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Saving costs and improving effluent by knowing what is happening in your bioreactor - Part II

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AerationWWTPEffluent quality

Here it is! Part II of a series of three articles describing a globally unique advanced modelling project in the water sector, explained in a practical and easy way. Although focused on wastewater here, ‘drinking/process water people’ can also benefit from reading it as the applied methodology is generic for most unit processes. This Part II shows how we used the 3D plant model, which was unprecedently proven to be accurate in Part I (includes video!),to virtually re-design the plant to lower effluent nitrate and saving operational costs. You will probably understand that changing a plant virtually is easier, faster, less risky and offers much more testing freedom compared to real-life trials at full-scale. We call it ‘what if’ scenario testing.

Figure 1: The aerated zone of one of the three identical bioreactors. The colours show simulated air distributions, with obviously higher oxygen levels near the inner wall, causing problems downstream

 

1. Part II: virtual re-design to improve effluent quality and save costs

The Eindhoven water resource recovery facility (WRRF) is a 750,000pe conventional activated sludge plant operated by Waterboard De Dommel (Netherlands). While the plant operators want to lower effluent nitrate, low levels are hard to get, especially during cold weather. Finding optimal performance of the existing bioreactor is done before a plant upgrade with an advanced denitrification step to see if upgrade is needed. If you’ve read Part I, you understand that the elevated oxygen levels near the intake of the anoxic tank may hinder denitrification in the bioreactor.

There are two very important aspects that will impact effluent quality and OpEx in this case:

  1. How you configure and operate the mixers
  2. How you configure and operate the aeration

Both interact, and sometimes counteract each other, and both can be ‘played with’ virtually.

2. How we changed the plant, virtually

Essentially, any CFD model starts with a 3D CAD model like this:

Figure 2: Top view (left) and 3D drawing (right) of the ‘outer ring’ of the bioreactor

So once you have a CAD drawing including the essential elements (propellers, aerators, recycle pumps etc),you can change it and simulate the impact of that change prior to implementation. And this is what we have experimented with.

Figure 3: ‘what if’ we reconfigure aerators (more upstream) and/or switch off certain propellers at certain flow rates?

OBJECTIVE: how do we lower the risk on high oxygen levels near the anoxic inlet (downstream from aerators),limiting effluent nitrate, while eventually saving costs?

STRATEGY:

  • Check the impact of turning off certain propellers at certain flow rates. Which propellers and which flow rates? Simulation must tell
  • Check the impact of re-configuring the aerators
  • Check the impact of changing both, simultaneously

We finally tested 10 different ‘what if’ scenarios.

3. Results

Changing important design factors such as aerator configuration and mixer operation has a major impact on a bioreactor. Advanced CFD gives you the knowledge that allows you to design and operate for that. The figures below show the gas holdup downstream the aeration (B is a few meters more downstream than A, and so forth).

Figure 4: how the bubbles spread in the bioreactor (top view)

Upstream mixers control how bubbles in the aeration zone (do not) spread. The impact strongly varies as function of the plant flow rate and if bubbles are not spread evenly, it has downstream consequences (see cross sectional views of the downstream region below). We noticed that at certain flow rates, it was better to totally switch off two of the 6 mixers in the bioreactor. Yes, this saves energy.

Figure 5: air distribution in the bioreactor, downstream of the aeration (cross sectional view)

Switching off mixers while maintaining sufficient liquid velocity

Switching off mixers… so, what about the risk on local sludge settling then? Let’s take a 3D look at the calculated local velocities. If you have read Part I, you now understand that these values are quite accurate. The dark blue regions with lowest velocities still had values of around 0.35 m/s, which is still very decent (typically, one does not want to go below 0.25 m/s).

Figure 6: local velocities of the mixed liquor at different depths in the bioreactor

So what is the winning scenario? The following graph evaluates all scenarios at once in terms of downstream gas holdup. (remember: downstream oxygen was causing nitrate build up in the anoxic zone during cold weather). Switching off mixers 5 and 6 at the right times (M56) could reduce the risk with 10% while saving energy. A hybrid scenario combining this with aerator reconfiguration resulted in 20% risk reduction. This is relevant taking planned retrofits in mind.

igure 7: downstream reduction of air (gas holdup) obtained with different design and operational scenarios

4. Conclusions

  • Virtual ‘what-if’ scenario testing is easier, faster, less risky and offers much more testing freedom compared to real-life trials at full-scale. Mixer operation and aerator configuration can be easily assessed.
  • An accurate CFD model gives you the confidence to actually take decisions based on the model. This is where the real value lies. This bioreactor model has proven accuracy (see Part I).
  • Plant operators and designers benefit from knowing the interaction of mixers and bubbles, both in terms of energy savings and effluent quality
  • Simple measures such as switching off one or more mixers at certain flow rates can be easy gains. The model will tell you which mixers at which flow rates.
  • Prior to any plant design or major retrofit, modelling the aeration system accurately is highly beneficial, certainly given the investment budgets in play.

Do you have questions or comments? Leave us a comment!

These results were presented at Weftec 2018 (New Orleans),World Water Congress 2018 (Tokyo) and will also be published scientifically in papers and an upcoming book.

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Next articles to come

  • Part III: impact of the modelling study in terms of cost saving and plant performance

Special thanks to:

  • Waterboard De Dommel: Tony Flameling, Peter van Horne, Han van Happen, Victor Claessen, Stefan Weijers, Peter van Dijk​
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