• Smart Structures and Systems
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• v.24 no.3
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• pp.303-317
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• 2019

Magneto-rheological fluid (MRF) rotatory dampers are normally used for controlling the constant rotation of machines and engines. In this research, such a device is proposed to act as variable stiffness device to alleviate the rotational oscillation existing in the many engineering applications, such as motor. Under such thought, the main purpose of this work is to characterize the nonlinear torque-angular displacement/angular velocity responses of an MRF based variable stiffness device in oscillatory motion. A rotational hysteresis model, consisting of a rotatory spring, a rotatory viscous damping element and an error function-based hysteresis element, is proposed, which is capable of describing the unique dynamical characteristics of this smart device. To estimate the optimal model parameters, a modified whale optimization algorithm (MWOA) is employed on the captured experimental data of torque, angular displacement and angular velocity under various excitation conditions. In MWOA, a nonlinear algorithm parameter updating mechanism is adopted to replace the traditional linear one, enhancing the global search ability initially and the local search ability at the later stage of the algorithm evolution. Additionally, the immune operation is introduced in the whale individual selection, improving the identification accuracy of solution. Finally, the dynamic testing results are used to validate the performance of the proposed model and the effectiveness of the proposed optimization algorithm.

• Journal of Korea Society of Industrial Information Systems
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• v.27 no.1
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• pp.37-48
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• 2022

In this study, a hybrid meta-heuristic approach is proposed for solving engineering design optimization problems. Various approaches in many literatures have been proposed to solve engineering optimization problems with various types of decision variables and complex constraints. Unfortunately, however, their efficiencies for locating optimal solution do not be highly improved. Therefore, we propose a hybrid meta-heuristic approach for improving their weaknesses. the proposed GA-VNS-HC approach is combining genetic algorithm (GA) for global search with variable neighborhood search (VNS) and hill climbing (HC) for local search. In case study, various types of engineering design optimization problems are used for proving the efficiency of the proposed GA-VNS-HC approach

• The Journal of the Korea institute of electronic communication sciences
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• v.13 no.2
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• pp.357-368
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• 2018

For well over 100 years, oil has enabled remote communities to generate electricity and enjoy the benefits of a consistent electrical supply. Relying solely on oil for electricity generation has left island and remote communities exposed to several risks and drawbacks. Oil-based electricity generation is often more expensive and subject to price volatility, which can result in the use of risky fuel hedging strategies. The residents of islands and remote communities express concern over the future impacts of climate change or insist on their opinions for the corresponding action with reduction of carbon emissions. These risks and drawbacks can be overcomed with continuing cost reductions in solar, wind, and energy storage technologies by maker. Reducing costs is not always a straightforward process, relying on more diversely and renewably arranged renewable energy sources led to reduced local construction cost in every situation reviewed in this study. In this paper, a convenient and simple design solution which will facilitate the optimum location and transmission route of renewable energy facility using GIS(Geographic Information System) is proposed. The suggested solutions exercised to the case of geomoon island using GIS and identified by local site survey.

• 제어로봇시스템학회:학술대회논문집
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• 2004.08a
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• pp.620-626
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• 2004

For general nonlinear processes, it is difficult to control with a linear model-based control method and nonlinear controls are considered. Among the numerous approaches suggested, the most rigorous approach is to use dynamic optimization. Many general engineering problems like control, scheduling, planning etc. are expressed by functional optimization problem and most of them can be changed into dynamic programming (DP) problems. However the DP problems are used in just few cases because as the size of the problem grows, the dynamic programming approach is suffered from the burden of calculation which is called as 'curse of dimensionality'. In order to avoid this problem, the Neuro-Dynamic Programming (NDP) approach is proposed by Bertsekas and Tsitsiklis (1996). To get the solution of seriously nonlinear process control, the interest in NDP approach is enlarged and NDP algorithm is applied to diverse areas such as retailing, finance, inventory management, communication networks, etc. and it has been extended to chemical engineering parts. In the NDP approach, we select the optimal control input policy to minimize the value of cost which is calculated by the sum of current stage cost and future stages cost starting from the next state. The cost value is related with a weight square sum of error and input movement. During the calculation of optimal input policy, if the approximate cost function by using simulation data is utilized with Bellman iteration, the burden of calculation can be relieved and the curse of dimensionality problem of DP can be overcome. It is very important issue how to construct the cost-to-go function which has a good approximate performance. The neural network is one of the eager learning methods and it works as a global approximator to cost-to-go function. In this algorithm, the training of neural network is important and difficult part, and it gives significant effect on the performance of control. To avoid the difficulty in neural network training, the lazy learning method like k-nearest neighbor method can be exploited. The training is unnecessary for this method but requires more computation time and greater data storage. The pH neutralization process has long been taken as a representative benchmark problem of nonlin ar chemical process control due to its nonlinearity and time-varying nature. In this study, the NDP algorithm was applied to pH neutralization process. At first, the pH neutralization process control to use NDP algorithm was performed through simulations with various approximators. The global and local approximators are used for NDP calculation. After that, the verification of NDP in real system was made by pH neutralization experiment. The control results by NDP algorithm was compared with those by the PI controller which is traditionally used, in both simulations and experiments. From the comparison of results, the control by NDP algorithm showed faster and better control performance than PI controller. In addition to that, the control by NDP algorithm showed the good results when it applied to the cases with disturbances and multiple set point changes.

• Journal of Wetlands Research
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• v.26 no.1
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• pp.10-20
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• 2024

The conservation and restoration of wetlands are essential tasks for the sustainable development of human society and the environment, providing vital benefits such as biodiversity maintenance, natural disaster mitigation, and climate change alleviation. This study aims to analyze the strategic interactions and interests among various stakeholders using game theory and to provide significant grounds for policy decisions related to wetland restoration and development. In this study, hypothetical scenarios were set up for three types of cities: large, medium, and small. Stakeholders such as governments, development companies, environmental groups, and local residents were identified. Strategic options for each stakeholder were developed, and a payoff matrix was established through discussions among wetland ecology experts. Subsequently, non-cooperative game theory was applied to analyze Nash equilibria and Pareto efficiency. In large cities, strategies of 'Wetland Conservation' and 'Eco-Friendly Development' were found beneficial for all stakeholders. In medium cities, various strategies were identified, while in small cities, 'Eco-Friendly Development' emerged as the optimal solution for all parties involved. The Pareto efficiency analysis revealed how the optimal solutions for wetland management could vary across different city types. The study highlighted the importance of wetland conservation, eco-friendly development, and wetland restoration projects for each city type. Accordingly, policymakers should establish regulations and incentives that harmonize environmental protection and urban development and consider programs that promote community participation. Understanding the roles and strategies of stakeholders and the advantages and disadvantages of each strategy is crucial for making more effective policy decisions.

• Journal of the Korea Society of Computer and Information
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• v.16 no.2
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• pp.25-31
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• 2011

Principal component analysis (PCA) is a well-known method for dimensionality reduction and feature extraction. Although PCA has been applied in many areas successfully, it is sensitive to outliers due to the use of sum-square-error. Several variants of PCA have been proposed to resolve the noise sensitivity and, among the variants, improved robust fuzzy PCA (RF-PCA2) demonstrated promising results. RF-PCA2, however, still can fall into a local optimum due to equal initial membership values for all data points. Another reason comes from the fact that RF-PCA2 is based on sum-square-error although fuzzy memberships are incorporated. In this paper, a variant of RF-PCA2 called RF-PCA3 is proposed. The proposed algorithm is based on the objective function of RF-PCA2. RF-PCA3 augments RF-PCA2 with the objective function of PCA and initial membership calculation using data distribution, which make RF-PCA3 to have more chance to converge on a better solution than that of RF-PCA2. RF-PCA3 outperforms RF-PCA2, which is demonstrated by experimental results.

• The Journal of the Acoustical Society of Korea
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• v.39 no.3
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• pp.151-162
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• 2020

This paper presents an acoustic inversion method for estimating the bubble size distribution. The estimation error of the attenuation coefficient represented by a Fredholm integral equation of the first kind is defined as an objective function, and an optimal solution is found by applying the Levenberg-Marquardt (LM) method. In order to validate the effectiveness of the inversion method, numerical simulations using two types of bubble distribution are performed. In addition, a series of experiments are carried out in a water tank (1.0 m × 0.54 m × 0.6 m), using bubbles generated by three different generators. Images of the distributed bubbles are obtained by a high-speed camera, and the insertion losses of the bubble layer are measured using a source and a hydrophone. The image is post-processed to glance a distribution characteristics of each bubble generator. Finally, the size distribution of bubbles is estimated by applying the inversion method to the measured insertion loss. From the inversion results, it was observed that the number of bubbles increases exponentially as the bubble size decreases, and then increases again after the local peak at 70 ㎛ - 120 ㎛.

• Journal of the Korean Institute of Intelligent Systems
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• v.13 no.2
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• pp.200-208
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• 2003

This paper proposes a separation and feature extraction of image signals using the independent component analysis(ICA) based on neural networks of efficient learning rule. The proposed learning rule is a hybrid fixed-point(FP) algorithm based on secant method and momentum. Secant method is applied to improve the performance by simplifying the 1st-order derivative computation for optimizing the objective function, which is to minimize the mutual informations of the independent components. The momentum is applied for high-speed convergence by restraining the oscillation in the process of converging to the optimal solution. The proposed algorithm has been applied to the composite images generated by random mixing matrix from the 10 images of $512\times512$-pixel. The simulation results show that the proposed algorithm has better performances of the separation speed and rate than those using the FP algorithm based on Newton and secant method. The proposed algorithm has been also applied to extract the features using a 3 set of 10,000 image patches from the 10 fingerprints of $256\times256$-pixel and the front and the rear paper money of $480\times225$-pixel, respectively, The simulation results show that the proposed algorithm has also better extraction speed than those using the another methods. Especially, the 160 basis vectors(features) of $16\times16$-pixel show the local features which have the characteristics of spatial frequency and oriented edges in the images.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.18 no.12
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• pp.140-149
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• 2017

Recently, it has become necessary to consider climate change when managing multi-purpose river functions. However, in terms of domestic rivers, the management of national and local rivers is separated and the river information cannot be integratedly handled. Especially, it is not sufficient to collect and update information by recycling reports for design and construction. In addition, the basic information of the rivers is dependent on the GIS-based RIMGIS system, but the reliability of the information is deteriorating due to the construction of spatial information using the river basement planning results. The purpose of this study is to investigate the current status of the information system with regard to the maintenance and operation of the river facilities. Through the verification of actual cases, the optimal solution was suggested from the point of view of practical information. As a result, we constructed an information system for the reliable maintenance of river facilities and examined the integrated information management plan. The results of this study can be used to improve the existing information and technical and institutional procedures for the integrated maintenance and operation of river facilities. It will be helpful to introduce the BIM as well as solve to the information gap with other fields through the establishment of an information framework to improve the information construction of river areas.

• Tunnel and Underground Space
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• v.29 no.6
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• pp.480-507
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• 2019

This paper aims at optimizing the auxiliary ventilation system in large-opening limestone mines with unducted fans. An extensive CFD and also site study were carried out for optimization at the blind entries. The fan location, operating mode, and layout are the parameters for optimization. Since the jet stream discharged from the auxiliary fan is flowing faster than 15 m/s in most of the cases, the stream collides with floor, sides or roof and even with the jet stream generated from the other fan placed upstream. Then, it is likely to lose a large portion of its inertial force and then its ventilation efficiency drops considerably. Therefore, the optimal fan installation interval is defined in this study as an interval that maximizes the uninterrupted flowing distance of the jet stream, while the cross-sectional installation location can be optimized to minimize the energy loss due to possible collision with the entry sides. Consequently, the optimization of the fan location will improve ventilation efficiency and subsequently the energy cost. A number of different three-dimensional computational domains representing a full-scale underground space were developed for the CFD study. The velocity profiles and the CO concentrations were studied to design and optimize the auxiliary ventilation system without duct and at the same time mine site experiments were carried out for comparison purposes. The ultimate goal is to optimize the auxiliary ventilation system without tubing to provide a reliable, low-cost and efficient solution to maintain the clean and safe work environment in local large-opening underground limestone mines.