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Uncertainties in flow assessment with cheap measurement sensors - IoT

Published: 12 May 2020

Wastewater flows in existing sewers are an important data that can influence decisions on future exploitation, renewal of the pipe network, minimizing inflow and infiltration as well as opportunities for wastewater heat recovery. One can also say that the higher the temporal and spatial resolution of the flow data, the better the decisions that can be made in the end.

However, continuously measuring wastewater flows at different locations in the sewers with traditional meters requires a lot of resources, based on water levels and water velocity. Another method is to install water level meters that are cheaper, require less maintenance and can therefore be installed in more places. The disadvantage, however, is that the flow needs to be calculated with Manning's equation and that the measurement accuracy can be greatly reduced due to uncertainties in the sewers geometry, the coefficient Ks strickler and the inclination or due to possible accumulations of e.g. sediment and fat that cause backwater flows in the system.

The purpose of the thesis is to investigate how uncertainty of flow measurements with cheap water level meters can be kept low by appropriate selection of measuring points, redundant measurements, measurement of other factors (eg temperature) and learning of patterns in real-time data that can indicate backwater or inflow. The work also aims at exploring how the measurements can support real-time operation and maintenance of sewer networks (indicating deviation from the system's regular operating mode), even in conditions that are not suitable for accurate measurement of wastewater flow.

The project work may involve data analysis and / or field work and / or lab work. The scope and detailed focus of the thesis project are determined after discussion and in consensus between the student, supervisor / examiner and any possibly interested municipality or municipal water and wastewater company.

Youen Pericault

Youen Pericault, PhD Student

Phone: +46 (0)920 493528
Organisation: Urban Water Engineering, Architecture and Water, Department of Civil, Environmental and Natural Resources Engineering
Annelie Hedström

Annelie Hedström, Associate Professor

Phone: +46 (0)920 492309
Organisation: Urban Water Engineering, Architecture and Water, Department of Civil, Environmental and Natural Resources Engineering