• 대한기계학회논문집
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• 제7권3호
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• pp.241-248
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• 1983

In the present work a time-dependent reliability model for a typical solar domestic hot water and heating system is developed using the method of Fault Tree Analysis and existing mathematical techniques. The reference system used in this analysis is a typical solar heating system. The system reliability structure has been identified with the aid of Fault Tree methods. In addition, a simulation of the solar system reliability has been performed employing the Monte Carlo method. In the computer simulation, failure rate data such as WASH-1400, MIL-HDBK-217B, and Green and Bourne are used as input data. These results show that the developed reliability model is capable of expressing the primary failure phenomena of the solar heating and domestic hot water system.

• Earthquakes and Structures
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• 제7권6호
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• pp.1061-1070
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• 2014

An iterative hybrid structural dynamic reliability prediction model has been developed under multiple-time interval loads with and without consideration of stochastic structural strength degradation. Firstly, multiple-time interval loads have been substituted by the equivalent interval load. The equivalent interval load and structural strength are assumed as random variables. For structural reliability problem with random and interval variables, the interval variables can be converted to uniformly distributed random variables. Secondly, structural reliability with interval and stochastic variables is computed iteratively using the first order second moment method according to the stress-strength interference theory. Finally, the proposed method is verified by three examples which show that the method is practicable, rational and gives accurate prediction.

• Smart Structures and Systems
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• 제14권4호
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• pp.559-567
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• 2014

The model of unit dynamic reliability of repairable k/n (G) system with unit strength degradation under repeated random shocks has been developed according to the stress-strength interference theory. The unit failure number is obtained based on the unit failure probability which can be computed from the unit dynamic reliability. Then, the transfer probability function of the repairable k/n (G) system is given by its Markov property. Once the transfer probability function has been obtained, the probability density matrix and the steady-state probabilities of the system can be retrieved. Finally, the dynamic reliability of the repairable k/n (G) system is obtained by solving the differential equations. It is illustrated that the proposed method is practicable, feasible and gives reasonable prediction which conforms to the engineering practice.

• 품질경영학회지
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• 제34권1호
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• pp.20-26
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• 2006

In the fields of mechanical reliability application, "zero" or "zero or one" failure tests are most commonly used for demonstrating reliability of a product since they reduce test duration and/or sample size compared to other test methods that guarantees the same reliability of a product with a given confidence level or consumer's risk. The test duration of the "zero or one" failure test is longer than that of "zero" failure test but it has advantage of smaller producer's risk. In this paper a two-stage test is developed that compromises the "zero" and "zero or one" failure tests. The properties of the proposed two-stage test are investigated and the three test methods are compared using a numerical example.

• 대한기계학회논문집A
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• 제28권5호
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• pp.593-602
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• 2004

We have developed a digital control rod control system not only to improve its performance but also to improve its reliability and speed of response so that it can replace the old fashioned analog system. However, a new developed digital control system should be tested to prove the validity by using any prototype or mock-up before application. The reliability prediction and the reliability block diagram analysis methods were adopted to verify the reliability of the developed hardware. For the case of software, especially fur a new developed control algorithm it has been tested to prove performances and validation by using a dynamic simulator and mock-up of control rod drive mechanism altogether. Here we want to present some key factors regarding to the new developed digital system with some verification procedures.

• Structural Engineering and Mechanics
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• 제70권1호
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• pp.81-96
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• 2019

In this paper, a hybrid uncertain model is applied to system reliability based design optimization (RBDO) of trusses. All random variables are described by random distributions but some key distribution parameters of them which lack information are defined by variation intervals. For system RBDO of trusses, the first order reliability method, as well as monotonicity analysis and the branch and bound method, are utilized to determine the system failure probability; and Improved (${\mu}+{\lambda}$) constrained differential evolution (ICDE) is employed for the optimization process. System reliability assessment of several numerical examples and system RBDO of different truss structures are proposed to verify our results. Moreover, the effect of different classes of interval distribution parameters on the optimum weight of the structure and the reliability index are also investigated. The results indicate that the weight of the structure is increased by increasing the uncertainty level. Moreover, it is shown that for a certain random variable, the optimum weight is more increased by the translation interval parameters than the rotation ones.

• Structural Engineering and Mechanics
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• 제78권2호
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• pp.209-218
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• 2021

For engineering, there are two major challenges in reliability analysis. First, to ensure the accuracy of simulation results, mechanical products are usually defined implicitly by complex numerical models that require time-consuming. Second, the mechanical products are fortunately designed with a large safety margin, which leads to a low failure probability. This paper proposes an efficient and high-precision adaptive active learning algorithm based on the Kriging surrogate model to deal with the problems with low failure probability and time-consuming numerical models. In order to solve the problem with multiple failure regions, the adaptive kernel-density estimation is introduced and improved. Meanwhile, a new criterion for selecting points based on the current Kriging model is proposed to improve the computational efficiency. The criterion for choosing the best sampling points considers not only the probability of misjudging the sign of the response value at a point by the Kriging model but also the distribution information at that point. In order to prevent the distance between the selected training points from too close, the correlation between training points is limited to avoid information redundancy and improve the computation efficiency of the algorithm. Finally, the efficiency and accuracy of the proposed method are verified compared with other algorithms through two academic examples and one engineering application.

• 한국정밀공학회지
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• 제27권5호
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• pp.36-47
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• 2010

The Korean Railroad Research Institute (KRRI) has developed the rubber tired AGT system (Model: K-AGT) between 1999 and 2005. The K-AGT is a light rail transit system does not require a driver and generally operates on an elevated railroad for transporting passengers. Accidents caused by driverless vehicles can severely affect social confidence, safety and economy therefore, it is very important to minimize the occurrences of such faults, and to accurately perform detailed maintenance tasks and thoroughly investigate the cause of any repeated failures. This research develops the web-based Preventive Maintenance (PM) system for the KAGT train system. The framework of the PM system is based on performing a reliability analysis and a failure mode effects analyses (FMEA) procedure on all the sub-systems in the K-AGT system. Out of the devices that have a low reliability, the high failure ranked devices are included high in the list for performing the overall maintenance plans. Through registration of historical failure data, the reliability indexes can be updated. Such a process is repeated continuously and can achieve very accurate predictions for device operational life times and failure rates. Therefore, this research describes the development of the overall PM system consists of a reliability analysis module, a failure mode effect analysis module, and maintenance request module.

• 한국신뢰성학회:학술대회논문집
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• 한국신뢰성학회 2005년도 학술발표대회 논문집
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• pp.357-376
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• 2005

• 제어로봇시스템학회논문지
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• 제17권11호
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• pp.1082-1089
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• 2011

Most engineered systems are designed with high levels of system redundancies to satisfy required reliability requirements under adverse events, resulting in high systems' LCCs (Life-Cycle Costs). Recent years have seen a surge of interest and tremendous advance in PHM (Prognostics and Health Management) methods that detect, diagnose, and predict the effects of adverse events. The PHM methods enable proactive maintenance decisions, giving rise to adaptive reliability. In this paper, we present a RAP (Resilience Allocation Problem) whose goal is to allocate reliability and PHM efficiency to components in an engineering context. The optimally allocated reliability and PHM efficiency levels serve as the design specifications for the system RBDO (Reliability-Based Design Optimization) and the system PHM design, which can be used to derive the detailed design of components and PHM units. The RAP is demonstrated using a simplified aircraft control actuator design problem resulting in a highly resilient actuator with optimally allocated reliability, PHM efficiency and redundancy for the given parameter settings.