Simulating danger for effective containment

Edward Throp throws light on how new simulation technologies can improve the containment effectiveness in clean rooms

The increasing concentration and toxicity of active ingredients in pharmaceutical production are leading to lower and lower occupational exposure limits (OELs). This presents a challenge to the manufacturers of containment technology. It is critical, therefore, that equipment such as downflow booths provide appropriate flow conditions to carry particulates and vapours away from operators.

Traditionally it has not been possible to investigate the effect of design changes or the placement of obstacles and new equipment in a room without physical testing, which is both costly and time consuming. Computational fluid dynamics (CFD) is a relatively new simulation technology that offers a cost-effective alternative to this.

CFD is often perceived as a highly technical analysis tool requiring large computer resources to be effective. However, with the ever-increasing performance of the personal computer coupled with modern, easy-to-use interfaces, more and more industries, including pharmaceuticals, are benefiting from the power of CFD modelling.

CFD is essentially a computer-based method to solve the fundamental equations governing fluid dynamics - these relating to conservation of mass, momentum and energy. By solving these equations on a 3D grid representing a physical domain the prediction of the fluid behaviour is possible. This allows designers and users to predict and visualise the performance of equipment from a single isolator to a complete cleanroom.

CFD allows the operator to model both the airflow and the fate of particulates in the room and also to obtain information relating to the number of air changes/minute, mean residence time and potential stagnant regions. CFD has been used to investigate, in detail, the flows in individual containment units such as isolators and laminar flow booths, highlighting causes of poor performance. It is then possible to change the design of the unit, e.g. the extract locations, on the computer, re-run the model and improve the design before committing to experimental testing and manufacture.

The same features are of concern when modelling the complete cleanroom environment, where the appropriate positioning of vents relative to extracts and equipment is critical for obtaining the desired performance. It is also possible to include thermal effects in the model; these could be of interest both for operator comfort and to ensure that no buoyancy driven flow structures interfere with the room's operation.

quickly scrutinised

A further strength of applying a CFD analysis to a problem is the ability to display the results in ways that deliver complex information in a highly visual and easy-to-understand format. This allows the fluid dynamics at work to be scrutinised quickly and efficiently, and visualisation of the results makes it far easier to quantify and highlight the impact of small design changes made exploratively to the model of, for instance, the cleanroom ventilation scheme.

easily tested

One example of the use of CFD to ensure an effective ventilation system in a cleanroom involved investigating the effect of moving and adding equipment such as isolators and LFUs in a space in an existing facility. The interaction between LFUs, isolators and the room airflow can have a significant impact both on the unit and the room performance.

The importance of equipment location is one element that can be critical to realising an effective system. Various positional arrangements can easily be tested to identify which yield maximum performance.

For example, figure 2 is a visualisation of the results from the analysis showing path lines from a ceiling vent in the cleanroom.

successful ventilation

The relative velocity of the airflow is given, colour coded to indicate a range of speeds measured in metres per second. The outer boundaries of the area being successfully ventilated can easily be seen, as well as the efficiency of the overall ventilation.

This is just one method of displaying graphically the results of a simulation and highlights the three dimensional nature of the flow structures.

It is possible to go much further and create such visualisations of final data for a number of chosen variables to ensure all the dynamics at work are fully understood. Figure 1 shows the age of the air on a slice through the domain. Here, red is used to indicate that air in the region of the centre of the far wall has been present for longer than the surrounding air.

It seems clear from the results that despite the presence of two ventilation units at ceiling level to the right of the far wall as we see it, the position of the tall object left of centre, allied with the bench directly adjacent, has resulted in a recirculation zone in which stale air is becoming trapped rather than being effectively removed.

This is shown more clearly by figure 3 giving the velocity vector plot, where the vectors have been coloured by time.

This example demonstrates the ability CFD analysis gives the user to interrogate final data in a variety of formats. CFD allows the user to identify anomalies suggested by other data collected, but for which there is no obvious answer.

A CFD analysis can be conducted both retrospectively to optimise or troubleshoot an existing cleanroom ventilation scheme, or pre-emptively on a potential new design for a facility yet to be built. The result either way can greatly reduce timescales with a corresponding reduction in costs.