• Proceedings of the KSME Conference
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• 2003.04a
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• pp.451-455
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• 2003

Major concern in modern industry is how to reduce the time and cost for product efficient production. Among many mechanical parts of a satellite, bracket plays an important role to support the load when the satellite is launched to space. so enough strength and stiffness. A designer could add unnecessary material and strength it so as not to fail when it used. But if mechanical part of satellite is over-designed, cost will rise and it also goes against to the aim of lightness. To achieve lightness and enough strength and stiffness, optimization algorithm should be introduced in design process. In this study, conceptual design of bracket is carried out to increase the performance of satellite. Some parameter which could change the weight of this part are selected as design variables. Total weight of bracket is to be minimized while displacement and stress should not exceed limit. Size optimization is done with 3D solid element and PLBA, the RQP algorithm. The weight of 0.262kg of initial model is reduced to 0.241kg after optimization process, so 9.8% of weight reduction is obtained.

• Proceedings of the KIEE Conference
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• 2015.07a
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• pp.179-180
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• 2015

High wind penetration might cause the frequency stability problem because a wind power plant (WPP) is operating in a maximum power tracking mode to extract the maximal energy from wind and thus does not react to the system frequency variation. Therefore, the system operators encourage a WPP to participate in frequency control, which includes inertia/orl and primary control. The frequency support capability of a WPP depends on the amount of kinetic energy (KE) and reserve. This paper formulates an optimization problem to maximize KE while retaining the required reserve. The proposed optimization problem would allow wind generators (WGs) with a smaller wind speed to retaine more KE. The performance of the proposed optimization problem was investigated in a 100-MW WPP consisting of 20 units of 5-MW permanent magnet synchronous generators using an EMTP-RV simulator. The results show that the proposed optimization problem successfully improves the frequency nadir more than a conventional reserve allocation that distributes WGs proportional to the current output.

• International Journal of Computer Science & Network Security
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• v.21 no.8
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• pp.342-352
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• 2021

Multicast Routings is a big challenge due to limitations such as node power and bandwidth Mobile Ad-hoc Network (MANET). The path to be chosen from the source to the destination node requires protocols. Multicast protocols support group-oriented operations in a bandwidth-efficient way. While several protocols for multi-cast MANETs have been evolved, security remains a challenging problem. Consequently, MANET is required for high quality of service measures (QoS) such infrastructure and application to be identified. The goal of a MANETs QoS-aware protocol is to discover more optimal pathways between the network source/destination nodes and hence the QoS demands. It works by employing the optimization method to pick the route path with the emphasis on several QoS metrics. In this paper safe routing is guaranteed using the Secured Multicast Routing offered in MANET by utilizing the Ant Colony Optimization (ACO) technique to integrate the QOS-conscious route setup into the route selection. This implies that only the data transmission may select the way to meet the QoS limitations from source to destination. Furthermore, the track reliability is considered when selecting the best path between the source and destination nodes. For the optimization of the best path and its performance, the optimized algorithm called the micro artificial bee colony approach is chosen about the probabilistic ant routing technique.

• International Journal of Computer Science & Network Security
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• v.23 no.8
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• pp.159-167
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• 2023

Objective: • To detect black hole and warm hole attacks in wireless sensor networks. • To give a solution for energy depletion and security breach in wireless sensor networks. • To address the security problem using strategic decision support system. Methods: The proposed stackelberg game is used to make the spirited relations between multi leaders and multi followers. In this game, all cluster heads are acts as leaders, whereas agent nodes are acts as followers. The game is initially modeled as Quadratic Programming and also use backtracking search optimization algorithm for getting threshold value to determine the optimal strategies of both defender and attacker. Findings: To find optimal payoffs of multi leaders and multi followers are based on their utility functions. The attacks are easily detected based on some defined rules and optimum results of the game. Finally, the simulations are executed in matlab and the impacts of detection of black hole and warm hole attacks are also presented in this paper. Novelty: The novelty of this study is to considering the stackelberg game with backtracking search optimization algorithm (BSOA). BSOA is based on iterative process which tries to minimize the objective function. Thus we obtain the better optimization results than the earlier approaches.

• Structural Engineering and Mechanics
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• v.88 no.4
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• pp.323-334
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• 2023

The submerged floating tunnel (SFT) infrastructure has been regarded as an emerging technology that efficiently and safely connects land and islands. The SFT route problem is an essential part of the SFT planning and design phase, with significant impacts on the surrounding environment. This study aims to develop an optimization model considering transportation and structure factors. The SFT routing problem was optimized based on two objective functions, i.e., minimizing total travel time and cumulative strains, using NSGA-II. The proposed model was applied to the section from Mokpo to Jeju Island using road network and wave observation data. As a result of the proposed model, a Pareto optimum curve was obtained, showing a negative correlation between the total travel time and cumulative strain. Based on the inflection points on the Pareto optimum curve, four optimal SFT routes were selected and compared to identify the pros and cons. The travel time savings of the four selected alternatives were estimated to range from 9.9% to 10.5% compared to the non-implemented scenario. In terms of demand, there was a substantial shift in the number of travel and freight trips from airways to railways and roadways. Cumulative strain, calculated based on SFT distance, support structure, and wave energy, was found to be low when the route passed through small islands. The proposed model helps decision-making in the planning and design phases of SFT projects, ultimately contributing to the progress of a safe, efficient, and sustainable SFT infrastructure.

• Nuclear Engineering and Technology
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• v.56 no.5
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• pp.1654-1666
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• 2024

The goal of this research is to propose a way to maximize small modular reactor (SMR) utilization to gain better market feasibility in support of carbon neutrality. For that purpose, a comprehensive tool was developed, combining off-design thermohydraulic models, economic objective models (levelized cost of electricity, annual profit), non-economic models (saved CO2), a parameter input sampling method (Latin hypercube sampling, LHS), and a multi-objective evolutionary algorithm (Non-dominated Sorting Algorithm-2, NSGA2 method) for optimizing a SMR-combined heat and power cycle (CHP) system design. Considering multiple objectives, it was shown that NSGA2+LHS method can find better optimal solution sets with similar computational costs compared to a conventional weighted sum (WS) method. Out of multiple multi-objective optimal design configurations for a 105 MWe design generation rating, a chosen reference SMR-CHP system resulted in its levelized cost of electricity (LCOE) below $60/MWh for various heat prices, showing economic competitiveness for energy market conditions similar to South Korea. Examined economic feasibility may vary significantly based on CHP heat prices, and extensive consideration of the regional heat market may be required for SMR-CHP regional optimization. Nonetheless, with reasonable heat market prices (e.g. district heating prices comparable to those in Europe and Korea), SMR can still become highly competitive in the energy market if coupled with a CHP system.

• Journal of Convergence for Information Technology
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• v.10 no.9
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• pp.1-7
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• 2020

In order to implement a smart factory for manufacturing innovation, more digital twins will be developed and applied gradually. In particular, simulation and optimization of digital twins makes it possible to support critical decision-making like a predictive maintenance of the equipment for manufacturing. In terms of a user perspective, this study suggests the conceptual framework of Digital Twin Management System (DTMS) for supporting the analytical and managerial activities for Digital Twins. We integrate the methods and structure of the area like Manufacturing Engineering, Decision Support Systems, and Optimization for developing the DTMS. The framework suggested in this study shows a typical DSS which consists of dialog management system, model management system and data management system. It also includes Analytical Digital Twins and simulations & optimization module. The framework is being applied in one of the most competitive and complex industrial sector. Also this study is meaningful to suggest a new direction of research.

• Journal of Electrical Engineering and Technology
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• v.13 no.6
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• pp.2511-2520
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• 2018

In this study, Multi-Radial Basis Function Support Vector Machine (Multi-RBF SVM) classifier is introduced based on a composite kernel function. In the proposed multi-RBF support vector machine classifier, the input space is divided into several local subsets considered for extremely nonlinear classification tasks. Each local subset is expressed as nonlinear classification subspace and mapped into feature space by using kernel function. The composite kernel function employs the dual RBF structure. By capturing the nonlinear distribution knowledge of local subsets, the training data is mapped into higher feature space, then Multi-SVM classifier is realized by using the composite kernel function through optimization procedure similar to conventional SVM classifier. The original training data set is partitioned by using some unsupervised learning methods such as clustering methods. In this study, three types of clustering method are considered such as Affinity propagation (AP), Hard C-Mean (HCM) and Iterative Self-Organizing Data Analysis Technique Algorithm (ISODATA). Experimental results on benchmark machine learning datasets show that the proposed method improves the classification performance efficiently.

• Structural Engineering and Mechanics
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• v.51 no.3
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• pp.377-402
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• 2014

In this study, optimal distribution of springs which supports a cantilever beam is investigated to minimize two objective functions defined. The optimal size and location of the springs are ascertained to minimize the tip deflection of the cantilever beam. Afterwards, the optimization problem of springs is set up to minimize the tip absolute acceleration of the beam. The Fourier Transform is applied on the equation of motion and the response of the structure is defined in terms of transfer functions. By using any structural mode, the proposed method is applied to find optimal stiffness and location of springs which supports a cantilever beam. The stiffness coefficients of springs are chosen as the design variables. There is an active constraint on the sum of the stiffness coefficients and there are passive constraints on the upper and lower bounds of the stiffness coefficients. Optimality criteria are derived by using the Lagrange Multipliers. Gradient information required for solution of the optimization problem is analytically derived. Optimal designs obtained are compared with the uniform design in terms of frequency responses and time response. Numerical results show that the proposed method is considerably effective to determine optimal stiffness coefficients and locations of the springs.

• Korean Journal of Construction Engineering and Management
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• v.6 no.6 s.28
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• pp.115-123
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• 2005

Design of steel $bridge^{\circ}AEs$ temporary works has conducted relying on the experiences of engineers based on the previous similar projects. Consequently, there have been arguments against over-design of temporary bents to be required at the actual construction sites, and unnecessary design changes have been issued at the construction stage. In this study, we have developed an optimum design support system for temporary works of the steel bridge construction through establishing the database for the materials to be needed for implementation of temporary works. We've also improved the accuracy and efficiency of the works through the design optimization for temporary works, and contributed to reduce design changes as well as to utilize the design informations at the construction stage.