David Steffelbauer

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.

Efficient Sensor Placement for Leak Localization Considering Uncertainties

Losses in water distribution systems can be between several percent in well maintained systems up to more than 50 percent in developing countries. Most of the losses originate from leaks. Therefore, a fast detection and localization of leaks is crucial for effectively reducing this losses in water distribution networks. Model-based leak localization has become increasingly popular in recent years. Certainly, the performance of these methods is linked to 1) the measurement locations in the system and 2) uncertainties at these locations. This paper provides a methodology that incorporates uncertainties of different types and sources in the optimal sensor placement problem for leak localization shown by the example of the effect of demand uncertainties on potential pressure measurement points. The problem is solved for different numbers of sensors and different strengths of uncertainties are taken into account. Additionally, to describe the relation between the number of sensors and the leak localization quality, a cost-benefit function is derived based on the different sensor placement results and GoF statistics. It was found that the function follows a power law. Results show that incorporating uncertainties leads to other optimal positions than without uncertainties, but the power law behavior still stays true. Additionally, more sensors are needed than without uncertainties.

Examples for Genetic Algorithm based optimal RFID tag antenna design

In this work a Genetic Algorithm is used to obtain optimal planar UHF RFID tag antenna topologies. The presented antenna design method is automated and solely requires very little human intervention. Different requirements like antenna dimension, conductive and dielectric materials, frequency range, etc. can be adjusted. This enables the automated design of tailored tag antennas for different requirements. Due to the complex behavior of UHF antennas numerical electromagnetic field simulation is essential. Simulation is carried out with the aid of ANSYS HFSS and ANSYS DESIGNER. In order to obtain meaningful results, high accuracy of the simulation is of vital importance. Therefore this work places emphasis on the comparison of simulation and measurement of prototypes. As a result of the evolutionary design, examples for narrowband and broadband antennas are presented. Two approaches were applied, one very fundamental, discretizing the available design space into pixel units. In addition a lattice based approach, promoting meander-like layouts, is implemented. Four antenna layouts are discussed in this work. All obtained tag antennas meet the required specifications and prove the abilities of the design approach.

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.

Fitness landscapes and distance metrics for model-based leakage localization

This paper aims to investigate the effect of distance metrics on the fitness landscape for model-based leakage localization and its impact on the performance of the differential evolution optimization algorithm applied to a theoretical water distribution network from literature.

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.

Selecting a series of storm events for a model-based assessment of combined sewer overflows

ABSTRACT The hydraulic verification of combined sewer systems as well as the assessment of combined sewer overflows (CSOs) can be conducted using a hydrodynamic model. Unfortunately, long-term simulations with hydrodynamic models for the assessment of CSOs can cause unacceptably long computation times. Using only a series of storm events instead of a precipitation continuum can reduce this time and enables parallel simulation of single storm events. We introduce a method to select this series of storm events. The method’s parameters have been optimized to replicate the overflow volume of the continuous simulation and to minimize the overall computation time. This optimization revealed a generally applicable parameter set that results in series of storm events that are shorter than the precipitation continuum by 86.2–95.2% for the investigated cases. Additionally, the deviation of overflow volume between continuous simulation and series simulation ranges between only 0.1% and 4.1%.