Detection and classification of vulnerable road users (VRUs) such as pedestrians and cyclists is a key requirement for the realization of fully autonomous vehicles. Radar-based classification of VRUs can be achieved by exploiting differences in the micro-Doppler signatures associated with VRUs. Specifically, machine learning (ML) algorithms can be trained to classify VRUs using the spectral content of radar signals. The performance of these models depends on the quality and quantity of the data used during the training process. Currently, data collection is typically done through measurements or low fidelity physics, primitive-based simulations. The feasibility of carrying out measurements to collect training data is typically limited by the vast amounts of data required and practicality issues when using VRUs like animals. In this paper, we present a computationally efficient, high fidelity physics-based simulation workflow that can be used to obtain a large quantity of spectrograms from the micro-Doppler signatures of VRUs. The simulations are conducted on full-scale VRU models with a 77 GHz, frequency-modulated continuouswave (FMCW) radar sensor model. Here, we collect the spectrograms of 4 targets; car, pedestrian, cyclist and dog at different speeds and angles-of-arrival. This data is then used to train a 5-layer convolutional neural network (CNN) that achieves nearly 100% classification accuracy after 5 epochs. Studies are conducted to investigate the impact of training data size, velocity and observation time window size on the accuracy of the CNN. Results from this study demonstrate how an accuracy of 95% can be realized using spectrograms obtained over a 0.2 s time window.

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The seismic safety of an arch dam is analyzed by calculating fragility curves for different damage and failure mechanisms. The model includes fluid–structure–foundation interaction and considers contact and material type nonlinearities. The ultimate limit state (failure) is studied by means of a plastic-damage concrete model, especially developed for cyclic loadings. The time histories of the ground motions are generated randomly by means of Kanai–Tajimi filter. Moreover, ten parameters of the model are considered as random variables, including the water level. To the best knowledge of the authors, for the first time, water-level variability is accounted for in a probabilistic seismic analysis of a dam. It is studied if it is admissible to increase the efficiency of the Monte Carlo simulation (MCS) by assuming lognormal distributions for the fragility curves. In general, the aim of this work is to show the possibilities and difficulties of probabilistic seismic analysis tools when applied to a sophisticated mechanical model of a real structure.

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It is shown by the fact of recent earthquakes that engineered dam structures are safe structures. Just minor structures and such, which have not been designed on engineering knowledge, have been damaged. To guarantee a safe dam design, it is necessary to account for the loading in an appropriate way together with the geotechnical site conditions. Based on these, the optimum layout of the structure can be found. For the dynamic loading of the dam structure intensive site specific investigations are needed. The interaction with the abutment is in most cases approximated by means of rigid body models, e.g. Londe or Goodman. To account for the dynamic interaction a more elaborated model is investigated based on calculations and results from the ICOLD “10th Benchmark Workshop on Numerical Analysis of Dams”. For this the orographic left rock wedge in the abutment of the Luzzone Dam is discretized within a numerical arch dam model accounting for the wedge mass gravitational forces. Time histories of accelerations are applied and fluid structure interaction is accounted for with added mass approach compared with fluid elements. The investigations on the stability are carried out within the finite element model and – with the time history of the dam thrust acting onto the wedge – with the Londe method. The results of the calculations are compared with respect to different distributions of the pore water pressure in the contact between rock wedge and underlying rock. It is to conclude that more sophisticated, realistic models show higher margins to entire system failure, which anticipates, that the existing model assumptions are conservative – as it is assumed. Die verheerenden Erdbebenereignisse der letzten Zeit zeigen, dass große Talsperren sehr sichere Bauwerke sind. Lediglich untergeordnete Bauwerke und solche, die nicht ingenieurmäßig geplant wurden, haben Schaden genommen. Um die Sicherheit einer Struktur gewährleisten zu können, sind alle Belastung und geologischen Randbedingungen zu berücksichtigen. Darauf basierend kann ein optimaler Entwurf gefunden werden. Für die Standsicherheitsnachweise ist eine genaue Untersuchung des Untergrunds erforderlich. Dabei werden meist Starrkörpermethoden, zum Beispiel nach Londe oder Goodman angewendet. Zur besseren Berücksichtigung der dynamischen Interaktion bei Erdbebenbelastung wird ein aufwändigeres Modell, basierend auf dem ICOLD “10th Benchmark Workshop on Numerical Analysis of Dams”, erstellt. Hierbei wird der bei der Luzzone Talsperre orographisch rechts liegende Felskeil in einem numerischen Modell der Bogenstaumauer diskretisiert, um dessen Eigengewicht direkt berücksichtigen zu können. Das Erdbeben wirkt dynamisch auf das Modell; die Fluid‐Struktur‐Interaktion wird mit addierten Massen und Acoustics Elementen simuliert. Die Untersuchung der Felskeilstabilität wird vergleichend mit der Finiten‐Elemente‐Methode und der Londe‐Methode durchgeführt. Dabei wird die auf den Keil wirkende Sperrenbeanspruchung in Rechnung gestellt. Die Ergebnisse der beiden Berechnunge...