bluuebunny/crossref_metadata_2025_split huggingface dataset:
Optimal Balancing of ILI Excavations and Integrity Confidence Through Engineering Assessment Methods
Authors: Biagiotti Stephen F. , Bruce Daniel , Neogi Bhaskar , Nidd Phillip G. , Prescott Jonathan 
Published: December 2024

Abstract
This paper demonstrates the utilization of an engineering assessment method to effectively balance the reduction of costly inline inspection (ILI) excavations while maintaining high pipeline integrity confidence levels. Faced with the challenge of frequent and expensive ILI excavations that disrupt operations and inflate maintenance costs, the pipeline industry seeks more efficient and targeted strategies. This study addresses this need by integrating and applying advanced engineering assessment techniques in the context of pipeline maintenance.
The process starts with a critical analysis of the current state of pipeline integrity management, identifying the primary issues related to reliability-based timeliness of ILI-driven excavations in achieving fitness for service. We then delve into a comprehensive review of various engineering assessment methods, including statistical analysis, predictive modeling, and risk-based assessment, highlighting their potential in enhancing decision-making in pipeline maintenance.
The paper uses a case study where various methodologies have been applied, providing empirical evidence of their effectiveness in reducing unnecessary excavations while preserving or enhancing pipeline integrity confidence levels. This case study demonstrates cost savings and operational efficiencies, underscoring the practicality and benefits of these methods.
A notable aspect of these efforts is the examination of the role engineering evaluation plays in processing and interpreting ILI data. These techniques, with their advanced predictive capabilities, offer nuanced insights that support more accurate and sophisticated engineering assessments and long-range planning.
Collapse Testing and Analysis of High Frequency Welded (HFW) Steel Pipes
Authors: Gavriilidis Ilias , Stamou Aris G. , Palagas Christos , Dourdounis Efthimios , Voudouris Nikos , Tazedakis Athanasios , Karamanos Spyros A. 
Published: December 2024

Abstract
Among many factors affecting the collapse limit of pipelines, the line pipe fabrication process has the strongest impact. The present study examines the collapse resistance of pipes fabricated by the High Frequency Welding (HFW) method and focuses on quantifying the effects of heat treatment with respect to the collapse limit of this class of cold formed pipes. The research is carried out for the case of two HFW line pipe specimens with 16 inch outer diameter (Do), 19.1 mm wall thickness (WT) and length equal to 17 times the outer pipe diameter (17Do). One of the HFW pipes has been coated prior to testing (“heat treated” pipe), while the other pipe remained bare (“as fabricated” pipe). Both pipe specimens were subjected to full-scale collapse in a large external pressure testing chamber to determine the collapse pressure and the propagation pressure of both pipes. The full-scale tests are simulated using advanced finite element (FE) tools, considering the actual material properties/geometry of each pipe before full-scale tests. The numerical predictions of the collapse pressure and propagation pressure are in a very good agreement with the experimental ones, while the FE models are also capable to predict the enhanced collapse pressure after coating.
Exploring the Role of Residual Stress in Correlating Yield Strength From Indentation-Based Nondestructive Measurements and Destructive Tensile Testing
Authors: Martin Peter , Brady Emily , Kornuta Jeffrey , Thorsson Solver , Nasouri Reza , Gibbs Jonathan , Veloo Peter 
Published: December 2024

Abstract
Nondestructive determination of the yield strength (YS) for in-ditch materials verification of line pipe is routinely accomplished using indentation methods such as the instrumented indentation test (IIT). While the IIT-predicted YS (YS(IIT)) is generally within ±10 % of the tensile test value (YS(TT)), it occasionally differs by as much as 25 %. This work explores the possible contribution of residual hoop stresses introduced during forming to this aspect of the IIT performance. While in-ditch inspections are rarely informed by prior knowledge of residual stress levels, a better understanding of the potential contribution from manufacturing-induced residual stresses may improve the ability to forecast when measured YS(IIT) values are most likely to accurately reflect benchmark YS(TT) values.
The current work compares results of IIT performed on 20 line pipes and on smaller coupons extracted from those same pipes. The results are interpreted based on the assumption that residual hoop stresses introduced during pipe forming are relieved in the coupons when they are extracted from the larger pipe sections. FEA simulations were performed for two of the pipes to explore the potential effect of residual stress and to guide analysis of the experimental data. The analysis revealed probable contributions from residual tensile hoop stresses in half of the pipes. Additional analyses identified limitations in using the Hollomon power law to model the plastic deformation and predict the yield strength from the indentation process. The results indicate that the Hollomon power law tends to underpredict yield strength in materials where the strain hardening exponent is below approximately 0.130 and overpredict it when it is above approximately 0.180.
Detailed Elastic-Plastic Finite Element Analysis Study to Determine an Optimal Process for Type-B Repair Sleeve Welding
Authors: Holloman Ryan L. , Baxter Samuel J. , Gowardhan Chinmay , Thorwald Greg , Turnquist Michael 
Published: December 2024

Abstract
A typical type-B sleeve consists of two half cylinders fillet-welded to the carrier pipe and joined together with butt welds. The butt welds will not impact the carrier pipe, but the residual stress produced from the fillet weld installation will impact the stability of any existing crack-like flaws in or near the new weld. The orientation and severity of the residual stresses can be reduced depending on the installation method. For instance, the residual stresses may differ if the upstream and downstream fillet welds are installed simultaneously versus sequentially, as simultaneous welding can restrict thermal contraction as the welds cool.
The sequence in which the fillet welds are installed can also impact the orientation and severity of residual stresses. Prior studies have demonstrated that sequential welding and more stopping points can decrease residual stresses. However, it is not clear whether this benefit will effectively offset the increased time needed to execute these procedures. Excess time required in the ditch presents commercial concerns and, more importantly, increased risk to safety and quality. It is increasingly difficult to maintain proper quality control requirements as more time is spent in the ditch. This, in turn, elevates the risk associated with environmental threats such as the formation of hydrogen cracking in the welds due to poor moisture control.
Quest Integrity and Colonial Pipeline executed a study utilizing detailed elastic-plastic finite element analysis to demonstrate if sequentially welding type-B repair sleeve fillet welds is beneficial compared to a simultaneous welding approach. Sleeve lengths of 0.5, 1.0, 2.0, and 4.0 ft were modeled for both sequential and simultaneous approaches. The initial results from this study identified that for longer sleeve lengths, the post-welding residual stresses were nearly identical between the two welding techniques. However, for shorter sleeve lengths, a sequential welding sequence generated lower residual stresses than the simultaneous process.
Additional analysis is in progress to further identify an optimal process for type-B sleeve repair welding to minimize residual stresses while also limiting the amount of time required in the ditch to execute the welding process. This additional work includes quantifying the impact of these welding procedures on the stability of potential crack-like flaws located in the repair welds, as well as the probability of failure associated with these potential flaws.
Assessment of Previously Examined Dent Recoated With Two-Part Epoxy and Later Found With Near Neutral Stress Corrosion Cracking - What Was Missed
Authors: Wu Shanshan , Bratton Joseph P. , Polasik Steven J. , Kemp David , Padgett Barbara N. 
Published: December 2024

Abstract
The pipeline industry continues to strive for improvements in managing mechanical damage and to learn from case studies. A technical case study will be presented for a rock dent from the original construction of the pipeline that was excavated, constraining rock removed, examined, and recoated with two-part epoxy external coating. The recoated dent was subsequently excavated as part of a later dig program and the field non-destructive testing (NDE) discovered the dent had developed external cracking through near-neutral pH stress corrosion cracking (NNpH SCC) while in service.
This paper aims to share the learnings from metallurgical analysis, finite element analysis, and a high-level root cause analysis and will cover the findings and contributing factors that allowed for NNpH SCC to occur on a dent externally coated with two-part epoxy and how a liquid operator is using the findings in its integrity management program when assessing dents.
Multiscale Multidisciplinary Machine Learning Modeling for Pipeline Risk Assessment
Authors: Liu Guanlan , Ayello Francois , Shabarchin Oleg , Langlois-Rahme Gabriel , Lu Dongliang 
Published: December 2024

Abstract
Ensuring the safety and reliability of pipeline systems across diverse components, materials and operating conditions necessitates the integration of information from various fields of expertise. Machine learning can be a powerful tool to analyze multiscale and multidisciplinary data, enhancing our ability to make informed decisions and manage pipeline risks effectively. Also, machine learning technology, when applied to pipeline risk assessment, can be used to organize valuable pipeline information, and uncover hidden correlations. However, machine learning faces challenges like overfitting and identifying false correlations without a real causal impact. Understanding the causes of pipeline failures is essential for taking appropriate actions. Since data can be imperfect with measurement error, a probabilistic risk prediction model is necessary to incorporate uncertainty considerations. This publication uses a previously published Bayesian network model for Stress Corrosion Cracking (SCC) pipeline risk assessment to demonstrate how Bayesian networks can be used to aggregate data at multiscale and from multidisciplinary factors. The model is reviewed with field data to share knowledge with pipeline engineers using machine learning for pipeline risk assessment.
Bank Erosion and Encroachment Model Development to Enhance Pipeline Integrity Management
Authors: Wlodarczyk Kyle , Davidson Sarah , Van Hove Harmen , Song Peter , Porter Dean 
Published: December 2024

Abstract
Bank erosion can expose pipelines at watercourse crossings or in floodplains at encroachment sites. Once a pipeline is exposed, failure can occur due to water loading, debris loading, excessive strain, or vortex-induced vibration (VIV). Empirical engineering formulae have been developed to predict scour depths in rivers and can be used at pipeline watercourse crossings to estimate the annual probability of pipeline exposure from scour. Vulnerability algorithms can then be used to estimate the annual probability of pipeline failure at watercourse crossings, which most commonly results from VIV. However, bank erosion has generally proven to be complex and time-consuming to assess, and it is therefore often considered at the site scale rather than at a screening level in system-wide assessments of hydrotechnical hazards.
This paper describes a novel bank erosion model developed and validated using morphological characteristics and historical aerial imagery from over 240 detailed assessments of pipeline watercourse crossings and encroachment sites across North America. The model predicts the rate of bank erosion based on channel and floodplain morphology, as well as other site characteristics such as debris presence where data exists. Based on these characteristics, as well as the actual rate of observed erosion where possible, a time to pipeline exposure is estimated at watercourse crossings and encroachment sites. The estimated time to pipeline exposure and bank protection type is then used to assign an annual probability of pipeline exposure.
This paper also addresses a gap in the current practice by providing a framework for assessing vulnerability at encroachment sites where flow is parallel or sub-parallel to the pipeline and VIV is unlikely to occur. The probability of pipeline failure at both watercourse crossings and encroachment sites can then be assessed by considering site-specific characteristics, such as the potential free span length, pipe properties, and pipeline operating conditions. As the models use morphological characteristics observable on the ground or in a desktop review and known pipeline data, the results can be used to prioritize actions (e.g., ground inspections or mitigation) at watercourse crossings and encroachment sites and to guide geohazard management strategies to enhance pipeline integrity management.
Getting to the Bottom of the Groove: NDE of SSWC
Authors: Futch David , Newton Christopher 
Published: December 2024

Abstract
Selective seam weld corrosion presents a set of unique circumstances that results in difficulty in accurately determining the groove depth. Classification and measurement of in-the-ditch selective seam weld corrosion (SSWC) has proved difficult due to many factors. On the classification side, lack of fusion (LOF) and SSWC often look similar and distinguishing between the two can prove challenging. Visual difficulties can then result in an incorrect classification which may affect the determined remaining life or repair criteria. On the sizing side, narrow SSWC may prevent sizing by pit gauges and surrounding corrosion may prevent phased array UT from measuring the depth. Surrounding external corrosion creates a difficult surface to land the NDE equipment and tight features prevent the use of hand tools, such as pit gages from reaching the bottom of the groove. Lack of a defined procedure can lead to a varying level of success when inspecting these features. Accurate depth measurements are critical when determining a fitness for service, remaining life, or even the appropriate repair method.
This paper focuses on the main task of a recent Pipeline Research Council International project, PRCI NDE 2-15, whereby the goal was to develop in-the-ditch evaluation methods and necessary tools to address difficulties associated with determining SSWC depth. Through a series of targeted NDE, a specialized NDE procedure was developed to identify external SSWC verses other defects such as lack of fusion or seam trim and measure external SSWC depth and length. In some cases, this NDE procedure combines multiple NDE techniques, each building on each other to determine the grooving depth. Finally, this protocol was validated through metallurgical examination.
This paper provides a first of its kind to provide the pipeline industry with guidance when attempting to inspect and properly classify SSWC. This paper provides the first step to gaining a better understanding of SSWC inspection.
Solving the Non-Linear ILI Sizing Challenge of Crack-Like Flaws With Bayesian Logic
Authors: Krynicki Joseph W. , Skow Jason , Gonzalez Gustavo , Dessein Thomas , Peng Lujian 
Published: December 2024

Abstract
The sizing performance of in-line inspection (ILI) tools are commonly illustrated on unity plots relating the ILI-reported size to a validation measurement, typically a non-destructive evaluation (NDE) field-measured height obtained using techniques expected to be more accurate than the ILI. The comparison of ILI and NDE field measurements is simplified as a linear relationship and tolerance interval. While the slope for a perfectly performing system is 1, it is rarely 1 in practice.
Pipeline operators have continuously strived for better ILI sizing performance to optimize maintenance cost and prioritize repairs. API 1163 has comprehensively addressed sizing performance with the incorporation of Level 3 (Bayesian Approach) that enables pipeline operators to bring new analysis techniques to validate performance, but the linearity of the model still presents challenges because it assumes the performance is consistent across all flaw sizes.
The challenges associated with a linear model are especially problematic for thin-wall pipelines due to height sizing errors. Height tends to be the most influential parameter for the fitness-for-service acceptance criteria of crack-like flaws.
In this paper, a non linear sizing model that uses Bayesian logic is described with the intention of enhancing ILI validation analysis and for future inclusion and interpretation by the API 1163 technical committee. A case study of a population of crack-like flaws is used to illustrate the non-linear sizing performance in ILI results and explain the causes for common sizing errors. While this paper focused on crack-like flaws, the non-linearity of ILI sizing performance is also applicable to metal loss ILI results.
Fault Diagnosis of a Crude Oil Pre-Treatment Systems Based on DOOBNs
Authors: Liu Daqian , Song Shangfei , Shen Siheng , Kang Qi , Li Xiaoping , Gong Jing 
Published: December 2024

Abstract
The crude oil pre-treatment system plays a crucial role in the domain of oil and gas gathering and transportation, serving as a linchpin in ensuring the efficient and secure flow of petroleum resources. Its main function is to process the wellhead production, and complete the dehydration and degassing of the production, bringing it up to the standards required for subsequent processes. The crude oil pre-treatment system is intricate, and its fault could potentially result in significant economic losses and catastrophic consequences. Therefore, the precise and expeditious identification of both the location and the reasons for the occurrence of faults within the crude oil pre-treatment system is of paramount importance. To address this imperative, a fault diagnosis model based on dynamic object-oriented Bayesian networks is designed to conduct fault attribution analysis on the system. The model is mainly composed of the static Bayesian networks and the Markov model. The static Bayesian network consists of Fault Layer, Fault Symptom Layer, and External Variable Layer, used to identify the causes of system faults. The Markov model is employed to determine the temporal evolution of the system’s states. In this study, static Bayesian networks is utilized not only to diagnose individual faults but also to successfully identify the causes of concurrent faults. Then, static Bayesian networks is extended in the time domain by 20 iterations. By inputting fault symptoms into the first static model, predictions of the system’s state are achieved, allowing the time of system maintenance completion to be determined. By inputting fault symptoms into the twentieth static model, a retrospective analysis of the system state is conducted, thereby determining the initiation time of the fault. The research indicates that the model’s results maintain a high level of consistency with on-site fault logs, providing crucial support for on-site production. Furthermore, this also validates the effectiveness, practicality, and accuracy of the model.
Simulation and Optimization of Gathering Pipeline Utilizing Electric Tracing at the Pipeline Center
Authors: Li Zhuochao , Xue Jiaqi , Xu Ning , Yan Fengyuan , Guo Yi , Pan Shiyuan , Liang Yongtu , Xie Zhengfang 
Published: December 2024

Abstract
Electric Tracing Technology at the Pipeline Center is widely used in the development of peripheral oil fields. However, the problems faced include low simulation accuracy, high equipment investment, and high energy consumption for operation. Initially, we analyzed the friction and heating effects caused by the insertion of electric cables into the Pipeline Center. This analysis was based on the laws of mass, momentum, and energy conservation. Consequently, we established a model for calculating the steady-state temperature and pressure of the gathering pipeline, which utilizes electric tracing at the pipeline center. This model enables accurate computation of temperature and pressure along the pipeline at different power. Subsequently, we developed a Mixed Integer Nonlinear Programming model with the objective of minimizing the sum of investment and operational costs. This model considers constraints such as flow balance, hydrothermal performance, power, and the length of the electrical tracing line. It was solved using a genetic algorithm. The solution comprises the design scheme of electric tracing equipment and operational plans, such as the heating method (point heating or electric tracing), heating power, and temperature. This approach achieves the optimization of the electric tracing gathering pipelines (ETGP). Taking a certain oilfield in Northeast China as an example, the simulation model’s calculated results for temperature and pressure are compared with field data, with relative errors all within 10%. The optimization results show a reduction in the length of electric tracing lines by 13.8% and a decrease in total power by 45.7%. By heating the oil to the minimum transportable temperature and then utilizing the electrical tracing technology to maintain this temperature, we minimize energy consumption during transportation.
A Flow State Estimation Framework Based on a Novel Natural Gas Pipeline Network Transient Simulation Method
Authors: Jiao Jianfeng , Xu Hailong , Guo Jing , Yang Baolong , Zhang Yan , Liu Jiyu , Gong Jing , Wen Kai 
Published: December 2024

Abstract
In recent years, the collaboration between natural gas systems and electricity power systems (EPS) has become increasingly close. The frequent and highly random energy flow conversions pose great challenges to the online flow state estimation of natural gas networks. In response to the issues of poor adaptability under transient flow conditions, difficulty in establishing a comprehensive network model, and high time costs in existing flow state estimation models, this study establishes a novel transient flow simulation model for natural gas pipeline networks (NGPN) based on the Box-Jenkins model. The Box-Jenkins model, known for its computational efficiency in parameter identification of dynamic systems in the field of automatic control, is derived for the first time in this study based on the partial differential equations of natural gas flow. A framework for transient flow state estimation is further established, which enables optimal state estimation at instrumented locations based on Kalman filtering. Additionally, the framework can utilize optimal estimation values to modify the transient flow calculation model based on optimization theory. Through verification with actual natural gas networks and commercial simulation software, the proposed transient flow simulation model for natural gas networks is shown to efficiently achieve flow state observation and model modification.