• Proceedings of the IEEK Conference
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• 1999.06a
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• pp.1033-1036
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• 1999

This paper proposes an efficient fault diagnosis for digital circuits using multilayer neural networks. The efficient learning algorithm is also proposed for the multilayer neural network, which is combined the steepest descent for high-speed optimization and the dynamic tunneling for global optimization. The fault-diagnosis system using the multilayer neural network of the proposed algorithm has been applied to the parity generator circuit. The simulation results shows that the proposed system is higher convergence speed and rate, in comparision with system using the backpropagation algorithm based on the gradient descent.

• The Transactions of the Korean Institute of Electrical Engineers
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• v.37 no.6
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• pp.368-375
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• 1988

This paper is concerned with the design of the optimal gains of the controller in the speed control system for the induction motor controlled by the microprocessor. The system is modelled with the discrete-time state equation, considering the time delay, for the facility of the optimization techniques. Introducing the conjugate gradient descent method, as the optimization technique, are derived the optimal gains, the gains which give the best transient characteristics. At the optimal gains obtained, the theoretcal transient responses are verified by experimental ones on a 5HP induction motor drive system.

• Journal of applied mathematics & informatics
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• v.28 no.5_6
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• pp.1239-1248
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• 2010

In this paper, an implementable BFGS bundle algorithm for solving a nonsmooth convex optimization problem is presented. The typical method minimizes an approximate Moreau-Yosida regularization using a BFGS algorithm with inexact function and the approximate gradient values which are generated by a finite inner bundle algorithm. The approximate subgradient of the objective function is used in the algorithm, which can make the algorithm easier to implement. The convergence property of the algorithm is proved under some additional assumptions.

• Journal of Sensor Science and Technology
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• v.27 no.4
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• pp.209-215
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• 2018

Recent research in animal behavior has shown that gradient information plays an important role in finding food and home. It is also important in optimization of performance because it indicates how the inputs should be adjusted for maximization/minimization of a performance index. We introduce perturbation as an additional input to obtain gradient information. Unlike the typical approach of calculating the gradient from the derivative, the proposed processing is very robust to noise since it is performed as a summation. Experimental results prove the validity of the process of spatial gradient acquisition. Quantitative indices for measuring the effect of the amplitude and the frequency are developed based on linear regression analysis. Drones are very useful for environmental monitoring and an autonomous path planning is required for unstructured environment. Guiding the drone for finding the origin of the interested physical property is done by estimating the gradient of the sensed value and generating the drone trajectories in the direction which maximizes the sensed value. Simulation results show that the proposed method can be successfully applied to identify the source of the physical quantity of interest by utilizing it for path planning of an autonomous drone in 3D environment.

• Computers and Concrete
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• v.24 no.4
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• pp.313-327
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• 2019

The purpose of the present study is to present a new approach to designing and selecting the details of multidimensional continuous RC beam by applying all strength, serviceability, ductility and other constraints based on ACI318-14 using Teaching Learning Based Optimization (TLBO) algorithm. The optimum reinforcement detailing of longitudinal bars is done in two steps. in the first stage, only the dimensions of the beam in each span are considered as the variables of the optimization algorithm. in the second stage, the optimal design of the longitudinal bars of the beam is made according to the first step inputs. In the optimum shear reinforcement, using gradient-based methods, the most optimal possible mode is selected based on the existing assumptions. The objective function in this study is a cost function that includes the cost of concrete, formwork and reinforcing steel bars. The steel used in the objective function is the sum of longitudinal and shear bars. The use of a catalog list consisting of all existing patterns of longitudinal bars based on the minimum rules of the regulation in the second stage, leads to a sharp reduction in the volume of calculations and the achievement of the best solution. Three example with varying degrees of complexity, have been selected in order to investigate the optimal design of the longitudinal and shear reinforcement of continuous beam.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.36 no.7
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• pp.739-744
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• 2012

The genetic algorithm (GA) is regarded as one of the best ways for determining a global solution. Because it does not require calculating the design sensitivity differently from the ordinary gradient-based method, it is appropriate for the design problem in the ultra-high frequency range; the ordinary gradient-based method has difficulty in calculating the sensitivity in this range. This paper deals with nano-aperture grating topology optimization based on the GA and the ON/OFF method. The objective of this study is to maximize the transmittance in the measuring area. The simulation and optimization processes are carried out by using the commercial package COMSOL associated with Matlab programming. The final optimal design gives around 21% performance improvement, compared with the initial model.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.30 no.4
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• pp.18-27
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• 2002

Aerodynamic shape optimization of two-dimensional airfoils in inviscid compressible flows is performed using a continuous adjoint formulation on unstructured meshes. Accurate evaluation of the gradient is achieved by using a reconstruction scheme based on the Laplacian averaging. A least-square method with extended stencil is used for flow gradient calculations. Proper convergence criterion is studied on Euler and adjoint equations for efficient design. The present method has been applied to RAE2822 and NACA0012 airfoils such that wave drag can be minimized by removing the shock wave. An inverse design is also performed to recover the shock wave on the designed RAE2822 airfoil.

• Nuclear Engineering and Technology
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• v.56 no.8
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• pp.3347-3358
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• 2024

Addressing the challenge of identifying an appropriate set of material and irradiation parameters for accurate simulation models using crystal plasticity finite element method (CPFEM), this study proposes a novel two-stage method for nano-indentation modeling of ion-irradiated face-centered cubic (FCC) materials. It includes implementing the strain-gradient crystal plasticity (SGCP) theory with irradiation effects and the calibration of simulation parameters using the particle swarm optimization (PSO) algorithm with experimental data. The proposed method consists of two stages: establishing CPFEM without irradiation effects in stage 1 and modeling irradiation effects based on CPFEM in stage 2. Modeling the nano-indentation test of ion-irradiated stainless steel 304 (SS304) using real experimental data is conducted to evaluate the efficiency of the proposed method. The accuracy of the calibration method using PSO is verified through comparisons between simulation and experimental results for force-indentation depth and hardness-indentation depth relationships under both unirradiated and irradiated conditions. Moreover, effect of ion-irradiation on the mechanical behavior during the nano-indentation of single crystal SS304 is also examined to demonstrate that the proposed method is a powerful approach for nano-indentation modeling of ion-irradiated FCC single crystals using SGCP theory and the PSO algorithm.

• Transactions of the Korean Society of Automotive Engineers
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• v.10 no.3
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• pp.176-184
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• 2002

The door stiffness is one of the important factors for the side impact. Generally, the researches have been conducted on the assembled door. A side impact door beam is installed in a door to protect occupants from the side impact. This research is only concentrated on the side impact beam and a side impact beam is designed. The cross section is defined to have an elliptic shape. An optimization problem is defined to find the design maximizing the intrusion stiffness within the specified weight. Design variables are the radii and the thickness of the ellipsoid. The analysis of the side impact is carried out by the nonlinear finite element method. The optimization problem is solved by two methods. One is the experimental design scheme using an orthogonal array. The other is the gradient-based optimization using the response surface method(RSM). Both methods have obtained the better designs than the current one.

• 한국전산유체공학회:학술대회논문집
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• 2005.04a
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• pp.191-196
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• 2005

For the improvement of aerodynamic performance of the turbine blade in a turbopump for the liquid rocket engine, the optimization of turbine profile shape has been studied. The turbine in a turbopump in this study is a partial admission of impulse type, which has twelve nozzles and supersonic inflow. Due to the separated nozzles and supersonic expansion, the flow field becomes complicates and shows oblique shocks and flow separation. To increase the blade power, redesign of the blade shape using CFD and optimization method was attempted. The turbine cascade shape was represented by four design parameters. For optimization, genetic algorithm based upon non-gradient search has been selected as a optimizer. As a result, the final blade has about 4 percent more blade power than the initial shape.