Han, F.; Diehl, M.; Roters, F.; Raabe, D.: Multi-scale modeling of plasticity. ICIAM 2019 - The 9th International Congress on Industrial and Applied Mathematics, Valencia, Spain (2019)
Liu, C.; Shanthraj, P.; Roters, F.; Raabe, D.: Phase-field/CALPHAD methods for multi-phase and multi-component microstructures. The 4th International Symposium on Phase Field Modelling in Materials Science (PF 19), Bochum, Germany (2019)
Sedighiani, K.; Diehl, M.; Roters, F.; Sietsma, J.; Raabe, D.: Obtaining constitutive parameters for a physics-based crystal plasticity model from macro-scale behavior. International Conference on Plasticity, Damage, and Fracture , Panama City, Panama (2019)
Diehl, M.; Shanthraj, P.; Eisenlohr, P.; Roters, F.; Raabe, D.: DAMASK - Düsseldorf Advanced Material Simulation Kit. Seminar of the Department of Mechanical Engineering and Applied Mechanics, University of Pennsylvania, Philadelphia, PA, USA (2018)
Diehl, M.; Shanthraj, P.; Eisenlohr, P.; Roters, F.; Raabe, D.: DAMASK - Düsseldorf Advanced Material Simulation Kit. Seminar of the Department of Mechanical Engineering, Villanova University, Villanova, PA, USA (2018)
Diehl, M.; Shanthraj, P.; Eisenlohr, P.; Roters, F.; Raabe, D.: DAMASK - The Düsseldorf Advanced Material Simulation Kit for Modeling Multi-Physics Crystal Plasticity, Thermal, and Damage Phenomena. WCCM 2018, 13th World Congress in Computational Mechanics, New York, USA (2018)
Han, F.; Diehl, M.; Roters, F.; Raabe, D.: Multi-scale modelling of sheet metal forming by coupling FEM with a CP-Spectral solver using the DAMASK modelling package. 10th European Solid Mechanics Conference (ESMC2018), Bologna, Italy (2018)
Roters, F.; Diehl, M.; Wong, S. L.; Shanthraj, P.; Raabe, D.: DAMASK: the Düsseldorf Advanced MAterial Simulation Kit for studying multi-physics crystal plasticity phenomena. 10 Years ICAMS - International Symposium, Bochum, Germany (2018)
Wong, S. L.; Laptyeva, G.; Brüggemann, T.; Karhausen, K.-F.; Roters, F.; Raabe, D.: An improved unified internal state variable model exploiting first principle calculations for flow stress modeling of aluminium alloys. International Conference on Aluminum Alloys (ICAA), Montreal, Canada (2018)
Roters, F.; Diehl, M.; Shanthraj, P.: Coupled Experimental-Numerical Analysis of Strain Partitioning in Metallic Microstructures: The Importance of a 3D Neighborhood. Schöntal Symposium on 'Dislocation based Plasticity, Schöntal, Germany (2018)
Roters, F.; Sharma, L.; Diehl, M.; Shanthraj, P.: Including Damage Modelling into Crystal Plasticity Simulations using the Düsseldorf Advanced Material Simulation Kit DAMASK. Symposium Nano and Micro Scale Damage in Metals, Utrecht, The Netherlands (2018)
Diehl, M.; Shanthraj, P.; Roters, F.; Raabe, D.: Simulation Study on Plasticity and Fracture in Aluminium Based on Real Microstructures. TMS 2018 Annual Meeting & Exhibition, Phoenix, AZ, USA (2018)
Scientists of the Max-Planck-Institut für Eisenforschung pioneer new machine learning model for corrosion-resistant alloy design. Their results are now published in the journal Science Advances
Recent developments in experimental techniques and computer simulations provided the basis to achieve many of the breakthroughs in understanding materials down to the atomic scale. While extremely powerful, these techniques produce more and more complex data, forcing all departments to develop advanced data management and analysis tools as well as…
Data-rich experiments such as scanning transmission electron microscopy (STEM) provide large amounts of multi-dimensional raw data that encodes, via correlations or hierarchical patterns, much of the underlying materials physics. With modern instrumentation, data generation tends to be faster than human analysis, and the full information content is…
The project’s goal is to synergize experimental phase transformations dynamics, observed via scanning transmission electron microscopy, with phase-field models that will enable us to learn the continuum description of complex material systems directly from experiment.
In order to prepare raw data from scanning transmission electron microscopy for analysis, pattern detection algorithms are developed that allow to identify automatically higher-order feature such as crystalline grains, lattice defects, etc. from atomically resolved measurements.