Bøger udgivet af Karlsruher Institut Fur Technologie

This work is about the inverse dynamics of underactuated flexible mechanical systems governed by quasi-linear hyperbolic partial differential equations subjected to time-varying Dirichlet boundary conditions that are enforced by unknown, spatially disjunct, hence non-collocated Neumann boundary conditions.

Accompanied with the development of the wireless communication technologies, the high data traffic is more necessary for civil and industrial applications than ever The concept of an intelligent reflective surface (IRS) has attracted considerable attention recently as a low-cost solution. As the main contribution, the dissertation creates new state-of-the-art and formulates a solid milestone for the IRS research field.

Ihrer Arbeit in der Originalsprache: This work aims at identifying relevant road surface characteristics to mitigate tire-road noise of free-rolling tires using a systematic approach. As using open porous roads is already known as an efficient measure to reduce tire rolling noise, this study will focus on compact road surfaces which have a low acoustic absorption. Measurements on standardized ISO 10844 test tracks and on public roads are used to study the norm's representativity and its completeness.

In this work, the first simulation model of oxygen depolarized cathodes (ODC), which are silver catalyst-based gas diffusion electrodes, is presented that considers the phase equilibrium of the gas-liquid interface and structure-related inhomogeneities in electrolyte distribution. By means of the model it has been identified that mass transport of water and ions in the liquid phase is a crucial factor for electrode performance and how it is influenced by the electrode structure.

Die Forschung im Bereich der Mikro-Energiegewinnungssysteme wurde durch den Bedarf an autarken, stabilen Energiequellen für vernetzte drahtlose Sensoren vorangetrieben. Abwärme, insbesondere bei Temperaturen unter 200 °C, stellt eine vielversprechende, aber mit den derzeitigen Umwandlungstechnologien schwer zu gewinnende Energiequelle dar. Research into micro energy harvesting systems has been driven by the need for self-sustaining, stable power sources for interconnected wireless sensors. Waste heat, particularly at temperatures below 200 °C, presents a promising but challenging energy source to recover using current conversion technology.

The work represents a toolbox for the design of a highly efficient photocatalytic process for solar-driven synthesis. The focus is the optimization of photoreactors and photocatalysts. The described photoreactor design strategy is based on numerical methods mapping radiation transport and additive manufacturing delivering prototypes. The photocatalyst engineering is based on suitable photocatalyst support strategies and a method for the determination of the quantum yield in photoreactions.

During the evolvement of autonomous driving technology, obtaining reliable 3-D environmental information is an indispensable task in approaching safe driving. The operational behavior of automotive radars can be precisely evaluated in a virtual test environment by modeling its surrounding, specifically vulnerable road users (VRUs). Such a realistic model can be generated based on the radar cross section (RCS) and Doppler signatures of a VRU. Therefore, this work proposes a high-resolution RCS measurement technique to determine the relevant scattering points of different VRUs.

Companies can be valuable partners in delivering essential goods but must be appropriately motivated to participate in humanitarian crisis management. This work provides valuable insights into the status of humanitarian crisis management from the perspective of different stakeholders. It shows the potential of collaborative approaches, addressing the strengths and incentives of stakeholders accordingly.

In this study the technical and economic feasibility of a 380 kV, 5 kA resistive type superconducting fault current limiter was investigated. Conceptual designs were developed with superconducting tapes cooled by liquid nitrogen and arranged in bifilar coils. A cryostat was designed using FEM simulations taking into account the non-linear voltage distribution. For the complete system including current limiting reactors and cooling system, the investment and operation costs were calculated.

Ein Gyrotron wird in magnetisch eingeschlossenen Plasmaexperimenten für Heizung, Stromtrieb, Plasmastabilisierung und Plasmadiagnostik verwendet. In dieser Arbeit wird der erste Entwurf und Bau eines Mehrfrequenz-/Mehrzweck Pre-Prototyp Gyrotrons in koaxialer Technologie vorgestellt, das bei (136)/170/204 GHz mit einer Ausgangsleistung von 2 MW arbeitet. Dies ist der erste Schritt zum Betrieb bei Frequenzen bis zu 240 GHz unter Verwendung der Koaxialhohlraum-Gyrotrontechnologie. A gyrotron is used in magnetically confined plasma experiments for heating, current drive, plasma stabilization and plasma diagnostics. This work presents the first design and construction of a multi-frequency / multi-purpose coaxial-cavity pre-prototype gyrotron operating at (136)/170/204 GHz with an output power of 2 MW. It is the first step towards operating frequencies up to 240 GHz using the coaxial-cavity gyrotron technology.

Although tremendous progress has been made in Artificial Intelligence (AI), it entails new challenges. The growing complexity of learning tasks requires more complex AI components, which increasingly exhibit unreliable behaviour. In this book, we present a model-driven approach to model architectural safeguards for AI components and analyse their effect on the overall system reliability.

This work develops a motion planner that compensates the deficiencies from perception modules by exploiting the reaction capabilities of a vehicle. The work analyzes present uncertainties and defines driving objectives together with constraints that ensure safety. The resulting problem is solved in real-time, in two distinct ways: first, with nonlinear optimization, and secondly, by framing it as a partially observable Markov decision process and approximating the solution with sampling.

The understanding and interpretation of complex 3D environments is a key challenge of autonomous driving. Lidar sensors and their recorded point clouds are particularly interesting for this challenge since they provide accurate 3D information about the environment. This work presents a multimodal approach based on deep learning for panoptic segmentation of 3D point clouds. It builds upon and combines the three key aspects multi view architecture, temporal feature fusion, and deep sensor fusion.

Optical measurement methods are becoming increasingly important for high-precision production of components and quality assurance. The increasing demand can be met by modern imaging systems with advanced optics, such as light field cameras. This work explores their use in the deflectometric measurement of specular surfaces. It presents improvements in phase unwrapping and calibration techniques, enabling high surface reconstruction accuracies using only a single monocular light field camera.

This work presents a single molecular motor driven by the current in an STM. Its chiral functional group is supposed to perform a rotation in a preferred direction, proven by Binomial tests to be statistically significant. The rotation is proposedly driven by the chiral-induced spin selectivity effect (CISS). However, the studies of the rotation on the dependence on the lateral tip position, voltage and current indicate that he CISS is unlikely to cause the preferred rotation direction.

In the last decades, superconducting devices have emerged as a promising platform for quantum technologies, including quantum sensing and quantum computing. Their key elements are Josephson junctions, which allow for coherent supercurrent tunneling between two weakly linked superconductors. If such a junction is extended in one direction to a long junction, the superconducting phase difference can vary in space and time and may allow for quantized phase windings that drive supercurrent vortices.

The transport of bacteria in turbulent river-like environments is addressed, where bacterial populations are frequently encountered attached to solids. This transport mode is investigated by studying the transient settling of heavy particles in turbulent channel flows featuring sediment beds. A numerical method is used to fully resolve turbulence and finite-size particles, which enables the assessment of the complex interplay between flow structures, suspended solids and river sediment.

We investigate deep material networks (DMN). We lay the mathematical foundation of DMNs and present a novel DMN formulation, which is characterized by a reduced number of degrees of freedom. We present a efficient solution technique for nonlinear DMNs to accelerate complex two-scale simulations with minimal computational effort. A new interpolation technique is presented enabling the consideration of fluctuating microstructure characteristics in macroscopic simulations.

The aim of this work is to model and experimentally characterize the anisotropic material behavior of SMC composites on the macroscale with consideration of the microstructure. Temperature-dependent thermoelastic behavior and failure behavior are modeled and the corresponding material properties are determined experimentally. Additionally, experimental biaxial damage investigations are performed. A parameter identification merges modeling and experiments and validates the models.

Configuring an anomaly-based Network Intrusion Detection System for cybersecurity of an industrial system in the absence of information on networking infrastructure and programmed deterministic industrial process is challenging. Within the research work, different self-learning frameworks to analyze passively captured network traces from PROFINET-based industrial system for protocol-based and process behavior-based anomaly detection are developed, and evaluated on a real-world industrial system.

I report on applications of slicing and program dependence graphs (PDGs) to software security. Moreover, I propose a framework that generalizes both data-flow analysis on control-flow graphs and slicing on PDGs. This framework can be used to systematically derive data-flow-like analyses on PDGs that go beyond slicing. I demonstrate that data-flow analysis can be systematically applied to PDGs and show the practicability of my approach.

Phosphorus is a crucial element in agriculture to feed the fast-growing global population. Its sustainable supply has ecological, social and human dimensions and it is classified as critical to European industries. On the other side, phosphate can also be critical for the producing countries as phosphate mining contributes to their national economies. This work investigates implications of environmental and social impacts and the resource governance to mitigate global phosphate criticality.

This cumulative habilitation thesis, proposes concepts for (i) modelling and analysing dependability based on architectural models of software-intensive systems early in development, (ii) decomposition and composition of modelling languages and analysis techniques to enable more flexibility in evolution, and (iii) bridging the divergent levels of abstraction between data of the operation phase, architectural models and source code of the development phase.