• KSCE Journal of Civil and Environmental Engineering Research
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• v.29 no.3A
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• pp.181-188
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• 2009

This study presented the basic data for determining reasonable construction method and evaluating the structural safety of suspension bridges. The analytical program was developed to conduct initial shape and natural frequency analysis, construction stage analysis and reliability analysis considering construction sequences. This program was based on analysis models of suspension bridges and reliability theories used in the previous study. A construction method was established considering various construction variables such as construction order and construction direction of girder and synchronized construction of main and side span etc. The dynamic construction analysis by a construction scheme was conducted with the developed program. Benefits of the characteristic analysis by the construction scheme was presented estimating structural response of critical members respectively. Structural reliability analysis by construction stage was conducted considering aleatory uncertainties. The safety of suspension bridges by established construction method was quantitatively estimated using reliability index and failure probability. Analytical results were re-estimated considering epistemic uncertainties, and critical percentile distributions of risk at the construction stage were presented using the frequency histogram.

• Structural Engineering and Mechanics
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• v.8 no.5
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• pp.477-490
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• 1999

The uncertainties associated with structural parameters and dynamic loading are identified and discussed. Structural parametric uncertainties are treated as random variables and dynamic wind load is simulated as a random process. Dynamic wind-induced responses of structures with parametric uncertainties are investigated by using stochastic finite element method. The formulas for structural dynamic reliability analysis considering the randomness of structural resistance and loading are proposed. Two numerical examples of high-rise structures are presented to illustrate the proposed methodology. The calculated results demonstrate that the variation in structural parameters indeed influences the dynamic response and the first passage probability evaluation of structures.

• Proceedings of the Computational Structural Engineering Institute Conference
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• 1989.10a
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• pp.40-45
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• 1989

In order to take account of the statistical properties of random variables used in the structural analysis, the conventional approach usually adopts the safety factor based on past experiences for the qualitative assessment of structural safety problem. Recently, new approach based on the probabilistic concept has been applied to the assessment of structural safety in order to circumvent the difficulties of the conventional approach in choosing the appropriate safety factor. Thus, computer program called "Probabilistic finite element method" is developed by incorporation the probabilistic concept into the conventional matrix method in order to investigate the effects of the random variables on the final output of the structural analysis. From the comparison of some examples, it can be concluded that the PFEM developed in this study deals with consistently with the uncertainty of random variables and provides the rational tool for the assessment of structural safety of plane frame.

• 한국신재생에너지학회:학술대회논문집
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• 2005.06a
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• pp.42-46
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• 2005

In spite of fast growing of prediction codes, there is still not negligible uncertainty in their results. This uncertainty affects on the turbine structural design and power production prediction. With the growing size of wind turbine, reducing this uncertainty is becoming one of critical issues for high performance and efficient wind turbine design. In this respect, there are international efforts to evaluate and tune prediction codes of wind turbine. As the reference data for this purpose, field test data is not appropriate because of its uncontrollable wind characteristics and its inherent uncertainty. Wind tunnel can provide controllable wind. For this reason, NREL has done the full scale test of the 10m turbine at NASA-Ames. With this reference data, a blind comparison has been done with participation of 18 organizations with 19 modeling tools. The results were not favorable. In Europe, a similar project is going on. Nine organizations from five countries are participating in the MEXICO project to do full scale wind tunnel tests and calculation with prediction codes. In this study. these two projects were reviewed in respect of wind tunnel test and its contribution. As a conclusion, it is suggested that scale model wind tunnel tests can be a complementary tool to calculation codes which were evaluated worse than expected.

• Structural Engineering and Mechanics
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• v.50 no.5
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• pp.697-708
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• 2014

The intentional buckling design of micro-films has various potential applications in engineering. The buckling amplitude and critical strain of micro-films are the crucial parameters for the buckling design. In the reported studies, the film parameters were regarded as deterministic. However, the geometrical and physical parameters uncertainty of micro-films due to manufacturing becomes prominent and needs to be considered. In the present paper, the probabilistic nonlinear buckling analysis of micro-films with uncertain parameters is proposed for design accuracy and reliability. The nonlinear differential equation and its asymptotic solution for the buckling micro-film with nominal parameters are firstly established. The mean values, standard deviations and variation coefficients of the buckling amplitude and critical strain are calculated by using the probability densities of uncertain parameters such as the film span length, thickness, elastic modulus and compressive force, to reveal the effects of the film parameter uncertainty on the buckling deformation. The results obtained illustrate the probabilistic relation between buckling deformation and uncertain parameters, and are useful for accurate and reliable buckling design in terms of probability.

• Smart Structures and Systems
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• v.15 no.3
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• pp.735-749
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• 2015

The major difficulty of using Bayesian probabilistic inference for system identification is to obtain the posterior probability density of parameters conditioned by the measured response. The posterior density of structural parameters indicates how plausible each model is when considering the uncertainty of prediction errors. The Markov chain Monte Carlo (MCMC) method is a widespread medium for posterior inference but its convergence is often slow. The differential evolution adaptive Metropolis-Hasting (DREAM) algorithm boasts a population-based mechanism, which nms multiple different Markov chains simultaneously, and a global optimum exploration ability. This paper proposes an improved differential evolution adaptive Metropolis-Hasting algorithm (IDREAM) strategy to estimate the posterior density of structural parameters. The main benefit of IDREAM is its efficient MCMC simulation through its use of the adaptive Metropolis (AM) method with a mutation strategy for ensuring quick convergence and robust solutions. Its effectiveness was demonstrated in simulations on identifying the structural parameters with limited output data and noise polluted measurements.

• Computational Structural Engineering
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• v.5 no.1
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• pp.97-108
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• 1992

This paper is an attempt to account for the uncertainty of the residual strength in the reliability analysis of structural systems. For this purpose the stochastic finite element method(SFEM) is linked to the system reliability analysis procedure. The stochastic finite element is known to be able to a more explicitly consider the effect of uncerainties of material and geometric variables on those of load effects in structural analysis procedure. The method has been applied to system as well as component reliability analysis of a plane structure. Comparison of the results by the present approach is made with the method in which the residual strength of failed component is treated as deterministic variable. Several case studies have been carried to show the effect of uncertainty in residual strength of a member after failure. Is has been conformed that reidual strength very much affect the system reliability level. It can be, hence, concluded that the uncertainties in the post-ultirnate behaviour may have to be taken into account in the system reliability analysis for a better a ssessment of the system reliability especially for a structure of which member behaviour is modelled as asemi-brittle model. And then the stochastic finite element method can efficiently evaluate the system reliability.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.13 no.3
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• pp.59-67
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• 1993

The variations of the natural frequencies and the peak response acceleration at the top of prestressed concrete reactor building due to random variability and/or model uncertainty of structural parameters are studied. The results may be used as essential input parameters in seismic probabilistic risk assessment or seismic margin assessment of the reactor building. The sensitivity test of each structural parameter is first performed to determine the most influential parameter upon the natural frequency of structure model. Then Monte Carlo simulation technique is applied to evaluate the effect of parameter variation on the natural frequencies and the peak response acceleration. The acceleration time history is obtained by direct integration scheme. As the study results, it is found that the fundamental natural frequency and the peak response acceleration at the top of the building are most strongly affected by Young's modulus among the structural parameters, in which the value of mean plus one standard deviation obtained by probabilistic approach deviates up to about (+)12% from the result of deterministic method. Considering the uncertainty of flexural rigidity, the structural responses vary in range of (-)4%~(+)14%.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.43 no.4
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• pp.178-189
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• 2020

The purpose of this study was to analyze structural relationships with regard to the effect of customer integration, which is a type of integration in the supply chain, and market orientation of supply chain on the resulting change in the supply chain and management performance. The results of analysis in this study are as follows: First, customer integration and market orientation had a positive effect on reducing the flexibility and uncertainty of SCM. The decreased flexibility and uncertainty of SCM had a positive effect on non-financial performance, which also had a positive effect on financial performance. Second, customer integration and market orientation had a positive effect on financial and non-financial performance indirectly by decreasing the flexibility and uncertainty of SCM. Third, the effect of customer integration and uncertainty of SCM on the flexibility of SCM changed depending on the position in the supply chain; the effect was larger in the distribution group. The implications based on the analysis results are as follows: It is expected that the ability to deal with market changes in the overall supply chain is improved by laying the foundation for cooperation through establishing information infrastructure, including sharing information with trade partners and integrating systems, and implementing customer integration based on these achievements. It is also necessary to consider the business types and characteristics of individual companies in establishing information infrastructure.

• Smart Structures and Systems
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• v.20 no.2
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• pp.207-217
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• 2017

Because of the inevitable uncertainties such as structural parameters, external excitations and measurement noises, the effects of uncertainties should be taken into consideration in structural damage detection. In this paper, two probabilistic structural damage detection approaches are proposed to account for the underlying uncertainties in structural parameters and external excitation. The first approach adopts the statistical moment-based structural damage detection (SMBDD) algorithm together with the sensitivity analysis of the damage vector to the uncertain parameters. The approach takes the advantage of the strength SMBDD, so it is robust to measurement noise. However, it requests the number of measured responses is not less than that of unknown structural parameters. To reduce the number of measurements requested by the SMBDD algorithm, another probabilistic structural damage detection approach is proposed. It is based on the integration of structural damage detection using temporal moments in each time segment of measured response time history with the sensitivity analysis of the damage vector to the uncertain parameters. In both approaches, probability distribution of damage vector is estimated from those of uncertain parameters based on stochastic finite element model updating and probabilistic propagation. By comparing the two probability distribution characteristics for the undamaged and damaged models, probability of damage existence and damage extent at structural element level can be detected. Some numerical examples are used to demonstrate the performances of the two proposed approaches, respectively.