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Grant: Alliance Grants

University of Waterloo

$120,000.00

Addressing Human Factors Challenges for Control Room Operators in Small Modular Reactors

EF 2023-24

Résumé
Small modular reactors (SMRs) are an emerging technology in the nuclear industry that may help meet the world's future energy needs. Human Factors (HF) design issues will arise due to technological innovations and operations. Operators may experience increased cognitive demands while monitoring several reactor units simultaneously from a central main control room (MCR) or remotely monitoring units. Automated procedures may reduce human error, but they may also lower operator awareness in cases where operators need to establish a suitable mental model of plant conditions. The primary human factors issues and research concerns for multi-unit operation are the impacts of switching tasks between units and from passive monitoring to the active control of operators' performance; workload, and vigilance dichotomy of prolonged monitoring when operators are more prone to boredom and errors, to overload due to concurrent failures on numerous units; MCR operations, particularly decision-aiding technology, on operators' performance. In this context, the proposed project aims to provide an adaptive and assistive AR interface that will intervene in real-time when high levels of workload or low levels of situation awareness (SA) are recognized in nuclear power plant operators, thereby assisting operators in limiting potential operator errors in decision-making. The expected outcomes will provide cutting-edge expertise and scientific data to improve government regulatory supervision of SMRs.
Programme
Alliance Grants
Emplacement
Ontario, Canada
Type de bénéficiaire
Academia
Type
Grant
Source
NSERC's Awards Data

Tel que publié

Application id
580479-2022
Name nom
Samuel, Siby SS
Department département
Systems Design Engineering
Organization id
33
Institution établissement
University of Waterloo
Province en
Ontario
Province fr
Ontario
Country en
CANADA
Country fr
CANADA
Fiscal year exercice financier
2023
Competition year année de concours
2022
Award amount
120000
Program id
ALLRP
Program name en
Alliance Grants
Program name fr
Subventions Alliance
Group en
RESEARCH PARTNERSHIPS
Group fr
PARTENARIATS DE RECHERCHE
Committee code
96
Committee name en
RPP Internal Decision Cttee
Committee name fr
Cté de décision interne - PPR
Area of application code
302
Area of application group en
Energy resources
Area of application group fr
Ressources d'énergie
Area of application en
Nuclear energy
Area of application fr
Énergie nucléaire
Research subject code
1600
Research subject group en
Industrial engineering
Research subject group fr
Industrial engineering
Research subject en
Génie industriel
Research subject fr
Génie industriel
Application title
Addressing Human Factors Challenges for Control Room Operators in Small Modular Reactors
Keyword
Control Rooms; Human Factors; Modeling; Operators; Prediction; Situation Awareness; Small Modular Reactors; Vigilance; Workload
Application summary
Small modular reactors (SMRs) are an emerging technology in the nuclear industry that may help meet the world's future energy needs. Human Factors (HF) design issues will arise due to technological innovations and operations. Operators may experience increased cognitive demands while monitoring several reactor units simultaneously from a central main control room (MCR) or remotely monitoring units. Automated procedures may reduce human error, but they may also lower operator awareness in cases where operators need to establish a suitable mental model of plant conditions. The primary human factors issues and research concerns for multi-unit operation are the impacts of switching tasks between units and from passive monitoring to the active control of operators' performance; workload, and vigilance dichotomy of prolonged monitoring when operators are more prone to boredom and errors, to overload due to concurrent failures on numerous units; MCR operations, particularly decision-aiding technology, on operators' performance. In this context, the proposed project aims to provide an adaptive and assistive AR interface that will intervene in real-time when high levels of workload or low levels of situation awareness (SA) are recognized in nuclear power plant operators, thereby assisting operators in limiting potential operator errors in decision-making. The expected outcomes will provide cutting-edge expertise and scientific data to improve government regulatory supervision of SMRs.