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Transient Creep Strain of Ultra High Strength Concrete with Heating and Loading (가열 및 하중조건에 따른 초고강도콘크리트의 과도변형)

  • Choe, Gyeong-Choel;Kim, Gyu-Yong;Yoon, Min-Ho;Lee, Young-Wook;Hwang, Ui-Chul;Yoo, Jae-Chul
    • Proceedings of the Korean Institute of Building Construction Conference
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    • 2015.05a
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    • pp.59-60
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    • 2015
  • In this study, stress-strain, thermal expansion strain, total strain and high temperature creep strain of ultra-high-strength concrete with compressive strengths of 80, 130, and 180MPa were experimentally evaluated considering elevated temperature and loading condition. Also, transient creep strain has been calculated by using the results of experiment. Experimental coefficient K was proposed with application of non-steady state creep model. It is considered that the experimental results of this study could be baseline data for deformation behavior analysis of ultra-high-strength concrete.

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Loads and motions for a spar-supported floating offshore wind turbine

  • Sultania, Abhinav;Manuel, Lance
    • Wind and Structures
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    • v.22 no.5
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    • pp.525-541
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    • 2016
  • An offshore wind turbine supported by a spar buoy floating platform is the subject of this study on tower and rotor extreme loads. The platform, with a 120-meter draft and assumed to be sited in 320 meters of water, supports a 5 MW wind turbine. A baseline model for this turbine developed at the National Renewable Energy Laboratory (NREL) is employed in stochastic response simulations. The support platform, along with the mooring system consisting of three catenary lines, chosen for loads modeling, is based on the "Hywind" floating wind turbine concept. Our interest lies in gaining an understanding of the dynamic coupling between the support platform motion and the turbine loads. We first investigate short-term response statistics using stochastic simulation for a range of different environmental wind and wave conditions. From this study, we identify a few "controlling" environmental conditions for which long-term turbine load statistics and probability distributions are established.

A Study of KHST Passenger Safety During Accidents by Computer Simulation Techniques (컴퓨터 시뮬레이션기법을 이용한 고속전철 승객안전도 해석 및 평가)

  • 윤영한;구정서;이재완
    • Proceedings of the KSR Conference
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    • 2002.10a
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    • pp.60-65
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    • 2002
  • The computer simulation techniques were adopted to evaluate effects of seating positions of passenger under the various accident scenarios. The baseline of computer simulation model was tunned by the sled impact tests which conducted under the upright and standard seating positions. This study shows the effect of relative velocity between occupant and struck vehicle while occupant is impacted to a front seat's seatback. Although, base on the current accident scenarios, KHST is performed well enough to protect average adult male occupants. However, Results from the tests indicate small size occupant or higher impact speed may cause sever neck and femur injuries.

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An Improved Hybrid Kalman Filter Design for Aircraft Engine based on a Velocity-Based LPV Framework

  • Liu, Xiaofeng
    • International Journal of Aeronautical and Space Sciences
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    • v.18 no.3
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    • pp.535-544
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    • 2017
  • In-flight aircraft engine performance estimation is one of the key techniques for advanced intelligent engine control and in-flight fault detection, isolation and accommodation. This paper detailed the current performance degradation estimation methods, and an improved hybrid Kalman filter via velocity-based LPV (VLPV) framework for these needs is proposed in this paper. Composed of a nonlinear on-board model (NOBM) and VLPV, the filter shows a hybrid architecture. The outputs of NOBM are used for the baseline of the VLPV Kalman filter, while the system performance degradation factors on-line estimated by the measured real system output deviations are fed back to the NOBM for its updating. In addition, the setting of the process and measurement noise covariance matrices' values are also discussed. By applying it to a commercial turbofan engine, simulation results show the efficiency.

Modeling Cross-morpheme Pronunciation Variation for Korean LVCSR (한국어 연속음성인식을 위한 형태소 경계에서의 발음 변화 현상 모델링)

  • Lee Kyong-Nim;Chung Minhwa
    • Proceedings of the KSPS conference
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    • 2003.05a
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    • pp.75-78
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    • 2003
  • In this paper, we describe a cross-morpheme pronunciation variation model which is especially useful for constructing morpheme-based pronunciation lexicon for Korean LVCSR. There are a lot of pronunciation variations occurring at morpheme boundaries in continuous speech. Since phonemic context together with morphological category and morpheme boundary information affect Korean pronunciation variations, we have distinguished pronunciation variation rules according to the locations such as within a morpheme, across a morpheme boundary in a compound noun, across a morpheme boundary in an eojeol, and across an eojeol boundary. In 33K-morpheme Korean CSR experiment, an absolute improvement of 1.16% in WER from the baseline performance of 23.17% WER is achieved by modeling cross-morpheme pronunciation variations with a context-dependent multiple pronunciation lexicon.

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Robust Speech Recognition by Utilizing Class Histogram Equalization (클래스 히스토그램 등화 기법에 의한 강인한 음성 인식)

  • Suh, Yung-Joo;Kim, Hor-Rin;Lee, Yun-Keun
    • MALSORI
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    • no.60
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    • pp.145-164
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    • 2006
  • This paper proposes class histogram equalization (CHEQ) to compensate noisy acoustic features for robust speech recognition. CHEQ aims to compensate for the acoustic mismatch between training and test speech recognition environments as well as to reduce the limitations of the conventional histogram equalization (HEQ). In contrast to HEQ, CHEQ adopts multiple class-specific distribution functions for training and test environments and equalizes the features by using their class-specific training and test distributions. According to the class-information extraction methods, CHEQ is further classified into two forms such as hard-CHEQ based on vector quantization and soft-CHEQ using the Gaussian mixture model. Experiments on the Aurora 2 database confirmed the effectiveness of CHEQ by producing a relative word error reduction of 61.17% over the baseline met-cepstral features and that of 19.62% over the conventional HEQ.

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Finite Element Analysis on the Dynamic Behavior of a Cylindrical Brake Device with Plastic Deformation (소성변형을 갖는 원통형 제동장치의 동적거동에 관한 유한요소해석)

  • 김지철;이학렬;심우전
    • Proceedings of the Korean Society of Tribologists and Lubrication Engineers Conference
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    • 2000.11a
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    • pp.199-204
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    • 2000
  • A cylindrical brake device with plastic deformation is designed to stop the object moving at high velocity. Baseline model is determined based on the design specification and analytic solutions. Using finite element method, effects of various design parameters, such as thickness of the cylinder, clearance between cylinder and rod, and cone angle, to the performance of the brake device are investigated. Cone-type brake device shows better performance than cylindrical brake device with constant thickness in that plastic hinges are generated sequentially from impact end to fixed boundary, thus increasing the reliability of braking operation.

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Forecasting COVID-19 confirmed cases in South Korea using Spatio-Temporal Graph Neural Networks

  • Ngoc, Kien Mai;Lee, Minho
    • International Journal of Contents
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    • v.17 no.3
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    • pp.1-14
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    • 2021
  • Since the outbreak of the coronavirus disease 2019 (COVID-19) pandemic, a lot of efforts have been made in the field of data science to help combat against this disease. Among them, forecasting the number of cases of infection is a crucial problem to predict the development of the pandemic. Many deep learning-based models can be applied to solve this type of time series problem. In this research, we would like to take a step forward to incorporate spatial data (geography) with time series data to forecast the cases of region-level infection simultaneously. Specifically, we model a single spatio-temporal graph, in which nodes represent the geographic regions, spatial edges represent the distance between each pair of regions, and temporal edges indicate the node features through time. We evaluate this approach in COVID-19 in a Korean dataset, and we show a decrease of approximately 10% in both RMSE and MAE, and a significant boost to the training speed compared to the baseline models. Moreover, the training efficiency allows this approach to be extended for a large-scale spatio-temporal dataset.

Estimating People's Position Using Matrix Decomposition

  • Dao, Thi-Nga;Yoon, Seokhoon
    • International journal of advanced smart convergence
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    • v.8 no.2
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    • pp.39-46
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    • 2019
  • Human mobility estimation plays a key factor in a lot of promising applications including location-based recommendation systems, urban planning, and disease outbreak control. We study the human mobility estimation problem in the case where recent locations of a person-of-interest are unknown. Since matrix decomposition is used to perform latent semantic analysis of multi-dimensional data, we propose a human location estimation algorithm based on matrix factorization to reconstruct the human movement patterns through the use of information of persons with correlated movements. Specifically, the optimization problem which minimizes the difference between the reconstructed and actual movement data is first formulated. Then, the gradient descent algorithm is applied to adjust parameters which contribute to reconstructed mobility data. The experiment results show that the proposed framework can be used for the prediction of human location and achieves higher predictive accuracy than a baseline model.

Design of 3D Laser Radar Based on Laser Triangulation

  • Yang, Yang;Zhang, Yuchen;Wang, Yuehai;Liu, Danian
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.13 no.5
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    • pp.2414-2433
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    • 2019
  • The aim of this paper is to design a 3D laser radar prototype based on laser triangulation. The mathematical model of distance sensitivity is deduced; a pixel-distance conversion formula is discussed and used to complete 3D scanning. The center position extraction algorithm of the spot is proposed, and the error of the linear laser, camera distortion and installation are corrected by using the proposed weighted average algorithm. Finally, the three-dimensional analytic computational algorithm is given to transform the measured distance into point cloud data. The experimental results show that this 3D laser radar can accomplish the 3D object scanning and the environment 3D reconstruction task. In addition, the experiment result proves that the product of the camera focal length and the baseline length is the key factor to influence measurement accuracy.