Multi-scale modeling and laser-assisted machining of metal matrix composites
Abstract
This study focuses on devising a multi-scale 2-D and 3-D finite element models for simulating laser assisted machining of metal matrix composites (MMC). These models are to assist in selecting machining parameters for laser-assisted machining of metal matrix composites. The two MMC’s studied in this research are an aluminum matrix reinforced by long alumina fibers and the other is an aluminum matrix reinforced by silicon carbide particles. The multi-scale heirarchical model bridges the atomic, micro and macro scales. In this model, molecular dynamics (MD) simulations are carried out to parameterize traction-separation laws for the aluminum-alumina and aluminum-silicon carbide interfaces in tensile and shear loadings at high temperatures. The interfaces are characterized by cohesive zone models (CZM), with the CZM traction-separation laws obtained from MD simulations. The parameterized CZM is then input into a finite element model to simulate the machining of fiber and particulate reinforced MMC. The multi-scale model is capable of predicting the cutting forces and post machined sub-surface damage. Average values of the predicted quantities are compared with experimental results, and the favorable agreement confirms the MD determined traction-separation laws and subsequently the validity of the multi-scale FEM. Laser-assisted machining (LAM) of the two MMC’s is evaluated for its potential to improve the machinability while minimizing the sub-surface damage. The effectiveness of the laser-assisted machining process is studied by measuring the cutting forces, specific cutting energy, surface roughness, sub-surface damage and tool wear under various material removal temperatures. The optimum material removal temperature is established as 300°C for both composite systems. LAM provides a 65% reduction in the surface roughness, specific cutting energy, tool wear rate and sub-surface damage over conventional machining using the same cutting conditions for the long-fiber MMC. For the particulate MMC, LAM provides a 37% reduction in the surface roughness, a 12% reduction in the specific cutting energy and a 1.7–2.35 times improvement in tool life over conventional machining dependent on the cutting speed. Experimental measurements of the cutting forces and the sub-surface damage are compared with simulation results, showing promising results.
Degree
Ph.D.
Advisors
Shin, Purdue University.
Subject Area
Mechanical engineering
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