No abstract

This paper describes the results of the numerical evaluation on crashworthiness and rollover characteristics of a lowfloor bus vehicle made of sandwich composites. The sandwich composite used for the vehicle structures was composed of aluminum honeycomb core and WR580/NF4000 glass-fabric/epoxy laminate facesheets. Material tests were conducted to determine the input parameters of the composite laminate facesheet model and the effective equivalent damage model for the orthotropic honeycomb core material. Crashworthiness and rollover analysis of the low-floor bus was conducted using the explicit finite element method (FEM) analysis code LS-DYNA3D with the lapse of time. The crash condition of the low-floor bus was a frontal accident with a speed of 60 km/h. Rollover analysis was done according to the safety rules of the European standards (ECE-R66). The angular and translation velocity and its angle with the ground just before impact for rollover were calculated using the dynamic analysis program. The results showed that the survival spaces for the driver and passengers were secured against frontal crashworthiness and rollover of the low-floor bus. In addition, the modified Chang-Chang failure criterion is recommended to predict the failure modes of the composite structures for crashworthiness and rollover analysis.

No abstract

No abstract

In this study, the fatigue characteristics and life of two types of woven fabric glass /epoxy laminate composites with WR580 glass fiber for carbody structures and GEP224 glass fiber for bogie frames were evaluated and compared with those of conventional metallic materials. Additionally, the laminate composite for carbody structures was reinforced with carbon plies to investigate the improvement of fatigue life. A fatigue test was conducted for tension-tension and tension-compression load with a stress ratio, R of 0.1 and -1, and up to endurance limit of 10 7 with frequency of 5Hz. In tension-compression fatigue test, the anti-buckling jig was designed to prevent buckling of specimen induced by compressive load. The Goodman diagrams were introduced to evaluate the fatigue life of laminate composites. The test results showed that the fatigue life of the GEP224 woven fabric glass/epoxy laminate composite with the stacking sequence of warp direction had a good performance in comparison with that of SM490A used to existing metal bogie frame. Also, the fatigue performance of WR580 woven fabric glass/epoxy laminate composite with the reinforcement of woven fabric carbon /epoxy ply had shown a significant improvement than that of a bare specimen without reinforcement.

This paper describes the evaluations of tension-compression fatigue characteristics and life for glass fiber/epoxy laminate composite applied to railway bogie to reduce weight. Test samples of tension-compression fatigue were composed of glass fiber/epoxy 4-harness woven laminate composites with different stacking sequence of warp-direction, fill-direction and ±45°-direction. The tension-compression fatigue test was conducted with stress ratio (R) of -1 and frequency of 5Hz. Goodman diagram were used to evaluate the fatigue characteristics and life of glass fiber/epoxy 4-harness satin woven laminate composite. Anti-buckling jig was designed to prevent buckling of specimen under compression load. The test results showed that the fatigue characteristics of glass fiber/epoxy 4-harness satin woven laminate composite with stacking sequence of warp-direction had a good performance in comparison with that of SM490 used to conventional metal railway bogie. 초 록 본 논문은 철도차량 경량화 재질로 적용된 유리섬유/에폭시 4-매 주자직 적층 복합재료의 인장-압축 피로특성을 평가하였 다. 유리섬유/에폭시 4-매 주자직 적층 복합재료의 인장-압축 피로시험은 경사, 위사 그리고 ±45° 방향으로 적층된 시험편에 대하여 수행하였다. 인장-압축 피로시험은 5Hz의 주파수를 갖으며, 응력비(R)는 -1로 수행하였다. 인장-압축 피로시험 수행 시 압축하중에 의한 시험편의 좌굴을 방지하기 위하여 좌굴방지지그를 설계하고 이를 시험에 적용하였다. 또한, Goodman 선도 는 유리섬유/에폭시 4-매 주자직 적층 복합재의 피로특성과 수명을 평가하기 위해 사용하였다. 유리섬유/에폭시 4-매 주자직 적층 복합재료의 인장-압축 피로시험결과 경사방향 적층 복합재의 피로특성이 기존 금속재 대차에 적용되는 SM490에 비하여 우수한 것으로 나타났다.

In recent years, deep learning (DL) has been widely studied using various methods across the globe, especially with respect to training methods and network structures, proving highly effective in a wide range of tasks and applications, including image, speech, and text recognition. One important aspect of this advancement is involved in the effort of designing and upgrading neural architectures, which has been consistently attempted thus far. However, designing such architectures requires the combined knowledge and know-how of experts from each relevant discipline and a series of trial-and-error steps. In this light, automated neural architecture search (NAS) methods are increasingly at the center of attention; this paper aimed at summarizing the basic concepts of NAS while providing an overview of recent studies on the applications of NAS. It is worth noting that most previous survey studies on NAS have been focused on perspectives of hardware or search strategies. To the best knowledge of the present authors, this study is the first to look at NAS from a computer vision perspective. In the present study, computer vision areas were categorized by task, and recent trends found in each study on NAS were analyzed in detail.

No abstract