Markus Günther

Systematic material and crack type specific pipe burst outflow simulations by means of EPANET2

The calculation of outflow from pipe bursts is of interest for water utilities, as the discharged water may cause large amounts of damage to the adjacent infrastructure. Therefore, the crack type specific relationship between leakage outflow and pressure is of interest. Recent findings offer new opportunities for burst outflow calculations with hydraulic models. In this paper, we compare two calculation approaches according to uncertainties caused by input parameters and give recommendations for the applicability of the methods. Simulations in a case study area have shown large leakage outflow differences between the two approaches for longitudinal cracks. For circumferential cracks, the differences are smaller. Further, due to the uncertain leak size and form of probable bursts we involved Monte Carlo simulations in the model approach. These allow the derivation of mean values and standard deviations of leakage outflow per pipe section to make the uncertainty of the results more transparent.

Cause and effect oriented sewer degradation evaluation to support scheduled inspection planning.

Managing the subsurface urban infrastructure, while facing limited budgets, is one of the main challenges wastewater utilities currently face. In this context targeted planning of inspection and maintenance measures plays a crucial role. This paper introduces a cause and effect oriented sewer degradation evaluation approach to support decisions on inspection frequencies and priorities. Therefore, the application of logistic regression models, to predict the probability of failure categories as an alternative to the prediction of sewer condition classes, was introduced. We assume that analysing the negative effects resulting from different failure categories in extension to a condition class-based planning approach offers new possibilities for targeted inspection planning. In addition, a cross validation process was described to allow for a more accurate prediction of sewer degradation. The described approach was applied to an Austrian sewer system. The results show that the failure category-based regression models perform better than the conventional condition class-oriented models. The results of the failure category predictions are presented with respect to negative effects the failure may have on the hydraulic performance of the system. Finally, suggestions are given for how this performance-oriented sewer section evaluation can support scheduled inspection planning.

Adige: an efficient smart water network based on long-range wireless technology

Outworn water distribution infrastructures require real-time monitoring and management of water pressure and flow, together with accurate leak detection and localization techniques. Smart water networks based on wireless sensors offer a huge potential in this domain, but their deployment and maintenance is often costly and labor-intensive. In this paper, we present Adige: an efficient smart water network architecture based on long-range wireless technology that improves the scalability and robustness of water distribution systems. We developed a sensor node prototype using a LoRa radio transceiver and used it to carry out a set of experiments showing the benefits of Adiges approach. Our evaluation shows that, in contrast to previous approaches, the use of long-range wireless technology allows to significantly reduce energy consumption while covering large areas indoors, outdoors, and underground.

Fault detection data creation using an experimental water distribution system

Model based event detection and localization states one method to deal with leakage occurrence in water distribution systems (WDS). Since access to hydraulic models and measurement data of real world systems is limited for researchers the opportunities for testing new model approaches on one and the same WDS are scarce. In this article we present an experimental water distribution system (EWDS-TUG) that allows for simulating scaled real world water demand and leakage scenarios. We show example experiments and the related measurement data along with metadata that are supposed to be provided to the scientific community for model testing.

Sensor Placement and Leakage Isolation with Differential Evolution

Leakages in water distribution systems (WDS) can cause significant economic losses. Therefore finding leaks in water pipes is nowadays a crucial task for water utilities. In this paper, the effects of leakages on the hydraulics of WDS, particularly with regard to flow and pressure, are investigated. From the discrepancy of the unperturbed and the perturbed WDS due to the occurrence of leakage a methodology is developed, which enables an efficient sensor placement of flow meters and pressure sensors. This is achieved by a Fault Sensitivity Matrix (FSM). A special Genetic Algorithm (GA) called Differential Evolution (DE), which saves significantly on computation time in large WDS, is used to find the optimal position of a minimum number of sensors. DE is chosen because of its good rate of convergence.Once an optimal sensor placement is obtained, DE is also used for leakage location. The methodology was tested in two different WDS. The first WDS is the model network Poulakis (2003) used. The second is a partial network in the city of Linz, where the task is to find an ideal sensor placement to guarantee efficient leakage isolation. In this paper we show that DE performs excellent on both tasks, the sensor placement and the leakage isolation, for the two investigated systems. Additionally the implementation of demand and measurement uncertainties is outlined.