Modelling pressure drop evolution on high temperature filters

Abstract A high temperature high pressure filtration facility is available at the ETSI-University of Seville, which allows testing different elements and cleaning reverse-flow pulse strategies using real coal ash under diverse operating conditions. The facility is capable of processing 850 Nm 3 /h gas flow rate at maximum temperature and pressure of 550 °C and 7.5 barg respectively. An extensive testing campaigns have been carried out with the aim of evaluating alternatives for hot gas filtration technologies and optimising the performance of commercial filtering elements. In this framework, this paper focuses on a semi-empirical model developed for predicting the rise of the pressure drop with time. The model is based on theoretical considerations and the application of the experimental data generated using four filtering elements (PTFE and 3MFB700 bag filters, DSN1020 and CS1150 rigid filters). Nonlinear regression has been used to estimate and validate the coefficient of the model (specific dust cake coefficient) with arbitraries relations between independent and dependent parameters, by using iterative estimation algorithms. This is a valuable tool to select the best filtration options and optimum cleaning strategies in high temperature applications. Investigations about the factors affecting the specific dust cake resistance coefficient (filtration velocity, temperature, filter medium) are also presented.

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