@article{SchwagerFleschSchwarzboezletal.2022,
  author    = {Schwager, Christian and Flesch, Robert and Schwarzb{\"o}zl, Peter and Herrmann, Ulf and Teixeira Boura, Cristiano Jos{\´e}},
  title     = {Advanced two phase flow model for transient molten salt receiver system simulation},
  series = {Solar Energy},
  volume    = {232},
  journal   = {Solar Energy},
  publisher = {Elsevier},
  address   = {Amsterdam},
  issn      = {0038-092X (print)},
  doi       = {10.1016/j.solener.2021.12.065},
  pages     = {362 -- 375},
  year      = {2022},
  abstract  = {In order to realistically predict and optimize the actual performance of a concentrating solar power (CSP) plant sophisticated simulation models and methods are required. This paper presents a detailed dynamic simulation model for a Molten Salt Solar Tower (MST) system, which is capable of simulating transient operation including detailed startup and shutdown procedures including drainage and refill. For appropriate representation of the transient behavior of the receiver as well as replication of local bulk and surface temperatures a discretized receiver model based on a novel homogeneous two-phase (2P) flow modelling approach is implemented in Modelica Dymola®. This allows for reasonable representation of the very different hydraulic and thermal properties of molten salt versus air as well as the transition between both. This dynamic 2P receiver model is embedded in a comprehensive one-dimensional model of a commercial scale MST system and coupled with a transient receiver flux density distribution from raytracing based heliostat field simulation. This enables for detailed process prediction with reasonable computational effort, while providing data such as local salt film and wall temperatures, realistic control behavior as well as net performance of the overall system. Besides a model description, this paper presents some results of a validation as well as the simulation of a complete startup procedure. Finally, a study on numerical simulation performance and grid dependencies is presented and discussed.},
  language  = {en}
}
@article{SerrorHackHenzeetal.2021,
  author    = {Serror, Martin and Hack, Sacha and Henze, Martin and Schuba, Marko and Wehrle, Klaus},
  title     = {Challenges and Opportunities in Securing the Industrial Internet of Things},
  series = {IEEE Transactions on Industrial Informatics},
  volume    = {17},
  journal   = {IEEE Transactions on Industrial Informatics},
  number    = {5},
  publisher = {IEEE},
  address   = {New York},
  issn      = {1941-0050},
  doi       = {10.1109/TII.2020.3023507},
  pages     = {2985 -- 2996},
  year      = {2021},
  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}
}
@inproceedings{TamaldinEschTonolietal.2020,
  author    = {Tamaldin, Noreffendy and Esch, Thomas and Tonoli, Andrea and Reisinger, Karl Heinz and Sprenger, Hanna and Razuli, Hisham},
  title     = {ERASMUS+ United CBHE Automotive International Collaboration from European to South East Asia},
  series = {Proceedings of the 2nd African International Conference on Industrial Engineering and Operations Management},
  booktitle = {Proceedings of the 2nd African International Conference on Industrial Engineering and Operations Management},
  publisher = {IEOM Society International},
  address   = {Southfield},
  isbn      = {978-1-7923-6123-4},
  issn      = {2169-8767},
  pages     = {2970 -- 2972},
  year      = {2020},
  abstract  = {The industrial revolution especially in the IR4.0 era have driven many states of the art technologies to be introduced. The automotive industry as well as many other key industries have also been greatly influenced. The rapid development of automotive industries in Europe have created wide industry gap between European Union (EU) and developing countries such as in South East Asia (SEA). Indulging this situation, FH JOANNEUM, Austria together with European partners from FH Aachen, Germany and Politecnico di Torino, Italy are taking initiative to close down the gap utilizing the Erasmus+ United Capacity Building in Higher Education grant from EU. A consortium was founded to engage with automotive technology transfer using the European framework to Malaysian, Indonesian and Thailand Higher Education Institutions (HEI) as well as automotive industries in respective countries. This could be achieved by establishing Engineering Knowledge Transfer Unit (EKTU) in respective SEA institutions guided by the industry partners in their respective countries. This EKTU could offer updated, innovative and high-quality training courses to increase graduate's employability in higher education institutions and strengthen relations between HEI and the wider economic and social environment by addressing University-industry cooperation which is the regional priority for Asia. It is expected that, the Capacity Building Initiative would improve the quality of higher education and enhancing its relevance for the labor market and society in the SEA partners. The outcome of this project would greatly benefit the partners in strong and complementary partnership targeting the automotive industry and enhanced larger scale international cooperation between the European and SEA partners. It would also prepare the SEA HEI in sustainable partnership with Automotive industry in the region as a mean of income generation in the future.},
  language  = {en}
}
@inproceedings{TamaldinMansorMatYaminetal.2022,
  author    = {Tamaldin, Noreffendy and Mansor, Muhd Rizuan and Mat Yamin, Ahmad Kamal and Bin Abdollah, Mohd Fazli and Esch, Thomas and Tonoli, Andrea and Reisinger, Karl Heinz and Sprenger, Hanna and Razuli, Hisham},
  title     = {Development of UTeM United Future Fuel Design Training Center Under Erasmus+ United Program},
  series = {Proceedings of the 7th International Conference and Exhibition on Sustainable Energy and Advanced Materials (ICE-SEAM 2021), Melaka, Malaysia},
  booktitle = {Proceedings of the 7th International Conference and Exhibition on Sustainable Energy and Advanced Materials (ICE-SEAM 2021), Melaka, Malaysia},
  editor    = {Bin Abdollah, Mohd Fadzli and Amiruddin, Hilmi and Singh, Amrik Singh Phuman and Munir, Fudhail Abdul and Ibrahim, Asriana},
  publisher = {Springer Nature},
  address   = {Singapore},
  isbn      = {978-981-19-3178-9},
  issn      = {2195-4356},
  doi       = {10.1007/978-981-19-3179-6_50},
  pages     = {274 -- 278},
  year      = {2022},
  abstract  = {The industrial revolution IR4.0 era have driven many states of the art technologies to be introduced especially in the automotive industry. The rapid development of automotive industries in Europe have created wide industry gap between European Union (EU) and developing countries such as in South-East Asia (SEA). Indulging this situation, FH Joanneum, Austria together with European partners from FH Aachen, Germany and Politecnico Di Torino, Italy is taking initiative to close the gap utilizing the Erasmus+ United grant from EU. A consortium was founded to engage with automotive technology transfer using the European ramework to Malaysian, Indonesian and Thailand Higher Education Institutions (HEI) as well as automotive industries. This could be achieved by establishing Engineering Knowledge Transfer Unit (EKTU) in respective SEA institutions guided by the industry partners in their respective countries. This EKTU could offer updated, innovative, and high-quality training courses to increase graduate's employability in higher education institutions and strengthen relations between HEI and the wider economic and social environment by addressing Universityindustry cooperation which is the regional priority for Asia. It is expected that, the Capacity Building Initiative would improve the quality of higher education and enhancing its relevance for the labor market and society in the SEA partners. The outcome of this project would greatly benefit the partners in strong and complementary partnership targeting the automotive industry and enhanced larger scale international cooperation between the European and SEA partners. It would also prepare the SEA HEI in sustainable partnership with Automotive industry in the region as a mean of income generation in the future.},
  language  = {en}
}
@inproceedings{ThomaFisherBertrandetal.2020,
  author    = {Thoma, Andreas and Fisher, Alex and Bertrand, Olivier and Braun, Carsten},
  title     = {Evaluation of possible flight strategies for close object evasion from bumblebee experiments},
  series = {Living Machines 2020: Biomimetic and Biohybrid Systems},
  booktitle = {Living Machines 2020: Biomimetic and Biohybrid Systems},
  editor    = {Vouloutsi, Vasiliki and Mura, Anna and Tauber, Falk and Speck, Thomas and Prescott, Tony J. and Verschure, Paul F. M. J.},
  publisher = {Springer},
  address   = {Cham},
  isbn      = {978-3-030-64312-6},
  doi       = {10.1007/978-3-030-64313-3_34},
  pages     = {354 -- 365},
  year      = {2020},
  language  = {en}
}
@inproceedings{ThomaFisherBraun2020,
  author    = {Thoma, Andreas and Fisher, Alex and Braun, Carsten},
  title     = {Improving the px4 avoid algorithm by bio-inspired flight strategies},
  series = {DLRK2020 - „Luft- und Raumfahrt - Verantwortung in allen Dimensionen"},
  booktitle = {DLRK2020 - „Luft- und Raumfahrt - Verantwortung in allen Dimensionen"},
  pages     = {10 Seiten},
  year      = {2020},
  language  = {en}
}
@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{ThomaThomessenGardietal.2023,
  author    = {Thoma, Andreas and Thomessen, Karolin and Gardi, Alessandro and Fisher, A. and Braun, Carsten},
  title     = {Prioritising paths: An improved cost function for local path planning for UAV in medical applications},
  series = {The Aeronautical Journal},
  journal   = {The Aeronautical Journal},
  number    = {First View},
  publisher = {Cambridge University Press},
  address   = {Cambridge},
  issn      = {0001-9240 (Print)},
  doi       = {10.1017/aer.2023.68},
  pages     = {1 -- 18},
  year      = {2023},
  abstract  = {Even the shortest flight through unknown, cluttered environments requires reliable local path planning algorithms to avoid unforeseen obstacles. The algorithm must evaluate alternative flight paths and identify the best path if an obstacle blocks its way. Commonly, weighted sums are used here. This work shows that weighted Chebyshev distances and factorial achievement scalarising functions are suitable alternatives to weighted sums if combined with the 3DVFH* local path planning algorithm. Both methods considerably reduce the failure probability of simulated flights in various environments. The standard 3DVFH* uses a weighted sum and has a failure probability of 50\% in the test environments. A factorial achievement scalarising function, which minimises the worst combination of two out of four objective functions, reaches a failure probability of 26\%; A weighted Chebyshev distance, which optimises the worst objective, has a failure probability of 30\%. These results show promise for further enhancements and to support broader applicability.},
  language  = {en}
}
@article{UlmerBraunChengetal.2023,
  author    = {Ulmer, Jessica and Braun, Carsten and Cheng, Chi-Tsun and Dowey, Steve and Wollert, J{\"o}rg},
  title     = {A human factors-aware assistance system in manufacturing based on gamification and hardware modularisation},
  series = {International Journal of Production Research},
  journal   = {International Journal of Production Research},
  publisher = {Taylor \& Francis},
  issn      = {0020-7543 (Print)},
  doi       = {10.1080/00207543.2023.2166140},
  year      = {2023},
  abstract  = {Assistance systems have been widely adopted in the manufacturing sector to facilitate various processes and tasks in production environments. However, existing systems are mostly equipped with rigid functional logic and do not provide individual user experiences or adapt to their capabilities. This work integrates human factors in assistance systems by adjusting the hardware and instruction presented to the workers' cognitive and physical demands. A modular system architecture is designed accordingly, which allows a flexible component exchange according to the user and the work task. Gamification, the use of game elements in non-gaming contexts, has been further adopted in this work to provide level-based instructions and personalised feedback. The developed framework is validated by applying it to a manual workstation for industrial assembly routines.},
  language  = {en}
}