The extended adjoint method

Stanislas Larnier; Mohamed Masmoudi

ESAIM: Mathematical Modelling and Numerical Analysis - Modélisation Mathématique et Analyse Numérique (2013)

  • Volume: 47, Issue: 1, page 83-108
  • ISSN: 0764-583X

Abstract

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Searching for the optimal partitioning of a domain leads to the use of the adjoint method in topological asymptotic expansions to know the influence of a domain perturbation on a cost function. Our approach works by restricting to local subproblems containing the perturbation and outperforms the adjoint method by providing approximations of higher order. It is a universal tool, easily adapted to different kinds of real problems and does not need the fundamental solution of the problem; furthermore our approach allows to consider finite perturbations and not infinitesimal ones. This paper provides theoretical justifications in the linear case and presents some applications with topological perturbations, continuous perturbations and mesh perturbations. This proposed approach can also be used to update the solution of singularly perturbed problems.

How to cite

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Larnier, Stanislas, and Masmoudi, Mohamed. "The extended adjoint method." ESAIM: Mathematical Modelling and Numerical Analysis - Modélisation Mathématique et Analyse Numérique 47.1 (2013): 83-108. <http://eudml.org/doc/273329>.

@article{Larnier2013,
abstract = {Searching for the optimal partitioning of a domain leads to the use of the adjoint method in topological asymptotic expansions to know the influence of a domain perturbation on a cost function. Our approach works by restricting to local subproblems containing the perturbation and outperforms the adjoint method by providing approximations of higher order. It is a universal tool, easily adapted to different kinds of real problems and does not need the fundamental solution of the problem; furthermore our approach allows to consider finite perturbations and not infinitesimal ones. This paper provides theoretical justifications in the linear case and presents some applications with topological perturbations, continuous perturbations and mesh perturbations. This proposed approach can also be used to update the solution of singularly perturbed problems.},
author = {Larnier, Stanislas, Masmoudi, Mohamed},
journal = {ESAIM: Mathematical Modelling and Numerical Analysis - Modélisation Mathématique et Analyse Numérique},
keywords = {adjoint method; topology optimization; calculus of variations},
language = {eng},
number = {1},
pages = {83-108},
publisher = {EDP-Sciences},
title = {The extended adjoint method},
url = {http://eudml.org/doc/273329},
volume = {47},
year = {2013},
}

TY - JOUR
AU - Larnier, Stanislas
AU - Masmoudi, Mohamed
TI - The extended adjoint method
JO - ESAIM: Mathematical Modelling and Numerical Analysis - Modélisation Mathématique et Analyse Numérique
PY - 2013
PB - EDP-Sciences
VL - 47
IS - 1
SP - 83
EP - 108
AB - Searching for the optimal partitioning of a domain leads to the use of the adjoint method in topological asymptotic expansions to know the influence of a domain perturbation on a cost function. Our approach works by restricting to local subproblems containing the perturbation and outperforms the adjoint method by providing approximations of higher order. It is a universal tool, easily adapted to different kinds of real problems and does not need the fundamental solution of the problem; furthermore our approach allows to consider finite perturbations and not infinitesimal ones. This paper provides theoretical justifications in the linear case and presents some applications with topological perturbations, continuous perturbations and mesh perturbations. This proposed approach can also be used to update the solution of singularly perturbed problems.
LA - eng
KW - adjoint method; topology optimization; calculus of variations
UR - http://eudml.org/doc/273329
ER -

References

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  1. [1] G. Allaire, F. de Gournay, F. Jouve and A.-M. Toader, Structural optimization using topological and shape sensitivity via a level set method. Control Cybern.34 (2005) 59–80. Zbl1167.49324MR2211063
  2. [2] H. Ammari and H. Kang, High-order terms in the asymptotic expansions of the steady-state voltage potentials in the presence of conductivity inhomogeneities of small diameter. SIAM J. Math. Anal.34 (2003) 1152–1166. Zbl1036.35050MR2001663
  3. [3] H. Ammari and H. Kang, Reconstruction of small inhomogeneities from boundary measurements. Lect. Notes Math. 1846 (2004). Zbl1113.35148MR2168949
  4. [4] H. Ammari and J.K. Seo, An accurate formula for the reconstruction of conductivity inhomogeneities. Adv. Appl. Math.30 (2003) 679–705. Zbl1040.78008MR1977849
  5. [5] H. Ammari, S. Moskow and M.S. Vogelius, Boundary integral formulae for the reconstruction of electric and electromagnetic inhomogeneities of small volume. ESAIM : COCV 9 (2003) 49–66. Zbl1075.78010MR1957090
  6. [6] H. Ammari, E. Iakovleva, D. Lesselier and G. Perrusson, MUSIC-type electromagnetic imaging of a collection of small three-dimensional inclusions. SIAM J. Sci. Comput.29 (2007) 674–709. Zbl1132.78308MR2306264
  7. [7] H. Ammari, E. Bonnetier, Y. Capdeboscq, M. Tanter and M. Fink, Electrical impedance tomography by elastic deformation. SIAM J. Appl. Math.68 (2008) 1557–1573. Zbl1156.35101MR2424952
  8. [8] H. Ammari, P. Garapon, H. Kang and H. Lee, A method of biological tissues elasticity reconstruction using magnetic resonance elastography measurements. Quart. Appl. Math.66 (2008) 139–175. Zbl1143.35384MR2396655
  9. [9] H. Ammari, P. Garapon, H. Kang and H. Lee, Separation of scales in elasticity imaging : a numerical study. J. Comput. Math.28 (2010) 354–370. Zbl1222.92051
  10. [10] S. Amstutz, M. Masmoudi and B. Samet, The topological asymptotic for the Helmoltz equation. SIAM J. Control Optim.42 (2003) 1523–1544. Zbl1051.49029MR2046373
  11. [11] S. Amstutz, I. Horchani and M. Masmoudi, Crack detection by the topological gradient method. Control Cybern.34 (2005) 81–101. Zbl1167.74437MR2211064
  12. [12] G. Aubert and P. Kornprobst, Mathematical Problems in Image Processing : Partial Differential Equations and the Calculus of Variations. Appl. Math. Sci. 147 (2001). Zbl1110.35001MR2244145
  13. [13] D. Auroux and M. Masmoudi, A one-shot inpainting algorithm based on the topological asymptotic analysis. Comput. Appl. Math.25 (2006) 251–267. Zbl1182.94006MR2321652
  14. [14] D. Auroux and M. Masmoudi, Image processing by topological asymptotic expansion. J. Math. Imag. Vision33 (2009) 122–134. MR2480980
  15. [15] D. Auroux and M. Masmoudi, Image processing by topological asymptotic analysis. ESAIM : Proc. Math. Methods Imag. Inverse Probl. 26 (2009) 24–44. Zbl1183.68679MR2498137
  16. [16] L.J. Belaid, M. Jaoua, M. Masmoudi and L. Siala, Image restoration and edge detection by topological asymptotic expansion. C. R. Acad. Sci. Paris342 (2006) 313–318. Zbl1086.68141MR2201955
  17. [17] M. Bonnet, Higher-order topological sensitivity for 2-d potential problems. application to fast identification of inclusions. Int. J. Solids Struct. 46 (2009) 2275–2292. Zbl1217.74095MR2517928
  18. [18] M. Bonnet, Fast identification of cracks using higher-order topological sensitivity for 2-d potential problems. Special issue on the advances in mesh reduction methods. In honor of Professor Subrata Mukherjee on the occasion of his 65th birthday. Eng. Anal. Bound. Elem. 35 (2011) 223–235. Zbl1259.74025MR2740347
  19. [19] Y. Capdeboscq and M.S. Vogelius, A general representation formula for boundary voltage perturbations caused by internal conductivity inhomogeneities of low volume fraction. ESAIM : M2AN 37 (2003) 159–173. Zbl1137.35346MR1972656
  20. [20] Y. Capdeboscq and M.S. Vogelius, Optimal asymptotic estimates for the volume of internal inhomogeneities in terms of multiple boundary measurements. ESAIM : M2AN 37 (2003) 227–240. Zbl1137.35347MR1991198
  21. [21] J. Fehrenbach and M. Masmoudi, Coupling topological gradient and Gauss-Newton methods, in IUTAM Symposium on Topological Design Optimization. Edited by M.P. Bendsoe, N. Olhoff and O. Sigmund. Springer (2006). 
  22. [22] J. Fehrenbach, M. Masmoudi, R. Souchon and P. Trompette, Detection of small inclusions using elastography. Inverse Probl.22 (2006) 1055–1069. Zbl1099.74028MR2235654
  23. [23] S. Garreau, P. Guillaume and M. Masmoudi, The topological asymptotic for pde systems : the elasticity case. SIAM J. Control Optim.39 (2001) 1756–1778. Zbl0990.49028MR1825864
  24. [24] P. Guillaume and M. Hassine, Removing holes in topological shape optimization. ESAIM : COCV 14 (2008) 160–191. Zbl1140.49029MR2375755
  25. [25] P. Guillaume and K. Sid Idris, The topological asymptotic expansion for the Dirichlet problem. SIAM J. Control Optim.41 (2002) 1042–1072. Zbl1053.49031MR1972502
  26. [26] P. Guillaume and K. Sid Idris, The topological sensitivity and shape optimization for the Stokes equations. SIAM J. Control Optim.43 (2004) 1–31. Zbl1093.49029MR2081970
  27. [27] M. Hassine, S. Jan and M. Masmoudi, From differential calculus to 0-1 topological optimization. SIAM, J. Control Optim. 45 (2007) 1965–1987. Zbl1139.49039MR2285710
  28. [28] S. Larnier and J. Fehrenbach, Edge detection and image restoration with anisotropic topological gradient, in IEEE International Conference on Acoustics Speech and Signal Processing (ICASSP) (2010) 1362–1365. 
  29. [29] L. Martin, Conception aérodynamique robuste. Ph.D. thesis, Université Paul Sabatier, Toulouse, France (2011). 
  30. [30] M. Masmoudi, The topological asymptotic, in Computational Methods for Control Applications, GAKUTO International Series, edited by R. Glowinski, H. Karawada and J. Periaux. Math. Sci. Appl. 16 (2001) 53–72. Zbl1082.93584
  31. [31] B. Mohammadi and O. Pironneau, Shape optimization in fluid mechanics. Annu. Rev. Fluid Mech.36 (2004) 255–279. Zbl1076.76020MR2062314
  32. [32] J. Ophir, I. Céspedes, H. Ponnekanti, Y. Yazdi and X. Li, Elastography : a quantitative method for imaging the elasticity of biological tissues. Ultrason. Imag.13 (1991) 111–134. 
  33. [33] J. Ophir, S. Alam, B. Garra, F. Kallel, E. Konofagou, T. Krouskop, C. Merritt, R. Righetti, R. Souchon, S. Srinivan and T. Varghese, Elastography : imaging the elastic properties of soft tissues with ultrasound. J. Med. Ultrason.29 (2002) 155–171. 
  34. [34] B. Samet, The topological asymptotic with respect to a singular boundary perturbation. C. R. Math.336 (2003) 1033–1038. Zbl1028.65123MR1993977
  35. [35] A. Schumacher, Topologieoptimisierung von Bauteilstrukturen unter Verwendung von Lopchpositionierungkrieterien. Ph.D. thesis, Universitat-Gesamthochschule Siegen, Germany (1995). 
  36. [36] J. Sokolowski and A. Zochowski, On the topological derivative in shape optimization. SIAM J. Control Optim.37 (1999) 1251–1272. Zbl0940.49026MR1691940
  37. [37] Z. Wang, A.C. Bovik, H.R. Sheikh and E.P. Simoncelli, Image quality assessment : from error visibility to structural similarity. IEEE Trans. Image Process.13 (2004) 600–612. 

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