Abstract

IKUMI, DS. Sensitivity analysis on a three-phase plant-wide water and resource recovery facility model for identification of significant parameters. Water SA [online]. 2020, vol.46, n.3, pp.476-492. ISSN 1816-7950.  http://dx.doi.org/10.17159/wsa/2020.v46.i3.8658.

Water and resource recovery facility (WRRF) mathematical models have been advancing towards their widespread application for sizing and operation of treatment plants to minimize energy consumption and cost while maximizing nutrient recovery and effluent quality. Effective utilisation of these models requires that they are well calibrated. However, difficulties (with important parameters not identified and uncertainties in interpretation of model output results) can be experienced in model calibration, especially due to (i) the intricate relationships of model output variables with model input factors (where parameters are inter-related to various model outputs), resulting in non-linearity, and (ii) the limitations (due to expensive and/or time-consuming experimental methods) experienced in procuring and reconciling data required for determination of the model input factors. This paper presents the performance of a sensitivity analysis, reinforced with expert-based reasoning, on a three-phase (aqueous-gas-solid) plant-wide model (PWM_SA, Ikumi et al., 2015), for identification of significant parameters, and highlights the ones requiring experimental determination, specific to the system. The sensitivity analysis exercise was performed using two methods - i.e., Morris screening (screening method) and standardised regression coefficient (SRC; based on regression). This process was useful towards detection of the parameters, which are not normally measured at WRRFs, but may require attention for future application of mathematical models in decision-making processes for WRRFs. These included the influent fractions of unbiodegradable and readily biodegradable organics, the kinetic constants for hydrolysis of biodegradable particulates, the elemental composition of the organics and the specific growth rate of autotrophic nitrifying biomass.

Keywords : sensitivity analysis; activated sludge; anaerobic digestion; plant-wide modelling.

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