A transient model for nozzle clogging

This model has been developed for transient simulation of clogging (also called as fouling) in submerged entry nozzle (SEN) during continuous casting. Three major steps of the clogging have been taken into account: (a) transport of non-metallic inclusions (NMIs) by turbulent melt flow towards the SEN wall; (b) interactions between melt and wall, and the adhesion of the NMI on the wall; (c) formation and growth of the clog by NMI deposition. The computational domain is divided into bulk and near-wall regions. An Eulerian-Lagrangian approach is employed to calculate the transport of NMIs by the turbulent flow; a stochastic near-wall model is adopted to trace particles in the turbulent boundary layer (near-wall region). The early stage of clogging is modeled by the dynamical change in wall roughness, while the late stage of the clogging is modeled by building a layer of porous clog region from the wall. This layer is called as ‘clog’, and it continues to grow by attaching more NMI particles. To evaluate the model, a laboratory experiment, which was designed to study the clogging of SEN during steel continuous casting, is simulated. It is verified that the model can reproduce the experiment: the calculated clogged section of the nozzle is qualitatively comparable with as-clogged sections in laboratory experiments; the calculated mass flow rate through the nozzle agrees with the experimentally-monitored result as well. New knowledge is obtained. (1) Clogging is a transient process interacting with the melt flow, and it includes the initial coverage of the nozzle wall with deposited particles, the evolution of a bulged clog front, and then the development of a branched structure. (2) Clogging is a stochastic and self-accelerating process. Finally, model capabilities/limitations, uncertainties for choosing the modeling parameters such as mesh size, Lagrangian time scale, the correction factor in the interpolation of clog permeability are studied and discussed. [Display omitted] •The transient model has been validated against a laboratory experiment data.•Uncertainties for modeling parameters have been studied.•The model can reproduce the experiment satisfactorily.•The modeling results provide new knowledge about clogging as a transient process.•Clogging is a stochastic and self-accelerating process.