scholarly journals STANDARD FORMAT AND CONTENT OF SAFETY ANALYSIS REPORTS FOR NUCLEAR POWER PLANTS (Revision 1).

1972 ◽  
Author(s):  
Keyword(s):  
Nuclear Power ◽  
Power Plants ◽  
Nuclear Power Plants ◽  
Safety Analysis ◽  
Standard Format

Canadian Nuclear Safety Commission: Readiness to Regulate SMRs in Canada

2011 ◽  
Author(s):  
S. Herstead ◽  
M. de Vos ◽  
S. Cook
Keyword(s):  
Nuclear Power ◽  
Power Plants ◽  
Nuclear Power Plants ◽  
Safety Analysis ◽  
Reactor Power ◽  
Nuclear Safety ◽  
Regulatory Framework ◽  
Nuclear Industry ◽  
Plant Design ◽  
Regulatory Documents

The success of any new build project is reliant upon all stakeholders — applicants, vendors, contractors and regulatory agencies — being ready to do their part. Over the past several years, the Canadian Nuclear Safety Commission (CNSC) has been working to ensure that it has the appropriate regulatory framework and internal processes in place for the timely and efficient licensing of all types of reactor, regardless of size. This effort has resulted in several new regulatory documents and internal processes including pre-project vendor design reviews. The CNSC’s general nuclear safety objective requires that nuclear facilities be designed and operated in a manner that will protect the health, safety and security of persons and the environment from unreasonable risk, and to implement Canada’s international commitments on the peaceful use of nuclear energy. To achieve this objective, the regulatory approach strikes a balance between pure performance-based regulation and prescriptive-based regulation. By utilizing this approach, CNSC seeks to ensure a regulatory environment exists that encourages innovation within the nuclear industry without compromising the high standards necessary for safety. The CNSC is applying a technology neutral approach as part of its continuing work to update its regulatory framework and achieve clarity of its requirements. A reactor power threshold of approximately 200 MW(th) has been chosen to distinguish between large and small reactors. It is recognized that some Small Modular Reactors (SMRs) will be larger than 200 MW(th), so a graded approach to achieving safety is still possible even though Nuclear Power Plant design and safety requirements will apply. Design requirements for large reactors are established through two main regulatory documents. These are RD-337 Design for New Nuclear Power Plants, and RD-310 Safety Analysis for Nuclear Power Plants. For reactors below 200 MW(th), the CNSC allows additional flexibility in the use of a graded approach to achieving safety in two new regulatory documents: RD-367 Design of Small Reactors and RD-308 Deterministic Safety Analysis for Small Reactors. The CNSC offers a pre-licensing vendor design review as an optional service for reactor facility designs. This review process is intended to provide early identification and resolution of potential regulatory or technical issues in the design process, particularly those that could result in significant changes to the design or analysis. The process aims to increase regulatory certainty and ultimately contribute to public safety. This paper outlines the CNSC’s expectations for applicant and vendor readiness and discusses the process for pre-licensing reviews which allows vendors and applicants to understand their readiness for licensing.

scholarly journals Analysis of Systems Thinking Safety by Artificial Intelligence (AI) Algorithm in South Korean Nuclear Power Plants (NPPs)

2021 ◽  
Vol 11 (10) ◽  
pp. 56-62
Author(s):  
Chang Hyun Baek ◽  
◽  
Kyung Bae Jang ◽  
Tae Ho Woo
Keyword(s):  
Artificial Intelligence ◽  
Nuclear Power ◽  
Power Plants ◽  
Nuclear Power Plants ◽  
Critical Factor ◽  
Safety Analysis ◽  
The Other ◽  
South Korean ◽  
Initial Stage ◽  
Relative Value

The artificial intelligence (AI) is applied to the safety analysis in the South Korean nuclear power plants (NPPs). The reinforcement learning (RL) is one of promising skills in the wise manipulations for the nuclear safety analysis where the reward is a critical factor to make the modelling. In the simulations, Y-axis means the relative value which shows the quantity of the accident possibility. The highest value is 4.0 in 46.25th year in which the values are increasing gradually. Otherwise, the values in the case with Agent gradually decrease. The highest value is near initial stage, which means the operation in NPPs is comparatively unstable. In the result, the values in the AI based controller graphs are higher than those of the other one. The RL algorithm is expressed by the Agent in this modelling, which is the most important factor in the AI-based operation in NPPs.

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