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Petr Krysl

dblp:89/6111 · DBLP profile ↗
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1ranked-venue papers
0as first author
0since 2021 · last 2002
0000-0003-1761-5047ORCID · reported

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

Graphics, computer vision, multimedia, augmented reality and games · 1

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 · 50% Geometric modeling and processing · 50%

Topics — the 1 heaviest of 2, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Geometric modeling and processing › mesh processing › mesh adaptation › mesh refinement
adaptive mesh refinement
0.012002
CHARMS: a simple framework for adaptive simulation · ACM Trans. Graph. 2002

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

hierarchical basis refinement · 0.0finite element method · 0.0
YearPublicationVenuePosition
2002 CHARMS: a simple framework for adaptive simulation
abstract
Finite element solvers are a basic component of simulation applications; they are common in computer graphics, engineering, and medical simulations. Although adaptive solvers can be of great value in reducing the often high computational cost of simulations they are not employed broadly. Indeed, building adaptive solvers can be a daunting task especially for 3D finite elements. In this paper we are introducing a new approach to produce conforming, hierarchical, adaptive refinement methods (CHARMS). The basic principle of our approach is to refine basis functions, not elements. This removes a number of implementation headaches associated with other approaches and is a general technique independent of domain dimension (here 2D and 3D), element type (e.g., triangle, quad, tetrahedron, hexahedron), and basis function order (piece-wise linear, higher order B-splines, Loop subdivision, etc.). The (un-)refinement algorithms are simple and require little in terms of data structure support. We demonstrate the versatility of our new approach through 2D and 3D examples, including medical applications and thin-shell animations.
Eitan Grinspun, Petr Krysl, Peter Schröder
ACM Trans. Graph.2