Recent studies have suggested that the strain hardening of low carbon martensitic steels can be better understood by considering the important microstructural heterogeneities, arising from the progressive nature of the martensitic transformation. In this work, these heterogeneities are systematically analyzed in three martensitic steels with different carbon contents, focusing on the correlated distributions of dislocation density and martensitic domain size. From these characterizations, the local flow strength distributions were obtained at the scale of the microstructure. A Masing-like micromechanical model was then used to predict the tensile behavior by combining the calculated yield strength distribution with a proportional distribution of deviatoric stresses. The model successfully reproduces the tensile behavior of the studied steels in the as-quenched state and, for the first time, quantitatively accounts for the role of microstructural heterogeneities. Moreover, the subsequent compressive test is successfully modeled without the introduction of any supplementary parameter, highlighting that the model effectively describes the essentially kinematic nature of strain-hardening in martensitic steels.

This paper introduces the use of internal variables, estimated through Model Predictive Control (MPC), for fault detection and diagnosis in process industries. To do so, a data-driven methodology is proposed. Three reconstruction techniques - Principal Component Analysis (PCA), Kernel Independent Component Analysis (KICA), and Autoencoder (AE) - are compared using data sets that combine plant measurements with internal variables. The methodology was tested on a hot-dip galvanizing line dedicated to the production of automotive steel and compared to the use of only plant measurements for the development of the reconstruction methods. The results showed that the incorporation of internal variables significantly enhances the overall fault detection rate. Finally, contribution plots were used to identify the faulty sensor. Copyright (c) 2024 The Authors.

A method to track in situ static recrystallization, key to control the mechanical performance in steels, was developed. It relies on monochromatic X-ray diffraction experiments. The validity is discussed by comparison with post-mortem methods (EBSD and hardness). The beginning of recrystallization is easily detected thanks to the precision and time resolution of our method. In addition, our method can easily be coupled with other in situ techniques to investigate phase transformation or recovery.

To overcome assumptions made when setting the fault detection index threshold based on reconstruction methods, a classifier is employed to extract hidden patterns in residual data. The faulty data of each fault type used in training the classifier represent only the equivalent of 10% of the fault-free data used in the modeling phase. This considers the fact that, in industrial reality, faulty data are rarer than fault-free data. The proposed methodology is applied to the fault diagnosis of a galvanizing line. The results obtained from this case study show that combining the autoencoder (AE) with a weak classifier such as a Decision Tree (DT) provides a better fault detection rate and a lower false alarm rate than the 95% confidence threshold traditionally associated with AE.

Tempering of low-carbon steels (less than about 0.3 wt.% C) may differ from the traditional precipitation sequence, which includes transition carbide precipitation, retained austenite decomposition and cementite precipitation. The main difference is the partial or total absence of transition carbides. In the present work, the effect of the carbon segregation on the mitigation of the precipitation of the latter is analyzed by combining multi-scale experimental investigations with a new precipitation model accounting for the carbon heterogeneities induced by the segregation. The full precipitation sequence is considered in order to study the impact of the segregation not only on the transition carbides, but also on the cementite which forms afterwards. The experimental work includes APT characterization of carbon segregation, in-situ HEXRD experiments to reveal precipitation kinetics, and TEM observations for carbide size measurements.The here-in developed precipitation mean-field and physics-based model combines two previous ones dedicated to the nucleation and growth of transition carbides and cementite and to the segregation of carbon at dislocations. It is shown that, even after water-quench, carbon atoms are already segregated on dislocations. The mitigation of transition carbide precipitation is caused by the presence of such segregations, which decrease the driving force for the transition carbide nucleation and enhance cementite precipitation. In agreement with previous experiments, the model also demonstrates that inside a martensitic microstructure, the precipitation sequence is different between the first (formed close to Ms temperature) and the last martensite (formed at room temperature) formed upon cooling, because of the difference in dislocation density, which influences the intensity of the segregation phenomenon.

An accurate knowledge of the value of young’s modulus is essential for design studies, for finite elements and modeling calculations and for giving reliable values for constitutive laws. Several ways to measure the elastic coefficients exist: Direct measurement by a tensile test; Measurement by an impulse excitation technique (resonant or damping frequency); Ultrasonic measurement. This paper proposes a comparative study of these different methods associated to other topics related to sample properties and manufacturing process. From this study, the best characterization methods selected are those by vibration.

Austenite formation was numerically investigated using Thermo-Calc/DICTRA in a deformed ferrite/pearlite microstructure to produce dual-phase steels. This work aims to better understand how the interface conditions (local equilibrium with negligible partitioning-LENP-or local equilibrium with partitioning-LEP) control the austenite growth kinetics during the intercritical annealing. Inspired by our experimental observations, two nucleation sites were considered. The austenite formed from pearlite islands showed a regime transition from LENP to LEP when the holding stage started. For the growth of austenite from isolated carbides, three stages were identified during the heating stage: first, slow growth under LEP; then, fast growth under LENP; and finally, after dissolution of the carbide, slow growth again. LENP and LEP interface conditions may coexist thanks to these regime transitions. In the case of competition, LEP conditions hinder austenite growth while it is promoted by LENP interface conditions. Such differences in growth kinetics explain, in part, the morphogenesis of dual-phase microstructures.

Recent studies on the mechanical behavior of martensitic steels show the importance of considering lath marten -site as a "polycrystalline aggregate " with a large distribution of the local yield strength. The latter depends on local microstructural features, such as lath sizes, carbon distribution (in solid solution, segregated to defects, in carbides) and density of defects Internal stresses have to be considered as an additional contribution to the yield strength participating to enlarge the distribution of the local flow stresses at the microstructure scale. This study focuses on one of these microstructural features, the dislocation density. Its evolution is followed in situ upon martensitic transformation by High Energy X-Ray Diffraction experiments on a synchrotron beamline. A previously introduced method, based on modified Williamson-Hall (mWH) analysis, is improved in order to take account of the martensite lattice tetragonality when applying the mWH method. The influence of the steel carbon content (0.11, 0.21 and 0.31 wt.% C steels) and of the cooling rate (-10,-50,-100 degrees C/s and water-quench) on the dislocation density evolution in martensite during the martensitic transformation is established. The effect of the cooling rate on the dislocation density is low between-10 and-100 degrees C/s, but becomes visible after the water-quench. The higher the C content, the higher the dislocation densities at the end of the transformation. The steels with higher C content also show a wider distribution of the local dislocation density and, therefore, of the local yield strength.

Recovery of severely deformed ferrite was followed in situ by High Energy X Ray Diffraction during heating and isothermal holding experiments. Dislocation densities during annealing were determined by a modified Williamson Hall method. The deduced recovery kinetics was compared to post-mortem hardness measurements. A temperature dependent saturation of recovery was exhibited during holding. Dislocation density drop and saturation behavior cannot be reproduced simultaneously by the classical physically based models.

The aim of this paper is to investigate the effective properties of Fe–TiB2 composites obtained after hot or cold rolling. The elastic moduli of both hot and cold rolled composites are measured experimentally using several methods. Microstructure analyses based on SEM observations are performed to characterize the distribution of particles and cracks, and are then used to generate 3D representative microstructures using the RSA method. This allows the numerical determination of the overall elastic behavior of Fe–TiB2 composites using full-field FFT-based simulations. In addition, Young’s moduli of the hot rolled Fe–TiB2 composites are also determined analytically using the mean-field homogenization scheme of Mori–Tanaka. The elastic properties determined experimentally, analytically and numerically are in a good agreement. Overall, a significant improvement of the specific stiffness in comparison to standard steels is achieved irrespective of the processing conditions.

The evolution of the dislocation densities in martensite and in austenite during the quench of a low-carbon (0.215 wt% C) steel is investigated in situ by the mean of a High Energy X-Ray Diffraction experiment on a synchrotron beamline. The line configuration offers an excellent time resolution well adapted to the studied martensitic transformation kinetics. The mean density of dislocations in martensite increases as the transformation proceeds confirming that dislocations are not homogeneously distributed between the laths in agreement with some recent post-mortem observations. The resulting spatial distribution of dislocations and the associated strain-hardening support the views assuming that lath martensite is a heterogeneous microstructure and behaves as a “multiphase” aggregate. In austenite, the increase in dislocation densities is even more significant meaning that austenite in martensite is also a hard phase, contradicting some recent theories attributing to films of retained austenite a major role in the plasticity of martensite.

Knowledge of phase transformation kinetics is a key point in designing steel grades, in particular modern high-performance grades, highly sought-after in energy and transportation applications. The design space for these grades is highly multi-dimensional given the numerous potential alloying elements. The characterization techniques that are usually relied on to assess transformation kinetics, such as metallography or dilatometry, are highly time consuming, due to their limitation to either a single transformation time or a single composition per experiment. The high-throughput approach showcased here overcomes those limitations by combining compositionally graded samples with time-and space-resolved in situ Xray diffraction, yielding full kinetic records over a range of compositions in a single run. Its application to low-alloy steel required addressing specific challenges related to the reactivity and thermodynamics of the material. The transformation of austenite into ferrite was chosen to illustrate its benefits. Using the rich resulting database, the transformation mechanism was examined quasi-continuously across sections of the composition space. Neither the paraequilibrium, nor the local equilibrium with negligible partitioning model, nor a transition from the former to the latter is applicable over the whole range of investigated conditions. Instead, the observed kinetics were explained by accounting for the solute drag exerted on the mobile interface. This work is a major contribution in accelerating the design of future low-alloy steel grades, involving the transformation of austenite into ferrite or any other transformation to which the present high-throughput methodology can be adapted. (c) 2021 Elsevier Ltd. All rights reserved.

An original mean field model for the nucleation and the growth of new recrystallized grains during annealing treatments of deformed, low-carbon ferritic steels is proposed in this paper. The model was calibrated on two steels extensively studied in the literature under both isothermal annealing and continuous heating schedules. It permits one to predict not only recrystallization kinetics but also advanced microstructural features (such as dislocation density, dislocation cell size and grain size) during complex heat treatments. Once calibrated, the model was applied to the case of a third ferrite/pearlite steel and was shown to accurately capture the effect of cold-rolling ratio on the recrystallization kinetics.

In-situ high energy X-Ray diffraction (HEXRD) was used on compositionally graded steels to study the effect of substitutional elements on ferrite growth kinetics in Fe–C–X and Fe–C–X–Y systems. Two systems were selected to illustrate the applicability of the combinatorial approach in studying such transformations, Fe–C–Mn and Fe–C–Mn–Mo. Comparison between the measured ferrite growth kinetics using HEXRD and the predicted ones using Para-Equilibrium (PE) and Local Equilibrium with Negligible Partitioning (LENP) models indicates that the fractions reached at the stasis of transformation are lower than the predicted ones. Experiments indicated a deviation of measured kinetics from both PE and LENP models when increasing Mn and decreasing Mo (in Fe–C–Mn–Mo system). The large amount of data that can be obtained using this approach can be used for validating existing models describing ferrite growth kinetics.