Multi-objective shape optimization of radio frequency cavities using an evolutionary algorithm
Marija Kranjcevic, Andreas Adelmann, Peter Arbenz, Alessandro, Citterio, Lukas Stingelin

TL;DR
This paper presents a multi-objective shape optimization approach for RF cavities using an evolutionary algorithm, aiming to improve design criteria such as frequency matching and impedance, demonstrated on the Swiss SLS-2 upgrade.
Contribution
It introduces a parallel evolutionary algorithm framework for multi-objective RF cavity shape optimization, incorporating constraint handling and detailed electromagnetic simulations.
Findings
Computed Pareto fronts for cavity shapes.
Identified cavity designs with improved properties.
Compared optimized shapes with existing cavity design.
Abstract
Radio frequency (RF) cavities are commonly used to accelerate charged particle beams. The shape of the RF cavity determines the resonant electromagnetic fields and frequencies, which need to satisfy a variety of requirements for a stable and efficient acceleration of the beam. For example, the accelerating frequency has to match a given target frequency, the shunt impedance usually has to be maximized, and the interaction of higher order modes with the beam minimized. In this paper we formulate such problems as constrained multi-objective shape optimization problems, use a massively parallel implementation of an evolutionary algorithm to find an approximation of the Pareto front, and employ a penalty method to deal with the constraint on the accelerating frequency. Considering vacuated axisymmetric RF cavities, we parameterize and mesh their cross section and then solve time-harmonic…
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
