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Given industrial applications, the costs for the operation and maintenance of a pump system typically far exceed its purchase price. For finding an optimal pump configuration which minimizes not only investment, but life-cycle costs, methods like Technical Operations Research which is based on Mixed-Integer Programming can be applied. However, during the planning phase, the designer is often faced with uncertain input data, e.g. future load demands can only be estimated. In this work, we deal with this uncertainty by developing a chance-constrained two-stage (CCTS) stochastic program. The design and operation of a booster station working under uncertain load demand are optimized to minimize total cost including purchase price, operation cost incurred by energy consumption and penalty cost resulting from water shortage. We find optimized system layouts using a sample average approximation (SAA) algorithm, and analyze the results for different risk levels of water shortage. By adjusting the risk level, the costs and performance range of the system can be balanced, and thus the
system’s resilience can be engineered
Algorithmic design and resilience assessment of energy efficient high-rise water supply systems
(2018)
High-rise water supply systems provide water flow and suitable pressure in all levels of tall buildings. To design such state-of-the-art systems, the consideration of energy efficiency and the anticipation of component failures are mandatory. In this paper, we use Mixed-Integer Nonlinear Programming to compute an optimal placement of pipes and pumps, as well as an optimal control strategy.Moreover, we consider the resilience of the system to pump failures. A resilient system is able to fulfill a predefined minimum functionality even though components fail or are restricted in their normal usage. We present models to measure and optimize the resilience. To demonstrate our approach, we design and analyze an optimal resilient decentralized water supply system inspired by a real-life hotel building.
Resilience as a concept has found its way into different disciplines to describe the ability of an individual or system to withstand and adapt to changes in its environment. In this paper, we provide an overview of the concept in different communities and extend it to the area of mechanical engineering. Furthermore, we present metrics to measure resilience in technical systems and illustrate them by applying them to load-carrying structures. By giving application examples from the Collaborative Research Centre (CRC) 805, we show how the concept of resilience can be used to control uncertainty during different stages of product life.
Das anhaltende Wachstum wissenschaftlicher Veröffentlichungen wirft die Fragestellung auf, wie Literaturana-lysen im Rahmen von Forschungsprozessen digitalisiert und somit produktiver realisiert werden können. Insbesondere in informationstechnischen Fachgebieten ist die Forschungspraxis durch ein rasant wachsendes Publikationsaufkommen gekennzeichnet. Infolgedessen bietet sich der Einsatz von Methoden der Textanalyse (Text Analytics) an, die Textdaten automatisch vorbereiten und verarbeiten können. Erkenntnisse entstehen dabei aus Analysen von Wortarten und Subgruppen, Korrelations- sowie Zeitreihenanalysen. Dieser Beitrag stellt die Konzeption und Realisierung eines Prototypen vor, mit dem Anwender bibliographische Daten aus der etablierten Literaturdatenbank EBSCO Discovery Service mithilfe textanalytischer Methoden erschließen können. Der Prototyp basiert auf dem Analysesystem IBM Watson Explorer, das Hochschulen lizenzkostenfrei zur Verfügung steht. Potenzielle Adressaten des Prototypen sind Forschungseinrichtungen, Beratungsunternehmen sowie Entscheidungsträger in Politik und Unternehmenspraxis.
The Carologistics team participates in the RoboCup Logistics League for the seventh year. The RCLL requires precise vision,
manipulation and path planning, as well as complex high-level decision
making and multi-robot coordination. We outline our approach with an
emphasis on recent modifications to those components.
The team members in 2018 are David Bosen, Christoph Gollok, Mostafa
Gomaa, Daniel Habering, Till Hofmann, Nicolas Limpert, Sebastian Schönitz,
Morian Sonnet, Carsten Stoffels, and Tarik Viehmann.
This paper is based on the last year’s team description.