• Korean Journal of Computational Design and Engineering
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• v.11 no.1
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• pp.27-40
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• 2006

The exchange of parameterized feature-based CAD models is important for product data sharing among different organizations and automation systems. The role of feature-based modeling is to gonerate the shape of product and capture design intends In a CAD system. A feature is generated by referring to topological entities in a solid. Identifying referenced topological entities of a feature is essential for exchanging feature-based CAD models through a neutral format. If the CAD data contains the modification history in addition to the construction history, a matching mechanism is also required to find the same entity in the new model (post-edit model) corresponding to the entity in the old model (preedit model). This problem is known as the persistent naming problem. There are additional problems arising from the exchange of parameterized feature-based CAD models. Authors have analyzed previous studies with regard to persistent naming and characteristics for the exchange of parameterized feature-based CAD models, and propose a solution to the persistent naming problem. This solution is comprised of two parts: (a) naming of topological entities based on the object spore information (OSI) and secondary name (SN); and (b) name matching under the proposed naming.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2007.04a
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• pp.305-308
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• 2007

In this paper we suggest an efficient evolutionary approach based on topological sort techniques for precedence constrained TSPs. The determination of optimal sequence has much to offer to downstream project management and opens up new opportunities for supply chains and logistics. Experimental results show that the suggested approach is a good alternative to locate optimal solution for complicated precedence constrained sequencing as in optimization method for instance.

• Bulletin of the Korean Mathematical Society
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• v.55 no.3
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• pp.851-863
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• 2018

We derive lower bounds of the scalar curvature on complete non-compact gradient Yamabe solitons under some integral curvature conditions. Based on this, we prove that potential functions of Yamabe solitons have at most quadratic growth for distance function. We also obtain a finite topological type property on complete shrinking gradient Yamabe solitons under suitable scalar curvature assumptions.

• Honam Mathematical Journal
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• v.43 no.3
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• pp.561-570
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• 2021

In this paper, applying the bifurcation method and topological analysis, we investigate the global structures of solutions for one-dimensional Minkowski-curvature problems under certain behavior of nonlinear term near zero.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.34 no.1
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• pp.33-41
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• 2011

This paper considers a topological optimization of a network design with mean packet delay and node connectivity constraints. The objective is to find the topological layout of links, at minimal cost. This Problem is known to be NP-hard. To efficiently solve the problem, a scatter search algorithm is proposed. An illustrative example is used to explain and test the proposal approach. Experimental results show evidence that the proposal approach performs more efficiently for finding a good solution or near optimal solution in comparison with a genetic approach.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.31 no.1
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• pp.101-107
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• 2008

This paper considers a topological optimization of a computer network design with a reliability constraint. The objective is to find the topological layout of links, at minimal cost, under the constraint that the network reliability is more than a given reliability. To efficiently solve the problem, a scatter search approach is proposed. Two illustrative examples are used to explain and test the proposed approach. Experimental results show evidence that the proposed approach performs more efficiently for finding a good solution or near optimal solution in comparison with a genetic algorithm approach.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.30 no.1
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• pp.82-88
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• 2007

This paper considers a topological optimization of a computer network design with a cost constraint. The objective is to find the topological layout of links, at maximal reliability, under the constraint that the network cost is less or equal than a given level of budget. This problem is known to be NP-hard. To efficiently solve the problem, a genetic approach is proposed. Two illustrative examples are used to explain and test the proposed approach. Experimental results show evidence that the proposed approach performs more efficiently for finding a good solution or near optimal solution in comparison with a simulated annealing method.

• International Journal of CAD/CAM
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• v.5 no.1
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• pp.69-81
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• 2005

As collaborative design and configuration design gain increasing importance in product development, it becomes essential to exchange parametric CAD models among participants. Parametric CAD models can be represented and exchanged in the form of a macro file or a part file that contains the modeling history of a product. The modeling history of a parametric CAD model contains feature specifications and each feature has selection information that records the name of the referenced topological entities. Translating this selection information requires solving the problems of how to identify the referenced topological entities of a feature (persistent naming problem) and how to convert the selection information into the format of the receiving CAD system (naming mapping problem). The present paper introduces the problem of exchanging parametric CAD models and proposes a solution to naming mapping.

• Structural Engineering and Mechanics
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• v.37 no.5
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• pp.475-487
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• 2011

In a flexible multi-body dynamic system the typical topological optimization method for structures cannot be directly applied, as the stiffness varies with position. In this paper, the topological optimization of the flexible multi-body dynamic system is converted into structural optimization using the equivalent static load method. First, the actual boundary conditions of the control system and the approximate stiffness curve of the mechanism are obtained from a flexible multi-body dynamical simulation. Second, the finite element models are built using the absolute nodal coordination for different positions according to the stiffness curve. For efficiency, the static reanalysis method is utilized to solve these finite element equilibrium equations. Specifically, the finite element equilibrium equations of key points in the stiffness curve are fully solved as the initial solution, and the following equilibrium equations are solved using a reanalysis method with an error controlled epsilon algorithm. In order to identify the efficiency of the elements, a non-dimensional measurement is introduced. Finally, an improved evolutional structural optimization (ESO) method is used to solve the optimization problem. The presented method is applied to the optimal design of a die bonder. The numerical results show that the presented method is practical and efficient when optimizing the design of the mechanism.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.21 no.3
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• pp.239-245
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• 2008

A level set based topological shape optimization using extended B-spline basis functions is developed for steady-state heat conduction problems. The only inside of complicated domain identified by the level set functions is taken into account in computation, so we can remove the effects of domain outside parts in heat conduction problem. The solution of Hamilton-Jacobi equation leads to an optimal shape according to the normal velocity field determined from the sensitivity analysis, minimizing a thermal compliance while satisfying a volume constraint. To obtain exact shape sensitivity, the precise normal and curvature of geometry need to be determined using the level set and B-spline basis functions. Using topological derivative concept, the nucleation of holes for topological changes can be made whenever and wherever necessary during the optimization.