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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.
In this paper we report on the characterization by X-ray computed tomography of calcium phosphate (CaP) and polycaprolactone (PCL) coatings on Ti-6Al-4V alloy scaffolds used as a material for medical implants. The cylindrical scaffold has greater porosity of the inner part than the external part, thus, mimicking trabecular and cortical bone, respectively. The prismatic scaffolds have uniform porosity. Surface of the scaffolds was modified with calcium phosphate (CaP) and polycaprolactone (PCL) by dip-coating to improve biocompatibility and mechanical properties. Computed tomography performed with X-ray and synchrotron radiation revealed the defects of structure and morphology of CaP and PCL coatings showing small platelet-like and spider-web-like structures, respectively.
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.
Near eutectic cast Al–Si alloys are the basis of all Al-alloys used for pistons due to their high fluidity and relatively high strength-to-weight ratio. Their microstructure is characterized by the presence of eutectic-Si embedded in an age hardenable -Al matrix. During solution heat treatment, the eutectic Si network undergoes a process of gradual disintegration, reducing the load bearing capability and the strength of the alloy. The improvement of the high temperature strength is achieved by addition of transition elements such as Cu, Mg or Ni through the formation of stiff intermetallic (IM) phases.
In present study a near-eutectic AlSi12CuMgNi alloy produced by squeeze casting was investigated in as-cast condition. The in-situ neutron diffraction compression tests revealed the stress partitioning mechanism between phases of the alloy. Large stresses were found in IMs, showing their significant role as a reinforcement elements. After the failure of IM and Si phases the load is transferred back to the Al matrix, inducing further plastic deformation in it, yet without creating microcracking. The neutron diffraction experiments were coupled with assessment of internal damage after ex-situ compression tests by synchrotron radiation computed tomography. The quantitative analysis of CT data revealed that local tensile stresses in IM and Si phases induce microcracks with preferential orientation, parallel to the axis of applied load.
Altogether, present experimental data was used as an input for the developed micromechanical model based on Maxwell homogenization scheme. In contrast to the neutron diffraction experiment, which can only determine stress differences between the axial and radial sample directions, the model allows predicting the principal stresses in each phase of the alloy.
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.