{"title":"Modeling snow accumulation in the bogie region caused by train slipstream based on sliding mesh and particle capture criteria","authors":"","doi":"10.1016/j.aej.2024.11.004","DOIUrl":null,"url":null,"abstract":"<div><div>The accumulated snow swept by the high-speed train's slipstream tends to aggregate on the train's bogie, thereby posing a significant threat to operational safety. In this paper, utilizing the sliding mesh technique and a novel particle injection scheme, the combination of Unsteady Reynolds-Average Navier-Stokes simulation, discrete phase model and particle capture criteria is employed to simulate and analyze the attachment components and accumulation mass of snow particles on the bogie of high-speed trains at speeds of 200 km/h, 250 km/h, and 300 km/h. The results indicate that for the first bogie, snow particles primarily enter from between the rear wheels and the cavity wall; for subsequent bogies, snow particles also enter from between the front wheels and the frame. The accumulation of snow on the rear bogies is markedly greater than on the front ones, with bogie 4 exhibiting the most severe accumulation. The cavity wall and frame of the bogie are the primary components where snow accumulates. Additionally, secondary snow accumulation components include bolster. With increasing speed, snow accumulation decreases on the first three bogies while increasing on the last three bogies. Bogie 4 is most affected by speed variations.</div></div>","PeriodicalId":7484,"journal":{"name":"alexandria engineering journal","volume":null,"pages":null},"PeriodicalIF":6.2000,"publicationDate":"2024-11-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"alexandria engineering journal","FirstCategoryId":"5","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S1110016824014212","RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"ENGINEERING, MULTIDISCIPLINARY","Score":null,"Total":0}
引用次数: 0
Abstract
The accumulated snow swept by the high-speed train's slipstream tends to aggregate on the train's bogie, thereby posing a significant threat to operational safety. In this paper, utilizing the sliding mesh technique and a novel particle injection scheme, the combination of Unsteady Reynolds-Average Navier-Stokes simulation, discrete phase model and particle capture criteria is employed to simulate and analyze the attachment components and accumulation mass of snow particles on the bogie of high-speed trains at speeds of 200 km/h, 250 km/h, and 300 km/h. The results indicate that for the first bogie, snow particles primarily enter from between the rear wheels and the cavity wall; for subsequent bogies, snow particles also enter from between the front wheels and the frame. The accumulation of snow on the rear bogies is markedly greater than on the front ones, with bogie 4 exhibiting the most severe accumulation. The cavity wall and frame of the bogie are the primary components where snow accumulates. Additionally, secondary snow accumulation components include bolster. With increasing speed, snow accumulation decreases on the first three bogies while increasing on the last three bogies. Bogie 4 is most affected by speed variations.
期刊介绍:
Alexandria Engineering Journal is an international journal devoted to publishing high quality papers in the field of engineering and applied science. Alexandria Engineering Journal is cited in the Engineering Information Services (EIS) and the Chemical Abstracts (CA). The papers published in Alexandria Engineering Journal are grouped into five sections, according to the following classification:
• Mechanical, Production, Marine and Textile Engineering
• Electrical Engineering, Computer Science and Nuclear Engineering
• Civil and Architecture Engineering
• Chemical Engineering and Applied Sciences
• Environmental Engineering