Vorträge
Vorträge 211 bis 220 von 759 | Gesamtansicht
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| Datum | Zeit | Ort | Vortrag |
|---|---|---|---|
| 14.07.22 | 15:00 | Am Schwarzenberg-Campus 3 (E), Raum 3.074 |
Skeleta and shapes related to random tessellations Daniel Hug, Karlsruher Institut für Technologie (KIT), Fakultät für Mathematik, Institut für Stochastik |
| 11.07.22 | 15:00 | Am Schwarzenberg-Campus 3 (E), Raum 3.074 |
Spectral inequalities and observability with sensor sets of decaying density Albrecht Seelmann, TU Dortmund, Fakultät für Mathematik We discuss spectral inequalities and observability for the harmonic oscillator and more general Schrödinger operators with confinement potentials on the whole space. It turns out that the (super-)exponential decay of the corresponding eigenfunctions allows to consider sensor sets with a density that exhibits a certain decay. This, in particular, permits sensors with finite measure. |
| 07.07.22 | 14:00 | Am Schwarzenberg-Campus 3 (E), Raum 3.074 & Zoom |
Asymptotic-preserving and hybrid finite-volume/Monte-Carlo methods for kinetic equations in the plasma edge of a fusion reactor* Giovanni Samaey, KU Leuven Nuclear fusion reactor design crucially depends on numerical simulation. The plasma can usually be modeled using fluid equations (for mass, momentum and energy). However, the reactor also contains neutral (non-charged) particles (which are important in its operation), of which both the position and velocity distribution is important. This leads to a Boltzmann-type transport equation that needs to be discretised with a Monte Carlo method. In high-collisional regimes, the Monte Carlo simulation describing the evolution of neutral particles becomes prohibitively expensive, because each individual collision needs to be tracked. |
| 07.07.22 | 10:30 | Big Blue Button |
Objektivierung des Fahrkomforts automatisierter Fahrzeuge [Masterarbeit] Nele Thomsen |
| 04.07.22 | 11:30 | Am Schwarzenberg-Campus 3 (E), Raum 3.074 |
Gaussian Kernel Ridge Regression using Matrix Decompositions for Preconditioning (Bachelorarbeit) Ons Gharbia |
| 01.07.22 | 09:00 | TUHH, Raum B0.001 und in Zoom |
WARTESCHLANGENTHEORIE IN ROBOTISIERTEN LAGERHALTUNGSSYSTEMEN [Habilitationskolloquium] Karsten Kruse Aufgrund des zunehmenden Wachstums im E-Commerce-Sektor haben robotisierte Lagerhaltungs- |
| 27.06.22 | 15:00 | Zoom |
Recent investigations on spectral sets and Crouzeix’s conjecture Felix Schwenninger, via Zoom We discuss recent developments around approaches to Crouzeix's conjecture, the statement that the numerical range is a 2 spectral set for any complex square matrix. This includes spectral constants for specific classes of operators. |
| 20.06.22 | 15:00 | Zoom |
An efficient numerical method for the Maxey-Riley equation Julio Urizarna Carasa The Maxey-Riley Equation (MRE) models the motion of a finite-sized, spherical particle moving in a fluid. Applications using the MRE are, for example, the study of the spread of Coronavirus particles in a room, the formation of clouds and the so-called marine snow. The MRE is a second-order, implicit integro-differential equation with a singular kernel at initial time. For over 35 years, researchers used approximations and numerical schemes with high storage requirements or ignored the integral term, although its impact can be relevant. A major break-through was reached in 2019, when Prasath et al. mapped the MRE to a time-dependent Robin-type boundary condition of the 1D Heat equation, thus removing the requirement to store the full history. They provided an implicit integral form of the solution by using the so-called Fokas method that could be later solved with numerical scheme and a nonlinear solver. While Prasath et al.’s method can deliver numerical solutions of very high accuracy, the need to evaluate nested integrals makes it computationally costly and it becomes impractical for computing trajectories of a large number of particles. In the talk, we will present a finite differences approach that it is not only storage efficient but also much faster. We will compare our approach to both Prasath et al.’s method as well as a to the numerical schemes developed by A. Daitche in 2013 for direct integration of the original Maxey-Riley equation with integral term. |
| 16.06.22 | 15:00 | Online |
Solving the traveling salesman problem via deep reinforcement learning [Masterarbeit] Darius Schaub |
| 10.06.22 | 11:00 | Am Schwarzenberg-Campus 3 (E), Raum 3.074 und Zoom |
Planung und Optimierung von Schnittpfaden für dynamisch begrenzte Kinematiken bzgl. Ausschussreduktion [Masterarbeit] Constantin Riß |
* Vortrag im Rahmen des Kolloquiums für Angewandte Mathematik





