Computational Uncertainty Quantification (B07*)

• Subject Area: Mathematics
• Term: from 2019 to 2023
• Project identifier: Deutsche Forschungsgemeinschaft (DFG) - Project number 251654672

Efficient sampling methods are central in the quantification of uncertainties, especially when real data is sparse. The focus in this project lies on the generation of random fields and sampling of the associated stochastic partial differential equation and, further, on the visualization of the distribution that is the solution to the stochastic dynamical system. Different risk measures require varied sampling strategies and the visualization needs to be adapted accordingly. Moreover, visualization itself introduces uncertainties that might be correlated to the inherent stochasticity of the system and also needs to be quantified.

• DFG Programme: CRC/Transregios
• Subproject of: TRR 161: Quantitative Methods for Visual Computing
• Applicant Institution: Universität Stuttgart
• Project Head: Professorin Dr. Andrea Barth