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Successful optimization requires an appropriate model of the system under consideration. When selecting a suitable level of detail, one has to consider solution quality as well as the computational and implementation effort. In this paper, we present a MINLP for a pumping system for the drinking water supply of high-rise buildings. We investigate the influence of the granularity of the underlying physical models on the solution quality. Therefore, we model the system with a varying level of detail regarding the friction losses, and conduct an experimental validation of our model on a modular test rig. Furthermore, we investigate the computational effort and show that it can be reduced by the integration of domain-specific knowledge.
Water distribution systems are an essential supply infrastructure for cities. Given that climatic and demographic influences will pose further challenges for these infrastructures in the future, the resilience of water supply systems, i.e. their ability to withstand and recover from disruptions, has recently become a subject of research. To assess the resilience of a WDS, different graph-theoretical approaches exist. Next to general metrics characterizing the network topology, also hydraulic and technical restrictions have to be taken into account. In this work, the resilience of an exemplary water distribution network of a major German city is assessed, and a Mixed-Integer Program is presented which allows to assess the impact of capacity adaptations on its resilience.
To maximize the travel distances of battery electric vehicles such as cars or buses for a given amount of stored energy, their powertrains are optimized energetically. One key part within optimization models for electric powertrains is the efficiency map of the electric motor. The underlying function is usually highly nonlinear and nonconvex and leads to major challenges within a global optimization process. To enable faster solution times, one possibility is the usage of piecewise linearization techniques to approximate the nonlinear efficiency map with linear constraints. Therefore, we evaluate the influence of different piecewise linearization modeling techniques on the overall solution process and compare the solution time and accuracy for methods with and without explicitly used binary variables.
In the study, the process chain of additive manufacturing by means of powder bed fusion will be presented based on the material glass. In order to reliably process components additively, new concepts with different solutions were developed and investigated.
Compared to established metallic materials, the properties of glass materials differ significantly. Therefore, the process control was adapted to the material glass in the investigations. With extensive parameter studies based on various glass powders such as borosilicate glass and quartz glass, scientifically proven results on powder bed fusion of glass are presented. Based on the determination of the particle properties with different methods, extensive investigations are made regarding the melting behavior of glass by means of laser beams. Furthermore, the experimental setup was steadily expanded. In addition to the integration of coaxial temperature measurement and regulation, preheating of the building platform is of major importance. This offers the possibility to perform 3D printing at the transformation temperatures of the glass materials. To improve the component’s properties, the influence of a subsequent heat treatment was also investigated.
The experience gained was incorporated into a new experimental system, which allows a much better exploration of the 3D printing of glass. Currently, studies are being conducted to improve surface texture, building accuracy, and geometrical capabilities using three-dimensional specimen.
The contribution shows the development of research in the field of 3D printing of glass, gives an insight into the machine and process engineering as well as an outlook on the possibilities and applications.
Thematisch widmet sich das Projekt Coolplan- AIR der Fortentwicklung und Feldvalidierung eines Berechnungs- und Auslegungstools zur energieeffizienten Kühlung von Gebäuden mit luftgestützten Systemen. Neben dem Aufbau und der Weiterentwicklung von Simulationsmodellen erfolgen Vermessungen der Gesamtsysteme anhand von Praxisanlagen im Feld. Der Schwerpunkt des Projekts liegt auf der Vermessung, Simulation und Integration rein luftgestützter Kühltechnologien. Im Bereich der Kälteerzeugung wurden Luft‐ Luft‐ Wärmepumpen, Anlagen zur adiabaten Kühlung bzw. offene Kühltürme und VRF‐ Multisplit‐ Systeme (Variable Refrigerant Flow) im Feld bzw. auf dem Teststand der HSD vermessen. Die Komponentenmodelle werden in die Matlab/Simulink‐ Toolbox CARNOT integriert und anschließend auf Basis der zuvor erhaltenen Messdaten validiert.
Einerseits erlauben die Messungen das Betriebsverhalten von Anlagenkomponenten zu analysieren. Andererseits soll mit der Vermessung im Feld geprüft werden, inwieweit die Simulationsmodelle, welche im Vorgängerprojekt aus Prüfstandmessungen entwickelt wurden, auch für größere Geräteleistungen Gültigkeit besitzen. Die entwickelten und implementierten Systeme, bestehend aus verschiedensten Anlagenmodellen und Regelungskomponenten, werden geprüft und dahingehend qualifiziert, dass sie in Standard- Auslegungstools zuverlässig verwendet werden können.
Zusätzlich wird ein energetisches Monitoring eines Hörsaalgebäudes am Campus Jülich durchgeführt, das u. a. zur Validierung der Kühllastberechnungen in gängigen Simulationsmodelle genutzt werden kann.