• Journal of the Korean Society for Aeronautical & Space Sciences
• /
• v.42 no.8
• /
• pp.661-673
• /
• 2014

In this paper, a precise orbit determination process was carried out based on KARISMA(KARI Collision Risk Management System) developed by KARI(Korea Aerospace Research Institute), in which optical tracking data of a geostationary satellite was used. The real optical tracking data provided by ESA(European Space Agency) for the ARTEMIS geostationary satellite was used. And orbit determination error was approximately 420 m compared to that of the ESA's orbit determination result from the same optical tracking data. In addition, orbit prediction was conducted based on the orbit determination result with optical tracking data for 4 days, and the position error for the orbit prediction during 3 days was approximately 500~600 m compared to that of ESA's result. These results imply that the performance of the KARISMA's orbit determination function is suitable to apply to the collision risk assessment for the space debris.

• Geomechanics and Engineering
• /
• v.12 no.3
• /
• pp.361-397
• /
• 2017

The unloading effect from excavations can cause the deformation of adjacent tunnels, which may seriously influence the operation and safety of those tunnels. However, systematic studies of the deformation characteristics of tunnels located along side excavations are limited, and simplified methods to predict the influence of excavations on tunnels are also rare. In this study, the simulation capability of a finite element method (FEM) considering the small-strain characteristics of soil was verified using a case study. Then, a large number of FEM simulations examining the influence of excavations on adjacent tunnels were conducted. Based on the simulation results, the deformation characteristics of tunnels at different positions and under four deformation modes of the retaining structure were analyzed. The results indicate that the deformation mode of the retaining structure has a significant influence on the deformation of certain tunnels. When the deformation magnitudes of the retaining structures are the same, the influence degree of the excavation on the tunnel increased in this order: from cantilever type to convex type to composite type to kick-in type. In practical projects, the deformation mode of the retaining structure should be optimized according to the tunnel position, and kick-in deformation should be avoided. Furthermore, two methods to predict the influence of excavations on adjacent tunnels are proposed. Design charts, in terms of normalized tunnel deformation contours, can be used to quantitatively estimate the tunnel deformation. The design table of the excavation influence zones can be applied to determine which influence zone the tunnel is located in.

• Proceedings of the KSRS Conference
• /
• 1998.09a
• /
• pp.236-241
• /
• 1998

The NOAA AVHRR remote sense SST data, collected by the National Fisheries Research and Development Institute (NFRDI), are analyzed in order to understand the spatial and temporal distributions of SST in the seas adjacent to Korea. Our study is based on 10-day SST images during last 7 years (1991-1997). For a time series analysis of multiple 557 images, all of images must be aligned exactly at the same position by adjusting the scales and positions of each SST image. We devised an algorithm which yields automatic detections of cloud pixels from multiple SST images. The cloud detection algorithm is based on a physical constraint that SST anomalies in the ocean do not exceed certain limits (we used $\pm$ 3$^{\circ}C$ as a criterion of SST anomalies). The remote sense SST data are tuned by comparing remote sense data with observed SST at coastal stations. Seasonal variations of SST are studied by harmonic fit of SST normals at each pixel. The SST anomalies are studied by statistical method. We found that the SST anomalies are rather persistent with time scales between 1 and 2 months. Utilizing the persistency of SST anomalies, we devised an algorithm for a prediction of future SST Model fit of SST anomalies to the Markov process model yields that autoregression coefficients of SST anomalies during a time elapse of 10 days are between 0.5 and 0.7. We plan to improve our algorithms of automatic cloud pixel detection and prediction of future SST. Our algorithm is expected to be incorporated to the operational real time service of SST around Korea.

• Journal of KIISE:Computing Practices and Letters
• /
• v.8 no.6
• /
• pp.765-777
• /
• 2002

For the battlefield analysis, it is required to get correct information about the identification and moving status of target enemy units. However, it is difficult for us to collect all of the information perfectly, because of the technology of communications, jamming, and tactics. Therefore, we need a reasoning function that predicts and analyzes future moving status for target units by using collected moving information and domain knowledge. Especially. since the moving units have characteristics of moving objects, which change their position and shape over time, they require functions to manage and predict locations of moving objects. Therefore, in this paper, we propose a location prediction system of moving units for battlefield analysis. The proposed system not only predicts unknown units, unidentified units, and main strike directions to application domain for battlefield analysis, but also estimates the past or future locations of moving objects not stored in a database.

• Journal of the Korea Institute of Military Science and Technology
• /
• v.16 no.4
• /
• pp.523-536
• /
• 2013

A recent air defense missile system is required to have a capability to intercept short-range super-high speed targets such as tactical ballistic missile(TBMs) by performing engagement control efficiently. Since flight time and distance of TBM are very short, the missile defense system should be ready to engage a TBM as soon as it takes an indication of the TBM launch. As a result, it has to predict TBM trajectory accurately with cueing information received from an early warning system, and designate search direction and volume for own radar to detect/track TBM as fast as it can, and also generate necessary engagement information. In addition, it is needed to engage TBM accurately via transmitting tracked TBM position and velocity data to the corresponding intercept missiles. In this paper, we proposed a method to estimate TBM trajectory based on the Kepler's law for the missile system to detect and track TBM using the cueing information received before the TBM arrives the apogee of the ballistic trajectory, and analyzed the bias of prediction error in terms of the transmission period of cueing data between the missile system and the early warning system.

• Journal of the Society of Naval Architects of Korea
• /
• v.57 no.1
• /
• pp.35-44
• /
• 2020

Propeller cavitation extent, pressure fluctuation induced by cavitation, pressure distribution on propeller blade, total velocity distribution and nominal wake distribution for a MR Taker were computed in both conditions of model test and sea trial using a code STAR-CCM⁺. Then some of the results were compared with model test data at LCT and full-scale measurement (Ahn et al (2014); Kim et al (2014)] in order to confirm the availability of a numerical prediction method and to get the physical insight of local flow around a ship and propeller. The nominal wake distributions computed and measured by LDV velocimeter on the variation of on-coming velocity show the wake contraction characteristics proposed by Hoekstra (1974). The numerical prediction of propeller cavitation extent on a blade angular position and pressure fluctuation level on each location of pressure sensors are very similar with the experimental results.

• Journal of the Korean Society of Propulsion Engineers
• /
• v.22 no.6
• /
• pp.111-117
• /
• 2018

In this study, an MEMS thrust measurement system was designed and a study on the performance prediction of system was performed to evaluate the performance of micro thruster. Thrust measurement system consists of beam, membrane, and piezoresistive sensor. An FEM analysis was carried out to verify the stability of the system, confirm the stress variation at the beam, and position the piezoresistive sensor. The stability of the designed system was verified by comparing the yield strength of the material with the maximum stress. The piezoresistive sensor was designed to be 20% of the length of the beam to obtain a high gauge factor. The size of the membrane and the beam of the reference model were designed to be $15mm{\times}15mm$, and $500{\mu}m{\times}500{\mu}m$, respectively.

• Proceedings of the National Institute of Ecology of the Republic of Korea
• /
• v.2 no.1
• /
• pp.1-14
• /
• 2021

The study has been carried out with an objective to prepare Siberian roe deer habitat potential maps in South Korea based on three geographic information system-based models including frequency ratio (FR) as a bivariate statistical approach as well as convolutional neural network (CNN) and long short-term memory (LSTM) as machine learning algorithms. According to field observations, 741 locations were reported as roe deer's habitat preferences. The dataset were divided with a proportion of 70:30 for constructing models and validation purposes. Through FR model, a total of 10 influential factors were opted for the modelling process, namely altitude, valley depth, slope height, topographic position index (TPI), topographic wetness index (TWI), normalized difference water index, drainage density, road density, radar intensity, and morphological feature. The results of variable importance analysis determined that TPI, TWI, altitude and valley depth have higher impact on predicting. Furthermore, the area under the receiver operating characteristic (ROC) curve was applied to assess the prediction accuracies of three models. The results showed that all the models almost have similar performances, but LSTM model had relatively higher prediction ability in comparison to FR and CNN models with the accuracy of 76% and 73% during the training and validation process. The obtained map of LSTM model was categorized into five classes of potentiality including very low, low, moderate, high and very high with proportions of 19.70%, 19.81%, 19.31%, 19.86%, and 21.31%, respectively. The resultant potential maps may be valuable to monitor and preserve the Siberian roe deer habitats.

• Korean Journal of Remote Sensing
• /
• v.40 no.3
• /
• pp.269-274
• /
• 2024

High-quality precipitation data are crucial for various industries, including disaster prevention. In South Korea, long-term high-quality data are collected through numerous ground observation stations. However, data between these stations are reprocessed into a grid format using interpolation methods, which may not perfectly match actual precipitation. A prime example of real-time observational grid data globally is the Integrated Multi-satellite Retrievals for Global Precipitation Measurement (GPM IMERG) from National Aeronautics and Space Administration (NASA), while in South Korea, ground radar data are more commonly used. GPM and ground radar data exhibit distinct differences due to their respective processing methods. This study aims to analyze the characteristics of GPM and Constant Altitude Plan Position Indicator(CAPPI),representative real-time grid data, by comparing them with ground-observed precipitation data. The study period spans from 2021 to 2022, focusing on hourly data from Automated Synoptic Observing System (ASOS) sites in South Korea. The GPM data tend to underestimate precipitation compared to ASOS data, while CAPPI shows errors in estimating low precipitation amounts. Through this comparative analysis, the study anticipates identifying key considerations for utilizing these data in various applied fields, such as recalculating design rainfall, thereby aiding researchers in improving prediction accuracy by using appropriate data.

• Nuclear Engineering and Technology
• /
• v.56 no.10
• /
• pp.4412-4422
• /
• 2024

The CFETR multipurpose overload robot (CMOR) is a critical component of the fusion reactor remote handling system. To accurately calculate and visualize the structural deformation and stress characteristics of the CMOR motion process, this paper first establishes a CMOR kinematic model to analyze the unfolding and working process in the vacuum chamber. Then, the dynamic model of CMOR is established using the Lagrangian method, and the rigid-flexible coupling modeling of CMOR links and joints is achieved using the finite element method and the linear spring damping equivalent model. The co-simulation results of the CMOR rigid-flexible coupled model show that when the end load is 2000 kg, the extreme value of the end-effector position error is more than 0.12 m, and the maximum stress value is 1.85 × 10⁸ Pa. To utilize the stress-strain data of CMOR, this paper designs a CMOR morphology prediction control system based on Unity software. Implanting CMOR finite element analysis data into the Unity environment, researchers can monitor the stress strain generated by different motion trajectories of the CMOR robotic arm in the control system. It provides a platform for subsequent research on CMOR error compensation and extreme operation warnings.