CFD modeling of turbulent flow and particle deposition in human lungs
Kassinos, Stavros C.
ΕκδότηςAffiliation: UCY-CompSci Computational Sciences Laboratory, Department of Mechanical and Manufacturing Engineering, University of Cyprus, Nicosia, Cyprus
Correspondence Address: Radhakrishnan, H.
UCY-CompSci Computational Sciences Laboratory, Department of Mechanical and Manufacturing Engineering, University of Cyprus, Nicosia, Cyprus
SourceProceedings of the 31st Annual International Conference of the IEEE Engineering in Medicine and Biology Society: Engineering the Future of Biomedicine, EMBC 2009
Google Scholar check
MetadataΕμφάνιση πλήρους εγγραφής
Understanding transport and deposition of inhaled particles in the human airways plays a crucial role in the targeted therapy of pulmonary diseases, and the administration of inhaled medicines. Numerous researchers have studied the inhalation of particles using experiments or computer models. Even though experiments have shown that the airflow in the trachea and the upper branches of the lung is turbulent, the flow is taken to be laminar in most computer models. Only few recently published papers have looked at the turbulent transport of air in the human airways. Even fewer results have been published on the effect of the upper airway structures on the turbulent airflow in the lungs or on the effect of the turbulence on particle deposition. The previously published turbulent models have also mainly used RANS methods to predict the flow. To study the unsteady flow and particle deposition in a human lung, an LES model with a dynamic Smagorinsky subgrid scale model was used. The model equations were solved to study steady inspirational flow at different flow rates for different particle sizes. Results indicate that the upper airway geometry produces turbulence in the flow and the deposition of particles is mainly affected by the particle size and Stokes number. ©2009 IEEE.
Showing items related by title, author, creator and subject.
Louca, Loucas S.; Stein, J. L.; Hulbert, G. M. (2010)In recent years, algorithms have been developed to help automate the production of dynamic system models. Part of this effort has been the development of algorithms that use modeling metrics for generating minimum complexity ...
Ersal, T.; Fathy, H. K.; Rideout, D. G.; Louca, Loucas S.; Stein, J. L. (2008)A dynamic system model is proper for a particular application if it achieves the accuracy required by the application with minimal complexity. Because model complexity often-but not always-correlates inversely with simulation ...
Sendur, P.; Stein, J. L.; Peng, H.; Louca, Loucas S. (American Society of Mechanical Engineers (ASME), 2002)Dynamic models of physical systems with physically meaningful states and parameters have become increasingly important, for design, control and even procurement decisions. The successful use of models in these contexts ...