工作量
核电站
任务(项目管理)
计算机科学
可靠性工程
任务分析
核能
领域(数学分析)
事故管理
模拟
工程类
系统工程
数学
核工程
核物理学
数学分析
物理
操作系统
生物
生态学
作者
Yang Liu,Qin Gao,Man Wu
出处
期刊:Ergonomics
[Taylor & Francis]
日期:2022-05-24
卷期号:66 (2): 261-290
被引量:4
标识
DOI:10.1080/00140139.2022.2079727
摘要
Excessive mental workload reduces operators' performance and threatens the safety of nuclear power plants (NPPs) in severe accident management (SAM). Given the lack of suitable mental workload measurement methods for SAM tasks, we proposed a Domain- and Task-Analytic Workload (DTAW) method to predict SAM workload. The DTAW method is developed in three stages: scenario construction based on work domain analysis, task analysis, and workload estimation with eight workload components scored through task-analytic and projective methods. To demonstrate its utility, we applied the method to construct two SAM scenarios and predict the mental workload demand of operators in these scenarios as compared to two design basis accident scenarios. With statistical analysis, the DTAW method can predict the overall subjective workload rated by NPP operators, be used to identify high-load tasks, cluster tasks with similar workload patterns, and provide direct implications for improving SAM strategies and supporting systems.Practitioner summary: To predict mental workload in severe accident management (SAM) scenarios in nuclear power plants, we proposed an analytic method and applied it to estimate mental workload in two SAM scenarios and two design basis accident (DBA) scenarios. We found that the workload pattern in SAM scenarios is different from that in DBA scenarios.
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