### Résumé

langue originale | Anglais |
---|---|

Lieu de publication | Aveiro, Portugal |

Éditeur | Andreas Öchsner, José Gracio, Frédéric Barlat |

état | Publié - 2005 |

### Empreinte digitale

### Citer ceci

*Matlab implementation of inverse diffusion methods Afina LUPULESCU, Christopher O BRIEN, Martin GLICKSMAN, Wei YANG,*Aveiro, Portugal: Andreas Öchsner, José Gracio, Frédéric Barlat.

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**Matlab implementation of inverse diffusion methods Afina LUPULESCU, Christopher O BRIEN, Martin GLICKSMAN, Wei YANG,** / Hubert, Renaud; LUPULESCU, Afina; O'BRIEN, Christopher; GLICKSMAN, Martin; YANG, Wei.

Résultats de recherche: Papier de travail › Article de travail

TY - UNPB

T1 - Matlab implementation of inverse diffusion methods Afina LUPULESCU, Christopher O BRIEN, Martin GLICKSMAN, Wei YANG,

AU - Hubert, Renaud

AU - LUPULESCU, Afina

AU - O'BRIEN, Christopher

AU - GLICKSMAN, Martin

AU - YANG, Wei

PY - 2005

Y1 - 2005

N2 - One of the authors (CJO) developed a MATLAB code called Inversemethods to determine concentration'dependent diffusivities from experimental data. This software allows comparison between the diffusivities calculated with four numerical methods: a) Boltzmann-Matano (BM), b) Sauer-Freise-den Broeder (SFB), c) Fictitious image'source method (error function approximation), and d) Fourier series image'source solutions. The choice of writing this code in MATLAB was meeting the requirements for portability, as MATLAB runs on various platforms and enables users to perform subsequent analyses on the data produced by this program. The BM and SFB methods are implemented following Simpson's rule to calculate the integrals, and employs a simple finite'difference method to calculate the derivatives. The software also implements a Savizky-Golay filtering algorithm that smoothes noisy penetration data by locally fitting a 3rd-order polynomial to 201 points. Such parameters were found to be most effective for noisy experimental data obtained using electron microprobe, proton-induced X-ray emission (PIXE), and Rutherford Back Scattering (RBS).

AB - One of the authors (CJO) developed a MATLAB code called Inversemethods to determine concentration'dependent diffusivities from experimental data. This software allows comparison between the diffusivities calculated with four numerical methods: a) Boltzmann-Matano (BM), b) Sauer-Freise-den Broeder (SFB), c) Fictitious image'source method (error function approximation), and d) Fourier series image'source solutions. The choice of writing this code in MATLAB was meeting the requirements for portability, as MATLAB runs on various platforms and enables users to perform subsequent analyses on the data produced by this program. The BM and SFB methods are implemented following Simpson's rule to calculate the integrals, and employs a simple finite'difference method to calculate the derivatives. The software also implements a Savizky-Golay filtering algorithm that smoothes noisy penetration data by locally fitting a 3rd-order polynomial to 201 points. Such parameters were found to be most effective for noisy experimental data obtained using electron microprobe, proton-induced X-ray emission (PIXE), and Rutherford Back Scattering (RBS).

KW - Fourier series

KW - Numerical methods

KW - Basics of diffusion

KW - Fictitious Image Source

KW - Savizky-Golay

KW - Sauer Freise den Broeder

KW - Boltzmann-Matano

M3 - Working paper

BT - Matlab implementation of inverse diffusion methods Afina LUPULESCU, Christopher O BRIEN, Martin GLICKSMAN, Wei YANG,

PB - Andreas Öchsner, José Gracio, Frédéric Barlat

CY - Aveiro, Portugal

ER -