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Tytuł artykułu

One-dimensional fully automatic h-adaptive isogeometric finite element method package

Treść / Zawartość
Identyfikatory
Warianty tytułu
Języki publikacji
EN
Abstrakty
EN
his paper deals with an adaptive finite element method originally developed by Prof. Leszek Demkowicz for hierarchical basis functions. In this paper, we investigate the extension of the adaptive algorithm for isogeometric analysis performed with B-spline basis functions. We restrict ourselves to h-adaptivity, since the polynomial order of approximation must be fixed in the isogeometric case. The classical variant of the adaptive FEM algorithm, as delivered by the group of Prof. Demkowicz, is based on a two-grid paradigm, with coarse and fine grids (the latter utilized as a reference solution). The problem is solved independently over a coarse mesh and a fine mesh. The fine-mesh solution is then utilized as a reference to estimate the relative error of the coarse-mesh solution and to decide which elements to refine. Prof. Demkowicz uses hierarchical basis functions, which (though locally providing Cp−1 continuity) ensure only C0 on the interfaces between elements. The CUDA C library described in this paper switches the basis to B-spline functions and proposes a one-dimensional isogeometric version of the h-adaptive FEM algorithm to achieve global Cp−1 continuity of the solution.
Wydawca
Czasopismo
Rocznik
Strony
439--459
Opis fizyczny
Bibliogr, 19 poz, wykr.
Twórcy
autor
  • AGH University of Science and Technology, Krakow, Poland
autor
  • AGH University of Science and Technology, Krakow, Poland
Bibliografia
  • [1] Babuska I., Guo B.: The hp-version of the finite element method, Part I: The basic approximation results. Computational Mechanics, pp. 21–41, 1986.
  • [2] Babuska I., Guo B.: The hp-version of the finite element method, Part II: General results and applications. Computational Mechanics, pp. 203–220, 1986.
  • [3] Babuska I., Rheinboldt W.C.: Error Estimates for Adaptive Finite Element Computations. SIAM Journal of Numerical Analysis, vol. 15(4), pp. 736–754, 1978.
  • [4] Bazilevs Y., Beirao Da Veiga L., Cottrell J.A., Hughes T.J.R., Sangalli G.: Isogeometric analysis: Approximation, stability and error estimates for h-refined meshes. Mathematical Models and Methods in Applied Sciences, vol. 16(7), pp. 1031–1090,2006.
  • [5] Becker R., Hartmut K., Rannacher R.: Adaptive finite element methods for optimal control of partial differential equations: Basic concept. SIAM Journal on Control and Optimisation, vol. 39(1), pp. 113–132, 2000.
  • [6] Belytschko T., Tabbara M.: H-adaptive finite element methods for dynamic problems,with emphasis on localization. International Journal for Numerical Methods in Engineering, vol. 36(24), pp. 4245–4265, 1993.
  • [7] Cottrell J., Hughes T.J., Bazilevs Y.: Isogeometric Analysis: Toward Integration of CAD and FEA. Wiley Publishing, 1st ed., 2009.
  • [8] Demkowicz L.: Computing with h-adaptive finite element methods. Part I. Elliptic and Maxwell problems with applications. Taylor & Francis, CRC Press, 2006.
  • [9] Eriksson K., Johnson C.: Adaptive Finite Element Methods for Parabolic Problems I: A Linear Model Problem. SIAM Journal on Numerical Analysis, vol. 28(1), pp. 43–77, 1991.
  • [10] Gang B., Guanghui H., Di L.: An h-adaptive finite element solver for the calculations of the electronic structures. Journal of Computational Physics, vol. 231(14), pp. 4967–4979, 2012.
  • [11] Kardani M., Nazem M., Abbo A.J., Sheng D., Sloan S.W.: Refined h-adaptive finite element procedure for large deformation geotechnical problems. Computational Mechanics, vol. 49(1), pp. 21–33, 2012.
  • [12] Krawezik G., Poole G.: Accelerating the ANSYS Direct Sparse Solver with GPUs. In: Symposium on Application Accelerators in High Performance Computing, SAAHPC, 2009.
  • [13] Kuznik K., Paszynski M., Calo V.: Grammar-Based Multi-Frontal Solver for One Dimensional Isogeometric Analysis with Multiple Right-Hand-Sides. Procedia Computer Science, vol. 18(0), pp. 1574–1583, 2013.
  • [14] Lucas R.F., Wagenbreth G., Davis D.M., Grimes R.: Multifrontal Computations on GPUs and Their Multi-core Hosts. In: VECPAR, Lecture Notes in Computer Science, vol. 6449, pp. 71–82, 2010.
  • [15] Niemi A.H., Babuˇska I., Pitkaranta J., Demkowicz L.: Finite element analysis of the Girkmann problem using the modern hp-version and the classical h-version. Engineering with Computers, vol. 28(2), pp. 123–134, 2012.
  • [16] Nochetto R.H., Siebert K.G., Veeser A.: Multiscale, Nonlinear and Adaptive Approximation. Springer, 2009.
  • [17] Piegl L., Tiller W.: The NURBS Book (Second Edition). Springer-Verlag New York, 1997.
  • [18] Wozniak M., Kuznik K., Paszynski M., Calo V., Pardo D.: Computational cost estimates for parallel shared memory isogeometric multi-frontal solvers. Computers and Mathematics with Applications, vol. 67(10), pp. 1864–1883, 2014.
  • [19] Yu C.D., Wang W., Pierce D.: A CPU-GPU Hybrid Approach for the Unsymmetric Multifrontal Method. Parallel Computing, vol. 37(12), pp. 759–770, 2011.
Uwagi
Opracowanie ze środków MNiSW w ramach umowy 812/P-DUN/2016 na działalność upowszechniającą naukę.
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-81a4f720-b26f-4b6b-a28b-49db57109854
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