Dr.-Ing. Karl Kalina
© TUD/NEFM
Dr.-Ing. Karl Kalina
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Chair of Computational and Experimental Solid Mechanics
Visiting address:
Zeunerbau, Room 356 George-Bähr-Straße 3c
01069 Dresden
Research
- Data-driven simulation techniques
- Usage of neural networks in solid mechanics
- Modeling and simulation of magnetoactive materials
- Nonlinear FEM, homogenisation methods
- Coupled Problems, constitutive modeling, parameter identification
- Charectirization and reconstruction of microstructures
- Postdoc in RTG 2868 D3 Graduiertenkolleg 2868
- ResearchGate, GoogleScholar
Teaching
- Lecture Materialtheorie in summer term
- Lecture Mehrskalige numerische Modellierung in winter term
- Tutorials for basic and advanced courses
Publications
2026
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A physics-augmented neural network framework for finite strain incompressible viscoelasticity, 15 Jun 2026, In: Computer Methods in Applied Mechanics and Engineering. 455, 32 p., 118892Electronic (full-text) versionResearch output: Contribution to journal > Research article
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Precise, efficient and flexible modeling of crystallizing elastomers based on physics-augmented neural networks, 15 Jun 2026, In: Computer Methods in Applied Mechanics and Engineering. 455, 118852Electronic (full-text) versionResearch output: Contribution to journal > Research article
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Inverse design of spinodoid structures using Bayesian optimization, Jan 2026, In: Computational mechanics : solids, fluids, engineered materials, aging infrastructure, molecular dynamics, heat transfer, manufacturing processes, optimization, fracture & integrity. 77, 1, p. 275-296, 22 p.Electronic (full-text) versionResearch output: Contribution to journal > Research article
2025
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A dual-stage constitutive modeling framework based on finite strain data-driven identification and physics-augmented neural networks, 1 Dec 2025, In: Computer Methods in Applied Mechanics and Engineering. 447, 118289Electronic (full-text) versionResearch output: Contribution to journal > Research article
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Data-Driven Inverse Design of Spinodoid Architected Materials, Nov 2025, In: GAMM-Mitteilungen. 48, 4, 23 p., e70008Electronic (full-text) versionResearch output: Contribution to journal > Research article
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When invariants matter: The role of I1 and I2 in neural network models of incompressible hyperelasticity, Nov 2025, In: Mechanics of Materials. 210, 105443Electronic (full-text) versionResearch output: Contribution to journal > Research article
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Inverse design of anisotropic microstructures using physics-augmented neural networks, Oct 2025, In: Journal of the Mechanics and Physics of Solids. 203, 106161Electronic (full-text) versionResearch output: Contribution to journal > Research article
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Neural networks meet phase-field: A hybrid fracture model, 30 Mar 2025, In: Computer Methods in Applied Mechanics and Engineering. 440 (2025), 27 p., 117937Electronic (full-text) versionResearch output: Contribution to journal > Research article
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Fast descriptor-based 2D and 3D microstructure reconstruction using the Portilla-Simoncelli algorithm, Feb 2025, In: Engineering with computers. 41 (2025), 1, p. 589-607, 19 p., 113043Electronic (full-text) versionResearch output: Contribution to journal > Research article
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Neural networks meet anisotropic hyperelasticity: A framework based on generalized structure tensors and isotropic tensor functions, 21 Jan 2025, In: Computer Methods in Applied Mechanics and Engineering. 437, 117725Electronic (full-text) versionResearch output: Contribution to journal > Research article
Conference Talks
2026
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Data-driven Inverse Design and Surrogate Modeling of Spinodoid Architected Materials Otto, A. (Speaker), Fritzen, F. (Involved person), Keshav, S. (Involved person), Kalina, K. A. (Involved person), Kästner, M. (Involved person) 16 Mar 2026 → 20 Mar 2026 Activity: Talk or presentation at external institutions/events > Talk/Presentation > Contributed
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Material Modeling with Neural Networks: Concepts for Enforcing Physics by Construction Kalina, K. A. (Speaker) 16 Mar 2026 → 20 Mar 2026 Activity: Talk or presentation at external institutions/events > Keynote > Invited
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A precise, efficient and flexible neural network model for strain-crystallizing rubber Friedrichs, K. (Speaker), Dammaß, F. G. (Involved person), Kalina, K. A. (Involved person), Kästner, M. (Involved person) 18 Mar 2026 Activity: Talk or presentation at external institutions/events > Talk/Presentation > Contributed
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A data-driven multiscale scheme for anisotropic finite strain magneto-elasticity Roth, H. T. (Speaker), Gebhart, P. (Involved person), Kalina, K. A. (Involved person), Wallmersperger, T. (Involved person), Kästner, M. (Involved person) 17 Mar 2026 Activity: Talk or presentation at external institutions/events > Talk/Presentation > Contributed
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A data-driven decoupled multiscale scheme for anisotropic finite strain magneto-elasticity Roth, H. T. (Speaker), Gebhart, P. (Involved person), Kalina, K. A. (Involved person), Wallmersperger, T. (Involved person), Kästner, M. (Involved person) 10 Mar 2026 Activity: Talk or presentation at external institutions/events > Talk/Presentation > Contributed
Awards
- Richard-von-Mises Awardee in appreciation for excellent scientific achievements in Applied Mathematics and Mechanics 2026
- DAAD research scholarship for young scientists with doctorates (04/23 – 09/23)
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TU Dresden Postdoc starter kit (01/23 – 09/24)
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Dr.-Klaus-Körper Awardee in appreciation for an excellent dissertation in Applied Mathematics and Mechanics 2022
Activity as a reviewer for scientific project proposals
Activity as a reviewer for scientific journals
- Acta Mechanica
- Archive of Applied Mechanics
- Cement and Concrete Composites
- Computational Mechanics
- Computer Methods in Applied Mechanics and Engineering
- Data-Centric Engineering
- European Journal of Mechanics - A/Solids
- Examples and Counterexamples
- International Journal for Numerical Methods in Engineering
- International Journal of Material Forming
- International Journal of Solids and Structures
- Journal of the Mechanics and Physics of Solids
- Mechanics of Materials
- Mechanics of Time-Dependent Materials
- Technische Mechanik