Model based, detailed fault analysis in the CERN PS complex equipment

In the CERN PS Complex of accelerators, about a thousand of equipment of various type (power converters, RF cavities, beam measurement devices, vacuum systems etc...) are controlled using the so-called Control Protocol, already described in previous Conferences. This Protocol, a model based equipment access standard, provides, amongst other facilities, a uniform and structured fault description and report feature. The faults are organized in categories, following their gravity, and are presented at two levels: the first level is global and identical for all devices, the second level is very detailed and adapted to the peculiarities of each single device. All the relevant information is provided by the equipment specialists and is appropriately stored in static and real time data bases; in this way a unique set of data driven application programs can always cope with existing and newly added equipment. Two classes of applications have been implemented, the first one is intended for control room alarm purposes, and the second one is oriented for specialists diagnostics. The system is completed by a fault history report facility permitting easy retrieval of faults previously occurred, for example during the night

Substorm-induced energetic electron precipitation:impact on atmospheric chemistry

Magnetospheric substorms drive energetic electron precipitation into the Earth's atmosphere. We use the output from a substorm model to describe electron precipitation forcing of the atmosphere during an active substorm period in April–May 2007. We provide the first estimate of substorm impact on the neutral composition of the polar middle atmosphere. Model simulations show that the enhanced ionization from a series of substorms leads to an estimated ozone loss of 5–50% in the mesospheric column depending on season. This is similar in scale to small to medium solar proton events (SPEs). This effect on polar ozone balance is potentially more important on long time scales (months to years) than the impulsive but sporadic (few SPE/year versus three to four substorms/day) effect of SPEs. Our results suggest that substorms should be considered an important source of energetic particle precipitation into the atmosphere and included in high-top chemistry-climate models

On the origin of high m magnetospheric waves

A survey of Advanced Rio-Imaging Experiment in Scandinavia data reveals evidence for a previously overlooked generation mechanism of high azimuthal wave number magnetospheric waves. Here we present observations of pulsating cosmic noise absorption with azimuthal wave numbers as high as 380, suggestive of precipitation modulation by magnetospheric waves. Dispersion relations of the small-scale precipitation pulsations are indicative of the proposed origin. Previous studies of magnetospheric waves, together with data from the Charge And Mass Magnetospheric Ion Composition Experiment (Magnetospheric Ion Composition Sensor) instrument aboard the Polar spacecraft, provide support for the theory

Electron flux models for different energies at geostationary orbit

Forecast models were derived for energetic electrons at all energy ranges sampled by the third-generation Geostationary Operational Environmental Satellites (GOES). These models were based on Multi-Input Single-Output Nonlinear Autoregressive Moving Average with Exogenous inputs methodologies. The model inputs include the solar wind velocity, density and pressure, the fraction of time that the interplanetary magnetic field (IMF) was southward, the IMF contribution of a solar wind-magnetosphere coupling function proposed by Boynton et al. (2011b), and the Dst index. As such, this study has deduced five new 1 h resolution models for the low-energy electrons measured by GOES (30–50 keV, 50–100 keV, 100–200 keV, 200–350 keV, and 350–600 keV) and extended the existing >800 keV and >2 MeV Geostationary Earth Orbit electron fluxes models to forecast at a 1 h resolution. All of these models were shown to provide accurate forecasts, with prediction efficiencies ranging between 66.9% and 82.3%