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Paper des Monats
- ja (1)
We propose a novel iterative segmentation algorithm (i.S.Sy.Da.T.A: Iterative Segmentation Synthetic Data Training Algorithm) employing Deep Convolutional Neural Networks and synthetic training data for X-ray tomographic reconstructions of complex microstructures. In our method, we reinforce the synthetic training data with experimental XCT datasets that were automatically segmented in the previous iteration. This strategy produces better segmentations in successive iterations. We test our algorithm with experimental XCT re constructions of a 6-phase Al-Si Matrix Composite reinforced with ceramic fibers and particles. We perform the analysis in 3D with a special network architecture that demonstrates good generalization with synthetic training data. We show that our iterative algorithm returns better segmentations compared to the standard single training approach. More specifically, phases possessing similar attenuation coefficients can be better segmented: for Al2O3 fibers, SiC particles, and Intermetallics, we see an increase of the Dice score with respect to the classic approach: from 0.49 to 0.54, from 0.66 to 0.72, and from 0.55 to 0.66 respectively. Furthermore, the overall Dice score increases from 0.77 to 0.79. The methods presented in this work are also applicable to other materials and imaging techniques.
The creep strengthening mechanisms in (age-hardenable) aluminum alloys are analyzed on the basis of a new microstructural study of powder samples, an analysis of a comprehensive revision of creep data from the literature, and a new modeling approach. A strategy based on the strength difference (SD) method to separate the contributions of solid solution atoms and precipitates to creep strengthening is proposed. The new methodology considers the combination of the two contributions avoiding the need of a threshold stress term in the creep equation. The contribution of both precipitates and solid solution is taken into account by means of the analysis of the lattice parameter variation with aging time. For this study, powders of two commercial AA2xxx alloys have been analyzed using diffraction methods. The experimental results are modeled using Lubarda’s approach combined with the SD method.
The creep strengthening mechanisms in (age-hardenable) aluminum alloys are analyzed on the basis of a new microstructural study of powder samples, an analysis of a comprehensive revision of creep data from the literature, and a new modeling approach. A strategy based on the strength difference (SD) method to separate the contributions of solid solution atoms and precipitates to creep strengthening is proposed. The new methodology considers the combination of the two contributions avoiding the need of a threshold stress term in the creep equation. The contribution of both precipitates and solid solution is taken into account by means of the analysis of the lattice parameter variation with aging time. For this study, powders of two commercial AA2xxx alloys have been analyzed using diffraction methods. The experimental results are modeled using Lubarda's approach combined with the SD method.
The printability of artificial defects inside the additively manufactured laser powder bed fusion (LPBF) 316L stainless steel is investigated. The printing parameters of the LPBF process are optimized to produce artificial defects with reproducible sizes at desired positions while minimizing redundant porosity. The smallest obtained artificial defect is 90 μm in diameter. The accuracy of the geometry of the printed defect depends on both the height and the diameter in the input model. The effect of artificial defects on the very-high-cycle fatigue (VHCF) behavior of LPBF 316L stainless steel is also studied. The specimens printed with artificial defects in the center are tested under VHCF using an ultrasonic machine. Crack initiation is accompanied by the formation of a fine granular area (FGA), typical of VHCF. Despite the presence of relatively large artificial defects, FGA formation is observed around accidental natural printing defects closer to the surface, which can still be considered as internal. The causes for this occurrence are discussed.
Average phase stress concentrations in multiphase metal matrix composites under compressive loading
(2016)
We develop a model to predict average over individual phases stress concentrations in a multiphase metal matrix composite under compressive loading. The model accounts for matrix plasticity through variation of the shear modulus with applied stress and for frac- ture of filler through change in the shape of the particles. Three micromechanical models are compared –non interaction approximation, Mori–Tanaka–Benveniste (MTB) scheme, and Maxwell scheme. Comparison with the experimental measurements of Cabeza et al. (2016) shows that Maxwell scheme generally predicts the stress concentration with satis- factory accuracy. Results of MTB scheme vary depending on the loading case and ignoring of the interaction leads to substantial overestimation of the stresses.
Combination of high-resolution time-of-flight (TOF) Neutron diffraction, scanning electron microscopy (SEM) and small angle neutron scattering (SANS) have been used to study hardening precipitation in 2014Al and 2124Al alloys. Neutron diffraction experiment revealed presence of tetragonal CuAl2 Phase (θ/θ´ precipitates) in 2014Al alloy and orthorhombic CuMgAl2 Phase (S-precipitates) in 2124Al alloy. SEM image analysis revealed that the θ/θ´-precipitates have platelet morphology while the S-precipitates exhibit rod-like shapes. From SANS data analysis the characteristic dimensions of precipitate particles and their polydisperse distributions were estimated.
Porosity in additively manufactured materials, such as laser powder bed fusion Ti-Al6-V4, can play an important role in their mechanical performance. Not only the total porosity but also the shape/morphology of the individual pores need to be considered. Therefore, it is necessary to determine the distributions of different defect types (especially fusing defects and keyhole pores) and their dependence on process parameters. We show that synchrotron X-ray refraction radiography allows analysis of large samples (up to several millimeters) without compromising the detectability of submicrometer defects. Correspondingly, a classification tool is introduced that is able to quantitatively distinguish defects such as keyhole pores and binding defects with a confidence level of 94 %, even when the shape cannot be discerned because of limited spatial resolution.
The paper presents the results of a series of combined mechanical and in-situ morphological investigations on highstrength strain-hardening cement-based Composites (SHCC). Tension and compression experiments were performed in a CT scanner employing a dedicated mechanical testing rig. The in-situ microtomographic scans enabled correlating the measured specimen response with relevant microstructural features and fracture processes. The microstructural segmentation of SHCC was performed in the framework of Deep Learning and it targeted an accurate segmentation of pores, fibers and aggregates. Besides their accurate volumetric representation, these phases were quantified in terms of content, size and orientation. The fracture processes were monitored at different loading stages and Digital Volume Correlation (DVC) was employed to spatially map the strains and cracks in the specimens loaded in compression. The DVC analysis highlighted the effect of loading conditions, specimen geometry and material heterogeneity at the mesolevel on the strain distribution and fracture localization.
Laser based powder bed fusion additive manufacturing offers the flexibility to incorporate standard and userdefined scan strategies in a layer or in between the layers for the customized fabrication of metallic components. In the present study, four different scan strategies and their impact on the development of microstructure, texture, and residual stresses in laser powder bed fusion additive manufacturing of a nickel-based superalloy Inconel 718 was investigated. Light microscopy, scanning electron microscopy combined with electron backscatter diffraction, and neutron diffraction were used as the characterization tools. Strong textures with epitaxially grown columnar grains were observed along the build direction for the two individual scan strategies. Patterns depicting the respective scan strategies were visible in the build plane, which dictated the microstructure development in the other planes. An alternating strategy combining the individual strategies in the successive layers and a 67◦ rotational strategy weakened the texture by forming finer microstructural features. Von Mises equivalent stress plots revealed lower stress values and gradients, which translates as lower distortions for the alternating and rotational strategies. Overall results confirmed the scope for manipulating the microstructure, texture, and residual stresses during laser powder bed fusion additive manufacturing by effectively controlling the scan strategies.