Development of Digital Twins for Water Treatment Systems

Sebastian Olivier Nymann Topalian

Research output: Book/ReportPh.D. thesis

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Abstract

The development of digital twins for water treatment systems is a complicated task with multiple solution strategies. In this thesis three different strategies are adopted to try and connect empirical information to the task of industrial dewatering of stabilized biosolids. First, a big data approach is developed to try and utilize existing infrastructure and information from sensors and production schedules from nearby units as well as upstream production information from a biotechnological production company to forecast polymer consumption at the dewatering facility. The approach enables the analysis of how upstream categorical information such as production information propagates through the system and impacts the dewatering operation. Second, an experimentalist approach is developed where samples are collected and analyzed by combining computer vision algorithms and quantitative image analysis. The computer vision approach aptly distinguishes between particles with different morphologies, which is an improvement in terms of interpretability compared to the conventional approach where only particle size descriptors are utilized. Finally, a third approach is developed, that of the control engineer, where the validation of a partial-degassing vessel and a color-camera are used to monitor total suspended solids in a situation where traditional measurement equipment has failed before. The three different approaches are discussed, and a suggestion is made to focus on ensuring the robustness of the online reject monitoring setup and developing a monitoring setup for the cake to effectively close the mass balance around the dewatering unit.
Original languageEnglish
Place of PublicationKgs. Lyngby
PublisherTechnical University of Denmark
Number of pages86
Publication statusPublished - 2024

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