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Cited by 371Structural Health Monitoring TechniquesControl Systems and IdentificationStatistical and numerical algorithms

Review of finite element model updating methods for structural applications

Open access
Ereiz, Suzana, Duvnjak, Ivan, Fernando Jiménez-Alonso, Javier·2022·Structures
DOI 10.1016/j.istruc.2022.05.041
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Abstract

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.

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  • Simplifying assumptions in some analytical techniques may lead to inaccuracies when dealing with complex geometry, such as sandwich structures with nonlinear materials or intricate failure modes.

    “Simplifying assumptions for some analytical techniques may lead to inaccuracies when dealing with complex geometry, such as sandwich structures with nonlinear materials or intricate failure modes [26].”

    From Machine Learning Algorithms for Prediction and Characterization of Cohesive Zone Parameters for Mixed-Mode Fracture (2024) · cites this paper as [26]

    The Introduction (page unavailable) says that structural idealization and simplification, as well as incorrect assumptions about geometry and nonlinear behavior, can create model uncertainty. It does not address sandwich structures or intricate failure modes, so those specific examples are not supported by our copy. (LLM, conf=0.86)

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Authors
Ereiz, S., Duvnjak, I., & Fernando Jiménez-Alonso, J.
Affiliations
University of Zagreb (HR)
Corresponding author
Ereiz, Suzana
ORCID
Venue
Structures
Publisher
Elsevier BV
Published
2022-07
Volume
41
Pages
684-723
ISSN
2352-0124 (ISSN-L)
DOI
10.1016/j.istruc.2022.05.041
OpenAlex
W4280574223
Cited by
371
References
292
Citations by year
2026: 94 · 2025: 138 · 2024: 90 · 2023: 44 · 2022: 5
FWCI
31.13
Type
journal article
Language
en
Open access
Licence
Locations
  • Structures (publishedVersion, cc-by)
  • idUS (Universidad de Sevilla) (submittedVersion, cc-by)
Funders
  • University of Zagreb
  • European Commission
  • European Regional Development Fund (KK.01.1.1.04.0041)
Topics
  • Physical Sciences › Engineering › Civil and Structural Engineering › Structural Health Monitoring Techniques
  • Physical Sciences › Engineering › Control and Systems Engineering › Control Systems and Identification
  • Physical Sciences › Mathematics › Applied Mathematics › Statistical and numerical algorithms
Keywords
finite element model updating, structural identification, design variables, response surface methodology, regularization methods, structural behavior

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