• Smart Structures and Systems
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• v.33 no.3
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• pp.177-188
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• 2024

The fatigue-induced sequential failure of a structure having structural redundancy requires system-level analysis to account for stress redistribution. System reliability-based design optimization (SRBDO) for preventing fatigue-initiated structural failure is numerically costly owing to the inclusion of probabilistic constraints. This study incorporates the Branch-and-Bound method employing system reliability Bounds (termed the B³ method), a failure-path structural system reliability analysis approach, with a metaheuristic optimization algorithm, namely grey wolf optimization (GWO), to obtain the optimal design of structures under fatigue-induced system failure. To further improve the efficiency of this new optimization framework, an additional bounding rule is proposed in the context of SRBDO against fatigue using the B³ method. To demonstrate the proposed method, it is applied to complex problems, a multilayer Daniels system and a three-dimensional tripod jacket structure. The system failure probability of the optimal design is confirmed to be below the target threshold and verified using Monte Carlo simulation. At earlier stages of the optimization, a smaller number of limit-state function evaluation is required, which increases the efficiency. In addition, the proposed method can allocate limited materials throughout the structure optimally so that the optimally-designed structure has a relatively large number of failure paths with similar failure probability.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.29 no.2
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• pp.141-148
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• 2016

The long-span bridges such as Incheon Bridge and Seohae Grand Bridge are located on the coastal region effected frequently by strong wind of typhoons. In order to ensure the wind-resistant performance of the structure, estimation of the proper design wind speed is very important. In this study, stochastic estimation of design wind speed incurred by typhoons is carried out. For this purpose, we first established probability distribution of climatological parameters such as central pressure depth, distance of closest approach, translation speed and heading to build statistical model of typhoons, which are employed in Monte Carlo simulation for hypothetical typhoons. Once a typhoon is generated with statistically justified parameters, wind speeds are estimated along its path using wind field model. Thousands of typhoons are generated and their peak wind speeds are utilized to establish the extreme wind speeds for different return period. The results are compared with design basic wind speeds in Korean Highway Bridge Design Code, showing that the present results agree well with similar studies while the existing code suggests higher design wind speed.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.28 no.4
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• pp.351-359
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• 2015

In order to exactly evaluate the seismic collapse capacity of a structure, probabilistic approach is required by considering uncertainties related to its structural properties and ground motion. Regardless of the types of uncertainties, they influence on the seismic response of a structures and their effects are required to be estimated. An incremental dynamic analysis(IDA) is useful to investigate uncertainty-propagation due to ground motion. In this study, a 3-story steel moment-resisting frame is selected for a prototype frame and analyzed using the IDA. The uncertainty-propagation is assessed with categorized parameters representing epistemic uncertainties, such as the seismic weight, the inherent damping, the yield strength, and the elastic modulus. To do this, the influence of the uncertainty-propagation to the seismic collapse capacity of the prototype frame is probabilistically evaluated using the incremental dynamic analyses based on the Monte-Carlo simulation sampling with the Latin hypercube method. Of various parameters related to epistemic uncertainty-propagation, the inherent damping is investigated to be the most influential parameter on the seismic collapse capacity of the prototype frame.

• Journal of the Korea Concrete Institute
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• v.18 no.2 s.92
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• pp.239-248
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• 2006

Recently, a variety of researches has been carried out to obtain a more controlled durability and long-term performance of concrete structures under chloride attack environments. In particular, new procedures for probability-based durability analysis/design have been noticed to be very valuable for the enhancement of service life of concrete structures. Although there is still a lack of relevant data, this approach has been successfully applied to some new concrete structures. In this paper, the diffusion equation based on Fick's second law has been solved with a time dependent diffusion coefficient and the probabilistic analysis of the durability performance has been carried out by using a Monte Carlo Simulation. From the results, the influence of each parameter on the durability of concrete structures was investigated and the new procedure for durability analysis was demonstrated in terms of chloride penetration data from various concrete structures. The new procedure might be very useful in designing important concrete structures and help to predict the remaining service life of existing concrete structures under chloride attack environments.

• Journal of the Institute of Electronics Engineers of Korea SD
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• v.38 no.11
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• pp.771-780
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• 2001

It is indispensable to use the process and device simulation tool in order to analyze accurately the electrical characteristics of ULSI CMOS devices, in addition to developing and manufacturing those devices. The 3D Monte Carlo (MC) simulation result is not efficient for large-area application because of the lack of simulation particles. In this paper is reported a new efficient simulation strategy for 3D MC ion implantation into large-area application using the 3D MC code of TRICSI(TRansport Ions into Crystal Silicon). The strategy is related to our newly proposed split-trajectory method and ion-splitting method(ion-shadowing approach) for 3D large-area application in order to increase the simulation ions, not to sacrifice the simulation accuracy for defects and implanted ions. In addition to our proposed methods, we have developed the cell based 3D interpolation algorithm to feed the 3D MC simulation result into the device simulator and not to diverge the solution of continuous diffusion equations for diffusion and RTA(rapid thermal annealing) after ion implantation. We found that our proposed simulation strategy is very computationally efficient. The increased number of simulation ions is about more than 10 times and the increase of simulation time is not twice compared to the split-trajectory method only.

• Journal of the Korea Concrete Institute
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• v.19 no.1
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• pp.91-102
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• 2007

Through lessons in recent earthquakes, the bridge engineering community recognizes the need for new seismic design methodologies based on the inelastic structural performance of RC bridge structures. This study represents results of performance-based fragility analysis of reinforced concrete (RC) bridge. Monte carlo simulation is performed to study nonlinear dynamic responses of RC bridge. Two-parameter log-normal distribution function is used to represent the fragility curves. These two-parameters, referred to as fragility parameters, are estimated by the traditional maximum likelihood procedure, which is treated each event of RC bridge pier damage as a realization of Bernoulli experiment. In order to formulate the fragility curves, five different damage states are described by two practical factors: the displacement and curvature ductility, which are mostly influencing on the seismic behavior of RC bridge piers. Five damage states are quantitatively assessed in terms of these seismic ductilities on the basis of numerous experimental results of RC bridge piers. Thereby, the performance-based fragility curves of RC bridge pier are provided in this paper. This approach can be used in constructing the fragility curves of various bridge structures and be applied to construct the seismic hazard map.

• The Journal of the Korea institute of electronic communication sciences
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• v.10 no.4
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• pp.499-505
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• 2015

Trend Impact Analysis(: TIA) is an advanced forecasting tool used in futures studies for identifying, understanding and analyzing the consequences of unprecedented events on future trends. An adaptive neuro-fuzzy inference system is a kind of artificial neural network that integrates both neural networks and fuzzy logic principles, It is considered to be a universal estimator. In this paper, we propose an advanced mechanism to generate more justifiable estimates to the probability of occurrence of an unprecedented event as a function of time with different degrees of severity using Adaptive Neuro-Fuzzy Inference System(: ANFIS). The key idea of the paper is to enhance the generic process of reasoning with fuzzy logic and neural network by adding the additional step of attributes simulation, as unprecedented events do not occur all of a sudden but rather their occurrence is affected by change in the values of a set of attributes. An ANFIS approach is used to identify the occurrence and severity of an event, depending on the values of its trigger attributes. The trigger attributes can be calculated by a stochastic dynamic model; then different scenarios are generated using Monte-Carlo simulation. To compare the proposed method, a simple simulation is provided concerning the impact of river basin drought on the annual flow of water into a lake.

• Journal of Korea Water Resources Association
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• v.41 no.1
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• pp.35-47
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• 2008

The low flow analysis is an important part in water resources engineering. Also, the results of low flow frequency analysis can be used for design of reservoir storage, water supply planning and design, waste-load allocation, and maintenance of quantity and quality of water for irrigation and wild life conservation. Especially, for identification of the uncertainty in frequency analysis, the Bayesian approach is applied and compared with conventional methodologies in at-site low flow frequency analysis. In the first manuscript, the theoretical background for the Bayesian MCMC (Bayesian Markov Chain Monte Carlo) method and Metropolis-Hasting algorithm are studied. Two types of the prior distribution, a non-data- based and a data-based prior distributions are developed and compared to perform the Bayesian MCMC method. It can be suggested that the results of a data-based prior distribution is more effective than those of a non-data-based prior distribution. The acceptance rate of the algorithm is computed to assess the effectiveness of the developed algorithm. In the second manuscript, the Bayesian MCMC method using a data-based prior distribution and MLE(Maximum Likelihood Estimation) using a quadratic approximation are performed for the at-site low flow frequency analysis.

• Progress in Medical Physics
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• v.21 no.1
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• pp.93-98
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• 2010

The aim of this work was to establish the methodology for event positioning by measuring depth of interaction (DOI) information and to evaluate the system sensitivity and spatial resolution of the new detector for I-125 and Tc-99m imaging. For this purpose, a Monte Carlo simulation tool, DETECT2000 and GATE were used to model the energy deposition and light distribution in the detector and to validate this approach. Our proposed detector module consists of a monolithic CsI(Tl) crystal with dimensions of $50.0{\times}50.0{\times}3.0\;mm^3$. The results of simulation demonstrated that the resolution is less than 1.5 mm for both I-125 and Tc-99m. The main advantage of the proposed detector module is that by using 3 mm thick CsI(Tl) with maximum-likelihood position-estimation (MLPE) method, high resolution I-125 imaging and high sensitivity Tc-99m imaging are possible. In this paper, we proved that our new detector to be a reliable design as a detector for a multi-energy SPECT.

• Journal of the Korea Concrete Institute
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• v.21 no.6
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• pp.681-688
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• 2009

The railroad bridges have been usually experienced by vibration and impact in service state. With this reason, it is important that the effective strengthening capacity should be considered to resist the kind of service loading. In this study, NSM strengthening technique is recommended for the concrete railroad bridge because of its better effective resistance for dynamic loading condition and strengthening cost than the conventional externally bonded strengthening using fiber sheet. However, to widely apply NSM method for the concrete railroad bridge, it needs that the strengthening ratio has to be reasonably evaluated with geometrical and material uncertainties, especially for the concrete bridge under long-term service state without the apparent design history and detail information such as concrete compressive strength, reinforcing ratio, railroad characteristics. The purpose of this study is to propose the critical strengthening ratio of CFRP plate for the targeted concrete railroad bridge with uncertainties of deterioration of the structures. To do this, Monte Carlo Simulation (MCS) for geometrical and material uncertainties have been applied so that this approach may bring the reasonable strengthening ratio of CFRP plate considering probabilistic uncertainties for the targeted concrete railroad bridge. Finally, the critical strengthening ratio of NSM strengthened by CFRP plate is calculated by using the limit state function based on the target reliability index of 3.5.