Published

2015-01-01

Estimation of the particle size distribution of colloids from multiangle dynamic light scattering measurements with particle swarm optimization

Estimación de distribución de tamaños de partículas de coloides a partir de mediciones de luz dinámica a múltiples ángulos con optimización por enjambre de partículas

Keywords:

Swarm Intelligence, Dynamic Light Scattering, Inverse Problem, Particle Swarm Optimization, Particle Size Distribution. (en)
Inteligencia de enjambres, dispersión de luz dinámica, problemas inversos, optimización por enjambre de partículas, distribución de tamaño de partículas (es)

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Authors

  • Leonardo Antonio Bermeo Varón Federal University de Rio de Janeiro.
  • Eduardo Caicedo Universidad del Valle, Percepción y Sistemas Inteligentes PSI.
  • Luis Clementi INTEC. Univ. Nac. del Litoral – CONICET. Facultad Regional Santa Fe. Univ. Tecnológica Nac.
  • Jorge Vega INTEC. Univ. Nac. del Litoral – CONICET. Facultad Regional Santa Fe. Univ. Tecnológica Nac.

In this paper particle Swarm Optimization (PSO) algorithms are applied to estimate the particle size distribution (PSD) of a colloidal system from the average PSD diameters, which are measured by multi-angle dynamic light scattering. The system is considered a nonlinear inverse problem, and for this reason the estimation procedure requires a Tikhonov regularization method. The inverse problem is solved through several PSO strategies. The evaluated PSOs are tested through three simulated examples corresponding to polysty-rene (PS) latexes with different PSDs, and two experimental examples obtained by simply mixing 2 PS standards. In general, the evalu-ation results of the PSOs are excellent; and particularly, the PSO with the Trelea’s parameter set shows a better performance than other implemented PSOs.

En este artículo se presenta una aplicación del algoritmo de optimización por Enjambre de Partículas (PSO) para estimar la distribución de tamaños de partículas (DTP) de un sistema coloidal a partir de los diámetros medios obtenidos por dispersión de luz dinámica a múltiples ángulos. Dado que se trata de un problema inverso no lineal en el proceso de estimación el problema es regularizado por medio del método de regularización de Tikhonov y finalmente se soluciona con diferentes estrategias del algoritmo de PSO. La evaluación del algoritmo de PSO es realizada a través de tres ejemplos simulados correspondientes a látex de poliestireno con diferentes DTP y dos ejemplos experimentales obtenidos a partir de una simple mezcla de dos estándares de poliestirenos. En general todos los resultados de estimación del algoritmo de PSO son excelentes, en particular, el algoritmo con definición de parámetros de Trelea que presenta mejor desempeño que las otras implementaciones de PSO.

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Copyright (c) 2015 Leonardo Antonio Bermeo Varón, Eduardo Caicedo, Luis Clementi, Jorge Vega

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