SBIR-STTR Award

This Phase I research project is to develop a nuclear powerplant accident management advisor system (AMAS). AMAS is designed to assist the operators of a plant experiencing accident conditions. It will help them in (1) diagnosing the plant state, (2) managing the event sequences (3) controlling the phenomena that may anse as a result of the accident and affect plant systems. Although the knowledge base necessary for the application of AMAS to nuclear powerplants must be developed based on the phenomenology of nuclear plant accident scenarios, the general conceptual framework and reasoning algorithms of AMAS may also be of interest for other types of process plant applications. Given the complex nature of the accident phenomenology and the uncertainty associated with instrumentation readings available under accident conditions, the AMAS approach focuses specifically on the problems of identifying plant states and the effects of operator actions, while utilizing the uncertain inputs from plant sensors and the uncertain knowledge of plant system responses to the accident.Anticipated Results/Potential Commercial Applications as described by the awardee:The ultimate goal of this research is to develop AMAS that uses special techniques to combine instrument information and to reduce the uncertainty associated with accident management assessment and decision-making in nuclear powerplants. If successfully developed, AMAS could find wide application in the electric utility industry, with substantial benefits expected in terms of the potential economic impacts of accidents and in terms of greater public safety.

___(NOTE: Note: no official Abstract exists of this Phase II projects. Abstract is modified by idi from relevant Phase I data. The specific Phase II work statement and objectives may differ)___ This Phase I research project is to develop a nuclear powerplant accident management advisor system (AMAS). AMAS is designed to assist the operators of a plant experiencing accident conditions. It will help them in (1) diagnosing the plant state, (2) managing the event sequences (3) controlling the phenomena that may anse as a result of the accident and affect plant systems. Although the knowledge base necessary for the application of AMAS to nuclear powerplants must be developed based on the phenomenology of nuclear plant accident scenarios, the general conceptual framework and reasoning algorithms of AMAS may also be of interest for other types of process plant applications. Given the complex nature of the accident phenomenology and the uncertainty associated with instrumentation readings available under accident conditions, the AMAS approach focuses specifically on the problems of identifying plant states and the effects of operator actions, while utilizing the uncertain inputs from plant sensors and the uncertain knowledge of plant system responses to the accident.Anticipated Results/Potential Commercial Applications as described by the awardee:The ultimate goal of this research is to develop AMAS that uses special techniques to combine instrument information and to reduce the uncertainty associated with accident management assessment and decision-making in nuclear powerplants. If successfully developed, AMAS could find wide application in the electric utility industry, with substantial benefits expected in terms of the potential economic impacts of accidents and in terms of greater public safety.