• 제어로봇시스템학회:학술대회논문집
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• 2001.10a
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• pp.92.5-92
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• 2001

The KOMPSAT-1(Korea Multi-Purpose Satellite-1) is the first multi-purpose satellite funded by Korean government for the purpose of remote sensing and scientific data gathering in KOREA. It has successfully achieved its own mission since Dec. 21, 1999. This paper provides an overview of the KOMPSAT-1 missions and addresses the nominal mission planning and operation flow. This paper also describes the routine operational orbit determination and orbit prediction process using GPS navigation solution data. Meanwhile, some problems due to inexperience of the multiple mission operations during LEOP(Launch & Early Orbit Phase) and early normal mission were investigated. Then, resolutions that include the development of new mission planning tool are addressed. The KOMPSAT-1´s missions become more complicated rather than its Initially designed ones. In order to accomplish ...

• Advances in aircraft and spacecraft science
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• v.7 no.1
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• pp.79-90
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• 2020

The dynamic coupling between shaker and test-article has been investigated by recent research through the so called Virtual Shaker Testing (VST) approach. Basically a VST model includes the mathematical models of the test-item, of the shaker body, of the seismic mass and the facility vibration control algorithm. The subsequent coupled dynamic simulation even if more complex than the classical hard-mounted sine test-prediction, is a closer representation of the reality and is expected to be more accurate. One of the most remarkable benefits of VST is the accurate quantification of the frequency down-shift (with respect to the hard-mounted value), typically affecting the first lateral resonance of heavy test-items, like medium or large size Spacecraft (S/Cs), once mounted on the shaker. In this work, starting from previous successful VST experiences, the parameters having impact on the frequency shift are identified and discussed one by one. A simplified analytical system is thus defined to propose an efficient and effective way of calculating the lower bound frequency shift through a simple equation. Such equation can be useful to correct the S/C lateral natural frequency measured during the test, in order to remove the contribution attributable to the shaker in use. The so-corrected frequency value becomes relevant when verifying the compliance of the S/C w.r.t. the frequency requirement from the Launcher Authority. Moreover, it allows to perform a consistent post-test correlation of the first lateral natural frequency of S/C FE model.

• Journal of Computational Design and Engineering
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• v.3 no.1
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• pp.1-13
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• 2016

The increase of consumer needs for quality metal cutting related products with more precise tolerances and better product surface roughness has driven the metal cutting industry to continuously improve quality control of metal cutting processes. In this paper, two different approaches are discussed. First, design of experiments (DOE) is used to determine the significant factors and then fuzzy logic approach is presented for the prediction of surface roughness. The data used for the training and checking the fuzzy logic performance is derived from the experiments conducted on a CNC milling machine. In order to obtain better surface roughness, the proper sets of cutting parameters are determined before the process takes place. The factors considered for DOE in the experiment were the depth of cut, feed rate per tooth, cutting speed, tool nose radius, the use of cutting fluid and the three components of the cutting force. Finally the significant factors were used as input factors for fuzzy logic mechanism and surface roughness is predicted with empirical formula developed. Test results show good agreement between the actual process output and the predicted surface roughness.

• 한국태양에너지학회:학술대회논문집
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• 2009.11a
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• pp.142-147
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• 2009

In order to achieve performance assessment and optimal control of a double-skin system, an accurate simulation model is required. In the previous study, a lumped simulation model of such system was developed. As a follow-up of the previous research, the first objective of this paper is to investigate how the mathematical model should be calibrated according to system configuration(cavity width, depth, height, airflow pattern, local environment, etc.). And the second objective of this study is to discuss the effect of local weather information. In conclusion, this paper describes that the model should be recalibrated according to configuration. And it is necessary to have local weather information for accurate prediction and optimal control of the system.

• Journal of Navigation and Port Research
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• v.45 no.6
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• pp.284-297
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• 2021

A simple kinematic model for the prediction of ship manoeuvres based on trial data is proposed in this study. The model consists of first order differential equations in surge, sway, and yaw directions which simulate the time series of each velocity component. Actually instead of sea trial data, dynamic model simulations are conducted with randomly varied control inputs such as propeller revolution rates and rudder angles. Based on learning of control inputs and velocity outputs of dynamic model simulations in sufficient time, kinematic model coefficients are optimized so that the kinematic model can be approximately reproduce the velocity outputs of dynamic model simulations with arbitrary control inputs. The resultant kinematic model is verified with new dynamic simulation sets.

• Journal of Korean Society for Atmospheric Environment
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• v.21 no.6
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• pp.573-583
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• 2005

Fugitive dust, which is emitted in the ambient air without first passing through a stack or duct designed to control flow, is frequently generated by means of wind erosion from storage yards at Pohang Steel Wokrs. The size distribution of fugitive dust is mostly in the range of coarse particulate which is deposited as soon as emitted and less harm to human health; however $20\%$ of fugitive dust contains PM 10 known as one of most harmful airborne pollutant. Consequently, effective control and reduction of fugitive dust is strongly requested by the local society, but it is not easy so far because the generation and dispersion of fugitive dust highly depends on meteorological conditions, and it being occurred for irregularity. This research presented a fugitive dust control system for each meteorological condition by providing statistical prediction data obtained from a statistical analysis on the probability of generating the threshold velocity at which the fugitive dust begins to occur, and the frequency occurring by season and by time of the wind direction that can generate atmospheric pollution when the dispersed dust spreads to adjacent residential areas. The research also built a fugitive dust detection system which monitors the weather conditions surrounding storage yards and the changes in air quality on a real-time basis and issues a warning message by identifying a situation where the fugitive dust disperses outside the site boundary line so that appropriate measures can be taken on a timely basis. Furthermore, in respect to the spraying of water to prevent the generation of fugitive dust from the storage piles at the storage yard, an advanced statistical meteorological analysis on the weather conditions in Pohang area and a case study of fugitive dust dispersion toward outside of working field during $2002\∼2003$ were carried out in order to decide an optimal water-spraying time and the number of spraying that can prevent the origin of fugitive dust emission. The results of this research are expected to create extremely significant effects in improving surrounding environment through actual reduction of the fugitive dust produced from the storage yard of Pohang Steel Works by providing a high-tech warning system capable of constantly monitoring the leakage of fugitive dust and water-spray guidance that can maximize the water-spraying effects.

• Structural Engineering and Mechanics
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• v.81 no.6
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• pp.665-675
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• 2022

The safety problems of giant hydraulic structures such as dams caused by terrorist attacks, earthquakes, and wars often have an important impact on a country's economy and people's livelihood. For the national defense department, timely and effective assessment of damage to or impending damage to dams and other structures is an important issue related to the safety of people's lives and property. In the field of damage assessment and vulnerability analysis, it is usually necessary to give the damage assessment results within a few minutes to determine the physical damage (crack length, crater size, etc.) and functional damage (decreased power generation capacity, dam stability descent, etc.), so that other defense and security departments can take corresponding measures to control potential other hazards. Although traditional numerical calculation methods can accurately calculate the crack length and crater size under certain combat conditions, it usually takes a long time and is not suitable for rapid damage assessment. In order to solve similar problems, this article combines simulation calculation methods with machine learning technology interdisciplinary. First, the common concrete gravity dam shape was selected as the simulation calculation object, and XFEM (Extended Finite Element Method) was used to simulate and calculate 19 cracks with different initial positions. Then, an LSTM (Long-Short Term Memory) machine learning model was established. 15 crack paths were selected as the training set and others were set for test. At last, the LSTM model was trained by the training set, and the prediction results on the crack path were compared with the test set. The results show that this method can be used to predict the crack propagation path rapidly and accurately. In general, this article explores the application of machine learning related technologies in the field of mechanics. It has broad application prospects in the fields of damage assessment and vulnerability analysis.

• The Transactions of the Korean Institute of Electrical Engineers B
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• v.53 no.3
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• pp.143-151
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• 2004

High-speed permanent magnet machines are likely to be a key technology for electric drives and motion control systems for many applications, since they are conductive to high efficiency, high power density, small size and low weight. In high-speed machines, the permanent magnets are often contained within a retaining sleeve. However, the sleeve and the magnets are exposed to high order flux harmonics, which cause parasitic eddy current losses. Rotor losses of high-speed machines are of great importance especially in high-speed applications, because losses heat the rotor, which is often very compact construction and thereby difficult to cool. This causes a danger of demagnetization of the NdFeB permanent magnets. Therefore, special attention should be paid to the prediction of the rotor losses. This paper is concerned with the rotor losses in permanent magnet high-speed machines that are caused by permeance variation due to stator slotting. First, the flux harmonics are determined by double Fourier analysis of the normal flux density data over the rotor surface. And then, the rectilinear model was used to calculate rotor losses in permanent magnet machines. Finally, Poynting vector have been used to investigate the rotor eddy current losses of high-speed Permanent magnet machine.

• Proceedings of the Computational Structural Engineering Institute Conference
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• 1992.10a
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• pp.67-72
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• 1992

The heat of hydration of cement causes the internal temperature rise at early age, particulary in massive concrete structures such as a footing of nuclear reactor building or a dam. As the result of the temperature rise and restraint of foundation, the thermal stress may induce cracks in concrete. Therefore, the prediction of the thermal stress is very important in the design and construction stages in order to control the cracks developed in massive concrete structures. And, in case of young concrete, creep effect by the temperature load is larger than That of old concrete. Thus the effect of creep must be considered for checking the cracks, serviceability, durability and leakage. This study is composed of two items. The first, it is to develop a finite element program which is capable of simulating the temperature history in mass concrete. The second, when the thermal stress of mass concrete structures considering creep is calculated by using the modified elastic modulus due to the inner temperature change. It is shown that the analytical results of this study is in comparably good agreement with JCI's analytical results.

• Research in Plant Disease
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• v.26 no.3
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• pp.121-133
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• 2020

Climate change, increased extreme weather and climate events, and rapidly changing socio-economic environment threaten agriculture and thus food security of our society. Therefore, it is urgent to shift from conventional farming to smart agriculture using big data and artificial intelligence to secure sustainable growth. In order to efficiently manage plant diseases through smart agriculture, agricultural big data that can be utilized with various advanced technologies must be secured first. In this review, we will first learn about agrometeorological big data consisted of meteorological, environmental, and agricultural data that the plant pathology communities can contribute for smart plant disease management. We will then present each sequential components of the smart plant disease management, which are prediction, monitoring and diagnosis, control, prevention and risk management of plant diseases. This review will give us an appraisal of where we are at the moment, what has been prepared so far, what is lacking, and how to move forward for the preparation of smart plant disease management.