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 Technology selection for inline topography measurement with rover-borne laser spectrometers(2024) Ryan, Conor; Haist, Tobias; Laskin, Gennadii; Schröder, Susanne; Reichelt, StephanThis work studies enhancing the capabilities of compact laser spectroscopes integrated into space-exploration rovers by adding 3D topography measurement techniques. Laser spectroscopy enables the in situ analysis of sample composition, aiding in the understanding of the geological history of extraterrestrial bodies. To complement spectroscopic data, the inclusion of 3D imaging is proposed to provide unprecedented contextual information. The morphological information aids material characterization and hence the constraining of rock and mineral histories. Assigning height information to lateral pixels creates topographies, which offer a more complete spatial dataset than contextual 2D imaging. To aid the integration of 3D measurement into future proposals for rover-based laser spectrometers, the relevant scientific, rover, and sample constraints are outlined. The candidate 3D technologies are discussed, and estimates of performance, weight, and power consumptions guide the down-selection process in three application examples. Technology choice is discussed from different perspectives. Inline microscopic fringe-projection profilometry, incoherent digital holography, and multiwavelength digital holography are found to be promising candidates for further development.Item Open Access Reliability as a key driver for a sustainable design of adaptive load-bearing structures(2022) Efinger, Dshamil; Ostertag, Andreas; Dazer, Martin; Borschewski, David; Albrecht, Stefan; Bertsche, BerndThe consumption of construction materials and the pollution caused by their production can be reduced by the use of reliable adaptive load-bearing structures. Adaptive load-bearing structures are able to adapt to different load cases by specifically manipulating internal stresses using actuators installed in the structure. One main aspect of quality is reliability. A verification of reliability, and thus the safety of conventional structures, was a design issue. When it comes to adaptive load-bearing structures, the material savings reduce the stiffness of the structure, whereby integrated actuators with sensors and a control take over the stiffening. This article explains why the conventional design process is not sufficient for adaptive load-bearing structures and proposes a method for demonstrating improved reliability and environmental sustainability. For this purpose, an exemplary adaptive load-bearing structure is introduced. A linear elastic model, simulating tension in the elements of the adaptive load-bearing structure, supports the analysis. By means of a representative local load-spectrum, the operating life is estimated based on Woehler curves given by the Eurocode for the critical notches. Environmental sustainability is increased by including reliability and sustainability in design. For an exemplary high-rise adaptive load-bearing structure, this increase is more than 50%.Item 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.