Development of Integrated Simulation System Seamaid for Human-Machine Interaction in Nuclear Power Plant: Its Practical Applications and Future Prospect

2001 ◽  
Vol 34 (16) ◽  
pp. 469-474
Author(s):  
Hidekazu Yoshikawa ◽  
Hiroshi Shimoda ◽  
Hirotake Ishii ◽  
Takashi Nakagawa ◽  
Wei Wu ◽  
...  
2020 ◽  
Vol 53 (5) ◽  
pp. 851-856
Author(s):  
Chuanzan Wang ◽  
Tao Huang ◽  
Aicheng Gong ◽  
Chao Lu ◽  
Rui Yang ◽  
...  

Author(s):  
Zhifei Yang ◽  
Xiaofei Xie ◽  
Xing Chen ◽  
Shishun Zhang ◽  
Yehong Liao ◽  
...  

It is reflected in the severe accident in Fukushima Daiichi that the emergency capacity of nuclear power plant needs to be enhanced. A nuclear plant simulator that can model the severe accident is the most effective means to promote this capacity. Until now, there is not a simulator which can model the severe accident in China. In order to enhance the emergency capacity in China, we focus on developing a full scope simulator that can model the severe accident and verify it in this study. The development of severe accident simulation system mainly includes three steps. Firstly, the integral severe accident code MELCOR is transplanted to the simulation platform. Secondly, the interface program must be developed to switch calculating code from RELAP5 code to MELCOR code automatically when meeting the severe accident conditions because the RELAP5 code can only simulate the nuclear power plant normal operation state and design basis accident but the severe accident. So RELAP5 code will be stopped when severe accident conditions happen and the current nuclear power plant state parameters of it should be transported to MELCOR code, and MELCOR code will run. Finally, the CPR1000 nuclear power plant MELCOR model is developed to analyze the nuclear power plant behavior in severe accident. After the three steps, the severe accident simulation system is tested by a scenario that is initiated by the station black out with reactor cooling pump seal leakage, HHSI, LHSI and auxiliary feed water system do not work. The simulation result is verified by qualitative analysis and comparison with the results in severe accident analysis report of the same NPP. More severe accident scenarios initiated by LBLOCA, MBLOCA, SBLOCA, SBO, ATWS, SGTR, MSLB will be tested in the future. The results show that the severe accident simulation system can model the severe accident correctly; it meets the demand of emergency capacity promotion.


2013 ◽  
Vol 421 ◽  
pp. 181-185
Author(s):  
Yan Li Qi ◽  
Yuan Xue ◽  
Tian Tian ◽  
Xing Jiang Chen ◽  
Xi Quan Fang

As the key equipment to ensure the stable operation of containment spray system in nuclear power plant, a RCC-M ejector with safe and credible performance is very important to make sure the containment integrality under lose of coolant accident (LOCA) or pipe broken. However, it was purchased from overseas supplier all along because of its special configuration, nonstandard design, severe safety level and small quantity demand. To implement equipment localization, and referring to practical applications of some nuclear plants, a RCC-M ejector is independently manufactured and tested, all performance could meet the requirement according to the test result. The RCC-M ejector is authenticated by experts by China Nuclear Energy Association, and the localization prototype research of this paper has great application and popularization value.


2013 ◽  
Vol 373-375 ◽  
pp. 1703-1709
Author(s):  
Jin Jin Xu ◽  
Zhong Wen ◽  
Kai Feng Zhang ◽  
Zheng Gang Guan ◽  
Chen Ye

In order to improve the effect of refueling training in nuclear power plant, the simulation system of refueling machine was designed and developed, combining the virtual reality technology with a real control console. The 3D virtual refueling environment of nuclear power plant was established by 3D modeling. Signals from touch screen and console are gathered by PLC and transmitted to PC graphics workstation, control the motion of virtual refueling machine, which realize the refueling operation simulation. The operation in failure modes was also realized in the system through the programming of failure database. The results show that the system runs normally and can simulate refueling operation in normal and abnormal modes, the training of refueling personnel is implemented effectively.


2021 ◽  
pp. 11-21
Author(s):  
Miki Sirola ◽  
John Einar Hulsund

In the Long-Term Degradation Management (LTDM) project we approach component ageing problems with data-analysis methods. It includes literature review about related work. We have used several data sources: water chemistry data from the Halden reactor, simulator data from the HAMBO simulator, and data from a local coffee machine instrumented with sensors. K-means clustering is used in cluster analysis of nuclear power plant data. A method for detecting trends in selected clusters is developed. Prognosis models are developed and tested. In our analysis ARIMA models and gamma processes are used. Such tasks as classification and time-series prediction are focused on. Methodologies are tested in experiments. The realization of practical applications is made with the Jupyter Notebook programming tool and Python 3 programming language. Failure rates and drifts from normal operating states can be the first symptoms of an approaching fault. The problem is to find data sources with enough transients and events to create prognostic models. Prognosis models for predicting possible developing ageing features in nuclear power plant data utilizing machine learning methods or closely related methods are demonstrated.


Author(s):  
Glen E. Schinzel

Today’s nuclear plant operator is challenged to safely operate a complex power plant while prudently managing the business aspects with efficiency. Risk insights provide a ready tool to aid today’s operators in effectively performing both of these sometimes contradictory tasks with a sound basis. While plants possess and maintain Probabilistic Risk Assessment (PRA) models, other regulatory applications are readily available to aid the nuclear operator. Some of these tools include 10CFR 50.69 Risk-informed Categorization and Treatment of Structures, Systems, and Components for Nuclear Power Reactors, Industry Initiative 4(b) Risk Managed Technical Specifications, and Industry Initiative 5(b) Risk-informed Surveillance Test Intervals. This paper will introduce each of these risk-informed tools and will discuss practical applications of these insights at the South Texas Project nuclear power plant. These insights are readily translatable to other nuclear power facilities. 10CFR 50.69 permits a risk-informed categorization of selected structures, systems, and components. For components determined to be Low Safety Significant, many of the current regulatory controls can be reduced while maintaining reasonable confidence that these ‘Low-ranked’ components continue to perform their design functional requirements. South Texas Project was the industry’s proto-type pilot for this effort. Initiative 4(b) is a risk-informed, configuration-based approach to managing Technical Specification allowed out of service times. The limiting, deterministic allowed outage times are replaced with a Configuration Risk Management Program which uses risk threshold values to determine the length of time a Technical Specification piece of equipment can remain out of service. An imposed back-stop of 30 days is used to limit the allowed outage time. This approach was approved for South Texas Project in July 2007, and South Texas Project was the industry pilot plant for this effort. Initiative 5(b) is a risk-informed approach to Technical Specification surveillance test intervals. This approach allows surveillance test intervals to be removed from Tech Specs and placed in an owner-controlled program. Once relocated, a blending of probabilistic and deterministic insights is used to assess proposed extensions of surveillance test intervals. Once implemented, a feedback process is relied upon to validate the acceptability of the revised testing interval. This approach was piloted by the Limerick Nuclear Station, and South Texas Project submitted a request in October 2007 to the NRC to pursue this initiative. The above risk insights have proven very effective at South Texas Project, and could aid other nuclear operators in making well-founded, informed decisions. Risk insights also allow a Station’s limited resources to be focused on those activities and equipment which are of greatest safety significance. These insights are valuable for current licensees, and may be very beneficial to apply toward new nuclear construction.


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