• Nuclear Engineering and Technology
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• v.55 no.9
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• pp.3126-3132
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• 2023

To meet the increasing heating needs of the China Fusion Experimental Tokamak Reactor (CFETR), the output power in each Lower Hybrid Current Drive (LHCD) transmission line should be increased from 250 kW to 500 kW. Therefore, a new high-power water load must be developed for the 4.6 GHz 500 kW LHCD system. This paper aims to report the most recent research progress of the water load: aluminum nitride (AlN) ceramic is used as the media material to isolate the water and vacuum, and the radio frequency (RF) simulation results show that the return loss of the water load is less than -25dB at 4.6 GHz over a wide temperature range. Under 500 kW continuous wave (CW) operation, the maximum temperatures of the ceramic and water are separately 67 ℃ and 62 ℃, resulting in thermal deformation of the ceramic of approximately 0.003 mm. Moreover, the AlN water load was tested on the 4.6 GHz 250 kW high-power test bench and found to work well with low reflected power.

• Journal of the Korean Society for Precision Engineering
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• v.12 no.6
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• pp.120-127
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• 1995

A nonlinear empirical state-space model of the Artificial Neural Network(ANN) has been developed. The nonlinear model structure incorporates characteristic, so as to enable identification of the transient response, as well as the steady-state response of a dynamic system. A hybrid feedfoward/feedback neural network, namely a Local Time Delayed Recurrent Multi-layer Perception(RMLP), is the model structure developed in this paper. RMLP is used to identify nonlinear dynamic system in an input/output sense. The feedfoward protion of the network architecture provides with the well-known curve fitting factor, while local recurrent and cross-talk connections provides the dynamics of the system. A dynamic learning algorithm is used to train the proposed network in a supervised manner. The derived dynamic learning algorithm exhibit a computationally desirable characteristic; both network sweep involved in the algorithm are performed forward, enhancing its parallel implementation. RMLP state-space and its associate learning algorithm is demonstrated through a simple examples. The simulation results are very encouraging.

• Nuclear Engineering and Technology
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• v.54 no.11
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• pp.4226-4230
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• 2022

The Korea Atomic Energy Research Institute (KAERI) has designed a Hybrid-Low Power Research Reactor (H-LPRR) which can be used for critical assembly and conventional research reactor as well. It is an open tank-in-pool type research reactor (Thermal Power: 50 kW_th) of which the most important applications are Neutron Activation Analysis (NAA), Radioisotope (RI) production, education and training. There are eight irradiation holes on the edge of the reactor core: IR (6 holes for RI production) and NA (2 holes for NAA) holes. In order to quantify the elemental concentration in target samples through the Instrumental Neutron Activation Analysis (INAA), it is necessary to measure neutron spectrum parameters such as thermal neutron flux, the deviation from the ideal 1/E epithermal neutron flux distribution (α), and the thermal-to-epithermal neutron flux ratio (f) for the irradiation holes. In this study, the MCNP6.1 code and FORTRAN 90 language are applied to determine the parameters for the two irradiation holes (NA-SW and NA-NW) in H-LPRR, and in particular its α and f parameters are compared to values of other research reactors. The results confirmed that the neutron irradiation holes in H-LPRR are designed to be sufficiently applied to neutron activation analysis, and its performance is comparable to that of foreign research reactors including the TRIGA MARK II.

• Nuclear Engineering and Technology
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• v.55 no.5
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• pp.1838-1854
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• 2023

This paper presents a hybrid algorithm to solve the multi-objective path planning (MOPP) problem for mobile robots in a static nuclear accident environment. The proposed algorithm mimics a real nuclear accident site by modeling the environment with a two-layer cost grid map based on geometric modeling and Monte Carlo calculations. The proposed algorithm consists of two steps. The first step optimizes a path by the hybridization of improved ant colony optimization algorithm-modified A^* (IACO-A^*) that minimizes path length, cumulative radiation dose and energy consumption. The second module is the high radiation dose rate avoidance strategy integrated with the IACO-A^* algorithm, which will work when the mobile robots sense the lethal radiation dose rate, avoiding radioactive sources with high dose levels. Simulations have been performed under environments of different complexity to evaluate the efficiency of the proposed algorithm, and the results show that IACO-A^* has better path quality than ACO and IACO. In addition, a study comparing the proposed IACO-A^* algorithm and recent path planning (PP) methods in three scenarios has been performed. The simulation results show that the proposed IACO-A^* IACO-A^* algorithm is obviously superior in terms of stability and minimization the total cost of MOPP.

• Journal of Auto-vehicle Safety Association
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• v.15 no.4
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• pp.95-101
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• 2023

As the popularization of autonomous vehicles is anticipated, it is expected that the variety of passenger postures will diversify. However, the current vehicle safety system is expected to be inadequate for accommodating these diverse passenger postures, particularly in reclined positions where severe injuries have been reported in frontal collisions. Therefore, it is necessary to investigate the biomechanical responses and tolerances of occupants in reclined postures. In this study, the behavior and injuries of a Hybrid-III dummy model in a reclined position are analyzed through frontal collision sled simulations equipped with the semi-rigid seat provided by the previous study, three-point safety belt with pretensioner and load limiter, and airbag models. The results are evaluated by comparing thouse reponses with post-mortem human surrogate (PMHS) data, and the findings are expected to be applicable to the basic design of a new restraint system suitable for various postures in autonomous vehicles.

• Journal of the korean academy of Pediatric Dentistry
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• v.51 no.1
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• pp.22-31
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• 2024

The objective of this study was to assess the wear resistance of tooth-colored materials used in crown restoration for primary molars with a chewing simulator. In this study, four groups-three experimental groups and one control group-were included. They consisted of three-dimensional (3D) printed resin crowns (NextDent and Graphy), milled nano-hybrid ceramic crowns (MAZIC Duro), and prefabricated zirconia crowns (NuSmile). Twelve mandibular second molar specimens were prepared from each group. In the wear experiment, 6.0 × 10⁵ cycles were conducted with a force of 50 N, and a 6 mm-diameter steatite ball was used as an antagonist. The amount of wear was calculated by comparing the scan files before and after the chewing simulation using 3D metrology software, and the worn cross-section was confirmed by scanning electron microscopy (SEM). The resin and ceramic groups did not exhibit any statistically significant differences. However, compared to other crown groups, the zirconia crown group demonstrated notably reduced levels of wear (p < 0.05). In SEM images, layers and cracks were observed in the 3D-printed resin crown groups, which differed from those in the other groups.

• Journal of the Korea Institute of Military Science and Technology
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• v.27 no.3
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• pp.416-427
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• 2024

The wake-homing underwater guided weapon that detects and tracks wake generated during voyage of a surface ship is impossible to avoid with the present acoustic deception torpedo defense system. Therefore, research on bubble-generating wake decoy is necessary to deceive wake-homing underwater guided weapon. Experiments in various environments are required to verify the effective operation method and performance of the wake decoy, but performance verification through underwater experiment is limited. In this paper, we develop a simulator for an torpedo defense system of surface ship, which is applied bubble-generating wake decoy, against acoustic, wake, and hybrid homing underwater guided weapon attack. The simulator includes surface ship model, acoustic decoy(static, mobile) model, bubble-generating wake decoy model, search and motion model of underwater guided weapon and so on. By integrating various models, MATLAB GUI simulator was developed. Through the simulation results for various environmental variables by this simulator, it is judged that effective operation method and performance verification of the bubble-generating wake decoy can be performed.

• Structural Engineering and Mechanics
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• v.89 no.3
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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.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.37C no.11
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• pp.1094-1103
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• 2012

Recently, software industry regarding national defense increases system development of distributed simulation system of M&S based to overcome limit of resource and expense. It is one of key technologies for offering of mutual validation among objects and reuse of objects which are discussed for developing these systems. RTI, implementation of HLA interface specification as software providing these technologies uses Federation Object Model for exchanging information with joined federates in the federation and each federate has a characteristic that is supposed to have identical FOM in the federation. This technology is a software which is to provide the core technology which was suggested by the United state's military M&S standard framework. Simulator, virtual simulation, and inter-connection between military weapons system S/W which executes on network which is M&S's core base technology, and it is a technology which also can be used for various inter-connection between S/W such as game and on-line phone. These days although RTI is used in military war game or tactical training unit field, there is none in Korea. Also, it is used in mobile-game, distribution game, net management, robot field, and other civilian field, but the number of examples are so small and informalized. Through this developing project, we developed the core technique and RTI software and provided performance of COTS level to improve communication algorithms.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.22 no.4
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• pp.580-586
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• 2021

The CAT methodology is a numerical analysis technique using CAE. Recently, a methodology of applying artificial intelligence techniques to a simulation has been studied. A previous study compared the deformation results according to the injection molding process using a machine learning technique. Although MLP has excellent prediction performance, it lacks an explanation of the decision process and is like a black box. In this study, data was generated using Autodesk Moldflow 2018, an injection molding analysis software. Several Machine Learning Algorithms models were developed using RapidMiner version 9.5, a machine learning platform software, and the root mean square error was compared. The decision-tree showed better prediction performance than other machine learning techniques with the RMSE values. The classification criterion can be increased according to the Maximal Depth that determines the size of the Decision-tree, but the complexity also increases. The simulation showed that by selecting an intermediate value that satisfies the constraint based on the changed position, there was 7.7% improvement compared to the previous simulation.