Title : Determination of phase stress flow curves in dual phase steels through micromechanical adaptive iteration algorithm
Abstract:
Finite Element (FE) micromechanical modelling has significantly advanced the simulation of dual- phase (DP) steels by incorporating key microstructural features such as phase distribution and strain partitioning. A major ongoing challenge, however, is the accurate determination of individual phase stress flow curves—essential inputs for predictive model accuracy. Conventional methods often depend on empirical equations derived from extensive experimental studies, which may not adapt well to variations in alloy composition or phase fractions.
This research introduces a numerical approach that integrates experimental uniaxial tensile test data with FE micromechanical models to address this challenge. Central to this methodology is the Micromechanical Adaptive Iteration Algorithm (MAIA), which iteratively solves for ferrite and martensite stress flow curves with minimal experimental data. MAIA operates in three main stages: initialization, adaptive iteration, and validation. Its core strength lies in the adaptive iteration process, which accounts for strain partitioning between soft ferrite and hard martensite phases across different strain levels. The algorithm achieves convergence within two iterations, maintaining an error margin of 2–3%, and significantly reduces the need for extensive material characterization or empirical parameter fitting.
The method was applied to various DP steel types, including fine-grained DP steel alloyed with vanadium, DP steel with an equiaxed microstructure, and DP steel with an elongated microstructure. MAIA effectively captured the influence of vanadium on phase behavior, particularly the reduction of ferrite’s strain contribution due to the increased strength of martensite. It also successfully calculated stress flow curves for ferrite and martensite across samples with different chemical compositions and microstructures. In all cases, the model accurately reproduced experimental tensile responses by the second iteration, demonstrating strong predictive performance.
Despite these strengths, the approach has limitations. The current modelling framework does not account for fracture mechanisms, grain size variations and grain boundary effects. As a result, while MAIA provides reliable estimates of flow behavior and strain hardening at early to intermediate strains, it is less accurate in predicting ultimate tensile strength (UTS) and uniform elongation and fracture strain.
In conclusion, MAIA presents a robust and efficient numerical method for extracting phase-specific stress flow curves in DP steels, reducing dependence on complex experimental methods. Its ability to adapt to different alloy systems and microstructures with limited input makes it a valuable tool for expanding the utility of FE micromechanical modelling in material design and analysis.
