Startseite An adaptive multigrid conjugate gradient method for the inversion of a nonlinear convection-diffusion equation
Artikel
Lizenziert
Nicht lizenziert Erfordert eine Authentifizierung

An adaptive multigrid conjugate gradient method for the inversion of a nonlinear convection-diffusion equation

  • Tao Liu EMAIL logo
Veröffentlicht/Copyright: 13. März 2018

Abstract

This paper considers the problem of estimating the permeability in a nonlinear convection-diffusion equation. To overcome the large calculation burden of conventional methods, we apply an adaptive multigrid conjugate gradient method to solve this inverse problem. This new method combines the multigrid multiscale idea with the conjugate gradient method, and adopts the necessary condition that the optimum solution should be the fixed point of the multigrid inversion method. Some numerical results verify that the proposed method both dramatically reduces the required computations and improves the inversion quality.

Award Identifier / Grant number: 11271102

Award Identifier / Grant number: A2017501001

Award Identifier / Grant number: XNB2015002

Funding statement: This work was supported by the National Natural Science Foundation of China (11271102), the Natural Science Foundation of He-bei Province of China (A2017501001) and the PhD Foundation of Northeast University at Qinhuangdao (XNB2015002).

References

[1] S. S. Adavani and G. Biros, Multigrid algorithms for inverse problems with linear parabolic PDE constraints, SIAM J. Sci. Comput. 31 (2008), no. 1, 369–397. 10.1137/070687426Suche in Google Scholar

[2] Y. Choi, D. Jeong and J. Kim, A multigrid solution for the Cahn–Hilliard equation on nonuniform grids, Appl. Math. Comput. 293 (2017), 320–333. 10.1016/j.amc.2016.08.026Suche in Google Scholar

[3] B. Engquist and S. Osher, One-sided difference approximations for nonlinear conservation laws, Math. Comp. 36 (1981), no. 154, 321–351. 10.1090/S0025-5718-1981-0606500-XSuche in Google Scholar

[4] M. S. Espedal and K. H. Karlsen, Numerical solution of reservoir flow models based on large time step operator splitting algorithms, Filtration in Porous Media and Industrial Application (Cetraro 1998), Lecture Notes in Math. 1734, Springer, Berlin (2000), 9–77. 10.1007/BFb0103975Suche in Google Scholar

[5] R. Fletcher and C. M. Reeves, Function minimization by conjugate gradients, Comput. J. 7 (1964), 149–154. 10.1093/comjnl/7.2.149Suche in Google Scholar

[6] U. Ghia, K. N. Ghia and C. T. Shin, High-Re solutions for incompressible flow using the Navier–Stokes equations and a multigrid method, J. Comput. Phys. 48 (1982), 387–411. 10.1016/0021-9991(82)90058-4Suche in Google Scholar

[7] W. Hackbusch, Multigrid Methods and Applications, Springer Ser. Comput. Math. 4, Springer, Berlin, 1985. 10.1007/978-3-662-02427-0Suche in Google Scholar

[8] A. Hasanov and B. Pektaş, Identification of an unknown time-dependent heat source term from overspecified Dirichlet boundary data by conjugate gradient method, Comput. Math. Appl. 65 (2013), no. 1, 42–57. 10.1016/j.camwa.2012.10.009Suche in Google Scholar

[9] C. H. Huang and W. C. Chen, A three-dimensional inverse forced convection problem in estimating surface heat flux by conjugate gradient method, Int. J. Heat Mass Transfer 43 (2000), 3171–3181. 10.1016/S0017-9310(99)00330-0Suche in Google Scholar

[10] C. H. Huang and M. N. Özisik, Inverse problem of determining unknown wall heat flux in laminar flow through a parallel plate duct, Numer. Heat Transfer 21 (1992), 55–70. 10.1080/10407789208944865Suche in Google Scholar

[11] C. H. Huang and S. P. Wang, A three-dimensional inverse heat conduction problem in estimating surface heat flux by conjugate gradient method, Int. J. Heat Mass Transfer 42 (1999), 3387–3403. 10.1016/S0017-9310(99)00020-4Suche in Google Scholar

[12] B. Kaltenbacher, M. Kaltenbacher and S. Reitzinger, Identification of nonlinear B-H curves based on magnetic field computations and multigrid methods for ill-posed problems, European J. Appl. Math. 14 (2003), no. 1, 15–38. 10.1017/S0956792502005089Suche in Google Scholar

[13] H. K. Kim and A. Charette, A sensitivity function-based conjugate gradient method for optical tomography with the frequency-domain equation of radiative transfer, J. Quant. Spectroscopy Radiative Transf. 104 (2007), 24–39. 10.1016/j.jqsrt.2006.08.007Suche in Google Scholar

[14] T. Liu, Reconstruction of a permeability field with the wavelet multiscale-homotopy method for a nonlinear convection-diffusion equation, Appl. Math. Comput. 275 (2016), 432–437. 10.1016/j.amc.2015.11.095Suche in Google Scholar

[15] I. E. Livieris, D. G. Sotiropoulos and P. Pintelas, On descent spectral CG algorithms for training recurrent neural networks, 13th Panellenic Conference of Informatics, IEEE Press, Piscataway (2009), 65–69. 10.1109/PCI.2009.33Suche in Google Scholar

[16] M. Mohammadiun, A. B. Rahimi and I. Khazaee, Estimation of the time-dependent heat flux using the temperature distribution at a point by conjugate gradient method, Int. J. Therm. Sci. 50 (2011), 2443–2450. 10.1016/j.ijthermalsci.2011.07.003Suche in Google Scholar

[17] S. G. Nash, A multigrid approach to discretized optimization problems, Optim. Methods Softw. 14 (2000), no. 1–2, 99–116. 10.1080/10556780008805795Suche in Google Scholar

[18] T. K. Nilssen, K. H. Karlsen, T. Mannseth and X.-C. Tai, Identification of diffusion parameters in a nonlinear convection-diffusion equation using the augmented Lagrangian method, Comput. Geosci. 13 (2009), no. 3, 317–329. 10.1007/s10596-008-9120-zSuche in Google Scholar

[19] T. S. Shores, Numerical methods for parameter identification in a convection-diffusion equation, ANZIAM J. 45 (2003/04), C660–C675. 10.21914/anziamj.v45i0.915Suche in Google Scholar

[20] C. R. Vogel and Q. Yang, Multigrid algorithm for least-squares wavefront reconstruction, Appl. Optics 45 (2006), 705–715. 10.1364/AO.45.000705Suche in Google Scholar PubMed

[21] L. Wang, H. Cao, X. Han, J. Liu and Y. Xie, An efficient conjugate gradient method and application to dynamic force reconstruction, J. Comput. Sci. 8 (2015), 101–108. 10.1016/j.jocs.2015.03.008Suche in Google Scholar

[22] J. C. Ye, C. A. Bouman, K. J. Webb and R. P. Millane, Nonlinear multigrid algorithms for Bayesian optical diffusion tomography, IEEE Trans. Image Process. 10 (2001), 909–922. 10.1109/83.923287Suche in Google Scholar

[23] J. Zhao and T. Liu, An adaptive multigrid conjugate gradient method for permeability identification of nonlinear diffusion equation, J. Inverse Ill-Posed Probl. 24 (2016), no. 1, 89–97. 10.1515/jiip-2014-0036Suche in Google Scholar

[24] J. Zhao, T. Liu and G. Feng, A nonlinear multigrid method for inversion of two-dimensional acoustic wave equation, J. Inverse Ill-Posed Probl. 22 (2014), no. 3, 429–448. 10.1515/jip-2012-0060Suche in Google Scholar

[25] J. Zhao, T. Liu and S. Liu, Identification of space-dependent permeability in nonlinear diffusion equation from interior measurements using wavelet multiscale method, Inverse Probl. Sci. Eng. 22 (2014), no. 4, 507–529. 10.1080/17415977.2013.792078Suche in Google Scholar

Received: 2016-09-19
Revised: 2017-07-19
Accepted: 2018-03-01
Published Online: 2018-03-13
Published in Print: 2018-10-01

© 2018 Walter de Gruyter GmbH, Berlin/Boston

Heruntergeladen am 10.10.2025 von https://www.degruyterbrill.com/document/doi/10.1515/jiip-2016-0062/html
Button zum nach oben scrollen