• Proceedings of the Computational Structural Engineering Institute Conference
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• 2001.04a
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• pp.102-109
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• 2001

In order to take account of the statistical properties of probability variables used in the structural analysis, the conventional approach using the safety factor based on past experience usually estimated the safety of a structure. The real structures could only be analyzed with the error in estimation of loads, material characters and the dimensions of the members. But the errors should be considered systematically in the structural analysis. Structural safety could not precisely be appraised by the traditional structural design concept. Recently, new approach based on the probability concept has been applied to the assessment of structural safety using the reliability concept. Thus, the computer program by the Probabilistic FEM is developed by incorporating the probabilistic concept into the conventional FEM method. This paper estimated for the reliability of a plane stress structure by Advanced First-Order Second Moment method using von Mises, Tresca and Mohr-Coulomb failure criterions. The reliability index and failure probability of attained by the Monte Carlo Simulation method with the von Mises criterion were same as PFEM, but the Monte Carlo Simulation were very time-consuming. The variance of member thickness and load could influence the reliability and failure probability most sensitively among the design variables from the results of the parameter analysis. And proper failure criterion must be used to design safely.

• Proceedings of the Computational Structural Engineering Institute Conference
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• 1991.04a
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• pp.34-42
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• 1991

This study is directed for the development of an efficient system-level Importance Sampling Technique for system reliability analysis of bridge structures Many methods have been proposed for structural reliability assessment purposes, such as the First-order Second-Moment Method, the Advanced Second-Moment Method, Computer Simulation, etc. The Importance Sampling Technique can be employed to obtain accurate estimates of the required probability with reasonable computation effort. Based on the observation and the results of application, it nay be concluded that Importance Sampling Method is a very effective tool for the system reliability analysis.

• Computational Structural Engineering
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• v.5 no.4
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• pp.113-124
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• 1992

This study proposes a Load Factors-based Analysis Model of Optimum Reliability for the High way bridge, which is most common type of structural design, and also proposes the theoretical bases of optimum nominal safety factors as well as optimum load and resistance factors based on the expected total cost minimization. Major 2nd moment reliability analysis and design theories including both MFOSM(Mean First Order 2nd Moment) Methods and AFOSM(Advanced First Order 2nd Moment) Methods are summarized and compared, and it has been found that Lind-Hasofer's approximate and an approximate Log-normal type reliability for mula are well suited for the proposed optimum reliability study.

• Structural Monitoring and Maintenance
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• v.1 no.4
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• pp.357-369
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• 2014

In the existing bridge management systems, assessment of the structural behavior is based on the results of visual inspections in which corresponding condition states are assigned to individual elements. In this process, limited attention is given to the correlation between bridge elements from structural perspective. Also, the uncertainty of parameters which affect the structural capacity is ignored. A system reliability-based assessment model is potentially an appropriate replacement for the existing procedures. The aim of this research is to evaluate the system reliability of existing conventional Steel-Reinforced bridge decks over time. The developed method utilizes the reliability theory and evaluates the structural safety for such bridges based on their failure mechanisms. System reliability analysis has been applied to simply-supported concrete bridge superstructures designed according to the Canadian Highway Bridge Design Code (CHBDC-S6) and the deterioration pattern is achieved based on the reliability estimates. Finally, the bridge condition index of an old existing bridge in Montreal has been estimated using the developed deterioration pattern. The results obtained from the developed reliability-based deterioration model and from the evaluation done by bridge engineers have been found to be in accordance.

• Proceedings of the Computational Structural Engineering Institute Conference
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• 1997.10a
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• pp.145-154
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• 1997

The results of optimum design by the deterministic approach adopted in the current design codes depend upon the safety levels of the applied code. But, it is now generally recognized that structural problems are nondeterministic and, consequently, that engineering optimum design must cope with uncertainties. Therefore, it is not an overstatement to affirm that the combination of reliability-based design procedures and optimization techniques is the only means of providing a powerful tool to obtain a practical optimum design solution. In the paper, reliability based optimum design procedure as a rational approach to optimum structural design is presented. The design constraints are formulated based on the ASD, LRFD and reliability theories. The reliability analysis is based on an advanced first-order second moment approach. Uncertainties in the structural strength and loading due to inherent variability as well as modeling and prediction errors are included in failure due to combined bending and shear. For the realistic reliability-based optimization of continuous steel box girder bridges, interactive non-linear limit state model is formulated based on the von Mises's combined stress yield criterion. Comparative results are presented when the ASD criteria are used for the optimum design of a structure under reliability constraints. In addition, this study comparatively shows the results of the optimum design for various criteria of design codes.

• Structural Engineering and Mechanics
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• v.82 no.3
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• pp.271-282
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• 2022

The active learning surrogate model based on adaptive sampling strategy is increasingly popular in reliability analysis. However, most of the existing sampling strategies adopt the trial and error method to determine the size of the Monte Carlo (MC) candidate sample pool which satisfies the requirement of variation coefficient of failure probability. It will lead to a reduction in the calculation efficiency of reliability analysis. To avoid this defect, a new method for determining the optimal size of the MC candidate sample pool is proposed, and a new structural reliability analysis method combining polynomial chaos-based Kriging model (PC-Kriging) with adaptive sampling region is also proposed (PCK-ASR). Firstly, based on the lower limit of the confidence interval, a new method for estimating the optimal size of the MC candidate sample pool is proposed. Secondly, based on the upper limit of the confidence interval, an adaptive sampling region strategy similar to the radial centralized sampling method is developed. Then, the k-means++ clustering technique and the learning function LIF are used to complete the adaptive design of experiments (DoE). Finally, the effectiveness and accuracy of the PCK-ASR method are verified by three numerical examples and one practical engineering example.

• Proceedings of the Computational Structural Engineering Institute Conference
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• 1998.10a
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• pp.61-68
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• 1998

It has become important to evaluate the qualitive reliability and condition assessment of existing structural systems in order to establish a rational program for repair and maintenance. Since most of if existing structural system may suffer from defect corrosion and damage, it is necessary to account for their effects in fuzzy reliability analysis, In this paper, an attempt is made to develope a reliability analysis for damaged structural systems using failure possibility theory. Damage state is specified in terms of linguistic valiables using natural language information and numerical information, which are defined by fuzzy sets. Using a subjective condition index of failure possibility and information of the damage state is introduced into the calculation of failure probability. The subjective condition index of quantitative and qualitative analysis method is newly proposed based on the fuzzy set operations, namely logical product, drastic product, logical sum and drastic sum

• Proceedings of the Earthquake Engineering Society of Korea Conference
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• 2000.04a
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• pp.233-240
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• 2000

Nuclear power plant structures may be exposed to aggressive environmental effects than may cause their strength and stiffness to decrease over their service lives, Although the physics of these damage mechanisms are reasonably well understood and quantitative evaluation of their effects on time-dependent structural behavior is possible in some instances such evaluations are generally very difficult and remain novel. The assessment of existing RC containment in nuclear power plants for continued service must provide quantitative evidence that they are able to withstand future extreme loads during a service period with an acceptable level of reliability. Rational methodologies to perform the reliability assessment can be developed from mechanistic models of structural deterioration using time-dependent structural reliability analysis to take earthquake loading uncertainties into account. The final goal of this study is to develop the reliability analysis of RC containment structures. The cause of the degrading is first clarified and the reliability assessment has been conducted. By introducing stochastic analysis based on random vibration theory the reliability analysis which can determine the failure probabilities has been established.

• Proceedings of the Computational Structural Engineering Institute Conference
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• 1991.10a
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• pp.57-62
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• 1991

For the purpose of developing the method for efficiently calculating the design sensitivity and the reliability for the complicated structure such as ship structure, the probabilistic finite element method is introduced to formulate the deterministic design sensitivity analysis method and incorporated with the second moment reliability methods such as MVFOSM, AFOSM and SORM. Also, the probabilistic design sensitivity analysis needed in the reliability-based design is performed. The reliability analysis is carried out for the initial yielding failure, in which the derivative derived in the deterministic desin sensitivity is used. The present PFEM-based reliability method shows good agreement with Monte Carlo method in terms with the variance of response and the associated probability of failure even at the first or first few iteration steps. The probabilistic design sensitivity analysis evaluates explicitly the contribution of each random variable to probability of failure. Further, the reliability index variation can be easily predicted by the variation of the mean and the variance of the random variables.

• Journal of the Korea institute for structural maintenance and inspection
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• v.1 no.1
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• pp.113-124
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• 1997

Based on the recent developments of the reliability-based structural analysis and design as well as the extending knowledge on the probabilistic characteristics of load and resistances, the probability based design criteria have been successfully developed for many standards. Since the probabilistic characteristics depend highly on the local load and resistances, it is recognized to develop the design criterion compatible with domestic requirements. The existing optimum design methods, which are generally based on the structural theory and certain engineering exprience, do not realistically consider the uncertainties of load and resistances and the basic reliability concepts. This study is directed to propose a optimum design based Expected Total Cost Minimization on two-way slab system which could possibly replace optimum design based traditional provisions of the current code, based on the AFOSM reliablity theory.