{"title":"齿轮箱的 CFD 模拟:实施网格聚类算法,高效模拟复杂系统结构","authors":"Marco Nicola Mastrone, Franco Concli","doi":"10.1186/s40712-021-00134-6","DOIUrl":null,"url":null,"abstract":"<div><p>In the last decade, computer-aided engineering (CAE) tools have become a determinant factor in the analysis of engineering problems. In fact, they bring a clear reduction of time in the design phase of a new product thanks to parametrical studies based on virtual prototypes. The application of such tools to gearboxes allowed engineers to study the efficiency and lubrication inside transmissions. However, the difficulties of handling the computational domain are still a concern for complex system configurations. For this reason, the authors maintain that it is fundamental to introduce time efficient algorithms that enable the effective study of any kind of gear, e.g., helical and bevel configurations. In this work, a new mesh handling strategy specifically suited for this kind of studies is presented. The methodology is based on the Global Remeshing Approach with Mesh Clustering (GRA<sup>MC</sup>) process that drastically reduces the simulation time by minimizing the effort for updating the grids. This procedure was tested on spur, helical, and bevel gears, thus demonstrating the flexibility of the approach. The comparison with experimentally measured power losses highlighted the good accuracy of the strategy. The algorithm was implemented in the opensource software OpenFOAM®.</p></div>","PeriodicalId":592,"journal":{"name":"International Journal of Mechanical and Materials Engineering","volume":"16 1","pages":""},"PeriodicalIF":3.4000,"publicationDate":"2021-08-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://jmsg.springeropen.com/counter/pdf/10.1186/s40712-021-00134-6","citationCount":"0","resultStr":"{\"title\":\"CFD simulations of gearboxes: implementation of a mesh clustering algorithm for efficient simulations of complex system’s architectures\",\"authors\":\"Marco Nicola Mastrone, Franco Concli\",\"doi\":\"10.1186/s40712-021-00134-6\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><p>In the last decade, computer-aided engineering (CAE) tools have become a determinant factor in the analysis of engineering problems. In fact, they bring a clear reduction of time in the design phase of a new product thanks to parametrical studies based on virtual prototypes. The application of such tools to gearboxes allowed engineers to study the efficiency and lubrication inside transmissions. However, the difficulties of handling the computational domain are still a concern for complex system configurations. For this reason, the authors maintain that it is fundamental to introduce time efficient algorithms that enable the effective study of any kind of gear, e.g., helical and bevel configurations. In this work, a new mesh handling strategy specifically suited for this kind of studies is presented. The methodology is based on the Global Remeshing Approach with Mesh Clustering (GRA<sup>MC</sup>) process that drastically reduces the simulation time by minimizing the effort for updating the grids. This procedure was tested on spur, helical, and bevel gears, thus demonstrating the flexibility of the approach. The comparison with experimentally measured power losses highlighted the good accuracy of the strategy. The algorithm was implemented in the opensource software OpenFOAM®.</p></div>\",\"PeriodicalId\":592,\"journal\":{\"name\":\"International Journal of Mechanical and Materials Engineering\",\"volume\":\"16 1\",\"pages\":\"\"},\"PeriodicalIF\":3.4000,\"publicationDate\":\"2021-08-05\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://jmsg.springeropen.com/counter/pdf/10.1186/s40712-021-00134-6\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"International Journal of Mechanical and Materials Engineering\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://link.springer.com/article/10.1186/s40712-021-00134-6\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q2\",\"JCRName\":\"MATERIALS SCIENCE, MULTIDISCIPLINARY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"International Journal of Mechanical and Materials Engineering","FirstCategoryId":"1085","ListUrlMain":"https://link.springer.com/article/10.1186/s40712-021-00134-6","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"MATERIALS SCIENCE, MULTIDISCIPLINARY","Score":null,"Total":0}
CFD simulations of gearboxes: implementation of a mesh clustering algorithm for efficient simulations of complex system’s architectures
In the last decade, computer-aided engineering (CAE) tools have become a determinant factor in the analysis of engineering problems. In fact, they bring a clear reduction of time in the design phase of a new product thanks to parametrical studies based on virtual prototypes. The application of such tools to gearboxes allowed engineers to study the efficiency and lubrication inside transmissions. However, the difficulties of handling the computational domain are still a concern for complex system configurations. For this reason, the authors maintain that it is fundamental to introduce time efficient algorithms that enable the effective study of any kind of gear, e.g., helical and bevel configurations. In this work, a new mesh handling strategy specifically suited for this kind of studies is presented. The methodology is based on the Global Remeshing Approach with Mesh Clustering (GRAMC) process that drastically reduces the simulation time by minimizing the effort for updating the grids. This procedure was tested on spur, helical, and bevel gears, thus demonstrating the flexibility of the approach. The comparison with experimentally measured power losses highlighted the good accuracy of the strategy. The algorithm was implemented in the opensource software OpenFOAM®.