Guang Chen

Application of genetic algorithms for optimizing the Johnson–Cook constitutive model parameters when simulating the titanium alloy Ti-6Al-4V machining process

Finite element simulation of metal machining requires accurate constitutive models to characterize the material stress–strain response in plastic deformation processes. An optimization methodology using genetic algorithms was developed to determine the Johnson–Cook material model for Ti–6Al–4V alloy. The optimization of the parameters resulted in lower errors between the calculated flow stress and the experimental values obtained through the split Hopkinson pressure bar tests at different temperatures (ranging from 25u2009°C to 900u2009°C) and strain rates (2000 and 2500s−1). Optimized Johnson–Cook constitutive parameters were used to calculate the flow stress under various conditions. The calculated results showed excellent agreement with the experimental values, with errors lower than 4%. In addition, Ti–6Al–4V alloy orthogonal cutting experiments were carried out to validate the finite element simulation results. The experimental chip morphology was compared with the simulation results obtained by the optimized Johnson–Cook model (M2) and the original Johnson–Cook model (M1). The simulated results (including chip morphology and cutting force) were affected by the flow stress model. Comparison of the experimental and simulated results revealed that the optimized Johnson–Cook model can provide relatively good prediction results for the titanium alloy machining process, especially for chip morphology prediction.

Constitutive modeling for Ti-6Al-4V alloy machining based on the SHPB tests and simulation

A constitutive model is critical for the prediction accuracy of a metal cutting simulation. The highest strain rate involved in the cutting process can be in the range of 104–106 s–1. Flow stresses at high strain rates are close to that of cutting are difficult to test via experiments. Split Hopkinson compression bar (SHPB) technology is used to study the deformation behavior of Ti-6Al-4V alloy at strain rates of 10–4–104s–1. The Johnson Cook (JC) model was applied to characterize the flow stresses of the SHPB tests at various conditions. The parameters of the JC model are optimized by using a genetic algorithm technology. The JC plastic model and the energy density-based ductile failure criteria are adopted in the proposed SHPB finite element simulation model. The simulated flow stresses and the failure characteristics, such as the cracks along the adiabatic shear bands agree well with the experimental results. Afterwards, the SHPB simulation is used to simulate higher strain rate(approximately 3×104 s–1) conditions by minimizing the size of the specimen. The JC model parameters covering higher strain rate conditions which are close to the deformation condition in cutting were calculated based on the flow stresses obtained by using the SHPB tests (10–4–104 s–1) and simulation (up to 3×104 s–1). The cutting simulation using the constitutive parameters is validated by the measured forces and chip morphology. The constitutive model and parameters for high strain rate conditions that are identical to those of cutting were obtained based on the SHPB tests and simulation.

A Numerical Model to Determine Temperature Distribution in Aluminum Alloy (2A12) Micro-Cutting

Heat generation during cutting process affects the machined workpiece material and influences the cutting forces and tool wear. In this paper, a static thermal analysis model is developed to determine temperature rise in aluminum alloy (2A12) micro-cutting. The modified model is established based on two-dimensional steady state heat diffusion equation along with heat losses by convection film coefficients at the surfaces. A negative heat source is applied to simulate the heat loss during chip formation process. Effects of chip length and negative heat source on temperature distribution are discussed. The simulation results are compared with experiment data. The final results indicated that the model with negative heat source is more accurate than that without negative heat source and 20mm chip length give best temperature field fitting to the experiment.

Effect of Various Cooling Strategies on Surface Roughness of High Speed Milling Ti-6Al-4V

This study focused on the side milling surface roughness of titanium alloy under various cooling strategies and cutting parameters. The experimental results show that the cooling strategies significantly affect the surface roughness in milling Ti-6Al-4V. Surface roughness (Ra) alterations are investigated. Cutting fluid strategy made nearly all the smallest and most stable roughness values. The surface roughness values produced by all cooling strategies are obviously affected by feed, radial depth-of-cut and cutting speed. However, axial depth-of-cut has little influence.