• Smart Structures and Systems
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• v.12 no.6
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• pp.641-659
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• 2013

In this paper is studied the influence of the uncertain mass distribution over the floors on the choice of the optimal parameters of a hybrid control system for tall buildings subjected to wind load. In particular, an optimization procedure is developed for the robust design of a hybrid control system that is based on an enhanced Monte Carlo simulation technique and the genetic algorithm. The large computational effort inherent in the use of a MC-based procedure is reduced by the employment of the Latin Hypercube Sampling. With reference to a tall building modeled as a multi degrees of freedom system, several numerical analyses are carried out varying the parameters influencing the floors' masses, like the coefficient of variation of the distribution and the correlation between the floors' masses. The procedure allows to obtain optimal designs of the control system that are robust with respect to the uncertainties on the distribution of the dead and live loads.

• Journal of Mechanical Science and Technology
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• v.17 no.12
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• pp.1938-1948
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• 2003

This paper represents that an enhanced genetic algorithm (EGA) is applied to optimal design of a squeeze film damper (SFD) to minimize the maximum transmitted load between the bearing and foundation in the operational speed range. A general genetic algorithm (GA) is well known as a useful global optimization technique for complex and nonlinear optimization problems. The EGA consists of the GA to optimize multi-modal functions and the simplex method to search intensively the candidate solutions by the GA for optimal solutions. The performance of the EGA with a benchmark function is compared to them by the IGA (Immune-Genetic Algorithm) and SQP (Sequential Quadratic Programming). The radius, length and radial clearance of the SFD are defined as the design parameters. The objective function is the minimization of a maximum transmitted load of a flexible rotor system with the nonlinear SFDs in the operating speed range. The effectiveness of the EGA for the optimal design of the SFD is discussed from a numerical example.

• Journal of Advanced Marine Engineering and Technology
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• v.30 no.5
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• pp.562-571
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• 2006

Finite element analysis is performed to evaluate structural reliability of an automotive pedal arm under conditions of the stiffness, the load and the endurance test specifications. Results of the analysis shows that the pedal arm is safe enough under the tests. A topology optimization is numerically implemented, overall shape of the pedal arm being verified to be reasonable, A design concept to insert holes in the arm is established, which may be used to reduce its weight.

• Structural Engineering and Mechanics
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• v.44 no.3
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• pp.325-337
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• 2012

In this article, the multi-objective optimization of cylindrical aluminum tubes under axial impact load is presented. The specific absorbed energy and the maximum crushing force are considered as objective functions. The geometric dimensions of tubes including diameter, length and thickness are chosen as design variables. D/t and L/D ratios are constricted in the range of which collapsing of tubes occurs in concertina or diamond mode. The Non-dominated Sorting Genetic Algorithm-II is applied to obtain the Pareto optimal solutions. A back-propagation neural network is constructed as the surrogate model to formulate the mapping between the design variables and the objective functions. The finite element software ABAQUS/Explicit is used to generate the training and test sets for the artificial neural networks. To validate the results of finite element model, several impact tests are carried out using drop hammer testing machine.

• Journal of the Korean Society of Manufacturing Technology Engineers
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• v.19 no.4
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• pp.434-439
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• 2010

A compliant mechanism is a mechanism that produces its motion by the flexibility of some or all of its members when input force or thermal load is applied. Whereas the topology optimizations based on homogenization and SIMP parameterization have been successfully applied for compliant mechanism design, ESO approach has been hardly considered yet for the optimization of these types of systems. In this paper, traditional ESO method is adopted to achieve the optimum design of a compliant mechanism for thermal load, since AESO method cannot consider the effect of both heat conduction and convection. Sensitivity number, a criterion for element removal in traditional ESO, was newly defined for input thermal loading. The procedure has been tested in numerical applications and compared with the results obtained by other methods to validate these approaches.

• Journal of the Korean Ceramic Society
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• v.56 no.3
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• pp.277-283
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• 2019

We have examined minimization of the number of impurity particles by replacing the load-lock chamber materials of the chemical vapor deposition equipment through optimization of the pumping method in the deposition chamber. In order to reduce the number of impurity particles in the chamber, the load-lock spacer material was changed from monomer casting nylon to Torlon. Furthermore, we controlled the pumping speed and number of pumping ports, which resulted in a reduction in the impurity particle generation from 2.67% to 0.52%. This study revealed that the selection of the material for the parts of a chemical vapor deposition chamber can minimize particle generation, thereby presenting a method of optimization method of the chemical vapor deposition chamber.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.27 no.1
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• pp.17-23
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• 2013

The BESS(Battery Energy Storage System) is an useful device for load leveling, but the high cost, installation space and safety issues are the main barriers for supplying it widely. The important factor in supplying BESS to customers successfully is the payback period. As most of the H/W cost factors are uncontrollable, the optimization of storage volume can be useful factor in improving payback period. In order to obtain optimized BESS volume, the load factor, demand ratio, peak shaving ratio, electric rates and benefits from DR participation of customer should be analyzed. In this paper, we could verify the peak cutting capability and cost effectiveness under the some proposed conditions and changing value of PCS and battery based on the customers data after volume optimization process was applied, and we can identified the saturation point of load factor and shortening of customer's payback period.

• Journal of KIISE
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• v.41 no.12
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• pp.1145-1151
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• 2014

In this paper, we propose MPLO(Multi-Path routing with Local Optimization) for load balancing in the tactical backbone network. The MPLO manages global metric and local metric separately. The global metric is propagated to other routers via a routing protocol and is used for configuring loop-free multi-path. The local metric reflecting link utilization is used to find an alternate path when congestion occurs. We verified MPLO could effectively distribute user traffic among available routers by simulation.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.61 no.6
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• pp.783-790
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• 2012

Electric Vehicles(EVs) and Plug-in Hybrid Electric Vehicles(PHEVs) which have the grid connection capability, represent an important power system issue of charging demands. Analyzing impacts EVs charging demands of the power system such as increased peak demands, developed by means of modeling a stochastic distribution of charging and a demand dispatch calculation. Optimization processes proposed to determine optimal demand distribution portions so that charging costs and demand can possibly be managed. In order to solve the problems due to increasing charging demand at the peak time, alternative electricity rate such as Time-of-Use(TOU) rate has been in effect since last year. The TOU rate would in practice change the tendencies of charging time at the peak time. Nevertheless, since it focus only minimizing costs of charging from owners of the EVs, loads would be concentrated at times which have a lowest charging rate and would form a new peak load. The purpose of this paper is that to suggest a scenario of load leveling for a power system operator side. In case study results, the vehicles as regular load with time constraints, battery charging patterns and changed daily demand in the charging areas are investigated and optimization results are analyzed regarding cost and operation aspects by determining optimal demand distribution portions.

• Journal of Electrical Engineering and Technology
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• v.10 no.3
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• pp.877-887
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• 2015

Rapid development of cities with constant increasing load and deregulation in electricity market had forced the transmission lines to operate near their threshold capacity and can easily lead to voltage instability and caused system breakdown. To prevent such catastrophe from happening, accurate readings of voltage stability condition is required so that preventive equipment and operators can execute security procedures to restore system condition to normal. This paper introduced Enhanced Hybrid Particle Swarm Optimization algorithm to estimate the voltage stability condition which utilized Fast Voltage Stability Index (FVSI) to indicate how far or close is the power system network to the collapse point when the reactive load in the system increases because reactive load gives the highest impact to the stability of the system as it varies. Particle Swarm Optimization (PSO) had been combined with the ANN to form the Enhanced Hybrid PSO-ANN (EHPSO-ANN) algorithm that worked accurately as a prediction algorithm. The proposed algorithm reduced serious local minima convergence of ANN but also maintaining the fast convergence speed of PSO. The results show that the hybrid algorithm has greater prediction accuracy than those comparing algorithms. High generalization ability was found in the proposed algorithm.