Project Details
Projekt
Hybrid modelling of heteroagglomeration in gas-borne flows using CFD-DEM simulation and machine learning methods
Applicant
Professor Dr.-Ing. Carsten Schilde
Subject Area
Mechanical Process Engineering
Term
since 2021
Project identifier
Deutsche Forschungsgemeinschaft (DFG) - Project number 462426077
The mechanistic understanding of particle processes is the basis for the creation of tailor-made particulate products with additional integrated functions. One way of combining existing particle properties or creating new functions through their combination is heteroagglomeration via gas phase processes. Submicron particle systems in particular have a particularly high potential for heteroagglomeration processes, but can only be characterised with great metrological effort due to the complex interplay between process parameters, disperse particle properties and particle interactions. The use of coupled flow (CFD) and particle simulations (DEM) offers the possibility to systematically investigate the heteroagglomeration processes of submicron particles as a function of process parameters, disperse particle properties and the different particle interactions. With the increase in computing power, much larger data sets can be generated from CFD-DEM simulations, allowing the derivation of mechanistic relationships and thus targeted and transferable process and product development. The use of realistic particle contact models and their sufficiently accurate parameterisation is crucial for the correct simulative representation of the heteroagglomerate structures obtained in the experiment. To calibrate and validate the CFD-DEM, defined spherical primary particles of different submicron sizes will be generated in a measurement setup and agglomerated in the subsequent agglomeration zone. Suitable measurement methods (FIB-SEM, AFM) have already been established and applied for the 3D reconstruction of the resulting structures and the measurement of particle interaction forces. The CFD-DEM data sets are generated by a semi-mechanistic modelling of physically inspired genetic programming, which is able to evaluate, further develop and combine existing mechanistic models. A major focus of the second funding period is the systematic investigation and modelling of the formation of photocatalytically active SiO2-TiO2 heteroagglomerates by experiment and CFD-DEM simulation, as well as the characterisation and simulation of the photocatalytic activity as a function of the heteroagglomerate structure.
DFG Programme
Priority Programmes
