ADAPTIVE DISCRETE MODELS OF FUNCTIONALLY REPRESENTED OBJECT SHAPES

DOI https://doi.org/10.15407/pmach2018.04.049
Journal Journal of Mechanical Engineering – Problemy Mashynobuduvannia
Publisher A. Podgorny Institute for Mechanical Engineering Problems
National Academy of Science of Ukraine
ISSN 0131-2928 (Print), 2411-0779 (Online)
Issue Vol. 21, no. 4, 2018 (December)
Pages 49-56
Cited by J. of Mech. Eng., 2018, vol. 21, no. 4, pp. 49-56

 

Author

Serhii VChoporov, Zaporizhzhia National University (6, Zhukovskyi Str., Zaporizhzhia, 69600, Ukraine), e-mail: s.choporoff@znu.edu.ua, ORCID: 0000-0001-5932-952X

 

Abstract

Designers often use a numerical analysis of mechanical engineering product models. The analysis is based on partial differential equations. One of the most used numerical methods is the finite element method, in which the continuous object model is replaced by a discrete one. As a result, the first stage of modeling is the construction of a discrete object shape model as the final union of simple shapes. The distribution of elements in a discrete object shape model has a significant impact on the accuracy of numerical analysis. One of the most universal approaches to the computer modeling of object shapes is functional representation. This approach is based on using implicit functions to determine the set of points that corresponds to the object shape. Moreover, implicit functions for complex objects can be created constructively using combinations of simpler functions. For this, one can apply the real functions that are proposed in the R-functions theory and correspond to logical operations. Although functional representation makes it possible to check whether a point belongs to a set, it requires that methods for constructing discrete models be developed. In this paper, a method is proposed for constructing adaptive discrete models of object shapes represented functionally. This method uses an estimate of the accuracy of the finite element analysis to determine the areas where nodes and elements are refined. In the process of refinement, the refinement templates of elements are used that are proposed for the most common elements (triangles, quadrangles, tetrahedra and hexagons), with reprojection on the domain boundary of boundary nodes. Examples of constructing adaptive discrete models for solving two- and three-dimensional problems of studying stress-strain state are shown.

 

Keywords: discrete model, object shape, implicit function, R-function, finite element method.

 

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References

  1. Rvachev, V. L. (1982). Teoriya R-funktsiy i nekotoryye eye prilozheniya [Theory of R-functions and some of its applications.]. Kiyev: Naukova dumka, 552 p. (in Russian).
  2. Maksimenko-Sheyko, K. V. (2009). R-funktsii v matematicheskom modelirovanii geometricheskikh obyektov i fizicheskikh poley [R-functions in mathematical modeling of geometric objects and physical fields]. Kharkov: IPMash NAN Ukrainy, 306 p. (in Russian).
  3. Maksymenko-Sheyko, K. V. & Sheyko, T. I. (2012). Mathematical modeling of geometric fractals using R-functions. Cybernetics and Systems Analysis, vol. 48, iss. 4, pp. 614–620. https://doi.org/10.1007/s10559-012-9442-7
  4. Lisnyak, A. A. (2013). Sposob postroyeniya diskretnykh matematicheskikh geometricheskikh obyektov. zadannykh s pomoshchyu R-funktsiy [A method for constructing discrete mathematical geometric objects defined by R-functions]. Visn. Zaporiz. nats. un-tu. Fiziko-matematichni nauki. − Visnyk of Zaporizhzhya National University. Physical and Mathematical Sciences, no. 1, pp. 59–69 (in Russian).
  5. Choporov, S. V. (2017). Sglazhivaniye setok chetyrekhugolnykh elementov s ispolzovaniyem lokalnoy minimizatsii funktsionala [Smoothing grids of quadrilateral elements using local minimization of the functional]. Vestn. Kherson. nats. tekhn. un-ta − Bulletin of Kherson National Technical University, vol. 2, no. 3 (62), pp. 234–239 (in Russian).
  6. Lisnyak, A. A. (2014). Diskretizatsiya granitsy trekhmernykh modeley geometricheskikh obyektov, zadannykh s pomoshchyu R-funktsiy [Surface discretization of R-functions defined geometrical objects]. Radioyelektronika. Informatika. Upravlinnya − Radio Electronics, Computer Science, Control, no. 1, pp. 82–88 (in Russian). https://doi.org/10.15588/1607-3274-2014-1-12
  7. Choporov, S. V. (2011). Postroyeniye neravnomernykh diskretnykh setok dlya funktsionalnykh matematicheskikh modeley na baze teorii R-funktsiy [Generation of nonuniform hexahedral element meshes for functional models on the basis of R-functions]. Radiioelektronia. Informatika. Uravleniye.  − Radio Electronics, Computer Science, Control, no. 2, pp. 70–75 (in Russian). https://doi.org/10.15588/1607-3274-2011-2-12
  8. Babuska, I., Flaherty, J. E., Henshaw, W. D., Hopcroft, J. E., Oliger, J. E., & Tezduyar, T. (1995). Modeling, mesh generation, and adaptive numerical methods for partial differential equations. New York: Springer-Verlag, 450 p. https://doi.org/10.1007/978-1-4612-4248-2
  9. Schwab, C. (1999). P- and HP-finite element methods. London: Clarendon, 386 p.
  10. Bank, R. E. (1998). PLTMG: A software package for solving elliptic partial differential equations: users’ guide 8.0. SIAM, 155 p. https://doi.org/10.1137/1.9780898719635
  11. Schneiders, R. (2000). Octree-based hexahedral mesh generation. International Journal of Computational Geometry & Applications, vol. 10, no. 04, pp. 383–398. https://doi.org/10.1142/S021819590000022X
  12. Tristano, J. R., Chen, Z., Hancq, D. A., & Kwok, W. (2003). Fully automatic adaptive mesh refinement integrated into the solution process. International Meshing Roundtable: Proc. the 12th Intern. Conf., Santa Fe, New Mexico, U.S.A., 14–17 September 2003. Sandia National Laboratories, pp. 307–314.

 

Received 12 October 2018

Published 30 December 2018