Coupling of peridynamics and inverse finite element method for shape sensing and crack propagation monitoring of plate structures

Kefal, Adnan; Diyaroglu, Cagan; Yıldız, Mehmet; Öterkuş, Erkan

doi:10.1016/j.cma.2021.114520

Cited by 42 publications

(11 citation statements)

References 103 publications

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“…Another limitation of the previous literature works is the requirement of a damage index threshold to detect the presence of the damage itself, which selection is subordinated to the specific case study. Only Kefal et al recently proposed a coupling of periodynamics analysis and iFEM for the crack propagation monitoring in composite plate structures [64], however, an automatic crack size estimation through the iFEM remains unexplored. For this reason, this work is aimed to define an automatic routine to perform damage size estimation in a realistic scenario within the iFEM approach.…”

Section: Of 29mentioning

confidence: 99%

Toward to an Automatic Crack Size Estimation with iFEM for Structural Health Monitoring

Oboe¹,

Poloni²,

Sbarufatti³

et al. 2023

Preprint

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The inverse Finite Element Method (iFEM) is a model-based technique to compute the displacement (and then the strain) field of a structure from strain measurements and a geometrical discretization of the same. Different literature works exploit the error between the numerically reconstructed strains and the experimental measurements to perform damage identification in a Structural Health Monitoring framework. However, only damage detection and localization are performed, without attempting a proper damage size estimation. The latter could be based on machine learning techniques, however, an a priori definition of the damage conditions would be required. To overcome these limitations, the present work proposes a new approach in which the damage is systematically introduced in the iFEM model to minimize its discrepancy with respect to the physical structure. This is performed with a maximum likelihood estimation framework, where the most accurate damage scenario is selected among a series of different models. The proposed approach is experimentally verified on an aluminum plate subjected to fatigue crack propagation, which enables the creation of a Digital-Twin of the structure itself. The strain field fed to the iFEM routine is experimentally measured with an Optical Backscatter Reflectometry fiber and the methodology is validated with independent observations of lasers and the Digital Image Correlation.

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Section: Of 29mentioning

confidence: 99%

Toward to an Automatic Crack Size Estimation with iFEM for Structural Health Monitoring

Oboe¹,

Poloni²,

Sbarufatti³

et al. 2023

Preprint

View full text Add to dashboard Cite

show abstract

“…Another limitation of the previous literature works is the requirement of a damage index threshold to detect the presence of the damage itself, whose selection is subordinated to the specific case study. Only Kefal et al recently proposed a coupling of periodynamics analysis and iFEM for crack monitoring in composite plate structures [ 65 ]; however, an automatic crack size estimation through the iFEM remains unexplored. For this reason, this work aims to define an automatic routine to perform damage size estimation in a realistic scenario within the iFEM approach.…”

Section: Introductionmentioning

confidence: 99%

Towards Automatic Crack Size Estimation with iFEM for Structural Health Monitoring

Oboe

Poloni

Sbarufatti

et al. 2023

Sensors

View full text Add to dashboard Cite

The inverse finite element method (iFEM) is a model-based technique to compute the displacement (and then the strain) field of a structure from strain measurements and a geometrical discretization of the same. Different literature works exploit the error between the numerically reconstructed strains and the experimental measurements to perform damage identification in a structural health monitoring framework. However, only damage detection and localization are performed, without attempting a proper damage size estimation. The latter could be based on machine learning techniques; however, an a priori definition of the damage conditions would be required. To overcome these limitations, the present work proposes a new approach in which the damage is systematically introduced in the iFEM model to minimize its discrepancy with respect to the physical structure. This is performed with a maximum likelihood estimation framework, where the most accurate damage scenario is selected among a series of different models. The proposed approach was experimentally verified on an aluminum plate subjected to fatigue crack propagation, which enables the creation of a digital twin of the structure itself. The strain field fed to the iFEM routine was experimentally measured with an optical backscatter reflectometry fiber and the methodology was validated with independent observations of lasers and the digital image correlation.

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“…The iFEM has been successfully applied to the monitoring of a container ship [ 19 , 20 ], wind turbines [ 21 , 22 ], and to complex aeronautical structures [ 23 ]. Colombo et al in [ 24 ] developed an iFEM-based damage detection methodology, and current research is expanding towards damage identification and quantification [ 25 , 26 , 27 , 28 ]; very recent developments are in the direction of a non-deterministic displacement reconstruction [ 29 ].…”

Section: Introductionmentioning

confidence: 99%

Variable Thickness Strain Pre-Extrapolation for the Inverse Finite Element Method

Poloni

Oboe

Sbarufatti

et al. 2023

Sensors

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The inverse Finite Element Method (iFEM) has recently gained much popularity within the Structural Health Monitoring (SHM) field since, given sparse strain measurements, it reconstructs the displacement field of any beam or shell structure independently of the external loading conditions and of the material properties. However, in principle, the iFEM requires a triaxial strain measurement for each inverse finite element, which is seldom feasible in practical applications due to both costs and cabling-related limitations. To alleviate this problem several techniques to pre-extrapolate the measured strains have been developed, so that interpolated or extrapolated strain values are inputted to elements without physical sensors: the benefit is that the required number of sensors can be reduced. Nevertheless, whenever the monitored components comprise regions of different thicknesses, each region of constant thickness must be extrapolated separately, due to thickness-induced discontinuities in the strain field. This is the case in many practical applications, especially those concerning fiber-reinforced composite laminates. This paper proposes to extrapolate the measured strain field in a thickness-normalized space, where the thickness-induced trends are removed; this novel method can significantly decrease the number of required sensors, effectively reducing the costs of iFEM-based SHM systems. The method is validated in a simple but informative numerical case study, highlighting the potentialities and benefits of the proposed approach for more complex application scenarios.

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Coupling of peridynamics and inverse finite element method for shape sensing and crack propagation monitoring of plate structures

Cited by 42 publications

References 103 publications

Toward to an Automatic Crack Size Estimation with iFEM for Structural Health Monitoring

Toward to an Automatic Crack Size Estimation with iFEM for Structural Health Monitoring

Towards Automatic Crack Size Estimation with iFEM for Structural Health Monitoring

Variable Thickness Strain Pre-Extrapolation for the Inverse Finite Element Method

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