06 Fakultät Luft- und Raumfahrttechnik und Geodäsie

Permanent URI for this collectionhttps://elib.uni-stuttgart.de/handle/11682/7

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    Towards improved targetless registration and deformation analysis of TLS point clouds using patch-based segmentation
    (2023) Yang, Yihui; Schwieger, Volker (Prof. Dr.-Ing. habil. Dr. h.c.)
    The geometric changes in the real world can be captured by measuring and comparing the 3D coordinates of object surfaces. Traditional point-wise measurements with low spatial resolution may fail to detect inhomogeneous, anisotropic and unexpected deformations, and thus cannot reveal complex deformation processes. 3D point clouds generated from laser scanning or photogrammetric techniques have opened up opportunities for an area-wise acquisition of spatial information. In particular, terrestrial laser scanning (TLS) exhibits rapid development and wide application in areal geodetic monitoring owing to the high resolution and high quality of acquired point cloud data. However, several issues in the process chain of TLS-based deformation monitoring are still not solved satisfactorily. This thesis mainly focuses on the targetless registration and deformation analysis of TLS point clouds, aiming to develop novel data-driven methods to tackle the current challenges. For most deformation processes of natural scenes, in some local areas no shape deformations occur (i.e., these areas are rigid), and even the deformation directions show a certain level of consistency when these areas are small enough. Further point cloud processing, like stability and deformation analyses, could benefit from the assumptions of local rigidity and consistency of deformed point clouds. In this thesis, thereby, three typical types of locally rigid patches - small planar patches, geometric primitives, and quasi-rigid areas - can be generated from 3D point clouds by specific segmentation techniques. These patches, on the one hand, can preserve the boundaries between rigid and non-rigid areas and thus enable spatial separation with respect to surface stability. On the other hand, local geometric information and empirical stochastic models could be readily determined by the points in each patch. Based on these segmented rigid patches, targetless registration and deformation analysis of deformed TLS point clouds can be improved regarding accuracy and spatial resolution. Specifically, small planar patches like supervoxels are utilized to distinguish the stable and unstable areas in an iterative registration process, thus ensuring only relatively stable points are involved in estimating transformation parameters. The experimental results show that the proposed targetless registration method has significantly improved the registration accuracy. These small planar patches are also exploited to develop a novel variant of the multiscale model-to-model cloud comparison (M3C2) algorithm, which constructs prisms extending from planar patches instead of the cylinders in standard M3C2. This new method separates actual surface variations and measurement uncertainties, thus yielding lower-uncertainty and higher-resolution deformations. A coarse-to-fine segmentation framework is used to extract multiple geometric primitives from point clouds, and rigorous parameter estimations are performed individually to derive high-precision parametric deformations. Besides, a generalized local registration-based pipeline is proposed to derive dense displacement vectors based on segmented quasi-rigid areas that are corresponded by areal geometric feature descriptors. All proposed methods are successfully verified and evaluated by simulated and/or real point cloud data. The choice of proposed deformation analysis methods for specific scenarios or applications is also provided in this thesis.
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    Experimental investigation of low-frequency sound and infrasound induced by onshore wind turbines
    (2024) Blumendeller, Esther; Cheng, Po Wen (Prof. Dr.)
    Climate change has a global impact and is increasingly affecting our environment. This is driving the continuous expansion of renewable energies, with wind energy playing a major role. As wind energy becomes more widespread, an increasing number of people will live near wind turbines in complex terrain. In such scenarios, wind turbines are often positioned at elevated locations, while residents live in valleys. In complex terrain, such as a steep escarpment, local turbulence, wind speed, and direction are strongly influenced by topography, contributing to the complexity of sound propagation or impacts the background noise situation in valleys, for example, due to shielding effects. The operation of wind turbines is associated with both visual and sound-related impact, with sound being generated at various frequencies. There is a growing interest in low-frequency sound and infrasound, characterized by long wavelengths that propagate over considerable distances without significant attenuation. This is in contrast to higher-frequency sound, and might increase the impact of wind turbine sound at residential areas located several hundred meters or a few kilometers away from the wind farm. In the context of complex terrain, this work investigates wind turbines in complex terrain as sources of low-frequency sound and infrasound. The investigations on characterization of sound generation and propagation are based on measurements in the vicinity of two wind farms. Measurements were conducted within four measurement campaigns at two wind farms located close to an escarpment at the Swabian Alb in Southern Germany over a period of about nine month. Acoustic data was obtained in the proximity of the wind turbines and at residential buildings in 1–1.7km distance to the wind farms in municipalities located within a valley. Besides acoustic measurements including the infrasonic frequency range, a comprehensive data set with ground motion data, wind turbine operating data, meteorological data and data from a noise reporting app supports the investigation. Two aspects require analysis: Firstly, the aspect of generation and propagation of wind turbine low-frequency sound and infrasound in complex terrain, and secondly, the relation with annoyance. Results show that sounds within the infrasonic range assigned to the blade passage at the tower are transmitted through the air over distances of 1 km. Low-frequency sounds were found to be amplitude-modulated and were investigated as amplitude modulation. Infrasound and amplitude modulation occurrences were more likely during morning, evening and night hours and during atmospheric conditions with positive lapse rate, vertical wind shear and low turbulence intensity. The occurrence of both infrasound and amplitude modulation was typically observed during rated rotational speed but below-rated power. To allow predictions, a standard prediction method was extended to include the lowfrequency sound and infrasound range and adapted to the measurement data in order to apply it to complex terrain. The sound level difference of the measured data aligns well with the predictions within the frequency range of 8 Hz and 250 Hz. Investigations regarding outdoor-to-indoor sound reductions showed influences from structural resonances and room modes, which depend on the characteristics of the building and the specific room under investigation. Combining acoustic measurements with annoyance reports showed that rated wind turbine operation appears to be a contributing factor in annoyance ratings obtained through a noise reporting app, ranging from “somewhat” to “very” levels. Furthermore, the analysis indicates that varying levels of annoyance at a distance of 1km from the wind farm, both outside and inside buildings, do not correspond to significant differences in the averaged and A-weighted sound pressure levels. Overall, this work contributes to a better understanding of the low-frequency sound and infrasound generated from wind turbines and provides insight into the sound characteristics of measured wind turbine sound at residential locations in complex terrains.
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    Entwicklung laserspektroskopischer Methoden zur Analyse der Verdunstungseigenschaften von Brennstofftropfen
    (Stuttgart : Deutsches Zentrum für Luft- und Raumfahrt, Institut für Verbrennungstechnik, 2021) Werner, Stefanie; Riedel, Uwe (Prof. Dr. rer. nat.)
    Die steigenden Emissionen des klimaschädlichen Treibhausgases CO2 durch die Verbrennung von fossilen, endlichen Energieträgern müssen möglichst schnell und nachhaltig reduziert werden. Ein vielversprechender Lösungsansatz zur Reduzierung der Schadstoffemissionen bei der Verbrennung liegt in dem Einsatz von alternativen und erneuerbaren Brennstoffen. Als Energieträger bieten sich auf Grund ihrer hohen Energiedichte vor allem flüssige Brennstoffe an. Diese werden typischerweise durch Druckzerstäubung in die Brennkammer eingebracht, verdunstet und dann mit dem Oxidationsmittel vermischt und verbrannt. Die Verdunstung der kleinen Brennstofftropfen des sogenannten Sprays ist von entscheidender Bedeutung für den Gesamtverbrennungsprozess in Verbrennungsmotoren und Gasturbinen. Im Allgemeinen bestimmt die Verdunstungsrate die Verbrennungsrate. Daher sind Modelle notwendig, die eine genaue Vorhersage der Brennstoffverdunstung ermöglichen. Zur Validierung dieser Modelle werden quantitative Messungen unter genau definierten Randbedingungen benötigt. Da die Prozesse in technischen Brennkammern sehr komplex sind, werden Experimente zur Tropfenverdunstung häufig mit linearen, monodispersen Tropfenketten durchgeführt, um die Kopplung zwischen den verschiedenen Effekten zu minimieren. Durch die geringe Größe der Tropfen (typischerweise wenige hundert Mikrometer oder weniger), erfordert die experimentelle Untersuchung eine hohe räumliche Auflösung. In dieser Arbeit wurden quantitative, laseroptische Messtechniken mit hoher räumlicher Auflösung zur experimentellen Untersuchung der Tropfenverdunstung an monodispersen Tropfenketten entwickelt. Mit den Messtechniken wurden Validierungsdaten für die Verdunstungseigenschaften von verschiedenen Brennstoffen bestimmt. Konzentrationsmessungen von verdunsteten Kohlenwasserstoffen wurden unter Verwendung von Infrarot-Laserabsorptionsspektroskopie und laserinduzierter Fluoreszenzspektroskopie (LIF) durchgeführt. Tropfenketten wurden mit einem Tropfenkettengenerator erzeugt, welcher vertikal in einem Strömungskanal installiert wurde. Die untersuchten Brennstoffe waren Cyclohexan, iso-Octan, n-Heptan, n-Pentan, 1-Butanol und Anisol. Der Strömungskanal wurde mit einer laminaren Luftströmung bei verschiedenen Temperaturen (313 K - 430 K) durchströmt. Da die untersuchten Tropfen einen Durchmesser in der Größenordnung von 120 bis 160 µm hatten und die Konzentrationsgradienten nahe der Tropfenoberfläche groß waren, war eine hohe räumliche Auflösung der Messtechniken erforderlich. Die Absorptionsmessungen wurden mit der Infrarotstrahlung eines HeNe-Lasers bei λ = 3,39 µm durchgeführt, um die CH-Streckschwingung der Kohlenwasserstoffe anzuregen. Die für die Quantifizierung der Brennstoffkonzentrationen benötigten Absorptionsquerschnitte wurden in einer beheizten Gaszelle für Temperaturen von 300 K - 773 K bestimmt. Die räumliche Auflösung im Strömungskanal betrug < 50 µm über eine Länge von 2 mm (Halbwertsbreite). Durch die Zylindersymmetrie und gute Stabilität der Tropfenketten konnten zeitliche Mittelungs- und Tomografieverfahren angewandt werden. Hierdurch konnten radiale Konzentrationsprofile an mehreren Positionen im Strömungskanal erhalten werden. Aus dem Anstieg der Dampfkonzentration an verschiedenen Messpositionen konnte die Verdunstungsrate bestimmt werden. Die Verdunstungsraten wurden in Abhängigkeit von der Mantelstromtemperatur (313 K - 430 K), der Tropfengeschwindigkeit (8 m/s - 23 m/s), der Tropfenerzeugungsfrequenz (12 kHz - 75 kHz) und dem Tropfenabstand (300 µm - 685 µm) gemessen. Im untersuchten Temperaturbereich steigt die Verdunstungsrate des Brennstoffs linear mit der Temperatur an. Die Reihenfolge der Brennstoffe in Bezug auf die Verdunstungsrate entspricht den Siedepunkten der einzelnen Brennstoffe. Da technische Brennstoffe häufig eine Mischung mehrerer Komponenten sind, ist die Untersuchung von Brennstoffgemischen von großem Interesse. Daher wurde ein Messverfahren entwickelt, um binäre Gemische zu untersuchen. Das Verfahren wurde verwendet, um eine Mischung aus Cyclohexan und Anisol zu untersuchen. Zwei Messtechniken - laserinduzierte Fluoreszenz (LIF) und Infrarot Absorptionsspektroskopie - wurden verwendet, um beide Spezies zu messen. Um λ = 3,39 µm ist der Absorptionsquerschnitt von Cyclohexan um etwa den Faktor 8 größer als von Anisol. Im untersuchten Fall war die Konzentration aufgrund des höheren Dampfdrucks ebenfalls deutlich größer. Daher konnte das Infrarot-Absorptionssignal praktisch ausschließlich Cyclohexan zugeordnet werden. Anisol hat bei Anregung bei λ = 266 nm eine sehr gute Fluoreszenzquantenausbeute, während Cyclohexan keine Fluoreszenz zeigt. LIF ermöglicht daher die Quantifizierung von Anisol (oder anderen Aromaten) ohne Interferenz durch Kohlenwasserstoffe. Es wurde ein Messverfahren entwickelt, welches Halationseffekte vermeidet, die typischerweise in planaren LIF-Experimenten an Tropfenketten auftreten. Kalibrationsmessungen, die im gleichen Strömungskanal durchgeführt wurden, ermöglichten die Quantifizierung der verdunsteten Anisolkonzentrationen. Die räumliche Auflösung betrug 80 µm. Ähnlich wie bei den Einzelkomponentenmessungen wurden Verdunstungsraten bestimmt. Wie aufgrund des niedrigeren Dampfdrucks zu erwarten, ist die Verdunstungsrate von Anisol niedriger als die von Cyclohexan. Die Verdunstungsrate von Cyclohexan in der binären Mischung stimmt gut mit den Einzelkomponentenmessungen überein. Das entwickelte Messverfahren ist sehr vielversprechend für weitere Untersuchungen an Mehrkomponentenmischungen. In dieser Arbeit konnte damit erstmals mit hoher räumlicher Auflösung die Verdunstung von Brennstoffkomponenten mittels Absorptionsspektroskopie in der Nähe von Brennstofftropfen untersucht werden. Zusätzlich wurden in Kombination mit laserinduzierter Fluoreszenzspektroskopie Messungen an binären Mischungen durchgeführt. Damit steht ein wertvoller Datensatz zur Validierung von numerischen Simulationen zur Verfügung.
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    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-Mi
    In 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.
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    Messungen im Bereich eines Windparks mit Fokus auf tief- und niederfrequente Schallemissionen und -immissionen
    (2022) Blumendeller, Esther; Gaßner, Laura; Müller, Florian; Wigger, Maayen; Berlinger, Philipp; Cheng, Po Wen
    Die Nutzung von Windenergie wird einen entscheidenden Anteil am erneuerbaren Energiemix der Zukunft haben. Während der Stromgewinnung geben Windenergieanlagen (WEA) Schall und Erschütterungen (seismische Wellen) in die Umgebung ab, vor allem im tieffrequenten Bereich. Im Zuge des interdisziplinären Verbundprojektes Inter-Wind werden akustische Messungen zur Unterstützung psychologischer Fragebögen, kombiniert mit seismischen und meteorologischen Messungen an Windparks auf der Schwäbischen Alb durchgeführt. Ziel des Projektes ist es, die Gründe für Belästigung der Anwohner in Zusammenhang mit den Immissionen der WEA zu verstehen. Hierbei liegt der Fokus auf dem tieffrequenten (20-200 Hz) und niederfrequenten (1-20 Hz) Bereich. Akustische und seismische Messungen wurden an einem Windpark auf der Schwäbischen Alb, mit drei WEA des Typs GE 2.75-120 durchgeführt. Parallel dazu konnten Anwohner Belästigungszeiträume über eine Geräuschmelde-App dokumentieren. In diesem Beitrag wird die Umsetzung einer interdisziplinären Messkampagne im Bereich des Tegelberg Windparks und eines Wohngebäudes in Tallage in ca. 1 km Entfernung zum Windpark beschrieben. Schließlich werden erste Ergebnisse der akustischen Messungen und interdisziplinären Untersuchung vorgestellt und diskutiert.
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    Analyzing and characterizing spaceborne observation of water storage variation : past, present, future
    (2024) Saemian, Peyman; Sneeuw, Nico (Prof. Dr.-Ing.)
    Water storage is an indispensable constituent of the intricate water cycle, as it governs the availability and distribution of this precious resource. Any alteration in the water storage can trigger a cascade of consequences, affecting not only our agricultural practices but also the well-being of various ecosystems and the occurrence of natural hazards. Therefore, it is essential to monitor and manage the water storage levels prudently to ensure a sustainable future for our planet. Despite significant advancements in ground-based measurements and modeling techniques, accurately measuring water storage variation remained a major challenge for a long time. Since 2002, the Gravity Recovery and Climate Experiment (GRACE) and its successor GRACE Follow-On (GRACE-FO) satellites have revolutionized our understanding of the Earth's water cycle. By detecting variations in the Earth's gravity field caused by changes in water distribution, these satellites can precisely measure changes in total water storage (TWS) across the entire globe, providing a truly comprehensive view of the world's water resources. This information has proved invaluable for understanding how water resources are changing over time, and for developing strategies to manage these resources sustainably. However, GRACE and GRACE-FO are subject to various challenges that must be addressed in order to enhance the efficacy of our exploitation of GRACE observations for scientific and practical purposes. This thesis aims to address some of the challenges faced by GRACE and GRACE-FO. Since the inception of the GRACE mission, scholars have commonly extracted mass changes from observations by approximating the Earth's gravity field utilizing mathematical functions termed spherical harmonics. Various institutions have already processed GRACE(-FO) data, known as level-2 data in the GRACE community, considering the constraints, approaches, and models that have been utilized. However, this processed data necessitates post-processing to be used for several applications, such as hydrology and climate research. In this thesis, we evaluate various methods of processing GRACE(-FO) level-2 data and assess the spatio-temporal effect of the post-processing steps. Furthermore, we aim to compare the consistency between GRACE and its successor mission, GRACE-FO, in terms of data quality and measurement accuracy. By analyzing and comparing the data from these two missions, we can identify any potential discrepancies or differences and establish the level of confidence in the accuracy and reliability of the GRACE-FO measurements. Finally, we will compare the processed level-3 products with the level-3 products that are presently accessible online. The relatively short record of the GRACE measurements, compared to other satellite missions and observational records, can limit some studies that require long-term data. This short record makes it challenging to separate long-term signals from short-term variability and validate the data with ground-based measurements or other satellite missions. To address this limitation, this thesis expands the temporal coverage of GRACE(-FO) observations using global hydrological, atmospheric, and reanalysis models. First, we assess these models in estimating the TWS variation at a global scale. We compare the performance of various methods including data-driven and machine learning approaches in incorporating models and reconstruct GRACE TWS change. The results are also validated against Satellite Laser Ranging (SLR) observations over the pre-GRACE period. This thesis develops a hindcasted GRACE, which provides a better understanding of the changes in the Earth's water storage on a longer time scale. The GRACE satellite mission detects changes in the overall water storage in a specific region but cannot distinguish between the different compartments of TWS, such as surface water, groundwater, and soil moisture. Understanding these individual components is crucial for managing water resources and addressing the effects of droughts and floods. This study aims to integrate various data sources to improve our understanding of water storage variations at the continental to basin scale, including water fluxes, lake water level, and lake storage change data. Additionally, the study demonstrates the importance of combining GRACE(-FO) observations with other measurements, such as piezometric wells and rain-gauges, to understand the water scarcity predicament in Iran and other regions facing similar challenges. The GRACE satellite mission provides valuable insights into the Earth's system. However, the GRACE product has a level of uncertainty due to several error sources. While the mission has taken measures to minimize these uncertainties, researchers need to account for them when analyzing the data and communicate them when reporting findings. This thesis proposes a probabilistic approach to incorporate the Total Water Storage Anomaly (TWSA) data from GRACE(-FO). By accounting for the uncertainty in the TWSA data, this approach can provide a more comprehensive understanding of drought conditions, which is essential for decision makers managing water resources and responding to drought events.
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    Forming a hybrid intelligence system by combining Active Learning and paid crowdsourcing for semantic 3D point cloud segmentation
    (2023) Kölle, Michael; Sörgel, Uwe (Prof. Dr.-Ing.)
    While in recent years tremendous advancements have been achieved in the development of supervised Machine Learning (ML) systems such as Convolutional Neural Networks (CNNs), still the most decisive factor for their performance is the quality of labeled training data from which the system is supposed to learn. This is why we advocate focusing more on methods to obtain such data, which we expect to be more sustainable than establishing ever new classifiers in the rapidly evolving ML field. In the geospatial domain, however, the generation process of training data for ML systems is still rather neglected in research, with typically experts ending up being occupied with such tedious labeling tasks. In our design of a system for the semantic interpretation of Airborne Laser Scanning (ALS) point clouds, we break with this convention and completely lift labeling obligations from experts. At the same time, human annotation is restricted to only those samples that actually justify manual inspection. This is accomplished by means of a hybrid intelligence system in which the machine, represented by an ML model, is actively and iteratively working together with the human component through Active Learning (AL), which acts as pointer to exactly such most decisive samples. Instead of having an expert label these samples, we propose to outsource this task to a large group of non-specialists, the crowd. But since it is rather unlikely that enough volunteers would participate in such crowdsourcing campaigns due to the tedious nature of labeling, we argue attracting workers by monetary incentives, i.e., we employ paid crowdsourcing. Relying on respective platforms, typically we have access to a vast pool of prospective workers, guaranteeing completion of jobs promptly. Thus, crowdworkers become human processing units that behave similarly to the electronic processing units of this hybrid intelligence system performing the tasks of the machine part. With respect to the latter, we do not only evaluate whether an AL-based pipeline works for the semantic segmentation of ALS point clouds, but also shed light on the question of why it works. As crucial components of our pipeline, we test and enhance different AL sampling strategies in conjunction with both a conventional feature-driven classifier as well as a data-driven CNN classification module. In this regard, we aim to select AL points in such a manner that samples are not only informative for the machine, but also feasible to be interpreted by non-experts. These theoretical formulations are verified by various experiments in which we replace the frequently assumed but highly unrealistic error-free oracle with simulated imperfect oracles we are always confronted with when working with humans. Furthermore, we find that the need for labeled data, which is already reduced through AL to a small fraction (typically ≪1 % of Passive Learning training points), can be even further minimized when we reuse information from a given source domain for the semantic enrichment of a specific target domain, i.e., we utilize AL as means for Domain Adaptation. As for the human component of our hybrid intelligence system, the special challenge we face is monetarily motivated workers with a wide variety of educational and cultural backgrounds as well as most different mindsets regarding the quality they are willing to deliver. Consequently, we are confronted with a great quality inhomogeneity in results received. Thus, when designing respective campaigns, special attention to quality control is required to be able to automatically reject submissions of low quality and to refine accepted contributions in the sense of the Wisdom of the Crowds principle. We further explore ways to support the crowd in labeling by experimenting with different data modalities (discretized point cloud vs. continuous textured 3D mesh surface), and also aim to shift the motivation from a purely extrinsic nature (i.e., payment) to a more intrinsic one, which we intend to trigger through gamification. Eventually, by casting these different concepts into the so-called CATEGORISE framework, we constitute the aspired hybrid intelligence system and employ it for the semantic enrichment of ALS point clouds of different characteristics, enabled through learning from the (paid) crowd.
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    Application of neural networks and transfer learning to turbomachinery heat transfer
    (2022) Baumann, Markus; Koch, Christian; Staudacher, Stephan
    Model-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.
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    Multiscale and multiphase modeling and numerical simulation of function-perfusion processes in the liver
    (Stuttgart : Institut für Statik und Dynamik der Luft und Raumfahrtkonstruktionen, Universität Stuttgart, 2023) Lambers, Lena; Ricken, Tim (Prof. Dr.-Ing.)
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    Passively mode-locked Tm-lasers for all-fiber high-energy nonlinear chirped pulse amplification
    (2023) Graf, Florian; Dekorsy, Thomas (Prof. Dr. rer. nat.)