Dynamic mechanical behavior, meso/micro-scale FEA simulation, and experimental study of machining advanced materials

Machining is one of the major manufacturing operations today in view of its economic significance. Work materials in machining experience a broad range of strain, strain rate, and temperature. It is well known that flow stress is a function of strain, strain rate, and temperature. However, the flow stress also highly depends on many other factors such as strain, strain rate, and temperature histories. These effects can be quite large and cannot be modeled by the equation-of-state models that assume that stress is a unique function of the total strain, strain rate, and temperature. Only a model that includes all of these pertinent factors is capable of predicting complex stress states in machining.; An internal state variable (ISV) based BCJ (Bammann-Chiesa-Johnson) plasticity model was explored in this dissertation to incorporate the effects of loading history as well as strain, strain rate, and temperature in machining titanium Ti-6Al-4V, AISI 52100 steel (62 HRc), and aluminum 6061-T6. The BCJ material constants were obtained by using a nonlinear regression fitting algorithm based on the same baseline of stress-strain data.; A hybrid modeling approach has been provided to simulate orthogonal cutting with the stagnation effect induced by cutting edge geometry. Chip morphology transition from saw-tooth to discontinuous chips in hard machining was successfully recovered. The cutting edge geometry has significant effects on chip morphology and flow stress and strain in the subsurface. Adaptive meshing can significantly reduce element distortions, stresses, strains, and temperatures in the subsurface and therefore improve mesh quality.; With the determined material constants, the simulations using the BCJ model can account adiabatic shear effect encountered in machining, while the conventional John-Cook (JC) model alone cannot. Experiments and FEA simulations of orthogonal cutting AISI 52100 steel (62 HRc), Ti-6Al-4V and aluminum 6061-T6 were performed. The predicted saw-tooth chip morphology and dimensions using the BCJ model are consistent with the machined chips, while the JC model yielded discontinuous chips. The predicted cutting temperatures can be qualitatively verified by the subsurface microstructure. In addition, subsurface stress, strain, and temperature were also different when using the BCJ versus the JC model.