• 대한조선학회논문집
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• 제37권1호
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• pp.118-126
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• 2000

저자들에 의해 기 제안한 바 있는 일반화 경사처짐법을 이용하여 이중 선각 유조선의 최적 구조 설계 시스템을 개발하였다. 최적화 기법으로는 직접탐색법의 일종인 Hooke와 Jeeves 방법을 사용하여 이산화변수를 용이하게 처리할 수 있도록 하였다. 일반화 경사처짐법과 최적화 기법을 결합하여 선급규정에 의한 종강도 부재의 최소 중량 설계프로그램과 일반화 경사처짐법에 의한 횡강도 부재 및 횡격벽 부재의 최소 중량 설계 프로그램을 개발하였다. 개발한 프로그램을 이용하여 tank 배치를 고려한 이중 선각 유조선의 최적 구조 설계를 수행하여 실적선의 설계 치수 및 선각 중량과 비교하였으며, 최소 중량을 주는 tank 배치와 tank type을 결정할 수 있었다.

• 한국복합재료학회:학술대회논문집
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• 한국복합재료학회 2000년도 춘계학술발표대회 논문집
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• pp.154-157
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• 2000

Distributed piezoelectric sensor and actuator system has been designed for the active vibration control of shell structure. PVDF is used for the materials of sensor/actuator. To prevent the adverse effect of spillover, distributed modal sensor/actuator system is established. Although shell structure is three-dimensional structure, the PVDF sensor/actuator system can be treated as two-dimensional Finite element programs are developed to consider curved structures having PVDF modal sensor/actuator. The nine-node Mindlin shell element with five nodal degree of freedoms is used for finite element discretization. The electrode patterns and lamination angle of PVDF sensor/actuator are optimized to design the modal sensor/actuator system Genetic algorithm is used for optimization. Sensor is designed to minimize the observation spillover, and actuator is designed to minimize the system energy of the control modes under a given initial condition. Modal sensor/actuator for the first and second modes of singly curved cantilevered shell structure are designed using mentioned methods. Discrete LQG method is used as a control law. Experimental demonstrations of the active vibration control with designed sensor/actuator system have been performed successfully.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제10권9호
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• pp.4405-4418
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• 2016

Automatic image completion techniques have difficulty processing images in which the target region has multiple planes or is non-facade. Here, we propose a new image completion method that uses belief propagation based on planar priorities. We first calculate planar information, which includes planar projection parameters, plane segments, and repetitive regularity extractions within the plane. Next, we convert this planar information into planar guide knowledge using the prior probabilities of patch transforms and offsets. Using the energy of the discrete Markov Random Field (MRF), we then define an objective function for image completion that uses the planar guide knowledge. Finally, in order to effectively optimize the MRF, we propose a new optimization scheme, termed Planar Priority-belief propagation that includes message-scheduling-based planar priority and dynamic label cropping. The results of experiment show that our approach exhibits advanced performance compared with existing approaches.

• Journal of Power Electronics
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• 제14권2호
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• pp.351-361
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• 2014

The discrete torque generation mechanism and inherently nonlinear magnetic characterization of switched reluctance motors lead to unacceptable torque ripples and limit the application of these motors. In this study, a phase current profiling technique and torque sharing function are proposed in consideration of magnetic saturation effects and by minimizing power loss in the commutation area between the adjacent phases. Constant torque trajectories are considered in incoming and outgoing phase current planes based on nonlinear T-i-theta curves obtained from experimental measurements. Optimum points on constant torque trajectories are selected by improving drive efficiency and minimizing copper loss in each rotor position. A novel analytic invertible function is introduced to express phase torque based on rotor position and its corresponding phase current. The optimization problem is solved by the proposed torque function, and optimum torque sharing functions are derived. A modification method is also introduced to enhance the torque ripple-free region based on simple logic rules. Compared with conventional torque sharing functions, the resultant reference current from the proposed method has less peak and effective values and exhibits lower copper loss. Experimental and simulation results from a four-phase 4 KW 8/6 SRM validate the effectiveness of the proposed method.

• Composites Research
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• 제13권2호
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• pp.40-50
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• 2000

종횡비가 다른 적층복합재료에 경사형 구조를 도입하고, 이것이 일방향으로의 하중을 받을 때의 좌굴특성을 최대화하기 위해서 복합재료의 각 층에서의 섬유부피분율과 두께를 변수로 sequential linear programming method를 이용하여 최적화 하였다. 이로부터 좌굴특성을 최대화 할 수 있는 최적구조를 제안하였다. 적층복합재료는 종횡비의 영향이 커서 종횡비가 1보다 작은 경우는 최외각층의 섬유부피분율을 최대화하는 방향으로 최적화가 이루어졌으나 종횡비가 2인 경우는 각층에서의 섬유부피분율과 두께비가 어느 정도 균형을 이루는 형태로 최적화가 이루어 졌다. 경사형 구조는 전통적인 균일구조의 복합재료에 비해서 섬유부피와 복합재료의 무게 절감에 큰 효과를 가지는 것으로 확인되었다.

• 대한산업공학회지
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• 제41권2호
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• pp.173-184
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• 2015

The application of radio frequency identification (RFID) sensor-tags in cold chain systems has recently received a great deal of attention. To design cold chain systems with RFID sensor-tags that minimize the initial investment and operational cost while fulfilling the functional and operational requirements, simulation study is one of the preferable and effective approaches. To simulate the possible design configurations, the individual components in a cold chain system can be extracted and implemented as a DEVS (Discrete Event System Specification) model. Based on the proposed DEVS model, a new cold chain simulation model can be efficiently created by simply connecting each DEVS model around the RFID sensor-tag of interest in sequence according to the structure of the cold chain system, and then executed (or simulated) on Java programming environments by the DEVSJAVA simulator. As a result of simulation, some key performance indexes such as reliability, accuracy or timeliness can be calculated and used to choose better components or to compare different system configurations of cold chain systems.

• Structural Engineering and Mechanics
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• 제35권1호
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• pp.19-35
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• 2010

This paper proposes a hybrid heuristic and criteria-based method of optimum design which combines the advantages of both the iterated simulated annealing (SA) algorithm and the rigorously derived optimality criteria (OC) for structural optimum design of reinforced concrete (RC) buildings under multi-load cases based on the current Chinese design codes. The entire optimum design procedure is divided into two parts: strength optimum design and stiffness optimum design. A modified SA with the strategy of adaptive feasible region is proposed to perform the discrete optimization of RC frame structures under the strength constraints. The optimum stiffness design is conducted using OC method with the optimum results of strength optimum design as the lower bounds of member size. The proposed method is integrated into the commercial software packages for building structural design, SATWE, and for finite element analysis, ANSYS, for practical applications. Finally, two practical frame-shear-wall structures (15-story and 30-story) are optimized to illustrate the effectiveness and practicality of the proposed optimum design method.

• 한국경영과학회지
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• 제41권3호
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• pp.23-36
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• 2016

We consider a model that minimizes the total cost incurred by assigning available weapons to existing targets in order to reduce enemy threats, which is called the weapon target assignment problem (WTAP). This study addresses the stochastic versions of WTAP, in which data, such as the probability of destroying a target, are given randomly (i.e., data are identified with certain probability distributions). For each type of random data or parameter, we provide a stochastic optimization model on the basis of the expected value or scenario enumeration. In particular, when the probabilities of destroying targets depending on weapons are stochastic, we present a stochastic programming formulation with a simple recourse. We show that the stochastic model can be transformed into a deterministic equivalent mixed integer programming model under a certain discrete probability distribution of randomness. We solve the stochastic model to obtain an optimal solution via the mixed integer programming model and compare this solution with that of the deterministic model.

• 대한기계학회논문집A
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• 제28권7호
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• pp.1038-1046
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• 2004

In order to acquire high-speed and high-precision performances in servomechanisms, an integrated design method have been proposed. Based on strict mathematical modeling and analysis of system performance according to design and operating parameters, a nonlinear constrained optimization problem including the relevant subsystem parameters of the servomechanism is formulated. Optimum design results of mechanical and electrical parameters are obtained according to the design parameters specified by designers through the integrated design processes. Motors are optimally selected from the servo motor database. Both the geometric errors referring to Abbe offset and the contour errors are minimized while required constraints such as stability conditions and saturated conditions are satisfied. This design methodology both offers the improved possibility to evaluate and optimize the dynamic motion performance of the servomechanism and improves the quality of the design process to achieve the required performance for high-speed/precision servomechanisms.

• International Journal of Control, Automation, and Systems
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• 제2권2호
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• pp.256-262
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• 2004

Conventionally, profile non-uniformity has been characterized by relying on approximated profile with angle or anisotropy. In this study, a new non-uniformity model for etch profile is presented by applying a discrete wavelet to the image obtained from a scanning electron microscopy (SEM). Prediction models for wavelet-transformed data are then constructed using a back-propagation neural network. The proposed method was applied to the data collected from the etching of tungsten material. Additionally, 7 experiments were conducted to obtain test data. Model performance was evaluated in terms of the average prediction accuracy (APA) and the best prediction accuracy (BPA). To take into account randomness in initial weights, two hundred models were generated for a given set of training factors. Behaviors of the APA and BPA were investigated as a function of training factors, including training tolerance, hidden neuron, initial weight distribution, and two slopes for bipolar sig-moid and linear function. For all variations in training factors, the APA was not consistent with the BPA. The prediction accuracy was optimized using three approaches, the best model based approach, the average model based approach and the combined model based approach. Despite the largest APA of the first approach, its BPA was smallest compared to the other two approaches.