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Drawing off the technical flexibility of building polygeneration systems to support a rapidly expanding renewable electricity grid requires the application of advanced controllers like model predictive control (MPC) that can handle multiple inputs and outputs, uncertainties in forecast data, and plant constraints amongst other features. In this original work, an economic-MPC-based optimal scheduling of a real-world building energy system is demonstrated and its performance is evaluated against a conventional controller. The demonstration includes the steps to integrate an optimisation-based supervisory controller into a standard building automation and control system with off-the-shelf HVAC components and usage of state-of-art algorithms for solving complex nonlinear mixed integer optimal control problems. With the MPC, quantitative benefits in terms of 6–12% demand-cost savings and qualitative benefits in terms of better controller adaptability and hardware-friendly operation are identified. Further research potential for improving the MPC framework in terms of field-level stability, minimising constraint violations, and inter-system communication for its deployment in a prosumer-network is also identified.
In this paper, the Bauschinger effect and latent hardening of single crystals are assessed in finite element calculations using a single crystal plasticity model with kinematic hardening. To this end, results of cyclic micro-bending experiments on single crystal Alloy 718 in different crystal orientations (single slip and multi slip) with respect to the loading direction are used to determine the slip system related material properties of the single crystal plasticity model. Two kinematic hardening laws are considered: a kinematic hardening law describing latent hardening and a kinematic hardening law without latent hardening. For the determination of material properties for both hardening laws, a gradient-based optimization method is used. The results show that the different strength levels observed for micro-bending tests on different crystal orientations can only be described with latent kinematic hardening well, whereas the pronounced Bauschinger effect is described well by both kinematic hardening laws. It is concluded that cyclic micro-bending experiments on single crystals using different crystal orientations give an appropriate data base for the determination of the slip system related material properties of the single crystal plasticity model with latent kinematic hardening.
As PV enters the terawatt era, reliability, sustainability and low carbon footprint of solar modules are key requirements. The N.I.C.E.TM technology from Apollon Solar is a good candidate for significant improvements in these areas. As the second-generation pilot line is now functional with IEC certification underway, we present a holistic assessment of N.I.C.E.TM technology compared with conventional module technology with encapsulant. This includes electrical performance and cost/consumables, reliability, and degradation mechanisms as well as sustainability aspects. In addition, the new generation of N.I.C.E.-wire modules are presented that use thin round Cu wires instead of flat ribbons for interconnection. This candidate technology for an alternative to the Smart Wire Connection Technology (SWCT) is investigated experimentally as well as via numerical simulations.
The isolation measures adopted during the COVID-19 pandemic brought light to discussions related to the importance of meaningful social relationships as a basic need to human well-being. But even before the pandemic outbreak in the years 2020 and 2021, organizations and scholars were already drawing attention to the growing numbers related to lonely people in the world (World Economic Forum, 2019). Loneliness is an emotional distress caused by the lack of meaningful social connections, which affects people worldwide across all age groups, mainly young adults (Rook, 1984). The use of digital technologies has gained prominence as a means of alleviating the distress. As an example, studies have shown the benefits of using digital games both to stimulate social interactions (Steinfield, Ellison & Lampe, 2008) and to enhance the effects of digital interventions for mental health treatments, through gamification (Fleming et al., 2017). It is with these aspects in mind that the gamified app Noneliness was designed with the intention of reducing loneliness rates among young students at a German university. In addition to sharing the related works that supported the application development, this chapter also presents the aspects considered for the resource's design, its main functionalities, and the preliminary results related to the reduction of loneliness in the target audience.
We aim to debate and eventually be able to carefully judge how realistic the following statement of a young computer scientist is: “I would like to become an ethical correctly acting offensive cybersecurity expert”. The objective of this article is not to judge what is good and what is wrong behavior nor to present an overall solution to ethical dilemmas. Instead, the goal is to become aware of the various personal moral dilemmas a security expert may face during his work life. For this, a total of 14 cybersecurity students from HS Offenburg were asked to evaluate several case studies according to different ethical frameworks. The results and particularities are discussed, considering different ethical frameworks. We emphasize, that different ethical frameworks can lead to different preferred actions and that the moral understanding of the frameworks may differ even from student to student.
Sweaty has already participated several times in RoboCup soccer competitions (Adult Size). Now the work is focused on stabilizing the gait. Moreover, we would like to overcome the constraints of a ZMP-algorithm that has a horizontal footplate as precondition for the simplification of the equations. In addition we would like to switch between impedance and position control with a fuzzy-like algorithm that might help to minimize jerks when Sweaty’s feet touch the ground.
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Mit dem Klimaschutzgesetz 2021 wurden von der Bundesregierung die Klimaschutzvorgaben verschärft und die Treibhausgasneutralität bis 2045 als Ziel verankert. Zur Erreichung dieses ambitionierten Ziels ist es notwendig, im Bereich der Mobilität weitgehend von Verbrennungsmotoren mit fossilen Kraftstoffen auf Elektromobilität mit regenerativ erzeugtem Strom umzusteigen. Dabei ist die zügige Bereitstellung einer ausreichenden Ladeinfrastruktur für die Elektrofahrzeuge eine große Herausforderung. Neben der Installation einer ausreichend großen Zahl von Ladepunkten selbst besteht die Herausforderung darin, diese in das bestehende Verteilungsnetz zu integrieren bzw. das Verteilungsnetz so auszubauen, dass weiter ein sicherer Netzbetrieb gewährleistet werden kann. Dabei sind insbesondere Lösungen gefragt, bei denen der Ausbau der Ladeinfrastruktur und der Netzbetriebsmittel durch intelligentes Management des Ladens so gering wie möglich gehalten wird, indem vorhandene oder neu zu installierender Hardware möglichst effizient genutzt wird.
Hier setzte das Projekt „Intelligente Ladeinfrastruktur für Elektrofahrzeuge auf dem Parkplatz der Hochschule Offenburg (INTLOG)“ (Projektlaufzeit 15.11.2020 – 30.09.2022) an. Inhalt des Projekts war es, einen Ladepark für den Parkplatz der Hochschule Offenburg mit 20 Ladepunkten à 11 kW und somit einer Gesamtladeleistung von 220 kW an einen vorhandenen Ortsnetztransformator mit 200 kW Nennleistung anzuschließen, der aber bereits von anderen Verbrauchern genutzt wurde. Das übergeordnete Ziel war es also, eine Ladeinfrastruktur von maßgeblichem Umfang in die bestehende Netzinfrastruktur ohne zusätzlichen Ausbau zu integrieren.
Dabei wurden zukunftsweisende Technologien genutzt und weiterentwickelt sowie teilweise in Praxis, im Labor und in der Computersimulation demonstriert.
Generative machine learning models for creative purposes play an increasingly prominent role in the field of dance and technology. A particularly popular approach is the use of such models for generating synthetic motions. Such motions can either serve as source of ideation for choreographers or control an artificial dancer that acts as improvisation partner for human dancers. Several examples employ autoencoder-based deep-learning architectures that have been trained on motion capture recordings of human dancers. Synthetic motions are then generated by navigating the autoencoder's latent space. This paper proposes an alternative approach of using an autoencoder for creating synthetic motions. This approach controls the generation of synthetic motions on the level of the motion itself rather than its encoding. Two different methods are presented that follow this principle. Both methods are based on the interactive control of a single joint of an artificial dancer while the other joints remain under the control of the autoencoder. The first method combines the control of the orientation of a joint with iterative autoencoding. The second method combines the control of the target position of a joint with forward kinematics and the application of latent difference vectors. As illustrative example of an artistic application, this latter method is used for an artificial dancer that plays a digital instrument. The paper presents the implementation of these two methods and provides some preliminary results.