Deep-Sea Accident Risk Posture Assessment Based on a Variable-Weighted Five-Element Connection Number
Publication: ASCE-ASME Journal of Risk and Uncertainty in Engineering Systems, Part A: Civil Engineering
Volume 10, Issue 2
Abstract
The operation risks for deep-sea oil spill recovery are characterized by their multiplicity, fuzziness, and dynamic nature. To more properly and comprehensively assess the operational risks for deep-sea oil spill recovery, an assessment method has been proposed on the basis of combinatorial weighting and multi-element connection number. A full-domain risk assessment index system was built, which consists of four dimensions, namely personnel, equipment, management, and environment, and the combinatorial weighting was performed for the subjective and objective assessment indexes via the rough set improved analytical hierarchy process (AHP) and entropy method, respectively. Furthermore, in accordance with the set pair theory, the risk trend assessment model, built upon the multi-element connection number, was developed to comprehensively illustrate the current state of safety control and the developmental trajectory of these risk factors. Finally, a case study of oil spill recovery operations was carried out. Compared with the conventional methods, the proposed method delivers index weights more consistent with the actual situation, due to the applications of combinatorial weighting based on the improved AHP and entropy methods, as well as the multi-element connection number. The analysis showed that this method can deliver a thorough, scientific, and systematic assessment of the status quo. Therefore, the trend of risks and targeted management measures for key risk factors can be obtained.
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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
This paper was supported by High Tech Ship project of the Ministry of Industry and Information Technology (Grant No. MC-201902-C01 and CBZ2N21-2), and the National Natural Science Foundation of China (Grant No. 71901029).
References
Ai, B., M. X. Jia, H. W. Xu, J. L. Xu, Z. Wen, B. S. Li, and D. Zhang. 2021. “Coverage path planning for maritime search and rescue using reinforcement learning.” Ocean Eng. 241 (Dec): 110098. https://doi.org/10.1016/j.oceaneng.2021.110098.
Aysegul, B. S. 2023. “Considerations on assistance and rescue at sea in the light of the increasing autonomy in shipping.” Mar. Policy 153 (Jul): 105639. https://doi.org/10.1016/j.marpol.2023.105639.
Chen, H. W., X. Gao, J. Liu, X. Zhang, H. J. Liu, and J. W. Huang. 2013. “Study on water ecological security evaluation model based on multivariate connection number and Markov chain.” Adv. Mater. Res. 726 (Sep): 4000–4007. https://doi.org/10.4028/www.scientific.net/AMR.726-731.4000.
Chen, X. 2015. China’s maritime search and rescue emergency plan system improves countermeasures research. Beijing: China Academy of Transportation Science.
Ding, L., H. Hu, and J. Ji. 2023. “Holistic value-at-risk assessment framework for fire risk assessment of heritage buildings based on analytic hierarchy process and text mining.” ASCE-ASME J. Risk Uncertainty Eng. Syst. Part A: Civ. Eng. 9 (1): 04022059. https://doi.org/10.1061/AJRUA6.RUENG-968.
Ehsan, A., A. Rouzbeh, G. Vikram, B. Jonathan, and F. Khan. 2018. “An ecological risk assessment model for Arctic oil spills from a subsea pipeline.” Mar. Pollut. Bull. 135 (Oct): 1117–1127. https://doi.org/10.1016/j.marpolbul.2018.08.030.
Gao, P., S. M. Li, X. Zhao, and Y. Chen. 2023. “Application of the five element correlation number in the ship-bridge colision risk assessment in medium and large reservoirs a case study of the three gorges reservoir region.” J. Saf. Environ. 23 (10): 3419–3428. https://doi.org/10.13637/j.issn.1009-6094.2022.1339.
Hammouda, S., Z. Chen, C. An, and K. Lee. 2021. “Recent advances in developing cellulosic sorbent materials for oil spill cleanup: A state-of-the-art review.” J. Cleaner Prod. 311 (Aug): 127630. https://doi.org/10.1016/j.jclepro.2021.127630.
Helios, C., J. A. Ana, and Sonia Castanedo. 2020. “Deep oil spill hazard assessment based on spatio-temporal met-ocean patterns.” Mar. Pollut. Bull. 154 (May): 111123. https://doi.org/10.1016/j.marpolbul.2020.111123.
Hu, Q. G., X. Z. Tian, and Z. M. He. 2021. “Green construction safety risk assessment of analytical model based on quintuple correlation coefficient set.” J. Saf. Environ. 21 (5): 1880–1888. https://doi.org/10.13637/j.issn..
Juan, S. E., P. Ricardo, and C. G. Antonio. 2008. “Influence of the heavy fuel spill from the Prestige tanker wreckage in the overlying seawater column levels of copper, nickel and vanadium (NE Atlantic ocean).” J. Mar. Syst. 72 (1–4): 350–357. https://doi.org/10.1016/j.jmarsys.2006.12.005.
Lee, M., and J. Y. Jung. 2015. “Pollution risk assessment of oil spill accidents in Garorim Bay of Korea.” Mar. Pollut. Bull. 100 (1): 297–303. https://doi.org/10.1016/j.marpolbul.2015.08.037.
Li, L., Z. Liu, and X. Du. 2021. “Improvement of analytic hierarchy process based on grey correlation model and its engineering application.” ASCE-ASME J. Risk Uncertainty Eng. Syst. Part A: Civ. Eng. 7 (2): 04021007. https://doi.org/10.1061/AJRUA6.0001126.
Ma, Q. D., D. Z. Zhang, C. P. Wan, J. F. Zhang, and N. C. Lyu. 2022. “Multi-objective emergency resources allocation optimization for maritime search and rescue considering accident black-spots.” Ocean Eng. 261 (Oct): 112178. https://doi.org/10.1016/j.oceaneng.2022.112178.
Mahdinia, M., M. S. Yarandi, E. Jafarinia, and A. Soltanzadeh. 2021. “Development of a new technique for safety risk assessment in construction projects based on fuzzy analytic hierarchy process.” ASCE-ASME J. Risk Uncertainty Eng. Syst. Part A: Civ. Eng. 7 (3): 04021037. https://doi.org/10.1061/AJRUA6.0001157.
Nelson, J. R., T. H. Grubesic, L. Sim, and K. Rose. 2018. “A geospatial evaluation of oil spill impact potential on coastal tourism in the Gulf of Mexico.” Comput. Environ. Urban Syst. 68 (Mar): 26–36. https://doi.org/10.1016/j.compenvurbsys.2017.10.001.
Nevalainen, M., I. Helle, and J. Vanhatalo. 2018. “Estimating the acute impacts of Arctic marine oil spills using expert elicitation.” Mar. Pollut. Bull. 131 (Jun): 782–792. https://doi.org/10.1016/j.marpolbul.2018.04.076.
Payam, A. H., and R. Mohammad. 2018. “Probabilistic risk assessment of oil spill from offshore oil wells in Persian Gulf.” Mar. Pollut. Bull. 136 (Nov): 291–299. https://doi.org/10.1016/j.marpolbul.2018.07.068.
Rafael, M. P., E. Cecilia, and C. M. Appendini. 2021. “Rapid assessment tool for oil spill planning and contingencies.” Mar. Pollut. Bull. 166 (May): 112196. https://doi.org/10.1016/j.marpolbul.2021.112196.
Rawat, S. S., H. Dincer, and S. Yuksel. 2023. “A hybrid weighting method with a new score function for analyzing investment priorities in renewable energy.” Comput. Ind. Eng. 185 (Nov): 109692. https://doi.org/10.1016/j.cie.2023.109692.
Tao, Y., F. F. Shen, and M. L. Hu. 2012. “A dynamic evaluation model of university leading cadre based on multivariate delay connection number.” Kybernetes 41 (5/6): 703–713. https://doi.org/10.1108/03684921211243356.
Tian, R. Q., Q. L. Shao, and F. L. Wu. 2020. “Four-dimensional evaluation and forecasting of marine carrying capacity in China: Empirical analysis based on the entropy method and grey Verhulst model.” Mar. Pollut. Bull. 160 (Nov): 111675. https://doi.org/10.1016/j.marpolbul.2020.111675.
Wang, H., and H. Chen. 2013. “Analysis of the marine oil spill emergency guarantee ability assessment based on SEM[C].” In Proc., Third Int. Conf. on Intelligent System Design and Engineering Applications (ISDEA), 329–332. Hong Kong: IEEE Computer Society. https://doi.org/10.1109/ISDEA.2012.81.
Xiong, W., P. H. van Gelder, and K. W. Yang. 2020. “A decision support method for design and operationalization of search and rescue in maritime emergency.” Ocean Eng. 207 (Jul): 107399. https://doi.org/10.1016/j.oceaneng.2020.107399.
Xu, J., F. Jiang, Z. Xie, and G. Wang. 2023. “Risk assessment method for the safe operation of long-distance pipeline stations in high-consequence areas based on fault tree construction: Case study of China–Myanmar natural gas pipeline branch station.” ASCE-ASME J. Risk Uncertainty Eng. Syst. Part A: Civ. Eng. 9 (1): 05022003. https://doi.org/10.1061/AJRUA6.RUENG-960.
Yin, W. H., Z. Qu, and Y. R. Li. 2020. “Risk evaluating of oil spill pollution in submarine pipelines based on fuzzy comprehensive evaluation.” Ship Ocean Eng. 49 (2): 84–88. https://doi.org/10.3963/j.issn.1671-7953.2020.02.022.
Yuan, Z., H. M. Chen, P. Xie, P. F. Zhang, J. Liu, and T. R. Li. 2021. “Attribute reduction methods in fuzzy rough set theory: An overview, comparative experiments, and new directions.” Appl. Soft Comput. 107 (Aug): 107353. https://doi.org/10.1016/j.asoc.2021.107353.
Zhang, G. R., E. Y. Wang, C. L. Zhang, Z. H. Li, and D. M. Wang. 2022. “A comprehensive risk assessment method for coal and gas outburst in underground coal mines based on variable weight theory and uncertainty analysis.” Process Saf. Environ. Prot. 167 (Nov): 97–111. https://doi.org/10.1016/j.psep.2022.08.065.
Zhang, K., and X. J. Liu. 2018. “Evaluation on oil spill pollution level of offshore oil platform based on improved AHP and extension theory.” J. Shanghai Marit. Univ. 39 (1): 98–103. https://doi.org/10.13340/j.jsmu.2018..
Zhao, J. R., J. D. Tian, F. X. Meng, M. L. Zhang, and Q. Wu. 2022. “Safety assessment method for storage tank farm based on the combination of structure entropy weight method and cloud model.” J. Loss Prev. Process Ind. 75 (Feb): 104709. https://doi.org/10.1016/j.jlp.2021.104709.
Zhao, M. 2012. “Research on dynamic performance evaluation method for supply chain based on multi-factor connection number[C].” In Proc., 2012 IEEE Int. Conf. on Engineering Technology and Economic Management (ICETEM2012), 886–888. New York: IEEE.
Zhao, X., F. Liu, B. Fu, and N. Fang. 2016. “Reliability analysis of hybrid multi-carrier energy systems based on entropy-based Markov model.” Proc. Inst. Mech. Eng. Part O: J. Risk Reliab. 230 (6): 561–569. https://doi.org/10.1177/1748006X16663056.
Zhou, X., L. Cheng, K. F. Min, X. Y. Zuo, Z. J. Yan, X. G. Ruan, S. S. Chu, and M. C. Li. 2020. “A framework for assessing the capability of maritime search and rescue in the South China sea.” Int. J. Disaster Risk Reduct. 47 (Aug): 101568. https://doi.org/10.1016/j.ijdrr.2020.101568.
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ASCE-ASME Journal of Risk and Uncertainty in Engineering Systems, Part A: Civil Engineering
Volume 10 • Issue 2 • June 2024
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© 2024 American Society of Civil Engineers.
History
Received: Jun 26, 2023
Accepted: Dec 21, 2023
Published online: Apr 2, 2024
Published in print: Jun 1, 2024
Discussion open until: Sep 2, 2024
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