04 Fakultät Energie-, Verfahrens- und Biotechnik

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Author: search.filters.author.Schmauder, SiegfriedStart date: 2021

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    Assessing fatigue life cycles of material X10CrMoVNb9-1 through a combination of experimental and finite element analysis
    (2023) Rahim, Mohammad Ridzwan Bin Abd; Schmauder, Siegfried; Manurung, Yupiter H. P.; Binkele, Peter; Dusza, Ján; Csanádi, Tamás; Ahmad, Meor Iqram Meor; Mat, Muhd Faiz; Dogahe, Kiarash Jamali
    This paper uses a two-scale material modeling approach to investigate fatigue crack initiation and propagation of the material X10CrMoVNb9-1 (P91) under cyclic loading at room temperature. The Voronoi tessellation method was implemented to generate an artificial microstructure model at the microstructure level, and then, the finite element (FE) method was applied to identify different stress distributions. The stress distributions for multiple artificial microstructures was analyzed by using the physically based Tanaka-Mura model to estimate the number of cycles for crack initiation. Considering the prediction of macro-scale and long-term crack formation, the Paris law was utilized in this research. Experimental work on fatigue life with this material was performed, and good agreement was found with the results obtained in FE modeling. The number of cycles for fatigue crack propagation attains up to a maximum of 40% of the final fatigue lifetime with a typical value of 15% in many cases. This physically based two-scale technique significantly advances fatigue research, particularly in power plants, and paves the way for rapid and low-cost virtual material analysis and fatigue resistance analysis in the context of environmental fatigue applications.
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    Increasing low-temperature toughness of 09Mn2Si steel through lamellar structuring by helical rolling
    (2021) Panin, Sergey; Vlasov, Ilya; Moiseenko, Dmitry; Maksimov, Pavel; Maruschak, Pavlo; Yakovlev, Alexander; Gomorova, Julia; Mishin, Ivan; Schmauder, Siegfried
    The aim of the paper was to investigate the helical rolling parameters (a number of passes) for the microstructural modification and the low-temperature impact toughness improvement of the 09Mn2Si High Strength Low-Alloyed (HSLA) steel. In order to achieve this purpose, work spent to crack initiation and propagation was analyzed and compared with patterns of fracture surfaces. The microstructure and impact toughness values were presented in the temperature range from +20 to -70°C. Also, the fracture mechanisms in individual regions on the fracture surfaces were discussed. In addition, a methodology for computer simulation of the process was developed and implemented within the framework of the excitable cellular automata method and its integration with the kinetic theory of fracture. Finally, a theoretical analysis of the effect of grain shapes and orientations on the strain response patterns of a certain meso-volume simulating the material after the helical rolling was carried out.
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    Simulation of the fatigue crack initiation in SAE 52100 martensitic hardened bearing steel during rolling contact
    (2022) Dogahe, Kiarash Jamali; Guski, Vinzenz; Mlikota, Marijo; Schmauder, Siegfried; Holweger, Walter; Spille, Joshua; Mayer, Joachim; Schwedt, Alexander; Görlach, Bernd; Wranik, Jürgen
    An investigation on the White Etching Crack (WEC) phenomenon as a severe damage mode in bearing applications led to the observation that in a latent pre-damage state period, visible alterations appear on the surface of the raceway. A detailed inspection of the microstructure underneath the alterations reveals the existence of plenty of nano-sized pores in a depth range of 80 µm to 200 µm. The depth of the maximum Hertzian stress is calculated to be at 127 µm subsurface. The present study investigates the effect of these nanopores on the fatigue crack initiation in SAE 52100 martensitic hardened bearing steel. In this sense, two micro-models by means of the Finite Element Method (FEM) are developed for both a sample with and a sample without pores. The number of cycles required for the crack initiation for both samples is calculated, using the physical-based Tanaka-Mura model. It is shown that pores reduce the number of cycles in bearing application to come to an earlier transition from microstructural short cracks (MSC) to long crack (LC) propagation significantly.
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    Deformation behavior investigation of auxetic structure made of poly(butylene adipate-co-terephthalate) biopolymers using finite element method
    (2023) Schneider, Yanling; Guski, Vinzenz; Schmauder, Siegfried; Kadkhodapour, Javad; Hufert, Jonas; Grebhardt, Axel; Bonten, Christian
    Auxetic structures made of biodegradable polymers are favorable for industrial and daily life applications. In this work, poly(butylene adipate-co-terephthalate) (PBAT) is chosen for the study of the deformation behavior of an inverse-honeycomb auxetic structure manufactured using the fused filament fabrication. The study focus is on auxetic behavior. One characteristic of polymer deformation prediction using finite element (FE) simulation is that no sounded FE model exists, due to the significantly different behavior of polymers under loading. The deformation behavior prediction of auxetic structures made of polymers poses more challenges, due to the coupled influences of material and topology on the overall behavior. Our work presents a general process to simulate auxetic structural deformation behavior for various polymers, such as PBAT, PLA (polylactic acid), and their blends. The current report emphasizes the first one. Limited by the state of the art, there is no unified regulation for calculating the Poisson’s ratio n for auxetic structures. Here, three calculation ways of n are presented based on measured data, one of which is found to be suitable to present the auxetic structural behavior. Still, the influence of the auxetic structural topology on the calculated Poisson’s ratio value is also discussed, and a suggestion is presented. The numerically predicted force-displacement curve, Poisson’s ratio evolution, and the deformed auxetic structural status match the testing results very well. Furthermore, FE simulation results can easily illustrate the stress distribution both statistically and local-topology particularized, which is very helpful in analyzing in-depth the auxetic behavior.
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    Experimental investigations of micro-meso damage evolution for a Co/WC-type tool material with application of digital image correlation and machine learning
    (2021) Schneider, Yanling; Zielke, Reiner; Xu, Chensheng; Tayyab, Muhammad; Weber, Ulrich; Schmauder, Siegfried; Tillmann, Wolfgang
    Commercial Co/WC/diamond composites are hard metals and very useful as a kind of tool material, for which both ductile and quasi-brittle behaviors are possible. This work experimentally investigates their damage evolution dependence on microstructural features. The current study investigates a different type of Co/WC-type tool material which contains 90 vol.% Co instead of the usual <50 vol.%. The studied composites showed quasi-brittle behavior. An in-house-designed testing machine realizes the in-situ micro-computed tomography (µCT) under loading. This advanced equipment can record local damage in 3D during the loading. The digital image correlation technique delivers local displacement/strain maps in 2D and 3D based on tomographic images. As shown by nanoindentation tests, matrix regions near diamond particles do not possess higher hardness values than other regions. Since local positions with high stress are often coincident with those with high strain, diamonds, which aim to achieve composites with high hardnesses, contribute to the strength less than the WC phase. Samples that illustrated quasi-brittle behavior possess about 100-130 MPa higher tensile strengths than those with ductile behavior. Voids and their connections (forming mini/small cracks) dominant the detected damages, which means void initiation, growth, and coalescence should be the damage mechanisms. The void appears in the form of debonding. Still, it is uncovered that debonding between Co-diamonds plays a major role in provoking fatal fractures for composites with quasi-brittle behavior. An optimized microstructure should avoid diamond clusters and their local volume concentrations. To improve the time efficiency and the object-identification accuracy in µCT image segmentation, machine learning (ML), U-Net in the convolutional neural network (deep learning), is applied. This method takes only about 40 min. to segment more than 700 images, i.e., a great improvement of the time efficiency compared to the manual work and the accuracy maintained. The results mentioned above demonstrate knowledge about the strengthening and damage mechanisms for Co/WC/diamond composites with >50 vol.% Co. The material properties for such tool materials (>50 vol.% Co) is rarely published until now. Efforts made in the ML part contribute to the realization of autonomous processing procedures in big-data-driven science applied in materials science.
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    Numerical investigations on the damage behaviour of a reconstructed anode for solid oxide fuel cell application
    (2021) Steier, Katharina; Guski, Vinzenz; Schmauder, Siegfried
    This paper addresses the damage behaviour of a nickel/yttria-stabilised zirconia (Ni-YSZ) anode, in order to understand microstructural degradation processes of Solid Oxide Fuel Cells (SOFCs) during long-term operation. Numerical investigations are carried out to analyse the failure mechanisms in detail. For this purpose, finite element (FE) models are generated from focused ion beam-scanning electron microscopy 3D image data, representing the anode microstructure with varying phase compositions. A brittle model and a ductile material model were assigned to the YSZ phase and the nickel phase, respectively. The porosity is found to affect the strength of the microstructure significantly, leading to low compressive strength results. A high Ni content generally increases the toughness of the overall structure. However, the orientation and the geometry of the nickel phase is essential. When the Ni phase is aligned parallel to the loading direction, a supporting effect on the microstructure is observed, resulting in a significant high toughness. On the contrary, a rapid failure of the sample occurs when the Ni phase is oriented perpendicular to the loading direction. Two main failure mechanisms are identified: (i) cracking at the Ni/YSZ interface and (ii) cracking of struts at the location of the smallest diameter.
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    A numerical method to improve the representativeness of real microstructure cut-outs applied in finite element simulations
    (2021) Schneider, Yanling; Wasserbäch, Werner; Schmauder, Siegfried; Zhou, Zhangjian; Zielke, Reiner; Tillmann, Wolfgang
    To improve the representativeness of a real microstructural cut-out for modeling purposes, a numerical method named as “boundary pixel color alteration (BPCA)” is presented to modify measured 2D microstructure cut-outs. Its physical background is related to the phase growth. For the application, the precondition is that the representativeness of the microstructure is already satisfied to a certain extent. This method resolves the problem that the phase composition of a small cut-out can have a large discrepancy to the real one. The main idea is to change the pixel color among neighboring pixels belonging to different phases. Our process simultaneously maintains most of the characteristics of the original morphology and is applicable for nearly all kinds of multi-phase or polycrystalline metallic alloys, as well. From our axisymmetric finite element (FE) simulations (ABAQUS ) applied with 2D real microstructures, it shows that the volume ratios of microstructural phases, as a function of the structure position to the symmetric axis, converge to phase area ratios in the 2D cut-out, even though the axisymmetric element volume is position dependent. A mathematical proof provides the reason for the aforementioned convergence. As examples to achieve real compositions and to numerically prove the aforementioned convergence, four different materials including multiphase polycrystals are implemented. An improvement of the predicted FE result is presented for the application of a modified microstructure (with a higher representativeness) compared to the original one.
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    Thermal fracture of functionally graded coatings with systems of cracks : application of a model based on the rule of mixtures
    (2023) Petrova, Vera; Schmauder, Siegfried; Georgiadis, Alexandros
    This paper is devoted to the problem of the thermal fracture of a functionally graded coating (FGC) on a homogeneous substrate (H), i.e., FGC/H structures. The FGC/H structure was subjected to thermo-mechanical loadings. Systems of interacting cracks were located in the FGC. Typical cracks in such structures include edge cracks, internal cracks, and edge/internal cracks. The material properties and fracture toughness of the FGC were modeled by formulas based on the rule of mixtures. The FGC comprised two constituents, a ceramic on the top and a metal as a homogeneous substrate, with their volume fractions determined by a power law function with the power coefficient λ as the gradation parameter for the FGC. For this study, the method of singular integral equations was used, and the integral equations were solved numerically by the mechanical quadrature method based on the Chebyshev polynomials. Attention was mainly paid to the determination of critical loads and energy release rates for the systems of interacting cracks in the FGCs in order to find ways to increase the fracture resistance of FGC/H structures. As an illustrative example, a system of three edge cracks in the FGC was considered. The crack shielding effect was demonstrated for this system of cracks. Additionally, it was shown that the gradation parameter λ had a great effect on the fracture characteristics. Thus, the proposed model provided a sound basis for the optimization of FGCs in order to improve the fracture resistance of FGC/H structures.
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    Many-scale investigations of the deformation behavior of polycrystalline composites: I - machine learning applied for image segmentation
    (2022) Schneider, Yanling; Prabhu, Vighnesh; Höss, Kai; Wasserbäch, Werner; Zhou, Zhangjian; Schmauder, Siegfried
    Our work investigates the polycrystalline composite deformation behavior through multiscale simulations with experimental data at hand. Since deformation mechanisms on the micro-level link the ones on the macro-level and the nanoscale, it is preferable to perform micromechanical finite element simulations based on real microstructures. The image segmentation is a necessary step for the meshing. Our 2D EBSD images contain at least a few hundred grains. Machine learning (ML) was adopted to automatically identify subregions, i.e., individual grains, to improve local feature extraction efficiency and accuracy. Denoising in preprocessing and postprocessing before and after ML, respectively, is beneficial in high quality feature identification. The ML algorithms used were self-developed with the usage of inherent code packages (Python). The performances of the three supervised ML models - decision tree, random forest, and support vector machine - are compared herein; the latter two achieved accuracies of up to 99.8%. Calculations took about 0.5 h from the original input dataset (EBSD image) to the final output (segmented image) running on a personal computer (CPU: 3.6 GHz). For a realizable manual pixel sortation, the original image was firstly scaled from the initial resolution 1080x1080 pixels down to 300x300. After ML, some manual work was necessary due to the remaining noises to achieve the final image status ready for meshing. The ML process, including this manual work time, improved efficiency by a factor of about 24 compared to a purely manual process. Simultaneously, ML minimized the geometrical deviation between the identified and original features, since it used the original resolution. For serial work, the time efficiency would be enhanced multiplicatively.
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    Many-scale investigations of deformation behavior of polycrystalline composites: II - micro-macro simultaneous FE and discrete dislocation dynamics simulation
    (2022) Schneider, Yanling; Rapp, Dennis-Michael; Yang, Yifang; Wasserbäch, Werner; Schmauder, Siegfried
    The current work numerically investigates commercial polycrystalline Ag/17vol.%SnO2 composite tensile deformation behavior with available experimental data. Such composites are useful for electric contacts and have a highly textured initial material status after hot extrusion. Experimentally, the initial sharp fiber texture and the number of Sigma3-twins were reduced due to tensile loading. The local inhomogeneous distribution of hardness and Young’s modulus gradually decreased from nanoindentation tests, approaching global homogeneity. Many-scale simulations, including micro-macro simultaneous finite element (FE) and discrete dislocation dynamics (DDD) simulations, were performed. Deformation mechanisms on the microscale are fundamental since they link those on the macro- and nanoscale. This work emphasizes micromechanical deformation behavior. Such FE calculations applied with crystal plasticity can predict local feature evolutions in detail, such as texture, morphology, and stress flow in individual grains. To avoid the negative influence of boundary conditions (BCs) on the result accuracy, BCs are given on the macrostructure, i.e., the microstructure is free of BCs. The particular type of 3D simulation, axisymmetry, is preferred, in which a 2D real microstructural cutout with 513 Ag grains is applied. From FE results, Sigma3-twins strongly rotated to the loading direction (twins disappear), which, possibly, caused other grains to rotate away from the loading direction. The DDD simulation treats the dislocations as discrete lines and can predict the resolved shear stress (RSS) inside one grain with dependence on various features as dislocation density and lattice orientation. The RSS can act as the link between the FE and DDD predictions.