Numerical analysis of Johnson-Cook damage model parameters effects on the cutting simulation of AISI 1045

Background: Failure model is the important basis for the research of material failure and fracture, and plays an important role in the finite element simulation of metal cutting. Johnson-Cook damage model is widely used to predict the failure of many materials. Its damage evolution is controlled by five parameters Objective: In order to decrease the cost of damage parameters identification and find out the damage parameters which have great influence on the simulation results. This work can provide an assistance in the optimization and selection of constitutive model parameters. Methods: Suitable Johnson-Cook damage model parameters, which can be used in the metal cutting simulation of AISI 1045 steel, are selected by comparing the simulation results and the experiments results. The cutting process of AISI 1045 steel is simulated by changing the Johnson-Cook damage parameters in the ABAQUS/Explicit. Results: The relevance of cutting force, feed force, cutting temperature, and deformation coefficient with five Johnson-Cook damage parameters are determined. Conclusion: The finite element simulation results show that the Johnson-Cook damage model parameters D2 and D3 have the biggest impact on the cutting simulation of AISI 1045 steel. Meanwhile, different Johnson-Cook damage parameters would take different changes to the simulation results

Analyzing the Effect of Particle Shape on Deformation Mechanism during Cutting Simulation of SiC P/Al Composites

To analyze the effect of particle shape on deformational behavior in the cutting simulation process for metal matrix composites (MMCs), two 2D mesoscopic-based finite element (FE) models reinforced with randomly distributed circular and irregular polygonal particles were developed. Different material properties (metal matrix phase, particle reinforced phase) and the properties of the particle–matrix interface were comprehensively considered in the proposed FE model. Systematic cutting experiments were conducted to compare the differences between two modeling approaches with respect to particle fracture, chip formation, cutting force and surface integrity. The results show that the irregular polygonal particle model is closer to the microstructure of MMCs, and is better able to reflect the deformation behavior of particles. The simulation model with irregular polygonal particles is even able to capture more details of the impact caused by particles, reflecting variations in the cutting force in the actual cutting process. The initiation and propagation of microcracks is mainly determined on the basis of particle geometry and further affects chip formation. Both models are able to correctly reflect surface defects, but the irregular polygonal particle model provides a more comprehensive prediction for the subsurface damage of MMCs.

JOHNSON–COOK MODEL COMBINED WITH COWPER–SYMONDS MODEL FOR BONE CUTTING SIMULATION WITH EXPERIMENTAL VALIDATION

Constitutive models are widely used to predict the mechanical behavior of different kinds of materials. Although the Johnson–Cook model for bovine bone and Cowper–Symonds model for human thoracic rib and tibia was developed, the predictability of these models was found good only at particular strain rates. This study addresses this lack of information by investigating the Cowper–Symonds model, Johnson–Cook model, and Johnson–Cook model combined with Cowper–Symonds model at different strain rates to utilize in the bone cutting simulation. Specimens prepared using two rear femurs harvested from a 3.50-year-old bovine were investigated at different strain rates (0.00001–1/s). A comparative study made among the stresses predicted from these models showed 29.41%, 10.91%, and 11.11% mean absolute percentage errors using Cowper–Symonds model, and 2.03%, 7.19%, and 3.62% mean absolute percentage errors using Johnson–Cook model, respectively, at 0.0001, 0.001 and 1/s strain rates. However, the Johnson–Cook model combined with the Cowper–Symonds model predicted the stress with a maximum of only 2.03% mean absolute percentage error. The potential of each model to utilize in the orthogonal bone cutting was also evaluated using Ansys® and found that the combined model predicted the cutting force close to experimental cutting force with minimal error (5.20%). The outcomes of this study can be used in the surgical practice and osteotomy procedure before commencing actual surgery.