Journal of Pipeline Science and Engineering最新文献

{"title":"A decision-making framework for scheduling of multiproduct pipeline under the fair opening","authors":"","doi":"10.1016/j.jpse.2024.100185","DOIUrl":"10.1016/j.jpse.2024.100185","url":null,"abstract":"<div><p>To promote the fair opening of pipeline facilities and improve the utilization efficiency of infrastructure, Chinese government has implemented the pipe network reform by learning from the successful experience of Europe and America. Under the market-oriented mode, the pipe carrier will rationally allocate the transport capacity to third-party customers according to their nominations and formulate a schedule in line with the operational process. Aiming at the new scheduling mode, this study develops a method for detailed scheduling of multiproduct pipelines under the market-oriented mode. The method consists of the sequence-decision model and the scheduling model, covering several operational aspects of real-world pipeline systems, such as multi-source injection, the constraints for contamination volume and the constraints for restart frequency of stations. Data from practical pipelines is adopted as the case study to validate the method. Results show that the proposed framework can improve the satisfaction of shippers to the greatest extent. The delivery satisfaction of each shipper at designated stations all reaches 100 %. The method guarantees the delivery quality of products, decreases the number of operation interruptions. The number of times that operation interruptions occur at stations does not exceed 2 times. To a certain extent, the operating cost of the pipe company will be reduced.</p></div>","PeriodicalId":100824,"journal":{"name":"Journal of Pipeline Science and Engineering","volume":"4 4","pages":"Article 100185"},"PeriodicalIF":4.8,"publicationDate":"2024-03-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S266714332400012X/pdfft?md5=94e65ccfc2cdc3da46ddf8170fc18f8c&pid=1-s2.0-S266714332400012X-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140399961","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Advances in intelligent identification of fiber-optic vibration signals in oil and gas pipelines","authors":"","doi":"10.1016/j.jpse.2024.100184","DOIUrl":"10.1016/j.jpse.2024.100184","url":null,"abstract":"<div><p>Based on the principles and characteristics of distributed fiber optic monitoring technology, this paper introduces the current research progress in identifying fiber optic vibration signals in oil and gas pipelines and summarizes their applications. Fiber optic vibration signal recognition is classified into traditional and intelligent methods. Traditional recognition relies on feature extraction, analyzing intrusion signals in the time, frequency, and time-frequency domains, and employing thresholding for detection. In contrast, intelligent recognition employs big data and artificial intelligence techniques, training on intrusion signal samples to build fiber optic signal analysis models for event classification and threat level assessment over time. The intelligent method, renowned for its high accuracy and adaptability, has emerged as a focal point of research compared to traditional methods. This paper meticulously examines the limitations of intelligent fiber optic vibration signal identification in pipelines and outlines the trajectory of intelligent signal recognition technology. Accelerating the deployment of distributed optical fiber monitoring technology in oil and gas pipelines and enhancing pipeline intelligent monitoring are crucial objectives.</p></div>","PeriodicalId":100824,"journal":{"name":"Journal of Pipeline Science and Engineering","volume":"4 4","pages":"Article 100184"},"PeriodicalIF":4.8,"publicationDate":"2024-03-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2667143324000118/pdfft?md5=885395892db8fe2fe61c79654701a304&pid=1-s2.0-S2667143324000118-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140402766","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Analysis of the influence of girth weld strength matching on pipe deformation mode and failure pattern","authors":"","doi":"10.1016/j.jpse.2024.100183","DOIUrl":"10.1016/j.jpse.2024.100183","url":null,"abstract":"&lt;div&gt;&lt;p&gt;A theory model with two kinds of material, which are used to describe the axis stress strain relationship of the pipe segment and girth weld joints, is proposed for the pipeline axial deformation analysis, and a pipeline deformation diagram is composed for the axis deformation combination within the pipeline design limit. According to the pipeline deformation diagram, it is found that the strength of the pipe segment at the design limit &lt;span&gt;&lt;math&gt;&lt;msubsup&gt;&lt;mi&gt;σ&lt;/mi&gt;&lt;mrow&gt;&lt;mrow&gt;&lt;mi&gt;b&lt;/mi&gt;&lt;/mrow&gt;&lt;/mrow&gt;&lt;mrow&gt;&lt;mi&gt;A&lt;/mi&gt;&lt;/mrow&gt;&lt;/msubsup&gt;&lt;/math&gt;&lt;/span&gt; plays a key role in the strength matching discussion. The pipeline axis deformation could be classified as three categories based on the yield strength &lt;span&gt;&lt;math&gt;&lt;msubsup&gt;&lt;mi&gt;σ&lt;/mi&gt;&lt;mrow&gt;&lt;mrow&gt;&lt;mi&gt;w&lt;/mi&gt;&lt;/mrow&gt;&lt;/mrow&gt;&lt;mrow&gt;&lt;mi&gt;Y&lt;/mi&gt;&lt;/mrow&gt;&lt;/msubsup&gt;&lt;/math&gt;&lt;/span&gt;, ultimate tensile strength &lt;span&gt;&lt;math&gt;&lt;mrow&gt;&lt;msubsup&gt;&lt;mi&gt;σ&lt;/mi&gt;&lt;mrow&gt;&lt;mrow&gt;&lt;mi&gt;w&lt;/mi&gt;&lt;/mrow&gt;&lt;/mrow&gt;&lt;mrow&gt;&lt;mi&gt;crit&lt;/mi&gt;&lt;/mrow&gt;&lt;/msubsup&gt;&lt;mspace&gt;&lt;/mspace&gt;&lt;/mrow&gt;&lt;/math&gt;&lt;/span&gt;of the weld joints and the pipe design strength &lt;span&gt;&lt;math&gt;&lt;msubsup&gt;&lt;mi&gt;σ&lt;/mi&gt;&lt;mrow&gt;&lt;mrow&gt;&lt;mi&gt;b&lt;/mi&gt;&lt;/mrow&gt;&lt;/mrow&gt;&lt;mrow&gt;&lt;mi&gt;A&lt;/mi&gt;&lt;/mrow&gt;&lt;/msubsup&gt;&lt;/math&gt;&lt;/span&gt;, which are &lt;span&gt;&lt;math&gt;&lt;mrow&gt;&lt;msubsup&gt;&lt;mi&gt;σ&lt;/mi&gt;&lt;mrow&gt;&lt;mrow&gt;&lt;mi&gt;w&lt;/mi&gt;&lt;/mrow&gt;&lt;/mrow&gt;&lt;mrow&gt;&lt;mi&gt;Y&lt;/mi&gt;&lt;/mrow&gt;&lt;/msubsup&gt;&lt;mo&gt;&gt;&lt;/mo&gt;&lt;msubsup&gt;&lt;mi&gt;σ&lt;/mi&gt;&lt;mrow&gt;&lt;mrow&gt;&lt;mi&gt;b&lt;/mi&gt;&lt;/mrow&gt;&lt;/mrow&gt;&lt;mrow&gt;&lt;mi&gt;A&lt;/mi&gt;&lt;/mrow&gt;&lt;/msubsup&gt;&lt;/mrow&gt;&lt;/math&gt;&lt;/span&gt;, &lt;span&gt;&lt;math&gt;&lt;mrow&gt;&lt;msubsup&gt;&lt;mi&gt;σ&lt;/mi&gt;&lt;mrow&gt;&lt;mrow&gt;&lt;mi&gt;w&lt;/mi&gt;&lt;/mrow&gt;&lt;/mrow&gt;&lt;mrow&gt;&lt;mi&gt;crit&lt;/mi&gt;&lt;/mrow&gt;&lt;/msubsup&gt;&lt;mo&gt;≥&lt;/mo&gt;&lt;msubsup&gt;&lt;mi&gt;σ&lt;/mi&gt;&lt;mrow&gt;&lt;mrow&gt;&lt;mi&gt;b&lt;/mi&gt;&lt;/mrow&gt;&lt;/mrow&gt;&lt;mrow&gt;&lt;mi&gt;A&lt;/mi&gt;&lt;/mrow&gt;&lt;/msubsup&gt;&lt;mo&gt;≥&lt;/mo&gt;&lt;msubsup&gt;&lt;mi&gt;σ&lt;/mi&gt;&lt;mrow&gt;&lt;mrow&gt;&lt;mi&gt;w&lt;/mi&gt;&lt;/mrow&gt;&lt;/mrow&gt;&lt;mrow&gt;&lt;mi&gt;Y&lt;/mi&gt;&lt;/mrow&gt;&lt;/msubsup&gt;&lt;/mrow&gt;&lt;/math&gt;&lt;/span&gt; and &lt;span&gt;&lt;math&gt;&lt;mrow&gt;&lt;msubsup&gt;&lt;mi&gt;σ&lt;/mi&gt;&lt;mrow&gt;&lt;mrow&gt;&lt;mi&gt;b&lt;/mi&gt;&lt;/mrow&gt;&lt;/mrow&gt;&lt;mrow&gt;&lt;mi&gt;A&lt;/mi&gt;&lt;/mrow&gt;&lt;/msubsup&gt;&lt;mo&gt;&gt;&lt;/mo&gt;&lt;msubsup&gt;&lt;mi&gt;σ&lt;/mi&gt;&lt;mrow&gt;&lt;mrow&gt;&lt;mi&gt;w&lt;/mi&gt;&lt;/mrow&gt;&lt;/mrow&gt;&lt;mrow&gt;&lt;mi&gt;crit&lt;/mi&gt;&lt;/mrow&gt;&lt;/msubsup&gt;&lt;/mrow&gt;&lt;/math&gt;&lt;/span&gt;. For &lt;span&gt;&lt;math&gt;&lt;mrow&gt;&lt;msubsup&gt;&lt;mi&gt;σ&lt;/mi&gt;&lt;mrow&gt;&lt;mrow&gt;&lt;mi&gt;w&lt;/mi&gt;&lt;/mrow&gt;&lt;/mrow&gt;&lt;mrow&gt;&lt;mi&gt;Y&lt;/mi&gt;&lt;/mrow&gt;&lt;/msubsup&gt;&lt;mo&gt;&gt;&lt;/mo&gt;&lt;msubsup&gt;&lt;mi&gt;σ&lt;/mi&gt;&lt;mrow&gt;&lt;mrow&gt;&lt;mi&gt;b&lt;/mi&gt;&lt;/mrow&gt;&lt;/mrow&gt;&lt;mrow&gt;&lt;mi&gt;A&lt;/mi&gt;&lt;/mrow&gt;&lt;/msubsup&gt;&lt;/mrow&gt;&lt;/math&gt;&lt;/span&gt;, the axis plastic deformation will distribute along the pipe segment and this is the ideal states for the pipeline. For &lt;span&gt;&lt;math&gt;&lt;mrow&gt;&lt;msubsup&gt;&lt;mi&gt;σ&lt;/mi&gt;&lt;mrow&gt;&lt;mrow&gt;&lt;mi&gt;b&lt;/mi&gt;&lt;/mrow&gt;&lt;/mrow&gt;&lt;mrow&gt;&lt;mi&gt;A&lt;/mi&gt;&lt;/mrow&gt;&lt;/msubsup&gt;&lt;mo&gt;&gt;&lt;/mo&gt;&lt;msubsup&gt;&lt;mi&gt;σ&lt;/mi&gt;&lt;mrow&gt;&lt;mrow&gt;&lt;mi&gt;w&lt;/mi&gt;&lt;/mrow&gt;&lt;/mrow&gt;&lt;mrow&gt;&lt;mi&gt;crit&lt;/mi&gt;&lt;/mrow&gt;&lt;/msubsup&gt;&lt;/mrow&gt;&lt;/math&gt;&lt;/span&gt;, the girth weld may fail as stress rupture with tensile strain as low as 0.003. For &lt;span&gt;&lt;math&gt;&lt;mrow&gt;&lt;msubsup&gt;&lt;mi&gt;σ&lt;/mi&gt;&lt;mrow&gt;&lt;mrow&gt;&lt;mi&gt;w&lt;/mi&gt;&lt;/mrow&gt;&lt;/mrow&gt;&lt;mrow&gt;&lt;mi&gt;crit&lt;/mi&gt;&lt;/mrow&gt;&lt;/msubsup&gt;&lt;mo&gt;≥&lt;/mo&gt;&lt;msubsup&gt;&lt;mi&gt;σ&lt;/mi&gt;&lt;mrow&gt;&lt;mrow&gt;&lt;mi&gt;b&lt;/mi&gt;&lt;/mrow&gt;&lt;/mrow&gt;&lt;mrow&gt;&lt;mi&gt;A&lt;/mi&gt;&lt;/mrow&gt;&lt;/msubsup&gt;&lt;mo&gt;≥&lt;/mo&gt;&lt;msubsup&gt;&lt;mi&gt;σ&lt;/mi&gt;&lt;mrow&gt;&lt;mrow&gt;&lt;mi&gt;w&lt;/mi&gt;&lt;/mrow&gt;&lt;/mrow&gt;&lt;mrow&gt;&lt;mi&gt;Y&lt;/mi&gt;&lt;/mrow&gt;&lt;/msubsup&gt;&lt;/mrow&gt;&lt;/math&gt;&lt;/span&gt;, the weld joint may endure the ","PeriodicalId":100824,"journal":{"name":"Journal of Pipeline Science and Engineering","volume":"4 3","pages":"Article 100183"},"PeriodicalIF":4.8,"publicationDate":"2024-03-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2667143324000106/pdfft?md5=6b761f5ff3953ff9f5b7e40c5734322e&pid=1-s2.0-S2667143324000106-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140275181","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A novel method for accurate pressure drop prediction in horizontal and near horizontal pipes using adaptive neuro fuzzy inference system based model","authors":"","doi":"10.1016/j.jpse.2024.100182","DOIUrl":"10.1016/j.jpse.2024.100182","url":null,"abstract":"<div><p>Effective flow line and piping network design depends on the accurate prediction of pressure drop in multiphase flow for horizontal and near horizontal pipes. Since early 1950, several empirical correlations and mechanistic models have been developed to predict pressure drop. All correlations used by the industry, in addition to their applicability limitations, fall short of providing the necessary precision of pressure drop predictions. However, compared to empirical correlations, the recently developed mechanistic models improved pressure drop prediction. To design and construct more dependable and economical surface piping networks and wells, it is still necessary to improve prediction accuracy. This study uses the Adaptive Neuro-Fuzzy Inference System (ANFIS) to create a model that predicts pressure drop in horizontal and near-horizontal pipelines with greater accuracy and simplicity. Using the ANFIS method, the fuzzy modelling procedure can gather knowledge about a set of data to determine the membership function parameters that will enable the associated fuzzy inference system to track input/output data most effectively. The model was created and tested using field data encompassing various variables. The model was developed using 450 different data sets that were collected from the Asian continent. 113 data sets were used for testing, and a total of 337 data sets were used for training. Trend analysis was carried out during the model development phase prior to the model’s completion. This is performed to make sure the model is stable and to make sure the created model is physically sound and accurately simulates the real physical process. To determine the percentage of error between the predicted value and the actual measured data, statistical analysis was carried out. To compare the performance of the new ANFIS model to earlier empirical correlations and mechanistic models, graphical and statistical techniques were also used. The new model outperformed known correlations and the most recent mechanistic models by a significant margin in producing incredibly accurate pressure drop predictions. The Dukler et al. empirical correlation, Beggs and Brill empirical correlation, Xiao mechanistic model, and Gomez mechanistic model had values of 25.284, 20.940, 30.122, and 20.817, respectively, while the ANFIS model had a value of 13.256 for the lowest average absolute percentage error. Additionally, the Duckler and Beggs &amp; Brill models came in second and third, with values of 0.908 and 0.906, respectively, and the ANFIS model had the highest coefficient of determination at 0.955.</p></div>","PeriodicalId":100824,"journal":{"name":"Journal of Pipeline Science and Engineering","volume":"4 3","pages":"Article 100182"},"PeriodicalIF":4.8,"publicationDate":"2024-03-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S266714332400009X/pdfft?md5=e947e07ac6c82e9c75493436465d91e9&pid=1-s2.0-S266714332400009X-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140275487","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Dent strain and stress analyses and implications concerning API RP 1183 - Part II: Examples of dent geometry and strain analyses during contact and re-rounding","authors":"Brian Leis ,&nbsp;Amin Eshraghi ,&nbsp;Brian Dew ,&nbsp;Frank Cheng","doi":"10.1016/j.jpse.2024.100173","DOIUrl":"10.1016/j.jpse.2024.100173","url":null,"abstract":"<div><p>API Recommended Practice (RP) 1183 considers three levels of assessment. Its Level 1 and Level 2 processes were considered viable for single peak dents with smooth profiles. The RP deals with more complex dents by way of a Level 3 approach that was reliant on finite element (FE) analysis.</p><p>Part II of this four-part series of papers has identified the assumptions central to the practices of the RP, and evaluated them in regard to fully symmetric dents whose geometry is broadly aligned with those assumptions. Thereafter, it has examined the effects of asymmetry and skew angle benchmarked relative to the symmetric dents. It becomes apparent that even for symmetric dents significant errors emerge in the RP’s practices based on its reliance on dent profiles characterized along their axial and transverse axes cut through the apex, and the effects of the plastic deformation history developed in forming the dent. As for Part I, it was found that the practices of RP 1183 can (1) incorrectly categorize dents, and (2) grossly underestimate dent severity due to asymmetry and skew angles considered acceptable for Level 2 assessment. Error analyses and trending indicated conservative as well as nonconservative errors, with some more than 300%.</p><p>As noted in Part I, Part III will consider cyclic loading of dents, and the viability of the dent stress and fatigue analyses that underlie the API RP 1183 Level 1 and Level 2 assessment practices, whereas Part IV considers the viability of the numerical formulations and modeling that underlie its practices.</p></div>","PeriodicalId":100824,"journal":{"name":"Journal of Pipeline Science and Engineering","volume":"4 1","pages":"Article 100173"},"PeriodicalIF":0.0,"publicationDate":"2024-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2667143324000015/pdfft?md5=4316bb49f31f65d5e2b4c265046df3a1&pid=1-s2.0-S2667143324000015-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139633173","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Estimation of deposit thickness in single-phase liquid flow pipeline using finite volume modelling","authors":"Susovan Pal ,&nbsp;Ranga Reddy Kottam ,&nbsp;Martin F. Lambert ,&nbsp;Prashanth Reddy Hanmaiahgari","doi":"10.1016/j.jpse.2023.100145","DOIUrl":"10.1016/j.jpse.2023.100145","url":null,"abstract":"<div><p>A significant problem with liquid pipelines can be the internal deposition of wax, sediments, tuberculation and biofilms which results in decreased flow assurance of the pipelines and higher pumping costs in addition to safety issues. Therefore, it is very important to monitor the deposits and roughness in the pipelines for the timely restoration of the intended supply. This paper proposes a finite volume model (FVM) based on an implicit flux limiter-Riemann solver (CLAWPACK) to estimate deposit thickness in oil and water pipelines. The novelty of the proposed method is that a snapshot of transient pressures along the pipeline only at a particular time instant (end of simulation) is considered in contrast to the widely used pressure time series for comparison between computed and measured pressures to detect changes in internal diameter and wall friction. The Newton-Raphson Method is used to iteratively estimate the deposition thickness to produce an equivalent response obtained from the pressure measurements of the physical pipeline system. The proposed methodology is applied to three operating crude oil pipelines and the maximum error found between computed and measured pressures and deposit thicknesses are 0.035% and 5 mm respectively. The results indicate that the proposed model is an accurate, efficient, faster and cost-saving alternative to complex invasive type pipeline assessment techniques.</p></div>","PeriodicalId":100824,"journal":{"name":"Journal of Pipeline Science and Engineering","volume":"4 1","pages":"Article 100145"},"PeriodicalIF":0.0,"publicationDate":"2024-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2667143323000379/pdfft?md5=4d695c168bb25f55db5076ce10a87418&pid=1-s2.0-S2667143323000379-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"84881575","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Data-driven model to predict burst pressure in the presence of interacting corrosion pits","authors":"Rioshar Yarveisy ,&nbsp;Faisal Khan ,&nbsp;Rouzbeh Abbassi","doi":"10.1016/j.jpse.2023.100146","DOIUrl":"10.1016/j.jpse.2023.100146","url":null,"abstract":"<div><p>This paper presents a data-driven approach to predict the pipelines’ corrosion-induced Burst failure. In this approach, different aspects of pit growth progression and spatial distribution of pits are simulated. The proposed approach takes advantage of population characteristics to model these aspects of the degradation paths for each pipe section down to the size of single joints. The insights obtained from simulations are used to project the degradation of each pipe section. Understanding corrosion behavior and field data are used to model the corrosion-related parameters such as corrosion pit dimensions, probability and time of initiation, and location. The failure is modeled using the probabilistic simulation considering degradation rate, interactions among pits, and material properties as stochastic variables. The proposed approach and included models are tested using multiple real-life inline inspection datasets. Validation of predicted properties shows prediction errors ranging from 3%–10% depending on the three remaining strength calculation approaches. This work aimed to serve as an important tool for risk-based maintenance prioritization, inspection interval assessment, and the fitness of service assessment of pipelines.</p></div>","PeriodicalId":100824,"journal":{"name":"Journal of Pipeline Science and Engineering","volume":"4 1","pages":"Article 100146"},"PeriodicalIF":0.0,"publicationDate":"2024-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2667143323000380/pdfft?md5=dcdc1753d7da883aff50fae90abef5f8&pid=1-s2.0-S2667143323000380-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"74025558","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Computational fluid dynamics driven mass transfer model for the prediction of CO2 corrosion in pipelines","authors":"Udayraj Thorat,&nbsp;Michael Jones,&nbsp;Richard Woollam,&nbsp;Joshua Owen,&nbsp;Richard Barker,&nbsp;Harvey Thompson,&nbsp;Gregory de Boer","doi":"10.1016/j.jpse.2023.100148","DOIUrl":"10.1016/j.jpse.2023.100148","url":null,"abstract":"<div><p>A novel, computational fluid dynamics (CFD) driven modelling methodology for predicting <span><math><mrow><mrow><mi>C</mi></mrow><msub><mrow><mi>O</mi></mrow><mn>2</mn></msub></mrow></math></span> corrosion rates in pipelines is presented. CFD is used to provide accurate predictions of the viscous sublayer thickness and turbulent diffusivities, which are then used within a mass transfer model of aqueous <span><math><mrow><mi>C</mi><msub><mi>O</mi><mn>2</mn></msub></mrow></math></span> corrosion. Comparisons with experimental measurements of corrosion rate in horizontal pipe flow and corresponding theoretical predictions, based on empirical correlations and previous CFD approaches, show the new approach is more accurate for flows in the range of pH 4 to 6. However, the key advantage of the new approach is its flexibility. Existing models are inaccurate and highly restrictive, having been derived for very simple cases, such as 1 D pipe flow. In contrast, the new methodology provides a firm, scientific foundation for predicting corrosion rates by determining conditions in the viscous sublayer in much more complex, and practically relevant, flow situations.</p></div>","PeriodicalId":100824,"journal":{"name":"Journal of Pipeline Science and Engineering","volume":"4 1","pages":"Article 100148"},"PeriodicalIF":0.0,"publicationDate":"2024-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2667143323000409/pdfft?md5=21b54194463c208186bb44f66e96e081&pid=1-s2.0-S2667143323000409-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135428505","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A numerical study of the slurry erosion in 90° horizontal elbows","authors":"Yijie Wang ,&nbsp;Xin Wang ,&nbsp;Peijuan Shang ,&nbsp;Zhenkang Xu ,&nbsp;Qiyu Huang","doi":"10.1016/j.jpse.2023.100149","DOIUrl":"10.1016/j.jpse.2023.100149","url":null,"abstract":"<div><p>The slurry erosion processes of horizontal elbows are investigated numerically using an Eulerian-Lagrangian method coupled with particle rebound and erosion model. First, a mechanical model for the internal multiphase flow involving slurry erosion in the 90° horizontal elbow is established and the corresponding governing equations are presented. Then, a two-way coupled numerical solution procedure is developed and its accuracy and stability are examined carefully using benchmark pipe flow models with experimental results. Using the validated numerical methods, the effects of flow velocity, fluid density and fluid viscosity on the flow and slurry erosion in the horizontal elbow are analyzed in detail. Finally, a prediction method of erosion rate distribution based on the pipe Froude number, particle Stokes number and the Dean number is proposed. In this method the pipe Froude number is employed to qualify the effect of ununiform distribution of particles, particle Stokes number and Dean number are combined to qualify the effects of inertia force, drag force and secondary flow. Using this approach, the location of the maximum erosion rate in horizontal elbows under different operating conditions can be predicted more conveniently.</p></div>","PeriodicalId":100824,"journal":{"name":"Journal of Pipeline Science and Engineering","volume":"4 1","pages":"Article 100149"},"PeriodicalIF":0.0,"publicationDate":"2024-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2667143323000410/pdfft?md5=8afcc5737659d8fb34c5226bfffc6cc6&pid=1-s2.0-S2667143323000410-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"136117648","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A machine learning regression approach for predicting uplift capacity of buried pipelines in anisotropic clays","authors":"Van Qui Lai ,&nbsp;Khamnoy Kounlavong ,&nbsp;Suraparb Keawsawasvong ,&nbsp;Truong Son Bui ,&nbsp;Ngoc Thi Huynh","doi":"10.1016/j.jpse.2023.100147","DOIUrl":"10.1016/j.jpse.2023.100147","url":null,"abstract":"<div><p>The uplift capacity of pipeline systems in geotechnical engineering is influenced by internal loading and external factors, making it a significant consideration in pipeline design problems. Previous research has conducted experimental tests and numerical solutions to investigate the relationship between force and displacement or the resistance of pipelines in numerous soil media. This paper proposes a machine-learning regression technique to predict the uplift capacity of buried pipelines in anisotropic clays with parametric analysis. Specifically, the Multivariate Adaptive Regression Spline (MARS) is employed to establish the relationship between input parameters, namely the depth ratio (<em>H/D</em>), anisotropic strength ratio (<em>r</em>_e), load inclination (<em>β</em>), overburden factor (<em>γH/S</em>_uc), adhesion factor (<em>α</em>), and the output uplift resistance (<em>N</em>) obtained from the finite element limit analysis (FELA), utilizing the AUS material model integrated with the OptumG2 commercial program. Furthermore, the sensitivity analysis outcome shows the embedded depth ratio is the most critical parameter, followed by the anisotropic strength ratio, overburden factor, load inclination, and adhesion factor. Additionally, the shear velocity field contours show that when the depth ratio and the load inclination increase, the dissipation of shear changes. Design data visualizations, tables, graph contours, and empirical equations are created and can be utilized to aid in the development of practical designs.</p></div>","PeriodicalId":100824,"journal":{"name":"Journal of Pipeline Science and Engineering","volume":"4 1","pages":"Article 100147"},"PeriodicalIF":0.0,"publicationDate":"2024-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2667143323000392/pdfft?md5=07bffd42498dbcf453fa6df57874078f&pid=1-s2.0-S2667143323000392-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135248205","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}