John Nijenhuis

CFD modelling and experimental validation of pressure drop and flow profile in a novel structured catalytic reactor packing

Abstract Packed beds of catalyst particles are normally described using models that contain a number of empirical parameters. The development of computer technology and CFD models makes it tempting to try to (1) fully simulate the flow in packed beds to obtain a more detailed understanding of the physical phenomena that take place in the bed, and (2) to use the CFD solutions to derive ‘simple’ correlations suitable for design purposes. In this paper it is shown that a commercial CFD code (CFX-5.3) can be used to predict, with an average error of about 10%, the pressure drop characteristics of packed beds of spheres that have a tube-to-particle-diameter ratio of 1.00 to 2.00. Packed beds with these unusually low tube-to-particle-diameter ratios can be used as unit cells in a novel type of structured catalytic reactor packing, proposed in this paper, that has very favorable pressure drop characteristics. The error of 10% in the pressure drop prediction by CFD is acceptable for design purposes. The CFD model is also able to predict local velocity profiles that were measured with LDA. The CFD results have been used to fit a simple two-parameter model that describes the experimental pressure drop data with an average error of about 20%. For a grid-independent CFD solution of laminar flow in a packed bed containing only 16 particles, already three million cells are required. However, it is anticipated that within five years from now the simulation of a packed bed containing a few hundred particles will be considered a ‘standard’ problem in terms of memory and calculation time requirements.

Fischer–Tropsch reaction–diffusion in a cobalt catalyst particle: aspects of activity and selectivity for a variable chain growth probability

The reaction–diffusion performance for the Fischer–Tropsch reaction in a single cobalt catalyst particle is analysed, comprising the Langmuir–Hinshelwood rate expression proposed by Yates and Satterfield and a variable chain growth parameter α, dependent on temperature and syngas composition (H2/CO ratio). The goal is to explore regions of favourable operating conditions for maximized C5+ productivity from the perspective of intra-particle diffusion limitations, which strongly affect the selectivity and activity. The results demonstrate the deteriorating effect of an increasing H2/CO ratio profile towards the centre of the catalyst particle on the local chain growth probability, arising from intrinsically unbalanced diffusivities and consumption ratios of H2 and CO. The C5+ space time yield, a combination of catalyst activity and selectivity, can be increased with a factor 3 (small catalyst particle, dcat = 50 μm) to 10 (large catalyst particle, dcat = 2.0 mm) by lowering the bulk H2/CO ratio from 2 to 1, and increasing temperature from 500 K to 530 K. For further maximization of the C5+ space time yield under these conditions (H2/CO = 1, T = 530 K) it seems more effective to focus catalyst development on improving the activity rather than selectivity. Furthermore, directions for optimal reactor operation conditions are indicated.

Early Agglomeration Recognition System (EARS)

In fluidised-bed combustion and gasification of biomass and waste, agglomeration of bed/ash particles is a major problem area. This paper deals with a new method for monitoring and controlling fluidised-bed hydrodynamics, which enables the recognition of agglomeration in an early stage and provides control measures to prevent further agglomeration and defluidisation. The method, named Early Agglomeration Recognition System (EARS), is based on recognising significant differences between reference time-series of pressure fluctuations and successive time-series measured during prolonged plant operation. The early recognition provides a time interval for taking dedicated actions to counteract the agglomeration. EARS thus can be a tool helping plant operators in preventing agglomeration induced plant shutdowns and minimising bed material make-up and residue production. Results are presented of small-scale experiments showing the effectiveness and selectivity of the early agglomeration recognition. Subsequently, the development of control strategies is discussed.Copyright