TY - CHAP A1 - Veettil, Yadu Krishna Morassery A1 - Rakshit, Shantam A1 - Schopen, Oliver A1 - Kemper, Hans A1 - Esch, Thomas A1 - Shabani, Bahman ED - Bin Abdollah, Mohd Fadzli ED - Amiruddin, Hilmi ED - Singh, Amrik Singh Phuman ED - Munir, Fudhail Abdul ED - Ibrahim, Asriana T1 - Automated Control System Strategies to Ensure Safety of PEM Fuel Cells Using Kalman Filters T2 - Proceedings of the 7th International Conference and Exhibition on Sustainable Energy and Advanced Materials (ICE-SEAM 2021), Melaka, Malaysia N2 - Having well-defined control strategies for fuel cells, that can efficiently detect errors and take corrective action is critically important for safety in all applications, and especially so in aviation. The algorithms not only ensure operator safety by monitoring the fuel cell and connected components, but also contribute to extending the health of the fuel cell, its durability and safe operation over its lifetime. While sensors are used to provide peripheral data surrounding the fuel cell, the internal states of the fuel cell cannot be directly measured. To overcome this restriction, Kalman Filter has been implemented as an internal state observer. Other safety conditions are evaluated using real-time data from every connected sensor and corrective actions automatically take place to ensure safety. The algorithms discussed in this paper have been validated thorough Model-in-the-Loop (MiL) tests as well as practical validation at a dedicated test bench. KW - control system KW - PEM fuel cells KW - Kalman filter Y1 - 2022 SN - 978-981-19-3178-9 SN - 978-981-19-3179-6 (E-Book) U6 - http://dx.doi.org/10.1007/978-981-19-3179-6_55 SN - 2195-4356 N1 - The 7th International Conference and Exhibition on Sustainable Energy and Advanced Material (ICE-SEAM 2021) was organized by Universiti Teknikal Malaysia Melaka (UTeM), Malaysia, in association with the Universitas Sebelas Maret (UNS), Indonesia, on 23 November 2021 SP - 296 EP - 299 PB - Springer Nature CY - Singapore ER - TY - CHAP A1 - Ayed, Anis Haj A1 - Striegan, Constantin J. D. A1 - Kusterer, Karsten A1 - Funke, Harald A1 - Kazari, M. A1 - Horikawa, Atsushi A1 - Okada, Kunio T1 - Automated design space exploration of the hydrogen fueled "Micromix" combustor technology N2 - Combined with the use of renewable energy sources for its production, Hydrogen represents a possible alternative gas turbine fuel for future low emission power generation. Due to its different physical properties compared to other fuels such as natural gas, well established gas turbine combustion systems cannot be directly applied for Dry Low NOx (DLN) Hydrogen combustion. This makes the development of new combustion technologies an essential and challenging task for the future of hydrogen fueled gas turbines. The newly developed and successfully tested “DLN Micromix” combustion technology offers a great potential to burn hydrogen in gas turbines at very low NOx emissions. Aiming to further develop an existing burner design in terms of increased energy density, a redesign is required in order to stabilise the flames at higher mass flows and to maintain low emission levels. For this purpose, a systematic design exploration has been carried out with the support of CFD and optimisation tools to identify the interactions of geometrical and design parameters on the combustor performance. Aerodynamic effects as well as flame and emission formation are observed and understood time- and cost-efficiently. Correlations between single geometric values, the pressure drop of the burner and NOx production have been identified as a result. This numeric methodology helps to reduce the effort of manufacturing and testing to few designs for single validation campaigns, in order to confirm the flame stability and NOx emissions in a wider operating condition field. Y1 - 2017 N1 - Proceedings of the 1st Global Power and Propulsion Forum GPPF 2017, Jan 16-18, 2017, Zurich, Switzerland SP - 1 EP - 8 ER - TY - JOUR A1 - Gorzalka, Philip A1 - Schmiedt, Jacob Estevam A1 - Schorn, Christian T1 - Automated Generation of an Energy Simulation Model for an Existing Building from UAV Imagery JF - Buildings N2 - An approach to automatically generate a dynamic energy simulation model in Modelica for a single existing building is presented. It aims at collecting data about the status quo in the preparation of energy retrofits with low effort and costs. The proposed method starts from a polygon model of the outer building envelope obtained from photogrammetrically generated point clouds. The open-source tools TEASER and AixLib are used for data enrichment and model generation. A case study was conducted on a single-family house. The resulting model can accurately reproduce the internal air temperatures during synthetical heating up and cooling down. Modelled and measured whole building heat transfer coefficients (HTC) agree within a 12% range. A sensitivity analysis emphasises the importance of accurate window characterisations and justifies the use of a very simplified interior geometry. Uncertainties arising from the use of archetype U-values are estimated by comparing different typologies, with best- and worst-case estimates showing differences in pre-retrofit heat demand of about ±20% to the average; however, as the assumptions made are permitted by some national standards, the method is already close to practical applicability and opens up a path to quickly estimate possible financial and energy savings after refurbishment. KW - Modelica KW - heat transfer coefficient KW - heat demand KW - building energy modelling KW - building energy simulation Y1 - 2021 U6 - http://dx.doi.org/10.3390/buildings11090380 SN - 2075-5309 N1 - This article belongs to the Special Issue "Application of Computer Technology in Buildings" VL - 11 IS - 9 PB - MDPI CY - Basel ER - TY - JOUR A1 - Neu, Eugen A1 - Janser, Frank A1 - Khatibi, Akbar A. A1 - Orifici, Adrian C. T1 - Automated modal parameter-based anomaly detection under varying wind excitation JF - Structural Health Monitoring N2 - Wind-induced operational variability is one of the major challenges for structural health monitoring of slender engineering structures like aircraft wings or wind turbine blades. Damage sensitive features often show an even bigger sensitivity to operational variability. In this study a composite cantilever was subjected to multiple mass configurations, velocities and angles of attack in a controlled wind tunnel environment. A small-scale impact damage was introduced to the specimen and the structural response measurements were repeated. The proposed damage detection methodology is based on automated operational modal analysis. A novel baseline preparation procedure is described that reduces the amount of user interaction to the provision of a single consistency threshold. The procedure starts with an indeterminate number of operational modal analysis identifications from a large number of datasets and returns a complete baseline matrix of natural frequencies and damping ratios that is suitable for subsequent anomaly detection. Mahalanobis distance-based anomaly detection is then applied to successfully detect the damage under varying severities of operational variability and with various degrees of knowledge about the present operational conditions. The damage detection capabilities of the proposed methodology were found to be excellent under varying velocities and angles of attack. Damage detection was less successful under joint mass and wind variability but could be significantly improved through the provision of the currently encountered operational conditions. Y1 - 2016 U6 - http://dx.doi.org/10.1177/1475921716665803 SN - 1475-9217 VL - 15 IS - 6 SP - 1 EP - 20 PB - Sage CY - London ER - TY - THES A1 - Pfaff, Raphael T1 - Automated processing of the ISL Doppler images Y1 - 2007 N1 - Hagen, Fernuniv., Bachelorarbeit, 2007 ER - TY - JOUR A1 - Grieger, Niklas A1 - Schwabedal, Justus T. C. A1 - Wendel, Stefanie A1 - Ritze, Yvonne A1 - Bialonski, Stephan T1 - Automated scoring of pre-REM sleep in mice with deep learning JF - Scientific Reports N2 - Reliable automation of the labor-intensive manual task of scoring animal sleep can facilitate the analysis of long-term sleep studies. In recent years, deep-learning-based systems, which learn optimal features from the data, increased scoring accuracies for the classical sleep stages of Wake, REM, and Non-REM. Meanwhile, it has been recognized that the statistics of transitional stages such as pre-REM, found between Non-REM and REM, may hold additional insight into the physiology of sleep and are now under vivid investigation. We propose a classification system based on a simple neural network architecture that scores the classical stages as well as pre-REM sleep in mice. When restricted to the classical stages, the optimized network showed state-of-the-art classification performance with an out-of-sample F1 score of 0.95 in male C57BL/6J mice. When unrestricted, the network showed lower F1 scores on pre-REM (0.5) compared to the classical stages. The result is comparable to previous attempts to score transitional stages in other species such as transition sleep in rats or N1 sleep in humans. Nevertheless, we observed that the sequence of predictions including pre-REM typically transitioned from Non-REM to REM reflecting sleep dynamics observed by human scorers. Our findings provide further evidence for the difficulty of scoring transitional sleep stages, likely because such stages of sleep are under-represented in typical data sets or show large inter-scorer variability. We further provide our source code and an online platform to run predictions with our trained network. Y1 - 2021 U6 - http://dx.doi.org/10.1038/s41598-021-91286-0 SN - 2045-2322 N1 - Corresponding author: Stephan Bialonski VL - 11 IS - Art. 12245 PB - Springer Nature CY - London ER - TY - CHAP A1 - Sildatke, Michael A1 - Karwanni, Hendrik A1 - Kraft, Bodo A1 - Schmidts, Oliver A1 - Zündorf, Albert T1 - Automated Software Quality Monitoring in Research Collaboration Projects T2 - ICSEW'20: Proceedings of the IEEE/ACM 42nd International Conference on Software Engineering Workshops Y1 - 2020 U6 - http://dx.doi.org/10.1145/3387940.3391478 SP - 603 EP - 610 ER - TY - JOUR A1 - Schmitz, Günter A1 - Oligschläger, U. A1 - Eifler, G. A1 - Lechner, H. T1 - Automated System for Optimized Calibration of Engine Management Systems Y1 - 1994 N1 - SAE International Congress and Exposition, Detroit, Feb. 28 - March 3 ; SAE- Paper-No.: 940151 ;