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An Element Free Galerkin Method Based on the Modified Moving Least Squares Approximation

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Abstract

This paper demonstrates that the recently developed modified moving least squares (MMLS) approximation possess the necessary properties which allow its use as an element free Galerkin (EFG) approximation method. Specifically, the consistency and invariance properties for the MMLS are proven. We demonstrate that MMLS shape functions form a partition of unity and the MMLS approximation satisfies the patch test. The invariance properties are important for the accurate computation of the shape functions by using translation and scaling to a canonical domain. We compare the performance of the EFG method based on MMLS, which uses quadratic base functions, to the performance of the EFG method which uses classical MLS with linear base functions, using both 2D and 3D examples. In 2D we solve an elasticity problem which has an analytical solution (bending of a Timoshenko beam) while in 3D we solve an elasticity problem which has an exact finite element solution (unconstrained compression of a cube). We also solve a complex problem involving complicated geometry, non-linear material, large deformations and contacts. The simulation results demonstrate the superior performance of the MMLS over classical MLS in terms of solution accuracy, while shape functions can be computed using the same nodal distribution and support domain size for both methods.

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References

  1. Miller, K., Horton, A., Joldes, G.R., Wittek, A.: Beyond finite elements: a comprehensive, patient-specific neurosurgical simulation utilizing a meshless method. J. Biomech. 45, 2698–2701 (2012)

    Article  Google Scholar 

  2. Horton, A., Wittek, A., Joldes, G.R., Miller, K.: A meshless total Lagrangian explicit dynamics algorithm for surgical simulation. Int. J. Numer. Method Biomed. Eng. 26, 977–998 (2010)

    Article  MATH  Google Scholar 

  3. Li, M., Miller, K., Joldes, G.R., Kikinis, R., Wittek, A.: Biomechanical model for computing deformations for whole-body image registration: a meshless approach. Int. J. Numer. Methods Biomed. Eng. (2016). doi:10.1002/cnm.2771

    Google Scholar 

  4. Jin, X., Joldes, G.R., Miller, K., Yang, K.H., Wittek, A.: Meshless algorithm for soft tissue cutting in surgical simulation. Comput. Methods Biomech. Biomed. Eng. 17, 800–811 (2014)

    Article  Google Scholar 

  5. Belytschko, T., Lu, Y.Y., Gu, L.: Element-free Galerkin methods. Int. J. Numer. Methods Eng. 37, 229–256 (1994)

    Article  MathSciNet  MATH  Google Scholar 

  6. Nayroles, B., Touzot, G., Villon, P.: Generalizing the finite element method: diffuse approximation and diffuse elements. Comput. Mech. 10, 307–318 (1992)

    Article  MATH  Google Scholar 

  7. Liu, G.R.: Meshfree Methods: Moving Beyond the Finite Element Method. CRC Press, Boca Raton (2010)

    MATH  Google Scholar 

  8. Joldes, G.R., Wittek, A., Miller, K.: Adaptive numerical integration in element-free Galerkin methods for elliptic boundary value problems. Eng. Anal. Bound. Elem. 51, 52–63 (2015)

    Article  MathSciNet  Google Scholar 

  9. Liu, G.-R., Gu, Y.-T.: An Introduction to Meshfree Methods and Their Programming. Springer, Berlin (2005)

    Google Scholar 

  10. Fasshauer, G.E.: Meshfree Approximation Methods with MATLAB. World Scientific Publishing Co. Inc, Singapore (2007)

    Book  MATH  Google Scholar 

  11. Joldes, G.R., Chowdhury, H.A., Wittek, A., Doyle, B., Miller, K.: Modified moving least squares with polynomial bases for scattered data approximation. Appl. Math. Comput. 266, 893–902 (2015)

    MathSciNet  Google Scholar 

  12. Chowdhury, H., Joldes, G., Wittek, A., Doyle, B., Pasternak, E., Miller, K.: Implementation of a modified moving least squares approximation for predicting soft tissue deformation using a meshless method. In: Doyle, B., Miller, K., Wittek, A., Nielsen, P.M.F. (eds.) Computational Biomechanics for Medicine, pp. 59–71. Springer, Berlin (2015)

    Google Scholar 

  13. Timoshenko, S., Goodier, J.N.: Theory of Elasticity, 3rd edn. McGraw-Hill, New York (1970)

    MATH  Google Scholar 

  14. Belytschko, T., Organ, D., Krongauz, Y.: A coupled finite element—element-free Galerkin method. Comput. Mech. 17, 186–195 (1995)

    Article  MathSciNet  MATH  Google Scholar 

  15. Zhang, G., Wittek, A., Joldes, G.R., Jin, X., Miller, K.: A three-dimensional nonlinear meshfree algorithm for simulating mechanical responses of soft tissue. Eng. Anal. Bound. Elem. 42, 60–66 (2014)

    Article  MathSciNet  MATH  Google Scholar 

  16. Joldes, G.R., Wittek, A., Miller, K.: An adaptive dynamic relaxation method for solving nonlinear finite element problems. Application to brain shift estimation. Int. J. Numer. Methods Biomed. Eng. 27, 173–185 (2011)

    Article  MathSciNet  MATH  Google Scholar 

  17. Joldes, G.R., Wittek, A., Miller, K.: Computation of intra-operative brain shift using dynamic relaxation. Comput. Methods Appl. Mech. Eng. 198, 3313–3320 (2009)

    Article  MathSciNet  MATH  Google Scholar 

  18. Miller, K.: Biomechanics of the Brain. Springer, Berlin (2011)

    Book  Google Scholar 

  19. Miller, K., Chinzei, K., Orssengo, G., Bednarz, P.: Mechanical properties of brain tissue in-vivo: experiment and computer simulation. J. Biomech. 33, 1369–1376 (2000)

    Article  Google Scholar 

  20. Joldes, G.R., Wittek, A., Couton, M., Warfield, S.K., Miller, K.: Real-time prediction of brain shift using nonlinear finite element algorithms. In: Medical Image Computing and Computer-Assisted Intervention—Miccai 2009, Pt II, Proceedings vol. 5762, pp. 300–307 (2009)

  21. Zhang, J.Y., Joldes, G.R., Wittek, A., Miller, K.: Patient-specific computational biomechanics of the brain without segmentation and meshing. Int. J. Numer. Methods. Biomed. Eng. 29, 293–308 (2013)

    Article  MathSciNet  Google Scholar 

  22. Most, T., Bucher, C.: A moving least squares weighting function for the element-free Galerkin method which almost fulfills essential boundary conditions. Struct. Eng. Mech. 21, 315–332 (2005)

    Article  Google Scholar 

  23. Chowdhury, H.A., Joldes, G.R., Wittek, A., Doyle, B., Pasternak, E., Miller, K.: Implementation of a modified moving least squares approximation for predicting soft tissue deformation using a meshless method. In: Doyle, B.J., Miller, K., Wittek, A., Nielsen, P.M.F. (eds.) Computational Biomechanics for Medicine: New Approaches and New Applications, pp. 59–71. Springer, New York (2015)

    Google Scholar 

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Acknowledgements

The first author is a recipient of the SIRF scholarship and acknowledges the financial support of the University of Western Australia. The financial support of Australian Research Council (Discovery Grants No. DP120100402 and DP160100714) is gratefully acknowledged. We wish to acknowledge the Raine Medical Research Foundation for funding G. R. Joldes through a Raine Priming Grant.

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Correspondence to Grand Roman Joldes.

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Chowdhury, H.A., Wittek, A., Miller, K. et al. An Element Free Galerkin Method Based on the Modified Moving Least Squares Approximation. J Sci Comput 71, 1197–1211 (2017). https://doi.org/10.1007/s10915-016-0337-z

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  • DOI: https://doi.org/10.1007/s10915-016-0337-z

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