• Structural Engineering and Mechanics
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• v.62 no.2
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• pp.125-138
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• 2017

Reliability-based design optimization (RBDO) is a powerful tool for design optimization when considering probabilistic characteristics of design variables. However, it is often computationally intensive because of the coupling of reliability analysis and cost minimization. In this study, the concept of reliability mapping function is defined based on the relationship between the reliability index obtained by using the mean value first order reliability method and the failure probability obtained by using an improved response surface method. Double-loop involved in the classical RBDO can be converted into single-loop by using the reliability mapping function. Since the computational effort of the mean value first order reliability method is minimal, RBDO by using reliability mapping functions should be highly efficient. Engineering examples are given to demonstrate the efficiency and accuracy of the proposed method. Numerical results indicated that the proposed method has the similar accuracy as Monte Carlo simulation, and it can obviously reduce the computational effort.

• Structural Engineering and Mechanics
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• v.38 no.2
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• pp.171-193
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• 2011

One of the possible alternatives of simulation-based time-dependent reliability assessment of pre-stressed biconcave and biconvex cable trusses, the Monte Carlo method, is applied in this paper. The influence of an excessive deflection of cable truss (caused by creep of cables and rheologic changes) on its time-dependent serviceability is investigated. Attention is given to the definition of the basic random variables and their statistical functions (basic, mutually dependent random variables such as the pre-stressing forces of the bottom and top cable, structural geometry, the Young's modulus of elasticity of the cables, and the independent variables, such as permanent load, wind, snow and thermal actions). Then, the determination of the response of the cable truss to the loading effects, and the definition of the limiting values considering serviceability of the structure are performed. The potential of the method, using direct Monte Carlo technique for simulation-based time-dependent reliability assessment as a powerful tool, is emphasized. Results obtained by the First order reliability method (FORM) are compared with those obtained by the Monte Carlo simulation technique.

• Journal of Electrical Engineering and Technology
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• v.8 no.4
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• pp.780-786
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• 2013

In the reliability-based design optimization of electromagnetic devices, the accurate and efficient reliability assessment method is very essential. The first-order sensitivity-assisted Monte Carlo Simulation is proposed in the former research. In order to improve its accuracy for wide application, in this paper, the second-order sensitivity analysis is presented by using the hybrid direct differentiation-adjoint variable method incorporated with the finite element method. By combining the second-order sensitivity with the Monte Carlo Simulation method, the second-order sensitivity-assisted Monte Carlo Simulation algorithm is proposed to implement reliability calculation. Through application to one superconductor magnetic energy storage system, its accuracy is validated by comparing calculation results with other methods.

• Journal of the Korean Society of Safety
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• v.32 no.3
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• pp.54-59
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• 2017

This paper presents an efficient finite analysis model and a simulation-based reliability analysis method for stowage device system failure of a container crane with respect to lateral load. A quasi-static analysis model is introduced to simulate the nonlinear resistance characteristics and failure of tie-down and stowage pin, which are the main structural stowage devices of a crane. As a reliability analysis method, a subset simulation method is applied considering the uncertainties of later load and mechanical characteristic parameters of stowage devices. An efficient Markov chain Monte Carlo (MCMC) method is applied to sample random variables. Analysis result shows that the proposed model is able to estimate the probability of failure of crane system effectively which cannot be calculated practically by crude Monte Carlo simulation method.

• Journal of the Korea Society for Simulation
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• v.22 no.4
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• pp.109-118
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• 2013

This paper adopts the system configuration to assess the reliability instead of making a fault tree (FT), which is a traditional method to analyze reliability of a certain system; this is the reliability block diagram (RBD) method. The RBD method is a graphical presentation of a system diagram connecting the subsystems of components according to their functions or reliability relationships. The equipment model for the reliability simulation is modeled based on the discrete event system specification (DEVS) formalism. In order to make various alternatives of target system, this paper also adopts the system entity structure (SES), an ontological framework that hierarchically represents the elements of a system and their relationships. To enhance the calculation time of reliability analysis, GPU-based accelerations are adopted to the reliability simulation.

• Journal of Electrical Engineering and Technology
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• v.8 no.2
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• pp.331-338
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• 2013

A new reliability calculation method is proposed based on design sensitivity analysis by the finite element method for nonlinear performance constraints in the optimal design of electromagnetic devices. In the proposed method, the reliability of a given design is calculated by using the Monte Carlo simulation (MCS) method after approximating a constraint function to a linear one in the confidence interval with the help of its sensitivity information. The validity and numerical efficiency of the proposed sensitivity-assisted MCS method are investigated by comparing its numerical results with those obtained by using the conventional MCS method and the first-order reliability method for analytic functions and the TEAM Workshop Problem 22.

• Journal of the Society of Naval Architects of Korea
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• v.59 no.4
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• pp.200-206
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• 2022

This study is to develop database by an experimental method for the development of condition based maintenance for auxiliary equipment in marine engine systems. Existing ships have been performing regular maintenance, so the actual measurement data development is very incomplete. Therefore, it is best to develop a database on land tests. In this paper, a database developed by an experimental method is presented. First, failure case analysis and reliability analysis were performed to select a failure mode. For the failure simulation test, a test bed for land testing was developed. The failure simulation test was performed based on the failure simulation scenario in which the failure simulation test plan was defined. A 1.5TB failure simulation database has been developed, and it is expected to serve as a basis for ship failure diagnosis and prediction algorithm model development.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2002.05a
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• pp.672-676
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• 2002

In this paper, a reliability-based design optimization method, which enables the determination of optimum design that incorporate confidence range for structures, is studied. Response surface method and Monte Carlo simulation are utilized to determine limit state function. The proposed method is applied to the I-type steel structure for reliability based optimal design.

• 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 Electrical Engineering and Technology
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• v.11 no.3
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• pp.575-584
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• 2016

Considering the randomness and uncertainty of wind power, a reliability model of WTGs is established based on the combination of the Weibull distribution and the Markov chain. To analyze the failure mode quickly, we use the switch-section partitioning method. After defining the first-level load zone node, we can obtain the supply power sets of the first-level load zone nodes with each WTG. Based on the supply sets, we propose the dynamic division strategy of island operation. By adopting the fault analysis method with the attributes defined in the switch-section, we evaluate the reliability of the distribution network with WTGs using a sequential Monte Carlo simulation method. Finally, using the IEEE RBTS Bus6 test system, we demonstrate the efficacy of the proposed model and method by comparing different schemes to access the WTGs.