• Proceedings of the Korean Society of Propulsion Engineers Conference
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• 2017.05a
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• pp.746-752
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• 2017

High test hydrogen peroxide has been widely developed as green propellant for thrusters. Hydrogen peroxide is decomposed in the catalyst bed to produce the thrust. Catalyst bed design optimization is considered through existing model for catalyst beds. To verify the model, static firing tests were conducted under various conditions using a 100 N scale $H_2O_2$ monopropellant thruster. Temperature and pressure estimations from the model were well correlated to the experimental data. The model is used to obtain optimal design parameters by analyzing the catalyst capacity and pressure drop data for various simulated conditions. Catalyst beds can be optimized from the analysis of the catalyst capacity and pressure drop correlation through catalyst bed modeling.

• Applied Chemistry for Engineering
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• v.34 no.6
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• pp.619-625
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• 2023

In order to solve problems caused by the heat load of hypersonic aircraft, this study examined the optimization of the Si/Al ratio of the catalyst and nickel ion exchange to improve the performance of the hydrocarbon decomposition reaction (endothermic reaction). It was confirmed that the catalysts prepared through Si/Al ratio optimization and nickel ion exchange showed about 10% improvement in heat absorption performance compared to thermal cracking at 4 MPa and 550 ℃. FT-IR and NH₃-TPD analyses were found to identify factors affecting activity changes, and it was observed that the Si/Al ratio of the HZSM-5 catalyst was closely correlated with acid site development and catalytic activity. In addition, TGA and O₂-TPO analyses were conducted to observe the carbon deposition inhibition properties of the nickel-added catalyst.

• Journal of Korean Society for Quality Management
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• v.50 no.4
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• pp.701-716
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• 2022

Purpose: This study aims to predict the dry cargo transportation market economy. The subject of this study is the BDI (Baltic Dry Index) time-series, an index representing the dry cargo transport market. Methods: In order to increase the accuracy of the BDI time-series, we have pre-processed the original time-series via time-series decomposition and data augmentation techniques and have used them for ANN learning. The ANN algorithms used are Multi-Layer Perceptron (MLP), Recurrent Neural Network (RNN), and Long Short-Term Memory (LSTM) to compare and analyze the case of learning and predicting by applying time-series decomposition and data augmentation techniques. The forecast period aims to make short-term predictions at the time of t+1. The period to be studied is from '22. 01. 07 to '22. 08. 26. Results: Only for the case of the MAPE (Mean Absolute Percentage Error) indicator, all ANN models used in the research has resulted in higher accuracy (1.422% on average) in multivariate prediction. Although it is not a remarkable improvement in prediction accuracy compared to uni-variate prediction results, it can be said that the improvement in ANN prediction performance has been achieved by utilizing time-series decomposition and data augmentation techniques that were significant and targeted throughout this study. Conclusion: Nevertheless, due to the nature of ANN, additional performance improvements can be expected according to the adjustment of the hyper-parameter. Therefore, it is necessary to try various applications of multiple learning algorithms and ANN optimization techniques. Such an approach would help solve problems with a small number of available data, such as the rapidly changing business environment or the current shipping market.

• Korean Management Science Review
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• v.32 no.1
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• pp.49-63
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• 2015

This paper investigates an aircraft-target assignment problem in consideration of deconfliction. The aircraft-target assignment problem is the problem to assign available aircrafts and weapons to targets that should be attacked, where the objective function is to minimize the total expected damage of aircrafts. Deconfliction is the way of dividing airspaces for aircraft flight to ensure the safety while performing the mission. In this paper, mixed integer programming model is suggested, where it considers deconfliction between aircrafts. However, the suggested MIP model is non-linear and limited to get solution for large size problem. The 2-phase decomposition model is suggested for efficiency and computation, where in the first phase target area is divided into sectors for deconfliction and in the second phase aircrafts and weapons are assigned to given targets for minimizing expected damage of aircraft. The proposed decomposition model shows outperforms the model developed for comparison in the computational experiment.

• Nuclear Engineering and Technology
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• v.55 no.3
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• pp.827-838
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• 2023

Centrifugal pump is a key part of nuclear power plant systems, and its health status is critical to the safety and reliability of nuclear power plants. Therefore, fault diagnosis is required for centrifugal pump. Traditional fault diagnosis methods have difficulty extracting fault features from nonlinear and non-stationary signals, resulting in low diagnostic accuracy. In this paper, a new fault diagnosis method is proposed based on the improved particle swarm optimization (IPSO) algorithm-based variational modal decomposition (VMD) and relevance vector machine (RVM). Firstly, a simulation test bench for rotor faults is built, in which vibration displacement signals of the rotor are also collected by eddy current sensors. Then, the improved particle swarm algorithm is used to optimize the VMD to achieve adaptive decomposition of vibration displacement signals. Meanwhile, a screening criterion based on the minimum Kullback-Leibler (K-L) divergence value is established to extract the primary intrinsic modal function (IMF) component. Eventually, the factors are obtained from the primary IMF component to form a fault feature vector, and fault patterns are recognized using the RVM model. The results show that the extraction of the fault information and fault diagnosis classification have been improved, and the average accuracy could reach 97.87%.

• Journal of applied mathematics & informatics
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• v.26 no.5_6
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• pp.1021-1035
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• 2008

In this paper, we analyze an N-design call center with skill-based routing, in which one pool of agents handles two types of calls and another pool of agents handles only one type of calls. The approximate analysis is motivated by a computational complexity that has been observed in the direct stochastic approach and numerical method for finding performance measures. The workforce staffing policy is very important to the successful management of call centers. So the allocation scheduling of the agents can be considered as the optimization problem of the corresponding queueing system to the call center. We use a decomposition algorithm which divides the state space of the queueing system into the subspaces for the approximate analysis of the N-design call center with two different types of agents. We also represent some numerical examples and show the impact of the system parameters on the performance measures.

• Journal of Communications and Networks
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• v.13 no.6
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• pp.633-638
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• 2011

In this paper, we consider resource allocation with proportional fairness in the downlink orthogonal frequency division multiple access relay networks, in which relay nodes operate in decode-and-forward mode. A joint optimization problem is formulated for relay selection, subcarrier assignment and power allocation. Since the formulated primal problem is nondeterministic polynomial time-complete, we make continuous relaxation and solve the dual problem by Lagrangian dual decomposition method. A near-optimal solution is obtained using Karush-Kuhn-Tucker conditions. Simulation results show that the proposed algorithm provides superior system throughput and much better fairness among users comparing with a heuristic algorithm.

• Bulletin of the Korean Chemical Society
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• v.26 no.8
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• pp.1177-1184
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• 2005

Ab initio quantum chemical molecular orbital calculations have been performed for the unimolecular decomposition of methacrylonitrile ($CH_3C(CN)=CH_2$), especially for HCN and $H_2$ molecular elimination channels. Structures and energies of the reactants, products, and relevant species along the individual reaction pathways were determined by MP2 gradient optimization and MP4 single point energy calculations. Direct four-center elimination of HCN and three-center elimination of H2 channels were identified. In addition, H or CN migration followed by HCN or H2 elimination channels via the methylcyanoethylidene intermediate was also identified. Unlike the case of crotonitrile previously studied, in which the dominant decomposition process was the direct three-center elimination of HCN, the most important reaction pathway should be the direct threecenter elimination of $H_2$ in the case of methacrylonitrile.

• 한국연소학회:학술대회논문집
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• 2015.12a
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• pp.107-108
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• 2015

The acoustic optimization of a swirl coaxial jet injector mounted upstream a combustion chamber is investigated to tackle combustion instabilities. The least damped modes are extracted with the help of the dynamic mode decomposition (DMD). The sensitivity of the heat release perturbation to the velocity perturbation for the second longitudinal mode is investigated by combining the Crocco's equation and the inhomogeneous wave equation and computing the flame transfer function (FTF). DMD and FTF results agree in terms of the optimized injector length.

• Geomechanics and Engineering
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• v.7 no.2
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• pp.149-164
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• 2014

One of the most advanced classes of techniques for ground response analysis is based on the use of Transfer Functions. They represent the ratio of Fourier spectrum of amplitude motion at the free surface to the corresponding spectrum of the bedrock motion and they are applied in frequency domain usually by FFT method. However, Fourier spectrum only shows the dominant frequency in each time step and is unable to represent all frequency contents in every time step and this drawback leads to inaccurate results. In this research, this process is optimized by decomposing the input motion into different frequency sub-bands using Wavelet Multi-level Decomposition. Each component is then processed with transfer Function relating to the corresponding component frequency. Taking inverse FFT from all components, the ground motion can be recovered by summing up the results. The nonlinear behavior is approximated using an iterative procedure with nonlinear soil properties. The results of this procedure show better accuracy with respect to field observations than does the Conventional method. The proposed method can also be applied to other engineering disciplines with similar procedure.