• K. Tian, G. Cheng, F. Marhauser, H. Wang
  JLAB, Newport News, Virginia

In this paper, we present benchmarking results for high-class 3D electromagnetic (EM) codes in designing RF cavities today. These codes include Omega3P [1], VORPAL [2], CST Microwave Studio [3], Ansoft HFSS [4], and ANSYS [5]. Two spherical cavities are selected as the benchmark models. We have compared not only the accuracy of resonant frequencies, but also that of surface EM fields, which are critical for superconducting RF cavities. By removing degenerated modes, we calculate all the resonant modes up to 10 GHz with similar mesh densities, so that the geometry approximation and field interpolation error related to the wavelength can be observed.

• A.S. Hofler, P. Evtushenko, F. Marhauser
  JLAB, Newport News, Virginia

Automation of DC photoinjector designs using a genetic algorithm (GA) based optimization is an accepted practice in accelerator physics. Allowing the gun cavity field profile shape to be varied can extend the utility of this optimization methodology to superconducting and normal conducting radio frequency (SRF/RF) gun based injectors. Finding optimal field and cavity geometry configurations can provide guidance for cavity design choices and verify existing designs. We have considered two approaches for varying the electric field profile. The first is to determine the optimal field profile shape that should be used independent of the cavity geometry, and the other is to vary the geometry of the gun cavity structure to produce an optimal field profile. The first method can provide a theoretical optimal and can illuminate where possible gains can be made in field shaping. The second method can produce more realistically achievable designs that can be compared to existing designs. In this paper, we discuss the design and implementation for these two methods for generating field profiles for SRF/RF guns in a GA based injector optimization scheme and provide preliminary results.