Comby Fractal Microchannel Network For Fluid Flow In Porous Media

Porous media, which widely found in nature and everyday life such as Biological organs andcirculatory systems, the water and nutrient delivery systems of plants, fracture network in water/oilreservoirs, micro-pore structure of engineering materials, etc, have been received much attentions in avariety of sciences and engineering fields Specially. The study of flow behavior for fluid flow in porousmedia is a meaningful subject in understanding nature processes.It not only may have somesignificance in the study of fluid transport properties and biological research technology (such as veinnetworks and human neural network), but also may have the potential in prediction of advancedstructures and functional materials.Firstly, the background knowledge of porous media and fractal geometry are introduced briefly.Secondly, Tortuosity model for flow of Newtonian incompressible fluid in two-dimensionalporous media with regular hexagon particles is presented based on the the structural properties of leafveins and geometrical method, and the analytical expression for the average tortuosity is derived bygeometrically averaging the representative flow paths. There is no empirical constant and everyparameter has its clear physical meaning in this model. The results from this proposed models arefound to be in good agreement with the available numerical models and they may be helpful forunderstanding the physical mechanism for tortuosity of flow paths in porous media.Thirdly, A Biomimetic Comby Fractal Microchannel (BCFM) network model based on fractaltheory and available experiment results is developed to investigate the optimized parameters such asthe total number of independent loops, the total length of venation, tortuosity, porosity and theirrelationships by applying the microchannel porous medium model to the plant nerve tissue firstly. Theresults show that the present model present a good agreement compared with the existing experimentaland theoretical results. To some extent, our results may be more accurate than others. The presentparametric study reveals that the BCFM network model may has some special properties, such asstability, good mechanical, saving materials and so on.