Dr.-Ing. Karl Kalina

2025

• Inverse design of anisotropic microstructures using physics-augmented neural networksJadoon, A. A., Kalina, K. A., Rausch, M. K., Jones, R. & Fuhg, J. N., 30 May 2025, In: Journal of the Mechanics and Physics of SolidsElectronic (full-text) versionResearch output: Contribution to journal > Research article
• Neural networks meet phase-field: A hybrid fracture modelDammaß, F., Kalina, K. A. & Kästner, M., May 2025, In: Computer Methods in Applied Mechanics and Engineering. 440, 117937Electronic (full-text) versionResearch output: Contribution to journal > Research article
• Inverse design of spinodoid structures using Bayesian optimizationRaßloff, A., Seibert, P., Kalina, K. A. & Kästner, M., 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
• Fast descriptor-based 2D and 3D microstructure reconstruction using the Portilla-Simoncelli algorithmSeibert, P., Rassloff, A., Kalina, K. & Kästner, M., Feb 2025, In: Engineering with computers. 41, 1, p. 589-607, 19 p., 113043Electronic (full-text) versionResearch output: Contribution to journal > Research article
• Neural networks meet anisotropic hyperelasticity: A framework based on generalized structure tensors and isotropic tensor functionsKalina, K. A., Brummund, J., Sun, W. & Kästner, M., 21 Jan 2025, In: Computer Methods in Applied Mechanics and Engineering. 437, 117725Electronic (full-text) versionResearch output: Contribution to journal > Research article

2024

• Utilizing physics‐augmented neural networks to predict the material behavior according to Yeoh's lawMaurer, L., Eisenträger, S., Kalina, K. & Juhre, D., 12 Nov 2024, In: Proceedings in Applied Mathematics and Mechanics: PAMM. 24, 4, e202400213Electronic (full-text) versionResearch output: Contribution to journal > Research article
• Viscoelasticty with physics-augmented neural networks: model formulation and training methods without prescribed internal variablesRosenkranz, M., Kalina, K. A., Brummund, J., Sun, W. & Kästner, M., 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
• Statistical analysis of effective crack properties by microstructure reconstruction and phase-field modelingSeibert, P., Hirsch, F., Kluge, M., Kalina, M., Kalina, K. & Kästner, M., 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
• Neural network-based multiscale modeling of finite strain magneto-elasticity with relaxed convexity criteriaKalina, K. A., Gebhart, P., Brummund, J., Linden, L., Sun, W. & Kästner, M., Mar 2024, In: Computer Methods in Applied Mechanics and Engineering. 421, 116739Electronic (full-text) versionResearch output: Contribution to journal > Research article
• Reconstructing Microstructures From Statistical Descriptors Using Neural Cellular AutomataSeibert, P., Raßloff, A., Zhang, Y., Kalina, K., Reck, P., Peterseim, D. & Kästner, M., 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