Advances in Microstructure Engineering of Steels.
49 بار بازدید -
هفته قبل
-
2024-06-20 Lecture by prof.
2024-06-20 Lecture by prof. Matthias Militzer.
Abstract:
The steel industry is engaged in a continuous development of high-performance steels and innovative processing strategies to meet the demands of sustainable growth in the energy, transportation and construction sectors.
Since the 1970’s thermomechanically-controlled processing (TMCP) of steels has motivated to develop microstructure-based process model and computational modelling has remained an important aspect to design microstructures and resulting properties of advanced high-performance steels. Initially semi-empirical state variable models were commonly employed but the tremendous development of computational power and resources has enabled to incorporate advanced computational materials science tools at different length and time scales into process modelling.
Multi-scale approaches combine atomistic scale simulations with meso-scale modelling on the microstructure length scale to establish predictive tools for the industrially relevant macro-scale. Austenite grain growth and decomposition are key aspects of microstructure evolution and thus the resulting properties of steels. For example, alloying elements and other solutes affect migration rates of grain boundaries and the austenite-ferrite interface. Thus, an interface-based alloy design approach has recently been proposed where phase-field modelling is informed by atomistic scale simulations using density functional theory (DFT). Utilizing binding energy data concluded from DFT a friction pressure approach has been adopted to account for solute drag and/or particle pinning. Alloy trend predictions can be made in this way and have been verified with experimental data including in-situ measurements of grain growth using laser ultrasonics and confocal scanning laser microscopy.
The extension of this methodology will be discussed for the design of new steels where residuals from scrap-based steelmaking are expected to be of relevance. The strengths and limitations of the proposed modelling approach will be critically reviewed.
Abstract:
The steel industry is engaged in a continuous development of high-performance steels and innovative processing strategies to meet the demands of sustainable growth in the energy, transportation and construction sectors.
Since the 1970’s thermomechanically-controlled processing (TMCP) of steels has motivated to develop microstructure-based process model and computational modelling has remained an important aspect to design microstructures and resulting properties of advanced high-performance steels. Initially semi-empirical state variable models were commonly employed but the tremendous development of computational power and resources has enabled to incorporate advanced computational materials science tools at different length and time scales into process modelling.
Multi-scale approaches combine atomistic scale simulations with meso-scale modelling on the microstructure length scale to establish predictive tools for the industrially relevant macro-scale. Austenite grain growth and decomposition are key aspects of microstructure evolution and thus the resulting properties of steels. For example, alloying elements and other solutes affect migration rates of grain boundaries and the austenite-ferrite interface. Thus, an interface-based alloy design approach has recently been proposed where phase-field modelling is informed by atomistic scale simulations using density functional theory (DFT). Utilizing binding energy data concluded from DFT a friction pressure approach has been adopted to account for solute drag and/or particle pinning. Alloy trend predictions can be made in this way and have been verified with experimental data including in-situ measurements of grain growth using laser ultrasonics and confocal scanning laser microscopy.
The extension of this methodology will be discussed for the design of new steels where residuals from scrap-based steelmaking are expected to be of relevance. The strengths and limitations of the proposed modelling approach will be critically reviewed.
هفته قبل
در تاریخ 1403/04/07 منتشر شده
است.
49
بـار بازدید شده