Risk and Uncertainty in Engineering Systems from the Perspective of Human Reliability
A special issue of Sustainability (ISSN 2071-1050). This special issue belongs to the section "Sustainable Engineering and Science".
Deadline for manuscript submissions: closed (30 June 2023) | Viewed by 237
Special Issue Editors
Interests: human reliability; probabilistic risk analysis; maritime safety; accident analysis; decision making
Special Issue Information
Dear Colleagues,
Despite the emergence of technological innovations in engineering systems, the effectiveness of the human element maintains its importance because it is seen as an important cause of potential negative consequences. Therefore, evaluating human performance is necessary. Human factors and risk are significantly interrelated. The human factor has a great impact on the emergence of potential risks. Thus, it must be taken into account in the analysis of potential risks.
Risk refers to potential losses resulting from hazards. Potential risks cause catastrophic consequences in terms of economic, environmental, and human life in critical engineering industries (such as aerospace, nuclear power, chemical, mining, railway, healthcare, and maritime industries). For this reason, it is of great importance to investigate the risk in engineering systems. In addition, there are many uncertainties in risk analysis processes, and uncertainties need to be included in the risk analysis process and undergo various improvements. In this direction, more consistent results are obtained. As a result, risk analyses should be carried out by using methods that take into account relations between modern technological systems and human elements.
This Special Issue focuses on developing risk analyses that consider uncertainties in terms of human reliability in engineering systems. We invite researchers to present their theoretical methods and numerical models.
Dr. Emre Akyuz
Prof. Dr. Ozcan Arslan
Guest Editors
Manuscript Submission Information
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Keywords
- human reliability
- risk analysis
- model and parameter uncertainties
- engineering judgment and expert opinions
- human factors
- safety risk assessment
