TY - JOUR
T1 - Multiscale microstructure modelling for nickel based superalloys
AU - Basoalto, H.C.
AU - Brooks, J.W.
AU - Di Martino, I.
PY - 2009/2/1
Y1 - 2009/2/1
N2 - The present paper is concerned with the development of multiscale modelling approaches for predicting the microstructural evolution and high temperature deformation characteristics of superalloys with special attention to creep and hot forming behaviour. A microstructure informed deformation model is presented that links rearrangements at the microscale to the overall macroscopic response of the material through a damage mechanics approach and results are presented on the application of the model to CMSX4. The control of microstructure, during the manufacture of nickel based superalloy components, is key to the development of the mechanical properties required for the high temperature applications typical of these materials. Results from empirical methods and a new physics based approach for modelling recrystallisation in polycrystalline superalloys are presented for the prediction of the grain size distributions produced during hot forming operations in lnconel alloy 718. A global macroscale modelling approach based on Neural Networks has been developed which includes the effects of composition, heat treatment and processing route and the effectiveness of the model for both property prediction and interpolation is demonstrated.
AB - The present paper is concerned with the development of multiscale modelling approaches for predicting the microstructural evolution and high temperature deformation characteristics of superalloys with special attention to creep and hot forming behaviour. A microstructure informed deformation model is presented that links rearrangements at the microscale to the overall macroscopic response of the material through a damage mechanics approach and results are presented on the application of the model to CMSX4. The control of microstructure, during the manufacture of nickel based superalloy components, is key to the development of the mechanical properties required for the high temperature applications typical of these materials. Results from empirical methods and a new physics based approach for modelling recrystallisation in polycrystalline superalloys are presented for the prediction of the grain size distributions produced during hot forming operations in lnconel alloy 718. A global macroscale modelling approach based on Neural Networks has been developed which includes the effects of composition, heat treatment and processing route and the effectiveness of the model for both property prediction and interpolation is demonstrated.
UR - http://www.scopus.com/inward/record.url?partnerID=yv4JPVwI&eid=2-s2.0-60549106394&md5=574da3111f3ff7d1dac09fe7424f3b43
U2 - 10.1179/174328408X382578
DO - 10.1179/174328408X382578
M3 - Article
AN - SCOPUS:60549106394
SN - 0267-0836
VL - 25
SP - 221
EP - 227
JO - Materials Science and Technology
JF - Materials Science and Technology
IS - 2
ER -