• Steel and Composite Structures
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• 제49권6호
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• pp.633-643
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• 2023

In this study, the natural frequencies of Functional Graded Materials (FGM) plates are predicted using Artificial Neural Network (ANN). A model based on Third-order Shear Deformation Theory (TSDT) and FEM is used to train the ANN model. Different training methods are tested to simulate input and output dependency. As this is a parametric model, several architectures and optimization algorithms were tested. The proposed model allows us to minimize the CPU time to evaluate candidate material properties for FGM plate material selection and demonstrate their influence on dynamic behavior. Consequently, the time required for the FGM design process (candidate materials for material selection) and the geometric optimization of the FGM structure would remain reasonable. The ANN model can help industries to produce FGM plates with good mechanical properties of the selected materials. I addition, this model can be used to directly predict vibration behavior by testing a large number of FGM plates, representing all possible combinations of metals and ceramics in today's industry, without having to solve any eigenvalue problems.

• Journal of applied mathematics & informatics
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• 제15권1_2호
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• pp.173-184
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• 2004

In this paper, we find the approximate solution of a second order nonlinear partial differential equation on a simple connected region in $R^2$. We transfer this problem to a new problem of second order nonlinear partial differential equation on a rectangle. Then, we transformed the later one to an equivalent optimization problem. Then we consider the optimization problem as a distributed parameter system with artificial controls. Finally, by using the theory of measure, we obtain the approximate solution of the original problem. In this paper also the global error in $L_1$ is controlled.

• Smart Structures and Systems
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• 제19권4호
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• pp.351-360
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• 2017

Protection of structures against natural hazards such as earthquakes has always been a major concern. Semi-active control combines the reliability of passive control and versatility and adaptability of active control. So it has recently become a preferred control method. This paper proposes an algorithm based on Uniform Deformation Theory to mitigate vulnerable buildings using magneto-rheological (MR) damper. Due to the successful performance of fuzzy logic in control of systems and its simplicity and intrinsically robustness, it is used here to regulate MR dampers. The particle swarm optimization (PSO) algorithm is also used as an adaptive method to develop a fuzzy control algorithm that is able to create uniform inter-story drifts. Results show that the proposed algorithm exhibited a desirable performance in reducing both linear and nonlinear seismic responses of structures. Performance of the presented method is indicated in compare with passive-on and passive-off control algorithms.

• Journal of the Korean Society of Manufacturing Process Engineers
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• 제11권2호
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• pp.125-136
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• 2012

Wrinkle and fracture are two major defects frequently found in the sheet metal forming process. In this process there are more than one design attributes to optimize and several uncontrollable factors which cannot be ignored in determining the optimal values of design variables. Therefore, attempts to reduce defects through a traditional optimization technique are often led to failures. In this research, a new design method for reducing the wrinkle and fracture under uncontrollable factors is presented by using decision-making theory. To avoid the psychological difficulties in determining the scaling constants of the multi-attribute utility function by using the ordinary lottery questions, a pair-wise comparison procedure is adapted to avoid this problem. The effectiveness of the proposed method is illustrated through a robust design of sheet metal forming process of a side member of an automotive body.

• The Transactions of the Korean Institute of Electrical Engineers A
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• 제48권2호
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• pp.82-88
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• 1999

In this paper, we propose a new structure optimization method of multilayer neural networks which begin and carry out learning from a bigger network. This method redundant links and neurons according to the rough set theory. In order to find redundant links, we analyze the variations of all weights and output errors in every step of the learning process, and then make the decision table from their variation of weights and output errors. We can find the redundant links from the initial structure by analyzing the decision table using the rough set theory. This enables us to build a structure as compact as possible, and also enables mapping between input and output. We show the validity and effectiveness of the proposed algorithm by applying it to the XOR problem.

• Journal of the Korean Society of Manufacturing Technology Engineers
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• 제8권2호
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• pp.27-34
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• 1999

The growth-strain method was used for shape optimization, which carries out the optimization by distributing uniformly the distributed parameter such as von Mises stress and shear strain energy density. Shape optimization is carried out by iteration of stress analysis and growth strain analysis. In this study, the effect of growth ratio in the method was investigated and then the range of the adequate value of the growth ratio was determined. Also the growth-strain method was improved by applying the linear PID control theory in order to control volume required by a designer. Finally, an automatic shape optimization system was built up by the improved growth-strain method with a commercial software using finite element method. The effectiveness and practicability of the developed shape optimization system was verified by some examples.

• Steel and Composite Structures
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• 제27권2호
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• pp.177-184
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• 2018

This study contributes to evaluate multiphase topology optimization design of plate-like structures on elastic foundations by using classic plate theory. Multi-material optimal topology and shape are produced as an alternative to provide reasonable material assignments based on stress distributions. Multi-material topology optimization problem is solved through an alternative active-phase algorithm with Gauss-Seidel version as an optimization model of optimality criteria. Stiffness and adjoint sensitivity formulations linked to thin plate potential strain energy are derived in terms of multiphase design variables and Winkler-Pasternak parameters considering elastic foundation to apply to the current topology optimization. Numerical examples verify efficiency and diversity of the present topology optimization method of elastic thin plates depending on multiple materials and Winkler-Pasternak parameters with the same amount of volume fraction and total structural volume.

• The Transactions of the Korean Institute of Electrical Engineers B
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• 제54권4호
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• pp.163-173
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• 2005

The conventional optimization study for electromagnetic systems has been mostly on the shape or size optimization. The goal for these optimization methods is to improve performance of electromagnetic systems by optimizing the interface shape of two different materials while their given layout or initial topology are held. The feasible topology can be diverse and an appropriate topology will give much better design results. In this paper we propose a theory and an algorithm for topology optimization of electromagnetic systems, which are based on the finite element method. The topology optimization technique employes a direct searching method of sensitivity analysis in which the information of material sensitivity is used. Two numerical examples of a switched reluctance motor and an electrostatic actuator of MEMS are tested and their design results show that the optimization method is valid and useful for the topology and basic layout design of electromagnetic systems.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 한국소음진동공학회 2006년도 추계학술대회논문집
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• pp.934-937
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• 2006

This investigation presents a topology formulation to design optimal poroelastic acoustic foams to maximize absorbing ability. For successful formulation, a single set of equations based on Biot's theory is adopted and an appropriate material interpolation strategy is newly developed. Because there was no earlier attempt to solve poroelastic acoustic foam design problems in topology optimization setting, many challenging issues including modeling and interpolation must be addressed. First, the simulation accuracy by a proposed unified model encompassing acoustic air and poroelastic material was checked against analytical and numerical results. Then a material interpolation scheme yielding a distinct acoustic air-poroelastic material distribution was developed. Using the proposed model and interpolation scheme, the topology optimization of a two-dimensional poroelastic acoustic foam for maximizing its absorption coefficient was carried out. Numerical results show that the absorption capacity of an optimized foam layout considerably increases in comparison with a nominal foam layout.

• Journal of Electrical Engineering and Technology
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• 제6권6호
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• pp.750-759
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• 2011

This paper focuses on the control of bidirectional power flow in the electric shipboard power systems, especially in the Medium-Voltage Direct Current (MVDC) shipboard power system. Bidirectional power control between the main MVDC bus and the local zones can improve the energy efficiency and control flexibility of electric ship systems. However, since the MVDC system contains various nonlinear loads such as pulsed power load and radar in various subsystems, the voltage of the MVDC and the local zones varies significantly. This voltage variation affects the control performance of the bidirectional DC-DC converters as exogenous disturbances. To improve the control performance regardless of uncertainties and disturbances, this paper proposes a novel controller design method of the bidirectional DC-DC converters using $L_1$ control theory and intelligent optimization algorithm. The performance of the proposed method is verified via large-scale real-time digital simulation of a notional shipboard MVDC power system.