TY - JOUR A1 - Stiemer, Luc Nicolas A1 - Thoma, Andreas A1 - Braun, Carsten T1 - MBT3D: Deep learning based multi-object tracker for bumblebee 3D flight path estimation JF - PLoS ONE N2 - 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. Y1 - 2023 U6 - http://dx.doi.org/10.1371/journal.pone.0291415 SN - 1932-6203 N1 - Corresponding author: Luc Nicolas Stiemer VL - 18 IS - 9 PB - PLOS CY - San Fancisco ER - TY - JOUR A1 - Christen, Marc A1 - Kowalski, Julia A1 - Bartelt, Perry T1 - RAMMS: Numerical simulation of dense snow avalanches in three-dimensional terrain JF - Cold Regions Science and Technology N2 - 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 Vallée de la Sionne test site. KW - RAMMS KW - snow KW - avalanche Y1 - 2010 U6 - http://dx.doi.org/10.1016/j.coldregions.2010.04.005 SN - 1872-7441 VL - 63 IS - 1-2 SP - 1 EP - 14 PB - Elsevier CY - Amsterdam ER - TY - JOUR A1 - Christen, Marc A1 - Bartelt, Perry A1 - Kowalski, Julia T1 - Back calculation of the In den Arelen avalanche with RAMMS: Interpretation of model results JF - Annals of Glaciology N2 - 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. KW - avalanche Y1 - 2010 SN - 1727-5644 U6 - http://dx.doi.org/10.3189/172756410791386553 VL - 51 IS - 54 SP - 161 EP - 168 PB - Cambridge University Press CY - Cambridge ER - TY - JOUR A1 - Lasai, Sven A1 - Kolm, Heiko A1 - Wahle, Michael A1 - Pohl, Reiner T1 - Schwingungsanalyse von Subsystemen mit Hilfe der Simulation JF - Automobiltechnische Zeitschrift - ATZ Y1 - 2000 SN - 0001-2785 VL - 102 IS - 4 SP - 266 EP - 270 ER - TY - JOUR A1 - Fornaciari, Andrea A1 - Guidetti, Marco A1 - Havermann, Marc A1 - Lettini, Antonio T1 - Maccine mobili più efficienti JF - Fluidotecnica N2 - 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 potrà contribuire in maniera significativa al miglioramento richiesto. Elettronica e idraulica sempre più protagoniste. Y1 - 2010 IS - 345 SP - 11 EP - 14 PB - Quine Business Publisher CY - Milano ER - TY - CHAP A1 - Havermann, Marc A1 - Seiler, F. A1 - Henning, P. ED - Dillmann, Andreas ED - Heller, Gerd ED - Klaas, Michael ED - Kreplin, Hans-Peter ED - Nitsche, Wolfgang ED - Schröder, Wolfgang T1 - Shock Tunnel Experiments and CFD Simulation of Lateral Jet Interaction in Hypersonic Flows T2 - New Results in Numerical and Experimental Fluid Mechanics VII; Contributions to the 16th STAB/DGLR Symposium Aachen, Germany 2008 Y1 - 2010 SN - 9783642142437 U6 - http://dx.doi.org/10.1007/978-3-642-14243-7_45 N1 - Notes on numerical fluid mechanics and multidisciplinary design 112 SP - 365 EP - 372 PB - Springer CY - Berlin ER - TY - JOUR A1 - Götten, Falk A1 - Havermann, Marc A1 - Braun, Carsten A1 - Gomez, Francisco A1 - Bil, Cees T1 - RANS Simulation Validation of a Small Sensor Turret for UAVs JF - Journal of Aerospace Engineering N2 - 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. Y1 - 2019 U6 - http://dx.doi.org/10.1061/(ASCE)AS.1943-5525.0001055 SN - 1943-5525 VL - 32 IS - 5 PB - ASCE CY - New York ER -