scholarly journals ATLAS Tile Calorimeter Conditions Database architecture and operations in Run 2

2020 ◽  
Vol 245 ◽  
pp. 02006
Author(s):  
Yuri Smirnov ◽  
Dhiman Chakraborty ◽  
Alexander Solodkov ◽  
Siarhei Harkusha
Keyword(s):  
Monte Carlo Simulation ◽  
Monte Carlo ◽  
Control System ◽  
Software Package ◽  
Atlas Detector ◽  
Calibration Data ◽  
Design And Implementation ◽  
Custom Made ◽  
Cool Conditions ◽  
Detector Control System

An overview of the Conditions Database (DB) structure for the hadronic Tile Calorimeter (TileCal), one of the sub-systems of the ATLAS detector at LHC, is presented. ATLAS Conditions DB stores the data on the ORACLE backend, and the design and implementation have been developed using the COOL (Conditions Objects for LCG) software package as a common persistency solution for the storage and management of the conditions data. TileCal conditions and calibration data are stored in 4 separate Databases, each with its own schema: TileCal Online and Offline DBs for data, DB for Monte Carlo simulation and Detector Control System (DCS) DB. In order to ensure smooth operation of the TileCal during data taking, experts perform the necessary calibrations, add the changes of detector status and other conditions data, prepare new conditions for data reprocessing and Monte Carlo production campaigns, and upload the new up-to-date information into DB using custom-made software tools. The procedure of TileCal conditions’ preparation, validation, uploading to DBs is described, and some DB-related statistics collected in Run 2 is presented.

scholarly journals Design and implementation of the ATLAS detector control system

2004 ◽  
Vol 51 (3) ◽  
pp. 495-501 ◽  
Author(s):  
H. Boterenbrood ◽  
H.J. Burckhart ◽  
J. Cook ◽  
V. Filimonov ◽  
B. Hallgren ◽  
...  
Keyword(s):  
Control System ◽  
Atlas Detector ◽  
Design And Implementation ◽  
Detector Control System

scholarly journals The Detector Control System for the magnetic field sensors in New Small Wheel phase I upgrade of ATLAS detector

2021 ◽  
Vol 2105 (1) ◽  
pp. 012026
Author(s):  
Stamatios Tzanos
Keyword(s):  
Magnetic Field ◽  
Control System ◽  
Hadron Collider ◽  
Atlas Detector ◽  
Magnetic Field Sensors ◽  
Atlas Experiment ◽  
Data Rates ◽  
Level 1 ◽  
The Magnetic Field ◽  
Detector Control System

Abstract In conjunction with the High Luminosity upgrade of the Large Hadron Collider accelerator at CERN, the ATLAS detector is also undergoing an upgrade to handle the significantly higher data rates. The muon end-cap system upgrade in ATLAS, lies with the replacement of the Small Wheel. The New Small Wheel (NSW) is expected to combine high tracking precision with upgraded information for the Level-1 trigger. To accomplish this, small Thin Gap Chamber (sTGC) and MicroMegas detector technologies are being deployed. Due to their installation location in ATLAS, the effects of Barrel Toroid and End-Cap Toroid magnets on NSW must be measured. For the final experiment at ATLAS, each sTGC large double wedge will be equipped with magnetic field Hall effect sensors to monitor the magnetic field near the NSW. The readout is done with an Embedded Local Monitor Board (ELMB) called MDT DCS Module (MDM). For the integration of this hardware in the experiment, first, a detector control system was developed to test the functionality of all sensors before their installation on the detectors. Subsequently, another detector control system was developed for the commissioning of the sensors. Finally, a detector control system based on the above two is under development for the expert panels of ATLAS experiment. In this paper, the sensor readout, the connectivity mapping and the detector control systems will be presented.

A simulation study of the Westgard multi-rule quality-control system for clinical laboratories

1990 ◽  
Vol 36 (3) ◽  
pp. 462-465 ◽  
Author(s):  
R Wood
Keyword(s):  
Monte Carlo Simulation ◽  
Quality Control ◽  
Monte Carlo ◽  
Control System ◽  
Simulation Study ◽  
Quality Control System ◽  
Power Curve ◽  
Clinical Laboratories

Abstract A particular version of the Westgard-Barry-Hunt-Groth (Westgard) multi-rule quality-control system is studied by Monte Carlo simulation. The principal focus is on the amount of distortion in the working power curve caused by skewness in the distribution of analyte measurements. The effect of using only the first two rejection modes of the Westgard system is also studied.

The back-end of the ATLAS detector control system

2008 ◽  
Author(s):  
S. Schlenker ◽  
H. J. Burckhart ◽  
J. Cook ◽  
V. Filimonov ◽  
S. Franz ◽  
...  
Keyword(s):  
Control System ◽  
Atlas Detector ◽  
Detector Control System

Design and implementation of the detector control system for the BESIII drift chamber cosmic ray test

2008 ◽  
Vol 32 (8) ◽  
pp. 649-652 ◽  
Author(s):  
Chen Xi-Hui ◽  
Xie Xiao-Xi ◽  
Li Xiao-Nan ◽  
Gao Cui-Shan ◽  
Zhang Yin-Hong ◽  
...  
Keyword(s):  
Control System ◽  
Cosmic Ray ◽  
Drift Chamber ◽  
Design And Implementation ◽  
Detector Control System

Modeling and Specification of Time-Limited Dispatch Categories for Commercial Aircraft

2008 ◽  
Vol 130 (2) ◽  
Author(s):  
D. R. Prescott ◽  
J. D. Andrews
Keyword(s):  
Monte Carlo Simulation ◽  
Monte Carlo ◽  
Control System ◽  
System Failure ◽  
Failure Rates ◽  
Simulation Approach ◽  
Commercial Aircraft ◽  
Modeling Systems ◽  
Certification Requirements ◽  
Reduced State

Time-limited dispatch allows the degraded redundancy dispatch of aircraft. Aircraft can be dispatched with certain control system faults and fault combinations for specified periods of time if the failure rates from those configurations meet certification requirements. The various system faults and fault combinations are assigned to dispatch categories according to these failure rates. This gives the dispatch criteria for the system. The overall failure rate of the system can then be calculated according to the dispatch criteria. Dispatch criteria are allocated to a small example system, and the system is subsequently modeled using a reduced-state Markov approach currently recommended in SAE ARP5107. An alternative method of setting dispatch criteria and modeling systems, using Monte Carlo simulation, is proposed in this paper, and this technique is also applied to the example system. Dispatch criteria applied to the different models are seen to differ, as are the system failure rates calculated using the different models. A method for setting the dispatch criteria for a system using a Monte Carlo simulation approach is introduced. The method is applied to a simple system, giving auditable results that exhibit the expected behavior for such a system. Because restrictive assumptions in the mathematics are unnecessary with Monte Carlo simulation, it is expected to give more accurate results in comparison to Markov approaches. Also, the results of the reduced-state Markov model appear to be largely dependent on failure rates, which are very difficult to determine.

scholarly journals Monte Carlo analysis of a control technique for a tunable white lighting system

2017 ◽  
Vol 50 (5) ◽  
pp. 716-728
Author(s):  
M Chakrabarti ◽  
A Thorseth ◽  
J Jepsen ◽  
D Dan-Corell ◽  
C Dam-Hansen
Keyword(s):  
Monte Carlo Simulation ◽  
Monte Carlo ◽  
Control System ◽  
System Performance ◽  
Control Mechanism ◽  
Light Output ◽  
Luminous Flux ◽  
Lookup Table ◽  
Control Technique ◽  
Lighting System

A simulated colour control mechanism for a multi-coloured LED lighting system is presented. The system achieves adjustable and stable white light output and allows for system-to-system reproducibility after application of the control mechanism. The control unit works using a pre-calibrated lookup table for an experimentally realized system, with a calibrated tristimulus colour sensor. A Monte Carlo simulation is used to examine the system performance concerning the variation of luminous flux and chromaticity of the light output. The inputs to the Monte Carlo simulation are variations of the LED peak wavelength, the LED rated luminous flux bin, the influence of the operating conditions, ambient temperature, driving current and the spectral response of the colour sensor. The system performance is investigated by evaluating the outputs from the Monte Carlo simulation. The outputs show that the applied control system yields an uncertainty on the luminous flux of 2.5% within a 95% coverage interval which is a significant reduction from the 8% of the uncontrolled system. A corresponding uncertainty reduction in Δu ′v ′ is achieved from an average of 0.0193 to 0.00125 within 95% coverage range after using the control system.

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