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2023 | OriginalPaper | Chapter

1. On Model Validation and Bifurcating Systems: An Experimental Case Study

Authors : Keith Worden, David J. Wagg, Malcolm Scott

Published in: Model Validation and Uncertainty Quantification, Volume 3

Publisher: Springer International Publishing

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Abstract

This chapter demonstrates some of the problems that can arise when validating models of nonlinear bifurcating systems and the approaches that can avoid them. Validation is the process of determining the extent to which a model accurately represents the structure or system of interest. Additional care needs to be taken when attempting to validate models of nonlinear systems because of bifurcations that may occur. These phenomena present a difficulty for validation because if a model does not precisely capture the bifurcation points, then the model’s predictions could be very inaccurate, even if the model is (parametrically) very close to the real system. This situation could lead to a good model being dismissed if data generated close to a bifurcation point were used to validate it. In this chapter, experimental data were gathered from a three-storey shear building structure with a harsh nonlinearity between the top two floors, and bifurcations were observed in the structural response. Two models are constructed here, with parameters estimated using Bayesian system identification: a linear model and a nonlinear model. Selected features and metrics were then used to compare the model predictions to the test data. The results show that an appropriate model could be rejected if an inappropriate validation strategy is employed, purely as a result of slightly misplaced bifurcations. It is demonstrated that discrimination can be improved by taking modelling uncertainties into account as part of the validation process.

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Literature
1.
go back to reference Worden, K.: Some thoughts on model validation for nonlinear systems. In: Proceedings of IMAC XVII – 17th International Modal Analysis Conference, Orlando, FL (2001) Worden, K.: Some thoughts on model validation for nonlinear systems. In: Proceedings of IMAC XVII – 17th International Modal Analysis Conference, Orlando, FL (2001)
2.
go back to reference Guide for the verification and validation of computational fluid dynamics simulations. Technical Report KAIAA-G-077-1998, American Institute of Aeronautics and Astronautics, 1998 Guide for the verification and validation of computational fluid dynamics simulations. Technical Report KAIAA-G-077-1998, American Institute of Aeronautics and Astronautics, 1998
3.
go back to reference Worden, K., Tomlinson, G.R.: Nonlinearity in Structural Dynamics: Detection, Identification and Modelling. Institute of Physics Press (2001)CrossRef Worden, K., Tomlinson, G.R.: Nonlinearity in Structural Dynamics: Detection, Identification and Modelling. Institute of Physics Press (2001)CrossRef
4.
go back to reference Thacker, B.H., Doebling, S.W., Hemez, F.M., Anderson, M.C., Pepin, J.E., Rodriguez, E.A.: Concepts of model verification and validation. Technical report, Los Alamos National Laboratory, 2004 Thacker, B.H., Doebling, S.W., Hemez, F.M., Anderson, M.C., Pepin, J.E., Rodriguez, E.A.: Concepts of model verification and validation. Technical report, Los Alamos National Laboratory, 2004
5.
go back to reference Nishio, M., Hemez, F.M., Worden, K., Park, G., Takeda, N., Farrar, C.R.: Feature extraction for structural dynamics model validation. In: Conference Proceedings of the Society for Experimental Mechanics, pp. 153–163 (2011) Nishio, M., Hemez, F.M., Worden, K., Park, G., Takeda, N., Farrar, C.R.: Feature extraction for structural dynamics model validation. In: Conference Proceedings of the Society for Experimental Mechanics, pp. 153–163 (2011)
6.
go back to reference Scott, M., Tiboaca, O.D., Barthorpe, R.J., Wagg, D.J., Worden, K.: On the validation of nonlinear MDOF system models. In: Proceedings of 27th International Conference on Noise & Vibration Engineering, Leuven (2016) Scott, M., Tiboaca, O.D., Barthorpe, R.J., Wagg, D.J., Worden, K.: On the validation of nonlinear MDOF system models. In: Proceedings of 27th International Conference on Noise & Vibration Engineering, Leuven (2016)
7.
go back to reference Qin, A.K., Suganthan, P.N.: Self-adaptive differential evolution algorithm for numerical optimization. In: Proceedings of 2005 IEEE Congress on Evolutionary Computation, vol. 2, pp. 1785–1791 (2005) Qin, A.K., Suganthan, P.N.: Self-adaptive differential evolution algorithm for numerical optimization. In: Proceedings of 2005 IEEE Congress on Evolutionary Computation, vol. 2, pp. 1785–1791 (2005)
8.
go back to reference Worden, K., Manson, G.: On the identification of hysteretic systems, Part I: fitness landscapes and evolutionary identification. Mech. Syst. Signal Process. 29, 201–212 (2012) Worden, K., Manson, G.: On the identification of hysteretic systems, Part I: fitness landscapes and evolutionary identification. Mech. Syst. Signal Process. 29, 201–212 (2012)
9.
go back to reference Worden, K., Becker, W.E.: On the identification of hysteretic systems, Part II: Bayesian sensitivity analysis and parameter confidence. Mech. Syst. Signal Process. 29, 213–227 (2012) Worden, K., Becker, W.E.: On the identification of hysteretic systems, Part II: Bayesian sensitivity analysis and parameter confidence. Mech. Syst. Signal Process. 29, 213–227 (2012)
10.
go back to reference Worden, K., Hensman, J.J.: Parameter estimation and model selection for a class of hysteretic systems using Bayesian inference. Mech. Syst. Signal Process. 32, 153–169 (2012)CrossRef Worden, K., Hensman, J.J.: Parameter estimation and model selection for a class of hysteretic systems using Bayesian inference. Mech. Syst. Signal Process. 32, 153–169 (2012)CrossRef
11.
go back to reference Worden, K., Tiboaca, O.D., Antoniadou, I., Barthorpe, R.J.: System identification of an MDOF experimental structure with a view towards validation and verification. In: Proceedings of the 33rd International Modal Analysis Conference, Orlando, FL (2015) Worden, K., Tiboaca, O.D., Antoniadou, I., Barthorpe, R.J.: System identification of an MDOF experimental structure with a view towards validation and verification. In: Proceedings of the 33rd International Modal Analysis Conference, Orlando, FL (2015)
12.
go back to reference Tiboaca, O.D., Green, P.L., Barthorpe, R.J., Antoniadou, I., Worden, K.: Bayesian inference and RJMCMC in structural dynamics – on experimental data. In: Proceedings of the 34th International Modal Analysis Conference, Orlando, FL (2016) Tiboaca, O.D., Green, P.L., Barthorpe, R.J., Antoniadou, I., Worden, K.: Bayesian inference and RJMCMC in structural dynamics – on experimental data. In: Proceedings of the 34th International Modal Analysis Conference, Orlando, FL (2016)
13.
go back to reference Liu, Y., Chen, W., Arendt, P., Huang, H.Z.: Towards a better understanding of validation metrics. J. Mech. Des. 133, 071005 (2011)CrossRef Liu, Y., Chen, W., Arendt, P., Huang, H.Z.: Towards a better understanding of validation metrics. J. Mech. Des. 133, 071005 (2011)CrossRef
14.
go back to reference Box, G.E.P., Cox, D.R.: An analysis of transformations. J. R. Stat. Soc. B 26, 211–252 (1964)MATH Box, G.E.P., Cox, D.R.: An analysis of transformations. J. R. Stat. Soc. B 26, 211–252 (1964)MATH
Metadata
Title
On Model Validation and Bifurcating Systems: An Experimental Case Study
Authors
Keith Worden
David J. Wagg
Malcolm Scott
Copyright Year
2023
DOI
https://doi.org/10.1007/978-3-031-04090-0_1