07 Fakultät Konstruktions-, Produktions- und Fahrzeugtechnik

Permanent URI for this collectionhttps://elib.uni-stuttgart.de/handle/11682/8

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    Application of data-driven surrogate models for active human model response prediction and restraint system optimization
    (2023) Hay, Julian; Schories, Lars; Bayerschen, Eric; Wimmer, Peter; Zehbe, Oliver; Kirschbichler, Stefan; Fehr, Jörg
    Surrogate models are a must-have in a scenario-based safety simulation framework to design optimally integrated safety systems for new mobility solutions. The objective of this study is the development of surrogate models for active human model responses under consideration of multiple sampling strategies. A Gaussian process regression is chosen for predicting injury values based on the collision scenario, the occupant's seating position after a pre-crash movement and selected restraint system parameters. The trained models are validated and assessed for each sampling method and the best-performing surrogate model is selected for restraint system parameter optimization.
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    Towards learning human-seat interactions for optimally controlled multibody models to generate realistic occupant motion
    (2023) Fahse, Niklas; Harant, Monika; Roller, Michael; Kempter, Fabian; Obentheuer, Marius; Linn, Joachim; Fehr, Jörg
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    Finite element simulations of motorcyclist interaction with a novel passive safety concept for motorcycles
    (2021) Maier, Steffen; Doléac, Laurent; Hertneck, Holger; Stahlschmidt, Sebastian; Fehr, Jörg
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    A non-intrusive nonlinear model reduction method for structural dynamical problems based on machine learning
    (2020) Kneifl, Jonas; Grunert, Dennis; Fehr, Jörg
    The paper uses a nonlinear non-intrusive model reduction approach, to derive efficient and accurate surrogate models for structural dynamical problems. Therefore, a combination of proper orthogonal decomposition along with regression algorithms from the field of machine learning is utilized to capture the dynamics in a reduced representation. This allows highly performant approximations of the original system. In this context, we provide a comparison of several regression algorithms based on crash simulations of a structural dynamic frame.
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    Evaluation of a novel passive safety concept for motorcycles with combined multi-body and finite element simulations
    (2020) Maier, Steffen; Doléac, Laurent; Hertneck, Holger; Stahlschmidt, Sebastian; Fehr, Jörg
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    Modeling, simulation, and vision-/MPC-based control of a PowerCube serial robot
    (2020) Fehr, Jörg; Schmid, Patrick; Schneider, Georg; Eberhard, Peter
    A model predictive control (MPC) scheme for a Schunk PowerCube robot is derived in a structured step-by-step procedure. Neweul-M² provides the necessary nonlinear model in symbolical and numerical form. To handle the heavy online computational burden concerning the derived nonlinear model, a linear time-varying MPC scheme is developed based on linearizing the nonlinear system concerning the desired trajectory and the a priori known corresponding feed-forward controller. Camera-based systems allow sensing of the robot on the one hand and monitoring the environments on the other hand. Therefore, a vision-based MPC is realized to show the effects of vision-based control feedback on control performance. A semi-automatic trajectory planning is used to perform two meaningful experimental studies in which the advantages and restrictions of the proposed (vision-based) linear time-varying MPC scheme are pointed out. Everything is implemented on a slim, low-cost control system with a standard laptop PC.
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    Role of rotated head postures on volunteer kinematics and muscle activity in braking scenarios performed on a driving simulator
    (2022) Kempter, Fabian; Lantella, Lorena; Stutzig, Norman; Fehr, Jörg; Siebert, Tobias
    Occupants exposed to low or moderate crash events can already suffer from whiplash-associated disorders leading to severe and long-lasting symptoms. However, the underlying injury mechanisms and the role of muscle activity are not fully clear. Potential increases in injury risk of non-nominal postures, i.e., rotated head, cannot be evaluated in detail due to the lack of experimental data. Examining changes in neck muscle activity to hold and stabilize the head in a rotated position during pre-crash scenarios might provide a deeper understanding of muscle reflex contributions and injury mechanisms. In this study, the influence of two different head postures (nominal vs. rotation of the head by about 63 ± 9° to the right) on neck muscle activity and head kinematics was investigated in simulated braking experiments inside a driving simulator. The braking scenario was implemented by visualization of the virtual scene using head-mounted displays and a combined translational-rotational platform motion. Kinematics of seventeen healthy subjects was tracked using 3D motion capturing. Surface electromyography were used to quantify muscle activity of left and right sternocleidomastoideus (SCM) and trapezius (TRP) muscles. The results show clear evidence that rotated head postures affect the static as well as the dynamic behavior of muscle activity during the virtual braking event. With head turned to the right, the contralateral left muscles yielded higher base activation and delayed muscle onset times. In contrast, right muscles had much lower activations and showed no relevant changes in muscle activation between nominal and rotated head position. The observed delayed muscle onset times and increased asymmetrical muscle activation patterns in the rotated head position are assumed to affect injury mechanisms. This could explain the prevalence of rotated head postures during a crash reported by patients suffering from WAD. The results can be used for validating the active behavior of human body models in braking simulations with nominal and rotated head postures, and to gain a deeper understanding of neck injury mechanisms.
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    An improved development process of production plants using digital twins with extended dynamic behaviour in virtual commissioning and control : Simulation@Operations
    (2023) Pfeifer, Denis; Scheid, Jonas; Kneifl, Jonas; Fehr, Jörg
    The challenges in automation system development are driven by short development cycles and individualization along with resource‐constraints. State of the art solutions do not provide the necessary digital tools to apply model‐based methods in automation engineering to achieve higher performing systems. To overcome these issues this paper presents a novel approach to address some of the current challenges in automation systems development using digital twins with extended dynamic behaviour. The study underscores how dynamic models can be imported through standardised interfaces into virtual commissioning (VC) tools, improving the development process by effectively utilising domain‐specific expertise. The paper highlights how these digital twins enhance not only the VC process but can also be applied to model‐based control methods. Initial experiments showcase the utility of digital twins in calculating dynamic acceleration limits during trajectory planning of CNC control and enhancing feed‐forward control. Further, the importance of parameter identification in achieving accurate system models is stressed. The initial results are promising, and future work aims to combine these methods in an industrial application involving a newly developed, individual lightweight robot, demonstrating the potential for enhanced design, accelerated development, and resource efficiency in automation systems.
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    Port-Hamiltonian fluid-structure interaction modelling and structure-preserving model order reduction of a classical guitar
    (2023) Rettberg, Johannes; Wittwar, Dominik; Buchfink, Patrick; Brauchler, Alexander; Ziegler, Pascal; Fehr, Jörg; Haasdonk, Bernard
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