A bimodal moment model for the simulation of particle growth

A bimodal moment method model for submicron fractal-like agglomerates undergoing Brownian coagulation

“…In a bimodal size distribution, the scavenging effect of Mode 1 on Mode 2 accounts for the main interaction mechanism between modes (Anand et al, 2012;Seipenbusch, Binder, & Kasper, 2008); thus, the differences in the geometric mean size, the magnitude and the geometric standard deviation between modes should be primarily considered. Similar works were performed in Jeong and Choi (2004) and Lee and Wu (2005). However, both of these previous works are limited to lognormal model studies with the model of .…”

“…Mode 1 Thus, the bimodal model must be able to capture not only the total quantities of the entire size distribution but also the quantities of each mode (Jung et al, 2002;Jeong & Choi, 2004;Lee & Wu, 2005). Therefore, the comparisons among these four studied B-TEMOM, B-QMOM3, B-QMOM4 and B-log MM models within each mode are taken into consideration in the present study.…”

“…In this section, the first three moments at each mode obtained from the B-TEMOM, B-log MM and B-QMOM3 as a function of the initial geometric standard deviation are compared. This comparison is performed because the geometric standard deviation was found to also affect the evolution of the bimodal size distribution (Jeong & Choi, 2004;Lee & Wu, 2005), in a manner similar to the number concentration and volume differences between modes. The investigated initial distributions correspond to D2, D8 and D9 presented in Table 1.…”

“…However, such processes cannot be represented by a normal unimodal size distribution model (Lee & Wu, 2005;Whitby & McMurry, 1997). Today, there are several bimodal or multimodal mathematical models available to describe the above aerosol processes within the moment method framework (Ackermann et al, 1998;Jeong & Choi, 2004Jung, Kim, & Lee, 2002;Lee & Wu, 2005;Whitby & McMurry, 1997).…”

Generalized TEMOM Scheme for Solving the Population Balance Equation

“…The initial geometric standard deviation was set to 1.200, 1.350, 1.600, and 1.800 (Figure 1), which covers the most common geometric standard deviations of natural aerosols. If the geometric standard deviation is higher, the aerosol size distribution can be considered a combination of several unimodal aerosols (Whitby and McMurry 1997;Jeong and Choi 2004). Thus, the model proposed in this work can still be applied to cases involving higher geometric standard deviations.…”