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EVALUATION OF FATIGUE LIFE OF AUTOMOTIVE ENGINE VALVES CONSIDERING THE DYNAMIC BEHAVIOR
Namgyu Jun,Chang-Sung Seok,Kibum Park 한국자동차공학회 2022 International journal of automotive technology Vol.23 No.6
Owing to the harsh operating environment inside an engine, the engine valves have a durability issue and exhibit the characteristics of accelerated fatigue failure under the influence of the dynamic load because of their dynamic behavior. This study proposes a fatigue life evaluation method using the maximum impact stress that can accurately evaluate the fatigue life of engine valves. In addition, the major engine design factors affecting the dynamic behavior of an engine valves were derived. It was confirmed that the impact speed between the valve head and seat is closely related to the fatigue characteristics of the engine valve.
Evaluation on Fatigue Characteristics of Tire Sidewall Rubber according to Aging Temperature
( Namgyu Jun ),( Byungwoo Moon ),( Yongseok Kim ),( Jae-mean Koo ),( Chang-sung Seok ),( Ui Seok Hong ),( Min Kyeong Oh ),( Seong Rae Kim ) 한국고무학회 2017 엘라스토머 및 콤포지트 Vol.52 No.3
Ultra-high performance (UHP) tires, for which demand has recently surged, are subject to severe strain conditions due to the low aspect ratio of their sidewalls. It is important to ensure sidewall material durability, since a sudden tire sidewall breakage during vehicle operation is likely to cause a major accident. In the automotive application of rubber parts, cracking is defined as a failure because when cracks occur, the mechanical properties of rubber change. According to Mars<sup>(8)</sup>, Andre<sup>(11)</sup> et al., strain and strain energy density (SED) are mainly used as a failure parameters and the SED is generally used as a fatigue damage parameter. In this study, the fatigue life curves of sidewall rubber of tires were determined by using the SED as fatigue damage parameter while the effect of aging on fatigue life was evaluated after obtaining the SED-Nf curves according to aging condition.
경도측정을 통한 SUH35 합금의 크리프 잔여 수명 예측
전남규(Namgyu Jun),석창성(Chang-Sung Seok),구재민(Jae-Mean Koo),최재구(Jaegu Choi),이종민(Jongmin Lee),남덕현(Dukhyun Nam),김가연(Gayeon Kim) 대한기계학회 2018 大韓機械學會論文集A Vol.42 No.9
SUH35 합금은 내열성, 내부식성이 뛰어난 합금으로서 주로 자동차 엔진의 배기밸브의 소재로 사용된다. 자동차 엔진밸브는 연소가스에 의해 고온 및 밸브시트와의 접촉으로 인장하중에 노출되며 이에 따라 미세조직 변화에 의한 내구성능감소가 나타난다. 따라서 재료에 가해진 손상량을 측정하여 부품의 잔여수명을 예측하는 기술은 매우 중요하다. Goto 등은 고온설비에서의 경도 값 감소현상을 이용하여 부품의 잔여 크리프 수명을 예측하는 방법을 제안하였다. 본 연구에서는 Goto 등의 모델을 참고하여 SUH35소재의 크리프 잔여수명을 예측하기 위해 열화 시킨 시편에 대한 경도측정 및 크리프 시험을 수행하였다. 경도와 크리프 하중의 상관관계를 분석하여 크리프 파단곡선을 통해 잔여수명을 예측할 수 있는 방법을 제시하였다. The SUH35 alloy is considered an alloy with excellent heat resistance and corrosion resistance properties, and is mainly used as a material for the exhaust valve of an automobile engine. Vehicle engine valves are exposed to high temperatures by combustion gases and to tensile loads by contact with the valve seat. As a result, a deterioration of the durability performance due to changes in the microstructure appears. Therefore, a technique of measuring the extent of damage to the material and predicting the remaining lifetime of the part is critical. Goto and others proposed a method to predict the remaining creep life of parts based on the reduction of the hardness value in high-temperature equipment. In this study, a hardness measurement and creep test were performed on degraded specimens to predict the residual creep life of the SUH35 material. Based on the analysis, the relationship between the degree of degradation and the creep stress was derived and a method of predicting the residual creep life using the creep rupture curve was proposed.
Deep learning approach to generate 3D civil infrastructure models using drone images
Jun-Haeng Heo,Ji-Hye Kwon,Shekhroz Khudoyarov,Namgyu Kim 국제구조공학회 2022 Smart Structures and Systems, An International Jou Vol.30 No.5
Three-dimensional (3D) models have become crucial for improving civil infrastructure analysis, and they can be used for various purposes such as damage detection, risk estimation, resolving potential safety issues, alarm detection, and structural health monitoring. 3D point cloud data is used not only to make visual models but also to analyze the states of structures and to monitor them using semantic data. This study proposes automating the generation of high-quality 3D point cloud data and removing noise using deep learning algorithms. In this study, large-format aerial images of civilian infrastructure, such as cut slopes and dams, which were captured by drones, were used to develop a workflow for automatically generating a 3D point cloud model. Through image cropping, downscaling/upscaling, semantic segmentation, generation of segmentation masks, and implementation of region extraction algorithms, the generation of the point cloud was automated. Compared with the method wherein the point cloud model is generated from raw images, our method could effectively improve the quality of the model, remove noise, and reduce the processing time. The results showed that the size of the 3D point cloud model created using the proposed method was significantly reduced; the number of points was reduced by 20-50%, and distant points were recognized as noise. This method can be applied to the automatic generation of high-quality 3D point cloud models of civil infrastructures using aerial imagery.