Modeling and simulation of the negative angle cutting with a combined constitutive model for U71Mn rail steel
Journal of Materials Research and Technology, ISSN: 2238-7854, Vol: 27, Page: 7852-7863
2023
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Research from Hangzhou Dianzi University Yields New Findings on Materials Research (Modeling and simulation of the negative angle cutting with a combined constitutive model for U71Mn rail steel)
2023 DEC 18 (NewsRx) -- By a News Reporter-Staff News Editor at Tech Daily News -- Researchers detail new data in materials research. According to
Article Description
Due to the increasing train axle load, running speed and traffic volume, rails are prone to severe rolling contact fatigue (RCF) defects. Repairing the rail profile by milling is the latest technology to solve the above hidden problems, but there are few related studies in recent years. In this paper, the milling maintenance process of rails is studied by using finite element method(FEM). This study examines the fracture behavior of U71Mn steel rail under various stress triaxiality conditions, temperatures, and strain rates. An electronic universal testing machine is utilized to conduct the experiments, and a Johnson-Cook (J-C) failure model for U71Mn steel rail is developed. A 3D cutting simulation model was developed using the Johnson-Cook (J-C) combined constitutive model. The accuracy and reliability of the numerical simulation model were confirmed by comparing the cutting force and chip morphology obtained from both simulation and experimental results. The cutting simulation model had an error rate of within 10 % when predicting the cutting force. Following that, the fracture zone and chip portion of the tensile specimen were metallographically analyzed. The applicability of the ductile failure criterion in describing the observed failure in the U71Mn rail has been proven.
Bibliographic Details
http://www.sciencedirect.com/science/article/pii/S2238785423029678; http://dx.doi.org/10.1016/j.jmrt.2023.11.194; http://www.scopus.com/inward/record.url?partnerID=HzOxMe3b&scp=85178148631&origin=inward; https://linkinghub.elsevier.com/retrieve/pii/S2238785423029678; https://dx.doi.org/10.1016/j.jmrt.2023.11.194
Elsevier BV
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