Professor
© TUD/NEFM
Professor for Computational and Experimental Solid Mechanics
NameProf. Dr.-Ing. habil. Markus Kästner
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Chair of Computational and Experimental Solid Mechanics
Visiting address:
Zeunerbau, Room 353 George-Bähr-Straße 3c
01069 Dresden
Research
Data-driven analysis of processes, materials and structures
- Microstructure characterisation and reconstruction
- Description of Process-Structure-Property (PSP) linkages
- Exploration of PSP linkages and inverse materials design
- Virtual Sensing und clustering for load and stress analysis
- Digital twins for predictive maintenance
Development of data- and model-driven modeling techniques
- Physics-constrained neural networks for material modeling
- Data-driven multi-scale modeling with automated data augmentation
- Phase-field modeling of fracture and structural evolution processes
- Modeling of coupled boundary value problems
Experimental characterization and modeling of materials
- Damage and failure of additively manufactured materials
- Process-dependent fatigue behavior of materials
- Inelastic, rate-dependent material behavior of polymers
- Damage and failure of fibre reinforced composites
- Magnetosensitive elastomers and fluids
- Parameter identification and experimental validation of material models
Selected projects
- DFG-Priority Programme SPP 2489 DaMic
- DFG-Research Training Group GRK 2868 D³
- AMTwin - Data-driven analysis of processes, materials and structures for additive manufacturing
- ePredict - Predictive maintenance for electromobility
- LRVTwin - a digital twin for light rail vehicles
- Drucksache - multiscale characterization and modeling of additively manufactured lattice structures
Publications
2023
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Overview of phase-field models for fatigue fracture in a unified framework, 4 Aug 2023, In: Engineering Fracture Mechanics. 288, 109318Electronic (full-text) versionResearch output: Contribution to journal > Research article
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A comparative study on different neural network architectures to model inelasticity, 18 Jul 2023, In: International Journal for Numerical Methods in Engineering. 124 (2023), 21, p. 4802-4840, 39 p.Electronic (full-text) versionResearch output: Contribution to journal > Research article
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Shape optimization of additively manufactured lattices based on triply periodic minimal surfaces, 5 Jul 2023, In: Additive Manufacturing. 73(2023), 9 p., 103659Electronic (full-text) versionResearch output: Contribution to journal > Research article
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Two-stage 2D-to-3D reconstruction of realistic microstructures: Implementation and numerical validation by effective properties, 1 Jul 2023, In: Computer Methods in Applied Mechanics and Engineering. 412, 116098Electronic (full-text) versionResearch output: Contribution to journal > Research article
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Conditional diffusion-based microstructure reconstruction, Jun 2023, In: Materials today communications. 35, 105608Electronic (full-text) versionResearch output: Contribution to journal > Research article
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Modeling the temperature dependent deformation behavior of fiber reinforced thermoplastics for the analysis of thermoforming processes, 30 May 2023, p. 254, 1 p.Electronic (full-text) versionResearch output: Contribution to conferences > Abstract
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Fatigue monitoring and maneuver identification for vehicle fleets using a virtual sensing approach, May 2023, In: International Journal of Fatigue. 170, 107554Electronic (full-text) versionResearch output: Contribution to journal > Research article
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AMTwin - Datengetriebene Prozess-, Werkstoff- und Strukturanalyse für die additive Fertigung, 1 Mar 2023, 8 p.Electronic (full-text) versionResearch output: Contribution to conferences > Paper
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FEANN: an efficient data-driven multiscale approach based on physics-constrained neural networks and automated data mining, 8 Feb 2023, In: Computational Mechanics : solids, fluids, engineered materials, aging infrastructure, molecular dynamics, heat transfer, manufacturing processes, optimization, fracture & integrity. 71, 5, p. 827-851, 25 p.Electronic (full-text) versionResearch output: Contribution to journal > Research article
2022
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Numerical and experimental studies on press-bolt joints for sheet metal applications - Static strength assessment, 1 Nov 2022, In: Journal of Advanced Joining Processes. 6, 6, p. 100132, 100132Electronic (full-text) versionResearch output: Contribution to journal > Research article
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