Pipeline System Research Articles

A Review on Evaluating the Optimization of Fibre Reinforced Polymer for Compound/Repair Clamp on Leaked Piping System using Computational Simulation

Most industries around world depend on pipelines to transfer millions of gallons of flammable and non-flammable materials. However, this pipeline system has been affected by exposure, which may cause the entire system to fail due to corrosion-based issues. Repair clamps have been used to prevent total failure from happening in a continuous run. However, current design of repair clamp is consisting of metal whereby long usage on corroded pipe could be much more affected. The weight factor will be affecting the fluid flow and the structure of pipe when used in long run. Therefore, in this research, new design for the repair clamp will be done and the material will be change to fibre reinforced polymer (FRP). The new design with FRP will be undergo various stimulation on SolidWorks to compare the properties of clamp and the effect on the affected pipe. Since the FRP material properties has been proven to be more stronger and sustainable compare steel that has been using currently, it will be much more effective to use. As a result, the new design will be much more sustain than the old metal repair clamp. Since the new clamp is lightweight, the weight no longer will affect the corroded pipe internally and externally. Moreover, in this research some of the current repair clamp parts has been reduced and changed to compromise with the usage of the FRP.

Evaluation of rapid gas decompression (RGD) resistance of sealing materials for hydrogen-doped pipeline valves

Abstract With the rapid development of hydrogen-doped natural gas pipelines, the evaluation of the applicability of hydrogen to natural gas pipeline systems is bound to gradually involve all aspects of natural gas pipelines. Targeted at the non-metallic sealing materials for valves of hydrogen-doped natural gas pipelines, this paper, according to the ISO 23936-2 standard, carried out the rapid gas decompression (RGD) tests of hydrogenated nitrile butadiene rubber (HNBR), fluorine rubber 246 (FKM246) and fluorine rubber 26 (FKM26), and the damage level of cracking failure for the rubber materials in the course of rapid release of gaseous medium was obtained (DL). The mechanical properties and volumetric dissolution rate of the three rubber materials were tested before and after the high-pressure gas mixture treatment, which explains the reason for the cracking failure of the rubber materials during the RGD test. The study obtained the influence law of high-pressure gas mixture with different hydrogen volume fractions on the RGD resistance of HNBR, FKM246, and FKM26, and selected the material with the optimal RGD resistance as FKM26, which can be used as a reference for the selection of sealing materials for the valves of hydrogen-doped natural gas pipelines in engineering.

Research on Closing Law of Guide Vane in a Francis turbine during the Load Rejection Process

Abstract It has become a general trend for new energy to be connected to the power grid, and the tasks of peak and frequency regulation undertaken by hydropower units are tough. Inevitably, the Francis turbine operates under a transient process, which brings serious pressure fluctuations and instability problems. In the present study, a three-dimensional simulation of Francis turbines with the water pipeline system during the load rejection process is carried out. Results indicated that when a straight line is used to close guide vanes, the Francis turbine generates significant rotational speed, which poses a threat to system safety and stability. Based on this, the sinusoidal closing law proposed in the present study can effectively reduce the maximum rotational speed by 2.6%. After the end of load rejection, the difference in rotational speed between the two closing laws is 5.15%.

Urban Flood Mitigation Strategies with Coupled Gray–Green Measures: A Case Study in Guangzhou City, China

The integration of gray and green infrastructure has proven to be a feasible approach for managing stormwater in established urban areas. However, evaluating the specific contributions of such coupled strategies is challenging. This study introduced a novel integrated hydrological-hydrodynamic model that takes into account the layout of low-impact development (LID) facilities along with pipeline alignment and rehabilitation. Reliable results from modeling were used to assess the individual contribution of LID and improved drainage facilities to urban flooding mitigation. We selected a natural island in Guangzhou City, China, as the study site. The results indicate that combining three LID measures, namely green roofs, sunken green spaces, and permeable pavements, can reduce total runoff by 41.7% to 25.89% for rainfall recurrence periods ranging from 1 year to 100 years, and decrease the volume of nodal overflow by nearly half during rainfall events of less than 10-year return period. By integrating LID measures with the upgraded gray infrastructure, the regional pipeline overloading condition is substantially alleviated, resulting in a significant improvement in pipeline system resilience. For urban flooding control, it is recommended to integrate sufficient green space and avoid pipe-laying structural issues during urban planning and construction. The findings may assist stakeholders in developing strategies to best utilize gray and green infrastructure in mitigating the negative effects of urban flooding.

Prediction of slug length distribution in horizontal large-diameter gas/liquid pipeline systems

Large-diameter (ID ≥ 0.1524 m) pipeline network systems are widely used in the food industry for grain transportation, in the chemical and nuclear industries for steam/water thermal distribution systems, in the oil and gas industry for crude oil transportation and exploitation, and in urban water supply and drainage systems. Due to the favorable operational and geometrical conditions in surface gas/liquid pipelines, slug flow often prevails, dominating the horizontal and slightly inclined flow pattern map. Formed liquid slugs at large-diameter pipeline entrances and dip can grow, accelerate, and overtake other slugs, resulting in high-momentum and long slugs ranging in length from a few meters to a few hundred meters. The discrepancy of current mechanistic models to predict slug length in large diameter pipes, and the scarcity of large diameter slug length data motivated this work to propose a combined mechanistic and empirical approach to predict full slug length distribution in large diameter surface pipeline systems. A first-principle mechanistic mean slug length model is improved by optimizing its closure relationships using a large-diameter lab and field slug length database. Furthermore, an empirical large-diameter slug length standard deviation dimensionless model is proposed and statistically validated. The proposed mean and standard deviation slug length models are combined to construct a probability distribution and maximum slug length models. Validation of the proposed model revealed an absolute average error of 27% and 31% for the mean and maximum slug lengths, respectively, vastly outperforming all existing models.

The invisible risks of the trans-Ecuadorian oil pipeline system: An analysis of social preferences in Quito

The invisible risks of the trans-Ecuadorian oil pipeline system: An analysis of social preferences in Quito

Nonlinear Augmented Reality Enabled Smart Water Leakage Identification and Infrastructure Management of Pipeline System

Nonlinear Augmented Reality Enabled Smart Water Leakage Identification and Infrastructure Management of Pipeline System

Analyses of gas pulsation characteristics in the discharge pipeline of a hyper compressor

For the analysis of gas pulsation characteristics in the pipeline systems of low density polyethylene (LDPE) hyper compressors, a time-domain calculation method for compressor pipeline gas pulsation based on real gas properties is proposed. First the thermophysical property tables are prepared with gas state parameters as independent and dependent variables. Then one-dimensional unsteady flow equations and characteristic equations for pipeline flow are established based on real gas properties. After setting pipeline parameters and boundary conditions, the flow equations are discretized using a two-step method at the inner points of the pipeline. The characteristic equations are discretized using the trapezoidal integration method at the boundary points. Thus, the time-domain solving of pulsating flow field in the pipeline is realized. A self-developed numerical code was used to conduct the time-domain calculation and analysis of gas pulsation in the discharge pipeline of a two-stage hyper compressor. The calculated pressure pulsation curves based on real gas properties are in good agreement with experimental data, with a maximum difference lower than 4% of the local average pressure, which is smaller than the difference between the results calculated based on the plane wave theory and the measured data. The analysis of gas pulsation characteristics shows that the pressure pulsation in the main pipeline is mainly contributed by the fundamental and second harmonics. The pressure pulsation in the safety valve branch is higher than that in the main pipeline, and the harmonic components falling into the acoustic resonance frequency range of this branch have significant amplitudes. The acoustic resonance frequency of the branch pipeline is not affected by the main pipeline. Pressure pulsation varies with changes in rotational speed and back pressure, and the pulsation level is more significantly affected by rotational speed compared to back pressure. The renovation scheme of connecting the safety valve branch and expansion tube in series can effectively reduce the pressure pulsation levels of the main pipeline and branch pipeline.

Hospital Oxygen Supply Overwhelmed Due to COVID-19: When Demand Exceeds Supply.

During the first wave of COVID-19, we experienced problems with our hospital oxygen supply system. This study aimed to analyze factors that stressed this system and rethink the design criteria of the gas pipeline system considering the varying oxygen demand. A retrospective study was conducted to describe problems that occurred at different stages in the oxygen supply system at our hospital due to increases in oxygen use in general, and the creation of an intermediate respiratory care unit (IRCU) and use of high-flow nasal cannula (HFNC) in particular. Herein, the characteristics and design criteria of the medical gas pipeline system are analyzed, and the steps taken to avoid future problems are outlined. Increases in oxygen use were observed at times of maximum occupancy, and these created vulnerabilities in the oxygen supply due to insufficient capacity in terms of cryogenic tanks, evaporators, and the piping network. The peak consumption was 3 times higher than the peak in the preceding 4 years. The use of HFNC therapy aggravated the problem; IRCU use accounting for as much as two-fifths of the total across the hospital. Steps taken subsequently prevented the recurrence of vulnerabilities. The design criteria for storage and distribution networks of medical gases in hospitals need to be revised considering new parameters for their implementation and the use of HFNC therapy in an IRCU. In particular, the cryogenic tanks, evaporators, and piping network for hospital wards are critical.

Robust Point Cloud Registration for Aircraft Engine Pipeline Systems.

Aircraft engine systems are composed of numerous pipelines. It is crucial to regularly inspect these pipelines to detect any damages or failures that could potentially lead to serious accidents. The inspection process typically involves capturing complete 3D point clouds of the pipelines using 3D scanning techniques from multiple viewpoints. To obtain a complete and accurate representation of the aircraft pipeline system, it is necessary to register and align the individual point clouds acquired from different views. However, the structures of aircraft pipelines often appear similar from different viewpoints, and the scanning process is prone to occlusions, resulting in incomplete point cloud data. The occlusions pose a challenge for existing registration methods, as they can lead to missing or wrong correspondences. To this end, we present a novel registration framework specifically designed for aircraft pipeline scenes. The proposed framework consists of two main steps. First, we extract the point feature structure of the pipeline axis by leveraging the cylindrical characteristics observed between adjacent blocks. Then, we design a new 3D descriptor called PL-PPFs (Point Line-Point Pair Features), which combines information from both the pipeline features and the engine assembly line features within the aircraft pipeline point cloud. By incorporating these relevant features, our descriptor enables accurate identification of the structure of the engine's piping system. Experimental results demonstrate the effectiveness of our approach on aircraft engine pipeline point cloud data.

STONKS: Quasi-real time XMM-Newton transient detection system

Over recent decades, astronomy has entered the era of massive data and real-time surveys. This is improving the study of transient objects -- although they still contain some of the most poorly understood phenomena in astrophysics, as it is inherently more difficult to obtain data to constrain the proposed models. In order to help detect these objects in their brightest state and build synergies with multi-wavelength real-time surveys, we have built a quasi-real time automatic transient detection system for the XMM-Newton pipeline: the Search for Transient Objects in New detections using Known Sources (STONKS) pipeline. STONKS detects long-term X-ray transient events by automatically comparing new XMM-Newton detections to any available archival X-ray data at this position, sending out an alert if the variability between observations (defined as the ratio between the maximum flux and the minimum flux or upper limit) is over 5. This required an initial careful cross-correlation and flux calibration of various X-ray catalogs from different observatories ( XMM-Newton Chandra Swift ROSAT, and eROSITA). A Bayesian framework was put into place to solve any ambiguous associations. We also systematically computed the XMM-Newton upper limits at the position of any X-ray source covered by the XMM-Newton observational footprint, even without any XMM-Newton counterpart. The behavior of STONKS was then tested on all 483 observations performed with imaging mode in 2021. Over the 2021 testing run, STONKS provided a daily alert rate of 0.7$^ $ alerts per day, about 80<!PCT!> of them corresponding to serendipitous sources. Among the detected variable serendipitous sources, there are: several highly variable active galactic nuclei (AGNs) and flaring stars, as well as new X-ray binary and ultra-luminous X-ray source candidates, some of which are present here. STONKS also detected targeted tidal disruption events, ensuring its ability to detect other serendipitous events. As a byproduct of our method, the archival multi-instrument catalog contains about one million X-ray sources, with 15<!PCT!> of them involving several catalogs and 60<!PCT!> of them having XMM-Newton (pointed or slew) upper limits. STONKS demonstrates a great potential for revealing future serendipitous transient X-ray sources, providing the community with the ability to follow-up on these objects a few days after their detection with the goal of obtaining a better understanding of their nature. The underlying multi-instrument archival X-ray catalog will be made available to the community and kept up to date with future X-ray data releases.

Assessment of transboundary environmental damage to the Baltic sea basin during construction and operation of the offshore pipeline system

Assessment of transboundary environmental damage to the Baltic sea basin during construction and operation of the offshore pipeline system

Hybrid quantum physics-informed neural networks for simulating computational fluid dynamics in complex shapes

Finding the distribution of the velocities and pressures of a fluid by solving the Navier–Stokes equations is a principal task in the chemical, energy, and pharmaceutical industries, as well as in mechanical engineering and in design of pipeline systems. With existing solvers, such as OpenFOAM and Ansys, simulations of fluid dynamics in intricate geometries are computationally expensive and require re-simulation whenever the geometric parameters or the initial and boundary conditions are altered. Physics-informed neural networks (PINNs) are a promising tool for simulating fluid flows in complex geometries, as they can adapt to changes in the geometry and mesh definitions, allowing for generalization across fluid parameters and transfer learning across different shapes. We present a hybrid quantum PINN (HQPINN) that simulates laminar fluid flow in 3D Y-shaped mixers. Our approach combines the expressive power of a quantum model with the flexibility of a PINN, resulting in a 21% higher accuracy compared to a purely classical neural network. Our findings highlight the potential of machine learning approaches, and in particular HQPINN, for complex shape optimization tasks in computational fluid dynamics. By improving the accuracy of fluid simulations in complex geometries, our research using hybrid quantum models contributes to the development of more efficient and reliable fluid dynamics solvers.

Three-layer and robust planning models to evaluate the strategies of defense layer, attack layer, and operation layer for optimal protection in natural gas pipeline network

Using game theory techniques, a three-layer planning model (THLPM) for the defense, attack, and operational layers has been established to address malicious damage to pipelines. A robust planning model was developed for situations with uncertain attack resources. In this model, the defense layer protects critical infrastructure within the network to minimize losses. The attack layer targets unprotected facilities based on the defensive strategy. The operational layer formulates the optimal pipeline transmission strategy based on the decisions of the defense and attack layers. By utilizing the duality theorem, the THLPM is transformed into a two-layer planning problem, which is then linearized and solved using a decomposition algorithm. Taking a specific ring-shaped pipeline network as an example, the study analyzes the significant role of backup pipelines in enhancing system resilience and evaluates the offensive and defensive strategies of THLPM. The effectiveness of THLPM in protecting the network was assessed, showing that when defense and attack resources are invested at levels 3 and 10, respectively, operational costs of the network are reduced by 54.2 % compared to a scenario without any defenses. The methods proposed in this paper are applicable to other pipeline systems.

Morphological Characteristics of Propane–Hydrogen Diffusion Flame: Experiments and Correlations

ABSTRACT This study investigated the flame height and liftoff height of turbulent diffusion jet flames of the Propane–Hydrogen mixed gas. A series of experiments have been conducted to examine their flame height and liftoff height with different concentrations of propane and hydrogen. The experimental results show that the flame height decreases with the increase in hydrogen concentration. The accuracy of the Froude number for the prediction of flame height has been verified. The liftoff height is proportional to the propane flow rate, while it was inversely proportional to the hydrogen concentration due to the increased laminar flame speed. A theoretical model incorporating laminar flame speed, heat release rate, and fuel exit velocity has been obtained. These investigations are crucial for enhancing safety in hydrogen-enriched pipeline systems, which is helpful for the use of hydrogen in energy systems and global sustainability efforts.

Vibroacoustic modeling of a compressor piping system

The paper presents a finite element model of the compressor piping, developed in the Ansys software package using the APDL language. The finite element model was developed taking into account the real conditions of fastening pipeline sections in the form of installed supports. The calculation of the pipeline system began with the calculation of flow pulsations generated by the compressor, which were converted into pressure pulsations. The calculation results in the form of pipe vibration amplitude were obtained for each piping pipeline. The results obtained were compared with the vibration parameters recommended by GOST 32569-2013.

Comparative study on the performance of butt fusion-welding processes for nuclear safety class large-diameter thick-walled PE pipes

New technologies in polymer synthesis and pipe extrusion equipment have led to the commercialization of high-performance, large-diameter, thick-wall high density polyethylene (HDPE) pipes. They have been used in the field of seawater transport and cooling to replace metal pipes, due to their advantages of high corrosion resistance and extensibility. Connection of HDPE pipe is important as it determines the safety of the entire piping system. Butt fusion welding is commonly used for HDPE pipe connection but may cause the formation of weak points in the welded joints, interfering the reliability of the pipeline system in the application of nuclear power plants. At present, there is a lack of research on evaluating the performance of welded joint for large-diameter thick-wall HDPE pipes made by butt fusion-welding. The purpose of this study is to investigate the influence of three different butt fusion-welding processes, i.e., single low pressure (SLP), single high pressure (SHP) and dual low pressure (DLP), by evaluating the performance of their welded joints, including characterizing tensile strength, extensibility, crystallinity and hardness. In specific, a thick-wall HDPE pipe with OD of 812.8 mm and wall thickness of 74 mm which is certified for nuclear safety class was used for study. Representative specimen from the outer, middle and inner part across the wall of the main pipe body and welded joints were taken for testing. Different test methods and specimens were designed to assess the feasibility of evaluating the welding performance from different welding process. The results showed that the mechanical properties of different locations of the welded joints were different, and the tensile strength and fracture energy of the middle part of the joint were lower than that of the inner and outer parts, which could be caused by the difference in the crystallinity and thickness of the melting zone influenced by welding processes, as can be seen from the analysis of DSC test and morphology observation. Hardness testing was conducted on the section of the welded joints, and it revealed that the micromechanical properties of the welded joints in the region of the heat-affected zone were enhanced significantly, which may be due to the annealing effect caused by welding process. In summary, The DLP process resulted in the best extensibility of the welded joints among three processes, suggesting that the joining pressure from welding process plays an important role in affecting the extensibility of the welded joints.

Transitioning to a Hydrogen Economy: Exploring the Viability of Adapting Natural Gas Pipelines for Hydrogen Transport through a Case Study on Compression vs. Looping

The growing importance of hydrogen as an energy carrier in a future decarbonised energy system has led to a surge in its production plans. However, the development of infrastructure for hydrogen delivery, particularly in the hard-to-abate sectors, remains a significant challenge. While constructing new pipelines entails substantial investment, repurposing existing pipelines offers a cost-effective approach to jump-starting hydrogen networks. Many European countries and, more recently, other regions are exploring the possibility of utilising their current pipeline infrastructure for hydrogen transport. Despite the recent efforts to enhance the understanding of pipeline compatibility and integrity for hydrogen transportation, including issues such as embrittlement, blend ratios, safety concerns, compressor optimisation, and corrosion in distribution networks, there has been limited or no focus on pipeline expansion options to address the low-energy density of hydrogen blends and associated costs. This study, therefore, aims to explore expansion options for existing natural gas high-pressure pipelines through additional compression or looping. It seeks to analyse the corresponding cost implications to achieve an affordable and sustainable hydrogen economy by investigating the utilisation of existing natural gas pipeline infrastructure for hydrogen transportation as a cost-saving measure. It explores two expansion strategies, namely pipeline looping (also known as pipeline reinforcement) and compression, for repurposing a segment of a 342 km × 36 inch existing pipeline, from the Escravos–Lagos gas pipeline system (ELPS) in Nigeria, for hydrogen transport. Employing the Promax® process simulator tool, the study assesses compliance with the API RP 14E and ASME B31.12 standards for hydrogen and hydrogen–methane blends. Both expansion strategies demonstrate acceptable velocity and pressure drop characteristics for hydrogen blends of up to 40%. Additionally, the increase in hydrogen content leads to heightened compression power requirements until approximately 80% hydrogen in the blends for compression and a corresponding extension in looping length until around 80% hydrogen in the blend for looping. Moreover, the compression option is more economically viable for all investigated proportions of hydrogen blends for the PS1–PS5 segment of the Escravos–Lagos gas pipeline case study. The percentage price differentials between the two expansion strategies reach as high as 495% for a 20% hydrogen proportion in the blend. This study offers valuable insights into the technical and economic implications of repurposing existing natural gas infrastructure for hydrogen transportation.

Selection of optimal intensity measures for seismic performance evaluation of underground utility tunnel and internal pipeline system

Seismic intensity measures (IMs), which are closely related to both earthquake hazards and structural responses, play a critical role in the performance-based earthquake engineering (PBEE) framework. This paper aims to investigate and define the most representative IMs for probabilistic seismic demand model (PSDM) for the longitudinal utility tunnel and internal pipeline system. Similar to the requirements by the Chinese Code for seismic design of urban rail transit structures, the utility tunnel in this study is assumed being buried in four typical engineering site classes for the analyses. Soil-tunnel-pipeline interactions are simulated using a double-beam system resting on a nonlinear foundation. Soil-tunnel interaction, tunnel-pipeline interaction and joint connections are modeled as nonlinear springs with different mechanical properties. A series of 17 pairs of outcrop ground-motion records and 27 commonly used IMs are selected in the analyses. Engineering demand parameter (EDP) is defined based on the maximum joint opening and the maximum strain of the utility tunnel and internal pipeline, respectively. The selected IMs for predicting the seismic responses of tunnel-pipeline systems are tested using different criteria, i.e., correction, efficiency, practicality, and proficiency. The final decision-making procedure employs a fuzzy multi-criteria decision method. The numerical results indicate that: (1) The velocity-related IMs are the most representative IMs based on the four criteria for structures buried in four sites of different conditions; (2) The optimal seismic IMs vary with different criteria, site classes and structure types. According to the fuzzy multi-criteria decision approach, optimal IMs for the tunnel-pipeline system are PGV, PGV, EPV and HI for site classes I – IV, respectively. The proposed optimal IMs can be utilized to construct seismic fragility curves of utility tunnel, internal pipeline and tunnel-pipeline systems in four different site classes.

Interpretable machine learning models for failure cause prediction in imbalanced oil pipeline data

Pipelines are critical arteries in the oil and gas industry and require massive capital investment to safely construct networks that transport hydrocarbons across diverse environments. However, these pipeline systems are prone to integrity failure, which results in significant economic losses and environmental damage. Accurate prediction of pipeline failure events using historical oil pipeline accident data enables asset managers to plan sufficient maintenance, rehabilitation, and repair activities to prevent catastrophic failures. However, learning the complex interdependencies between pipeline attributes and rare failure events presents several analytical challenges. This study proposes a novel machine learning (ML) framework to accurately predict pipeline failure causes on highly class-imbalanced data compiled by the United States Pipeline and Hazardous Materials Safety Administration. Natural language processing techniques were leveraged to extract informative features from unstructured text data. Furthermore, class imbalance in the dataset was addressed via oversampling and intrinsic cost-sensitive learning (CSL) strategies adapted for the multi-class case. Nine machine and deep learning architectures were benchmarked, with LightGBM demonstrating superior performance. The integration of CSL yielded an 86% F1 score and a 0.82 Cohen kappa score, significantly advancing prior research. This study leveraged a comprehensive Shapley Additive explanation analysis to interpret the predictions from the LightGBM algorithm, revealing the key factors driving failure probabilities. Leveraging sentiment analysis allowed the models to capture a richer, more multifaceted representation of the textual data. This study developed a novel CSL approach that integrates domain knowledge regarding the varying cost impacts of misclassifying different failure types into ML models. This research demonstrated an effective fusion of text insights from inspection reports with structured pipeline data that enhances model interpretability. The resulting AI modeling framework generated data-driven predictions of the causes of failure that could enable transportation agencies with actionable insights. These insights enable tailored preventative maintenance decisions to proactively mitigate emerging pipeline failures.