Demo Data from EDBT 2026 / reviewers in the wild / expert
Ruben Partono
dblp:336/8042
· DBLP profile ↗
1ranked-venue papers
0as first author
1since 2021 · last 2022
—ORCID · none
Domains — the database's venue-derived domains; a paper can count in several
Graphics, computer vision, multimedia, augmented reality and games · 1 · 1 since 2021
Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.
| Computer graphics and multimedia
1 paper |
Computer animation and physical simulation · 100% |
Topics — the 3 heaviest of 3, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Computer animation and physical simulation
fluid simulation |
0.6 | 1 | 2022 | Curl-Flow: Boundary-Respecting Pointwise Incompressible Velocity Interpolation for Grid-Based Fluids · ACM Trans. Graph. 2022 |
Computer animation and physical simulation › fluid simulation
incompressible fluid simulation |
0.6 | 1 | 2022 | Curl-Flow: Boundary-Respecting Pointwise Incompressible Velocity Interpolation for Grid-Based Fluids · ACM Trans. Graph. 2022 |
Computer animation and physical simulation › fluid simulation
solid-fluid coupling |
0.6 | 1 | 2022 | Curl-Flow: Boundary-Respecting Pointwise Incompressible Velocity Interpolation for Grid-Based Fluids · ACM Trans. Graph. 2022 |
Methods — techniques the papers use, named apart from their topics
vector potential reconstruction · 0.6parallel sweeping · 0.6level set · 0.6gauge transformation · 0.6
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2022 | Curl-Flow: Boundary-Respecting Pointwise Incompressible Velocity Interpolation for Grid-Based FluidsabstractWe propose to augment standard grid-based fluid solvers with pointwise divergence-free velocity interpolation, thereby ensuring exact incompressibility down to the sub-cell level. Our method takes as input a discretely divergence-free velocity field generated by a staggered grid pressure projection, and first recovers a corresponding discrete vector potential. Instead of solving a costly vector Poisson problem for the potential, we develop a fast parallel sweeping strategy to find a candidate potential and apply a gauge transformation to enforce the Coulomb gauge condition and thereby make it numerically smooth. Interpolating this discrete potential generates a point-wise vector potential whose analytical curl is a pointwise incompressible velocity field. Our method further supports irregular solid geometry through the use of level set-based cut-cells and a novel Curl-Noise-inspired potential ramping procedure that simultaneously offers strictly non-penetrating velocities and incompressibility. Experimental comparisons demonstrate that the vector potential reconstruction procedure at the heart of our approach is consistently faster than prior such reconstruction schemes, especially those that solve vector Poisson problems. Moreover, in exchange for its modest extra cost, our overall Curl-Flow framework produces significantly improved particle trajectories that closely respect irregular obstacles, do not suffer from spurious sources or sinks, and yield superior particle distributions over time. Jumyung Chang, Ruben Partono, Vinicius C. Azevedo, Christopher Batty |
ACM Trans. Graph. | 2 |