No abstract

This study investigates the prediction of maraging steel C250 microgrinding forces by incorporating phase transformation effects with the manufacturing process mechanics. The results could consequently increase the accuracy of the prediction and better understand the influence of phase evolution on the materials processing. Based on a detailed analysis of microgrinding mechanics and thermodynamics, an iterative blending scheme integrating phase transformation kinetics and material genome analysis is developed. The physical-based formulation, experimental validation, and computational configuration are presented herein for the microgrinding forces, quantifying phase transformation effects. According to the results, the implementation of the iterative blending scheme can help achieve a higher prediction accuracy of microgrinding forces. Besides, the iterative blending would enable the consideration of the interactive relation between process mechanics and microstructure evolution through materials genome analysis.

No abstract

No abstract

The phase transformation in the grinding process could have a significant impact on the processing performance of the products. Although grinding process can lead to high heating and strain rates, the current studies on the phase transformation typically consider temperature only that limits their accuracy. In this study, based on the phase transformation model, by conducting the micro-grinding experiment of maraging steel C250, the mechanism controlling impacts of heating and strain rates on phase transformation has been analyzed, and a new process optimization scheme to control phase transformation has been proposed. In this research was determinate main characteristic parameters of the phase transformation prediction model and influence of the heating rate parameters on the structure of the material. The main conclusions of this work are aimed increasing productivity, as well as criteria for optimizing the micro grinding process are defined.