limited by the durations of the events they are designed to detect on C-Mod. These detectors may be applicable to SPARC as well, and extrapolations of their expected performances to a SPARC-like environment are made.

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Publication Details

Journal
Nuclear Fusion
Published
2025-09-16
DOI
https://doi.org/10.1088/1741-4326/ae074e
Primary Topic
Fluid Dynamics Simulations and Interactions
Type
article
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article

Design and development of an off-normal warning system for SPARC

Y. Wei, Cristina Rea, A. Saperstein, Mark D. Boyer et al.
Nuclear Fusion
Fluid Dynamics Simulations and Interactions
article

Design and development of an off-normal warning system for SPARC

Y. Wei, Cristina Rea, A. Saperstein, Mark D. Boyer, R. Sweeney, G. Trevisan
article en

Abstract

Abstract The SPARC tokamak is a compact, high-field, and high-current device that will rely on disruption mitigation and prevention strategies to address the risks associated with its high stored energy densities. In order to implement these strategies, a system will be in place to both predict the onset of disruptive instabilities and inform their avoidance. This paper details the design of an off-normal warning system that accommodates many of the needs that a similar system on SPARC may need for triggering disruption alarms. One of the more novel accommodations is the introduction of a control-oriented metric for optimizing the sensitivity of warning alarms, the ‘damage’ metric, which acts to minimize the accumulated damage to the machine associated with disruptions. Another includes the extension of the points-based stability model (Gerhardt et al 2013 Nucl. Fusion 53 063021) to accommodate ease of use in day-to-day operation, improving both its interpretability and tunability through reduced input-space complexity and flexible point-assignment mappings. The benefits of these designs are demonstrated through the development and testing of alarms for detecting radiative collapses and vertical displacement events on Alcator C-Mod. Their compatibility with triggering the disruption mitigation system based on their distribution of warning times is investigated, and found to be limited by the durations of the events they are designed to detect on C-Mod. These detectors may be applicable to SPARC as well, and extrapolations of their expected performances to a SPARC-like environment are made.

Nuclear FusionVol. 65(11)
Fusion (United States) (US), Plasma Technology (United States) (US), Fusion Academy (US), Massachusetts Institute of Technology (US), Commonwealth Fund (US)
Openalex Percentile: Top 74%
Fluid Dynamics Simulations and Interactions
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