Open Access

The paper industry is the industry with the third highest energy consumption in the European Union. Using recycled paper instead of fresh fibers for papermaking is less energy consuming and saves resources. However, adhesive contaminants in recycled paper are particularly problematic since they reduce the quality of the resulting paper-product. To remove as many contaminants and at the same time obtain as many valuable fibres as possible, fine screening systems, consisting of multiple interconnected pressure screens, are used. Choosing the best configuration is a non-trivial task: The screens can be interconnected in several ways, and suitable screen designs as well as operational parameters have to be selected. Additionally, one has to face conflicting objectives. In this paper, we present an approach for the multi-criteria optimization of pressure screen systems based on Mixed-Integer Nonlinear Programming. We specifically focus on a clear representation of the trade-off between different objectives.

Ensuring access to water and sanitation for all is Goal No. 6 of the 17 UN Sustainability Development Goals to transform our world. As one step towards this goal, we present an approach that leverages remote sensing data to plan optimal water supply networks for informal urban settlements. The concept focuses on slums within large urban areas, which are often characterized by a lack of an appropriate water supply. We apply methods of mathematical optimization aiming to find a network describing the optimal supply infrastructure. Hereby, we choose between different decentral and central approaches combining supply by motorized vehicles with supply by pipe systems. For the purposes of illustration, we apply the approach to two small slum clusters in Dhaka and Dar es Salaam. We show our optimization results, which represent the lowest cost water supply systems possible. Additionally, we compare the optimal solutions of the two clusters (also for varying input parameters, such as population densities and slum size development over time) and describe how the result of the optimization depends on the entered remote sensing data.

The development of resilient technical systems is a challenging task, as the system should adapt automatically to unknown disturbances and component failures. To evaluate different approaches for deriving resilient technical system designs, we developed a modular test rig that is based on a pumping system. On the basis of this example system, we present metrics to quantify resilience and an algorithmic approach to improve resilience. This approach enables the pumping system to automatically react on unknown disturbances and to reduce the impact of component failures. In this case, the system is able to automatically adapt its topology by activating additional valves. This enables the system to still reach a minimum performance, even in case of failures. Furthermore, timedependent disturbances are evaluated continuously, deviations from the original state are automatically detected and anticipated in the future. This allows to reduce the impact of future disturbances and leads to a more resilient system behaviour.

The course Physics for Electrical Engineering is part of the curriculum of the bachelor program Electrical Engineering at University of Applied Science Aachen. Before covid-19 the course was conducted in a rather traditional way with all parts (lecture, exercise and lab) face-to-face. This teaching approach changed fundamentally within a week when the covid-19 limitations forced all courses to distance learning. All parts of the course were transformed to pure distance learning including synchronous and asynchronous parts for the lecture, live online-sessions for the exercises and self-paced labs at home. Using these methods, the course was able to impart the required knowledge and competencies. Taking the teacher’s observations of the student’s learning behaviour and engagement, the formal and informal feedback of the students and the results of the exams into account, the new methods are evaluated with respect to effectiveness, sustainability and suitability for competence transfer. Based on this analysis strong and weak points of the concept and countermeasures to solve the weak points were identified. The analysis further leads to a sustainable teaching approach combining synchronous and asynchronous parts with self-paced learning times that can be used in a very flexible manner for different learning scenarios, pure online, hybrid (mixture of online and presence times) and pure presence teaching.

Water supply of high-rise buildings requires pump systems to ensure pressure requirements. The design goals of these systems are energy and cost efficiency, both in terms of fixed cost as well as during operation. In this paper, cost optimal decentralized and tree-shaped water distribution networks are computed, where placements of pumps at different locations in the building are allowed. We propose a branch-and-bound algorithm for solving the corresponding mixed-integer nonlinear program, which exploits problem specific structure and outperforms state-of-the-art solvers. A further desirable feature is that the system is K-resilient, i.e., still able to operate under K pump failures during the use phase. Using a characterization of resilient solutions via a system of inequalities, the branch-and-bound scheme is extended by a separation algorithm to produce cost optimal resilient solutions. This implicitly solves a multilevel optimization problem which contains the computation of worst-case failures. Moreover, using a large set of test instances, the increased energy-efficiency of decentralized networks for the supply of building is shown and properties of resilient layouts are discussed.