2008
DOI: 10.1016/j.jcp.2007.09.029
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Shape determination for deformed electromagnetic cavities

Abstract: The measured physical parameters of a superconducting cavity differ from those of the designed ideal cavity. This is due to shape deviations caused by both loose machine tolerances during fabrication and by the tuning process for the accelerating mode. We present a shape determination algorithm to solve for the unknown deviations from the ideal cavity using experimentally measured cavity data. The objective is to match the results of the deformed cavity model to experimental data through least-squares minimiza… Show more

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Cited by 21 publications
(50 citation statements)
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“…Shape optimization studies have been performed with adjoint gradient information (inverse eigenvalue problems) (Akcelik et al, 2005(Akcelik et al, , 2008b. Because adjoint variables enable gradient calculation at a given design point regardless of the number of design variables, achieving a near-optimal shape in a reasonable turnaround time has become feasible (Lee, 2010;Choi et al, 2008;Xiao et al, 2011).…”
Section: Particle Accelerator Designmentioning
confidence: 99%
“…Shape optimization studies have been performed with adjoint gradient information (inverse eigenvalue problems) (Akcelik et al, 2005(Akcelik et al, , 2008b. Because adjoint variables enable gradient calculation at a given design point regardless of the number of design variables, achieving a near-optimal shape in a reasonable turnaround time has become feasible (Lee, 2010;Choi et al, 2008;Xiao et al, 2011).…”
Section: Particle Accelerator Designmentioning
confidence: 99%
“…In accelerator physics, it is desirable to find the cavity shape that maximizes the quality factor of a fixed accelerating mode while minimizing the quality factor of (parasitic) higher-order modes [23,24]. This design problem can be formulated as an eigensystem-constrained shape optimization problem of the form in Eq.…”
Section: Background and Related Workmentioning
confidence: 99%
“…Then, for example, the objective functions are scalarized, i.e., the multi-objective optimization problem is converted into a single-objective optimization problem, usually with the help of some predetermined weights, and a gradient-based optimization method is applied, starting from the already found cavity shape [23]. Approaches that employ scalarization and gradient-based methods for EM shape optimization problems where the frequency of the accelerating mode has to match a given target frequency and one or a few properties of the EM field of the three-dimensional cavity shape need to be optimized are published in [24][25][26].…”
Section: Introductionmentioning
confidence: 99%