• Journal of Magnetics
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• v.17 no.1
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• pp.46-50
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• 2012

A reliability-based optimization method for electromagnetic design is presented to take uncertainties of design parameters into account. The method can provide an optimal design satisfying a specified confidence level in the presence of uncertain parameters. To achieve the goal, the reliability index approach based on the firstorder reliability method is adopted to deal with probabilistic constraint functions and a double-loop optimization algorithm is implemented to obtain an optimum. The proposed method is applied to the TEAM Workshop Problem 22 and its accuracy and efficiency is verified with reference of Monte Carlo simulation results.

• Proceedings of the Korean Geotechical Society Conference
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• 2008.10a
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• pp.779-783
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• 2008

LRFD Resistance factors for static bearing capacity of driven steel pipe piles were calibrated in the freamework of reliability theory. Reliability analysis was performed by the First Order Reliability Method (FORM) using resistance bias factor statistics.The target reliability indices are selected as 2.0 and 2.33 for group pile case and 2.5 for single pile case, based on the reliability level of the current design practice and considering redundancy of pile group, acceptable risk level, construction quality control, and significance of individual structure.

• Structural Engineering and Mechanics
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• v.3 no.2
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• pp.135-144
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• 1995

Since structural systems may fail in any one of several failure modes, computation of system reliability is always difficult. A method using numerical quadrature for computing structural system reliability with either one or more than one failure mode is presented in this paper. Statistically correlated safety margin equations are transformed into a group of uncorrelated variables and the joint density function of these uncorrelated variables can be generated by using the Maximum Entropy Method. Structural system reliability is then obtained by integrating the joint density function with the transformed safety domain enclosed within a set of linear equations. The Gaussian numerical integration method is introduced in order to improve computational accuracy. This method can be used to evaluate structural system reliability for Gaussian or non-Gaussian variables with either linear or nonlinear safety boundaries. It is also valid for implicit safety margins such as computer programs. Both the theory and the examples show that this method is simple in concept and easy to implement.

• Journal of Aerospace System Engineering
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• v.15 no.2
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• pp.16-25
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• 2021

Reliability of fatigue strength on Aircraft Composites(GFRP) Structures was assessed in this paper. Fatigue strength of GFRP was used through the existing fatigue test data with Monte Carlo method. The S_a-N_f curve of composites fatigue strength was assumed as normal distribution and reliability was analyzed using SSIT model. Fatigue stress was designed IAW ASTM F3114-15 with special safety factor of S_sf=1.2~2.0. Reliability was calculated by analytic method and FORM. Sensitivity for the effect of mean and standard deviation of fatigue strength as well as fatigue stability was evaluated. This result can be usefully applied to reliability and fatigue design for composite structures of light weight aircraft.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.36 no.2
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• pp.223-230
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• 2012

The strength of brittle material has commonly been characterized by a normal distribution or Weibull distribution, but it may fit the gamma distribution for some material. The use of an extreme value distribution is proper when the largest values of a set of stresses dominate the failure of the material. This paper presents a formula for reliability estimation based on stress-strength interference theory that is applicable when the strength of material is distributed like a gamma distribution and the stress is distributed like an extreme value distribution. We verified the validity of the equation for the reliability estimation by examining the relationships among the factor of safety, the coefficient of variation, and the reliability. The required minimum factor of safety and the highest allowable coefficient of variation of stress can be estimated by choosing an objective reliability and estimating the reliabilities obtained for various factors of safety and coefficients of variation.

• Journal of the Korean Society of Safety
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• v.11 no.1
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• pp.16-26
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• 1996

In a series of original papers, [1-17] efficient methods and algorithms have been presented, for the exact solution of many reliability problems represented by binary networks. A starting point of these methods was the concept of domination, firstly introduced in ,elation with reliability problems in [2]. It's application to directed networks resulted in the development of a topological formula for the classical problem of the two terminal reliability. This result was extended later to the all-terminal and the k-terminal reliability problems. All papers mentioned above use a path oriented representation for the network topology. In practical applications, however, it is common and often advantageous to work with cut sets. This article considers the Domination theory for reliability problem of a network. Some topological formula are derived and the power and the application of this formula are shown through the alternative proof of topological formula of A. Satyanarayana [2].

• Structural Engineering and Mechanics
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• v.62 no.3
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• pp.365-372
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• 2017

Reliability analysis is a probabilistic approach to determine a safety level of a system. Reliability is defined as a probability of a system (or a structure, in structural engineering) to functionally perform under given conditions. In the 1960s, Basler defined the reliability index as a measure to elucidate the safety level of the system, which until today is a commonly used parameter. However, the reliability index has been formulated based on the pivotal assumption which assumed that the considered limit state function is normally distributed. Nevertheless, it is not guaranteed that the limit state function of systems follow as normal distributions; therefore, there is a need to define a new reliability index for no-normal distributions. The main contribution of this paper is to define a sophisticated reliability index for limit state functions which their distributions are non-normal. To do so, the new definition of reliability index is introduced for non-normal limit state functions according to the probability functions which are calculated based on the convolution theory. Eventually, as the state of the art, this paper introduces a simplified method to calculate the reliability index for non-normal distributions. The simplified method is developed to generate non-normal limit state in terms of normal distributions using series of Gaussian functions.

• Smart Structures and Systems
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• v.16 no.2
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• pp.367-382
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• 2015

This paper aims to conduct the reliability-based assessment of the welded joint in the orthotropic steel bridge deck by use of a mesh-insensitive structural stress (MISS) method, which is an effective numerical procedure to determine the reliable stress distribution adjacent to the weld toe. Both the solid element model and the shell element model are first established to investigate the sensitivity of the element size and the element type in calculating the structural stress under different loading scenarios. In order to achieve realistic condition assessment of the welded joint, the probabilistic approach based on the structural reliability theory is adopted to derive the reliability index and the failure probability by taking into account the uncertainties inherent in the material properties and load conditions. The limit state function is formulated in terms of the structural resistance of the material and the load effect which is described by the structural stress obtained by the MISS method. The reliability index is computed by use of the first-order reliability method (FORM), and compared with a target reliability index to facilitate the safety assessment. The results achieved from this study reveal that the calculation of the structural stress using the MISS method is insensitive to the element size and the element type, and the obtained structural stress results serve as a reliable basis for structural reliability analysis.

• Proceedings of the ESK Conference
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• 1996.04a
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• pp.113-127
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• 1996

In Human Reliability Analysis(HRA), the uncertainties involved in many factors that affect human reliability have to be represented as the quantitative forms. Conventional probability- based human reliability theory is used to evaluate the effect of those uncertainties but it is pointed out that the actual human reliability should be different from that of conventional one. Conventional HRA makes use of error rates, however, it is difficult to collect data enough to estimate these error rates, and the estimates of error rates are dependent only on engineering judgement. In this paper, the error possibility that is proposed by Onisawa is used to represent human reliability, and the error possibility is obtained by use of fuzzy reasoning that plays an important role to clarify the relation between human reliability and human error. Also, assuming these factors are connected to the top event through Fault Tree structure, the influence and correlation of these factors are measured by fuzzy operation. When a fuzzy operation is applied to Fault Tree Analysis, it is possible to simplify the operation applying the logic disjuction and logic conjuction to structure function, and the structure of human reliability can be represented as membership function of the top event. Also, on the basis of the the membership function, the characteristics of human reliability can be evaluated by use of the concept of pattern recognition.

• Journal of Magnetics
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• v.19 no.1
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• pp.78-83
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• 2014

This paper proposes an efficient reliability-based optimization method for designing a superconducting magnetic energy system in presence of uncertainty. To evaluate the probability of failure of constraints, samplingbased reliability analysis method is employed, where Monte Carlo simulation is incorporated into dynamic Kriging models. Its main feature is to drastically reduce the numbers of iterative designs and computer simulations during the optimization process without sacrificing the accuracy of reliability analysis. Through comparison with existing methods, the validity of the proposed method is examined with the TEAM Workshop Problem 22.