Gierden, C.; Kochmann, J.; Waimann, J.; Svendsen, B.; Reese, S.: A Review of FE-FFT-Based Two-Scale Methods for Computational Modeling of Microstructure Evolution and Macroscopic Material Behavior. Archives of Computational Methods in Engineering (2022)
Gierden, C.; Waimann, J.; Svendsen, B.; Reese, S.: A geometrically adapted reduced set of frequencies for a FFT-based microstructure simulation. Computer Methods in Applied Mechanics and Engineering 386, 114131 (2021)
Gierden, C.; Waimann, J.; Svendsen, B.; Reese, S.: FFT-based simulation using a reduced set of frequencies adapted to the underlying microstructure. Computer Methods in Materials Science 21 (1), pp. 51 - 58 (2021)
Shanthraj, P.; Liu, C.; Akbarian, A.; Svendsen, B.; Raabe, D.: Multi-component chemo-mechanics based on transport relations for the chemical potential. Computer Methods in Applied Mechanics and Engineering 365, 113029 (2020)
Mianroodi, J. R.; Svendsen, B.: Effect of Twin Boundary Motion and Dislocation-Twin Interaction on Mechanical Behavior in Fcc Metals. Materials 13 (10), 2238 (2020)
Alipour, A.; Reese, S.; Svendsen, B.; Wulfinghoff, S.: A grain boundary model considering the grain misorientation within a geometrically nonlinear gradient-extended crystal viscoplasticity theory. Proceedings of the Royal Society A: Mathematical, Physical and Engineering Sciences 476 (2235), 20190581 (2020)
Svendsen, B.: Constitutive relations for polar continua based on statistical mechanics and spatial averaging. Proceedings of the Royal Society A: Mathematical, Physical and Engineering Sciences 476 (2233), 20190407 (2020)
Po, G.; Admal, N. C.; Svendsen, B.: Non-local Thermoelasticity Based on Equilibrium Statistical Thermodynamics. Journal of Elasticity 139, pp. 37 - 59 (2020)
International researcher team presents a novel microstructure design strategy for lean medium-manganese steels with optimized properties in the journal Science
This project is a joint project of the De Magnete group and the Atom Probe Tomography group, and was initiated by MPIE’s participation in the CRC TR 270 HOMMAGE. We also benefit from additional collaborations with the “Machine-learning based data extraction from APT” project and the Defect Chemistry and Spectroscopy group.