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• W3081065019 endingPage "1141" @default.
• W3081065019 startingPage "1141" @default.
• W3081065019 abstract "The state of materials and accordingly the properties of structures are changing over the period of use, which may influence the reliability and quality of the structure during its life-time. Therefore identification of the model parameters of the system is a topic which has attracted attention in the content of structural health monitoring. The parameters of a constitutive model are usually identified by minimization of the difference between model response and experimental data. However, the measurement errors and differences in the specimens lead to deviations in the determined parameters. In this article, the Choboche model with a damage is used and a stochastic simulation technique is applied to generate artificial data which exhibit the same stochastic behavior as experimental data. Then the model and damage parameters are identified by applying the sequential Gauss-Markov-Kalman filter (SGMKF) approach as this method is determined as the most efficient method for time consuming finite element model updating problems among filtering and random walk approaches. The parameters identified using this Bayesian approach are compared with the true parameters in the simulation, and further, the efficiency of the identification method is discussed. The aim of this study is to observe whether the mentioned method is suitable and efficient to identify the model and damage parameters of a material model, as a highly non-linear model, for a real structural specimen using a limited surface displacement measurement vector gained by Digital Image Correlation (DIC) and to see how much information is indeed needed to estimate the parameters accurately even by considering the model error and whether this approach can also practically be used for health monitoring purposes before the occurrence of severe damage and collapse." @default.
• W3081065019 created "2020-09-01" @default.
• W3081065019 creator A5002304596 @default.
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• W3081065019 creator A5037684251 @default.
• W3081065019 creator A5062849809 @default.
• W3081065019 creator A5066474131 @default.
• W3081065019 date "2020-08-24" @default.
• W3081065019 modified "2023-10-01" @default.
• W3081065019 title "Bayesian Parameter Determination of a CT-Test Described by a Viscoplastic-Damage Model Considering the Model Error" @default.
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• W3081065019 doi "https://doi.org/10.3390/met10091141" @default.
• W3081065019 hasPublicationYear "2020" @default.
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