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Eingeladener Vortrag
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The quality of components made by laser beam melting (LBM) additive manufacturing is naturally influenced by the quality of the powder bed. A packing density <1 and porosity inside the powder particles lead to intrinsic voids in the powder bed. Since the packing density is determined by the particle size and shape distribution, the determination of these properties is of significant interest to assess the printing process. In this work, the size and shape distribution, the amount of the particle’s intrinsic porosity, as well as the packing density of micrometric powder used for LBM, have been investigated by means of synchrotron X-ray computed tomography (CT). Two different powder batches were investigated: Ti–6Al–4V produced by plasma atomization and stainless steel 316L produced by gas atomization. Plasma atomization particles were observed to be more spherical in terms of the mean anisotropy compared to particles produced by gas atomization. The two kinds of particles were comparable in size according to the equivalent diameter. The packing density was lower (i.e., the powder bed contained more voids in between particles) for the Ti–6Al–4V particles. The comparison of the tomographic results with laser diffraction, as another particle size measurement technique, proved to be in agreement.
The 3D microstructure of an Al alloy matrix composite with two ceramic reinforcements was investigated by synchrotron X-ray tomography. A deep learning algorithm was used for the segmentation of four different phases. We show that convolutional networks with the U-Net architecture are able to solve complex segmentation tasks with small amount of training data.
Damage Analysis in Metal Matrix Composites by means of Synchrotron Radiation Computed Tomography
(2017)
The damage evolution after compression tests of two types of MMC, consisting of eutectic AlSi12CuMgNi alloy and reinforced with 15vol% of Al2O3 fibers and with 7vol% of Al2O3 fibers+15vol% of SiC particles was studied by synchrotron CT. Internal damage at different pre-strain conditions in eutectic Si, intermetallic phases and Al2O3 fibers was observed, as well as debonding of SiC particles.
We present two examples of the potential of synchrotron X-ray refraction techniques. First, we focus on the 3D imaging of hydrogen assisted cracks in an EN AW – 6060 aluminium alloy which are otherwise undetected by absorption-based CT. The second work is a quantitative analysis of the damage evolution in an Al/Al2O3 Metal Matrix Composite during interrupted in-situ tensile load.
The availability of high-performance Al alloys in AM is limited due to difficulties in printability, requiring both the development of synergetic material and AM process to mitigate problems such as solidification cracking during laser powder bed fusion (LPBF). The goal of this work was to investigate the failure mechanism in a LPBF 7017 Aluminium alloy + 3 wt% Zr + 0.5 wt% TiC. The processing leads to different categories of Zr-rich inclusions, precipitates and defects.
Aluminum alloys are extensively used in the automotive industry. Particularly, squeeze casting production of Al-Si alloys is employed in the conception of metal matrix composites (MMC) for combustion engines. Such materials are of a high interest since they allow combining improved mechanical properties and reduced weight and hence improve efficiency. We investigate two types of MMCs, which can be potentially used for production of combustion engine pistons: 1) a near-eutectic cast AlSi12CuMgNi alloy reinforced with 15%vol. Al2O3 random planar oriented short fibers and 2) the same alloy reinforced with 7%vol. Al2O3 random planar oriented short fibers + 15%vol. SiC particles.
Complex 3D microstructure of the samples in as-cast condition, consisting of four and five phases (Al matrix, eutectic Si, intermetallics, Al2O3 fibers and SiC particles) was investigated by synchrotron computed tomography (CT). Advanced methods based on machine learning were applied for segmentation of all phases. This allowed extracting quantitative information such as volume fraction, shape and interconnectivity of every phase.
In-situ compression tests during neutron diffraction experiments were used to track the load transfer among phases, while CT on pre-strained samples to monitor and quantify damage. A micromechanical model was developed to simulate the evolution of the internal stress of each phase during uniaxial compression. We showed that in composites with the Al2O3 fiber mat plane perpendicular to the load axis the Al-alloy matrix presents a large hydrostatic stress component, i.e. undergoes compression also in the direction transverse to the external load. This feature holds with and without the addition of SiC ceramic reinforcement and is absent in the case when the Al2O3 fiber mat plane is parallel to the load axis. We show, that the intermetallics play a decisive role at very high loads, when all other reinforcement phases suffer (extensive) damage. The addition of SiC particles does alleviate the load on the Al2O3 fibers, on the eutectic Si, and on the intermetallic phases in both cases of parallel and orthogonal (to the load axis) Al2O3 fiber orientation. Apart from the beneficial addition of ceramic reinforcement, the presence of intermetallic phase and eutectic silicon, forming an interconnected network even at high loads, when single particles break, confers peculiar properties to these multi-phase composites.
The micromechanical behavior of an annealed Ti-6Al-4V material produced by Laser Powder Bed Fusion was characterized by means of in-situ synchrotron X-ray diffraction during a tensile test. The lattice strain evolution was obtained parallel and transversal to the loading direction. The elastic constants were determined and compared with the conventionally manufactured alloy. In the plastic regime, a lower plastic anisotropy exhibited by the lattice planes was observed along the load axis (parallel to the building direction) than in the transverse direction.
Also, the load transfer from α to β phase was observed, increasing global ductility of the material. The material seems to accumulate a significant amount of intergranular strain in the transverse direction.
Micromechanical response of multi-phase Al-alloy matrix composites under uniaxial compression
(2020)
Aluminum alloys are extensively used in the automotive industry. Particularly, squeeze casting production of Al-Si alloys is employed in the conception of metal matrix composites (MMC) for combustion engines. Such materials are of a high interest since they allow combining improved mechanical properties and reduced weight and hence improve efficiency. Being a multiphase material, most MMCs show complex micromechanical behavior under different load conditions. In this work we investigated the micromechanical behavior of two MMCs, both consisting of a near-eutectic cast AlSi12CuMgNi alloy, one reinforced with 15%vol. Al2O3 short fibers and the other with 7%vol. Al2O3 short fibers + 15%vol. SiC particles. Both MMCs have complex 3D microstructure consisting of four and five phases: Al-alloy matrix, eutectic Si, intermetallics, Al2O3 fibers and SiC particles.
The in-situ neutron diffraction compression experiments were carried out on the Stress-Spec beamline and disclosed the evolution of internal phase-specific stresses in both composites. In combination with the damage mechanism revealed by synchrotron X-ray computed tomography (SXCT) on plastically pre-strained samples, this allowed understanding the role of every composite’s phase in the stress partitioning mechanism. Finally, based on the Maxwell scheme, a micromechanical model was utilized. The model perfectly rationalizes the experimental data and predicts the evolution of principal stresses in each phase.
Regardless of the experimental care practiced in acquiring X-ray computed tomography (XCT) data, artifacts might still exist, such as noise and blur. This is typical for fast XCT data acquisitions (e.g., in-situ investigations), or low-dose XCT. Such artifacts can complicate subsequent analysis of the data. Digital filters can moderately cure extensive artifacts. The selection of filter type, intensity, and order of application is not always straight forward. To tackle these problems, a complete sequential multilevel, multi-scale framework: BAM SynthCOND, employing newly designed deep convolutional neural networks (DCNNs), was formulated. Although data conditioning with neural networks is not uncommon, the main complication is that completely artifact-free XCT data for training do not exist. Thus, training data were acquired from an in-house developed library (BAM SynthMAT) capable of generating synthetic XCT material microstructures. Some novel DCNN architectures were introduced (2D/3D ACEnet_Denoise, 2D/3D ACEnet_Deblur) along with the concept of Assertive Contrast Enhancement (ACE) training, which boosts the performance of neural networks trained with continuous loss functions. The proposed methodology accomplished very good generalization from low resemblance synthetic training data. Indeed, denoising, sharpening (deblurring), and even ring artifact removal performance were achieved on experimental post-CT scans of challenging multiphase Al-Si Metal Matrix Composite (MMC) microstructures. The conditioning efficiencies were: 92% for combined denoising/sharpening, 99% for standalone denoising, and 95% for standalone sharpening. The results proved to be independent of the artifact intensity. We believe that the novel concepts and methodology developed in this work can be directly applied on the CT projections prior to reconstruction, or easily be extended to other imaging techniques such as: Microscopy, Neutron Tomography, Ultrasonics, etc.
The most substantial innovations in radiographic imaging techniques of the last two decades aim at enhanced image contrast of weakly absorbing micro and nano structures by taking advantage of X-ray refraction effects occurring at outer and inner surfaces. The applications range from fibre reinforced plastics to biological tissues. These techniques comprise, among others, X-ray refraction topography, diffraction enhanced imaging, phase contrast imaging, Talbot-Lau grating interferometry, and refraction enhanced imaging. They all make use of selective beam deflections up to a few minutes of arc: the X-ray refraction effect. In contrast to diffraction, this type of interaction has a 100 % scattering cross section, as shown experimentally. Since X-ray refraction is very sensitive to the orientation of interfaces, it is additionally a tool to detect, e.g., fibre or pore orientation. If the detector resolution exceeds the size of (small) individual features, one detects the integral information (of inner surfaces) within the gauge volume. We describe the above-mentioned techniques, and show their experimental implementation in the lab and at a synchrotron source. We also show strategies for data processing and quantitative analysis.