Author: Pommerenke, H.W.
Paper Title Page
TUPAG07 Efficient Computation of Lossy Higher Order Modes in Complex SRF Cavities Using Reduced Order Models and Nonlinear Eigenvalue Problem Algorithms 270
 
  • H.W. Pommerenke, J. Heller, U. van Rienen
    Rostock University, Faculty of Computer Science and Electrical Engineering, Rostock, Germany
 
  Superconducting radio frequency (SRF) cavities meet the demanding performance requirements of modern accelerators and high-brilliance light sources. For the operation and design of such resonators, a very precise knowledge of their electromagnetic resonances is required. The non-trivial cavity shape demands a numerical solution of Maxwell’s equations to compute the resonant eigenfrequencies, eigenmodes, and their losses. For large and complex structures this is hardly possible on conventional hardware due to the high number of degrees of freedom required to obtain an accurate solution. In previous work it has been shown that the considered problems can be solved on workstation computers without extensive simplification of the structure itself by a combination of State-Space Concatenation (SSC) and Newton iteration to solve the arising nonlinear eigenvalue problem (NLEVP). First, SSC is applied to the complex, closed and thus lossless RF structure. SSC employs a combination of model order reduction and domain decomposition, greatly reducing the computational effort by effectively limiting the considered frequency domain. Next, a perturbation approach based on SSC is used to describe the resonances of the same geometry subject to external losses. This results in a NLEVP which can be solved efficiently by Newton’s method. In this paper, we expand the NLEVP solution algorithm by a contour integral technique, which increases the completeness of the solution set.  
slides icon Slides TUPAG07 [11.204 MB]  
DOI • reference for this paper ※ https://doi.org/10.18429/JACoW-ICAP2018-TUPAG07  
About • paper received ※ 18 October 2018       paper accepted ※ 24 October 2018       issue date ※ 26 January 2019  
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