Investigation flexural behavior of hybrid-reinforced layered filament wound pipes using experimental tests and numerical model

Masoumi, M.; Abdellahi, Sayyed Behzad; Hejazi, Sayyed Mahdi

doi:10.1177/15280837211034244

Cited by 5 publications

(4 citation statements)

References 35 publications

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“…Micromechanics rules for mechanical properties of GFRP layers [44][45][46]. Mechanical properties of the GFRP layers can be obtained using the equations below:…”

Section: Data Availability Statementmentioning

confidence: 99%

Enhanced ANN Predictive Model for Composite Pipes Subjected to Low-Velocity Impact Loads

et al. 2023

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This paper presents an enhanced artificial neural network (ANN) to predict the displacement in composite pipes impacted by a drop weight having different velocities. The impact response of fiber-reinforced polymer composite pipes depends on several factors including thickness, stacking sequence, and the number of layers. These factors were investigated in an earlier study using sensitivity analysis, and it was found that they had the most prominent effect on the impact resistance of the composite pipes. In this present study, composite pipes with a diameter of 54 mm are considered to explore the damages induced by low-velocity impact and the influence of these damages on their strength. To evaluate the effect of low-velocity, the pipes were exposed to impacts at different velocities of 1.5, 2, 2.5, and 3 m/s, and preliminary damage was initiated. Next, we used Jaya and E-Jaya algorithms to enhance the ANN algorithm for good training and prediction. The Jaya algorithm has a basic structure and needs only two requirements, namely, population size and terminal condition. Recently, Jaya algorithm has been widely utilized to solve various problems. Due to its single learning technique and limited population information, Jaya algorithm may quickly be trapped in local optima while addressing complicated optimization problems. For better prediction, an enhanced Jaya (E-Jaya) algorithm has been presented to enhance global searchability. In this study, ANN is enhanced based on the influential parameters using E-Jaya to test its effectiveness. The results showed the effectiveness of the E-Jaya algorithm for best training and prediction compared with the original algorithm.

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“…Micromechanics rules for mechanical properties of GFRP layers [44][45][46]. Mechanical properties of the GFRP layers can be obtained using the equations below:…”

Section: Data Availability Statementmentioning

confidence: 99%

Enhanced ANN Predictive Model for Composite Pipes Subjected to Low-Velocity Impact Loads

et al. 2023

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“…Afterward, the actual load based on the experimental procedure is applied to the macro model to analyze the mechanical behavior of the composite. 17,21–24…”

Section: Introductionmentioning

confidence: 99%

“…Afterward, the actual load based on the experimental procedure is applied to the macro model to analyze the mechanical behavior of the composite. 17,[21][22][23][24] According to previous studies, the majority of research has been focused on tensile and flexural properties of the NC3DOW composites and there are limitation papers that have investigated other properties such as the torsional behavior of NC3DOW composites. The torsional behavior of the composite shows the effect of fiber orientation and shear stiffness of the composite.…”

Section: Introductionmentioning

confidence: 99%

Torsional behavior of non-crimp orthogonal woven composite using experimental and numerical methods

Aghaei

Varsei

Ajeli

et al. 2022

Journal of Industrial Textiles

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Nowadays, using three dimensional fabric as a reinforcement part in the composite has been increased. Non-crimp three dimensional orthogonal woven fabric is a subgroup of 3D woven fabrics that in this study was used to fabricate composite preforms. The fabrics were produced by glass yarn in two different fiber volume fractions. All fabric preforms were utilized to produce composites with polyester and epoxy resins. To compare the torsional behavior of the composites, a torsion test was applied to all samples and torque-revolution curves from the experimental results were compared together. Results showed that composites that were fabricated by epoxy resin have more torsional strength in comparison with composites in that their matrix is polyester resin. Moreover, preforms with high fiber volume fractions showed high torsional strength in each type of matrix. The torsion strength of high volume fraction for polyester matrix was 47.34 KPa, however for the sample with epoxy matrix the torsion strength was determined 81.26 KPa. Furthermore, a multiscale finite element model was applied to calculate elastic constants and predict the torsional behavior of the composites. The numerical results were compared with experimental results that a good agreement between numerical and experimental results was observed. Therefore, the proposed model can predict the torsional behavior of the composite with different fiber volume fractions.

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“…In this method, a unit-cell of the composite is modeled at the meso scale, and the essential parameters are extracted from the meso model. 19,20 Recently, researchers have used Vassiliadis et al's 15 model to create weft-knitted loop geometry at the meso scale. 7,9,[21][22][23] In this model, the geometry of the weft-knitted loop based on the coordinate points of the loop geometry is created in a three-dimensional space.…”

Section: Introductionmentioning

confidence: 99%

Multi-scale finite element modeling of bending behavior of 3D multi-cell spacer weft-knitted composites with different structures

Yang

Eskenati

2021

Polymers and Polymer Composites

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In the present study, a multi-scale finite element model is proposed to predict the linear and nonlinear behavior of the 3D multi-cell spacer weft-knitted composite under bending load. In this study, a unit-cell of the composite which includes plain and biaxial weft-knitted structures was modeled at the meso scale. Periodic boundary conditions were applied to the meso model to calculate the elastic constants of each composite structure. In order to obtain failure parameters of the composites, the Puck failure criterion model was utilized by a VUMAT code for the meso model. Afterward, the elastic constants of the composites based on a Python code were extracted from the meso model. Moreover, failure parameters that include tensile and compressive strength through the fiber and transverse directions were obtained from the meso model. All elastic and failure parameters were used for the macro model which is created with different profiles under bending load. The numerical results at the meso scale showed that the presence of the weft and warp yarns inside the biaxial weft-knitted composite increases the strength of the composite through the course and wale directions. Moreover, the stiffness of the composite would be improved. So, the samples that contained a biaxial composite had more stiffness and bending strength in comparison with plain composite samples because the top and bottom layers were manufactured by the biaxial weft-knitted structure. Besides, the comparison between numerical and experimental force–deflection curves showed that the proposed model could predict the linear and nonlinear behavior of the composites with high accuracy. So, this model can be used for other textile composites with complex shapes to predict the mechanical behavior of them.

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Investigation flexural behavior of hybrid-reinforced layered filament wound pipes using experimental tests and numerical model

Cited by 5 publications

References 35 publications

Enhanced ANN Predictive Model for Composite Pipes Subjected to Low-Velocity Impact Loads

Enhanced ANN Predictive Model for Composite Pipes Subjected to Low-Velocity Impact Loads

Torsional behavior of non-crimp orthogonal woven composite using experimental and numerical methods

Multi-scale finite element modeling of bending behavior of 3D multi-cell spacer weft-knitted composites with different structures

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