• Wind and Structures
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• v.13 no.6
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• pp.519-528
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• 2010

A meteorological model, RAMS, and a commercial computational fluid dynamics (CFD) model, FLUENT are combined as a one-way off-line nested modeling system, namely, RAMS/FLUENT system. The system is experimentally applied in the wind simulation over a complex terrain, with which numerical simulations of wind field over Foyeding weather station located in the northwest mountainous area of Beijing metropolis are performed. The results show that the method of combining a meteorological model and a CFD model as a modeling system is reasonable. In RAMS/FLUENT system, more realistic boundary conditions are provided for FLUENT rather than idealized vertical wind profiles, and the finite volume method (FVM) of FLUENT ensures the capability of the modeling system on describing complex terrain in the simulation. Thus, RAMS/FLUENT can provide fine-scale realistic wind data over complex terrains.

• Proceedings of the Korean Society of Computational and Applied Mathematics Conference
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• 2003.09a
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• pp.1-1
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• 2003

In this talk, a reduced-order modeling methodology based on centroidal Voronoi tessellations (CVT's)is introduced. CVT's are special Voronoi tessellations for which the generators of the Voronoi diagram are also the centers of mass (means) of the corresponding Voronoi cells. The discrete data sets, CVT's are closely related to the h-means clustering techniques. Even with the use of good mesh generators, discretization schemes, and solution algorithms, the computational simulation of complex, turbulent, or chaotic systems still remains a formidable endeavor. For example, typical finite element codes may require many thousands of degrees of freedom for the accurate simulation of fluid flows. The situation is even worse for optimization problems for which multiple solutions of the complex state system are usually required or in feedback control problems for which real-time solutions of the complex state system are needed. There hava been many studies devoted to the development, testing, and use of reduced-order models for complex systems such as unsteady fluid flows. The types of reduced-ordered models that we study are those attempt to determine accurate approximate solutions of a complex system using very few degrees of freedom. To do so, such models have to use basis functions that are in some way intimately connected to the problem being approximated. Once a very low-dimensional reduced basis has been determined, one can employ it to solve the complex system by applying, e.g., a Galerkin method. In general, reduced bases are globally supported so that the discrete systems are dense; however, if the reduced basis is of very low dimension, one does not care about the lack of sparsity in the discrete system. A discussion of reduced-ordering modeling for complex systems such as fluid flows is given to provide a context for the application of reduced-order bases. Then, detailed descriptions of CVT-based reduced-order bases and how they can be constructed of complex systems are given. Subsequently, some concrete incompressible flow examples are used to illustrate the construction and use of CVT-based reduced-order bases. The CVT-based reduced-order modeling methodology is shown to be effective for these examples and is also shown to be inexpensive to apply compared to other reduced-order methods.

• Journal of the Korean Institute of Intelligent Systems
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• v.10 no.6
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• pp.616-628
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• 2000

In this paper, we present the modeling of the ozone prediction system using Neuro-Fuzzy approaches. The mechanism of ozone concentration is highly complex, nonlinear, and nonstationary, the modeling of ozone prediction system has many problems and the results of prediction is not a good performance so far. The Dynamic Polynomial Neural Network(DPNN) which employs a typical algorithm of GMDH(Group Method of Data Handling) is a useful method for data analysis, identification of nonlinear complex system, and prediction of a dynamical system. The structure of the final model is compact and the computation speed to produce an output is faster than other modeling methods. In addition to DPNN, this paper also includes a Fuzzy Logic Method for modeling of ozone prediction system. The results of each modeling method and the performance of ozone prediction are presented. The proposed method shows that the prediction to the ozone concentration based upon Neuro-Fuzzy approaches gives us a good performance for ozone prediction in high and low ozone concentration with the ability of superior data approximation and self organization.

• Journal of Korean Institute of Industrial Engineers
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• v.33 no.3
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• pp.364-372
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• 2007

The cost modeling of the LCD manufacturing system with the repair and the rework process is hard to achieve because of it's complex manufacturing process. The technical cost modeling divides each process separately and hierarchically, so it is very useful to calculate the total manufacturing cost of the complex manufacturing system. We applied the method to the complex LCD manufacturing system to obtain more accurate cost model. Yields are the most important control parameters in manufacturing. In this paper, we propose a yield based cost model for the LCD manufacturing system and reveal the relationship between manufacturing yield and cost. Through the model, we can estimate the manufacturing cost on the basis of yields that are control indicators of manufacturing. Some simulations are performed to observe the effects of the yield to the cost, and the results are coincide with the real situation. With the proposed model, we expect to develop some optimization problems for enlarging productivity in the LCD industry.

• 제어로봇시스템학회:학술대회논문집
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• 1994.10a
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• pp.243-246
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• 1994

In this paper, a self-learning fuzzy controller is designed with a fuzzy approximation of an inverse model. The aim of an identification is to find an input command which is control of a system output. It is intuitional and easy to use a classical adaptive inverse modeling method for the identification, but it is difficult and complex to implement it. This problem can be solved with a fuzzy approximation of an inverse modeling. The fuzzy logic effectively represents the complex phenomena of the real world. Also fuzzy system could be represented by the neural network that is useful for a learning structure. The rule of a fuzzy inverse model is modified by the gradient descent method. The goal is to be obtained that makes the design of fuzzy controller less complex, and then this self-learning fuzz controller can be used for nonlinear dynamic system. We have applied this scheme to a nonlinear Ball and Beam system.

• Korean Journal of Computational Design and Engineering
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• v.13 no.3
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• pp.187-199
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• 2008

This paper describes a C++ class hierarchy of implicit objects for geometry modeling and processing. This class structure provides a software kernel for integrating many various models and methods found in current implicit modeling areas. The software kernel includes primitive objects playing a role of unit element in creating a complex shape, and operator objects used to construct more complex shape of implicit object formed with the primitive objects and other operators. In this paper, class descriptions of these objects are provided to better understand the details of the algorithm or implementation, and its instance examples to show the capabilities of the object classes for constructive shape geometry. In addition, solid modeling system shown as an application example demonstrates that the proposed implicit object classes allow us to carry out modern solid modeling techniques, which means they have the capabilities to extend to various applications.

• The Transactions of the Korean Institute of Electrical Engineers A
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• v.53 no.5
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• pp.257-265
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• 2004

The complex documentation involved in power system analysis software require a well-defined and friendly database system. We have developed an object-oriented database management system for power system analysis, and have described load flow analysis and transient stability analysis using object-oriented database(OODB). Database management systems are widely used and achieve high reliability of data management in the engineering fields. However relational database system have shortcomings in application to power system analysis. ill relational database, the data model is too simple for modeling complex data and database languages are very different from programming languages. Object-oriented techniques are sufficiently powerful to support data-modeling requirements of GUI applications. The GUI is implemented using C++ on a MS windows platform. The OODB supports data modeling requirements of GUI applications and the performance is well acceptable for Gill applications.

• Proceedings of the Korean Institute of Building Construction Conference
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• 2009.11a
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• pp.253-256
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• 2009

To the success of the megaproject including various and complex facilities, it is needed to establish a database system. Developments in data collection, storage and extracting technology have enabled iPMIS to manage various and complex information about cost and time. Especially, when we consider that both the go and no go decision in feasibility, Cost is an important and clear criteria in megaproject. Thus, Cost data modeling is the basis of the system and is necessary process. This research is focus on the structure and definition about CBS data which is collected from sites. We used four tools which are Function Analysis in VE, Casual loop Diagram in System Dynamics, Decision Tree in Data-mining, and Normalization in SQL to identify its cause and effect relationship on CBS data. Cost data modeling provide iPMIS with helpful guideline.

• Journal of Power System Engineering
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• v.14 no.3
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• pp.52-57
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• 2010

Interlaminar stresses near the free edges of composite laminates have been analyzed considering wall effects. Interface modeling of bonding layer was introduced to explain the wall effect. Using Lekhnitskii stress functions and the principle of complementary virtual work, the interlaminar stresses were obtained, which satisfied the traction free boundary conditions not only at the free edges, but also at the top and bottom surfaces of laminates. The interface modeling provides not singular stresses but concentrated finite interlaminar stresses. The significant amount of reductions of stresses at the free edge are observed compared to the results without interface modeling. The real stress state can be predicted accurately and the results demonstrate the usefulness of the proposed interface modeling for the strength design of composite laminates.

• Journal of Korean Institute of Industrial Engineers
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• v.37 no.2
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• pp.96-104
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• 2011

Modeling and simulation of human-involved complex systems pose challenges to representing human decision makings into logical systems because of the nondeterministic and dynamic nature of human behaviors. In modeling perspectives, human's activities in systems can increase uncertainty and complexity, because he or she can potentially access all other resources within the system and change the system states. To address all of these human involvements in the system, this research suggests applying the Finite State Automata (FSA)-based formal modeling of human-involved systems that incorporates the ecological concept of affordances to an evacuation simulation, so that human behavioral patterns under urgent and dynamic emergency situations can be considered in the real-time simulation. The proposed simulation methodologies were interpreted using the warehouse fire evacuation simulation to clarify the applicability of the proposed methodology. This research is expected to merge system engineering technologies and human factors, and come out to the new predictive modeling methodology for disaster simulations. This research can be applied to a variety of applications such as building layout designs and building access control systems for emergency situations.