R. Bruce, collimation team, FLUKA teamR. Bruce, collimation team, FLUKA team

Update: Comparison between Update: Comparison between Run 1 loss maps and Run 1 loss maps and

simulationssimulations

R. Bruce, 2014.03.31 1

R. Bruce, 2014.03.31

Outline

• Introduction and motivationIntroduction and motivation

• Reminder of previous results – IPAC13 – and improvements Reminder of previous results – IPAC13 – and improvements since thensince then

• SixTrack results for perfect machineSixTrack results for perfect machine

• Influence of impact parameterInfluence of impact parameter

• SixTrack results with imperfectionsSixTrack results with imperfections

• Comparison with measurements using FLUKA Comparison with measurements using FLUKA

• Summary and statusSummary and status

2

Motivation

R. Bruce, 2014.03.31 3

• Very high stored energy in LHC (nominal 362 MJ). Maximum specified loss rate from beam is 500 kW, while design quench limit is 8.5 W/m. We need a very efficient collimation system!

• We need a very good understanding of the beam cleaning and the ability quantitatively predict losses around ring

• SixTrack with collimation routine used for past and present machine configurations.

• We have a strong interest to verify the predictive power of SixTrack! Preliminary comparisons shown in CWG talks 25.10.10 and 19.12.2011, more detailed study in IPAC13 and CWG 2013.05.06

500 kWBeam loss

collimation Cold magnets

< 8.5 W/m

Previous results

• IPAC13, with updates in Daresbury HiLumi meeting: Presented systematic comparison of loss maps from SixTrack and measurements in Run 1.

• SixTrack counts number of lost protons. BLMs measure secondary shower particles. => For quantitative comparison, used FLUKA simulations at a few selected BLMs.

– Factor 3-6 discrepancy at TCTs, a bit less in IR7 DS

R. Bruce, 2014.03.31 4

Previous results - TCTs

R. Bruce, 2014.03.31 5

Updates since IPAC13

• Since then, several updates:

– Improved data analysis. Included more loss maps and de-selected measurements with suspected hierarchy violation, in particular H resonance loss maps where V was done just before and vice versa.

– Improved halo modelling for better control of the impact parameter – important in particular with imperfections and large center errors! Details: CWG 2013.10.14

– Improved scattering routine (see Claudia’s talk)

– Improved parameters for machine imperfections, based on detailed analysis of data from Run 1 (orbit, beta-beat).

• Running SixTrack with optics imperfections, not only collimator imperfections as in previous studies

R. Bruce, 2014.03.31 6

SixTrack vs measurements

• 2011 example from now on

– β*=1.5m

– Relaxed collimator settings

• Example: horizontal losses B1, resonance crossing

• Qualitatively good agreement of loss locations around the ring

R. Bruce, 2014.03.31 7

… Zoom in IR7

• Decreasing losses along insertion, leakage to the DS a few orders of magnitude lower than initial loss

• Note: BLM signals caused by showers, SixTrack shows lost protons. Cannot compare directly without shower simulation

• Simulated DS losses grouped in two “clusters”: cell 8-9 and 11-12

– Single diffractive protons with energy offsets

– Clusters explained by oscillation of locally generated dispersion since TCP

R. Bruce, 2014.03.31 8

Influence of impact parameter b

• Significant uncertainty of actual impact parameters on the TCP in the machine

– Crossing 3rd order resonance: b=2-15 um (simulations)

– Losses from diffusion in stable conditions: 0.02 < b < 0.3 um (measurements, PRSTAB 16 021003, 2013)

– Fast losses from instabilities: ?

• Uncertainties raises several questions:

– Are the loss maps representative of physics losses?

– Are the simulations representative of the machine?

• Check: scan over impact parameters

R. Bruce, 2014.03.31 9

Influence of impact parameter

R. Bruce, 2014.03.31 10

• At small b<100 um, losses on the machine aperture are rather independent of the impact parameter => uncertainties on b less important

• Some variations caused instead by changing ratio between TCP jaws

• Different halo distributions give comparable results

Imperfections

• Imperfections at collimators, magnetic elements and aperture deteriorate the cleaning performance by up to a factor ~4 in our studied scenario

– Accounting for tilts, center errors, gap errors, optics errors, jaw flatness errors and aperture misalignments

R. Bruce, 2014.03.31 11

With FLUKA shower simulations:10 highest BLMs in the IR7 DS

R. Bruce, 2014.03.31 12

• Simulating showers reaching BLMs with FLUKA for a quantitative comparison at a few selected BLMs: IR7 DS and TCTs

• IR7 DS: 2011 quench test simulation – identical machine configuration

– To include imperfections: scaling up the FLUKA result by the increase of nearby primary losses seen by SixTrack

– Agreement typically within a factor 2, not worse than a factor 3

With FLUKA shower simulations:TCTs

• With FLUKA, including cross-talk between BLMs

• Agreement typically within a factor 2 or better, never worse than 3

R. Bruce, 2014.03.31 13

Paper in preparation

• More details on the full study soon to be published

R. Bruce, 2014.03.31 14

Summary

• SixTrack and FLUKA used in the design of collimation in present and future LHC configurations

– It is of significant interest to understand the accuracy of the predictions

– Also, it’s an interesting scientific study: 1) tracking particles over hundreds of turns through ~5000 magnets and the material of the collimators 2) Shower simulation through detailed geometry to estimate energy deposition in BLM

• Using the 2011 data, and following many significant improvements since IPAC, we have a rather successful benchmark

– Good qualitative agreement SixTrack-BLM measurements in terms of loss locations and relative distribution of losses

– Quantitative agreement, when including transfer function proton loss→BLM from FLUKA shower simulations, typically within a factor 2. Very good when considering the complexity of simulation chain and the many uncertainties (imperfections, halo distribution and diffusion etc.)

• Results give confidence in the simulation tools for future studies

R. Bruce, 2014.03.31 15