Limit of stokesian settling concentration characterizes sludge settling velocity.

Abstract Flocculent settling (stokesian) is predominant within ideally operating clarifiers, and the shift to ‘slower’ hindered settling (non-stokesian) causes both failure and poor effluent quality. Therefore, a new metric for settling characteristics was developed and classified as Limit of Stokesian Settling (LOSS). The technique consisted of determining the total suspended solids (TSS) concentration at which mixed liquor settling characteristics transition from stokesian to non-stokesian settling. An image analytical technique was developed with the aid of MATLAB ® to identify this transition. The MATLAB tool analyzed RGB images from video, and identified the presence of an interface by a dramatic shift in the Red indices. LOSS data for Secondary activated-sludge systems were analyzed for a period of 60 days at the Blue Plains Advanced Wastewater Treatment Plant. LOSS for secondary systems typically occurred between 600 and 700 mg TSS/L but reached 1000 mg TSS/L for a good settling secondary sludge and 500 mg TSS/L for a poor settling secondary sludge, settling quality was based on hindered settling rates. In addition, LOSS was collected for granular systems seeded with cyclone underflow from Strass Wastewater Treatment Plant, it was observed that LOSS was higher for granular systems ranging from 1600 to 5500 mg TSS/L for low and high levels of granulation, respectively. The monovalent to divalent cation ratio (M/D) was increased with the addition of sodium ions to deteriorate settling properties. Samples adjusted with higher M/D consistently had 100 mg TSS/L (15%) decrease in LOSS from the control. LOSS numbers collected experimentally were validated with the Takacs et al. (1991) settling model. When compared to flux curves with small changes in sludge matrix, LOSS was proven to be faster at characterizing hindered settling velocity and was less erratic. This is the first time a measurement method has been developed to characterize the transition from stokesian to non-stokesian settling. Additionally, this is the first step in developing new metrics to predict clarifier failure, and determine effluent quality through the development of flocculent settling metrics.