TY - JOUR A1 - Bergmann, Ole A1 - Möhren, Felix A1 - Braun, Carsten A1 - Janser, Frank T1 - On the influence of elasticity on swept propeller noise JF - AIAA SCITECH 2023 Forum N2 - 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. Y1 - 2023 U6 - http://dx.doi.org/10.2514/6.2023-0210 N1 - Session: Propeller, Open Rotor, and Rotorcraft Noise II AIAA SCITECH 2023 Forum, 23-27 January 2023, National Harbor, MD & Online PB - AIAA ER - TY - CHAP A1 - Grund, Raphael M. A1 - Altherr, Lena ED - Reiff-Stephan, Jörg ED - Jäkel, Jens ED - Schwarz, André T1 - Development of an open source energy disaggregation tool for the home automation platform Home Assistant T2 - Tagungsband AALE 2023 : mit Automatisierung gegen den Klimawandel N2 - 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. KW - Home Automation Platform KW - Home Assistant KW - Open Source KW - Machine Learning KW - Energy Disaggregation Y1 - 2023 SN - 978-3-910103-01-6 U6 - http://dx.doi.org/10.33968/2023.02 N1 - 19. AALE-Konferenz. Luxemburg, 08.03.-10.03.2023. BTS Connected Buildings & Cities Luxemburg (Tagungsband unter https://doi.org/10.33968/2023.01) SP - 11 EP - 20 PB - le-tex publishing services GmbH CY - Leipzig ER - TY - CHAP A1 - Lahrs, Lennart A1 - Krisam, Pierre A1 - Herrmann, Ulf T1 - Envisioning a collaborative energy system planning platform for the energy transition at the district level T2 - The 36th International Conference on Efficiency, Cost, Optimization, Simulation and Environmental Impact of Energy Systems N2 - 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. KW - Energy system planning KW - District energy planning platform KW - District data model KW - Renewable energy integration Y1 - 2023 U6 - http://dx.doi.org/10.52202/069564-0284 N1 - 25-30 JUNE, 2023, Las Palmas de Gran Canaria, Spain SP - 3163 EP - 3170 PB - Procedings of ECOS 2023 ER - TY - CHAP A1 - Schulte, Jonas A1 - Schwager, Christian A1 - Noureldin, Kareem A1 - May, Martin A1 - Teixeira Boura, Cristiano José A1 - Herrmann, Ulf T1 - Gradient controlled startup procedure of a molten-salt power-to-heat energy storage plant based on dynamic process simulation T2 - SolarPACES: Solar Power & Chemical Energy Systems N2 - 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. KW - Power plants KW - Energy storage KW - Associated liquids Y1 - 2023 SN - 978-0-7354-4623-6 U6 - http://dx.doi.org/10.1063/5.0148741 SN - 1551-7616 (online) SN - 0094-243X (print) N1 - 27th International Conference on Concentrating Solar Power and Chemical Energy Systems 27 September–1 October 2021 Online IS - 2815 / 1 PB - AIP conference proceedings / American Institute of Physics CY - Melville, NY ER - TY - CHAP A1 - Schwager, Christian A1 - Angele, Florian A1 - Schwarzbözl, Peter A1 - Teixeira Boura, Cristiano José A1 - Herrmann, Ulf T1 - Model predictive assistance for operational decision making in molten salt receiver systems T2 - SolarPACES: Solar Power & Chemical Energy Systems N2 - 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. KW - Power plants KW - Associated liquids KW - Decision theory KW - Electrochemistry Y1 - 2023 SN - 978-0-7354-4623-6 U6 - http://dx.doi.org/10.1063/5.0151514 SN - 1551-7616 (online) SN - 0094-243X (print) N1 - 27th International Conference on Concentrating Solar Power and Chemical Energy Systems 27 September–1 October 2021 Online IS - 2815 / 1 PB - AIP conference proceedings / American Institute of Physics CY - Melville, NY ER - TY - JOUR A1 - Schulze, Sven A1 - Feyerl, Günter A1 - Pischinger, Stefan T1 - Advanced ECMS for hybrid electric heavy-duty trucks with predictive battery discharge and adaptive operating strategy under real driving conditions JF - Energies N2 - 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. KW - Energy management strategies KW - ECMS KW - CO2 emission reduction targets KW - Driving cycle recognition KW - Predictive battery discharge Y1 - 2023 U6 - http://dx.doi.org/10.3390/en16135171 SN - 1996-1073 N1 - The article belongs to the Special Issue "Energy Management Strategies of Electrified Vehicles toward the Real-World Driving". VL - 16 IS - 13 PB - MDPI CY - Basel ER - TY - JOUR A1 - Fayyazi, Mojgan A1 - Sardar, Paramjotsingh A1 - Thomas, Sumit Infent A1 - Daghigh, Roonak A1 - Jamali, Ali A1 - Esch, Thomas A1 - Kemper, Hans A1 - Langari, Reza A1 - Khayyam, Hamid T1 - Artificial intelligence/machine learning in energy management systems, control, and optimization of hydrogen fuel cell vehicles N2 - Environmental emissions, global warming, and energy-related concerns have accelerated the advancements in conventional vehicles that primarily use internal combustion engines. Among the existing technologies, hydrogen fuel cell electric vehicles and fuel cell hybrid electric vehicles may have minimal contributions to greenhouse gas emissions and thus are the prime choices for environmental concerns. However, energy management in fuel cell electric vehicles and fuel cell hybrid electric vehicles is a major challenge. Appropriate control strategies should be used for effective energy management in these vehicles. On the other hand, there has been significant progress in artificial intelligence, machine learning, and designing data-driven intelligent controllers. These techniques have found much attention within the community, and state-of-the-art energy management technologies have been developed based on them. This manuscript reviews the application of machine learning and intelligent controllers for prediction, control, energy management, and vehicle to everything (V2X) in hydrogen fuel cell vehicles. The effectiveness of data-driven control and optimization systems are investigated to evolve, classify, and compare, and future trends and directions for sustainability are discussed. KW - optimization system KW - intelligent control KW - fuel cell vehicle KW - machine learning KW - artificial intelligence KW - intelligent energy management Y1 - 2023 U6 - http://dx.doi.org/10.3390/su15065249 N1 - This article belongs to the Special Issue "Circular Economy and Artificial Intelligence" VL - 15 IS - 6 SP - 38 PB - MDPI CY - Basel ER - TY - BOOK A1 - Janser, Frank A1 - Havermann, Marc A1 - Hoeveler, Bastian A1 - Hertz, Cyril A1 - Bergmann, Ole T1 - Strömungslehre und Aerodynamik : inkompressible Profile und Tragflügelaerodynamik, Band 2 N2 - Das vorliegende Buch dient als Grundlage für die Bachelor- und Master-Ausbildung von Studierenden im Fachgebiet Strömungslehre und Aerodynamik. Im hier behandelten Teilbereich der inkompressiblen Profile und Tragflügelaerodynamik werden schwerpunktmäßig die folgenden Themen besprochen: - Profilaerodynamik - Tragflügelaerodynamik - Flugzeugpolare - Methoden zur Flugbereichserweiterung - Schwebeschub und Schwebeleistung - Propellerblattaerodynamik - Numerische Methoden zur Tragflügelberechnung Y1 - 2023 SN - 978-3-8107-0261-6 PB - Mainz CY - Aachen ET - 4. Auflage ER - TY - CHAP A1 - Neth, Jannik A1 - Schuba, Marko A1 - Brodkorb, Karsten A1 - Neugebauer, Georg A1 - Höner, Tim A1 - Hack, Sacha T1 - Digital forensics triage app for android T2 - ARES '23: Proceedings of the 18th International Conference on Availability, Reliability and Security N2 - Digital forensics of smartphones is of utmost importance in many criminal cases. As modern smartphones store chats, photos, videos etc. that can be relevant for investigations and as they can have storage capacities of hundreds of gigabytes, they are a primary target for forensic investigators. However, it is exactly this large amount of data that is causing problems: extracting and examining the data from multiple phones seized in the context of a case is taking more and more time. This bears the risk of wasting a lot of time with irrelevant phones while there is not enough time left to analyze a phone which is worth examination. Forensic triage can help in this case: Such a triage is a preselection step based on a subset of data and is performed before fully extracting all the data from the smartphone. Triage can accelerate subsequent investigations and is especially useful in cases where time is essential. The aim of this paper is to determine which and how much data from an Android smartphone can be made directly accessible to the forensic investigator – without tedious investigations. For this purpose, an app has been developed that can be used with extremely limited storage of data in the handset and which outputs the extracted data immediately to the forensic workstation in a human- and machine-readable format. KW - Android KW - Digital triage KW - Triage-app Y1 - 2023 SN - 9798400707728 U6 - http://dx.doi.org/10.1145/3600160.3605017 N1 - ARES 2023: The 18th International Conference on Availability, Reliability and Security. August 29 - September 1, 2023. Benevento, Italy. PB - ACM ER - TY - JOUR A1 - Thoma, Andreas A1 - Thomessen, Karolin A1 - Gardi, Alessandro A1 - Fisher, A. A1 - Braun, Carsten T1 - Prioritising paths: An improved cost function for local path planning for UAV in medical applications JF - The Aeronautical Journal N2 - Even the shortest flight through unknown, cluttered environments requires reliable local path planning algorithms to avoid unforeseen obstacles. The algorithm must evaluate alternative flight paths and identify the best path if an obstacle blocks its way. Commonly, weighted sums are used here. This work shows that weighted Chebyshev distances and factorial achievement scalarising functions are suitable alternatives to weighted sums if combined with the 3DVFH* local path planning algorithm. Both methods considerably reduce the failure probability of simulated flights in various environments. The standard 3DVFH* uses a weighted sum and has a failure probability of 50% in the test environments. A factorial achievement scalarising function, which minimises the worst combination of two out of four objective functions, reaches a failure probability of 26%; A weighted Chebyshev distance, which optimises the worst objective, has a failure probability of 30%. These results show promise for further enhancements and to support broader applicability. KW - Path planning KW - Cost function KW - Multi-objective optimization Y1 - 2023 U6 - http://dx.doi.org/10.1017/aer.2023.68 SN - 0001-9240 (Print) SN - 2059-6464 (Online) IS - First View SP - 1 EP - 18 PB - Cambridge University Press CY - Cambridge ER -