Contact
+49 711 685 66626
+49 711 685 66400
Email
Pfaffenwaldring 9
70569 Stuttgart
Deutschland
Room: 3.103
Subject
Uncertainty Quantification and Possibility Theory in Engineering Applications
- Könecke, T.; Hose, D.; Frie, L.; Hanss, M.; Eberhard, P.: Analysis of mixed uncertainty through possibilistic inference by using error estimation of reduced order surrogate models. In: Proceedings of USD2022 International Conference on Uncertainty in Structural Dynamics, Leuven, 2022.
- Könecke, T.; Hanss, M.: On Processing Heterogeneous Sources of Limited Data for Uncertainty Quantification in a Possibilistic Framework. In: Proceedings of the 5th International Conference on Uncertainty Quantification in Computational Sciences and Engineering, Athens, 2023. DOI: 10.7712/120223.10343.19772
- Frie, L.; Könecke, T.; Hanss, M.; Eberhard, P.: Possibilistic Uncertainty Quantification for Parametrically Reduced Models of Dynamic Systems with Many Inputs. In: Proceedings of the 49th European Rotorcraft Forum, Bückeburg, 2023.
- Könecke, T.; Ebel, H.; Hanss, M.: Possibilistic Robot Localization Using Visual Landmarks. In: Proceedings in Applied Mathematics and Mechanics, 2024.
- Könecke, T.; Hanss, M.: Exploring Possibilistic Potentials in Uncertainty Quantification for Modal Analysis Techniques. In: Proceedings of USD2024 International Conference on Uncertainty in Structural Dynamics, Leuven, 2024.
- July 25, 2022: ITM Statusseminar, Hösbach, "Uncertainty Quantification through Imprecise Probabilities & Possibility Theory".
- September 13, 2022: 9th International Conference on Uncertainty in Structural Dynamics (USD), Leuven. "Analysis of mixed uncertainty through possibilistic inference by using error estimation of reduced order surrogate models".
- June 12, 2023: 5th ECCOMAS Thematic Conference on Uncertainty Quantification in Computational Sciences and Engineering (UNCECOMP), Athens. "On Processing Heterogeneous Sources of Limited Data for Uncertainty Quantification in a Possibilistic Framework".
- July 19, 2023: ITM Statusseminar, Hösbach, "Possibility Theory, Baby".
- March 20, 2024: 93rd Annual Meeting of the International Association of Applied Mathematics and Mechanics (GAMM), Magdeburg. "Possibilistic Robot Localization Using Visual Landmarks".
- July 15, 2024: ITM Statusseminar, Monbachtal, "Towards Applied Possibilistic Uncertainty Quantification".
- September 10, 2024: 10th International Conference on Uncertainty in Structural Dynamics (USD), Leuven. "Exploring Possibilistic Potentials in Uncertainty Quantification for Modal Analysis Techniques".
- Robust Optimization-based Obstacle Avoidance for Mobile Robots, Bachelor Thesis.
Institute of Engineering and Computational Mechanics, University of Stuttgart, 2024. (running)
In co-supervision with Mario Rosenfelder, M.Sc. and Jan Schneider, M.Sc. - Numerical Analysis of Modal Parameters of a Guitar Soundboard Under Consideration of Uncertainties, Master Thesis.
Institute of Engineering and Computational Mechanics, University of Stuttgart, 2024. (running)
In co-supervision with Pierfrancesco Cillo, M.Sc. - Design and Implementation of a µ-Synthesis Controller for an Unstable System in Simulation and Hardware, Project Thesis.
Institute of Engineering and Computational Mechanics, University of Stuttgart, 2024. (running)
In co-supervision with Arnim Kargl, M.Sc. - Uncertainty Quantification of Quantum Algorithms Using a Possibilistic Approach, Study Thesis.
Institute of Engineering and Computational Mechanics, University of Stuttgart, 2024. (running)
In co-supervision with Jan Schneider, M.Sc. - Implementation and Optimization of Neural Networks for Possibilistic Uncertainty Representation, Project Thesis.
Institute of Engineering and Computational Mechanics, University of Stuttgart, 2024. (running)
In co-supervision with Jan Schneider, M.Sc. - Using Possibility Theory to Design a Robust Optimal Control Scheme for a Highly Dynamic System, Master Thesis.
Institute of Engineering and Computational Mechanics, University of Stuttgart, 2024. (running)
In co-supervision with Mario Rosenfelder, M.Sc. and Jan Schneider, M.Sc. - Possibilistic Uncertainty Modeling in Neural Networks, Bachelor Thesis.
Institute of Engineering and Computational Mechanics, University of Stuttgart, 2024.
In co-supervision with Jan Schneider, M.Sc. - Identification of Non-measurable Parameters of Mechanical Systems from Experimental Data Using Reduced Order Models, Master Thesis.
Institute of Engineering and Computational Mechanics, University of Stuttgart, 2024.
In co-supervision with Lennart Frie, M.Sc. - Design and Realization of a Fast Optimal Transform, Seminar Thesis.
Institute of Engineering and Computational Mechanics, University of Stuttgart, 2024.
In co-supervision with Lennart Frie, M.Sc. - Considering Uncertainty in Optimization-based Control of Mechanical Systems, Bachelor Thesis.
Institute of Engineering and Computational Mechanics, University of Stuttgart, 2023.
In co-supervision with Mario Rosenfelder, M.Sc. - Dynamic Robot Localization Using a Possibilistic Filter, Master Thesis.
Institute of Engineering and Computational Mechanics, University of Stuttgart, 2023.
In co-supervision with Dr.-Ing. Henrik Ebel - Development of a Camera-based Localization System for Mobile Robots, Project Thesis.
Institute of Engineering and Computational Mechanics, University of Stuttgart, 2023.
In co-supervision with Dr.-Ing. Henrik Ebel - Set-Membership Particle Filter for Robot Localization, Bachelor Thesis.
Institute of Engineering and Computational Mechanics, University of Stuttgart, 2022.
In co-supervision with Dr.-Ing. Henrik Ebel and Hannes Eschmann, M.Sc.
- Teaching assistant of the lecture Uncertainty Quantification (ST 2022)
- Supervision of the seminar in Applied Mechanics I (WT 2022/23)
- Teaching assistant of the lecture Uncertainty Quantification (ST 2023)
- Advisor for practical training Machine Foundation (ST 2023)
- Teaching assistant of the lecture Uncertainty Quantification (ST 2024)
- Advisor for practical training Machine Foundation (ST 2024)
- Management of institute vehicles
- Maintenance and administration of the software package FAMOUS for uncertainty quantification in dynamic systems.