• The Korean Journal of Applied Statistics
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• v.27 no.5
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• pp.693-703
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• 2014

When setting up an experiment for extrapolation at multiple points outside the design space, we often face a difficulty in which point we should emphasize even if the polynomial model under consideration is given. In this paper we propose various methods under two possible scenarios that deal with extrapolations. One considered in this paper is the situation when the model assumed can be extended beyond the design space. In this setting, the many classical methods(including various approaches the authors proposed before) were revisited in the context of extrapolation. But the real problem arises when there is an uncertainty concerning the validity of the assumed model. Therefore, the second scenario is to develop an appropriate procedure when we have limited information about model. Consequently, a hybrid approach is suggested to deal with this issue of how to handle the multiple extrapolating under model uncertainty. A search algorithm was implemented because the classical exchange algorithm was found difficult to handle the complexity of the problem.

• Transactions of the Korean Society of Automotive Engineers
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• v.13 no.6
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• pp.84-92
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• 2005

This paper is concerned with optimum design of a center-pillar assembly induced by the high-speed side impact of the vehicle. In order to simulate deformation behavior of the center-pillar assembly, simplified finite element model of the center-pillar and a moving deformable barrier are developed based on results of the crash analysis of a full vehicle model. In optimization of the deformation shape of the center-pillar, S-shaped deformation is targeted to guarantee reduction of the injury level of a driver dummy in the crash test. Tailor-welded blanks are adopted in the simplified center-pillar model to control the deformation shape of the center-pillar assembly. The thickness of each part which constitutes the simplified model is selected as a design parameter. The thickness of parts which have significant effect on the deformation mechanism are selected as design parameters with sensitivity analysis based on the design of experiment technique. The objective function is constructed so as to minimize the weight and lead to an S-mode deformation shape. The result shows that the simplified model can be utilized effectively for optimum design of the center-pillar members with remarkable saving of computing time.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.11 no.8
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• pp.2975-2982
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• 2010

In this paper, embedded control system of segway robot using model based design is presented. Design of control program in embedded system can be implemented simply and easily by model based design method using MATLAB/SIMULINK. Segway robot is consisted of a NXT Mindstorms controller, two DC servo motors, a ultrasonic sensor, a gyro sensor, and a light sensor. It is a unstable nonlinear system and has a control problem of body pitch angle. So controller of segway robot is designed using state feedback LQR control. It is confirmed through design and experiment of controller that the model based design method, that is not depend on target processor, has merits compared with the text based design in aspects such as a program development, an error detection/modify, and an insight of software structure.

• International Journal of High-Rise Buildings
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• v.2 no.1
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• pp.79-83
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• 2013

Shaking table test is an important and useful method to help structural engineers get better knowledge about the seismic performance of the buildings with complex structure, just like Shanghai tower. According to Chinese seismic design guidelines, buildings with a very complex and special structural system, or whose height is far beyond the limitation of interrelated codes, should be firstly studied through the experiment on seismic behavior. To investigate the structural response, the weak storey and crack pattern under earthquakes of different levels, and to help the designers improve the design scheme, the shaking table model tests of a scaled model of Shanghai tower were carried out at the State Key Laboratory of Disaster Reduction in Civil Engineering, Tongji University, Shanghai, China. This paper describes briefly the structural system, the design method and manufacture process of the scaled model, and the test results as well.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.29 no.9 s.240
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• pp.1199-1208
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• 2005

Nowadays, it is performed actively to optimize by using an approximate model. This is called the approximate optimization. In addition, the sequential approximate optimization (SAO) is the repetitive method to find an optimum by considering the convergence of an approximate optimum. In some recent studies, it is proposed to increase the fidelity of approximate models by applying the sequential sampling. However, because the accuracy and efficiency of an approximate model is directly connected with the design area and the termination criteria are not clear, sequential sampling method has the disadvantages that could support an unreasonable approximate optimum. In this study, the SAO is executed by using trust region, Kriging model and Optimal Latin Hypercube design (OLHD). Trust region is used to guarantee the convergence and Kriging model and OLHD are suitable for computer experiment. finally, this SAO method is applied to various optimization problems of highly nonlinear mathematical functions. As a result, each approximate optimum is acquired and the accuracy and efficiency of this method is verified by comparing with the result by established method.

• Design & Manufacturing
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• v.18 no.2
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• pp.64-73
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• 2024

The purpose of this paper is to introduce a fusion method that combines the design of experiments (DOE) and machine learning to optimize the bias of plastic products. The study focuses on the plastic motor housing used in automobiles, which is manufactured through plastic injection molding. Achieving optimal molding for the motor housing involves the optimization of various molding conditions, including injection pressure, injection time, holding pressure, mold temperature, and cooling time. Failure to optimize these conditions can lead to increased product deformation. To minimize the deformation of the motor housing, the widely used Taguchi method, which is one of the design of experiment techniques, was employed to identify the injection molding conditions that affect deformation. Machine learning was then applied to various models based on the identified molding conditions. Among the models, the Random Forest model emerged as the most effective in predicting deformation amounts. The validity of the Random Forest model was also confirmed through verification. The verification results demonstrated the excellent prediction accuracy of the trained Random Forest model. By utilizing the validated model, molding conditions that minimize deformation were determined. Implementation of these optimal molding conditions led to a reduction of approximately 5.3% in deformation compared to the conditions before optimization. It is noteworthy that all injection molding outcomes presented in this paper were obtained through robust injection molding simulations, ensuring both research objectivity and speed.

• Journal of the Korea Society for Simulation
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• v.16 no.4
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• pp.23-31
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• 2007

Anti-Air Warfare(AAW) functionality of the naval combat system is the key functionality to ensure the ship's survivability. We have applied a novel method using model-based-simulation to analyze and design AAW functionality of the Patrol Killer Experimemnt Combat System. In this approach, an AAW functional model is described with the FSM(Finite State Machine) and directly executed for the AAW simulation. After prototyping using model based simulation, Hardware In Loop Simulation(HILS) is conducted as the AAW functionality is interfaced with the other ones of the combat system for completing the integration of the system components. This incremental and iterative development approach based on the model based simulation can minimize the development risks and costs caused by the system complexity for military system, bringing out the merit of the rapid prototyping.

• Journal of Korean Society of Water Science and Technology
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• v.26 no.6
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• pp.3-12
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• 2018

The objective of this study was to evaluate the radius of influence of effluent of water treatment system developed for the purpose of improvement of reservoir water quality using fluorescent dye (Rhodamine-WT) tracer experiment and 3-D numerical model. The tracer experiment was carried out in a medium-sized agricultural reservoir with a storage capacity of $227,000m^3$ and an average depth of 1.6 m. A guideline with a total length of 160 m was installed at intervals of 10 m in the horizontal direction from the discharge part, and a Rhodamine measurement sensor (YSI 6130, measurement range $0-200{\mu}g/L$) was used to measure concentration changes in time, distance, and depth. Experimental design was established in advance through Jet theory and the diffusion process was simulated using ELCOM, a three dimensional hydraulic dynamics model. As a result of the study, the direct effect radius of the jet emitted from the applied water treatment system was about 50-70 m, and the radius of physical effect by the advection diffusion was judged to be 100-120 m. The numerical simulations of effluent advection-diffusion of the water treatment system using ELCOM showed very similar results to those of the impact radius analysis using the tracer experiment and jet flow empirical equations. The results provide valuable information on the spatial extent of the water quality improvement devices installed in the reservoir and the facility layout design.

• Journal of Ocean Engineering and Technology
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• v.29 no.1
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• pp.56-61
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• 2015

To improve the accuracy of a machine, research needs to be conducted on the relationship between the output variables and design variables of a spindle-shaped part from the thermal and static viewpoints. Therefore, research was carried out by examining the correlation of each variable to find the optimum conditions. Moreover, DOE (design of experiments) was extensively used. The model used in this study was a grinding spindle to which a hydrostatic bearing was applied. This model was used in a preliminary analysis based on the experimental results of the previous studies. The influences of the output variables and design variables were compared through a main effect analysis. Generated response surfaces were applied to the Kriging model. To optimize the model, a screening method was selected. In comparison with the initial model, the deformation of the optimized model designed by DOE decreased by 4.1 μm, while the thermal deformation decreased by 1.2 μm. Therefore, it was efficient to design a spindle-shaped part through DOE to improve the accuracy of the machine.

• Korean Chemical Engineering Research
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• v.45 no.1
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• pp.93-102
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• 2007

The objective of this study is to develop a 3D DMFC model for modeling gas evolution and flow patterns to design optimal flow field for gas management. The gas management on the anode side is an important issue in DMFC design and it greatly influences the performance of the fuel cell. The flow field is tightly related to gas management and distribution. Since experiment for the optimal design of various flow fields is difficult and expensive due to high bipolar plate cost, computational fluid dynamics (CFD) is implemented to solve the problem. A two-fluid model was developed for CFD based flow field design. The CFD analysis is used to visualize and to analyze the flow pattern and to reduce the number of experiments. Case studies of typical flow field designs such as serpentine, zigzag, parallel and semi-serpentine type illustrate applications of the model. This study presents simulation results of velocity, pressure, methanol mole fraction and gas content distribution. The suggested model is verified to be useful for the optimal flow field design.