摘要
Previous work （Hussain et al. （2013）. Chemical Engineering Science, 101, 35） has pointed out that the conventional, one-dimensional population balance equation for aggregation can be expanded to accurately reproduce the results of discrete simulations of spray fluidized bed agglomeration. However, some parameters had to be imported from the discrete simulation （Monte-Carlo）. The present paper shows how the expanded population balance can be run without importing parameters from the Monte-Carlo simulation. The expanded population balance still reproduces the results of Monte-Carlo simulations accurately, taking into account key micro-scale phenomena （sessile droplet drying, efficiency of collisions）, but with much lower computational cost. Required input parameters are just the drying time of sessile droplets （calculated in advance）, and the prefactor of an equation that correlates particle collision frequency with fluidized bed expansion. In this way, the expanded population balance is, apart from autonomous, also （nearly） predictive. Its performance is demonstrated by comparisons with both Monte-Carlo results and experimental data for various operating conditions （binder mass flow rate, gas temperature）. Despite formally being a one-dimensional expression, the expanded population balance captures additional properties, such as the number of wet particles and the number of droplets in the system, which are even difficult to measure in exoeriments.
Previous work （Hussain et al. （2013）. Chemical Engineering Science, 101, 35） has pointed out that the conventional, one-dimensional population balance equation for aggregation can be expanded to accurately reproduce the results of discrete simulations of spray fluidized bed agglomeration. However, some parameters had to be imported from the discrete simulation （Monte-Carlo）. The present paper shows how the expanded population balance can be run without importing parameters from the Monte-Carlo simulation. The expanded population balance still reproduces the results of Monte-Carlo simulations accurately, taking into account key micro-scale phenomena （sessile droplet drying, efficiency of collisions）, but with much lower computational cost. Required input parameters are just the drying time of sessile droplets （calculated in advance）, and the prefactor of an equation that correlates particle collision frequency with fluidized bed expansion. In this way, the expanded population balance is, apart from autonomous, also （nearly） predictive. Its performance is demonstrated by comparisons with both Monte-Carlo results and experimental data for various operating conditions （binder mass flow rate, gas temperature）. Despite formally being a one-dimensional expression, the expanded population balance captures additional properties, such as the number of wet particles and the number of droplets in the system, which are even difficult to measure in exoeriments.
基金
financial support provided by the German Science Foundation(DFG) within the framework of graduate school GRK-1554
by the Alexander von Humboldt Foundation(research fellowship for Jitendra Kumar)
