06 Fakultät Luft- und Raumfahrttechnik und Geodäsie
Permanent URI for this collectionhttps://elib.uni-stuttgart.de/handle/11682/7
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Item Open Access Smart ground support equipment : the design and demonstration of robotic ground support equipment for small spacecraft integration and verification(2024) Kottmeier, Sebastian; Wittje, Philipp; Klinkner, Sabine; Essmann, Olaf; Suhr, Birgit; Kirchler, Jan-Luca; Ho, Tra-MiIn order to reduce the costs of integration and verification processes and to optimize the assembly, integration and verification (AIV) flow in the prototype development of small- and medium-sized spacecrafts, an industrial six-axis robot was used as a universal mechanical ground support equipment instead of a tailored prototype specific ground support equipment (GSE). In particular, a robotic platform offers the possibility of embedding verification steps such as mass property determination into the integration process while offering a wider range of ergonomic adaption due to the enhanced number of degrees of freedom compared to a classical static Mechanical GSE (MGSE). This reduces development costs for projects and enhances the flexibility and ergonomics of primarily mechanical AIV operations. In this paper, the robotic MGSE system is described, the operational prospects for in-line verification are elaborated and an example is given showing the possibilities and challenges of its operational use as well as its in-line mass determination capabilities. For this purpose, a method has been developed that allows for the precise measurement of the spacecraft mass using the robot’s existing technology without the need for additional hardware. Subsequent work will extend this to determine the center of gravity and the moments of inertia of the payload on the robotic MGSE.Item Open Access Application of neural networks and transfer learning to turbomachinery heat transfer(2022) Baumann, Markus; Koch, Christian; Staudacher, StephanModel-based predictive maintenance using high-frequency in-flight data requires digital twins that can model the dynamics of their physical twin with high precision. The models of the twins need to be fast and dynamically updatable. Machine learning offers the possibility to address these challenges in modeling the transient performance of aero engines. During transient operation, heat transferred between the engine’s structure and the annulus flow plays an important role. Diabatic performance modeling is demonstrated using non-dimensional transient heat transfer maps and transfer learning to extend turbomachinery transient modeling. The general form of such a map for a simple system similar to a pipe is reproduced by a Multilayer Perceptron neural network. It is trained using data from a finite element simulation. In a next step, the network is transferred using measurements to model the thermal transients of an aero engine. Only a limited number of parameters measured during selected transient maneuvers is needed to generate suitable non-dimensional transient heat transfer maps. With these additional steps, the extended performance model matches the engine thermal transients well.Item Open Access Validation of the safety requirements of the landing gear using fault tree analysis(2022) Iven, Leander; Zaidi, YaseenWe analyze the functionality of the landing system of a regional aircraft in the extension and cruise flight modes and validate safety requirements through the fault tree analysis. The main landing gear system is captured in the electromechanical-fluidic domain and system behavior is abstracted in an elementary hydraulic circuit. The functional representation is then constructed into a fault tree which allows analysis of the failure propagation originating at different branch terminals, for instance, at the main landing gear actuator which extends the gear and holds it retracted during the cruise, door actuator, door uplocks, and hydraulic power supply. Each component is assigned a failure probability. Each failure mode is abstracted as a top-level event having a probability of failure and through Boolean combinations of component failures in the lower branches. Two reliability aspects considered are the availability to fully lower the landing gear and the integrity of inadvertent gear or door extension while cruising. Architectural changes through undercarriage system reconfiguration and component redundancy have been exploited to improve system failure rates. The analysis determines the overall system failure rate against the flight cycles. The process is agile to accommodate design changes with the evolution of architecture during the systems engineering lifecycle.Item Open Access Simulating asteroid impacts and meteor events by high-power lasers : from the laboratory to spaceborne missions(2023) Ferus, Martin; Knížek, Antonín; Cassone, Giuseppe; Rimmer, Paul B.; Changela, Hitesh; Chatzitheodoridis, Elias; Uwarova, Inna; Žabka, Ján; Kabáth, Petr; Saija, Franz; Saeidfirozeh, Homa; Lenža, Libor; Krůs, Miroslav; Petera, Lukáš; Nejdl, Lukáš; Kubelík, Petr; Křivková, Anna; Černý, David; Divoký, Martin; Pisařík, Michael; Kohout, Tomáš; Palamakumbure, Lakshika; Drtinová, Barbora; Hlouchová, Klára; Schmidt, Nikola; Martins, Zita; Yáñez, Jorge; Civiš, Svatopoluk; Pořízka, Pavel; Mocek, Tomáš; Petri, Jona; Klinkner, SabineMeteor plasmas and impact events are complex, dynamic natural phenomena. Simulating these processes in the laboratory is, however, a challenge. The technique of laser induced dielectric breakdown was first used for this purpose almost 50 years ago. Since then, laser-based experiments have helped to simulate high energy processes in the Tunguska and Chicxulub impact events, heavy bombardment on the early Earth, prebiotic chemical evolution, space weathering of celestial bodies and meteor plasma. This review summarizes the current level of knowledge and outlines possible paths of future development.Item Open Access Uncertainty quantification for full-flight data based engine fault detection with neural networks(2022) Weiss, Matthias; Staudacher, Stephan; Mathes, Jürgen; Becchio, Duilio; Keller, ChristianCurrent state-of-the-art engine condition monitoring is based on a minimum of one steady-state data point per flight. Due to the scarcity of available data points, there are difficulties distinguishing between random scatter and an underlying fault introducing a detection latency of several flights. Today’s increased availability of data acquisition hardware in modern aircraft provides continuously sampled in-flight measurements, so-called full-flight data. These full-flight data give access to sufficient data points to detect faults within a single flight, significantly improving the availability and safety of aircraft. Artificial neural networks are considered well suited for the timely analysis of an extensive amount of incoming data. This article proposes uncertainty quantification for artificial neural networks, leading to more reliable and robust fault detection. An existing approach for approximating the aleatoric uncertainty was extended by an Out-of-Distribution Detection in order to take the epistemic uncertainty into account. The method was statistically evaluated, and a grid search was performed to evaluate optimal parameter combinations maximizing the true positive detection rates. All test cases were derived based on in-flight measurements of a commercially operated regional jet. Especially when requiring low false positive detection rates, the true positive detections could be improved 2.8 times while improving response times by approximately 6.9 compared to methods only accounting for the aleatoric uncertainty.Item Open Access Editorial for PFG issue 5/2023(2023) Gerke, Markus; Cramer, MichaelItem Open Access Electrical conductivity of monolithic and powdered carbon aerogels and their composites(2024) Kröner, Jessica; Platzer, Dominik; Milow, Barbara; Schwan, MarinaThe electrical conductivity of powdered carbon aerogels is one of the key factors required for electro-chemical applications. This study investigates the correlation between the structural, physical, mechanical and electrical properties of pure and activated carbon aerogels, as well as aerogel-composites. The thermal activation with carbon dioxide led to higher electrical conductivity and a decrease in density and particle size. Furthermore, the influence of applied force, compressibility of aerogels and aerogel composites on electrical conductivity was studied. A number of different carbonaceous powdered additives with various morphologies, from almost spherical to fiber- and flake-like shaped, were investigated. For two composites, theoretical values for conductivity were calculated showing the great contribution of particle shape to the conductivity. The results show that the conductive behavior of composites during compression is based on both the mechanical particle arrangement mechanism and increasing particle contact area.Item Open Access Particle image velocimetry measurements in accelerated, transonic wake flows(2022) Richter, Judith; Alexopoulos, Charalampos; Weigand, BernhardThis paper reports on particle image velocimetry (PIV) measurements in compressible accelerated wake flows generated by two different central injector types, which are mounted in a convergent-divergent nozzle. The injectors differ by the extent of their trailing edge located either in the subsonic (injector A) or supersonic flow region (injector B). In addition, the undisturbed nozzle flow without injector is studied as a reference case. The PIV results reveal typical wake flow structures expected in subsonic (injector A) and supersonic (injector B) wake flows. They further show that the Reynolds stresses Rexxand Reyysignificantly decay in all three cases due to the strong acceleration throughout the nozzle. Interestingly, in the case of injector A, the flow stays non-isotropic with Reyy>Rexxalso far downstream in the supersonic flow region. These measurements were motivated by the lack of velocity data needed to validate numerical simulations. That is why this paper additionally contains results from (unsteady) Reynolds-averaged Navier-Stokes ((U)RANS) simulations of the two wake flows investigated experimentally. The URANS simulation of the injector A case is able to accurately predict the entire flow field and periodic fluctuations at the wake centerline. However, in the case of injector B, the RANS simulation underestimates the far wake centerline velocity by about 4%.Item Open Access A time-accurate inflow coupling for zonal LES(2023) Blind, Marcel P.; Kleinert, Johannes; Lutz, Thorsten; Beck, AndreaGenerating turbulent inflow data is a challenging task in zonal large eddy simulation (zLES) and often relies on predefined DNS data to generate synthetic turbulence with the correct statistics. The more accurate, but more involved alternative is to use instantaneous data from a precursor simulation. Using instantaneous data as an inflow condition allows to conduct high fidelity simulations of subdomains of, e.g. an aircraft including all non-stationary or rare events. In this paper, we introduce a toolchain that is capable of interchanging highly resolved spatial and temporal data between flow solvers with different discretization schemes. To accomplish this, we use interpolation algorithms suitable for scattered data in order to interpolate spatially. In time, we use one-dimensional interpolation schemes for each degree of freedom. The results show that we can get stable simulations that map all flow features from the source data into a new target domain. Thus, the coupling is capable of mapping arbitrary data distributions and formats into a new domain while also recovering and conserving turbulent structures and scales. The necessary time and space resolution requirements can be defined knowing the resolution requirements of the used numerical scheme in the target domain.Item Open Access Technology selection for holistic analysis of hybrid-electric commuter aircraft(2022) Zumegen, Clemens; Strathoff, Philipp; Stumpf, Eike; Wensveen, Jasper van; Rischmüller, Carsten; Hornung, Mirko; Geiß, Ingmar; Strohmayer, AndreasElectric powertrains have different characteristics than conventional powertrains with combustion engines and require unconventional aircraft designs to evolve their full potential. Therefore, this paper describes a method to identify potential aircraft designs with electrified powertrains. Promising technology options in the fields of powertrain architecture, aerodynamic interactions, onboard systems and operating strategies were collected by the project partners of the LuFo project GNOSIS. The effect of the technology options on a commuter aircraft was evaluated in terms of global emissions ( CO2), local emissions ( NOXand noise) and operating costs. The evaluation considers an entry into service in 2025 and 2050 and is based on the reference aircraft Beechcraft 1900D. Literature review and simplified calculations enabled the evaluation of the aerodynamic interactions, systems and operating strategies. A preliminary aircraft design tool assessed the different powertrain architectures by introducing the two parameters ’power hybridization’ and ’power split’. Afterwards, compatible technology options were compiled into technology baskets and ranked using the shortest euclidean distance to the ideal solution and the farthest euclidean distance to the worst solution (Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) method). An analysis of the CS 23 regulations leads to a high-wing design and excluded the partial turbo-electric powertrain architecture with the gas turbine in the aircraft tail. For 2025, a partial turbo-electric powertrain with two additional electric driven wingtip propellers was selected. A serial hybrid powertrain, which uses a gas turbine or fuel cell in combination with a battery, powers distributed electric propulsors at the wing leading edge in 2050. In both scenarios, the aircraft design includes an electric environmental control system, an electric driven landing gear and electro-hydraulic actuators for the primary flight control and landing gear.