Universität Stuttgart
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Item Open Access Correlating and predicting thermal conductivity and self-diffusion from entropy scaling using PCP-SAFT(Stuttgart : Universität Stuttgart, Institut für Technische Thermodynamik und Thermische Verfahrenstechnik, 2022) Hopp, Madlen; Groß, Joachim (Prof. Dr.-Ing.)For a complete description and design of thermodynamic processes, knowledge of the properties of all substances involved is absolutely necessary. While the equilibrium properties are already well understood, there is still a lack of a handy description of the transport properties. Entropy scaling is an intriguingly simple approach for correlating and predicting transport properties of real substances and mixtures. As convincingly documented in the literature entropy scaling is indeed a firm concept for the shear viscosity of real substances, including hydrogen-bonding species and strongly non-spherical species and for mixtures. In this thesis, we investigate whether the entropy scaling approach is applicable for the thermal conductivity as well as the self-diffusion coefficients of pure substances. In accordance with the entropy scaling approach proposed by Y. Rosenfeld [Phys. Rev. A 1977, 15, 2545-2549], we observe that the thermal conductivity and the self-diffusion coefficient of real substances, once made dimensionless with an appropriate reference expression, only depend on residual entropy. We propose suitable reference expressions for both properties, to calculate the coefficients of pure substances from entropy scaling using the Perturbed-Chain Polar Statistical Associating Fluid Theory (PCP-SAFT) equation of state. Good entropy scaling behavior is found for the entire fluid region for water and more than 130 organic substances from various chemical families: linear and branched alkanes, alkenes, aldehydes, aromatics, ethers, esters, ketones, alcohols and acids. Models for both, thermal conductivity and self-diffusion coefficient, show satisfying robustness for extrapolating the coefficients to conditions rather distant from state points where experimental data is available. Additionally, a predictive group-contribution method for thermal conductivity based on entropy scaling is derived. The excess entropy for this approach is calculated using the group-contribution PCP-SAFT equation of state. The model is applicable for gaseous phases and for liquid-phase conditions covering wide ranges of temperature and pressure.Item Open Access Assessing fatigue life cycles of material X10CrMoVNb9-1 through a combination of experimental and finite element analysis(2023) Rahim, Mohammad Ridzwan Bin Abd; Schmauder, Siegfried; Manurung, Yupiter H. P.; Binkele, Peter; Dusza, Ján; Csanádi, Tamás; Ahmad, Meor Iqram Meor; Mat, Muhd Faiz; Dogahe, Kiarash JamaliThis paper uses a two-scale material modeling approach to investigate fatigue crack initiation and propagation of the material X10CrMoVNb9-1 (P91) under cyclic loading at room temperature. The Voronoi tessellation method was implemented to generate an artificial microstructure model at the microstructure level, and then, the finite element (FE) method was applied to identify different stress distributions. The stress distributions for multiple artificial microstructures was analyzed by using the physically based Tanaka-Mura model to estimate the number of cycles for crack initiation. Considering the prediction of macro-scale and long-term crack formation, the Paris law was utilized in this research. Experimental work on fatigue life with this material was performed, and good agreement was found with the results obtained in FE modeling. The number of cycles for fatigue crack propagation attains up to a maximum of 40% of the final fatigue lifetime with a typical value of 15% in many cases. This physically based two-scale technique significantly advances fatigue research, particularly in power plants, and paves the way for rapid and low-cost virtual material analysis and fatigue resistance analysis in the context of environmental fatigue applications.Item Open Access Smooth or with a snap! Biomechanics of trap reopening in the Venus flytrap (Dionaea muscipula)(2022) Durak, Grażyna M.; Thierer, Rebecca; Sachse, Renate; Bischoff, Manfred; Speck, Thomas; Poppinga, SimonFast snapping in the carnivorous Venus flytrap (Dionaea muscipula) involves trap lobe bending and abrupt curvature inversion (snap‐buckling), but how do these traps reopen? Here, the trap reopening mechanics in two different D. muscipula clones, producing normal‐sized (N traps, max. ≈3 cm in length) and large traps (L traps, max. ≈4.5 cm in length) are investigated. Time‐lapse experiments reveal that both N and L traps can reopen by smooth and continuous outward lobe bending, but only L traps can undergo smooth bending followed by a much faster snap‐through of the lobes. Additionally, L traps can reopen asynchronously, with one of the lobes moving before the other. This study challenges the current consensus on trap reopening, which describes it as a slow, smooth process driven by hydraulics and cell growth and/or expansion. Based on the results gained via three‐dimensional digital image correlation (3D‐DIC), morphological and mechanical investigations, the differences in trap reopening are proposed to stem from a combination of size and slenderness of individual traps. This study elucidates trap reopening processes in the (in)famous Dionaea snap traps - unique shape‐shifting structures of great interest for plant biomechanics, functional morphology, and applications in biomimetics, i.e., soft robotics.Item Open Access Über die Lösung der Navier-Stokes-Gleichungen mit Hilfe der Moore-Penrose-Inversen des Laplace-Operators im Vektorraum der Polynomkoeffizienten(2024) Große-Wöhrmann, Bärbel; Resch, Michael (Prof. Dr.-Ing.)Die bekannten numerischen Standard-Verfahren zur Lösung partieller Differentialgleichungen basieren auf einer räumlichen Diskretisierung des Berechnungsgebiets. Ihre Performance und Skalierbarkeit auf modernen massiv-parallelen Höchstleistungsrechnern ist von der Verfügbarkeit effizienter numerischer Verfahren zur Lösung linearer Gleichungssysteme abhängig. Angesichts grundlegender Herausforderungen erscheint die Entwicklung neuer Lösungsansätze sinnvoll. Ich stelle in dieser Arbeit einen Polynomansatz zur Lösung partieller Differentialgleichungen vor, der nicht auf einer räumlichen Diskretisierung beruht und mit Hilfe der Moore-Penrose-Inversen des Laplace-Operators die Entkopplung der Navier-Stokes-Gleichungen ermöglicht. Dabei ist der Grad der Polynome nicht grundsätzlich beschränkt, so dass eine hohe räumliche Auflösung erreicht werden kann.Item Open Access Depth from axial differential perspective(2022) Faulhaber, Andreas; Krächan, Clara; Haist, TobiasWe introduce an imaging-based passive on-axis technique for measuring the distance of individual objects in complex scenes. Two axially separated pupil positions acquire images (can be realized simultaneously or sequentially). Based on the difference in magnification for objects within the images, the distance to the objects can be inferred. The method avoids some of the disadvantages of passive triangulation sensors (e.g., correspondence, shadowing), is easy to implement and offers high lateral resolution. Due to the principle of operation it is especially suited for applications requiring only low to medium axial resolution. Theoretical findings, as well as follow-up experimental measurements, show obtainable resolutions in the range of few centimeters for distances of up to several meters.Item Open Access Multiscale modeling and stability analysis of soft active materials : from electro- and magneto-active elastomers to polymeric hydrogels(Stuttgart : Institute of Applied Mechanics, 2023) Polukhov, Elten; Keip, Marc-André (Prof. Dr.-Ing.)This work is dedicated to modeling and stability analysis of stimuli-responsive, soft active materials within a multiscale variational framework. In particular, composite electro- and magneto-active polymers and polymeric hydrogels are under consideration. When electro- and magneto-active polymers (EAP and MAP) are fabricated in the form of composites, they comprise at least two phases: a polymeric matrix and embedded electric or magnetic particles. As a result, the obtained composite is soft, highly stretchable, and fracture resistant like polymer and undergoes stimuli-induced deformation due to the interaction of particles. By designing the microstructure of EAP or MAP composites, a compressive or a tensile deformation can be induced under electric or magnetic fields, and also coupling response of the composite can be enhanced. Hence, these materials have found applications as sensors, actuators, energy harvesters, absorbers, and soft, programmable, smart devices in various areas of engineering. Similarly, polymeric hydrogels are also stimuli-responsive materials. They undergo large volumetric deformations due to the diffusion of a solvent into the polymer network of hydrogels. In this case, the obtained material shows the characteristic behavior of polymer and solvent. Therefore, these materials can also be considered in the form of composites to enhance the response further. Since hydrogels are biocompatible materials, they have found applications as contact lenses, wound dressings, drug encapsulators and carriers in bio-medicine, among other similar applications of electro- and magneto-active polymers. All above mentioned favorable features of these materials, as well as their application possibilities, make it necessary to develop mathematical models and numerical tools to simulate the response of them in order to design pertinent microstructures for particular applications as well as understand the observed complex patterns such as wrinkling, creasing, snapping, localization or pattern transformations, among others. These instabilities are often considered as failure points of materials. However, many recent works take advantage of instabilities for smart applications. Investigation of these instabilities and prediction of their onset and mode are some of the main goals of this work. In this sense, the thesis is organized into three main parts. The first part is devoted to the state of the art in the development, fabrication, and modeling of soft active materials as well as the continuum mechanical description of the magneto-electro-elasticity. The second part is dedicated to multiscale instabilities in electro- and magneto-active polymer composites within a minimization-type variational homogenization setting. This means that the highly heterogeneous problem is not resolved on one scale due to computational inefficiency but is replaced by an equivalent homogeneous problem. The effective response of the macroscopic homogeneous problem is determined by solving a microscopic representative volume element which includes all the geometrical and material non-linearities. To bridge these two scales, the Hill-Mandel macro-homogeneity condition is utilized. Within this framework, we investigate both macroscopic and microscopic instabilities. The former are important not only from a physical point of view but also from a computational point of view since the macroscopic stability (strong ellipticity) is necessary for the existence of minimizers at the macroscopic scale. Similarly, the investigation of the latter instabilities are also important to determine the pattern transformations at the microscale due to external action. Thereby the critical domain of homogenization is also determined for computation of accurate effective results. Both investigations are carried out for various composite microstructures and it is found that they play a crucial role in the response of the materials. Therefore, they must be considered for designing EAP and MAP composites as well as for providing reliable computations. The third part of the thesis is dedicated to polymeric hydrogels. Here, we develop a minimization-based homogenization framework to determine the response of transient periodic hydrogel systems. We demonstrate the prevailing size effect as a result of a transient microscopic problem, which has been investigated for various microstructures. Exploiting the elements of the proposed framework, we explore the material and structural instabilities in single and two-phase hydrogel systems. Here, we have observed complex experimentally observed and novel 2D pattern transformations such as diamond-plate patterns coupled with and without wrinkling of internal surfaces for perforated microstructures and 3D pattern transformations in thin reinforced hydrogel composites. The results indicate that the obtained patterns can be controlled by tuning the material and geometrical parameters of the composite.Item Open Access Magnetic putty as a reconfigurable, recyclable, and accessible soft robotic material(2023) Li, Meng; Pal, Aniket; Byun, Junghwan; Gardi, Gaurav; Sitti, MetinMagnetically hard materials are widely used to build soft magnetic robots, providing large magnetic force/torque and macrodomain programmability. However, their high magnetic coercivity often presents practical challenges when attempting to reconfigure magnetization patterns, requiring a large magnetic field or heating. In this study, magnetic putty is introduced as a magnetically hard and soft material with large remanence and low coercivity. It is shown that the magnetization of magnetic putty can be easily reoriented with maximum magnitude using an external field that is only one‐tenth of its coercivity. Additionally, magnetic putty is a malleable, autonomous self‐healing material that can be recycled and repurposed. The authors anticipate magnetic putty could provide a versatile and accessible tool for various magnetic robotics applications for fast prototyping and explorations for research and educational purposes.Item Open Access Physics-informed regression of implicitly-constrained robot dynamics(2022) Geist, Andreas René; Allgöwer, Frank (Prof. Dr.-Ing.)The ability to predict a robot’s motion through a dynamics model is critical for the development of fast, safe, and efficient control algorithms. Yet, obtaining an accurate robot dynamics model is challenging as robot dynamics are typically nonlinear and subject to environment-dependent physical phenomena such as friction and material elasticities. The respective functions often cause analytical dynamics models to have large prediction errors. An alternative approach to analytical modeling forms the identification of a robot’s dynamics through data-driven modeling techniques such as Gaussian processes or neural networks. However, solely data-driven algorithms require considerable amounts of data, which on a robotic system must be collected in real-time. Moreover, the information stored in the data as well as the coverage of the system’s state space by the data is limited by the controller that is used to obtain the data. To tackle the shortcomings of analytical dynamics and data-driven modeling, this dissertation investigates and develops models in which analytical dynamics is being combined with data-driven regression techniques. By combining prior structural knowledge from analytical dynamics with data-driven regression, physics-informed models show improved data-efficiency and prediction accuracy compared to using the aforementioned modeling techniques in an isolated manner.Item Open Access Single-band versus two-band description of magnetism in infinite-layer nickelates(2023) Plienbumrung, Tharathep; Daghofer, Maria; Morée, Jean-Baptiste; Oleś, Andrzej M.We present a weak-coupling analysis of magnetism in infinite-layer nickelates, where we compare a single-band description with a two-band model. Both models predict that (i) hybridization due to hopping is negligible, and (𝑖𝑖) the magnetic properties are characterized by very similar dynamic structure factors, 𝑆(𝑘⃗ ,𝜔), at the points (𝜋,𝜋,0) and (𝜋,𝜋,𝜋). This gives effectively a two-dimensional description of the magnetic properties.Item Unknown Performance comparison of CFD microbenchmarks on diverse HPC architectures(2024) Galeazzo, Flavio C. C.; Garcia-Gasulla, Marta; Boella, Elisabetta; Pocurull, Josep; Lesnik, Sergey; Rusche, Henrik; Bnà, Simone; Cerminara, Matteo; Brogi, Federico; Marchetti, Filippo; Gregori, Daniele; Weiß, R. Gregor; Ruopp, AndreasOpenFOAM is a CFD software widely used in both industry and academia. The exaFOAM project aims at enhancing the HPC scalability of OpenFOAM, while identifying its current bottlenecks and proposing ways to overcome them. For the assessment of the software components and the code profiling during the code development, lightweight but significant benchmarks should be used. The answer was to develop microbenchmarks, with a small memory footprint and short runtime. The name microbenchmark does not mean that they have been prepared to be the smallest possible test cases, as they have been developed to fit in a compute node, which usually has dozens of compute cores. The microbenchmarks cover a broad band of applications: incompressible and compressible flow, combustion, viscoelastic flow and adjoint optimization. All benchmarks are part of the OpenFOAM HPC Technical Committee repository and are fully accessible. The performance using HPC systems with Intel and AMD processors (x86_64 architecture) and Arm processors (aarch64 architecture) have been benchmarked. For the workloads in this study, the mean performance with the AMD CPU is 62% higher than with Arm and 42% higher than with Intel. The AMD processor seems particularly suited resulting in an overall shorter time-to-solution.