• Proceedings of the Korean Nuclear Society Conference
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• 1997.10a
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• pp.469-474
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• 1997

To provide tile information ell severe accident progression is very important for advanced or new type of nuclear power plant (NPP) design. A parametric study, therefore was performed to investigate the effect of thermal hydraulic design parameters ell severe accident progression of pressurized water reactors (PWRs), Nine parameters, which are considered important in NPP design or severe accident progression, were selected among the various thermal hydraulic design parameters. The backpropagation neural network (BPN) was used to determine parameters, which might more strongly affect the severe accident progression, among mile parameters. For training. different input patterns were generated by the latin hypercube sampling (LHS) technique and then different target patterns that contain core uncovery time and vessel failure time were obtained for Young Gwang Nuclear (YGN) Units 3&4 using modular accident analysis program (MAAP) 3.0B code. Three different severe accident scenarios, such as two loss of coolant accidents (LOCAs) and station blackout(SBO), were considered in this analysis. Results indicated that design parameters related to refueling water storage tank (RWST), accumulator and steam generator (S/G) have more dominant effects on the progression of severe accidents investigated, compared to tile other six parameters.

• Proceedings of the Korean Society for Emotion and Sensibility Conference
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• 1999.11a
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• pp.31-31
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• 1999

In the preliminary design stage of an automotive interior, human sensibility is first analyzed and applied to design parameters for satisfying consumers needs using optimization and engineering judgement. Then designers try to design components that meet these needs using empirical and trial-and-error procedures. This process usually yields poor results because it is difficult to find a feasible design that satisfies the targets by trial-and-error (a feasible design is one that satisfies consumers needs and design constraints). To improve this process, we need tools to link the human sensibility with the design parameters that define the geometry of the components of an automotive interior. A methodology is presented for developing a tool for design guidance of an automotive interior. This tool translates the human sensibility into the design parameters that define the geometry of the components of an automotive interior. This tool, called interpreter, rapidly predicts the human sensibility of a given automotive interior and presents design parameters that meet or exceed given human sensibility to satisfy consumers needs and design constraints. The methodology is demonstrated on the interior design of an actual automotive.

• Transactions of the Korean Society of Mechanical Engineers
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• v.8 no.1
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• pp.1-9
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• 1984

In the utilization of solar energy most often a flat solar collector is used for solar heating, system. Since solar energy is absorbed through this solar collector, it is considered to be a most important part in the whole solar heating system. The purpose of the present investigation is to evaluate the influence of varying design parameters for thermal performances of flat-plate solar collector. By analysing these parameters, optimum design of solar collector would become possible. Specification of the existing solar collector are utilized in calculation as a starting point. Analysis is carried out numerically for "Unit Solar Collector" which is composed of fin and tube. Among design parameters. such parameters as mass flow rate per unit area, tube spacing and fin thickness are selected as variables in the computer simulation model. Results are presented for thermal performances of flat-plate solar collector for each important design parameters, so that predictions become possible through numerical analysis without performing experiments whenever it is required. required.

• Journal of the Korean Society for Precision Engineering
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• v.14 no.2
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• pp.66-73
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• 1997

In many optimal methods for the structural design, the structural analysis is performed with the given design parameters. Then the design sensitivity is calculated based on its structural anaysis results. There-after, the design parameters are changed iteratively. But genetic algorithm is a optimal searching technique which is not depend on design sensitivity. This method uses for many design para- meter groups which are generated by a designer. The generated design parameter groups are become initial population, and then the fitness of the all design parameters are calculated. According to the fitness of each parameter, the design parameters are optimized through the calculation of reproduction process, degradation and interchange, and mutation. Those are the basic operation of the genetic algorithm. The changing process of population is called a generation. The basic calculation process of genetic algorithm is repeatly accepted to every generation. Then the fitness value of the element of a generation becomes maximum. Therefore, the design parameters converge to the optimal. In this study, the optimal design pro- cess of a machine tool structure for static loading is presented to determine the optimal base supporting points and structure thickness using a genetic algorithm.

• International Journal of Automotive Technology
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• v.7 no.7
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• pp.795-801
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• 2006

A No Spin Differential (NSD) design has been improved from evaluation of two NSD models utilizing the axiomatic approach. New design parameters of the second level are developed to satisfy the independence axiom. The design matrices are determined to decouple the relationship between design parameters and process parameters. The values of process parameters are then determined to optimize and improve the NSD design. Consequently a unique and evolutionary NSD design is achieved with the aid of the axiomatic approach.

• Proceedings of the Korean Society of Tribologists and Lubrication Engineers Conference
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• 2001.06a
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• pp.257-262
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• 2001

A numerical analysis is undertaken to show tile influence of bearing design parameters on tile load capacity of air lubricated spiral grooved thrust bearing. The governing equation derived from the mass balance is solved by the finite difference method. Optimal values for various design parameters are obtained to maximize the load capacity. The design parameters are the groove angle, the groove width ratio, the groove height ratio, arid the seal ratio.

• Proceedings of the KSR Conference
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• 1998.11a
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• pp.413-420
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• 1998

In this study, optimum design methodology for rail vehicle suspension characteristics is suggested. Three parameters, primary lateral/longitunal stiffness and secondary lateral stiffness, are selected as design parameters. critical speed, suspension stroke trade-off and derailment coefficient are selectee as performance constraints. The optimum parameters to maximize ride quality are evaluated under the constraints. Steady-state curiving model to be able to evaluate derailment coefficient is developed. The combined design procedure is developed to evaluate Three parameters at the same time.

• Journal of Biosystems Engineering
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• v.24 no.3
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• pp.183-194
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• 1999

Using the dynamic model and simulation program TDA developed in the previous paper, effects of design parameters of an agricultural tractor-trailer system on its vertical seat vibrations were investigated. The tractor-trailer system was excited by traversing over a half-sine bump. The excitation frequencies were determined by traveling velocity of the tractor and a half-sine bump selected appropriately. TDA predicted the autospectra of the vertical seat accelerations with different values of design parameters and compared them to analyze their effects. The design parameters included positions of engine, cab, and seat mountings as well as their dynamic properties. The results of this study suggested guidelines with which an improved structure of tractor may be developed in the early stage of design for a better ride quality.

• Computers and Concrete
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• v.13 no.4
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• pp.547-567
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• 2014

Precast Seismic Structural Systems (PRESSS) provided an iterative procedure for obtaining optimum design of unbonded post-tensioned coupled precast concrete wall systems. Although PRESSS procedure is effective, however, it is lengthy and laborious. The purpose of this research is to employ Artificial Neural Network (ANN) to predict the optimum design parameters for such wall systems while avoiding the demanding iterative process. The developed ANN model is very accurate in predicting the nondimensional optimum design parameters related to post-tensioning reinforcement area, yield force of shear connectors and ratio of moment resisted by shear connectors to the design moment. The Mean Absolute Percent Error (MAPE) for the test data for these design parameters is around %1 and the correlation coefficient is almost equal to 1.0. The developed ANN model is then used to study the effect of different design parameters on wall behavior. It is observed that the design moment and the concrete strength have the most influence on the wall behavior as compared to other parameters. Several design examples were presented to demonstrate the accuracy and effectiveness of the ANN model.

• Transactions of the Korean Society of Mechanical Engineers
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• v.14 no.6
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• pp.1464-1473
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• 1990

Optimal design parameters are estimated from the sensitivity function and performance index variation. Suspension design modification for performance improvement and basic materials for practical applications are presented. The linear quarter model of a vehicle suspension is analyzed in order to represent the utilities of sensitivity analysis, and sensitivity function is determined in the frequency domain. The change of frequency response function is predicted, which depends on the design parameter variation and the property is verified by computer simulation. As an investigation results of sensitivity function for the vibrational amplitude of sprung mass to road profile input, it is shown that the most sensitive parameters are the suspension damping and the suspension stiffness. In order to identify the effects of these two parameters to the performance of suspension system, the performance index variation according to the changes of parameters is considered and then optimal design parameters are determined. It is verified that the system response is improved noticeably in the both of frequency and time domain after the design modification with the optimal parameters.