• Transactions of the Korean Society of Automotive Engineers
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• v.20 no.6
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• pp.1-8
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• 2012

Multidisciplinary design optimization (MDO) for a suspension component of the vehicle front suspension was performed in this research. Shapes and thicknesses of the subframe were optimized to satisfy multi-disciplinary design requirements; weight, fatigue, crash, noise, vibration, and harshness (NVH), and kinematic and compliance (K&C). Analyses procedures of the performance disciplines were integrated and automated by using the process integration and design optimization (PIDO) technique, and the integrated and automated analyses environments enabled various types of analytic design methodologies for solving the MDO problem. We applied an approximate optimization technique which involves sequential sampling and metamodeling. Since the design variables for thicknesses should be dealt as discrete variables. the evolutionary algorithm is selected as optimization technique. The MDO problem was formulated three types of problems according to the order of priorities among the performance disciplines, and the results of MDO provided design alternatives for various design situations.

• Advances in Computational Design
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• v.2 no.3
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• pp.195-210
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• 2017

Simultaneous optimization of trusses which concurrently takes into account design variables related to the size, shape and topology of the structure is recognized as highly complex optimization problems. In this class of optimization problems, it is possible to encounter several unstable mechanisms throughout the solution process. However, to obtain a feasible solution, these unstable mechanisms somehow should be rejected from the set of candidate solutions. This study proposes triangular unit based method (TUBM) instead of ground structure method, which is conventionally used in the topology optimization, to decrease the complexity of search space of simultaneous optimization of the planar truss structures. TUBM considers stability of the triangular units for 2 dimensional truss systems. In addition, integrated particle swarm optimizer (iPSO) strengthened with robust technique so called improved fly-back mechanism is employed as the optimizer tool to obtain the solution for these class of problems. The results obtained in this study show the applicability and efficiency of the TUBM combined with iPSO for the simultaneous optimization of planar truss structures.

• Korean Journal of Computational Design and Engineering
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• v.8 no.4
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• pp.231-242
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• 2003

Multidisciplinary Design Optimization (MDO) is an optimization technique considering simultaneously multiple disciplines such as dynamics, mechanics, structural analysis, thermal and fluid analysis and electromagnetic analysis. A software system enabling multidisciplinary design optimization is called MDO framework. An MDO framework provides an integrated and automated design environment that increases product quality and reliability, and decreases design cycle time and cost. The MDO framework also works as a common collaborative workspace for design experts on multiple disciplines. In this paper, we present the architecture for an MDO framework along with the requirement analysis for the framework. The requirement analysis has been performed through interviews of design experts in industry and thus we claim that it reflects the real needs in industry. The requirements include integrated design environment, friendly user interface, highly extensible open architecture, distributed design environment, application program interface, and efficient data management to handle massive design data. The resultant MDO framework is datasever-oriented and designed around a centralized data server for extensible and effective data exchange in a distributed design environment among multiple design tools and software.

• Wind and Structures
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• v.30 no.4
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• pp.379-392
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• 2020

The paper presents a Life-Cycle Cost-based optimization framework for wind-excited tall buildings equipped with Tuned Mass Dampers (TMDs). The objective is to minimize the Life-Cycle Cost that comprises initial costs of the structure, the control system and costs related to repair, maintenance and downtime over the building's lifetime. The integrated optimization of structural sections and mass ratio of the TMDs is carried out, leading to a set of Pareto optimal solutions. The main advantage of the proposed methodology is that, differently from the traditional optimal design approach, it allows to perform the unified design of both the structure and the control system in a Life Cycle Cost Analysis framework. The procedure quantifies wind-induced losses, related to structural and nonstructural damage, considering the stochastic nature of the loads (wind velocity and direction), the specificity of the structural modeling (e.g., non-shear-type vibration modes and torsional effects) and the presence of the TMDs. Both serviceability and ultimate limit states related to the structure and the TMDs' damage are adopted for the computation of repair costs. The application to a case study tall building allows to demonstrate the efficiency of the procedure for the integrated design of the structure and the control system.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.29 no.2 s.233
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• pp.262-269
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• 2005

Optimization of a satellite structure under severe space launching environments is performed considering various design constraints. Simulate annealing, one of combinatorial optimization techniques, is used to optimize the satellite. The optimization results by the simulated annealing are compared to those by the method of modified feasible direction and genetic algorithm. Ten bar truss structure is optimized for feasibility study of the simulated annealing. Finally, the satellite structure is optimized by the simulated annealing algorithm under space environment. Weights of the satellite upper platform and propulsion module are minimized with consideration of several static and dynamic constraints. MSC/NASTRAN is used to find the static and dynamic responses. Simulated annealing has been programmed and integrated with the finite element analysis program for optimization. It is shown that the simulated annealing algorithm can be extended to the optimization of space structures.

• Magazine of the Korean Society of Agricultural Engineers
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• v.37 no.E
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• pp.31-39
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• 1995

Weight minimization for the steel bridge girders using an approximation based optimization technique is presented. To accomplish this, an optimization oriented finite element program is used to achieve continuous weight reduction until the optimum is reached. To reduce computational cost, approximation techniques are adopted during the optimization process. Constraint deletion as well as intermediate design variables and responses are also used for higher qualitv of approximations and for a better convergence rate. Both the reliability and the effectiveness of the underlying optimization method are reviewed.

• Journal of Magnetics
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• v.19 no.3
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• pp.295-299
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• 2014

Recently, module-integrated converter (MIC) research has shown interest in small-scale photovoltaic (PV) generation. The converter is capable of efficient power generation. In this system, the high frequency transformer should be made compact, and demonstrate high efficiency characteristics. This paper presents a core structure optimization procedure to improve the efficiency of a high frequency transformer of compact size. The converter circuit is considered in the finite element analysis (FEA) model, in order to obtain an accurate FEA result. The results are verified by the testing of prototypes.

• Journal of the Earthquake Engineering Society of Korea
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• v.12 no.2
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• pp.9-22
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• 2008

This paper presents an integrated optimal design technique of a hybrid structure-damper system for improving the seismic performance of the structure. The proposed technique corresponds to the optimal distribution of the stiffness and dampers. The multi-objective optimization technique is introduced to deal with the optimal design problem of the hybrid system, which is reformulated into the multi-objective optimization problem with a constraint of target reliability in an efficient manner. An illustrative example shows that the proposed technique can provide a set of Pareto optimal solutions embracing the solutions obtained by the conventional sequential design method and single-objective optimization method based on weighted summation scheme. Based on the stiffness and damping capacities, three representative designs are selected among the Pareto optimal solutions and their seismic performances are investigated through the parametric studies on the dynamic characteristics of the seismic events. The comparative results demonstrate that the proposed approach can be efficiently applied to the optimal design problem for improving the seismic performance of the structure.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.40 no.4
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• pp.211-220
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• 2017

The application of the theoretical model to real assembly lines has been one of the biggest challenges for researchers and industrial engineers. There should be some realistic approach to achieve the conflicting objectives on real systems. Therefore, in this paper, a model is developed to synchronize a real system (A discrete event simulation model) with a theoretical model (An optimization model). This synchronization will enable the realistic optimization of systems. A job assignment model of the assembly line is formulated for the evaluation of proposed realistic optimization to achieve multiple conflicting objectives. The objectives, fluctuation in cycle time, throughput, labor cost, energy cost, teamwork and deviation in the skill level of operators have been modeled mathematically. To solve the formulated mathematical model, a multi-objective simulation integrated hybrid genetic algorithm (MO-SHGA) is proposed. In MO-SHGA each individual in each population acts as an input scenario of simulation. Also, it is very difficult to assign weights to the objective function in the traditional multi-objective GA because of pareto fronts. Therefore, we have proposed a probabilistic based linearization and multi-objective to single objective conversion method at population evolution phase. The performance of MO-SHGA is evaluated with the standard multi-objective genetic algorithm (MO-GA) with both deterministic and stochastic data settings. A case study of the goalkeeping gloves assembly line is also presented as a numerical example which is solved using MO-SHGA and MO-GA. The proposed research is useful for the development of synchronized human based assembly lines for real time monitoring, optimization, and control.

• 시스템엔지니어링워크숍
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• s.4
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• pp.1-4
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• 2004