• Proceedings of the Korean Geotechical Society Conference
• /
• 2006.03a
• /
• pp.189-198
• /
• 2006

This paper concerns the finite element (FE) modeling approach for NATM tunneling in water bearing ground within the framework of stress-pore pressure coupled analysis. Fundamental interaction mechanism of ground and groundwater lowering was first examined and a number of influencing factors on the results of coupled FE analysis were identified. A parametric study was then conducted on the influencing factors such as soil-water characteristics, location of hydraulic boundary conditions, the way of modeling drainage flow, among others. The results indicate that the soil-water characteristics plays the most important role in the tunneling-induced settlement characteristics. Based on the results, modeling guidelines were suggested for stress-pore prssure coupled finite element modeling of NATM tunneling.

• Asia pacific journal of information systems
• /
• v.6 no.1
• /
• pp.223-240
• /
• 1996

The paper proposes an approach, called OPNets, for modeling and validating manufacturing systems that is based on object-oriented high-level Petri nets. In OPNets, modeling components of Petri net are constructed into hierarchical objects that communicate with each other by passing messages. To enhance the reusability and maintainability, OPNets organizes a system into hierarchical objects that inherit attributes and behavioral properties from the object of super class and object-interaction relations are separated from the internal structure of object. The modeling scheme of OPNets tries to resolve the complexity problems of Petri net. To illustrate the modeling schemes of OPNets, a storage/retrieval example has been proposed.

• Journal of Electrical Engineering and Technology
• /
• v.3 no.4
• /
• pp.451-459
• /
• 2008

Accurate load modeling is essential for power system static and dynamic analysis. By the nature of the problem of parameter estimation for power system load modeling using actual measurements, multiple local optimal solutions may exist and local methods can be trapped in a local optimal solution giving possibly poor performance. In this paper, Trust-Tech, a novel methodology for global optimization, is applied to tackle the multiple local optimal solutions issue in measurement-based power system load modeling. Multiple sets of parameter values of a composite load model are obtained using Trust-Tech in a deterministic manner. Numerical studies indicate that Trust-Tech along with conventional local methods can be successfully applied to power system load model parameter estimation in measurement-based approaches.

• Journal of the Korean School Mathematics Society
• /
• v.14 no.1
• /
• pp.43-64
• /
• 2011

The purpose of this study was to analyze the progress of children's abstraction and to investigate how elementary students understand through mathematical modeling approach in the sixth grader's learning of surface area. Each small group showed their own level on abstraction in mathematical modeling progress. The participants showed improvements in understanding regarding to surface area context.

• Proceedings of the Korean Society of Precision Engineering Conference
• /
• 2002.10a
• /
• pp.954-957
• /
• 2002

The objective of design process modeling is a systematic support of rapid redesign process fur a modified input data. The design process modeling is realized by storing key parameters or geometric entities used in the intermediate design steps and reusing them for change of the designed parts or assemblies according to the modified input. In this paper, we adopted and implemented the design process modeling approach to our injection mold design system developed based on the Unigraphics system. It was proved that the productivity of mold redesign process is raised highly by introducing the design process modeling technique mold design system.

• Archives of design research
• /
• v.20 no.2 s.70
• /
• pp.53-64
• /
• 2007

Web development has multidisciplinary features involving diverse team members. Owing to the diverse backgrounds, however, there may be communication problems among web team members, especially between designers and programmers. Programmers often use a graphical modeling notation to communicate their designs. The graphical modeling concepts can also be helpful to designers, but most designers generally find graphical modeling notations hard to understand. We, therefore, propose an interactive computer-aided collaborative web design system including revised web graphical model notations to improve communication between web designers and programmers. We have designed and implemented a computational prototype to validate the approach and illustrate how the prototype works using concrete examples.

• Journal of International Society for Simulation Surgery
• /
• v.2 no.1
• /
• pp.10-12
• /
• 2015

Purpose It has been stated that patient satisfaction is the crucial factor for determining success in plastic surgery. The convergence of medical science and computer vision has made easier to satisfy patients who wants to have plastic surgery. In this paper, we try to apply 3D face modeling in plastic surgical area. Materials and Methods The author introduces a method for accurate 3D face modeling techniques using a statistical model-based 3D face modeling approach in a mirror system. Results We could successfully obtain highly accurate 3D face shape results. Conclusion The method suggested could be used for acquiring 3D face models from 2D face image and the result obtained from this could be effectively used for plastic surgical areas.

• Journal of the Korean Institute of Telematics and Electronics S
• /
• v.35S no.4
• /
• pp.58-66
• /
• 1998

In many situations, it is very important to identify a certain unkown system, it from its input-output data. For this purpose, several system modeling algorithms have been suggested heretofore, and studies regarding the fuzzy modeling based on its nonlinearity get underway as well. Generatlly, fuzzy models have the capability of dividing input space into several subspaces, compared to linear ones. But hitherto subggested fuzzy modeling algorithms do not take into consideration the correlations between components of sample input data and address them independently of each other, which results in ineffective partition of input space. Therefore, to solve this problem, this letter proposes a new fuzzy modeling algorithm which partitions the input space more efficiently that conventional methods by taking into consideration correlations between components of sample data. As a way to use correlation and divide the input space, the method of principal component is ued. Finally, the results of computer simulation are given to demonstrate the validity of this algorithm.

• Proceedings of the Korea Society for Simulation Conference
• /
• 2000.11a
• /
• pp.142-149
• /
• 2000

Most of supply chain simulation models have been developed on the basis of discrete-event simulation. Since supply chain systems are neither completely discrete nor continuous, the need of constructing a model with aspects of both discrete-event simulation and continuous is provoked, resulting in a combined discrete-continuous simulation. Continuous simulation concerns the modeling over time of a system by a representation in which the state variables change continuously with respect to time. In this paper, an architecture of combined modeling for supply chain simulation is proposed, which presents the equation of continuous part in supply chain and how these equations are used supply chain simulation models. A simple supply chain model is demonstrated the possibility and the capability of this approach.

• Journal of Intelligence and Information Systems
• /
• v.8 no.2
• /
• pp.51-69
• /
• 2002

In the supply chain environment on the web, collaborative problem solving and case-based modeling has been getting more important, because it is difficult to cope with diverse problem requirements and inefficient to manage many models as well. Hence, the approach on case-based modeling is required. This paper provides a framework that generates a goal model based on multiple cases, modeling knowledge, and forward chaining and it also develops a search algorithm through sensitivity analysis to reduce the modeling effort.