• Structural Engineering and Mechanics
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• 제57권4호
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• pp.763-783
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• 2016

A methodology based on Teaching Learning-Based Optimization (TLBO) algorithm is proposed for optimum design of reinforced concrete retaining walls. The objective function is to minimize total material cost including concrete and steel per unit length of the retaining walls. The requirements of the American Concrete Institute (ACI 318-05-Building code requirements for structural concrete) are considered for reinforced concrete (RC) design. During the optimization process, totally twenty-nine design constraints composed from stability, flexural moment capacity, shear strength capacity and RC design requirements such as minimum and maximum reinforcement ratio, development length of reinforcement are checked. Comparing to other nature-inspired algorithm, TLBO is a simple algorithm without parameters entered by users and self-adjusting ranges without intervention of users. In numerical examples, a retaining wall taken from the documented researches is optimized and the several effects (backfill slope angle, internal friction angle of retaining soil and surcharge load) on the optimum results are also investigated in the study. As a conclusion, TLBO based methods are feasible.

• 한국자동차공학회논문집
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• 제12권5호
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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.

• Structural Engineering and Mechanics
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• 제89권3호
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• pp.309-321
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• 2024

In this paper, the effect of semi-rigid connections on the stability bearing capacity of cross-bracings in steel tubular transmission towers is investigated. Herein, a prediction method based on the hybrid model which is a combination of particle swarm optimization (PSO) and backpropagation neural network (BPNN) is proposed to accurately predict the stability bearing capacity of cross-bracings with semi-rigid connections and to efficiently conduct its probabilistic assessment. Firstly, the establishment of the finite element (FE) model of cross-bracings with semi-rigid connections is developed on the basis of the development of the mechanical model. Then, a dataset of 7425 samples generated by the FE model is used to train and test the PSO-BPNN model, and the accuracy of the proposed method is evaluated. Finally, the probabilistic assessment for the stability bearing capacity of cross-bracings with semi-rigid connections is conducted based on the proposed method and the Monte Carlo simulation, in which the geometric and material properties including the outer diameter and thickness of cross-sections and the yield strength of steel are considered as random variables. The results indicate that the proposed method based on the PSO-BPNN model has high accuracy in predicting the stability bearing capacity of cross-bracings with semi-rigid connections. Meanwhile, the semi-rigid connections could enhance the stability bearing capacity of cross-bracings and the reliability of cross-bracings would significantly increase after considering semi-rigid connections.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제9권8호
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• pp.2840-2853
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• 2015

A major challenge in network service providers is to provide adequate resources in service level agreements based on forecasts of future demands. In this paper, we address the problem of capacity provisioning in a network subject to demand uncertainty such that a network coded multicast is applied as the data delivery mechanism with limited budget to purchase extra capacity. We address some particular type of uncertainty sets that obtain a tractable constrained capacity provisioning problem. For this reason, we first formulate a mathematical model for the problem under uncertain demand. Then, a robust optimization model is proposed for the problem to optimize the worst-case system performance. The robustness and effectiveness of the developed model are demonstrated by numerical results. The robust solution achieves more than 10% reduction and is better than the deterministic solution in the worst case.

• Journal of Power Electronics
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• 제19권5호
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• pp.1315-1325
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• 2019

Aiming at the negative sequence and harmonic problems in the operation of railway static power conditioners, an optimization compensation strategy for negative sequence and harmonics is studied in this paper. First, the hybrid RPC topology and compensation principle are analyzed to obtain different compensation zone states and current capacities. Second, in order to optimize the RPC capacity configuration, the minimum RPC compensation capacity is calculated according to constraint conditions, and the optimal compensation coefficient and compensation angle are obtained. In addition, the voltage unbalance ${\varepsilon}_U$ and power factor requirements are satisfied. A PSO (Particle Swarm Optimization) algorithm is used to calculate the three indexes for minimum compensating energy. The proposed method can precisely calculate the optimal compensation capacity in real time. Finally, MATLAB simulations and an experimental platform verify the effectiveness and economics of the proposed algorithm.

• FOCUS: LIFE SCIENCE
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• 제1호
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• pp.9.1-9.5
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• 2024

Method development for complex low molecular mass (LMM) samples using reversed-phase (RP) separation conditions presents significant challenges due to the presence of many unknown analytes over wide concentration ranges. This guide aims to optimize method parameters-column length (L), temperature (T), flow rate (F), and final mobile phase conditions (Øfinal)-to maximize separation peak capacity. Validated by prior research, this protocol benefits laboratories dealing with metabolomics, natural products, and contaminant screening. This practical guide provides a structured approach to maximizing peak capacity for complex LMM separations. It complements computational optimization strategies and offers a step-by-step method development process. The Snyder-Dolan test is highlighted as essential for determining the need for gradient or isocratic elution and guiding column length decisions. The decision tree framework helps analysts prioritize variable optimization to develop effective separation methods for complex samples.

• 한국통신학회논문지
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• 제5권1호
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• pp.60-69
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• 1980

크고 複雜한 線形回路方程式을 갖는 큰 계통의 回路를 解析하기 위해서는 매우 많은 記憶容量과 時間이 必要하다. 이러한 記憶容量과 계산 時間을 줄이기 위해서 본 論文에서는 Sparse 行列을 利用하여 增幅回路의 最適 設計를 하였다.

• Nuclear Engineering and Technology
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• 제54권4호
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• pp.1363-1373
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• 2022

The recent seismic events that occurred in South Korea have increased the interest in the re-evaluation of the seismic capacity of nuclear power plant (NPP) equipment, which is often conservatively estimated. To date, various approaches-including the Bayesian method proposed by the United States (US) Electric Power Research Institute -have been developed to quantify the seismic capacity of NPP equipment. Among these, the Bayesian approach has advantages in accounting for both prior knowledge and new information to update the probabilistic distribution of seismic capacity. However, data availability and region-specific issues exist in applying this Bayesian approach to Korean NPP equipment. Therefore, this paper proposes to construct an earthquake experience database by combining available earthquake records at Korean NPP sites and the general location of equipment within NPPs. Also, for the better representation of the seismic demand of Korean earthquake datasets, which have distinct seismic characteristics from those of the US at a high-frequency range, a broadband frequency range optimization is suggested. The proposed data construction and seismic demand optimization method for seismic capacity re-evaluation are demonstrated and tested on a 480 V motor control center of a South Korea NPP.

• 대한전자공학회:학술대회논문집
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• 대한전자공학회 2003년도 신호처리소사이어티 추계학술대회 논문집
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• pp.99-102
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• 2003

Computing environments of Embedded Systems are different from those of desktop computers so that they have resource constraints such as CPU processing, memory capacity, power, and etc.. Thus, when a desktop S/W is ported into embedded systems, optimization should be seriously considered. In this paper, we investigate several S/W optimization techniques to be considered for porting H.263 encoder into a high performance DSP, TMS320C6711. Through experiments, it is found that optimization techniques employed can make a big performance improvement.

• 대한건축학회논문집:구조계
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• 제35권3호
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• pp.43-48
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• 2019

Since the revision of the Rationalization of Energy Use Law, the spread of new and renewable energy in buildings has been promoted. In addition, the production of electric power and thermal energy is an important issue in the change of energy paradigm centered on the use of distributed energy. Among them, geothermal energy is attracting attention as a high-performance energy-saving technology capable of coping with heating / cooling and hot water load by utilizing the constant temperature zone of the earth. However, there is a disadvantage that the initial investment cost is high as a method of calculating the capacity of a geothermal facility by calculating the maximum load. The disadvantages of these disadvantages are that the geothermal energy supply is getting stagnant and the design of the geothermal system needs to be supplemented. In this study, optimization design of geothermal system was carried out using optimization tool. As a result of the optimization, the ground heat exchanger decreased by 30.8%, the capacity of the heat pump decreased by 7.7%, and the capacity of the heat storage tank decreased by about 40%. The simulation was performed by applying the optimized value to the program and confirmed that it corresponds to the load of the building. We also confirmed that all of the constraints used in the optimization design were satisfied. The initial investment cost of the optimized geothermal system is about 18.6% lower than the initial investment cost.