On the use of transfer modeling to design new steels with excellent rotating bending fatigue resistance even in the case of very small calibration datasets

In this research a machine learning model for predicting the rotating bending fatigue strength and the high-throughput design of fatigue resistant steels is proposed. In this transfer prediction framework, machine learning models are first trained to estimate tensile properties (yield strength, tensile strength and elongation) on the basis of...

Numerical simulation of precipitation kinetics in multicomponent alloys

A universal numerical model based on the particle size distribution (PSD) approach has been developed for the simulation of precipitation kinetics in multicomponent alloys during isothermal ageing. Nucleation was implemented utilizing the classical nucleation theory (CNT). Growth and coarsening were modeled by a single growth kinetics...

Effect of Nb on Microstructural Evolution and Mechanical Properties of Hot-Rolled Quenching and Partitioning Steels Containing Bainite

Herein, the effect of Nb content on the phase transformation kinetics, microstructure, and mechanical properties of hot-rolled quenching and partitioning (Q&P) steel is investigated. The characteristics of three C–Mn–Si–Ti steels (0.18C, 2.0Si, 2.6Mn, and 0.015Ti) containing 0, 0.027, or 0.061 wt% Nb are compared. Results reveal that...

A generic high-throughput microstructure classification and quantification method for regular SEM images of complex steel microstructures combining EBSD labeling and deep learning

We present an electron backscattered diffraction (EBSD)-trained deep learning (DL) method integrating traditional material characterization informatics and artificial intelligence for a more accurate classification and quantification of complex microstructures using only regular scanning electron microscope (SEM) images. In this method, EBSD...

Microstructure and dislocation structure evolution during creep life of Ni-based single crystal superalloys

The high performance of Ni single crystal superalloys during high temperature low stress creep service, is intrinsically determined by the combined effects of microstructural evolution and the dislocation behaviour. In the field of the evolution of dislocation network, two main recovery mechanism based on dislocation migration dominate the...

A first step towards computational design of W-containing self-healing ferritic creep resistant steels

In this work, we combine a generic alloy-by-design model with a novel concept, the nucleation barrier for the formation of Laves phase to fill the creep cavities, in order to develop multi-component creep resistant steels with kinetically tuned self-healing behaviour. In the model the high-temperature long-term strength is estimated by...

Determination of mode switching in cyclic partial phase transformation in Fe-0.1C-xMn alloys as a function of the Mn concentration

Controlling the kinetics of austenite decomposition by controlled partitioning of alloying elements, in particular carbon and manganese, is the key factor for optimizing the microstructures of advanced high-strength steels. In this study, a systematic set of computational and experimental cyclic partial phase transformations in low to medium...

Physical metallurgy-guided machine learning and artificial intelligent design of ultrahigh-strength stainless steel

With the development of the materials genome philosophy and data mining methodologies, machine learning (ML) has been widely applied for discovering new materials in various systems including high-end steels with improved performance. Although recently, some attempts have been made to incorporate physical features in the ML process, its...

A Novel Approach for Controlling the Band Formation in Medium Mn Steels

Formation of the microstructural ferrite/pearlite bands in medium Mn steels is an undesirable phenomenon commonly addressed through fast cooling treatments. In this study, a novel approach using the cyclic partial phase transformation concept is applied successfully to prevent microstructural band formation in a micro-chemically banded Fe-C...

Predicting the cooperative effect of Mn–Si and Mn–Mo on the incomplete bainite formation in quaternary Fe–C alloys

Predicting the effect of alloying elements on the degree of incomplete austenite to bainite transformation in low carbon steels is of great industrial importance. This study introduces an extended Gibbs energy balance model which makes use of an additive approach to calculate the coupled effect of Mn, Si and Mo on the fraction of bainitic...

On the Relationship between the Chromium Concentration, the Z-Phase Formation and the Creep Strength of Ferritic-Martensitic Steels

In this study, the long term creep strength behavior of commercial heat resistant martensitic/ferritic steels with Cr levels ranging from 1 to 15 wt% is analyzed by linking their computed equilibrium compositions to their creep properties. At lower Cr levels, the calculated strength due to precipitation hardening agrees well with the...

The Compositional Dependence of the Microstructure and Properties of CMSX-4 Superalloys

The degradation of creep resistance in Ni-based single-crystal superalloys is essentially ascribed to their microstructural evolution. Yet there is a lack of work that manages to predict (even qualitatively) the effect of alloying element concentrations on the rate of microstructural degradation. In this research, a computational model is...

Prediction and Validation of the Austenite Phase Fraction upon Intercritical Annealing of Medium Mn Steels

In this research, the effects of Mn and Si concentration and that of the isothermal intercritical holding temperature on the austenite-to-ferrite (? ? ?) and the martensite-to-austenite (?? ? ?) phase transformations are studied for a series of Fe-C-Mn-Si steels with up to 7 wt pct Mn. The model is based on the local equilibrium (LE) concept....

Process-time Optimization of Vacuum Degassing Using a Genetic Alloy Design Approach

This paper demonstrates the use of a new model consisting of a genetic algorithm in combination with thermodynamic calculations and analytical process models to minimize the processing time during a vacuum degassing treatment of liquid steel. The model sets multiple simultaneous targets for final S, N, O, Si and Al levels and uses the total slag...