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Nonlinear dynamic analysis of shear- and torsion-free rods using isogeometric discretization and outlier removal
No full textIn this paper, we present a discrete formulation of nonlinear shear- and torsion-free rods introduced by Gebhardt and Romero (Acta Mechanica 232(10):3825–3847, 2021) that uses isogeometric discretization and robust time integration. Omitting the director as an independent variable field, we reduce the number of degrees of freedom and obtain discrete solutions in multiple copies of the Euclidean space ℝ³, which is larger than the corresponding multiple copies of the manifold ℝ³×S² obtained with standard Hermite finite elements. For implicit time integration, we choose the same integration scheme as Gebhardt and Romero in (2021) that is a hybrid form of the midpoint and the trapezoidal rules. In addition, we apply a recently introduced approach for outlier removal by Hiemstra et al. (Comput Methods Appl Mech Eng 387:114115, 2021) that reduces high-frequency content in the response without affecting the accuracy, ensuring robustness of our nonlinear discrete formulation. We illustrate the efficiency of our nonlinear discrete formulation for static and transient rods under different loading conditions, demonstrating good accuracy in space, time and the frequency domain. Our numerical example coincides with a relevant application case, the simulation of mooring lines
An Electron Microscopy Study on the Prevention of SiC-Fiber Decomposition via the Integration of a Buffer Layer into ZrB₂-based Ceramics
No full textSiC-fiber (SiCf) reinforced ZrB₂-based ultra-high temperature ceramics (UHTCs) demonstrate improvements in several critical aspects of pure ZrB₂. These include the poor failure tolerance, challenging densification at high pressure and temperature, the low oxidation resistance, and the high overall density. Further, MoSi₂ is a notable sintering additive for ZrB₂, which not only enhances densification and mechanical properties at high temperatures but also provides elevated oxidation resistance up to a minimum of 1650°C. The combination of both, SiC fibers and MoSi₂ within one ZrB₂ ceramic shows promise. However, active oxidation of the SiC fibers limits its possible application to temperatures of 1500°C and is not compatible with the required sintering temperature of MoSi₂ of approximately 1750°C. Moreover, the fibers suffer from deterioration due to reactions with Mo or Mo-compounds, yet taking place during the sintering process and thus jeopardizing its beneficial effects to the ZrB₂-SiCf ceramic. Hence, combining SiC fibers and MoSi₂ in a pure ZrB₂ ceramic has not been feasible thus far. A novel approach, based on the concept of functionally graded materials (FGM), aims to obviate the adverse reactions between the fibers and Mo or Mo compounds during the sintering process. A Mo-diffusion-resistant buffer layer is introduced between the SiCf-containing ZrB₂-ZrSi₂ bulk and the outermost oxidation-protective ZrB₂-MoSi₂ layer. This buffer layer consists of ZrB₂ doped with either Si₃N₄ or the polymer-derived ceramics (PDCs) SiCN and SiHfBCN.
Scanning Electron Microscopy (SEM) joint with Energy-Dispersive X-ray Spectroscopy (EDS) investigations confirmed that this sample geometry and selected compositions effectively prevent SiC-fiber degradation by interactions with MoSi₂. In contrast, the SiC fibers in a reference sample lacking a buffer layer experienced significant degradation due to MoSi₂ diffusion into the fiber core. A comparison of the three buffer layer systems studied here revealed that incorporating Si₃N₄ resulted in moderate changes in the fiber structure, whereas PDC-doped samples exhibited minor structural changes within the fibers.
Microstructural investigations via (scanning) transmission electron microscopy ((S)TEM) endorse the buffer layer in its function as a diffusion barrier for MoSi₂, as only negligible amounts of Mo inside the buffer layers and the fiber/bulk are detectable. Within the buffer layer, the microstructure is dominated by the formation of SiC, BN, Zr(Hf)O₂, and Zr₂CN, which are high-temperature stable compounds and do not impair the overall UHTC-performance of the ZrB₂ ceramic. The changes in the SiC-fibers structure can be primarily ascribed to reactions with the ZrB₂-ZrSi₂ bulk.
Derived from the microstructural investigations the overall diffusion mechanisms in the reference sample without a buffer layer and the samples containing a buffer layer were deduced. The layered structure of the samples is concomitant with different eutectics formed in each zone of the composites. Due to the buffer layer, the formation of an early eutectic at the top layer-bulk interface is avoided, being otherwise responsible for unhampered Mo diffusion towards the fibers. Moreover, the sequential progression of the eutectic melts, beginning in the SiC-fiber-containing ZrB₂-ZrSi₂ bulk and extending through the buffer layer up to the top layer, ultimately prohibits a progressive diffusion of a Mo-Si melt phase towards the fibers, preventing their structural disintegration by MoSi₂.
Subsequent oxidation at temperatures of 1500°C and 1650°C for 15 min demonstrates the sustained efficacy of all buffer layers. Only very minor modifications were observed in the buffer layer or fibers compared to non-oxidized samples, affirming the persistent effectiveness of the buffer layers in impeding the UHTC-composite degradation during oxidation
Learning-based Hybrid Models for Operating 4th Generation District Heating Systems
No full textIt is anticipated that district heating networks will undergo a substantial transformation in the forthcoming years. The conventional approach to district heating involves distributing heat from a single, high-temperature heating plant to dispersed consumers through a mostly tree-like network. Upcoming, so-called 4th generation district heating networks, on the other hand, are characterised by lower supply temperatures, distributed and flexibly operated heat sources, and loop-based grid layouts. This system transition necessitates novel approaches to address grid operation tasks. A particular challenge in this endeavour is the lack of real-time consumer demand measurements. The acquisition of real-time consumption data is costly, both financially and in terms of organisational resources. If these measurements are not available, the resulting thermal demand uncertainty has to be reflected in the operation algorithms. Moreover, since the physical equations describing heating grids are nonlinear, mapping the demand’s uncertainty onto the grid states can result in multimodal probability distributions, even if the initial demand uncertainty has a simple Gaussian form. It is, therefore, infeasible to find adequate parametric representations for the grid state’s uncertainty. Therefore, we propose to utilise learning-based hybrid models to model state uncertainties in state estimation and heating plant control tasks for 4th generation district heating systems. The idea of hybrid models is to integrate machine learning models with established stochastic algorithms. In particular, we employ surrogate models that approximate thermal power flow calculations, i.e., the mapping from the thermal powers and feed-in temperatures at producers and consumers onto the grid states. The possibility of rapid evaluation of these surrogate models then enables the usage of classic sampling-based stochastic algorithms, omitting the necessity for parametric uncertainty representations. The thesis first presents novel algorithms to facilitate the efficient construction of the required surrogate models. Then, it shows hybrid approaches for state estimation and heating plant control for 4th generation district heating grids. The training of a surrogate model requires a large number of training samples. These samples can be generated by solving the thermal power flow for randomly generated input values. However, this approach is impeded by its high computational costs, as the thermal power flow is defined implicitly and is consequently solved via iterative algorithms. Instead, we propose an importance-sampling-based approach, wherein we define a Proxy distribution over the mass flow rates at consumers and suppliers. By initially drawing samples from this proxy distribution, training samples can be obtained via an iterationfreealgorithm. In our numerical tests, our approach reduces the computation times for generating training samples by up to two orders of magnitude and achieves high effective sample rates of over 99.9% in all test settings. Our first application then is the state estimation task. Here, the objective is to approximate the posterior distribution over the grid states, given a prior distribution over the thermal powers and some measurements of selected grid states. We propose to employ a Markov Chain Monte Carlo algorithm to generate samples which represent the desired posterior distribution. As it is not possible to generate grid state samples directly, the Markov chains propose candidates consisting of thermal power values. For each candidate, the corresponding grid state is computed by solving the thermal power flow problem and the state is then compared against the measured values. By approximating the thermal power flow computations with a surrogate model, this procedure becomes computationally feasible to be used in real-time operation. Experiments on test heating grids demonstrate hat the approach is capable of approximating complex uncertainty distributions over grid state and achieves low computation times. Our second application for hybrid models is the control of heating grids, specifically ofthe powers and Feed-in temperatures of the heating plants. Depending on the uncertain thermal demand, these setpoints should be adjusted such that a grid state within predefined bounds is maintained. The resulting control task is formulated as a nonlinear stochastic optimal control problem. The uncertain thermal demands are, again, represented via samples. Whereas the decision variables of the optimal control problem are located in the space of thermal powers and feed-in temperatures, some boundary constraints, e.g., minimal supply temperatures at consumer sites, are defined in the space of grid states. These constraints can be efficiently verified, by passing the setpoints and thermal demands samples through a surrogate model, which approximates the thermal power flow. Tests on a grid with two heat suppliers demonstrate that our proposed hybrid approach clearly outperforms the linearisation-based baseline in terms of optimisation costs and risk of constraint violations while achieving low computation times. The two applications presented here demonstrate that hybrid approaches can adequately represent uncertainty distributions over grid states in district heating grids. They allow for estimating the probability of grid constraint violations as well as deducing optimal responses to minimise this probability. The approaches have low computation times, which allows them to be used in online operational settings. Overall, the proposed hybrid models allow the utilisation of the flexibility of 4th generation district heating networks without requiring a complete set of measurements first
Occlusion Detection for Face Image Quality Assessment
No full textThe accuracy of 2D-image-based face recognition systems depends on the quality of the compared face images. One factor that affects the recognition accuracy is the occlusion of face regions, e.g., by opaque sunglasses or medical face masks. Being able to assess the quality of captured face images can be useful in various scenarios, e.g., in a border entry/exit system. This paper discusses a method for detecting face occlusions and for measuring the percentage of occlusion of a face using face segmentation and face landmark estimation techniques. The method is applicable to arbitrary face images, not only to frontal or nearly frontal face images. The method was evaluated by applying it to publicly available face image data sets and analyzing the results obtained. The evaluation shows that the proposed method enables the effective detection of face occlusions
Superhydrophobe, wasserbasierte und regenerative Papierbeschichtungen: Entwicklung innovativer Co-Kristallisationsmaterialien aus biobasierten Celluloseestern und Wachsen
No full textDer Feuchtigkeitsschutz von Papier ist für zahlreiche Anwendungen von zentraler Bedeutung. Superhydrophobe Beschichtungen stellen eine vielversprechende Lösung für höchstmögliche Wasserresistenz dar, doch ihre Implementierung im industriellen Maßstab ist nach wie vor herausfordernd. In dieser Arbeit wird eine neuartige, nachhaltige Beschichtung auf Basis von Cellulosestearoylester (CSE) und Ethylenglycoldistearat (EGDS) entwickelt, die durch spontane Kristallisation beim Abkühlen aus dem geschmolzenen Zustand charakteristische flower-like Mikrostrukturen ausbildet und exzellente wasserabweisende Eigenschaften aufweist. Die Beschichtung zeichnet sich durch ihre thermische Regenerierbarkeit, die Möglichkeit einer wasserbasierten Applikation sowie ihre Integration in industrielle Papierverarbeitungsprozesse inkl. Recycling aus. Darüber hinaus wird ihr Potenzial für innovative Anwendungen, insbesondere papierbasierte Nebelfänger zur effizienten Wassergewinnung aus Nebel, untersucht. Die Forschungsergebnisse verdeutlichen die Relevanz dieser Technologie für nachhaltige funktionale Oberflächen und eröffnen neue Perspektiven für ökologische und technologische Anwendungsfelder
Ermittlung und quantitative Beschreibung des Schwellenwertverhaltens von IN718 unter Hochtemperaturbedingungen
No full textZur Bewertung der Kritikalität von Anfangsdefekten in rotierenden Komponenten von Turbomaschinen, die hochzyklischen Ermüdungsbeanspruchungen ausgesetzt sind, wird auf zyklische Risswiderstandskurven (R-Kurven), die das Schwellenwertverhalten gegen Rissausbreitung physikalisch kurzer Ermüdungsrisse beschreiben, zurückgegriffen. Im Rahmen dieser Arbeit wird eine Versuchstechnik zur experimentellen Ermittlung von zyklischen R-Kurven bei Raumtemperatur auf Hochtemperaturbedingungen übertragen. Mithilfe von soft- und hardwareseitigen Optimierungen eines bestehenden Prüfstands zur Durchführung von Rissfortschrittsversuchen kann das Schwellenwertverhalten von Nickelbasislegierungen am Beispiel von drei unterschiedlich (zwei herkömmlich gefertigte - geschmiedet und gegossen und eine additiv gefertigte - im PBF-LB/M Prozesse hergestellte) gefertigten Materialvarianten von IN718 unter Hochtemperaturbedingungen
bei den drei Lastverhältnissen −1, 0 und 0,5 ermittelt werden. Insbesondere die fehlende optische Zugänglichkeit der untersuchten Proben sowie die für hochfeste Materialien typischen sehr kurzen Rissverlängerungen stellen die größten Herausforderungen beim Erreichen dieses Ziels dar. Basierend auf den experimentell ermittelten zyklischen R-Kurven werden Methoden entwickelt, mit denen die Anteile aktiver Rissschließmechanismen, die das Schwellenwertverhalten maßgeblich beeinflussen, quantifiziert werden können. Der Einfluss von plastischen Verformungen um die Rissspitze und entlang der Rissflanken wird über eine Finite Elemente basierte Rissfortschrittssimulation quantifiziert, wobei der Beanspruchungsverlauf aus den experimentell ermittelten zyklischen R-Kurven gewonnen und für diese Simulation risslängenabhängig vorgegeben wird. Auf diese Weise werden plastizitätsinduzierte Rissschließanteile für IN718 bei 650 °C für die drei untersuchten Lastverhältnisse −1, 0 und 0,5 quantifiziert. Detaillierte Untersuchungen dieser Rissschließanteile zeigen, dass eine Betrachtung auf Basis der Maximalbeanspruchung bei unterschiedlichen Lastverhältnissen zur Bewertung des Anteils an plastitzitätsinduziertem Rissschließen,
wie sie in analytischen Ansätzen angewendet wird, alleine nicht ausreicht. Vielmehr muss die Beanspruchungsschwingbreite in die Ergebnisinterpretation miteinbezogen werden. Der Einfluss von sich ausbildenden Oxidschichten oder von akkumulierenden Oxidpartikeln auf das Rissausbreitungsverhalten wird über den Vergleich zwischen zyklischen R-Kurven, die an Luft ermittelt werden, mit solchen, die im Vakuum ermittelt werden, quantifiziert. Die sehr ähnliche chemische Zusammensetzung der drei untersuchten Materialvarianten von IN718 sorgt für vergleichbare Anteile von oxidinduziertem Rissschließen zwischen den Materialzuständen. Sie fallen dabei für alle drei untersuchten Lastverhältnisse sehr gering verglichen mit dem Gesamtrissschließanteilen aus, da dieses Material bei der Versuchstemperatur von 650 °C eine sehr gute Korrosionsbeständigkeit aufweist. Gestützt werden diese Untersuchung durch die Auswertung von isothermen Auslagerungsversuchen bei 650 °C, die das sehr ähnliche Oxidationsverhalten und die geringe Oxidationsneigung der Materialvarianten nochmal verdeutlichen. Über die Berücksichtigung der plastizitätsinduzierten und oxidinduzierten Rissschließanteile in den Gesamtrissschließanteilen werden
rauheitsinduzierte Rissschließanteile für die drei Materialvarianten unter den Versuchsbedingungen ermittelt. Die Verzahnung von Rissflanken, die zu rauheitsinduziertem Rissschließen führt, wird mithilfe von fraktographischen Untersuchungen der Bruchflächen an Proben aus Schwellenwertversuchen interpretiert. Die Übertragung der experimentellen Versuchstechnik zur Ermittlung zyklischer R-Kurven von Raumtemperaturauf Hochtemperaturbedingungen und die Entwicklung einer Vorgehensweise zur Quantifizierung aktiver Rissschließmechanismen im Kurzrissbereich ermöglichen eine Vertiefung des Verständnisses des Ausbreitungsverhaltens physikalisch kurzer Risse in Nickelbasiswerkstoffen. Auf diese Weise wird ein wichtiger Beitrag
zur bruchmechanischen Bewertung der Kritikalität von Anfangsdefekten bezogen auf die Lebensdauer in Bauteilen unter hochzyklischer Ermüdungsbeanspruchung geleistet
Exploration and Assessment Methods for Petrothermal Potentials in Crystalline Basements
No full textGeothermal energy offers vast potential for sustainable heat and electricity production. Developing and exploiting this potential applying hydrothermal systems is often bound to permeable horizons or fault zone sections. Hydrothermal potential is therefore spatially constrained, and consumer and potential need to spatially overlap for economic exploitation. Petrothermal systems on the other hand, target tight reservoir or basement formations that are ubiquitously present. Therefore, petrothermal potential can be exploited in vicinity of heat or power consumer.
Low natural permeability needs to be compensated by engineering processes e.g., reservoir stimulation and is therefore artificially enhanced. By such engineering processes, natural petrothermal potential can be exploited with e.g., enhanced (or engineered) geothermal systems (EGS). Stimulation can be performed hydraulically, chemically, or thermally but reservoir stimulation also increases initial investment. However, economic feasibility and success of petrothermal reservoir systems depend on a variety of chemical and physical properties. Before development, petrothermal potentials need to be evaluated carefully on both, a regional scale to identify high-potential areas but also on a reservoir scale to build detailed reservoir models. The presented assessment offers a scalable scheme to evaluate the natural or geogenic petrothermal potential based on physical input parameters such as petrophysical properties, reservoir volume and temperature. The scheme further allows to assess EGS potentials considering chemical constraints such as petrography or radiogenic heat production but also geological or structural circumstances such as reservoir geometry or depth or engineering factors such as the recovery factor. The geothermal potential is assessed and displayed on a parameterized 3D geological model. Geogenic potential is quantitatively evaluated based on heat in place calculations. Furthermore, in a qualitative potential assessment which is based on an analytic hierarchy process (AHP) for weighting input factors, EGS potentials are qualified.
The assessment scheme is demonstrated on a regional scaled basement reservoir in the Hessian Mid-German Crystalline High. Potentials are evaluated on a total of eight modeling units, representing geological units of the Odenwald such as Frankenstein complex, Flasergranitoid zone, Tromm and Weschnitz intrusion but also Heidelberg granite. These units are traced beneath the sedimentary cover of the Upper Rhine Graben using geophysical survey data. Additionally, 3D gravimetric modeling helped to delineate three modeling units beneath the Buntsandstein cover of the Odenwald and adjacent NE striking Mid-German Crystalline High in the Spessart and Rhön region. Each modeling unit is studied extensively in a petrophysical property screening on outcrop analogues and if available completed with well samples. The dataset is round off with data gathered in a petrophysical and geochemical survey in Qinghai, China, investigating a comparable reservoir system as well as literature data if necessary
Automated Cephalometric Landmark Localization using a Coupled Shape Model
No full textCephalometric analysis is an important method in orthodontics for the diagnosis and treatment of patients. It is performed manually in clinical practice, therefore automation of this time consuming task would be of great assistance. In order to provide dentists with such tools, a robust and accurate identification of the necessary landmarks is required. However, poor image quality of lateral cephalograms like low contrast or noise make this task difficult. In this paper, an approach for automatic landmark localization is presented and used to find 19 landmarks in lateral cephalometric images. An initial predicting of the individual landmark locations is done by using a 2-D coupled shape model to utilize the spatial relation between landmarks and other anatomical structures. These predictions are refined with a Hough Forest to determine the final landmark location. The approach achieves competitive performance with a successful detection rate of 70.24% on 250 images for the clinically relevant 2mm accuracy range
Breaking it down, to build it back up: Attacks and Defenses for RPKI
No full textThe Border Gateway Protocol (BGP) is the glue that holds the Internet together and enables packets to reach their destinations. However, BGP is not secure by design. It is vulnerable to hijacking attacks and route leaks, and the community has tried for decades to find a solution for this design error.
The Resource Public Key Infrastructure (RPKI) has emerged as the only currently feasible solution to BGP's woes. It is an intuitive, flexible infrastructure that allows any BGP security protocol that relies on distributed, cryptographically verifiable data, to get incorporated and effectively deployed across BGP routers. RPKI already covers over 50% of network prefixes and is deployed by at least 27% of networks in the world. It has already proven its benefits over the past few years due to many BGP hijacks, which went unnoticed by those deploying RPKI, but caused severe consequences for those who didn't. RPKI has proven itself so successful, that the Federal Communications Commission (FCC) published a recommendation on routing security, where they suggested mandating the use of RPKI for all major ISP providers in the US. However, not all that glitters is gold. While RPKI is an excellent approach to solving the security issues of BGP, it is not perfect.
In this work, the author evaluates the security of the RPKI ecosystem as a whole, and that of all RPKI software components individually. The author discovers a range of attacks that lead to the silent downgrade of RPKI protection, or the Denial-of-Service (DoS) of RPKI components, and evaluates current RPKI deployment practices only to discover trends that are concerning when extrapolated to full RPKI deployment. Finally, this work also provides the first attempt to mitigate all above mentioned RPKI issues through a distributed infrastructure that enhances RPKI component security and efficiency, and is backwards compatible with the current RPKI environment.
This thesis is based on work published in 6 full papers and 2 posters in international academic conferences. This work resulted in the discovery of 18 vulnerabilities in RPKI code, and the issuance of 5 Common Vulnerabilities and Exposures (CVEs)
Benchmarking Analytical Query Processing in Intel SGXv2
No full textTrusted Execution Environments (TEEs), such as Intel’s Software Guard Extensions (SGX), are increasingly being adopted to address trust and compliance issues in the public cloud. Intel SGX’s second generation (SGXv2) addresses many limitations of its predecessor (SGXv1), offering the potential for secure and efficient analytical cloud DBMSs. We assess this potential and conduct the first in-depth evaluation study of analytical query processing
algorithms inside SGXv2. Our study reveals that, unlike SGXv1, state-of-the-art algorithms like radix joins and SIMD-based scans are a good starting point for achieving high-performance query processing inside SGXv2. However, subtle hardware and software differences still influence code execution inside SGX enclaves and cause substantial overheads. We investigate these differences and propose new optimizations to bring the performance inside enclaves on par with native code execution outside enclaves