26 Finite Element Model Updating Using the Separable Shadow Hybrid Monte Carlo Technique 275 110 100 90 80 70 60 50 Acceptance rate (%) 40 30 20 10 0 3 3.2 3.4 3.6 3.8 Time step (ms) 4 4.2 4.4 4.6 4.8 S2HMC HMC Fig. 26.2 The acceptance rate obtained for different time steps using HMC and S2HMC methods References 1. Onãte E (2009) Structural analysis with the finite element method. Linear statics. Volume 1: basis and solids. Springer, Dordrecht 2. Rao SS (2004) The finite element method in engineering, 4th edn. Elsevier Butterworth Heinemann, Burlington 3. Friswell MI, Mottershead JE (1995) Finite element model updating in structural dynamics. Kluwer Academic Publishers, Dordrecht 4. Marwala T (2010) Finite element model updating using computational intelligence techniques. Springer, London, UK 5. Bishop CM (2006) Pattern recognition and machine learning. Springer, New York 6. Yuen KV (2010) Bayesian methods for structural dynamics and civil engineering. Wiley, New York 7. Cheung SH, Beck JL (2009) Bayesian model updating using Hybrid Monte Carlo simulation with application to structural dynamic models with many uncertain parameters. J Eng Mech 135(4):243–255 8. Boulkaibet I, Marwala T, Mthembu L, Friswell MI, Adhikari S (2012) Sampling techniques in Bayesian finite element model updating. Proc Soc Exp Mech 29:75–83 9. Izaguirre JA, Hampton SS, Comput J (2004) Shadow hybrid Monte Carlo: an efficient propagator in phase space of macromolecules. J Comput Phys 200:581–604 10. Neal RM (2000) Slice sampling. Technical report no. 2005. Department of Statistics, University of Toronto 11. Hanson KM (2001) Markov Chain Monte Carlo posterior sampling with the Hamiltonian method. Proc SPIE 4322:456–467 12. Ewins DJ (1984) Modal testing: theory and practice. Research Studies Press, Letchworth 13. Marwala T, Sibisi S (2005) Finite element model updating using Bayesian approach. In Proceedings of the international modal analysis conference, Orlando, FL, USA, 2005. ISBN: 0-912053-89-5 14. Bishop CM (1995) Neural networks for pattern recognition. Oxford University Press, Oxford 15. Ching J, Leu SS (2009) Bayesian updating of reliability of civil infrastructure facilities based on condition-state data and fault-tree model. Reliab Eng Syst Saf 94(12):1962–1974 16. Boulkaibet I, Mthembu L, Marwala T, Friswell MI, Adhikari S (2013) Finite element model updating using the shadow hybrid Monte Carlo technique. Proc Soc Exp Mech 6:489–498 17. Sweet CR, Hampton SS, Skeel RD, Izaguirre JA (2009) A separable shadow Hamiltonian hybrid Monte Carlo method. J Chem Phys 131(17):174106 18. Beskos A, Pillai NS, Roberts GO, Sanz-Serna JM, Stuart AM (2013) Optimal tuning of the hybrid Monte-Carlo algorithm. Bernoulli 19: 1501–1534 19. Carvallo J, Datta BN, Gupta A, Lagadapati M (2007) A direct method for model updating with incomplete measured data and without spurious modes. Mech Syst Signal Process 21(7):2715–2731 20. Datta BN (2002) Finite element model updating, eigenstructure assignment and eigenvalue embedding techniques for vibrating systems. Mech Syst Signal Process 16:83–96 21. Guyon I, Elisseeff A (2003) An introduction to variable and feature selection. J Mach Learn Res 3:1157–1182 22. Link M, Friswell MI (2003) Generation of validated structural dynamic models—results of a benchmark study utilizing the GARTEUR SMAG19 Testbed. Mech Syst Signal Process 17(1):9–20, COST Action Special Issue 23. Mthembu L (2012) Finite element model updating. Ph.D. thesis, Faculty of Engineering and the Built Environment, University of the Witwatersrand
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