07 Fakultät Konstruktions-, Produktions- und Fahrzeugtechnik

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

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Author: search.filters.author.Fehr, JörgStart date: 2000

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Now showing 1 - 10 of 28
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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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    On the validation of human body models with a driver-in-the-loop simulator
    (2018) Kempter, Fabian; Fehr, Jörg; Stutzig, Norman; Siebert, Tobias
    For the development of modern integrated safety systems, standard simulation models of anthropometric test devices, often called crash test dummies, are inappropriate for Pre-Crash investigations due to missing activation possibilities, tuned characteristics for one specific accident scenario and high passive stiffness properties. To validate safety concepts getting active prior to the crash new tools like suitable virtual models of human occupants are required. Human Body Models (HBM) provide a higher biofidelity and can be equipped with active muscle elements enabling different muscle activation strategies. To improve the muscle activation strategy and the stiffness properties of active HBMs, validation processes on the basis of low-acceleration experiments are inevitable. In contrast to Post Mortem Human Surrogates only low-severity tests can be performed with real human subjects. This paper presents the workflow of a validation process based on an academic scale Driver-in-the-Loop (DiL) simulator in combination with a synchronized measurement chain consisting of an Optitrack stereo vision and an electromyography detection system.
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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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    Well-scaled, a-posteriori error estimation for model order reduction of large second-order mechanical systems
    (2019) Grunert, Dennis; Fehr, Jörg; Haasdonk, Bernard
    Model Order Reduction is used to vastly speed up simulations but it also introduces an error to the simulation results, which needs to be controlled. The performance of the general to use, a-posteriori error estimator of Ruiner et al. for second-order systems is analyzed and a bottleneck is found in the offline stage making it unusable for larger models. We use the spectral theorem, power series expansions, monotonicity properties, and self-tailored algorithms to speed up the offline stage largely by one polynomial order both in terms of computation time as well as storage complexity. All properties are proven rigorously. This eliminates the aforementioned bottleneck. Hence, the error estimator of Ruiner et al. can finally be used for large, linear, second-order mechanical systems reduced by any model reduction method based on Petrov-Galerkin reduction. The examples show speedups of up to 28.000 and the ability to compute much larger systems with a fixed amount of memory.
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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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    Implementation and validation of the extended Hill-type muscle model with robust routing capabilities in LS-DYNA for active human body models
    (2017) Kleinbach, Christian; Martynenko, Oleksandr; Promies, Janik; Häufle, Daniel F. B.; Fehr, Jörg; Schmitt, Syn
    In the state of the art finite element AHBMs for car crash analysis in the LS-DYNA software material named *MAT_MUSCLE (*MAT_156) is used for active muscles modeling. It has three elements in parallel configuration, which has several major drawbacks: restraint approximation of the physical reality, complicated parameterization and absence of the integrated activation dynamics. This study presents implementation of the extended four element Hill-type muscle model with serial damping and eccentric force-velocity relation including Ca2+ dependent activation dynamics and internal method for physiological muscle routing.
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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.