The hydraulics of leakage and intrusion flows through leak openings in pipes is complicated by variations in the leak areas owing to changes in pressure. This paper argues that the pressure–area relationship can reasonably be assumed to be a linear function, and a modified orifice equation is proposed for more realistic modeling of leakage and intrusion flows. The properties of the modified orifice equation are explored for different classes of leak openings. The implications for the current practice of using a power equation to model leakage and intrusion flows are then investigated. A mathematical proof is proposed for an equation linking the parameters of the modified orifice and power equations using the concept of a dimensionless leakage number. The leakage exponent of a given leak opening is shown to generally not be constant with variations in pressure and to approach infinity when the leakage number approaches a value of minus one. Significant modeling errors may result if the power equation is extrapolated beyond its calibration pressure range or at high exponent values. It is concluded that the modified orifice equation and leakage number provide a more realistic description of leakage and intrusion flows, and it is recommended that this approach be adopted in modeling studies.

Water loss from leaking pipes represents a substantial loss of revenue as well as environmental and public health concerns. Leak location is normally identified by placing sensors either side of the leak and recording and analysing the leak noise. The leak noise contains information about the leak's characteristics, including its shape. Whilst a tool which non-invasively provides information about a leak's shape from the leak noise would be useful for water industry practitioners, no tool currently exists. This study evaluates the effect of various leak shapes on the vibration signal and presents a unique methodology for predicting the leak shape from the vibration signal. An innovative signal processing technique which utilises the machine learning method random forest classifiers is used in combination with a number of signal features in order to develop a leak shape prediction algorithm. The results demonstrate a robust methodology for predicting leak shape at several leak flow rates within several backfill types, providing a useful tool for water companies to assess leak repair based on leak shape.

One of the most fundamental tasks for robots inspecting water distribution pipes is localization, which allows for autonomous navigation, for faults to be communicated, and for interventions to be instigated. Pose-graph optimization using spatially varying information is used to enable localization within a feature-sparse length of pipe. We present a novel method for improving estimation of a robot’s trajectory using the measured acoustic field, which is applicable to other measurements such as magnetic field sensing. Experimental results show that the use of acoustic information in pose-graph optimization reduces errors by 39% compared to the use of typical pose-graph optimization using landmark features only. High location accuracy is essential to efficiently and effectively target investment to maximise the use of our aging pipe infrastructure.

Although we do not understand the complex behavior of leaks in thick-walled plastic pipes, the ability to model them is essential to the assessment and mitigation of the real losses from drinking water–distribution systems. A methodology was followed whereby numerical and physical experimental data were used to develop a generalized model that quantified both the structural and leak dynamics of longitudinal slits in thick-walled viscoelastic pipes. The dimensionally homogeneous time- and pressure-dependent leakage model was validated using experimental data independent from the physical observations used for the viscoelastic calibration. This was shown to be an effective tool to predict the distinct short- and long-term responses. Such accurate models, which describe the characteristic response of complex leaks, are crucial in improving the understanding of leakage behavior and management.

Laboratory experiments have shown that pipe-wall adhered material can be mobilised by transients, where steady-state hydraulic conditions cannot. This process is critical to managing water quality risks in drinking water distribution systems.