In this study non-invasive low field magnetic resonance imaging (MRI) technology was used to monitor fouling induced changes in fiber-by-fiber hydrodynamics inside a multi-fiber hollow fiber membrane module containing 401 fibers. Using structural and velocity images the fouling evolution of these membrane modules were shown to exhibit distinct trends in fiber-by-fiber volumetric flow, with increasing fouling causing a decrease in the number of flow active fibers. This study shows that the fouling rate is not evenly distributed over the parallel fibers, which results in a broadening of the fiber to fiber flowrate distribution. During cleaning, this distribution is initially broadened further, as relatively clean fibers are cleaned more rapidly compared to clogged fibers. By tracking the volumetric flow rate of individual fibers inside the modules during the fouling-cleaning cycle it was possible to observe a fouling memory-like effect with residual fouling occurring preferentially at the outer edge of the fiber bundle during repeated fouling-cleaning cycle. These results demonstrate the ability of MRI velocity imaging to quantitatively monitor these effects which are important when testing the effectiveness of cleaning protocols due to the long term effect that residual fouling and memory-like effect may have on the operation of membrane modules.

Early fouling warning is important for the economical operation of membrane separation systems. In parallel multi-channel flow systems, flow re-distribution between channels due to fouling is often associated with maloperation. In the current research we use low magnetic field NMR to monitor multi-fiber hollow fiber membrane modules undergoing a fouling-cleaning cycle and show that rapid detection of fouling is possible by detecting the loss of signal coherence associated with flow re-distribution within the 401 hollow fiber membrane module. This effect is demonstrated to be both reproducible, and reversible via membrane cleaning. The results demonstrate a strong correlation between the coherence signal magnitude and the number of fibers fouled. This may be used in practice for high sensitivity early warning, and to monitor the efficiency of cleaning. This approach may also be particularly useful in the case of detecting residual fouling after cleaning, evidenced in this research by significant flow re-distribution between the before fouling and after cleaning signal coherence.