Bohunice Simulator Data Collection Project

Author(s):  
Ivan Cˇilli´k ◽  
Ja´n Procha´ska

The paper describes the way and results of human reliability data analysis collected as a part of the Bohunice Simulator Data Collection Project (BSDCP), which was performed by VUJE Trnava, Inc. with funding support from the U.S. DOE, National Nuclear Security Administration. The goal of the project was to create a methodology for simulator data collection and analysis to support activities in probabilistic safety assessment (PSA) and human reliability assessment for Jaslovske Bohunice nuclear power plant consisting of two sets of twin units: two VVER 440/V-230 (V1) and two VVER 440/V-213 (V2) reactors. During the project training of V-2 control room crews was performed at VUJE-Trnava simulator. The simulator training and the data collection were done in parallel. The main goal of BSDCP was to collect suitable data of human errors under simulated conditions requiring the use of symptom-based emergency operating procedures (SBEOPs). The subjects of the data collection were scenario progress time data, operator errors, and real-time technological parameters. The paper contains three main parts. The first part presents preparatory work and semi-automatic computer-based methods used to collect data and to check technological parameters in order to find hidden errors of operators, to be able to retrace the course of each scenario for purposes of further analysis, and to document the whole training process. The first part gives also an overview of collected data scope, human error taxonomy, and state classifications for SBEOP instructions coding. The second part describes analytical work undertaken to describe time distribution necessary for execution of various kinds of instructions performed by operators according to the classification for coding of SBEOP instructions. It also presents the methods used for determination of probability distribution for different operator errors. Results from the data evaluation are presented in the last part of the paper. An overview of observed human error probabilities (HEP) according to the developed taxonomy is given. HEP observed during training process were used as reference input data for HRA (Human Reliability Assesment) within existing PSAs performed by VUJE. Observing two different training seasons offered an opportunity to compare a progress achieved through the training process. This paper shows us how it is possible to make this kind of comparison in order to establish an objective measure of training quality and to determine training weaknesses. Results gained during the project-evoked interest of different NPPs (Nuclear Power Plant) in Slovak Republic to collect and process simulator data for further improvement of human factor safety, operational procedures, training process, etc.

Author(s):  
Ronald Boring ◽  
Thomas Ulrich ◽  
Roger Lew ◽  
Martin Rasmussen Skogstad

The authors have recently developed a microworld, a simplified process control simulator, to simulate a nuclear power plant. The microworld provides an environment that can be readily manipulated to gather data using a range of participants, from students to fully qualified operators. Because the microworld represents a simplified domain, it is possible to have more precise experimental control compared with the complex and confounding environment afforded by a full-scope simulator. In this paper, we discuss collecting human reliability data from a microworld. We review the generalizability of human error data from the microworld compared to other data sources like full-scope simulator studies and compare advantages and disadvantages of microworld simulator studies to support human reliability data collection needs.


1983 ◽  
Vol 27 (2) ◽  
pp. 170-174 ◽  
Author(s):  
A. N. Beare ◽  
R. E. Dorris

The purpose of this study was to empirically establish error rates for control selection and operation during proceduralized tasks in nuclear power plant control rooms. Data were collected in high fidelity simulators from licensed operators and students in the final stages of training prior to licensing by a Performance Measurement System (PMS) which recorded control manipulations and plant parameters. The PMS data were compared to a list of Procedural Task Elements (PTE) derived from the procedures used in responding to the casualties. Any action called for by the PTE list and not taken was considered an error of omission. A subject matter expert reviewed the PMS record of actions for errors in selection or operation of controls. The observed error rates (OERs) for commission errors were in close agreement with the human error probabilities (HEPs) given in NUREG/CR-1278. The omission OER was an order of magnitude higher than that given in NUREG/CR-1278. However, this number may be an artifact of the way simulator training is conducted, as the operators did not have the time to recover omitted actions that would be available in a real plant.


2019 ◽  
Vol 7 (2B) ◽  
Author(s):  
Vanderley Vasconcelos ◽  
Wellington Antonio Soares ◽  
Raissa Oliveira Marques ◽  
Silvério Ferreira Silva Jr ◽  
Amanda Laureano Raso

Non-destructive inspection (NDI) is one of the key elements in ensuring quality of engineering systems and their safe use. This inspection is a very complex task, during which the inspectors have to rely on their sensory, perceptual, cognitive, and motor skills. It requires high vigilance once it is often carried out on large components, over a long period of time, and in hostile environments and restriction of workplace. A successful NDI requires careful planning, choice of appropriate NDI methods and inspection procedures, as well as qualified and trained inspection personnel. A failure of NDI to detect critical defects in safety-related components of nuclear power plants, for instance, may lead to catastrophic consequences for workers, public and environment. Therefore, ensuring that NDI is reliable and capable of detecting all critical defects is of utmost importance. Despite increased use of automation in NDI, human inspectors, and thus human factors, still play an important role in NDI reliability. Human reliability is the probability of humans conducting specific tasks with satisfactory performance. Many techniques are suitable for modeling and analyzing human reliability in NDI of nuclear power plant components, such as FMEA (Failure Modes and Effects Analysis) and THERP (Technique for Human Error Rate Prediction). An example by using qualitative and quantitative assessesments with these two techniques to improve typical NDI of pipe segments of a core cooling system of a nuclear power plant, through acting on human factors issues, is presented.


Author(s):  
Shen Yang ◽  
Geng Bo ◽  
Li Dan

According to the research of nuclear power plant human error management, it is found that the traditional human error management are mainly based on the result of human behavior, the event as the point cut of management, there are some drawbacks. In this paper, based on the concept of the human performance management, establish the defensive human error management model, the innovation point is human behavior as the point cut, to reduce the human errors and accomplish a nip in the bud. Based on the model, on the one hand, combined with observation and coach card, to strengthen the human behavior standards expected while acquiring structured behavior data from the nuclear power plant production process; on the other hand, combined with root cause analysis method, obtained structured behavior data from the human factor event, thus forming a human behavior database that show the human performance state picture. According to the data of human behavior, by taking quantitative trending analysis method, the P control chart of observation item and the C control chart of human factor event is set up by Shewhart control chart, to achieve real-time monitoring of the process and result of behavior. At the same time, development Key Performance Indicators timely detection of the worsening trend of human behavior and organizational management. For the human behavior deviation and management issues, carry out the root cause analysis, to take appropriate corrective action or management improvement measures, so as to realize the defense of human error, reduce human factor event probability and improve the performance level of nuclear power plant.


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