• International Journal of Automotive Technology
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• v.7 no.1
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• pp.109-114
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• 2006

Half-beads of multi-layer-steel cylinder head gaskets take charge of sealing of lubrication oil and coolant between the cylinder head and the block. Since the head lifts off periodically due to the combustion gas pressure, both the dynamic sealing performance and the fatigue durability are essential for the gasket. A finite element model of the halfbead has been developed and verified with experimental data. The half-bead forming process was included in the model to consider the residual stress effects. The model is employed to assess the dependence of the sealing performance and the fatigue durability on the design parameters of half-bead such as the width and height of bead and the flat region length. The assessment results show that the sealing performance can be enhanced without significant deterioration of the fatigue durability in a certain range of the half-bead width. In the other cases the improvement of sealing performance is accompanied by the loss of the fatigue durability. Among three parameters, the bead width has the strongest influence.

• Journal of the Korean Society for Precision Engineering
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• v.17 no.1
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• pp.120-128
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• 2000

One of the major limitations of productivity and quality in metal cutting is the machining accuracy of machine tools. The machining accuracy is affected by geometric errors, thermally-induced errors, and the deterioration of the machine tools. Geometric and thermal errors of machine tools should be measured and compensated to manufacture high quality products. In metal cutting, the machining accuracy is more affected by thermal errors than by geometric errors. This paper models of the thermal errors for error analysis and develops on-the-machine measurement system by which the volumetric error are measured and compensated. The thermal error is modeled by means of angularity errors of a column and thermal drift error of the spindle unit which are measured by the touch probe unit with a star type styluses and a designed spherical ball artifact (SBA). Experiments, performed with the developed measurement system, show that the system provides a high measuring accuracy, with repeatability of $\pm$2${\mu}{\textrm}{m}$ in X, Y and Z directions. It is believed that the developed measurement system can be also applied to the machine tools with CNC controller. In addition, machining accuracy and product quality can be improved by using the developed measurement system when the spherical ball artifact is mounted on the modular fixture.

• Journal of the Korean Dietetic Association
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• v.25 no.1
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• pp.44-58
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• 2019

Predicting the number of meals in a foodservice organization is an important decision-making process that is essential for successful food production, such as reducing the amount of residue, preventing menu quality deterioration, and preventing rising costs. Compared to other demand forecasts, the menu of dietary personnel includes diverse menus, and various dietary supplements include a range of side dishes. In addition to the menus, diverse subjects for prediction are very difficult problems. Therefore, the purpose of this study was to establish a method for predicting the number of meals including predictive modeling and considering various factors in addition to menus which are actually used in the field. For this purpose, 63 variables in eight categories such as the daily available number of people for the meals, the number of people in the time series, daily menu details, weekdays or seasons, days before or after holidays, weather and temperature, holidays or year-end, and events were identified as decision variables. An ensemble model using six prediction models was then constructed to predict the number of meals. As a result, the prediction error rate was reduced from 10%~11% to approximately 6~7%, which was expected to reduce the residual amount by approximately 40%.

• Proceedings of the Korea Water Resources Association Conference
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• 2023.05a
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• pp.139-139
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• 2023

산사태는 사면에서 발생하는 대표적인 토사재해이다. 그리고 산사태가 발생하여 사면이 붕괴하였을 때 동반되어 나타나는 토석류는 지형 변화의 중요한 원인으로 간주한다. 산사태와 토석류가 도시나 농촌 등 인구가 밀집된 지역에서 발생할 경우 직접적인 인명 피해와 재산 피해를 발생시키며, 댐이나 저수지가 위치한 유역에서 발생할 경우 댐/저수지에 토사가 유입되어 유효저수량을 감소시킴으로써 시설물의 기능을 저하할 수 있다. 댐/저수지의 지속적인 운영과 관리하고 이러한 피해를 최소화하기 위해서는 수치 모형을 활용하여 현상을 이해하고, 분석하는 것이 필수적이다. 하지만 한국은 국토 70%의 산지에 약 18,000개의 댐과 저수지가 설치되어 있으나, 댐과 저수지 유역에서 발생하는 산사태와 토석류에 대한 연구는 미흡한 실정이다. 이에 본 연구는 댐이나 저수지 유역에서 발생하는 산사태-토석류로 인해 해당 시설물에 발생하는 피해를 집중적으로 분석하고자 수치모형을 활용하였다. 또한 산지에서 발생하는 토사재해의 특성을 반영하고자 식생을 고려하기 위한 분포 시나리오를 구축하여 사면 안정성 및 토석류 유동에 있어서 식생의 영향을 파악하였습니다.

• Journal of Soil and Groundwater Environment
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• v.28 no.3
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• pp.1-11
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• 2023

Permeable reactive barrier (PRB) is a prominent in-situ remedial option for cleanup of contaminated groundwater and has been gaining increasing popularity in recent years. Funnel-and-gate systems, comprised of two side wings of impermeable walls and a central gate wall, are frequently implemented in many sites, but often suffers from bypassing of groundwater due to the progressive clogging of the gate wall over extended period of time. This study investigated technical feasibility of a hybrid funnel-and-gate system designed to address the flow deterioration in the gate wall. The key attribute of the proposed hybrid system is the operation of drainage units at the barrier walls and rear end of the gate wall. A conceptual modeling with MODFLOW indicated the groundwater inside the barrier was maintained at appropriate level to be guided toward the gate wall, yielding constant discharging of groundwater from the gate.

• Journal of Korean Association for Spatial Structures
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• v.23 no.4
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• pp.81-88
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• 2023

Numerous factors contribute to the deterioration of reinforced concrete structures. Elevated temperatures significantly alter the composition of the concrete ingredients, consequently diminishing the concrete's strength properties. With the escalation of global CO2 levels, the carbonation of concrete structures has emerged as a critical challenge, substantially affecting concrete durability research. Assessing and predicting concrete degradation due to thermal effects and carbonation are crucial yet intricate tasks. To address this, multiple prediction models for concrete carbonation and compressive strength under thermal impact have been developed. This study employs seven machine learning algorithms-specifically, multiple linear regression, decision trees, random forest, support vector machines, k-nearest neighbors, artificial neural networks, and extreme gradient boosting algorithms-to formulate predictive models for concrete carbonation and thermal impact. Two distinct datasets, derived from reported experimental studies, were utilized for training these predictive models. Performance evaluation relied on metrics like root mean square error, mean square error, mean absolute error, and coefficient of determination. The optimization of hyperparameters was achieved through k-fold cross-validation and grid search techniques. The analytical outcomes demonstrate that neural networks and extreme gradient boosting algorithms outshine the remaining five machine learning approaches, showcasing outstanding predictive performance for concrete carbonation and thermal effect modeling.

• Journal of the Korea Safety Management & Science
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• v.26 no.3
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• pp.101-106
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• 2024

The health and working conditions of employees have become increasingly important issues in modern society. In recent years, there has been a continuous rise in problems related to the deterioration of workers' alth, which seriously affects their safety and overall quality of life. Although existing research has investigated various factors affecting workers' health and working conditions, there is still a lack of studies that scientifically analyze and identify key variables from the vast number of factors. This study employs the Lasso (Least Absolute Shrinkage and Selection Operator) technique to mathematically analyze the key variables influencing workers' health status and satisfaction with their working environment. Lasso is a technique used in machine learning to identify a small number of variables that impact the dependent variable among a large set of variables, thereby reducing model complexity and improving predictive accuracy. The results of the study can be utilized in efficiently improving workers' health and working environments by focusing on a smaller set of impactful variables.

• Journal of Intelligence and Information Systems
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• v.21 no.1
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• pp.99-118
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• 2015

Object-oriented programming languages have been widely selected for developing modern information systems. The use of concepts relating to object-oriented (OO, in short) programming has reduced efforts of reusing pre-existing codes, and the OO concepts have been proved to be a useful in interpreting system requirements. In line with this, we have witnessed that a modern conceptual modeling approach supports features of object-oriented programming. Unified Modeling Language or UML becomes one of de-facto standards for information system designers since the language provides a set of visual diagrams, comprehensive frameworks and flexible expressions. In a modeling process, UML users need to consider relationships between classes. Based on an explicit and clear representation of classes, the conceptual model from UML garners necessarily attributes and methods for guiding software engineers. Especially, identifying an association between a class of part and a class of whole is included in the standard grammar of UML. The representation of part-whole relationship is natural in a real world domain since many physical objects are perceived as part-whole relationship. In addition, even abstract concepts such as roles are easily identified by part-whole perception. It seems that a representation of part-whole in UML is reasonable and useful. However, it should be admitted that the use of UML is limited due to the lack of practical guidelines on how to identify a part-whole relationship and how to classify it into an aggregate- or a composite-association. Research efforts on developing the procedure knowledge is meaningful and timely in that misleading perception to part-whole relationship is hard to be filtered out in an initial conceptual modeling thus resulting in deterioration of system usability. The current method on identifying and classifying part-whole relationships is mainly counting on linguistic expression. This simple approach is rooted in the idea that a phrase of representing has-a constructs a par-whole perception between objects. If the relationship is strong, the association is classified as a composite association of part-whole relationship. In other cases, the relationship is an aggregate association. Admittedly, linguistic expressions contain clues for part-whole relationships; therefore, the approach is reasonable and cost-effective in general. Nevertheless, it does not cover concerns on accuracy and theoretical legitimacy. Research efforts on developing guidelines for part-whole identification and classification has not been accumulated sufficient achievements to solve this issue. The purpose of this study is to provide step-by-step guidelines for identifying and classifying part-whole relationships in the context of UML use. Based on the theoretical work on Meta-model Formalization, self-check forms that help conceptual modelers work on part-whole classes are developed. To evaluate the performance of suggested idea, an experiment approach was adopted. The findings show that UML users obtain better results with the guidelines based on Meta-model Formalization compared to a natural language classification scheme conventionally recommended by UML theorists. This study contributed to the stream of research effort about part-whole relationships by extending applicability of Meta-model Formalization. Compared to traditional approaches that target to establish criterion for evaluating a result of conceptual modeling, this study expands the scope to a process of modeling. Traditional theories on evaluation of part-whole relationship in the context of conceptual modeling aim to rule out incomplete or wrong representations. It is posed that qualification is still important; but, the lack of consideration on providing a practical alternative may reduce appropriateness of posterior inspection for modelers who want to reduce errors or misperceptions about part-whole identification and classification. The findings of this study can be further developed by introducing more comprehensive variables and real-world settings. In addition, it is highly recommended to replicate and extend the suggested idea of utilizing Meta-model formalization by creating different alternative forms of guidelines including plugins for integrated development environments.

• Journal of the Korea Society for Simulation
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• v.29 no.1
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• pp.71-79
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• 2020

As the urbanization trend in modern society continues, the concentration of the population induces the urban problems in the residential area. One of the well-known issues among various urban problems is the garbage problem, which causes deterioration of the residential environment of citizens and directly affects the satisfaction of municipal administration. Such garbage problem cannot be accurately predicted by analyzing the amount of waste emitted from residential areas, but it is necessary to analyze the lifestyle and characteristics of residents living in residential areas. In this study, we propose an agent-based residential modeling and simulation environment using discrete event system formalism to analyze the garbage problem and satisfaction level according to the distribution of residents in the residential area. To model the behavior of the residents, we utilized the Atomic Model to capture the temporal behavior. Also, we used the Coupled Model to model the multi-family and the building to enhance the reusability of the simulation model. Also, this study carried out simulation modeling and simulation for a multi-family residential area. The simulation results of the multi-family housing area show that considering the characteristics of the residents gives better results compared to the simulation results without considering the characteristics.

• Journal of the Korean GEO-environmental Society
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• v.22 no.12
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• pp.33-40
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• 2021

The deterioration of underground facilities, disturbance of the ground due to underground development activities, and changes in ground water can cause ground subsidence accidents in the urban areas. The investigation on the geotechnical and hydraulic factors affecting the ground subsidence accident is very significant to predict the ground subsidence risk in advance. In this study, an analysis DB was constructed through 3D ground modeling to utilize the currently operating geotechnical survey information DB and ground water behavior information for risk prediction. Additionally, using these results, the relationship between the actual ground subsidence occurrence history and ground conditions and ground water level changes was confirmed. Furthermore, the methodology used to visualize the risk of ground subsidence was presented by reconstructing the engineering characteristics of the soil presented according to the Unified Soil Classification System (USCS) in the existing geotechnical survey information into the internal erosion sensitivity of the soil, Based on the result, it was confirmed that the ground in the area where the ground subsidence occurred consists of more than 40% of sand (SM, SC, SP, SW) vulnerable to internal erosion. In addition, the effect of the occurrence frequency of ground subsidence due to the change in ground water level is also confirmed.