• Journal of the Korean Society of Manufacturing Technology Engineers
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• v.19 no.5
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• pp.637-644
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• 2010

This paper presents a reliability-based shape optimization (RBSO) using the growth-strain method. An actual design involves uncertain conditions such as material property, operational load, Poisson's ratio and dimensional variation. The purpose of the RBSO is to consider the variations of probabilistic constraint and performances caused by uncertainties. In this study, the growth-strain method was applied to shape optimization of reliability analysis. Even though many papers for reliability-based shape optimization in mathematical programming method and ESO (Evolutionary Structural Optimization) were published, the paper for the reliability-based shape optimization using the growth-strain method has not been applied yet. Growth-strain method is applied to performance measure approach (PMA), which has probabilistic constraints that are formulated in terms of the reliability index, is adopted to evaluate the probabilistic constraints in the change of average mises stress. Numerical examples are presented to compare the DO with the RBSO. The results of design example show that the RBSO model is more reliable than deterministic optimization. It was verified that the reliability-based shape optimization using growth-strain method are very effective for general structure. The purpose of this study is to improve structure's safety considering probabilistic variable.

• Journal of Electrical Engineering and Technology
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• v.12 no.5
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• pp.1743-1753
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• 2017

Since there are multiple random variables in the probabilistic load flow (PLF) calculation of distribution system containing distributed generation (DG) and electric vehicle charging load (EVCL), a Monte Carlo method based on composite sampling method is put forward according to the existing simple random sampling Monte Carlo simulation method (SRS-MCSM) to perform probabilistic assessment analysis of voltage quality of distribution system containing DG and EVCL. This method considers not only the randomness of wind speed and light intensity as well as the uncertainty of basic load and EVCL, but also other stochastic disturbances, such as the failure rate of the transmission line. According to the different characteristics of random factors, different sampling methods are applied. Simulation results on IEEE9 bus system and IEEE34 bus system demonstrates the validity, accuracy, rapidity and practicability of the proposed method. In contrast to the SRS-MCSM, the proposed method is of higher computational efficiency and better simulation accuracy. The variation of nodal voltages for distribution system before and after connecting DG and EVCL is compared and analyzed, especially the voltage fluctuation of the grid-connected point of DG and EVCL.

• Steel and Composite Structures
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• v.15 no.1
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• pp.15-39
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• 2013

The sensitivities of a structural response due to variation of its design parameters are prerequisite in the majority of the algorithms used for fundamental problems in engineering as system uncertainties, identification and probabilistic assessments etc. The paper presents the concept of probabilistic sensitivity of suspension bridges with respect to near-fault ground motion. In near field earthquake ground motions, large amplitude spectral accelerations can occur at long periods where many suspension bridges have significant structural response modes. Two different types of suspension bridges, which are Bosporus and Humber bridges, are selected to investigate the near-fault ground motion effects on suspension bridges random response sensitivity analysis. The modulus of elasticity is selected as random design variable. Strong ground motion records of Kocaeli, Northridge and Erzincan earthquakes are selected for the analyses. The stochastic sensitivity displacements and internal forces are determined by using the stochastic sensitivity finite element method and Monte Carlo simulation method. The stochastic sensitivity displacements and responses obtained from the two different suspension bridges subjected to these near-fault strong-ground motions are compared with each other. It is seen from the results that near-fault ground motions have different impacts stochastic sensitivity responses of suspension bridges. The stochastic sensitivity information provides a deeper insight into the structural design and it can be used as a basis for decision-making.

• Proceedings of the Computational Structural Engineering Institute Conference
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• 2006.04a
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• pp.275-282
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• 2006

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 tolernce 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 etimate 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 simulation and got the probabilistic sensitivity. The sensitivity of structural response with respect to in constant 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.

• Journal of the Korea Society for Simulation
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• v.26 no.1
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• pp.39-46
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• 2017

An arrangement of passive sonars is considered to be a fixed underwater surveillance system for detecting an anti-submarine consistently. An effectiveness score for optimizing the arrangement of passive sonars is defined in a function of the probability of detection and localization. These two features contain various probabilistic variations including seasons, sea states, depths of water, etc. Due to this reason, the effectiveness scores show probabilistic characteristics from the input of the arrangement of passive sonars. This paper defines the optimization problem having the results of probabilistic characteristics from various parameters of input conditions. Also, we suggest a simulation-based process of deciding the optimized arrangement of passive sonars using DPSO(Discrete binary version of PSO) method.

• Journal of Welding and Joining
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• v.23 no.6
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• pp.61-66
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• 2005

A probabilistic approach for evaluating failure risk is suggested in this paper. Probabilistic fracture analyses were performed for a pressurized pipe of a Cr-Mo steel reflecting variation of material properties at high temperature. A crack was assumed to be located along the weld fusion line. Probability density functions of major variables were determined by statistical analyses of material creep and creep crack growth data measured by the previous experimental studies by authors. Distributions of these variables were implemented in Monte Carlo simulation of this study. As a fracture parameter for characterizing growth of a fusion line crack between two materials with different creep properties, $C_t$ normalized with $C^*$ was employed. And the elapsed time was also normalized with tT, Resultingly, failure probability as a function of operating time was evaluated fur various cases. Conventional deterministic life assessment result was turned out to be conservative compared with that of probabilistic result. Sensitivity analysis for each input variable was conducted to understand the most influencing variable to the analysis results. Internal pressure, creep crack growth coefficient and creep coefficient were more sensitive to failure probability than other variables.

• Structural Engineering and Mechanics
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• v.71 no.2
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• pp.197-210
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• 2019

Probabilistic buckling behavior of sandwich panel considering random system parameters using a radial basis function (RBF) approach is presented in this paper. The random system properties result in an uncertain response of the sandwich structure. The buckling load of laminated sandwich panel is obtained by employing higher-order-zigzag theory (HOZT) coupled with RBF and probabilistic finite element (FE) model. The in-plane displacement variation of core as well as facesheet is considered to be cubic while transverse displacement is considered to be quadratic within the core and constant in the facesheets. Individual and combined stochasticity in all elemental input parameters (like facesheets thickness, ply-orientation angle, core thickness and properties of material) are considered to know the effect of different degree of stochasticity, ply- orientation angle, boundary conditions, core thickness, number of laminates, and material properties on global response of the structure. In order to achieve the computational efficiency, RBF model is employed as a surrogate to the original finite element model. The stiffness matrix of global response is stored in a single array using skyline technique and simultaneous iteration technique is used to solve the stochastic buckling equations.

• Journal of the Korean GEO-environmental Society
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• v.13 no.11
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• pp.81-91
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• 2012

This paper mainly deals with the analysis of probabilistic characteristics of the disturbed function proposed to predict dynamic behavior of Geosynthetic-soil interface as the lining and cover systems used in waste landfills. Calibration and statistical property estimation of the parameters in the disturbed function model were first performed using many experimental data obtained from a new multi-purpose interface apparatus (M-PIA). In order to analyze the effect due to changes in chemical degradation and normal loads condition, probabilistic properties such as mean, coefficient of variation and distribution type of the disturbed function were evaluated using both the LHS method known to be a very efficient sampling scheme and the estimated statistical property of A and Z. As a result, variation of the disturbed function is found to range approximately from 10~28% according to the level of ${\xi}_D$ and Weibull appears to be the most adequate distribution type at almost all levels of ${\xi}_D$. It is concluded that a probabilistic safety assessment method for Geosynthetic-soil interface considering uncertainty in shear strength can be developed by utilizing probabilistic properties of the disturbed function obtained in this study.

• Economic and Environmental Geology
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• v.33 no.4
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• pp.295-307
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• 2000

Probabilistic analysis is a powerful method to quantify variability and uncertainty common in engineering geology fields. In rock slope engineering, the uncertainty and variation may be in the form of scatter in orientations and geometries of discontinuities, and also test results. However, in the deterministic analysis, the factor of safety which is used to ensure stability of rock slopes, is based on the fixed representative values for each parameter without a consideration of the scattering in data. For comparison, in the probabilistic analysis, these discontinuity parameters are considered as random variables, and therefore, the reliability and probability theories are utilized to evaluate the possibility of slope failure. Therefore, in the probabilistic analysis, the factor of safety is considered as a random variable and replaced by the probability of failure to measure the level of slope stability. In this study, the stochastic properties of discontinuity parameters are evaluated and the stability of rock slope is analyzed based on the random properties of discontinuity parameters. Then, the results between the deterministic analysis and the probabilistic analysis are compared and the differences between the two analysis methods are explained.

• Journal of the Korean Geotechnical Society
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• v.25 no.11
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• pp.87-103
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• 2009

To determine the reliable probabilistic distribution model of geotechnical properties, outlier and randomness test for analysis data, parameter estimation of probabilistic distribution model, and goodness-of-fit test for model parameter and probabilistic distribution model have to be performed in sequence. In this paper, the probabilistic distribution model's geotechnical properties of Songdo area in Incheon are estimated by the above proposed procedure. Also, the coefficient of variation (COV) representing the variability of geotechnical properties is determined for several geotechnical properties. Reliable probabilistic distribution model and COV of geotechnical properties can be used for probability-based design procedure and reasonable choice of design value in deterministic design method.