Abstract
Subsea lifting operations are dangerous and expensive. One typical problem is the amplification of dynamic forces on the lifting cable at deep water due to resonance of the cable-equipment system. So, it is necessary to guarantee that the cable is always tensioned to prevent slack conditions that lead to snap loads, and at the same time, the cable must be below its structural limit. Several models have been presented to analyze this phenomenon, but they did not consider uncertainties in the determination of the hydrodynamic coefficients (\(C_a\) and \(C_d\)), which affect considerably the response of the system. Therefore, the objective of this study is to evaluate the influence of the variability of these coefficients via a statistical description of the problem, using Markov Chain Monte Carlo, accept-reject method, maximum likelihood and Monte Carlo simulation in an integrated way. The variability on the structural resistance of the cable is also considered and a reliability study is presented. The stochastic analysis is compared with the deterministic one, and it is concluded that there is a probability of failure and slacking that could be neglected if the deterministic approach is used, which makes the stochastic analysis a more realistic diagnosis of the problem.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Similar content being viewed by others
References
Cabrera-Miranda, J.M., Paik, J.K.: On the probabilistic distribution of loads on a marine riser. Ocean Eng. 134, 105–118 (2017). https://doi.org/10.1016/j.engstruct.2013.05.002
Campanile, A., Piscopo, V., Scamardella, A.: Statistical properties of bulk carrier longitudinal strength. Marine Struct. 39, 438–462 (2014). https://doi.org/10.1016/j.marstruc.2014.10.007
Casella, G., Robert, C.P., Wells, M.T.: Generalized accept-reject sampling schemes. In: A Festschrift for Herman Rubin. Institute of Mathematical Statistics, vol. 5, pp. 442-447 (2004). https://doi.org/10.1214/lnms/1196285403
CIMAF. Manual Técnico de Cabos de Aço (Brazilian steel cables catalog) (2009). https://www.aecweb.com.br/cls/catalogos/aricabos/CatalogoCIMAF2014Completo.pdf
Congdon, P.: Bayesian Statistical Modelling. Wiley, New York (2007)
Fernandes, A.C., Mineiro, F.P.S.: Assessment of hydrodynamic properties of bodies with complex shapes. Appl. Ocean Res. 29, 155–166 (2007). https://doi.org/10.1016/j.apor.2007.04.002
Geweke, J.: Evaluating the accuracy of sampling-based approaches to the calculation of posterior moments. In: Bayesian Statistics, vol. 4, pp. 169–193. Oxford University Press (1992). https://pdfs.semanticscholar.org/2e86/50b01dd557ffb15113c795536ea7c6ab1088.pdf
Grigoriu, M.: Stochastic Systems: Uncertainty Quantification and Propagation. Springer, New York (2012)
Journée, J.M.J., Massie, W.W.: Offshore hydromechanics. TU Delft (2000). http://resolver.tudelft.nl/uuid:31938f94-4e5b-4b69-a249-b88f8c3e59cf
Niedzwecki, J.M., Sreekumar, K.T.: Snap loading of marine cable systems. Appl. Ocean Res. 13(1), 2–11 (1991). https://doi.org/10.1016/S0141-1187(05)80035-5
Raftery, A.E., Lewis, S.: How many iterations in the Gibbs sampler? vol. 4, pp. 763–773. Oxford University Press (1991)
Ribeiro, L.H.M.S., et al.: Modelling of ISO 9001 certifications for the American countries: a Bayesian approach. Total Qual. Manag. Bus. Excellence 30, 1–26 (2019). https://doi.org/10.1080/14783363.2019.1696672
Teixeira, A.P., Ivanov, L.D., Soares, C.G.: Assessment of characteristic values of the ultimate strength of corroded steel plates with initial imperfections. Eng. Struct. 56, 517–527 (2013). https://doi.org/10.1016/j.engstruct.2013.05.002
Tommasini, R.B., Carvalho, L.O., Pavanello, R.: A dynamic model to evaluate the influence of the laying or retrieval speed on the installation and recovery of subsea equipment. Appl. Ocean Res. 77, 34–44 (2018). https://doi.org/10.1016/j.apor.2018.05.001
Zhang, X., Zhang, L., Hu, J.: Real-time risk assessment of a fracturing manifold system used for shale-gas well hydraulic fracturing activity based on a hybrid Bayesian network. J. Nat. Gas Sci. Eng. 62, 79–91 (2019). https://doi.org/10.1016/j.jngse.2018.12.001
Acknowledgment
The authors gratefully acknowledge: the financial support of the São Paulo Research Foundation (FAPESP) process number 2019/00315-8, and process number 18/15894-0, and the financial support of the National Council for Scientific and Technological Development – CNPq (308551/2017-6) and of the Coordenação de Aperfeiçoamento de Pessoal de NÃvel Superior (CAPES) for the continuous support for the research.
Author information
Authors and Affiliations
Corresponding authors
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2021 Springer Nature Switzerland AG
About this paper
Cite this paper
da Silva Ribeiro, L.H.M., de Padua Agripa Sales, L., Tommasini, R.B. (2021). Uncertainty Quantification in Subsea Lifting Operations. In: De Cursi, J. (eds) Proceedings of the 5th International Symposium on Uncertainty Quantification and Stochastic Modelling. Uncertainties 2020. Lecture Notes in Mechanical Engineering(). Springer, Cham. https://doi.org/10.1007/978-3-030-53669-5_11
Download citation
DOI: https://doi.org/10.1007/978-3-030-53669-5_11
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-030-53668-8
Online ISBN: 978-3-030-53669-5
eBook Packages: EngineeringEngineering (R0)