TY - CONF A1 - Gesell, Stephan T1 - Numerical calculation of ΔCTOD for thermomechanical fatigue crack growth N2 - The cyclic crack tip opening displacement ΔCTOD is a promising loading Parameter to quantify the crack propagation under thermomechanical fatigue (TMF). In this work, suitable techniques are investigated and compared for an accurate calculation of ΔCTOD under TMF loading using a viscoplastic temperature dependent material model. It turned out that collapsed special crack tip elements give the best results. An efficient FEM-technique is developed to simulate the incremental crack growth by successive remeshing, whereby the deformations and internal state variables are mapped from the old mesh onto the new one. The developed techniques are demonstrated and discussed for two-dimensional examples like TMF-specimens. Recommendations are made regarding important numerical control parameters like optimal size of crack tip elements, length of crack growth increment in relation to plastic zone size and ΔCTOD value. T2 - ESIS Technical Meeting on Numerical Methods (TC8) CY - Online meeting DA - 06.04.2021 KW - Crack tip opening displacement KW - Thermomechanical fatigue KW - Crack growth PY - 2021 AN - OPUS4-52410 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Ganesh, Rahul A1 - Gesell, Stephan A1 - Kuna, M. A1 - Fedelich, Bernard A1 - Kiefer, B. T1 - Numerical calculation of ΔCTOD for thermomechanical fatigue crack growth N2 - The cyclic crack tip opening displacement ΔCTOD is a promising loading Parameter to quantify the crack propagation under thermomechanical fatigue (TMF). In this work, suitable techniques are investigated and compared for an accurate calculation of ΔCTOD under TMF loading using a viscoplastic temperature dependent material model. It turned out that collapsed special crack tip elements give the best results. An efficient FEM-technique is developed to simulate the incremental crack growth by successive remeshing, whereby the deformations and internal state variables are mapped from the old mesh onto the new one. The developed techniques are demonstrated and discussed for two-dimensional examples like TMF-specimens. Recommendations are made regarding important numerical control parameters like optimal size of crack tip elements, length of crack growth increment in relation to plastic zone size and ΔCTOD value. N2 - Zur Bewertung des Rissfortschritts unter thermomechanischer Ermüdung (TMF) ist die zyklische Rissöffnungsverschiebung ΔCTOD ein aussichtsreicher bruchmechanischer Beanspruchungsparameter. In dieser Arbeit werden unter Anwendung eines viskoplastischen, temperaturabhängigen Materialmodells geeignete FEM-Techniken für die akkurate Berechnung des ΔCTOD bei TMF erprobt und verglichen. Als beste Technik hat sich die Verwendung kollabierter Rissspitzenelemente erwiesen. Es wurde ein effizienter FEM-Algorithmus zur Simulation der Rissausbreitung mit inkrementeller Neuvernetzung entwickelt, bei dem die Verformungen und inelastischen Zustandsvariablen jeweils vom alten auf das neue Netz übertragen werden. Die erarbeiteten Techniken werden am Beispiel von zweidimensionalen Strukturen und TMF-Proben vorgestellt und diskutiert. Dabei werden wesentliche Kontrollparameter der Simulation wie optimale Grösse der Rissspitzenelemente, Länge des Rissinkrementes in Relation zur plastischen Zone und dem ΔCTOD-Wert empfohlen. T2 - 53. Tagung des Arbeitskreises "Bruchmechanik und Bauteilsicherheit" CY - Online meeting DA - 18.02.2021 KW - Crack tip opening displacement KW - Thermomechanical fatigue KW - Crack growth PY - 2021 SP - 1 EP - 10 PB - DVM (Deutscher Verband für Materialforschung und -prüfung) CY - Berlin AN - OPUS4-52519 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Ganesh, R. A1 - Gesell, Stephan A1 - Fedelich, Bernard A1 - Kuna, Meinhard A1 - Kiefer, B. T1 - Procrackplast: Eine Software zur Simulation des 3D-Risswachstums unter großen plastischen Deformationen T1 - Procrackplast: A software for simulating 3D crack growth under large plastic deformation N2 - The finite element software ProCrackPlast is developed for the automated simulation of fatigue crack growth in arbitrarily loaded three-dimensional components with large scale plastic deformations, in particular under cyclic thermomechanical (TMF) loading. ProCrackPlast is developed by extending the software Procrack, created at TU Freiberg for linear-elastic crack growth simulations. The pre-processing, FEM analysis, and the post-processing in ProCrackPlast are done by the commercial software ABAQUS. ProCrackPlast resorts to a crack growth procedure which adaptively updates the crack in finite increments based on the fracture-mechanical parameter, cyclic crack tip opening displacement ΔCTOD . Features of this software along with two application examples of fatigue crack growth in a typical cast steel, Ni-Resist, are presented in this paper to show its capability and performance. N2 - Es wird die Finite-Element-Software ProCrackPlast vorgestellt, die eine automatische Simulation der Ermüdungsrissausbreitung in beliebig belasteten dreidimensionalen Bauteilen mit größeren plastisch verformten Bereichen ermöglicht, insbesondere bei thermomechanischer Wechselbelastung (TMF). ProCrackPlast entstand durch Erweiterung des Programs ProCrack, das an der TU Freiberg für linear-elastische inkrementelle Rissfortschrittsanalysen entwickelt wurde. Das Pre-Processing, die FEM Analyse und das Post-Processing werden mit Hilfe der kommerziellen FE-Software ABAQUS durchgeführt. ProCrackPlast beruht auf einem Algorithmus, mit dem der Rissfortschritt adaptiv in endlichen Inkrementen unter Verwendung des bruchmechanischen Parameters der zyklischen Rissöffnungsverschiebung ΔCTOD gesteuert wird. Die Funktionseigenschaften dieser Software werden anhand von zwei Anwendungsbeispielen zum Ermüdungsrisswachstum für einen typischen Stahlguss, Ni-Resist, exemplarisch dargestellt, um die Möglichkeiten und Leistungsfähigkeit von ProCrackPlast zu demonstrieren. T2 - 54. Tagung des Arbeitskreises "Bruchmechanik und Bauteilsicherheit" CY - Online meeting DA - 22.02.2021 KW - Automated finite element analysis KW - Automatische Finite Element Simulation KW - Thermomechanical fatigue KW - Crack growth KW - Thermomechanische Ermüdung KW - Rissausbreitung PY - 2022 SP - 205 EP - 214 PB - Deutscher Verband für Materialforschung und -prüfung e.V. AN - OPUS4-54435 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Ferrari, Bruno T1 - Microstructural evolution of PBF-LB/M Inconel 718 during solution-aging heat treatments - an in-situ x-ray diffraction study N2 - Inconel 718 (IN718) is a traditional age-hardenable nickel-based alloy that has been increasingly processed by additive manufacturing (AM) in recent years. In the as-solidified condition, IN718 exhibits chemical segregation and the undesired Laves phase, requiring a solution annealing (SA) prior to aging. The material produced by AM does not respond to the established thermal routines in the same way as conventionally produced IN718, and there is still no consensus on which routine yields optimal results. This work aims to provide a fundamental understanding of the heat treatment (HT) response by continuously monitoring the microstructural evolution during SA via time-resolved synchrotron x-ray diffraction, complemented by ex-situ scanning electron microscopy (SEM). The samples were produced by laser powder bed fusion to a geometry of 10x20x90 mm³, from which Ø1x5 mm³ cylindric specimens were extracted. Two different scanning strategies – incremental 67° rotations, Rot, and alternating 0°/67° tracks, Alt – were used, leading to two different as-built conditions. 1-hour SAs were carried out in the beamline ID22 of the ESRF at 50 KeV. Two SA temperatures, SA1 = 1020 °C, and SA2 = 1080 °C were tested for each scanning strategy. Data were processed using the software PDIndexer. In the as-built state, all samples showed typical subgrain columnar cell structures with predominant Nb/Mo segregation and Laves phase at the cell walls, as seen by SEM. The Alt scan induced higher intensity on the Laves peaks than the Rot scan, suggesting a greater content of Laves. Chemical homogenization in the SA was largely achieved during the heating ramp (Fig. 1). SA2 eliminated the Laves peaks just before reaching 1080 °C, and mitigated differences between Rot and Alt samples. On the other hand, SA1 induced the precipitation of the generally detrimental δ phase, also observed by SEM. Furthermore, the Rot scan showed higher δ peak intensities than the Alt scan, indicating a higher content of δ in the latter. No signs of recrystallization were observed in any of the investigated SAs. T2 - FEMS EUROMAT 2023 CY - Frankfurt a. M., Germany DA - 03.09.2023 KW - Additive Manufacturing KW - X-Ray Diffraction KW - Inconel 718 KW - Heat Treatments KW - Microstructure PY - 2023 AN - OPUS4-58392 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - JOUR A1 - Ruffini, A. A1 - Le Bouar, Y. A1 - Finel, A. A1 - Epishin, A. I. A1 - Fedelich, Bernard A1 - Feldmann, Titus A1 - Viguier, B. A1 - Poquillon, D. T1 - Dislocations interacting with a pore in an elastically anisotropic single crystal nickel-base superalloy during hot isostatic pressing N2 - The formation of pores in CMSX-4 nickel based superalloys is detrimental to the service life of the material. A way to avoid the problem is to treat the superalloys under Hot Isostatic Pressing (HIP), which enables a large volume fraction of pores to be annihilated. This paper aims to understand the contribution of plastic activity related to the gliding of dislocations on the pore annihilation. Simulations based on a phase-field model of dislocation are performed and make it possible to consider the strong anisotropy of the CMSX-4 under HIP conditions in conjunction to the strong elastic heterogeneity introduced by the pore. For pores with a radius of few micrometers, it is shown that edge parts of dislocation lines that present an extra half atomic plane oriented towards the pore are stacked above and under it in the direction which is perpendicular to their slip-planes, causing an increase of the number of dislocation along the four octahedral directions of the FCC single crystal which intersect the pore center. Results are streamlined within the isotropic elastic theory of dislocations. Effects of elastic anisotropy and dislocation reactions are also investigated in order to specify what would be the dislocation configuration around a pore in CMSX-4 under HIP conditions. Notably, the elastic anisotropy is shown to significantly modify the arrangement of dislocations close to the pore equator. Simulations also allow for the characterization of pore/dislocation interactions when dislocations are involved in Low Angle Boundaries as experimentally observed. KW - HIP KW - Superalloys KW - Dislocation KW - Pore KW - Phase-field PY - 2022 DO - https://doi.org/10.1016/j.commatsci.2021.111118 SN - 0927-0256 VL - 204 SP - 1 EP - 14 PB - Elsevier CY - Amsterdam AN - OPUS4-54220 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - JOUR A1 - Darvishi Kamachali, Reza T1 - Melting upon Coalescence of Solid Nanoparticles N2 - The large surface-to-volume ratio of nanoparticles is understood to be the source of many interesting phenomena. The melting temperature of nanoparticles is shown to dramatically reduce compared to bulk material. Yet, at temperatures below this reduced melting point, a liquid-like atomic arrangement on the surface of nanoparticles is still anticipated to influence its properties. To understand such surface effects, here, we study the coalescence of Au nanoparticles of various sizes using molecular dynamics simulations. Analysis of the potential energy and Lindemann index distribution across the nanoparticles reveals that high-energy, high-mobility surface atoms can enable the coalescence of nanoparticles at temperatures much lower than their corresponding melting point. The smaller the nanoparticles, the larger the difference between their melting and coalescence temperatures. For small enough particles and/or elevated enough temperatures, we found that the coalescence leads to a melting transition of the two nominally solid nanoparticles, here discussed in relation to the heat released due to the surface reduction upon the coalescence and the size dependence of latent heat. Such discontinuous melting transitions can lead to abrupt changes in the properties of nanoparticles, important for their applications at intermediate temperatures. KW - Nanoparticles KW - Molecular Dynamics KW - Surface-induced Melting PY - 2022 UR - https://nbn-resolving.org/urn:nbn:de:kobv:b43-552183 DO - https://doi.org/10.3390/solids3020025 VL - 3 IS - 2 SP - 361 EP - 373 PB - MDPI AN - OPUS4-55218 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - JOUR A1 - Elfetni, Seif A1 - Darvishi Kamachali, Reza T1 - PINNs-MPF: A Physics-Informed Neural Network framework for Multi-Phase-Field simulation of interface dynamics N2 - We present PINNs-MPF framework, an application of Physics-Informed Neural Networks (PINNs) to handle Multi-Phase-Field (MPF) simulations of microstructure evolution. A combination of optimization techniques within PINNs and in direct relation to MPF method are extended and adapted. The numerical resolution is realized through a multi-variable time-series problem by using fully discrete resolution. Within each interval, space, time, and phases/grains are treated separately, constituting discrete subdomains. PINNs-MPF is equipped with an extended multi-networking (parallelization) concept to subdivide the simulation domain into multiple batches, with each batch associated with an independent NN trained to predict the solution. To ensure continuity across the spatio-temporal-phasic subdomains, a Master NN efficiently is to handle interactions among the multiple networks and facilitates the transfer of learning. A pyramidal training approach is proposed to the PINN community as a dual-impact method: to facilitate the initialization of training when dealing with multiple networks, and to unify the solution through an extended transfer of learning. Furthermore, a comprehensive approach is adopted to specifically focus the attention on the interfacial regions through a dynamic meshing process, significantly simplifying the tuning of hyper-parameters, serving as a key concept for addressing MPF problems using machine learning. We perform a set of systematic simulations that benchmark foundational aspects of MPF simulations, i.e., the curvature-driven dynamics of a diffuse interface, in the presence and absence of an external driving force, and the evolution and equilibrium of a triple junction. The proposed PINNs-MPF framework successfully reproduces benchmark tests with high fidelity and Mean Squared Error (MSE) loss values ranging from 10^−6 to 10^−4 compared to ground truth solutions. KW - Machine learning KW - PINNs KW - Phase-field method KW - Microstructure evolution KW - Parallel training KW - Neural networks PY - 2025 UR - https://nbn-resolving.org/urn:nbn:de:kobv:b43-629740 DO - https://doi.org/10.1016/j.enganabound.2025.106200 SN - 0955-7997 VL - 176 SP - 1 EP - 22 PB - Elsevier CY - Amsterdam AN - OPUS4-62974 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - JOUR A1 - Elfetni, Seifallah A1 - Darvishi Kamachali, Reza T1 - PINNs-MPF: An Efficient Physics-Informed Machine Learning-based Solver for Multi-Phase-Field Simulations using Tensorflow N2 - This paper introduces PINNs-MPF, a novel Machine Learning-based solver designed for Multi-Phase-Field (MPF) and diffuse interface simulations, offering innovative approaches to address complex challenges in addressing microstructure evolution in polycrystalline materials using Machine Learning. The framework not only surpasses current limitations in handling multi-phase problems but also allows for potential upscaling to tackle more intricate scenarios. Developed in Python, the related code leverages optimized libraries like TensorFlow, showcasing efficiency and potential scalability in materials science and engineering simulations. This framework, integrating advanced techniques such as multi-networking and training optimization, setting a new standard in predictive capabilities and understanding complex physical phenomena. KW - Machine Learning KW - Microstructure Simulation KW - Phase Field PY - 2025 UR - https://nbn-resolving.org/urn:nbn:de:kobv:b43-631917 DO - https://doi.org/10.1016/j.simpa.2025.100753 SN - 2665-9638 VL - 24 SP - 1 EP - 4 PB - Elsevier B.V. AN - OPUS4-63191 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - JOUR A1 - Zhou, X. A1 - Wei, Y. A1 - Kühbach, M. A1 - Zhao, H. A1 - Vogel, F. A1 - Darvishi Kamachali, Reza A1 - Thompson, G. B. A1 - Raabe, D. A1 - Gault, B. T1 - Revealing in-plane grain boundary composition features through machine learning from atom probe tomography data N2 - Grain boundaries (GBs) are planar lattice defects that govern the properties of many types of polycrystalline materials. Hence, their structures have been investigated in great detail. However, much less is known about their chemical features, owing to the experimental difficulties to probe these features at the atomic length scale inside bulk material specimens. Atom probe tomography (APT) is a tool capable of accomplishing this task, with an ability to quantify chemical characteristics at near-atomic scale. Using APT data sets, we present here a machine-learning-based approach for the automated quantification of chemical features of GBs. We trained a convolutional neural network (CNN) using twenty thousand synthesized images of grain interiors, GBs, or triple junctions. Such a trained CNN automatically detects the locations of GBs from APT data. Those GBs are then subjected to compositional mapping and analysis, including revealing their in-plane chemical decoration patterns. We applied this approach to experimentally obtained APT data sets pertaining to three case studies, namely, Ni-P, Pt-Au, and Al-Zn-Mg-Cu alloys. In the first case, we extracted GB specific segregation features as a function of misorientation and coincidence site lattice character. Secondly, we revealed interfacial excesses and in-plane chemical features that could not have been found by standard compositional analyses. Lastly, we tracked the temporal evolution of chemical decoration from early-stage solute GB segregation in the dilute limit to interfacial phase separation, characterized by the evolution of complex composition patterns. This machine-learning-based approach provides quantitative, unbiased, and automated access to GB chemical analyses, serving as an enabling tool for new discoveries related to interface thermodynamics, kinetics, and the associated chemistry-structure-property relations. KW - Machine learning KW - Digitalization KW - Alloy microstructure PY - 2022 UR - https://nbn-resolving.org/urn:nbn:de:kobv:b43-543049 DO - https://doi.org/10.1016/j.actamat.2022.117633 SN - 1359-6454 VL - 226 SP - 1 EP - 15 PB - Elsevier CY - Amsterdam AN - OPUS4-54304 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Darvishi Kamachali, Reza T1 - On the origin of embrittlement in Mn containing and Zn-coated steels N2 - Grain boundary embrittlement in medium-Mn steels and liquid metal embrittlement (LME) in Zn-coated high strength steels are among key challenges on the way of safe application of sustainable steels for automotive industry. Using a novel density-based model for grain boundaries, we reveal that the affinity of a grain boundary to attract Mn and Zn atoms result in a segregation transition accompanied by interfacial structural changes. In case of the Zn, the simulations show that the amount of segregation abruptly increases with decreasing temperature, while the Zn content in the alloy, required for triggering the segregation transition, decreases. The results are discussed in the context of CALPHAD-integrated density-based grain boundary phase diagrams. T2 - DPG 2024 CY - Berlin, Germany DA - 17.03.2024 KW - Phase-Field Simulation KW - CALPHAD KW - Steels KW - Density-based Thermodynamics PY - 2024 AN - OPUS4-60743 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER -