• KOREAN JOURNAL OF PACKAGING SCIENCE & TECHNOLOGY
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• v.28 no.3
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• pp.211-215
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• 2022

Air distribution occupies an important position in the smart unit load container design process for agricultural products. Inner air may be uncomfortable because of its temperature, speed, direction, and volume flow rate. It doesn't matter how efficient the ventilation equipment is if the air is not distributed well. The main aim of this study was to design the inlet and outlet fan locations of smart unit load container for agricultural products. A numerical study was performed on the effects of the location of inlet air and outlet air in relation to the container cooling sources on air distribution and thermal comfort. A concept of combining inner container cooling sources with the exhaust outlet was employed in this investigation. Also, in this research, the developed CFD (Computational Fluid Dynamics) models were thoroughly validated. This system was adopted for use in container spaces, where the exhaust outlet was located. In this study, the location of the inlet was derived through CFD for a container with a size of 1,100×1,100×1,700 mm, and it was derived that the inlet was located at the center of the lower part of the container for efficient air flow. It was efficient to position the outlet through the air inlet in the center of the lower part of the container at the top of the same side.

• Journal of Drive and Control
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• v.19 no.1
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• pp.16-25
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• 2022

The purpose of this study was to calculate and analyze the engine load factor of major agricultural operations using a 78 kW class agricultural tractor for estimating the emission of air pollutants and greenhouse. Engine load data were collected using controller area network (CAN) communication. Main agricultural operations were selected as plow tillage (PT), rotary tillage (RT), baler operation (BO), loader operation (LO), driving on soil (DS), and driving on concrete (DC). The engine power was calculated using the measured engine load data. A weight factor was applied to load factor for considering usage ratio according to agricultural operations. Weight factors for different agricultural operations were calculated to be 27.4%, 32.9%, 17.5%, 7.7%, 4.5%, and 10.0% for PT, RT, BO, LO, DS, and DC, respectively. As a result of the field test, load factors were 0.74, 0.93, 0.41, 0.23, 0.27, and 0.21 for PT, RT, BO, LO, DS, and DC, respectively. The engine load factor was the highest for RT. Finally, as a result of applying the weight factor for usage ratio of agricultural operations, the integrated engine load factor was estimated to be 0.63, which was about 1.31 times higher than the conventional applied load factor of 0.48. In future studies, we plan to analyze the engine load factor by considering various horsepower and working conditions of the tractor.

• Journal of Drive and Control
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• v.20 no.1
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• pp.16-26
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• 2023

Although the upland field area of Korea is high as 44.8%, the platform optimized for the upland field is insufficient. It is necessary to develop an optimized platform for the upland field because the upland field environment is an irregular environment with many slopes. In addition, due to the characteristic of agricultural operations, the traction power and torque of the platform have to be sufficient. Therefore, in this study, a simulation model that can predict the traction power and driving torque of a crawler-type platform for the upland field was developed and validated using the specifications of the crawler platform. The simulation model was developed using Amesim (19.1, Siemens, Germany). The development of the model was conducted using the specifications of the platform. A measurement system was developed to validate the simulation model. The traction power data of the simulation model was validated with the traction force and vehicle speed. The driving torque data of the simulation model was validated with the torque of the sprocket on the crawler system. As a result of the analysis, the error between measurement and simulation results occurred within 10%, and it was determined that the traction power and driving torque prediction of the crawler platform using this model was possible.

• Smart Media Journal
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• v.11 no.5
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• pp.9-16
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• 2022

Recently, agricultural sites are automating into digital agricultural smart farms by applying technologies such as big data and Internet of Things (IoT). These smart farms aim to increase production and improve crop quality by measuring the environment of crops, investigating and processing data. Production prediction is an important study in smart farm digital agriculture, which is a high-tech agriculture, and it is necessary to analyze environmental data using big data and further standardized research to manage the quality of growth information data. In this paper, environmental and production data collected from smart farm strawberry farms were analyzed and studied. Based on regression analysis, crop production prediction models were analyzed using Ridge Regression, LightGBM, and XGBoost. Among the three models, the optimal model was XGBoost, and R2 showed 82.5 percent explanatory power. As a result of the study, the correlation between the amount of positive fluid absorption and environmental data was confirmed, and significant results were obtained for the production prediction study. In the future, it is expected to contribute to the prevention of environmental pollution and reduction of sheep through the management of sheep by studying the amount of sheep absorption, such as information on the growing environment of crops and the ingredients of sheep.

• Smart Structures and Systems
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• v.16 no.5
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• pp.807-833
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• 2015

While tuned mass dampers are found to be effective in suppressing vibration in a tall building, integrating it with a semi-active control system enables it to perform more efficiently. In this paper a forty-story tall steel-frame building designed according to the Canadian standard, has been studied with and without semi-active and passive tuned mass dampers. The building is assumed to be located in the Vancouver, Canada. A magneto-rheological fluid based semi-active tuned mass damper has been optimally designed to suppress the vibration of the structure against seismic excitation, and an appropriate control procedure has been implemented to optimize the building's semi-active tuned mass system to reduce the seismic response. Furthermore, the control system parameters have been adjusted to yield the maximum reduction in the structural displacements at different floor levels. The response of the structure has been studied with a variety of ground motions with low, medium and high frequency contents to investigate the performance of the semi-active tuned mass damper in comparison to that of a passive tuned mass damper. It has been shown that the semi-active control system modifies structural response more effectively than the classic passive tuned mass damper in both mitigation of maximum displacement and reduction of the settling time of the building.

• Korean Journal of Air-Conditioning and Refrigeration Engineering
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• v.19 no.8
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• pp.577-584
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• 2007

A variable-flow-rate balancing valve has been developed and optimized to apply to a distributor in a hot-water heating system. Fluid dynamic performance of the system was evaluated by comparing the results with the previous pressure difference control valve (PDCV) system. In view of the variations of pressure drop and flow rate according to the sequential closing of the control valves, the present system which is named "smart system distributor", is very stable without a certain flow rate concentration. The level of pressure drop variation is also low as compared with the previous system with a PDCV. In view of the occurrence of cavitation, the present system is quite superior to the previous system because the instantaneous pressures at all sections are much higher than the vapor pressure. On the other hand, the previous system has a possibility of cavitation when one or more control valves are closed.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2002.11b
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• pp.210-215
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• 2002

MR(Magnetorheogical) fluid composed of fine iron powders dispersed in silicon oil is utilized to many smart structures and devices because of its significant rheological property change by the application of an external magnetic field. When we deal with the shock wave attenuation of warship structures, we should be able to characterize the high frequency behavior of MR fluids. So far, however, many efforts have been focused on the material characterization of MR fluids at low frequencies below 100Hz. In this paper, the MR fluid property characterization at high frequency region is performed. An experimental setup based on wave transmission technique is made and the storage modulus as well as the loss modulus of MR fluids are found from the measured data of speed sound and attenuation. Details of the experiment are addressed and the obtained storage and loss moduli are addressed at $50kHz{\sim}100kHz$.

• Smart Structures and Systems
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• v.5 no.3
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• pp.261-277
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• 2009

A fuzzy-sliding mode controller is presented to control the dynamics of semi-active suspension systems of vehicles using magneto-rheological (MR) fluid dampers. A full car model is used to design and evaluate the performance of the proposed semi-active controlled suspension system. Four mixed mode MR dampers are designed, manufactured, and integrated with four independent sliding mode controllers. The siding mode controller is designed to decrease the energy consumption and maintain robustness. In order to overcome the chattering of the sliding mode controllers, a fuzzy logic control strategy is merged into the sliding mode controller. The proposed fuzzy-sliding mode controller is designed and fabricated. The performance of the semi-active suspensions is evaluated in both the time and frequency domains. The obtained results demonstrate that the proposed fuzzy-sliding mode controller can effectively suppress the vibration of vehicles and improve their ride comfort and handling stability. Furthermore, it is shown that the "chattering" of the sliding mode controller is smoothed when it is integrated with a fuzzy logic control strategy. Although the cost function of the fuzzy-sliding mode control is a slightly higher than that of a classical LQR controller, the control effectiveness and robustness are enhanced considerably.

• Computers and Concrete
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• v.20 no.6
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• pp.671-682
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• 2017

In this research, seismic response of pipes is examined by applying nanotechnology and piezoelectric materials. For this purpose, a pipe is considered which is reinforced by carbon nanotubes (CNTs) and covered with a piezoelectric layer. The structure is subjected to the dynamic loads caused by earthquake and the governing equations of the system are derived using mathematical model via cylindrical shell element and Mindlin theory. Navier-Stokes equation is employed to calculate the force due to the fluid in the pipe. Mori-Tanaka approach is used to estimate the equivalent material properties of the nanocomposite and to consider the effect of the CNTs agglomeration on the scismic response of the structure. Moreover, the dynamic displacement of the structure is extracted using harmonic differential quadrature method (HDQM) and Newmark method. The main goal of this research is the analysis of the seismic response using piezoelectric layer and nanotechnology. The results indicate that reinforcing the pipeline by CNTs leads to a reduction in the displacement of the structure during an earthquake. Also the negative voltage applied to the piezoelectric layer reduces the dynamic displacement.

• Journal of the Society of Naval Architects of Korea
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• v.59 no.6
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• pp.393-399
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• 2022

During the ship hull design process, resistance performance estimation is generally calculated by simulation using computational fluid dynamics. Since such hull resistance performance simulation requires a lot of time and computation resources, the time taken for simulation is reduced by CPU clusters having more than tens of cores in order to complete the hull design within the required deadline of the ship owner. In this paper, we propose a method for estimating resistance performance of ship hull by simulation using a graph neural network. This method converts the 3D geometric information of the hull mesh and the physical quantity of the surface into a mathematical graph, and is implemented as a deep learning model that predicts the future simulation state from the input state. The method proposed in the resistance performance experiment of simple hull showed an average error of about 3.5 % throughout the simulation.