Steffen Brier , Alexander Geist , Janine Glänzel , Christian Naumann , Joachim Regel , Martin Dix , Steffen Ihlenfeldt
{"title":"刀具环境与工作空间的耦合CFD模型,用于确定机床铣削射流冷却过程中的对流换热","authors":"Steffen Brier , Alexander Geist , Janine Glänzel , Christian Naumann , Joachim Regel , Martin Dix , Steffen Ihlenfeldt","doi":"10.1016/j.procir.2025.02.049","DOIUrl":null,"url":null,"abstract":"<div><div>The responsible use of resources is an essential part of the manufacturing of industrial products. This includes the economical use of cooling lubricant and requires precise knowledge of the cooling mechanisms and their effect on the accuracy of the machine tool and thus the thermal error. A temporal and spatial resolution of the dynamic coolant flow near the tool and in the entire workspace in a single model would require a large simulation time. Therefore, a composite model was developed, that consists of a near-tool model and a larger surrounding workspace model. The required static near-tool cooling lubricant distribution is obtained via data discretization methods from a separate static simulation that resolves the turbulence of the cooling lubricant created by the tool rotation. The identified coolant distribution is integrated into a CFD near-tool model (with simplified tool geometry) which is coupled with a surrounding CFD workspace model. The workspace model is thus able to identify the effects of the coolant wetting on the machine surface temperature and finally, using thermo-elastic FEM simulations, on the resulting thermal error. This approach allows the composite model to simulate the entire workspace with reduced simulation effort and map the coolant-influenced heat transfer coefficients on the machine surface.</div></div>","PeriodicalId":20535,"journal":{"name":"Procedia CIRP","volume":"133 ","pages":"Pages 280-285"},"PeriodicalIF":0.0000,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Coupled CFD model of tool environment and workspace to determine the convective heat transfer in jet cooling of milling processes in machine tools\",\"authors\":\"Steffen Brier , Alexander Geist , Janine Glänzel , Christian Naumann , Joachim Regel , Martin Dix , Steffen Ihlenfeldt\",\"doi\":\"10.1016/j.procir.2025.02.049\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><div>The responsible use of resources is an essential part of the manufacturing of industrial products. This includes the economical use of cooling lubricant and requires precise knowledge of the cooling mechanisms and their effect on the accuracy of the machine tool and thus the thermal error. A temporal and spatial resolution of the dynamic coolant flow near the tool and in the entire workspace in a single model would require a large simulation time. Therefore, a composite model was developed, that consists of a near-tool model and a larger surrounding workspace model. The required static near-tool cooling lubricant distribution is obtained via data discretization methods from a separate static simulation that resolves the turbulence of the cooling lubricant created by the tool rotation. The identified coolant distribution is integrated into a CFD near-tool model (with simplified tool geometry) which is coupled with a surrounding CFD workspace model. The workspace model is thus able to identify the effects of the coolant wetting on the machine surface temperature and finally, using thermo-elastic FEM simulations, on the resulting thermal error. This approach allows the composite model to simulate the entire workspace with reduced simulation effort and map the coolant-influenced heat transfer coefficients on the machine surface.</div></div>\",\"PeriodicalId\":20535,\"journal\":{\"name\":\"Procedia CIRP\",\"volume\":\"133 \",\"pages\":\"Pages 280-285\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2025-01-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Procedia CIRP\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S2212827125001283\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Procedia CIRP","FirstCategoryId":"1085","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S2212827125001283","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Coupled CFD model of tool environment and workspace to determine the convective heat transfer in jet cooling of milling processes in machine tools
The responsible use of resources is an essential part of the manufacturing of industrial products. This includes the economical use of cooling lubricant and requires precise knowledge of the cooling mechanisms and their effect on the accuracy of the machine tool and thus the thermal error. A temporal and spatial resolution of the dynamic coolant flow near the tool and in the entire workspace in a single model would require a large simulation time. Therefore, a composite model was developed, that consists of a near-tool model and a larger surrounding workspace model. The required static near-tool cooling lubricant distribution is obtained via data discretization methods from a separate static simulation that resolves the turbulence of the cooling lubricant created by the tool rotation. The identified coolant distribution is integrated into a CFD near-tool model (with simplified tool geometry) which is coupled with a surrounding CFD workspace model. The workspace model is thus able to identify the effects of the coolant wetting on the machine surface temperature and finally, using thermo-elastic FEM simulations, on the resulting thermal error. This approach allows the composite model to simulate the entire workspace with reduced simulation effort and map the coolant-influenced heat transfer coefficients on the machine surface.