10 papers
Fourier Neural Operators for Rayleigh-Bénard Convection
Chelsea Maria John, Thibaut Lunet, Sebastian Götschel +3
We propose an improved Fourier Neural Operator (FNO) for modeling two-dimensional Rayleigh-Bénard convection by predicting time increments instead of full solutions, achieving hig…
Tracking in-silico Lagrangian sensors in a lab-scale stirred tank reactor
Vamika Rathi, Fatima Sehar, Finn Sommer +4
Lagrangian sensors have shown promise to improve operator awareness of conditions inside a chemical reactor but three-dimensional tracking remains a mostly unsolved challenge. We e…
Adjoint-based Perfusion Estimation from Dynamic Contrast-Enhanced Ultrasound: Advection-Diffusion and Two-Compartment Models
Sophie Externbrink, Ahmed El Kaffas, Dimitre Hristov +1
Tumor perfusion and vascular properties are important determinants of a cancer's response to therapy. In this paper, we discuss the estimation of spatially varying blood flow veloc…
Bathymetry Reconstruction by Bayesian Inference
Lars Stietz, Sebastian Götschel, Peter Schleper +1
Bathymetry reconstruction is an important problem in various fields, including oceanography and environmental monitoring. This paper presents a Bayesian inference approach to recon…
Parallel performance of shared memory parallel spectral deferred corrections
Philip Freese, Sebastian Götschel, Thibaut Lunet +2
We investigate the parallel performance of Parallel Spectral Deferred corrections, a numerical approach that provides small-scale parallelism for the numerical solution of initial…
Enforcing boundary conditions for physics-informed neural operators
Niklas Göschel, Sebastian Götschel, Daniel Ruprecht
Machine-learning based methods like physics-informed neural networks and physics-informed neural operators are becoming increasingly adept at solving even complex systems of partia…