Detector integration of severe accident management instrumentation for robotic applications at nuclear reactor facilities

dc.contributor.advisorWaller, Edward
dc.contributor.authorNusrat, Omar
dc.date.accessioned2021-08-31T19:10:08Z
dc.date.accessioned2022-03-25T18:49:45Z
dc.date.available2021-08-31T19:10:08Z
dc.date.available2022-03-25T18:49:45Z
dc.date.issued2021-08-01
dc.degree.disciplineNuclear Engineering
dc.degree.levelMaster of Applied Science (MASc)
dc.description.abstractIn the aftermath of a nuclear accident, robots can be used to monitor and assess radiological contamination, preventing harmful exposure to plant personnel. In this work, several detectors were evaluated to be supplemented onto the Husky UGV. Specifically, the RadEye Gamma Survey Meter, the PurpleAir Air-Quality (PA) sensor, and the NaI(Tl) scintillator were examined and their measurement parameters optimized. Optimization was done to satisfy mitigation requirements outlined in regulatory severe accident management guidelines (SAMGs). A software component (Severe Accident Radioactivity Classification; SARC) was developed with the detector components, facilitating detector integration and analysis to aid emergency responders. For the RadEye, 20 seconds was determined to be the optimal collection time; the long term stability and short-term sensitivity of the PA was evaluated; and two spectra measured with the NaI(Tl) were examined. Future work involves further integration of SARC and the addition of advanced capabilities such as infrastructure damage detection.en
dc.description.sponsorshipUniversity of Ontario Institute of Technologyen
dc.identifier.urihttps://hdl.handle.net/10155/1328
dc.language.isoenen
dc.subjectRadiation detectionen
dc.subjectSevere accident managementen
dc.subjectAir samplingen
dc.subjectRoboticsen
dc.titleDetector integration of severe accident management instrumentation for robotic applications at nuclear reactor facilitiesen
dc.typeThesisen
thesis.degree.disciplineNuclear Engineering
thesis.degree.grantorUniversity of Ontario Institute of Technology
thesis.degree.nameMaster of Applied Science (MASc)

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