• Journal of the Korean Society for Railway
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• v.11 no.3
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• pp.280-285
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• 2008

Two kinds of failure model, that is, the Gurson model and a shear failure model were used for the finite element analyses of simple and notch tensile specimens and axial compression of a fracture tube with initial saw-cuts. The parameter values for the shear failure model were determined by a combined experimental and numerical analysis of the notch tensile specimens. After fitting the numerical parameters such as the yielding stress and the fracture shear strains, the Gurson model and the shear failure model were applied to the analysis of the fracture tube. Although the Gurson model and the shear failure model showed similar fracture behavior for the case of the tensile specimens, the respective results were different in the axial force and the crack growth rate of the fracture tube. That is, the shear failure model required more axial force to make the cracks propagate along the tube than the Gurson model. These are believed to show the lack of damage evolution process of the shear failure model. To decide which model is better in the tube analysis, experimental verification will be necessary.

• Proceedings of the KSME Conference
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• 2003.04a
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• pp.310-315
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• 2003

This paper presents the effect of boundary condition of failure pressure model for buried pipelines on failure prediction by using a failure probability model. The first order Taylor series expansion of the limit state function is used in order to estimate the probability of failure associated with various corrosion defects for long exposure periods in years. A failure pressure model based on a failure function composed of failure pressure and operation pressure is adopted for the assessment of pipeline failure. The effects of random variables such as defect depth, pipe diameter, defect length, fluid pressure, corrosion rate, material yield stress, material ultimate tensile strength and pipe thickness on the failure probability of the buried pipelines are systematically studied by using a failure probability model for the corrosion pipeline.

• Journal of the Korean Data and Information Science Society
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• v.14 no.2
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• pp.393-403
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• 2003

In this paper, various replacement policies for the general failure model are considered. There are two types of failure in the general failure model. One is Type I failure (minor failure) which can be removed by a minimal repair and the other is Type II failure (catastrophic failure) which can be removed only by a complete repair. In this model, when the unit fails at its age t, Type I failure occurs with probability 1-p(t) and Type II failure occurs with probability p(t), $0{\leq}p(t){\leq}1$. Under the model, optimal replacement policies for the long-run average cost rate and the limiting efficiency are considered. Also taking the cost and the efficiency into consideration at the same time, the properties of the optimal policies under the Cost-Priority-Criterion and the Efficiency-Priority-Criterion are obtained.

• Journal of Korean Society for Quality Management
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• v.31 no.3
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• pp.185-192
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• 2003

In this paper, the properties on the optimal replacement policies for the general failure model are developed. In the general failure model, two types of system failures may occur : one is Type I failure (minor failure) which can be removed by a minimal repair and the other, Type II failure (catastrophic failure) which can be removed only by complete repair. It is assumed that, when the unit fails, Type I failure occurs with probability 1-p and Type II failure occurs with probability p, $0\leqp\leq1$. Under the model, the system is minimally repaired for each Type I failure, and it is repaired completely at the time of the Type II failure or at its age T, whichever occurs first. We further assume that the repair times are non-negligible. It is assumed that the minimal repair times in a renewal cycle consist of a strictly increasing geometric process. Under this model, we study the properties on the optimal replacement policy minimizing the long-run average cost per unit time.

• Journal of the Korean Data and Information Science Society
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• v.14 no.4
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• pp.997-1005
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• 2003

In this paper, the problem of determining optimal burn-in time is considered under a general failure model. There are two types of failure in the general failure model. One is Type I failure (minor failure) which can be removed by a minimal repair and the other is Type II failure (catastrophic failure) which can be removed only by a complete repair. In this model, when the unit fails at its age t, Type I failure occurs with probability 1 - p(t) and Type II failure occurs with probability p(t), $0{\leq}p(t)\leq1$. Under the model, the properties of optimal burn-in time maximizing mean time to the catastrophic failure during field operation are obtained. The obtained results are also applied to some illustrative examples.

• International Journal of Precision Engineering and Manufacturing
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• v.4 no.6
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• pp.12-19
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• 2003

This paper presents the effect of boundary conditions in various failure pressure models published for the estimation of failure pressure. Furthermore, this approach is extended to the failure prediction with the aid of a failure probability model. The first order Taylor series expansion of the limit state function is used in order to estimate the probability of failure associated with each corrosion defect in buried pipelines for long exposure period with unit of years. A failure probability model based on the von-Mises failure criterion is adapted. The log-normal and standard normal probability functions for varying random variables are adapted. The effects of random variables such as defect depth, pipe diameter, defect length, fluid pressure, corrosion rate, material yield stress, material ultimate tensile strength and pipe thickness on the failure probability of the buried pipelines are systematically investigated for the corrosion pipeline by using an adapted failure probability model and varying failure pressure model.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.32 no.12
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• pp.1063-1071
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• 2008

This paper provides a failure pressure evaluation model for local wall-thinned elbows. In this study, parametric finite element analyses are performed on the elbows containing local wall-thinning defect at their intrados and extrados, and the failure pressures are obtained from the analysis results by applying a local failure criterion that was validated by real-scale pipe tests. An evaluation model including the effects of thinning depth, length, circumferential angle, thinning location, and elbow geometries on the failure pressure is derived based on the evaluated failure pressures. The proposed model agrees well with the results of finite element analyses and reasonably estimates the dependence of failure pressure on the wall-thinning dimensions and elbow geometries. Also, the comparison with experimental data demonstrates that the proposed evaluation model can accurately predict the failure pressure of local wall-thinned elbows.

• International Journal of Reliability and Applications
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• v.10 no.2
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• pp.101-107
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• 2009

In the accelerated tests, the importance of correct failure analysis must be strongly emphasized. Understanding the failure mechanisms is requisite for designing and conducting successful accelerated life test. Under this presumption, a rational method must be identified to relate the results of accelerated tests quantitatively to the reliability or failure rates in use conditions, using a scientific acceleration transform. Most widely used models for relating the results of accelerated tests quantitatively to the reliability or failure rates in use conditions are an accelerated failure time model and a proportional hazards model. The purpose of this research is to compare the usability of the accelerated failure time model and proportional hazards model in the accelerated life tests.

• Journal of the Earthquake Engineering Society of Korea
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• v.28 no.2
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• pp.113-119
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• 2024

Existing reinforced concrete buildings with seismically deficient column details affect the overall behavior depending on the failure type of column. This study aims to develop and validate a machine learning-based prediction model for the column failure modes (shear, flexure-shear, and flexure failure modes). For this purpose, artificial neural network (ANN), K-nearest neighbor (KNN), decision tree (DT), and random forest (RF) models were used, considering previously collected experimental data. Using four machine learning methodologies, we developed a classification learning model that can predict the column failure modes in terms of the input variables using concrete compressive strength, steel yield strength, axial load ratio, height-to-dept aspect ratio, longitudinal reinforcement ratio, and transverse reinforcement ratio. The performance of each machine learning model was compared and verified by calculating accuracy, precision, recall, F1-Score, and ROC. Based on the performance measurements of the classification model, the RF model represents the highest average value of the classification model performance measurements among the considered learning methods, and it can conservatively predict the shear failure mode. Thus, the RF model can rapidly predict the column failure modes with simple column details.

• International Journal of Reliability and Applications
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• v.2 no.3
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• pp.199-207
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• 2001

The failure rate functions between successive failures are of concatenated form. We allow the parameters of failure rate function change after a certain failure and its fixing. We confine out attention to a model wherein the interfailure times are described by its failure rate function. We suggest an adaptive failure rate function with a change-point under the assumption that interfailure times are record value statistics from a Weibull distribution. The proposed model will be applied through a practical example of software failure data.