• 한국전산유체공학회:학술대회논문집
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• 2000.05a
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• pp.66-72
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• 2000

Aerodynamic sensitivity analysis is performed for the Navier-Stokes equations coupled with two-equation turbulence models using a discrete adjoint method and a direct differentiation method respectively. Like the mean flow equations, the turbulence model equations are also hand-differentiated to accurately calculate the sensitivity derivatives of flow quantities with respect to design variables in turbulent viscous flows. Both the direct differentiation code and the adjoint variable code adopt the same time integration scheme with the flow solver to efficiently solve the differentiated equations. The sensitivity codes are then compared with the flow solver in terms of solution accuracy, computing time and computer memory requirements. The sensitivity derivatives obtained from the sensitivity codes with different turbulence models are compared with each other. Using two-equation turbulence models, it is observed that a usual assumption of constant turbulent eddy viscosity in adjoint methods may lead to seriously inaccurate results in highly turbulent flows.

• International Journal of Automotive Technology
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• v.7 no.5
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• pp.595-601
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• 2006

Two No Spin Differential(NSD) models were benchmarked for a project of Dual-Use Technology. The Axiomatic approach is utilized to evaluate the designs of the models. The Independence Axiom is satisfied at the top level of design but not at the second level, which implies the design exhibits coupling and will admit design improvements. The detailed process of design evaluation is described. It is shown that it is possible to develop a unique and evolutionary NSD design by solving the problems that cause coupling within two models.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 1997.10a
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• pp.115-120
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• 1997

System identification is the task of inferring a mathematical description of a dynamic system from a series of measurements of the system. There are several motives for establishing mathematical descriptions of dynamic systems. Typical applications encompass simulation, prediction, fault diagnostics, and control system design. The paper demonstrates that neural networks can be used effective for the identification of nonlinear dynamical systems. The content of this paper concerns dynamic neural network models, where not all inputs to and outputs from the networks are measurable. Only one model type is treated, the well-known Innovation State Space model(Kalman Predictor). The identification is based only on input/output measurements, so in fact a non-linear Extended Kalman Filter problem is solved. Even for linear models this is a non-linear problem without any assurance of convergence, and in spite of this fact an attempt is made to apply the principles from linear models, an extend them to non-linear models. Computer simulation results reveal that the identification scheme suggested are practically feasible.

• The Korean Journal of Ceramics
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• v.6 no.1
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• pp.1-5
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• 2000

Particle packing properties are important to develop high technology products in the field of cement and concrete. Two types of particle packing models for aggregates with sand and cement were introduced: the loose and the dense aggregate packing. Aggregate packing models with randomly generated sand and cement particles in the interstices of aggregates fit the Furnas model very well. Different aggregate models show different packing properties with the experimental results. Main reason for the difference with the experimental results is due to sand rearrangement in the loose aggregate packing model and to aggregate relaxation in the dense aggregate packing model. In the experimental situation, aggregates seem to be more disordered and have a relaxed packing structure in the dense packing, and sands seem to have a more rearranged packing structure in the loose packing model.

• Transactions of the Korean Society of Machine Tool Engineers
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• v.11 no.1
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• pp.1-9
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• 2002

Reverse engineering is an emerging technology to obtain CAD models from existing physical parts in the case that CAD models are not available or paras are changed an(1 modified so that new CAD models for final parts are necessary. Reverse engineering helps designers to quickly generate computer interpretable data from existing Physical objects So it is applying for field of Rapid Prototyping NC Processing CAE, Inspection and so on. The objective of this study is to develop the software that deals with unorganized point data and quickly obtains CAD model. In this paper, several models such as human\`s bone, car, are experimented by the proposed methods.

• Journal of Environmental Impact Assessment
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• v.5 no.1
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• pp.95-105
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• 1996

Meteorological Joint Frequency Function required indispensably in long-term air quality prediction models were discussed for practical application in Korea. The algorithm, proposed by Turner(l964), is processed with daily solar insolation and cloudiness and height basically using Pasquill's atmospheric stability classification method. In spite of its necessity and applicability, the computer program, called STAR(STability ARray), had some significant difficulties caused from the difference in meteorological data format between that of original U.S. version and Korean's. To cope with the problems, revised STAR program for Korean users were composed of followings; applicability in any site of Korea with regard to local solar angle modification; feasibility with both of data which observed by two classes of weather service centers; and examination on output format associated with prediction models which should be used.

• Journal of Institute of Control, Robotics and Systems
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• v.8 no.3
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• pp.233-242
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• 2002

A kinematic modeling method is proposed which models the sliding and skidding at the wheels as pseudo joints and utilizes those pseudo joint variables as augmented variables. Kinematic models of various type of wheels are derived based on this modeling method. Then, the transfer method of augmented generalized coordinates is applied to obtain inverse and forward kinematic models of mobile robots. The kinematic models of five different types of planar mobile robots are derided to show the effectiveness of the proposed modeling method.

• IE interfaces
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• v.11 no.1
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• pp.75-84
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• 1998

The important issue for intra-city vehicle scheduling is to measure and store actual vehicle travel speeds between customer locations. Travel speeds(and times) in nearly all metropolitan areas change drastically during the day because of congestion in certain parts of the city road network. We propose three models for estimating departure time-dependent travel speeds between locations that relieve much burden for the data collection and computer storage requirements. Two of the three models use a least squares method and the rest one employs a neural network trained with the back-propagation rule. On a real-world study using the travel speed data collected in Seoul, we found out that the neural network model is more accurate than the other two models.

• Journal of the military operations research society of Korea
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• v.22 no.1
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• pp.30-42
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• 1996

This study deals with an optimal firecar location and allocation models under uncertain enemy attack at the airforce base. It allocates just one firecar on the runaway and the other firecars on the headquarter of firecar company in usual situation. It is possible for several facilities at the airforce base to be attacked simultaneously by missiles enemy air attacker, other things under uncertain enemy attack. We formulate two stochastic LP location-allocation models to deal with uncertainty. One model is to locate all firecars on one site like present situation. We generate a new firecar location with a weighted average method. We call this model "centralized allocation model". The other model is to distribute firecars on several possible sites. We call this model "distributed allcoation model". Finally, we compare two models with computer experimentations on 8 airforce bases.on 8 airforce bases.

• Korean Journal of Computational Design and Engineering
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• v.14 no.1
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• pp.33-41
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• 2009

Triangular mesh models are widely used in reverse engineering, computer graphics, rapid prototyping and NC(numerical controller) tool-path generation. Triangular mesh models are generated from point clouds, surface models and solid models. A halfedge-based triangular mesh data structure is proposed and the development considerations are presented. In the presented data structure, halfedge is the key data structure. Halfedge stores its triangle index and the order in the triangle. Triangles do not store the halfedge lists explicitly. Halfedge is referred by value and defined when it is required. Proposed data structure supports four design requirements: efficient rendering, compact memory, supporting efficient algorithms and easy programming.