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Water and sand leakage in shield tunnels has become more of a research interest in recent years. On the other hand, accidents involving underground engineering can take many forms and occur often. These accidents pose a risk to people’s lives as well as their property, and it is imperative that studies on underground engineering catastrophes be conducted without delay. In this paper, a technique for indoor model tests for disaster and erosion in shield tunnels is utilized to investigate the process of crater, water, and sand leakage evolution in shield tunnels. The change in water pressure at the leaking joint is inversely proportional to the magnitude of the water input rate, and the change in soil pressure is inversely proportional to the distance from the leakage joint. Both changes occurred in the same direction. Notably, the soil’s initial effective stress was also considered to maintain compatibility with actual engineering works. The preliminary findings suggest that soil-effective stress may cause erosion resulting in the soil arching effect. Tests with one and two leakage spots were carried out using this foundation. Compared to the scenario where two leakage sites are opened simultaneously, it was discovered that opening the two leakage points one after the other might result in a more extensive erosion area of superposition. The double leakage point test results indicate that the point where leakage occurs first causes another leakage point because the erosion area created when two leakage points are opened successively will be larger than the erosion area created when two leakage points are opened simultaneously. When two leakage points under a tunnel are close to each other, the width and depth of the soil erosion groove under the tunnel caused by the two leakage points leaking one after another are significantly larger than those caused by two leakage points leaking simultaneously and are also substantially larger than a single leakage point. After a leakage disaster occurs in the tunnel, the water and soil pressure near the leakage point will continue to decrease. The closer the leakage point, the greater the reduction. Until the leakage erosion converges, the water and soil pressure will tend to stabilize.

Currently, a total of 3.6 billion people live in water-deficient areas, and the population living in water-deficient areas may reach from 4.8 to 5.7 billion by 2050. Despite that, the water distribution system (WDS) loses an average of 35% of its water resources, and the leakage rates may reach even higher values in some regions. The dual pressures of the lack of water resources and severe WDS leakage become even more problematic considering that commonly used leakage detection methods are time-consuming, labour-intensive, and can only detect single-point leakages. For multiple leakage point detection, these methods often perform poorly. To solve the problem of multiple leakage point detection, this paper presents a method for multiple leakage point detection based on a convolutional neural network (CNN). A CNN can forecast the leakages from a macro-perspective. It extracts the features of the collected historical leakage data by constructing a CNN model and predicts whether the real-time data are leakage data or not based on the learning of the features that are extracted from the historical data. The experimental results show that the detection accuracies based on 21 sensors of one, two, and three leakage points are 99.63%, 98.58% and 95.25%, respectively. After the number of sensors is reduced to eight, the leakage detection accuracies of one, two, and three leakage points are 96.43%, 94.88% and 91.56%, respectively.

The article deals with a diagnosis of multiple leaks from liquid transmission pipelines using analytical methods. Such solutions, based on advanced mathematical models of pipeline flow dynamics, usually turn out to be very complex and time-consuming. However, under certain operating conditions, a simpler approach may also be useful. Such an idea is presented in this paper, proposing two simplified methods for diagnosing double leakages. In principle, these methods apply to both simultaneous and non-simultaneous leaks. The first one uses a static model of a pipeline involving two leaks and takes advantage of the minimization of the objective function defined as the squared deviation of the modeled pressures from the pressures measured on the pipeline. The second method uses a pipeline flow model of a static type in combination with a gradient indicator aimed at detecting leaks and employing algorithms assigned to determining the location and size of leaks. The results of methods’ validation, based on tests carried out with the use of measurement data obtained from an experimental water pipeline, were also presented. The outcomes of the performed tests proved the methods’ effectiveness in terms of detection, isolation, localization, and intensity estimation of both simultaneous and non-simultaneous double leakages.

The detection of multiple leakages in pipeline systems has been one of the challenging issues for the control of water loss in water distribution systems. Inverse transient analysis can be a useful principle for predicting leakage through the calibration of location and leakage quantity, based on the pressure reflection that originates from an abnormal boundary condition. In this study, an innovative leakage detection method is proposed to address unknown conditions on multiple leakage dimensions through introduction of revised leakage expressions based on a frequency domain approximation. A multiple leakage function was modified for an efficient representation of multiple abnormalities at a reservoir pipeline valve system. An iterative metaheuristic scheme (IMS) was designed to handle an optimization scheme for multiple leakages using a pressure response for a discharge impulse introduced through value manipulation. In order to address unsteady friction in hydraulic transients combined with multiple leakages, both one-dimensional and two-dimensional models were used to derive leakage expressions for turbulent and laminar flow conditions. An isolated multiple leakage function (IMLF) was proposed to exclusively encapsulate the impact of leakages and unsteady fiction. Considering uncertainties in the hydraulic transient propagation, data noise, and multiple local optima issues in large parameter calibrations, three advanced schemes were modularized to improve detectability of IMS. Several hypothetical examples were presented to show the potential of IMS, validity of three advanced schemes, and robustness in multiple leakage prediction compared to existing approaches.

Leakage is responsible for pressure reduction and water loss in water distribution systems. Approaches for detection of leaks, based on the pressure variation impact from the boundary condition of a leakage point, have been explored to calibrate location and leakage quantity. Even through expression in the frequency domain allows precise description of abnormalities along pipeline systems, existing leakage formulations suffer from complexity in the analytical derivation for multiple leakage conditions. This study proposes an alternative method, the multiple leakage function (MLF), for an efficient multiple leakage representation of a reservoir pipeline valve system in the frequency domain. To address unsteady friction impact on a multiple leakage situation, the MLF was used with one-dimensional and two − dimensional unsteady friction models. Model validation was achieved by comparing impedance frequency responses with those of existing approaches. Strengths associated with the MLF were discussed in terms of model parsimony, computational accuracy, and leak detection capability. Feasibility of the MLF was confirmed for robustness in the leakage implementation sequence and for identification of any single leakage, which is useful in detecting multiple leakages in real systems.

Internal multiples are very difficult to remove due to their complex raypaths and poor velocity discrimination with primaries. The layer-related common focus point (CFP) method has proven to be effective for internal multiple removal, however, single application leads to multiple leakage when there are several strong reflecting boundaries in the subsurface. In order to reduce this leakage, we propose successive application of the layer-related CFP method for internal multiple removal through cascaded processing of several time levels. In this paper, we concisely reformulate the theory of the boundary- and layer-related CFP methods and compare their robustness to velocity errors. For the layer-related version in particular, we illustrate the specific steps of the method using synthetic data examples. Finally, the successive layer-related CFP method is tested on Mississippi Canyon field data.

The natural fire in the mining area is the main source of mine fires, and the distribution of spontaneous combustion “three zones” is a key issue in mine fire prevention and suppression. In order to study the change law of spontaneous combustion “three zones” in the mining area with multiple air leakage paths, a segmented numerical simulation method is proposed. In order to consider the common influence of various factors, we firstly establish the coupled model of oxygen consumption rate of coal relics, the regional fluidity model of the porous medium and the three-dimensional distribution model of void rate in the mining area. Then, based on this, the corresponding conditions of air leakage speed, air leakage location and oxygen concentration are set in each stage of numerical simulation. The mathematical model shows that: the oxygen consumption rate of coal shows an approximate exponential growth trend with the increase in temperature, which is proportional to the original oxygen concentration; the void rate of the mining area shows a logarithmic distribution with a tendency of “double hump” proportional coupling. The numerical simulation results show that: the width of the “oxidation zone” decreases gradually along the tendency when there is only air leakage from the working face; the smaller airflow and lower oxygen concentration in the overlying mining area will increase the width of the “oxidation zone” in the coverage area; air leakage from the shelf road will form an “oxidation zone” near the entrance of the shelf road. The leakage of air from the shelf road will form an “oxidized zone” near the entrance of the shelf road; the leakage of air from the adjacent mining area will increase the width of the overall “dispersal zone” and “oxidized zone” due to the larger air flow and higher oxygen concentration. The comparison with the monitoring data of the downhole bundle tube verifies the rationality of the mathematical model and the accuracy of the numerical simulation results.

The safe operation of hydrogen transmission pipeline stations is paramount for the widespread adoption of hydrogen energy. This study addresses the significant hazard of hydrogen leakage in high-pressure pipeline stations by employing numerical simulations to investigate the dispersion behavior under various conditions. It specifically focuses on the complex interplay between meteorological factors, operational parameters, and station layout. A key finding is that the structural configuration of obstacles—namely their height and distance from the leakage source—serves as the dominant mechanism controlling the evolution of the hazard radius, overshadowing the influence of traditional parameters like wind speed and leak diameter in obstructed environments. Based on this insight, a novel and robust predictive model for the dynamic hazard radius was developed using multiple regression analysis. The model accurately quantifies the impact of leakage duration, obstacle spacing, and obstacle height, achieving an excellent fit (R[sup.2] = 0.9848) with a prediction error of less than 5% compared to simulation data. This study provides valuable insights for defining risk zones and supports the development of effective safety measures and emergency response strategies for hydrogen infrastructure, thereby contributing to the secure and sustainable deployment of hydrogen energy.

Antibiotic resistance against present antibiotics is rising at an alarming rate with need for discovery of advanced methods to treat infections caused by resistant pathogens. Silver nanoparticles are known to exhibit satisfactory antibacterial and antibiofilm activity against different pathogens. In the present study, the AgNPs were synthesized chemically and characterized by UV-Visible spectroscopy, scanning electron microscopy, and X-ray diffraction. Antibacterial activity against MDR K. pneumoniae strains was evaluated by agar diffusion and broth microdilution assay. Cellular protein leakage was determined by the Bradford assay. The effect of AgNPs on production on extracellular polymeric substances was evaluated. Biofilm formation was assessed by tube method qualitatively and quantitatively by the microtiter plate assay. The cytotoxic potential of AgNPs on HeLa cell lines was also determined. AgNPs exhibited an MIC of 62.5 and 125 μg/ml, while their MBC is 250 and 500 μg/ml. The production of extracellular polymeric substance decreased after AgNP treatment while cellular protein leakage increased due to higher rates of cellular membrane disruption by AgNPs. The percentage biofilm inhibition was evaluated to be 64% for K. pneumoniae strain MF953600 and 86% for MF953599 at AgNP concentration of 100 μg/ml. AgNPs were evaluated to be minimally cytotoxic and safe at concentrations of 15-120 μg/ml. The data evaluated by this study provided evidence of AgNPs being safe antibacterial and antibiofilm compounds against MDR K. pneumoniae.

This study addresses the critical issue of mechanical seal failures in nuclear power plant main feedwater pumps through systematic design optimization. A comprehensive multi-objective optimization framework is established, considering leakage, temperature rise, pumping flow rate, and wear rate simultaneously. K-epsilon and FTSI software are utilized to establish computational models, coupled with the NSGA-II algorithm for parameter optimization. The optimized design achieves a 48.6% reduction in leakage while maintaining superior pumping performance. Experimental validation demonstrates the reliability of the proposed domestic mechanical seal design through systematic groove geometry exploration and performance verification tests.