• Composites Research
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• v.32 no.5
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• pp.258-264
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• 2019

In this paper, a progressive failure analysis method was developed using the Hashin failure criterion and crack band model. Using the failure criterion, the failure initiation was evaluated. If the failure initiation is occurred, the damage variables at each failure modes (fiber tension & compression, matrix tension & compression) was calculated according to linear softening degradation behavior and the variables are used to derive the damaged stiffness matrix. The damaged stiffness matrix is reflected to damaged material and the progressive failure analysis is continued until the damage variables to be 1 that complete failure of material. A series of processes were performed using FE commercial code ABAQUS with user defined material subroutine (UMAT). To evaluate the proposed progressive failure model, the experimental results of open hole composite laminate tests was compared with numerical result. Using digital image correlation system, the strain behavior also was compared. The proposed numerical results were coincided well with the experimental results.

• Aerospace Engineering and Technology
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• v.9 no.1
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• pp.9-16
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• 2010

In this study, structural analyses were carried out on the composite sandwich panel which was tested under compression loading. In the structural analyses, three types of finite element modelling were considered and linear buckling analysis and nonlinear analysis were performed for each FE-model. Through the analyses, it was found that shell elements for face parts and solid elements for core part were appropriate for the better prediction of the buckling load of the panel. If the material failure of the face is critical than overall buckling of the sandwich panel, the use of one shell element through the thickness direction was suitable in the FE-model for the better predictions of failure location and failure load.

• Composites Research
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• v.16 no.1
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• pp.13-18
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• 2003

Prediction of composite fatigue life is not a straightforward matter, depending on various failure modes and their interactions. In this paper, a methodology is presented to predict fatigue life and residual strength of composite materials based on Phenomenological Model(non-linear fatigue damage model). It is assumed that the residual strength is a monotonically decreasing function of the number of loading cycles and applied fatigue stress ratio and the model parameters(strength degradation parameter and fatigue shape parameter) are assumed as function of fatigue life. Then S-N curve is used to extract model parameters that are required to characterize the stress levels comprising a randomly-ordered load spectrum. Different stress ratios (${\sigma}_{min}/{\;}{\sigma}_{max}$) are handled with Goodman correction approach(fatigue envelope) and the residual strength after an arbitrary load cycles is represented by two parameter weibull functions.

• Journal of the Earthquake Engineering Society of Korea
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• v.12 no.1
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• pp.11-20
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• 2008

In probabilistic seismic analysis of nonlinear structural system, dynamic analysis is performed to obtain the distribution of the response estimate using input ground motion time histories which correspond to a given seismic hazard level. This study investigates the differences in the distribution of the responses and the failure probability according to input ground motion models. Two types of input ground motion models are considered: real earthquake records scaled to specified intensity level and artificial input ground motion fitted to design response spectrum. Simulation results fir a nonlinear SDOF system demonstrate that the spectrum matched input ground motion produces larger failure probability than those of scaled input ground motion due to biased responses. Such tendency is more remarkable in the site of soft soil conditions. Analysis results show that such difference of failure probability is due to the conservative estimation of design response spectrum in the range of long period of ground motion.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.29 no.5 s.236
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• pp.754-761
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• 2005

The 40\% of wall thickness criterion which has been used as a plugging rule of steam generator tubes is applicable only to a single cracked tube. In the previous studies performed by authors, several global failure prediction models were introduced to estimate the failure loads of steam generator tubes containing two adjacent parallel axial through-wall cracks. These models were applied for thin plates with two parallel cracks and the COD base model was selected as the optimum one. The objective of this study is to verify the applicability of the proposed optimum global failure prediction model for real steam generator tubes with two parallel axial through-wall cracks. For the sake of this, a series of plastic collapse tests and finite element analyses have been carried out fur the steam generator tubes with two machined parallel axial through-wall cracks. Thereby, it was proven that the proposed optimum failure prediction model can be used as the best one to estimate the failure load quite well. Also, interaction effects between two adjacent cracks were assessed through additional finite element analyses to investigate the effect on the global failure behavior.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.26 no.4D
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• pp.593-600
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• 2006

Joint opening of jointed concrete pavement is caused by change in temperature and humidity of adjoined slab. The magnitude of joint opening influences on the load-transfer-efficiency and the behavior of sealant. If temperature or humidity decreases, joint opening increases. Generally maximum joint opening of a given joint is predicted by using AASHTO equation. While different magnitudes of joint opening at the individual joints have been observed in a given pavement section, AASHTO equation is limited to predict average joint opening in a given pavement section. Therefore the AASHTO equation may underestimate maximum joint for the half of joint in a given pavement section. Joints showing larger opening than the designed may experience early joint sealant failure, early faulting. Also unexpected spalling may be followed due to invasion of fine aggregate into the joints after sealant pop-off. In this study, the variation of the joint opening in a given pavement section was investigated based on the LTPP SMP data. Factors affecting on the variation are explored. Finally a probabilistic joint opening model is developed. This model can account for the reliability of the magnitude of joint opening so that the designer can select the ratio of underestimated joint opening.

• International Journal of Highway Engineering
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• v.13 no.4
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• pp.41-50
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• 2011

It is well-known that pavement is easily damaged by several factors including permanent deformation and fatigue crack, causing service life of the pavement to be shorter than expected. It is very important to predict amount of permanent deformation for designing pavement and developing design method of pavement. A new model of permanent deformation of pavement materials based on concept of shear stress ratio has been proposed because the lower pavement materials are highly affected by shear strength of the material. In this study a large repetitive triaxial load test has been adapted for performing test of permanent deformation of crushed subbase materials. The test procedure which includes concept of shear stress ratio has been newly developed. Several important model parameters can be obtained from the test that can be used for making correct permanent deformation model of the material.

• Journal of the Korea Convergence Society
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• v.13 no.2
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• pp.249-255
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• 2022

This study proposed an analysis framework for real-time prediction of CNC processing defects using machine learning-based models that are recently attracting attention as processing defect prediction methods, and applied it to CNC machines. Analysis shows that the XGBoost, CatBoost, and LightGBM models have the same best accuracy, precision, recall, F1 score, and AUC, of which the LightGBM model took the shortest execution time. This short run time has practical advantages such as reducing actual system deployment costs, reducing the probability of CNC machine damage due to rapid prediction of defects, and increasing overall CNC machine utilization, confirming that the LightGBM model is the most effective machine learning model for CNC machines with only basic sensors installed. In addition, it was confirmed that classification performance was maximized when an ensemble model consisting of LightGBM, ExtraTrees, k-Nearest Neighbors, and logistic regression models was applied in situations where there are no restrictions on execution time and computing power.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.30 no.8
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• pp.103-111
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• 2002

Steady-state creep analysis of power generation turbine blade is carried out considering thermal loads and centrifugal forces. Creep strains and stresses of the turbine blade are calculated for 3-D finite clement model of the turbine blade. From the numerical results, creep life of the turbine blade is predicted. The results of creep analysis during about 200 hours indicate that creep strains of the turbine blade do not reach the rupture strain of GTD111. Creep stresses of the turbine blade are relaxed as time increases. Maximum creep strain occurs at the tip section of the airfoil pressure surface. The maximum creep strain of the turbine blade is expected close to the rupture strain after 50,000 hours approximately. The turbine blade may not have creep damage for the starting procedure of the turbine.

• Composites Research
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• v.19 no.3
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• pp.7-14
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• 2006

In this paper, an integrated probabilistic strength analysis was conducted to predict the reliability of a composite pressure vessel under inner pressure loading condition. As a probabilistic strength analysis, the probabilistic progressive failure model consisting of progressive failure model and Monte Carlo simulation was incorporated with a commercial FEA code, ABAQUS Standard, to perform the probabilistic failure analysis of composite structure which has a complex shape and boundary conditions. As design random variables, the laminar strengths of each direction were considered. Finally, from probabilistic strength analysis, the scattering of burst pressure could be explained and the reliability of composite pressure vessel could be obtained for each component. In case of composite structures in mass production, the effects of uncertainties in material and manufacturing on the performance of composite structures would apparently become larger. So, the probabilistic strength analysis is essential for the structural design of composite structures in mass production.