Łukasz Makowski

Shear Flow of Aggregated Nanosuspensions–Fundamentals and Model Formulation

Theoretical aspects of shear flows of aggregated nanosuspensions are presented and applied to formulate appropriate models. Technological context of this work is related to formulation of stable suspensions of nanoparticles of specific rheological properties by breaking‐up nanoparticle clusters in high shear devices. Accordingly the population balance modeling is applied with kinetics including effects of aggregation, breakage and restructuring of aggregates; effects of suspension rheology on the flow are included as well. Rheological model includes the effect of clustering of primary nanoparticles. Population balances are solved using QMOM that is linked to the CFD code. Results of numerical simulations are presented for laminar and turbulent flows. Part of the 1st International Conference on Industrial Processes for Nano and Micro Products, London, 2007.

Break‐Up of Nanoparticle Clusters—Process Modeling

A general model for suspension formulation that includes effects of particle breakage and clustering on suspension structure and resulting rheology is applied here to simulate agglomerate dispersion. The model employs the QMOM population balance to simulate variation of agglomerate size and structure in a system of complex geometry. As an example of such system a rotor–stator mixer is applied. Simulations are performed with the CFD code Fluent supplemented with UDFs for process kinetics, aggregate structure, and suspension rheology. A method of application of the population balance equation to describe evolution of fractal aggregates is presented and effects of application of either uniform or erosion daughter distribution are compared.

Large Eddy Simulations on Selected Problems in Chemical Engineering

The paper focuses on an application of large eddy simulations to predict a course of complex processes in the non-premixed, turbulent reactive flows of incompressible fluids. The simulations and experiments were carried out in two impinging jet reactors. The subgrid model for concentration variance, supplied with a new dynamic coefficient for the scale-similarity model, which takes into account the spatial variation of the turbulence Reynolds number and depends on the Schmidt number, as well as a numerical cell size, was presented. Obtained numerical results were compared with the experimental data using particle image velocimetry and planar laser induced fluorescence methods for fluids characterized by different Schmidt numbers. The LES method was subsequently used to predict the course of parallel chemical reactions and a precipitation process. In both cases a very good agreement with the experimental results was obtained. Finally, the results of the new model for subgrid-scale diffusivity coefficient are presented.