Abstract
Inferring the operational state of a reactor facility, using measurements from an independent in-situ monitoring system, is critical to the assessment of its compliance to agreements. We consider the problem of inferring the on/off operational state of a facility by using gas effluents and radiation measurements collected at the reactor's off-gas ventilation stack and within its surrounding area. Effluent release concentrations of three noble gases, namely, Ar-41, Cs-138, and Xe-138, are collected inside the ventilation stack and provided every four hours. Gamma spectra is recorded every second by a radiation detector located about 100 meters offset from the stack, which is affected by weather and nearby conditions. We study classifiers based on the correlation coefficient (CC) method [1] applied to individual modalities and their combinations. We implement CC classifiers using ground truth measurements collected over 2 operational cycles of High Flux Isotope Reactor (HFIR) at Oak Ridge National Laboratory (ORNL) in year 2017.
| Original language | English |
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| Title of host publication | 2018 IEEE Nuclear Science Symposium and Medical Imaging Conference, NSS/MIC 2018 - Proceedings |
| Publisher | Institute of Electrical and Electronics Engineers Inc. |
| ISBN (Electronic) | 9781538684948 |
| DOIs | |
| State | Published - Nov 2018 |
| Event | 2018 IEEE Nuclear Science Symposium and Medical Imaging Conference, NSS/MIC 2018 - Sydney, Australia Duration: Nov 10 2018 → Nov 17 2018 |
Publication series
| Name | 2018 IEEE Nuclear Science Symposium and Medical Imaging Conference, NSS/MIC 2018 - Proceedings |
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Conference
| Conference | 2018 IEEE Nuclear Science Symposium and Medical Imaging Conference, NSS/MIC 2018 |
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| Country/Territory | Australia |
| City | Sydney |
| Period | 11/10/18 → 11/17/18 |
Funding
Figure 4. ROC plot of classifiers based on effluent and radiation modalities. V. CONCLUSION The operational-state classification problem for HFIR is complex, with multiple factors complicating the task, including, sharing of the stack with another facility, sub-optimal location of NaI detector, and lack of detector network. However, Ar-41 being a primary by-product of HFIR, is a good discriminator from the other facility’s activities. Future work includes identifying effective locations for NaI detectors, utilizing a network of such detectors located around the stack, and developing effective fusers to combine their measurements with multiple effluent measurements. ACKNOWLEDGMENT This work has been carried out at Oak Ridge National Laboratory managed by UTBattelle, LLC for U.S. Department of Energy under Contract No. DE-AC05-00OR22725. REFERENCES [1] C. Ramirez and N. S. V. Rao, “Facility on/off inference by fusing multiple effluence measurements,” in IEEE Nuclear Science Symposium, 2017.