• International Journal of Aeronautical and Space Sciences
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• v.17 no.2
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• pp.240-252
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• 2016

In this paper, an on-board orbit propagator and compressing trajectory method based on B-spline for a lunar explorer are proposed. An explorer should recognize its own orbit for a successful mission operation. Generally, orbit determination is periodically performed at the ground station, and the computed orbit information is subsequently uploaded to the explorer, which would generate a heavy workload for the ground station and the explorer. A high-performance computer at the ground station is employed to determine the orbit required for the explorer in the parking orbit of Earth. The method not only reduces the workload of the ground station and the explorer, but also increases the orbital prediction accuracy. Then, the data was compressed into coefficients within a given tolerance using B-spline. The compressed data is then transmitted to the explorer efficiently. The data compression is maximized using the proposed methods. The methods are compared with a fifth order polynomial regression method. The results show that the proposed method has the potential for expansion to various deep space probes.

• The Proceedings of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.7 no.4
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• pp.26-33
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• 1993

The acoustic emission automatic detection system is developed to observe tree deterioration phenomena. Applying an alternating voltage of 15(kVnns) toXLPE tree specimens, many pulses of small amplitude are detected when the bush type tree developes branch type and a few pulses of high amplitude prcxluced as branch type propagated to bush type tree. Therefore, it is known that pulses having small amplitude operates as a destructive factor. It is observed that the skewness of the amplitude and the number of average pulses as distribution tendency of three dimension are characteristic quantity of AE pulses. As the trajectory of skewness is farther from the origin on the S-plane, it is more likely to breakdown.

• Nuclear Engineering and Technology
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• v.55 no.6
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• pp.2011-2017
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• 2023

Gas submerged jet is an outstanding thermohydraulic phenomenon in pool scrubbing of fission products during a severe nuclear accident. Experiments were performed on the hydraulic characteristics in the ranges of air mass flux 0.1-1400 kg/m²s and nozzle diameter 10-80 mm. The results showed that the dependence of inlet pressure on the mass flux follows a power law in subsonic jets and a linear law in sonic jets. The effect of nozzle submerged depth was negligible. The isolated bubbling regime, continuous bubbling regime, transition regime, and jetting regime were observed in turn, as the mass flux increased. In the bubbling regime and jetting regime, the air volume fraction distribution was approximately symmetric in space. Themelis model could capture the jet trajectory well. In the transition regime, the air volume fraction distribution loses symmetry due to the bifurcated secondary plume. The Li correlation and Themelis model showed sufficient accuracy for the prediction of jet penetration length.

• Korean Journal of Applied Biomechanics
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• v.17 no.1
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• pp.81-90
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• 2007

The effort identifying positioning information of the moving object in real time has been a issue not only in sport biomechanics but also other academic areas. In order to solve this issue, this study tried to track the movement of a pitched ball that might provide an easier prediction because of a clear focus and simple movement of the object. Machine learning has been leading the research of extracting information from continuous images such as object tracking. Though the rule-based methods in artificial intelligence prevailed for decades, it has evolved into the methods of statistical approach that finds the maximum a posterior location in the image. The development of machine learning, accompanied by the development of recording technology and computational power of computer, made it possible to extract the trajectory of pitched baseball from recorded images. We present a method of baseball tracking, based on object tracking methods in machine learning. We introduce three state-of-the-art researches regarding the object tracking and show how we can combine these researches to yield a novel engine that finds trajectory from continuous pitching images. The first research is about mean shift method which finds the mode of a supposed continuous distribution from a set of data. The second research is about the research that explains how we can find the mode and object region effectively when we are given the previous image's location of object and the region. The third is about the research of representing data into features that we can deal with. From those features, we can establish a distribution to generate a set of data for mean shift. In this paper, we combine three works to track baseball's location in the continuous image frames. From the information of locations from two sets of images, we can reconstruct the real 3-D trajectory of pitched ball. We show how this works in real pitching images.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.18 no.5
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• pp.183-193
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• 2019

This study developed a shockwave detection and prediction of their extinction point method based on continuous wavelet transform using trajectory data from probe vehicles equipped with automotive sensors.. To analyze the effectiveness of the proposed method, this paper proposed two measures which are a distance error between the extinction points of the predictor and an time-location error of the extinction points. The proposed concept was proved using the micro simulation based experiment with three exogenous variables of traffic volume, lane-close duration, market penetration of probe vehicles. The analysis results show that the proposed method is capable of detecting the traffic shockwaves as well as predicting their extinction point, and also that the accuracy of the proposed method is highly dependent on the rate of the probe vehicles.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.49 no.12
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• pp.989-996
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• 2021

In the case of an unmanned aerial vehicle using a battery as a power source, there are restrictions in performing the mission because the battery capacity is limited. To extend the mission capability, it is important to minimize battery usage while the flight to the mission area. In addition, by using the battery usage prediction model, the possibility of mission completeness can be determined and it can be a criterion for selecting an emergent landing point in the mission planning stage. In this paper, we propose a battery usage prediction model considering as one of the environmental factors in the three-dimensional space. The required power is calculated according to the flight geometry of an unmanned aerial vehicle. True battery usage which is predicted from the required power is verified through the comparison with the battery usage prediction model. The optimal flight trajectory that minimizes battery usage is produced and compared with the shortest travel distance.

• Journal of Korean Society of Coastal and Ocean Engineers
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• v.34 no.1
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• pp.11-18
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• 2022

In order to improve the accuracy of particle tracking prediction techniques near the Korean Strait, this study compared and analyzed a particle tracking model based on a seawater flow numerical model and a machine learning based on a particle tracking model using field observation data. The data used in the study were the surface drifter buoy movement trajectory data observed in the Korea Strait, prediction data by machine learning (linear regression, decision tree) using the tide and wind data from three observation stations (Gageo Island, Geoje Island, Gyoboncho), and prediciton data by numerical models (ROMS, MOHID). The above three data were compared through three error evaluation methods (Correlation Coefficient (CC), Root Mean Square Errors (RMSE), and Normalized Cumulative Lagrangian Separation (NCLS)). As a final result, the decision tree model had the best prediction accuracy in CC and RMSE, and the MOHID model had the best prediction results in NCLS.

• Geomechanics and Engineering
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• v.32 no.1
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• pp.49-68
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• 2023

The three-dimensional failure criterion is essential for maintaining wellbore stability and sand production problem. The convenient factor for a stable wellbore is mud weight and borehole orientation, i.e., mud window design and selection of borehole trajectory. This study proposes a new three-dimensional failure criterion with linear relation of three in-situ principal stresses. The number of failure criteria executed to understand the phenomenon of rock failure under in-situ stresses is the Mohr-Coulomb criterion, Hoek-Brown criterion, Mogi-Coulomb criterion, and many more. A new failure criterion is the extended Mohr-Coulomb failure criterion with the influence of intermediate principal stress (σ₂). The influence of intermediate principal stress is considered as a weighting of (σ₂) on the mean effective stress. The triaxial compression test data for eleven rock types are taken from the literature for calibration of material constant and validation of failure prediction. The predictions on rock samples using new criteria are the best fit with the triaxial compression test data points. Here, Drucker-Prager and the Mogi-Coulomb criterion are also implemented to predict the failure for eleven different rock types. It has been observed that the Drucker-Prager criterion gave over prediction of rock failure. On the contrary, the Mogi-Coulomb criterion gave an equally good prediction of rock failure as our proposed new 3D failure criterion. Based on the yield surface of a new 3D linear criterion it gave the safest prediction for the failure of the rock. A new linear failure criterion is recommended for the unique solution as a linear relation of the principal stresses rather than the dual solution by the Mogi-Coulomb criterion.

• Journal of the Korean Society for Marine Environment & Energy
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• v.12 no.4
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• pp.264-272
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• 2009

Due to an oil spill accident occurred in Taean coastal zone wide range of coastal waters were polluted. Inaccurate prediction of spilled oil trajectory is known as a cause that has increased the pollution damage in the beginning stage. In this study, a numerical modeling of spilled oil dispersion has been conducted to know which physical factors caused the severe and wide pollution. Especially the simulation is focused on how to model hydrodynamic circulation accurately. The simulation results showed that the hydrodynamic flow is very important in predicting oil fate, specially, in the short-term dispersion of spilled oil.

• Journal of Electrical Engineering and Technology
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• v.12 no.1
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• pp.272-283
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• 2017

In this paper, an improved predictive functional control (PFC) scheme for permanent magnet synchronous motor (PMSM) control system is proposed, on account of the standard PFC method cannot provides a satisfying disturbance rejection performance in the case of strong disturbances. The PFC-based method is first introduced in the control design of speed loop, since the good tracking and robustness properties of the PFC heavily depend on the accuracy of the internal model of the plant. However, in orthodox design of prediction model based control method, disturbances are not considered in the prediction model as well as the control design. A minimum-order observer (MOO) is introduced to estimate the disturbances, which structure is simple and can be realized at a low computational load. This paper adopted the MOO to observe the load torque, and the observations are then fed back into PFC model to rebuild it when considering the influence of perturbation. Therefore, an improved PFC strategy with torque compensation, called the PFC+MOO method, is presented. The validity of the proposed method was tested via simulation and experiments. Excellent results were obtained with respect to the speed trajectory tracking, stability, and disturbance rejection.