Advances in correlating filter cake properties with particle collective characteristics

The purpose this work is to build a data handling strategy in order to achieve a better knowledge of a given particulate system and of removing, to some extent, the existing cloudiness regarding the correlation between the filter cake properties and the characteristics of the particles that have been put together for forming it. Common sense suggests that a connection should exist between cake properties and particle characteristics; however, due to its complex character, it has been the prevailing opinion that the only way to know cake properties is to measure them, which is a severe drawback for process engineers, who are compelled to make forecasts about what happens if changes occur within the process. In this sense, the results of this work provide a skeleton in which perceptive engineers can suit the proper information for converting a given amount of results into experience. Once this connection is established, predictions of the filter performance are theoretically possible, using kinetic models that have been extensively studied by other authors. Three cake attributes were found to be necessary for the determination of cake building kinetics and gas-pressure-driven cake deliquoring kinetics: porosity, permeability and capillary pressure. These attributes were comprehensively investigated to elucidate the effect of variations in particle size distribution on them. In this work it has been demonstrated that the cake properties (namely porosity, permeability, irreducible saturation, void size distribution index and mean capillary pressure), can be successfully correlated with particle collective characteristics (mean size, particle size distribution width and particle shape). This relationship is strongly dependent on cake-building mode and is, of course, substancespecific. Accordingly, a data handling strategy is suggested for collecting and analyzing information from a given substance enabling a confident estimation on how other particle assemblies of the same substance behave at certain operating conditions. No magic solution is proposed, the only way to perform a proper handling of a solid-liquid separation system is “knowing the material”, that is, converting a given amount of results into experience. The results of this work claim to offer process engineers an intelligent way to understand the behavior of the substance they are dealing with: “perform some selected measurements, fit them in a proper way and make reasonable predictions about the behavior of the substance, no matter its particle size distribution”. It will be always necessary to make experiments and to fit some parameters, which is, by far, better than the previous state of the art: “measure the desired property in order to know it”.