ec simulations for hl-hlc beam scenarios
DESCRIPTION
EC Simulations for HL-HLC Beam Scenarios. C. M. Bhat ECLOUD Meeting CERN October 1, 2012. Motivation of the PS Expt. . Can Bunch lengthening be a viable e-cloud mitigation technique for the LHC or the HL-LHC ? - PowerPoint PPT PresentationTRANSCRIPT
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EC Simulations for HL-HLC Beam Scenarios
C. M. BhatECLOUD Meeting
CERN
October 1, 2012
USMotivation of the PS Expt. Can Bunch lengthening be a viable e-cloud mitigation technique for the LHC or the HL-LHC? PS studies undeniably proved that bunch
profiles have significant effect on e-cloud growth. BSM50 mode gives rise to about a factor of two smaller e-cloud growth. Objective is to extend the studies to the LHC using HL-LHC beam parameters
Simulations Only ECLOUD and PyECLOUD
2012 2C. M. Bhat
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C. M. Bhat 3
Comparison between ECLOUD and PyECLOUD simulations
2012
PyEcloud: heatload(iii)=const*[sum(En_imp_eV_time)-sum(En_emit_eV_time)];const= eV*frev*(2808/288)
ECLOUD:Ave_heatload = Average of 2nd column of "eloss.data"
Gaussian Bunches
PyeCloud gives 5% smaller heat-load in arcs
PyeCloud gives ~35% larger heat-load in arcs !?!
ARC Sections:Bunch Intensity= 2.20E+11 ppb
PyeCloud ECLOUD PyeC/ECdMax=1.1 R0=0.2 0.29 W/m 0.3 W/m 0.96dMax=1.1 R0=0.25 0.29 W/m 0.31 W/m 0.95dMax=1.5 R0=0.2 1.22 W/m 1.29 W/m 0.95dMax=1.5 R0=0.25 1.31 W/m 1.37 W/m 0.96
Drift Sections:Bunch Intensity= 2.20E+11 ppb
PyeCloud ECLOUD PyeC/ECdMax=1.1 R0=0.2 4.55 W/m 3.41 W/m 1.33dMax=1.1 R0=0.25 4.62 W/m 3.47 W/m 1.33dMax=1.5 R0=0.2 8.88 W/m 6.41 W/m 1.39dMax=1.5 R0=0.25 9.07 W/m 6.59 W/m 1.38
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Simulated Bunch Profiles (ESME) and Analytical form for WB
2012
These bunch profiles are used to generate one SPS batch of injected beam to the LHC25 nsec filling pattern: 288 bunches with 200 nsec kicker gap between every 72 bunches50 nsec filling pattern: 144 bunches with 200 nsec kicker gap between every 36 bunches
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HL-LHC Beam Parameters
2012
0.56 1.12 0.89
2.54 2.6615.8 13.23.12 2.66
590 590
0.31 0.33
7.4x 8.5xBeam Brightness (R.U.) 1 2.9 3.8Pileup Llevel=5L0 19(27) 140 140
x
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Simulations with ECLOUD and PyECLOUD
2012
Parameters ValuesProton Energy 7000 GeV
Number of Bunches/turn 2808 @ 25nsec bunch spacing 1404 @ 50nsec bunch spacing
Bunch Intensity 2.2E11ppb @ 25nsec bunch spacing 3.5E11ppb @ 50nsec bunch spacing
Bunch spacing 25 and 50nsecBunch Length (4s) Varying in the range of 0.9-1.33 nsecBunch Shape/Profiles Varying shapesKicker Gap 200nsecBeam Pipe: H and V Aperture (half) 2.2cm(H), 1.73cm(V)
Material of the Beam Pipe TiZrV Non-evaporable Getter (NEG) Coated
Beam Transvers Emit. e x =e y 2.5 mm for 25 nsec bunch spacing 3.0 mm for 50 nsec bunch spacing
Latti ce Function at the Detector b x and by= 86.37 m, 92.04 m
Source of primary electrons & Relfectivity
100% Photo emission 20%
Primary electron emission yield 0.00087Reflected electron Distribution cos2y
Maximum SEY yield dMax 1.3 to 1.7R0: Probability for Elastic Reflection in the Limit of Zero Primary Energy of Electrons
0.2 t 0.7
Electron Energy at dMax (eV) 239.5
=239.5 eV
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Average Heatload for the HLLHC beam scenarios
2012
BSMBLM
0
PyECLOUD
ECLOUD &
PyECLOUD
USConclusions
We find that changing the bunch profiles will keep EC growth nearly constant. So BSM is not going to help EC growth in the LHC. However, foreseen use of second harmonic Landau cavity that would change bunch profiles (shorter or nearly flat bunches) and makes beam longitudinally more stable, will not pose any additional EC related problem in the LHC/HL-LHC.
2012 C. M. Bhat 8
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Comparison between ECLOUD and PyECLOUD simulations
2012