3D inverse scattering by level set with zero capacity connecting set. Wave guide optimization by ¿zone¿

Dubois, Pierre; Dedeban, Claude; Zolésio, Jean-Paul

doi:10.1109/eucap.2006.4584914

Cited by 2 publications

(3 citation statements)

References 2 publications

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“…When the initial guess was different in shape and far in location from the true target, more iterations and frequencies were needed; however, the evolving object always converged to the true one [7][8][9][10]. The initial guess was also selected as four spheres, they merged into one sphere demonstrating the successful convergence of the level set algorithm in the work by Dubios et al [18]. Therefore for simplicity in this work, the initial guess of the 3D bacteria was selected to be a sphere of radius 1.5 µm located at the center of the computational domain.…”

Section: Numerical Resultsmentioning

confidence: 91%

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Inverse Scattering Shape Reconstruction of 3d Bacteria Using the Level Set Algorithm

Hassan¹,

Hajihashemi²,

El-Shenawee³

2012

PIER B

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Abstract-Bacteria exist in a variety of groups of shapes, sizes, and single or multiple cell formations. In this paper, the level set shape reconstruction technique, the method of moments, and the marching cubes methods are integrated in the high frequency band for imaging three dimensional bacteria. The time step and the resolution of the marching cubes method are investigated to smooth the error function of the level set and hence speed up the convergence at high frequencies. The numerical results demonstrate the robustness of the level set algorithm for the detection of bacteria based on their shapes. The three dimensional shape reconstructions of unknown bacteria can be utilized to classify biological warfare agents.

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Section: Numerical Resultsmentioning

confidence: 91%

“…As published in the literature (e.g., [7][8][9][10]18]), the level set method has been proven to be robust. Therefore the algorithm always converges to the true target regardless of the initial guess.…”

Section: Numerical Resultsmentioning

confidence: 99%

Inverse Scattering Shape Reconstruction of 3d Bacteria Using the Level Set Algorithm

Hassan¹,

Hajihashemi²,

El-Shenawee³

2012

PIER B

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“…Wang and Wang [47] proposed the incorporation of the superimposed FEM into level set-based topology optimization. Dubois et al [48] proposed the use of a 3D surface mesh generated by the marching cube method [49] for optimization. Zhou et al [50] demonstrated that the adaptive mesh generating scheme proposed by Perrson and Strang [51] can be employed for level set-based topology optimization.…”

Section: Introductionmentioning

confidence: 99%

A level set‐based topology optimization method targeting metallic waveguide design problems

Yamasaki

Nomura

Kawamoto

et al. 2011

Numerical Meth Engineering

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SUMMARYIn this paper, we propose a level set-based topology optimization method targeting metallic waveguide design problems, where the skin effect must be taken into account since the metallic waveguides are generally used in the high-frequency range where this effect critically affects performance. One of the most reasonable approaches to represent the skin effect is to impose an electric field constraint condition on the surface of the metal. To implement this approach, we develop a boundary-tracking scheme for the arbitrary Lagrangian Eulerian (ALE) mesh pertaining to the zero iso-contour of the level set function that is given in an Eulerian mesh, and impose Dirichlet boundary conditions at the nodes on the zero iso-contour in the ALE mesh to compute the electric field. Since the ALE mesh accurately tracks the zero iso-contour at every optimization iteration, the electric field is always appropriately computed during optimization. For the sensitivity analysis, we compute the nodal coordinate sensitivities in the ALE mesh and smooth them by solving a Helmholtz-type partial differential equation. The obtained smoothed sensitivities are used to compute the normal velocity in the level set equation that is solved using the Eulerian mesh, and the level set function is updated based on the computed normal velocity. Finally, the utility of the proposed method is discussed through several numerical examples.

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3D inverse scattering by level set with zero capacity connecting set. Wave guide optimization by ¿zone¿

Cited by 2 publications

References 2 publications

Inverse Scattering Shape Reconstruction of 3d Bacteria Using the Level Set Algorithm

Inverse Scattering Shape Reconstruction of 3d Bacteria Using the Level Set Algorithm

A level set‐based topology optimization method targeting metallic waveguide design problems

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