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RFQ Development for FETS

RFQ Development for FETS. Simon Jolly Imperial College 7 th January 2010. FETS RFQ Development. FETS will utilise a 4m-long, 324 MHz four-vane RFQ channel, consisting of four resonantly coupled sections. RFQ focuses beam from LEBT and accelerates it to 3MeV, ready for Chopper/MEBT.

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RFQ Development for FETS

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  1. RFQ Development for FETS Simon Jolly Imperial College 7th January 2010

  2. FETS RFQ Development • FETS will utilise a 4m-long, 324 MHz four-vane RFQ channel, consisting of four resonantly coupled sections. • RFQ focuses beam from LEBT and accelerates it to 3MeV, ready for Chopper/MEBT. • 4-vane cold model showed agreement between CST simulations and bulk RF properties. • Previous beam dynamics simulations, based on field maps produced with a field approximation code, provide a baseline for the new design. • Novel design method currently under development to combine CAD and electromagnetic modeling with beam dynamics simulations in GPT. Simon Jolly, Imperial College

  3. FETS Integrated RFQ Design • Would like to have a method of designing RFQ where all steps are integrated: • Engineering design. • EM modelling. • Beam dynamics simulations. • Integrating design steps allows us to characterise effects of: • Fringe fields and higher order modes. • Particular CNC machining techniques and options on beam dynamics. Simon Jolly, Imperial College

  4. CST Mesh Density • A lot of effort on optimising meshing in CST. • Need a field map that gives transmission results similar to RFQSIM. • Important to quantify whether we can model Electrostatic field of vanes with enough accuracy in CST to measure beam dynamics. • Non-trivial: modelling 30mm x 30mm x 4m volume with micron accuracy. • Changes in beam dynamics MUST be unaffected by coarseness of CST field meshing so we can compare to optimised field. Simon Jolly, Imperial College

  5. First CST Field Map • Produced with CST, tracked with GPT: • Transmission = 99% • Mean energy = 1.31 MeV • Energy rms = 261 keV Simon Jolly, Imperial College

  6. Increase Vane Radius An educated guess: increasing tip radius should improve quadrupole field close to beam axis. Try field mesh with larger tip radius… Simon Jolly, Imperial College

  7. Vane Tip Field Maps 3.24 mm 7 mm Simon Jolly, Imperial College

  8. Second CST Field Map • Increase vane radius to 7mm “by hand”: • Transmission = 99.6% • Mean energy = 3.02 MeV • Energy rms = 14 keV Simon Jolly, Imperial College

  9. 7 mm Vane Tips • The Good News: we now have a vane shape that produces comparable transmission results to RFQSIM field! • The Bad News: we can’t actually build it… • 7 mm vane tip radius exceeds Kilpatrick Limit… Simon Jolly, Imperial College

  10. 22/4/09 State Of Play (Previous UKNF) • CAD modelling process now pretty mature: can model vane, rod and “vod” with parameter adjustment on-the-fly (everything except no. of cells). • Models import into CST and output to GPT: beam dynamics simulations well understood. • Definite issues in CST modelling: • We think we see “plateau” at 4,100 points and 0.5mm point spacing of output file. • Clear discrepancies with Alan’s field map: good transmission and energy with r = 7mm vane, r = 3.2mm rod but NOT r = 3.2mm vane! It should match… • Are the discrepancies real or down to faulty method? • Need to ensure we’re not re-inventing the wheel: RFQ’s have been designed before without this process. • Need to ensure CAM systems will understand our CAD models so we can manufacture what we’re designing (this is the point…). Simon Jolly, Imperial College

  11. Corrected Input Values • Couldn’t understand why increasing the radius of curvature made the results closer to Alan’s field map. • The solution: • Inconsistencies in the units of the RFQSIM input file. • Reported radius was incorrect, so RFQSIM actually modelling a larger radius. • Reran RFQSIM with corrected values to get new modulation parameters. Simon Jolly, Imperial College

  12. Third CST Field Map • Using corrected input values: • Transmission = 93.8% • Mean energy = 2.77 MeV • Energy rms = 470 keV Simon Jolly, Imperial College

  13. Incoherent Acceleration • Better results: • Some particles accelerated to the full 3 MeV. • Still not achieving coherent acceleration, even with new modulation parameters. • This result published at PAC’09. • Most obvious way to improve results is to increase mesh density: • Prior studies with 7mm vanes showed current mesh density was sufficient. • Smaller radius of curvature (3.24 mm) needs tighter mesh to model vane tip region. • CST at computational limit: split RFQ into 5 sections and mesh separately. Simon Jolly, Imperial College

  14. Fourth CST Field Map • Modelling RFQ in 5 sections: • Transmission = 99.8% • Mean energy = 1.98 MeV • Energy rms = 378 keV Simon Jolly, Imperial College

  15. High Mesh Particle Losses • Many possible causes of problems in fourth CST field map: • Try hexahedral rather than tetrahedral meshing. • Try open and tangential boundary conditions. • Better meshing with tetrahedral mesh and tangential boundary. • Eventually found the problem was in the reconstruction of the RFQ from the five sections: • one of the sections was using the parameters from a different section, and so the modulation pattern was incorrect. • reran with correct reconstruction Simon Jolly, Imperial College

  16. Fifth CST Field Map • Five sections reconstructed into whole RFQ, high mesh density, tangential boundary: • Transmission = 100% • Mean energy = 3.03 MeV • Energy rms = 12 keV Simon Jolly, Imperial College

  17. Varying CST Mesh (640 points) Simon Jolly, Imperial College

  18. Varying CST Mesh (4700 points) Simon Jolly, Imperial College

  19. Particle Tracking For High/Low Mesh

  20. Conclusions • Finally seeing match between RFQSIM optimised field map and CST field map from CAD modelling. • Each step has required a lot of effort for small progress, but that progress has proved extremely valuable. • Advantages of this process already starting to become apparent: for example, very easy to modify CAD model based on thermal/stress simulations (Scott Lawrie) and measure effect on beam dynamics. • Next steps: • Output CAD model to Comsol, repeat process from CST to produce more easily adaptable field map (tighter integration with Inventor and Matlab). • Compare CST coarse, fine, Comsol and RFQSIM field maps point-by-point to determine whether discrepancies are a result of poor field mapping or more accurate modelling of vane tips. Simon Jolly, Imperial College

  21. Transverse Field Map Comparison Simon Jolly, Imperial College

  22. Transverse Field Map Comparison

  23. rod axis r0 (mm) ma r0 (mm) a L/2 beam axis L RFQ Design Parameters • RFQ parameterised by 3 (+ 1) parameters: • a and m parameters define modulation depth. • r0 defines the mean vane distance from the beam axis and is derived from a and m. • r gives the radius of curvature (vane) or mean radius (rod). • L defines the length of each cell (half sinusoidal period). • For field approximation method, these values generated for idealised RFQ field. Simon Jolly, Imperial College

  24. RFQ Parameters (from TUP066, LINAC06) Simon Jolly, Imperial College

  25. RFQ Design Stages Simon Jolly, Imperial College

  26. RFQ CAD Modelling • Autodesk Inventor CAD package used to model RFQ cold model (and a lot more besides…). • Inventor can dynamically link to parameters in Excel spreadsheet: • Change spreadsheet parameters and model updates automatically. • Use spline to approximate sinusoidal vane shape: only 2% difference. Simon Jolly, Imperial College

  27. CST MicroWave Studio E-field Modelling • Four vanes from inventor imported by a macro. • Model cut into 6 sections (5 plus matching section) for ease of modelling and to increase CST mesh density. • Potentials and boundary conditions defined in the macro. • Run solver to produce electrostatic field map. Simon Jolly, Imperial College

  28. Beam Dynamics Simulations • GPT used for beam dynamics simulations. • Import electrostatic field map from text file produced by CST. • Integration algorithm traces particle movements through time-varying field. • Compare results to field map from optimised RFQ field expansion. Simon Jolly, Imperial College

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