• 한국공간정보시스템학회:학술대회논문집
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• 2004.05a
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• pp.43-52
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• 2004

The objective of this study is the development of size, shape and topology discrete optimum design algorithm which is based on the genetic algorithms. The algorithm can perform both shape and topology optimum designs of trusses. The developed algerian was implemented in a computer program. For the optimum design, the objective function is the weight of trusses and the constraints are stress and displacement. The basic search method for the optimum design is the genetic algorithms. The algorithm is known to be very efficient for the discrete optimization. The genetic algorithm consists of genetic process and evolutionary process. The genetic process selects the next design points based on the survivability of the current design points. The evolutionary process evaluates the survivability of the design points selected from the genetic process. The efficiency and validity of the developed size, shape and topology discrete optimum design algorithms were verified by applying the algorithm to optimum design examples

• Journal of Korean Association for Spatial Structures
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• v.2 no.3 s.5
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• pp.93-102
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• 2002

The objective of this study is the development of size, shape and topology discrete optimum design algorithm which is based on the genetic algorithms. The algorithm can perform both shape and topology optimum designs of trusses. The developed algorithm was implemented in a computer program. For the optimum design, the objective function is the weight of trusses and the constraints are stress and displacement. The basic search method for the optimum design is the genetic algorithms. The algorithm is known to be very efficient for the discrete optimization. The genetic algorithm consists of genetic process and evolutionary process. The genetic process selects the next design points based on the survivability of the current design points. The evolutionary process evaluates the survivability of the design points selected from the genetic process. The efficiency and validity of the developed size, shape and topology discrete optimum design algorithms were verified by applying the algorithm to optimum design examples

• Steel and Composite Structures
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• v.47 no.3
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• pp.365-374
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• 2023

This paper presents a new scheme for constructing locking-free finite elements in thick and thin plates, called Discrete Shear Gap element (DSG), using multiphase material topology optimization for triangular elements of Reissner-Mindlin plates. Besides, common methods are also presented in this article, such as quadrilateral element (Q4) and reduced integration method. Moreover, when the plate gets too thin, the transverse shear-locking problem arises. To avoid that phenomenon, the stabilized discrete shear gap technique is utilized in the DSG3 system stiffness matrix formulation. The accuracy and efficiency of DSG are demonstrated by the numerical examples, and many superior properties are presented, such as being a strong competitor to the common kind of Q4 elements in the static topology optimization and its computed results are confirmed against those derived from the three-node triangular element, and other existing solutions.

• Honam Mathematical Journal
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• v.34 no.3
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• pp.451-465
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• 2012

Since there are several kinds of continuities of maps between digital spaces, the paper compares them, which can play an important role in digital topology and discrete geometry.

• Journal of Korean Society of Steel Construction
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• v.13 no.6
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• pp.673-681
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• 2001

The objective of this study is the development of size, shape and topology discrete optimum design algorithm which is based on the genetic algorithm. The algorithm can perform both shape and topology optimum designs of trusses. The developed algorithm was implemented in a computer program. For the optimum design, the objective function is the weight of trusses and the constraints are stress and displacement. The basic search method for the optimum design is the genetic algorithm. The algorithm is known to be very efficient for the discrete optimization. The genetic algorithm consists of genetic process and evolutionary process. The genetic process selects the next design points based on the survivability of the design points selected form the genetic process. The evolutionary process evaluates the survivability of the design points. The evolutionary process evaluates the survivability of the design points selected form the genetic process. The efficiency and validity of the developed size, shape and topology discrete optimum design algorithm was verified by applying the algorithm to optimum design examples.

• International Journal of CAD/CAM
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• v.7 no.1
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• pp.41-49
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• 2007

In density-based topology optimization, 0/1 solutions are sought. Discrete topological problems are often relaxed with continuous design variables so that they can be solved using continuous mathematical programming. Although the relaxed methods are practical, grey areas appear in the optimum topologies. SIMP (Solid Isotropic Microstructures with Penalization) employs penalty schemes to suppress the intermediate densities. SRV (the Sum of the Reciprocal Variables) drives the solution to a 0/1 layout with the SRV constraint. However, both methods cannot effectively remove all the grey areas. SRV has some numerical aspects. In this work, a new scheme SIMP-SRV is proposed by combining SIMP and SRV approaches, where SIMP is employed to generate an intermediate solution to initialize the design variables and SRV is then adopted to produce the final design. The new method turned out to be very effective in conjunction with the method of moving asymptotes (MMA) when using for the stiffness topology optimization of continuum structures for minimum compliance. The numerical examples show that the hybrid technique can effectively remove all grey areas and generate stiffer optimal designs characterized with a sharper boundary in contrast to SIMP and SRV.

• Proceedings of the KIEE Conference
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• 2008.07a
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• pp.655-656
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• 2008

This research presents a topology optimization to minimize eddy current loss maintaining mechanical robustness of structure part in electrical machines A design sensitivity equation for the topology optimization is derived by employing the discrete system equations combined with the adjoint variable method. As a numerical example, frame design of a C-core actuator is performed by the proposed method.

• Korean Journal of Computational Design and Engineering
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• v.14 no.4
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• pp.281-289
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• 2009

Topology optimization has been widely used for the optimal structure design for weight reduction and high performance. Since the result of three-dimensional topology optimization is represented by the discrete material distribution in finite elements, it is hard to interpret from a design point of view. In this paper, the method for interpreting three-dimensional topology optimization resuIt into a series of cross-sectional curve representation is proposed and interfaced with the existing CAD system for the practical use. The concept of node density and virtual grid is introduced to transform element density values into grid density and material boundaries in each cross section are identified based on the element volume rate to satisfy the amount of material specified in the original design intent. Design exampIes show that three-dimensional topology result can be converted into a form of curve CAD model and the seamless interface with CAD software can be achieved.

• Structural Engineering and Mechanics
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• v.55 no.6
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• pp.1157-1176
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• 2015

This study presents optimizing structural topology patterns using regularization of Heaviside function. The present method needs not filtering process to typical SIMP method. Using the penalty formulation of the SIMP approach, a topology optimization problem is formulated in co-operation, i.e., couple-signals, with design variable values of discrete elements and a regularized Heaviside step function. The regularization of discontinuous material distributions is a key scheme in order to improve the numerical problems of material topology optimization with 0 (void)-1 (solid) solutions. The weak forms of an equilibrium equation are expressed using a coupled regularized Heaviside function to evaluate sensitivity analysis. Numerical results show that the incorporation of the regularized Heaviside function and the SIMP leads to convergent solutions. This method is tested using several examples of a linear elastostatic structure. It demonstrates that improved optimal solutions can be obtained without the additional use of sensitivity filtering to improve the discontinuous 0-1 solutions, which have generally been used in material topology optimization problems.

• Journal of Power Electronics
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• v.18 no.6
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• pp.1771-1779
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• 2018

Modern trams with a super capacitor have gained a lot of attention in recent years due to its reliability, convenience, energy conservation and environmental friendliness. Because of its special charging characteristic, the traditional charging structure and control strategy cannot satisfy its charging requirements. This paper presents a new charging topology for fast charging modern trams with a super capacitor and it designs a controller using continuous control set model predictive control (CCS-MPC). There are three contributions in this paper. First, a new charging structure is designed and its mathematics model is derived. The cascade structure is adopted instead of the parallel structure to simplify the control process and to keep the rated power of the controllable part low. Second, a MPC control strategy is proposed to satisfy the charging characteristic. The optimal control signal can be obtained by solving the designed optimization problem. The optimal control signal is related to the discrete control action. In addition, mapping between the continuous control signal and the discrete control action is designed. Third, a semi-physical experimental platform is built to verify the proposed topology and control method. The simulation model and experiment platform are built to verify the correctness of the new structure and its control method. The results obtained show that the new topology can work effectively.