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Towards the Diagnosis and Simulation of Discrepancies in Dynamical Models

  • P. L. Green
Conference paper
Part of the Conference Proceedings of the Society for Experimental Mechanics Series book series (CPSEMS)

Abstract

Models are frequently used to make predictions in regions where experimental testing is difficult. This often involves extrapolating to regions far from where the model was validated. In this paper an example is shown where, despite using a Bayesian analysis to quantify parameter estimation uncertainties, such an extrapolation performs poorly. It is then demonstrated that, in the presence of measurement noise, treating a system’s parameters as being time-variant (even if this is not believed to be true) can reveal fundamental flaws in a model. Finally, existing methods which can be used to quantify model error—the inevitable discrepancies that arise because of approximations made during model development—are extended towards dynamical systems.

Keywords

Verification and validation Particle filter Gaussian process Nonlinear dynamics System identification 

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Copyright information

© The Society for Experimental Mechanics, Inc. 2016

Authors and Affiliations

  1. 1.School of Engineering, Centre for Engineering SustainabilityInstitute for Risk and Uncertainty, University of LiverpoolLiverpoolUK

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