Article in Journal ART-2017-03

BibliographyInci, Gizem; Kronenburg, Andreas; Weeber, Rudolf; Pflüger, Dirk: Langevin Dynamics Simulation of Transport and Aggregation of Soot Nano-particles in Turbulent Flows.
In: Flow, Turbulence and Combustion.
University of Stuttgart, Faculty of Computer Science, Electrical Engineering, and Information Technology.
pp. 1-21, english.
Springer, January 2017.
ISSN: 1573-1987; DOI: 10.1007/s10494-016-9797-3.
Article in Journal.
CR-SchemaJ.2 (Physical Sciences and Engineering)
KeywordsAggregation; Dissipation rate; Langevin dynamics; Soot particles; Turbulence
Abstract

The present paper uses Langevin dynamics (LD) to investigate the aggregation of soot nano-particles in turbulent flows. Interparticle forces are included, and the computation of the individual particles by LD is retained even after aggregate formation such that collision events and locations can be based on center-to-center particle distances without invoking any modelling assumptions of aggregate shape and/or collision frequency. We focus on the interactions between the specific hydrodynamic conditions and the particle properties and their effect on the resulting agglomerates' morphologies. The morphology is characterized by the fractal dimension, Df. Computations of particle aggregation in homogeneous isotropic turbulence and in shear flows dominated by counter-rotating vortices with a wide range of turbulence intensities and particle sizes indicate that the evolution of the agglomerates' shapes can be adequately parameterized by the size of the agglomerates and the Knudsen and Péclet numbers, the latter being based on the smallest turbulence scales. The computations further suggest that the shapes of agglomerates of certain sizes are relatively independent of time and relatively insensitive to larger turbulence structures. The fractal dimensions are modelled as functions of radius of gyration, Kn and Pe. The fitted expressions show good agreement with the LD simulations and represent the entire growth process of the agglomerates. A direct comparison of selected aggregates with experimental data shows very good qualitative agreement. A thorough quantitative validation of the evolution of the computed aggregate characteristics is, however, presently hindered by the challenges for and therefore lack of suitable experiments under appropriately controlled conditions.

Department(s)University of Stuttgart, Institute of Parallel and Distributed Systems, Simulation of Large Systems
Entry dateMarch 17, 2017
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