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TestimonialBehind the scenes

Today is the day that I finished my first month at AM-TEAM as their business development manager. After various positions and functions, including a number of years abroad, I ended up in Ghent again, amongst my peers – engineers. In the past I’ve had brief contacts with modelling, but as it was stored somewhere far away in my memory I had to refresh this knowledge, and learn a lot of new things about its possible applications. I should say ‘current’ applications as well, as I discovered a lot has changed since I graduated ten years ago.

A good time to reflect on and share with you what I’ve learned so far about CFD and advanced modelling.

(For a complete overview on the application of CFD I would like to refer you to our website:

1.CFD can simulate complex processes

Where as I knew CFD could be used for water, air,… simulations I wasn’t aware that we can model multiphase situations like for example a bioreactor with water, sludge, sand, air,… We can even add biokinetics to the simulation. This increases its applicability tremendously.
The picture below shows the ‘gears’, as we call them, that can be integrated into the models. As you can see we’ve migrated quite far from just a single phase model to predict flows!

Figure 1: We apply a plug-and-play strategy: if a simple CFD model can do the job, we'll use it. In other cases we 'gear up'

image sludge blanket - solids profile EBPRimage VFA concentration EBPR

Figure 2:Example of a multiple phase model coupled with biokinetics for an Enhanced Biological Phosphorus Removal reactor – see also visualisation solids profile, right: visualisation Volatile Fatty Acid production)

2.CFD is reliable

What I discovered working at AM-TEAM is that you can simulate tons of situations very reliable through the use of CFD. Going from multiphase-models, to simulations coupled to biokinetics, to transient situations, and so on, my colleagues manage to predict outcomes very reliably. We know that from historic validation. Today, we only validate our models in a few cases, when it is a new model or our client insists on it, and we’ve managed to produce very accurate results, strengthening our trust in our models and our client’s confidence in their processes. So the good news is that in the majority of the cases no measurement data is needed and it becomes a purely ‘virtual project’.

So, for me, often being a sceptic who thought there was always a margin of error that limited the applicability of simulations, this was an eye-opener! On top of that I realised that not relying on these modern simulation tools can also entail certain risks and downstream costs associated to the process.

(It is important to note that for this an experienced AND CRITICAL CFD-team is needed, who question and check everything. Your model is only as good as its creator and its input!)

Graph chlorides concentration to treatment plant - model vs measurement data

Figure 3:The dynamic model (purple line) could predict reality (blue data points) very well. This model was used to run different 'what-if' scenarios to make better operational decisions.

See also the case of a large drinking water basin:

3.As computational power has surged speed is no longer an issue

Another thing I learned is that computational power has surged the past decade, enabling engineers to run heavy models in a short timeframe. Think for example about the high performance computing (HPC) infrastructure AM-TEAM has access to.
This allows us to run multiphase-models, large-scale models, etc. within a short timeframe.

image AM-TEAM's first in-house server

Figure 4: A screenshot of AM-TEAM’s first in-house server

4.Success factors and some publicity

Yes, obviously, I will end with some publicity for AM-TEAM – what kind of business development manager would I be if not!

But I’ll start with reusing some of my colleagues content explaining CFD Success factors (see also

As you can see in the picture below multiple parameters add to the success of a simulation.

image CFD succes factors

Figure 5: CFD success factors

It is clear that CFD requires complex and specialised skills and is, as we say in Dutch, ‘not from the cat’ (‘niet van/voor de poes’ – difficult, not easy).
A good model is only as good as the expert handling it. Compare it to flying a plane: a good pilot can do great stuff.

At AM-TEAM I’ve encountered very experienced CFD engineers, combining knowledge about the industry they serve (water- and process-industry) with a profound knowledge of advanced modelling and a critical mind. It’s a dedicated team that stays on top of the latest developments (be it through our work for clients or in cooperation with research institutes and platforms).

Coming from a more ‘classic’ engineering background they’ve managed to convince me of the huge possibilities of CFD, and I believe it will disrupt the ‘physical’ way of engineering through pilot testing.


As you can see, my colleagues at AM-TEAM managed to convert me into a ‘CFD-believer’, acknowledging the huge added value of advanced modelling we can bring to the industry.

I believe that in the coming years its importance will only rise – due to its capacity to optimise all kind of processes with a limited cost (compared to pilot-testing),the increase in computational power and a general trend towards digitalisation.
It will allow us a freedom of testing hundreds of set-ups and parameters using only computational power, which will encourage innovation.

On the other hand, I also think that we should familiarise CFD and advanced modelling to the public, so they can look at it with a critical eye and see the opportunities it brings. That way we can ensure its quality and confidence in its capabilities.

I am looking forward to your feedback on this blog – let me know what you think about it!


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