• Journal of the Korean Society of Industry Convergence
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• v.24 no.1
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• pp.31-43
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• 2021

In this study, approximate design optimization using various meta-models was performed for the structural design of active type deck support frame. The active type deck support frame was newly developed to facilitate both transportation and installation of 20,000 ton class offshore plant topside. Structural analysis was carried out using the finite element method to evaluate the strength performance of the active type deck support frame in its initial design stage. In the structural analysis, the strength performances were evaluated for various design load conditions that were regulated in ship classification organization. The approximate optimum design problem based on meta-model was formulated such that thickness sizing variables of main structure members were determined by achieving the minimum weight of the active type deck support frame subject to the strength performance constraints. The meta-models used in the approximate design optimization were response surface method, Kriging model, and Chebyshev orthogonal polynomials. The results from approximate design optimization were compared to actual non-approximate design optimization. The Chebyshev orthogonal polynomials among the meta-models used in the approximate design optimization represented the most pertinent optimum design results for the structure design of the active type deck support frame.

• Journal of Convergence for Information Technology
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• v.11 no.1
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• pp.109-117
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• 2021

In this paper, the meta-model based approximate optimization was carried out for the structure design of an ocean automatic salt collector in order to minimize the structure weight. The structural analysis was performed by using the finite element method to evaluate the strength performance of the ocean automatic salt collector in its initial design. In the structural analysis, it was evaluated the strength performance of the design load conditions. The optimum design problem was formulated so that design variables of main structure thickness would be determined by minimizing the structure weight subject to strength performance constraints. The meta-models used in the approximate optimization were the response surface method, Kriging model, and Chebyshev orthogonal polynomials. Regarding to the numerical characteristics, the solution results from approximate optimization techniques were compared to the results of non-approximate optimization. The Chebyshev orthogonal polynomials among the meta-models used in the approximate optimization showed the most appropriate optimum design results for the structure design of the ocean automatic salt collector.

• Computers and Concrete
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• v.21 no.5
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• pp.505-511
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• 2018

This paper investigates the potential of a hybrid model which combines the least squares support vector machine (LSSVM) and an improved particle swarm optimization (IMPSO) techniques for prediction of concrete compressive strength. A modified PSO algorithm is employed in determining the optimal values of LSSVM parameters to improve the forecasting accuracy. Experimental data on concrete compressive strength in the literature were used to validate and evaluate the performance of the proposed IMPSO-LSSVM model. Further, predictions from five models (the IMPSO-LSSVM, PSO-LSSVM, genetic algorithm (GA) based LSSVM, back propagation (BP) neural network, and a statistical model) were compared with the experimental data. The results show that the proposed IMPSO-LSSVM model is a feasible and efficient tool for predicting the concrete compressive strength with high accuracy.

• Proceedings of the KSME Conference
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• 2003.04a
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• pp.451-455
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• 2003

Major concern in modern industry is how to reduce the time and cost for product efficient production. Among many mechanical parts of a satellite, bracket plays an important role to support the load when the satellite is launched to space. so enough strength and stiffness. A designer could add unnecessary material and strength it so as not to fail when it used. But if mechanical part of satellite is over-designed, cost will rise and it also goes against to the aim of lightness. To achieve lightness and enough strength and stiffness, optimization algorithm should be introduced in design process. In this study, conceptual design of bracket is carried out to increase the performance of satellite. Some parameter which could change the weight of this part are selected as design variables. Total weight of bracket is to be minimized while displacement and stress should not exceed limit. Size optimization is done with 3D solid element and PLBA, the RQP algorithm. The weight of 0.262kg of initial model is reduced to 0.241kg after optimization process, so 9.8% of weight reduction is obtained.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.24 no.5
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• pp.543-551
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• 2011

The paper deals with the comparative study of design optimization based on various approximation techniques in strength design of riser support structure installed on floating production storage and offloading unit(FPSO) using offshore operation loading conditions. The design optimization problem is formulated such that structural member sizing variables are determined by minimizing the weight of riser support structure subject to the constraints of structural strength in terms of loading conditions. The approximation techniques used in the comparative study are response surface method based sequential approximate optimization(RBSAO), Kriging based sequential approximate optimization(KBSAO), and the enhanced moving least squares method(MLSM) based approximate optimization such as CF(constraint feasible)-MLSM and Post-MLSM. Commercial process integration and design optimization(PIDO) tools are employed for the applications of RBSAO and KBSAO. The enhanced MLSM based approximate optimization techniques are newly developed to ensure the constraint feasibility. In the context of numerical performances such as design solution and computational cost, the solution results from approximate techniques based design optimization are compared to actual non-approximate design optimization.

• Proceedings of the Korean Society For Composite Materials Conference
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• 2001.05a
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• pp.155-158
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• 2001

The layup optimization by genetic algorithm (GA) for the strength of laminated composites with free-edge is presented. For the calculation of interlaminar stresses of composite laminates with free edges, extended Kantorovich method is applied. In the formulation of GA, repair strategy is adopted for the satisfaction of given constraints. In order to consider the bounded uncertainty of material properties, convex modeling is used. Results of GA optimization with scattered properties are compared with those of optimization with nominal properties. The GA combined with convex modeling can work as a practical tool for light weight design of laminated composite structures since uncertainties are always encountered in composite materials.

• Transactions of the Korean Society of Machine Tool Engineers
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• v.15 no.5
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• pp.123-130
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• 2006

In manufacturing, process automation and parameter optimization are required in order to improve productivity. Especially in welding process, productivity and weldablity should be considered to determine the process parameter. In this paper, optimization methodology was proposed to determine the welding conditions using the objective function in terms of productivity and weldablity. In order to conduct this, welding experiments were carried out. Tensile test was performed to evaluate the weldability. Neural network model to estimate tensile strength using the laser power, welding speed, and wire feed rate was developed. Objective function was defined using the normalized tensile strength which represented the weldablilty and welding speed and wire feed rate which represented the productivity. The optimal welding parameters which maximized the objective function were determined.

• Structural Engineering and Mechanics
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• v.52 no.4
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• pp.815-827
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• 2014

Buckling optimization of laminated composite plates is significant as they fail because of buckling under in-plane compressive loading. The plate is usually modeled without cutout so that the buckling strength is found analytically using classical laminate plate theory (CLPT). However in real world applications, the composite plates are modeled with cutouts for getting them assembled and to offer the provisions like windows, doors and control system. Finite element analysis (FEA) is used to analyze the buckling strength of the plate with cutouts and it leads to high computational cost when the plate is optimized. In this article, a genetic algorithm based optimization technique is used to optimize the composite plate with cutout. The computational time is highly reduced by replacing FEA with artificial neural network (ANN). The effectiveness of the proposed method is explored with two numerical examples.

• Transactions of Materials Processing
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• v.26 no.1
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• pp.41-47
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• 2017

Cyclic behavior of advanced high strength steel sheets was measured using an inverse-optimization approach with pre-straining and bending. First, tensile specimens were pre-strained, and three-point bending was conducted for the pre-strained specimens. By using the inverse finite element optimization, the combined isotropic-kinematic hardening parameters that minimize the error between the measured and predicted bending force-displacement curves. The measured cyclic behavior agreed well with the cyclic behavior measured by sheet tension-compression test, which confirms the validity of the measuring procedure based on inverse optimization.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.22 no.3
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• pp.277-287
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• 2009

Recently, the high-strength steel of 400~600MPa tensile strength is producing in the country. Use of high-strength steel member in the design of high-rise buildings is expected to increase the efficiency of structural design in the aspect of structure material weight and cost, however it has been used only a narrow extent. No efficient design method to use high-strength steel in the design of high-rise buildings has been developed. Therefore, in this study structural cost optimization technique that can minimize the structural material cost of high-rise buildings using high-strength steels is developed. The efficiency of the technique is evaluated by comparing the experience-based design for 6 high-rise building examples. As a result, the proposed techniques can save 7~21% of structural material cost compared with experienced-based design. And also, the rough guideline for effective use of high-strength steels in the structural design of high-rise buildings is introduced on the basis of results.