• Geomechanics and Engineering
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• v.29 no.3
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• pp.249-258
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• 2022

A disc cutter is an excavation tool on a tunnel boring machine (TBM) cutterhead; it crushes and cuts rock mass while the machine excavates using the cutterhead's rotational movement. Disc cutter wear occurs naturally. Thus, along with the management of downtime and excavation efficiency, abrasioned disc cutters need to be replaced at the proper time; otherwise, the construction period could be delayed and the cost could increase. The most common prediction models for TBM performance and for the disc cutter lifetime have been proposed by the Colorado School of Mines and Norwegian University of Science and Technology. However, design parameters of existing models do not well correspond to the field values when a TBM encounters complex and difficult ground conditions in the field. Thus, this study proposes a series of machine learning models to predict the disc cutter lifetime of a shield TBM using the excavation (machine) data during operation which is response to the rock mass. This study utilizes five different machine learning techniques: four types of classification models (i.e., K-Nearest Neighbors (KNN), Support Vector Machine, Decision Tree, and Staking Ensemble Model) and one artificial neural network (ANN) model. The KNN model was found to be the best model among the four classification models, affording the highest recall of 81%. The ANN model also predicted the wear rate of disc cutters reasonably well.

• Communications for Statistical Applications and Methods
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• v.24 no.4
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• pp.397-419
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• 2017

A four-parameter extended fatigue lifetime model called the odd Birnbaum-Saunders geometric distribution is proposed. This model extends the odd Birnbaum-Saunders and Birnbaum-Saunders distributions. We derive some properties of the new distribution that include expressions for the ordinary moments and generating and quantile functions. The method of maximum likelihood and a Bayesian approach are adopted to estimate the model parameters; in addition, various simulations are performed for different parameter settings and sample sizes. We propose two new models with a cure rate called the odd Birnbaum-Saunders mixture and odd Birnbaum-Saunders geometric models by assuming that the number of competing causes for the event of interest has a geometric distribution. The applicability of the new models are illustrated by means of ethylene data and melanoma data with cure fraction.

• Journal of Korean Society of Steel Construction
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• v.14 no.5 s.60
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• pp.627-639
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• 2002

Bridge construction is almost complete in many countries. Thus, the government and highway agencies change their focus from constructing to maintaining. Effectively maintaining bridges require predicting their lifespan using a system reliability viewpoint. Likewise, maintenance models based on the system reliability concept should be developed. Thus, this study developed maintenance models for preventive maintenance and essential maintenance using system reliability and lifetime distributions. The optimal maintenance strategy for an existing bridge was obtained using the developed maintenance models.

• Journal of Radiation Protection and Research
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• v.46 no.3
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• pp.83-97
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• 2021

Background: The lifetime risk of lung cancer incidence due to radiation for nonsmokers is overestimated because of the use of the average cancer baseline risk among a mixed population, including smokers. In recent years, the generalized multiplicative (GM)-excess relative risk (ERR) model has been developed in the life span study of atomic bomb survivors to consider the joint effect of radiation and smoking. Based on this background, this paper discusses the issues of radiation risk assessment considering smoking in two parts. Materials and Methods: In Part 1, we proposed a simple method of estimating the baseline risk for nonsmokers using current smoking data. We performed sensitivity analysis on baseline risk estimation to discuss the birth cohort effects. In Part 2, we applied the GM-ERR model for Japanese smokers to calculate lifetime attributable risk (LAR). We also performed a sensitivity analysis using other ERR models (e.g., simple additive (SA)-ERR model). Results and Discussion: In Part 1, the lifetime baseline risk from mixed population including smokers to nonsmokers decreased by 54% (44%-60%) for males and 24% (18%-29%) for females. In Part 2, comparison of LAR between SA- and GM-ERR models showed that if the radiation dose was ≤200 mGy or less, the difference between these ERR models was within the standard deviation of LAR due to the uncertainty of smoking information. Conclusion: The use of mixed population for baseline risk assessment overestimates the risk for lung cancer due to low-dose radiation exposure in Japanese males.

• Communications for Statistical Applications and Methods
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• v.28 no.6
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• pp.595-610
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• 2021

Recently a few articles have derived robust first-order rotatable and D-optimal designs for the lifetime response having distributions gamma, lognormal, Weibull, exponential assuming errors that are correlated with different correlation structures such as autocorrelated, intra-class, inter-class, tri-diagonal, compound symmetry. Practically, a first-order model is an adequate approximation to the true surface in a small region of the explanatory variables. A second-order model is always appropriate for an unknown region, or if there is any curvature in the system. The current article aims to extend the ideas of these articles for second-order models. Invariant (free of the above four distributions) robust (free of correlation parameter values) second-order rotatable designs have been derived for the intra-class and inter-class correlated error structures. Second-order rotatability conditions have been derived herein assuming the response follows non-normal distribution (any one of the above four distributions) and errors have a general correlated error structure. These conditions are further simplified under intra-class and inter-class correlated error structures, and second-order rotatable designs are developed under these two structures for the response having anyone of the above four distributions. It is derived herein that robust second-order rotatable designs depend on the respective error variance covariance structure but they are independent of the correlation parameter values, as well as the considered four response lifetime distributions.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.40 no.3
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• pp.92-98
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• 2017

The rapid growth of engineering technology and the emergence of systemized and large-scale engineering systems have resulted in complexity and uncertainty throughout the lifecycle activities of engineering systems. This complex and large-scale engineering system consists of numerous components, but system failure can be caused by failure of any one of a number of components. There is a real difficulty in managing such a complex and large-scale system as a part. In order to efficiently manage the system and have high reliability, it is necessary to structure a system with a complex structure as a sub-system. Also, in the case of a system in which cause of failures exist at the same time, it is required to identify the correlation of the components lifetime and utilize it for the design policy or maintenance activities of the system. Competitive risk theory has been used as a theory based on this concept. In this study, we apply the competitive risk theory to the models with combined structure of series and parallel which is the basic structure of most complex engineering systems. We construct a competing risks model and propose a mathematical model of net lifetime and crude lifetime for each cause of failure, assuming that the components consisting a parallel system are mutually dependent. In addition, based on the constructed model, the correlation of cause of failure is mathematically analyzed and the hazard function is derived by dividing into net lifetime and crude lifetime.

• Journal of Power System Engineering
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• v.14 no.6
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• pp.61-66
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• 2010

Engineering asset management (EAM) requires the accurate assessment of current and the prediction of future asset health condition. Suitable mathematical models that are capable of predicting time-to-failure and the probability of failure in future time are essential. In general reliability models, lifetime of component and system is estimated using failure time data. This paper deals with the reliability assessment of elevators using life of main components. Especially this work is concerned with the stochastic nature of life of elevator components. First, we investigate the Weibull statistical analysis of lifetime data for the components. The final goal is to establish the mathematical model for reliability assessment. This work provides more perspectives to future research in the fields of reliability and maintainability.

• Journal of the Korean Society for Railway
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• v.8 no.6 s.31
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• pp.544-549
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• 2005

Nowadays, most of bridge networks are complete or close to completion. The biggest challenge railroad./highway agencies and departments of transportation face is the maintenance of these networks, keeping them safe and serviceable, with limited funds. To maintain the bridges effectively, there is an urgent need to predict their remaining life from a system reliability viewpoint. And, it is necessary to develop the maintenance models based on system reliability concept. In this paper, maintenance models are developed for preventive maintenance and essential maintenance by using system reliability and lifetime distributions. The proposed model is applied to an existing railroad bridge. The optimal maintenance strategy of this bridge is obtained in terms of services life extension and cumulative maintenance cost.

• Proceedings of the Korean Institute of Electrical and Electronic Material Engineers Conference
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• 2004.07a
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• pp.405-408
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• 2004

In this work, Analytical model for voltage and current characteristics of NPT(Non-PunchThrough) IGBT(Insulated Gate Bipolar Transistor) was represented. voltage and current characteristics models were based on prediction on power loss of NPT IGBT during transient condition. For Analytical current model, excess carrier concentration and accumulated charge in active base width was analyzed with time variance. Analytical models were simulated by varying lifetime of excess minority carrier.

• Journal of Korean Society for Atmospheric Environment
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• v.8 no.1
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• pp.29-37
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• 1992

The risk of benzo(a)pyrene for cancer in the ambient air of Seoul was assessed by using the extrapolation methods. The average daily lifetime exposure of benzo(a)pyrene in the ambient air of Seoul was calculated at 6.97-24.30ng/$m^2$/day, which was based on the occurrence analysis of benzo(a)pyrene in the residential(Bull Kwang Dong) and traffic areas(Shin Chon) of Seoul. Using the dose scaling based on body surface area in comparisons of toxicity for extrapolation from animal to human and mathematical models from the high dose region, the low-dose risk was estimated. The response probabilities were estimated by the tolerance distribution models; Probit, Logit and Weibull model. They were consistent with the observed ones at experimental dose region. The unit risk estimates of these models were too low to be used. One-hit and multistage model to prove more conservative risk was selected. As a redult, the lifetime unit risk of benzo(a)pyrene for cancer and virtually safe dose were calculated; One-hit model provided the risk 2.8 $\times 10^{-7}$ and 3.4ng/$m^3$, respectively and multistage model provided 5.2 $\times 10^{-7}$ and 1.9ng/$m^3$ as the more conservatives. The lifetime excess risk estimates of benzo(a)pyrene for cancer were calculated at 0.37-1.30 persons/million persons by one-hit model and 0.69-2.41 persons/million persons by multistage model, which was considered in without virtual risk.