Navigational Risk of Inland Water Transportation: A Case Study in the Songhua River, China
Publication: ASCE-ASME Journal of Risk and Uncertainty in Engineering Systems, Part A: Civil Engineering
Volume 9, Issue 4
Abstract
Compared with ocean transportation, inland waterway transportation (IWT) has issues such as a low configuration standard of navigation equipment, insufficient crew knowledge and skills, and the relatively more complex hydrographic environment of inland waterways. To recognize and quantify the risk of IWT, this study proposes a novel risk assessment method. Firstly, text mining by Python is applied to recognize the risk influential factors (RIFs) from marine accident investigation reports (MAIRs), and a risk evaluation hierarchy system is established. Secondly, a risk assessment model which integrates failure mode and effects analysis (FMEA), a belief rule-based Bayesian network (BRBN) and evidential reasoning (ER) is proposed to quantify the risk level of influential factors. Finally, a case study of the Songhua River was carried out to verify the feasibility and practicality of the established risk evaluation index system and research methods. The targeted preventive measures are proposed to improve the safety of IWT. This study shows that misobservation and poor safety awareness are the most important human factors affecting the safety of IWT, whereas the organizational factors have relatively low risk priority. It is suggested that stakeholders should strengthen the assessment of crew members and improve their ability to recognize hazards.
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Data Availability Statement
All data, models, or code that support the findings of this study are available from the corresponding author upon reasonable request.
Acknowledgments
The authors gratefully acknowledge support from the National Natural Science Foundation of China (Grant No. 52101399), Bolian Research Funds of Dalian Maritime University (Grant No. 3132023617), and the Fundamental Research Funds for the Central Universities (Grant No. 3132023138). This work also was supported by the EU H2020 ERC Consolidator Grant program (TRUST Grant No. 864724).
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Published In
ASCE-ASME Journal of Risk and Uncertainty in Engineering Systems, Part A: Civil Engineering
Volume 9 • Issue 4 • December 2023
Copyright
© 2023 American Society of Civil Engineers.
History
Received: Jun 17, 2023
Accepted: Aug 22, 2023
Published online: Oct 16, 2023
Published in print: Dec 1, 2023
Discussion open until: Mar 16, 2024
ASCE Technical Topics:
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- Bayesian analysis
- Business management
- Case studies
- Disaster risk management
- Engineering fundamentals
- Failure analysis
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- Methodology (by type)
- Navigation (waterway)
- Practice and Profession
- Public administration
- Public health and safety
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- River engineering
- Rivers and streams
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- Transportation engineering
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