Availability and Reliability Issues for ILC Page: 2 of 4
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(e.g. e- linac energy overhead or e+ DR extraction kicker
strength or luminosity) was degraded too much, and plans
to fix things that degrade that parameter. Based on the
required repairs, it calculates how long the downtime
must be to repair the necessary items. It then schedules
other items for repair, allowing the downtime to be
extended by as much as 50 to 100%. Some other issues
must also be taken into account:
" If an access to the accelerator tunnel is required, one
hour is allowed for prompt radiation to decay before
entry. One hour is also allowed for locking up, turning
on and standardizing power supplies.
" The devices chosen for repair are those that give the
most bang for the buck (most improvement in the
parameter per hour of repair time).
" The number of people in the accelerator tunnel can be
limited to minimize the chaos of tracking who is in the
" There are no regularly scheduled maintenance
shutdowns, except an annual 3 month shutdown.
Interventions occur only when the accelerator is
broken, which is the practice at most operating HEP
accelerators. In real life, maintenance might be
planned when the energy overhead was getting low
without waiting to actually run out of energy.
However, since the simulation does not add any
penalty for unplanned or off-hours downtimes, this
becomes a subtlety which does not really impact the
" Things which break during the downtime are just
ignored (It is assumed they are immediately fixed).
The long recovery time which is described in the next
paragraph is intended to account for this.
The simulation assumes that all repairs are completed
on schedule. It seemed an unnecessary complication to
throw random numbers to distribute the repair times
around the MTTR as the simulation integrates over a long
enough time period to average out such variations.
Recovery of the beam is modeled in a crude fashion
which matches the qualitative experience on many
accelerators. This common experience is that it takes time
to recover good beams after a downtime. In fact, the
longer the down, the longer the recovery time.
Contributions to the recovery come from myriad factors
* Hardware failures - devices such as pumps and power
supplies which break because they were turned off
during the shutdown or devices which just happen to
break while the accelerator was down and were not
" Environmental factors - temperature changes caused
by the access or ground motion over a few hour period
which can be significant enough to require retuning
" Human error - mistakes made in doing the repairs
(valves left closed, cables left disconnected...) or
failure to restore settings after hardware or software
" Parameter drifts - multiple parameters which are
continuously tracked and optimized during normal
operation which all need to be found and retuned
" Commissioning - hardware or software improvements
made during the shutdown which need to be tested,
Rather than trying to model recovery procedures in
detail, availSim simply assumes that the time it takes to
get good beam out of a region of the accelerator is
proportional to the time that region was without beam.
The constants of proportionality used for each region
were 10%, except for the DRs and interaction region, for
which 20% was used. In real operation, the beam quality
recovers gradually as each region is tuned up in
succession, and the luminosity gradually ramps up to
nominal. The simulation simplifies this by assuming that
the machine goes from no beam at the end of a region to
perfect beam at the end of the recovery time. Similarly,
the luminosity jumps from zero up to the design value
immediately at the end of the entire recovery/tuning time.
While this is certainly an oversimplification, if the
recovery time used in the simulation is considered to be
the time it takes to get back to half the design luminosity,
then the overall effect is reasonably well reproduced.
Machine Development (MD) is an essential tax on the
operating efficiency of any accelerator. It is time used to
better characterize the machine, develop new tuning
procedures, and test possible future improvements. The
amount of time spent on MD varies through the life of a
project, with more MD required in the early stages or
after a major upgrade. For this simulation, the ILC is
assumed to have operated for a few years and to have
settled into a nominal schedule of MD, which would
occupy approximately 10% of the time. As with the
recovery time, the MD was allocated to the individual
regions of the machine. Each region was allocated 1%
MD with the exception of the DRs, which were given 2%.
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Himel, T.; Nelson, J.; Phinney, N.; /SLAC; Ross, M. & /Fermilab. Availability and Reliability Issues for ILC, article, June 27, 2007; [Menlo Park, California]. (digital.library.unt.edu/ark:/67531/metadc878283/m1/2/: accessed January 16, 2019), University of North Texas Libraries, Digital Library, digital.library.unt.edu; crediting UNT Libraries Government Documents Department.