Stochastic Model Updating of Bolt-Jointed Structure for Structural Dynamics Applications
Keywords:Bolted-joint, Contact interface, Stochastic model updating, Uncertainty quantification
Structural stiffness exerts from joint connections and contact interfaces are significantly affect the dynamic behaviour of the bolt-jointed structure. Randomness in the joint connections due to the manufacturing variability in the identical bolted joints and uncertainty in contact interfaces due to the assambled and reassambled of the joint structure make sets of the dynamic behaviour of the bolt-jointed structure always inconsistent. On this account, a stochastic analytical model needs to be developed for the bolt-jointed structure to be used for uncertain parameters quantification. Hence, this paper is intended to propose an accurate and efficient stochastic analytical modelling of bolt-jointed structure in predicting the dynamic behaviour of the structure due to the randomness in the joint connections and uncertainty in contact interfaces. The aim of the study was accomplished by investigating four different finite element (FE) models of bolt-jointed structure with different element connectors to represent the bolted joints connections, namely rigid element (RBE), beam element (CBEAM), and 2 types of spring elements namely CELAS and CBUSH. Stochastic modelling was conducted by coupled the appropriate FE models with Latin Hypercube Sampling (LHS) algorithm to provide variability sampling due to the randomness in the bolted joints. The experimental modal analysis was performed by reassembled and disassembled the bolted joints to extract the variability in the dynamic behaviour, and the results were compared with LHS using statistical characteristics. Stochastic model updating then was used to minimise the discrepancies between experimental result and predicted model. The result has shown that the CBUSH is the most appropriate connector to accurately predict the dynamic behaviour of the bolt-jointed structure under variability conditions using the stochastic model updating method.
- 2021-07-14 (2)
- 2021-06-28 (1)
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Copyright (c) 2021 M.A.S. Aziz Syah, M. A. Yunus, M.N. Abdul Rani, R. Omar, Akhil Mora
This work is licensed under a Creative Commons Attribution 4.0 International License.