Mechanical Engineering Research Works

Permanent URI for this collectionhttp://hdl.handle.net/1903/1661

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Causal Pathways Leading to Human Failure Events in Information-Gathering System Response Activities
(2023-07) Levine, Camille S; Al-Douri, Ahmad; Groth, Katrina M; Groth, Katrina M
Human Failure Events (HFEs) are complex, multi layer events culminating with a human machine team’s failure to complete a plant objective. HFEs can be further described by Crew Failure Modes CFMs which document specific ways the objective tasks may be un successfully performed. In turn, these CFMs are affected by Performance Influencing Factors (PIFs ), some of which exert a more direct influence than others. However, in current Human Reliability Analysis HRA methods, the multitude s of causal relationshi ps between PIFs, CFMs, and HFEs are not explicitly modeled. This work seeks to fill that gap by developing structured causal models that document direct and indirect pathways from PIFs, through CFMs, and into HFEs. This work is intended to expand the curre nt application of causal based HRA modeling beyond control room environments to external environments under natural hazard scenarios. A Bayesian network of information gathering operator activities in response to a system demand is developed by following the causal mapping methodology defined in Zwirglmaier et al. 2017 )). The relationships in this structure are substantiated with existing psychological and organizational literature, thereby allowing for the identification of the main causal pathways leadin g to a particular CFM, and therefore an HFE. The work draws upon proximate causes of failure from the NRC’s NUREG 2114 , CFMs in the Phoenix HRA method, and PIFs from Groth’s 2012 hierarchy. Capturing these causal pathways provides the foundation for an imp roved causal basis of HRA, which represents a promising strategy for enhancing the accuracy and technical basis of HRA. Future efforts will include validation of the structures, constructing similar models for decision
Identifying Human Failure Events (HFEs) for External Hazard Probabilistic Risk Assessment
(2022-06) Al-Douri, Ahmad; Levine, Camille S; Groth, Katrina M; Groth, Katrina M
In recent years, several advancements in nuclear power plant (NPP) probabilistic risk assessment (PRA) have been driven by increased understanding of external hazards, plant response, and uncertainties. However, major sources of uncertainty associated with external hazard PRA remain. One source discussed in this study is the close coupling of physical impacts on plants and overall plant risk under hazard events due to the significant human actions that are carried out to enable plant response and recovery from natural hazards events. This makes human reliability and human-plant interactions important elements in to consider in enhancing PRA to address external hazards. One of the challenges in considering human responses is that most existing human reliability analysis (HRA) models, such as SPAR-H and THERP, were not developed for assessing ex-control room actions and hazard response. To support this new scope for HRA, HRA models will need to be developed or modified to support identification of human activities, causal factors, and uncertainties inherent in external hazard response, thereby providing insights regarding event timing and physical event conditions as they relate to human performance. In this study, the first step of such work is performed by identifying human failure events (HFEs) for human response to flooding hazards. These HFEs are human actions or inactions that are involved in human response to flooding hazards and could contribute to the loss of a critical function for the plant in the scenario being examined. Several resources are used to identify these HFEs, including flooding reports from the Nuclear Regulatory Commission (e.g. NUREG/CR-7256: Effects of Environmental Conditions on Manual Actions for Flood Protection and Mitigation), interviews with experienced PRA and HRA analysts, and tabletop walkdowns of flooding scenarios with a project team. Also, task decomposition analyses using the cognitive-based Phoenix HRA model are also used to identify HFEs. This paper will discuss early results of these analyses.
Why Do Human-Machine Teams Fail: Investigating Failure Mechanisms in Human Reliability Analysis
(2023-07) Paglioni, Vincent P; Levine, Camille S; Al-Douri, Ahmad; Groth, Katrina M; Groth, Katrina M
Human Reliability Analysis (HRA), whether qualitative or quantitative, typically focuses on the how of “human failure.” For instance, the possible modes (Crew Failure Modes – CFMs) of failure define how a Major Crew Function (MCF) can be unsuccessfully performed by a crew of operators. The CFMs are typically associated with various Performance Influencing Factors (PIFs) that change the probability of occurrence (and thus, the probability of failing the MCF). However, the cognitive and/or physical pathways that result in a specific CFM (i.e., the question of why a failure occurs) are not often explicitly included in HRA methods. Even in Bayesian network (BN) models, these failure pathways are found implicitly (if at all) in the encoded causal relationships between the lower-level PIFs and higher-level CFMs. Our work posits that failure mechanisms may be revealed by cognitive-physical patterns underlying the presence of identified failure modes, i.e., specific sets of PIFs and/or subtasks (crew activity primitives – CAPs) specify failure mechanisms that can result in the failure mode. Our research reviews previous works that cover failure mechanisms in HRA and identifies possible failure mechanisms in tasks related to information gathering. We then extrapolate this finding to propose a definition for the failure mechanism in HRA and a preliminary procedure for identifying and modeling failure mechanisms in BN models.