A Dimension‐reduced Pressure Solver for Liquid Simulations

By Ryoichi Ando, Nils Thürey, C. Wojtan. 2015

34 citations recorded by the source corpus.

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

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. Nils Thürey
2. Steffen Wiewel
3. Moritz Becher
4. Cheng Yang
5. Xubo Yang
6. Xiangyun Xiao
7. Suvranu De
8. Rahul

In Computer Graphics and Computer-Aided Design

1. Steffen Wiewel
2. Moritz Becher
3. Nils Thürey
4. Cheng Yang
5. Xubo Yang
6. Xiangyun Xiao
7. Suvranu De
8. Rahul

Citations in the corpus

• Latent Space Physics: Towards Learning the Temporal Evolution of Fluid Flow (2018, methodology): “E.g., techniques for dimensionality reduction [LZF10,ATW15], and fast solvers [MST10,ICS ∗ 14] have been proposed to diminish its runtime impact.”
• Data‐driven projection method in fluid simulation (2016, background): “In fluid simulation, the most common idea is to transform the solving process into low-dimensional space [13,14].”
• Data-driven synthesis of smoke flows with CNN-based feature descriptors (2017, unknown): “vection step [Kim et al. 2005; Selle et al. 2008], post-processing animations with additional synthetic turbulence [Kim et al. 2008; Narain et al. 2008], and speeding up the pressure projection step [Ando et al. 2015; Lentine et al. 2010]. We take a di˛erent perspective to e˝ciently realize high res”