Numerical simulation and experimental validation of biofilm formation

In this Reserch , a state-of-the-art 3D computational model has been developed to investigate biofilms in a multi-physics framework using smoothed particle hydrodynamics (SPH) based on a continuum approach. Biofilms are in fact aggregation of microorganisms such as bacteria. Biofilm formation is a complex process in the sense that several physical phenomena are coupled and consequently different time-scales are involved. On one hand, biofilm growth is driven by biological reaction and nutrient diffusion and on the other hand, it is influenced by the fluid flow causing biofilm deformation and interface erosion in the context of fluid and deformable solid interaction (FSI). The geometrical and numerical complexity arising from these phenomena poses serious complications and challenges in grid-based techniques such as finite element (FE). Such issues are generally referred to as mesh distortion. Here the solution is based on SPH as one of the powerful meshless methods. SPH based computational modeling is quite new in the biological community and the method is uniquely robust in capturing the interface-related processes of biofilm formation especially erosion. The fact is that SPH is a versatile tool owing to its adaptive Lagrangian nature in the problems whose geometry is temporarily varying (dynamic). Moreover, its mesh-less feature is considered to be favorable in interpreting the method as a particle based one. Hence, it is quite straight forward to incorporate complex interactions and ad-hoc rules at the particle level into the method. This is the case for the problems with coupled governing equations with different time and length scale. In this thesis all different physics which account for biofilm formation have been implemented in the framework of SPH and one can say that this tool is purely SPH based. Besides the numerical simulation, experiments were conducted by our partners in the medical school of Hannover. The obtained numerical results show a good agreement with experimental and published data which demonstrates that the model is capable of predicting overall spatial and temporal evolution of the biofilms. The developed tool can be employed in either controlling the detrimental biofilms or harnessing the beneficial ones.