• International Journal of Reliability and Applications
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• v.2 no.3
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• pp.209-240
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• 2001

Computer-based simulation and analysis is used extensively in engineering for a variety of tasks. Despite the steady and continuing growth of computing power and speed, the computational cost of complex high-fidelity engineering analyses and simulations limit their use in important areas like design optimization and reliability analysis. Statistical approximation techniques such as design of experiments and response surface methodology are becoming widely used in engineering to minimize the computational expense of running such computer analyses and circumvent many of these limitations. In this paper, we compare and contrast five experimental design types and four approximation model types in terms of their capability to generate accurate approximations for two engineering applications with typical engineering behaviors and a wide range of nonlinearity. The first example involves the analysis of a two-member frame that has three input variables and three responses of interest. The second example simulates the roll-over potential of a semi-tractor-trailer for different combinations of input variables and braking and steering levels. Detailed error analysis reveals that uniform designs provide good sampling for generating accurate approximations using different sample sizes while kriging models provide accurate approximations that are robust for use with a variety of experimental designs and sample sizes.

• Computational Structural Engineering
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• v.4 no.2
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• pp.111-117
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• 1991

The analysis method calculating the mean and standard deviation for the eigenvalue of complicated structures in which the limit state equation is implicitly expressed is formulated and applied to the buckling analysis by combining probabilistic finite element method with direct differential method which is a kind of sensitivity analysis technique. Also, the probability of buckling failure is calculated by combining classical reliability techniques such a MVFOSM and AFOSM. As random variables external load, elastic modulus, sectional moment of inertia and member length are chosen and Parkinson's iteration algorithm in AFOSM is used. The accuracy of the results by this study is verified by comparing the results with the crude Monte Carlo simulation and Importance Sampling Method. Through the case study of some structures the important aspects of buckling reliability analysis are discussed.

• Journal of Korean Society for Quality Management
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• v.46 no.3
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• pp.641-650
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• 2018

Purpose: This article provides a cause of breakage and a method for improving reliability of the headlight system installed in the main battle tank K2. Method: The natural frequency of the headlight system is estimated by using the finite element method. In addition, the allowable stress level under the severe conditions is provided through vibration test of a single item and a system level. Results: Based on the finite element analysis and the vibration test in the frequency domain, the lamp of the left headlight system fails by the resonance effect. Conclusion: For improving the reliability of the headlight system, the thickness of protector frame is increased to avoid the resonance effect.

• Proceedings of the KIEE Conference
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• 2005.11b
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• pp.125-128
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• 2005

This paper illustrates potential applications of POM/OPM/BOR, which are used for deterministic reliability evaluation in the operation mode (operational planning and operating) in Korea Power System. Deterministic reliability evaluation in this paper bases the philosophy of the marginality and the limitation of physical quantity (voltage and thermal in main) under contingency analysis. The POM/OPM/BOR tools have been developed by V&R (Vaimann and Research) in USA. Before case studies, main frame and feature of the tools are introduced in brief. Case studies of the actual power system of Korea are demonstrated for checking the application possibility of POM/OPM/BOR.

• Structural Engineering and Mechanics
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• v.84 no.3
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• pp.323-335
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• 2022

The main idea of the framework is to seamlessly combine a reasonably accurate and fast surrogate model with the importance sampling strategy. Developing a surrogate model for predicting structures' dynamic responses is challenging because it involves high-dimensional inputs and outputs. For this purpose, a novel surrogate model based on cutting-edge deep learning architectures specialized for capturing temporal relationships within time-series data, namely Long-Short term memory layer and Transformer layer, is designed. After being properly trained, the surrogate model could be utilized in place of the finite element method to evaluate structures' responses without requiring any specialized software. On the other hand, the importance sampling is adopted to reduce the number of calculations required when computing the failure probability by drawing more relevant samples near critical areas. Thanks to the portability of the trained surrogate model, one can integrate the latter with the Importance sampling in a straightforward fashion, forming an efficient framework called TTIS, which represents double advantages: less number of calculations is needed, and the computational time of each calculation is significantly reduced. The proposed approach's applicability and efficiency are demonstrated through three examples with increasing complexity, involving a 1D beam, a 2D frame, and a 3D building structure. The results show that compared to the conventional Monte Carlo simulation, the proposed method can provide highly similar reliability results with a reduction of up to four orders of magnitudes in time complexity.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.10 no.5
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• pp.359-363
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• 2017

The LED (Liquid Emitting Diode) frame device is a big part of the representative display industry in Korea. LED is an essential part for TV, monitor, notebook, and mobile phone. In Japan, Taiwan, China and other countries, investment in LEDs has been strengthened, and productivity has become an important issue. However, as the size of the parts becomes smaller, the inconsistent inspection by the human eye becomes a problem of reliability, so that the automatic inspection process becomes an essential issue in the field of LED module inspection. In this paper, we investigate defects in visual inspection process using computer vision technology. The inspection of the LED frame is made quickly and accurately, thereby improving the efficiency of the process and shortening the inspection time. As a result of applying the inspection system to the field, we confirmed that it is possible to inspect quickly and accurately.

• Journal of the Earthquake Engineering Society of Korea
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• v.11 no.2 s.54
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• pp.39-45
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• 2007

In this study the probability and the reliability-based seismic performance evaluation procedure proposed in the FEMA-355F was applied to a reinforced concrete moment frame building. For the FEMA procedure, which was originally developed for steel moment frame structures, to be applied to other structural systems, the capacity should be re-defined and the factors reflecting the uncertainties related to capacity and demand need to be determined. To perform the evaluation procedure a prototype building was designed per IBC 2003, and inelastic dynamic analyses were conducted applying site-specific ground motions to determine the parameters for performance evaluation. According to the analysis results, distribution of the determined capacities turned out to be relative]y smaller than that of the demands, which showed that the defined capacity was reasonable. It was also shown that the prototype building satisfied the target performance since the determined confidence levels exceeded the otjectives for both local and global collapses.

• International Journal of Concrete Structures and Materials
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• v.18 no.3E
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• pp.173-181
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• 2006

The objectives of this study are to evaluate the reliability of an existing nonlinear analysis program for predicting the inelastic behavior of reinforced concrete frame with seismic details and to observe the redistribution of the internal forces, which can not be easily measured by an experiment. In order to carry out this task, the nonlinear analysis program of IDARC 2D(3) was run on a 2-bay, 2-story moment-resisting reinforced concrete plane frame with seismic details. (1) The effort to obtain the results of the analysis similar to those of experiment was made by determining the appropriate values of model parameters. The comparison of the analysis results with those of experiment and the observation of the distribution of internal forces obtained through nonlinear analysis points to the following conclusions. (1) The overall relationship between lateral load and lateral displacement given by the analysis is similar to that of experiment. However, the values of initial stiffness and the amount of energy dissipation in the initial displacement steps given by the analysis show larger values than those of experiment. (2) The analysis provided detailed information on the distribution and redistribution of internal forces and proved useful in elucidating the crack pattern, the sequence of the occurrence of plastic hinges, and the failure or yielding mechanism for the whole structure. (3) In spite of the similarity in overall behavior of analysis and experiment, there exists a significant discrepancy in some local behaviors. Furthermore, the hysteresis in the relationship between moment and curvature in some column ends have shown sudden deteriorations in strength, which can not be interpreted satisfactorily at the present time. Therefore, it is necessary to develop a better analytical model to fill this knowledge gap.

• Journal of the Institute of Convergence Signal Processing
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• v.20 no.3
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• pp.171-176
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• 2019

Drones are highly utilized because they can efficiently acquire long-distance videos. In drone operation, the speed, which is the magnitude of the velocity, can be set, but the moving direction cannot be set, so accurate information about the drone's movement should be estimated. In this paper, we estimate the velocity of the drone moving at a constant speed and direction. In order to estimate the drone's velocity, the displacement of the target frame to minimize the sum of absolute difference (SAD) of the reference frame and the target frame is obtained. The ground truth of the drone's velocity is calculated using the position of a certain matching point over all frames. In the experiments, a video was obtained from the drone moving at a constant speed at a height of 150 meters. The root mean squared error (RMSE) of the estimated velocities in x and y directions and the RMSE of the speed were obtained showing the reliability of the proposed method.

• Journal of the Korea Institute of Building Construction
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• v.23 no.3
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• pp.273-284
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• 2023

This study is centered on the combined use of LiDAR(Light Detection and Ranging) and AR(Augmented Reality) technologies during vertical and horizontal frame measurements in construction projects. The intention is to enhance the quality control procedure, elevate accuracy, and curtail manual labor along with time expenditure. Present methods for accuracy inspection in frame construction often grapple with reliability concerns due to subjective interpretation and the scope for human error. This research recommends the application of LiDAR and AR technologies to counter these issues and augment the efficiency of the inspection process, along with facilitating the dissemination of results. The suggested technique involves the collection of 3D point cloud data of the frame utilizing LiDAR and leveraging this data for checks on construction accuracy. Furthermore, the inspection outcomes are fed into a BIM (Building Information Modeling) model, and the results are visualized via AR. Upon juxtaposing this methodology with the current approach, it is evident that it offers benefits in terms of objective inspection, speed, precise result sharing, and potential enhancements to the overall quality and productivity of construction projects.