Field Of Human Reliability Analysis Research Articles

Study on dynamic evolution of operators’ behavior in digital nuclear power plant main control room – Part I: Qualitative analysis

Digitalization is a trend in large-scale complex systems such as nuclear power plants (NPPs). It changes the way main control room (MCR) operators interact with systems. Many studies shows that the adoption of digital technology has brought some new risks for MCR operators, and whether the reliability of these technologies can meet safety and economic requirements has become one of the urgent problems that NPPs must solve. The study consists of two parts. In Part I, we investigated the dynamic evolution of operators’ four behaviors: monitoring and detection (MD), situation assessment (SA), response planning (RP), and response implementation (RI). This paper incorporates Boolean network (BN) analysis into the field of human reliability analysis (HRA), by applying semi-tensor product of matrix (STP), whereby the dynamics evolution of operators’ behavior can be expressed in an algebraic form. Utilizing this algebraic representation, a BN analysis model is proposed, on which we based a qualitative analysis. An illustrative example is given to show how to construct the BN model via experimental data. We also discuss the advantage of the proposed methodology, its feasibility and highlighting the future work remaining.

Phoenix – A model-based Human Reliability Analysis methodology: Qualitative Analysis Procedure

Phoenix method is an attempt to address various issues in the field of Human Reliability Analysis (HRA). Built on a cognitive human response model, Phoenix incorporates strong elements of current HRA good practices, leverages lessons learned from empirical studies, and takes advantage of the best features of existing and emerging HRA methods. Its original framework was introduced in previous publications. This paper reports on the completed methodology, summarizing the steps and techniques of its qualitative analysis phase. The methodology introduces the “Crew Response Tree” which provides a structure for capturing the context associated with Human Failure Events (HFEs), including errors of omission and commission. It also uses a team-centered version of the Information, Decision and Action cognitive model and “macro-cognitive” abstractions of crew behavior, as well as relevant findings from cognitive psychology literature and operating experience, to identify potential causes of failures and influencing factors during procedure-driven and knowledge-supported crew-plant interactions. The result is the set of identified HFEs and likely scenarios leading to each. The methodology itself is generic in the sense that it is compatible with various quantification methods, and can be adapted for use across different environments including nuclear, oil and gas, aerospace, aviation, and healthcare.

Two techniques of sensitivity and uncertainty analysis of fuzzy expert systems

Problems characterized by qualitative uncertainty described by expert judgments can be addressed by the fuzzy logic modeling paradigm, structured within a so-called fuzzy expert system (FES) to handle and propagate the qualitative, linguistic assessments by the experts. Once constructed, the FES model should be verified to make sure that it represents correctly the experts’ knowledge. For FES verification, typically there is not enough data to support and compare directly the expert- and FES-inferred solutions. Thus, there is the necessity to develop indirect methods for determining whether the expert system model provides a proper representation of the expert knowledge. A possible way to proceed is to examine the importance of the different input factors in determining the output of the FES model and to verify whether it is in agreement with the expert conceptualization of the model. In this view, two sensitivity and uncertainty analysis techniques applicable to generic FES models are proposed in this paper with the objective of providing appropriate tools of verification in support of the experts in the FES design phase. To analyze the insights gained by using the proposed techniques, a case study concerning a FES developed in the field of human reliability analysis has been considered.

Quantitative analysis of ATM safety issues using retrospective accident data: The dynamic risk modelling project

The “dynamic risk modelling project” was a research activity aimed at developing a simulation approach able to provide a quantitative analysis of some critical activities of air traffic control (ATC) operators considering the organizational context in which they take place, the main cognitive processes underneath, and the possibility to inform the analysis using retrospective accident data. The pilot study presented in the present paper is aimed at providing an overview of possible opportunities related to the use of a cognitive simulator within the Eurocontrol framework called ConOps (which is a detailed description of future operational concept for air traffic in Europe). The approach chosen within the field of HRA (Human Reliability Analysis) made use of a cognitive simulator developed within the Department of Industrial Engineering in Politecnico di Milano. The simulator was built based on an Information Processing Level very much compatible with the one embedded in a method used by Eurocontrol for collecting accident data named HERA. Thanks to this similarity the pilot application was able to modify the calibration process of the simulator and make use of the retrospective accident data that was available in Eurocontrol collected using the HERA classification scheme. The resulting approach can interact with standard risk assessment methodologies in order to analyze the criticalities arising from human performance in the ATC working contexts in the light of past experience.

Error mode prediction

The study of accidents (‘human errors’) has been dominated by efforts to develop ‘error’ taxonomies and ‘error’ models that enable the retrospective identification of likely causes. In the field of Human Reliability Analysis (HRA) there is, however, a significant practical need for methods that can predict the occurrence of erroneous actions— qualitatively and quantitatively. The present experiment tested an approach for qualitative performance prediction based on the Cognitive Reliability and Error Analysis Method (CREAM). Predictions of possible erroneous actions were made for operators using different types of alarm systems. The data were collected as part of a large-scale experiment using professional nuclear power plant operators in a full scope simulator. The analysis showed that the predictions were correct in more than 70% of the cases, and also that the coverage of the predictions depended critically on the comprehensiveness of the preceding task analysis.

Human-centered modeling in human reliability analysis: some trends based on case studies

As an informal working group of researchers from France, Germany and The Netherlands created in 1993, the EARTH association is investigating significant subjects in the field of human reliability analysis (HRA). Our initial review of cases from nuclear operating experience showed that decision-based unrequired actions (DUA) contribute to risk significantly on the one hand. On the other hand, our evaluation of current HRA methods showed that these methods do not cover such actions adequately. Especially, practice-oriented guidelines for their predictive identification are lacking. We assumed that a basic cause for such difficulties was that these methods actually use a limited representation of the stimulus-organism-response (SOR) paradigm. We proposed a human-centered model, which better highlights the active role of the operators and the importance of their culture, attitudes and goals. This orientation was encouraged by our review of current HRA research activities. We therefore decided to envisage progress by identifying cognitive tendencies in the context of operating and simulator experience. For this purpose, advanced approaches for retrospective event analysis were discussed. Some orientations for improvements were proposed. By analyzing cases, various cognitive tendencies were identified, together with useful information about their context. Some of them match psychological findings already published in the literature, some of them are not covered adequately by the literature that we reviewed. Finally, this exploratory study shows that contextual and case-illustrated findings about cognitive tendencies provide useful help for the predictive identification of DUA in HRA. More research should be carried out to complement our findings and elaborate more detailed and systematic guidelines for using them in HRA studies.

The phenotype of erroneous actions

The study of human actions with unwanted consequences, in this paper referred to as human erroneous actions, generally suffers from inadequate operational taxonomies. The main reason for this is the lack of a clear distinction between manifestations and causes. The failure to make this distinction is due to the reliance on subjective evidence which unavoidably mixes manifestations and causes. The paper proposes a clear distinction between the phenotypes (manifestations) and the genotypes (causes) of erroneous actions. A logical set of phenotypes is developed and compared with the established "human error" taxonomies as well as with the operational categories which have been developed in the field of human reliability analysis. The principles for applying the set of phenotypes as practical classification criteria are developed and described. A further illustration is given by the report of an action monitoring system (RESQ) which has been implemented as part of a larger set of operator support systems and which shows the viability of the concepts. The paper concludes by discussing the principal issues of error detection, in particular the trade-off between precision and meaningfulness.

Another view of the state of human reliability analysis (HRA)

Abstract This note discusses the author's view of the guest editorial by E. M. Dougherty, Jr. This author considers that HRA exhibits the normal progression of science in which breakthroughs are infrequent. Progress has been made in the field of HRA and has been due to the efforts of persons such as Swain, Rasmussen, Wreathall and others. This note tries to clarify the underlying concepts of the human cognitive reliability (HCR) correlation and answer some of the misconceptions about HCR given in the guest editorial. Additionally, the note touches on the usefulness of simulator results for calculation and estimation for HRA purposes. The note draws attention to the fact that the methods advanced in EPRI NP-6560 are not the same as those in NUREG/CR-4550. Finally, the note calls for the organization of a meeting for the various specialists to discuss their HRA approaches in front of their peers.