Authors: Hem Bahadur Motra; Andrea Dimmig-Osburg; Jörg Hildebrand
Addresses: Department of Civil Engineering, Bauhaus-Universität Weimar, Weimar, Germany; Research Training Group 1462, Berkaerstrasse 9, 99425 Weimar, Germany ' Department of Civil Engineering, F.A. Finger Institute of Polymer Materials, Bauhaus-Universität, Weimar, Germany ' Department of Civil Engineering, Institute of Simulation and Experiment (SimEx), Bauhaus-Universität, Weimar, Germany
Abstract: This paper presents a methodology for uncertainty quantification in cyclic creep analysis. The BP model, the Whaley and Neville model, the modified MC90 for cyclic loading and the modified hyperbolic function for cyclic loading are used for uncertainty quantification. Three types of uncertainties are included in Uncertainty Quantification (UQ): (i) natural variability in loading materials' properties; (ii) data uncertainty due to measurement errors; and (iii) modelling uncertainty and errors during cyclic creep analysis. This study finds that the BP model performs the best for cyclic creep prediction followed by the modified hyperbolic model and modified MC90 model. Furthermore, a global Sensitivity Analysis (SA) that considers the uncorrelated and correlated parameters is used to quantify the contribution of each source of uncertainty to the overall uncertainty of the prediction as well as to identifying the important parameters. The errors in determining the input quantities and the model itself can produce significant changes in creep prediction values.
Keywords: cyclic creep prediction; input variables; stochastic; sensitivity analysis; uncertainty quantification; quality assessment; model quality; modelling; concrete degradation; concrete strength; concrete stiffness; Monte Carlo simulation.
International Journal of Reliability and Safety, 2014 Vol.8 No.2/3/4, pp.262 - 283
Available online: 20 May 2015 *Full-text access for editors Access for subscribers Purchase this article Comment on this article