Papers by Author: De Ning Zou

Abstract: The precipitation behavior of nitrides and carbides occurred in aging process for 10Cr21Mn16NiN austenitic stainless steel at intermediate temperature was investigated by use of thermodynamic calculation, metallography and electron microscopy analysis. The precipitates evolved from chain-like initiatively along grain boundaries at lower aging temperature, to that along grain boundaries and inside the grain of austenite with more content as the temperature rising gradually. When aging at 800 °C, precipitates became layered tablet shaped and the composition was ascertained the mixture of Cr₂N and M₂₃C₆. At a certain temperature, the volume fraction of precipitates for the aged testing steel by air cooling was slightly higher than that by water quenching.

Abstract: Elevated compression tests were conducted on 2205 duplex stainless steel using a Gleeble 3800 thermal simulator under constant strain rates ranging from 0.1 s−1 to 50 s−1 and at deformation temperatures ranging from 900°C to 1200°C for the sample. All tests were performed at a total true strain of 0.9. The elevated temperature deformation behavior of the 2205 duplex stainless steel was characterized based on an analysis of the stress–strain curves. A set of constitutive equations for 2205 duplex stainless steel was proposed by employing hyperbolic sine function. The equations revealed the dependence of flow stress on strain, strain rate and temperature. In order to evaluate the accuracy of the constitutive equations, the mean errors of flow stress between the experimental data and predicted results were calculated. The results showed that there was a good agreement between the prediction and experimental values.

Abstract: The hot deformation behavior of super 13Cr martensitic stainless steel was investigated using artificial neural network (ANN). Hot compression tests were carried out at the temperature range of 950°C to 1200°C and strain rate range of 0.1–50s^–1 at an interval of an order of magnitude. Based on the limited experimental data, the ANN model for the constitutive relationship existed between flow stress and strain, strain rate and deformation temperature was developed by back-propagation (BP) neural network method. A three layer structured network with one hidden layer and ten hidden neurons was trained and the normalization method was employed in training for avoiding over fitting. Modeling results show that the developed ANN model can efficiently predict the flow stress of the steel and reflect the hot deformation behavior in the whole deforming process.

Abstract: Supermartensitic stainless steel grades are widely used in oil and gas industries to substitute duplex and super duplex stainless steels these years. In this paper the corrosion behavior of supermartensitic stainless steels with different chemical compositions, S-165 and HP, was investigated in Cl^- environment. All the samples were treated by quenching at 1000 °C followed by tempering at 630 °C for 2h. After heat treatment, potentiodynamic polarization curves and electrochemical impedance spectroscopy (EIS) were determined on both kinds of samples. Polarization curves shows that the metastable pitting nucleuses were formed in passive area and the Cr content is the most important factor leading to the differences of pitting potential. The potentiodynamic polarization curves were conducted at various NaCl contents (5000, 15000 and 35000 ppm) and emphasized the need to account for the Cl^- sensitivity of samples under corrosion environment. The results show that, the pitting potential decrease with the increase of chloride contents. The behavior of passive film was analyzed by electrochemical impedance spectroscopy.

Abstract: In this investigation a theoretical model based on artificial neural network (ANN) and genetic algorithm (GA) have been developed to optimize the heat treatment technological parameters for achieving the excellent mechanical property of super-martensitic stainless steel (SMSS). The ANN was used to correlate the heat treatment technological conditions to the mechanical property. The GA and ANN were incorporated to find the optimal technological parameters. The result shows that the most optimal heat treatment technological is 1003.9°C×0.5h (air cooling) +629.75°C+2.06h (air cooling). By comparing the prediction values with the experimental data it is demonstrated that the combined GA–ANN algorithm is efficient and strong method to find the optimum heat treatment technological for producing super-martensitic stainless steel.

Abstract: In this study, the effect of original thicknesses of plate, the thicknesses of plate after rolling and rolling reduction on the strength in 301 stainless steel was modeled by means of artificial neural network (ANN). The experimental data were collected to obtain training set and testing set. The normalization method was employed for avoiding over-fitting. The optimal ANN method architecture was determined by according to the trial and error procedure. The results of the ANN model were in good agreement with experimental data. As can be seen from the result, we believe that the neural network model can efficiently predict the relationship between mechanical properties and rolling reduction in 301 austenitic stainless steel.

Abstract: In this paper, artificial neural networks (ANN) has been proposed to determine the stresses of 13Cr supermartensitic stainless steel (SMSS) welds based on various deformation temperatures and strains using experimental data from tensile tests. The experiments provided the required data for training and testing. A three layer feed-forward network, deformation temperature and strain as input parameters while stress as the output, was trained with automated regularization (AR) algorithm for preventing overfitting. The results showed that the best fitting training dataset was obtained with ten units in the hidden layer, which made it possible to predict stress accurately. The correlation coefficients (R-value) between experiments and prediction for the training and testing dataset were 0.9980 and 0.9943, respectively, the biggest absolute relative error (ARE) was 6.060 %. As seen that the ANN model was an efficient quantitative tool to evaluate and predict the deformation behavior of type 13Cr SMSS welds during tensile test under different temperatures and strains.

Abstract: The various temperature solution experiments were carried out in this paper, which for 2205 duplex stainless steel joints welded by manual arc welding. The evolutions of microstructure in pre/post solution treatment and the contents of ferrite phase were conducted by using optical microscope and ferrite scope detector. The analysis results in the welded, the heat affected and the base metal regions show that suitable solution treatment is effective to adjust the welded microstructure condition. The austenite in each region transformed into ferrite when the temperature enhanced from 1050 to 1200°C. This resulted in increasing the volume of ferrite and coarsening the grain. All microstructure characteristics of the three regions were taken into account, it deduced that the feasible solution temperature range was 1050~1100°C for 2205 duplex stainless steel welded joint.

Abstract: Specimens of 2507 super-duplex stainless steel aging at 850°C for 5 min, 15 min and 60 min were investigated to evaluate the pitting corrosion resistance in 3.5% NaCl solution at 30°C and 50°C. The results are correlated with the microstructures obtained with different aging time. The precipitation of σ phase remarkably decreases the pitting corrosion resistance of the steel and the specimen aged for 60 min presents the lowest pitting potential at both 30°C and 50°C. With increasing the ambient temperature from 30°C to 50°C, the pitting potential exhibits a reduction tendency, while this tendency is less obviously in enhancing the ambient temperature than in extending the isothermal aging duration from 5 to 60 min. SEM analysis shows that the surrounding regions of σ phase are the preferable sites for the formation of corrosion pits which grew up subsequently. This may be attributed to the lower content of corrosion resistance elements in these regions formatted with σ phase precipitation.

Abstract: Color-optical microscopy, energy spectrum analysis, hardness measuring, tensile and corrosion testing were conducted to investigate characteristics of microstructure, mechanical properties and corrosion resistance of S32750 super-duplex stainless steel aged at 850～920°C. The results indicate that with the increase of aging temperature and aging time the content of σ phase increases, while the ferrite content decreases. The forming and growing of σ phase obtained during aging causes an increase in hardness and a reduction in ductility of the aged steel. Moreover, increasing aging time the corrosion resistance reduces, owing to a new formed austenite occurs.