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
- ResearchGate, GoogleScholar
Teaching
- Lecture Materialtheorie in summer term
- Lecture Mehrskalige numerische Modellierung in winter term
- Tutorials for basic and advanced courses
Publications
2024
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Fast descriptor-based 2D and 3D microstructure reconstruction using the Portilla-Simoncelli algorithm , 22 Jul 2024, In: Engineering with computers. 19 p.Electronic (full-text) versionResearch output: Contribution to journal > Research article
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Viscoelasticity with physics-augmented neural networks: model formulation and training methods without prescribed internal variables , 6 May 2024, In: Computational Mechanics. 2024Electronic (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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Statistical analysis of effective crack properties by microstructure reconstruction and phase-field modeling , 2024, In: Archive of applied mechanics. 94, 9, 17 p.Electronic (full-text) versionResearch output: Contribution to journal > Research article
2023
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Neural networks meet hyperelasticity: A guide to enforcing physics , Oct 2023, In: Journal of the Mechanics and Physics of Solids. 179, 105363Electronic (full-text) versionResearch output: Contribution to journal > Research article
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On the relevance of descriptor fidelity in microstructure reconstruction , 15 Sep 2023, In: PAMM. 23, 3, e202300116Electronic (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, 21, p. 4802-4840, 39 p.Electronic (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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Phase-field modelling and analysis of rate-dependent fracture phenomena at finite deformation , Apr 2023, In: Computational mechanics. 72, 5, p. 859–883, 25 p.Electronic (full-text) versionResearch output: Contribution to journal > Research article
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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. 71, 5, p. 827-851, 25 p.Electronic (full-text) versionResearch output: Contribution to journal > Research article
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
- Cement and Concrete Composites
- Computational Mechanics
- Computer Methods in Applied Mechanics and Engineering
- Data-Centric Engineering
- 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