Bayesian Modelling of Offshore Platforms

Conference paper
First Online:
Part of the Conference Proceedings of the Society for Experimental Mechanics Series book series (CPSEMS)

Abstract

This paper details a case study, where Bayesian methods are used to estimate the model parameters of an offshore platform. This first involves running a series of Finite Element simulations using the Ramboll Offshore Structural Analysis Programs (ROSAP)—developed by Ramboll Oil & Gas—thus establishing how the modal characteristics of an offshore structure model vary as a function of its material properties. Data based modelling techniques are then used to emulate the Finite Element model, as well as estimates of model error. The uncertainties associated with estimating the hyperparameters of the data based modelling techniques are then analysed utilising Markov chain Monte Carlo (MCMC) methods. The resulting analysis takes account of the uncertainties which arise from measurement noise, model error, model emulation and parameter estimation.

Keywords

System identification Model updating Offshore platform Gaussian process Uncertainty quantification 
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References

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    Ramboll Oil & Gas: Ramboll Offshore Structural Analysis Programs (ROSAP). www.ramboll.com/oil-gas.
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Copyright information

© The Society for Experimental Mechanics, Inc. 2016

Authors and Affiliations

  1. 1.Institute for Risk and Uncertainty, Centre for Engineering SustainabilitySchool of Engineering, University of LiverpoolLiverpoolUK
  2. 2.Ramboll Oil & GasEsbjergDenmark
  3. 3.Siemens Wind PowerBrandeDenmark

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