• Proceedings of the Korean Society of Precision Engineering Conference
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• 1997.04a
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• pp.589-594
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• 1997

We have already presented the constraint satisfaction algorithm which could solve the losed loop problem in constraint network by using local constraint propagation, variable elimination and constraint modularization. With this algorithm, we have implemented a knowledge-based system (intelligent CAD) for supporting machine design interactively. In this paper, we present newer constraint satisfaction algorithm which can solve inequalities or under-constrained problems in constraint network, interactively and efficiently. This algorithm is a hybrid type of using both declarative description (constraint represention) and optimization algorithm (Simulated Annealing), simultaneously. The under-constrained problems are represented by constraint networks and satisfied completely with this algorithm. The usefulness of our algorithm will be illustrated by the application to a gear design.

• Journal of Korea Society of Digital Industry and Information Management
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• v.6 no.4
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• pp.45-56
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• 2010

This paper suggests constraint data modeling based on constraint data presentation techniques to perform complex spatial database operation naturally. We were able to identify the limitation of extendibility of dimension and non-equal framework via relevant research for former schema of spatial database and query processing. Therefore we described generalized tuple of spatial data and the definition of suggested constraint data modeling. Also we selected MLPQ/PReSTO tool among constraint database prototype and compare standard functionality of ARC/VIEW. Then we design scenario for spatial operation using MLPQ/PReSTO and we suggested application effect after query processing. Based on above explanation, we were able to identify that we can process spatial data naturally and effectively using simple constraint routine on same framework via constraint data modeling.

• Journal of the Korean Society for Precision Engineering
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• v.14 no.9
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• pp.116-123
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• 1997

We have already presented the constraint satisfaction algorithm which could solve the closed loop porblem in constraint network by using local constraint propagation, variable elimination and constraint modularization. With this algorithm, we have implemented a knowledge-based system (intelligent CAD) for supporting machine design interactively. In this paper, we present newer constraint satisfaction algorithm which can solve inequalities or under-constrained problems in constraint network, interactively and effi- ciently. This algorithm is a hybrid type of using both declarative description (constraint representation) and optimization algorithm (Simulated Annealing), simultaneously. The under-constrained problems are represented by constraint networks and satisfied completely with this algorithm. The usefulness of our algorithm will be illustrated by the application to a gear design.

• International Journal of CAD/CAM
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• v.6 no.1
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• pp.173-181
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• 2006

In this paper, an integration framework of Geometric Constraint Solving Engine and AutoCAD is presented, and a dynamic geometric constraint system is introduced. According to inherent orientation features of geometric entities and various Object Snap results of AutoCAD, the' proposed system can automatically construct an under-constrained geometric constraint model during interactive drawing. And then the directed constraint graph in a geometric constraint model is realtime modified in order to produce an optimal constraint solving sequence. Due to the open object-oriented characteristics of AutoCAD, a set of user-defined entities including basic geometric elements and graphics constraint relations are defined through derivation. And the custom-made Object Reactor and Command Reactor are also constructed. Several powerful characteristics are achieved based on these user-defined entities and reactors, including synchronously processing geometric constraint information while saving and opening DWG files, visual constraint relations, and full adaptability to Undo/Redo operations. These characteristics of the proposed system can help the designers more easily manage geometric entities and constraint relations between them.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.29 no.5B
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• pp.508-519
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• 2004

This paper proposed two multi-path constraint-based routing algorithms for Internet traffic engineering using MPLS. In normal constraint-based shortest path first (CSPF) routing algorithm, there is a high probability that it cannot find the required path through networks for a large bandwidth constraint that is one of the most important constraints for traffic engineering, The proposed algorithms can divide the bandwidth constraint into two or more sub-constraints and find a constrained path for each sub-constraint, if there is no single path satisfying the whole constraint. Extensive simulations show that they enhance the success probability of path setup and the utilization of network resources.

• 제어로봇시스템학회:학술대회논문집
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• 2005.06a
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• pp.1098-1100
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• 2005

The floorplanning problem is an essential design step in VLSI layout design and it is how to place rectangular modules as density as possible. And then, as the DSM advances, the VLSI chip becomes more congested even though more metal layers are used for routing. Usually, a VLSI chip includes several buses. As design increases in complexity, bus routing becomes a heavy task. To ease bus routing and avoid unnecessary iterations in physical design, we need to consider bus planning in early floorplanning stage. In this paper, we propose a floorplanning method for topological constraint consisting of bus constraint and memory constraint. The proposed algorithms based on Genetic Algorithm(GA) is adopted a sequence pair. For selection control, new objective functions are introduced for topological constraint. Studies on floor planning and cell placement have been reported as being applications of GA to the LSI layout problem. However, no studies have ever seen the effect of applying GA in consideration of topological constraint. Experimental results show improvement of bus and memory constraint.

• Journal of the Korea Society for Simulation
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• v.18 no.2
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• pp.57-64
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• 2009

Stable and effective constraint enforcement system is one of the crucial components for physically-based dynamic simulations. This paper presents analysis and evaluation for traditional constraint enforcement systems(Lagrange Multiplier method, Baumgarte stabilization method, Post-stabilization method, Implicit constraint enforcement method, Fast projection method) to provide a guideline to users who need to integrate a suitable constraint enforcement system into their dynamic simulations. The mathematical formulations for traditional constraint enforcement systems are presented in this paper. This paper describes a summary of evaluation which consists of constraint error comparison, computational cost, and dynamic behavior analysis to verify the efficiency of each traditional constraint enforcement system.

• Journal of Mechanical Science and Technology
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• v.18 no.1
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• pp.122-131
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• 2004

A constraint equation-based control law design for large angle attitude maneuvers of flexible spacecraft is addressed in this paper The tip displacement of the flexible spacecraft model is prescribed in the form of a constraint equation. The controller design is attempted in the way that the constraint equation is satisfied throughout the maneuver. The constraint equation leads to a two-point boundary value problem which needs backward and forward solution techniques to satisfy terminal constraints. An observer-based tracking control law takes the constraint equation as the input to the dynamic observer. The observer state is used in conjunction with the state feedback control law to have the actual system follow the observer dynamics. The observer-based tracking control law eventually turns into a stabilized system with inherent nature of robustness and disturbance rejection in LQR type control laws.

• Proceedings of the Computational Structural Engineering Institute Conference
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• 2007.04a
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• pp.141-144
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• 2007

Given a number of training data, a traditional BPN is normally trained by minimizing the absolute difference between target outputs and approximate outputs. When BPN is used as a meta-model for inequality constraint function, approximate optimal solutions are sometimes actually infeasible in a case where they are active at the constraint boundary. The paper describes the development of the efficient BPN based meta-model that enhances the constraint feasibility of approximate optimal solution. The modified BPN based meta-model is obtained by including the decision condition between lower/upper bounds of a constraint and an approximate value. The proposed approach is verified through a simple mathematical function and a ten-bar planar truss problem.

• Structural Engineering and Mechanics
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• v.47 no.1
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• pp.131-147
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• 2013

In this paper, constraint-based fracture mechanics analyses of hollow cylinders with internal circumferential crack under tensile loading are conducted. Finite element analyses of the cracked cylinders are carried out to determine the fracture parameters including elastic T-stresses, and fully-plastic J-integrals. Linear elastic finite element analysis is conducted to obtain the T-stresses, and elastic-plastic analysis is conducted to obtain the fully plastic J-integrals. A wide range of cylinder geometries are studied, with cylinder radius ratios of $r_i/r_o$ = 0.2 to 0.8 and crack depth ratio a/t = 0.2 to 0.8. Fully plastic J-integrals are obtained for Ramberg-Osgood power law hardening material of n = 3, 5 and 10. These fracture parameters are then used to construct conventional and constraint-based failure assessment diagrams (FADs) to determine the maximum load carrying capacity of cracked cylinders. It is demonstrated that these tensile loaded cylinders with circumferential cracks are under low constraint conditions, and the load carrying capacity are higher when the low constraint effects are properly accounted for, using constraint-based FADs, comparing to the predictions from the conventional FADs.