Pore network modelling using image processing techniques

Purpose The knowledge of structural parameters of nonwovens media is poorly understood. The pores size distribution (PSD) function is one of those parameters. The difficulty is not only the understanding of the distribution of pores but also the identification of pores geometry distribution (PGD) and their behaviour concerning the dynamic fluid transportation. The purpose of this paper is to present an efficient and reliable method based on image analysis which on one hand, performs the estimation of the PSD function and takes into account the geometric aspect of pores, and on the other hand, analyses liquid wicking in very thin filter media. Design/methodology/approach The proposed methods, in this paper, are applied on thin filter media made of polyester. The samples have not sudden any treatment. The authors set up an optical test bed in order to observe the dynamic properties of the samples. Dynamic raw data about the liquid wicking are extracted directly from video sequences using the appropriate test bed. The structural parameters are extracted from the non-wetted samples. Findings Obtained results allow a better understanding of the liquid wicking in very thin filter media. In addition to the PSD function, the PGD function adds informations about the shape of pores. The dynamic data of the liquid wicking explains that pores have different behaviour when liquid reached them. It can be deduced from this study that the fluid transport in the pore network is defined by three main parameters: geometric parameter (size, shape), capillary action and pores connection in the network. Research limitations/implications The led back-lighting system is not sufficient to observe precisely the liquid wicking. An additional front-lighting will be added in further studies. Originality/value The extraction of dynamic properties from video sequences, by performing image analysis is an original method to characterise the porosity in thin media filter.