• Journal of the Korean Society of Manufacturing Process Engineers
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• v.21 no.9
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• pp.78-84
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• 2022

An air circuit breaker (ACB) is an electrical protection device that interrupts abnormal fault currents that result from overloads or short circuits in a low-voltage power distribution line. The ACB consists of a main circuit part for current flow, mechanism part for the opening and closing operation of movable conductors, and arc-extinguishing part for arc extinction during the breaking operation. The driving mechanism of the ACB is a spring energy charging type. The faster the contact opening speed of the movable conductors during the opening process, the better the breaking performance. However, there is a disadvantage that the durability of mechanism decreases in inverse proportion to the use of a spring capable of accumulating high energy to configure the breaking speed faster. Therefore, to simultaneously satisfy the breaking performance and mechanical endurance of the ACB, its driving mechanism must be optimized. In this study, a dynamic model of the ACB was developed using the MDO(Mechanism Dynamics Option) module of CREO, which is widely used in multibody dynamics analysis. To improve the opening velocity, the Taguchi design method was applied to optimize the design parameters of an ACB with many linkages. In addition, to evaluate the improvement in the operating characteristics, the simulation and experimental results were compared with the MDO model and improved prototype sample, respectively.

• Nuclear Engineering and Technology
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• v.54 no.9
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• pp.3516-3525
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• 2022

The high capture cross-section (𝜎_c) of Gadolinium (Gd-155 and Gd-157) causes reactivity penalty and swing at the initial stage of fuel burnup in Pressurized Water Reactor (PWR). The present study is concerned with the feasibility of the combination of mixed burnable poison with both low and high 𝜎_c as an approach to minimize these effects. Two considered reference designs are fuel assemblies with 24 IBA rods of Gd₂O₃ and Er₂O₃ respectively. Models comprise nuclear fuel with a homogeneous mixture of Er₂O₃, AmO₂, SmO₂, and HfO₂ with Gd₂O₃ as well as the coating of PaO₂ and ZrB₂ on the Gd₂O₃ pellet's outer surface. The infinite multiplication factor was determined and reactivity was calculated considering 3% neutron leakage rate. All models except Er₂O₃ and SmO₂ showed expected results namely higher values of these parameters than the reference design of Gd₂O₃ at the early burnup period. The highest value was found for the model of PaO₂ and Gd₂O₃ followed by ZrB₂ and HfO₂. The cycle burnup, discharge burnup, and cycle length for three batch refueling were calculated using Linear Reactivity Model (LRM). The pin power distribution, energy-dependent neutron flux and Fuel Temperature Coefficient (FTC) were also studied. An optimization of model 1 was carried out to investigate effects of different isotopic compositions of Gd₂O₃ and absorber coating thickness.

• Nuclear Engineering and Technology
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• v.53 no.7
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• pp.2184-2194
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• 2021

The Free-Piston Stirling engine (FPSE) is of interest for many research in aerospace due to its advantages of long operating life, higher efficiency, and zero maintenance. In this study, a 1-kW FPSE was proposed by analyzing the requirements of Space Reactor Power Systems (SRPS), of which performance was evaluated by developing a code through the Simple Analysis Method. The results of SAM showed that the critical parameters of FPSE could satisfy the designed requirements. The heater of the FPSE was designed with the copper rectangular fins to enhance heat transfer, and the parametric study of the heater was performed with Computational Fluid Dynamics (CFD) software STAR-CCM⁺. The Performance Evaluation Criteria (PEC) was used to evaluate the heat transfer enhancement of the fins in the heater. The numerical results of the CFD program showed that pressure drop and Nusselt number ratio had a linear growth with the height of fins, and PEC number decreased as the height of fins increased, and the optimum height of the fin was set as 4 mm according to the minimum heat exchange surface area. This paper can provide theoretical supports for the design and numerical analysis of an FPSE for SRPSs.

• Geomechanics and Engineering
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• v.27 no.5
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• pp.527-535
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• 2021

The creep characteristics of rock is of great significance for the study of long-term stability of engineering, so it is necessary to carry out indoor creep test and creep model of rock. First of all, in different water-bearing state and different positive pressure conditions, the granite is graded loaded to conduct indoor shear creep test. Through the test, the shear creep characteristics of granite are obtained. According to the test results, the stress-strain isochronous curve is obtained, and then the long-term strength of granite under different conditions is determined. Then, the fractional-order calculus software element is introduced, and it is connected in series with the spring element and the nonlinear viscoplastic body considering the creep acceleration start time to form a nonlinear viscoplastic creep model with fewer elements and fewer parameters. Finally, based on the shear creep test data of granite, using the nonlinear curve fitting of Origin software and Levenberg-Marquardt optimization algorithm, the parameter fitting and comparative analysis of the nonlinear creep model are carried out. The results show that the test data and the model curve have a high degree of fitting, which further explains the rationality and applicability of the established nonlinear visco-elastoplastic creep model. The research in this paper can provide certain reference significance and reference value for the study of nonlinear creep model of rock in the future.

• Investigative Magnetic Resonance Imaging
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• v.26 no.2
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• pp.125-134
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• 2022

Purpose: The aim of this study was to investigate the change in signal sensitivity over different acquisition start times and optimize the scanning window to provide the maximal signal sensitivity of [1-¹³C]pyruvate and its metabolic products, lactate and alanine, using spatially localized hyperpolarized 3D ¹³C magnetic resonance spectroscopic imaging (MRSI). Materials and Methods: We acquired 3D ¹³C MRSI data from the brain (n = 3), kidney (n = 3), and liver (n = 3) of rats using a 3T clinical scanner and a custom RF coil after the injection of hyperpolarized [1-¹³C]pyruvate. For each organ, we obtained three consecutive 3D ¹³C MRSI datasets with different acquisition start times per animal from a total of three animals. The mean signal-to-noise ratios (SNRs) of pyruvate, lactate, and alanine were calculated and compared between different acquisition start times. Based on the SNRs of lactate and alanine, we identified the optimal acquisition start timing for each organ. Results: For the brain, the acquisition start time of 18 s provided the highest mean SNR of lactate. At 18 s, however, the lactate signal predominantly originated from not the brain, but the blood vessels; therefore, the acquisition start time of 22 s was recommended for 3D ¹³C MRSI of the rat brain. For the kidney, all three metabolites demonstrated the highest mean SNR at the acquisition start time of 32 s. Similarly, the acquisition start time of 22 s provided the highest SNRs for all three metabolites in the liver. Conclusion: In this study, the acquisition start timing was optimized in an attempt to maximize metabolic signals in hyperpolarized 3D ¹³C MRSI examination with [1-¹³C] pyruvate as a substrate. We investigated the changes in metabolic signal sensitivity in the brain, kidney, and liver of rats to establish the optimal acquisition start time for each organ. We expect the results from this study to be of help in future studies.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.16 no.2
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• pp.365-380
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• 2022

The target detection algorithm based on supervised learning is the current mainstream algorithm for target detection. A high-quality dataset is the prerequisite for the target detection algorithm to obtain good detection performance. The larger the number and quality of the dataset, the stronger the generalization ability of the model, that is, the dataset determines the upper limit of the model learning. The convolutional neural network optimizes the network parameters in a strong supervision method. The error is calculated by comparing the predicted frame with the manually labeled real frame, and then the error is passed into the network for continuous optimization. Strongly supervised learning mainly relies on a large number of images as models for continuous learning, so the number and quality of images directly affect the results of learning. This paper proposes a dataset STAR-24K (meaning a dataset for Space TArget Recognition with more than 24,000 images) for detecting common targets in space. Since there is currently no publicly available dataset for space target detection, we extracted some pictures from a series of channels such as pictures and videos released by the official websites of NASA (National Aeronautics and Space Administration) and ESA (The European Space Agency) and expanded them to 24,451 pictures. We evaluate popular object detection algorithms to build a benchmark. Our STAR-24K dataset is publicly available at https://github.com/Zzz-zcy/STAR-24K.

• Earthquakes and Structures
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• v.22 no.1
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• pp.1-13
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• 2022

When a building suffers damages under moderate to severe loading condition, its physical properties such as damping and stiffness parameters will change. There are different practical methods besides various numerical procedures that have successfully detected a range of these changes. Almost all the previous proposed methods used to work with translational components of mode shapes, probably because extracting these components is more common in vibrational tests. This study set out to investigate the influence of using both rotational and translational components of mode shapes, in detecting damages in 3-D steel structures elements. Three different sets of measured components of mode shapes are examined: translational, rotational, and also rotational/translational components in all joints. In order to validate our assumptions two different steel frames with three damage scenarios are considered. An iterative model updating program is developed in the MATLAB software that uses the OpenSees as its finite element analysis engine. Extensive analysis shows that employing rotational components results in more precise prediction of damage location and its intensity. Since measuring rotational components of mode shapes still is not very convenient, modal dynamic expansion technique is applied to generate rotational components from measured translational ones. The findings indicated that the developed model updating program is really efficient in damage detection even with generated data and considering noise effects. Moreover, methods which use rotational components of mode shapes can predict damage's location and its intensity more precisely than the ones which only work with translational data.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.16 no.8
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• pp.2529-2551
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• 2022

Visual servoing (VS) based on the Kalman filter (KF) algorithm, as in the case of KF-based image-based visual servoing (IBVS) systems, suffers from three problems in uncalibrated environments: the perturbation noises of the robot system, error of noise statistics, and slow convergence. To solve these three problems, we use an IBVS based on KF, African vultures optimization algorithm enhanced extreme learning machine (AVOA-ELM), and fuzzy logic (FL) in this paper. Firstly, KF online estimation of the Jacobian matrix. We propose an AVOA-ELM error compensation model to compensate for the sub-optimal estimation of the KF to solve the problems of disturbance noises and noise statistics error. Next, an FL controller is designed for gain adaptation. This approach addresses the problem of the slow convergence of the IBVS system with the KF. Then, we propose a visual servoing scheme combining FL and KF-AVOA-ELM (FL-KF-AVOA-ELM). Finally, we verify the algorithm on the 6-DOF robotic manipulator PUMA 560. Compared with the existing methods, our algorithm can solve the three problems mentioned above without camera parameters, robot kinematics model, and target depth information. We also compared the proposed method with other KF-based IBVS methods under different disturbance noise environments. And the proposed method achieves the best results under the three evaluation metrics.

• Corrosion Science and Technology
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• v.22 no.1
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• pp.21-29
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• 2023

In this paper, a SiC nano electroless nickel plating layer with excellent corrosion resistance was fabricated using the Taguchi method. The electroless plated low carbon steel was subjected to tests to examine the influence of corrosive media, microhardness, and corrosion rate on the corrosion resistance of this alloy. Three different corrosive media (HCl, Na₂SO₄, and NaCl) at various temperatures (80, 90, and 100 ℃) were used, and at three different times (40, 80, and 120 min.) with a speed of stirring equal to 500 rpm. The results of microhardness were found from 134.276 HV to 278.578 HV at various conditions, while the corrosion rate results were obtained from 0.89643 mpy to 7.12571 mpy at different circumstances. Corrosion, and mechanical characteristics were explained using Taguchi design. Taguchi technique was used to account for all possible combinations of elements in order to conduct a complete study. Models that link the response and procedure parameters were developed using the results of these tests, and the analysis of variance was utilized to validate these models (ANOVA). For maximum efficiency, a function called "desirability" was applied to all responses at once.

• Journal of Korean Port Research
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• v.11 no.2
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• pp.145-156
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• 1997

The purpose in this study is development of model for the Container Terminals of Pusan Port, First of all, Quantitive and Qualititve factors are characterized which effects on Physical Distribution System in Container Terminals. The System Dynamics method is used to develope the model by using these factor. This model is able to present the timinig of investment in Container Terminals of Pusan Port. Six models are showed by change of parameters in System Dynamics, in this paper. In the model, Five feedback loop were found. Loop 1 : Number of Liners$\rightarrow$Number of Congested ships$\rightarrow$Port's Charges$\rightarrow$Export & Import Cargo Volumes$\rightarrow$Number of Liners$\rightarrow$The will to investment of government$\rightarrow$Length of berth→Number of Liners. Negative loop was acquired. Loop 2 : Port's Charge$\rightarrow$Economic of Port$\rightarrow$The will to Private management$\rightarrow$Efficiency for Port's Operation$\rightarrow$Port's Charges. Positive loop was acquired. Loop 3 : Number of Congested ships$\rightarrow$Planning for future development$\rightarrow$Information Service$\rightarrow$Support service for port's user$\rightarrow$Number of Congested ships. Negative loop was acquired. Loop 4 : Number of Congested ships$\rightarrow$Planning for future development$\rightarrow$Extent of stacking area$\rightarrow$Number of handling equipmint$\rightarrow$Number of Congested ships. Negative loop was acquired. Loop 5 : Export & Import Cargo Volumes$\rightarrow$Number of Liners$\rightarrow$Econmic of Port$\rightarrow$Support service for port's user$\rightarrow$Export & Import Cargo Volumes. Positive loop was acquired. System's level variables were selected as followings ; Number of Liners, Number of Congested ships, Export & Import Carge Volumes, Length of berth, and Port's Charges. As result of simmulation of model, fluctuation of respective year was found in level variables. This fluctuation can be used properly to present timing of investment.