Part recognition–based simplification of triangular mesh models for ships and plants

  • Kiyoun Kwon
  • Duhwan MunEmail author


Among the methods of expressing the shapes of components in ships and plants, the triangular mesh model provides a simple structure and convenient visualization, supports numerous support tools, and can be used in various engineering tasks. Recently, there have been efforts to visualize entire ships and plants for design review, interference checks, process monitoring, and establishing maintenance space; however, because such triangular mesh models are very large, they require high-performance computing resources and are time-consuming. In order to resolve such issues, a method of triangular mesh model simplification is proposed considering the features of large-capacity ship and plant structures. This method generates B-rep models for each part that constitutes the triangular mesh model. Also, the part types including beams, shells, and small parts are recognized from the B-rep model. Finally, mesh simplification corresponding to the recognized part type is carried out. Application of the proposed mesh simplification method enables rapid generation of a low level of detail (LOD) version of the large-scale triangular mesh model.


Large-scale data Model simplification Part recognition Ships and plants Triangular mesh 


Funding information

This study was supported by the Industry Core Technology Development Program (Project ID: 10080662) funded by the MOTIE and by Institute of Information & communications Technology Planning & Evaluation (IITP) grant (Project ID: 2019-0-01304) funded by the MSIT of the Korean government.


  1. 1.
    Kang Y, Kim BC, Mun D, Han S (2014) Method to simplify ship outfitting and plant equipment three-dimensional (3-D) computer-aided design (CAD) data for construction of an equipment catalog. J Mar Sci Technol 19(2):185–196CrossRefGoogle Scholar
  2. 2.
    Ball A, Ding L, Patel M (2007) Lightweight formats for product model data exchange and preservation, PV 2007 Conference, Oberpfaffenhofen, Germany, October 2007Google Scholar
  3. 3.
    Toriya H (2008) Benefits of lightweight 3D data. 3D manufacturing innovation, revolutionary change in Japanese manufacturing with digital data. Springer, London, pp 33–50Google Scholar
  4. 4.
    Kwon KY (2019) Design point generation method from lightweight model for dimensional quality management in shipbuilding. J Ship Prod Des.
  5. 5.
    Veron P, Leon JC (1998) Shape preserving polyhedral simplification with bounded error. 22(5):565–585Google Scholar
  6. 6.
    Sheffer A (2001) Model simplification for meshing using surface clustering. Comput Aided Des 33(13):925–934CrossRefGoogle Scholar
  7. 7.
    Foucault G, Cuilliere JC, Francois V, Leon JC, Maranzana R (2008) Adaptation of CAD model topology for finite element analysis. Comput Aided Des 40(2):176–196CrossRefGoogle Scholar
  8. 8.
    Lee SH, Lee K (2012) Simultaneous and incremental feature-based multiresolution modeling with feature operations in part design. Comput Aided Des 44(5):457–483CrossRefGoogle Scholar
  9. 9.
    Kwon S, Kim BC, Mun D, Han S (2015) Graph-based simplification of feature-based 3D CAD models for preserving connectivity. J Comput Inf Sci Eng 15(3):031010–031010-14CrossRefGoogle Scholar
  10. 10.
    Liu W, Zhou X, Zhang X, Niu Q (2015) Three-dimensional (3D) CAD model lightweight scheme for large-scale assembly and simulation. Int J Comput Integr Manuf 28(5):520–533CrossRefGoogle Scholar
  11. 11.
    Kwon S, Kim BC, Mun D, Han S (2015) Simplification of feature-based 3D CAD assembly data of ship and offshore equipment using quantitative evaluation metrics. Comput Aided Des 59:140–154CrossRefGoogle Scholar
  12. 12.
    Ramanathan M, Gurumoorthy B (2002) Constructing medial axis transform of planar domains with curved boundaries. Comput Aided Des 35:619–632CrossRefGoogle Scholar
  13. 13.
    Woo Y (2014) Abstraction of mid-surfaces from solid models of thin-walled parts: a divide-and-conquer approach. Comput Aided Des 47:1–11CrossRefGoogle Scholar
  14. 14.
    Zhu H, Shao Y, Liu Y, Zhao J (2016) Automatic hierarchical mid-surface abstraction of thin-walled model based on rib decomposition. Adv Eng Softw 97:60–71CrossRefGoogle Scholar
  15. 15.
    Kwon KY, Lee BC, Chae SW (2006) Medial surface generation using chordal axis transformation in shell structures. Comput Struct 84(26–27):1673–1683CrossRefGoogle Scholar
  16. 16.
    Quadros WR (2008) An approach for extracting non-manifold mid-surfaces of thin-wall solids using chordal axis transform. Eng Comput 24(3):305–319CrossRefGoogle Scholar
  17. 17.
    Schroeder WJ, Zarge JA, Lorensen WE (1992) Decimation of triangle meshes. In Proceedings of SIGGRAPH 26(2):65–70CrossRefGoogle Scholar
  18. 18.
    Soucy M, Laurendeau D (1996) Multiresolution surface modeling based on hierarchical triangulation. Comput Vis Image Underst 63(1):1–14CrossRefGoogle Scholar
  19. 19.
    Hoppe H (1996) Progressive meshes. In: Proceedings of the 23rd annual conference on computer graphics and interactive techniques, pp 99–108Google Scholar
  20. 20.
    Rossignac J, Borrel P (1993) Multi-resolution 3D approximations for rendering complex scenes, modeling in computer graphics. Springer, Berlin, Heidelber, pp 455–465Google Scholar
  21. 21.
    Mercado-Colmenero JM, Paramio MR, Perez-Garcia JM, Martin-Doñate C (2016) A new hybrid method for demoldability analysis of discrete geometries. Comput Aided Des 80:43–60CrossRefGoogle Scholar
  22. 22.

Copyright information

© Springer-Verlag London Ltd., part of Springer Nature 2019

Authors and Affiliations

  1. 1.School of Industrial EngineeringKumoh National Institute of TechnologyGumi-siSouth Korea
  2. 2.Department of Precision Mechanical EngineeringKyungpook National UniversitySangju-siSouth Korea

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