Eulerian solid-fluid coupling

By Yun Teng, D. Levin, Theodore Kim. 2016

55 citations recorded by the source corpus.

Subfields: Computational Mechanics, Computer Graphics and Computer-Aided Design, Mechanics of Materials

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Computational Mechanics

1. Lukas Prantl
2. Nils Thürey
3. Boris Bonev
4. Steffen Wiewel
5. Moritz Becher

In Computer Graphics and Computer-Aided Design

1. Lukas Prantl
2. Nils Thürey
3. Boris Bonev
4. Steffen Wiewel
5. Moritz Becher

Citations in the corpus

• Data-driven synthesis of smoke flows with CNN-based feature descriptors (2017, unknown): “eloped over the years, More accurate advection schemes [Kim et al. 2005; Selle et al. 2008] are often employed, and many applications require interactions with obstacle boundaries [Batty et al. 2007; Teng et al. 2016]. Additionally, methods to increase the resolution of flows with procedural turbule”
• Pre-computed Liquid Spaces with Generative Neural Networks and Optical Flow (2017, background): “2015] or coupling Lagrangian and Eulerian reduced representations [Teng et al. 2016].”