• Transactions of the Korean Society of Automotive Engineers
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• v.5 no.2
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• pp.111-119
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• 1997

The operating characteristics of the check valve in the clutch piston of an automatic transmission have a great effect on the shifting performance. This paper addresses the modeling, dynamic analysis, and optimization of the check valve. It was found that the vortex causes a pressure drop, which is related to the rotating speed of the clutch piston, oil volume discharged from the check valve, and valve geometry. Maximizing the oil volume discharged, geometry of the check valve is optimized. The results can be used to design an improved check valve which provides a suitable oil pressure curves for achieving smoother shifting.

• Proceedings of the Korean Society For Composite Materials Conference
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• 2000.11a
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• pp.169-172
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• 2000

Although extensive efforts have been devoted to the optimal design of composite laminated plates in recent years, some practical issues still need further research. One of them is the handling of the uncertainties in material properties, which were ignored in most researches in the past. In this paper, the convex modeling is used in calculating the failure criterion, given as constraint, to consider the uncertain material properties in the thickness optimization. Numerical results show that the optimal thickness increases when the uncertainties of elastic moduli considered, which shows such uncertainties should not be ignored for safe and reliable designs.

• Proceedings of the KSME Conference
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• 2004.04a
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• pp.733-738
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• 2004

This paper deals with feedback control of a hydraulic unit for direct yaw moment control, a method used to actively maintain the dynamic stability of an automobile. The uncertain parameters and complex structure naturally call for empirical modeling of the hydraulic unit, which readily results in a control-oriented model with high fidelity. The identified model is cross-validated against experimental data under various conditions, which helps to establish model uncertainty. Then, the $H_{\infty}$ optimization technique is employed to synthesize a controller with guaranteed robust stability and performance against the model uncertainty. The performance of the synthesized controller is verified using experimental results, which shows the viability of the proposed approach in a real-world application.

• Proceedings of the KIEE Conference
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• 1999.07g
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• pp.2911-2913
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• 1999

This paper suggest an optimal identification method to complex and nonlinear system modeling that is based on Fuzzy-Neural Network(FNN). The FNN modeling implements parameter identification using HCM algorithm and optimal identification algorithm structure combined with two types of optimization theories for nonlinear systems, we use a HCM Clustering Algorithm to find initial parameters of membership function. The parameters such as parameters of membership functions, learning rates and momentum coefficients are adjusted using optimal identification algorithm. The proposed optimal identification algorithm is carried out using both a genetic algorithm and the improved complex method. Also, an aggregate objective function(performance index) with weighted value is proposed to achieve a sound balance between approximation and generalization abilities of the model. To evaluate the performance of the proposed model, we use the time series data for gas furnace, the data of sewage treatment process and traffic route choice process.

• Proceedings of the KIEE Conference
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• 2003.07d
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• pp.2040-2042
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• 2003

In this paper, we propose a new method about wavelet-based fuzzy modeling using a DNA coding method. DNA coding techniques is known that expression of knowledge is various than Genetic Algorithm(GA) usually by made optimization technique because done base in structure of biologic DNA and optimization performance is superior. The reposed method make fuzzy system model in wavelet transform and equivalence relation after identification with coefficient of wavelet transform using a DNA coding techniques. Also, can get fuzzy model effectively of nonlinear system using advantage of strong wavelet transform about function that have sudden change. In this paper, in order to demonstrate the superiority of the proposed method compared with GA.

• Proceedings of the Korean Powder Metallurgy Institute Conference
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• 2006.09a
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• pp.362-363
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• 2006

Nano-structured tungsten carbide compacts with cobalt matrices (WC-Co) offer new opportunities for achieving superior hardness and toughness combinations. A unified modeling and simulation tool has been developed to produce maps of sintering pathways from nanocrystalline WC powder to sintered nano-structured WC-Co compacts. This tool includes (1) die compaction, (2) grain growth, (3) densification, (4) sensitivity analysis, and (5) optimization. All material parameters were obtained by curve fitting based on results with two WC-Co powders. Critical processing parameters are determined based on sensitivity analysis and are optimized to minimize grain size with high density.

• Nuclear Engineering and Technology
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• v.53 no.9
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• pp.2953-2959
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• 2021

A new practical modeling of the Norton's power law creep is proposed and implemented to analyze the high temperature behaviors of Alloy 690 SG tube material. In the model, both the stress exponent n and the rate constant B are simply treated as the temperature dependent parameters. Based on the two-step optimization procedure, the temperature function of the rate constant B(T) was determined for the data set of each B value after fixing the stress exponent n value by using the prior optimized function at each temperature. This procedure could significantly reduce the numerical errors when using the power law creep equations. Based on the better description of the steady-state creep rates, the experimental rupture times could also be well predicted by using the Monkman-Grant relationship. Furthermore, the difference in tensile strengths at high temperatures could be very well estimated by assuming the imaginary creep stress related to the given strain rate after correcting the temperature effects on the elastic modulus.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.30 no.7
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• pp.113-122
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• 2002

Control system modeling and optimal bending filter design for KSR-III (Korea Sounding Rocket III) are performed. Rigid rocket dynamics, aerodynamics, sloshing, structural bending, actuator dynamics, sensor dynamics and on-board computer characteristics are considered for control system modeling. Compensation for time-varying control system parameters is conducted by gain-scheduling. A filter to stabilize bending mode is designed using parameter optimization technique. Resultant attitude control system can satisfy required frequency domain stability margin.

• Structural Engineering and Mechanics
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• v.66 no.2
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• pp.173-183
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• 2018

This paper proposes a developed optimization model for steel frames with semi-rigid beam-to-column connections and fixed bases using teaching-learning-based optimization (TLBO) and genetic algorithm (GA) techniques. This method uses rotational deformations of frame members ends as an optimization variable to simultaneously obtain the optimum cross-sections and the most suitable beam-to-column connection type. The total cost of members plus connections cost of the frame are minimized. Frye and Morris (1975) polynomial model is used for modeling nonlinearity of semi-rigid connections, and the $P-{\Delta}$ effect and geometric nonlinearity are considered through a stepped analysis process. The stress and displacement constraints of AISC-LRFD (2016) specifications, along with size fitting constraints, are considered in the design procedure. The developed model is applied to three benchmark steel frames, and the results are compared with previous literature results. The comparisons show that developed model using both LTBO and GA achieves better results than previous approaches in the literature.

• Journal of the Korean Society of Manufacturing Process Engineers
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• v.18 no.3
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• pp.74-81
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• 2019

Herein, we performed a comparative study on approximate multi-objective design optimization, to realize a structural design to improve the weight and vibration performances of the knuckle - a car suspension component - considering various load conditions and vibration characteristics. In the approximate multi-objective optimization process, a regression meta-model was generated using the response surfaces method (RSM), while Kriging and back-propagation neural network (BPN) methods were applied for interpolation meta-modeling. The Pareto solutions, multi-objective optimal solutions, were derived using the non-dominated sorting genetic algorithm (NSGA-II). In terms of the knuckle design considered in this study, the characteristics and influence of the meta-model on multi-objective optimization were reviewed through a comparison of the approximate optimization results with the meta-models and the actual optimization.