TY - JOUR A1 - Evsevleev, Sergei A1 - Cabeza, S. A1 - Mishurova, Tatiana A1 - Garcés, G. A1 - Sevostianov, I. A1 - Requena, G. A1 - Boin, M. A1 - Hofmann, M. A1 - Bruno, Giovanni T1 - Stress-induced damage evolution in cast AlSi12CuMgNi alloy with one and two ceramic reinforcements. Part II: Effect of reinforcement orientation N2 - While there is a large body of literature on the micro-mechanical behavior of metal matrix composites (MMCs) under uniaxial applied stress, very little is available on multi-phase MMCs. In order to cast light on the reinforcement mechanisms and damage processes in such multi-phase composites, materials made by an Al-based piston alloy and containing one and two ceramic reinforcements (planar-random oriented alumina fibers and SiC particles) were studied. In-situ compression tests during neutron diffraction experiments were used to track the load transfer among phases, while X-ray computed tomography on pre-strained samples was used to monitor and quantify damage. We found that damage progresses differently in composites with different orientations of the fiber mat. Because of the presence of intermetallic network, it was observed that the second ceramic reinforcement changed the load transfer scenario only at very high applied load, when also intermetallic particles break. We rationalized the present results combining them with previous investigations and using a micromechanical model. KW - Multi-phase KW - Metal matrix composites KW - Intermetallics KW - Computed tomography KW - In-situ neutron diffraction KW - Piston alloy KW - Load transfer PY - 2020 U6 - https://doi.org/10.1007/s10853-019-04069-4 SN - 1573-4803 VL - 55 IS - 3 SP - 1049 EP - 1068 PB - Springer AN - OPUS4-49460 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Evsevleev, Sergei A1 - Mishurova, Tatiana A1 - Garces, G. A1 - Sevostianov, I. A1 - Hofmann, M. A1 - Bruno, Giovanni T1 - Micromechanical response of multi-phase Al-alloy matrix composites under uniaxial compression N2 - 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. T2 - MLZ User Meeting 2020 CY - Online meeting DA - 09.12.2020 KW - Metal matrix composite KW - Neutron diffraction KW - Damage mechanism KW - Load transfer KW - Computed tomography PY - 2020 AN - OPUS4-52032 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - JOUR A1 - Evsevleev, Sergei A1 - Paciornik, S. A1 - Bruno, Giovanni T1 - Advanced Deep Learning-Based 3D Microstructural Characterization of Multiphase Metal Matrix Composites N2 - The quantitative analysis of microstructural features is a key to understanding the micromechanical behavior of metal matrix composites (MMCs), which is a premise for their use in practice. Herein, a 3D microstructural characterization of a five-phase MMC is performed by synchrotron X-ray computed tomography (SXCT). A workflow for advanced deep learning-based segmentation of all individual phases in SXCT data is shown using a fully convolutional neural network with U-net architecture. High segmentation accuracy is achieved with a small amount of training data. This enables extracting unprecedently precise microstructural parameters (e.g., volume fractions and particle shapes) to be input, e.g., in micromechanical models. KW - Computed tomography KW - Convolutional neural networks KW - Deep learning KW - Metal matrix composites KW - Segmentations PY - 2020 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:kobv:b43-504261 SN - 1438-1656 VL - 22 IS - 4 SP - 1901197 PB - WILEY-VCH Verlag GmbH & Co. KGaA CY - Weinheim AN - OPUS4-50426 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER -