• Nuclear Engineering and Technology
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• v.56 no.2
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• pp.644-654
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• 2024

After the Tohoku earthquake and tsunami (Japan, 2011), regulatory efforts to mitigate external hazards have increased both the safety requirements and the total capital cost of nuclear power plants (NPPs). In these circumstances, identifying not only disaster robustness but also cost-effective capacity setting of NPPs has become one of the most important tasks for the nuclear power industry. A few studies have been performed to relocate the seismic capacity of NPPs, yet the effects of multiple hazards have not been accounted for in NPP capacity optimization. The major challenges in extending this problem to the multihazard dimension are (1) the high computational costs for both multihazard risk quantification and system-level optimization and (2) the lack of capital cost databases of NPPs. To resolve these issues, this paper proposes an effective method that identifies the optimal multihazard capacity of NPPs using a multi-objective genetic algorithm and the two-stage direct quantification of fault trees using Monte Carlo simulation method, called the two-stage DQFM. Also, a capacity-based indirect capital cost measure is proposed. Such a proposed method enables NPP to achieve safety and cost-effectiveness against multi-hazard simultaneously within the computationally efficient platform. The proposed multihazard capacity optimization framework is demonstrated and tested with an earthquake-tsunami example.

• Journal of Electrical Engineering and Technology
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• v.13 no.2
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• pp.659-668
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• 2018

This paper proposes an optimization approach of a grid-connected photovoltaic and wind hybrid energy system including energy storage considering voltage fluctuation in the electricity grid. A techno-economic analysis is carried out in order to minimize the size of hybrid system by considering the benefit-cost. Lithium-ion battery type is used for both managing the electricity selling to the grid and reducing voltage fluctuation. A new technique is developed to limit the voltage perturbation caused by the solar irradiance and the wind speed through determining the state-of-charge of battery for every hour of a day. Improved particle swarm optimization (PSO) methods, referred to as FC-VACPSO which combines Fast Convergence Particle Swarm Optimization (FCPSO) method and Variable Acceleration Coefficient Based Particle Swarm Optimization (VACPSO) method are used to solve the optimization problem. A comparative study has been performed between standard PSO method and PSO based methods to extract the best size with the benefit cost. A sensitivity analysis has been studied for different kinds and costs of batteries, by considering variable and constant state-ofcharge of battery. The simulations, performed under Matlab environment, yield good results using the FC-VACPSO method regarding the convergence and the benefit cost of the hybrid system.

• Journal of Korean Society of Transportation
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• v.12 no.3
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• pp.5-13
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• 1994

In the fields of rail and road design, most vertical alignment design have been thus far heavily dependent upon trial-and-errors of experienced engineers. However, it has long been inefficient in productivity of designing process. In order to overcome this inefficiency, this paper presents the optimal vertical alignment design method using mathematical optimization techniques. For optimization, mathematical model to minimize the construction cost is formulated and the separable programming technique and the Zoutendijk method are introduced to solve it. As result, it is shown that this optimization technique can give efficient solutions to all vertical alignment design fields with properly-estimated cost function.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.58 no.8
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• pp.1485-1495
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• 2009

This paper presents a novel approach to economic dispatch (ED) with nonconvex fuel cost function as combinatorial optimization problems (COP) while most of the conventional researches have been developed as function optimization problems (FOP). One nonconvex fuel cost function can be divided into several convex fuel cost functions, and each convex function can be regarded as a generation type (G-type). In that case, ED with nonconvex fuel cost function can be considered as COP finding the best case among all feasible combinations of G-types. In this paper, a genetic algorithm is applied to solve the COP, and the ${\lambda}-P$ function method is used to calculate ED for the fitness function of GA. The ${\lambda}-P$ function method is reviewed briefly and the GA procedure for COP is explained in detail. This paper deals with two kinds of ED problems, namely ED with multiple fuel units (EDMF) and ED with prohibited operating zones (EDPOZ). The proposed method is tested for all the ED problems, and the test results show an improvement in solution cost compared to the results obtained from conventional algorithms.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.26 no.12
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• pp.50-55
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• 2012

This paper presents an application of optimization method for efficient operation in micro grid. For operational efficiency, the objective function in a diesel generator consists of the fuel cost function similar to the cost functions used for the conventional fossil-fuel generating plants. The wind turbine generator is modeled by the characteristics of variable output. The cost function of fuel cell plant considers the efficiency of fuel cell. Particle swarm optimization(PSO) and sequential quadratic programming(SQP) are used for solving the problem of microgrid system operation. Also, from the results this paper presents the way to attend power markets which can buy and sell power from upper lever grids by connecting a various generation resources to micro grid.

• Transactions of the Korean Society of Mechanical Engineers
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• v.16 no.2
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• pp.236-247
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• 1992

Optimization has been developed to minimize the cost function while satisfying constraints. Nonlinear Programming method is used as a tool for the optimization. Usually, cost and constraint function calculations are required in the engineering applications, but those calculations are extremely expensive. Especially, the function and sensitivity analyses cause a bottleneck in structural optimization which utilizes the Finite Element Method. Also, when the functions are quite noisy, the informations do not carry out proper role in the optimization process. An algorithm called "Second-order Approximation Method" has been proposed to overcome the difficulties recently. The cost and constraint functions are approximated by the second-order Taylor series expansion on a nominal points in the algorithm. An optimal design problem is defined with the approximated functions and the approximated problem is solved by a nonlinear programming numerical algorithm. The solution is included in a candidate point set which is evaluated for a new nominal point. Since the functions are approximated only by the function values, sensitivity informations are not needed. One-dimensional line search is unnecessary due to the fact that the nonlinear algorithm handles the approximated functions. In this research, the method is analyzed and the performance is evaluated. Several mathematical problems are created and some standard engineering problems are selected for the evaluation. Through numerical results, applicabilities of the algorithm to large scale and complex problems are presented.presented.

• Journal of Applied Reliability
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• v.18 no.3
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• pp.229-239
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• 2018

Purpose: There is a difficulty in Environmental Stress Screening (ESS) test design for weapon system's electrical/electronic components/products in small and medium-sized enterprises. To overcome this difficulty, I propose an easy ESS test design approach algorithm that is optimized with only one environment tolerance design information parameter (${\Delta}T$). Methods: To propose the mass production weapon system ESS test design for cost-effective optimization, I define an optimum cost-effective mathematical model ESS test algorithm model based on modified MIL-HDBK-344, MIL-HDBK-2164 and DTIC Technical Report 2477. Results: I clearly confirmed and obtained the quantitative data of ESS effectiveness and cost optimization along our ESS test design algorithm through the practical case. I will expect that proposed ESS test method is used for ESS process improvement activity and cost cutting of mass production weapon system manufacturing cost in small and medium-sized enterprises. Conclusion: In order to compare the effectiveness of the proposed algorithm, I compared the effectiveness of the existing ESS test and the proposed algorithm ESS test based on the existing weapon system circuit card assembly for signal processing. As a result of the comparison, it was confirmed that the test time was reduced from 573.0 minutes to 517.2minutes (9.74% less than existing test time).

• Journal of the Korean Society of Safety
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• v.24 no.5
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• pp.48-56
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• 2009

This paper presents the procedure for the optimal design of a PSC-I girder bridge considering life cycle cost (LCC). The load carrying capacity curves for the concrete deck, PSC-I girder and $\pi$-type pier were derived and used for the estimate of service lives. Total life cycle cost for the service life was calculated as sum of initial cost, damage cost, maintenance cost, repair and rehabilitation cost, user cost, and disposal cost. The advanced First Order Second Moment method was used to estimate the damage cost. The optimization method was applied to the design of PSC-I girder bridge. The objective function was set to the annual cost, which is defined by dividing the total life cycle cost by the service life, and constraints were formulated on the basis of Korean Standards. The optimal design was performed for various service lives and the effects of design factors were investigated.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.39 no.8
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• pp.823-830
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• 2015

Structural optimization pursues improved performance of structures. Nowadays, structural optimization is applied to the design of huge and complex structures such as an airplane. As the number of the finite elements is increased, the analysis solution becomes more accurate. However, the design cost using the finite element model is significantly increased. The component mode synthesis method that is using the substructure synthesis method is frequently employed in order to keep the accuracy and reduce the cost. A new design method for structural optimization is proposed to reduce the design cost and to consider the dynamic effect of the structure. The proposed method reduces the design cost by applying the equivalent static loads on the design domain. An example of linear dynamic response optimization is solved and the efficiency of the proposed method is demonstrated.

• Structural Engineering and Mechanics
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• v.81 no.1
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• pp.93-102
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• 2022

The optimum design of reinforced concrete cantilever retaining walls subjected to seismic loads is an extremely important challenge in structural and geotechnical engineering, especially in seismic zones. This study proposes an adaptive sperm swarm optimization algorithm (ASSO) for economic design of retaining structure under static and seismic loading. The proposed ASSO algorithm utilizes a time-varying velocity damping factor to provide a fine balance between the explorative and exploitative behavior of the original method. In addition, the new method considers a reasonable velocity limitation to avoid the divergence of the sperm movement. The proposed algorithm is benchmarked with a set of test functions and the results are compared with the standard sperm swarm optimization (SSO) and some other robust metaheuristic from the literature. For seismic optimization of retaining structures, Mononobe-Okabe method is employed for dynamic loading conditions and total construction cost of the structure is considered as the single objective function. The optimization constraints include both geotechnical and structural restrictions and the design variables are the geometrical dimensions of the wall and the amount of steel reinforcement. Finally, optimization of two benchmark retaining structures under static and seismic loads using the ASSO algorithm is presented. According to the numerical results, the ASSO may provide better optimal solutions, and the designs obtained by ASSO have a lower cost by up to 20% compared with some other methods from the literature.