Gaidai multivariate risk assessment method for cargo ship dynamics

References

• Abioye, O., Dulebenets, M., Kavoosi, M., Pasha, J., & Theophilus, O. (2021). Vessel schedule recovery in Liner shipping: Modeling alternative recovery options. IEEE Transactions on Intelligent Transportation Systems, 22(10), 6420–21. https://doi.org/10.1109/TITS.2020.2992120
   Web of Science ®Google Scholar
• Andersen, I. M. V., & Jensen, J. J. (2014). Measurements in a container ship of wave induced deck panel girder stresses in excess of design values. Marine Structures, 37, 54–85. https://doi.org/10.1016/j.marstruc.2014.02.006
   Web of Science ®Google Scholar
• Balakrishna, R., Gaidai, O., Wang, F., Xing, Y., & Wang, S. (2022). A novel design approach for estimation of extreme load responses of a 10-MW floating semi-submersible type wind turbine. Ocean Engineering, 261, 112007. https://doi.org/10.1016/j.oceaneng.2022.112007
   Web of Science ®Google Scholar
• Bicen, S., Kandemir, C., & Celik, M. (2021). A human risk assessment analysis to crankshaft overhauling in dry-docking of a General cargo ship. Proceedings of the Institution of Mechanical Engineers Part M: Journal of Engineering for the Maritime Environment, 235(1), 93–109. https://doi.org/10.1177/1475090220948338
   Web of Science ®Google Scholar
• Bureau Veritas, B. V. (2012). NR 493, classification of mooring systems for permanent offshore units.
   Google Scholar
• Chen, X., Yan, R., Shining, W., Zhiyuan, L., Haoyu, M., & Wang, S. (2021). A fleet deployment model to minimize the covering time of maritime rescue missions. Maritime Policy & Management, 50(6), 724–749. https://doi.org/10.1080/03088839.2021.2017042
   Web of Science ®Google Scholar
• DNV-RP-C205. (2010). Environmental conditions and environmental loads.
   Google Scholar
• DNV-RP-H103. (2011). Modelling and analysis of marine operations.
   Google Scholar
• Drummen, I., Storhaug, G. , & Moan, T. (2008). Experimental and numerical investigation of fatigue damage due to wave-induced vibrations in a containership in head seas. Journal of Marine Science and Technology, 13, 428–445. https://doi.org/10.1007/s00773-008-0006-5
   Web of Science ®Google Scholar
• Dulebenets, M. (2022). Multi objective collaborative agreements amongst shipping lines and marine terminal operators for sustainable and environmental-friendly ship schedule design. Journal of Cleaner Production, 342(12), 130897. https://doi.org/10.1016/j.jclepro.2022.130897
   Google Scholar
• Ellermann, K. (2008). Nonlinear dynamics of offshore systems in random seas. In IUTAM symposium on fluid-structure interaction in ocean engineering (pp. 45–56). Springer.
   Google Scholar
• Elmi, Z., Prashant, S., Vamshi, K., Meriga, V., Goniewicz, K., Borowska-Stefanska, M., Wisniewski, S., & Dulebenets, M. (2022). Uncertainties in Liner shipping and ship schedule recovery: A state-of-the-art review. Journal of Marine Science and Engineering, 10(5), 563. https://doi.org/10.3390/jmse10050563
   Web of Science ®Google Scholar
• European Maritime Safety Agency (EMSA). (2021). Annual overview of Marine casualties and incidents. European Maritime Safety Agency.
   Google Scholar
• Falzarano, J., Su, Z., Jamnongpipatkul, A. (2012), Application of stochastic dynamical system to nonlinear ship rolling problems, Proceedings of the 11th International Conference on the Stability of Ships and Ocean Vehicles, Athens, Greece
   Google Scholar
• Gaidai, O., Cao, Y., & Loginov, S. (2023). Global cardiovascular diseases death rate prediction. Current Problems in Cardiology, 48(5), 101622. https://doi.org/10.1016/j.cpcardiol.2023.101622
   PubMed Web of Science ®Google Scholar
• Gaidai, O., Cao, Y., Xing, Y., & Balakrishna, R. (2023). Extreme springing response statistics of a tethered platform by deconvolution. International Journal of Naval Architecture and Ocean Engineering, 15, 100515. https://doi.org/10.1016/j.ijnaoe.2023.100515
   Web of Science ®Google Scholar
• Gaidai, O., Cao, Y., Xing, Y., & Wang, J. (2023). Piezoelectric Energy Harvester Response Statistics. Micromachines, 14(2), 271. https://doi.org/10.3390/mi14020271
   PubMed Web of Science ®Google Scholar
• Gaidai, O., Cao, Y., Xu, X., & Xing, Y. (2023). Offloading operation bivariate extreme response statistics for FPSO vessel. Scientific Reports, 13(1). https://doi.org/10.1038/s41598-023-31533-8
   Web of Science ®Google Scholar
• Gaidai, O., Fu, S., & Xing, Y. (2022). Novel risk assessment method for multidimensional nonlinear dynamic systems. Marine Structures, 86, 103278. https://doi.org/10.1016/j.marstruc.2022.103278
   Web of Science ®Google Scholar
• Gaidai, O., Liu, Z., Wang, K., & Bai, X. (2023). Current COVID-19 Epidemic Risks in Brazil. Epidemiology International Journal, 7(2), 1–10. https://doi.org/10.23880/eij-16000259
   Google Scholar
• Gaidai, O., Sheng, J., Cao, Y., Zhang, F., Zhu, Y., & Loginov, S. (2024). Public health system sustainability assessment by Gaidai hypersurface approach. Current Problems in Cardiology, 49(3), 102391. https://doi.org/10.1016/j.cpcardiol.2024.102391
   PubMedGoogle Scholar
• Gaidai, O., Sheng, J., Cao, Y., Zhu, Y., & Loginov, S. (2024). Generic COVID-19 epidemic forecast for Estonia by Gaidai multivariate risk assessment method. Franklin Open. https://doi.org/10.1016/j.fraope.2024.100075
   Google Scholar
• Gaidai, O., Sheng, J., Cao, Y., Zhu, Y., Wang, K., & Liu, Z. (2024). Limit hypersurface state of art gaidai reliability approach for oil tankers Arctic operational safety. Journal of Ocean Engineering and Marine Energy. https://doi.org/10.1007/s40722-024-00316-2
   Google Scholar
• Gaidai, O., Storhaug, G., Naess, A. (2010a). Extreme value statistics of ship rolling. PRADS Proceedings. Practical Design of Ships and Other Floating Structures. Vol 2, 457–466.
   Google Scholar
• Gaidai, O., Storhaug, G., Naess, A. (2010b). Extreme value statistics of whipping response for large ships. PRADS Proceedings. Practical Design of Ships and Other Floating Structures. Vol 2, 1210–1221.
   Google Scholar
• Gaidai, O., Storhaug, G., & Naess, A. (2016). Extreme large cargo ship panel stresses by bivariate 4-parameter bivariate Weibull method method. Ocean Engineering, 123, 432–439. https://doi.org/10.1016/j.oceaneng.2016.06.048
   Web of Science ®Google Scholar
• Gaidai, O., Storhaug, G., & Naess, A. (2018). Statistics of extreme hydro elastic response for large ships. Marine Structure, 61, 142–154. https://doi.org/10.1016/j.marstruc.2018.05.004
   Web of Science ®Google Scholar
• Gaidai, O., Wang, F., Cao, Y., & Liu, Z. (2024). 4400 TEU cargo ship dynamic analysis by Gaidai risk assessment method. Journal of Shipping and Trade, 9(1), 2024. https://doi.org/10.1186/s41072-023-00159-4
   Google Scholar
• Gaidai, O., Wang, F., & Sun, J. (2024). Energy harvester risk assessment study by Gaidai risk assessment method. Climate Resilience and Sustainability, 3(1). https://doi.org/10.1002/cli2.64
   Google Scholar
• Gaidai, O., Wang, K., Wang, F., Xing, Y., & Yan, P. (2022). Cargo ship aft panel stresses prediction by deconvolution. Marine Structures, 88, 103359. https://doi.org/10.1016/j.marstruc.2022.103359
   Web of Science ®Google Scholar
• Gaidai, O., Wang, F., Wu, Y., Xing, Y., Medina, A., & Wang, J. (2022). Offshore renewable energy site correlated wind-wave statistics. Probabilistic Engineering Mechanics, 68. https://doi.org/10.1016/j.probengmech.2022.103207
   Web of Science ®Google Scholar
• Gaidai, O., Wang, F., Wu, Y., Xing, Y., Rivera Medina, A., & Wang, J. (2022). Offshore renewable energy site correlated wind-wave statistics. Probabilistic Engineering Mechanics, 68, 103207. https://doi.org/10.1016/j.probengmech.2022.103207
   Web of Science ®Google Scholar
• Gaidai, O., Wang, F., Yakimov, V. (2023). COVID-19 multi-state epidemic forecast in India. Proceedings of the Indian National Science Academy. https://doi.org/10.1007/s43538-022-00147-5
   Google Scholar
• Gaidai, O., Wang, F., Yakimov, V., Sun, J., & Balakrishna, R. (2023). Lifetime assessment for riser systems. Green Technology, Resilience, and Sustainability, 3(1). https://doi.org/10.1007/s44173-023-00013-7
   Google Scholar
• Gaidai, O., Wu, Y., Yegorov, I., Alevras, P., Wang, J., & Yurchenko, D. (2022). Improving performance of a nonlinear absorber applied to a variable length pendulum using surrogate optimization. Journal of Vibration and Control, 30(1–2), 156–168. https://doi.org/10.1177/10775463221142663
   Web of Science ®Google Scholar
• Gaidai, O., & Xing, Y. (2022a). A novel bio-system risk assessment approach for multi-state COVID-19 epidemic forecast. Engineered Science. https://doi.org/10.30919/es8d797
   Google Scholar
• Gaidai, O., & Xing, Y. (2022b). A novel multi regional risk assessment method for COVID-19 death forecast. Engineered Science. https://doi.org/10.30919/es8d799
   Google Scholar
• Gaidai, O., & Xing, Y. (2022c). Novel risk assessment method validation for offshore structural dynamic response. Ocean Engineering, 266(5), 113016. https://doi.org/10.1016/j.oceaneng.2022.113016
   Google Scholar
• Gaidai, O., & Xing, Y. (2023). Prediction of death rates for cardiovascular diseases and cancers. Cancer Innovation, 2(2), 140–147. https://doi.org/10.1002/cai2.47
   PubMedGoogle Scholar
• Gaidai, O., Xing, Y., & Balakrishna, R. (2022). Improving extreme response prediction of a subsea shuttle tanker hovering in ocean current using an alternative highly correlated response signal. Results in Engineering, 15, 100593. https://doi.org/10.1016/j.rineng.2022.100593
   Google Scholar
• Gaidai, O., Xing, Y., Balakrishna, R., & Xu, J. (2023). Improving extreme offshore windspeed prediction by using deconvolution. Heliyon, 9(2), e13533. https://doi.org/10.1016/j.heliyon.2023.e13533
   PubMed Web of Science ®Google Scholar
• Gaidai, O., Xing, Y., & Xu, X. (2023). Novel methods for coupled prediction of extreme windspeeds and wave heights. Scientific Reports, 13(1). https://doi.org/10.1038/s41598-023-28136-8
   Web of Science ®Google Scholar
• Gaidai, O., Xing, Y., Xu, J., & Balakrishna, R. (2023). Gaidai-xing risk assessment method validation for 10-MW floating wind turbines. Scientific Reports, 13(1). https://doi.org/10.1038/s41598-023-33699-7
   Web of Science ®Google Scholar
• Gaidai, O., Xu, J., Hu, Q., Xing, Y., & Zhang, F. (2022). Offshore tethered platform springing response statistics. Scientific Reports, 12(1), 41598–022–25806–x. https://doi.org/10.1038/s41598-022-25806-x
   Web of Science ®Google Scholar
• Gaidai, O., Xu, X., & Xing, Y. (2023). Novel deconvolution method for extreme FPSO vessel hawser tensions during offloading operations. Results in Engineering, 17, 100828. https://doi.org/10.1016/j.rineng.2022.100828
   Google Scholar
• Gaidai, O., Xu, J., Xing, Y., Hu, Q., Storhaug, G., Xu, X., & Sun, J. (2022). Cargo vessel coupled deck panel stresses risk assessment study. Ocean Engineering, 268, 113318. https://doi.org/10.1016/j.oceaneng.2022.113318
   Web of Science ®Google Scholar
• Gaidai, O., Xu, J., Yakimov, V., & Wang, F. (2023a). Analytical and computational modeling for multi-degree of freedom systems: Estimating the likelihood of an FOWT Structural Failure. Journal of Marine Science and Engineering, 11(6), 1237. https://doi.org/10.3390/jmse11061237
   Web of Science ®Google Scholar
• Gaidai, O., Xu, J., Yakimov, V., & Wang, F. (2023b). Liquid carbon storage tanker disaster resilience. Environment Systems and Decisions. https://doi.org/10.1007/s10669-023-09922-1
   Google Scholar
• Gaidai, O., Xu, J., Yan, P., Xing, Y., Wang, K., & Liu, Z. (2023). Novel methods for risk assessment study of multi-dimensional non-linear dynamic systems. Scientific Reports, 13(1), 3817. https://doi.org/10.1038/s41598-023-30704-x
   PubMed Web of Science ®Google Scholar
• Gaidai, O., Xu, J., Yan, P., Xing, Y., Wu, F., & Zhang, Y. (2022). Novel methods for windspeeds prediction across multiple locations. Scientific Reports, 12(1), 19614. https://doi.org/10.1038/s41598-022-24061-4
   PubMed Web of Science ®Google Scholar
• Gaidai, O., Yakimov, V., & Balakrishna, R. (2023). Dementia death rates prediction. BMC Psychiatry, 23(691). https://doi.org/10.1186/s12888-023-05172-2
   PubMedGoogle Scholar
• Gaidai, O., Yakimov, V., Hu, Q., & Loginov, S. (2024). Multivariate risks assessment for complex bio-systems by Gaidai risk assessment method. Systems and Soft Computing, 6, 200074. https://doi.org/10.1016/j.sasc.2024.200074
   Google Scholar
• Gaidai, O., Yakimov, V., Niu, Y., & Liu, Z. (2023). Gaidai-Yakimov risk assessment method for high-dimensional spatio-temporal biosystems. Biosystems, 235, 105073. https://doi.org/10.1016/j.biosystems.2023.105073
   PubMed Web of Science ®Google Scholar
• Gaidai, O., Yakimov, V., Sun, J., & van Loon, E.-J. (2023). Singapore COVID-19 data cross-validation by the Gaidai risk assessment method. Npj Viruses, 1(1). https://doi.org/10.1038/s44298-023-00006-0
   Google Scholar
• Gaidai, O., Yakimov, V., & van Loon, E. (2023). Influenza-type epidemic risks by spatio-temporal Gaidai-Yakimov method. Dialogues in Health, 3(2), 100157. https://doi.org/10.1016/j.dialog.2023.100157
   Google Scholar
• Gaidai, O., Yakimov, V., Wang, F. (2024). Gaidai Multivariate Reliability Method for Energy Harvester Operational Safety, given manufacturing imperfections. International Journal of Precision Engineering and Manufacturing. https://doi.org/10.1007/s12541-024-00977-x
   Google Scholar
• Gaidai, O., Yakimov, V., Wang, F., Hu, Q., Storhaug, G., & Wang, K. (2023). Lifetime assessment for container vessels. Applied Ocean Research, 139, 103708. https://doi.org/10.1016/j.apor.2023.103708
   Web of Science ®Google Scholar
• Gaidai, O., Yakimov, V., Wang, F., Sun, J., & Wang, K. (2024). Bivariate risk assessment analysis for floating wind turbines. International Journal of Low-Carbon Technologies”, 19, 55–64. https://doi.org/10.1093/ijlct/ctad108
   Web of Science ®Google Scholar
• Gaidai, O., Yakimov, V., Wang, F., Xing, Y., & Zhang, F. (2023). Safety design study for energy harvesters. Sustainable Energy Research, 10(1). https://doi.org/10.1186/s40807-023-00085-w
   PubMedGoogle Scholar
• Gaidai, O., Yakimov, V., Wang, F., Zhang, F., & Balakrishna, R. (2023). Floating wind turbines structural details fatigue life assessment. Scientific Reports, 13(1). https://doi.org/10.1038/s41598-023-43554-4
   Web of Science ®Google Scholar
• Gaidai, O., Yakimov, V., & Zhang, F. (2023). COVID-19 spatio-temporal forecast in England. Biosystems, 233, 105035. https://doi.org/10.1016/j.biosystems.2023.105035
   PubMed Web of Science ®Google Scholar
• Gaidai, O., Yan, P., & Xing, Y. (2022a). A novel method for prediction of extreme windspeeds across parts of Southern Norway. Frontiers in Environmental Science, 10. https://doi.org/10.3389/fenvs.2022.997216
   Web of Science ®Google Scholar
• Gaidai, O., Yan, P., & Xing, Y. (2022b). Prediction of extreme cargo ship panel stresses by using deconvolution. Frontiers in Mechanical Engineering, 8. https://doi.org/10.3389/fmech.2022.992177
   PubMed Web of Science ®Google Scholar
• Gaidai, O., Yan, P., & Xing, Y. (2023). Future world cancer death rate prediction. Scientific Reports, 13(1). https://doi.org/10.1038/s41598-023-27547-x
   Web of Science ®Google Scholar
• Gaidai, O., Yan, P., Xing, Y., Xu, J., Wu, Y. (2022). A novel statistical method for long-term coronavirus modelling.F1000 research. https://orcid.org/0000-0003-0883-48542
   PubMedGoogle Scholar
• Gaidai, O., Yan, P., Xing, Y., Xu, J., & Wu, Y. (2023). Gaidai risk assessment method for long-term coronavirus modelling. F1000 Research, 11, 1282. https://doi.org/10.12688/f1000research.125924.3
   PubMedGoogle Scholar
• Gaidai, O., Yan, P., Xing, Y., Xu, J., Zhang, F., & Wu, Y. (2023). Cargo vessel under ice loadings. Scientific Reports, 13(1). https://doi.org/10.1038/s41598-023-34606-w
   Google Scholar
• ISSC. (2009). Proceedings of the 17th international ship and offshore structures congress: III.1 ultimate strength. In C. D. Jang, S. Y. Hong, Eds. International ship and offshore structures congress, Korea.
   Google Scholar
• Jovanović, I., Perčić, M., Koričan, M., Vladimir, N., & Fan, A. (2022). Investigation of the viability of unmanned autonomous container ships under different carbon pricing scenarios. Journal of Marine Science and Engineering, 10(12), 1991. https://doi.org/10.3390/jmse10121991
   Web of Science ®Google Scholar
• Liu, Z., Gaidai, O., Xing, Y., & Sun, J. (2023). Deconvolution approach for floating wind turbines. Energy Science & Engineering, 11(8), 2742–2750. https://doi.org/10.1002/ese3.1485
   Web of Science ®Google Scholar
• OCIMF, Oil Company International Marine Form. (2007). Mooring Equipment Guide.
   Google Scholar
• Rahim, G. P. (2019). Container ship accident analysis due to container stacked on deck as an attempt to improve maritime logistic system. E3S Web of Conferences, 130, 01010. https://doi.org/10.1051/e3sconf/201913001010
   Google Scholar
• Stanisic, D., Efthymiou, M., Kimiaei, M., & Zhao, W. (2018). Design loads and long term distribution of mooring line response of a large weathervaning vessel in a tropical cyclone environment. Marine Structures, 61, 361–380. https://doi.org/10.1016/j.marstruc.2018.06.004
   Web of Science ®Google Scholar
• Storhaug, G., Moe, E. (2007). Measurements of wave induced vibrations on-board a large container vessel operating in harsh environment. Proceedings of the 10th international symposium on practical design of ships and other floating structures, Houston, US (pp. 64–72).
   Google Scholar
• Su, Z. (2012). Nonlinear response and stability analysis of vessel rolling motion in random waves using stochastic dynamical systems. Texas University.
   Google Scholar
• Sun, J., Gaidai, O., & Wang, F. (2023). Gaidai risk assessment method for fixed offshore structures. Journal of the Brazilian Society of Mechanical Sciences and Engineering, 46(27). https://doi.org/10.1007/s40430-023-04607-x
   Google Scholar
• Sun, J., Gaidai, O., Xing, Y., Wang, F., & Liu, Z. (2023). On safe offshore energy exploration in the Gulf of Eilat. Quality and Risk Assessment Engineering International, 39(7), 2957–2966. https://doi.org/10.1002/qre.3402
   Google Scholar
• Tomic, B., Turk, A., & Čalić, B. (2018). Recent advances in damage stability assessment with application on a container vessel. Journal of Maritime & Transportation Science, 2(Special edition 2), 167–184. https://doi.org/10.18048/2018-00.167
   Google Scholar
• Wang, Y., & Wang, S. (2021). Deploying, scheduling, and sequencing heterogeneous vessels in a liner container shipping route. Transportation Research Part E: Logistics & Transportation Review, 151(2). https://doi.org/10.1016/j.tre.2021.102365
   Google Scholar
• Xing, Y., & Gaidai, O. (2023). Multi-regional COVID-19 epidemic forecast in Sweden. Digital Health, 9(9), 205520762311629. https://doi.org/10.1177/20552076231162984
   Google Scholar
• Xu, X., Sahoo, P., Evans, J., & Tao, Y. (2019). Hydrodynamic performances of FPSO and shuttle tanker during side-by-sideoffloading operation, ships and offshore structures. Ships and Offshore Structures, 14(sup1), 292–299. https://doi.org/10.1080/17445302.2019.1580845
   Google Scholar
• Yakimov, V., Gaidai, O., Wang, F., & Wang, K. (2023). Arctic naval launch and recovery operations, under ice impact interactions. Applications in Engineering Science, 15, 100146. https://doi.org/10.1016/j.apples.2023.100146
   Google Scholar
• Yakimov, V., Gaidai, O., Wang, F., Xu, X., Niu, Y., & Wang, K. (2023). Fatigue assessment for FPSO hawsers. International Journal of Naval Architecture and Ocean Engineering, 15, 100540. https://doi.org/10.1016/j.ijnaoe.2023.100540
   Web of Science ®Google Scholar
• Zhang, J., Gaidai, O., & Gao, J. (2018). Bivariate extreme value statistics of offshore jacket support stresses in Bohai bay. The Journal of Offshore Mechanics and Arctic Engineering, 140(4), 041305. https://doi.org/10.1115/1.4039564
   Web of Science ®Google Scholar
• Zhang, J., Gaidai, O., Ji, H., & Xing, Y. (2023). Operational risk assessment study of ice loads acting on cargo vessel bow. Heliyon, 9(4), e15189. https://doi.org/10.1016/j.heliyon.2023.e15189
   PubMedGoogle Scholar
• Zhang, J., Gaidai, O., Wang, K., Xua, L., Ye, R., & Xu, X. (2019). A stochastic method for the prediction of icebreaker bow extreme stresses. Applied Ocean Research, 87, 95–101. https://doi.org/10.1016/j.apor.2019.03.019
   Web of Science ®Google Scholar