Simulating multimodal floc size distributions of suspended cohesive sediments with lognormal subordinates: Comparison with mixing jar and settling column experiments

Abstract

The Floc Size Distributions (FSDs) of suspended fine-grained sediment flocs play a prime role to estimate their own fate and the transport of contaminates attached to the flocs. However, developing an efficient flocculation model that is capable of simulating continuous and multimodal FSDs is still a challenge. Recently, the population balance equation solved by the Quadrature-Based Method of Moments (QBMM) with lognormal kernel density functions has been developed to investigate the aggregation and breakage processes. It coincides with some recent observations which describe a measured FSD in coastal waters with a set of constituted lognormal distributions.The newly developed lognormal QBMM was tested with several ideal flocculation kinetic kernels, none of which, however, was used for interpreting cohesive sediment dynamics. Therefore, it raised our interest to evaluate the model performance for fine-grained sediments in shear turbulence dominated environments. In this study, additional validations against two kaolinite laboratory experiments were tested in the framework of the extended QBMM. It is hypothesized that these subordinate lognormal distributions share the same value of standard deviation. Different from the previous methods, the common standard deviation is determined empirically to reduce the number of tracers and better represent the FSDs. With sediment flocculation kinetics, the predicted FSDs reasonably reproduce the FSDs observed in both the mixing chamber and the settling column experiments. Despite the lacking of explicit descriptions of microbial effects at the current stage, this model has the potential to be implemented into large-scale particle transport models and deserves a more in-depth study in the future.

An Extended Entropic Model for Cohesive Sediment Flocculation in a Piecewise Varied Shear Environment

“…In other research areas, such as sanitary engineering, water treatment works, and colloidal science, particle flocculation is an essential element in some dynamic processes, and related studies regarding its mechanism are always a research focus [18][19][20][21][22][23][24][25][26][27][28][29]. Especially, the temporal evolution of the floc size distribution of cohesive particles in a turbulent fluid has been investigated by many researchers via theoretical formulation [2,9,[30][31][32], numerical simulation [33][34][35][36][37][38][39], and experimental observation [6,23,26,40] in many disciplines. At present, there are three kinds of deterministic flocculation models in the literature, as summarized by Shen et al (2015) [37].…”

“…The first kind is the Lagrangian flocculation model originally proposed by Winterwerp (1998) [9] and its modified versions [2,28,31,32]. The second kind of flocculation model is the population balance model (PBM) [10,34,[36][37][38]41], which is based on a classic equation originally by Smoluchowski (1918) [34,[42][43][44]. The third kind of flocculation model is based on the lattice Boltzmann method [37,39,45].…”

An Analytical Study on Wave-Current-Mud Interaction

“…Wave-mud interactions have been widely studied in several aspects including wave height attenuation ( [11][12][13]), mud mass transport as the bed load ( [8,9,[14][15][16]] among many others), stratified two-phase flows ( [12,17]), and, suspended load (e.g., the most recent ones are [18,19]). Many analytical and experimental studies have been carried to reveal the unknown aspects of the wave-mud interactions (e.g., wave attenuation and mud mass transport).…”