Symposium presentation - National Symposium of applied biological sciences 2017

1. Spatio-temporal modelling of filter cake formation in
filtration processes
Bram De Jaegher
W. Naessens, J. Baetens, I. Nopens
Model-based analysis and optimisation of bioprocesses
DEPARTMENT OF MATHEMATICAL MODELLING, STATISTICS AND BIOINFORMATICS

3. L. Zeman, L. Denault, Characterization of microfiltration membranes by image analysis of electron micrographs, Part
I. Method development, Journal of Membrane Science, 71 (1992), 221-231

5. C. Y. Tang, et al., Characterization of humic acid fouled reverse osmosis and nanofiltration membranes by transmission
electron microscopy and streaming potential measurements, Environmental Science and Technology, 41 (2007), 942-949

6. Membrane filtration
Membrane filtration Modelling Validation Conclusion 2/8

7. Membrane filtration
Membrane filtration Modelling Validation Conclusion 2/8

8. Membrane filtration
Membrane filtration Modelling Validation Conclusion 2/8

9. Modelling
Resistance-in-series (RIS) Machine learning
Membrane filtration Modelling Validation Conclusion 3/8

10. Modelling
Resistance-in-series (RIS) Machine learning
Membrane filtration Modelling Validation Conclusion 3/8

11. Modelling
Mechanistic framework
Navier-stokes equations for fluid flow → OpenFOAM
Agent based model for disperse phase → Matlab
Membrane filtration Modelling Validation Conclusion 4/8

12. Modelling
Membrane filtration Modelling Validation Conclusion 5/8

13. Validation
Membrane filtration Modelling Validation Conclusion 6/8

14. Validation
Membrane filtration Modelling Validation Conclusion 6/8

15. Validation
Membrane filtration Modelling Validation Conclusion 6/8

16. Validation
Membrane filtration Modelling Validation Conclusion 6/8

17. Validation
Membrane filtration Modelling Validation Conclusion 6/8

18. Validation
Membrane filtration Modelling Validation Conclusion 7/8

19. Conclusion
Progress towards:
understanding the mechanisms of filter cake formation
quantifying the impact of:
particle size
crossflow velocity
lift forces
...
Future work:
improving behaviour of particles in the filter cake
extending interaction between filter cake and liquid phase
use the Segr´e-Silberberg effect to reduce membrane fouling?
Membrane filtration Modelling Validation Conclusion 8/8

20. Conclusion
Progress towards:
understanding the mechanisms of filter cake formation
quantifying the impact of:
particle size
crossflow velocity
lift forces
...
Future work:
improving behaviour of particles in the filter cake
extending interaction between filter cake and liquid phase
use the Segr´e-Silberberg effect to reduce membrane fouling?
Membrane filtration Modelling Validation Conclusion 8/8

21. Model-based analysis and optimisation of bioprocesses
Bram.DeJaegher@UGent.be