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[Fakultät 3]

Basis functions meet spatiospectral localization: studies in spherical coordinates,
Herr Xinpeng Huang, M.Sc.

Freitag, 13. September 2024, 10:00 Uhr

Hörsaal Geophysik, MEI-0080, Otto-Meißer-Bau, Gustav-Zeuner-Straße 12, EG

In the presented work, we study several basis systems satisfying certain spatial/spectral localization conditions on the unit sphere and the ball embedded in Euclidean space of dimension d ≥ 2. For the spherical setup, we investigate some properties of the Hardy-Hodge decomposition for locally supported fields, and propose a multi-scale basis system that is suitable for modeling the Hardy components of such spherical vector fields and allows a simple mapping between the Hardy spaces. In the case of the solid ball, we revisit the Slepian spatiospectral concentration problems for the spherical Fourier-Jacobi, spherical Fourier-Bessel, as well as the multivariate algebraic polynomial systems. We investigate the bimodal distribution phenomena of the eigenvalues of concentration o perators and give an asymptotic characterization of the Shannon number for these setups, which lay a foundation for the utilization of associated Slepian bases and localized spectral analysis.

[Fakultät 4]

Development and characterization of MgO and TiO2 reinforced
Steel Ceramic Composites resistant to long-term contact with  
liquid aluminum alloys, Herr Dipl.-Ing. Piotr Malczyk

Freitag, 25. Oktober 2024, 14:00 Uhr

Hörsaal Silikattechnik, SIL-0118, Haus Silikattechnik, Agricolastraße 17, EG

The PhD thesis provides detailed description of a successful development of MgO and TiO2 particle reinforced Steel Ceramic Composites (SCC) for molten aluminum alloy applications. For this purpose, the influence of MgO and TiO2 addition and subsequent pre-oxidation surface treatment on the structure of SCCs and their corrosion resistance against long-term contact with liquid aluminum alloys was investigated. The initiation and progression of corrosion processes were thoroughly analyzed by means of newly developed DSC-aided corrosion tests, high temperature electrochemical studies and adapted wettability measurements. The gained insights led to the recognition of most important factors contributing to the corrosion, including both the electrochemical and the chemical driving forces arising between the SCCs and aluminum alloy. The evaluation of long-term corrosion resistance was performed with the help of finger immersion tests, crucible corrosion tests and subsequent SEM/EDS/EBSD and XRD analyses aiming at the determination of elements most prone to the dissolution in the liquid aluminum alloy and formation of corrosion phases. The pre-oxidized MgO reinforced SCC revealed superior corrosion resistance, being capable of withstanding more than 168 h of contact with liquid aluminum alloy.

[Fakultät 3]

Land subsidence analysis using InSAR, hydro-mechanical coupled
modeling, and machine learning: A case study in Hanoi, Vietnam,
Herr Hong Ha Tran, M.Sc.

Dienstag, 29. Oktober 2024, 14:00 Uhr

Hörsaal Helmut-Härtig-Bau, HHB-1035, Gustav-Zeuner-Straße 1, 1. OG

Land subsidence has been a long-standing issue in Hanoi, causing significant infrastructural damage in urban areas. This study uses PSInSAR and decomposition analysis on Sentinel-1 SAR data to analyze vertical and horizontal ground movements in the study area of Hanoi. A hydro-mechanical (HM) model utilizing Richards‘ mechanics was developed to assess the relation between groundwater drawdown, aquifer recharge, and settlement at selected sites of the study area. InSAR and HM model data revealed significant subsidence in southern Hanoi with rates over 20 mm/yr, while the northern region remained stable. Vertical displacement was primary, with negligible horizontal movement. The HM model indicated that ground-water withdrawal could be compensated by lateral inflow and surface water infiltration. A sensitivity analysis using machine learning (CatBoost model optimized with the GWO-WOA method) identified groundwater recharge and aquifer permeability as key factors in land subsidence. Keywords: land subsidence, InSAR, decomposition, hydro-mechanical modeling, OpenGeoSys, machine learning, CatBoost GWO-WOA, Hanoi