The nature of the hazard connected with the large inventory of radioactive material in an operating nuclear power plant is significantly different from the safety challenge posed by other forms of electricity generation. The question of safety adequacy underlies basic decisions made by owners, regulators and the public in deciding whether or not to maintain or expand the role of nuclear energy in addressing future energy supply needs. Due to the historical evolution of the computational availability and to the development of new datasets and techniques, risk assessment experienced an evolution in its methods and accuracy. Classic approaches to safety assessment are still widely used in the nuclear industry and from regulatory bodies. In fact, risk assessment is an invaluable mean to take decisions concerning nuclear power plant design, operations and siting. The main risk assessment techniques are Deterministic Risk Assessment (DRA) and Probabilistic Risk Assessment. An integrated approach is called Computational Risk Assessment, where its major limitation is connected with the computational burden it requires. This work describes new methods for computational risk assessments in two main areas of the nuclear industry: design and operations. For the former, a new computational method to describe the transport of radioactive sources inside of the containment during a severe accident will be described and discussed in its mathematical framework for the application to the source term problem. For the latter, an Expert System for managing abnormal conditions will be presented, aiming to aid operators of a nuclear power plant for decision-making during delicate circumstances. Then, the Expert System will be applied to a case study involving the operations of a pressurizer during an in-surge transient and the outcomes will be compared with the ones deriving by the use of a PID system.
La natura del rischio associato alla presenza di materiale radioattivo in un impianto nucleare operativo è significativamente diversa da qualsiasi altra sfida di sicurezza posta da altre forme di generazione di elettricità. La domanda sull’adeguatezza della sicurezza diventa di capitale importanza per le decisioni sul mantenimento e sviluppo dell’energia nucleare per assolvere alle future richieste energetiche globali. L’analisi del rischio ha vissuto un’evoluzione nei metodi e nell’accuratezza grazie allo sviluppo di nuovi dati e alla disponibilità computazionale che ne permette un trattamento adeguato. Tuttavia, approcci classici sono ancora largamente utilizzati nell’industria nucleare e dagli enti regolatori. Infatti, l’analisi del rischio risulta essere uno strumento fondamentale per prendere decisioni in merito al design, alle operations e alla localizzazione di un impianto nucleare. Chiaramente, ciò comporta lo sviluppo di nuove tecniche per migliorare quelle attualmente esistenti. Le principali tecniche di analisi del rischio sono il “Deterministic Risk Assessment”, o analisi deterministica (DSA) e il “Probabilistic Risk Assessment”, o analisi probabilistica (PSA). Un approccio integrato è quello del “Computational Risk Assessment” (CRA), in cui il peso computazionale richiesto diventa di primaria importanza. Questo lavoro descrive nuovi metodi per il CRA nelle sue applicazioni per il design e le operations di un impianto nucleare. Nel primo caso, considerando il framework del PSA, viene descritto un nuovo metodo computazionale per il trasporto di fonti radioattive all’interno dell’edificio di contenimento durante un incidente severo e viene presentata una discussione matematica per la sua applicazione al problema del source term. Nel secondo caso, invece, viene proposto un Expert System per la gestione di condizioni anormali di funzionamento dell’impianto, con l’obiettivo di facilitare il compito degli operatori in dette circostanze. Infine, l’Expert System è stato studiato su un transitorio di tipo in-surge di un pressurizzatore ed, infine, le sue presentazioni sono comparate con quelle di un generico sistema PID.
Development and application of computational methods for risk assessment of nuclear power plants
DAMATO, MICHELE
2017/2018
Abstract
The nature of the hazard connected with the large inventory of radioactive material in an operating nuclear power plant is significantly different from the safety challenge posed by other forms of electricity generation. The question of safety adequacy underlies basic decisions made by owners, regulators and the public in deciding whether or not to maintain or expand the role of nuclear energy in addressing future energy supply needs. Due to the historical evolution of the computational availability and to the development of new datasets and techniques, risk assessment experienced an evolution in its methods and accuracy. Classic approaches to safety assessment are still widely used in the nuclear industry and from regulatory bodies. In fact, risk assessment is an invaluable mean to take decisions concerning nuclear power plant design, operations and siting. The main risk assessment techniques are Deterministic Risk Assessment (DRA) and Probabilistic Risk Assessment. An integrated approach is called Computational Risk Assessment, where its major limitation is connected with the computational burden it requires. This work describes new methods for computational risk assessments in two main areas of the nuclear industry: design and operations. For the former, a new computational method to describe the transport of radioactive sources inside of the containment during a severe accident will be described and discussed in its mathematical framework for the application to the source term problem. For the latter, an Expert System for managing abnormal conditions will be presented, aiming to aid operators of a nuclear power plant for decision-making during delicate circumstances. Then, the Expert System will be applied to a case study involving the operations of a pressurizer during an in-surge transient and the outcomes will be compared with the ones deriving by the use of a PID system.File | Dimensione | Formato | |
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https://hdl.handle.net/10589/139150