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SLAC KLYSTRON LECTURES

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... of position, E(r), B(r), D(r), H(r), and particle current and charge fields, J(r), and r(r). Initial Conditions: D = r B = 0. Constitutive Relations: E = D / e H = B / m ... – PowerPoint PPT presentation

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Title: SLAC KLYSTRON LECTURES


1
  • SLAC KLYSTRON LECTURES
  • Lecture 14
  • June 23, 2004
  • 2-D and 3-D MAGIC Simulation Software
  • Applied to Klystron Design Examples
  • David Smithe and Larry Ludeking
  • ATK Mission Research
  • magic_at_mrcwdc.com
  • George Caryotakis, Glenn Scheitrum, Daryl Sprehn,
    and Bob Steele
  • Stanford Linear Accelerator Center

2
Outline
  • Example of Klystron Simulation in MAGIC Software
  • Overview of FD-TD-PIC Computation Method
  • Various Different Uses for the Software
  • The B-Factory Klystron Template
  • Challenges for the Future

3
Geometry-Based Simulation Example 7 Cavity
Klystron
Voltage at Input Cavity
Voltage at Output Cavity
(Courtesy of SLAC)
4
Klystron Output Cavity Example
  • Penultimate and 5-stage output cavity.
  • Beam is bunched in several previous cavities.
  • (Magic 2D, simulation courtesy of SLAC.)

click for movie
5
Theoretical Basis of MAGIC2D and MAGIC3D
  • Maxwells Equations
  • There are electromagnetic vector fields as a
    function of position, E(r), B(r), D(r), H(r), and
    particle current and charge fields, J(r), and
    r(r).
  • Initial Conditions ??D r ??B 0
  • Constitutive Relations E D / e H B / m
  • Evolution Equations ?tB -??E ?tD ??H - J
  • Relativistic Lorentz Force
  • There are particles with position vector, xi, and
    relativistic momentum-per-mass vector, pi.
  • Velocity Relation gi (1pi / c2)½ vi pi
    / gi
  • Evolution Equations ?txi vi ?tpi (qi/mi)
    E(xi) vi ? Bi(xi)

6
Theoretical Basis of MAGIC2D and MAGIC3D (cont.)
  • Plus Many-Many Model Equations
  • Materials (e, s, and m, perfect conductors,
    polarizers, foils, films, etc.)
  • Boundary conditions (periodic, absorbing,
    transmission line, etc.)
  • Particle Emission models (thermionic, secondary,
    explosive, etc.)
  • Lumped circuit elements (resistor, inductor,
    cable, capacitor, etc.)
  • Static magnetic fields (coils, imported from
    other codes, etc.)
  • RF sources (voltage ports, current drivers,
    etc.)
  • Initial conditions (field solver, particle
    populations, etc.)
  • Feedback circuits

7
Time Domain Simulation
  • MAGIC is simulation, not analysis. The goal is
    to mimic nature, with as little a priori
    knowledge as possible. As with nature, one
    starts with an initial system state, and evolves
    the system forward in time, without prejudice as
    to what the future system will or should look
    like. Diagnostics allow the researcher to
    observe the system, and if fortunate, interpret
    what is happening in a physical sense.
  • This is Time Domain. So MAGIC Is FD-TD-PIC.
  • Simulation is essentially a metal-less
    laboratory.
  • Example If a device must be properly tuned in a
    real laboratory, then it will need to be
    similarly tuned in simulation.
  • Example If a device cant work in the
    laboratory, it will be very difficult, or
    hopefully impossible, to force it to work somehow
    in simulation.
  • Example If the lab results are confusing, the
    simulation results might also be confusing. But,
    of course, MAGIC has diagnostics no lab has!

8
Matrix Formulation
  • Field components are E?dl, D?dA/dt,
  • H?dl, and B?dA/dt.
  • All derivatives, ?x , ??, and ?t, become
    matrices with 0,1.

Divergence of B Gausss Law Continuity
Faradays Law Amperes Law
Material Properties
9
Uses for Simulation Software
  • General qualitative understanding of physical
    processes
  • Evaluation of difficult-to-predict parameters
    for spreadsheet analysis
  • Plasma wave-number
  • Trans-conductance
  • Beam Loading, real and imaginary parts
  • Evaluation of difficult-to-analyze components
  • Penultimate and Output Cavities
  • Magnetic focusing of time-dependent bunched-beam
  • Entire end-to-end simulation

10
Qualitative Understanding
  • Many special diagnostics allow one to visualize
    the physics, and better understand it
  • Example bunch behavior in an SBK output cavity
  • It is usually simple to try unusual geometry or
    situations, once the basic geometry is in place
  • Example one absent beam line in an MBK

click for movie
11
Parameter Evaluation - Plasma Wavenumber
  • Excite cavity, pass steady-state beam through it,
    and watch bunching develop as beam passes through
    long drift tube. Tells where to place next
    cavity.

¼ lp
12
Parameter Evaluation Beam Loading
  • Ring-down Simulation. Pump up cavity with beam
    present, turn off pump. Signal will decay,
    giving Qbeam. Oscillation will also shift
    frequency slightly to beam loaded frequency.

Beam Loaded Frequency
13
Difficult Components Output Cavity
  • In the output cavity
  • Small-signal analysis is no longer valid
  • Particles in bunches may overtake one-another
  • Space charge forces are accentuated because of
    tight bunching
  • Radial transport is significant
  • Extended interaction regions imply more than one
    possible mode
  • Coupler geometry may be significant
  • Simulation is almost a necessity
  • Example ¾ - p mode output cavity

click for movie
14
Sheet Beam Output Cavity
  • Uses 3-cavity extended interaction, coupler load
    in 3rd cavity end only
  • Example Checking for constant phase across
    width of sheet beam

click for movie
15
Difficult Components Acceleration of Bunched
Beam
  • Klystron-like device, called a Reltron.
  • Two stages of DC voltage applied
  • Input cavity between the stages

click for movie
16
Entire End-to-end Simulation of B-Factory Klystron
17
The B-Factory Klystron Template
  • Pre-written MAGIC2D input file of complete
    klystron, for public use
  • Find it in Vacuum Electronics book by Barker et
    al.
  • Find it at SLAC website
  • User-friendly interface allows novices to
    redesign aspect of the klystron including cavity
    frequencies, Qs, spacings, and gap parameters.

18
Template Design and Optimization Capability
  • The template allows one to load previous results.
    The design iterative process is a repetition of
    device tuning runs, followed by a full-up
    hot-test run for result.

19
Template Cavity Parameters
  • Dialogs allow specification of all major cavity
    parameters

20
Template Tuning Results
  • Results of each iteration are tracked, and error
    between actual and desired values is given.

21
Template Hot Test Setup
  • Hot test parameters are set in a dialogue box

22
Template Hot Test Run
  • PHASESPACE plots during the hot test run show
    qualitative behavior

23
Template Hot Test Results
  • Results are provided in graphics and tabular form.

24
Challenges for the Future Problem Size
Simulation Geometry
  • Always need more cells in 3-D
  • Example Multiple Beam Klystron
  • Parallel processing will help.

Non-Uniform Grid
Grid resolution of Beam Tubes 12 cells across
tube.
25
Challenges for the Future Relativistic Devices
  • Numerical Cerenkov instability remains a
    manageable nuisance
  • HIGH_Q algorithm damps instability without
    loading cavities
  • Grid jiggling allows standard un-damped
    algorithms
  • Still looking for more convenient solutions to
    the problem.

26
Challenges for the Future Maintaining
Reliability
  • SLAC has developed an HTML driven Automated Test
    Suite to allow fast verification of MAGIC results
    on a large suite of different test cases.
  • Provides quick verification of new versions of
    the software.

27
Summary
  • The MAGIC software has been used for studying
    klystrons at SLAC for at least 8 years.
  • As computer speed increases, the potential uses
    of the software have evolved from 2-D physics
    studies to 3-D design work.
  • This talk has provided an overview and many
    examples of the use of the MAGIC software in
    klystron problems.
  • An public klystron template, based on SLACs
    B-factory klystron is available for use,
    experimentation, and education.
  • Parallel processing capability and active
    software development programs offer promise for
    even more capability in the future.
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