Statistical analysis of fine resolution flow datasets helps characterizing flow behaviour in primary clarifiers: a decision support method

Abstract

Abstract In situ measurement campaigns of primary clarifiers are rarely implemented properly because of their cost, time, and energy demand. Hydrodynamic modelling possibilities for such reactors have been intensely examined recently, but on-site factors affecting flow characteristics (e.g. flow distributors) have not received sufficient attention. This paper describes the use of ANOVA in examining fine resolution flow datasets and the related decision support method for in situ measurement campaigns and subsequent modelling processes. The characteristics of the flow and the applicability of 2D and 3D methods to investigate hydrodynamic features are discussed through the example of a rectangular primary clarifier, also considering the reproducibility of measurements ranging from typical nominal flow rates to peak loads. Based on the data, recommendations are provided on the adequate sizing of a measurement campaign, potentially reduced to a single longitudinal section (2D measurement). According to our results, performing hydrodynamic measurements with a 2D-arrangement of measuring points is sufficient in the case of such clarifiers, also with regard to the design processes. When applying the described methods, the related efforts and costs may be reduced and estimated more easily. However, care should be taken when applying this method to determine the spacing of measuring points correctly.