Kollmannsberger, Stefan PD. Dr.-Ing. habil. Archives - Additive Manufacturing in Construction (AMC) TRR277

Lightweight return-mapping surrogates for multiscale plasticity: a practical guide

2026 | A. Daneshyar, L. Hermann, S. Kollmannberger Computational Mechanics https://doi.org/10.1007/s00466-026-02849-9 Data | Zenodo, 2026 …

Scan-based Fatigue Prediction of DED-Arc Additively Manufactured Steel Components

2026 | M. Horstjan, M. Müggenburg, M. Christmann, S. Vogts, S. Kollmannsberger, K. Thiele, J. Unglaub: Scan-based Fatigue Prediction of DED-Arc Additively Manufactured Steel Components Additive Manufacturing, 2026, https://doi.org/10.1016/j.addma.2026.105243 Data…

Viscoplastic Modeling the Evolving Mechanical Properties of Shotcrete 3D Printing Material

2026 | Q.T. La, K.A. Meyer, S. Kollmannsberger, R. Jänicke: Viscoplastic Modeling the Evolving Mechanical Properties of Shotcrete 3D Printing Material Proceedings in Applied Mathematics and Mechanics, 2026, https://doi.org/10.1002/pamm.70094 Data…

A Plastic Damage Model With Mixed Isotropic–Kinematic Hardening for Low-Cycle Fatigue in 7020 Aluminum

2025 | A. Daneshyar, D. Siebert, C. Radlbeck, S. Kollmannsberger: A Plastic Damage Model With Mixed Isotropic–Kinematic Hardening for Low-Cycle Fatigue in 7020 Aluminum Fatigue & Fracture of Engineering Materials &…

Prof. Dr.-Ing. habil. Stefan Kollmannsberger

is Professor at Bauhaus-University Weimar and is Head of the Chair of Data Science in Civil Engineering. He was head of the work group ‘Simulation in Applied Mechanics’ at the Chair of Computational Modeling and Simulation and has a fifteen year-long scientific record in that field. In this project, he is responsible for the development of simulation methods for metal based artefacts.

Predicting fatigue life of additively manufactured lattice structures using the image-based Finite Cell Method and average strain energy density

2024 | R. De Biasi, O. Oztoprak, F. Zanini, S. Carmignato, S. Kollmannsberger, M. Benedetti: Predicting fatigue life of additively manufactured lattice structures using the image-based Finite Cell Method and…

The discontinuous strain method: accurately representing fatigue and failure

2024 | L. Herrmann, A. Daneshyar, S. Kollmannsberger: The discontinuous strain method: accurately representing fatigue and failure, Computational Mechanics, 2024, https://doi.org/10.1007/s00466-024-02526-9 Data | Zenodo,2024, https://doi.org/10.5281/zenodo.10215919.

Generative adversarial networks enable outlier detection and property monitoring for additive manufacturing of complex structures

2024 | A. Henkes, L. Herrmann, H. Wessels, S. Kollmannsberger: Generative adversarial networks enable outlier detection and property monitoring for additive manufacturing of complex structures Engineering Applications of Artificial Intelligence,…

TRR277 Person: Kollmannsberger, Stefan PD. Dr.-Ing. habil.

Lightweight return-mapping surrogates for multiscale plasticity: a practical guide

Project B 06

Project C 01

Scan-based Fatigue Prediction of DED-Arc Additively Manufactured Steel Components

Viscoplastic Modeling the Evolving Mechanical Properties of Shotcrete 3D Printing Material

A Plastic Damage Model With Mixed Isotropic–Kinematic Hardening for Low-Cycle Fatigue in 7020 Aluminum

Prof. Dr.-Ing. habil. Stefan Kollmannsberger

Predicting fatigue life of additively manufactured lattice structures using the image-based Finite Cell Method and average strain energy density

The discontinuous strain method: accurately representing fatigue and failure

Generative adversarial networks enable outlier detection and property monitoring for additive manufacturing of complex structures

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