In this study global sensitivity analysis is performed to identify influential as well as non-influentialparameters in a model of a University Cape Town Membrane Bioreactor (UCT-MBR). Inparticular, the Standardised Regression Coefficients (SRC) and Extended-FAST sensitivity analysismethods are applied. The sensitivity of model variables towards parameter variation is analysed forCODTOT, SNH4, SNO3, SPO, and MLSS along five reactor compartments. Both methods indicate that theparameters identified as being influential differ from section to section due to the differentprocesses involved. Moreover, the relevant influence of the membrane filtration parameters isdetected in the first plant section due to the influence of the recycled sludge. It is found that thecomputationally less expensive SRC method is applied outside its range of applicability with R2 =(0.3-0.6) < 0.7. Nevertheless, the ranking obtained with the SRC method for the influentialparameters is very similar to that of the Extended-FAST method, except for MLSS. However, toobtain reliable quantitative information on variance decomposition and to detect and quantify (insome cases considerable) interactions present among parameters the use of the computationallymore expensive Extended-FAST is found to be necessary in this case study.
|Number of pages||10|
|Publication status||Published - 2011|