• Computational Structural Engineering : An International Journal
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• v.1 no.1
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• pp.59-69
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• 2001

This study is intended to propose a systematic approach for reliability-based assessment of life cycle cost (LCC) effectiveness and economic efficiency for cost-effective seismic upgrading of existing bridges. The LCC function is expressed as the sum of the upgrading cost and all the discounted life cycle damage costs, which is formulated as a function of the Park-Ang damage index and structural damage probability. The damage costs are expressed in terms of direct damage costs such as repair/replacement costs, human losses and property damage costs, and indirect damage costs such as road user costs and indirect regional economic losses. For dealing with a variety of uncertainties associated with earthquake loads and capacities, a simulation-based reliability approach is used. The SMART-DRAIN-2DX, which is a modified version of the well-known DRAIN-2DX, is extended by incor-porating LCC analysis based on the LCC function developed in the study. Economic efficiencies for optimal seismic upgradings of the continuous PC segmental bridges are assessed using the proposed LCC functions and benefit-cost ratio.

• Structural Engineering and Mechanics
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• v.75 no.6
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• pp.771-784
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• 2020

Reliability analysis techniques combining with various surrogate models have attracted increasing attention because of their accuracy and great efficiency. However, they primarily focus on the structures with continuous response, while very rare researches on the reliability analysis for structures with discontinuous response are carried out. Furthermore, existing adaptive reliability analysis methods based on importance sampling (IS) still have some intractable defects when dealing with small failure probability, and there is no related research on reliability analysis for structures involving discontinuous response and small failure probability. Therefore, this paper proposes a novel reliability analysis method called AGPC-IS for such structures, which combines adaptive Gaussian process classification (GPC) and adaptive-kernel-density-estimation-based IS. In AGPC-IS, an efficient adaptive strategy for design of experiments (DoE), taking into consideration the classification uncertainty, the sampling uniformity and the regional classification accuracy improvement, is developed with the purpose of improving the accuracy of Gaussian process classifier. The adaptive kernel density estimation is introduced for constructing the quasi-optimal density function of IS. In addition, a novel and more precise stopping criterion is also developed from the perspective of the stability of failure probability estimation. The efficiency, superiority and practicability of AGPC-IS are verified by three examples.

• Proceedings of the Computational Structural Engineering Institute Conference
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• 2003.10a
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• pp.103-114
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• 2003

This paper aims to propose a method that helps maintenance engineers to evaluate the damage states of bridge structure systems by using a Fuzzy Fault Tree Analysis. It may be stated that Fuzzy Fault Tree Analysis may be very useful for the systematic and rational fuzzy reliability assessment for real bridge structure systems problems because the approach is able to effectively deal with all the related bridge structural element damages in terms of the linguistic variables that incorporate systematically experts experiences and subjective judgement. This paper considers these uncertainties by providing a fuzzy reliability-based framework and shows that the identification of the optimum maintenance scenario is a straightforward process. This is achieved by using a computer program for LIFETIME. This program can consider the effects of various types of actions on the fuzzy reliability index profile of a deteriorating structures. Only the effect of maintenance interventions is considered in this study. However. any environmental or mechanical action affecting the fuzzy reliability index profile can be considered in LIFETIME. Numerical examples of deteriorating bridges are presented to illustrate the capability of the proposed approach. Further development and implementation of this approach are recommended for future research.

• Structural Engineering and Mechanics
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• v.70 no.1
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• pp.81-96
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• 2019

In this paper, a hybrid uncertain model is applied to system reliability based design optimization (RBDO) of trusses. All random variables are described by random distributions but some key distribution parameters of them which lack information are defined by variation intervals. For system RBDO of trusses, the first order reliability method, as well as monotonicity analysis and the branch and bound method, are utilized to determine the system failure probability; and Improved (${\mu}+{\lambda}$) constrained differential evolution (ICDE) is employed for the optimization process. System reliability assessment of several numerical examples and system RBDO of different truss structures are proposed to verify our results. Moreover, the effect of different classes of interval distribution parameters on the optimum weight of the structure and the reliability index are also investigated. The results indicate that the weight of the structure is increased by increasing the uncertainty level. Moreover, it is shown that for a certain random variable, the optimum weight is more increased by the translation interval parameters than the rotation ones.

• Smart Structures and Systems
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• v.14 no.5
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• pp.847-867
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• 2014

There are continuous efforts to mitigate structural losses from earthquakes and manage risk through seismic risk assessment; seismic fragility curves are widely accepted as an essential tool of such efforts. Seismic fragility curves can be classified into four groups based on how they are derived: empirical, judgmental, analytical, and hybrid. Analytical fragility curves are the most widely used and can be further categorized into two subgroups, depending on whether an analytical function or simulation method is used. Although both methods have shown decent performances for many seismic fragility problems, they often oversimplify the given problems in reliability or structural analyses owing to their built-in assumptions. In this paper, a new method is proposed for the development of seismic fragility curves. Integration with sophisticated software packages for reliability analysis (FERUM) and structural analysis (ZEUS-NL) allows the new method to obtain more accurate seismic fragility curves for less computational cost. Because the proposed method performs reliability analysis using the first-order reliability method, it provides component probabilities as well as useful byproducts and allows further fragility analysis at the system level. The new method was applied to a numerical example of a 2D frame structure, and the results were compared with those by Monte Carlo simulation. The method was found to generate seismic fragility curves more accurately and efficiently. Also, the effect of system reliability analysis on the development of seismic fragility curves was investigated using the given numerical example and its necessity was discussed.

• Journal of the Korea institute for structural maintenance and inspection
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• v.12 no.4
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• pp.133-140
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• 2008

The design method of the reinforced concrete structures is converting from the current limit state design method to the reliability based design method and active studies have been done in the US, Europe, and Japan etc. Performance based design method is considering lots of uncertainty of current design provision rationally and make sure that structure have a reliable reliability and safety. The main area of these studies is to secure the non-linear analysis technology with high reliability. The data for reinforced concrete columns tested by many researchers are used to verify the applicability of the nonlinear finite element analysis program (RCAHEST, Reinforced Concrete Analysis in Higher Evaluation System Technology). A comparison is made between analysis and test, calculated safety factor based on reliability theories to applies to analysis result.

• Geomechanics and Engineering
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• v.22 no.5
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• pp.433-439
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• 2020

Tunnels are one of the most important constructions in civil engineering. The damage to these structures caused enormous costs. Therefore, the safe and economic design of these structures has long been considered. However, both applied loads on the tunnels as well as the resistance of the structural members are naturally uncertain parameters, hence, the design of these structures requires considering the probabilistic approaches. This study aims to determine the load and resistant factors of lining tunnels concerning the earthquake extreme events limit state function. For this purpose, tunnels that have been designed according to the previous design codes (AASHTO Tunnel LRFD 2017) and using reliability analysis, the optimum reliability of these structures for different loading scenarios is determined. In this paper, the tunnel is considered circular. Finally, the proper load and resistance factors are calculated corresponding to the obtained target reliability. Based on the performed calibration earthquake extreme events limit state function, the result of this study can be recommended to AASHTO Tunnel LRFD 2017.

• Structural Engineering and Mechanics
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• v.25 no.3
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• pp.311-330
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• 2007

Model-based predictions of structural behavior are negatively affected by uncertainties of various type and in various stages of the structural analysis. The present paper focusses on dynamic analysis and addresses the effects of uncertainties concerning material and geometric parameters, mainly in the context of modal analysis of large-scale structures. Given the large number of uncertain parameters arising in this case, highly scalable simulation-based methods are adopted, which can deal with possibly thousands of uncertain parameters. In order to solve the reliability problem, i.e., the estimation of very small exceedance probabilities, an advanced simulation method called Line Sampling is used. In combination with an efficient algorithm for the estimation of the most important uncertain parameters, the method provides good estimates of the failure probability and enables one to quantify the error in the estimate. Another aspect here considered is the uncertainty quantification for closely-spaced eigenfrequencies. The solution here adopted represents each eigenfrequency as a weighted superposition of the full set of eigenfrequencies. In a case study performed with the FE model of a satellite it is shown that the effects of uncertain parameters can be very different in magnitude, depending on the considered response quantity. In particular, the uncertainty in the quantities of interest (eigenfrequencies) turns out to be mainly caused by very few of the uncertain parameters, which results in sharp estimates of the failure probabilities at low computational cost.

• Proceedings of the Computational Structural Engineering Institute Conference
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• 1989.04a
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• pp.1-4
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• 1989

Since 1960's, structural engineers have recognized that tile inherent random nature of loadings and materials as well as the imperfect structural analysis may be important factors in tile structural safety evaluation. Based on the successful developments of the reliability based structural analysis and design, the design criteria of tile standards are recently developed(or modified) in the light of the probabilistic concepts. To develop the probability-based design criteria for tile domestic buildings, the probabilistic characters of loadings acting on structures should be defined first. In this study, therefore, live load data on apartment buildings have collected and analyzed in a systematic manner, and their probabilistic characteristics have been studied. Based oil the results, the lifetime extreme values are computed and compared with current design loads. More rational design loads are suggested, which are more consistent in the probabilistic concepts.

• 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.