• 한국전산구조공학회:학술대회논문집
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• 한국전산구조공학회 2010년도 정기 학술대회
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• pp.476-479
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• 2010

In recent years, the deterioration of infrastructures is especially considered. In prestress concrete bridges, one of the important mechanisms of deterioration is the corrosion of the post-tensioned tendon due to environmental agents. In this study, the reliability analysis is performed for a prestress concrete box girder bridge under the pitting corrosion attack with considering the inspection and failure cost. The variation of life-time performance depending on inspection methods have to be quantified. The inspection methods with different accuracy of corrosion detection are presented and applied for model of reliability analysis. The computer program for analysis reliability index of the structure as well as updating process is obtained. An existing bridge is applied for illustrating the influence of inspection cost on the behaviors of structure. Subsequently, the benefit of inspection has shown to predict the time to failure of structure.

• Structural Engineering and Mechanics
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• 제55권5호
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• pp.979-999
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• 2015

This paper proposes a novel reliability analysis method which computes reliability index, most probable point and probability of failure of uncertain systems more efficiently and accurately with compared to Monte Carlo, first-order reliability and response surface methods. It consists of Initial and Simulation steps. In Initial step, a number of space-filling designs are selected throughout the variables space, and then in Simulation step, performances of most of samples are estimated via interpolation using the space-filling designs, and only for a small number of the samples actual performance function is used for evaluation. In better words, doing so, we use a simple interpolation function called "reduced" function instead of the actual expensive-to-evaluate performance function of the system to evaluate most of samples. By using such a reduced function, total number of evaluations of actual performance is significantly reduced; hence, the method can be called Reduced Function Evaluations method. Reliabilities of six examples including series and parallel systems with multiple failure modes with truncated and/or non-truncated random variables are analyzed to demonstrate efficiency, accuracy and robustness of proposed method. In addition, a reliability-based design optimization algorithm is proposed and an example is solved to show its good performance.

• 한국안전학회지
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• 제35권1호
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• pp.25-33
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• 2020

In most plant layout optimization researches, MILP(Mixed Integer Linear Programming) problems, in which the objective function includes the costs of pipelines connecting process equipment and cost associated with safety issues, have been employed. Based on these MILP problems, various optimization solvers have been applied to investigate the optimal solutions. To consider safety issues on the objective function of MILP problems together, the accurate information about the impact and the frequency of potential accidents in a plant should be required to evaluate the safety issues. However, it is really impossible to obtain accurate information about potential accidents and this limitation may reduce the reliability of a plant layout problem. Moreover, in real industries such as plant engineering companies, the plant layout is previously fixed and the considerations of various safety instruments and systems have been performed to guarantee the plant safety. To reflect these situations, the two step optimization problems have been designed in this study. The first MILP model aims to minimize the costs of pipelines and the land size as complying sufficient spaces for the maintenance and safety. After the plant layout is determined by the first MILP model, the optimal locations of blast walls have been investigated to maximize the mitigation impacts of blast walls. The particle swarm optimization technique, which is one of the representative sampling approaches, is employed throughout the consideration of the characteristics of MILP models in this study. The ethylene oxide plant is tested to verify the efficacy of the proposed model.

• Journal of Power Electronics
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• 제18권3호
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• pp.841-852
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• 2018

This paper presents a dual-algorithm search method (GWO-GSO) combining grey wolf optimization (GWO) and golden-section optimization (GSO) to realize maximum power point tracking (MPPT) for photovoltaic (PV) systems. First, a modified grey wolf optimization (MGWO) is activated for the global search. In conventional GWO, wolf leaders possess the same impact on decision-making. In this paper, the decision weights of wolf leaders are automatically adjusted with hunting progression, which is conducive to accelerating hunting. At the later stage, the algorithm is switched to GSO for the local search, which play a critical role in avoiding unnecessary search and reducing the tracking time. Additionally, a novel restart judgment based on the quasi-slope of the power-voltage curve is introduced to enhance the reliability of MPPT systems. Simulation and experiment results demonstrate that the proposed algorithm can track the global maximum power point (MPP) swiftly and reliably with higher accuracy under various conditions.

• 대한기계학회논문집A
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• 제24권12호
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• pp.3053-3060
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• 2000

Alternative formulation is presented for robust optimization problems and an efficient computational scheme for reliability estimation is proposed. Both design variables and design parameters considered as random variables about their nominal values. To ensure the robustness of objective performance a new cost function bounding the performance and a new constraint limiting the performance variation are introduced. The constraint variations are regulated by considering the probability of feasibility. Each probability constraint is transformed into a sub-optimization problem and then is resolved with the modified advanced first order second moment(AFOSM) method for computational efficiency. The proposed robust optimization method has advantages that the mean value and the variation of the performance function are controlled simultaneously and the second order sensitivity information is not required even in case of gradient based optimization. The suggested method is examined by solving three examples and the results are compared with those for deterministic case and those available in literature.

• 한국정밀공학회지
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• 제26권1호
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• pp.138-145
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• 2009

High-efficiency and high-quality machining has become a fact of life for numerous machine shops in recent years. And high-efficiency machining is the most significant tool to enhance productivity. In this study, to achieve high-efficiency machining in turning process, a spindle speed optimization method was proposed based on a cutting power model. The cutting force and power were estimated from the cutting parameters such as specific cutting force, feed, depth of cut, and spindle speed. The time delay due to the acceleration or deceleration of spindle was considered to predict a more accurate machining time. Especially, the good agreement between the predicted and measured cutting forces showed the reliability of the proposed optimization method, and the effectiveness of the proposed optimization method was demonstrated through the simulation results associated with the productivity enhancement in turning process

• Tribology and Lubricants
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• 제39권3호
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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.

• 한국신뢰성학회지:신뢰성응용연구
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• 제10권2호
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• pp.149-160
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• 2010

This paper presents a study of an availability evaluation for I&C(Instrumentation and Control) System which it applied for nuclear power plant. The system availability assessment have been implemented to the reactor protection system by the adoption of Markov process. Results are satisfied to the requirement of EPRI and APR1400. Based on the research of I&C system assessment, it will contribute to improve the availability of system and impact the design concept with new design optimization.

• 한국지반공학회:학술대회논문집
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• 한국지반공학회 2010년도 춘계 학술발표회
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• pp.427-434
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• 2010

Load Resistance Factor Design method is used increasingly in geotechnical design world widely and resistance factors for drilled shafts are suggested by AASHTO. However, these resistance factors are determined for intact rock conditions, by comparison most of bedrocks in Korea are weathered condition, so that applying the AASHTO resistance factors is not reasonable. Thus, this study suggests the proper resistance factors for design of drilled shaft in Korea. The 22 cases of pile load test data from 8 sites were chosen and reliability-based approach is used to analyze the data. Reliability analysis was performed by First Order Second Moment Method (FOSM) applying 4 bearing capacity equations. As a result, when the Factor of Safety(FOS) were selected as 3.0, the target reliability index($\beta_c$) were evaluated about 2.01~2.30. Resistance factors and load factors are determined from optimization based on above results. The resistance factors ranged between 0.48 and 0.56 and load factor for dead load and live load are evaluated approximately 1.25 and 1.75 respectively. However, when the target reliability are considered as 3.0, the resistance factors are evaluated as approximately 50% of results when the target reliability index were 2.0.

• Journal of Magnetics
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• 제19권4호
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• pp.378-384
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• 2014

Optimization design and robust design are significant measures for improving the performance and reliability of electromagnetic devices (EMDs, specifically refer to relays, contactors in this paper). However, the implementation of the above-mentioned design requires substantial calculation; consequently, on the premise of guaranteeing precision, how to improve the calculation speed is a problem that needs to be solved. This paper proposes a new method for establishing an approximate model for the EMD. It builds a relationship between the input and output of the EMD with different coil voltages and air gaps, by using a user-defined interpolating function. The coefficient of the fitting function is determined based on a quantum particle swarm optimization (QPSO) method. The effectiveness of the method proposed in this paper is verified by the electromagnetic force calculation results of an electromagnetic relay with permanent magnet.