An analytic model for situation assessment of nuclear power plant operators based on Bayesian inference

2006 ◽  
Vol 91 (3) ◽  
pp. 270-282 ◽  
Author(s):  
Man Cheol Kim ◽  
Poong Hyun Seong
Author(s):  
Emilie M. Roth

An empirical study was conducted examining operator performance in cognitively demanding simulated nuclear power plant emergencies. During emergencies operators follow highly prescriptive written procedures. The objectives of the study were to understand and document what role higher-level cognitive activities such as diagnosis, or more generally ‘situation assessment,’ play in guiding operator performance, given that operators utilize procedures in responding to the events. The study examined crew performance in two simulated emergencies. Up to 11 crews from each of two plants participated in two simulated emergencies for a total of 38 cases analyzed. Crew performance was videotaped and partial transcripts were produced and analyzed. The results revealed a number of instances where higher-level cognitive activities such as situation assessment and response planning enabled operators to handle aspects of the situation that were not fully addressed by the procedures. This paper describes these cases and discusses their implications for the design of computer-based support systems.


2020 ◽  
Vol 39 (5) ◽  
pp. 6339-6350
Author(s):  
Esra Çakır ◽  
Ziya Ulukan

Due to the increase in energy demand, many countries suffer from energy poverty because of insufficient and expensive energy supply. Plans to use alternative power like nuclear power for electricity generation are being revived among developing countries. Decisions for installation of power plants need to be based on careful assessment of future energy supply and demand, economic and financial implications and requirements for technology transfer. Since the problem involves many vague parameters, a fuzzy model should be an appropriate approach for dealing with this problem. This study develops a Fuzzy Multi-Objective Linear Programming (FMOLP) model for solving the nuclear power plant installation problem in fuzzy environment. FMOLP approach is recommended for cases where the objective functions are imprecise and can only be stated within a certain threshold level. The proposed model attempts to minimize total duration time, total cost and maximize the total crash time of the installation project. By using FMOLP, the weighted additive technique can also be applied in order to transform the model into Fuzzy Multiple Weighted-Objective Linear Programming (FMWOLP) to control the objective values such that all decision makers target on each criterion can be met. The optimum solution with the achievement level for both of the models (FMOLP and FMWOLP) are compared with each other. FMWOLP results in better performance as the overall degree of satisfaction depends on the weight given to the objective functions. A numerical example demonstrates the feasibility of applying the proposed models to nuclear power plant installation problem.


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