6 papers · 1 filter
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…
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…
Space-time parallel scaling of Parareal with a physics-informed Fourier Neural Operator coarse propagator applied to the Black-Scholes equation
Abdul Qadir Ibrahim, Sebastian Götschel, Daniel Ruprecht
Iterative parallel-in-time algorithms like Parareal can extend scaling beyond the saturation of purely spatial parallelization when solving initial value problems. However, they re…
Improving Efficiency of Parallel Across the Method Spectral Deferred Corrections
Gayatri ÄakloviÄ, Thibaut Lunet, Sebastian Götschel +1
Parallel-across-the method time integration can provide small scale parallelism when solving initial value problems. Spectral deferred corrections (SDC) with a diagonal sweeper, wh…
Adaptive time step selection for Spectral Deferred Correction
Thomas Saupe, Sebastian Götschel, Thibaut Lunet +2
Spectral Deferred Correction (SDC) is an iterative method for the numerical solution of ordinary differential equations. It works by refining the numerical solution for an initial…