SCCS Colloquium - Oct 9, 2019
|Date:||October 9, 2019|
|Time:||15:00 - 16:00|
Fritz Hofmeier: Applying the Spatially Adaptive Combination Technique to Uncertainty Quantification
This is a Bachelor's thesis submission talk, in German. Fritz is advised by Michael Obersteiner.
The topic of this bachelor thesis is the utilization of the single-dimension spatially adaptive sparse grid refinement strategy for uncertainty quantification. Frequent uncertainty quantification tasks are the calculation of moments and polynomial chaos expansion coefficients. Since these calculations require weighted multidimensional integration, the sparseSpACE Python framework is extended to support probability distributions as weight functions for high-dimensional adaptive quadrature. The test results indicate that for composite trapezoidal quadrature the implemented weighted integration is more accurate than integration with the inverse transformation method.
Keywords: sparse grids, uncertainty quantification, weighted quadrature
Henri Rößler: Simulation of diffraction effects of sound waves
This is a Bachelor's thesis submission talk, in German. Henri is advised by Carsten Uphoff.
The objective of this thesis is to simulate the propagation of sound waves in virtual environments, in order to enable the auralization of diffraction effects. To accomplish this efficiently, without having to simulate each source signal individually, the acoustic domain can be treated as a linear, time-invariant (LTI) system. As such, it is fully describable by its impulse response, which embodies the reverberation characteristics of the simulated environment. These can then be transferred to arbitrary source signals via a convolution operation, once the impulse response has been simulated using the ADER-DG method. This approach not only significantly accelerates the auralization, it also incorporates important physical effects, such as refraction and diffraction.
Keywords: ADER-DG method, Acoustics, Diffraction, Convolution Reverberation, Sound waves, Finite Volume Method