• Proceedings of the Computational Structural Engineering Institute Conference
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• 2002.10a
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• pp.263-270
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• 2002

This study proposes a multi-objective optimum design method for a rational optimization of high-speed railway bridges. This multi-objective optimization is found to be effective in optimizing multi-objective problems that incorporate cost and dynamic responses such as vertical acceleration and displacement. These design factors are so important in the high-speed railway bridges. And the trade off method which is one of the most typical multi-objective optimization methods is used in this study, since the dynamic factors are formulated as objective function and also considered as constraints. And the Pareto curve can be obtained by performing the multi-objective optimization for real high-speed railway bridges. Thus, it is found that more reasonable design can be obtained when compared with those using conventional design procedure.

• Journal of Computational Design and Engineering
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• v.2 no.3
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• pp.165-175
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• 2015

One of the current challenges in the domain of the multicriteria shape optimization is to reduce the calculation time required by conventional methods. The high computational cost is due to the high number of simulation or function calls required by these methods. Recently, several studies have been led to overcome this problem by integrating a metamodel in the overall optimization loop. In this paper, we perform a coupling between the Normal Boundary Intersection - NBI - algorithm with Radial Basis Function - RBF - metamodel in order to have a simple tool with a reasonable calculation time to solve multicriteria optimization problems. First, we apply our approach to academic test cases. Then, we validate our method against an industrial case, namely, shape optimization of the bottom of an aerosol can undergoing nonlinear elasto-plastic deformation. Then, in order to select solutions among the Pareto efficient ones, we use the same surrogate approach to implement a method to compute Nash and Kalai-Smorodinsky equilibria.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.25 no.9
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• pp.1444-1451
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• 2001

The evolutionary structural optimization(ESO) method has been under continuous development since 1992. The bidirectional evolutionary structural optimization(BESO) method is made of additive and removal procedure. The BESO method is very useful to search the global optimum and to reduce the computational time. This paper presents the ranked bidirectional evolutionary structural optimization(R-BESO) method which adds elements based on a rank, and the performance indicator which can estimate a fully stressed model. The R-BESO method can obtain the optimum design using less iteration number than iteration number of the BESO.

• Korean Journal of Computational Design and Engineering
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• v.10 no.5
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• pp.349-355
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• 2005

This paper concerns about how and why design frameworks for optimization should consider various software development environments such as MATLAB, VB, VBscript, Python, Tcl, PHP, Perl, and JAVA. The frameworks can be utilized by many engineers who have a basic concept about the optimization theory and/or basic knowledge about the computer programming languages. The framework will integrate a number of remote CAE tools, automatically execute them for design optimization, and have the capabilities of post-processing of data such as objective functions, state variables and design variables using a third-party spreadsheet program like Excel. The prototype framework developed in this study will be applied to various examples of optimization problems and show the validity of the proposed method of a framework implemenation.

• Journal of Hydrogen and New Energy
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• v.20 no.6
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• pp.492-498
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• 2009

Six sigma methode was applied for optimization of flow field design of a proton exchange membrane fuel cell (PEMFC). The optimization between number of channel and channel/rib width was suggested in this paper with six sigma method. With the help of six sigma design of experiment (DOE) the number of experiments may be reduced dramatically. The fuel cell channel design optimization with results of these experiments with a 100 $cm^2$ serpentine flow field indicates a optimization data for a given constant operating conditions.

• Wind and Structures
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• v.21 no.5
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• pp.505-521
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• 2015

A general approach of aerodynamic optimization of tall buildings is presented in this paper, focusing on how to best compromise wind issues with other design aspects in the most efficient manner. The given approach is reinforced by establishing an empirical method that can quickly assess the across-wind loads and accelerations as a function of building frequencies, building dimensions, aspect ratios, depth-to-width ratios, and site exposures. Effects of corner modifications, including chamfered corner and recessed corner, can also be assessed in early design stages. Further, to assess the effectiveness of optimization by tapering, stepping or twisting building elevations, the authors introduce a method that takes use of sectional aerodynamic data derived from a simple wind tunnel pressure testing to estimate reductions on overall wind loads and accelerations for various optimization options, including tapering, stepping, twisting and/or their combinations. The advantage of the method is to considerably reduce the amount of wind tunnel testing efforts and speed up the process in finding the optimized building configurations.

• Wind and Structures
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• v.18 no.1
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• pp.21-35
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• 2014

The latest developments in topology optimization are integrated with Computational Fluid Dynamics (CFD) for the conceptual design of building structures. The wind load on a building is simulated using CFD, and the structural response of the building is obtained from finite element analysis under the wind load obtained. Multiple wind directions are simulated within a single fluid domain by simply expanding the simulation domain. The bi-directional evolutionary structural optimization (BESO) algorithm with a scheme of material interpolation is extended for an automatic building topology optimization considering multiple wind loading cases. The proposed approach is demonstrated by a series of examples of optimum topology design of perimeter bracing systems of high-rise building structures.

• Proceedings of the Computational Structural Engineering Institute Conference
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• 2002.04a
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• pp.335-342
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• 2002

A continuum-based design sensitivity analysis (DSA) method fur non-shape problems is developed for geometrically nonlinear elastic structures. The non-shape problem is characterized by the design variables that are not associated with the domain of system like sizing, material property, loading, and so on. Total Lagrangian formulation with the Green-Lagrange strain and the second Piola-Kirchhoff stress is employed to describe the geometrically nonlinear structures. The spatial domain is discretized using the 4-node isoparametric plane stress/strain elements. The resulting nonlinear system is solved using the Newton-Raphson iterative method. To take advantage of the derived analytical sensitivity In topology optimization, a fast and efficient design sensitivity analysis method, adjoint variable method, is employed and the material property of each element is selected as non-shape design variable. Combining the design sensitivity analysis method and a gradient-based design optimization algorithm, an automated design optimization method is developed. The comparison of the analytical sensitivity with the finite difference results shows excellent agreement. Also application to the topology design optimization problem suggests a very good insight for the layout design.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.23 no.6
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• pp.683-691
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• 2010

In this paper, using an adjoint variable method, we develop a design sensitivity analysis(DSA) method applicable to heat conduction problems in steady state. Also, a topology design optimization method is developed using the developed DSA method. Design sensitivity expressions with respect to the thermal conductivity are derived. Since the already factorized system matrix is utilized to obtain the adjoint solution, the cost for the sensitivity computation is trivial. For the topology design optimization, the design variables are parameterized into normalized bulk material densities. The objective function and constraint are the thermal compliance of structures and allowable material volume respectively. Through several numerical examples, the developed DSA method is verified to yield very accurate sensitivity results compared with finite difference ones, requiring less than 0.25% of CPU time for the finite differencing. Also, the topology optimization yields physical meaningful results.

• 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.