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Study on the material removal process in ultrasonic-assisted grinding of SiC ceramics using smooth particle hydrodynamic (SPH) method

  • Jianguo CaoEmail author
  • Yongbo Wu
  • Jianyong Li
  • Qinjian Zhang
ORIGINAL ARTICLE

Abstract

Ultrasonic-assisted grinding, a promising processing technique for machining hard and brittle materials, is already quite extensively employed in manufacturing industries. However, the material removal mechanism in ultrasonic-assisted grinding is not yet fully understood, which hinders its further application. This study investigates the material removal process in ultrasonic-assisted scratching (UAS) of SiC ceramics using both simulation and experiment method, in order to detail the material removal mechanism in ultrasonic-assisted grinding. A conventional scratching (CS) test was also carried out, but without ultrasonic vibration for comparison. The simulated workpiece is modeled by smooth particle hydrodynamic (SPH) particles. Results show the following: (1) the SPH method is suitable to investigate the material removal mechanism during ultrasonic-assisted grinding of hard and brittle materials. (2) The profile of scratching trace in ultrasonic vibration (UV) is a sinusoidal path. UV vibrating in the direction vertical to the workpiece results in material removed in either a continuous or a discontinuous mode. UV vibrating in the direction parallel to the workpiece expands the cutting area. (3) The groove depth in UAS is much bigger than that in CS. (4) UV results in the impact of the abrasive grain on the workpiece, causing the deformation field to spread from the impact site and leading to deeper scratching depths and larger radial and lateral cracks.

Keywords

Ultrasonic Grinding SiC ceramics Mechanism Material removal SPH 

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Copyright information

© Springer-Verlag London 2015

Authors and Affiliations

  • Jianguo Cao
    • 1
    Email author
  • Yongbo Wu
    • 2
  • Jianyong Li
    • 1
  • Qinjian Zhang
    • 1
  1. 1.School of Mechanical, Electronic and Control EngineeringBeijing Jiaotong UniversityBeijingPeople’s Republic of China
  2. 2.Department of Machine Intelligence & Systems EngineeringAkita Prefectural UniversityYurihonjoJapan

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