• Aerospace Engineering and Technology
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• v.4 no.2
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• pp.15-20
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• 2005

Most of studies for the ground load and ground behavior of landing gear have been conducted with an assumption that the structure of landing gear was rigid body. The assumption of rigid body during design process results in many errors or discrepancy. High ground load occurs in 3 directions on the shock absorbing strut during landing. This ground load initiated high structural deformation. In this study, the flex-multi-body dynamics is applied to adapt flexible bodies, so the results of analysis can be described close to landing gears real behaviour.

• Journal of the Korea Society of Computer and Information
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• v.16 no.12
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• pp.103-112
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• 2011

Motion estimation (ME) is regarded as an important component in a video encoding process, because it consumes a large computation complexity. H.264/AVC requires additional computation overheads for fractional search and interpolation. This causes a problem that computational complexity is increased. In Motion estimation, SATD(Sum of Transform Difference) has the characteristics of a parabolic based on the minimum point. In this paper, we propose new prediction algorithm to reduce search point in motion estimation by sub-pixel interpolation characteristics. The proposed algorithm reduces the time of encoding process by decreasing computational complexity. Experimental results show that the proposed method reduces 20% of the computation complexity of motion estimation, while the degradation in video quality is negligible.

• Proceedings of the Korean Institute Of Construction Engineering and Management
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• 2006.11a
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• pp.137-142
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• 2006

Cost and duration is important factors which directly affect profit therefore must be forecasted correctly to accomplish success of projects. So construction company uses EVMS(Earned Value Management System) to forecast final cost and duration. But previous forecasting model has low accuracy because of its linear forecasting method and can't reflect characteristic of company and project and changes as each progress. This paper presents cost and duration forecasting model using the slope prediction of cost and duration as each progress to reflect the various characteristics of construction industry. EVMS data of 23 road construction projects was used to make up regression analysis equation of slope forecasting model.

• Journal of KIISE:Computing Practices and Letters
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• v.10 no.3
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• pp.273-281
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• 2004

There is the temporal correlation of the video sequence between the motion vector of current block and the motion vector of previous block. In this paper, we propose the prediction search algorithm for block matching using the temporal correlation of the video sequence and the center-biased property of motion vectors. The proposed algorithm determines the location of a better starting point for the search of an exact motion vector using the point of the smallest SAD(sum of absolute difference) value by the predicted motion vector from the same block of the previous frame and the predictor candidate point on each search region. Simulation results show that PSNR(Peak-to-Signal Noise Ratio) values are improved up to the 1.06㏈ as depend on the video sequences and improved about 0.19∼0.46㏈ on an average except the full search(FS) algorithm.

• Proceedings of the Korea Water Resources Association Conference
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• 2023.05a
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• pp.460-460
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• 2023

최근 범 지구적인 기후변화로 인해 집중호우가 빈번히 발생하고 침수피해가 증가하고 있다. 이에 따른 침수 피해 위험이 큰 지하상가, 지하 주차장, 반지하 주택 등의 침수 발생이 잦아지며 인명 및 재산 피해 발생이 커지고 있다. 이러한 지역은 인근 하수관로의 수위에 따라 침수 영향을 크게 받게 된다. 이에 따른 강우·유출 관계는 침수피해에 대해 대처하기 위해 시공간적 강우 특성이 반영된 하수관로 수위 예측이 중요하다고 판단된다. 이에 본 연구에서 수위 자료는 서울시 하수관로 수위 현황 자료를 활용하였으며, 강수량 자료는 서울 내 서초구 일대의 강수량 자료를 활용하여 연구를 진행하였다. 대상 지역은 저지대에 위치해 침수가 잦은 서초구 서초동으로 선정하였으며, 분석에 사용된 기간은 2012년부터 2021년까지의 수위 자료를 화용하여 이를 바탕으로 순환 신경망인 RNN의 일종이며, 다른 모델의 구조와 비교하여 더욱 간단하고 효율적인 ESN(Echo State Network) 알고리즘을 사용하여 수위 예측을 진행하였다. 분석을 위해 대상 지역의 강수 사상이 발생하여 하수관로의 수위의 변동이 큰 기간을 선정하여 분석을 실시하였다. 2012년부터 2018년까지의 자료를 학습(training) 자료로 활용하였으며, 모형의 검증 위해 통계분석을 실시하여 검증하였다.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 1990.10a
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• pp.173-178
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• 1990

로터-베어링축계는 증기및 가스터빈, 터보 발전기, 압축기등 거의 모든 산업 기계류에서 동력 전달의 기본 도구로써 사용되고 있다. 즉 회전에 의한 동력 의전달은 비교적 간단히 대용량의 동력을 효율적으로 전달할 수 있다. 이에 따라 회전기계류에 대한 연구는 산업 혁명 이후 꾸준히 발전되어 온바, 특히 근래에 들어와 산업기계류의 경쟁이 치열하여짐에 따라 산업기계류의 고정 밀화, 고속화, 고신뢰화 요구가 증대하고 있는 현실을 비추어 볼때, 산업 기 계류의 근간을 이루고 있는 로터-베어링 축계의 안정성을 포함한 진동에 관 한 문제는 회전기계류 설계의 주요 기술로써 연구.개발의 필요성이 매우 높 다 하겠다. 회전축계 진동 관련 연구는 두 분야로 대별될 수 있는데 언밸런 스(Unbalance)에 의한 Synchronous진동과 여러가지 원인에 의해 계의 불안 정성을 유발시키는 Nonsynchronous진동으로 나눌 수 있다. 본 연구에서는 이들 연구의 기본이 되는 회전축-베어링계 동특성 해석 프로그램을 개발하 였다. 여러가지 방법이 있으나 여기서는 Holzer가 비틀림 진동에 적용하고, Mykiestad(2)와 Prohl(3)에 의하여 회전축의 횡 진동에 적용된 이후 Lund(4) 등에 의하여 베어링의 영향등이 첨가된 전달 매트릭스 (Transfer Matrix) 방 법을 이용하여 임계속도(Critical Speed), 모우드 형태(Mode shapes)를 예측 하고 불안정 판정(Instability Criteria)등을 할 수 있는 프로그램을 개발하였 다. 특히 Murphy(1)의 다항식 방법(Polynomial Method)에 기본을 두어 기존 의 전달 매트릭스가 가지고 있던 반복, 수렴 시간 문제와 빠뜨리는 임계속도 예측에 대한 개선을 이루었으며 기존 논문과 실험 결과와의 비교 검토를 통 하여 개발된 프로그램의 신뢰성을 검토하였다. 특히, 각종 회전 기계의 소형 화, 경량화 추세에 따라 지반이나 케이싱이 경량이거나 유연하여 회전축과 동적으로 연성된 경우 회전축-베어링-지반으로 이루어진 2중구조의 회전축 계 동특성을 해석할 수 있는 프로그램을 개발하므로서 회전 기계류의 진동 전반에 걸친 문제점에 대한 그 원인과 현상을 명확히 분석하여 국내의 전기 계류의 보다 신뢰성있는 설계 및 제작자료를 확보하는데 기여할 수 있게 하 였다.

• Proceedings of the Korean Society of Propulsion Engineers Conference
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• 2011.11a
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• pp.22-29
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• 2011

Critical speed of high thrust liquid rocket engine turbopump is obtained through a rotordynamic analysis and a unloaded turbopump test is peformed for validation of the numerical model. The first critical speed predicted by the numerical analysis is correlated well with the test result for the bearing unloaded rotor condition only considering mass unbalance load. Using the previous rotordynamic model, critical speed variation is estimated as a function of varied bearing stiffness due to pump and turbine radial loads with relative angle difference. From the numerical analysis, it is found that the relative angle difference of pump and turbine radial loads greatly affects the critical speed. However, additional axial load reduces the effect derived from the relative angle difference of radial loads.

• Journal of the Korean Society of Propulsion Engineers
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• v.16 no.4
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• pp.42-49
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• 2012

Critical speed of high thrust liquid rocket engine turbopump is obtained through a rotordynamic analysis and a unloaded turbopump test is peformed for validation of the numerical model. The first critical speed predicted by the numerical analysis is correlated well with the test result for the bearing unloaded rotor condition only considering mass unbalance load. Using the previous rotordynamic model, critical speed variation is estimated as a function of varied bearing stiffness due to pump and turbine radial loads with relative angle difference. From the numerical analysis, it is found that the relative angle difference of pump and turbine radial loads greatly affects the critical speed. However, additional axial load reduces the effect derived from the relative angle difference of radial loads.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2021.05a
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• pp.189-192
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• 2021

This study applies a deep learning-based long short-term memory(LSTM) model to track tracking technology. In the case of existing track tracking technology, the weight of constant velocity, constant acceleration, stiff turn, and circular(3D) flight is automatically changed when tracking track in real time using LMIPDA based on Kalman filter according to flight characteristics of an aircraft such as constant velocity, constant acceleration, stiff turn, and circular(3D) flight. In this process, it is necessary to improve performance of changing flight characteristic weight, because changing flight characteristics such as stiff turn flight during constant velocity flight could incur the loss of track and decreasing of the tracking performance. This study is for improving track tracking performance by predicting the change of flight characteristics in advance and changing flight characteristic weigh rapidly. To get this result, this study makes deep learning-based Long Short-Term Memory(LSTM) model study the plot and target of simulator applied with radar error model, and compares the flight tracking results of using Kalman filter with those of deep learning-based Long Short-Term memory(LSTM) model.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.37 no.8A
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• pp.669-678
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• 2012

In this paper, we propose an efficient fast integer-pel motion estimation for H.264/AVC using local statistics of local motion vectors. Using neighboring motion vectors, we define a new statistical property that is used to determine a mode of motion search range of current block. In addition, an adaptive motion search range compensated method that is based on cumulative statistics of previous coded blocks is addressed to solve the problem of the statistical motion search range decision method. Experimental results show that proposed algorithm has the capability to reduce the computational cost over the other methods.