• Structural Engineering and Mechanics
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• v.72 no.6
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• pp.713-722
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• 2019

Micromechanics is a technique for the analysis of composites or heterogeneous materials which focuses on the components of the intended structure. Each one of the components can exhibit isotropic behavior, but the microstructure characteristics of the heterogeneous material result in the anisotropic behavior of the structure. In this research, the general mechanical properties of a 3D anisotropic and heterogeneous Representative Volume Element (RVE), have been determined by applying periodic boundary conditions (PBCs), using the Asymptotic Homogenization Theory (AHT) and strain energy. In order to use the homogenization theory and apply the periodic boundary conditions, the ABAQUS scripting interface (ASI) has been used along with the Python programming language. The results have been compared with those of the Homogeneous Boundary Conditions method, which leads to an overestimation of the effective mechanical properties. According to the results, applying homogenous boundary conditions results in a 33% and 13% increase in the shear moduli G₂₃ and G₁₂, respectively. In polymeric composites, the fibers have linear and brittle behavior, while the resin exhibits a non-linear behavior. Therefore, the nonlinear effects of resin on the mechanical properties of the composite material is studied using a user-defined subroutine in Fortran (USDFLD). The non-linear shear stress-strain behavior of unidirectional composite laminates has been obtained. Results indicate that at arbitrary constant stress as 80 MPa in-plane shear modulus, G₁₂, experienced a 47%, 41% and 31% reduction at the fiber volume fraction of 30%, 50% and 70%, compared to the linear assumption. The results of this study are in good agreement with the analytical and experimental results available in the literature.

• Composites Research
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• v.32 no.5
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• pp.249-257
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• 2019

In this paper, the buckling behavior of triaxially braided circular arch with monosymmetric open section subjected to three-point bending was studied experimentally and numerically. First, test specimens were manufactured using vacuum assisted resin transfer molding (VARTM). Then the specimen was tested under three-point bending to determine the ultimate buckling strength. Before performing the numerical analysis, effective material properties of the braided composite were obtained through micro-meso scale analysis virtual testing validated with available test results. Then linear buckling analysis and geometrically non-linear post buckling analysis, established to simulate the test setup, were performed to study the buckling behavior of the composite frame. Analysis results were compared with experimentally obtained ones for verification. The effect of manufacturing defects of tow misalignment, irregular surface and resin rich region, and uncertainties during test setup were studied using numerical models. From the numerical analyses performed it was observed that both manufacturing defect and uncertainties had effect on the buckling behavior and strength.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.33 no.3
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• pp.833-841
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• 2013

In the case of composite material, a variety of characteristics were expressed depending on the materials that were composed of. In this study, the materials showing non-linear shear behavior were investigated among FRP composite. Each specimen was designed and analyzed according to ASTM D4255 method: regulations on the 2-rail. The dependent variables included in this experiment were a variety of fiber, fiber volume ratio, fiber array direction, temperature, material homogeneity. For determination of characteristics based on the fiber array, fiber array direction of 0, 30, 45, and 60 degrees were selected for test specimen. Temperature of 25, 40, 60, and $80^{\circ}C$ were considered for investigation of FRP materials'shear behavior based on the external temperature. Nonlinear shear behavior was observed throughout the FRP composite material in this study. Also, using vinyl ester resins, high fiber volume ratio, and fiber array direction of 45 degree appeared to show the most prominent nonlinear shear behavior. As for the findings related to the temperature change, non-linear behavior was decreased as the external temperature increased. For factory manufactured product, non-linear behavior was relatively at parity in comparison to the behavior found in the hand lay-up FRP composite specimen.

• Steel and Composite Structures
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• v.42 no.2
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• pp.151-159
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• 2022

This study discusses a hypothetical method for tracking the propagation damage of Carbon Reinforced Fiber Plastic (CRFP) components underneath vibration fatigue. The High Cycle Fatigue (HCF) behavior of composite materials was generally not as severe as this of admixture alloys. Each fissure initiation in metal alloys may quickly lead to the opposite. The HCF behavior of composite materials is usually an extended state of continuous degradation between resin and fibers. The increase is that any layer-to-layer contact conditions during delamination opening will cause a dynamic complex response, which may be non-linear and dependent on temperature. Usually resulted from major deformations, it could be properly surveyed by a non-contact investigation system. Here, this article discusses the scanning laser application of that vibrometer to track the propagation damage of CRFP components underneath fatigue vibration loading. Thus, the study purpose is to demonstrate that the investigation method can implement systematically a series of hypothetical means and dynamic characteristics. The application of the relaxation method based on numerical simulation in the Artificial Intelligence (AI) Evolved Bat (EB) strategy to reduce the dynamic response is proved by numerical simulation. Thermal imaging cameras are also measurement parts of the chain and provide information in qualitative about the temperature location of the evolution and hot spots of damage.

• Proceedings of the KSR Conference
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• 2010.06a
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• pp.557-563
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• 2010

Mode II interlaminar fracture toughness was measured and fractured surfaces were observed of carbon/epoxy and glass/epoxy woven fabric composites for carbody structure. Woven fabric carbon/epoxy and glass/epoxy composites that made with prepreg and epoxy resin(RS1222) are used in carbody structure of Korean tilting train(TTX) and low floor bus. ENF(End Notched Flexure) specimens having $120mm{\times}20m{\times}5mm$ shape and 35mm initial crack were made with each composites and three point bending tests according to ASTM D790 were conducted for these specimens. Crack lengths in tests were recorded using optical microscope and digital camcorder. NL(Non Linear), 5% offset and Max. load points in load -displacement curves were checked and mode II interlaminar fracture toughness of these points were calculated and compared. Fractured surfaces of specimens were observed using optical microscope and mode II delamination behavior of each composites was discussed.

• Nuclear Engineering and Technology
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• v.54 no.1
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• pp.310-317
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• 2022

The mass attenuation coefficient is the primary physical parameter to model narrow beam gamma-ray attenuation. A new machine learning based approach is proposed to model gamma-ray shielding behavior of composites alternative to theoretical calculations. Two fuzzy logic algorithms and a neural network algorithm were trained and tested with different mixture ratios of vanadium slag/epoxy resin/antimony in the 0.05 MeV-2 MeV energy range. Two of the algorithms showed excellent agreement with testing data after optimizing adjustable parameters, with root mean squared error (RMSE) values down to 0.0001. Those results are remarkable because mass attenuation coefficients are often presented with four significant figures. Different training data sizes were tried to determine the least number of data points required to train sufficient models. Data set size more than 1000 is seen to be required to model in above 0.05 MeV energy. Below this energy, more data points with finer energy resolution might be required. Neuro-fuzzy models were three times faster to train than neural network models, while neural network models depicted low RMSE. Fuzzy logic algorithms are overlooked in complex function approximation, yet grid partitioned fuzzy algorithms showed excellent calculation efficiency and good convergence in predicting mass attenuation coefficient.