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1차원 충돌 동역학 모델을 이용한 한국형 고속전철의 충돌안전도 평가
조현직(Cho Hyun-Jik),구정서(Koo Jeong Seo),윤영한(Youn Young Han) 한국철도학회 2002 한국철도학회 학술발표대회논문집 Vol.- No.-
In this study, the crashworthiness of KHST is evaluated by analysing a nonlinear spring/bar-damper-mass model using 1 dimensional collision dynamics. The numerical results show that KHST can easily absorb kinetic energy at lower impact force and acceleration in heavy collisions, when compared with KTX. Also, in a light collision like a traint-to-train accident at speed under 8 kph, the carbody and components of KHST can be protected without any damage except a energy absorbing tube to be replaced easily. However, KTX may be much damaged in the light collision because there is no energy absorbing tube. In conclusion, the crashworthy performance of KHST has been much improved than that of KTX, although there remains something to be improved for a better performance.
충돌동역학 모델링 기법에 따른 충돌가속도 응답특성 분석
조현직(Cho Hyun-Jik),김운곤(Kim Woon-Gon),구정서(Koo Jeong-Seo) 한국철도학회 2008 한국철도학회 학술발표대회논문집 Vol.- No.-
In the Rail Safety Regulations article 16, deceleration rate in the survival spaces should be limited as far as is practicable to 5g, and shall not be more than 7.5g. As it is impractical to evaluate complete train behaviour by testing, the achievement of the objectives shall be validated by dynamic simulations corresponding to the reference collisions scenarios. But initial design and evaluation procedure, impact dynamics model which classified 1D and 2D is more useful than full scale model. This paper presents acceleration response characteristics between 1D and 2D dynamics model under head-on collision in standard collision scenarios.
국내 철도차량안전법 요구 압괴 성능의 대형장애물 수치모델 개발
조현직(Cho Hyun-Jik),구정서(Koo Jeong-Seo),이장욱(Lee Jang-Wook),박경창(Park Kyoung-Chang),박근수(Park Geun-Soo) 한국철도학회 2009 한국철도학회 세미나자료 Vol.2009 No.5
This study aims to develope a numerical model of the huge obstacle defined in the Korean Rollingstock Safety Regulations. The shape and mechanical properties to be satisfied in the numerical model were based on the Regulations. Through a troublesome trial and error simulations, we developed the numerical model of the huge obstacle to satisfy physical properties of the specified guideline in the regulations. By applying the developed numerical obstacle, we carried out a crash simulation to evaluate vehicle crashworthiness.
철도안전법 시행지침 16조의 충격가속도 평가를 위한 객차의 데이터 필터링 연구
조현직(Cho Hyun-Jik),김운곤(Kim Woon-Gon),구정서(Koo Jeong-Seo),송달호(Song Dhal-Ho) 한국철도학회 2008 한국철도학회 학술발표대회논문집 Vol.- No.-
In the article 16 of the domestic rolling stock crashworthiness regulations, the collision acceleration level during collision accidents should remain under the maximum 7.5g and the average 5g. By the way, the accelerations obtained in crash simulations and tests contain many kinds of high frequency components due to numerical oscillations or noisy signals. So, this paper aims to develop reliable post-processing methods to filter high frequency oscillations and extract the rigid body motions of passenger rail cars. For this study we used the 1-dimensional dynamic model of KHST (Korean high-speed train), and evaluated acceleration data at the driver"s area in the first power car and the passenger area in the following trailer.
이준현(Joon-Hyun Lee),김명준(Myeong-Joon Kim),김태훈(Tae-Hoon Kim),이진석,신제창(Che-Chang Shin),이량(Yang Li),조현직(Hyun-Jik Cho),강철구(Chul-Goo Kang) 대한기계학회 2021 대한기계학회 춘추학술대회 Vol.2021 No.11
Deep learning algorithms such as LSTM and CNN that can classify timeseries data can be applied to an air compressor to detect anomalies. In the encoder-decoder structure, the encoder compresses the original data and the decoder reconstructs the characteristic of the original data from the compressed data. In this paper, actual raw data from the sensors attached in a screw air compressor of a railway vehicle is preprocessed by using a moving window and normalization, and then LSTM encoder-decoder and CNN encoder-LSTM decoder logics are examined for detecting anomalies exising in the sensor data. The CNN encoder-LSTM decoder logic showed slightly better performance than the LSTM encoder-decoder logic. The validity of the logics is demonstrated by using Python codes.
박경창(Kyoung-Chang Park),조현직(Hyun-Jik Cho),이장욱(Jang-Wook Lee),박근수(Guen-Soo Park) 한국철도학회 2013 한국철도학회 학술발표대회논문집 Vol.2013 No.11
유럽에서 트램은 접근성 및 친환경성이 뛰어난 대표적인 교통수단이다. 트램은 전용 철로를 이용하는 일반 철도 차량과는 달리 다른 교통 수단 (버스, 승용차 및 화물차 등)과 교차되어 운용 되면서 기존의 철도 차량보다 높은 이용자 편의성을 가지고 있으나, 다른 교통 수단에 대한 충돌 사고 발생 확률이 높다. 본 논문은 국토해양부 개발사업을 통해 설계 및 제작된 무가선 저상트램을 대상으로 국외 충돌안전 기준인 EN15227 사양을 적용하여 충돌안전성능을 평가를 수행하였다. 충돌안전성능 평가에 사용된 충돌 시나리오는 정면충돌과 경사면의 소형장애물과의 충돌이다. 본 연구를 통해 국내에서 개발된 무가선 저상트램의 충돌안전성능은 EN15227의 설계기준에 만족함을 확인하였다. Tram is becoming one of the most popular means of transportation in Europe because of it"s advantage such as accessibility and eco-friendly. Meanwhile the trams are operated with other kinds of road transportations, the accident can be happened not only with itself but also with other road vehicles. Accordingly the crashworthiness design needs to be complied with recently released standard EN15227. This paper describes the crashworthiness assessment according to EN15227. There are two kinds of crash scenario and two kinds of criteria for each. The first scenario : A front-end colliding between two identical trams at 15km/h. The second scenario : A front colliding into a 3ton road-crossing obstacle placed on the railway at 25km/h with an incidence of 45 deg. Explicit FEA has been used for the evaluation.
구정서(Koo Jeong-Seo),조현직(Cho Hyun-Jik),이승일(Lee Sung-Il),권태수(Kwon Tae-Soo) 한국철도학회 2006 한국철도학회 학술발표대회논문집 Vol.- No.-
As Rolling stocks, which are composed of heavy units, run along predefined tracks at relatively high speeds, it is impossible to stop shortly without accidents using emergency braking in case a person stay on the track. Therefore train-to-human collision accidents over 200 cases occurs every year and the tolls suffer very serious damage. To consider some countermeasures to reduce injury at train-to-human collision accidents, the concerning statical data were analysed to investigate human injury severity for accident patterns and collision speeds. Based on these statistical data analyses, some standard scenarios for train-to-human collision accidents were derived to cover about 75% of the fatal accidents.
유한요소해석을 이용한 철도차량 시트프레임의 정적 강도 평가에 관한 연구
구정서(Koo Jeong seo),조현직(Cho Hyun Jik) 한국철도학회 2003 한국철도학회 학술발표대회논문집 Vol.- No.-
In this paper, the structural strengths of a rolling stock seat were numerically evaluated under several design load conditions based on the UIC requirements. The rolling stock seat was designed for the high speed train of a Chinese conventional line. To maximize its weight reduction and structural strength, some aluminium alloys like 6NO1-T5 and ALDC8-T5 were applied to the base frame, side frame and armrest. The designed seat frame satisfied the strength requirements on inertia loads due to accelerations, and fatigue test conditions. However, it violated the requirements on the static test of UIC 566 OR. Some design modifications were suggested and numerically evaluated to satisfy the static test requirements.
1차원 모델을 이용한 한국형 고속전철의 충돌 안전도 평가
구정서(Koo Jeong Seo),조현직(Cho Hyun Jik),김동성(Kim Dong Sung),윤영한(Youn Young Han) 한국철도학회 2001 한국철도학회 학술발표대회논문집 Vol.- No.-
The best method to evaluate crashworthiness of a trainset as a whole is to analyse one dimensional dynamic model composed of nonlinear dampers, springs and bars, and masses. In this study, crashworthiness of KHST was evaluated by analysing a nonlinear spring/bar-damper-mass model. The numerical results show that the KHST can easily absorb kinetic energy at lower impact force and acceleration in a heavy collision, when compared with KTX. Also, the KHST can be protected from any damage in its carbody and components except the prepared energy absorbing tube in a light collision, like a traint-to-train accident at speed under 8 kph. However, the KTX can be much damaged in the a light collision because there is no energy absorbing tube.
김명준(Myeong-Joon Kim),조현직(Hyun-Jik Cho),강철구(Chul-Goo Kang) 대한기계학회 2022 大韓機械學會論文集A Vol.46 No.2
최근 철도산업에서 인공지능 기술을 기반으로 하여 이상을 감지하고 수명을 예측하는 연구가 큰 관심을 받고 있다. 본 연구에서는 실제 철도차량 공기압축기 센서에서 얻은 데이터를 기반으로 LSTM 신경망을 이용하여 공기압축기의 이상을 감지하는 알고리즘을 제시하고 실제 데이터에 대해 적용 가능성을 확인한다. 실제 철도차량의 정상데이터를 입력하여 신경망을 학습시키고, 정상데이터에서 계산된 이상스코어 최대값을 이상감지 기준값으로 설정하는 방법을 제안한다. 인위적으로 생성한 이상데이터를 모델의 입력으로 사용하여 이상감지 성능을 확인하고 이상스코어 이동평균의 효용성을 검증한다. Recently, researches on detecting anomalies and predicting a lifespan using artificial intelligence have been attracting considerable attention in the railway industry. In this study, we propose an algorithm to detect anomalies of the air compressor using the LSTM network based on the data obtained from sensors installed in a railway vehicle, and we confirm the applicability of this to the actual system. The LSTM network is trained using actual normal data as input, and a method to set the maximum anomaly score as the threshold for anomaly detection is introduced. The performance of the proposed method is demonstrated using artificially generated abnormal data as the input of the trained model and using the moving average of anomaly score for smoothing.