107 citations · 278 across the 5 of their papers we have counts for
6 papers
Plug-and-Play Benchmarking of Reinforcement Learning Algorithms for Large-Scale Flow Control
Jannis Becktepe, Aleksandra Franz, Nils Thuerey +1
Reinforcement learning (RL) has shown promising results in active flow control (AFC), yet progress in the field remains difficult to assess as existing studies rely on heterogeneou…
INC: An Indirect Neural Corrector for Auto-Regressive Hybrid PDE Solvers
Hao Wei, Aleksandra Franz, Bjoern List +1
When simulating partial differential equations, hybrid solvers combine coarse numerical solvers with learned correctors. They promise accelerated simulations while adhering to phys…
PICT -- A Differentiable, GPU-Accelerated Multi-Block PISO Solver for Simulation-Coupled Learning Tasks in Fluid Dynamics
Aleksandra Franz, Hao Wei, Luca Guastoni +1
Despite decades of advancements, the simulation of fluids remains one of the most challenging areas of in scientific computing. Supported by the necessity of gradient information i…
Physics Informed Neural Fields for Smoke Reconstruction with Sparse Data
Mengyu Chu, Lingjie Liu, Quan Zheng +4
High-fidelity reconstruction of fluids from sparse multiview RGB videos remains a formidable challenge due to the complexity of the underlying physics as well as complex occlusion…
tempoGAN: A Temporally Coherent, Volumetric GAN for Super-resolution Fluid Flow
You Xie, Aleksandra Franz, Mengyu Chu +1
We propose a temporally coherent generative model addressing the super-resolution problem for fluid flows. Our work represents a first approach to synthesize four-dimensional physi…
Data-Driven Synthesis of Smoke Flows with CNN-based Feature Descriptors
Mengyu Chu, Nils Thuerey
We present a novel data-driven algorithm to synthesize high-resolution flow simulations with reusable repositories of space-time flow data. In our work, we employ a descriptor lear…