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2024
- Strauß, A., Kneifl, J., Tkachuk, A., Fehr, J., & Bischoff, M. (2024). Accelerated Non‐linear Stability Analysis Based on Predictions From Data‐Based Surrogate Models. International Journal for Numerical Methods in Engineering, 126, Article 1. https://doi.org/10.1002/nme.7649
- Kneifl, J., Fehr, J., Brunton, S. L., & Kutz, J. N. (2024). Multi-hierarchical surrogate learning for explicit structural dynamical systems using graph convolutional neural networks. Computational Mechanics. https://doi.org/10.1007/s00466-024-02553-6
- Rodegast, P., Maier, S., Kneifl, J., & Fehr, J. (2024). On using machine learning algorithms for motorcycle collision detection. Discover Applied Sciences, 6, Article 6. https://doi.org/10.1007/s42452-024-06014-w
- Conti, P., Kneifl, J., Manzoni, A., Frangi, A., Fehr, J., Brunton, S. L., & Kutz, J. N. (2024). VENI, VINDy, VICI: a variational reduced-order modeling framework with uncertainty quantification. https://doi.org/10.48550/arXiv.2405.20905
- Rettberg, J., Kneifl, J., Herb, J., Buchfink, P., Fehr, J., & Haasdonk, B. (2024). Data-driven identification of latent port-Hamiltonian systems. https://doi.org/10.48550/arXiv.2408.08185
2023
- Kneifl, J., Rosin, D., Avci, O., Röhrle, O., & Fehr, J. (2023). Low-dimensional data-based surrogate model of a continuum-mechanical musculoskeletal system based on non-intrusive model order reduction. Archive of Applied Mechanics. https://doi.org/10.1007/s00419-023-02458-5
- Pfeifer, D., Scheid, J., Kneifl, J., & Fehr, J. (2023). 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. https://doi.org/10.1002/pamm.202300225
2022
- Kneifl, J., Hay, J., & Fehr, J. (2022). Real-time Human Response Prediction Using a Non-intrusive Data-driven Model Reduction Scheme. IFAC-PapersOnLine, 55, Article 20. https://doi.org/10.1016/j.ifacol.2022.09.109
- Nicodemus, J., Kneifl, J., Fehr, J., & Unger, B. (2022). Physics-informed Neural Networks-based Model Predictive Control for Multi-link Manipulators. IFAC-PapersOnLine, 55, Article 20. https://doi.org/10.1016/j.ifacol.2022.09.117
2021
- Kneifl, J., Grunert, D., & Fehr, J. (2021). A non-intrusive nonlinear model reduction method for structural dynamical problems based on machine learning. International Journal for Numerical Methods in Engineering. https://doi.org/10.1002/nme.6712
- Kneifl, J., & Fehr, J. (2021). Machine Learning Algorithms for Learning Nonlinear Terms of Reduced Mechanical Models in Explicit Structural Dynamics. Pamm, 20, Article S1. https://doi.org/10.1002/pamm.202000353
- Betreuung der Vorlesung Model Reduction of Mechanical Systems (WS 2024/2025)
- Betreuung der Vorlesung Model Reduction of Mechanical Systems (WS 2023/2024)
- Betreuung des Seminars Technische Mechanik II (SS 2023)
- Betreuung der Vorlesung Model Reduction of Mechanical Systems (WS 2022/2023)
- Betreuung der Vorlesung Model Reduction of Mechanical Systems (WS 2021/2022)
- Betreuung der Vorlesung Model Reduction of Mechanical Systems (WS 2020/2021)
15. Juli 2024: ITM Statusseminar, Monbachtal (Bad Liebenzell): "VENI, VINDy, VICI: a variational reduced-order modeling framework with uncertainty quantification"
04. März 2024: Young Mathemations in Model Order Reduction Conference 2024 (YMMOR), Stuttgart: "Data-driven MOR and Surrogate Modeling of Dynamical Systems"
20. Oktober 2023: ITM Dynamiktag, Stuttgart: "Ein Fisch geht auf Reisen von Kalmaren, H-Indizes und Kreiselsymposien"
14. September 2023: Seminar Visit @ DICA, Politecnico Milano, Milan: "Data-driven Surrogate Modeling of Structural Dynamical Systems"
18. Juli 2023: ITM Statusseminar, Kloster Schmerlenbach, Hösbach: "Multihierarchic Surrogate Modeling using Graph Convolutional Neural Networks"
05. Juli 2023: Mechanics Seminar, University of Brasília Mathematics Department, Brasília: „Data-driven Surrogate Modeling of Structural Dynamical Systems"
09. Mai 2023: Campus Feminarum, Stuttgart: „Parsimonious Human Body Models Using Data-driven Model Reduction”
29. Februar 2023: SIAM Conference on Computational Science and Engineering (CSE23), Amsterdam: „Multi-hierarchic Data-driven Reduced Order Models based on Mesh Simplification and Graph Convolutional Autoencoders”
27. Januar 2023: SimTech Seminar on Model Reduction and Data Techniques for
Surrogate Modelling, Stuttgart: „Surrogate Models from Simulation Data in Structural Dynamics”
07. Dezember 2022: MOR-Day, Stuttgart: „Real-time Human Response Prediction Using a Non-intrusive Data-driven Model Reduction Scheme”
27. Juli 2022: 10th Vienna International Conference on Mathematical Modelling, Wien, Österreich: „Real-time Human Response Prediction Using a Non-intrusive Data-driven Model Reduction Scheme”
26. Juli 2022: ITM Statusseminar, Kloster Schmerlenbach, Hösbach: "On Different Types of Autoencoders for Dimensionality Reduction of Structural Dynamical Systems"
12. Januar 2022: Virtual talk at the ML Session on “Data Spotlight: Data-driven methods for engineering applications": "Data-driven Model Reduction
for Structural Dynamical Problems"
25. November 2021: ITM Statusseminar, Monbachtal (Bad Liebenzell): "Data-driven Model Order Reduction"
20. Oktober 2020: Virtual talk at the 6th GAMM AG DATA Workshop; "Machine Learning Algorithms for Learning Nonlinear Terms of Reduced Mechanical Models in Explicit Structural Dynamics"
Kneifl, Jonas; Rosin, David; Avci, Okan; Röhrle, Oliver; Fehr, Jörg, 2023, "Continuum-mechanical Forward Simulation Results of a Human Upper-limb Model Under Varying Muscle Activations", https://doi.org/10.18419/darus-3302, DaRUS, V1
Kneifl, Jonas; Hay, Julian; Fehr, Jörg, 2022, "Human Occupant Motion in Pre-Crash Scenario", https://doi.org/10.18419/darus-2471, DaRUS, V1
Kneifl, Jonas; Fehr, Jörg, 2020, "Deformation of a Structural Frame of a Racing Kart Colliding against a Rigid Wall", https://doi.org/10.18419/darus-1150, DaRUS, V1
22. March 2023: Beiratssiztung InnovationsCampus Mobilität: „Transportable echtzeitfähige digitale Zwillinge (TEDZ)”
05. July 2022: SimTech Statusseminar, Bad Boll: „Reusage and Reanalysis of Simulation Data"
"Development of a Multi-Fidelity Surrogate Model To Represent Hierarchical and Contradicting Databases", Bachelorarbeit BSC-167. Institut für Technische und Numerische Mechanik, Universität Stuttgart, 2024. Betreuung gemeinsam mit Niklas Fahse, M.Sc.
"Erweiterung der Datenbasis eines gelernten Mensch-Sitz-Interaktionsmodells für optimalgesteuerte Mehrkörpermodelle durch augmentierte und synthetisierte Daten", Projektarbeit SA-47. Institut für Technische und Numerische Mechanik, Universität Stuttgart, 2024. Betreuung gemeinsam mit Niklas Fahse, M.Sc.
"Parameterisation of the digital twin of an industrial robot through parameter identification methods", Forschungsarbeit FA-522. Institut für Technische und Numerische Mechanik, Universität Stuttgart, 2024. Betreuung gemeinsam mit Denis Pfeifer, M.Sc.
"Low-Dimensional Discovery of Port-Hamiltonian Systems by Combining Model Order Reduction and Machine Learning", Forschungsmodul SimTech.
Universität Stuttgart, Institut für Technische und Numerische Mechanik, 2023.
Betreuung gemeinsam mit Johannes Rettberg, M.Sc.
"Realisierung einer experimentellen Insassen-Sitz-Interaktionsstudie bei Variation der Sitzposition einschliesslich eines Versuchsaufbaus samt Datenerfassung zur Generierung von Ersatzmodellen", Masterarbeit MSC-340. Institute of Engineering and Computational Mechanics, University of Stuttgart, 2023. Supervision together with Niklas Fahse, M.Sc.
"Investigation of the suitability of surrogate models for predicting human-seat interaction with varying seat position using human body models", Studienarbeit. Institut für Technische und Numerische Mechanik, Universität Stuttgart, 2022. Betreuung gemeinsam mit Fabian Kempter, M.Sc.
"Collision detection of a motorcycle in accident scenarios using machine learning algorithms", Masterarbeit. Institut für Technische und Numerische Mechanik, Universität Stuttgart, 2022. Betreuung gemeinsam mit Steffen Maier, M.Sc.
"Discovering Friction Models from Experimental Data using Physics-informed Neural Networks", Forschungsmodul. Institut für Parallele und Verteilte Systeme / Institut für Technische und Numerische Mechanik, Universität Stuttgart, 2022.
"Application of Linear Model Order Reduction Methods to Accelerate Nonlinear Crash Simulations", Studienarbeit. Institut für Technische und Numerische Mechanik, Universität Stuttgart, 2022.
"Matrixapproximation mittels CUR Zerlegung", Sonstige Arbeit SA-34. Institut für Technische und Numerische Mechanik, Universität Stuttgart, 2021.
"Application of Physics Informed Neural Networks for the Approximation of Differential Equations in the Field of Rigid Body Dynamics", Masterarbeit MSC-316. Institut für Technische und Numerische Mechanik, Universität Stuttgart, 2021.
"Untersuchung der Eignung von Ersatzmodellen zur Analyse des Haltungseinflusses bei Heckaufprallevents anhand eines Hals-Nackenmodells", Studienarbeit STUD-510. Institut für Technische und Numerische Mechanik, Universität Stuttgart, 2021. Betreuung gemeinsam mit Fabian Kempter,M.Sc.