期刊：
Progress in Nuclear Energy,2022年144:104086 ISSN：0149-1970
通讯作者：
Pengcheng Li
作者机构：
[Luo, Zhuhua; Li, Pengcheng; Liu, Yahua; Dai, Licao] Univ South China, Sch Resources Environm & Safety Engn, Hengyang 421001, Hunan, Peoples R China.;[Jin, Xiao; Luo, Zhuhua; Li, Pengcheng; Liu, Yahua; Liu, Zhen; Dai, Licao] Univ South China, Human Factor Inst, Hengyang 421001, Hunan, Peoples R China.
通讯机构：
[Pengcheng Li] S;School of Resources, Environment and Safety Engineering, University of South China, Hengyang 421001, Hunan, People's Republic of China<&wdkj&>Human Factor Institute, University of South China, Hengyang 421001, Hunan, People's Republic of China
关键词：
Team situation awareness;Human reliability analysis;Dynamic Bayesian network;Digital nuclear power plants
摘要：
Team situation awareness (TSA) reliability is an important factor for team reliability. Moreover, situation awareness (SA) is a prominent problem in digital nuclear power plants (NPPs). Currently, since there is no suitable method to dynamically assess TSA reliability, we constructed a dynamical assessment method of TSA reliability based on a dynamic Bayesian network (DBN) to evaluate TSA reliability. First of all, a TSA causal concept model through qualitative analysis, expert group discussion and sample data analysis. On this basis, the quantitative assessment method of TSA reliability was constructed based on DBN and obtained probability distribution of variables. A standardized method was established to obtain the probability distribution of variables. Furthermore, we evaluated TSA dynamic reliability in a steam generator tube rupture (SGTR) accident. The results showed that the error probability of TSA decreased, and the level of TSA reliability continuously increased in SGTR. TSA reliability can be dynamically predicted by causal reasoning, the most important cause of TSA error could be identified by diagnostic reasoning, which provided theoretical support for the targeted prevention of human error. Finally, this established method was proved to be reasonable through sensitivity analysis.
作者机构：
[Li, Pengcheng; Zhang, Li; Li, Xiaofang; Dai, Licao] Univ South China, Human Factor Inst, Hengyang 421001, Hunan, Peoples R China.;[Li, Pengcheng] Univ N Carolina, Syst Engn & Engn Management, Charlotte, NC 28223 USA.;[Li, Pengcheng] Univ South China, Sch Nucl Sci & Technol, Hengyang 421001, Hunan, Peoples R China.
通讯机构：
[Dai, Licao] U;Univ South China, Human Factor Inst, Hengyang 421001, Hunan, Peoples R China.
关键词：
Model validation;Simulation experiment;SA reliability;Fuzzy logic-AHP;Digital nuclear power plants
摘要：
Situation awareness (SA) reliability of operators is an important component of human reliability analysis (HRA) in digital nuclear power plants (NPPs). Therefore, how to identify effectively and reliably the risk of SA errors is of great significance for SA error prevention and risk reduction. SA reliability assessment model or method based on fuzzy logic and analytic hierarchy process (AHP) is forwarded in the first paper. In order to prove its effectiveness and reliability, sensitivity analysis and simulator experiments are applied to testify our model in this paper. The results show that the proposed assessment model of SA reliability has a certain degree of sensitivity as well as an accuracy of prediction, and there are a strong correlation and consistency between the predicted value from fuzzy inference system and the real value (or observed value) from simulator experiments. Although there are some differences between the predicted value and the real value based on the perspective of HRA, the model can be used to predict SA error probability or SA reliability within the range of 10 error factors as well as provide data and theoretical support for SA reliability assessment.
作者机构：
[Li, Pengcheng; Zhang, Li; Li, Xiaofang; Dai, Licao] Univ South China, Human Factor Inst, Hengyang 421001, Hunan, Peoples R China.;[Li, Pengcheng] Univ N Carolina, Syst Engn & Engn Management, Charlotte, NC 28223 USA.;[Li, Pengcheng] Univ South China, Sch Nucl Sci & Technol, Hengyang 421001, Hunan, Peoples R China.;[Zou, Yanhua] Hunan Inst Technol, Inst Human Factor & Safety Management, Hengyang 421002, Hunan, Peoples R China.
通讯机构：
[Li, Pengcheng] U;Univ South China, Human Factor Inst, Hengyang 421001, Hunan, Peoples R China.
关键词：
Situation awareness reliability;Fuzzy logic;Analytic hierarchy process;Digital nuclear power plants
摘要：
In digital control rooms, situation awareness (SA) reliability has become an important element affecting operator's reliability. In order to establish a more reasonable assessment method of SA reliability under the condition of very lack of data, based on the established influential factor model of SA reliability considering the causality relationship of performance shaping factors (PSFs) in this paper, a fuzzy logic and analytic hierarchy process (AHP)-based method is established to more objectively assess SA reliability. The weight of PSFs is identified using AHP, and a fuzzy logic method is used to simulate the fuzzy assessment and reasoning process of operator's SA reliability, and a standardized method is built to determine the fuzzy rule base of fuzzy reasoning system for SA reliability assessment for reducing the subjectivity and uncertainty of expert judgment. Finally, an example is provided to illustrate the specific application of the proposed method. The results show that the established method takes account of the weight of PSFs and their causal influencing relationship, and the fuzzy logic method used to assess SA reliability can overcome the subjectivity and uncertainty of expert judgment, which makes the assessment results more objective and realistic. Furthermore, the method can be used to get more SA error data and have a wide range of application value.
期刊：
Fuzzy Sets and Systems,2016年293(C):127-143 ISSN：0165-0114
通讯作者：
Li, Peng-cheng
作者机构：
[Chen, Wei; Li, Peng-cheng; Zhao, Ming; Zhang, Li; Dai, Li-cao] Univ South China, Human Factor Inst, Hengyang 421001, Hunan, Peoples R China.;[Li, Peng-cheng; Chen, Guo-hua] S China Univ Technol, Inst Safety Sci & Engn, Guangzhou 510641, Guangdong, Peoples R China.;[Dai, Li-cao] Cent S Univ, Sch Info Phys & Geomat Engn, Changsha 410083, Hunan, Peoples R China.;[Chen, Wei] Hunan Univ, Sch Business Adm, Changsha 410082, Hunan, Peoples R China.
通讯机构：
[Li, Peng-cheng] U;Univ South China, Human Factor Inst, Hengyang 421001, Hunan, Peoples R China.
关键词：
ASEPaccident sequence evaluation programBHEPbasic human error probabilityCHEPconditional human error probabilityCPCcommon performance conditionCREAMcognitive reliability and error analysis methodDTdecision treeDependencyDigital control systemFuzzy logicHEARThuman error assessment and reduction techniqueHEPhuman error probabilityHFEshuman failure eventsHRAhuman reliability analysisHSIhuman-system interfaceHuman factorHuman reliability analysisI&Cinstrumentation and controlMCRsmain control roomsNPPsnuclear power plantsPSAprobabilistic safety assessmentROreactor operatorSGTRsteam generator single tube ruptureSPAR-Hstandardized plant analysis risk-human reliability analysis methodSROsenior reactor operatorSTAshift technical advisorTHERPtechnique for human error rate predictionTOturbine operatorVDUvideo display unit
摘要：
In a digital control system, the dependency model between the actions of operators differs from that in a conventional control room because information sharing and the main control room (MCR) operations are team operations. Dependencies between the actions of operators are more common in a digital control system compared with a conventional control room because operators share the same information and MCR operations are directed by team decisions. Therefore, assessing the dependencies between operators is an important aspect of human reliability analysis. In this study, we use a fuzzy logic-based approach to evaluate the dependencies among the actions of operators in the present study. First, the factors that influence the dependency levels among the actions of operators are identified by analyzing the characteristic human factors in a digital control system and an analytical model of the dependencies is then constructed. Second, a method for analyzing the dependencies between the actions of operators is established based on a fuzzy logic approach. This method can simulate vague and uncertain knowledge, but it also provides a clear explanation of the origins of results and their reasoning process by tracing the steps in reasoning. Therefore, traceability and repeatability are characteristics of the proposed method. Third, we present a case study to demonstrate the proposed approach. Finally, we demonstrate that the results obtained are reasonable and that the established model is stable based on validations that involve data comparisons and a sensitivity analysis of the model. In a digital control system, the dependency model between the actions of operators differs from that in a conventional control room because information sharing and the main control room (MCR) operations are team operations. Dependencies between the actions of operators are more common in a digital control system compared with a conventional control room because operators share the same information and MCR operations are directed by team decisions. Therefore, assessing the dependencies between operators is an important aspect of human reliability analysis. In this study, we use a fuzzy logic-based approach to evaluate the dependencies among the actions of operators in the present study. First, the factors that influence the dependency levels among the actions of operators are identified by analyzing the characteristic human factors in a digital control system and an analytical model of the dependencies is then constructed. Second, a method for analyzing the dependencies between the actions of operators is established based on a fuzzy logic approach. This method can simulate vague and uncertain knowledge, but it also provides a clear explanation of the origins of results and their reasoning process by tracing the steps in reasoning. Therefore, traceability and repeatability are characteristics of the proposed method. Third, we present a case study to demonstrate the proposed approach. Finally, we demonstrate that the results obtained are reasonable and that the established model is stable based on validations that involve data comparisons and a sensitivity analysis of the model.
期刊：
Mathematical Problems in Engineering,2015年2015:1-14 ISSN：1024-123X
通讯作者：
Zou, Qingming
作者机构：
[Zou, Qingming] Univ South China, Sch Econ & Management, Changsha 421001, Hunan, Peoples R China.;[Ye, Guangyu] S China Univ Technol, Sch Business Adm, Guangzhou 510640, Guangdong, Peoples R China.
通讯机构：
[Zou, Qingming] U;Univ South China, Sch Econ & Management, Changsha 421001, Hunan, Peoples R China.
关键词：
digital main control room;cognitive reliability;human factors issues;human errors;bayesian network
摘要：
Currently, there is a trend in nuclear power plants (NPPs) toward introducing digital and computer technologies into main control rooms (MCRs). Safe generation of electric power in NPPs requires reliable performance of cognitive tasks such as fault detection, diagnosis, and response planning. The digitalization of MCRs has dramatically changed the whole operating environment, and the ways operators interact with the plant systems. If the design and implementation of the digital technology is incompatible with operators' cognitive characteristics, it may have negative effects on operators' cognitive reliability. Firstly, on the basis of three essential prerequisites for successful cognitive tasks, a causal model is constructed to reveal the typical human performance issues arising from digitalization. The cognitive mechanisms which they impact cognitive reliability are analyzed in detail. Then, Bayesian inference is used to quantify and prioritize the influences of these factors. It suggests that interface management and unbalanced workload distribution have more significant impacts on operators' cognitive reliability.
摘要：
In the system reliability and safety assessment, the focuses are not only the risks caused by hardware or software, but also the risks caused by "human error". There are uncertainties in the traditional human error risk assessment (e.g. HECA) due to the uncertainties and imprecisions in Human Error Probability (HEP), Error-Effect Probability (EEP) and Error Consequence Severity (ECS). While fuzzy logic can deal with uncertainty and imprecision. It is an efficient tool for solving problems where knowledge uncertainty may occur. The purpose of this paper is to develop a new Fuzzy Human Error Risk Assessment Methodology (FHERAM) for determining Human Error Risk Importance (HERI) as a function of HEP, EEP and ECS. The modeling technique is based on the concept of fuzzy logic, which offers a convenient way of representing the relationships between the inputs (i.e. HEP, EEP, and ECS) and outputs (i.e. HERI) of a risk assessment system in the form of IF THEN rules. It is implemented on fuzzy logic toolbox of MATLAB using Mamdani techniques. A case example is presented to demonstrate the proposed approach. Results show that the method is more realistic than the traditional ones, and it is practicable and valuable. (C) 2010 Elsevier Ltd. All rights reserved.
关键词：
Group decision support;uncertainty;analytic network process;group Fuzzy ANP;aggregation;site remedial countermeasures
摘要：
Handling uncertainty in decision making is recently receiving considerable attention by researchers. Advances in group Fuzzy analytic network process (ANP) are discussed to support decision making because of the complexity and vagueness under uncertainty. An adaptive group Fuzzy ANP group decision support system (DSS) under uncertainty is put forth that makes up for some deficiencies in the conventional ANP. Fuzzy judgments are firstly used when it is difficult to characterize the uncertainty by point-valued judgments due to partially known information, and a bipartite graph is formulated to model the problem of group decision making under uncertainty. Then, a Fuzzy prioritization method is proposed to derive the local priorities from missing or inconsistent Fuzzy pairwise comparison judgments. As a result of the unlikeliness for all the decision makers to evaluate all elements under uncertainty, an original aggregation method is developed to cope with the situation where some of the local priorities are missing. Finally, an evaluation of petroleum contaminated site remedial countermeasures using the proposed group Fuzzy ANP, indicates that the presented group DSS can effectively handle uncertainty and support group decision making with high level of user satisfaction.
作者机构：
[Wang, S] Chinese Acad Sci, Inst Syst Sci, Acad Math & Syst Sci, Beijing 100080, Peoples R China.;Nanhua Univ, Sch Econ & Management, Hengyang 421001, Peoples R China.
通讯机构：
[Wang, S] C;Chinese Acad Sci, Inst Syst Sci, Acad Math & Syst Sci, Beijing 100080, Peoples R China.
摘要：
The effects of Japanese yen's depreciation on Chinese exports in 2002 (only considering the exports of the Mainland of China) are analysed. An AR(2) valuation function for the Chinese exports is constructed. The results on sensitivity tests show that the depreciation of Japanese yen would not bring severe effects on the Chinese exports in 2002, though the increasing trend of Chinese exports would become slower.
