Dr.-Ing. Karl Kalina

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
2025
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Neural networks meet phase-field: A hybrid fracture model , May 2025, In: Computer Methods in Applied Mechanics and Engineering. 440, 117937Electronic (full-text) versionResearch output: Contribution to journal > Research article
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Inverse design of spinodoid structures using Bayesian optimization , 19 Feb 2025, In: Computational mechanics : solids, fluids, engineered materials, aging infrastructure, molecular dynamics, heat transfer, manufacturing processes, optimization, fracture & integrity. 104726Electronic (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, 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
2024
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Utilizing physics‐augmented neural networks to predict the material behavior according to Yeoh's law , 12 Nov 2024, In: Proceedings in Applied Mathematics and Mechanics: PAMM. 24, 4, e202400213Electronic (full-text) versionResearch output: Contribution to journal > Research article
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Viscoelasticty with physics-augmented neural networks: model formulation and training methods without prescribed internal variables , 6 May 2024, In: Computational Mechanics : solids, fluids, engineered materials, aging infrastructure, molecular dynamics, heat transfer, manufacturing processes, optimization, fracture & integrity. 74, 6, p. 1279-1301, 23 p.Electronic (full-text) versionResearch output: Contribution to journal > Research article
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Statistical analysis of effective crack properties by microstructure reconstruction and phase-field modeling , 25 Apr 2024, In: Archive of applied mechanics. 94 (2024), 9, p. 2471-2487, 17 p.Electronic (full-text) versionResearch output: Contribution to journal > Research article
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Neural network-based multiscale modeling of finite strain magneto-elasticity with relaxed convexity criteria , Mar 2024, In: Computer Methods in Applied Mechanics and Engineering. 421, 116739Electronic (full-text) versionResearch output: Contribution to journal > Research article
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Reconstructing Microstructures From Statistical Descriptors Using Neural Cellular Automata , 18 Jan 2024, In: Integrating materials and manufacturing innovation. 13, 1, p. 272-287, 16 p.Electronic (full-text) versionResearch output: Contribution to journal > Research article
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Fast reconstruction of microstructures with ellipsoidal inclusions using analytical descriptors , Jan 2024, In: Computer aided design : CAD. 166, 103635Electronic (full-text) versionResearch output: Contribution to journal > Research article
Conference Talks
2024
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Physics-augmented neural networks for the constitutive modeling of viscoelastic materials Rosenkranz, M. (Speaker), Kalina, K. A. (Involved person), Brummund, J. (Involved person), Sun, W. (Involved person), Kästner, M. (Involved person) 7 Feb 2024 Activity: Talk or presentation at external institutions/events > Talk/Presentation > Contributed
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Multiscale Modeling with Physics-Augmented Neural Networks Kalina, K. A. (Speaker), Brummund, J. (Involved person), Gebhart, P. (Involved person), Linden, L. (Involved person), Sun, W. (Involved person), Kästner, M. (Involved person) 6 Feb 2024 → 7 Feb 2024 Activity: Talk or presentation at external institutions/events > Talk/Presentation > Contributed
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Inverse design of spinodoids from sparse data through Bayesian optimization Raßloff, A. (Speaker), Seibert, P. (Involved person), Kalina, K. A. (Involved person), Kästner, M. (Involved person) 6 Feb 2024 Activity: Talk or presentation at external institutions/events > Talk/Presentation > Contributed
2023
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Viscoelasticty with physics-augmented neural networks: Model formulation and training methods without prescribed internal variables Rosenkranz, M. (Speaker), Kalina, K. A. (Involved person), Brummund, J. (Involved person), Kästner, M. (Involved person) 19 Dec 2023 Activity: Talk or presentation at external institutions/events > Talk/Presentation > Contributed
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Data-driven modeling of viscoelastic materials using physics-augmented neural networks Rosenkranz, M. (Speaker), Kalina, K. A. (Involved person), Brummund, J. (Involved person), Kästner, M. (Involved person) 22 Aug 2023 Activity: Talk or presentation at external institutions/events > Talk/Presentation > Contributed
Awards
- 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
- 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
- Journal of the Mechanics and Physics of Solids
- Mechanics of Materials
- Mechanics of Time-Dependent Materials
- Technische Mechanik