An overview on constitutive modelling to predict elevated temperature flow behaviour of fast reactor structural materials


This overview emphasized the aspects of formulation and application of various constitutive models developed by us in recent past viz. Johnson- Cook (JC), modified Zerilli-Armstrong (MZA), strain compensated Arrhenius type model and artificial neural network (ANN) model to predict elevated temperature flow behaviour of fast reactor structural materials. It has been shown that the JC model is not able to represent the high temperature flow behaviour of both alloy D9 and the modified 9Cr-1Mo as it does not incorporate the coupled effect of strain and temperature, and of strain rate and temperature. The new materials model based on Zerilli-Armstrong (ZA) equation considers the coupled effects of temperature and strain and of strain rate and temperature on the flow stress and hence has the capability to predict flow stress over a wider domain temperature and strain rate in comparison with JC model. The formulation and application of strain compensated Arrhenius type constitutive model to predict high temperature flow behaviour of alloy D9 and modified 9Cr-1Mo has been discussed. Development and application of a generic ANN based constitutive model to predict high temperature deformation behaviour of austenitic stainless steels has been highlighted. Finally, a comparative analysis of the merits and shortcomings of these models has been made.

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Samantaray, D., Mandal, S., Bhaduri, A.K. et al. An overview on constitutive modelling to predict elevated temperature flow behaviour of fast reactor structural materials. Trans Indian Inst Met 63, 823–831 (2010).

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  • constitutive modelling
  • structural materials
  • johnson-cook, modified zerilli-armstrong
  • strain compensated arrhenius type model
  • artificial neural network