A Dislocation Density‐Based Unified Constitutive Model of Multipass Deformation

Abstract

Quantitative relations between the softening mechanism and the constitutive model are determined based on the dislocation density, the influences of various deformation parameters, the dynamic softening mechanism, and static softening mechanism. A unified explicit constitutive model of multipass deformation is established by coupling the microstructural model of Q345B steel (the equivalent of ASTM A572Gr50). The flow stress curves under different deformation conditions are obtained from a Gleeble-3500 thermosimulation machine during hot compression deformation, including single-pass and double-pass compression for Q345B. From the experimental results, a new method to identify parameters is developed to determine the material parameters for the unified constitutive model and to establish their analytic expressions. The results predicted from the proposed model are also presented for validation and compared with the experimental results. The proposed model can accurately describe the stressstrain curves during dynamic recovery on the high-stress stage, during dynamic recrystallization, steady flow state, and next pass after the completion of static softening. In addition, the errors from the model are adequately analyzed to make further improvements.

Quantification of static softening process and its effects on work hardening characteristics of a typical high strength steel during multi-pass deformation

“…where a 3 is a material constant. Furthermore, the relationship between flow stress and deformation temperature can be defined by equation (13) [54]:…”

“…For the flow behaviors of multi-pass deformation, Zhang et al [12] studied the effects of strain rate on the flow behaviors of Ti-6Al-4V alloy during multi-pass deformation. Jia et al [13] established a dislocation density-based constitutive model for the flow behaviors of Q345B steel during multi-pass deformation. Chen et al [14] proposed a phenomenological constitutive model for low-alloyed steel, which includes 34 material constants.…”

Dislocation Density–Based Model and Stacked Auto‐Encoder Model for Ti‐55511 Alloy with Basket‐Weave Microstructures Deformed in α + β Region

“…[2,[20][21][22] Developing accurate constitutive models is one effective method to simulate or predict the complex material flow behaviors. [23] The constitutive models mainly include phenomenological constitutive models, [24][25][26][27] physical-based constitutive models, [28][29][30][31][32] and data-based intelligent algorithm models. [33][34][35] Because of the high prediction precision, the phenomenological constitutive models are generally applied to forecast the flow behaviors of steels, [17,36] aluminum alloys, [37] titanium alloys, [38][39][40][41] etc.…”

Hot Deformation Behavior of V–Ti Microalloy Steels

“…There are many models of constitutive relationship between flow stress and strain rate and deformation temperature, but these models do not consider the effect of strain on flow stress, and cannot directly simulate and predict the deformation process directly. [ 3–5 ]…”

“…There are many models of constitutive relationship between flow stress and strain rate and deformation temperature, but these models do not consider the effect of strain on flow stress, and cannot directly simulate and predict the deformation process directly. [3][4][5] Wei et al [6] studied the constitutive relationship through a physical-based method combining strain effects, explaining the temperature dependence of Young's modulus and austenite self-diffusion coefficient. Using statistical parameters to quantify the accuracy and reliability of the equation may be another way to predict the flow stress in hot working.…”