کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
267974 | 504421 | 2010 | 10 صفحه PDF | دانلود رایگان |
![عکس صفحه اول مقاله: Uncertainty and sensitivity analysis of creep models for uncorrelated and correlated input parameters Uncertainty and sensitivity analysis of creep models for uncorrelated and correlated input parameters](/preview/png/267974.png)
The intention of this paper is to evaluate the uncertainties and sensitivities of creep prediction models of standard concrete. The development of creep prediction models has been a field of extensive research and many different models have already been proposed. The four major models are: model GL2000 by Gardner and Lockman, model MC90 according to CEB-FIP Model Code 1990, model ACI209 according to the American Concrete Institute and model B3 by Bažant and Bajewa. First, a sensitivity study is performed in order to determine the parameters which mostly contribute to the uncertainties of the model prediction. This is done for uncorrelated and correlated input parameters and the differences are pointed out. Due to high parameter correlation, most standard sensitivity methods are not applicable and, therefore, a new method developed by Xu and Gertner is applied. Second, the uncertainties of the creep prediction for all of the models are compared and reveal significant differences. Due to the consideration of parameter and model uncertainties, a measure for the total variation of the model response is achieved. A special FEM code is developed to include the existing creep models in structural analysis. Utilising the FEM application, arbitrarily distributed creep strains, non-linear creep and single reinforcement bars can be taken into account. Finally, this FEM code is used and the prescribed creep models and uncertainty method are applied to a pre-stressed concrete bridge. The uncertainties of the loss of pretensioning force and axial shortening are calculated and show a reduction in comparison to uncertainties of pure creep strain. Together, the presented method proves its ability to determine uncertainties and sensitivities of models of time-dependent behaviour for uncorrelated and correlated parameters in an efficient way.
Journal: Engineering Structures - Volume 32, Issue 11, November 2010, Pages 3758–3767