Construction of Stable and Lightweight Technical Structures Inspired by Ossification of Bones Using Osteogenetic P Systems

  • Alexander Melcher
  • Ilija Vukorep
  • Thomas HinzeEmail author
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 11399)


Vertebrates come with a skeleton of bones whose inner structure combines two contradicting properties in a fascinating way: On the one hand, bones are stable and robust against mechanical stress, and on the other hand they are lightweight to minimise the energy necessary for motion of the organism. By means of a biological process called ossification, the inner structure of bones becomes permanently optimised during organism’s lifetime which implies a high adaptability to varying environmental and behavioural needs. An appropriate computational model of ossification provides a promising bionics tool with widespread applicability for instance in architecture for construction of technical structures. To this end, we introduce the framework of osteogenetic P systems able to generate and to manage the spatial inner structure of bones in a dynamical manner during ossification. Starting from an initial porous network of interwoven filaments surrounded by vesicles, a variety of osteoblasts and osteoclasts is placed alongside the filaments throughout the whole network. External forces, freely configurable in their intensity and effective direction, affect the outer nodes of the network inducing a spatial distribution of mechanical stress in its inner filamentary structure. Now, the osteoblasts move towards heavily loaded positions and strengthen the corresponding filaments while osteoclasts eliminate filamentary material wherever dispensible. Over time, the inner network structure adapts to its demands by strong filaments along the main force lines. Complementing our framework of osteogenetic P systems, we demonstrate its practicability using two case studies: The first one describes generation of a dice-shaped cage resistant against weights on top. The second study addresses construction of an arched bridge with two opposite bearings.


  1. 1.
    Albanese, A., et al.: The effect of nanoparticle size, shape, and surface chemistry on biological systems. Annu. Rev. Biomed. Eng. 14, 1–16 (2012)CrossRefGoogle Scholar
  2. 2.
    van Amsterdam, E.: Construction Materials for Civil Engineering. Juta & Company (2000)Google Scholar
  3. 3.
    Ananthanatayanan, A., Azadi, M., Kim, S.: Towards a bio-inspired leg design for high-speed running. Bioinspiration Biomimetics 7(4), 046005 (2012)CrossRefGoogle Scholar
  4. 4.
    Bathe, K.J., Wilson, E.L.: Numerical Methods in Finite Element Analysis. Prentice Hall, Upper Saddle River (1976)zbMATHGoogle Scholar
  5. 5.
    Baumgartner, A., et al.: Soft kill option: the biological way to find an optimum structure topology. Int. J. Fatigue 14(6), 387–393 (1992)CrossRefGoogle Scholar
  6. 6.
    Becker, M., Golay, P.: Rhino NURBS 3D Modeling. Updog Publishers (2009)Google Scholar
  7. 7.
    Bose, S., Vahabzadeh, S., Bandyopadhyay, A.: Bone tissue engineering using 3D printing. Mater. Today 16(12), 496–504 (2013)CrossRefGoogle Scholar
  8. 8.
    Cacciagrano, D., Corradini, F., Merelli, E., Tesei, L.: Multiscale bone remodelling with spatial P systems. EPTCS 40, 70–84 (2010)CrossRefGoogle Scholar
  9. 9.
    Desai, Y.M., Eldho, T.I., Shah, A.H.: Finite Element Method with Applications in Engineering. Person, London (2011)Google Scholar
  10. 10.
    Frisco, P., Gheorghe, M., Pérez-Jiménez, M.J. (eds.): Applications of Membrane Computing in Systems and Synthetic Biology. ECC, vol. 7. Springer, Cham (2014). Scholar
  11. 11.
    Frost, H.M.: From Wolff’s law to the Utah paradigm: insights about bone physiology and its clinical applications. Anat. Rec. 262, 398–419 (2001)CrossRefGoogle Scholar
  12. 12.
    Gerhard, F., et al.: In silico biology of bone modelling and remodelling: adaptation. Philos. Trans. R. Soc. 367, 2011–2030 (2009)CrossRefGoogle Scholar
  13. 13.
    McGinnis, P.M.: Biomechanics of Sport and Exercise. Human Kinetics, Champaign (2005)Google Scholar
  14. 14.
    Hibbeler, R.C.: Engineering Mechanics: Statics. Pearson Prentice Hall, Upper Saddle River (2007)zbMATHGoogle Scholar
  15. 15.
    Hinze, T., Grützmann, K., Höckner, B., Sauer, P., Hayat, S.: Categorised counting mediated by blotting membrane systems for particle-based data mining and numerical algorithms. In: Gheorghe, M., Rozenberg, G., Salomaa, A., Sosík, P., Zandron, C. (eds.) CMC 2014. LNCS, vol. 8961, pp. 241–257. Springer, Cham (2014). Scholar
  16. 16.
    Hinze, T., Weber, L.L., Hatnik, U.: Walking membranes: grid-exploring P systems with artificial evolution for multi-purpose topological optimisation of cascaded processes. In: Leporati, A., Rozenberg, G., Salomaa, A., Zandron, C. (eds.) CMC 2016. LNCS, vol. 10105, pp. 251–271. Springer, Cham (2017). Scholar
  17. 17.
    Huiskes, R., et al.: Effects of mechanical forces on maintenance and adaptation of form in trabecular bone. Nature 405, 704–706 (2000)CrossRefGoogle Scholar
  18. 18.
    Kanungo, T., et al.: An efficient \(k\)-means clustering algorithm: analysis and implementation. IEEE Trans. Pattern Anal. Mach. Intell. 24(7), 881–892 (2002)CrossRefGoogle Scholar
  19. 19.
    Khoshnevis, B., et al.: Mega-scale fabrication by contour crafting. Int. J. Ind. Syst. Eng. 1(3), 301–320 (2006)Google Scholar
  20. 20.
    Kozlov, A., et al.: Bio-inspired design: aerodynamics of boxfish. Procedia Eng. 105, 323–328 (2015)CrossRefGoogle Scholar
  21. 21.
    Lian, Q., Wu, Z.: Membrane computing based virtual network embedding algorithm with path splitting. Appl. Mech. Mater. 687, 2997–3002 (2014)CrossRefGoogle Scholar
  22. 22.
    Nachtigall, W., Pohl, G.: Bau-Bionik. Springer, Heidelberg (2013). Scholar
  23. 23.
    Nachtigall, W., Wisser, A.: Bionics by Examples: 250 Scenarios from Classical to Modern Times. Springer, Cham (2014). Scholar
  24. 24.
    Paun, G., Rozenberg, G., Salomaa, A. (eds.): The Oxford Handbook of Membrane Computing. Oxford University Press, Oxford (2009)Google Scholar
  25. 25.
    Robling, A.G., Castillo, A.B., Turner, C.H.: Biomechanical and molecular regulation of bone remodeling. Annu. Rev. Biomed. Eng. 8, 455–498 (2006)CrossRefGoogle Scholar
  26. 26.
    Trotter, M., et al.: Densities of bones of white and negro skeletons. J. Bone Joint Surg. 42a, 50–58 (1960)CrossRefGoogle Scholar
  27. 27.
    Vukorep, I.: Autonomous big-scale additive manufacturing using cable-driven robots. In: Proceedings 34th International Symposium on Automation and Robotics in Construction (ISARC 2017), Taipeh, pp. 254–259 (2017)Google Scholar
  28. 28.
    Weinkamer, R., Fratzl, P.: Mechanical adaptation of biological materials - the examples of bone and wood. Mater. Sci. Eng. 31, 1164–1173 (2011)CrossRefGoogle Scholar
  29. 29.
    Wolff, J.: Das Gesetz der Transformation der Knochen. Hirschwald, Berlin (1892)Google Scholar
  30. 30.
    Yongxiang, L.U.: Significance and progress of bionics. Springer J. Bionic Eng. 1(1), 1–3 (2004)CrossRefGoogle Scholar

Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  • Alexander Melcher
    • 1
  • Ilija Vukorep
    • 2
  • Thomas Hinze
    • 3
    Email author
  1. 1.Niessink Engineering GmbHEdemissenGermany
  2. 2.Chair of Digital Design DepartmentBrandenburg University of TechnologyCottbusGermany
  3. 3.Department of BioinformaticsFriedrich Schiller University JenaJenaGermany

Personalised recommendations