Physical and statistical model for predicting a transmembrane pressure jump for a membrane bioreactor

Membrane bioreactors (MBRs) have been widely used to purify wastewater for reuse. However, MBRs are subject to fouling, which is the phenomenon whereby foulants absorb or deposit on the membrane. After long-term operation of MBRs under a condition of constant-rate filtration, transmembrane pressure (TMP) increases rapidly. This TMP jump is one factor making the operation of MBRs difficult. We therefore propose the construction of a model that predicts the timing of a TMP jump. First, a nonlinear function for determining whether a TMP jump will happen was derived from physical knowledge. We then analyzed the nonlinear function statistically with measurement data and constructed a model that detects a TMP jump. The performance of the proposed method was confirmed through the analyses of two data sets obtained from the literature and a data set recorded for a real industrial MBR plant.

► MBRs have been widely used to purify wastewater for reuse.
► After the operation of MBRs in the long term, TMP increases rapidly.
► Our goal is to detect this TMP jump with highly predictive accuracy.
► We proposed a physical and statistical discriminant model of TMP jumps.
► The performance of the proposed method was confirmed with a variety of data sets.