Lab-Scale Design, Demonstration and Safety Assessment of an FPGA-Based Post Accident Monitoring System for Westinghouse AP1000 Nuclear Power Plants
Notice bibliographique
Résumé
A Field Programmable Gate Array (FPGA) is a type of integrated circuit (IC), which is programmed after it is manufactured. FPGAs are referred to as a form of programmable hardware, as there is typically no software or operating system running on the FPGA itself. A significant amount of design work has been performed regarding the application of FPGAs in the nuclear field in recent years, with much of that work centered around safety related Instrumentation and Control (I&C) systems and safety systems. These new FPGA based systems are considered to be viable alternatives to replace many old I&C systems that are commonly used in Nuclear Power Plants (NPPs). Many of these older analog and digital systems are obsolete, and it has become increasingly difficult to maintain and repair them. FPGAs possess certain advantages over traditional analog circuits, PLCs and microprocessors, when considering nuclear I&C and safety system applications. This paper describes how FPGA technology has been used to construct a lab-scale implementation of a Post-Accident Monitoring System (PAMS), for a Westinghouse AP1000 Nuclear Power Plant, using a National Instruments “cRIO” chassis and I/O modules. This system will perform the major functions of the existing PAMS, including monitoring the vital values such as temperature, water level, pressure, flow rate, radiation levels and neutron flux in the event of a serious reactor accident. These values are required in standards such as United States Nuclear Regulatory Commission (NRC), Canadian Nuclear Safety Commission (CNSC), International Electrotechnical Commission (IEC), and Institute of Electrical and Electronics Engineers (IEEE). All of the input signals are read and processed using the FPGA, which includes alarms if the values go beyond the specified range, or if the values change rapidly. The values were then output to the computer through the FPGA interface to provide information to the operator, as well as being sent through analog and digital output modules for further processing. The system was tested using both simulated and real inputs from sensors. Furthermore, the reliability of the new system has also been analyzed, using the Dynamic Flowgraph Methodology (DFM). DFM has been successfully applied in both the nuclear and aerospace fields, and has been described as one of the best methodologies for modeling software/hardware interactions, by the scientific literature as well as in NRC reports. DFM was applied to fine-tune the design parameters by determining the potential causes of faults in the design, as well as to highlight the effectiveness of DFM in nuclear and in FPGA applications.
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Prédiction distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,001 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».