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Electron Backscatter Diffraction (EBSD) is a widely used approach for characterising the microstructure of various materials. However, it is difficult to accurately distinguish similar (body centred cubic and body centred tetragonal, with small tetragonality) phases in steels using standard EBSD software. One method to tackle the problem of phase distinction is to measure the tetragonality of the phases, which can be done using simulated patterns and cross‐correlation techniques to detect distortion away from a perfectly cubic crystal lattice. However, small errors in the determination of microscope geometry (the so‐called pattern or projection centre) can cause significant errors in tetragonality measurement and lead to erroneous results. This paper utilises a new approach for accurate pattern centre determination via a strain minimisation routine across a large number of grains in dual phase steels. Tetragonality maps are then produced and used to identify phase and estimate local carbon content. The technique is implemented using both kinetically simulated and dynamically simulated patterns to determine their relative accuracy. Tetragonality maps, and subsequent phase maps, based on dynamically simulated patterns in a point‐by‐point and grain average comparison are found to consistently produce more precise and accurate results, with close to 90% accuracy for grain phase identification, when compared with an image‐quality identification method. The error in tetragonality measurements appears to be of the order of 1%, thus producing a commensurate ∼0.2% error in carbon content estimation. Such an error makes the technique unsuitable for estimation of total carbon content of most commercial steels, which often have carbon levels below 0.1%. However, even in the DP steel for this study (0.1 wt.% carbon) it can be used to map carbon in regions with higher accumulation (such as in martensite with nonhomogeneous carbon content).

Electron Backscatter Diffraction (EBSD) is a widely used approach for characterising the microstructure of various materials. However, it is difficult to accurately distinguish similar (BCC and BCT) phases in steels using standard EBSD software due to the small difference in crystal structure. One method to tackle the problem of phase distinction is to measure the tetragonality, or apparent ‘strain’ in the crystal lattice, of the phases. This can be done by comparing experimental EBSD patterns with simulated patterns via cross‐correlation techniques, to detect distortion away from a perfectly cubic crystal lattice. However, small errors in the determination of microscope geometry (the so‐called pattern or projection centre) can cause significant errors in tetragonality measurement and lead to erroneous results. This paper utilises a new approach for accurate pattern centre determination via a strain minimisation routine across a large number of grains in dual phase steels. Tetragonality maps are then produced and used to identify phase and estimate local carbon content. The technique is implemented using both simple kinetically simulated and more complex dynamically simulated patterns to determine their relative accuracy. Tetragonality maps, and subsequent phase maps, based on dynamically simulated patterns in a point‐by‐point and grain average comparison are found to consistently produce more precise and accurate results, with close to 90% accuracy for grain phase identification, when compared with an image‐quality identification method. The error in tetragonality measurements appears to be of the order of 1%, thus producing a commensurate error in carbon content estimation. Such an error makes an estimate of total carbon content particularly unsuitable for low carbon steels; although maps of local carbon content may still be revealing.

Application of the method developed in this paper will lead to better understanding of the complex microstructures of steels, and the potential to design microstructures that deliver higher strength and ductility for common applications, such as vehicle components.

 

Modeling springback in sheet materials is challenging in aluminum alloys, especially when a complex strain path is applied. This paper presents results from pure bending experiments on AA 6016-T4 sheet material, where various plastic pre-strains were first applied prior to bending. A crystal plasticity based elasto-plastic selfconsistent (EPSC) model that includes the effect of backstress in the hardening law was used to predict final part shape after unloading. The backstress term in the model was calibrated using geometrically necessary dislocation (GND) content, measured experimentally by high resolution electron backscattered diffraction (HREBSD). The EPSC model predicted springforward angles for unstrained 1 mm AA 6016-T4 sheet with an error of 0.4% (0.3◦) in the worst case, while the J2 plasticity isotropic model overpredicted springforward angles by as much as 2.4% (2◦). For cases where uniaxial, plane-strain, and biaxial pre-strains were first imparted to the sheets before bending, the EPSC model with backstress accurately predicted the transition from springforward to springback, while the EPSC model without backstress did not. Backstress influence on model accuracy, which increased with greater pre-strain levels, appears to be correlated to the statistically stored dislocation (SSD) density computed by the model at the end of each pre-strain step. 

The current work studies the correlations between microstructure and retained austenite (RA) transformation, in a single-quenched and partitioned (Q&P) 1180 steel microstructure, through in situ tensile tests combined with electron backscatter diffraction (EBSD) analysis. This allows the study of RA stability across a limited range of morphological characteristics to be studied in the absence of confounding factors introduced by varying the entire steel microstructure. Among the microstructural attributes of interest, RA grain aspect ratio is found to have the largest influence on transformation rate, where globular-shaped grains transform more slowly than those with a more lenticular shape. Furthermore, by tracking individual grains during deformation, it is apparent that larger grains transformed more slowly than smaller grains; a purely statistical study of grain size vs strain might conclude that smaller grains are more stable, but in reality, the smaller grains transform faster and are simply statistically replaced by partially transformed larger grains. These conclusions are in contrast to relationships that might be inferred from previous studies where the entire steel microstructure was varied, along with the morphology of the RA. 

Automotive stampings undergo complex strain paths during drawing, stretching, and bending operations which develop large plastic strain gradients within the material. Aluminum sheet alloys are increasingly used for vehicle structure lightweighting, but limited formability and high levels of springback present challenges to the manufacturing and assembly processes. The current work explores the springback levels in AA6016-T4 sheet after pure bending operations. Finite element modeling is performed using both isotropic and elasto-plastic self-consistent (EPSC) crystal plasticity approaches. The EPSC model incorporates backstresses informed by GND content, as measured via high-resolution EBSD. Its predictions are shown to be more accurate than those of the isotropic model. The benefits and limitations of the current EPSC model are discussed. 

Continuous bending under tension (CBT) is known to achieve elongation-to-failure well above that achieved under a conventional uniaxial simple tension (ST) strain path. However, the detailed mechanism for supplying this increased ductility has not been fully understood. It is clear that the necking that occurs in a typical ST specimen is avoided by constantly moving the region of plastic deformation during the CBT process. The volume of material in which the flow stress is greatest is limited to a moving line where the rollers contact the sheet and superimpose bending stress on the applied tensile load. Hence the condition of a large volume of material experiencing stress greater than the material flow stress, leading to strain localization during ST, is avoided. However, the magnitude of the contribution of this phenomenon to the overall increase in elongation is unclear. In the current set of experiments, an elongation to fracture (ETF) of 4.56x and 3.7x higher than ST was achieved by fine-tuning CBT forming parameters for Q&P 1180 and TBF 1180, respectively. A comparison of maximum local strains near the final point of fracture in ST and CBT sheets via digital image correlation revealed that avoidance of localization of plastic strain during CBT accounts for less than half of the increased elongation in the CBT specimens for two steels containing different amounts of retained austenite (RA). Geometrically necessary dislocation evolution is monitored using high-resolution EBSD (HREBSD) for both strain paths, indicating a lower hardening rate in the CBT samples in the bulk of the sheet, potentially relating to the cyclical nature of the stress in the outer layers of the sheet. Interestingly, the GND evolution in the center of the sheet, which does not experience the same amplitude of cyclic stress, follows the ST behavior more closely than the sheet edges. This appears to contribute to a precipitous drop in residual ductility for the specimens that are pulled in ST after partial CBT processing. The rate of transformation of RA is also tracked in the steels, with a significantly lower rate of transformation during CBT, compared to ST. This suggests that a slower transformation rate achieved under CBT also contributed to higher strain-to-failure levels.