• Journal of Korean Society of Industrial and Systems Engineering
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• v.22 no.50
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• pp.127-137
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• 1999

This study is concerned with the loading problems in flexible manufacturing system(FMS). The loading problem in FMS is a complex one, when the number of machine and job is increased. It may be time-consuming and even impossible to achieve an optimal solution about this problem mathematically. Thus, a heuristic method is recommended in order to gain near-optimal solutions in a practically acceptable time. A new loading algorithm is developed with a multi-criterion objective of considering the workload unbalance, and maximizing the machine utilization, throughput for critical resources such as the number of tool slots and the number of working hours in a scheduling period and so on. The results of SAS analysis indicated that true average throughput of proposed heuristic loading statistically exceeds that of Shanker and Srinivasulus loading algorithm at the significance level of 0.1.

• Proceedings of the Korean Geotechical Society Conference
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• 2009.09a
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• pp.1011-1016
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• 2009

In this study, to performed laboratory model tests in order to verify on load transfer condition of drilled shaft under lateral loading. To conducted model test on polystyle drilled shaft under multi layer ground conditions. In model test, to measured the strain of drilled shaft and displacement under later loading. In order to verify on model test results, to conduct the numerical analysis.

• Journal of Electrical Engineering and Technology
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• v.8 no.3
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• pp.490-498
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• 2013

This paper discusses the application of evolutionary multi-objective optimization algorithms namely Non-dominated Sorting Genetic Algorithm-II (NSGA-II) and Modified NSGA-II (MNSGA-II) for solving the Combined Economic Emission Dispatch (CEED) problem with valve-point loading. The valve-point loading introduce ripples in the input-output characteristics of generating units and make the CEED problem as a non-smooth optimization problem. IEEE 57-bus and IEEE 118-bus systems are taken to validate its effectiveness of NSGA-II and MNSGA-II. To compare the Pareto-front obtained using NSGA-II and MNSGA-II, reference Pareto-front is generated using multiple runs of Real Coded Genetic Algorithm (RCGA) with weighted sum of objectives. Furthermore, three different performance metrics such as convergence, diversity and Inverted Generational Distance (IGD) are calculated for evaluating the closeness of obtained Pareto-fronts. Numerical results reveal that MNSGA-II algorithm performs better than NSGA-II algorithm to solve the CEED problem effectively.

• Journal of Electrical Engineering and Technology
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• v.9 no.2
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• pp.423-432
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• 2014

Non-dominated Sorting Genetic Algorithm-II (NSGA-II) is applied for solving Combined Economic Emission Dispatch (CEED) problem with valve-point loading of thermal generators. This CEED problem with valve-point loading is a nonlinear, constrained multi-objective optimization problem, with power balance and generator capacity constraints. The valve-point loading introduce ripples in the input-output characteristics of generating units and make the CEED problem as a nonsmooth optimization problem. To validate its effectiveness of NSGA-II, two benchmark test systems, IEEE 30-bus and IEEE 118-bus systems are considered. To compare the Pareto-front obtained using NSGA-II, reference Pareto-front is generated using multiple runs of Real Coded Genetic Algorithm (RCGA) with weighted sum of objectives. Comparison with other optimization techniques showed the superiority of the NSGA-II approach and confirmed its potential for solving the CEED problem. Numerical results show that NSGA-II algorithm can provide Pareto-front in a single run with good diversity and convergence. An approach based on Technique for Ordering Preferences by Similarity to Ideal Solution (TOPSIS) is applied on non-dominated solutions obtained to determine Best Compromise Solution (BCS).

• Nuclear Engineering and Technology
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• v.56 no.8
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• pp.3425-3434
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• 2024

The main features of the loading pattern optimization (LPO) problem, such as high-dimensionality, multi-modality, and non-linearity, make it difficult to achieve a truly optimal configuration. In recent years, metaheuristic methods have been successfully used to solve this problem. In this research, a discrete golden eagle optimization (DGEO) algorithm has been developed to solve the LPO problem in the first cycle of VVER-1000 reactor core. To evaluate the proposed algorithm, a linear multi-purpose fitness function has been used to improve the safety parameters of the reactor core by obtaining a flatter power distribution during the first cycle, and also to enhance the economic parameters by increasing the cycle length and reducing the cost of fuel recycling. For this purpose, a FORTRAN program has been written to map the DGEO algorithm for the LPO problem using the PMAX and PARCS core calculation code to compute the fitness function in each iteration. To speed up the calculations, parallel computing has been applied in the written program. The results demonstrated that the loading pattern, which is suggested by the DGEO algorithm, enhances all the safety and economic parameters in the fitness function. Thus, the DGEO algorithm is highly reliable for the LPO problems in the VVER 1000 reactor core.

• Journal of the Korean Geotechnical Society
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• v.27 no.4
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• pp.67-76
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• 2011

Numerical analyses were performed to analyze the behavior of a suction pile under lateral loads with different soil layer conditions (uniform clay layer, uniform sand layer, and multi layers consisting of clay and sand layers) and different loading locations (top, middle, and bottom of the suction pile). The results of the analyses revealed that, regardless of the soil layer conditions, the lateral resistances at the loading location of the middle of the suction pile were the maximum. For the given loading locations, the lateral resistances of the suction pile for the uniform sand layer were relatively higher than those for the multi layer. By analyzing translations and rotations of the suction pile, it was identified that the amount of translation was highly dependent on both the soil layer condition and the lateral loading location while the rotated angle varied significantly with the lateral loading location, but not much with soil layer condition.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.20 no.5
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• pp.565-572
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• 2007

This paper addresses the kinematic study for the structural analysis of the S60ME-C multi-cylinder vessel engine. The load conditions such as the lateral force and the reaction force by the crank-shaft are required for the FEM analysis. The driving parts in vessel engine are assumed to be in frictionless rigid plane motion. We analytically derive dynamic forces for a single cylinder by using the dynamic force equilibrium. But, for the structural analysis for a single cylinder block, we use the loading conditions of two neighboring cylinders. Meanwhile, we use the single cylinder's loading condition to calculate the multi-cylinder's loading conditions, because each cylinder shows a cyclic loading pattern with respect to the crank arm's rotation angle.

• Proceedings of the Korean Nuclear Society Conference
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• 1999.05a
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• pp.25-25
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• 1999

• Proceedings of the Korean Nuclear Society Conference
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• 1999.05a
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• pp.250-250
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• 1999

• Transactions of the Korean Society of Pressure Vessels and Piping
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• v.11 no.2
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• pp.68-74
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• 2015

Time domain response analysis for vibro-impact nonlinear behavior of multi-span tube with loose supports was performed using commercial FEA code and user subroutine. Support geometry of multi-span tube with a finite gap is realistically modeled by analytical rigid surface. Model of hydrodynamic force is based on the Qusai-steady model which accounts for the inclined angle of relative flow velocity and time delay between flow force and resulting tube motion. During tube vibration from flow loading, impact and friction at the support location is simulated using commercial FEA code with master slave contact algorithm. Analysis results has reasonable agreement with those of references and test experience. Plan of further refinement of analysis model and future test verification is briefly introduced.