Publications

Philipp Rodegast, Steffen Maier, Jonas Kneifl, und Jörg Fehr. On using machine learning algorithms for motorcycle collision detection. Discover Applied Sciences, (6)6:326, 2024. [PUMA: PN7-6(II) PN7-6 EXC2075] URL

Jonas Kneifl, David Rosin, Okan Avci, Oliver Röhrle, und Jörg Fehr. Low-dimensional data-based surrogate model of a continuum-mechanical musculoskeletal system based on non-intrusive model order reduction. Archive of Applied Mechanics, (93)9:3637--3663, 2023. [PUMA: PN7-6(II) PN7 PN7-6] URL

Jonas Kneifl, Jörg Fehr, Steven L. Brunton, und J. Nathan Kutz. Multi-hierarchical surrogate learning for explicit structural dynamical systems using graph convolutional neural networks. Computational Mechanics, 05.10.2024. [PUMA: curated PN7-6(II) PN7 PN7-6 EXC2075] URL

J. Kneifl, J. Hay, und J. Fehr. Real-time Human Response Prediction Using a Non-intrusive Data-driven Model Reduction Scheme. IFAC-PapersOnLine, (55)20:283--288, Elsevier BV, 2022. [PUMA: EXC2075 PN7 PN7-6 curated] URL

Fabian Kempter, Christian Kleinbach, Martin Staudenmeyer, und Jörg Christoph Fehr. An Active Female Human Body Model for Simulation of Rear-End Impact Scenarios. 91st Annual Meeting of the International Association of Applied Mathematics and Mechanics (GAMM), 20, 1:e202000068, Wiley, 2021. [PUMA: EXC2075 PN4 PN7 PN7-6 curated]

Jonas Kneifl, und Jörg Fehr. Machine Learning Algorithms for Learning Nonlinear Terms of Reduced Mechanical Models in Explicit Structural Dynamics. Proceedings in Applied Mathematics and Mechanics, 2020. [PUMA: EXC2075 PN7 PN7-6 curated]

Jonas Kneifl, David Rosin, Okan Avci, Oliver Röhrle, und Jörg Fehr. Low-dimensional data-based surrogate model of a continuum-mechanical musculoskeletal system based on non-intrusive model order reduction. Archive of applied mechanics, (93):3637-3663, Springer, 2023. [PUMA: EXC2075 PN7 PN7-1(II)Röhrle PN7-1.2 PN7-6 curated]

Julian Hay, Lars Schories, Eric Bayerschen, Peter Wimmer, Oliver Zehbe, Stefan Kirschbichler, und Jörg Christoph Fehr. Application of data-driven surrogate models for active human model response prediction and restraint system optimization. Frontiers in applied mathematics and statistics, (9):1-16, Frontiers Media, 2023. [PUMA: EXC2075 PN7 PN7-6 curated]

Denis Pfeifer, Andreas Baumann, Marco Giani, Christian Scheifele, und Jörg Fehr. Hybrid Digital Twins Using FMUs to Increase the Validity and Domain of Virtual Commissioning Simulations. Advances in Automotive Production Technology – Towards Software-Defined Manufacturing and Resilient Supply Chains, Springer, 2023. [PUMA: EXC2075 PN4 PN7 PN7-6 PN7-6(II) curated]

Jonas Kneifl, David Rosin, Okan Avci, Oliver Röhrle, und Jörg Christoph Fehr. Continuum-mechanical Forward Simulation Results of a Human Upper-limb Model Under Varying Muscle Activations. 2023. [PUMA: EXC2075 PN7 PN7-1(II)Röhrle PN7-6 curated]

Niklas Fahse, Matthew Millard, Fabian Kempter, Steffen Maier, Michael Roller, und Jörg Fehr. Dynamic Human Body Models in Vehicle Safety: An Overview. GAMM-Mitteilungen, (46)2:e202300007, 2023. [PUMA: EXC310 PN4 PN7 PN7-6 PNX curated] URL

Denis Pfeifer, Jonas Scheid, Jonas Kneifl, und Jörg Fehr. An improved development process of production plants using digital twins with extended dynamic behaviour in virtual commissioning and control – Simulation@Operations. Proceedings in Applied Mathematics & Mechanics, 2023. [PUMA: EXC2075 PN7 PN7-6 PN7-6(II) curated]

Jonas Kneifl, Julian Hay, und Jörg Fehr. Human Occupant Motion in Pre-Crash Scenario. 2022. [PUMA: EXC2075 PN2 PN7 PN7-6 curated]

Jonas Nicodemus, Jonas Kneifl, Jörg Fehr, und Benjamin Unger. Physics-informed Neural Networks-based Model Predictive Control for Multi-link Manipulators. IFAC-PapersOnLine, (55)20:331--336, Elsevier, 2022. [PUMA: EXC2075 PN4 PN4-8 PN7 PN7-6 curated] URL

Jonas Kneifl, David Rosin, Oliver Röhrle, und Jörg Fehr. Low-dimensional Data-based Surrogate Model of a Continuum-mechanical Musculoskeletal System Based on Non-intrusive Model Order Reduction. arXiv, 2023. [PUMA: EXC2075 PN7 PN7-1(II)Röhrle PN7-6 curated] URL

Jonas Kneifl, Dennis Grunert, und Joerg Fehr. A non-intrusive nonlinear model reduction method for structural dynamical problems based on machine learning. International Journal for Numerical Methods in Engineering, Wiley, April 2021. [PUMA: EXC2075 PN7 PN7-6 curated] URL

Jonas Kneifl, und Jörg Fehr. Machine Learning Algorithms for Learning Nonlinear Terms of Reduced Mechanical Models in Explicit Structural Dynamics. PAMM, (20)S1Wiley, März 2021. [PUMA: EXC2075 PN7 PN7-6 curated] URL