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The dynamic behaviour of Resistive Plate Chambers

The dynamic behaviour of Resistive Plate Chambers. Presented by Marcello Abbrescia University and INFN - Bari - Italy. VII Workshop on Resistive Plate Chambers and related detectors. Clermont-Ferrand FRANCE October 20-22, 2003. x sat. Exponential growth. Saturation. . “Drift”.

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The dynamic behaviour of Resistive Plate Chambers

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  1. The dynamic behaviour of Resistive Plate Chambers Presented by Marcello Abbrescia University and INFN - Bari - Italy VII Workshop on Resistive Plate Chambers and related detectors Clermont-Ferrand FRANCE October 20-22, 2003

  2. xsat Exponential growth Saturation  “Drift” Exponential growth Drift The story up to now Many quantities in the formula above are themselves stochasticvariables. The induced charge is the “convolution” of all these variables. A Monte Carlo rather elaborated RPC 2003 Clermont-Ferrand October 20th, 2003 Marcello Abbrescia - University of Bari

  3. When saturation does not play Charge Spectra shape: these are the most fundamental information you can get Freon rich mixture Gap: 9 mm Comparison between Monte-Carlo predictions and experimental data Gap: 2 mm Argon rich mixture : primary cluster density (from 3 to 5 cl/mm) : 1st Townsend “effective” coefficient RPC 2003 Clermont-Ferrand October 20th, 2003 Marcello Abbrescia - University of Bari

  4. ...and when saturation becomes important Simulation This is not a fit! Experiment HV=9.2 kV Gas mixture: C2H2F4/C4H10 97/3 + SF6 2% Input for simulation: Colucci et al., NIM A 425 (1999) 84-91 Experimental data from Camarri et al., NIM A 414 (1998) 317-324 RPC 2003 Clermont-Ferrand October 20th, 2003 Marcello Abbrescia - University of Bari

  5. Simulation Experiment HV=9.4 kV ...and when saturation becomes important This is not a fit! Gas mixture: C2H2F4/C4H10 97/3 + SF6 2% Input for simulation: Colucci et al., NIM A 425 (1999) 84-91 Experimental data from Camarri et al., NIM A 414 (1998) 317-324 RPC 2003 Clermont-Ferrand October 20th, 2003 Marcello Abbrescia - University of Bari

  6. Simulation Experiment HV=9.5 kV ...and when saturation becomes important This is not a fit! Inefficiency peak Saturation broad peak Gas mixture: C2H2F4/C4H10 97/3 + SF6 2% Input for simulation: Colucci et al., NIM A 425 (1999) 84-91 Experimental data from Camarri et al., NIM A 414 (1998) 317-324 RPC 2003 Clermont-Ferrand October 20th, 2003 Marcello Abbrescia - University of Bari

  7. Simulation Experiment HV=9.7 kV ...and when saturation becomes important This is not a fit! Saturation broad peak Inefficiency peak Gas mixture: C2H2F4/C4H10 97/3 + SF6 2% Input for simulation: Colucci et al., NIM A 425 (1999) 84-91 Experimental data from Camarri et al., NIM A 414 (1998) 317-324 RPC 2003 Clermont-Ferrand October 20th, 2003 Marcello Abbrescia - University of Bari

  8. Simulation Experiment HV=9.9 kV ...and when saturation becomes important This is not a fit! Saturation broad peak Inefficiency peak Gas mixture: C2H2F4/C4H10 97/3 + SF6 2% Input for simulation: Colucci et al., NIM A 425 (1999) 84-91 Experimental data from Camarri et al., NIM A 414 (1998) 317-324 RPC 2003 Clermont-Ferrand October 20th, 2003 Marcello Abbrescia - University of Bari

  9. Simulation Experiment HV=10.1 kV ...and when saturation becomes important This is not a fit! Saturation broad peak Inefficiency peak Gas mixture: C2H2F4/C4H10 97/3 + SF6 2% Input for simulation: Colucci et al., NIM A 425 (1999) 84-91 Experimental data from Camarri et al., NIM A 414 (1998) 317-324 RPC 2003 Clermont-Ferrand October 20th, 2003 Marcello Abbrescia - University of Bari

  10. Cg Cb Rb The “single cell” model None of the simulations up to now take into account the role of the bakelite resistivity ...we could be simulating metal or insulating electrodes  Recovery time independent of the cell dimension ... typical avalanche radius: 100 m typical avalanche charge: 1 pC typical external charge contained in 100 m: 10 pC A few numbers: RPC 2003 Clermont-Ferrand October 20th, 2003 Marcello Abbrescia - University of Bari

  11. High HV “at start” Big pulses What happens in the “single cell” =20 Hz Applied HV =1500 ms Area of the cell = 1 mm2 There is a sort of feedback ...   5  1011cm RPC 2003 Clermont-Ferrand October 20th, 2003 Marcello Abbrescia - University of Bari

  12. Effective HV vs. rate Applied HV 10 Hz The effective HV diminishes and its distribution is broader. 13 Hz 20 Hz (...until HVeff is too low) • Two consequences: • lower HV at high rate • greater HV variations at high rate RPC 2003 Clermont-Ferrand October 20th, 2003 Marcello Abbrescia - University of Bari

  13. Efficiency vs. rate Experiment  4  1010 cm Simulation  8  1010 cm From C. Bacci et al., NIM A 352(1995) 552-556 Cut-off rate of the experimental efficiency well simulated: slightly higher value of resistivity needed (significant?) RPC 2003 Clermont-Ferrand October 20th, 2003 Marcello Abbrescia - University of Bari

  14. Rate capability dependances  8  1010 cm  1011 cm HV=10100 V  4  1011 cm HV=9800 V HV=9600 V  1012 cm HV=9200 V  4  1011 cm HV=10100 V independent of applied voltage Cut-off rate True in the “single cell” model only strongly dependent on resistivity RPC 2003 Clermont-Ferrand October 20th, 2003 Marcello Abbrescia - University of Bari

  15. Rate capability in streamer mode  8  1010 cm Streamer charge distribution has been simulated also by “artificially” multiplying by 10 both avalanche charge, and area on the electrodes. Cut off rate reproduced also in the streamer case. Simulation streamer Exp. avalanche Efficiency rate dependance different. Exp. streamer From R. Arnaldi et al., NIM A 456(2000) 73-76 RPC 2003 Clermont-Ferrand October 20th, 2003 Marcello Abbrescia - University of Bari

  16. Efficiency vs. HV and rate Very good agreement ~ 2 Hz/cm2 At high rate the shape of the simulated efficiency curve seem to change and differ from the experimental one. ~ 1.5 kHz/cm2 Experimental Simulation Data from G. Aielli et al., NIM A 478(2002) 271-276 RPC 2003 Clermont-Ferrand October 20th, 2003 Marcello Abbrescia - University of Bari

  17. 1. Systematics on drift velocity 2. “Instrumental” effects not reproduced Possible Reasons Time resolution Data from C. Bacci et al., NIM A 352(1995) 552-556 Simulated Experimental 0.2 kHz/cm2 =0.9 ns 1 kHz/cm2 =1.2 ns 4 kHz/cm2 =1.6 ns General behaviour well reproduced ... Simulated time resolutions slightly less than experimental. RPC 2003 Clermont-Ferrand October 20th, 2003 Marcello Abbrescia - University of Bari

  18. Time delay and resolution vs. rate Time Delay Time resolution 4 ns 3.8 ns Experimental (arbitary zero) Experimental Simulation (absolute scale) Simulation The absolute scale of the simulation refers to the passage of the ionising particle. RPC 2003 Clermont-Ferrand October 20th, 2003 Marcello Abbrescia - University of Bari

  19. avalanche “small” “large” Cg Rs,b Cb Rb  The future: The multi cell model The area of the inefficiency cell increases as the bakelite surface resistivity decreases. The net results is that the current flows not only in the “central” cell, but also in the neighbouring ones. “Surface” coupling resistors RPC 2003 Clermont-Ferrand October 20th, 2003 Marcello Abbrescia - University of Bari

  20. Conclusions It is the first time the role of resistivityis taken into account in simulation of ResistivePlate Chambers ... The model of the dry water becomes wet. Even the single cell model reproduces well the efficiency and time resolution vs. rate. The role of resistivity and collected charge seems to be clear. Charge spectra are well understood. • Slight differences remain, both for the “static” and the “dynamic” case ... could be due to • uncertainty in gas (and other) parameters. • possible refinements of the model. RPC 2003 Clermont-Ferrand October 20th, 2003 Marcello Abbrescia - University of Bari

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