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Kaloyan S. Kirilov

dblp:375/9159 · DBLP profile ↗
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2ranked-venue papers
2as first author
2since 2021 · last 2026
—ORCID · none

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

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

Interdisciplinary, comprehensive, and emerging computing
2 papers
Computational science and engineering · 100%
Computer graphics and multimedia
2 papers
Geometric modeling and processing · 100%

Topics — the 2 heaviest of 3, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Geometric modeling and processing › mesh generation
mesh curving
1.322026
High-order curvilinear mesh generation from third-party meshes · Comput. Aided Des. 2026
Mesh generation of curvilinear polygons for the high-order virtual element method (VEM) · Comput. Aided Des. 2026
Computational science and engineering
numerical simulation
0.312026
High-order curvilinear mesh generation from third-party meshes · Comput. Aided Des. 2026

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

derivative-free optimization · 2.0CAD boundary representation queries · 2.0
YearPublicationVenuePosition
2026 Mesh generation of curvilinear polygons for the high-order virtual element method (VEM)
abstract
We present a proof-of-concept methodology for generating curvilinear polygonal meshes suitable for high-order discretisations by the Virtual Element Method (VEM). A VEM discretisation requires the definition of a set of boundary and internal points used to define basis functions and compute integrals of polynomials. The procedure to locate these points on the boundary borrows ideas from previous work on a posteriori high-order mesh generation in which the geometrical inquiries to a B-rep model of the computational domain are performed via an interface to CAD libraries. Here we describe the steps of the procedure that transforms a straight-sided polygonal mesh, generated using third-party software, into a curvilinear boundary-conforming mesh. We discuss criteria for ensuring and verifying the validity of the mesh. Using an elliptic partial differential equation with Dirichlet boundary conditions as a model problem, we show that VEM discretisations on such meshes achieve the expected rates of convergence as the mesh resolution is increased. This is followed by an illustrative application of the method to the generation of a curvilinear polygonal mesh for an aerofoil geometry. We discuss polygonal curvilinear mesh quality and its enhancement, and use the motion of a cell vertex to appraise three elemental quality metrics, namely convexity, regularity and isotropy, and highlight some of the difficulties associated in their use for mesh quality optimisation. A derivative-free optimisation method is utilised to enhance curvilinear polygonal meshes by maximising a suitable measure of mesh quality. We propose such measure as a combination of the three quality metrics and apply it to optimise a distorted initial mesh for a ring geometry. We show that a suitable version of the convexity metric is effective in untangling invalid meshes. The VEM solution of a model elliptic equation is obtained for a ring geometry where a distorted and an optimised mesh show low errors, indicating that the VEM is robust and relatively insensitive to mesh distortion, and a reduction of the error in the optimised mesh. Finally, we use a more complex geometry, a computational domain for an aerofoil, as a benchmark to further illustrate the ability of the convexity metric to untangle meshes, and also to assess the suitability of two quality measures as optimisation targets to improve the overall quality of curvilinear polygonal meshes.
Kaloyan S. Kirilov, Jingtian Zhou, Joaquim Peiró, Mashy Green, David Moxey, Lourenço Beirão da Veiga, Alessandro Russo 0002, Franco Dassi
Comput. Aided Des.1
2026 High-order curvilinear mesh generation from third-party meshes
Kaloyan S. Kirilov, Jingtian Zhou, Joaquim Peiró, David Moxey
Comput. Aided Des.1