PSAM 16 - Session W13 Overview

PSAM 16 Conference Session W13 Overview

Session Chair: Ronald Boring (ronald.boring@inl.gov)

Paper 1 AG183

Lead Author: Agnieszka Tubis Co-author(s): Szymon Haładyn szymon.haladyn@pwr.edu.pl

Human error risk analysis in the cargo logistics process in the airport zone
Human errors are a common cause of disruptions in the logistics service process. In order to eliminate them, enterprises introduce automatic solutions to routine logistics operations. However, not in every system is it possible to automate the process of handling loads. Some operations still require human intervention, or the economic calculation does not justify using autonomous solutions. In these situations, it is necessary to implement solutions that will eliminate or reduce the impact of the human factor on the risk of adverse events. The article aims to analyze the risk of human errors in cargo logistics handling at the airport. Field tests were carried out at a selected airport. On their basis, the identification of adverse events and their analysis using qualitative and quantitative risk assessment methods were carried out. The assessment results made it possible to develop dedicated solutions to improve the crew's competencies with the use of Virtual Reality technology.

Human error risk analysis in the cargo logistics process in the airport zone

Human errors are a common cause of disruptions in the logistics service process. In order to eliminate them, enterprises introduce automatic solutions to routine logistics operations. However, not in every system is it possible to automate the process of handling loads. Some operations still require human intervention, or the economic calculation does not justify using autonomous solutions. In these situations, it is necessary to implement solutions that will eliminate or reduce the impact of the human factor on the risk of adverse events. The article aims to analyze the risk of human errors in cargo logistics handling at the airport. Field tests were carried out at a selected airport. On their basis, the identification of adverse events and their analysis using qualitative and quantitative risk assessment methods were carried out. The assessment results made it possible to develop dedicated solutions to improve the crew's competencies with the use of Virtual Reality technology.

Paper AG183 | Download the paper file. | Download the presentation PowerPoint file.

Name: Agnieszka Tubis (agnieszka.tubis@pwr.edu.pl)

Bio:

Country: ---
Company: Wroclaw University of Science and Technology
Job Title: University professor

Paper 2 GA178

Lead Author: Gayoung Park Co-author(s): Awwal M. Arigi, Seo-Ryong Koo, Jonghyun Kim

Dependency Analysis of Human Failures in Multi-Unit Scenarios: Types and Evaluation Method
Abstract: Dependency between human failure events (HFEs) is often analyzed as a part of the conventional human reliability analysis (HRA) process for nuclear power plants (NPPs). Many regulators suggested that the probabilistic risk assessment (PRA) should be included in the dependency between HFEs. In this study, we aim to investigate characteristics based on the results, performing dependencies on about 800 combinations in a multi-unit cutset. From 2017 to 2021, we participated in a project to develop a multi-unit PSA model for regulatory use. It was developed for nine nuclear power plants at the Kori site in Korea. We performed HEP quantification and dependency required in the PSA model and provided the results. This was analyzed using the multi-unit HFE dependency evaluation method. We developed a set of multi-units HFE dependency evaluation elements and their evaluation criteria based on the framework of the single-unit evaluation elements that have been utilized in the HRA practice for NPPs. The result of this work will be used to modify the recently developed multi-unit HFE dependency analysis method for qualitative analysis.

Dependency Analysis of Human Failures in Multi-Unit Scenarios: Types and Evaluation Method

Abstract: Dependency between human failure events (HFEs) is often analyzed as a part of the conventional human reliability analysis (HRA) process for nuclear power plants (NPPs). Many regulators suggested that the probabilistic risk assessment (PRA) should be included in the dependency between HFEs. In this study, we aim to investigate characteristics based on the results, performing dependencies on about 800 combinations in a multi-unit cutset. From 2017 to 2021, we participated in a project to develop a multi-unit PSA model for regulatory use. It was developed for nine nuclear power plants at the Kori site in Korea. We performed HEP quantification and dependency required in the PSA model and provided the results. This was analyzed using the multi-unit HFE dependency evaluation method. We developed a set of multi-units HFE dependency evaluation elements and their evaluation criteria based on the framework of the single-unit evaluation elements that have been utilized in the HRA practice for NPPs. The result of this work will be used to modify the recently developed multi-unit HFE dependency analysis method for qualitative analysis.

Paper GA178 | Download the paper file. | Download the presentation pdf file.

Name: Gayoung Park (gayoungpark@chosun.kr)

Bio: She is third years Ph.D. student. she work in the human engineering and risk analysis laboratory at the university of chosun. She is studying human engineering and human reliability analysis.

Country: KOR
Company: Chosun University
Job Title: Ph.D. student

Paper 3 JE124

Lead Author: Jeeyea Ahn Co-author(s): Jooyoung Park, jooyoung.park@inl.gov Ronald L. Boring, ronald.boring@inl.gov Thomas A. Ulrich, thomas.ulrich@inl.gov Yunyeong Heo, Yunyeong.Heo@inl.gov

The HUNTER Dynamic Human Reliability Analysis Tool: Graphical User Interface
The initial version of the Human Unimodel for Nuclear Technology to Enhance Reliability (HUNTER) simulation software implementation was a Python command line application. The model defining the scenario was manually constructed within input decks that were not user friendly. For the current version of HUNTER, a graphical user interface (GUI) was designed and developed to ease the model creation, editing, and simulation execution. The GUI supports creation and editing of the overall model and sub-model elements grouped under the three main simulation modules (individual, environment, task module). The GUI provides distinct interface sections with visual representations for each of these simulation modules. Visual representations of model objects and their visual arrangement within the modules clearly convey the underlying structure of the simulation code and ease model creation and editing. For example, what was input through the command line or a text editor in the past is now implemented as an intuitive and visualized interaction such as clicking a button or turning a toggle on and off so that analysts can focus on creating the model without having to contend with esoteric text files and their detail syntax requirements.

The HUNTER Dynamic Human Reliability Analysis Tool: Graphical User Interface

The initial version of the Human Unimodel for Nuclear Technology to Enhance Reliability (HUNTER) simulation software implementation was a Python command line application. The model defining the scenario was manually constructed within input decks that were not user friendly. For the current version of HUNTER, a graphical user interface (GUI) was designed and developed to ease the model creation, editing, and simulation execution. The GUI supports creation and editing of the overall model and sub-model elements grouped under the three main simulation modules (individual, environment, task module). The GUI provides distinct interface sections with visual representations for each of these simulation modules. Visual representations of model objects and their visual arrangement within the modules clearly convey the underlying structure of the simulation code and ease model creation and editing. For example, what was input through the command line or a text editor in the past is now implemented as an intuitive and visualized interaction such as clicking a button or turning a toggle on and off so that analysts can focus on creating the model without having to contend with esoteric text files and their detail syntax requirements.

Paper JE124 | Download the paper file. |

Name: Jeeyea Ahn (jeeya@unist.ac.kr)

Bio: I am a graduate student of the nuclear safety and HMI evolution lab (NuSAPHE: pronounced as nu-safe) at UNIST. I am interested in nuclear safety and human/organizational factors, and I am also interested in research in various fields to prevent accidents caused by human error in nuclear power plants. I am currently studying nuclear safety culture, which has been considered one of the important organizational factors.

Country: KOR
Company: Ulsan National Institute of Science and Technology
Job Title: Combined m.s.-ph.d. student (ph.d candidate)

Paper 4 JO68

Lead Author: Jooyoung Park Co-author(s): Ronald Boring, Ronald.Boring@inl.gov Thomas Ulrich, Thomas.Ulrich@inl.gov

An Approach to Dynamic Human Reliability Analysis using EMRALD Dynamic Risk Assessment Tool
Research for dynamic human reliability analysis (HRA) (a.k.a., simulation-based or computation-based HRA) has been required, as many researchers have emphasized the importance of dynamic approaches to probabilistic safety assessment (PSA). Transiting from static to dynamic HRA may be beneficial to realistically model and evaluate human actions as they would be performed in a system. In the static HRA, a human action is divided into human components like diagnosis and execution, then is quantified by summing the error probabilities of the components. However, this approach may miss the dynamic characteristic of the actual operation that operators continuously diagnose the given situation and execute proper actions based on procedures. Furthermore, the static HRA has estimated time availability for human actions based on structured interviews with knowledgeable experts like operators. It may be also challengeable to specifically evaluate if they can finish the actions by considering unexpected factors critical to the system safety. To treat these challenges, this study proposes an approach to dynamic HRA using the Event Modeling Risk Assessment using Linked Diagram (EMRALD) software, which is a dynamic risk assessment tool developed by Idaho National Laboratory. In this study, how to model human actions using the software and evaluate the error probabilities will be suggested. The applicability of this approach will be also investigated through an extended loss of AC power scenario. Then, major insights from this dynamic HRA approach against the static one will be discussed in the paper.

An Approach to Dynamic Human Reliability Analysis using EMRALD Dynamic Risk Assessment Tool

Research for dynamic human reliability analysis (HRA) (a.k.a., simulation-based or computation-based HRA) has been required, as many researchers have emphasized the importance of dynamic approaches to probabilistic safety assessment (PSA). Transiting from static to dynamic HRA may be beneficial to realistically model and evaluate human actions as they would be performed in a system. In the static HRA, a human action is divided into human components like diagnosis and execution, then is quantified by summing the error probabilities of the components. However, this approach may miss the dynamic characteristic of the actual operation that operators continuously diagnose the given situation and execute proper actions based on procedures. Furthermore, the static HRA has estimated time availability for human actions based on structured interviews with knowledgeable experts like operators. It may be also challengeable to specifically evaluate if they can finish the actions by considering unexpected factors critical to the system safety. To treat these challenges, this study proposes an approach to dynamic HRA using the Event Modeling Risk Assessment using Linked Diagram (EMRALD) software, which is a dynamic risk assessment tool developed by Idaho National Laboratory. In this study, how to model human actions using the software and evaluate the error probabilities will be suggested. The applicability of this approach will be also investigated through an extended loss of AC power scenario. Then, major insights from this dynamic HRA approach against the static one will be discussed in the paper.

Paper JO68 | Download the paper file. |

Name: Jooyoung Park (jooyoung.park@inl.gov)

Bio:

Country: USA
Company: Idaho National Laboratory
Job Title: Scientist