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Im Hinblick auf die Klimaziele der Bundesrepublik Deutschland konzentriert sich das Projekt Diggi Twin auf die nachhaltige Gebäudeoptimierung. Grundlage für eine ganzheitliche Gebäudeüberwachung und -optimierung bildet dabei die Digitalisierung und Automation im Sinne eines Smart Buildings. Das interdisziplinäre Projekt der FH Aachen hat das Ziel, ein bestehendes Hochschulgebäude und einen Neubau an klimaneutrale Standards anzupassen. Im Rahmen des Projekts werden bekannte Verfahren, wie das Building Information Modeling (BIM), so erweitert, dass ein digitaler Gebäudezwilling entsteht. Dieser kann zur Optimierung des Gebäudebetriebs herangezogen werden, sowie als Basis für eine Erweiterung des Bewertungssystems Nachhaltiges Bauen (BNB) dienen. Mithilfe von Sensortechnologie und künstlicher Intelligenz kann so ein präzises Monitoring wichtiger Gebäudedaten erfolgen, um ungenutzte Energieeinsparpotenziale zu erkennen und zu nutzen. Das Projekt erforscht und setzt methodische Erkenntnisse zu BIM und digitalen Gebäudezwillingen praxisnah um, indem es spezifische Fragen zur Energie- und Ressourceneffizienz von Gebäuden untersucht und konkrete Lösungen für die Gebäudeoptimierung entwickelt.
Next-generation aircraft designs often incorporate multiple large propellers attached along the wingspan (distributed electric propulsion), leading to highly flexible dynamic systems that can exhibit aeroelastic instabilities. This paper introduces a validated methodology to investigate the aeroelastic instabilities of wing–propeller systems and to understand the dynamic mechanism leading to wing and whirl flutter and transition from one to the other. Factors such as nacelle positions along the wing span and chord and its propulsion system mounting stiffness are considered. Additionally, preliminary design guidelines are proposed for flutter-free wing–propeller systems applicable to novel aircraft designs. The study demonstrates how the critical speed of the wing–propeller systems is influenced by the mounting stiffness and propeller position. Weak mounting stiffnesses result in whirl flutter, while hard mounting stiffnesses lead to wing flutter. For the latter, the position of the propeller along the wing span may change the wing mode shapes and thus the flutter mechanism. Propeller positions closer to the wing tip enhance stability, but pusher configurations are more critical due to the mass distribution behind the elastic axis.
High aerodynamic efficiency requires propellers with high aspect ratios, while propeller sweep potentially reduces noise. Propeller sweep and high aspect ratios increase elasticity and coupling of structural mechanics and aerodynamics, affecting the propeller performance and noise. Therefore, this paper analyzes the influence of elasticity on forward-swept, backward-swept, and unswept propellers in hover conditions. A reduced-order blade element momentum approach is coupled with a one-dimensional Timoshenko beam theory and Farassat's formulation 1A. The results of the aeroelastic simulation are used as input for the aeroacoustic calculation. The analysis shows that elasticity influences noise radiation because thickness and loading noise respond differently to deformations. In the case of the backward-swept propeller, the location of the maximum sound pressure level shifts forward by 0.5 °, while in the case of the forward-swept propeller, it shifts backward by 0.5 °. Therefore, aeroacoustic optimization requires the consideration of propeller deformation.
In order to reduce energy consumption of homes, it is important to make transparent which devices consume how much energy. However, power consumption is often only monitored aggregated at the house energy meter. Disaggregating this power consumption into the contributions of individual devices can be achieved using Machine Learning. Our work aims at making state of the art disaggregation algorithms accessibe for users of the open source home automation platform Home Assistant.
Residential and commercial buildings account for more than one-third of global energy-related greenhouse gas emissions. Integrated multi-energy systems at the district level are a promising way to reduce greenhouse gas emissions by exploiting economies of scale and synergies between energy sources. Planning district energy systems comes with many challenges in an ever-changing environment. Computational modelling established itself as the state-of-the-art method for district energy system planning. Unfortunately, it is still cumbersome to combine standalone models to generate insights that surpass their original purpose. Ideally, planning processes could be solved by using modular tools that easily incorporate the variety of competing and complementing computational models. Our contribution is a vision for a collaborative development and application platform for multi-energy system planning tools at the district level. We present challenges of district energy system planning identified in the literature and evaluate whether this platform can help to overcome these challenges. Further, we propose a toolkit that represents the core technical elements of the platform. Lastly, we discuss community management and its relevance for the success of projects with collaboration and knowledge sharing at their core.
The integration of high temperature thermal energy storages into existing conventional power plants can help to reduce the CO2 emissions of those plants and lead to lower capital expenditures for building energy storage systems, due to the use of synergy effects [1]. One possibility to implement that, is a molten salt storage system with a powerful power-to-heat unit. This paper presents two possible control concepts for the startup of the charging system of such a facility. The procedures are implemented in a detailed dynamic process model. The performance and safety regarding the film temperatures at heat transmitting surfaces are investigated in the process simulations. To improve the accuracy in predicting the film temperatures, CFD simulations of the electrical heater are carried out and the results are merged with the dynamic model. The results show that both investigated control concepts are safe regarding the temperature limits. The gradient controlled startup performed better than the temperature-controlled startup. Nevertheless, there are several uncertainties that need to be investigated further.
Despite the challenges of pioneering molten salt towers (MST), it remains the leading technology in central receiver power plants today, thanks to cost effective storage integration and high cost reduction potential. The limited controllability in volatile solar conditions can cause significant losses, which are difficult to estimate without comprehensive modeling [1]. This paper presents a Methodology to generate predictions of the dynamic behavior of the receiver system as part of an operating assistance system (OAS). Based on this, it delivers proposals if and when to drain and refill the receiver during a cloudy period in order maximize the net yield and quantifies the amount of net electricity gained by this. After prior analysis with a detailed dynamic two-phase model of the entire receiver system, two different reduced modeling approaches where developed and implemented in the OAS. A tailored decision algorithm utilizes both models to deliver the desired predictions efficiently and with appropriate accuracy.
Die IMechE Railway Challenge wird jährlich in Stapleford, Großbritannien ausgetragen. Im Rahmen der Challenge entwickeln und bauen Studierende eine Lokomotive und vergleichen sich in verschiedenen Disziplinen, darunter eine automatisierte Zielbremsung, optimale Energierückgewinnung beim Bremsen und minimale Geräuschemissionen. Neben diesen und weiteren technischen Wettbewerbsdisziplinen treten die Fahrzeuge und die Teams auch in nicht-technischen Disziplinen wie einer Business Case Challenge an.
The eVTOL industry is a rapidly growing mass market expected to start in 2024. eVTOL compete, caused by their predicted missions, with ground-based transportation modes, including mainly passenger cars. Therefore, the automotive and classical aircraft design process is reviewed and compared to highlight advantages for eVTOL development. A special focus is on ergonomic comfort and safety. The need for further investigation of eVTOL’s crashworthiness is outlined by, first, specifying the relevance of passive safety via accident statistics and customer perception analysis; second, comparing the current state of regulation and certification; and third, discussing the advantages of integral safety and applying the automotive safety approach for eVTOL development. Integral safety links active and passive safety, while the automotive safety approach means implementing standardized mandatory full-vehicle crash tests for future eVTOL. Subsequently, possible crash impact conditions are analyzed, and three full-vehicle crash load cases are presented.
To fulfil the CO2 emission reduction targets of the European Union (EU), heavy-duty (HD) trucks need to operate 15% more efficiently by 2025 and 30% by 2030. Their electrification is necessary as conventional HD trucks are already optimized for the long-haul application. The resulting hybrid electric vehicle (HEV) truck gains most of the fuel saving potential by the recuperation of potential energy and its consecutive utilization. The key to utilizing the full potential of HEV-HD trucks is to maximize the amount of recuperated energy and ensure its intelligent usage while keeping the operating point of the internal combustion engine as efficient as possible. To achieve this goal, an intelligent energy management strategy (EMS) based on ECMS is developed for a parallel HEV-HD truck which uses predictive discharge of the battery and adaptive operating strategy regarding the height profile and the vehicle mass. The presented EMS can reproduce the global optimal operating strategy over long phases and lead to a fuel saving potential of up to 2% compared with a heuristic strategy. Furthermore, the fuel saving potential is correlated with the investigated boundary conditions to deepen the understanding of the impact of intelligent EMS for HEV-HD trucks.