Assessment of the modeling error of an approximate Light Scattering model by processing accurate simulated data

This paper presents the analysis of the modeling error of an approximate model in a Static Light Scattering (SLS) problem for the morphological characterization of particle systems through the estimation of the Particle Size Distribution (PSD). The modelling error of the employed approximate model called the Local Monodisperse Approximation (LMA) is obtained by means of processing simulated data generated by a theoretically accurate model called the Vrij's Finite Mixture Model (VFMM). As a simplification on the procedure, PSDs are supposed to be well-represented by a log-normal distribution. The data generated by the VFMM is processed by solving an inverse parametric problem using a Least-Squares approach. Bias on estimations is studied in function of all significant system parameters.