Computational framework for model updating of large scale linear and nonlinear finite element models using state of the art evolution strategy

Giagopoulos, Dimitrios; Αραϊλόπουλος, Αλέξανδρος

doi:10.1016/j.compstruc.2017.07.004

Cited by 42 publications

(36 citation statements)

References 27 publications

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“…Let a parameterized class of linear structural models used to model the dynamic behavior of the structure and let    N R be the set of free structural model parameters to be identified using the measured modal data. The overall measure of fit of the linear model, between the measured and the model predicted characteristics is formed in the following expression, combining modal and frequency response residuals [30,31]:…”

Section: Modal and Frequency Response Residuals -Linear Modelsmentioning

confidence: 99%

Vibration Based Structural Health Monitoring of Composite Carbon Fiber Structural Systems

Zacharakis¹,

Αραϊλόπουλος²,

Markogiannaki³

et al. 2019

Proceedings of the 3rd International Conference on Uncertainty Quantification in Computational Sciences and Engineering (UNCECO

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A vibration based computational framework for damage identification of composite cylindrical parts, produced on a spinning axis by winded carbon fibers, cascaded on specified number of plies, in various angles and directions, was presented in this work. First, a discrete FE model of the examined structure is developed, by consecutive shell and solid elements, simulating each carbon fiber ply and resin matrix. Focusing on the updating methodology, coupled with robust, accurate and efficient finite element analysis software, the linear and non-linear behavior of the composite parts was examined under various load conditions followed by equivalent experimental trials, in order to classify the material properties (isotropic, orthotropic, anisotropic) and develop a high-fidelity FE model. This is achieved through combining modal residuals, that include the lowest identified modal frequencies and mode shapes, with response residuals, that include shape and amplitude correlation coefficients considering measured and analytical frequency response functions and time-histories of strains and accelerations. Single objective structural identification strategies without the need of sub-structuring methods, are used for estimating the parameters (material properties in each deformation plane) of the finite element model, based on minimizing the deviations between the experimental and analytical dynamic characteristics. A stochastic optimization evolution strategy is applied in parallel computing, to solve the single-objective optimization problem, arising from combining the above residuals. The effect of model error, finite element model parameterization, number of measured modes and number of mode shape components on the optimal models along with and their variability, are examined.

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Section: Modal and Frequency Response Residuals -Linear Modelsmentioning

confidence: 99%

Vibration Based Structural Health Monitoring of Composite Carbon Fiber Structural Systems

Zacharakis¹,

Αραϊλόπουλος²,

Markogiannaki³

et al. 2019

Proceedings of the 3rd International Conference on Uncertainty Quantification in Computational Sciences and Engineering (UNCECO

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“…The computational framework applied in this work has been introduced by Giagopoulos and Arailopoulos 42 and involves an iterative process during which the solution is being sought by randomly sampling a search space.…”

Section: Applied Model-updating Frameworkmentioning

confidence: 99%

Structural health monitoring and fatigue damage estimation using vibration measurements and finite element model updating

Giagopoulos

Αραϊλόπουλος

Dertimanis

et al. 2018

Structural Health Monitoring

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In this work, a computational framework is proposed for fatigue damage estimation in structural systems by integrating operational experimental measurements in a high-fidelity, large-scale finite element model. The proposed method is applied in a linear steel substructure of a lignite grinder assembly at a Public Power Corporation power plant. A finite element model of the steel base is developed and updated to match the dynamic characteristics measured in real operating conditions. This is achieved through coupled use of numerical and experimental methods for identifying, updating, and optimizing a high-fidelity finite element model. The full stress time histories of the complex mechanical assembly are estimated, at critical locations, by imposing operational vibration measurements from a limited number of sensors in the updated finite element model. Fatigue damage and remaining lifetime is subsequently estimated via commonly adopted engineering approaches, such as Palmgren-Miner damage rule, S-N curves, and rainflow cycle counting. Incorporation of a numerical model of the structure in the response estimation procedure permits stress estimation at unmeasured locations, thereby enabling the drawing of a complete and substantially dense fatigue map consistent with the vibration measurements. Fatigue predictions via the proposed framework are highly correlated to experimental fatigue results, proving the efficiency and applicability of the framework.

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“…Different processes from digitization to simulation have been proposed in the literature, in civil engineering, medical field, mechanical engineering [1][2][3]. The thin-walled parts can be reconstructed by using different strategies depending on the geometrical complexity of their structure.…”

Section: Introductionmentioning

confidence: 99%

Reverse Engineering and Process Modeling of Geometrically Complex Stiffened Shell Structures

Wolff¹,

Batoz²,

Delamézière³

et al. 2021

14th WCCM-ECCOMAS Congress

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Thin-walled stiffened shell structures are very common as industrial products and their analyses by the finite element method can be difficult, in particular when the part is geometrically complex as found in the field of packaging. When the initial CAD definition is not available, reverse engineering is necessary, often based on the use of 3D scanners, in order to obtain a performing 3D geometrical model before considering finite element computations. The process of data capture to FEM can be time consuming and difficult for parts with several 3D stiffeners, depending on the strategies to reconstruct the part. This work focuses on the evaluation of three strategies applied to quite simple thin-walled parts using Geomagic and Abaqus software for the reconstruction and the simulation, respectively. Regarding FE simulations we focus on the computations of the first free frequency since this situation offers interesting comparison with experimental results. The criteria for the evaluation of the strategy are the times for scanning and processing of the data, the reconstruction, of the geometry for the FEM computations. We also study the influence of the strategies on the results of the simulations. These results depend on the type of element used and the present study reveals that for certain strategies the choice is restricted to the use of solid (mainly tetrahedron) elements, while another strategy allows the use of shell or solidshell elements. In this that case only one element through the thickness is used leading to very acceptable results for reduced calculation times but for a longer backward reconstruction time. The advantages and drawbacks of the 3D geometry reconstruction combined with FEM computational strategies are discussed.

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Computational framework for model updating of large scale linear and nonlinear finite element models using state of the art evolution strategy

Cited by 42 publications

References 27 publications

Vibration Based Structural Health Monitoring of Composite Carbon Fiber Structural Systems

Vibration Based Structural Health Monitoring of Composite Carbon Fiber Structural Systems

Structural health monitoring and fatigue damage estimation using vibration measurements and finite element model updating

Reverse Engineering and Process Modeling of Geometrically Complex Stiffened Shell Structures

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