• Composites Research
• /
• 제21권5호
• /
• pp.15-22
• /
• 2008

본 논문은 샌드위치 복합재가 적용된 자동무인경전철 차체 구조물의 구조 안전성 및 충돌 안전성 결과에 대해 서술하고 있다. 차체 구조물에 적용된 샌드위치 복합재는 알루미늄 하니컴 심재와 WR580/NF4000 유리섬유/에폭시 적층 복합재 면재로 이루어져 있다. 차체 구조물에 적용되는 적층 복합재 면재에 대해 기계적 시험을 통하여 물성을 획득하였고, 직교 이방성 특성을 갖는 하니컴 심재의 물성은 유효등가손상모델을 적용하였다. ANSYS v11.0을 이용한 유한요소 해석은 JIS E 1105 기준과 ASCE 21-98 기준에 따라서 자동무인경전철 차체의 구조 안전성을 평가하였다. 충돌해석은 외연유한요소 해석 프로그램인 LS-DYNA3D를 이용하였다. 충돌 조건은 강체벽에 10km/h의 속도로 정면충돌 사고를 모사하였다. 또한, 수성된 Chang-Chang 파손기준시은 충돌 후 복합재 구조물의 파손 모드를 평가하는데 추천된다.

• 한국정보통신학회논문지
• /
• 제26권12호
• /
• pp.1794-1799
• /
• 2022

최근 증가하고 있는 도로 위 적재 불량 화물차는 비정상적인 무게 중심으로 인해 물체 낙하, 도로 파손, 연쇄 추돌 등 교통안전에 위해가 되고 한번 사고가 발생하면 큰 피해가 유발할 수 있다. 하지만 이러한 비정상적인 무게 중심은 적재 불량 차량 인식을 위한 주행 중 축중 시스템으로는 검출이 불가능하다는 한계점이 있다. 본 논문에서는 이러한 사회 문제를 야기하는 적재 불량 차량을 관리하기 위한 객체 인식 기반 AI 모델을 구축하고자 한다. 또한 AI-Hub에 공개된 약 40만 장의 데이터셋을 비교 분석하여 전처리를 통해 적재 불량 차량 검지 AI 모델의 성능을 향상시키는 방법을 제시한다. 또한 객체 추적을 통해 실시간 검지를 수행하는 방법을 제안한다. 이를 통해, 원시 데이터를 활용한 학습 성능 대비 약 23% 향상된 적재 불량 차량의 검출 성능을 나타냄을 보였다. 본 연구 결과를 통해 공개 빅데이터를 보다 효율적으로 활용하여, 객체 인식 기반 적재 불량 차량 탐지 모델 개발에 적용할 수 있을 것으로 기대된다.

• 한국자동차공학회논문집
• /
• 제18권1호
• /
• pp.99-104
• /
• 2010

It is a frequent occurrence in urban traffic - a low-speed collision in which one vehicle hits the back of another. The vehicles often sustain expensive damage. Bumpers can reduce this damage, but only line up so the initial contact in an impact is bumper to bumper. Then the bumpers on the colliding vehicles have to absorb the crash energy, keeping damage away from expensive sheet metal, lights, and other components. In real world accidents, Bumper mismatches in crashes are increasing, and the resulting repair costs from low-speed collisions are escalating. In this study, we investigated the bumper rail height and analyzed their effects on repair cost. Futhermore, Our 16kph front-into-rear crash tests demonstrates bumper mismatch problem.

• Environmental Analysis Health and Toxicology
• /
• 제24권4호
• /
• pp.351-357
• /
• 2009

To investigate the alleviative effects of jujube water extract (JWE) on the inflammation and skin barrier damage, both the irradiation of UVB and the application of squalene monohydroperoxide (Sq-OOH) were applied to the back skin of experimental animals for 4 weeks. And at the same time experimental materials were applied topically. Six weeks female SKH-1 hairless mice were divided into five groups (five animals for each group) including normal (N; saline), control (C; UVB+Sq-OOH+saline), vehicle control (VC; UVB+Sq-OOH+vehicle), positive control (PC; UVB+Sq-OOH+0.01% retinoic acid) and experimental (E; UVB+Sq-OOH+JWE) groups. The skin erythema index in the E group was significantly low compared to the C group (p<0.05). Lipid (p<0.05) and water (p<0.01) capacities in the E group were significantly high compared to the C group. In comparison with the C group, E group showed a relatively well preserved lipid lamellae in the epidermis and a relatively much less infiltration of mast cells in the dermis or hypodermis. As for the both absolute and relative weights of the spleen, PC group were significantly higher than the other groups. These results suggest that JWE have a considerably inhibitory effect on the inflammation and the skin barrier damage induced by UVB irradiation and Sq-OOH application.

• 한국재료학회지
• /
• 제21권11호
• /
• pp.623-627
• /
• 2011

This is a study on the distribution of acoustic emission parameters during a burst test for a type-II CNG vehicle fuel tank. A resonant AE sensor with a central frequency of 150 kHz was attached to the composite materials in the center of the fuel tank. The pressure was increased from 30 to 100% of the expected burst pressure and was maintained for 10 minutes at each level. Damage at 70% of expected burst pressure occurred by various damage mechanisms including fiber breakage and delamination, while that of below 60% only occurred by matrix crack initiation and growth. The count, duration and rise time of the AE signal at 60% of the expected burst pressure are distributed below 500, 5000 ${\mu}s$ and 300 ${\mu}s$, respectively. Then, at above 70% they increased with pressure by superimposing of individual AE signal generated at a nearby place. These results confirmed that the analysis of the distribution of AE parameters is an effective tool for estimating damage of a CNG fuel tank.

• 한국컴퓨터정보학회논문지
• /
• 제24권8호
• /
• pp.37-43
• /
• 2019

The existing smart farm technology has been systematized for the mass production rather than the consumer. There are many problems such as economical aspect to apply to actual rural environment due to aging. The purpose of this study is to apply smart farm technology based on the applicability of population aged in rural areas. Due to the heat wave, the crops in general greenhouse cultivation facilities suffered from damage such as sunlight damage. To minimize such damage, adjust the temperature and humidity environment or install a light-shielding film. However, the workers in the rural areas are aging and the elderly who are farming alone have a lot of difficulties in doing so. In the case of people with weak physical strength, there is a danger that they may lead to safety accidents when carrying heavy loads. In this paper, we propose 'Smart Palm capable of automatic transportation function', applying small smart vehicles that follow workers to existing smart farms to improve and prevent these problems. It is a smart farm that performs the control functions of the existing smart greenhouse environment, installs the rail for each trough, and has a vehicle that follows the worker. The smart app can directly control the greenhouse and the vehicle remotely manually.

• Smart Structures and Systems
• /
• 제32권5호
• /
• pp.309-318
• /
• 2023

The appropriate maintenance of highway roads is critical for the safe operation of road networks and conserves maintenance costs. Multiple methods have been developed to investigate the surface of roads for various types of cracks and potholes, among other damage. Like road surface damage, the condition of expansion joints in concrete pavement is important to avoid unexpected hazardous situations. Thus, in this study, a new system is proposed for autonomous expansion joint monitoring using a vision-based system. The system consists of the following three key parts: (1) a camera-mounted vehicle, (2) indication marks on the expansion joints, and (3) a deep learning-based automatic evaluation algorithm. With paired marks indicating the expansion joints in a concrete pavement, they can be automatically detected. An inspection vehicle is equipped with an action camera that acquires images of the expansion joints in the road. You Only Look Once (YOLO) automatically detects the expansion joints with indication marks, which has a performance accuracy of 95%. The width of the detected expansion joint is calculated using an image processing algorithm. Based on the calculated width, the expansion joint is classified into the following two types: normal and dangerous. The obtained results demonstrate that the proposed system is very efficient in terms of speed and accuracy.

• 한국산학기술학회논문지
• /
• 제16권11호
• /
• pp.7329-7334
• /
• 2015

본 연구는 전복에서 사고의 특성과 운전자의 행동특성을 분석하기 위한 연구이다. 연구기간은 2011년 1월에서 2014년 5월까지이며 연구대상은 전복사고로 응급의료센터에 내원한 운전자 102명이었다. 연구도구는 교통안전공단 인체상해 데이터를 이용하였으며 여기에는 자동차의 손상정도와 환자의 데이터를 수집하여 정리된 내용으로 차량의 기본정보와 환자정보, 손상의 역학적 원인과 사진 상의 손상정보, 환자의 임상적 손상정보를 모두 포함하고 있다. 자료분석은 SPSS 18.0을 이용하여 기술통계, ANOVA, Chi-square test 분석을 시행하였다. 분석 결과 차량종류에 따른 손상정도계수(Injury Severity Score) 평균 점수는 작은 차량에서 6.00점, 높은 차량에서 11.78점, 그 외 차량에서 14.70점을 보였고 세 집단 간 유의한 차이는 보이지 않았다(P=.267). 안전벨트 착용 여부에서 남자가 여자에 비해 안전벨트를 유의하게 착용하지 않는 것을 볼 수 있었으며 (P=.007), 차량 종류나 날씨 등이 안전벨트 착용 여부와 상관관계를 보이지는 않았다(P=.755, P=.793). 하지만 차량의 크기가 작을수록 운전자들이 안전벨트를 차용하지 않는 경향을 보였고, 날씨가 맑은 날 오히려 안전벨트를 좀 더 착용하는 경향을 볼 수 있었다. 마지막으로 전복 사고에서도 다른 사고 유형에서와 마찬가지로 안전벨트 착용 여부가 손상에 큰 영향을 미치는 것을 확인할 수 있었다.

• Tribology and Lubricants
• /
• 제40권4호
• /
• pp.111-117
• /
• 2024

Due to global CO₂ emission reductions and fuel efficiency regulations, the trend toward transitioning from internal combustion engine vehicles to electric vehicles (EVs) has accelerated. Consequently, the problem of EV failures has become a focal point of active research. The parasitic capacitance generated during motor-shaft rotation induces voltage that deteriorates the raceway and ball surfaces of bearings, causing electrical damage in EVs. Despite numerous attempts to address this issue, most studies have been conducted under high viscosity lubricant and low load conditions. However, due to factors such as high-speed operation, rapid acceleration and deceleration, motor heating, and motor system-decelerator integration, current EV applications have shown diminished stability in lubrication films of motor bearings, thereby leveraging the investigation to address the risk of electrical damage. This study investigates the electrical damage to rolling bearing elements in EV motor drive systems. The experimental analysis focuses on the effects of electric currents and operational loads on bearing integrity. A test rig is designed to generate high-rate voltage specific to a motor system's parasitic capacitance, and bearing samples are exposed to these currents for specified durations. Component evaluation involves visual inspections and vibration measurements. In addition, a predictive model for electrical failure is developed based on accumulated data, which demonstrates the ability to predict the likelihood of electrical failure relative to the duration and intensity of current exposure. This in turn reduces uncertainties in practical applications regarding electrical erosion modes.

• 한국항만학회지
• /
• 제13권1호
• /
• pp.101-112
• /
• 1999

Traffic accidents increase with the increase of the vehicles in operation on the street. Especially big traffic accidents composed of over 3 killed or 20 injured accidents with the property damage become one of the serious problems to be solved in most of the cities. The purpose of this study is to build the discrimination model on big traffic accidents using the Quantification II theory for establishing the countermeasures to reduce the big traffic accidents. The results are summarized as follows. 1)The existing traffic accident related model could not explain the phenomena of the current traffic accident appropriately. 2) Based on the big traffic accident types vehicle-vehicle, vehicle-alone, vehicle-pedestrian and vehicle-train accident rates 73%, 20.5% 5.6% and two cases respectively. Based on the law violation types safety driving non-fulfillment center line invasion excess speed and signal disobedience were 48.8%, 38.1% 2.8% and 2.8% respectively. 3) Based on the law violation types major factors in big traffic accidents were road and environment, human, and vehicle in order. Those factors were vehicle, road and environment, and human in order based on types of injured driver’s death. 4) Based on the law violation types total hitting and correlation rates of the model were 53.57% and 0.97853. Based on the types of injured driver’s death total hitting and correlation rates of the model were also 71.4% and 0.59583.