Reaction Kinetics of the Hydrogenation of Phenol in a Tubular Reactor

The reaction kinetic parameters for the hydrogenation of phenol to cyclohexanone are determined for the liquid phase reaction with the palladium catalyst supported on an electrospun PVDF membrane. Runs of the reactor were completed at catalyst loadings of 40, 50, and 60 g/m2, and tube diameters of 0.187 in and 0.25 in with a runtime of ten hours. One-dimensional and two-dimensional models of the experimental setup were developed. Fitting data to the one-dimensional model found that the pre-exponential factor was 2.50 x 104, the activation energy was 7.69 kJ/mol, and the order with respect to phenol was 0.171. The two-dimensional model improves on the one-dimensional model by accounting for diffusion from the bulk solution to the surface of the tube. A computer program using a genetic algorithm was written in order to fit the data to the two-dimensional model. The genetic algorithm was tested using an elliptic paraboloid for the objective function. The test program was found to require approximately 800000 generations reaching a convergence of 10-6. The results of the test were within three significant figures of the expected location of the minimum of the paraboloid

Mechanische und Strömungsmechanische Topologieoptimierung mit der Phasenfeldmethode

In engineering work, the optimization of the microstructure of a material, of mechanically loaded components and of components influencing the flow behaviour is important. Understanding the behavior of flows in geological structures can be used to optimize the design of geothermal power plants. In this thesis, methods from continuum mechanics, fluid mechanics and the phase field method are presented for the optimization of such processes and examples of optimizations are shown

Mechanische und Strömungsmechanische Topologieoptimierung mit der Phasenfeldmethode

In der Ingenieursarbeit ist die Optimierung ein Aspekt bei der Mikrostruktur eines Werkstoffs, bei mechanisch belasteter bzw. bei beströmter Bauteile und (geologischer) Strukturen. Vorgestellt werden Methoden für die Optimierung basierend auf der Kontinuumsmechanik, der Strömungsmechanik und der Phasenfeldmethode. Die Simulationen wurden mit dem Softwarepaket Parallel Algorithms for Crystal Evolution in 3D (Pace3D) durchgeführt

Bayesian optimization framework for data-driven materials design

The improvement of experimental design and the optimization of materials’properties with complex and partially unknown behaviors are common problems in material science. In the context of aqueous foams, the microstructure has a major influence on the properties of the resulting foam. Multiple interlinked parameters yield a large design space that requires tuning to tailor the microstructure evolution and resulting physical qualities. Our goal is a data-driven framework that uses machine learning to guide both experiments and simulations in an autonomous closed-loop. This iterative approach presents a valuable opportunity to accelerate materials development processes. A design of experiments methodology utilizing Bayesian Optimization is used to efficiently explore and exploit the search space, while minimizing the number of required evaluations. This approach allows to select the next most informative evaluation to perform, autonomously and adaptively learning from the already acquired data. The designed workflow is implemented into the data platform Kadi4Mat1, which provides the possibility of storing heterogeneous provenance data, along with a common workspace to integrate analysis methods and visualization. Our contribution within Kadi4Mat strongly relies on the reuse of data, and it is an example of the close interoperability between experimental and simulation research that the platform supports, in full alignment with the FAIR principles. Acknowledgements: This work is funded by the Ministry of Science, Research and Art Baden-Württemberg (MWK-BW) in the project MoMaF–Science Data Center, with funds from the state digitization strategy digital@bw (project number 57)

Brittle anisotropic fracture propagation in quartz sandstone: insights from phase-field simulations

<jats:title>Abstract</jats:title><jats:p>We developed a generalized multiphase-field modeling framework for addressing the problem of brittle fracture propagation in quartz sandstones at microscopic length scale. Within this numerical approach, the grain boundaries and crack surfaces are modeled as diffuse interfaces. The two novel aspects of the model are the formulations of (I) anisotropic crack resistance in order to account for preferential cleavage planes within each randomly oriented quartz grain and (II) reduced interfacial crack resistance for incorporating lower fracture toughness along the grain boundaries that might result in intergranular crack propagation. The presented model is capable of simulating the competition between inter- and transgranular modes of fracturing based on the nature of grain boundaries, while exhibiting preferred fracturing directions within each grain. In the full parameter space, the model can serve as a powerful tool to investigate the complicated fracturing processes in heterogeneous polycrystalline rocks comprising of grains of distinct elastic properties, cleavage planes, and grain boundary attributes. We demonstrate the performance of the model through the representative numerical examples.</jats:p&gt