Search Results (173)

Pressurized pipelines are critical components in hydraulic engineering systems, including urban water supply networks and hydroelectric power plants. These systems are susceptible to air entrapment during operations such as filling and emptying, which can reduce the effective flow area and trigger critical pressure surges or sub-atmospheric conditions. One-dimensional approaches, namely the Rigid Water Column (RWC) and Elastic Water Column (EWC) models, are the most widely used due to their balance between physical accuracy and computational practicality. EWC models have been widely used to analyze transient phenomena in pipe filling and water hammer processes; however, their application to emptying operations is limited. For this reason, this study develops an EWC-based formulation for emptying operations and assesses pressure behavior through a dimensionless analysis for different air pocket configurations. The developed model couples the Method of Characteristics (MOC) with a polytropic air pocket model, enabling the representation of wave propagation effects that RWC-based models cannot capture. The formulation is verified against 24 experimental cases, yielding a mean absolute error of 0.35% in minimum pressure prediction. The results show that dimensionless air pocket ratios $x_0/L_T$ between 0.17 and 0.83 produce minimum pressures between 0.309 and 0.877 $p_{atm}^{*}$, confirming that smaller initial air pocket volumes generate the most severe depressurization conditions. The inclusion of an air valve in the most critical scenario effectively prevents sub-atmospheric pressure development, underscoring the protective role of air admission devices. These findings provide a dimensionless framework for characterizing transient pressure risk during pipeline emptying across different operational conditions. Full article

The hydrodynamic and tribological characteristics of a sucker-rod pump valve assembly with a modified seat equipped with a turbulizer are investigated. The study aims to extend service life by controlling the flow structure and reducing contact loads in the ball–seat pair. A combined approach is employed, integrating computational fluid dynamics (CFD) simulations with physical experiments. The results show that an increase in turbulence intensity does not lead to a proportional improvement in performance due to energy dissipation; however, an optimal turbulizer geometry is identified that ensures directed swirl flow and efficient transfer of angular momentum. It is established that the theoretical number of ball rotations in oil is 24 over 5 s, whereas the experiment conducted in water yields 30 rotations over the same period, which is attributed to viscosity effects. An empirical relationship is proposed to describe transitions between the “free flow,” “flow with ball,” and “turbulized flow” regimes, taking into account the rheological properties of the fluid; the validity of the model is confirmed by computational experiments. It is demonstrated that reducing contact forces is a more critical factor than maximizing hydraulic efficiency. Full article

Pressure-reducing valves (PRVs) play a key role in water distribution networks (WDNs), where they are employed to regulate pressure levels and mitigate leakage. The present work describes an experimental study designed to investigate the transient response of a PRV installed at the inlet of a laboratory-scale district metered area (DMA). The closure of a downstream valve along a service line reproduces a typical end-user action and generates a pressure surge propagating through the system. Two distinct operating scenarios were examined, and the analysis of the measured pressure signals offers a basis for discussing the effect of hydraulic transients on the network. Full article

To mitigate the risks of pressure surges and water hammer during accidental pump trips in industrial cooling water systems, accurate boundary modeling of cooling towers is essential. This study employs the Method of Characteristics (MOC) to evaluate four equivalent models for the central riser shaft: Model A (constant level), Model B (two-way surge tank), Model C (dynamic coupling of shaft and distribution channel), and Model D (composite structure). Results indicate that Model A fails to reflect actual hydraulic states, producing an unrealistic pump reverse speed of −253.24 r/min and overly conservative estimates. While Models B, C, and D exhibit similar pressure trends, Model C most accurately captures the physical drainage process, realistically simulating how the shaft level stabilizes at the distribution channel elevation before declining. By accurately reflecting engineering hydraulics, Model C provides the most reliable basis for water hammer safety assessments. It is recommended for optimizing pump valve closure strategies, vacuum breaker installations, and siphon protection designs in power plant systems. Full article

Draining operations using pressurised air can produce sub-atmospheric pressures that pose a significant risk to structural integrity, given the pipe stiffness class. This research presents a modelling strategy for predicting water velocities during the occurrence of this phenomenon. The proposed approach combines a physically based hydraulic formulation with machine learning techniques for making this prediction. A calibrated rigid water column model is first employed to reproduce the transient interaction between the expanding air phase and the draining water column. Input parameters include pipe bridge height varying from 0.5 to 3.0 m, a valve loss dimensionless coefficient ranging from 2.0 to 14.0, and an initial water column length between 163.0 and 286.3 m. Subsequently, a Monte Carlo scheme is used to generate a representative dataset. A total of 28 models were assessed, among which a wide neural network demonstrated superior predictive capability, achieving root-mean-square error values between 0.043 and 0.056 m/s and coefficients of determination ranging from 0.996 to 0.997 for the validation and testing stages, respectively. Sensitivity analyses indicate that the minor loss coefficient governs the water velocity response, whereas geometric features such as the pipe bridge height exert a comparatively minor influence. Full article

Reliable monitoring of hydraulic networks is essential for efficient and sustainable water management in agriculture. To address the growing need for intelligent, low-latency anomaly detection in such systems, we propose HydroNeuro, a domain-aware embedded framework that integrates hydraulic domain knowledge with data-driven neural inference for the real-time detection of leaks and obstructions. Rather than embedding physical equations directly into the learning objective, we leverage established hydraulic principles, including Bernoulli’s equation and the Darcy–Weisbach formulation, to structure the experimental design, interpret pressure–flow relationships, and ensure physical consistency of the learned representations. These principles confirm that pressure deviations induced by leaks or obstructions are causally explainable and measurable. We employ a fractional factorial design (FFD) to optimize valve activation combinations and sensor configurations during dataset acquisition, thereby reducing redundant experiments, water circulation, and energy consumption while limiting mechanical stress on system components. We deploy a lightweight neural network on an ESP32 microcontroller using TensorFlow Lite for Microcontrollers to enable energy-efficient, low-latency edge inference under severe hardware constraints. Our experimental validation on a laboratory-scale hydraulic testbed demonstrates anomaly detection accuracy exceeding 96%, with strong robustness under sensor noise and hydraulic perturbations. Compared to a multiple linear regression baseline, the proposed neural model reduces the prediction error from an RMSE of 0.58 to 0.12. By coupling physically consistent experimental modeling with embedded neural inference, HydroNeuro provides a scalable and practically deployable solution for autonomous hydraulic monitoring in precision irrigation and smart water distribution systems. Full article

Water utilities frequently perform pipeline-emptying operations for maintenance, repair, and operational management. This process involves transient flow conditions with entrapped air. It must be carefully controlled, as the expansion of air pockets can generate sub-atmospheric pressures that may lead to pipeline collapse. The mathematical modelling of emptying processes with air valves has been extensively studied in recent years; however, such approaches typically rely on complex algebraic–differential equation systems. This study advances understanding of this phenomenon by proposing a novel procedure that uses a machine learning model to approximate system behaviour while avoiding fully coupled hydraulic formulations. An experimental facility consisting of a pipeline with an internal diameter of 0.042 m and a total length of 4.6 m was used, in conjunction with a complete regulation valve manoeuvre. The system was first calibrated using experimental data and subsequently employed in Monte Carlo simulations to generate a dataset for training the machine learning model. The results demonstrate that a Rational Quadratic Gaussian Process Regression model can accurately predict the minimum sub-atmospheric pressure, achieving a coefficient of determination greater than 0.999 during validation and testing. The proposed framework is presented as a proof-of-concept and has been validated only for the specific case study analysed. While the results highlight its potential to support planning for emptying operations under varying air-admission conditions and air-pocket sizes, further validation is required before generalising to real-world water distribution systems. For practical implementation, the model must be appropriately trained for each specific installation. Full article

The ongoing evolution of hydraulic modelling software has expanded its application to increasingly complex scenarios, including unsteady-state situations. This study investigates the modelling of a portion of the Water Distribution System in the city of Trieste executed by using a commercial software. The results highlight the software’s ability to capture the dynamic behaviour of the system and provide insights for optimizing pressure control. Full article

Horizontal wells in bottom-water reservoirs are highly susceptible to water coning during production. Consequently, accurately evaluating the water-control performance of inflow control valves (ICVs) is critical for optimizing completion strategies. Conventional semi-analytical models often struggle to capture the transient dynamics of multiphase flow, while standard numerical reservoir simulators fail to explicitly resolve the complex geometries of completion hardware. To address these limitations, this study proposes a multiscale composite modeling framework tailored for bottom-water reservoirs. At the near-well scale, a semi-analytical model is developed to characterize wellbore hydraulics and the pressure drops induced by ICV completions. At the reservoir scale, a numerical model is employed to simulate multiphase fluid transport, with the two scales coupled via cross-scale pressure field mapping. Validation against NETool software under steady-state conditions confirms the physical consistency of the near-well model in determining zonal flow allocation. Comparisons with conventional equivalent well numerical models demonstrate that the proposed composite model offers superior resolution of ICV-induced flow redistribution, yielding distinct production performance profiles. Furthermore, the integration of a Particle Swarm Optimization (PSO) algorithm enables the dynamic optimization of ICV settings. Results indicate that this composite framework provides a robust theoretical and computational basis for designing and evaluating intelligent water-control completions in bottom-water reservoirs. Full article

To address peak edge operation and excessive valve switching in hydraulically coupled multi-zone campus irrigation, this study proposes a collaborative scheduling framework that combines short-term evapotranspiration (ET) forecasting with safety-constrained reinforcement learning. Temperature, relative humidity, and light intensity are used to construct vapor pressure deficit and radiation proxy features, and a lightweight predictor provides two-hour-ahead ET statistics as forward-looking disturbance information. A safety layer composed of Top-2 gating and total flow projection is then used to map policy outputs into a feasible action space under parallel irrigation and total flow constraints. Using seven consecutive days of field data from October 2025, the proposed method reduced total water consumption to 131.04 m³, corresponding to reductions of 9.13% and 6.12% relative to fixed-schedule and hysteresis threshold rotational irrigation, respectively. It also reduced the maximum total flow from 2.00 to 1.60 L/s, lowered valve switching cycles to 12, and reduced the border ratios at 0.90 and 0.95 to 0. Additional ablation, sensing noise/packet loss, and Top-K extension experiments further showed that ET forecasting improves anticipatory scheduling, whereas safety projection is essential for zero-violation operation. These results demonstrate that the proposed framework provides a practical and deployable solution for safe and water-efficient multi-zone irrigation scheduling under shared pump constraints. Full article

Terminal valve closures are the main causes of hydraulic transient pressure in long-distance gravitational water supply pipelines. Therefore, reducing the hydraulic transient pressure in water supply systems through appropriate valve closure strategies is crucial. In this study, a mathematical model for the hydraulic transients contained in gravitational water supply pipelines was established using the method of characteristics for transient flows. On the basis of an actual project, MATLAB 2025b programming was used to calculate the effects of different valve closure strategies on the hydraulic transient pressure in a water supply system under various flow rate operating conditions. The results showed that the appropriate valve closure strategy should be determined according to the high-flow-rate operating conditions of the water supply system. Although extending the valve closure time can significantly reduce the fluctuations exhibited by the hydraulic transient pressure, an excessively long closure time may compromise the control efficiency of the water supply system. Compared with the linear valve closure strategy, the two-stage valve closure strategy produces smaller changes in the hydraulic transient pressure, thus reducing the hydraulic transient pressure fluctuations caused by valve closures to a certain extent. The two-stage valve closure strategy decreases the valve closure time and therefore improves the safety and flexibility of pipeline operations. This study provides a reference for determining the optimal valve closure strategy for terminal valves in similar water supply projects. Full article

Urban water distribution systems often dissipate excess hydraulic energy through pressure-reducing valves to maintain safe operating conditions, particularly in cities with complex topography. This study investigates the potential for sustainable energy recovery using microturbines in a large-scale urban water distribution system, with a focus on the city of Busan, South Korea. A digital twin of the Busan water transmission and distribution network was developed to analyze system-wide hydraulic characteristics, including elevation, hydraulic head, pressure, and flow. Candidate locations for microturbine installation were identified based on existing pressure regulation points and quantified using hydraulic simulation results. The recoverable power and energy potential were estimated by considering flow rate, available head difference, and turbine efficiency, and the model results were validated using operational data and field investigations at selected sites. The results show that significant recoverable energy is concentrated at pressure-reducing valve locations where excess pressure coincides with high flow rates and substantial pressure differentials under representative operating conditions. The maximum recoverable energy at a single site was estimated to be approximately 16.9 MWh/month, indicating that distributed microturbine installations can provide meaningful supplementary energy recovery. The findings demonstrate that digital twin–based analysis offers a systematic and practical approach for identifying energy recovery opportunities in urban water distribution systems and can support more energy-efficient and sustainable water utility operations. Full article

Nowadays, most water meters are mechanical and intended to be installed on pipes completely filled with water. But the pipelines of a water supply network may contain air, which poses a metrological problem: if this air flows through the domestic intakes, it can propel the moving part of the meters, resulting in an overestimation of water consumption. By how much? There is a surprising lack of field data on this topic. So, the case of one house is reported: it is located at the top of a steep and sparsely occupied street, with water typically supplied for a few hours per day. The house’s meter (multi-jet) was estimating a huge and erratic consumption: several times more than what would be normally expected on average, and with some daily peaks exceeding the built storage capacity (underground cistern plus roof tank). After one year of monitoring, including the installation of a few devices, it is concluded that: (1) the house’s meter was affected by air in the water supply network (most likely for different reasons, of which three are discussed); (2) a small air-release valve installed just upstream from the meter did not solve the problem; (3) another mechanical meter (single-jet) installed just downstream was also affected by air (although to a lesser extent), and (4) reliable estimates of water consumption were finally obtained with an ultrasonic meter installed at the domestic intake (and with a mechanical meter installed at the roof tank’s outlet). Thus, the case reported emphasizes the need to study more how air in pipelines affects mechanical water meters and to sometimes consider alternatives for measuring domestic water consumption. Full article

The application of computational simulation in industrial engineering plays a critical role in designing sustainable infrastructure solutions. We applied a hexagonal green pavement system developed through digital simulation to address challenges in urban stormwater management. The system comprises an upper base layer that bears structural loads and a lower support layer designed for water infiltration and drainage. Structural performance was evaluated using SolidWorks simulations under static loads of up to 1100 N. The results indicate that stress values remain within the material’s yield strength, ensuring structural reliability. Hydraulic performance was also assessed using various valve opening scenarios to simulate different rainfall intensities. The system demonstrated effective infiltration capability, with flow retardation coefficients ranging from 0.66 to 0.80. These findings validate the system’s potential to reduce surface runoff and mitigate urban flooding. The study results highlight how digital simulation, as part of a digital twin framework, can support the development of resilient, modular infrastructure for sustainable urban drainage. This approach represents a practical application of industrial engineering computation to advance smart and eco-friendly urban systems. Full article

Urban water distribution networks face increasing challenges related to operational efficiency and demand variability, which require accurate hydraulic modeling and robust calibration frameworks that address data limitations. This study develops and applies a hydraulic simulation model of the water distribution network of the city of Lamia, in Greece. The model represents both the external aqueducts and the internal distribution system of pipelines, storage tanks, pumping stations, and pressure-reducing valves. Hydraulic simulation was performed using a 72 h Extended-Period (EPS) with hourly demand patterns, while calibration/validation were based on SCADA-derived operational data. Several statistical indicators demonstrated strong agreement between observed and simulated values. The results confirm the model’s ability to accurately reproduce real network operation, providing a foundation for Digital Twin implementation, operational optimization, and sustainable urban water management. Full article