• Nuclear Engineering and Technology
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• v.55 no.2
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• pp.460-474
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• 2023

A simple but accurate mathematical model is crucial for dynamic simulations and controller design of helical coil once-through steam generator (OTSG). This paper presents a three-region movable boundary dynamic model of the helical coil OTSG. Based on the secondary side fluid conditions, the OTSG is divided into subcooled region (two control volumes), two-phase region (two control volumes) and superheated region (three control volumes) with movable boiling boundaries between each region. The nonlinear dynamic model is derived based on mass, energy and momentum conservation equations. And the linear model is obtained by using the transfer function and state space transformation, which is a 37-order model of five input and three output. Validations are made under full-power steady-state condition and four transient conditions. Results show good agreements among the nonlinear model, linear model and the RELAP5 model, with acceptable errors. This model can be applied to dynamic simulations and controller design of helical coil OTSG with constant primary-side flow rate.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.26 no.11
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• pp.1679-1685
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• 2022

In this paper, we propose an optimal multi-hop transmission scheme to maximize the end-to-end data rate from the source to the destination node in a wireless powered communication network. The frame structure for multi-hop transmission is presented to transmit multi-hop data while harvesting energy. Then, the transmission time of each node that maximizes the end-to-end transmission rate is determined through mathematical analysis in consideration of different harvested energy and link quality among nodes. We derive an optimization problem through system modeling of the considered wireless powered multi-hop transmission, and prove that there is a global optimal solution by verifying the convexity of this optimization problem. This analysis facilitates to find the optimal solution of the considered optimization problem. The proposed optimal multi-hop transmission scheme maximizes the end-to-end rate by allocating the transmission time for each node that equalizes the transmission rates of all links.

• Journal of Korean Society for Quality Management
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• v.50 no.1
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• pp.153-167
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• 2022

Purpose: The purpose of this study is to guide the operation managers who plan daily production of large mass-processing facility that services multi-customers with multi-product, small-batch item characteristics by providing the practical best production quantity and the inventory allowed to build. Methods: Close observation of a subcontract paint-shop operator captured the daily decision process which was reflected in the subcontractor-unique mathematical model and the system dynamics simulation model. Multiple simulations were run to find the practical best production quantity and the maximum allowable stock level of inventory that did not undermine the profit from practical best daily production. Actual data and a few constant values were obtained from the firm under study. Results: While the inventory holding cost for the customer-owned material harms the total profit of the subcontractor, the running cost of the processing facility hinders production in small batches. This balances the maximum possible productions and results in practical best daily production which can be found through simulation runs with actual data. The maximum level of stocked inventory is deduced from the practical best daily production. Conclusion: To build a large volume that enables economy-of-scale production, operators should deal with multi-product small-batch items from multiple customers. When the planned schedule of the time and amount of material in-flow tend not to be reliable, operators can find it practical to execute level production across the planning horizon instead of adjusting to day-to-day in-flow fluctuations.

• Smart Structures and Systems
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• v.31 no.3
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• pp.213-227
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• 2023

A passive prismatic-shaped isolation platform (PIP) is proposed to realize enhanced quasi-zero stiffness (QZS) effect. The design concept uses a horizontal spring to produce a tunable negative stiffness and installs oblique springs inside the cells of the prismatic structure to provide a tunable positive stiffness. Therefore, the QZS effect can be achieved by combining the negative stiffness and the positive stiffness. To this aim, firstly, the mathematical modeling and the static analysis are conducted to demonstrate this idea and provide the design basis. Further, with the parametric study and the optimal design of the PIP, the enhanced QZS effect is achieved with widened QZS range and stable property. Moreover, the dynamic analysis is conducted to investigate the vibration isolation performance of the proposed PIP. The analysis results show that the widened QZS property can be achieved with the optimal designed structural parameters, and the proposed PIP has an excellent vibration isolation performance in the ultra-low frequency due to the enlarged QZS range. Compared with the traditional QZS isolator, the PIP shows better performance with a broader isolation frequency range and stable property under the large excitation amplitude.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.28 no.1B
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• pp.137-147
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• 2008

Soil Vapor Extraction (SVE) has been extensively used to remove volatile organic compounds (VOCs) from the vadoze zone. In order to investigate the removal mechanism during SVE operation, laboratory modeling experiments were carried out and tailing effect could be observed in later stage of the experiment. Tailing effect means that removal rate of contaminants gets significantly to decrease in later stage of SVE operation. Also, mathematical model simulating the tailing effect was used, which considers rate-limited diffusion in a water film during mass transfer among gas, liquid, and solid phases. Measurement data obtained through the experiment was used as input data of the numerical analyses. Sensitivity analysis was performed to examine the effect of each parameter on required time to reach final target concentration. Finally, it was found that the concentration in the soil phase decreased significantly with a liquid and gas diffusion coefficient larger, actual path length shorter, and water saturation smaller.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.26 no.4B
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• pp.433-437
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• 2006

Recently, mathematical modeling for the activated sludge process is important to design and control of wastewater treatment plant. Nevertheless, there is a lack of information regarding the pathway of substrate utilization between external and internal substrates in biological nutrient removal (BNR). In this research, a new activated sludge model (step growth model) is proposed and compare with ASM No.3. This model structure is consist of five processes; aerobic storage, growth on external substrate and stored intercellular storage compounds (ISCs), endogenous respiration and aerobic respiration of ISCs. The predicted results by the step growth model were more good accordance with the results of oxygen utilization rate (OUR) and TCOD experiment than that of the ASM No.3.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2022.10a
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• pp.110-113
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• 2022

Nowadays, breaking through the conventional traffic signal control method based on mathematical optimization, artificial intelligence began to be used in the area. In response to this trend, many studies are ongoing to figure out how to utilize AI technology properly for traffic signal optimization. They just simply focus on which method will work well besides lots of machine learning techniques and abandon the reward function engineering. In many cases, the reward function consists of the average delay of the vehicles in the intersection. However, this may lead to AI's misunderstanding about the traffic signal control: what AI regards as a good situation may not be realistic. Even the reward function itself may not meet the service level. Therefore, this study analyzes the problems of previous reward functions and will suggest how to reward function can be enhanced.

• Journal of Korea Society of Industrial Information Systems
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• v.29 no.1
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• pp.49-62
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• 2024

In this paper, a sustainable closed-loop supply chain (SCLSC) network model is proposed for domestic mobile phone industry. Economic, environmental and social factors are respectively considered for reinforcing the sustainability of the SCLSC network model. These three factors aim at minimizing total cost, minimizing total amount of CO₂ emission, and maximizing total social influence resulting from the establishment and operation of facilities at each stage of the SCLSC network model. Since they are used as each objective function in modeling, the SCLSC network model can be a multi-objective optimization problem. A mathematical formulation is used for representing the SCLSC network model and a hybrid meta-heuristic approach is proposed for efficiently solving it. In numerical experiment, the performance of the proposed hybrid meta-heuristic approach is compared with those of conventional meta-heuristic approaches using some scales of the SCLSC network model. Experimental results shows that the proposed hybrid meta-heuristic approach outperforms conventional meta-heuristic approaches.

• Journal of IKEEE
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• v.28 no.2
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• pp.136-144
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• 2024

In this paper, we propose a PID controller for altitude control of quadrotor system with experimental analysis. The Routh-Hurwitz test is applied to analyze the system to which our proposed controller is applied. We also summarize experimental data in which the gain values of kP, kI, and kD are changed using MATLAB and Simulink based on mathematical modeling of the quadrotor system. Based on the summarized experimental data, we analyze the effect of changes in each gain values (k_P, k_I, k_D) of PID controller on altitude control of quadrotor, and present an algorithm for tuning the PID controller gain values. The PID controller with the proposed algorithm is applied to AR.Drone system, subsequently and result are verifised through experiments.

• The Journal of the Acoustical Society of Korea
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• v.43 no.1
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• pp.9-18
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• 2024

The importance of active sonar systems is emerging due to the quietness of underwater targets and the increase in ambient noise due to the increase in maritime traffic. However, the low signal-to-noise ratio of the echo signal due to multipath propagation of the signal, various clutter, ambient noise and reverberation makes it difficult to identify underwater targets using active sonar. Attempts have been made to apply data-based methods such as machine learning or deep learning to improve the performance of underwater target recognition systems, but it is difficult to collect enough data for training due to the nature of sonar datasets. Methods based on mathematical modeling have been mainly used to compensate for insufficient active sonar data. However, methodologies based on mathematical modeling have limitations in accurately simulating complex underwater phenomena. Therefore, in this paper, we propose a sonar signal synthesis method based on a deep neural network. In order to apply the neural network model to the field of sonar signal synthesis, the proposed method appropriately corrects the attention-based encoder and decoder to the sonar signal, which is the main module of the Tacotron model mainly used in the field of speech synthesis. It is possible to synthesize a signal more similar to the actual signal by training the proposed model using the dataset collected by arranging a simulated target in an actual marine environment. In order to verify the performance of the proposed method, Perceptual evaluation of audio quality test was conducted and within score difference -2.3 was shown compared to actual signal in a total of four different environments. These results prove that the active sonar signal generated by the proposed method approximates the actual signal.