Interpass Time Research Articles

Determination of Activation Energy For Static Re-Crystallization in Nb- Ti Low Carbon Micro Alloyed Steel

Data required for calculation the static re-crystallization kinetics have been evaluated from laboratory simulations. Series of two hit isothermal tests were conducted on high temperature torsion machine. These tests were conducted on four different temperatures and using inter-pass times between 0.5 and 5s with aim to investigate the influence of thermal activation on static re-crystallization. All tests were conducted on temperatures over TNR temperature, i.e. in temperature range in which all niobium is present only in solid solution. Method of evaluation of re-crystallization fraction was mechanical metallography, i.e. evaluation based on shape of each stress- strain curve. The fraction softening was calculated for all temperatures, together with avrami exponent, nA, and activation energy for re-crystallization, QSRX. Activation energy for static re-crystallization QSRX  281 KJ/mol and avrami exponent nA  1 determined in this work are in excellent agreement with previously reported data.

Development of a semi-empirical bond strength model for multi-pass hot roll bonding based on the characterizations using the truncated-cone experiment

With special reference to the modelling of hot roll bonding, new experimental procedures to measure the resulting bond strength for a combination of AA6016 and AA8079 aluminum alloys at elevated temperatures and various strain rates using laboratory tests are proposed. The data acquired by this procedure is used to developed and calibrate a semi-empirical model, which accurately predicts the resulting bond strength within an error of 2 MPa on average. It is shown that the bond strength generally follows the flow stress regarding the dependency on temperature and strain. Additionally, inter-pass times can increase the bond strength, provided that both a suitable temperature and timespan are realized. Contrary, multiple consecutive height reductions were found to reduce the bond strength.

The Performance of Niobium-Microalloying Ultra-High-Strength Bridge Cable Steel during Hot Rolling.

This study focuses on exploring the effects of niobium (Nb)-microalloying on the properties of steel for ultra-high-strength bridge cables during hot-rolling processes. We employed a combination of dual-pass compression tests, stress-strain curve analysis, and Electron Backscatter Diffraction (EBSD) techniques to investigate the influence of Nb-microalloying on the static recrystallization behavior and grain size of the steel. The key findings reveal that Nb-microalloying effectively inhibits static recrystallization, particularly at higher temperatures, significantly reducing the volume fraction of recrystallized grains, resulting in a finer grain size and enhanced deformation resistance. Secondly, at a deformation temperature of 975 °C, Nb-containing steel exhibited finer grain sizes compared to Nb-free steel when held for 10 to 50 s; however, the grain size growth accelerated when the hold time exceeded 50 s, likely linked to the increased deformation resistance induced by Nb. Lastly, this research proposes optimal hot-rolling process parameters for new bridge cable steel, recommending specific finishing rolling temperatures and inter-pass times for both Nb-containing and Nb-free steels during the roughing and finishing stages. This study suggests optimal hot-rolling parameters for both Nb-containing and Nb-free steels, providing essential insights for improving hot-rolling and microalloying processes in high-carbon steels for bridge cables.

Microstructural Evolution in a 0.09% Niobium Low Carbon Steel during Controlled Hot Deformation

A series of plane strain compression tests were carried out in order to simulate the thermomechanical controlled processing of a 0.09wt% Nb low carbon steel, in a scheme of multipass finish rolling at 950 °C with interpass times of 10 s. It was observed that after the first two finishing passes a remarkable grain refinement can be achieved, since the recrystallisation was fully suppressed and abundant ultrafine ferrite was transformed dynamically during the deformation. The addition of a third finishing pass however, led to partial recrystallisation. A deep characterisation of the dynamic ferrite was carried out by diverse methods conducting to relevant findings that contribute to a better elucidation of the dynamic transformation. The results obtained indicated that the dynamic formation of a colony of Widmanstätten ferrite plates during deformation, initiates with the formation of a pair of self-accommodating plates followed by face-to-face sympathetic nucleation of new plates at one of the faces of the pairs of plates already formed. Furthermore, the crystal orientation within the dynamic ferrite phase was analysed with EBSD, it was observed that during the coalescence of plates, prior to the full polygonisation of grains, the ferrite adopts a transitory morphology which possesses particular crystallographic characteristics.

Application of machine learning methods for the prediction of roll force and torque during plate rolling of micro-alloyed steel

Machine learning technique is extensively used to establish the relationship between non-linear data sets which cannot be described mathematically and thus an exact analytic model is either intractable or too time-consuming to develop. During hot rolling, the effect of process parameters that cannot be captured in mathematical models, such as roll dimensions and its wear, the inter-pass time between rolling passes, temperature variation has been incorporated using multivariate supervised machine learning technique for accurate prediction of roll force and torque during plate rolling of micro-alloyed steel. An ensemble method was used to combine various machine learning techniques and average them to develop one final predictive model. K-cross validation of the model was carried out to validate the results and ensure the model gets the correct pattern of data. Root mean square error of ensemble roll force model was compared with roll force calculation using Sims theory. It was found that the machine learning model can predict the roll force and torque accurately as it takes care of various non-linear process variables which cannot be accounted for mathematically. The R-value of the machine learning model was >98 %, whereas it was 92.2 % for roll force calculation using Sims theory.

Grain Size Distribution of DP 600 Steel Using Single-Pass Asymmetrical Wedge Test

Grain size distribution after the completion of a phase transformation was studied through the laboratory-controlled hot-plastic deformation of dual phase 600 (DP 600) steel using a specially prepared asymmetric single-pass hot-rolling wedge test with a refined reheating grain size instead of the usual coarse-grained starting microstructure observed in practice. The experiment was performed to reduce generally needed experimental trials to observe the microstructure development at elevated temperatures, where stable and unstable conditions could be observed as in the industrial hot-rolling practice. For this purpose, experimental stress–strain curves and softening behaviors were used concerning FEM simulations to reproduce in situ hot-rolling conditions to interpret the grain size distribution. The presented study revealed that the usual approach found in the literature for microstructure investigation and evolution with a hot-rolling wedge test was deficient concerning the observed field of interest. The degree of potential error concerning the implemented deformation per notch position, as well as the stress–strain rate and related mean flow stresses, were highly related to the geometry of the specimen and the material behavior itself, which could be defined by the actual hardening and softening kinetics (recrystallization and grain growth at elevated temperatures and longer interpass times). The grain size distribution at 1100–1070 °C was observed up to a 3.45 s−1 strain rate and, based on its stable forming behavior according to the FEM simulations and the optimal refined grain size, the optimal deformation was positioned between e = 0.2 and e = 0.5.

Dynamic and Postdynamic Recrystallization Behavior of GWZ Magnesium Alloy Under Double‐Hit Hot Compression

Herein, dynamic and postdynamic recrystallization behaviors of GWZ magnesium are investigated. Toward this end, the single‐hit and double‐hit hot compression tests are conducted under strain rate of 0.001 s−1 at 400 °C. The prestrains of 0.1 and 0.5 are considered to investigate the effect of interpass time (5–300 s) on the compressive strength level. At the low strain level of 0.1, the contribution of Hall–Petch effect is considerable due to the occurrence of static recrystallization. In addition, the rare earth texture component is eliminated during interpass annealing. This causes increasing the strength of the material during second pass of hot compression. In contrast, at higher imposed strain, the strength level decreases with increasing the interpass time of annealing. The high amount of strain is completely consumed and the remaining stored energy is not high enough to trigger the occurrence of static recrystallization. The occurrence of metadynamic recrystallization and subsequent growth are characterized. In addition, the texture does not change in respect of the intensity or numbers/types of components. Accordingly, the observed decreasing trend of the strength is justified relying on the occurrence grain growth.

Coupling of an analytical rolling model and reinforcement learning to design pass schedules: towards properties controlled hot rolling

Rolling is a well-established forming process employed in many industrial sectors. Although highly optimized, process disruptions can still lead to undesired final mechanical properties. This paper demonstrates advances in pass schedule design based on reinforcement learning and analytical rolling models to guarantee sound product quality. Integrating an established physical strengthening model into an analytical rolling model allows tracking the microstructure evolution throughout the process, and furthermore the prediction of the yield strength and ultimate tensile strength of the rolled sheet. The trained reinforcement learning algorithm Deep Deterministic Policy Gradient (DDPG) automatically proposes pass schedules by drawing upon established scheduling rules combined with novel rule sets to maximize the final mechanical properties. The designed pass schedule is trialed using a laboratory rolling mill while the predicted properties are confirmed using micrographs and materials testing. Due to its fast calculation time, prospectively this technique can be extended to also account for significant process disruptions such as longer inter-pass times by adapting the pass schedule online to still reach the desired mechanical properties and avoid scrapping of the material.

Production of a Non-Stoichiometric Nb-Ti HSLA Steel by Thermomechanical Processing on a Steckel Mill

Obtaining high levels of mechanical properties in steels is directly linked to the use of special mechanical forming processes and the addition of alloying elements during their manufacture. This work presents a study of a hot-rolled steel strip produced to achieve a yield strength above 600 MPa, using a niobium microalloyed HSLA steel with non-stoichiometric titanium (titanium/nitrogen ratio above 3.42), and rolled on a Steckel mill. A major challenge imposed by rolling on a Steckel mill is that the process is reversible, resulting in long interpass times, which facilitates recrystallization and grain growth kinetics. Rolling parameters whose aim was to obtain the maximum degree of microstructural refinement were determined by considering microstructural evolution simulations performed in MicroSim-SM® software and studying the alloy through physical simulations to obtain critical temperatures and determine the CCT diagram. Four ranges of coiling temperatures (525–550 °C/550–600 °C/600–650 ° C/650–700 °C) were applied to evaluate their impact on microstructure, precipitation hardening, and mechanical properties, with the results showing a very refined microstructure, with the highest yield strength observed at coiling temperatures of 600–650 °C. This scenario is explained by the maximum precipitation of titanium carbide observed at this temperature, leading to a greater contribution of precipitation hardening provided by the presence of a large volume of small-sized precipitates. This paper shows that the combination of optimized industrial parameters based on metallurgical mechanisms and advanced modeling techniques opens up new possibilities for a robust production of high-strength steels using a Steckel mill. The microstructural base for a stable production of high-strength hot-rolled products relies on a consistent grain size refinement provided mainly by the effect of Nb together with appropriate rolling parameters, and the fine precipitation of TiC during cooling provides the additional increase to reach the requested yield strength values.

Analysis of the Microstructure Development of Nb-Microalloyed Steel during Rolling on a Heavy-Section Mill.

It is not realistic to optimize the roll pass design of profile rolling mills, which typically roll hundreds of profiles, using physical modelling or operational rolling. The use of reliable models of microstructure evolution is preferable here. Based on the mathematical equations describing the microstructure evolution during hot rolling, a modified microstructure evolution model was presented that better accounts for the influence of strain-induced precipitation (SIP) on the kinetics of static recrystallization. The time required for half of the structure to soften, t0.5, by static recrystallization was calculated separately for both situations in which strain-induced precipitation occurred or did not occur. On this basis, the resulting model was more sensitive to the description of grain coarsening in the high-rolling-temperature region, which is a consequence of the rapid progress of static recrystallization and the larger interpass times during rolling on cross-country and continuous mills. The modified model was verified using a plain strain compression test (PSCT) simulation of rolling a 100-mm-diameter round bar performed on the Hydrawedge II hot deformation simulator (HDS-20). Four variants of simulations were performed, differing in the rolling temperature in the last four passes. For comparison with the outputs of the modified model, an analysis of the austenite grain size after rolling was performed using optical metallography. For indirect comparison with the model outputs, the SIP initiation time was determined based on the NbX precipitate size distribution obtained by TEM. Using the PSCT and the outputs from the modified microstructure evolution model, it was found that during conventional rolling, strain-induced precipitation occurs after the last pass and thus does not affect the austenite grain size. By lowering the rolling temperature, it was possible to reduce the grain size by up to 56 μm, while increasing the mean flow stress by a maximum of 74%. The resulting grain size for all four modes was consistent with the operating results.

Stochastic model describing evolution of microstructural parameters during hot rolling of steel plates and strips

Enhancing strength-ductility synergy of materials has been for decades an objective of research on structural metallic materials. It has been shown by many researchers that significant improvement of this synergy can be obtained by tailoring heterogeneous multiphase microstructures. Since large gradients of properties in these microstructures cause a decrease of the local fracture resistance, the objective of research is to obtain smoother gradients of properties by control of the manufacturing process. Advanced material models are needed to design such microstructures with smooth gradients. These models should supply information about distributions of various microstructural features, instead of their average values. Models based on stochastic internal variables meet this requirement. Our objective was to account for the random character of the recrystallization and to transfer this randomness into equations describing the evolution of dislocations and grain size during hot deformation and during interpass times. The idea of this stochastic model is described in the paper. Experiments composed of uniaxial compression tests were performed to supply data for the identification and verification of the model in the hot deformation and static recrystallization parts. Histograms of the grain size were measured after hot deformation and at different times after the end of deformation. Identification and validation of the model were performed. The validated model, which predicts evolution of heterogeneous multiphase microstructure, is the main output of our work. The model was implemented in the finite element program for hot rolling of plates and sheets and simulations of these processes were performed. The model’s capability to compare and evaluate various rolling strategies are demonstrated in the paper.

Effect of Niobium Supersaturation in Austenite on the Static Recrystallization Behavior of Carbon Structural Steels

This work describes the effect of Nb supersaturation in austenite on the suppression of static recrystallization of austenite during an isothermal holding period following hot deformation. The investigation involved three carbon structural steels with varying Nb concentration at constant C (0.20 pct) and N (0.007 pct) levels. The isothermal double-hit deformation technique led to the determination of T5 pct and T95 pct (recrystallization-stop and full recrystallization temperatures, respectively) as a function of a true strain and interpass time. The results indicate that the T5 pct increases with increasing Nb supersaturation in austenite at a rate of 40 °C per 0.006 pct Nb supersaturation for a true stain ε=0.40. At each respective T5 pct, all tested steels exhibited an Nb supersaturation ratio ≥ 7.5 in austenite. A high, localized strain-induced precipitation of Nb(CN) was observed at the austenite subgrain boundaries in the unrecrystallized microstructure. This translated into higher values for local precipitate-pinning forces (FPIN), which were significantly higher than that predicted from equilibrium thermodynamics. The critical FPIN for retardation of static recrystallization was found to be 1.6 MPa at the respective T5 pct for each steel. The present study has contributed to advancing our knowledge of the interplay between Nb solute supersaturation and volume fraction of Nb(CN) precipitation in particular for carbon structural steels. It has also highlighted an opportunity to apply niobium, even an ultra-low addition (i.e., < 100 ppm) to commodity-grade structural steels to reduce overall alloying costs.

Study on static softening behavior and hot working performance of Fe-0.2C-7Mn steel

Static softening behavior and hot working performance of medium Mn steel (Fe-0.2C-7Mn) are studied by 2-step and interrupt hot compression test with a Gleeble-3500 thermal-mechanical simulator. The results show that static softening behavior of the steel exhibits obvious sensitivity to the deformation temperature, inter-pass time and strain rate. But deformation temperature has a more significant effect on the static recrystallization (SRX) grain size than strain rate. 3D hot working processing maps are established, that low temperature and medium strain rate (850 °C ∼ 925 °C and 0.02 s−1 ∼ 0.3 s−1) are the preferred thermal deformation conditions for the test steel. Microstructure observations indicate that both static recovery (SRV) and SRX occur within inter-pass time, and SRV is the predominant mechanism in determining softening fraction. The microstructure is composed of film-like α at room temperature, and most of the nucleation of SRX preferably take place at triple junctions of grains or prior grain boundaries. Besides, high-angle grain boundaries (HAGBs) migration produce twin boundaries during grain growth and the main nucleation mechanism of the SRX is strain-induced boundary migration. The kinetics model of static softening is established and the experimental values are consistent with predicted ones, which proves the reliability of the model.

Physical and Numerical Simulations for Predicting Distribution of Microstructural Features during Thermomechanical Processing of Steels.

The design of modern construction materials with heterogeneous microstructures requires a numerical model that can predict the distribution of microstructural features instead of average values. The accuracy and reliability of such models depend on the proper identification of the coefficients for a particular material. This work was motivated by the need for advanced experimental data to identify stochastic material models. Extensive experiments were performed to supply data to identify a model of austenite microstructure evolution in steels during hot deformation and during the interpass times between deformations. Two sets of tests were performed. The first set involved hot compressions with a nominal strain of 1. The second set involved hot compressions with lower nominal strains, followed by holding at the deformation temperature for different times. Histograms of austenite grain size after each test were measured and used in the identification procedure. The stochastic model, which was developed elsewhere, was identified. Inverse analysis with the objective function based on the distance between the measured and calculated histograms was applied. Validation of the model was performed for the experiments, which were not used in the identification. The distance between the measured and calculated histograms was determined for each test using the Bhattacharyya metric and very low values were obtained. As a case study, the model with the optimal coefficients was applied to the simulation of the selected industrial hot-forming process.

Metadynamic recrystallization in A5083 aluminum alloy with homogenized and as-extruded initial microstructures

The static softening behavior of A5083 aluminum alloy with different initial microstructures was studied using various characterization techniques. To calculate the recrystallized fraction, in the compression test, a new method based on the offset yield stress method and the Hall–Petch relationship was proposed, which is more accurate than the conventional methods and applicable even when the initial microstructure is complex. And in the stress relaxation test, a method proposed in our previous study was applied, indicating that this method could be employed in materials with incomplete recrystallization or a complex initial microstructure. Although the as-extruded initial microstructure led to a more developed metadynamic recrystallization, the recrystallization became heterogeneous, compared with the homogenized initial microstructure. When the anvil was not unloaded during the interpass time, the resulting external stress accelerated static recovery but impeded metadynamic recrystallization. New insights were discussed that challenge the conventional view in metadynamic recrystallization. First, metadynamic recrystallization always required an incubation time, unless the experimental conditions were sufficiently favorable for recrystallization. Second, when recovery was active, not only the dynamic recrystallized grains but also the recovery-enhanced subgrains were the potential nuclei for the subsequent metadynamic recrystallization.

Effect of hot rolling parameters on recovery mechanism in 436 (17%Cr, Nb-Mo) ferritic stainless steel

Ferritic stainless steel (FSS) grades are widely used for applications that require high strength and corrosion resistance. Their cost and versatility in the steel market have attracted a lot of interest from both industry and academic research. Despite their desirable properties, these steels grades experience surface defects as a result of microstructural evolution that evolves due to softening mechanism. The current study simulated the roughing hot rolling processes of AISI 436 (17%Cr, Nb-Mo) FSS to study the effects of inter-pass time and strain on the precipitation behaviour and the softening mechanisms in 436 FSS. The softening mechanisms and the resulting microstructures were investigated using SEM-EBSD technique. The results revealed Particle Stimulated Nucleation of new grains during the simulated roughing rolling which promoted recrystallisation due to strain accumulation. Stored deformation energy was found to increase with an increase in interpass time and strain.

Electron backscatter diffraction postprocessing techniques for studying recrystallisation phenomenon of Ferritic Stainless Steel

The following article looks at using scanning electron microscopy- electron back scatter diffraction techniques to study recrystallisation structures produced through hot rolling of 436 ferritic stainless steel. Characterisation of recrystallisation textures was undertaken through analysis of misorientation angle distribution diagrams, orientation distribution function maps, inverse pole figures and Taylor factor maps. These techniques were applied in a case study where typical industrial hot rolling conditions were simulated through uniaxial compression tests in a Bähr Dilatometer 850D, whereby the effect of strain rate and interpass time on recrystallisation structures was investigated.

Ultra-low niobium (ULNb) alloying design solution for commodity grade structural steels

Conventionally the addition of micro-alloying elements such as niobium (Nb), typically ≥ 0.020w t%Nb, has been associated with high strength low alloy (HSLA) steels with lower carbon content and processed by means of Thermo-Mechanical rolling. Here it is well established, that Nb has the strongest effect in retarding static recrystallisation of austenite during inter-pass times by precipitate pinning mechanism. Due to the lower solubility of Nb in austenite at typical carbon levels associated with commodity grade structural steels (i.e., ≥0.15wt.%C), the use of Nb has been somewhat limited and widely regarded to be applied only when higher strengths, ≥355 MPa and/or low temperature impact toughness properties are specified.However, recent laboratory studies coupled with industrial trials have demonstrated an alternative solution to make commodity grade structural steels, without making any changes to existing processing routes employed. By using Ultra-Low Niobium (ULNb) additions (i.e., ≤100ppmNb) it is possible to enable cost savings in ferro-alloying expenditure coupled with a reduction in grade specific GWPe/tonne of steel produced. This paper summarises and presents these recent findings and discusses the metallurgical background towards extracting greater value from existing commodity grade structural steels through Ultra-Low additions of Nb.

Physical simulation of finish rolling of microalloyed steels in isothermal conditions

The aim of this work was to establish a temperature of finish rolling stage of Nb/Ti microalloyed steel containing 0.06 wt.% C, 0.77 wt.% Mn, 0.039 wt.% Nb and 0.015 wt.% Ti, using physical simulation. Samples were subjected to laboratory simulation at a twist plastometer at high temperatures, i.e. between 825 and 950?C. Five pass deformation and interpass times were selected in accordance with a processing parameters at five stand finishing hot strip mill. Restoration (recovery and/or recrystallization) behavior was evaluated by calculation of Fraction Softening (FS) and Area Softening Parameter (ASP) values. At 950?C all individual pass stress-strain curves, FS and ASP show full recrystallization in all interpass intervals. On the other hand, with a decrease in temperature to the interval of 875-825?C, the extent of restoration is decreasing, leading to recovery as a sole softening mechanism at 825?C, which was confirmed by the stress-strain curve shape, and values of FS and ASP. It is assumed that, due to high supersaturation, strain-induced precipitation promoted pinning of grain and subgrain boundaries and suppressed recrystallization. Therefore, the critical temperature for finish rolling was estimated to be 825?C.

Multistage strain aging phenomenon of low-carbon steels with rolling pre-strain

In this study, a multistage strain aging method that used rolling pre-strain (compression) was developed to study the effects of temperature, and inter-pass time on static strain aging behavior of low carbon steel. An increase in hardness and strength caused by work hardening due to the forming process and aging at every stage of aging that is calculated separately. To comparing the effects of multistage aging against typical strain aging, the samples were rolled and subjected to the aging process both exist in typical one-stage aging that setting a 20% rolling pre-strain and in multiple stages pre-strain by setting a 5% rolling ratio in four stages. The mechanical properties of aged samples are compared with each other to study the effects of time and temperatures on strength and hardness. To evaluate the effects of pre-strain type (tensile or compression) on mechanical properties, one sample was subjected to tensile and compared with rolling pre-strain samples in similar conditions. The results show that in multistage static strain aged samples with rolling pre-strain, the peak of the strain stress curve occurs in 10–15 min rather than samples that aged after tensile pre-strain. Multistage strain aging increased samples’ strength by 10% and reduced their plasticity by 5%. To evaluate the effects of temperature on the time, we propose the maximum hardness and strength, the aging temperature of the samples was increased to 250 °C and it was observed that the maximum hardness and strength time is reduced by 10 min.