07 Fakultät Konstruktions-, Produktions- und Fahrzeugtechnik
Permanent URI for this collectionhttps://elib.uni-stuttgart.de/handle/11682/8
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Item Open Access 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, JörgSurrogate 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.Item Open Access 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, JörgItem Open Access Finite element simulations of motorcyclist interaction with a novel passive safety concept for motorcycles(2021) Maier, Steffen; Doléac, Laurent; Hertneck, Holger; Stahlschmidt, Sebastian; Fehr, JörgItem Open Access 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, TobiasOccupants 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.Item Open Access 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, JörgThe 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.Item Open Access 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, BernardItem Open Access Accident simulations of a novel restraint safety concept for motorcyclists(2023) Maier, Steffen; Fehr, JörgItem Open Access Combining knowledge and information - graph-based description of driving scenarios to enable holistic vehicle safety(2023) Bechler, Florian; Fehr, Jörg; Neininger, Fabian; Knöß, Stefan; Grotz, BernhardCurrently, vehicle safety is based on knowledge from injury values, crash pulses, and driving kinematics which leads to intervention strategies separated into isolated domains of active and passive safety. In this contribution, it is shown how vehicle safety can be approached holistically, allowing for human-centered and scenario-based safety decision-making. For this purpose, information from interior and exterior vehicle sensors can be linked by a mathematical framework, combining the knowledge that is already available in the individual domains. A universal graph representation for driving scenarios is developed to master the complexity of driving scenarios and allow for an optimized and scenario-based intervention strategy to minimize occupant injury values. This novel approach allows for the inclusion of sub-models, expert knowledge, results from previous simulations, and annotated databases. The resulting graph can be expanded dynamically for other objects or occupants to reflect all available information to be considered in case of urgency. As input, interior and exterior vehicle sensor data is used. Further information about the driving situation is subsequently derived from this input and the interaction between those states is described by the graph dynamically. For example, occupant attentiveness is derived from measurable eye gaze and eyelid position. From this quantity, reaction time can be estimated in turn. Combined with exterior information, it is possible to decide on the intervention strategy like e.g. alerting the driver. Physical or data-based functional dependencies can be used to represent such interactions. The uncertainties of the inputs and from the surrogate models are included in the graph to ensure a reliable decision-making process. An example of the decision-making process, by modeling the states and actuators as partially observable Markov decision process (POMDP), shows how to optimize the airbag efficiency by influencing the head position prior to an impact. This approach can be extended by additional parameters like driving environment, occupant occupancy, and seating positions in further iterations to optimize the intervention strategy for occupants. The proposed framework integrates scenario-based driving dynamics and existing knowledge from so far separated safety systems with individual activation logic and trigger points to enable holistic vehicle safety intervention strategies for the first time. It lays the foundation to consider new safety hardware, sensor information, and safety functions through a modular, and holistic approach.Item Open Access Documenting research software in engineering science(2022) Hermann, Sibylle; Fehr, JörgThe reuse of research software needs good documentation, however, the documentation in particular is often criticized. Especially in non-IT specific disciplines, the lack of documentation is attributed to the lack of training, the lack of time or missing rewards. This article addresses the hypothesis that scientists do document but do not know exactly what they need to document, why, and for whom. In order to evaluate the actual documentation practice of research software, we examined existing recommendations, and we evaluated their implementation in everyday practice using a concrete example from the engineering sciences and compared the findings with best practice examples. To get a broad overview of what documentation of research software entailed, we defined categories and used them to conduct the research. Our results show that the big picture of what documentation of research software means is missing. Recommendations do not consider the important role of researchers, who write research software, whose documentation takes mainly place in their research articles. Moreover, we show that research software always has a history that influences the documentation.Item Open Access Characterisation of an energy absorbing foam for motorcycle rider protection in LS-DYNA(2021) Maier, Steffen; Helbig, Martin; Hertneck, Holger; Fehr, Jörg
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