Multiple Leaks Research Articles

Multipoint leak localization for pipelines via acoustic wave amplitude ratio

Pipeline leak localization is significant for maintaining the regular operation of pipelines. This paper proposes a multipoint leak localization method for pipelines via the acoustic wave amplitude ratio, which addresses the issue of the traditional time delay estimation method (TDE) not being able to locate multiple leaks simultaneously. Firstly, a multipoint leak localization method for pipelines is established without time delay estimation and acoustic velocity. This method merely needs to determine the amplitude of the leakage acoustic wave propagating to both ends of the pipeline to achieve leakage localization. Secondly, the improved empirical wavelet transform (IEWT) method denoises the leakage acoustic wave, which can obtain an accurate acoustic amplitude to reduce the localization error. Finally, the trouble that the mutation factor and crossover probability cannot be adaptively selected in the differential evolution (DE) algorithm is improved, and the improved differential evolution (IDE) algorithm is used to solve the objective function to obtain the position of each leakage point. Field experiments show that the multipoint leak localization method proposed in this paper has perfect accuracy, and the minimum localization error is 11 m.

Intracranial findings in spontaneous intracranial hypotension: Does the severity of abnormalities correspond with certainty and/or multifocality of cerebrospinal fluid leaks?

Spontaneous intracranial hypotension (SIH) is caused by spinal cerebrospinal fluid (CSF) leaks. This study assessed whether the certainty and/or multifocality of CSF leaks is associated with the severity of intracranial sequelae of SIH. A retrospective review was completed of patients with suspected SIH that underwent digital subtraction myelogram (DSM) preceded by brain MRI. DSMs were evaluated for the presence or absence of a CSF leak, categorized both as positive/negative/indeterminate and single versus multifocal. Brain MRIs were assessed for intracranial sequelae of SIH based on two probabilistic scoring systems (Dobrocky and Mayo methods). For each system, both an absolute "numerical" score (based on tabulation of findings) and "categorized" score (classification of probability) were tabulated. 174 patients were included; 113 (64.9%) were female, average age 52.0 ± 14.3years. One or more definite leaks were noted in 76 (43.7%) patients; an indeterminate leak was noted in 22 (12.6%) patients. 16 (16.3%) had multiple leaks. There was no significant difference in the severity of intracranial findings between patients with a single versus multiple leaks (p values ranged from .36 to .70 using categorized scores and 0.22-0.99 for numerical scores). Definite leaks were more likely to have both higher categorized intracranial scores (Mayo p = .0008, Dobrocky p = .006) and numerical scores (p = .0002 for Mayo and p = .006 for Dobrocky). Certainty of a CSF leak on diagnostic imaging is associated with severity of intracranial sequelae of SIH, with definite leaks having significantly more intracranial findings than indeterminate leaks. Multifocal leaks do not cause greater intracranial abnormalities.

Online fault detection and localization of multiple oil pipeline leaks using model-based residual generation and friction identification

Online fault detection and localization of multiple oil pipeline leaks using model-based residual generation and friction identification

Numerical Simulation and Environmental Impact Assessment of VOCs Diffusion Based on Multi-Emission Sources in the Natural Gas Purification Plant

The rising number of natural gas purification plants has raised concerns about safety and environmental issues related to VOC (Volatile Organic Compounds) leakage. Therefore, it is crucial to conduct in-depth research on oil vapor emission patterns in these plants. Taking a typical natural gas purification plant as an example, a 1:1 scale model was established. Using methanol as the simulated medium, a study was conducted to investigate the impact of multiple leaks on the dispersion process of VOCs at the plant, combining field sampling with numerical simulation. The results indicate that wind speed influences the concentration of oil vapor, particularly on the leeward side, where vortex and reflux phenomena occur. The area of high concentration of oil vapor at v = 4 m·s−1 is eight times that at v = 8 m·s−1. Gravity and eddy currents contribute to the accumulation of oil vapor, especially closer to the central area of the plant where surrounding buildings obstruct dispersion. Smaller distances between leakage sources result in higher concentrations of oil vapor in the central region, leading to a larger affected area in the event of an accident. The study holds significant practical significance for the research, prevention, and management of leakage and dispersion incidents.

Multi-leakage localization in water supply pipes based on convolutional blind source separation

In acoustic-based methods for water pipeline leak localization, there are few studies on complex multi-leak localization since these sources mix with and affect each other during propagation. In this paper, a novel multi-leak localization method based on the convolutional blind source separation (CBSS) algorithm is proposed, in which the time delays are estimated by the quadrature filter of the demixing matrix or the cross-correlation function between the separated signals and the measured signals, and then the leakage locations are found by linear localization formula. In theory, this paper analyzes the basic principle of the algorithm for locating multiple leaks. In simulation results, the algorithm’s feasibility is verified. In addition, it is obtained that the location distribution of the leakage sources will affect the location of the peak of the delay, and that strong noise will reduce the applicability of the algorithm. In prototype experiments, the algorithm is verified to locate the leaks effectively. This paper is the first to apply CBSS to multi-leakage localization, providing a feasible solution to this complex problem.

Locating Multiple Leaks in Water Distribution Networks Combining Physically Based and Data-Driven Models and High-Performance Computing

Locating Multiple Leaks in Water Distribution Networks Combining Physically Based and Data-Driven Models and High-Performance Computing

Two-Leak Case Diagnosis Based on Static Flow Model for Liquid Transmission Pipelines.

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.

Time-reversal technique for pipeline defect detection.

In this paper, time-reversal (TR) technique is proposed for the detection of discrete defects (e.g., leaks and blockages) in pressurized fluid-filled pipelines using active transient waves. The proposed technique is based on the one-dimensional wave equation and decouples the search for the location from that of the size of the defect. Another key feature of this method is that the measured pressure head signal can be truncated so as to eliminate undesirable reflections from unknown or uncertain parts of the pipe system so as not to compromise the accuracy and robustness of the detection. The proposed method is tested through numerical simulations for a single leak, multiple leaks, and multiple mixed-type of defects (i.e., leaks and blockages) in elastic as well as visco-elastic pipe systems. The proposed method is also validated through laboratory experiments wherein leaks and blockages of various sizes are considered. The sensitivity analysis of the method with respect to wave speed and signal-to-noise ratio (SNR) is also performed. In all cases, the method has shown accurate results in terms of localization, classification, and size estimation of the defects even for SNR as low as 0 dB.

Isotopic characterisation and mobile detection of methane emissions in a heterogeneous UK landscape

Characterising methane (CH4) sources and their stable isotope values at the regional level is important for taking effective mitigation actions as well as more accurately constraining global atmospheric CH4 budgets. We performed dual stable isotope (13C, 2H) analysis of CH4 emission sources as well as mobile 13C measurements in North-West England, in a region with a mix of natural and anthropogenic emission sources as well as potentially exploitable shale gas deposits. Dual isotope analysis was performed for enteric fermentation, animal waste, landfill gas, wetlands, and natural gas from the regional distribution network. Microbial emission sources’ δ13C values ranged from −72.1 ± 0.31‰ to −53.1 ± 1.17‰ with agricultural sources and landfills showing partially overlapping values (−65.3 ± 0.41‰ to −72.1 ± 0.31‰ and −59.2 ± 0.26‰ to −70.4‰, respectively). However, the use of a dual isotope approach with δ2H provided additional separation between agricultural (−340 ± 0.8‰ to −322 ± 19.5‰) and landfill (−312 ± 0.3‰ to −282‰) CH4. All microbial sources were clearly distinct from natural gas with mean values of −39.5 ± 1.38‰ and −184 ± 4.9‰ for δ13C and δ2H, respectively. Mobile measurements conducted over a distance of 557 km detected emissions from two out of four surveyed managed landfills in the region. Multiple gas leaks were detected, which may confound emissions from other thermogenic sources. When separating the surveyed area by land-use into agricultural and urban, we found that background levels of CH4 were more depleted by around 1‰ in areas with agricultural land use compared to urban areas, but emissions from gas leaks and landfills are present in both categories. Our findings highlight the complexity of isoscapes in regions with multiple types of emission sources and the value of dual-isotope measurements in source attribution.

Spontaneous Intracranial Hypotension Due to CSF Leak at Multiple Spinal Levels—A Case Report and Literature Review

Abstract Introduction Spontaneous intracranial hypotension (SIH) is a misdiagnosed condition characterized by low cerebrospinal fluid (CSF) volume and an orthostatic headache that worsens with upright posture due to CSF leak at spinal dural defects. SIH due to CSF leak at multiple spinal levels is a rare condition, and only a few cases have been reported in the literature. Here, we report a case of SIH with a CSF leak at multiple spinal levels. The treatment options and efficacy of epidural blood patch (EBP) injection were discussed in this article. Case Report A 36-year-old man presented with complaints of orthostatic headache for 2 months and a computed tomography myelogram demonstrated CSF leaks at multiple spinal levels through the dural defects at C5-C6, C6-C7, C7-T1, T1-T2 levels, and at L1, L2, L3, and L4 vertebral levels on the left side. He was managed with a targeted EBP injection and he improved symptomatically within 24 hours of the EBP injection. Summary SIH is an entity that results from CSF leakage, often through spinal dural defects due to mechanical tear by osteophyte complex, disc prolapse, connective tissue disorders, CSF-venous fistula, and leaking meningeal diverticula. SIH can result from single or multiple dural leaks, but spinal leaks at multiple levels are uncommon. To the best of our knowledge, a total number of 163 cases have been reported in the literature so far. With good success rates, targeted EBP injection with autologous blood is an effective treatment option for both single-level and multiple-level spinal leaks.

Algorithm for Locating Multiple Leaks in a Pipeline with an Invariance Condition

This paper addresses the problem of multiple leaks’ location in a pipeline by considering available measurements of pressure and flow rate at the ends of the pipeline. New conditions are derived that allow the establishment of a well-posed identification problem for two leaks. These conditions are deduced from the existence of the redundant description of the intermediate flow in the line, the invariance of the conduit's physical parameters with respect to the flow's operating points, and the relationship that links the hydraulic gradients of the respective scenarios of one and two leaks. These joint conditions, which have not been established before, eliminate the assumption of sequential leaks reported in the literature and are the paper's main contribution. Moreover, a minimization algorithm considering these conditions is introduced here. Synthetic data demonstrate the proposed algorithm's effectiveness for five situations.

Linear phase detector for detecting multiple leaks in water pipes

Acoustic signals measured at either side of a leak have been widely used for locating leaks in buried water distribution pipes. Conventional acoustic leak localization techniques (e.g, cross-correlation) may only pick up the strongest leak when multiple leaks exist in the same pipe. In this paper, a new method based on a linear phase detector has been proposed to address this issue for leak detection in water pipes. The linear phase detector utilizes the phase curve between the leak signals measured at two sides of the leaks. It involves an inverse optimization process that optimally identifies linear phase segments in the phase curve. Multiple leaks can be identified by these linear phase segments with different slopes which are correlated with the leak locations. Field investigations have been carried out on a water pipe which is a part of the water distribution system in a busy city area. The field experimental results validated the proposed method with two leaks close to each other being successfully detected.

Symptom: Runny Nose Six Years After Acoustic Neuroma Surgery

Symptom: Runny Nose Six Years After Acoustic Neuroma Surgery

Fast Detection and Localization of Multiple Leaks in Water Distribution Network Jointly Driven by Simulation and Machine Learning

The leakage control in water distribution networks (WDNs) is of high concern in the water supply industry. One direct and effective way to reduce leakage is to adopt leakage detection and localization methods to guide water utilities to repair broken pipes in time. In order to achieve higher accuracy in the leakage detection process in WDN with multiple leaks, a novel multiple leak detection and localization framework (MLDLF) based on existing pressure and flow measurements is proposed. The MLDLF decomposed the problem into three substages: model calibration, leakage identification, and leakage localization. After using the calibrated hydraulic model to predict pressure values and estimate overall leakage flow in each area in the first stage, the data-driven methods, STLK, including the seasonal and trend decomposition using loess (STL decomposition) and the k-means clustering method, were performed in the identification stage to distinguish different leakage scenarios so as to determine the occurrence time of every leakage event. Finally, combined with the stepwise model–based fault diagnosis method, leakages were located gradually with high computational efficiency. A case study of applying MLDLF to the WDN of L-Town showed that 56.52% of the leakage events were successfully identified and located with the economic score reaching €264,873, indicating the robustness and good applicability of MLDLF in identifying and localizing all types of leaks under multiple leakage scenarios.

Neck Pain With Abdominal Distention in a Patient With Systemic Lupus Erythematosus

Question: A 13-year-old boy admitted for systemic lupus erythematosus (SLE) presented mild neck pain, throat pain, and abdominal distention. The SLE was diagnosed 6 months previously, and he received steroid pulse therapy, tacrolimus, and hydroxychloroquine for its treatment. Prolonged steroid therapy was required for his refractory status. Three months previously, he had an episode of right-sided cervical lymphadenitis caused by Staphylococcus aureus. He had no history of trauma. The patient had a good appetite and denied having symptoms such as dyspnea, cough, abdominal pain, nausea, vomiting, diarrhea, and bloody stool. A physical examination revealed right-sided neck pain with mild subcutaneous emphysema. No abnormalities were observed in his throat. Abdominal distention without tenderness was found. Laboratory tests were negative for elevated inflammatory markers, hemoconcentration, and lactic acidosis. Radiography demonstrated linear air leaks in the neck, multiple air leaks along the trachea, free air, and a curvilinear collection of gas within the bowel wall (Figures A and B). Given these physical and radiological findings, what is the most likely diagnosis? See the Gastroenterology website (www.gastrojournal.org) for more information on submitting to Gastro Curbside Consult. Additional contrast computed tomography performed for a possible intestinal perforation found pneumomediastinum (Figures C and D), massive free air in the abdomen, and extensive air accumulation within a thickened bowel wall (Figures E, F, and G). Based on the mild clinical appearance and laboratory findings, pneumatosis cystoides intestinalis and pneumomediastinum without intestinal perforation were diagnosed. Careful observation with oxygen therapy, antibiotic administration, bowel rest, and total parenteral nutrition were begun, and the steroid dosage was gradually reduced. As a result, the patient recovered in 2 weeks without surgical intervention. Based on the clinical course and follow-up radiography and computed tomography findings, we concluded that his condition was idiopathic pneumatosis cystoides intestinalis with pneumomediastinum. Idiopathic pneumatosis cystoides intestinalis is characterized by the presence of gas within the intestinal submucosa or subserosa. The condition may be asymptomatic or present mild, nonspecific clinical manifestations, such as abdominal distention, discomfort, nausea, diarrhea, and anorexia, which may lead to an underdiagnosis of this condition.1Heng Y. Schuffler M.D. Haggitt R.C. et al.Pneumatosis intestinalis: a review.Am J Gastroenterol. 1995; 90: 1747-1758PubMed Google Scholar The risk factors of pneumatosis cystoides intestinalis have not been definitively identified, but prolonged administration of steroids or immunosuppressive agents is thought to be involved in its onset.2Mizoguchi F. Nanki T. Miyasaka N. Pneumatosis cystoides intestinalis following lupus enteritis and peritonitis.Intern Med. 2008; 47: 1267-1271Crossref PubMed Scopus (23) Google Scholar Atrophy of submucosal tissue caused by prolonged steroid therapy may also occur. Gastrointestinal involvement in SLE takes various forms,3Frittoli R.B. Vivaldo J.F. Costallat L.T.L. et al.Gastrointestinal involvement in systemic lupus erythematosus: a systematic review.J Transl Autoimmun. 2021; 4100106Crossref PubMed Scopus (12) Google Scholar making the correct diagnosis particularly important. The clinical presentations of our patient were not caused by complications of SLE because his clinical SLE activity was under control with prednisolone, tacrolimus, and hydroxychloroquine. The fact that reducing the prednisolone dosage did not exacerbate his condition corroborated our diagnosis. We herein described a case of massive pneumatosis cystoides intestinalis with pneumomediastinum accompanied by mild symptoms. Appropriately evaluating the symptoms, even when they are mild, is necessary in patients with prolonged steroid therapy.

Transmission Loss as an Indicator of Multiple Leaks in a Pipeline

Transmission Loss as an Indicator of Multiple Leaks in a Pipeline

Failure Analysis of the Metal Hose Puncture and Leakage in a Natural Gas Reinjection Station

The metal hose in the pump room of an oilfield natural gas reinjection station has multiple punctures and leaks. In order to analyze the reasons for the failures, a macro inspection, hydrostatic pressure and blasting test were carried out on a new hose of the same specification. Phase organization analysis, macro inspection, physical and chemical inspection, scanning electron microscopy (SEM), energy spectrum analysis, metallographic analysis and composition analysis of the conveying medium were carried out on the two failed hoses. The results show that the hydrostatic pressure test of the same batch of the new hoses of this specification meets the requirements of the standard, however the burst pressure does not meet the requirements of the standard. The failure is caused by the welding quality problems at the joint connection, welding defects such as weld bead, incomplete penetration and welding slag. The existence of deformation-induced martensite is found in the metallographic structure of the failed hose corrugated tube. There is tensile stress in the service environment, and a high content of corrosive medium Cl- in the conveying medium. Under the action of internal stress, the internal corrosive medium causes corrugation, the tube undergoes stress corrosion, thus initiating corrosion cracks and propagating along the grain boundaries, leading to the cracks and failure accidents.

Building an Efficient Intrusion Detection System using Feature Selection and Machine Learning

Abstract: With the increase in internet activity and as the world goes digital as the days go, the risk of exposure to malicious activities also increased rapidly. The intruders/hackers use various methods to gain unauthorized access to one's computer or any other device, Network Intrusion is one of the methods by which intruders attack the network of the user, the user can be an individual or an organization based on the intention/agenda of the attackers. Significant Reasons for intrusion are Hacktivism, Steal Money or Data, and Spying. Due to the internet being a vast place, it is challenging to pinpoint a particular way in which Network Intrusion takes place, therefore a Network Intrusion Detection System needs to be put in place in order to deal with the issues regarding Network Intrusions. There are multiple leaks or data extortion that happened previously and, in this paper, the dataset released based on a leak from KDD99 is used. An improved version of KDD99 (NSL-KDD) is used in this study. NSLKDD datasets have been used for training the Machine Learning Model. Given the number of attributes in the dataset, it was difficult to use all attributes so, feature selection methods were used to get the best attributes to develop an efficient Machine Learning model. In this analysis of Machine Learning algorithms, the algorithms under consideration are Logistic Regression, Support Vector Machine, Decision Tree, Random Forest, and Naive-Bayes. For comparison of the performance of the algorithms metrics like Accuracy Score, Confusion Matrix, and Classification Report were considered to find the best algorithm among them.

Regression patterns of central serous chorioretinopathy using en face optical coherence tomography

To study the regression patterns of subretinal fluid (SRF) in central serous chorioretinopathy (CSCR) on sequential en face optical coherence tomography (OCT) and its relationship to leak locations. Retrospective study on patients with acute CSCR. Inclusion criteria were (i) availability of data, sequential OCT and OCT angiography (B scan and en face OCT) every 2 weeks until resolution of SRF or 6 months, whichever is earlier; (ii) single active leak. Exclusion criteria were (i) presence of macular neovascularization or atypical CSCR, (ii) diffuse pigment epitheliopathy, (iii) multiple leaks. Serial en face OCT scans were evaluated and the area of SRF was measured using ImageJ software. Correlation coefficient was calculated for the regression rate of SRF area and central retinal thickness (CRT) over the first month of follow-up and the time of complete SRF resolution. Out of the 25 eyes, 20 eyes demonstrated a centripetal regression, and 5 eyes demonstrated a centrifugal regression. In eyes with a leakage point <1000μ from the fovea, 86% resolved in a centripetal fashion, and in eyes with leak site ≥1000μ away from fovea, 70% eyes resolved centripetally. There was a correlation (r=-0.47, p=0.018) of the rate regression of SRF area during the first month and timing of resolution. In contrast, this correlation was absent (r=-0.16, p=0.44) for CRT regression. Our en face-based analysis of sequential OCTs of regressing CSCR demonstrated a tendency for the subfoveal SRF to resolve towards the end or a centripetal pattern of regression. Prediction of resolution of SRF at 1 month is better with en face area of SRF in comparison to CRT.

Pressure-Leak Duality for Leak Detection and Localization in Water Distribution Systems

Water utilities are challenged to reduce their water losses through detecting, localizing, and repairing leaks as quickly as possible in their aging distribution systems. In this work, we solve this challenging problem by detecting multiple leaks simultaneously in a water distribution network for the Battle of the Leak Detection and Isolation Methods. The performance of leak detection and localization depends on how well the system roughness and demand are calibrated. In addition, existing leaks affect the diagnosis performance unless they are identified and explicitly represented in the model. To circumvent this chicken-and-egg dilemma, we decompose the problem into multiple levels of decision-making (a hierarchical approach) where we iteratively improve the water distribution network model and so are able to solve the multileak diagnosis problem. First, a combination of time series and cluster analysis is used on smart meter data to build patterns for demand models. Second, point and interval estimates of pipe roughnesses are retrieved using least squares to calibrate the hydraulic model, utilizing the demand models from the first step. Finally, the calibrated primal model is transformed into a dual model that intrinsically combines sensor data and network hydraulics. This dual model automatically converts small pressure deviations caused by leaks into sharp and localized signals in the form of virtual leak flows. Analytical derivations of sensitivities with respect to these virtual leak flows are calculated and used to estimate the leakage impulse responses at candidate nodes. Subsequently, we use the dual network to (1) detect the start time of the leaks, and (2) compute the Pearson correlation of pressure residuals, which allows further localization of leaks. This novel dual modeling approach resulted in the highest true-positive rates for leak isolation among all participating teams in the competition.