Research on radial ultrasonic vibration-assisted biomimetic tool cutting of subsurface damage in CFRP
Source abstract
Abstract
Carbon fiber-reinforced polymer (CFRP) composites find extensive applications in various fields, including aerospace, defense, and biomedical engineering. However, the high strength, high hardness, and anisotropy of CFRP make it prone to defects like delamination, burrs, and tearing during conventional machining. A numerical simulation was first performed to evaluate three common micro-textured tool profiles for their ability to reduce subsurface damage in CFRP cutting. Based on the results, the elliptical texture profile was chosen due to its superior performance in suppressing subsurface damage. Then, leveraging the data from the depth profile equation of the bamboo rat’s upper incisors, a bionic tool featuring a gradient elliptical texture was designed and proposed. This design applies elliptical textures with varying depths to the tool’s rake face. Second, previous studies have not considered the combined use of radial ultrasonic vibration and a bionic textured tool inspired by the bamboo rat to study its effect on inhibiting subsurface damage in CFRP. The mechanistic study of radial ultrasonic vibration-assisted cutting of CFRP is first conducted through geometric modeling, and then validated by comparative experiments against conventional cutting to evaluate its efficacy in subsurface damage suppression. The findings demonstrate that the proposed bionic gradient elliptical textured tool, when assisted by radial ultrasonic vibration, achieved substantial reductions in overall subsurface damage—by 46.86%, 38.27%, and 50.72% at fiber orientation angles of 45°, 90°, and 135°, respectively—compared to conventional cutting with a non-textured tool.
Source: crossref · Quality: baseline
Research context
OpenAlex topics: Advanced machining processes and optimization · Erosion and Abrasive Machining · Advanced Surface Polishing Techniques
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
Affiliations
Shanghai University of Engineering Science
Datang Beijing-Tianjin-Hebei Energy Development Co
Ningbo Institute of Technology
Zhejiang University
Funding
Ningbo Key R&D Program Project
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