• 한국해안·해양공학회논문집
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• 제21권1호
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• pp.15-29
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• 2009

방파제 피복 블록은 주로 Hudson 공식과 van der Meer 공식을 사용하여 설계되고 있다. 각 공식을 사용하여 저항과 하중이 같아지는 최소 중량을 각각 산정하며 그 중 큰 값을 설계중량으로 채택한다. 이렇게 설계된 국내 무역항 12곳과 연안항 8곳의 방파제 피복 블록에 대하여 신뢰성 해석을 수행하였다. 신뢰성 해석 결과 산정된 파괴확률은 각 항만별 피복 블록의 안정성을 평가하는 기준이 된다. 최소 중량으로 설계한 경우에 파괴확률은 모든 항만에서 거의 비슷하게 계산되어 기존 방파제 피복 블록의 안전수준을 정량적으로 평가할 수 있게 되었다. 그리고 결정론적 설계법의 설계 기준인 안전율과 신뢰성 설계법의 설계 기준인 파괴확률은 뚜렷한 선형관계를 이루고 있다는 것을 확인했다. 이를 통해 기존 구조물의 파괴확률은 안전율을 통해 정량적으로 파악할 수 있게 되었다. 이 결과는 향후 방파제 피복블록의 목표파괴확률을 결정하는 중요한 자료로 사용될 것이다.

• Structural Engineering and Mechanics
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• 제25권3호
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• pp.347-363
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• 2007

A novel methodology, referred to as Auxiliary Domain Method (ADM), allowing for a very efficient solution of nonlinear reliability problems is presented. The target nonlinear failure domain is first populated by samples generated with the help of a Markov Chain. Based on these samples an auxiliary failure domain (AFD), corresponding to an auxiliary reliability problem, is introduced. The criteria for selecting the AFD are discussed. The emphasis in this paper is on the selection of the auxiliary linear failure domain in the case where the original nonlinear reliability problem involves multiple objectives rather than a single objective. Each reliability objective is assumed to correspond to a particular response quantity not exceeding a corresponding threshold. Once the AFD has been specified the method proceeds with a modified subset simulation procedure where the first step involves the direct simulation of samples in the AFD, rather than standard Monte Carlo simulation as required in standard subset simulation. While the method is applicable to general nonlinear reliability problems herein the focus is on the calculation of the probability of failure of nonlinear dynamical systems subjected to Gaussian random excitations. The method is demonstrated through such a numerical example involving two reliability objectives and a very large number of random variables. It is found that ADM is very efficient and offers drastic improvements over standard subset simulation, especially when one deals with low probability failure events.

• 한국지반신소재학회논문집
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• 제18권4호
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• pp.193-204
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• 2019

본 연구에서는 국내 16개의 무공케이슨 방파제 설계자료를 이용하여 원호활동에 대한 신뢰성분석을 통하여 신뢰성 수준을 분석하였다. 신뢰성 분석을 위하여 지반의 강도 및 단위중량, 피복재와 상치구조물의 단위중량, 상치구조물 상부에 재하되는 하중의 불확실성을 결정하였다. 해석변수의 불확실성을 반영하여 임의로 재현된 무공케이슨 방파제 물성에 대하여 Bishop 간편법을 이용하여 하중 및 저항을 산정하였다. 충분히 많은 회수의 무공케이슨 방파제에 대한 해석을 Monte Carlo Simulation으로 수행하였고, 모든 해석 케이스에 도출된 하중과 저항 값을 수집하여 통계분석을 하였다. Monte Carlo Simulation으로부터 도출되는 파괴확률이 아주 낮은 경우가 파괴확률의 수렴 문제가 발생하여 하중과 저항의 통계특성을 반영하여 FORM(First-Order Reliability Method) 해석을 통해 신뢰수준을 평가하였다. 무공케이슨 방파제의 안전율, 하중 및 저항의 불확실성, 하중 및 저항의 상관성이 신뢰수준에 미치는 영향을 분석하였다.

• 산업기술연구
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• 제28권B호
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• pp.157-165
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• 2008

Level II AFDA and Level III MCS reliability models are applied to analyze the stability of armor units on trading and coastal harbors in Korea. Hudson's formula and Van der Meer's formula are used in this reliability analysis. Also, probability density functions of reliability index and probability of failure are derived by the additional analysis. In addition, the partial safety factors of all harbors related to armor units can be straightforwardly evaluated by the inverse-reliability method. The upper and lower limits and average level of partial safety factors can be statistically investigated with the results of all cases applied in this paper. Therefore, it may be possible to design armor units of new breakwaters including the uncertainty of random variable and target level by using the present results.

• 한국해안해양공학회지
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• 제16권3호
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• pp.142-151
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• 2004

수리학적 안정성과 구조적 안정성을 동시에 만족시키면서 피복재의 중량을 산정할 수 있는 방법이 수립되었다. 수리학적 안정성은 Hudson의 경험식을 이용하여, 구조적 안정성은 충격하중 작용시 피복재 내부에 발생되는 최대인장응력을 산정, 피복재의 인장 저항력과 비교하는 개념으로 해석되었다. 이와 같이 산정된 수리학적 안정성과 구조적 안정성에 대한 적용한계를 재현기간별 설계 유의파고, 피복재의 중량, 그리고 인장 저항력의 함수로 제시하여 실무자들이 쉽게 사용할 수 있도록 하였다. 또한 결정론적 산정법의 불확실성을 고려하기 위하여 수리학적 안정성과 구조적 안정성에 대한 신뢰성 해석이 추가로 수행되었다. 두 파괴모드를 하나의 직렬계로 구성하여, 신뢰성설계법에서 이용되는 목표파괴확률을 가지고 단면파괴율의 함수로 피복재의 최적중량을 산정할 수 있었다.

• 로봇학회논문지
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• 제15권4호
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• pp.398-403
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• 2020

Robot's throwing control is difficult to accurately calculate because of air resistance and rotational inertia, etc. This complexity can be solved by using machine learning. Reinforcement learning using reward function puts limit on adapting to new environment for robots. Therefore, this paper applied deep reinforcement learning using neural network without reward function. Throwing is evaluated as a success or failure. AI network learns by taking the target position and control policy as input and yielding the evaluation as output. Then, the task is carried out by predicting the success probability according to the target location and control policy and searching the policy with the highest probability. Repeating this task can result in performance improvements as data accumulates. And this model can even predict tasks that were not previously attempted which means it is an universally applicable learning model for any new environment. According to the data results from 520 experiments, this learning model guarantees 75% success rate.

• 한국자동차공학회논문집
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• 제11권2호
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• pp.104-110
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• 2003

As exhaust emission standards are more stringent, higher conversion efficiency of automotive catalytic converter is required. In addition, catalytic converter is deteriorated during mileage accumulation of vehicle. Therefore the specification of catalytic converter should be decided in consideration of emission standards and deterioration. Because the decision of the specification of catalytic converter is required at the beginning of vehicle development procedure, it is important and necessary to fix the target values of green vehicle exhaust emissions. To do this, a linear regression analysis was done with in-use exhaust emissions data of 5 different kinds of vehicle that received US94 emission standards certification, and data handling methods including some statistical estimation were proposed. As a result, the fixed target values of NMHC, CO, NOx of green vehicle against US94 emission standards were 0.079, 0.83, 0.116, respectively. And expected in-use deterioration factor of NMHC, CO, NOx were 1.75, 2.02, 1.38, respectively. And also it was blown that even if failure rate is 30% after 80,000km driven, it might be sufficiently safe from emission failure confirmatory test of Korea. It is hopeful to make a database of in-use emissions to increase the confidence in correctness of the calculated target values.

• 산업경영시스템학회지
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• 제33권4호
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• pp.209-217
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• 2010

Reliability tools such as QFD and FMEA identify voice of customer related to product design, its use, how failures may occur, the severity of such failures, and the probability of the failure occurring. With these identified items, a development team can focus on the design process and the major issues facing the product in its potential use environment for the customer. The purpose of this research is to develop a reliability estimation process of agricultural machinery components using QFD, FMEA, and field failure data. Based on QFD method, customer requirements, engineering design elements and part characteristics were deployed. Using the field failure data, failures are investigated, and Weibull B10 life are estimated. This estimation process is useful for preparing the design input and planning the durability target.

• 한국안전학회지
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• 제27권5호
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• pp.64-69
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• 2012

The concept of SIL is applied in the most of all standards relating to functional system safety. However there are problems for the people to apply SIL to their plants. as these standards don't include sufficient informations. In this regards, this paper will suggest the direction of SIL application and concept based on IEC 61508 and IEC 61511. A Safety Integrity Level(SIL) is the discrete level(one out of possible fours), corresponding to a range of the probability of an E/E/PE (Electric/Electrical/Programmable Electrical) safety-related system satisfactorily performing the specific safety functions under all the stated conditions within a stated period of time. SIL can be divided into the target SIL(or required SIL) and the result SIL. The target SIL is determined by the risk analysis at the analysis phase of safety lifecycle and the result SIL is calculated during SIL verification at the realization phase of safety lifecycle. The target SIL is determined by the risk analysis like LOPA(Layer Of Protection Analysis), Risk Graph, Risk Matrix and the result SIL is calculated by HFT(Hardware Fault Tolerance), SFF(Safe Failure Fraction) and PFDavg(average Probability of dangerous Failure on Demand). SIL is applied to various areas such as process safety, machinery(road vehicles, railway application, rotating equipment, etc), nuclear sector which functional safety is applied. The functional safety is the part of the overall safety relating to the EUC and the EUC control system that depends on the correct functioning of the E/E/PE safety-related systems and other risk reduction measures. SIL is applied only to the functional safety of SIS(Safety Instrumented System) in safety. EUC is the abbreviation of Equipment Under Control and is the equipment, machinery, apparatus or plant used for manufacturing, process, transportation, medical or other activities.

• 품질경영학회지
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• 제43권3호
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• pp.373-382
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• 2015

Purpose: In this paper, we developed a reliability index (RI) to efficiently compare reliability of products based on the design, development and production information such as reliability tests, quality, product life-cycle management. RI also can be applied to reliability prediction of a novel product as well as comparison evaluation among existing products. Methods: For evaluating RI, we proposed evaluation process which is composed of five steps. Target modules are selected based on warranty data and correlation analysis. Scores of selected target modules are calculated by scoring function. Finally, weights of RI model are determined by optimization method. Results: This paper presented an empirical analysis based on failure data of mobile devices. In this case study, we demonstrated that there is a direct correlation between evaluated RI and field failure probability of each product. Conclusion: We proposed the index for comprehensive and effective assessment of product reliability level. From the procedure of this study, we expected to be applied for reliability estimation of novel products and deduction of field failure-related factors.