• 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.

• 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.

• Earthquakes and Structures
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• v.17 no.2
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• pp.131-141
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• 2019

Structural control systems have uncertainties in their structural parameters and control devices which by using reliability analysis, uncertainty can be modeled. In this paper, reliability of controlled structures equipped with semi-active Magneto-Rheological (MR) dampers is investigated. For this purpose, at first, the effect of the structural parameters and damper parameters on the reliability of the seismic responses are evaluated. Then, the reliability of MR damper force is considered for expected levels of performance. For sensitivity analysis of the parameters exist in Bouc- Wen model for predicting the damper force, the importance vector is utilized. The improved first-order reliability method (FORM), is used to reliability analysis. As a case study, an 11-story shear building equipped with 3 MR dampers is selected and numerically obtained experimental data of a 1000 kN MR damper is assumed to study the reliability of the MR damper performance for expected levels. The results show that the standard deviation of random variables affects structural reliability as an uncertainty factor. Thus, the effect of uncertainty existed in the structural model parameters on the reliability of the structure is more than the uncertainty in the damper parameters. Also, the reliability analysis of the MR damper performance show that to achieve the highest levels of nominal capacity of the damper, the probability of failure is greatly increased. Furthermore, by using sensitivity analysis, the Bouc-Wen model parameters which have great importance in predicting damper force can be identified.

• 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.

• Structural Engineering and Mechanics
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• v.6 no.8
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• pp.901-919
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• 1998

Most reliability-based analyses focus on the reliability of the individual components of a structure. There are many advantages to examining the components in combination as an entire structural system. This paper illustrates an algorithm used in the computer program RELSYS (RELiability of SYStems) which computes the system reliability of any structure which can be modeled as a series-parallel combination of its components. A first-order method is used to initially compute the reliability of each individual component. The system reliability is computed by successively reducing the series and parallel systems until the system has been simplified to a single equivalent component. Equivalent alpha vectors are used to account for the correlation between failure modes during the system reduction process.

• International conference on construction engineering and project management
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• 2020.12a
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• pp.225-234
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• 2020

Reliability-based structural optimization usually requires designers or engineers model different designs manually, which is considered very time consuming and all possibilities cannot be fully explored. Otherwise, a lot of time are needed for designers or engineers to learn mathematical modeling and programming skills. Therefore, a framework that integrates generative design, structural simulation and reliability theory is proposed. With the proposed framework, various designs are generated based on a set of rules and parameters defined based on visual programming, and their structural performance are simulated by OpenSees. Then, reliability of each design is evaluated based on the simulation results, and an optimal design can be found. The proposed framework and prototype are tested in the optimization of a steel frame structure, and results illustrate that generative design based on visual programming is user friendly and different design possibilities can be explored in an efficient way. It is also reported that structural reliability can be assessed in an automatic way by integrating Dynamo and OpenSees. This research contributes to the body of knowledge by providing a novel framework for automatic reliability evaluation and structural optimization.

• Transactions of the Korean Society for Noise and Vibration Engineering
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• v.22 no.1
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• pp.81-87
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• 2012

This paper establishes a modeling and simulation procedure for structural response and reliability of a cylindrical array sensor on submarines under the shock generated by underwater explosion. The structural reliability of SONAR is important because the submarine could get out of combat ability by the structural damage of the SONAR upon explosion. A cylindrical array sensor was first modeled using the finite element method. Modal analysis was then performed for the check of the reliability of the modeling. The shock resistance simulations were performed for the responses to the structural shock waves and for the responses to the directly applied underwater shock waves, according to BV-043 and MIL-STD-901D, respectively. The stresses of the structure were evaluated with von-Mises scheme. Vulnerable regions were exposed through mapping the maximum stress to the structural model. Maximum stress of the SONAR was compared with the yield stress of the material to examine the structural reliability.

• Earthquakes and Structures
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• v.7 no.6
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• pp.1061-1070
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• 2014

An iterative hybrid structural dynamic reliability prediction model has been developed under multiple-time interval loads with and without consideration of stochastic structural strength degradation. Firstly, multiple-time interval loads have been substituted by the equivalent interval load. The equivalent interval load and structural strength are assumed as random variables. For structural reliability problem with random and interval variables, the interval variables can be converted to uniformly distributed random variables. Secondly, structural reliability with interval and stochastic variables is computed iteratively using the first order second moment method according to the stress-strength interference theory. Finally, the proposed method is verified by three examples which show that the method is practicable, rational and gives accurate prediction.

• Computational Structural Engineering : An International Journal
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• v.2 no.1
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• pp.1-10
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• 2002

Information on the distribution of the basic random variables is essential for the accurate evaluation of structural reliability. The usual method for determining the distribution is to fit a candidate distribution to the histogram of available statistical data of the variable and perform appropriate goodness-of-fit tests. Generally, such candidate distributions would have two parameters that may be evaluated from the mean value and standard deviation of the statistical data. In the present paper, a-parameter Gamma distribution, whose parameters can be directly defined in terms of the mean value, standard deviation and skewness of available data, is suggested. The flexibility and advantages of the distribution in fitting statistical data and its significance in structural reliability evaluation are identified and discussed. Numerical examples are presented to demonstrate these advantages.

• International Journal of High-Rise Buildings
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• v.9 no.2
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• pp.175-185
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• 2020

Currently, few studies have been conducted to comprehend the seismic reliability of post-tensioned (PT) CLT shear wall structures, due to the complexity of this kind of structural system as well as due to lack of a reliable structural model. In this paper, a set of 4-, 8-, 12-, and 16-storey benchmark PT CLT shear wall structures (PT-CLTstrs) were designed using the direct displacement-based design method, and their calibrated structural models were developed. The seismic reliability of each PT-CLTstr was assessed based on the fragility analysis and based on the response surface method (RSM), respectively. The fragility-based reliability index and the RSM-based reliability index were then compared, for each PT-CLTstr and for each seismic hazard level. Results show that the RSM-based reliabilities are slightly less than the fragility-based reliabilities. Overall, both the RSM and the fragility-based reliability method can be used as efficient approaches for assessing the seismic reliabilities of the PT-CLTstrs. For these studied mid- and high-rise benchmark PT-CLTstrs, following their fragility-based reliabilities, the 8-storey PT-CLTstr is subjected to the least seismic vulnerability; while, following their RSM-based reliabilities, the 4-storey PT-CLTstr is subjected to the least seismic vulnerability