Review of finite element model updating methods for structural applications

被引:177
作者
Ereiz, Suzana [1 ]
Duvnjak, Ivan [1 ]
Jimenez-Alonso, Javier Fernando [2 ]
机构
[1] Univ Zagreb, Fac Civil Engn, Zagreb 10000, Croatia
[2] Univ Seville, Escuela Super Ingn, Seville 4109, Spain
关键词
Finite element model updating (FEMU); Static testing; Dynamic testing; Structural Maintenance; Finite element modelling; Civil Engineering structures; MODAL STRAIN-ENERGY; FREQUENCY-RESPONSE FUNCTIONS; PARAMETER GENETIC ALGORITHM; DAMAGE DETECTION; SYSTEM-IDENTIFICATION; OPTIMIZATION METHOD; CRACK IDENTIFICATION; SENSITIVITY-ANALYSIS; BAYESIAN-ESTIMATION; MULTISTAGE APPROACH;
D O I
10.1016/j.istruc.2022.05.041
中图分类号
TU [建筑科学];
学科分类号
0813 ;
摘要
At the time of designing structures up to date, the density and magnitude of the load have increased, and the requirements for regulation have also become more stringent. To ensure the essential requirements, especially the mechanical resistance and stability, the numerical modelling of the structure is carried out according to the current regulations. Due to various assumptions, idealization, discretization, and parameterizations that are introduced numerical modelling, obtained numerical model may not always reflect the actual structural behavior. It is known that these structures have a hidden resistance that can be determined by combining experimental investigations (static or/and dynamic tests) and finite element model updating methods to minimize the differences between the actual and predicted structural behavior. This paper provides a review of the FEMU process and methods used and summarizes the FEMU approach to help future engineers to select the appropriate method for solving some discussed issues. First, the main terms important for understanding FEMU are introduced. The whole process of model updating is described step by step: selection of updating parameters (design variables), definition of the model updating problem, its solution using different FEMU methods. An overview of the following methods is given: sensitivity-based, maximum likelihood, non-probabilistic, probabilistic, response surface and regularization methods. Each of the method is presented with the corresponding mathematical background, implementation steps, and examples of studies from the literature.
引用
收藏
页码:684 / 723
页数:40
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