Local Austenite grain size distribution in hot bar rolling of AISI 4135 Steel

In this paper, the local distribution of austenite grain size (AGS) was experimentally determined by conducting single round-oval and square-diamond pass hot bar rolling experiments of AISI4135 steel. The rolling experiments were carried out using the laboratory mill. The local distribution of AGS was also determined numerically. In order to predict AGS distribution, the AGS evolution model was combined with three dimensional non-isothermal finite element analyses by adopting a modified additivity rule. AGS evolution model was experimentally determined from hot torsion test according to Hodgson's model. The predicted results were in a reasonably good agreement with experimental results.

Microstructure evolution modeling of square-diamond pass hot bar rolling of AISI 4135 steel

In this study, kinetics of the static (SRX) and metadynamic recrystallization (MDRX) of AISI4135 steel was investigated using hot torsion tests. Continuous torsion tests were carried out to determine the critical strain for dynamic recrystallization (DRX). The times for 50% recrystallization of SRX and MDRX were determined, respectively, by means of interrupted torsion tests. Furthermore, austenite grain size (AGS) evolution due to recrystallization (RX) was measured by optical microscopy. With the help of the evolution model established, the AGS for hot bar rolling of AISI4135 steel was predicted numerically. The predicted AGS values were compared with the results using the other model available in the literature and experimental results to verify its validity. Then, numerical predictions depending on various process parameters such as interpass time, temperature, and roll speed were made to investigate the effect of these parameters on AGS distributions for square-diamond pass rolling. Such numerical results were found to be beneficial in understanding the effect of processing conditions on the microstructure evolution better and control the rolling processes more accurately.

Dice-rolling games : yahtzee, poker dice and others

Provides information on some dice rolling games and the social need for mathematical information on gambling. Pass the pig; Heads, tails or odds; Yahtzee.

Eccentricity and hardness control in cold rolling mills with a dynamically constructed neural controller

The main objective of a steel strip rolling process is to produce high quality steel at a desired thickness.  Thickness reduction is the result of the speed difference between the incoming and the outgoing steel strip and the application of the large normal forces via the backup and the work rolls.  Gauge control of a cold rolled steel strip is achieved using the gaugemeter principle that works adequately for the input gauge changes and the strip hardness changes.  However, the compensation of some factors is problematic, for example, eccentricity of the backup rolls.  This cyclic eccentricity effect causes a gauge deviation, but more importantly, a signal is passed to the gap position control so to increase the eccentricity deviation.  Consequently, the required high product tolerances are severely limited by the presence of the roll eccentricity effects.
In this paper a direct model reference adaptive control (MRAC) scheme with dynamically constructed neural controller was used.  The aim here is to find the simplest controller structure capable of achieving an optimal performance.  The stability of the adaptive neural control scheme (i.e. the requirement of persistency of excitation and bounded learning rates) is addressed by using as the inputs to the reference model the plant's state variables.  In such a case, excitation is due to actual plant signals (states) affected by plant disturbances and noise.  In addition, a reference model in the form of a filter with a desired transfer function using Modulus Optimum design was used to ensure variance in the desired dynamic characteristics of the system.  The gradually decreasing learning rate employed by the neural controller in this paper is aimed at eliminating controller instability resulting from over-aggressive control.  The moving target problem (i.e. the difficulty of global neural networks to perfrom several separate computational tasks in closed -loop control) is addressed by the localized architecture of the controller.  The above control scheme and learning algorithm offers a method for automatic discovery of an efficient controller.
The resulting neural controller produces an excellent disturbance rejection in both cases of eccentricity and hardness disturbances, reducing the gauge deviation due to eccentricity disturbance from 33.36% to 4.57% on average, and the gauge deviation due to hardness disturbance from 12.59% to 2.08%.

Optimization of alloy design and hot rolling conditions for shape memory in Fe–Mn–Si-based alloys

The effect of composition and hot rolling conditions on the shape memory effect (SME) in the Fe–Mn–Si-based system has been studied to obtain improved shape memory without the need to rely on “training”. It has been found that the texture is not markedly affected by rolling conditions, and texture is therefore not a major factor in explaining variations in SME with processing conditions. Decreasing the pre-deformation temperature to below the Ms was found to have a beneficial effect on shape memory. It was found that the best SME was achieved in an alloy that had Ms just above room temperature, and had been processed by hot rolling followed by recovery annealing. Alloys of different compositions exhibited different optimum rolling temperatures for maximum shape memory performance.

Use of residual hydrogen to produce CP-Ti powder compacts for low temperature rolling

The present work investigates the optimal level of residual hydrogen in partially de-hydrogenated powder to produce CP-Ti plate compacts using ECAP with back pressure which are subsequently rolled at low temperature. A comparative study of the compaction of two TiH₂ powders and a CP-Ti powder, with particle sizes 150 um, 50um and 45 um respectively, has been carried out. The hydride powders have also been compacted in a partially de-hydrogenated state. The optimal level of residual hydrogen with respect to the density of the resulting compact and the associated mechanical properties has been defined. ECAP at 300°C produced compacts from these partially de-hydrogenated powders of 99.5% theoretical density, while CP-Ti was compacted to almost full theoretical density under the same ECAP conditions. Therefore, the compaction of powder by ECAP does not benefit from temporary hydrogen alloying.

These compacts then were rolled at temperatures ranging from room temperature to 500°C with an 80% reduction in a single pass. Heat treatment after the rolling can modify the microstructure to improve the resulting mechanical properties and in this regard the temporary alloying with hydrogen has been observed to offer some significant benefits. It is shown the ECAP followed by low temperature rolling is a promising route to the batch production of fully dense CP-Ti wrought product from powder feedstock that avoids the need to subject the material to temperatures greater than 500°C. This low temperature route is expected to be efficient from an energy point of view and it also avoids the danger of interstitial contamination that accompanies most high temperature powder processing.

Deformation behaviour of ultrafine grained steel produced by cold rolling of martensite

An ultrafine grained Nb microalloyed steel was produced by cold rolling of martensite followed by annealing heat treatments at different times to study its effect on the microstructure and mechanical behaviour of the ultrafine grained steel. High strength was achieved by this thermomechanical processing due to the formation of cell and subgrain dislocation substructure; however annealing reduced both strength and elongation.

Modeling and control of flatness in cold rolling mill using fuzzy petri nets

Today, having a good flatness control in steel industry is essential to ensure an overall product quality, productivity and successful processing. Flatness error, given as difference between measured strip flatness and target curve, can be minimized by modifying roll gap with various control functions. In most practical systems, knowing the definition of the model in order to have an acceptable control is essential. In this paper, a fuzzy Petri net method for modeling and control of flatness in cold rolling mill is developed. The method combines the concepts of Petri net and fuzzy control theories. It focuses on the fuzzy decision making problems of the fuzzy rule tree structures. The method is able to detect and recover possible errors that can occur in the fuzzy rule of the knowledge-based system. The method is implemented and simulated. The results show that its error is less than that of a PI conventional controller.

Development of asymmetric rolling for the better control over structure and mechanical properties in IF steel

In the present study, the effects of kinematic and geometric asymmetries in rolling during multi-pass processing of IF steel are examined. The theoretical investigation by final element simulations and experimental investigations by means of electron-backscatter diffraction analysis and tensile tests suggest that asymmetric rolling increases the total imposed strain compared to symmetric rolling, and largely re-distributes the strain components due to additional shear. This enhances the intensity of grain refinement, strengthens and tilts crystallographic orientations, and increases mechanical strength. The effect is highest in the asymmetric rolling with differential roll diameters.