AQUA Studienpreisträger 2020

Aron Negusse Asfaha

Die AQUA Stiftung verleiht den AQUA Studienpreis 2020 an Aron Negusse Asfaha für seine herausragende Master-Arbeit mit dem Titel "Optimal Design of Pressure Measurement for Stochastic Calibration of Water Distribution Hydraulic Models".

Aron Negusse Asfaha hat von 2016 bis 2019 den internationalen Studiengang "WAREM - Water Resources Engineering and Management" an der Universität Stuttgart belegt. Seine herausragende Master-Arbeit zum Thema "Optimal Design of Pressure Measurement for Stochastic Calibration of Water Distribution Hydraulic Models" wurde von PD Dr.-Ing. Sergey Oladyshkin vom Institut für Wasser- und Umweltsystemmodellierung betreut. Die Arbeit befasst sich mit dem Kalibrierungsproblem von Wasserverteilungsmodellen, die der Schlüssel für jede Analyse, Design-Bewertung oder Beurteilung sind, die an den Wasserversorgungsrohrnetzen durchgeführt werden soll.

Zusammenfassung der Arbeit in Englisch

This thesis focuses on establishing a meaningful relationship between information gain and the required acceptable model calibration. The calibration of water Distribution (WD) models is key to any analysis, design evaluation or assessment to be carried out on the WD pipe networks. Several calibration procedures have been developed through the years but still much progress needs to be made, to tackle the challenges in water distribution. The extensive costs and time wasted in acquiring measurement (pressure) data for calibration has made the company RBS-wave doubtful of its efficiency since no hard and fast rule exist to govern measurements. Ac-cording to the German
standards for gas and water works (DVGW) regulation only a minimum recommended use of pressure measuring instruments are provided. In reference to this number the RBS-wave uses four times as much measuring instruments. This boosted the motivation of this thesis to aim at optimizing the number and location of pressure measuring instruments sufficient to provided calibration within acceptable limits. A tool for probabilistic assessment, within the Bayesian framework was adopted from a previous thesis on which this thesis is based. Hence an assessment on calibrated project of the RBS-wave was carried out to achieve similar calibration results but with less measurement information. This guided the second phase of the thesis where a synthetic distribution network was
developed to calibrate and identifying the intentional installed network errors by systematically placing the loggers at nodes were high values of coefficient of variation were expressed. Four scenarios were created and analysed to narrow the gap between the recommended DVGW number of measuring instruments, and the number of instruments used by the RBS-wave to achieve optimal use of instrumentation for measurement.

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