A novel method for predicting the grain size of superalloy forgings based on the fuzzy method and the FEM

Grain size is one of the important indexes for characterizing the microstructures and properties of superalloy forgings. Under the condition that the quality of the raw material is specified, the grain size of superalloy forgings is the result of synthetic inter action of thermomechanical parameters. Thus, the relationship between grain size and thermomechanical parameters belongs to the fuzzy concept for which the extension is uncertain. Based on the results of isothermal constant-strain-rate compression tests, the membership function for characterizing the grain size of superalloy forgings was first established in terms of the thermomechanical forging parameters. Combining the proposed membership function with thermoviscoplastic coupled numerical simulation software based on the finite element method, a new method was formulated for the prediction of the grain size of superalloy forgings. The results predicted by using the method presented in the paper are in close agreement with the experimental data and measured grain size of an IN718 alloy disk forging. The proposed method can serve as the guide for optimizing the forging process and controlling the forging quality of difficult-to-deformation materials.