1000 resultados para Steel


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The strengthening mechanism responsible for the unique combination of ultimate tensile strength and elongation in a multiphase Fe-0.2C-1.5Mn-1.2Si-0.3Mo-0.6Al-0.02Nb (wt%) steel was studied. The microstructures with different volume fractions of polygonal ferrite, bainite and retained austenite were simulated by controlled thermomechanical processing. The interrupted tensile test was used to study the bainitic ferrite, retained austenite and polygonal ferrite behaviour as a function of plastic strain. X-ray analysis was used to characterise the volume fraction and carbon content of retained austenite. Transmission electron microscopy was utilised to analyse the effect of bainitic ferrite morphology on the strain induced transformation of retained austenite and retained austenite twinning as a function of strain in the bulk material. The study has shown that the austenite twinning mechanism is more preferable than the transformation induced plasticity (TRIP) mechanism during the early stages of deformation for a microstructure containing 15% polygonal ferrite, while the transformation induced plasticity effect is the main mechanism when there is 50% of polygonal ferrite in the microstructure. The bainitic ferrite morphology affects the deformation mode of retained austenite during straining. The polygonal ferrite behaviour during straining depends on dislocation substructure formed due to the deformation and the additional mobile dislocations caused by the TRIP effect. Operation of TRIP or twinning mechanisms depends not only on the chemical and mechanical stability of retained austenite, but also on the interaction of the phases during straining.

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The microstructure and crystallographic texture characteristics were studied in a 22Cr-6Ni-3Mo duplex stainless steel subjected to plastic deformation in torsion at a temperature of 1000 °C using a strain rate of 1 s−1. High-resolution EBSD was successfully used for precise phase and substructural characterization of this steel. The austenite/ferrite ratio and phase morphology as well as the crystallographic texture, subgrain size, misorientation angles and misorientation gradients corresponding to each phase were determined over large sample areas. The deformation mechanisms in each phase and the interrelationship between the two are discussed.

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The evolution of crystallographic texture and deformation substructure was studied in a type 316L austenitic stainless steel, deformed in rolling at 900 °C to true strain levels of about 0.3 and 0.7. Electron backscatter diffraction (EBSD) and transmission electron microscopy (TEM) were used in the investigation and a comparison of the substructural characteristics obtained by these techniques was made. At the lower strain level, the deformation substructure observed by EBSD appeared to be rather poorly developed. There was considerable evidence of a rotation of the pre-existing twin boundaries from their original orientation relationship, as well as the formation of highly distorted grain boundary regions. In TEM, at this strain level, the substructure was more clearly revealed, although it appeared rather inhomogeneously developed from grain to grain. The subgrains were frequently elongated and their boundaries often approximated to traces of {111} slip planes. The corresponding misorientations were small and largely displayed a non-cumulative character. At the larger strain, the substructure within most grains became well developed and the corresponding misorientations increased. This resulted in better detection of sub-boundaries by EBSD, although the percentage of indexing slightly decreased. TEM revealed splitting of some sub-boundaries to form fine microbands, as well as the localized formation of microshear bands. The substructural characteristics observed by EBSD, in particular at the larger strain, generally appeared to compare well with those obtained using TEM. With increased strain level, the mean subgrain size became finer, the corresponding mean misorientation angle increased and both these characteristics became less dependent on a particular grain orientation. The statistically representative data obtained will assist in the development of physically based models of microstructural evolution during thermomechanical processing of austenitic stainless steels.

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An in situ laser-scanning confocal microscopy study has been undertaken into Widmanstätten ferrite formation in an Fe–C alloy, in combination with electron backscattered diffraction. It has been found for the first time that the sympathetic nucleation of Widmanstätten ferrite on grain boundary allotriomorphs can exhibit a step wise change in orientation and growth direction until the most favourable growth conditions are achieved.

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The increasing application of hydroforming for the production of automotive lightweight components is mainly due to the attainable advantages regarding part properties and improving technology of the forming equipment. However, the high pressure requirements during hydroforming decreases the costs benefit and make the part expensive. Another requirement of automotive industries is weight reduction and better crash performance. Thereby steel industries developed advanced high strength steels which have high strength, good formability and better crash performance. Even though the thickness of the sheet to form the component is reduced, the pressure requirement to form the part during expansion is still high during high pressure hydroforming. This paper details the comparison between high and low pressure tube hydroforming for the square cross-section geometry. It is determined that the internal pressure and die closing force required for low pressure tube hydroforming process is much less than that of high pressure tube hydroforming process. The stress and thickness distribution of the part during tube crushing were critically analysed. Further, the stress distribution and forming mode were studied in this paper. Also friction effect on both processes was discussed.

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This paper focuses on the development of a hybrid phenomenological/inductive model to improve the current physical setup force model on a five stand industrial hot strip finishing mill. We approached the problem from two directions. In the first approach, the starting point was the output of the current setup force model. A feedforward multilayer perceptron (MLP) model was then used to estimate the true roll separating force using some other available variables as additional inputs to the model.

It was found that it is possible to significantly improve the estimation of a roll separating force from 5.3% error on average with the current setup model to 2.5% error on average with the hybrid model. The corresponding improvements for the first coils are from 7.5% with the current model to 3.8% with the hybrid model. This was achieved by inclusion, in addition to each stand's force from the current model, the contributions from setup forces from the other stands, as well as the contributions from a limited set of additional variables such as: a) aim width; b) setup thickness; c) setup temperature; and d) measured force from the previous coil.

In the second approach, we investigated the correlation between the large errors in the current model and input parameters of the model. The data set was split into two subsets, one representing the "normal" level of error between the current model and the measured force value, while the other set contained the coils with a "large" level of error. Additional set of data with changes in each coil's inputs from the previous coil's inputs was created to investigate the dependency on the previous coil.

The data sets were then analyzed using a C4.5 decision tree. The main findings were that the level of the speed vernier variable is highly correlated with the large errors in the current setup model. Specifically, a high positive speed vernier value often correlated to a large error. Secondly, it has been found that large changes to the model flow stress values between coils are correlated frequently with larger errors in the current setup force model.