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- Einspielen <Werkstoff> (7)
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- Finite-Elemente-Methode (4)
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The SG1-mediated solution polymerization of methyl methacrylate (MMA) and oligo(ethylene glycol) methacrylate (OEGMA, Mₙ = 300 g mol⁻¹) in the presence of a small amount of functional/reactive styrenic comonomer is investigated. Moieties such as pentafluorophenyl ester, triphenylphosphine, azide, pentafluorophenyl, halide, and pyridine are considered. A comonomer fraction as low as 5 mol% typically results in a controlled/living behavior, at least up to 50% conversion. Chain extensions with styrene for both systems were successfully performed. Variation of physical properties such as refractive index (for MMA) and phase transition temperature (for OEGMA) were evaluated by comparing to 100% pure homopolymers. The introduction of an activated ester styrene derivative in the polymerization of OEGMA allows for the synthesis of reactive and hydrophilic polymer brushes with defined thickness. Finally, using the example of pentafluorostyrene as controlling comonomer, it is demonstrated that functional PMMA-b-PS are able to maintain a phase separation ability, as evidenced by the formation of nanostructured thin films.
Manufacturing process simulation (MPS) has become more and more important for aviation and the automobile industry. A highly competitive market requires the use of high performance metals and composite materials in combination with reduced manufacturing cost and time as well as a minimization of the time to market for a new product. However, the use of such materials is expensive and requires sophisticated manufacturing processes. An experience based process and tooling design followed by a lengthy trial-and-error optimization is just not contemporary anymore. Instead, a tooling design process aided by simulation is used more often. This paper provides an overview of the capabilities of MPS in the fields of sheet metal forming and prepreg autoclave manufacturing of composite parts summarizing the resulting benefits for tooling design and manufacturing engineering. The simulation technology is explained briefly in order to show several simplification and optimization techniques for developing industrialized simulation approaches. Small case studies provide examples of an efficient application on an industrial scale.
The emergence of automotive-grade LiDARs has given rise to new potential methods to develop novel advanced driver assistance systems (ADAS). However, accurate and reliable parking slot detection (PSD) remains a challenge, especially in the low-light conditions typical of indoor car parks. Existing camera-based approaches struggle with these conditions and require sensor fusion to determine parking slot occupancy. This paper proposes a parking slot detection (PSD) algorithm which utilizes the intensity of a LiDAR point cloud to detect the markings of perpendicular parking slots. LiDAR-based approaches offer robustness in low-light environments and can directly determine occupancy status using 3D information. The proposed PSD algorithm first segments the ground plane from the LiDAR point cloud and detects the main axis along the driving direction using a random sample consensus algorithm (RANSAC). The remaining ground point cloud is filtered by a dynamic Otsu’s threshold, and the markings of parking slots are detected in multiple windows along the driving direction separately. Hypotheses of parking slots are generated between the markings, which are cross-checked with a non-ground point cloud to determine the occupancy status. Test results showed that the proposed algorithm is robust in detecting perpendicular parking slots in well-marked car parks with high precision, low width error, and low variance. The proposed algorithm is designed in such a way that future adoption for parallel parking slots and combination with free-space-based detection approaches is possible. This solution addresses the limitations of camera-based systems and enhances PSD accuracy and reliability in challenging lighting conditions.
The behaviour of infilled reinforced concrete frames under horizontal load has been widely investigated, both experimentally and numerically. Since experimental tests represent large investments, numerical simulations offer an efficient approach for a more comprehensive analysis. When RC frames with masonry infill walls are subjected to horizontal loading, their behaviour is highly non-linear after a certain limit, which makes their analysis quite difficult. The non-linear behaviour results from the complex inelastic material properties of the concrete, infill wall and conditions at the wall-frame interface. In order to investigate this non-linear behaviour in detail, a finite element model using a micro modelling approach is developed, which is able to predict the complex non-linear behaviour resulting from the different materials and their interaction. Concrete and bricks are represented by a non-linear material model, while each reinforcement bar is represented as an individual part installed in the concrete part and behaving elasto-plastically. Each brick is modelled individually and connected taking into account the non-linearity of a brick mortar interface. The same approach is followed using two finite element software packages and the results are compared with the experimental results. The numerical models show a good agreement with the experiments in predicting the overall behaviour, but also very good matching for strength capacity and drift. The results emphasize the quality and the valuable contribution of the numerical models for use in parametric studies, which are needed for the derivation of design recommendations for infilled frame structures.