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Civil-Comp Proceedings
ISSN 1759-3433
CCP: 109
PROCEEDINGS OF THE FOURTH INTERNATIONAL CONFERENCE ON SOFT COMPUTING TECHNOLOGY IN CIVIL, STRUCTURAL AND ENVIRONMENTAL ENGINEERING
Edited by: Y. Tsompanakis, J. Kruis and B.H.V. Topping
Paper 23

Uncertainty Propagation and Global Sensitivity Analysis in Hybrid Simulation using Polynomial Chaos Expansion

G. Abbiati1, S. Marelli1, O.S. Bursi2, B. Sudret1 and B. Stojadinovic1

1The Institute of Structural Engineering, Department of Civil, Environmental and Geomatic Engineering, Swiss Federal Institute of Technology, Zurich, Switzerland
2Department of Civil, Environmental and Mechanical Engineering, University of Trento, Italy

Full Bibliographic Reference for this paper
G. Abbiati, S. Marelli, O.S. Bursi, B. Sudret, B. Stojadinovic, "Uncertainty Propagation and Global Sensitivity Analysis in Hybrid Simulation using Polynomial Chaos Expansion", in Y. Tsompanakis, J. Kruis, B.H.V. Topping, (Editors), "Proceedings of the Fourth International Conference on Soft Computing Technology in Civil, Structural and Environmental Engineering", Civil-Comp Press, Stirlingshire, UK, Paper 23, 2015. doi:10.4203/ccp.109.23
Keywords: hybrid simulation, dynamic response, global sensitivity analysis, Sobol index, surrogate modeling, polynomial chaos expansion.

Summary
Hybrid simulation is a very effective testing strategy for simulating the dynamic response of structural systems whose dimensions and complexities exceed the capacity of conventional testing facilities. The hybrid model of the prototype structure, which combines numerical and physical substructures, accurately reproduces the overall dynamic response of the structure with reduced costs and effort. In current practice, the parameters that characterize the numerical subdomain are deterministic. The values of these parameters are often determined through deliberate simplifications, ignoring the associated uncertainties. However, the effect of uncertainties may be significant. The objective of the work, presented in this paper, is to use uncertainty quantification and global sensitivity analysis to evaluate the effect of uncertainties on the response of a hybrid model in simulations. Sobol indices are selected to explain the total variance of output parameters, e.g. maximum absolute displacement peaks, with respect to the variance of input parameters, e.g. viscous damping. In detail, a generalized polynomial chaos expansion of the hybrid system response is derived and Sobol indices are post-processed from the entailing polynomial coefficients. The proposed approach is illustrated using a nonlinear two-degrees-of-freedom benchmark case study that covers a class of prototype typical for hybrid simulation tests.

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