• Steel and Composite Structures
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• v.47 no.5
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• pp.569-585
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• 2023

This paper proposes an efficient approach for the structural topology optimization of bi-directional functionally graded structures by incorporating popular radial basis functions (RBFs) into an implicit level set (ILS) method. Compared to traditional element density-based methods, a level set (LS) description of material boundaries produces a smoother boundary description of the design. The paper develops RBF implicit modeling with multiquadric (MQ) splines, thin-plate spline (TPS), exponential spline (ES), and Gaussians (GS) to define the ILS function with high accuracy and smoothness. The optimization problem is formulated by considering RBF-based nodal densities as design variables and minimizing the compliance objective function. A LS-RBF optimization method is proposed to transform a Hamilton-Jacobi partial differential equation (PDE) into a system of coupled non-linear ordinary differential equations (ODEs) over the entire design domain using a collocation formulation of the method of lines design variables. The paper presents detailed mathematical expressions for BiDFG beams topology optimization with two different material models: continuum functionally graded (CFG) and mechanical functionally graded (MFG). Several numerical examples are presented to verify the method's efficiency, reliability, and success in accuracy, convergence speed, and insensitivity to initial designs in the topology optimization of two-dimensional (2D) structures. Overall, the paper presents a novel and efficient approach to topology optimization that can handle bi-directional functionally graded structures with complex geometries.

• Proceedings of the KSME Conference
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• 2003.11a
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• pp.1322-1327
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• 2003

It is important to determine supporting locations for structural stability of a structure under non-uniform load in space interfered by other parts. In this case, There are many local optima with discontinuous design space. Therefore, The traditional optimization methods based on derivative are not suitable. Whereas, Genetic algorithm(GA) based on stochastic search technique is a very robust and general method. This paper has been presented to determine supporting locations of the vertical supports for reducing stress of the KSTAR(Korea super Superconducting Tokamak Advanced Research) IVCC(In-vessel control coil) under non-uniform electromagnetic load and space interfered by other parts using genetic algorithm. For this study, we develop a program combining finite element analysis with a genetic algorithm to perform structural analysis of IVCC. In addition, this paper presents a technique to perform optimization with FEM when design variables are trapped in an incongruent design space.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.16 no.1
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• pp.1-8
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• 2003

Topology optimization has been evolved into a very efficient conceptual design tool and has been utilized into design engineering processes. Traditional topology optimization has been using homogenization method and optimality criteria method. homogenization method provides relationship equation between structure which includes many holes and stiffness matrix in FEM. Optimality criteria method is used to update design variables while maintaining that volume fraction is uniform. Traditional topology optimization has advantage of good convergence but has disadvantage of too much convergency time. In one way to solve this problem, element removal method using the criterion of an average stress is presented. As the result of examples, it is certified that convergency time is very reduced.

• Journal of Ocean Engineering and Technology
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• v.29 no.5
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• pp.331-341
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• 2015

A degasser is a separation unit used in drilling to separate gas from the drilling mud. The degasser used in offshore drilling was developed at an early stage of drilling. Since its development, the design of the degasser’s internal structure has been optimized, with many limitations due to the restrictions of experimental and computational performance measurement methods. Despite the recent development of CFD technology for multiphase flow analysis, CFD has only been used in a limited way for degasser internal flow analysis and design optimization. In this study, a design optimization procedure for a degasser’s internal structure design was proposed, and CFD analyses of three types of internal structural designs were performed to evaluate the separation performance. The CFD result for each design type was used for the design optimization and, as the result, an optimized design is proposed.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.34 no.8
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• pp.24-32
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• 2006

Using a deterministic design optimization, the effect of uncertainty can result in violation of constraints and deterioration of performances. For this reason, design optimization is required to guarantee reliability for constraints and ensure robustness for an objective function under uncertainty. Therefore, this study drew Monte Carlo Simulation(MCS) for the evaluation of reliability and robustness, and selected an artificial neural network as an approximate model that is suitable for MCS. Applying to the aero-structural optimization problem of aircraft wing, we can explore robuster optima satisfying the sigma level of reliability than the baseline.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.22 no.1
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• pp.53-63
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• 2009

Use of high-strength steel members in building of high-rise buildings and large scale structures is expected to increase the effectiveness of structural design by reducing the weight and cost of structures. So far, high-strength steel members have been used in a very limited way because it is hard to select the proper strengths of steel members in a systematic way with the consideration of the structural cost. In this paper, therefore, a structural optimization technique based on Genetic algorithm is developed for effective use of high-strength steel members in structural design of high-rise buildings with the form of building frame system. The stability and efficiency of the technique is evaluated by using to a 35-story building. As a result, a stable and reliable optimal solution was obtained with a difference of 2.63% between individual and mean optimal structural costs.

• Steel and Composite Structures
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• v.47 no.2
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• pp.147-165
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• 2023

The paper contrasts conventional seismic design with a design that incorporates buckling-restrained bracing in three-dimensional reinforced concrete buildings (BRBs). The suboptimal structures may be found using the multi-objective chimp optimization algorithm (MEN-ChOA). Given the constraints and dimensions, ChOA suffers from a slow convergence rate and tends to become stuck in local minima. Therefore, the ChOA is improved by niching and evolutionary operators to overcome the aforementioned problems. In addition, a new technique is presented to compute seismic and dead loads that include all of a structure's parts in an algorithm for three-dimensional frame design rather than only using structural elements. The performance of the constructed multi-objective model is evaluated using 12 standard multi-objective benchmarks proposed in IEEE congress on evolutionary computation. Second, MEN-ChOA is employed in constructing several reinforced concrete structures by the Mexico City building code. The variety of Pareto optimum fronts of these criteria enables a thorough performance examination of the MEN-ChOA. The results also reveal that BRB frames with comparable structural performance to conventional moment-resistant reinforced concrete framed buildings are more cost-effective when reinforced concrete building height rises. Structural performance and building cost may improve by using a nature-inspired strategy based on MEN-ChOA in structural design work.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.26 no.4
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• pp.241-246
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• 2013

From the numerical results of density-based topology design optimization, a CAD geometric model is constructed and fabricated using 3D printer to experimentally validate the optimal design. In the process of topology design optimization, we often experience checkerboard phenomenon and complicated branches, which could result in the manufacturing difficulty of the obtained optimal design. Sensitivity filtering and morphology methods are used to resolve the aforementioned issues. Identical volume fraction is used in both numerical and experimental models for precise validation. Through the experimental comparison of stiffness in various designs including the optimal design, it turns out that the optimal design has the highest stiffness and the experimental result of compliance matches very well with the numerical one.

• Journal of Advanced Marine Engineering and Technology
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• v.33 no.1
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• pp.19-27
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• 2009

Globally, customer appreciation and demand for quieter products has driven noise control engineers to develop efficient and quieter products in a relatively short time. In the vehicles and ship industry, noise has become an important attribute because of the competitive market and increasing customer awareness. Noise reduction is often achieved through structural modifications by typical approaches. In the present paper, author describes a fundamental study on optimum design of curvature. Bezier curve. and rib attachment to reduce noise from simple panel using a genetic algorithm(GA). The acoustic optimization procedure employed p-FEM for structural analysis, the Rayleigh integral method for acoustic analysis and the GA for searching optimum design. In the optimization procedure. the objective function to be minimized is the average sound power radiated from an objective structure over a given frequency range $0{\sim}300$ Hz.

• Proceedings of the Computational Structural Engineering Institute Conference
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• 1992.04a
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• pp.73-78
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• 1992

A stochastic simulated anneal ins (SSA) is a recent approach to the solution of problems characterized by large number of interacting degrees of freedom. SSA simulates the degrees of freedom in a problem in a such a way that they are a collection of atoms slowly being coolded into a ground state which would correspond to the stationary point of the problem. In this paper, for a randomly disturbed current design, SSA optimization technique is used, which establishes a probabilistic criterion for acceptance or rejection of current design and iteratively improves it to arrive at a stationary Point at which critical temperature is reached. Simple truss optimization problem which consider as their constraints only the tensile and compressive yielding strength of the members are tested using SSA. Satisfactory results are obtained and some discussions are given for the behavior of SSA on the tested truss structures.