• Journal of Mechanical Science and Technology
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• v.18 no.9
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• pp.1512-1518
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• 2004

Rescaled Simulated Annealing (RSA) has been adapted to solve combinatorial optimization problems in which the available computational resources are limited. Simulated Annealing (SA) is one of the most popular combinatorial optimization algorithms because of its convenience of use and because of the good asymptotic results of convergence to optimal solutions. However, SA is too slow to converge in many problems. RSA was introduced by extending the Metropolis procedure in SA. The extension rescales the state's energy candidate for a transition before applying the Metropolis criterion. The rescaling process accelerates convergence to the optimal solutions by reducing transitions from high energy local minima. In this paper, structural optimization examples using RSA are provided. Truss structures of which design variables are discrete or continuous are optimized with stress and displacement constraints. The optimization results by RSA are compared with the results from classical SA. The comparison shows that the numbers of optimization iterations can be effectively reduced using RSA.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.11 no.4
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• pp.247-253
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• 2011

A sustainability of electricity supply has emerged as a critical issue for low carbon green growth in South Korea. Wind power is the fastest growing source of renewable energy. However, due to its own intermittency and volatility, the power supply generated from wind energy has variability in nature. Hence, accurate forecasting of wind speed and power plays a key role in the effective harvesting of wind energy and the integration of wind power into the current electric power grid. This paper presents a short-term wind speed prediction method based on support vector regression. Moreover, particle swarm optimization is adopted to find an optimum setting of hyper-parameters in support vector regression. An illustration is given by real-world data and the effect of model regularization by particle swarm optimization is discussed as well.

• Journal of Electrical Engineering and Technology
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• v.10 no.4
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• pp.1780-1785
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• 2015

In this paper, the adaptive particle swarm optimization (APSO) algorithm is employed to design a gain-enhanced antenna with a reflector for energy harvesting. We placed the reflector below the main radiating element. Its back-radiated field is reflected and added to the forward radiated field, which could increase the antenna gain. We adopt the adaptive particle swarm optimization (APSO) algorithm, which improves the speed of convergence with a high frequency solver. The result shows that performance of the optimized design successfully satisfied the design goal of the frequency band, gain and axial ratio.

• Journal of Microbiology and Biotechnology
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• v.14 no.6
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• pp.1163-1169
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• 2004

An unstructured mathematical model is presented for lactic acid fermentation based on the energy balance. The proposed model reflects the energy metabolic state and then predicts the cell growth, lactic acid production, and glucose consumption rates by relating the above rates with the energy metabolic rate. Fermentation experiments were conducted under various initial lactic acid concentrations of 0, 30, 50, 70, and 90 g/l. Also, a genetic algorithm was used for further optimization of the model parameters and included the operations of coding, initialization, hybridization, mutation, decoding, fitness calculation, selection, and reproduction exerted on individuals (or chromosomes) in a population. The simulation results showed a good fit between the model prediction and the experimental data. The genetic algorithm proved to be useful for model parameter optimization, suggesting wider applications in the field of biological engineering.

• The KSFM Journal of Fluid Machinery
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• v.17 no.3
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• pp.5-12
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• 2014

This paper presents a design optimization for meridional profile and blade angle ${\theta}$ of a centrifugal compressor with DOE (design of experiments) and RSM (response surface method). Control points of the $3^{rd}$ order Bezier curve are used for design parameters and specific overall efficiency is used as object function. The response surface function shows good agreement with the 3D computational results. Three different optimized designs are proposed and compared with reference design at design point and off-design point. Contours of relative Mach number, static entropy, and total pressure are analyzed for improvement of performance by optimization. Off-design performance analysis is conducted by total pressure and efficiency.

• International Journal of Fluid Machinery and Systems
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• v.10 no.3
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• pp.264-273
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• 2017

In order to be able to predict the maximum Annual Energy Production (AEP) for tidal power plants, an AEP optimization tool based on Evolutionary Algorithms was developed by ANDRITZ HYDRO. This tool can simulate all operating modes of the units (bi-directional turbine, pump and sluicing mode) and provide the optimal plant operation that maximizes the AEP to the control system. For the Swansea Bay Tidal Power Plant, the AEP optimization evaluated all different hydraulic and operating concepts and defined the optimal concept that led to a significant AEP increase. A comparison between the optimal plant operation provided by the AEP optimization and the full load operating strategy is presented in the paper, highlighting the advantage of the method in providing the maximum AEP.

• Transactions of the Korean Society of Automotive Engineers
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• v.12 no.5
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• pp.94-100
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• 2004

In order to improve the frontal crash performance of an Aluminum Space Frame Vehicle, this presents a systematic optimal design process to maximize the crush energy absorption capacity of side-members while satisfying the maximum displacement constraint. In this study, five design types are studied for selecting a good collapse initiator. Then, for the selected collapse initiator type, 7 design variables are defined to represent cross section shape, thickness and bead interval. The systematic optimization processor, R-INOPL uses DOE, RSM and numerical optimization techniques. R-INOPL uses only 14 analyses to solve the 7 design variable optimization problem the final design can improve 103.9% of the internal energy and reduce 13.9% of the maximum displacement.

• Smart Structures and Systems
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• v.25 no.1
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• pp.47-56
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• 2020

This paper proposes a model-based approach for structural damage identification and quantification. Using pseudo modal strain energy and mode shape vectors, a damage-sensitive objective function is introduced which is suitable for damage estimation and quantification in shear frames. Whale optimization algorithm (WOA) is used to solve the problem and report the optimal solution as damage detection results. To illustrate the capability of the proposed method, a numerical example of a shear frame under different damage patterns is studied in both ideal and noisy cases. Furthermore, the performance of the WOA is compared with particle swarm optimization algorithm, as one the widely-used optimization techniques. The applicability of the method is also experimentally investigated by studying a six-story shear frame tested on a shake table. Based on the obtained results, the proposed method is able to assess the health of the shear building structures with high level of accuracy.

• Nuclear Engineering and Technology
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• v.53 no.7
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• pp.2268-2276
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• 2021

Spent nuclear fuel, which can degrade during long-term storage, must be transported intact in normal transport conditions. In this regard, many studies, including those involving Multi-Modal Transportation Test (MMTT) campaigns, have been conducted. In order to transport the spent fuel safely, a tie-down structure for supporting and transporting a cask containing the spent fuel is essential. To ensure its structural integrity, a method for finding an optimum conceptual design for the tie-down structure is presented. An optimized transportation test model of a tie-down structure for the KORAD-21 metal cask is derived based on the proposed optimization approach, and the transportation test model is manufactured by redesigning the optimized model to enable its producibility. The topology optimization approach presented in this paper can be used to obtain optimum conceptual designs of tie-down structures developed in the future.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.14 no.11
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• pp.4595-4610
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• 2020

In the practical communication environment, the accurate channel state information (CSI) is difficult to obtain, which will cause the mismatch of resource and degrade the system performance. In this paper, to account for the channel uncertainties, a robust power allocation scheme for a downlink Non-orthogonal multiple access (NOMA) heterogeneous network (HetNet) is designed to maximize energy efficiency (EE), which can ensure the quality of service (QoS) of users. We conduct the robust optimization model based on worse-case method, in which the channel gains belong to certain ellipsoid sets. To solve the non-convex non-liner optimization, we transform the optimization problem via Dinkelbach method and sequential convex programming, and the power allocation of small cell users (SCUs) is achieved by Lagrange dual approach. Finally, we analysis the convergence performance of proposed scheme. The simulation results demonstrate that the proposed algorithm can improve total EE of SCUs, and has a fast convergence performance.