The influence of crystalliser configuration on the accuracy and precision of gibbsite crystallisation kinetics estimates

Physical simulation of precipitation of radioactive element oxalates by using the harmless neodymium oxalate for studying the agglomeration phenomena

“…Thus, a sizeindependent kernel should be used to represent the agglomeration phenomenon. Even if it is not a theoretical kernel, it is frequently observed in other studies [11,12,14,[17][18][19]. The constant kernel can be considered as the resultant of the influence on the agglomerate formation of many mechanisms and random under the influence of external (for example, the hydrodynamic parameters) and internal factors the elementary particles can be reorganised inside the agglomerates leading to the formation of smaller agglomerates; the pores of bigger agglomerates can be filled by smaller or elementary solid particles without the observable change of the global agglomerate volume.…”

Influence of the Estimation Procedure on the Accuracy and Precision of Aluminum Trihydroxide Crystallization Kinetics from Dynamic Data

“…In this work, using the experimental uncertainties described below, 1000 computer-generated replicate CSD data sets, N , were obtained by loading the original CSD data, N̄ , with random normally distributed errors where z is a 1000 × m s × m array of normally distributed random numbers with zero mean and variance 1. More details on the application of Monte Carlo simulation to aluminum trihydroxide crystallization studies can be found in Li et al…”

“…Using Monte Carlo methods combined with dynamic crystallizer simulations, Li et al . investigated the influence of experimental design on the accuracy and precision of the aluminum trihydroxide crystallization kinetics estimates. They report that the crystallizer configuration (e.g., batch, semibatch, etc.)…”

“…The importance of crystallization experimental design to kinetic parameter estimation and parameter confidence limits is treated in detail by Rawlings et al 3 The effect of different crystallizer configurations on the accuracy and precision of the estimated aluminum trihydroxide kinetics was investigated by Li et al 11 Their experiments showed that, even at the same supersaturation and operating conditions, there were differences in the kinetics estimates. They attributed the differences to uncertainties in the parameter estimates, arising from interplay between the different functional forms of the output CSD data from the different configurations with the uncertainty in the measurement of CSD and uncertainties associated with the parameter estimation procedure.…”

A hybrid stochastic/fixed-sectional method for solving the population balance equation

“…The hybrid sectional Monte Carlo solution discussed in this work stands as a numerical method to solve for a PDF balance equation. It should not be confused with direct Monte Carlo solutions of non-inertial particles dynamics, which aim at performing a direct numerical simulation of the elementary physical phenomena acting on the particles (Falope et al, 2001;Li et al, 2001;Oullion et al, 2009;Pesmazoglou et al, 2016). The presented method also differs from constant number Monte Carlo methods (Smith & Matsoukas, 1998) or differentially weighted Monte Carlo approaches (Lee et al, 2015;Patterson et al, 2011;Zhao & Zheng, 2013).…”