Integrating Novel Stellarator Single-Stage Optimization Algorithms to Design the Columbia Stellarator Experiment

TL;DR

This paper presents novel single-stage optimization algorithms for designing the Columbia Stellarator Experiment, enabling the simultaneous optimization of plasma shape and coil configuration within engineering constraints.

Contribution

It introduces and applies new single-stage optimization techniques to stellarator design, improving the integration of plasma and coil optimization for the CSX.

Findings

Optimized plasma geometries meet physics and engineering constraints.

Methods successfully handle increased degrees of freedom.

Configurations achieve desired plasma shapes with minimal coil strain.

Abstract

The Columbia Stellarator eXperiment (CSX), currently being designed at Columbia University, aims to test theoretical predictions related to QA plasma behavior, and to pioneer the construction of an optimized stellarator using three-dimensional, non-insulated high-temperature superconducting (NI-HTS) coils. The magnetic configuration is generated by a combination of two circular planar poloidal field (PF) coils and two 3D-shaped interlinked (IL) coils, with the possibility to add windowpane coils to enhance shaping and experimental flexibility. The PF coils and vacuum vessel are repurposed from the former Columbia Non-Neutral Torus (CNT) experiment, while the IL coils will be custom-wound in-house using NI-HTS tapes. To obtain a plasma shape that meets the physics objectives with a limited number of coils, novel single-stage optimization techniques are employed, optimizing both the plasma and coils concurrently, in particular targeting a tight aspect ratio QA plasma and minimized strain on the HTS tape. Despite the increased complexity due to the expanded degrees of freedom, these methods successfully identify optimized plasma geometries that can be realized by coils meeting engineering specifications. This paper discusses the derivation of the constraints and objectives specific to CSX, and describe how two recently developed single-stage optimization methodologies are applied to the design of CSX. A set of selected configurations for CSX is then described in detail.