Smart simulation solution

Louise Smyth

Ulrich Heck reveals the merits of using computational fluid dynamics for filter applications

Using computational fluid dynamics (CFD) to optimise flow configurations is becoming increasingly popular in many industries. Fluid flow in process engineering poses specific challenges, in particular with regard to the precise definition and modelling of these problems. Here, the engineer often has to handle complex mixtures of different phases, for example bubbles in liquids in reactors, free surfaces between liquids and gases in mixers or complex particle flows in fluidised beds.

Over the past few years, excellent progress has been reached for accurate modelling of various multiphase applications by using cost-effective open source solver technology, such as the CFD toolbox OpenFOAM. In combination with increasing performance of multi-core computer systems or cloud hardware services for CFD, these techniques have become far more essential and affordable for SMEs for the development and optimisation of process engineering.

One application of multiphase flows in process engineering is the separation of particles at filters. DHCAE Tools has developed a specialised simulation tool to optimise the incoming flow into filters, based on OpenFOAM.

How the solution works

In the first step, the continuous flow is estimated, for example, the carrying gas in a filter plant considering the base resistance to the clean filter. The filter elements are modelled as transmissive faces for the carrying gas, causing a local pressure loss, depending on the local flow velocity.

Millions of virtual particle parcels are inserted and the flow paths of the particles are estimated using a so-called Lagrangian approach. The forces acting on the particles (drag, gravity or other force fields) are balanced and result in the particle motion. Particles may settle due to gravity or if they can stick at walls.

Those particles reaching the filter are trapped: they stick at the filter faces and increase the resistance for the carrying fluid locally. The resistance increase depends on the local amount of particles that are settled at the particular position of the filter.

The continuous flow field is then updated. The carrier fluid will search for a new path through the filter region, providing the lowest resistance. This will again change the subsequent particle separation on the filter face. In total, the complete process of filter loading can be modelled, including the shifting of transporting fluid phase followed by changes of the retention regions of subsequent particles.

The engineer gets a detail view inside the filter loading process in complex arrangements and can optimise the inflow or the filter itself to realise three key results: longer lifecycles of the filter; reduced pressure losses, resulting in lower operation costs; or more effective utilisation of filter material.

These models have been verified by DHCAE Tools for typical cases of particle separation at filters in literature and by measuring the shift of carrying gas depending on the loading in real filter plants. Due to the generalised model approach, they can be used for different kinds of filter applications, for instance for filters where the fluid is liquid or gaseous.

Dr Ulrich Heck is MD of DHCAE Tools

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