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Iván Alduán

dblp:40/10491 · DBLP profile ↗
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2ranked-venue papers
1as first author
0since 2021 · last 2017
—ORCID · none

Domains — the database's venue-derived domains; a paper can count in several

Graphics, computer vision, multimedia, augmented reality and games · 2 · 1 first-author

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

TopicWeightPapersLastEvidence papers
Computer animation and physical simulation › multibody dynamics simulation
constrained dynamics
0.312017
Conformation constraints for efficient viscoelastic fluid simulation · ACM Trans. Graph. 2017
Computer animation and physical simulation › physically-based modeling
position-based dynamics
0.312017
Conformation constraints for efficient viscoelastic fluid simulation · ACM Trans. Graph. 2017
Computer animation and physical simulation › fluid simulation › viscous fluid simulation
viscoelastic fluid simulation
0.312017
Conformation constraints for efficient viscoelastic fluid simulation · ACM Trans. Graph. 2017

Methods — techniques the papers use, named apart from their topics

constitutive model · 0.3conformation tensor · 0.3
YearPublicationVenuePosition
2017 DYVERSO: A Versatile Multi-Phase Position-Based Fluids Solution for VFX
abstract
Abstract Many impressive fluid simulation methods have been presented in research papers before. These papers typically focus on demonstrating particular innovative features, but they do not meet in a comprehensive manner the production demands of actual VFX pipelines. VFX artists seek methods that are flexible, efficient, robust and scalable, and these goals often conflict with each other. In this paper, we present a multi‐phase particle‐based fluid simulation framework, based on the well‐known Position‐Based Fluids (PBF) method, designed to address VFX production demands. Our simulation framework handles multi‐phase interactions robustly thanks to a modified constraint formulation for density contrast PBF. And, it also supports the interaction of fluids sampled at different resolutions. We put special care on data structure design and implementation details. Our framework highlights cache‐efficient GPU‐friendly data structures, an improved spatial voxelization technique based on Z‐index sorting, tuned‐up simulation algorithms and two‐way‐coupled collision handling based on VDB fields. Altogether, our fluid simulation framework empowers artists with the efficiency, scalability and versatility needed for simulating very diverse scenes and effects.
Iván Alduán, Ángel Tena, Miguel A. Otaduy
Comput. Graph. Forum1
2017 Conformation constraints for efficient viscoelastic fluid simulation
abstract
The simulation of high viscoelasticity poses important computational challenges. One is the difficulty to robustly measure strain and its derivatives in a medium without permanent structure. Another is the high stiffness of the governing differential equations. Solutions that tackle these challenges exist, but they are computationally slow. We propose a constraint-based model of viscoelasticity that enables efficient simulation of highly viscous and viscoelastic phenomena. Our model reformulates, in a constraint-based fashion, a constitutive model of viscoelasticity for polymeric fluids, which defines simple governing equations for a conformation tensor. The model can represent a diverse palette of materials, spanning elastoplastic, highly viscous, and inviscid liquid behaviors. In addition, we have designed a constrained dynamics solver that extends the position-based dynamics method to handle efficiently both position-based and velocity-based constraints. We show results that range from interactive simulation of viscoelastic effects to large-scale simulation of high viscosity with competitive performance.
Héctor Barreiro, Ignacio García-Fernández, Iván Alduán, Miguel A. Otaduy
ACM Trans. Graph.3