TY - CHAP A1 - Altherr, Lena A1 - Ederer, Thorsten A1 - Schänzle, Christian A1 - Lorenz, Ulf A1 - Pelz, Peter F. T1 - Algorithmic system design using scaling and affinity laws T2 - Operations Research Proceedings 2015 N2 - Energy-efficient components do not automatically lead to energy-efficient systems. Technical Operations Research (TOR) shifts the focus from the single component to the system as a whole and finds its optimal topology and operating strategy simultaneously. In previous works, we provided a preselected construction kit of suitable components for the algorithm. This approach may give rise to a combinatorial explosion if the preselection cannot be cut down to a reasonable number by human intuition. To reduce the number of discrete decisions, we integrate laws derived from similarity theory into the optimization model. Since the physical characteristics of a production series are similar, it can be described by affinity and scaling laws. Making use of these laws, our construction kit can be modeled more efficiently: Instead of a preselection of components, it now encompasses whole model ranges. This allows us to significantly increase the number of possible set-ups in our model. In this paper, we present how to embed this new formulation into a mixed-integer program and assess the run time via benchmarks. We present our approach on the example of a ventilation system design problem. KW - Optimal Topology KW - Piecewise Linearization KW - Ventilation System KW - Similarity Theory Y1 - 2017 SN - 978-3-319-42901-4 SN - 978-3-319-42902-1 U6 - https://doi.org/10.1007/978-3-319-42902-1 N1 - International Conference of the German, Austrian and Swiss Operations Research Societies (GOR, ÖGOR, SVOR/ASRO), University of Vienna, Austria, September 1-4, 2015 SP - 605 EP - 611 PB - Springer CY - Cham ER - TY - CHAP A1 - Altherr, Lena A1 - Ederer, Thorsten A1 - Vergé, Angela A1 - Pelz, Peter F. T1 - Algorithmische Struktursynthese eines hydrostatischen Getriebes T2 - Antriebssysteme 2015 : Elektrik, Mechanik, Fluidtechnik in der Anwendung Y1 - 2015 SN - 978-3-18-092268-3 N1 - Antriebssysteme 2015 - Elektrik, Mechanik, Fluidtechnik in der Anwendung. VDI/VDE-Fachtagung. 11.11.15-12.11.15, Aachen. Veröffentlicht in der Reihe VDI-Berichte, Bandnummer 2268. SP - 145 EP - 155 PB - VDI-Verlag CY - Düsseldorf ER - TY - CHAP A1 - Schänzle, Christian A1 - Altherr, Lena A1 - Ederer, Thorsten A1 - Lorenz, Ulf A1 - Pelz, Peter F. T1 - As good as it can be: Ventilation system design by a combined scaling and discrete optimization method T2 - Proceedings of FAN 2015 N2 - The understanding that optimized components do not automatically lead to energy-efficient systems sets the attention from the single component on the entire technical system. At TU Darmstadt, a new field of research named Technical Operations Research (TOR) has its origin. It combines mathematical and technical know-how for the optimal design of technical systems. We illustrate our optimization approach in a case study for the design of a ventilation system with the ambition to minimize the energy consumption for a temporal distribution of diverse load demands. By combining scaling laws with our optimization methods we find the optimal combination of fans and show the advantage of the use of multiple fans. Y1 - 2015 N1 - Proceedings of FAN 2015, Lyon (France), 15 – 17 April 2015 SP - 1 EP - 11 ER - TY - CHAP A1 - Altherr, Lena A1 - Ederer, Thorsten A1 - Farnetane, Lucas S. A1 - Pöttgen, Philipp A1 - Vergé, Angela A1 - Pelz, Peter F. T1 - Multicriterial design of a hydrostatic transmission system via mixed-integer programming T2 - Operations Research Proceedings 2015 N2 - In times of planned obsolescence the demand for sustainability keeps growing. Ideally, a technical system is highly reliable, without failures and down times due to fast wear of single components. At the same time, maintenance should preferably be limited to pre-defined time intervals. Dispersion of load between multiple components can increase a system’s reliability and thus its availability inbetween maintenance points. However, this also results in higher investment costs and additional efforts due to higher complexity. Given a specific load profile and resulting wear of components, it is often unclear which system structure is the optimal one. Technical Operations Research (TOR) finds an optimal structure balancing availability and effort. We present our approach by designing a hydrostatic transmission system. Y1 - 2017 SN - 978-3-319-42901-4 SN - 978-3-319-42902-1 U6 - https://doi.org/10.1007/978-3-319-42902-1_41 N1 - International Conference of the German, Austrian and Swiss Operations Research Societies (GOR, ÖGOR, SVOR/ASRO), University of Vienna, Austria, September 1-4, 2015 SP - 301 EP - 307 PB - Springer CY - Cham ER - TY - CHAP A1 - Büsgen, André A1 - Klöser, Lars A1 - Kohl, Philipp A1 - Schmidts, Oliver A1 - Kraft, Bodo A1 - Zündorf, Albert T1 - Exploratory analysis of chat-based black market profiles with natural language processing T2 - Proceedings of the 11th International Conference on Data Science, Technology and Applications N2 - Messenger apps like WhatsApp or Telegram are an integral part of daily communication. Besides the various positive effects, those services extend the operating range of criminals. Open trading groups with many thousand participants emerged on Telegram. Law enforcement agencies monitor suspicious users in such chat rooms. This research shows that text analysis, based on natural language processing, facilitates this through a meaningful domain overview and detailed investigations. We crawled a corpus from such self-proclaimed black markets and annotated five attribute types products, money, payment methods, user names, and locations. Based on each message a user sends, we extract and group these attributes to build profiles. Then, we build features to cluster the profiles. Pretrained word vectors yield better unsupervised clustering results than current state-of-the-art transformer models. The result is a semantically meaningful high-level overview of the user landscape of black market chatrooms. Additionally, the extracted structured information serves as a foundation for further data exploration, for example, the most active users or preferred payment methods. KW - Clustering KW - Natural Language Processing KW - Information Extraction KW - Profile Extraction KW - Text Mining Y1 - 2022 SN - 978-989-758-583-8 U6 - https://doi.org/10.5220/0011271400003269 SN - 2184-285X N1 - 11th International Conference on Data Science, Technology and Applications DATA - Volume 1, 83-94, 2022, Lisbon, Portugal SP - 83 EP - 94 ER - TY - CHAP A1 - Ostkotte, Sebastian A1 - Peters, Constantin A1 - Hüning, Felix A1 - Bragard, Michael T1 - Design, implementation and verification of an rotational incremental position encoder based on the magnetic Wiegand effect T2 - 2022 ELEKTRO (ELEKTRO) N2 - This paper covers the use of the magnetic Wiegand effect to design an innovative incremental encoder. First, a theoretical design is given, followed by an estimation of the achievable accuracy and an optimization in open-loop operation. Finally, a successful experimental verification is presented. For this purpose, a permanent magnet synchronous machine is controlled in a field-oriented manner, using the angle information of the prototype. KW - Position Encoder KW - Rotational Encoder KW - Wiegand Effect KW - Angle Sensor KW - Incremental Encoder Y1 - 2022 SN - 978-1-6654-6726-1 SN - 978-1-6654-6727-8 U6 - https://doi.org/10.1109/ELEKTRO53996.2022.9803477 SN - 2691-0616 N1 - 2022 ELEKTRO (ELEKTRO), 23-26 Mai 2022, Krakow, Poland. PB - IEEE ER - TY - CHAP A1 - Lorenz, Imke-Sophie A1 - Altherr, Lena A1 - Pelz, Peter F. T1 - Resilience enhancement of critical infrastructure – graph-theoretical resilience analysis of the water distribution system in the German city of Darmstadt T2 - 14th WCEAM Proceedings N2 - Water suppliers are faced with the great challenge of achieving high-quality and, at the same time, low-cost water supply. Since climatic and demographic influences will pose further challenges in the future, the resilience enhancement of water distribution systems (WDS), i.e. the enhancement of their capability to withstand and recover from disturbances, has been in particular focus recently. To assess the resilience of WDS, graph-theoretical metrics have been proposed. In this study, a promising approach is first physically derived analytically and then applied to assess the resilience of the WDS for a district in a major German City. The topology based resilience index computed for every consumer node takes into consideration the resistance of the best supply path as well as alternative supply paths. This resistance of a supply path is derived to be the dimensionless pressure loss in the pipes making up the path. The conducted analysis of a present WDS provides insight into the process of actively influencing the resilience of WDS locally and globally by adding pipes. The study shows that especially pipes added close to the reservoirs and main branching points in the WDS result in a high resilience enhancement of the overall WDS. KW - Resilient infrastructure KW - Resilience assessment KW - Resilience metric graph theory KW - Water distribution system KW - Case study Y1 - 2020 SN - 978-3-030-64228-0 SN - 978-3-030-64227-3 U6 - https://doi.org/10.1007/978-3-030-64228-0_13 N1 - 14th WCEAM Proceedings. World Congress on Engineering Asset Management, 28-31 July 2019, Singapore Part of the Lecture Notes in Mechanical Engineering book series (LNME) SP - 137 EP - 149 PB - Springer CY - Cham ER - TY - CHAP A1 - Schänzle, Christian A1 - Altherr, Lena A1 - Ederer, Thorsten A1 - Pelz, Peter T1 - TOR – Towards the energetically optimal ventilation system KW - Energy KW - Efficiency KW - Ventilation System KW - Discrete Optimisation KW - TGA Y1 - 2015 N1 - EST 2015, Karlsruhe, 19-21 Mai 2015 ER - TY - CHAP A1 - Nikolovski, Gjorgji A1 - Reke, Michael A1 - Elsen, Ingo A1 - Schiffer, Stefan T1 - Machine learning based 3D object detection for navigation in unstructured environments T2 - 2021 IEEE Intelligent Vehicles Symposium Workshops (IV Workshops) N2 - In this paper we investigate the use of deep neural networks for 3D object detection in uncommon, unstructured environments such as in an open-pit mine. While neural nets are frequently used for object detection in regular autonomous driving applications, more unusual driving scenarios aside street traffic pose additional challenges. For one, the collection of appropriate data sets to train the networks is an issue. For another, testing the performance of trained networks often requires tailored integration with the particular domain as well. While there exist different solutions for these problems in regular autonomous driving, there are only very few approaches that work for special domains just as well. We address both the challenges above in this work. First, we discuss two possible ways of acquiring data for training and evaluation. That is, we evaluate a semi-automated annotation of recorded LIDAR data and we examine synthetic data generation. Using these datasets we train and test different deep neural network for the task of object detection. Second, we propose a possible integration of a ROS2 detector module for an autonomous driving platform. Finally, we present the performance of three state-of-the-art deep neural networks in the domain of 3D object detection on a synthetic dataset and a smaller one containing a characteristic object from an open-pit mine. KW - 3D object detection KW - LiDAR KW - autonomous driving KW - Deep learning KW - Three-dimensional displays Y1 - 2021 SN - 978-1-6654-7921-9 U6 - https://doi.org/10.1109/IVWorkshops54471.2021.9669218 N1 - 2021 IEEE Intelligent Vehicles Symposium Workshops (IV Workshops), 11-17 July 2021, Nagoya, Japan. SP - 236 EP - 242 PB - IEEE ER - TY - CHAP A1 - Amir, Malik A1 - Bauckhage, Christian A1 - Chircu, Alina A1 - Czarnecki, Christian A1 - Knopf, Christian A1 - Piatkowski, Nico A1 - Sultanow, Eldar T1 - What can we expect from quantum (digital) twins? T2 - Wirtschaftsinformatik 2022 Proceedings N2 - Digital twins enable the modeling and simulation of real-world entities (objects, processes or systems), resulting in improvements in the associated value chains. The emerging field of quantum computing holds tremendous promise forevolving this virtualization towards Quantum (Digital) Twins (QDT) and ultimately Quantum Twins (QT). The quantum (digital) twin concept is not a contradiction in terms - but instead describes a hybrid approach that can be implemented using the technologies available today by combining classicalcomputing and digital twin concepts with quantum processing. This paperpresents the status quo of research and practice on quantum (digital) twins. It alsodiscuses their potential to create competitive advantage through real-timesimulation of highly complex, interconnected entities that helps companies better address changes in their environment and differentiate their products andservices. KW - Artificial Intelligence KW - Digital Twin Evolution KW - Machine Learning KW - Quantum Computing KW - Quantum Machine Learning Y1 - 2022 N1 - 17. Internationale Tagung Wirtschaftsinformatik, 21. – 23. Februar 2022, Nürnberg (online) SP - 1 EP - 14 PB - AIS Electronic Library (AISeL) ER -