• Transactions of the Korean Society of Mechanical Engineers A
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• v.34 no.11
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• pp.1705-1713
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• 2010

The reliable fatigue life for hybrid composite joint structures was estimated by a statistical method for evaluating fatigue life; the results of the fatigue test varied widely. Cyclic bending tests were performed on a cantilever beam with a hybrid composite joint, which was developed for the body of a low-floor bus. In order to estimate the fatigue life of the hybrid composite joint structure by comparing the data obtained during the fatigue tests, the most suitable probabilistic density function among the normal, lognormal, and Weibull distributions was selected. The probabilistic-stress-life (P-S-N) curves calculated by using the selected Weibull distribution was suggested for process of statistical fatigue life estimation and reliability design.

• Composites Research
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• v.22 no.2
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• pp.7-13
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• 2009

With the wide application of fiber-reinforced composite material in aero-structures and mechanical parts, the design of composite joint have become a very important research area because they are often the weakest areas in composite structures. In this paper, the failure strengths of the hybrid composite joints which were composed of a combination of an adhesive joint and a mechanical joint were evaluated and predicted. The 10 hybrid joint specimens which have different w/d, e/d and adherend thickness were manufactured and tested. The damage zone theory and the failure area index method were used for the failure prediction of the adhesive joint and the mechanical joint, respectively and the hybrid joints were assumed to be failures if either of the two failure criteria was satisfied. From the results of experiments and analyses, the failure strengths of the hybrid joints could be predicted to within 25.5%.

• Proceedings of the Korean Society For Composite Materials Conference
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• 2004.04a
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• pp.228-231
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• 2004

For the bolted joint of the composite structure, quasi-isotropic stacking is generally used to increase the bearing strength. For the bolted joint of uni-directional composite, the fatigue life limit of the bolted joint can be improved by applying clamping force though the static strength is still very low. In this paper, the static and fatigue characteristics of hybrid joint are investigated which can overcome the disadvantage of the bolted joint of uni-directional composite under static loading by applying adhesive joining. The experimental result shows that the static strength and fatigue life can be improved by applying clamping force to the hybrid joint and the hybrid joint is a good solution for the efficiency of the composite structures.

• Composites Research
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• v.32 no.1
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• pp.37-44
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• 2019

The reinforcement effect of micro-bolt for a bonded scarf joint was investigated. Three scarf ratios of 1/10, 1/20, and 1/30 were considered to examine the effect of scarf patch configuration on joint strength. To maintain the same density of micro-bolt, 16, 32, and 48 bolts were installed in the scarf joint specimens with scarf ratios of 1/10, 1/20, and 1/30, respectively. Tests were also carried out on the joints that are bonded with only adhesive and that are fastened with only micro-bolts to obtain reference values. The average failure loads of the adhesive joints with scarf ratios of 1/10, 1/20, and 1/30 were 29.7, 39.6, and 44.8 kN, respectively. In case of micro-bolt reinforcement, the failure loads at the same scarf ratios were 28.4, 37.2, and 40.1 kN, respectively, which corresponds to 96, 94, and 90% of the pure adhesive joint failure loads. In the case of using only micro-bolts, the failure loads were only 13-25% of the average failure loads of pure adhesive joints. Fatigue test was also conducted for the joints with scarf ratio of 1/10. The results show that the fatigue strength of hybrid joints using both adhesive and microbolts together slightly increased compared to the fatigue strength of adhesive joint, but the rate of increase was small to 2-3%. Through this study, it was confirmed that the reinforcement effect of micro-bolt is negligible in the scarf joints where shear stress is dominating the failure, unlike in the structure where peel stress is dominant.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.34 no.1
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• pp.55-60
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• 2010

The honeycomb composite joint structure designed for application to a tilting KTX railroad car body is subjected to bending loads of a cantilever type. Honeycomb sandwich composite panel-joint attached in the real tilting car body was fabricated and sectioned as several beam-joint specimens for the bending test. The fracture behaviors of these specimens under static loads were different from those under cyclic loads. Static bending loads caused shear deformation and fracture in the honeycomb core region, while fatigue cyclic bend loading caused delamination along the interface between the composite skin and the honeycomb core, and/or caused a fracture in the welded part jointed with the steel under-frame. These fracture behaviors could occur in other industrial honeycomb composite joints with similar sub-structures, and be used for improving design parameters of a honeycomb composite joint structure.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.48 no.10
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• pp.773-782
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• 2020

The development of joint FE models for deep learning neural network (DLNN)-based hybrid FEA is presented. Material models of bolts and bearings in the front axle of tractor, showing complex behavior induced by various tightening conditions, were replaced with DLNN models. Bolts are modeled as one-dimensional Timoshenko beam elements with six degrees of freedom, and bearings as three-dimensional solid elements. Stress-strain data were extracted from all elements after finite element analysis subjected to various load conditions, and DLNN for bolts and bearing were trained with Tensorflow. The DLNN-based joint models were implemented in the ABAQUS user subroutines where stresses from the next increment are updated and the algorithmic tangent stiffness matrix is calculated. Generalization of the trained DLNN in the FE model was verified by subjecting it to a new loading condition. Finally, the DLNN-based FEA for the front axle of the tractor was conducted and the feasibility was verified by comparing with results of a static structural experiment of the actual tractor.