E. Todesco for the QBT CERN, Geneva Switzerland CERN, 20th January 2016 LMC SECOND UPDATE ON QUENCH BEHAVIOUR TEAM ACTIVITIES AND STRATEGIES TOWARDS 7 TeV E. Todesco for the QBT CERN, Geneva Switzerland

RECENT ACTIVITIES Recent work www.cern.ch/qbt 7 meetings in July-December 2015 Average partecipation: 8, total number of colleagues: 17 Recent work Investigation on the difference between firms Recall of the features of the 3000 production and main events Shape of distributions and strategy for having more information at 7 TeV SM18 test Flattop quenches

COMPOSITION B. Auchmann M. Bajko G. De Rijk P. Fessia P. Ferracin P. Hagen S. Le Naour J. C. Perez M. Modena F. Savary R. Schmidt J. Ph. Tock E. Todesco D. Tommasini A. Verweij G. Willering

BRIEF RECALL OF RESULTS Result I: 2015 confirmed that 3000 series magnets quench more than 2000/1000 series: 140 quenches of 3000 series, 27 of 2000 series and 5 of 1000 series Result II: In the 3000 series, the production is not homogeneous Differences are statistically significant Degradation at 3150-3200 (that went on 45) Number of quenches per magnet in 3000 series with statistical error

2008 VS 2015 What can we expect for the future? Two sectors can be compared: apparent paradox S56 powered at 11100 A 23 quenches in 2008, 16 quenches in 2015 S45 powered to 10300 A 3 quenches in 2008, 10 quenches in 2015 Adding statistical error with two sigma S56: 23±8 in 2008 versus 16±7 in 2015 S34: 3±6 in 2008 versus 10±6 in 2015 Result III: Data are compatible with a scenario where at each warm up we start in the same condition as at the beginning of the previous training

2015 VS VIRGIN TRAINING Did 3000 series totally lost memory? In virgin condition: 46% of 3000 series, i.e. 191±20 quenches In 2015: 34% of 3000 series, i.e. 142±19 quenches Result IV: data compatible with a partial but small preservation of memory for 3000 series HC «a bit better» than virgin training Training of virgin magnets during production

WHICH MAGNETS ARE BAD IN 56? Two extreme situations can be imagined: In 56 there are some bad magnets, always quenching, and other good magnets, never quenching In this case, all magnet quenching in 2008 will quench in 2015 In 56 all magnets are belonging to the same distribution, with a probability p of quenching In this case, the probability of having magnet quenching in 2008 and in 2015 will be p2(0.25)2=6% So it is enough to count how many magnet quenched both in 2008 and in 2015 3 magnets quenched in 2008 and 2015: 3358, 3330 and 3336 out of 84, ie 3% Result V: S56 data compatible with magnets belonging to the same distribution (no bad or good magnets) No evidence of magnets to be removed in LS2

SHAPE OF DISTRIBUTIONS We test the hypothesis of a Gaussian quench probability for the lower part of the quench spectrum

SHAPE OF DISTRIBUTIONS Integral of the distribution is the training curve, an erf function

SHAPE OF DISTRIBUTIONS Interesting result: HC data of 3000 except 45 are compatible with a Gaussian Statistical error (2s) is associated to having 350 magnets Gaussian parameters: m=11.6 kA s=0.73 kA

SHAPE OF DISTRIBUTIONS For 45, we quenched 75% of the magnets Erf fit does not look so nice …

SHAPE OF DISTRIBUTIONS For 45, we quenched 75% of the magnets Erf fit does not look so nice … But since the sample is 62 magnets only, statistical error is larger, and it fits within 2 sigma Gaussian parameters: m=10.75 kA s=0.45 kA

SHAPE OF DISTRIBUTIONS It does not look gaussian, the beginning is too steep First quenches are too low Tentative parameters: m=12.3 kA s=0.75 kA This is a shaky fit, we do not have enough data

FIRST RESULT The apparently chaotic training of the LHC can be seen in terms of three Gaussian distributions Where the 2000 series part has some discrepancies in the initial part

SHAPE OF DISTRIBUTIONS A good fraction of HC data are compatible with Gaussian distribution for the first quench We now that extrapolation is a dangerous exercice the whole distribution cannot be Gaussian (some asymmetry should be on the short sample side) Let’s go back to the production data where we have access to the whole distribution for the first and second quench

PRODUCTION DATA 1000 case: first half gaussian, second half a bit slower as expected Distribution falls faster on the short sample side as expected from the physics

PRODUCTION DATA A very effective and very inelegant patch Using two Gaussian distribution with the same average and two different sigma, very good agreeement Sigma on the upper part 30% smaller than in the lower part Gaussian parameters: m=12.0 kA s1=0.70 kA s2=0.45 kA

PRODUCTION DATA The same approach works for the 2000 case Sigma on the upper part 30% smaller than in the lower part Gaussian parameters: m=11.35 kA s1=0.90 kA s2=0.60 kA We know that this fit has a dark side, there is work in progress on fit with asymmetric distributions xn exp –x2

PRODUCTION DATA The same approach works for the 2000 case Sigma on the upper part 30% smaller than in the lower part Gaussian parameters: m=11.35 kA s1=0.90 kA s2=0.60 kA We know this fit has a dark side, we are working on asymmetric distributions xn exp –x2

PRODUCTION DATA 3000 case Does not fit Gaussian - another sign that something went wrong in 3000 production? But we will see that the second quench fits

A TENTATIVE EXTRAPOLATION Accouting for the asymmetry observed in production Assuming the shaky fit for the 2000 series Assuming an a priori 5% 1000 series magnets quenching to reach 7 TeV We end up with 450 quenches to 7 TeV Plus the second quench – for which very little data are available on HC

SECOND QUENCH IN PRODUCTION DATA In virgin condition, 30% of 3000 series magnet had a second quench below 7 TeV Asssuming that it cannot go worse , we have to add a most 140 quenches

A TENTATIVE EXTRAPOLATION So our best estimate with available data is 450 first quenches plus at most 150 second quenches Estimate is rather linear in the 6.5-7 TeV range so for pushing the LHC today towards 7 TeV is about 50 quenches per 100 GeV, plus the second quench If we consider case after a thermal cycle, we have to add the 170 quenches to go to 6.5 TeV

A TENTATIVE STRATEGY Possible strategy: push S12 and S45 to 7 TeV before LS2 45 – to see the 3000 series second quench (we already quenched 75% of 3000 magnets,) 12 – to see the 1000 and 2000 behaviour (there are only 9 3000 series magnets) These two sectors are also requiring the lower number of quenches, so we maximize information and minimize the risk

SUMMARY The HC training curves are compatible with an erf fit, with the physical meaning that the lowest part of the quench distribution is Gaussian-like We have to separate 2000 from 3000, and 45 from the 3000 set The production data support this statement, showing Gaussian shape over half of the distribution Work to fit with asymmetric distribution is ongoing An extrapolation to 7 TeV gives 450 first quenches Plus the second quench, for which an upper bound of 150 can be given To have a more solid extrapolation a possible strategy is to push S12 and S45 to 7 TeV This should cost about 50 first quenches