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Obstructions monitoring in sewerage pipes.
KTH, School of Architecture and the Built Environment (ABE), Sustainable development, Environmental science and Engineering, Land and Water Resources Engineering.
2016 (English)Independent thesis Advanced level (degree of Master (Two Years)), 20 credits / 30 HE creditsStudent thesis
Abstract [en]

When a malfunction in the collection system occurs and a pipe overflows, the wastewater may be discharged in the natural environment. To avoid such pollution, nuisances to inhabitants living nearby and extra cost for the operator, there is an issue of detecting early enough the buildup of obstructions in sewerage pipes in order to react before the damage is done.

The aim of this thesis was thus to develop a decision support tool to detect obstructions and to optimize cleaning operations. Some additional specifications were the file size for sending by email, the simplicity of setup and use, the visual attractiveness and a quick visualization of results. The tool consists of two Excel files coupled with a database which permits to send a daily email to the operator with the functioning state of each measurement point. However, the tool does not do everything, human analysis is necessary to have a critical eye on the results and to decide when to trigger a cleaning operation.

The main perspective at the end of this thesis is the replacement of the preventive cleaning operations that were previously performed with a fixed frequency per year by conditional cleaning operations triggered by the tool and to observe the decrease of cleaning operations. Other perspectives are to spread the tool to other sites and to use the received feedbacks to adjust the different parameters and eventually to determine an automatic trigger condition of cleaning operations.

Place, publisher, year, edition, pages
, TRITA-LWR Degree Project, ISSN 1651-064X ; 2016:02
Keyword [en]
Obstruction, Sedimentation, Conditional cleaning operation, Prediction, Decision support tool, Excel
National Category
Civil Engineering
URN: urn:nbn:se:kth:diva-190608OAI: diva2:952292
Available from: 2016-08-15 Created: 2016-08-12 Last updated: 2016-08-15Bibliographically approved

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Land and Water Resources Engineering
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