Large Loss Of Coolant Accidents Research Articles

Performance evaluation of a new signal processing system design to improve CANDU SDS1 trip response during large break LOCA events

ABSTRACTPerformance of a recently developed signal processing system for CANDU (Canada Deuterium Uraniu) reactor shutdown system 1 (SDS1) is evaluated in this paper. The evaluation is carried out in MATLAB/Simulink software environment as well as with an existing power measurement and signal processing system. The new signal processing algorithm is obtained based on the synthesis of several first order low pass filters with different delayed time constants. Throughout this paper, a special attention has been paid to compare the new signal processing system with the existing one. The dynamic behavior of the new signal processing system in the practical large loss of coolant accidents (LLOCA) events has also been examined. Simulation results show that during the LLOCA event, the reactor trip time, as well as the peak power, is decreased remarkably. Through the simulation studies, it has convincingly demonstrated that the new signal processing system has significant advantages over the existing system in terms of the improved trip response and accommodation of the spurious trip immunity. This advantage will significantly enhance the safety margin, or will bring economical benefits to nuclear power plants.

Lessons Learned from 21 Nuclear Plant Probabilistic Risk Assessments

In the short time that plant-specific, full-scope probabilistic risk assessments (PRAs) have been performed, extensive progress has been made in understanding and managing risk. After performing over 20 PRAs, one of the most impressive lessons learned is that quantitative risk management is tedious and hard work. It requires great attention to plant details and all the resources involved, including procedures, training, maintenance, quality control, staffing, engineering support, and, of course, a detailed knowledge of the plant, its systems, and the way they operate and interact with each other.It is clear that one of the greatest values of a comprehensive risk model is an increased understanding of the plant. Furthermore, that increased understanding is focused on the behavior of the plant under abnormal conditions. Those things important to risk are made visible and are prioritized. The basis exists to identify options for controlling risk in a systematic and logical way. The options can be evaluated not only in terms of the possible reduction in risk but also with respect to life-cycle costs and overall plant performance.One of the real challenges facing practitioners of quantitative risk assessment is to avoid undue emphasis on the numerical results. The numerical aspect of risk analysis should be viewed as a disciplining process, not as the end in itself The temptation to get into a “numbers game” is strong, and it should be resisted. The real emphases should be on exposing what is driving the risk and on taking specific actions to keep it under control; that is, the perspective ought to be one of risk management. Experience indicates that such an emphasis can result in enormous benefits. These results have impacted all aspects of nuclear plant safety, including training, regulatory compliance, preventive measures, maintenance prioritizing, spare parts, outage planning, and the basic decision-making process associated with power plant operations.The impact of plant-specific PRAs on traditional issues of safety has been major. Outstanding examples are large loss-of-coolant accidents (LOCAs), containment capacities, single-failure criteria, separate and independent safety trains, frontline safety system dependencies, system response requirements, system redundancy, the role of external events, and the role of selected support systems. Large LOCAs are not a major contributor to risk; most containment capacities greatly exceed their design basis; frontline safety systems are more dependent on support systems than previously believed; multiple failures are important contributors to risk; system response is sequence dependent; system redundancy is often not as important as system location and support system requirements; external events are often important contributors, especially to older plants; and support systems such as room ventilation are far more important to risk than perceived.Just as many lessons have been learned about nuclear plant risk through the application of quantitative risk assessment, there have also been many lessons learned about how to do risk assessments. Examples have to do with data handling, plant and system modeling, capturing the operator’s perspective, controlling the scope, transferring of technology, and achieving scrutability. There is still much room for improvement in all these and other areas. Yet, the progress toward real-time and continuous quantitative risk management has been extremely encouraging. The key is to have patience and not expect the process to be automatic.