Skip to main content
Fachgebiete
Automobil + Motoren Bauwesen + Immobilien Business IT + Informatik Elektrotechnik + Elektronik Energie + Nachhaltigkeit Finance + Banking Management + Führung Marketing + Vertrieb Maschinenbau + Werkstoffe Versicherung + Risiko
DE
EN
Themenseiten
Organisationspsychologie Projektmanagement Marketing Smart Manufacturing
Bücher
Zeitschriften
Weitere Formate
Podcasts Webinare Technik Webinare Wirtschaft Kongresse Veranstaltungskalender Awards
Jetzt Einzelzugang starten
Zugang für Unternehmen
Referenzkunden
MTZ-Fachkongress

Antriebe und Energiesysteme von morgen


Austausch von Automobil- und Energiewirtschaft

Am 14./15. Mai geht es in Chemnitz um die Mobilitätswende durch Elektro- und Wasserstofffahrzeuge.
Erweiterte Suche
Anmelden
nach oben
Engineering with Computers
Erschienen in: Engineering with Computers 2/2024

09.05.2023 | Original Article

Memory-efficient boundary-preserving tetrahedralization of large three-dimensional meshes

verfasst von: Ziya Erkoç, Uğur Güdükbay, Hang Si

Erschienen in: Engineering with Computers | Ausgabe 2/2024

Einloggen

Aktivieren Sie unsere intelligente Suche, um passende Fachinhalte oder Patente zu finden.

search-config
loading …

Abstract

We propose a divide-and-conquer algorithm to tetrahedralize three-dimensional meshes in a boundary-preserving fashion. It consists of three stages: Input Partitioning, Surface Closure, and Merge. We first partition the input into several pieces to reduce the problem size. We apply 2D Triangulation to close the open boundaries to make new pieces watertight. Each piece is then sent to TetGen, a Delaunay-based tetrahedral mesh generator tool that forms the basis for our implementation. We finally merge each tetrahedral mesh to calculate the final solution. In addition, we apply post-processing to remove the vertices we introduced during the input partitioning stage to preserve the input triangles. The benefit of our approach is that it can reduce peak memory usage or increase the speed of the process. It can even tetrahedralize meshes that TetGen cannot do due to the peak memory requirement.

Graphical abstract

Vorheriger Artikel A novel optimization-based physics-informed neural network scheme for solving fractional differential equations
Nächster Artikel Digital twin based lifecycle modeling and state evaluation of cable-stayed bridges

Sie haben noch keine Lizenz? Dann Informieren Sie sich jetzt über unsere Produkte:

Springer Professional "Technik"

Online-Abonnement

Mit Springer Professional "Technik" erhalten Sie Zugriff auf:

  • über 67.000 Bücher
  • über 390 Zeitschriften

aus folgenden Fachgebieten:

  • Automobil + Motoren
  • Bauwesen + Immobilien
  • Business IT + Informatik
  • Elektrotechnik + Elektronik
  • Energie + Nachhaltigkeit
  • Maschinenbau + Werkstoffe




 

Jetzt Wissensvorsprung sichern!

Jetzt informieren

Springer Professional "Wirtschaft+Technik"

Online-Abonnement

Mit Springer Professional "Wirtschaft+Technik" erhalten Sie Zugriff auf:

  • über 102.000 Bücher
  • über 537 Zeitschriften

aus folgenden Fachgebieten:

  • Automobil + Motoren
  • Bauwesen + Immobilien
  • Business IT + Informatik
  • Elektrotechnik + Elektronik
  • Energie + Nachhaltigkeit
  • Finance + Banking
  • Management + Führung
  • Marketing + Vertrieb
  • Maschinenbau + Werkstoffe
  • Versicherung + Risiko

Jetzt Wissensvorsprung sichern!

Jetzt informieren

Springer Professional "Wirtschaft"

Online-Abonnement

Mit Springer Professional "Wirtschaft" erhalten Sie Zugriff auf:

  • über 67.000 Bücher
  • über 340 Zeitschriften

aus folgenden Fachgebieten:

  • Bauwesen + Immobilien
  • Business IT + Informatik
  • Finance + Banking
  • Management + Führung
  • Marketing + Vertrieb
  • Versicherung + Risiko




Jetzt Wissensvorsprung sichern!

Jetzt informieren
Literatur
1.
Susersic TI, Filipovic N (2020) Computational modeling of dry-powder inhalers for pulmonary drug delivery. In: Filipovic N (ed) Computational modeling in bioengineering and bioinformatics. Academic Press, Cambridge, pp 257–288CrossRef
2.
Anderson P, Fels S, Harandi NM, Ho A, Moisik S, Sánchez CA, Stavness I, Tang K (2017) FRANK: a hybrid 3D biomechanical model of the head and neck. In: Payan Y, Ohayon J (eds) Biomechanics of living organs, vol 1. Translational epigenetics. Academic Press, Oxford, pp 413–447CrossRef
3.
Payan Y, Ohayon J (eds) (2017) Biomechanics of living organs. Translational epigenetics, vol 1. Academic Press, Oxford
4.
Tu J, Yeoh G-H, Liu C (2018) CFD mesh generation: a practical guideline. In: Tu J, Yeoh G-H, Liu C (eds) Computational fluid dynamics, 3rd edn. Butterworth-Heinemann, Oxford, pp 125–154CrossRef
5.
Molino N, Bridson R, Teran J, Fedkiw R (2003) A crystalline, red green strategy for meshing highly deformable objects with tetrahedra. In: Shepherd J (ed) Proceedings of the 12th International Meshing Roundtable, IMR 2003, pp 103–114
6.
Teran J, Sifakis E, Irving G, Fedkiw R (2005) Robust quasistatic finite elements and flesh simulation. In: Proceedings of the ACM SIGGRAPH/Eurographics Symposium on Computer Animation. SCA ’05. Association for Computing Machinery, New York, NY, USA, pp 181–190
7.
Sifakis E, Der KG, Fedkiw R (2007) Arbitrary cutting of deformable tetrahedralized objects. In: Proceedings of the ACM SIGGRAPH/Eurographics Symposium on Computer Animation. SCA ’07. Eurographics Association, Goslar, DEU, pp 73–80
8.
Montazerin N, Akbari G, Mahmoodi M (2015) Developments in turbomachinery flow: forward curved centrifugal fans, vol 1. Woodhead Publishing, Sawston
9.
Driscoll M (2019) The impact of the finite element method on medical device design. J Med Biol Eng 39:171–172CrossRef
10.
Mollica F, Ambrosio L (2009) The finite element method for the design of biomedical devices. In: Merolli A, Joyce TJ (eds) Biomater Hand Surg. Springer, Milano, pp 31–45CrossRef
11.
Wittek A, Miller K (2020) Computational biomechanics for medical image analysis. In: Zhou SK, Rueckert D, Fichtinger G (eds) Handbook of medical image computing and computer assisted intervention. The Elsevier and MICCAI society book series. Academic Press, London, pp 953–977CrossRef
12.
Freutel M, Schmidt H, Dürselen L, Ignatius A, Galbusera F (2014) Finite element modeling of soft tissues: material models, tissue interaction and challenges. Clin Biomech 29(4):363–372CrossRef
13.
Galbusera F, Niemeyer F (2018) Mathematical and finite element modeling. In: Galbusera F, Wilke H-J (eds) Biomechanics of the spine. Academic Press, Oxford, pp 239–255
14.
Schneider T, Hu Y, Gao X, Dumas J, Zorin D, Panozzo D (2019) A large scale comparison of tetrahedral and hexahedral elements for finite element analysis. arXiv preprint arXiv:​1903.​09332
15.
Shewchuk JR (2008) General-dimensional constrained Delaunay and constrained regular triangulations, I: combinatorial properties. Discret Comput Geom 39(1):580–637MathSciNetCrossRef
16.
Lagae A, Dutré P (2008) Accelerating ray tracing using constrained tetrahedralizations. Comput Graph Forum 27(4):1303–1312CrossRef
17.
18.
Hu Y, Zhou Q, Gao X, Jacobson A, Zorin D, Panozzo D (2018) Tetrahedral meshing in the wild. ACM Trans Graph 37(4):60–16014CrossRef
19.
20.
Dey TK, Levine JA (2009) Delaunay meshing of piecewise smooth complexes without expensive predicates. Algorithms 2(4):1327–1349MathSciNetCrossRef
21.
Dobrzynski C (2012) MMG3D: tetrahedral fully automatic remesher. User Guide. Technical Report RT-0422, HAL Id: hal-00681813, The National Institute for Research in Digital Science and Technology (INRIA). Available at: https://​hal.​inria.​fr/​hal-00681813/​document. Accessed 10 Oct 2022
22.
Chew LP (1993) Guaranteed-quality mesh generation for curved surfaces. In: Proceedings of the Ninth Annual Symposium on Computational Geometry. SCG ’93. Association for Computing Machinery, New York, NY, USA, pp 274–280
23.
Chernikov AN, Chrisochoides NP (2008) Algorithm 872: parallel 2D constrained Delaunay mesh generation. ACM Trans Math Softw 34(1):1–20MathSciNetCrossRef
24.
Linardakis L, Chrisochoides N (2008) Algorithm 870: A static geometric medial axis domain decomposition in 2D Euclidean space. ACM Trans Math Softw 34(1):1–28MathSciNetCrossRef
25.
Coll N, Guerrieri M (2017) Parallel constrained Delaunay triangulation on the GPU. Int J Geogr Inf Sci 31(7):1467–1484CrossRef
26.
Blandford DK, Blelloch GE, Kadow C (2006) Engineering a compact parallel Delaunay algorithm in 3D. In: Proceedings of the Twenty-second Annual Symposium on Computational Geometry. SoCG ’06, pp 292–300
27.
Chernikov AN, Chrisochoides NP (2008) Three-dimensional Delaunay refinement for multi-core processors. In: Proceedings of the 22nd Annual International Conference on Supercomputing. ICS ’08. Association for Computing Machinery, New York, NY, USA, pp 214–224
28.
Cignoni P, Montani C, Scopigno R (1998) DeWall: a fast divide and conquer Delaunay triangulation algorithm in e\(^d\). Comput Aided Des 30(5):333–341CrossRef
29.
Chen M-B, Chuang T-R, Wu J-J (2004) Efficient parallel implementations of near Delaunay triangulation with high performance Fortran. Concurr Comput 16(12):1143–1159CrossRef
30.
Marot C, Pellerin J, Remacle J-F (2019) One machine, one minute, three billion tetrahedra. Int J Numer Method Eng 117(9):967–990MathSciNetCrossRef
31.
Hu Y, Schneider T, Wang B, Zorin D, Panozzo D (2020) Fast tetrahedral meshing in the wild. ACM Trans Graph 39(4):117–111718CrossRef
32.
Kohout J, Kolingerová I, Žára J (2005) Parallel Delaunay triangulation in \(E^{2}\) and \(E^{3}\) for computers with shared memory. Parallel Comput 31(5):491–522MathSciNetCrossRef
33.
Joshi BJ, Ourselin S (2003) BSP-assisted constrained tetrahedralization. In: Proceedings of the 12th International Meshing Roundtable. IMR ’03, pp. 251–260
34.
Smolik M, Skala V (2014) Fast parallel triangulation algorithm of large data sets in E\(^2\) and E\(^3\) for in-core and out-core memory processing. Proceedings of the international conference on computational science and its applications ICCSA 14. Springer, Cham, pp 301–314
35.
Erkoç Z, Aman A, Güdükbay U, Si H (2021) Out-of-core constrained Delaunay tetrahedralizations for large scenes. In: Garanzha VA, Kamenski L, Si H (eds) Numerical geometry, grid generation and scientific computing. Springer, Cham, pp 113–124CrossRef
36.
Zhao W, Gao S, Lin H (2007) A robust hole-filling algorithm for triangular mesh. Vis Comput 23(12):987–997CrossRef
37.
Tekumalla LS, Cohen E (2004) A hole-filling algorithm for triangular meshes. Technical Report UUCS-04-019, School of Computing, University of Utah, UT, USA
38.
39.
Shewchuk JR (1996) Triangle: engineering a 2D quality mesh generator and Delaunay triangulator. Proceedings of workshop on applied computational geometry. Springer, Cham, pp 203–222
40.
41.
Dagum L, Menon R (1998) OpenMP: an industry standard API for shared-memory programming. IEEE Comput Sci Eng 5(1):46–55CrossRef
Metadaten
Titel
Memory-efficient boundary-preserving tetrahedralization of large three-dimensional meshes
verfasst von
Ziya Erkoç
Uğur Güdükbay
Hang Si
Publikationsdatum
09.05.2023
Verlag
Springer London
Erschienen in
Engineering with Computers / Ausgabe 2/2024
Print ISSN: 0177-0667
Elektronische ISSN: 1435-5663
DOI
https://doi.org/10.1007/s00366-023-01826-7

Weitere Artikel der Ausgabe 2/2024

Engineering with Computers 2/2024 Zur Ausgabe

Original Article

Dynamic parameterization of a modified SEIRD model to analyze and forecast the dynamics of COVID-19 outbreaks in the United States

Original Article

Strong form mesh-free hp-adaptive solution of linear elasticity problem

Original Article

Bayesian active learning approach for estimation of empirical copula-based moment-independent sensitivity indices

Original Article

Dynamic crack propagation in anisotropic solids under non-classical thermal shock

Original Article

Lattice-Boltzmann LES modelling of a full-scale, biogas-mixed anaerobic digester

Original Article

Lagrangian particle-based simulation of waves: a comparison of SPH and PFEM approaches

Neuer Inhalt

    Bildnachweise