It is well known that both the separation efficiency and the corresponding pressure loss of a depth filter increase with the increasing dust load on the filter – apart from possible re-release of deposited dust particles, e.g., due to strongly varying gas volume flows. The corresponding time behavior of depth filters is referred to as filtration kinetics. Looking at the positive side of filtration kinetics, the filtration kinetics of a depth filter offer the possibility of subsequently adjusting the separation behavior of a given depth filter by means of targeted preloading of the filter. “Targeted preloading” here refers to the controlled loading of a depth filter with a defined quantity of defined particle fractions before the filter is actually used in order to achieve improved, individual separation behavior of the respective depth filter without structural/design changes.

This paper presents a model-based theoretical study using a recently developed multi-layer model with offset for cake growth, which enables the description of particle separation during the entire filtration process with a holistic, coherent model concept – i.e., without model switching between depth and surface filtration. The results from model calculations based on examples are intended to show whether targeted preloading can theoretically be a useful filter solution in specific application scenarios. To this end, not only the separation behavior and flow resistance at the beginning of the filtration process are presented, but also their time behavior during ongoing filter operation in order to achieve a holistic evaluation...