• Proceedings of the Computational Structural Engineering Institute Conference
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• 2001.04a
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• pp.154-161
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• 2001

A procedure of the design optimization for steel box girder bridges using micro genetic algorithms(μGA) is developed. The effect of population size is investigated and the efficiency and reliability of μGA is demonstrated in the optimum design of steel box girder bridges. Optimum design problems of steel box girder bridges are formulated, where tile design of concrete slab is based on the USD specifications and steel box girder based on LRFD respectively. Design of optimizations of single-span and 2-span steel box girder bridges are performed with the population size of 5, 40, 80, and 120, respectively The μGA-based optimum design of the 3-span steel box girder bridge is compared with SQP results.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2007.11a
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• pp.571-572
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• 2007

• Journal of the KSME
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• v.54 no.2
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• pp.28-34
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• 2014

이 글에서는 신뢰성 기반 최적설계(RBDO: Reliability-Based Design Optimization)의 필요성을 설명하고, RBDO를 위해 필요한 기술을 소개하며, RBDO기술이 산업계에 적용되는 사례연구를 통해 기술적 어려움과 향후 연구방향을 제시하고자 한다.

• 한국항공운항학회:학술대회논문집
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• 2005.11a
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• pp.227-232
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• 2005

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2009.04a
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• pp.430-435
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• 2009

• Tribology and Lubricants
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• v.39 no.3
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• pp.94-101
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• 2023

Automotive wheel bearings are a critical component of vehicles that support their weight and facilitate rotation. Life and stiffness are significant performance characteristics of wheel bearings. Designing wheel bearings involves finding optimal design variables that satisfy both performances. CO₂ emission reduction and fuel efficiency regulations attribute to the recent increase in design requirements for lightweight and compact automotive parts while maintaining performance. However, achieving a design that maintains performance while reducing weight poses challenges, as performance and weight are generally inversely proportional. In this study, we perform design optimization of automotive wheel bearings considering life and stiffness. We develop a program that calculates the basic rated life and modified rated life based on international standards for evaluating the life of wheel bearings. We develop a regression equation using regression analysis to address the time-consuming stiffness analysis during repetitive analysis. We perform ANOVA and main effect analyses to understand the statistical characteristics of the developed regression equation. Furthermore, we verify its reliability by comparing the predicted and test results. We perform design optimization using the developed life prediction program, stiffness regression equation and weight regression equation. We select bearing specifications and geometry as design variables, weight as the cost function, and life and stiffness as constraints. Through design optimization, we investigate the influence of design variables on the cost function and constraints by comparing the initial and optimal design values.

• Journal of Electrical Engineering and Technology
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• v.8 no.4
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• pp.780-786
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• 2013

In the reliability-based design optimization of electromagnetic devices, the accurate and efficient reliability assessment method is very essential. The first-order sensitivity-assisted Monte Carlo Simulation is proposed in the former research. In order to improve its accuracy for wide application, in this paper, the second-order sensitivity analysis is presented by using the hybrid direct differentiation-adjoint variable method incorporated with the finite element method. By combining the second-order sensitivity with the Monte Carlo Simulation method, the second-order sensitivity-assisted Monte Carlo Simulation algorithm is proposed to implement reliability calculation. Through application to one superconductor magnetic energy storage system, its accuracy is validated by comparing calculation results with other methods.

• Journal of Korean Society for Quality Management
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• v.43 no.3
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• pp.373-382
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• 2015

Purpose: In this paper, we developed a reliability index (RI) to efficiently compare reliability of products based on the design, development and production information such as reliability tests, quality, product life-cycle management. RI also can be applied to reliability prediction of a novel product as well as comparison evaluation among existing products. Methods: For evaluating RI, we proposed evaluation process which is composed of five steps. Target modules are selected based on warranty data and correlation analysis. Scores of selected target modules are calculated by scoring function. Finally, weights of RI model are determined by optimization method. Results: This paper presented an empirical analysis based on failure data of mobile devices. In this case study, we demonstrated that there is a direct correlation between evaluated RI and field failure probability of each product. Conclusion: We proposed the index for comprehensive and effective assessment of product reliability level. From the procedure of this study, we expected to be applied for reliability estimation of novel products and deduction of field failure-related factors.

• Proceedings of the Korean Society of Propulsion Engineers Conference
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• 2008.03a
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• pp.330-339
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• 2008

Ground-based interceptors(GBI) comprise a major element of the strategic defense against hostile targets like Intercontinental Ballistic Missiles(ICBM) and reentry vehicles(RV) dispersed from them. An optimum design of the subsystems is required to increase the performance and reliability of these GBI. Propulsion subsystem design and optimization is the motivation for this effort. This paper describes an effort in which an entire GBI missile system, including a multi-stage solid rocket booster, is considered simultaneously in a Genetic Algorithm(GA) performance optimization process. Single goal, constrained optimization is performed. For specified payload and miss distance, time of flight, the most important component in the optimization process is the booster, for its takeoff weight, time of flight, or a combination of the two. The GBI is assumed to be a multistage missile that uses target location data provided by two ground based RF radar sensors and two low earth orbit(LEO) IR sensors. 3Dimensional model is developed for a multistage target with a boost phase acceleration profile that depends on total mass, propellant mass and the specific impulse in the gravity field. The monostatic radar cross section (RCS) data of a three stage ICBM is used. For preliminary design, GBI is assumed to have a fixed initial position from the target launch point and zero launch delay. GBI carries the Kill Vehicle(KV) to an optimal position in space to allow it to complete the intercept. The objective is to design and optimize the propulsion system for the GBI that will fulfill mission requirements and objectives. The KV weight and volume requirements are specified in the problem definition before the optimization is computed. We have considered only continuous design variables, while considering discrete variables as input. Though the number of stages should also be one of the design variables, however, in this paper it is fixed as three. The elite solution from GA is passed on to(Sequential Quadratic Programming) SQP as near optimal guess. The SQP then performs local convergence to identify the minimum mass of the GBI. The performance of the three staged GBI is validated using a ballistic missile intercept scenario modeled in Matlab/SIMULINK.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.42 no.3
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• pp.299-309
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• 2022

This paper presents a new class of the vehicular live load factor for a reliability-based bridge design code. The significance of the current vehicular live load factor of 1.8 is investigated based on the return period of the vehicular live load and the design life of a bridge. It is shown that the current vehicular live load factor corresponds to a return period of 6.7 million years for a 100-year design life, which seems to be unrealistic in an engineering sense, and that the target reliability of 3.72 is set to too high without any reasoning for the gravitational load-governed limit state compared with that of the other limit states. In case the same return period as the design wind velocity or the ground acceleration is employed for the vehicular live load, the corresponding vehicular live load factor becomes around 1.15, and the target reliability index for the return period may be selected as 2.0 or 2.5 depending on the governing load effect. The complete sets of the load-resistance factors for the proposed target reliability indices are evaluated through optimization.