An experimental implementation of inverse finite element method for real-time shape and strain sensing of composite and sandwich structures

Kefal, Adnan; Tabrizi, Isa Emami; Tansan, Murat; Kısa, Erdal; Yıldız, Mehmet

doi:10.1016/j.compstruct.2020.113431

Cited by 56 publications

(21 citation statements)

References 60 publications

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“…The explained failure mechanisms for the thick hybrid samples were reproducible, hence it can be implied that replacing carbon layers in AC laminate with glass fiber plies can contribute to the predictability of failure path under flexural loading condition. This information can be used efficiently for shape sensing approaches such as iFEM-RZT [62,63] and to identify the susceptible locations for failure in hybrid fiber laminates while implementing SHM techniques such as active sensing methods [64].…”

Section: Flexural Behavior and Predictability Of Failure Path For Hyb...mentioning

confidence: 99%

An experimental investigation on damage mechanisms of thick hybrid composite structures under flexural loading using multi-instrument measurements

Gul

Tabrizi

Okan

et al. 2021

Aerospace Science and Technology

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Section: Flexural Behavior and Predictability Of Failure Path For Hyb...mentioning

confidence: 99%

An experimental investigation on damage mechanisms of thick hybrid composite structures under flexural loading using multi-instrument measurements

Gul

Tabrizi

Okan

et al. 2021

Aerospace Science and Technology

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“…With the recent development of composite materials and their application in different structures, monitoring their structural integrity and safety has become an important topic of interest in the field of SHM [ 39 , 40 , 41 ]. In this regard, many researchers have employed iFEM to perform deformation reconstruction, strain sensing, and the stress monitoring of composite structures [ 42 , 43 , 44 , 45 ]. These studies include applications of iFEM to at/curved composite structures with thin/thick or moderately thick lamination regimes.…”

Section: Introductionmentioning

confidence: 99%

Sensor Placement Optimization for Shape Sensing of Plates and Shells Using Genetic Algorithm and Inverse Finite Element Method

Ghasemzadeh

Kefal

2022

Sensors

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This paper reports the first investigation of the inverse finite element method (iFEM) coupled with the genetic algorithm (GA) to optimize sensor placement models of plate/shell structures for their real-time and full-field deformation reconstruction. The primary goal was to reduce the number of sensors in the iFEM models while maintaining the high accuracy of the displacement results. Here, GA was combined with the four-node quadrilateral inverse-shell elements (iQS4) as the genes inherited through generations to define the optimum positions of a specified number of sensors. Initially, displacement monitoring of various plates with different boundary conditions under concentrated and distributed static/dynamic loads was conducted to investigate the performance of the coupled iFEM-GA method. One of these case studies was repeated for different initial populations and densities of sensors to evaluate their influence on the accuracy of the results. The results of the iFEM-GA algorithm indicate that an adequate number of individuals is essential to be assigned as the initial population during the optimization process to ensure diversity for the reproduction of the optimized sensor placement models and prevent the local optimum. In addition, practical optimization constraints were applied for each plate case study to demonstrate the realistic applicability of the implemented method by placing the available sensors at feasible sites. The iFEM-GA method’s capability in structural dynamics was also investigated by shape sensing the plate subjected to different dynamic loadings. Furthermore, a clamped stiffened plate and a curved shell were also considered to assess the applicability of the proposed method for the shape sensing of complex structures. Remarkably, the outcomes of the iFEM-GA approach with the reduced number of sensors agreed well with those of the full-sensor counterpart for all of the plate/shell case studies. Hence, this study reveals the superior performance of the iFEM-GA method as a viable sensor placement strategy for the accurate shape sensing of engineering structures with only a few sensors.

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“…On this basis, smoothed iFEM approach has been proposed by coupling enhanced iFEM formulation with smoothing element analysis for effective shape sensing application [54]. The predictive capability of the enhanced iFEM approaches was numerically and experimentally assessed on real-time displacement monitoring of moderately thick sandwich structures [55][56]. In addition to top/bottom sensor, these iFEM formulations require an additional set of interlaminar in-situ strain data (which can be obtained from embedded FBG sensors) for thick structures.…”

Section: Introductionmentioning

confidence: 99%

Experimental and numerical investigation on large deformation reconstruction of thin laminated composite structures using inverse finite element method

Abdollahzadeh

Ali

Yıldız

et al. 2022

Thin-Walled Structures

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An experimental implementation of inverse finite element method for real-time shape and strain sensing of composite and sandwich structures

Cited by 56 publications

References 60 publications

An experimental investigation on damage mechanisms of thick hybrid composite structures under flexural loading using multi-instrument measurements

An experimental investigation on damage mechanisms of thick hybrid composite structures under flexural loading using multi-instrument measurements

Sensor Placement Optimization for Shape Sensing of Plates and Shells Using Genetic Algorithm and Inverse Finite Element Method

Experimental and numerical investigation on large deformation reconstruction of thin laminated composite structures using inverse finite element method

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