Investigation of the hydrodynamic behavior of diatom aggregates using particle image velocimetry

Abstract

The hydrodynamic behavior of diatom aggregates has a significant influence on the interactions and flocculation kinetics of algae. However, characterization of the hydrodynamics of diatoms and diatom aggregates in water is rather difficult. In this laboratory study, an advanced visualization technique in particle image velocimetry (PIV) was employed to investigate the hydrodynamic properties of settling diatom aggregates. The experiments were conducted in a settling column filled with a suspension of fluorescent polymeric beads as seed tracers. A laser light sheet was generated by the PIV setup to illuminate a thin vertical planar region in the settling column, while the motions of particles were recorded by a high speed charge-coupled device (CCD) camera. This technique was able to capture the trajectories of the tracers when a diatom aggregate settled through the tracer suspension. The PIV results indicated directly the curvilinear feature of the streamlines around diatom aggregates. The rectilinear collision model largely overestimated the collision areas of the settling particles. Algae aggregates appeared to be highly porous and fractal, which allowed streamlines to penetrate into the aggregate interior. The diatom aggregates have a fluid collection efficiency of 10%-40%. The permeable feature of aggregates can significantly enhance the collisions and flocculation between the aggregates and other small particles including algal cells in water.

Copepod Grazing Influences Diatom Aggregation and Particle Dynamics

“…Another test was through the parameters obtained from the fit of the ESD and sinking velocities data for C. neogracile and S. marinoi aggregates. Power law regressions between aggregates ESD and sinking velocity are characterized by A and B constant parameters that are comparable to those described in literature for in situ marine snow (Shanks, 2002;Iversen et al, 2010), with B values ranging from 0.4 to 1.3, corresponding to fractal dimensions between 1.4 and 2.3 (calculated using equation 6 from Xiao et al, 2012). In every situation where copepods fragmented the large aggregates or re-aggregated the small aggregates, the regression linking aggregate ESD and sinking velocities remained the same with unchanged A and B and so the fractal dimension D that may be derived from B (Long et al, 2015).…”

Interactions between microplastics and phytoplankton aggregates: Impact on their respective fates

“…As discussed earlier, aggregates are not perfectly spherical, they are fractal (De la Rocha et al, 2007;Kilps et al, 1994;Logan et al, 1990) and porous particles Ploug et al, 2002;Stolzenbach et al, 1993). Porosity and permeability impact sinking rate (Xiao et al, 2012, Li andYuan, 2002) and increase with size due to fractal dimension. Larger aggregates have more macropores in which water can flow through easier increasing thus settling velocity of aggregates by decreasing drag forces (Li and Yuan, 2002).…”

“…But considering that R. salina aggregates are both more permeable and more fragile than C. neogracile aggregates, two possible hypotheses may explain such high microbeads incorporation by R. salina. First, increase of aggregate permeability enhance encountering between small particles and aggregates as the small particles are not moved away from the aggregate by Brownian motions but can go through aggregates macropores and be captured (Xiao et al, 2012;Kiørboe, 2008). Second, fragility and thus plasticity of the R. salina aggregates may provoke constant breakage and rearrangement.…”

3D electro-thermal modelling and experimental validation of lithium polymer-based batteries for automotive applications

“…Particle image velocimetry is a whole‐flow‐field technique used to obtain instantaneous velocity measurements and related properties of fluids in a cross section of a flow . The flow is seeded with small tracer particles and illuminated with a sheet of laser light so that particles are visible .…”