Adjoint approach to calculating shape gradients for three-dimensional magnetic confinement equilibria. Part II: Applications
Elizabeth J. Paul, Thomas Antonsen, Jr., Matt Landreman, and W., Anthony Cooper

TL;DR
This paper presents an efficient adjoint method to compute shape gradients for three-dimensional magnetic confinement equilibria, significantly reducing computational costs in stellarator optimization.
Contribution
It extends the adjoint approach to MHD equilibria, enabling rapid calculation of shape derivatives for various figures of merit in stellarator design.
Findings
Adjoint method reduces computation time by about 1000 times compared to direct methods.
Successfully applied to multiple figures of merit including magnetic well and ripple.
Validated results with numerical codes VMEC and ANIMEC, showing high accuracy.
Abstract
The shape gradient is a local sensitivity function that provides the change in a figure of merit associated with a perturbation to the shape of the object. The shape gradient can be used for gradient-based optimization, sensitivity analysis, and tolerance calculations. However, it is generally expensive to compute from finite-difference derivatives for shapes which are described by many parameters, as is the case for stellarator geometry. In an accompanying work (Antonsen et al. 2019), generalized self-adjointness relations are obtained for MHD equilibria. These describe the relation between perturbed equilibria due to changes in the rotational transform or toroidal current profiles, displacements of the plasma boundary, modifications of currents in the vacuum region, or the addition of bulk forces. These are applied to efficiently compute the shape gradient of functions of…
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