This paper presents a systematic methodology to characterise the influent sludge in terms of the ADM1 components from the experimental measurements traditionally used in wastewater engineering. For this purpose, a complete characterisation of the model components in their elemental mass fractions and charge has been used, making a rigorous mass balance for all the process transformations and enabling the future connection with other unit-process models. It also makes possible the application of mathematical algorithms for the optimal characterisation of several components poorly defined in the ADM1 report. Additionally, decay and disintegration have been necessarily uncoupled so that the decay proceeds directly to hydrolysis instead of producing intermediate composites. The proposed methodology has been applied to the particular experimental work of a pilot-scale CSTR treating real sewage sludge, a mixture of primary and secondary sludge. The results obtained have shown a good characterisation of the influent reflected in good model predictions. However, its limitations for an appropriate prediction of alkalinity and carbon percentages in biogas suggest the convenience of including the elemental characterisation of the process in terms of carbon in the analytical program.
This paper presents the characterisation procedure of different types of sludge generated in a wastewater treatment plant to be reproduced in a mathematical model of the sludge digestion process. The automatic calibration method used is based on an optimisation problem and uses a set of mathematical equations related to the a priori knowledge of the sludge composition, the experimental measurements applied to the real sludge, and the definition of the model components.In this work, the potential of the characterisation methodology is shown by means of a real example, taking into account that sludge is a very complex matter to characterise and that the models for digestion also have a considerable number of model components. The results obtained suit both the previously reported characteristics of the primary, secondary and mixed sludge, and the experimental measurements specially done for this work. These three types of sludge have been successfully characterised to be used in complex mathematical models.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.