Stellarator island divertor shape optimization for reduced peak heat fluxes

TL;DR

This paper introduces an automated algorithm for designing stellarator island divertors that significantly reduces peak heat fluxes while satisfying engineering constraints, using Bayesian optimization and robustness testing.

Contribution

The paper presents a novel automated method for optimizing stellarator island divertor shapes with reduced computational cost and validated robustness across plasma conditions.

Findings

Achieved 95% reduction in computational cost with Bayesian optimization.

Designed divertors meeting heat flux and engineering constraints.

Validated robustness of solutions across different plasma parameters.

Abstract

An automated algorithm to construct island divertors for stellarators is presented and is used to find divertors that meet heat flux requirements determined by engineering and material limits. The algorithm uses just two initial conditions: two starting coordinates on the island separatrix. We leverage the simplicity of the algorithm to explore the divertor parameter space in a fixed magnetic equilibrium. Heat loads are approximated using the field line diffusion model implemented in the FLARE code. Optimal divertor solutions that satisfy engineering requirements are found using a parameter scan and a Bayesian optimization routine. The optimization achieves a 95% reduction in computational cost compared to the parameter scan. The resulting divertors are proven to be robust to varying plasma parameters through simulations with different cross-field heat diffusivities. This work represents a first step towards island divertor optimization for stellarators.