• Journal of Technologic Dentistry
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• v.1 no.1
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• pp.37-43
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• 1979

• Transactions of the Korean Society of Mechanical Engineers A
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• v.24 no.6 s.177
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• pp.1479-1490
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• 2000

The design process of the motor driven tilt/telescopic steering column is established by axiomatic design approach in conceptual design stage. By selecting independent design variables for improvin g performance of the steering system, each detailed design can be carried out independently. In the detailed design, the safety in crash environment and vibration reduction are considered. An occupant analysis code SAFE(Safety Analysis For occupant crash Environment) is utilized to simulate the body block test. Segments, contact ellipsoids and spring-damper elements are used to model the steering column in SAFE. The model is verified by the result of the body block test. After the model is validated, the energy absorbing components are designed using an orthogonal array. Occupant analyses are performed for the cases of the orthogonal array. Final design is determined for the minimum occupant injury. For vibrational analysis, a finite element model of the steering column is defined for the modal analysis. The model is validated by the vibration experiment. Size and shape variables are selected for the optimization process. An optimization is conducted to minimize the weight subjected to various constraints.

• Journal of the Korean Society for Railway
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• v.8 no.3
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• pp.267-275
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• 2005

Prestressed concrete girder(PSC girder) bridges have been used widely at the railway as well as highway because they are great in the functional and economical efficiency. Also they have the advantage of convenience of design and construction. However it could be easily verified that the section of PSC girder is excessive design, which has much redundancy against design loads. Thus, in this paper the formulation of the optimum design for PSC girder railway bridge is suggested and dominant design variables and constraints are inquired as performing the optimum design. In order to effective optimum design, design variables are formulated as PSC girder sectional dimension and girder space. The objective is adopted as total cost of PSC girder railway bridge. Also, constraints are formulated according to Korean railway design specification and considering construction-ability such as PS anchorage and girder space. Using the proposed optimum design system, optimum PSC girder railway bridge design has been performed. And from the results of analysis it is suggested to denote the optimum section which satisfies the structural safety and economical efficiency all together.

• Korean Journal of Computational Design and Engineering
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• v.12 no.3
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• pp.163-170
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• 2007

A torque converter, connected to a transmission/transaxle input shaft, connects, multiplies and interrupts the flow of engine torque into the transmission. Damper springs are usually equipped in a torque converter to convert stably the torque power supplied from engine. Damper Springs generally have the most flexible design variables among vehicle transmission parts, so that they could be effective design factors to improve the entire vehicle's performance. Damper spring, however, has geometric complexity after it equipped in a torque converter. For that reason, modeling a damper spring requires expert's knowledge to determine many design parameters and satisfy the functional requirements at the same time. In this paper, we introduce an optimum design method applied in detailed-design stage to reduce design process and financial loss caused by adequate design. Many design variables have to be classified and structuralized for Optimization. This also could make designer concentrate on functional requirements of damper spring, not on design possibility. In addition, modeling an assembled spring has technical restriction with primitives of the current major CAD solutions because of complexity of assembled spring shape. Thus, one of modeling solution presented in this paper since detailed and exact modeling is important for CAE or DMU.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.20 no.5
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• pp.551-556
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• 2007

High pressure storage of the agent gas in fire suppression system was composed of tank, main valve and safety valve, which prevents the fracture of the high pressure storage. The safety valve has circular thin plate as fracture plate that was destroyed over fracture pressure. When inner pressure of the storage is reached the fracture pressure, the safety valve discharges gas and degrades simultaneously the inner pressure of the storage. There are design variables such as flow path diameter, inner diameter of the plastic packing ring, thickness of plate and fillet radius. In this variables, thickness of plate is set to be a value of 0.2mm. The main effect of variables on the inner pressure, has been decided using factorial design and statistical analysis. Therefore, the relation of variables are expressed by regression equation. It is disclosed results that the difference of fracture pressures between the equation and experiment has $2{\sim}5%$. Finally, using response surface method, the optimal design of the safety valve could be decided with safety pressure of 25MPa, where the fracture occurs on circular thin plate.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.6 no.4
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• pp.1-9
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• 1986

In this paper research results of developing a method of selecting design variables of an optimization problem from a finite set of pre-specified numbers, which can be utilized for the structural optimization with standardized structural members, is presented. The method first finds a continuous optimum under the assumption that design variables can be varied continuously. Then a pseudo-optimum is determined by selecting numbers from the set that are near to the continuous optimum and do not violate constraints. The pseudo-optimum is further improved to obtain the final discrete optimum from the set which minimizes cost function of the problem. In this research, the method is combined with the gradient projection optimization algorithm. The method is applied to several minimum weight truss optimization problems with constraints on the stresses, displacements, and design variables. As the results, it is found that the method can be efficiently applied to various optimization problems of which design variables must be chosen from a standard.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.34 no.7
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• pp.28-34
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• 2006

In general engineering problems, the purpose of an optimization is to get optimal design variables. It is the same problem to fix the total amount of the design variables and to judge the optimal mixing proportions of the design variables. That is to say, we can recompose the engineering problems in the concepts of the mixture amount experiments. The goal of mixture amount method is to get the response surfaces of varying both the mixing proportion of component and the total amount of the mixture. The solution of the aircraft fuselage optimization problem is obtained by the mixture amount method and genetic algorithm. In this study, it is shown that the mixture amount method can be utilized for the aircraft structural optimization problem. Also, this method in this study can be applied for the optimization problems over 12 design variables which is impossible for D-optimal design.

• Magazine of the Korea Concrete Institute
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• v.5 no.4
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• pp.167-178
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• 1993

The objective of this paper is to look into the possibility of the detailed and practical optimum design of rt:inforced concrete beam using methods oi discrete mathematical programming. In this discrete optimum formulation, the design variables are the overall depth, width and effective depth of members, and area of longitudinal reinforcement. In addition, the details such as the amount of web reinforcement and cutoff points of longitudinal reinforcement are also considered as variables. Total cost has been used as the objective function. The constraints include the code requirments such as flexural strength, shear strength, ductility, serviceability, concrete cover. spacing, web reinforcement, and development length and cutoff points of longitudinal renforcement. An optimization algorithm is presented for effective optimum design of R.C. beam with discrete de sign variables. First, the continuous variable optimization can be achieved by Feasible Direction Method. Using the results obtained from the continuous variable optimization, a branch and bound method is used to obtained the discrete design values. The proposed algorithm is applied to test problem for reliability, and the results are compared with those of graphical method and rounded-up method. And a simply supported R.C. beam and a two-span continuous R.C. beam are presented as numerical examples for effectiveness and applicability. It is considered that the presented algorithm can be effectively applied to the discrete optimum design of R.C. beams.

• Transactions of the Korean Society of Automotive Engineers
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• v.17 no.5
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• pp.16-25
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• 2009

Testing engine performance using an engine dynamometer requires high technical researchers and many facilities. Nowadays, different variables of CAE program are used for identifying the engine performance instead of engine dynamometer test. This is more convenience, as it does not necessitate an abundance of engine dynamometer experiments and, in addition, produces better results. However, CAE programs also contain various variables which can affect engine performance. Those are coupled with each other, thus making it difficult to determine the effectiveness of different variables on engines. DoE (Design of Experiments) methodology is an efficient way to verify the magnitude of effectiveness on engine performance as well as making responses to be optimized at once without trial & error. This study used data from WAVE simulations, which modeled the DOHC SI engine with in-line 4 cylinders at 1500, 3000 and 4500rpm. DoE methodology is designed properly to determine the effectiveness of five variables on power, BSFC, and volumetric efficiency, as well as to find the optimal response conditions at each rpm through a minimized number of experiments. After finishing DoE process, all the results are examined concerning the reliability of test through a verification experiment.

• IE interfaces
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• v.12 no.4
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• pp.551-556
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• 1999

In this paper, we compare the performance of three data mining classification algorithms(neural network, decision tree, logistic regression) in consideration of various characteristics of categorical input and output data. $2^{4-1}$. 3 fractional factorial design is used to simulate the comparison situation where factors used are (1) the categorical ratio of input variables, (2) the complexity of functional relationship between the output and input variables, (3) the size of randomness in the relationship, (4) the categorical ratio of an output variable, and (5) the classification algorithm. Experimental study results indicate the following: decision tree performs better than the others when the relationship between output and input variables is simple while logistic regression is better when the other way is around; and neural network appears a better choice than the others when the randomness in the relationship is relatively large. We also use Taguchi design to improve the practicality of our study results by letting the relationship between the output and input variables as a noise factor. As a result, the classification accuracy of neural network and decision tree turns out to be higher than that of logistic regression, when the categorical proportion of the output variable is even.