• Journal of Korean Society of Coastal and Ocean Engineers
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• v.21 no.1
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• pp.15-29
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• 2009

Most breakwater armor blocks are designed by using Hudson's or van der Meer's formula. The minimum weight of armor blocks is calculated by equating the resistance to the load in each formula. The larger value is then chosen as the design weight. In this study, we have performed reliability analyses for thus designed breakwater armor blocks of 12 trade harbors and 8 coastal harbors in Korea. The probability of failure calculated by the reliability analysis provides a criterion for evaluating the stability of armor blocks. The calculated probability of failure was almost same for all the breakwaters so that we were able to quantitatively evaluate the safety level of armor blocks of existing breakwaters. We also found that the safety factor used in the deterministic design method and the probability of failure in the reliability design method show a linear relationship. Therefore the probability of failure of existing breakwaters can be quantitatively calculated from the safety factors. The calculated probability of failure could also be used for determining the target probability of failure in the future.

• Structural Engineering and Mechanics
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• v.25 no.3
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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.

• Journal of the Korean Geosynthetics Society
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• v.18 no.4
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• pp.193-204
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• 2019

Reliability analyses of sixteen domestic design cases of open cell caisson breakwaters against circular sliding failure were conducted in this study. For the reliability analyses, uncertainties of parameters of soils, mound, and concrete cap were assessed. Bishop simplified method was used to obtain load and resistance of open cell caisson breakwater for randomly generated open cell caisson breakwater. Sufficient number of Monte Carlo simulations were conducted for randomly generated open cell caisson breakwaters, and statistical analysis was conducted on loads and resistances collected from the large number of Monte Carlo simulations. Probability of failure produced from Monte Carlo simulation has a nonconvergence issue for very low probability of failure; therefore, First-Order Reliability Method (FORM) was conducted using the statistical characteristics of loads and resistances of open cell caisson breakwaters. In addition, effects of safety factor, uncertainties of load and resistance, and correlation between load and resistance on reliability of open cell caisson breakwaters against circular sliding failure were examined.

• Journal of Industrial Technology
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• v.28 no.B
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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.

• Journal of Korean Society of Coastal and Ocean Engineers
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• v.16 no.3
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• pp.142-151
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• 2004

A method for the determination of concrete armor unit weights with hydraulic stability and structural stability may be formulated in this paper. The hydraulic stability is analyzed by using Hudson's formula, the structural stability is also studied by evaluation of maximum flexural tensile stresses in armor unit induced by the impact loads and by comparison of those with the tensile resistance strength directly. The applicable criteria for concrete armor units can be represented as a function of design wave heights with return period, armor weights, and tensile strengths for the practical uses. In addition, reliability analyses for two failure modes are carried out to take into account some uncertainties. Finally, a series system for two-failure mode analysis can be made up straightforwardly, by which the optimal weights of armor units can be estimated with the various relative breakages, given the specific target probability of failure under the concepts of reliability-based design method.

• The Journal of Korea Robotics Society
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• v.15 no.4
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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.

• Transactions of the Korean Society of Automotive Engineers
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• v.11 no.2
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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.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.33 no.4
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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.

• Journal of the Korean Society of Safety
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• v.27 no.5
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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.

• Journal of Korean Society for Quality Management
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• v.43 no.3
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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.