• Nuclear Engineering and Technology
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• v.54 no.3
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• pp.926-939
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• 2022

The area of this study will cover the location-wise seismic response variation of an electrical cabinet in nuclear power point (NPP) based on classical reliability analysis. The location-based seismic ground motion (GM) selection is carried out with the help of probabilistic seismic hazard analysis using PSHRisktool, where the variation of reliability analysis can be understood from the relation between the reliability index and intensity measure. Two different approaches such as the first-order second moment method (FOSM) and Monte Carlo Simulation (MCS) are helped to evaluate and compare the reliability assessment of the cabinet. The cabinet is modeled with material uncertainty utilizing Steel01 as the material model and the fiber section modeling approach is considered to characterize the section's nonlinear reaction behavior. To verify the modal frequency, this study compares the FEM result with recorded data using Least-Squares Complex Exponential (LSCE) method from the impact hammer test. In spite of a few investigations, the main novelty of this study is to introduce the reader to check and compare the seismic reliability assessment variation in different seismic locations and for different earthquake levels. Alongside, the betterment can be found by comparing the result between two considered reliability estimation methods.

• Transactions of the Korean Society of Mechanical Engineers
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• v.19 no.7
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• pp.1657-1664
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• 1995

For dynamic analysis of flexible structures, classical linear modeling has been widely used due to its several good aspects. However, it was found that the modeling often lost its accuracy. So, it is important to know the valid range of the modeling before it is used. more complicated modelings are needed to obtain reliable results only outside the valid range of the classical linear modeling. In this study, some rigid body motions of flexible structures which lead to the failure of the classical linear modeling are investigated. Hybrid deformation variable modeling, which is proved to be accurate in previous studies, is used to figure out the valid range of the classical linear modeling through numerical examples.

• Structural Engineering and Mechanics
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• v.38 no.1
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• pp.125-140
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• 2011

This study presents an innovative method to estimate the reliability sensitivity based on the low-discrepancy sampling which is a new technique for structural reliability analysis. Two advantages are contributed to the method: one is that, by developing a general importance sampling procedure for reliability sensitivity analysis, the partial derivative of the failure probability with respect to the distribution parameter can be directly obtained with typically insignificant additional computations on the basis of structural reliability analysis; and the other is that, by combining various low-discrepancy sequences with the above importance sampling procedure, the proposed method is far more efficient than that based on the classical Monte Carlo method in estimating reliability sensitivity, especially for problems of small failure probability or problems that require a large number of costly finite element analyses. Examples involving both numerical and structural problems illustrate the application and effectiveness of the method developed, which indicate that the proposed method can provide accurate and computationally efficient estimates of reliability sensitivity.

• International Journal of CAD/CAM
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• v.7 no.1
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• pp.61-69
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• 2007

The objective of this work is to integrate reliability analysis into topology optimization problems. We introduce the reliability constraint in the topology optimization formulation, and the new model is called Reliability-Based Topology Optimization (RBTO). The application of the RBTO model gives a different topology relative to the classical topology optimization that should be deterministic. When comparing the structures resulting from the deterministic topology optimization and from the RBTO model, the RBTO model yields structures that are more reliable than the deterministic ones (for the same weight). Several applications show the importance of this integration.

• Structural Engineering and Mechanics
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• v.76 no.6
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• pp.675-685
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• 2020

As the classical response surface method (RSM), the polynomial RSM is so easy-to-apply that it is widely used in reliability analysis. However, the trade-off of accuracy and efficiency is still a challenge and the "curse of dimension" usually confines RSM to low dimension systems. In this paper, based on the univariate decomposition, the polynomial RSM is executed in a new mode, called as DPRSM. The general form of DPRSM is given and its implementation is designed referring to the classical RSM firstly. Then, in order to balance the accuracy and efficiency of DPRSM, its adaptive order revision around the most probable point (MPP) is proposed by introducing the univariate polynomial order analysis, noted as RDPRSM, which can analyze the exact nonlinearity of the limit state surface in the region around MPP. For testing the proposed techniques, several numerical examples are studied in detail, and the results indicate that DPRSM with low order can obtain similar results to the classical RSM, DPRSM with high order can obtain more precision with a large efficiency loss; RDPRSM can perform a good balance between accuracy and efficiency and preserve the good robustness property meanwhile, especially for those problems with high nonlinearity and complex problems; the proposed methods can also give a good performance in the high-dimensional cases.

• Proceedings of the KSR Conference
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• 2010.06a
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• pp.621-626
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• 2010

According to development of method and device of Finite Element Analysis, the strength of welded joint is demonstrated by Finite Element Analysis not classical calculations. On the FEA, all of the joints for carbody are assumed to be ideal connections and the yield stress of welded joint is assumed to be the same to base metal. On these assumption, FEA is appropriate to evaluate the overall stability and strength of whole carbody. The classical calculation is appropriate to evaluate strength of specific welded joint and to determine the weld method and properties. Some project request strength calculation of the specific welded joints in addition to FEA, because of the demonstration of stability. The objective of this paper is the check of the consistency of the FEA result for the welded joints by the stress comparison between Detailed FE Model and classical calculation and the evaluation of the reliability of FEA result.

• 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.

• 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.

• Journal of Yeungnam Medical Science
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• v.35 no.1
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• pp.63-69
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• 2018

Background: Kinovea software that tracking semi-automatically the motion in video screen has been used to study motion-related tasks in several studies. However, the validation of this software in open field test to assess locomotor activity have not been studied yet. Therefore, this study aimed to examine the reliability and validity of this software in analyzing locomotor activities. Methods: Thirty male Institute Cancer Research mice were subjected in this study. The results examined by this software and the classical method were compared. Test-retest reliability and inter-rater reliability were analyzed with Pearson's correlation coefficient and intraclass correlation coefficient (ICC). The validity of this software was analyzed with Pearson's correlation coefficient. Results: This software showed good test-retest reliability (ICC=0.997, 95% confidence interval [CI]=0.975-0.994, p<0.001). This software also showed good inter-rater reliability (ICC=0.987, 95% CI=0.973-0.994, p<0.001). Furthermore, in three analyses for the validity of this software, there were significant correlations between two methods (Pearson's correlation coefficient=0.928-0.972, p<0.001). In addition, this software showed good reliability and validity in the analysis locomotor activity according to time interval. Conclusion: This study showed that this software in analyzing drug-induced locomotor activity has good reliability and validity. This software can be effectively used in animal study using the analysis of locomotor activity.

• 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.