• Journal of the Korea Society for Simulation
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• 제23권2호
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• pp.25-33
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• 2014

In this study, the border security problem of the ROK Army is examined by applying the agent-based modeling and simulation (ABMS) concept as well as its platform, MANA. Based on the approximately optimized behavior of the infiltrator obtained using genetic algorithm (GA), we evaluate the GOP border security system which consists of human resources, surveillance, as well as command and control (C2) systems. We use four measures of effectiveness (MOEs) to evaluate its performance, and we apply a near optimal latin hypercube (NOLH) design to deal with the large number of factors of interest in our model. By using a NOLH design, our simulation runs are implemented efficiently. We hope the results of this study provide valuable data for deciding the configuration of the border security system structure and the number of soldiers assigned in the platoon.

• Transactions of the Korean Society of Automotive Engineers
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• 제20권4호
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• pp.46-51
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• 2012

Injection pressure, an important factor in filling process, should be minimized to enhance injection molding quality. Injection pressure can be controlled by valve gate open timing. In this work, we decided the valve gate open timing to minimize the injection pressure. To solve this design problem, we integrated MAPS-3D (Mold Analysis and Plastic Solution-3Dimension), a commercial injection molding CAE tool, to PIAnO (Process Integration, Automation and Optimization), a commercial PIDO (Process Integration, and Design Optimization) tool using the file parsing method. In order to reduce computational cost, we performed an approximate optimization using meta-models that replaced expensive computer simulations. At first, we carried out DOE (Design of Experiments) using OLHD (Optimal Latin Hypercube Design) available in PIAnO. Then, we built Kriging models using the simulation results at the sampling points. Finally, we used micro GA (Genetic Algorithm) available in PIAnO. Using the proposed design approach, the injection pressure has been reduced by 13.7% compared to the initial one. This design result clearly shows the validity of the proposed design approach.

• Journal of Computational Design and Engineering
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• 제3권3호
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• pp.179-190
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• 2016

A kind of modified epoxy resin sheet molding compounds of the impeller has been designed. Through the test, the non-metal impeller has a better environmental aging performance, but must do the waterproof processing design. In order to improve the stability of the impeller vibration design, the influence of uncertainty factors is considered, and a multi-objective robust optimization method is proposed to reduce the weight of the impeller. Firstly, based on the fluid-structure interaction, the analysis model of the impeller vibration is constructed. Secondly, the optimal approximate model of the impeller is constructed by using the Latin hypercube and radial basis function, and the fitting and optimization accuracy of the approximate model is improved by increasing the sample points. Finally, the micro multi-objective genetic algorithm is applied to the robust optimization of approximate model, and the Monte Carlo simulation and Sobol sampling techniques are used for reliability analysis. By comparing the results of the deterministic, different sigma levels and different materials, the multi-objective optimization of the SMC molding impeller can meet the requirements of engineering stability and lightweight. And the effectiveness of the proposed multi-objective robust optimization method is verified by the error analysis. After the SMC molding and the robust optimization of the impeller, the optimized rate reached 42.5%, which greatly improved the economic benefit, and greatly reduce the vibration of the ventilation system.

• Transactions of the Korean Society of Mechanical Engineers B
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• 제35권8호
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• pp.763-771
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• 2011

An optimization procedure for the design of a ventilation axial-flow fan is presented in this paper. Flow analyses of the preliminary fan are performed by solving three-dimensional Reynolds-averaged Navier-Stokes equations via a finite-volume solver with the shear-stress transport turbulence model as a turbulence closure. Three variables, the hub-to-tip ratio and the stagger angles at the mid and tip spans, are selected for the optimization. The Latin-hypercube sampling method as a design-of-experiments technique is used to generate twenty-five design points within the design space. and the weighted average surrogate models, WTA1, WTA2, and WTA3, are applied for find optimal designs. The results show that the efficiency is considerably enhanced.