New process technologies that enable the shift from conventional biological wastewater treatment processes to resource recovery systems are matched by an increasing demand for predictive capabilities. Mathematical models are excellent tools to meet this demand, but they runtime still hinders parameter indetification and real-time control.
In collaboration with Kris villez from the Department Process Engineering at Eawag, we are developing emulators to accelerate the different modules that compose the simulators of Nitrification bioreactors.
One important step in the simulation of these systems is the calulation of the pH based on the state of the reactor12. The pH is estimated by a root finding process that could be accelerated inducing an overall speed up of the simulator.
We have been working on simplified versions of the root finding module. The first test was in 2-dimensions and a later one in 4-dimensions. The results are promising and next we will tackle the 12-dimensional case.
We will make the final dataset publicly available.
Masic, A., Srinivasan, S., Billeter, J., Bonvin, D., & Villez, K. (2017). Identification of Biokinetic Models using the Concept of Extents. Environmental Science & Technology. http://doi.org/10.1021/acs.est.7b00250 ↩
Flores-Alsina, X., Kazadi Mbamba, C., Solon, K., Vrecko, D., Tait, S., Batstone, D. J., Jeppsson, U., Gernaey, K. V. (2015). A plant-wide aqueous phase chemistry module describing pH variations and ion speciation/pairing in wastewater treatment process models. Water Research, 85, 255–265. http://doi.org/10.1016/j.watres.2015.07.014 ↩