Reactor Facility Operational State Classification Using Gas Effluents and Radiation Measurements

Camila Ramirez; Nageswara S.V. Rao

doi:10.1109/NSSMIC.2018.8824384

Reactor Facility Operational State Classification Using Gas Effluents and Radiation Measurements

Camila Ramirez, Nageswara S.V. Rao

Autonomous and Complex Systems

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

1 Scopus citations

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
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	https://doi.org/10.1109/NSSMIC.2018.8824384
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

Conference

Conference	2018 IEEE Nuclear Science Symposium and Medical Imaging Conference, NSS/MIC 2018
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.

Funders	Funder number
U.S. Department of Energy
Oak Ridge National Laboratory

Access to Document

10.1109/NSSMIC.2018.8824384

Cite this

Ramirez, C., & Rao, N. S. V. (2018). Reactor Facility Operational State Classification Using Gas Effluents and Radiation Measurements. In 2018 IEEE Nuclear Science Symposium and Medical Imaging Conference, NSS/MIC 2018 - Proceedings Article 8824384 (2018 IEEE Nuclear Science Symposium and Medical Imaging Conference, NSS/MIC 2018 - Proceedings). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/NSSMIC.2018.8824384

Ramirez, Camila ; Rao, Nageswara S.V. / Reactor Facility Operational State Classification Using Gas Effluents and Radiation Measurements. 2018 IEEE Nuclear Science Symposium and Medical Imaging Conference, NSS/MIC 2018 - Proceedings. Institute of Electrical and Electronics Engineers Inc., 2018. (2018 IEEE Nuclear Science Symposium and Medical Imaging Conference, NSS/MIC 2018 - Proceedings).

@inproceedings{527ce62218ba4e3f9a22e72a8434512d,

title = "Reactor Facility Operational State Classification Using Gas Effluents and Radiation Measurements",

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.",

author = "Camila Ramirez and Rao, {Nageswara S.V.}",

note = "Publisher Copyright: {\textcopyright} 2018 IEEE.; 2018 IEEE Nuclear Science Symposium and Medical Imaging Conference, NSS/MIC 2018 ; Conference date: 10-11-2018 Through 17-11-2018",

year = "2018",

month = nov,

doi = "10.1109/NSSMIC.2018.8824384",

language = "English",

series = "2018 IEEE Nuclear Science Symposium and Medical Imaging Conference, NSS/MIC 2018 - Proceedings",

publisher = "Institute of Electrical and Electronics Engineers Inc.",

booktitle = "2018 IEEE Nuclear Science Symposium and Medical Imaging Conference, NSS/MIC 2018 - Proceedings",

}

Ramirez, C & Rao, NSV 2018, Reactor Facility Operational State Classification Using Gas Effluents and Radiation Measurements. in 2018 IEEE Nuclear Science Symposium and Medical Imaging Conference, NSS/MIC 2018 - Proceedings., 8824384, 2018 IEEE Nuclear Science Symposium and Medical Imaging Conference, NSS/MIC 2018 - Proceedings, Institute of Electrical and Electronics Engineers Inc., 2018 IEEE Nuclear Science Symposium and Medical Imaging Conference, NSS/MIC 2018, Sydney, Australia, 11/10/18. https://doi.org/10.1109/NSSMIC.2018.8824384

Reactor Facility Operational State Classification Using Gas Effluents and Radiation Measurements. / Ramirez, Camila; Rao, Nageswara S.V.
2018 IEEE Nuclear Science Symposium and Medical Imaging Conference, NSS/MIC 2018 - Proceedings. Institute of Electrical and Electronics Engineers Inc., 2018. 8824384 (2018 IEEE Nuclear Science Symposium and Medical Imaging Conference, NSS/MIC 2018 - Proceedings).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

TY - GEN

T1 - Reactor Facility Operational State Classification Using Gas Effluents and Radiation Measurements

AU - Ramirez, Camila

AU - Rao, Nageswara S.V.

PY - 2018/11

Y1 - 2018/11

N2 - 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.

AB - 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.

UR - http://www.scopus.com/inward/record.url?scp=85073104690&partnerID=8YFLogxK

U2 - 10.1109/NSSMIC.2018.8824384

DO - 10.1109/NSSMIC.2018.8824384

M3 - Conference contribution

AN - SCOPUS:85073104690

T3 - 2018 IEEE Nuclear Science Symposium and Medical Imaging Conference, NSS/MIC 2018 - Proceedings

BT - 2018 IEEE Nuclear Science Symposium and Medical Imaging Conference, NSS/MIC 2018 - Proceedings

PB - Institute of Electrical and Electronics Engineers Inc.

T2 - 2018 IEEE Nuclear Science Symposium and Medical Imaging Conference, NSS/MIC 2018

Y2 - 10 November 2018 through 17 November 2018

ER -

Ramirez C, Rao NSV. Reactor Facility Operational State Classification Using Gas Effluents and Radiation Measurements. In 2018 IEEE Nuclear Science Symposium and Medical Imaging Conference, NSS/MIC 2018 - Proceedings. Institute of Electrical and Electronics Engineers Inc. 2018. 8824384. (2018 IEEE Nuclear Science Symposium and Medical Imaging Conference, NSS/MIC 2018 - Proceedings). doi: 10.1109/NSSMIC.2018.8824384

Reactor Facility Operational State Classification Using Gas Effluents and Radiation Measurements

Abstract

Publication series

Conference

Funding

Access to Document

Other files and links

Fingerprint

Cite this