• Structural Engineering and Mechanics
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• v.15 no.2
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• pp.239-248
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• 2003

The dynamic response analysis of closed loop control system based on probability for the intelligent truss structures with random parameters is presented. The expressions of numerical characteristics of structural dynamic response of closed loop control system are derived by means of the mode superposition method, in which the randomness of physical parameters of structural materials, geometric dimensions of active bars and passive bars, applied loads and control forces are considered simultaneously. The influences of the randomness of them on structural dynamic response are inspected by several engineering examples and some significant conclusions are obtained.

• Journal of the Korea Society for Simulation
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• v.21 no.3
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• pp.71-78
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• 2012

This research discusses the application of the control variables to achieve a more precise estimation for the target response in queueing network simulation. The efficiency of control variable method in estimating the response depends upon how we choose a set of control variables strongly correlated with the response and how we construct a function of selected control variables. For a class of queuing network simulations, the random variables that drive the simulation are basically the service-time and routing probability random variables. Most of applications of control variable method focus on utilization of the service time random variables for constructing a controlled estimator. This research attempts to suggest a controlled estimator which uses these two kinds of random variables and explore the efficiency of these estimators in estimating the reponses for computer network system. Simulation experiments on this model show the promising results for application of routing probability control variables. We consider the applications of the routing probability control variables to various simulation models and combined control variables using information of service time and routing probability together in constructing a control variable as future researches.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2005.06a
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• pp.1682-1685
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• 2005

System algorithms estimated by deterministic input may occur the error between predicted and actual output. Especially, actual system can't predict the exact outputs due to uncertainty and tolerance of input parameters. A single output to a set of inputs has a limited value without the variation. Hence, we should consider various scatters caused by the load assessment, material characteristics, stress analysis and manufacturing methods in order to perform the robust design or estimate the reliability of structure. The system design with uncertainty should perform the probabilistic structural optimization with the statistical response and the reliability. This method calculated the probability distributions of the characteristics such as stress by combining stress analysis, response surface methodology and Monte-Carlo Method and got the probabilistic sensitivity. The sensitivity of structural response with respect to inconstant design variables was estimated by fracture probability. Therefore, this paper proposed the probabilistic reliability design method for fracture of uncorved freight end beam and the design criteria by fracture probability.

• 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.

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

• Journal of The Korean Society of Agricultural Engineers
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• v.60 no.2
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• pp.95-101
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• 2018

The objective of this study is to evaluate the liquefaction cyclic shear stress ratio considering the soil uncertainty. In this study, the probabilistic ground response analysis and the cyclic shear stress ratio analysis for the liquefaction potential evaluation are performed considering the soil variability. The statistical properties of input ground parameters were analyzed to investigate the parameters affecting the seismic response analysis. The Probabilistic analysis was carried out by Monte Carlo Simulation method. The ground response analysis was performed considering the soil variability and the probability distribution characteristics of the ground acceleration. The probability distribution of the peak ground acceleration by seismic characteristics was presented. The differences of liquefaction shear stress ratio results according to soil variability were compared and analyzed. The maximum acceleration of the ground by the deterministic method was analyzed to be overestimation of the ground amplification phenomenon. Also, the shear stress ratio was overestimated.

• Journal of the Society of Naval Architects of Korea
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• v.52 no.1
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• pp.88-95
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• 2015

For the frequency-domain spectral fatigue analysis, the probability density function of stress range needs to be estimated based on the stress spectrum only, which is a frequency domain representation of the response. The probability distribution of the stress range of the narrow-band spectrum is known to follow the Rayleigh distribution, however the PDF of wide-band spectrum is difficult to define with clarity due to the complicated fluctuation pattern of spectrum. In this paper, efforts have been made to figure out the links between the probability density function of stress range to the structural response of wide-band Gaussian random process. An artificial neural network scheme, known as one of the most powerful system identification methods, was used to identify the multivariate functional relationship between the idealized wide-band spectrums and resulting probability density functions. To achieve this, the spectrums were idealized as a superposition of two triangles with arbitrary location, height and width, targeting to comprise wide-band spectrum, and the probability density functions were represented by the linear combination of equally spaced Gaussian basis functions. To train the network under supervision, varieties of different wide-band spectrums were assumed and the converged probability density function of the stress range was derived using the rainflow counting method and all these data sets were fed into the three layer perceptron model. This nonlinear least square problem was solved using Levenberg-Marquardt algorithm with regularization term included. It was proven that the network trained using the given data set could reproduce the probability density function of arbitrary wide-band spectrum of two triangles with great success.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2004.10a
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• pp.700-703
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• 2004

A reliability analysis and design procedure based on the design of experiment (DOE) is combined with the response surface method (RSM) for numerical efficiency. The procedure established is based on a 3$^n$ full factorial DOE for numerical quadrature using explicit formula of optimum levels and weights derived for general distributions. The full factorial moment method (FFMM) shows good performance in terms of accuracy and ability to treat non-normally distributed random variables. But, the FFMM becomes very inefficient because the number of function evaluation required increases exponentially as the number of random variables considered increases. To enhance the efficiency, the response surface moment method (RSMM) is proposed. In RSMM, experiments only with high probability are conducted and the rest of data are complemented by a quadratic response surface approximation without mixed terms. The response surface is updated by conducting experiments one by one until the value of failure probability is converged. It is calculated using the Pearson system and the four statistical moments obtained from the experimental data. A measure for checking the relative importance of an experimental point is proposed and named as influence index. During the update of response surface, mixed terms can be added into the formulation.

• Structural Engineering and Mechanics
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• v.23 no.5
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• pp.505-523
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• 2006

An unrestrained plane rigid body resting on a horizontal surface which shakes horizontally and vertically may assume one of the five modes of response: rest, slide, slide-rock, rock, and free flight. The first four are nontrivial modes of motion. It is important to study which one of these responses is started from rest as in most studies it is often assumed that the initial mode is the particular mode of response. Criteria governing the initiation of modes are first briefly discussed. It is shown that the commencement of response modes depends on the aspect ratio of the body, coefficients of static and kinetic friction at the body-base interface, and the magnitude of maximum base accelerations. Considering the last two factors as random variables, the initiation of response modes is next studied from a probabilistic point of view. Type 1 extreme value and lognormal distributions are employed for maximum base excitations and coefficient of friction respectively. Analytical expressions for computing the probability values of each mode of response are derived. The effects of slenderness ratio, vertical acceleration, and statistical distributions of maximum acceleration and coefficient of friction are shown through numerical results and plots.

• Journal of the Korean Statistical Society
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• v.32 no.2
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• pp.103-119
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• 2003

Properties of stochastic regression imputation are discussed under the uniform within-cell response model. Variance estimator is proposed and its asymptotic properties are discussed. A limited simulation is also presented.