Number of Blocks per Pole
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Transcript of Number of Blocks per Pole
Number of Blocks per Pole
Diego Arbelaez
Option – Number of Blocks per Pole• Required magnetic field tolerance of ~10-4
• For a single gap this can be achieved with one block per pole by correcting permanent magnet block errors with various shimming strategies For example: can correct a block strength error with a pole position error i.e. one error is compensated with a different type of error
• Some errors can be compensated by performing block location sorting• For a variable gap undulator the different error signatures may not
scale equally as a function of gap• It is desirable to have the pole energization be as uniform as
reasonably possible• Pole energization uniformity can be improved by using multiple blocks
per pole that have been sorted
Slide 2
One or Two Blocks per Pole Analysis
Magnetic field error calculation• Investigate the effect of various type of errors including block strength
and angle and pole position errors• Determine the scaling of these errors as a function of gap
Do the different errors scale differently with gap? Will compensating one type of error with another type at one gap lead to
errors at a different gap?
Sorting simulations• Monte Carlo simulations are performed to determine how much
improvement is obtained in the block Br distribution when two blocks are used
• Simulated Annealing simulation is used for the sorting of the permanent magnet blocks within the undulator to determine the effect of the block population uniformity on field integral and phase errors
Slide 3
2D Undulator Magnetic Model
• Infinite permeability poles and permanent magnet blocks (charge sheets) Poles are on constant scalar potential Decompose into direct and indirect flux
• Direct flux comes from permanent magnet blocks into the poles• Indirect flux is due to variations in the scalar potentials of the
poles Scalar potential of each pole is determined by setting the
net flux through each pole to zero
Capacitance Matrix relates the indirect flux between poles to their potential difference
Slide 4
Error Analysis
• Permanent magnet block errors are modeled by excess charges
• Poles errors are modeled by a boundary value perturbation
Neglecting higher order term:
; For block error
; For pole errorSlide 5
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Various errors
Br strength error
Br angle error bottom block Br angle error top block
Pole height error
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Error Normalized Flux SignaturesBr strength error
Br angle error bottom block Br angle error top block
Pole height error
0.2% Br error
25 μmerror
0.1°error
0.1°error
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Error Normalized Integral SignaturesBr strength error
Br angle error bottom block Br angle error top block
Pole height error
0.2% Br error
25 μmerror
0.1°error
0.1°error
Error Analysis Conclusions
• Error analysis model allows a variety of errors to be studied with minor modifications to the model
• There is not net steering caused by the above errors• The pole height error is more localized than the block
strength errors• The Br strength error causes a net displacement• The normalized flux from the pole height error is fairly
invariant with gap• The normalized flux for block errors varies significantly with
gap• Due to different gap scaling of errors it is desirable to have
the blocks energized as uniformly as possible
Slide 9
Permanent Magnet Sorting
• Determine how the distribution of Br for a population of permanent magnet blocks is affected by Number of blocks per pole Uniformity of the population Total number in the population
• Monte Carlo simulations are performed to determine the distribution of average Br for the sorted blocks
• Assume that the individual block population is normally distributed with mean μ and standard deviation σ
• Blocks with abs(Br-μ) > fσ (where f is a prescribed factor) are rejected from the population
Slide 10
Monte Carlo Algorithm
• Select a normally distributed random value with the assigned μ and σ If abs(Br-μ) < fσ keep the value in the population otherwise proceed to the
next random number Repeat until there are N values in the population
• Perform sorting• Repeat for M random populations of N values each
Sorting:• Two blocks per pole
Generate two populations of blocks (upper and lower) Multiply the upper blocks by the energization reduction factor Sort the lower and upper block populations in descending order Combine the lower block with the lowest Br and the upper block with the
highest Br Repeat for the next lowest and highest until all blocks have been paired
Slide 11
Two Block Sort Results
Simulation Parameters: N = 260M = 10000μ = 1.32σ = 0.01μf = 2
One block per pole distribution
Improvement due to sortingTwo blocks per pole distribution
Slide 12
Simulated Annealing Sorting Algorithm
• Simulated Annealing algorithm Swap two blocks within the undulator Compute the change in the objective function (dE) If dE = 0 -> accept the change If dE > 0 -> probability of accepting the change obeys Boltzmann
distribution (i.e. P(dE) α exp(-dE/T) ) Start at high T and reduce until a minimum is obtained
• Objective function First field integral uniformity Second field integral uniformity Phase errors
• Only Br strength errors are assumed• One and two block populations from the Monte Carlo simulation are
used as the input• Results are for a single gap
Slide 13
Simulated Annealing Sorting Results
• One Block (standard deviation = 1% of Br) RMS Second integral error = 0.10μT-m2
RMS Phase error = 1.7°• Two Blocks after sort algorithm
RMS Second integral error = 0.01μT-m2
RMS Phase error = 0.34°
Slide 14
Sorting Conclusions
• Two block sort improves the uniformity of energization by ~ one order of magnitude
• Further sorting can be performed by selecting the position of each block along the undulator to minimize trajectory and phase errors
• After sorting tuning will be performed (e.g. by varying the pole positions)
• Pole and block errors scale differently as a function of gap
• It is desirable to have the pole energization be as uniform as possible to have proper tuning for the entire range of the undulator gap
Slide 15
Cost/Benefit of Options
• Estimated costs for blocks: HXU: $2M SXU: $2.9M
• One block vs. two: VAC estimate: two ~20% more Assume a total of 30-40% more with extra handling
• Cost of 2 vs. 1 is estimated to be $1.5M - $2M• Two blocks per pole improves the energization
uniformity by ~ one order of magnitude• One block makes tuning over gap range more difficult,
increases risk
Slide 16