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Institute: search.filters.UBSInstitut.Graduate School of Excellence for Advanced Manufacturing Engineering (GSaME)Publication Type: search.filters.UBSTyp.Zeitschriftenartikel

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Now showing 1 - 10 of 22
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    Estimation of the depth limit for percussion drilling with picosecond laser pulses
    (2018) Förster, Daniel J.; Weber, Rudolf; Holder, Daniel; Graf, Thomas
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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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    Process limits for percussion drilling of stainless steel with ultrashort laser pulses at high average powers
    (2022) Brinkmeier, David; Holder, Daniel; Loescher, André; Röcker, Christoph; Förster, Daniel J.; Onuseit, Volkher; Weber, Rudolf; Abdou Ahmed, Marwan; Graf, Thomas
    The availability of commercial ultrafast lasers reaching into the kW power level offers promising potential for high-volume manufacturing applications. Exploiting the available average power is challenging due to process limits imposed by particle shielding, ambient atmosphere breakdown, and heat accumulation effects. We experimentally confirm the validity of a simple thermal model, which can be used for the estimation of a critical heat accumulation threshold for percussion drilling of AISI 304 steel. The limits are summarized in a processing map, which provides selection criteria for process parameters and suitable lasers. The results emphasize the need for process parallelization.
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    Simulation model for digital twins of pneumatic vacuum ejectors
    (2022) Stegmaier, Valentin; Schaaf, Walter; Jazdi, Nasser; Weyrich, Michael
    Increasing productivity, as well as flexibility, is required for the industrial production sector. To meet these challenges, concepts in the field of “Industry 4.0” are arising, such as the concept of Digital Twins. Vacuum handling systems are a widespread technology for material handling in industry and face the same challenges and opportunities. In this field, a key issue is the lack of Digital Twins containing behavior models for vacuum handling systems and their components in different applications and use cases. A novel concept for modeling and simulating the fluidic behavior of pneumatic vacuum ejectors as key components of vacuum handling systems is proposed. In order to increase the simulation accuracy, the concept can access instance‐specific data of the used asset instead of object‐specific data. The model and the data are part of the Digital Twins of pneumatic vacuum ejectors, which shall be able to be combined with other components to represent a Digital Twin of entire vacuum handling systems. The proposed model is validated in an experimental test setup and in an industrial application delivering sufficiently accurate results.
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    Tuning the hardness of produced parts by adjusting the cooling rate during laser-based powder bed fusion of AlSi10Mg by adapting the process parameters
    (2022) Leis, Artur; Traunecker, David; Weber, Rudolf; Graf, Thomas
    The mechanical properties of parts produced by laser-based powder bed fusion (LPBF) are mainly determined by the grain structure in the material, which is governed by the cooling rate during solidification. This cooling rate strongly depends on the scan velocity and the absorbed laser power. Experiments with varying process parameters were performed to develop and validate an analytical model that predicts the hardness of printed AlSi10Mg parts. It was found that it is possible to tune the hardness of additively manufactured parts of AlSi10Mg in a range between 60 ± 9 HV0.5 and 100 ± 10 HV0.5 by adjusting the cooling rate during solidification with adapted process parameters.
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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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    Analytical model for the depth progress of percussion drilling with ultrashort laser pulses
    (2021) Holder, Daniel; Weber, Rudolf; Graf, Thomas; Onuseit, Volkher; Brinkmeier, David; Förster, Daniel J.; Feuer, Anne
    A simplified analytical model is presented that predicts the depth progress during and the final hole depth obtained by laser percussion drilling in metals with ultrashort laser pulses. The model is based on the assumption that drilled microholes exhibit a conical shape and that the absorbed fluence linearly increases with the depth of the hole. The depth progress is calculated recursively based on the depth changes induced by the successive pulses. The experimental validation confirms the model and its assumptions for percussion drilling in stainless steel with picosecond pulses and different pulse energies.
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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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    Inversely 3D-printed β-TCP scaffolds for bone replacement
    (2019) Seidenstücker, Michael; Lange, Svenja; Esslinger, Steffen; Latorre, Sergio H.; Krastev, Rumen; Gadow, Rainer; Mayr, Hermann O.; Bernstein, Anke