• Proceedings of the Korean Geotechical Society Conference
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• 2008.10a
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• pp.375-394
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• 2008

This paper discusses two user-friendly reliability techniques that could be implemented easily using the ubiquitous EXCEL. The techniques are First-Order Reliability Method with non-Gaussian random variables expressed using Hermite polynomials and collocation-based stochastic response surface method. It is believed that ease of implementation would popularize use of reliability-based design in practice.

• Structural Engineering and Mechanics
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• v.42 no.2
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• pp.175-189
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• 2012

This paper presents an algorithm for structural reliability with the response surface method. For this aim, an approach with three stages is proposed named as improved response surface method. In the algorithm, firstly, a quadratic approximate function is formed and design point is determined with First Order Reliability Method. Secondly, a point close to the exact limit state function is searched using the design point. Lastly, vector projected method is used to generate the sample points and Second Order Reliability Method is performed to obtain reliability index and probability of failure. Five numerical examples are selected to illustrate the proposed algorithm. The limit state functions of three examples (cantilever beam, highly nonlinear limit state function and dynamic response of an oscillator) are defined explicitly and the others (frame and truss structures) are defined implicitly. ANSYS finite element program is utilized to obtain the response of the structures which are needed in the reliability analysis of implicit limit state functions. The results (reliability index, probability of failure and limit state function evaluations) obtained from the improved response surface are compared with those of Monte Carlo Simulation, First Order Reliability Method, Second Order Reliability Method and Classical Response Surface Method. According to the results, proposed algorithm gives better results for both reliability index and limit state function evaluations.

• Journal of Mechanical Science and Technology
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• v.20 no.10
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• pp.1662-1669
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• 2006

Since randomness and uncertainties of design parameters are inherent, the robust design has gained an ever increasing importance in mechanical engineering. The robustness is assessed by the measure of performance variability around mean value, which is called as standard deviation. Hence, constraints in robust optimization problem can be approached as probability constraints in reliability based optimization. Then, the FOSM (first order second moment) method or the AFOSM (advanced first order second moment) method can be used to calculate the mean values and the standard deviations of functions describing constraints and object. Among two methods, AFOSM method has some advantage over FOSM method in evaluation of probability. Nevertheless, it is difficult to obtain the mean value and the standard deviation of objective function using AFOSM method, because it requires that the mean value of function is always positive. This paper presented a special technique to overcome this weakness of AFOSM method. The mean value and the standard deviation of objective function by the proposed method are reliable as shown in examples compared with results by FOSM method.

• Structural Engineering and Mechanics
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• v.72 no.2
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• pp.203-216
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• 2019

Reliability analysis of composite structures considering random variation of involved parameters is quite important as composite materials revealed large statistical variations in their mechanical properties. The reliability analysis of such structures by the first order reliability method (FORM) and Monte Carlo Simulation (MCS) based approach involves repetitive evaluations of performance function. The response surface method (RSM) based metamodeling technique has emerged as an effective solution to such problems. In the application of metamodeling for uncertainty quantification and reliability analysis of composite structures; the finite element model is usually formulated by either classical laminate theory or first order shear deformation theory. But such theories show significant error in calculating the structural responses of composite structures. The present study attempted to apply the RSM based MCS for reliability analysis of composite shell structures where the surrogate model is constructed using higher order shear deformation theory (HSDT) of composite structures considering the uncertainties in the material properties, load, ply thickness and radius of curvature of the shell structure. The sensitivity of responses of the shell is also obtained by RSM and finite element method based direct approach to elucidate the advantages of RSM for response sensitivity analysis. The reliability results obtained by the proposed RSM based MCS and FORM are compared with the accurate reliability analysis results obtained by the direct MCS by considering two numerical examples.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.29 no.8 s.239
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• pp.1102-1108
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• 2005

The integrity of nuclear piping systems has to be maintained sufficiently all the times during operation. In order to maintain the integrity, reliable assessment procedures including fracture mechanics analysis, etc, are required. Up to now, the integrity assessment has been performed using conventional deterministic approach even though there are lots of uncertainties to hinder a rational evaluation. In this respect, probabilistic approach is considered as an appropriate method for piping system evaluation. The objectives of this paper are to develop a probabilistic assessment program using reliability index and simulation technique and to estimate the damage probability of wall-thinned pipes in secondary systems. The probabilistic assessment program consists of three evaluation modules which are first order reliability method, second order reliability method and Monte Carlo simulation method. The developed program has been applied to evaluate damage probabilities of wall-thinned pipes subjected to internal pressure, global bending moment and combined loading. The sensitivity analysis results as well as prototypal evaluation results showed a promising applicability of the probabilistic integrity assessment program.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.60 no.7
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• pp.1354-1359
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• 2011

This paper presents a novel methodology for improving the reliability of electromagnetic devices and machines based on the reliability-based design optimization method. To achieve this, the method includes reliability analysis and optimization process taking into account uncertainties of design variables. One of the first-order reliability analysis techniques, called reliability index approach, is adopted to evaluate the reliability of performance functions with respect to probabilistic design variables. The proposed method has been successfully applied to designing a superconducting magnetic energy storage system. For verifying the efficiency and accuracy of the method, the results are compared with those of conventional optimization methods.

• 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.

• Wind and Structures
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• v.27 no.3
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• pp.175-186
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• 2018

With the continuous increase of span lengths, modern bridges are becoming much more flexible and more prone to flutter under wind excitations. A reasonable probabilistic flutter analysis of long-span bridges involving random and uncertain variables may have to be taken into consideration. This paper presents a method for estimating the reliability index and failure probability due to flutter, which considers the very important variables including the extreme wind velocity at bridge site, damping ratio, mathematical modeling, and flutter derivatives. The Aizhai Bridge in China is selected as an example to demonstrate the numerical procedure for the flutter reliability analysis. In the presented method, the joint probability density function of wind speed and wind direction at the deck level of the bridge is first established. Then, based on the fundamental theories of structural reliability, the reliability index and failure probability due to flutter of the Aizhai Bridge is investigated by applying the Monte Carlo method and the first order reliability method (FORM). The probabilistic flutter analysis can provide a guideline in the design of long-span bridges and the results show that the structural damping and flutter derivatives have significant effects on the flutter reliability, more accurate and reliable data of which is needed.

• Proceedings of the Korean Geotechical Society Conference
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• 2008.10a
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• pp.427-435
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• 2008

A reliability based slope stability assessment method is proposed and examined considering the variation of matric suction which is measured by a real time slope monitoring system. Mean value first order reliability method and advanced first order reliability method are used to calculate reliability indices of a slope. The applicability of methods is compared by applying them to the range of matric suctions measured by the real-time monitoring system. Sensitivity analysis is also performed to examine the contribution of random variables to the reliability index of slope. Finally, the proposed method is applied to a model slope. The results show that the reliability index of slope can be used for efficient slope management by quantifying the risk of slope in real time.

• 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.