S. Venugopal

Artificial neural network modeling to evaluate and predict the deformation behavior of stainless steel type AISI 304L during hot torsion

The deformation behavior of type 304L stainless steel during hot torsion is investigated using artificial neural network (ANN). Torsion tests in the temperature range of 600-1200^oC and in the (maximum surface) strain rate range of 0.1-100s^-^1 were carried out. These experiments provided the required data for training the neural network and for subsequent testing. The input parameters of the model are strain, log strain rate and temperature while torsional flow stress is the output. A three layer feed-forward network was trained with standard back propagation (BP) and Resilient propagation (Rprop) algorithm. The paper makes a robust comparison of the performances of the above two algorithms. The network trained with Rprop algorithm is found to perform better and also needs less number of iterations for convergence. The developed ANN model employing this algorithm could efficiently track the work hardening, dynamic softening and flow localization regions of the deforming material. Sensitivity analysis showed that temperature and strain rate are the most significant parameters while strain affects the flow stress only moderately. The ANN model, described in this paper, is an efficient quantitative tool to evaluate and predict the deformation behavior of type 304L stainless steel during hot torsion.

Constitutive flow behaviour of austenitic stainless steels under hot deformation: artificial neural network modelling to understand, evaluate and predict

An artificial neural network (ANN) model is developed to predict the constitutive flow behaviour of austenitic stainless steels during hot deformation. The input parameters are alloy composition and process variables whereas flow stress is the output. The model is based on a three-layer feed-forward ANN with a back-propagation learning algorithm. The neural network is trained with an in-house database obtained from hot compression tests on various grades of austenitic stainless steels. The performance of the model is evaluated using a wide variety of statistical indices. Good agreement between experimental and predicted data is obtained. The correlation between individual alloying elements and high temperature flow behaviour is investigated by employing the ANN model. The results are found to be consistent with the physical phenomena. The model can be used as a guideline for new alloy development.

Processing maps for hot working of commercial grade wrought stainless steel type AISI 304

The hot-working behaviour of commercial grade wrought stainless steel type AISI 304 is characterized using processing maps developed on the basis of the dynamic material model and hot compression data in the temperature range 600–1250°C and strain rate range 0.001–100 s–. The material exhibits a dynamic recrystallization (DRX) domain in the temperature range 1000–1200°C at a strain rate of 0.01 s−1. Optimum hot workability occurs at 1100°C and 0.01 s−1, which corresponds to a peak efficiency of 32% in the DRX domain. Finer grain sizes are obtained at 1000°C and all strain rates. In comparison with low interstitial stainless steel type AISI 304 L, the DRX occurs at lower strain rate and temperature. This result is attributed to the strong primary effect of interstitial carbon enhancing the rate of DRX nucleation. Flow instabilities occur in the entire region above the DRX domain. Flow localization occurs in the regions of instability at temperatures lower than 1000°C and ferrite formation is responsible for the instability at higher temperatures.

Validation of processing maps for 304L stainless steel using hot forging, rolling and extrusion

The development of a microstructure in 304L stainless steel during industrial hot-forming operations, including press forging (mean strain rate of 0.15 s(-1)), rolling/extrusion (2-5 s(-1)), and hammer forging (100 s(-1)) at different temperatures in the range 600-1200 degrees C, was studied with a view to validating the predictions of the processing map. The results have shown that excellent correlation exists between the regimes exhibited by the map and the product microstructures. 304L stainless steel exhibits instability bands when hammer forged at temperatures below 1100 degrees C, rolled/extruded below 1000 degrees C, or press forged below 800 degrees C. All of these conditions must be avoided in mechanical processing of the material. On the other hand, ideally, the material may be rolled, extruded, or press forged at 1200 degrees C to obtain a defect-free microstructure.

Ultrasonic velocity measurements for characterizing the annealing behaviour of cold worked austenitic stainless steel

Precise measurements of shear wave velocities have been made in 20% cold worked and annealed samples of alloy D9 (Ti-modified austenitic stainless steel) to characterize the microstructural changes during annealing. The variation in wave velocity with annealing time exhibited a three stage behaviour. In the first stage, a slight increase in the velocity during recovery regime has been observed. This is followed by a significant increase in the velocity in the recrystallization regime (second stage) and reaching saturation on completion of recrystallization (third stage). Microstructural observations using optical metallography confirmed these three stages. The maximum variation in velocity is observed only when the polarization or the propagation direction of the shear wave is alingned with the cold working direction. Variation in shear wave velocity during annealing process, in general, is just opposite to that of the variation in longitudinal wave velocity. A number of velocity measurements were made by changing the propagation and polarization directions of the shear waves with respect to the cold working direction. Based on these measurements, a suitable velocity ratio parameter is suggested for determining the degree of recrystallization during annealing of cold worked alloy D9.

Capability of a Feed-Forward Artificial Neural Network to Predict the Constitutive Flow Behavior of As Cast 304 Stainless Steel Under Hot Deformation

A model is developed to predict the constitutive flow behavior of as cast 304 stainless steel during hot deformation using artificial neural network (ANN). The inputs of the neural network are strain, strain rate, and temperature, whereas flow stress is the output. Experimental data obtained from hot compression tests in the temperature range 1023-1523 K, strain range 0.1-0.5, and strain rate range 10 -3 -10 2 s -1 are employed to develop the model. A three-layer feed-forward ANN is trained with standard back propagation and some upgraded algorithms like resilient propagation (Rprop) and superSAB. The performances of these algorithms are evaluated using a wide variety of standard statistical indices. The results of this study show that Rprop algorithm performs better as compared to others and thereby considered as the most efficient algorithm for the present study. It has been shown that the developed ANN model can efficiently and accurately predict the hot deformation behavior of as cast 304 stainless steel. Finally, an attempt has been made to quantify the extrapolation ability of the developed network.

OPTIMIZATION OF COLD AND WARM WORKABILITY IN STAINLESS STEEL TYPE AISI 316L USING INSTABILITY MAPS

The deformation characteristics of stainless steel type AISI 316L under compression in the temperature range 20 to 600 degrees C and strain rate range 0.001 to 100 s(-1) have been studied with a view to characterizing the flow instabilities occurring in the microstructure. At temperatures lower than 100 degrees C and strain rates higher than 0.1 s(-1), 316L stainless steel exhibits flow localization whereas dynamic strain aging (DSA) occurs at intermediate temperatures and below 1 s(-1). To avoid the above flow instabilities, cold working should be carried out at strain rates less than 0.1 s(-1). Warm working of stainless steel type AISI 316L may be done in the temperature and strain rate regime of: 300 to 400 degrees C and 0.001 s(-1) 300 to 450 degrees C and 0.01 s(-1): 450 to 600 degrees C and 0.1 s(-1); 500 degrees C and 1 s(-1) since these regions are free from flow instabilities like DSA and flow localization. The continuum criterion, developed on the basis of the principles of maximum rate of entropy production and separability of the dissipation function, predicts accurately all the above instability features.

A journey with prasad’s processing maps

The constitutive flow behavior of austenitic stainless steel types AISI 304L, 316L, and 304 in the temperature range of 873 K (600 °C) to 1473 K (1200 °C) and strain-rate range of 0.001 s−1–100 s−1 has been evaluated with a view to establishing processing-microstructure-property relationships during hot working. The technique adopted for the study of constitutive behavior is through establishing processing maps and instability maps, and interpreting them on the basis of dynamic materials model (DMM). The processing maps for 304L have revealed a domain of dynamic recrystallization (DRX) occurring at 1423 K (1150 °C) at 0.1 s−1, which is the optimum condition for hot working of this material. The processing maps of 304 predict DRX domain at 1373 K (1100 °C) and 0.1 s−1. Stainless steel type 316L undergoes DRX at 1523 K (1250 °C) and 0.05 s−1. At 1173 K (900 °C) and 0.001 s−1 this material undergoes dynamic recovery (DRY). In the temperature and strain rate regimes other than DRX and DRY domains, austenitic stainless steels exhibit flow localization. Large-scale experiments using rolling, forging, and extrusion processes were conducted with a view to validating the conclusions arrived at from the processing maps. The “safe” processing regime predicted by processing maps has been further refined using the values of apparent activation energy during deformation. The validity and the merit of this refining procedure have been demonstrated with an example of press forging trials on stainless steel 316L. The usefulness of this approach for manufacturing stainless steel tubes and hot rolled plates has been demonstrated.

Influence of state of stress on the processing map for hot working of stainless steel type AISI 304L : compression vs. torsion

Abstract Processing maps for hot working of stainless steel of type AISI 304L have been developed on the basis of the flow stress data generated by compression and torsion in the temperature range 600–1200 °C and strain rate range 0.1–100 s−1. The efficiency of power dissipation given by 2m/(m+1) where m is the strain rate sensitivity is plotted as a function of temperature and strain rate to obtain a processing map, which is interpreted on the basis of the Dynamic Materials Model. The maps obtained by compression as well as torsion exhibited a domain of dynamic recrystallization with its peak efficiency occurring at 1200 °C and 0.1 s−1. These are the optimum hot-working parameters which may be obtained by either of the test techniques. The peak efficiency for the dynamic recrystallization is apparently higher (64%) than that obtained in constant-true-strain-rate compression (41%) and the difference in explained on the basis of strain rate variations occurring across the section of solid torsion bar. A region of flow instability has occurred at lower temperatures (below 1000 °C) and higher strain rates (above 1 s−1) and is wider in torsion than in compression. To achieve complete microstructure control in a component, the state of stress will have to be considered.

Processing map for cold and hot working of stainless steel type AISI 304 L

A processing map for stainless steel of type AISI 304 L has been developed in the temperature range 20–1250°C and strain-rate range 0.001–100 s−1 on the basis of the dynamic materials model. A domain of dynamic recrystallization has been observed with its peak efficiency of 35% occurring at 1250°C and 0.1 s−1 and these are the optimum parameters for hot working of the stainless steel. In the intermediate-temperature range, the stainless steel exhibits flow localization which restricts warm working of this material to smaller strains with intermediate annealing. Cold forming may be done at strain rates higher than about 0.01 s−1 since at lower strain rates martensite formation may cause flow instability.