@article{BoehnischBraunMuscarelloetal.2023, author = {B{\"o}hnisch, Nils and Braun, Carsten and Muscarello, Vincenzo and Marzocca, Pier}, title = {A sensitivity study on aeroelastic instabilities of slender wings with a large propeller}, series = {AIAA SCITECH 2023 Forum}, journal = {AIAA SCITECH 2023 Forum}, publisher = {AIAA}, doi = {10.2514/6.2023-1893}, pages = {1 -- 14}, year = {2023}, abstract = {Next-generation aircraft designs often incorporate multiple large propellers attached along the wingspan. These highly flexible dynamic systems can exhibit uncommon aeroelastic instabilities, which should be carefully investigated to ensure safe operation. The interaction between the propeller and the wing is of particular importance. It is known that whirl flutter is stabilized by wing motion and wing aerodynamics. This paper investigates the effect of a propeller onto wing flutter as a function of span position and mounting stiffness between the propeller and wing. The analysis of a comparison between a tractor and pusher configuration has shown that the coupled system is more stable than the standalone wing for propeller positions near the wing tip for both configurations. The wing fluttermechanism is mostly affected by the mass of the propeller and the resulting change in eigenfrequencies of the wing. For very weak mounting stiffnesses, whirl flutter occurs, which was shown to be stabilized compared to a standalone propeller due to wing motion. On the other hand, the pusher configuration is, as to be expected, the more critical configuration due to the attached mass behind the elastic axis.}, language = {de} } @inproceedings{ThomaStiemerBraunetal.2023, author = {Thoma, Andreas and Stiemer, Luc and Braun, Carsten and Fisher, Alex and Gardi, Alessandro G.}, title = {Potential of hybrid neural network local path planner for small UAV in urban environments}, series = {AIAA SCITECH 2023 Forum}, booktitle = {AIAA SCITECH 2023 Forum}, publisher = {AIAA}, doi = {10.2514/6.2023-2359}, pages = {13 Seiten}, year = {2023}, abstract = {This work proposes a hybrid algorithm combining an Artificial Neural Network (ANN) with a conventional local path planner to navigate UAVs efficiently in various unknown urban environments. The proposed method of a Hybrid Artificial Neural Network Avoidance System is called HANNAS. The ANN analyses a video stream and classifies the current environment. This information about the current Environment is used to set several control parameters of a conventional local path planner, the 3DVFH*. The local path planner then plans the path toward a specific goal point based on distance data from a depth camera. We trained and tested a state-of-the-art image segmentation algorithm, PP-LiteSeg. The proposed HANNAS method reaches a failure probability of 17\%, which is less than half the failure probability of the baseline and around half the failure probability of an improved, bio-inspired version of the 3DVFH*. The proposed HANNAS method does not show any disadvantages regarding flight time or flight distance.}, language = {en} } @article{StiemerThomaBraun2023, author = {Stiemer, Luc Nicolas and Thoma, Andreas and Braun, Carsten}, title = {MBT3D: Deep learning based multi-object tracker for bumblebee 3D flight path estimation}, series = {PLoS ONE}, volume = {18}, journal = {PLoS ONE}, number = {9}, publisher = {PLOS}, address = {San Fancisco}, issn = {1932-6203}, doi = {10.1371/journal.pone.0291415}, pages = {e0291415}, year = {2023}, abstract = {This work presents the Multi-Bees-Tracker (MBT3D) algorithm, a Python framework implementing a deep association tracker for Tracking-By-Detection, to address the challenging task of tracking flight paths of bumblebees in a social group. While tracking algorithms for bumblebees exist, they often come with intensive restrictions, such as the need for sufficient lighting, high contrast between the animal and background, absence of occlusion, significant user input, etc. Tracking flight paths of bumblebees in a social group is challenging. They suddenly adjust movements and change their appearance during different wing beat states while exhibiting significant similarities in their individual appearance. The MBT3D tracker, developed in this research, is an adaptation of an existing ant tracking algorithm for bumblebee tracking. It incorporates an offline trained appearance descriptor along with a Kalman Filter for appearance and motion matching. Different detector architectures for upstream detections (You Only Look Once (YOLOv5), Faster Region Proposal Convolutional Neural Network (Faster R-CNN), and RetinaNet) are investigated in a comparative study to optimize performance. The detection models were trained on a dataset containing 11359 labeled bumblebee images. YOLOv5 reaches an Average Precision of AP = 53, 8\%, Faster R-CNN achieves AP = 45, 3\% and RetinaNet AP = 38, 4\% on the bumblebee validation dataset, which consists of 1323 labeled bumblebee images. The tracker's appearance model is trained on 144 samples. The tracker (with Faster R-CNN detections) reaches a Multiple Object Tracking Accuracy MOTA = 93, 5\% and a Multiple Object Tracking Precision MOTP = 75, 6\% on a validation dataset containing 2000 images, competing with state-of-the-art computer vision methods. The framework allows reliable tracking of different bumblebees in the same video stream with rarely occurring identity switches (IDS). MBT3D has much lower IDS than other commonly used algorithms, with one of the lowest false positive rates, competing with state-of-the-art animal tracking algorithms. The developed framework reconstructs the 3-dimensional (3D) flight paths of the bumblebees by triangulation. It also handles and compares two alternative stereo camera pairs if desired.}, language = {en} } @article{ChristenKowalskiBartelt2010, author = {Christen, Marc and Kowalski, Julia and Bartelt, Perry}, title = {RAMMS: Numerical simulation of dense snow avalanches in three-dimensional terrain}, series = {Cold Regions Science and Technology}, volume = {63}, journal = {Cold Regions Science and Technology}, number = {1-2}, publisher = {Elsevier}, address = {Amsterdam}, issn = {1872-7441}, doi = {10.1016/j.coldregions.2010.04.005}, pages = {1 -- 14}, year = {2010}, abstract = {Numerical avalanche dynamics models have become an essential part of snow engineering. Coupled with field observations and historical records, they are especially helpful in understanding avalanche flow in complex terrain. However, their application poses several new challenges to avalanche engineers. A detailed understanding of the avalanche phenomena is required to construct hazard scenarios which involve the careful specification of initial conditions (release zone location and dimensions) and definition of appropriate friction parameters. The interpretation of simulation results requires an understanding of the numerical solution schemes and easy to use visualization tools. We discuss these problems by presenting the computer model RAMMS, which was specially designed by the SLF as a practical tool for avalanche engineers. RAMMS solves the depth-averaged equations governing avalanche flow with accurate second-order numerical solution schemes. The model allows the specification of multiple release zones in three-dimensional terrain. Snow cover entrainment is considered. Furthermore, two different flow rheologies can be applied: the standard Voellmy-Salm (VS) approach or a random kinetic energy (RKE) model, which accounts for the random motion and inelastic interaction between snow granules. We present the governing differential equations, highlight some of the input and output features of RAMMS and then apply the models with entrainment to simulate two well-documented avalanche events recorded at the Vall{\´e}e de la Sionne test site.}, language = {en} } @article{ChristenBarteltKowalski2010, author = {Christen, Marc and Bartelt, Perry and Kowalski, Julia}, title = {Back calculation of the In den Arelen avalanche with RAMMS: Interpretation of model results}, series = {Annals of Glaciology}, volume = {51}, journal = {Annals of Glaciology}, number = {54}, publisher = {Cambridge University Press}, address = {Cambridge}, isbn = {1727-5644}, doi = {10.3189/172756410791386553}, pages = {161 -- 168}, year = {2010}, abstract = {Two- and three-dimensional avalanche dynamics models are being increasingly used in hazard-mitigation studies. These models can provide improved and more accurate results for hazard mapping than the simple one-dimensional models presently used in practice. However, two- and three-dimensional models generate an extensive amount of output data, making the interpretation of simulation results more difficult. To perform a simulation in three-dimensional terrain, numerical models require a digital elevation model, specification of avalanche release areas (spatial extent and volume), selection of solution methods, finding an adequate calculation resolution and, finally, the choice of friction parameters. In this paper, the importance and difficulty of correctly setting up and analysing the results of a numerical avalanche dynamics simulation is discussed. We apply the two-dimensional simulation program RAMMS to the 1968 extreme avalanche event In den Arelen. We show the effect of model input variations on simulation results and the dangers and complexities in their interpretation.}, language = {en} } @article{LasaiKolmWahleetal.2000, author = {Lasai, Sven and Kolm, Heiko and Wahle, Michael and Pohl, Reiner}, title = {Schwingungsanalyse von Subsystemen mit Hilfe der Simulation}, series = {Automobiltechnische Zeitschrift - ATZ}, volume = {102}, journal = {Automobiltechnische Zeitschrift - ATZ}, number = {4}, isbn = {0001-2785}, pages = {266 -- 270}, year = {2000}, language = {de} } @article{FornaciariGuidettiHavermannetal.2010, author = {Fornaciari, Andrea and Guidetti, Marco and Havermann, Marc and Lettini, Antonio}, title = {Maccine mobili pi{\`u} efficienti}, series = {Fluidotecnica}, journal = {Fluidotecnica}, number = {345}, publisher = {Quine Business Publisher}, address = {Milano}, pages = {11 -- 14}, year = {2010}, abstract = {Secondo le attuali normative tutte le macchine mobili, entro il 2012, dovranno essere soggette a un incremento di efficienza energetica. Un'evoluzione del sistema idraulico potr{\`a} contribuire in maniera significativa al miglioramento richiesto. Elettronica e idraulica sempre pi{\`u} protagoniste.}, language = {it} } @inproceedings{HavermannSeilerHenning2010, author = {Havermann, Marc and Seiler, F. and Henning, P.}, title = {Shock Tunnel Experiments and CFD Simulation of Lateral Jet Interaction in Hypersonic Flows}, series = {New Results in Numerical and Experimental Fluid Mechanics VII; Contributions to the 16th STAB/DGLR Symposium Aachen, Germany 2008}, booktitle = {New Results in Numerical and Experimental Fluid Mechanics VII; Contributions to the 16th STAB/DGLR Symposium Aachen, Germany 2008}, editor = {Dillmann, Andreas and Heller, Gerd and Klaas, Michael and Kreplin, Hans-Peter and Nitsche, Wolfgang and Schr{\"o}der, Wolfgang}, publisher = {Springer}, address = {Berlin}, isbn = {9783642142437}, doi = {10.1007/978-3-642-14243-7_45}, pages = {365 -- 372}, year = {2010}, language = {en} } @article{GoettenHavermannBraunetal.2019, author = {G{\"o}tten, Falk and Havermann, Marc and Braun, Carsten and Gomez, Francisco and Bil, Cees}, title = {RANS Simulation Validation of a Small Sensor Turret for UAVs}, series = {Journal of Aerospace Engineering}, volume = {32}, journal = {Journal of Aerospace Engineering}, number = {5}, publisher = {ASCE}, address = {New York}, issn = {1943-5525}, doi = {10.1061/(ASCE)AS.1943-5525.0001055}, pages = {Article number 04019060}, year = {2019}, abstract = {Recent Unmanned Aerial Vehicle (UAV) design procedures rely on full aircraft steady-state Reynolds-Averaged-Navier-Stokes (RANS) analyses in early design stages. Small sensor turrets are included in such simulations, even though their aerodynamic properties show highly unsteady behavior. Very little is known about the effects of this approach on the simulation outcomes of small turrets. Therefore, the flow around a model turret at a Reynolds number of 47,400 is simulated with a steady-state RANS approach and compared to experimental data. Lift, drag, and surface pressure show good agreement with the experiment. The RANS model predicts the separation location too far downstream and shows a larger recirculation region aft of the body. Both characteristic arch and horseshoe vortex structures are visualized and qualitatively match the ones found by the experiment. The Reynolds number dependence of the drag coefficient follows the trend of a sphere within a distinct range. The outcomes indicate that a steady-state RANS model of a small sensor turret is able to give results that are useful for UAV engineering purposes but might not be suited for detailed insight into flow properties.}, language = {en} }