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

• Wind and Structures
• /
• v.21 no.6
• /
• pp.609-623
• /
• 2015

Seismic reliability analysis of a jacket-type support structure for an offshore wind turbine was performed. When defining the limit state function by using the dynamic response of the support structure, a number of dynamic calculations must be performed in a First-Order Reliability Method (FORM). That means analysis costs become too high. In this paper, a new reliability analysis approach using a static response is used. The dynamic effect of the response is considered by introducing a new parameter called the Peak Response Factor (PRF). The probability distribution of PRF can be estimated by using the peak value in the dynamic response. The probability distribution of the PRF was obtained by analyzing dynamic responses during a set of ground motions. A numerical example is presented to compare the proposed approach with the conventional static response-based approach.

• Journal of Korean Institute of Industrial Engineers
• /
• v.36 no.4
• /
• pp.212-218
• /
• 2010

This paper shows accuracy comparison results of reliability estimation methods for one-shot systems with respect to sample sizes. To compare accuracy in reliability estimation methods, quantal-response data, characterizing one-shot systems, were simulated using failure times of LED obtained through the accelerated life test, and then the true reliability over time was evaluated using the failure times. The simulated quantal-response data were used to estimate the true reliability through applying reliability estimation methods in open literature. Accuracy of each reliability estimation method was compared in terms of both SSE (Sum of Squared Error) and MSE (Mean Squared Error), and then estimation trend for each method is found. Feasible bounds which true reliability would exist within were estimated through applying the found trends to quantal-response data set of a real weapon system.

• Journal of the Korea Institute of Military Science and Technology
• /
• v.13 no.6
• /
• pp.982-989
• /
• 2010

This paper shows accuracy comparison results of reliability estimation methods for one-shot systems such as ammunitions. Quantal-response data, following a binomial distribution at each sampling time, characterizes lifetimes of one-shot systems. Various quantal-response data of different sample sizes are simulated using lifetime data randomly sampled from assumed weibull distributions with different shape parameters but the identical scale parameter in this paper. Then, reliability estimation methods in open literature are applied to the simulated quantal-response data to estimate true reliability over time. Rankings in estimation accuracy for different sample sizes are determined using t-test of SSE. Furthermore, MSE at each time, including both bias and variance of estimated reliability metrics for each method are analyzed to investigate how much both bias and variance contribute the SSE. From the MSE analysis, MSE provides reliability estimation trend for each method. Parametric estimation method provides more accurate reliability estimation results than the other methods for most of sample sizes.

• Journal of Ocean Engineering and Technology
• /
• v.29 no.5
• /
• pp.342-350
• /
• 2015

A seismic reliability analysis of the jacket-type support structure for an offshore wind turbine was performed. When defining the limit state function using the dynamic response of the support structure, numerous dynamic calculations should be performedin an approach like the FORM (first-order reliability method). This causes a substantial increase in the analysis cost. Therefore, in this paper, a new reliability analysis approach using the static response is used. The dynamic effect of the response is considered by introducing a new parameter called the peak response factor (PRF). The probability distribution of the PRF could be estimated using the peak value of the dynamic response. The probability distribution of the PRF was obtained for a set of ground motions. A numerical example is considered to compare the proposed approach with the conventional static-response-based approach.

• Earthquakes and Structures
• /
• v.2 no.3
• /
• pp.279-295
• /
• 2011

This paper develops a probabilistic methodology for the seismic reliability analysis of structures with random properties. The earthquake loading is assumed to be described in terms of response spectra. The proposed methodology takes advantage of the response spectra and thus does not require explicit dynamic analysis of the actual structure. Uncertainties in the structural properties (e.g. member cross-sections, modulus of elasticity, member strengths, mass and damping) as well as in the seismic load (due to uncertainty associated with the earthquake load specification) are considered. The structural reliability is estimated by determining the failure probability or the reliability index associated with a performance function that defines safe and unsafe domains. The structural failure is estimated using a performance function that evaluates whether the maximum displacement has been exceeded. Numerical illustrations of reliability analysis of elastic and elastic-plastic single-story frame structures are presented first. The extension of the proposed method to elastic multi-degree-of-freedom uncertain structures is also studied and a solved example is provided.

• Structural Engineering and Mechanics
• /
• v.62 no.2
• /
• pp.139-142
• /
• 2017

For the conventional computational methods for structural reliability analysis, the common limitations are long computational time, large number of iteration and low accuracy. Thus, a new novel method for structural reliability analysis has been proposed in this paper based on response surface method incorporated with an improved genetic algorithm. The genetic algorithm is first improved from the conventional genetic algorithm. Then, it is used to produce the response surface and the structural reliability is finally computed using the proposed method. The proposed method can be used to compute structural reliability easily whether the limit state function is explicit or implicit. It has been verified by two practical engineering cases that the algorithm is simple, robust, high accuracy and fast computation.

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

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

• Wind and Structures
• /
• v.10 no.1
• /
• pp.45-60
• /
• 2007

Transmission tower is a vital component in electrical system. In order to accurately compute the dynamic response and reliability of transmission tower under the excitation of wind loading, a new method termed as probability density evolution method (PDEM) is introduced in the paper. The PDEM had been proved to be of high accuracy and efficiency in most kinds of stochastic structural analysis. Consequently, it is very hopeful for the above needs to apply the PDEM in dynamic response of wind-excited transmission towers. Meanwhile, this paper explores the wind stochastic field from stochastic Fourier spectrum. Based on this new viewpoint, the basic random parameters of the wind stochastic field, the roughness length $z_0$ and the mean wind velocity at 10 m heigh $U_{10}$, as well as their probability density functions, are investigated. A latticed steel transmission tower subject to wind loading is studied in detail. It is shown that not only the statistic quantities of the dynamic response, but also the instantaneous PDF of the response and the time varying reliability can be worked out by the proposed method. The results demonstrate that the PDEM is feasible and efficient in the dynamic response and reliability analysis of wind-excited transmission towers.