• Journal of the Ergonomics Society of Korea
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• v.30 no.1
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• pp.99-108
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• 2011

Almost all companies have paid much attention to the safety management ranging from maintenance to operation even at the stage of designing in order to prevent accidents, but fatal accidents continue to increase throughout the world. In particular, it is essential to systematically prevent such fatal accidents as fire, explosion or leakage of toxic gas at factories in order to not only protect the workers and neighbors but also prevent economic losses and environmental pollution. Though it is well known that accident probability is very low in NPP(Nuclear Power Plants), the reason why many researches are still being performed about the accidents is the results may be so severe. HRA is the main process to make preparation for possibility of human error in designing of the NPP. But those techniques have some problems and limitation as follows; the evaluation sensitivity of those techniques are out of date. And the evaluation of human error is not coupled with the design process. Additionally, the scope of the human error which has to be included in reliability assessment should be expanded. This work focuses on the coincidence of human error and mechanical failure for some important performance shaping factors to propose a method for improving safety effectively of the process industries. In order to apply in these purposes into the thesis, I found 63 critical Performance Shaping Factors of the eight dimensions throughout studies that I executed earlier. In this study, various analysis of opinion of specialists(Personal Factors, Training, Knowledge or Experience, Procedures and Documentation, Information, Communications, HMI, Workplace Design, Quality of Environment, Team Factors) and the guideline for construction of PSF were accomplished. The selected method was AHP which simplifies objective conclusions by maintaining consistency. This research focused on the implementation process of PSF to evaluate the process of PSF at each phase. As a result, we propose an evaluation model of PSF as a tool to find critical problem at each phase and improve on how to resolve the problems found at each phase. This evaluation model makes it possible to extraction of PSF succesfully by presenting the basis of assessment which will be used by enterprises to minimize the trial and error of construction process of PSF.

• Journal of Ocean Engineering and Technology
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• v.36 no.4
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• pp.251-269
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• 2022

The process-based XBeach model has numerous empirical parameters because of insufficient understanding of hydrodynamics and sediment transport on the nearshore; hence, it is necessary to calibrate parameters to apply to various study areas and wave conditions. Therefore, the calibration process of parameters is essential for the improvement of model performance. Generally, the trial-and-error method is widely used; however, this method is passive and limited to various and comprehensive parameter ranges. In this study, the Generalized Likelihood Uncertainty Estimation (GLUE) method was used to estimate the optimal range of three parameters (gamma, facua, and gamma2) using morphological field data collected in Maengbang beach during the four typhoons that struck from September to October 2019. The model performance and optimal range of empirical parameters were evaluated using Brier Skill Score (BSS) along with the baseline profiles, sensitivity, and likelihood density analysis of BSS in the GLUE tools. Accordingly, the optimal parameter combinations were derived when facua was less than 0.15 and simulated well the shifting shape, from crescentic sand bar to alongshore uniform sand bars in the surf zone of Maengbang beach after storm impact. However, the erosion and accretion patterns nearby in the surf zone and shoreline remain challenges in the XBeach model.

• Journal of Powder Materials
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• v.31 no.3
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• pp.213-219
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• 2024

Additive Manufacturing (AM) is a process that fabricates products by manufacturing materials according to a three-dimensional model. It has recently gained attention due to its environmental advantages, including reduced energy consumption and high material utilization rates. However, controlling defects such as melting issues and residual stress, which can occur during metal additive manufacturing, poses a challenge. The trial-and-error verification of these defects is both time-consuming and costly. Consequently, efforts have been made to develop phenomenological models that understand the influence of process variables on defects, and mechanical/ electrical/thermal properties of geometrically complex products. This paper introduces modeling techniques that can simulate the powder additive manufacturing process. The focus is on representative metal additive manufacturing processes such as Powder Bed Fusion (PBF), Direct Energy Deposition (DED), and Binder Jetting (BJ) method. To calculate thermal-stress history and the resulting deformations, modeling techniques based on Finite Element Method (FEM) are generally utilized. For simulating the movements and packing behavior of powders during powder classification, modeling techniques based on Discrete Element Method (DEM) are employed. Additionally, to simulate sintering and microstructural changes, techniques such as Monte Carlo (MC), Molecular Dynamics (MD), and Phase Field Modeling (PFM) are predominantly used.

• Proceedings of the Korean Geotechical Society Conference
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• 2009.09a
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• pp.1441-1446
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• 2009

Numerical analysis is a powerful method in evaluating the soil-pile-structure interaction under the dynamic loading, and this approach has been applied to the practical area due to the development of computer technology. Finite Difference Method, one of the most popular numerical methods, is sensitive to the shape and the number of mesh. However, the trial and error approach is conducted to obtain the accurate results and the reasonable simulation time because of the lack of researches about mesh size and the number. In this study, FLAC 3D v3.1 program(FDM) is used to simulate the dynamic pile model tests, and the numerical results are compared with the 1G shaking table tests results. With the different size and shape of mesh, the responses of pile behavior and the simulation time are estimated, and the optimum mesh sizes in dynamic analysis of single pile is studied.

• Geomechanics and Engineering
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• v.34 no.1
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• pp.29-41
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• 2023

The 3D geospatial modeling of geotechnical information can aid in understanding the geotechnical characteristic values of the continuous subsurface at construction sites. In this study, a geostatistical optimization model for the three-dimensional (3D) mapping of subsurface stratification and the SPT-N value based on a trial-and-error rule was developed and applied to a dam emergency spillway site in South Korea. Geospatial database development for a geotechnical investigation, reconstitution of the target grid volume, and detection of outliers in the borehole dataset were implemented prior to the 3D modeling. For the site-specific subsurface stratification of the engineering geo-layer, we developed an integration method for the borehole and geophysical survey datasets based on the geostatistical optimization procedure of ordinary kriging and sequential Gaussian simulation (SGS) by comparing their cross-validation-based prediction residuals. We also developed an optimization technique based on SGS for estimating the 3D geometry of the SPT-N value. This method involves quantitatively testing the reliability of SGS and selecting the realizations with a high estimation accuracy. Boring tests were performed for validation, and the proposed method yielded more accurate prediction results and reproduced the spatial distribution of geotechnical information more effectively than the conventional geostatistical approach.

• Korean Journal of Artificial Intelligence
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• v.11 no.4
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• pp.15-20
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• 2023

Machine learning is comprised of supervised learning, unsupervised learning and reinforcement learning as the type of data and processing mechanism. In this paper, as input and output are unclear and it is difficult to apply the concrete modeling mathematically, reinforcement learning method are applied for crawling robot in this paper. Especially, Q-Learning is the most effective learning technique in model free reinforcement learning. This paper presents a method to implement a crawling robot that is operated by finding the most optimal crawling method through trial and error in a dynamic environment using a Q-learning algorithm. The goal is to perform reinforcement learning to find the optimal two motor angle for the best performance, and finally to maintain the most mature and stable motion about EV3 Crawling robot. In this paper, for the production of the crawling robot, it was produced using Lego Mindstorms with two motors, an ultrasonic sensor, a brick and switches, and EV3 Classroom SW are used for this implementation. By repeating 3 times learning, total 60 data are acquired, and two motor angles vs. crawling distance graph are plotted for the more understanding. Applying the Q-learning reinforcement learning algorithm, it was confirmed that the crawling robot found the optimal motor angle and operated with trained learning, and learn to know the direction for the future research.

• 제어로봇시스템학회:학술대회논문집
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• 2003.10a
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• pp.433-437
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• 2003

Quantitative Feedback Theory (QFT) is one of effective methods of robust controller design. In QFT design we can considers the phase information of the perturbed plant so it is less conservative than $H_{\infty}$ and ${\mu}$-synthesis methods and as be shown, it is more transparent than the sensitivity reduction methods mentioned . In this paper we want to overcome the major drawback of QFT method which is lack of an automatic method for loop-shaping step of the method so we focus on the following problem: Given a nominal plant and QFT bounds, synthesize a controller that achieves closed-loop stability and satisfies the QFT boundaries. The usual approach to this problem involves loop-shaping in the frequency domain by manipulating the poles and zeros of the nominal loop transfer function. This process now aided by recently developed computer aided design tools proceeds by trial and error and its success often depends heavily on the experience of the loop-shaper. Thus for the novice and First time QFT user, there is a genuine need for an automatic loop-shaping tool to generate a first-cut solution. Clearly such an automatic process must involve some sort of optimization, and while recent results on convex optimization have found fruitful applications in other areas of control theory we have tried to use LMI theory for automating the loop-shaping step of QFT design.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.21 no.10
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• pp.1656-1665
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• 1997

The intake noise, a major source of vehicle noises, has rapidly become a noticeable, and has been studied to reduce the level. Traditionally, the intake system has been developed through a experiment, namely, the trial and error process. This approach requires very high cost and long time consuming to develop the systm. Recently, FEM and BEM are becoming useful in analysis of the intake system, and the results of analysis are very valid. But because this techniques also require high cost and long analysis time, this technique is generally not practical tool at the early stage of the development. In this study, the software was developed to predict and analyze the acoustic characteristics of the intake system. It was based on the Transfer Matrix Method and operated to analyze a simplified intake system in a personal computer. It can be used early in the design stage of development of the intake system. This study presented a improvement to reduce the level of the intake noise, which modified the specification of the intake system. And the improvement were verified by NIT/SYSNOISE, FE analysis commercial software, and testing a prototype.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.21 no.10
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• pp.1648-1655
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• 1997

The intake noise, a major source of vehicle noises, has rapidly become a noticeable, and has been studied to reduce the level. Traditionally, the intake system has been developed through a experiment, namely, the trial and error process. This approach requires very high cost and long time consuming to develop the system. Recently, FEM and BEM are becoming useful in analysis of the intake system, and te results of analysis are very valid. But because these techniques also require high cost and long analysis time, these are generally not practical tool at the early stage of the development of an intake system. In this study, the software was developed to predict and analyze the acoustic characteristics of an intake system. It was based on the Transfer Matrix Method and operated to analyze a simplified intake system in a personal computer. It can be used early in the design stage of development of the intake system. This study presented an improvement to reduce the level of an intake noise. It was to select the optimum position of a resonator and verified by NIT/SYSNOISE, FE analysis commercial software, and testing a prototype.

• Journal of Welding and Joining
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• v.21 no.2
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• pp.76-81
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• 2003

Due to the environmental problem, automotive companies are trying to reduce the weight of car body. Therefore, WP(Transformation Induced Plasticity) steels, which are hish strength and ductility have been developed. The application of TRIP steel to the members has been reported to increase the energy absorption capability. Welding process is a complex process; therefore deciding the optimal welding conditions is an effective method on the basis of the experimental data. However, using a trial-and-error method from the beginning in such a wide area, in order to decide the optimal conditions requires too many numbers of experiments. To overcome these problems and to decide the optimal conditions, response surface methodology was used. Response surface methodology is a collection of mathematical and statistical techniques that are for the modeling and analysis of problems in which a response of interest is influenced by several variables and the objective is to optimize this response. The introduced method was applied to the resistance spot welding process of the TRIP steel and the welding parameters were optimized. (Received December 6, 2002)