Grain refinement mechanism under high strain-rate deformation in machined surface during high speed machining Ti6Al4V

2019 
Abstract The mechanical and physical properties of component surfaces are determined by the evolution of microstructures during high speed machining (HSM). In order to investigete the crystalline structure and formation mechanism of the highly perturbed surface layer, a novel characterization technique, precession electron diffraction (PED), is applied for quantitative characterization of the nano-scaled microstructures of machined surfaces, including phase distribution, grain size, character of grain boundary, grain orientation distribution and geometrical necessary dislocation (GND) density distribution. The deformation conditions of machined surface are used to analyze the evolution of microstructure under the effects of high strain-rate during machining process. Nano-crystalline structures are observed under high strain-rate deformation in the highly perturbed layer of machined surfaces. The calculation results based on crystal orientation information show that high GND density up to 10 6 /m 2 is generated and deformed nano-twins boundary is 14% of total grain boundary, which demonstrate that both dislocation slip and twinning contribute to the plastic deformation during HSM. Composite stress state and rapid heating of HSM surface produce large numbers of nanoscale β phase precipitations, which has critical pinning effects on dislocation and grain boundary movement, and will inhibit grains recovery and growth until nanoscale grains are formed. As high strain rate combined with precipitation of second phase particles is the main factor for nanoscale grains formation, HSM could be considered as an effective method to control the deformation conditions through selecting proper machining parameters in order to acquire component surface with nanocrystalline structure.
    • Correction
    • Source
    • Cite
    • Save
    • Machine Reading By IdeaReader
    53
    References
    22
    Citations
    NaN
    KQI
    []