Volume 4, Issue 4, August 2019, Page: 84-92
Quantifying the Uncertainty of Identified Parameters of Prestressed Concrete Poles Using the Experimental Measurements and Different Optimization Methods
Feras Alkam, Institution of Structural Mechanics, Bauhaus University Weimar, Weimar, Germany
Tom Lahmer, Institution of Structural Mechanics, Bauhaus University Weimar, Weimar, Germany
Received: Aug. 15, 2019;       Accepted: Sep. 6, 2019;       Published: Sep. 20, 2019
DOI: 10.11648/j.eas.20190404.13      View  26      Downloads  43
Abstract
Prestressed concrete poles nowadays are widely used in supporting the catenary cables of train systems. Compared to their importance to the functionality of the train system, this type of structures have not yet received adequate attention from researchers. We have started tracing the changes in the dynamic behavior of these poles caused by the train passing and the degradation of the materials over a long-time period. In this aim, we installed a structural monitoring system on three of them along one of the high-speed train tracks in Germany. The efficient analysis of the recorded measurements by this system requires a well-known data covering the real material properties of the given structures considering uncertainties of the different parameters. In this paper, we inversely identify the material properties of the poles using deterministic and probabilistic approaches based on the experimental measurements of a full-scale structure and Finite Elements Models. In the deterministic approach, the parameters are identified using the simplex optimization algorithm. Uncertainty of the identified parameters is quantified using a Markov Estimator. In the probabilistic approach, Bayesian inference is utilized for better estimation of the probability distribution of the parameters. Both approaches are suitable for the estimation of mean values of the parameters. The Bayesian method, even though computationally more demanding, is additionally suitable for determining the probability distributions and quantifying the uncertainties of the identified parameters and the correlations between each pair of them. The results show the efficiency of each approach to identify the parameters of the poles. For a rough estimation of the mean values, we recommend the deterministic approach as a simple tool. Conversely, the Bayesian approach is recommended for more detailed and accurate estimation.
Keywords
Bayesian Inference, Optimization, Markov Estimator, Parameter Identification, Inverse Problem, Prestressed Concrete Catenary Poles
To cite this article
Feras Alkam, Tom Lahmer, Quantifying the Uncertainty of Identified Parameters of Prestressed Concrete Poles Using the Experimental Measurements and Different Optimization Methods, Engineering and Applied Sciences. Vol. 4, No. 4, 2019, pp. 84-92. doi: 10.11648/j.eas.20190404.13
Copyright
Copyright © 2019 Authors retain the copyright of this article.
This article is an open access article distributed under the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/) which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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