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Canberra NetCAM, Dynamic Radiation Source and CAM Alarm Modeling

LA-UR-12-24875. Canberra NetCAM, Dynamic Radiation Source and CAM Alarm Modeling . James T. Voss Jonathan A. Hudston Tom McLean RP-2 Group Los Alamos National Laboratory Los Alamos, NM, 87545. Presented at 2012 HPIC Meeting, UNM-LA, Los Alamos, NM September 24-26 2012.

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Canberra NetCAM, Dynamic Radiation Source and CAM Alarm Modeling

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  1. LA-UR-12-24875 Canberra NetCAM, Dynamic Radiation Source and CAM Alarm Modeling James T. Voss Jonathan A. Hudston Tom McLean RP-2 Group Los Alamos National Laboratory Los Alamos, NM, 87545 Presented at 2012 HPIC Meeting, UNM-LA, Los Alamos, NM September 24-26 2012

  2. Introduction: Outline • Introduction • Evaluation recap • Evaluation update • Suggested areas for future improvement • Current NetCAM performance • Alarm algorithms and set points • Alarm modeling • Dynamic radiation source testing • Conclusions

  3. Introduction • Canberra NetCAM evaluation began 9/2008 at LANL • Selected as candidate for continuous air monitor at the RLUOB facility • Perceived advantages of NetCAM dongle over ASM1000 • Cost ($3.5 K cheaper than ASM1000) • Networking capability (built-in web browser) • Peak-shape fitting algorithm included • Immediate problems found with: • Hardware • Firmware • User interface • Intra and Inter-communications • Documentation incomplete • Spent next 3.5 years resolving these issues

  4. Introduction • NetCAM dongle • Up to 8 CAM heads can be connected • but 1:1 configuration selected for RLUOB • RS-232 output to PC ( terminal emulator) console program • RJ-45 ethernet connections (unit has built-in web browser) • Remote monitoring using RadHawk (RadNet-compliant) listener • Has wireless capability too ( not used at LANL) • AS1700 CAM head • 1700 mm2 PIPs detector • Efficiency of ~32% for electroplated distributed 239Pu source • Flow rates ~ 2cfm • Original firmware: version 1.10 (now have 2.4)

  5. Canberra NetCAM • Panel PC functions as local display (runs embedded Win XP) • Dongle configuration • 2 RJ-45 ports • RS-485 (to CAM head) • RS-232 for console connection

  6. Recent issues and resolutions • Power supplies for Panel PC and NetCAM dongle not UL-listed • Also leakage voltage of >30v AC measured on dongle • Resolved using quality power supplies • Sigma-based DAC-h alarm limit not correctly calculated • Issue fixed by Canberra • Acute false alarm rate abnormally high • Issue identified through modeling of NetCAM performance (discussed later) • Issue fixed by Canberra

  7. Canberra NetCAM • Extensive list of required fixes satisfactorily completed earlier this year • Now offers reliable, robust operation • Able to automatically reboot to restore normal operation • Couples low detection limits with low false alarm probability • Acceptance test passed 7/2012 • Alarm response tests (acute and chronic) • Performance tests • Reliability tests • 54 NetCAM units delivered to RLUOB facility in 8/2012 • Additional 13 units purchased as spares

  8. Future NetCAM improvements • Revise calculation of sigma-based DAC-h alarm limit i.e. : • Net TRU counts = Gross counts – sum of tail contributions • Variance in Net counts = Gross counts + sum of tail contributions • Modify automatic energy calibration scheme • Currently too restrictive and unable to locate or track 7.69 MeV peak • Modify performance test algorithm • Currently takes >7 minutes whereas ASM1000 took ~ 2 minutes • Allow user to select chronic analysis update frequency • Currently fixed at 4 minute intervals

  9. NetCAM alarm algorithms: acute alarm • Acute alarm solely resides with the Alpha-Sentry CAM head • Based on a user-set count interval (6 - 60 seconds) • Counts in TRU region (2.8 - 5.8 MeV by default) and Rn region (5.8 - 6.0 MeV by default) summed • Alarm sounds if following conditions satisfied - the number of counts per channel in the TRU ROI is twice that of the Rn ROI - the number of TRU ROI counts exceeds the user-set minimum

  10. NetCAM acute alarm set points • Traditional LANL acute alarm set points; • 12 second count time • 80 or more TRU ROI counts required to generate an alarm • Default ROI boundaries used • Experience has shown that these settings adequately prevent false alarms but are they optimal ?

  11. Acute alarm optimization: Spreadsheet analysis tool

  12. Acute alarm optimization: Spreadsheet analysis tool

  13. Acute alarm optimization: Spreadsheet analysis tool

  14. Acute alarm optimization: Spreadsheet analysis tool

  15. Acute alarm: Calculated 239Pu DAC-h activity at TRU count rates corresponding to 1 false alarm per year per 60 NetCAMs * Assumptions: 2 cfm, 30% detection efficiency, DAC factor = 5E-12 μCi/cm3andenergy calibration is correct

  16. Acute alarm: Calculated 239Pu DAC-h activity corresponding to detection probabilities of 50% and 95% per count interval * Assumptions: 2 cfm, 30% detection efficiency, DAC factor = 5E-12 μCi/cm3

  17. Modeling of NetCAM alarm response • FORTRAN program written to simulate NetCAM performance • Code samples background and TRU spectral distributions specified by user • Respective total count rates independently set by user • Poisson stats used for number of bkg. and TRU counts and associated energies per 6 second update frequency • Both contributions are summed to form an integrated spectrum • Performs acute and chronic alarm (Valley mode) analysis under conditions specified by user • analysis frequency, ROI settings, cycle time, alarm set points, etc ….. • valley (tail-fitting) mode used for chronic analysis • Both true and blind man’s differential approaches are considered

  18. Acute alarm modeling vs spreadsheet predictions

  19. Acute alarm: Calculated average time-to-alarm as function of average 239Pu DAC-h activity

  20. NetCAM chronic alarm algorithms • Blindman’s differential approach used for NetCAM chronic analysis • Spectrum refreshed at end of each count cycle • Valley mode • Sequential exponential tail-fitting and subtraction of tail counts • Net counts in TRU ROI used to determine activity • recent improvements avoid non-physical net TRU cpm results • Uncertainty calculation incorrectly implemented by Canberra • grossly overestimates uncertainty in net counts • compensates by using a relatively small kσ factor • Alarm sounds when the fixed DAC-h limit and sigma-based limit are exceeded • an analysis every 4 minutes and at end of count cycle • Peaks mode • Not seriously considered as default analysis mode after some early problems

  21. Chronic alarm modeling

  22. NetCAM alarm modeling: conclusions • Code appears to emulate NetCAM behaviour well • Predictions are dependent on background spectrum and count rate • Current number of TRU counts required for an acute alarm appears to be too conservative • Valley analysis mode capable of 239Pu detection limits of 2 DAC-h with negligible false alarm rates based on available Rn/Tn background data • Count cycle times of about 12 minutes appear optimal • Alarm response time can be as good or even better than true differential approach if NetCAM algorithm allowed freedom to analyze data more frequently

  23. Dynamic radiation source • Problem: • Evaluation of CAM heads (sensitivity, time-to-alarm) • Currently dependent on radioactive aerosols • Time intensive, expensive and requires specialized facility • Solution: • Dynamic Radiation Source (DRS) • Mimics the challenge of plutonium aerosol detection

  24. Production DRS: Overhead view

  25. Introduction: Advantages of DRS • Provides non-specialized in-house testing • Low cost (~2K) versus ~10K per aerosol test • Multiple test scenarios with various CAMs • Reproducibility • Supports iterative development of CAM analysis algorithms • No contamination issues • Rn/Tn background spectrum also present

  26. DRS: Alpha Sentry/ASM1000 count rate variation

  27. DRS: Alpha Sentry / NetCAM dongle test data 15 minutes

  28. DRS: Alpha Sentry / NetCAM dongle test data

  29. DRS: Alpha Sentry / NetCAM dongle test data

  30. DRS: Alpha Sentry / NetCAM dongle test data

  31. DRS: Alpha Sentry / NetCAM dongle test data

  32. Result summary: Average time to alarm (2 DAC-h limit)

  33. Conclusions • Canberra NetCAM now capable of providing reliable operation and protecting workers • low alarm limits coupled with low false alarm probability • optimized alarm set points can be calculated using modeling • example of an ultimately successful collaboration between vendor and customer • Further beneficial improvements to NetCAM are readily achievable • DRS shown to be a useful tool in evaluating CAM chronic alarm algorithms • Empirical data lends support to the modeling predictions.

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