bluuebunny/crossref_metadata_2025_split huggingface dataset:
Fatigue Analysis of Pipe Hammering During Construction
Authors: Chen Roger , Anthony Joseph , Farrow Kenny 
Published: December 2022

Abstract
Pneumatic hammering may be used to assist with pipe installation and/or removal of stuck pipe during horizontal directional drilling and straight bore crossing operations. Pipe stresses induced during hammering are often poorly understood or undocumented.
To gain a better understanding of the induced stresses, elastic wave analyses were performed to simulate stress waves which travel from the struck end of the pipe and back via reflection from the other end. Due to the nature of the reflections, even compressive hammering (e.g., for pullback assist) results in tensile stress waves (and potential fatigue damage), which sometimes goes unrecognized.
To predict the damage accumulation at planar circumferential flaws (e.g., girth weld defects) from repeated hammering, flaw growth analyses were performed via Paris Law fracture mechanics formulations. An initial flaw based on NDE detection limits was grown to the maximum permitted by API 1104 weld quality requirements. This assumes that the hammered pipe will be used within the pipeline construction assembly and must therefore meet initial inspection requirements for screening of in-situ welds.
For this study, different combinations of pipe diameter, wall thickness, pneumatic hammer model, input energy and soil type were investigated to discover trends and determine limits on hammering force and hammering hours. Allowable hours for a particular set of parameters are provided, along with recommendations concerning monitoring of hammering operations, constructability considerations, and future work to refine the methodology presented herein.
Risk-Based Data-Driven Optimization of Pipeline Inspection Interval
Authors: SooTot Josiah , Oviedo Fernando , Zheng Guanbo , Yap Keng 
Published: December 2022

Abstract
In-line inspection (ILI) is a standard industry practice in managing the safety of buried transmission pipelines. It is important to develop a planning strategy for each ILI program to ensure pipeline safety while maintaining cost-efficiency. Defaulting to the maximum inspection interval allowed by regulations without analyzing time-dependent threats affecting a pipeline segment could lead to loss of containment. An optimal inspection interval serves as another barrier in the defense-in-depth safety concept. In this paper, a risk-based data-driven analysis approach is presented to optimize the inspection interval in terms of operational costs while managing the failure risks. The objective function is formulated to consist of cost components (in present value) and weighted residual risk of failure. The cost components are associated with the periodic inline inspections, as well as the expected mitigation actions. The annual mitigation cost is incurred by the number of features that are sentenced for excavation, field inspection, and repair every year according to the risk of failure. A shorter inspection interval would increase the total ILI cost; however, this would also curtail the rising cost of mitigation due to potential feature growth, as well as the residual risk of failure that depends on the mitigation program. The risk of failure is estimated in terms of the probability and consequence of failure. The residual risk is calculated based on features that are either unmitigated or potentially undetected by the in-line inspection tool run. To demonstrate the application of this approach, numerical examples based on external corrosion are provided to show how various conditions of a pipeline segment affect the optimality of inspection interval. The results support further application of the analysis approach in an industrial scale system-wide analysis, such that optimal inspection intervals can be dynamically updated at segment level using the latest ILI data as they become available in an ILI program.
Reliability Analysis of Dented Pipelines in the Absence of Deformation Profiles
Authors: SooTot Josiah , Killeen Katie , Yap Keng , Hassanien Sherif 
Published: December 2022

Abstract
Dents associated with stress risers contribute to pipeline degradation, as they may increase the likelihood of loss-of-containment incidents. The regulatory-based dent and threat integration integrity management utilizes dent depth and potential interaction with stress risers such as crack, corrosion, and/or welds criteria. However, there have been industry incidents that passed such criteria and still resulted in loss of containment. As part of pushing the boundaries of pipeline integrity assessment towards quantitative risk assessment (QRA), a semi-quantitative analysis of dents (SQuAD) had been recently developed; where a strain-based limit state is used to account for pipe properties, dent geometry, and threat integration uncertainties. SQuAD utilizes deformation surface profile reported by caliper in-line inspection (ILI) tools to estimate the radius of dent curvature. Deformation surface profiles are usually provided by the ILI vendors, but it may not be practical to obtain these profiles on all dent features reported across a pipeline system. In the absence of such data, pipeline operators face a challenge in assessing dent severity using the QRA framework. Herein, a practical surrogate model of dent curvature parameters is proposed to enable the use of SQuAD approach without full knowledge of deformation profiles. The surrogate model is a function of ILI reported dent characteristics (i.e., depth, width, and length) and provides a width and length scaling scheme that makes use of dent shape factors. Based on a set of dent cases, the analysis results obtained from SQuAD approach with the surrogate model using several scaling schemes were compared against those obtained from SQuAD approach with ILI-based deformation surface data. It was concluded that with a proper scaling scheme, SQuAD-based surrogate model approach can produce reasonable results with sufficient conservatism compared to the SQuAD-based ILI deformation approach. The proposed approach is suitable for dent integrity screening decision purpose, which would help pipeline operators to assess, rank, and prioritize resources in dent and threat integration integrity management programs.
Probabilistic Corrosion Assessment for Natural Gas Storage Wells
Authors: Ayton Brent , Dessein Thomas , Fraser Alex , Shironishi Mari , Sera Travis , Shapiro Daniel 
Published: December 2022

Abstract
Regulations for gas storage wells require that operators perform initial and subsequent mechanical integrity evaluations as determined using risk assessment [1], incorporated by reference in 49 CFR 192.12 for U.S. operators [2]. As a well ages, metal loss on the casing can grow, increasing the probability of a failure from corrosion. Inspection and repair programs manage this probability by reducing uncertainty in the casing condition and repairing significant metal loss anomalies. However, performing a casing inspection involves a considerable amount of risk, which can vary depending on the well configuration [3]. The benefit of inspection and repair needs to be balanced with the inspection risk to determine the interval that minimizes the overall risk. This paper demonstrates that if detailed information about a well’s configuration, loading, and existing corrosion population is considered, a probabilistic corrosion analysis can be completed to determine a reinspection date that minimizes the overall risk of a release.
A probabilistic implementation of the Level II analysis found in API 579 Fitness-For-Service is described and recommended for these assessments [4]. The deterministic version of this model is the most accurate for predicting burst pressures of casings with metal loss under a wide range of loading conditions [5].
The measurement error of inspection tools and their reporting thresholds relative to typical corrosion rates presents many challenges in calculating corrosion rates deterministically. Calculating unrealistically high growth rates and apparent negative growth rates using inspection data is common. Using the tool measurement error and the distribution of calculated growth rates across several wells, a Bayesian updating approach is described, grouping anomalies in similar environments to develop credible growth rate distributions specific to each joint on a well.
This paper provides several assessments of realistic storage well configurations and corrosion populations to demonstrate how the probabilistic corrosion assessment can determine an inspection interval that minimizes the overall risk and ultimately inform integrity maintenance plans on a well-by-well basis. The examples span a wide range of well conditions to illustrate that the optimal inspection and repair program depends on each well’s configuration, loading, and existing corrosion population. The effect of a corrosion anomaly’s depth in the well and the cement quality on the expected release rate and the resulting risk is also examined.
Engineering Approach for Ductile Fracture Arrest Based on CTOA
Authors: Xu Su , Bassindale C. , Wang X. , Williams B. W. , Tyson W. R. , Guan C. 
Published: December 2022

Abstract
Ductile fracture propagation control and arrest are important elements in fracture control of pipelines transporting natural gas and other high-vapour-pressure media (e.g., dense-phase carbon dioxide). The most familiar crack arrest methodology, the Battelle Two-Curve Method (BTCM), is based on Charpy absorbed energy, and is well known to under-predict requirements for current high-strength high-toughness steels. Adjustments have been made, either by using correction factors or using absorbed energy from the drop-weight tear test (DWTT), but these remain empirical. The crack-tip opening angle (CTOA) has been proposed for a number of years as a fundamental parameter to characterize propagation toughness in aerospace and pipeline applications. It is convenient for finite element (FE) modelling of fracture in full-scale structures such as pipe. However, early procedures to measure pipe CTOA by a “two-specimen” method have been shown to be unreliable. Moreover, previous CTOA models (PFRAC and PICPRO) produced very different results.
Recent work has addressed both shortcomings, including validation of a practical test for determining CTOA of pipe steels (ASTM E3039) and development of reliable FE models for axial crack propagation in pipes. Fracture resistance curves (crack velocity as a function of pressure at constant CTOA) including the effect of backfill have been computed over a wide range of variables. For a given design (pipe geometry, gas pressure and backfill) only tensile properties and CTOA are required to determine conditions for arrest; there are no adjustable constants in the methodology. Results to date are in good agreement with full-scale burst tests (FSBTs) by researchers at TC Energy and at the University of Tokyo, and with Maxey’s original treatment of the effect of backfill on fracture velocity at high pressures.
Learnings From Implementing an API 1173 Compliant Management System
Authors: Potter Dale , Jean Mark S. 
Published: December 2022

Abstract
In July of 2015, the American Petroleum Institute (API) published Recommended Practice (RP) 1173 to provide an industry framework for the development of a Pipeline Safety Management System (PSMS). Regulators and industry companies worked together to develop the RP, providing the basis for enhanced public safety and protection.
Recognizing the inherent benefits to their organization, CHS’ pipelines and terminals division began developing their API RP 1173 compliant management system in February 2016. They were early adopters of this new management system approach and have had several years to not only develop their frameworks, policies, procedures, templates, and tools, but also to implement and ingrain them within their organization. The approach taken was methodic and systematic and focussed on right-sizing their system to match their specific organizational requirements. This supported CHS’ focus on building and applying the right pieces of their system in the right order to build organizational momentum and adoption. Roles and responsibilities throughout the organization were carefully defined to support implementation, administration, and management of the system. The establishment of CHS’ management system not only supported improved safety, but it also helped support the integration and alignment of different pipeline business areas. Throughout CHS’ development and implementation of its management system, key challenges and learnings were identified.
This paper will outline the approach taken by CHS to assess and implement API RP 1173 within their pipeline and terminals division. The paper will outline the specific steps taken, the approach to building their company-specific framework and the learnings that were discovered along their journey. This paper will be of specific interest to those companies that may be in various stages of developing and implementing API RP 1173 within their respective organizations.
Pig Sweep®: Nanoparticles Transform Pipeline Cleaning & Integrity Management
Authors: Clapper Justin , Williamson George , Pearson Kyle , Allred Bud 
Published: December 2022

Abstract
This paper details the evolution of a new and innovative cleaning agent for heavy oil and natural gas pipelines. Information is offered regarding the reason for development and the research involved in formulation of a nanotechnology product. Application details, economic and operational benefits from case histories involved with cleaning two different pipelines, and a preview of a recently developed laboratory testing program is presented.
Oil, gas, and multi-phase pipelines can be fouled with several types of deposits or internally restrictive debris. Common types of foulants and the detrimental effects on pipeline operation are reviewed. A nanotechnology product has shown to be highly effective at removal of a wide variety of foulants. Pig Sweep® provides a nanotechnology-based mechanical cleaning mechanism as opposed to a chemical reaction. The cleaning mechanism and model that potentially protects the pipe wall surface from future deposition or debris collection is reviewed.
The case histories include on-line cleaning of two different pipelines. The first resulted in the removal of more than 41,000 pounds of solids from a 344-mile long, 36″ diameter, dry gas pipeline system. The second case study was performed on a 63-mile, 24″ diameter, dry gas pipeline which resulted in reduced pressure drop, significant operational savings from reduced compression requirements, and significant increased throughput.
Probabilistic Analysis Applied to the Risk of SCC Failure
Authors: Riccardella Scott , Malinowski Owen , Riccardella Pete , Potts Steve , Moran Sean , Thompson Kelly , Reo Ann 
Published: December 2022

Abstract
This paper discusses a model developed and applied to evaluate the probability of Stress Corrosion Cracking (SCC) failure in a large gas pipeline system spanning approximately 8,500 miles. A machine learning algorithm (neural network) was applied to the system, which has experienced nearly 500 prior instances of SCC. Subject matter experts were interviewed to help identify key system factors that contributed to the prevalence of SCC and these factors were incorporated in the neural network algorithm. Key factors such as coating type, vintage, operating stress as a percentage of SMYS, distance to compressor station, and seam type were evaluated in the model for correlation with SCC occurrence. A Bayesian analysis was applied to ensure the model aligned with the prevalence of SCC encountered. A Probabilistic Fracture Mechanics (PFM) model was then applied to relate the probability of SCC existing to the probability of rupture.
Advanced Reliability Analysis at Slope Crossings
Authors: Fowler Matthew , Ndubuaku Kachi , Yoosef-Ghodsi Nader 
Published: December 2022

Abstract
Pipelines cross diverse terrain and as a result are subjected to a variety of geotechnical hazards. Depending on the location of the pipeline relative to a geotechnical threat, it may be subjected to external forces which could lead to pipeline deformation or failure. Generally, geotechnical threats manifest as slope movement, subsidence/settlement, seismic waves, or frost heave/thaw settlement. While similar analysis techniques may have tangential applicability to all these threats, this paper focuses on the landslide/slope movement scenario. Here, the authors present an approach for evaluating pipelines in areas where slope movement is known or has the potential to occur. The methodology uses advanced finite element analysis (FEA) and statistical reliability techniques to estimate the probability of failure (PoF) of the pipeline at a given site. A case study where the method was employed is also presented. The presented process serves as an advanced analysis tool within a geohazard reliability program. This in-depth PoF analysis can be conducted after a screening level assessment has highlighted a given site.
The data required for the analysis includes, at minimum: basic pipe properties, operational information, inertial measurement unit (IMU) in line inspection (ILI) pipeline centerline data, depth of cover survey data, and some estimation of relevant soil to pipe interaction parameters. Other information that can be incorporated to enhance accuracy and reduce conservatism include geotechnical reports and instrumentation measurements (e.g. slope inclinometers or strain gauges). The uncertainties associated with the inputs are estimated based on standards or subject matter expert (SME) input. Incorporating the defined uncertainties, numerical models are created using the commercially available finite element (FE) analysis software ABAQUS, where the pipe is modeled using pipe beam elements and the soil to pipe interactions is modeled using pipe-soil interaction elements. The FE models are processed using a design of experiments (DoE) approach to define response surfaces for both compressive and tensile strain demands. Strain capacities are estimated using the Dorey (U of A) and CRES (PRCI) models for compressive and tensile strains, respectively. Using the resulting relationships for strain demands and capacities, Monte Carlo simulations are completed using the previously defined uncertainties. The simulated cases where strain demand exceeds capacity produce an estimation of probability of exceedance (PoE). Finally, the PoF is obtained by multiplying the PoE by an estimated likelihood of slope movement occurring and impacting the pipe.
Optimizing Operator Systems Through the Use of Flexible Composite Pipe
Authors: Nemeth Alex , Czapski Debra , Alexander Chris 
Published: December 2022

Abstract
Pipelines play a critical role in the world-wide demand for energy. Pipeline operators face ever-increasing challenges in operating high-pressure pipelines, and the need for safely and reliably transporting oil and gas products has never been more demanding in terms of our world-wide aging infrastructure. Global expectations associated with Environmental, Social, and Governance (ESG) criteria present even greater challenges for pipeline operators.
The installation of flexible composite pipe offers an alternative to current integrity management practices such as localized repair methods, as well as more invasive methods such as HDD and pipe replacements. In addition to rehabilitating aging pipelines, flexible composite pipe can be used as a means for repurposing existing infrastructure for transporting and storage of non-conventional products like hydrogen and CO2 for carbon sequestration.
With the aging pipeline infrastructures and the world-wide interest in ESG, flexible composite pipe offers an opportunity as a transformational technology to meet the current and future needs of pipeline operators. It is not uncommon for innovative technologies to experience slow adoption. This is especially true in industries that are capital intensive and regulated, such as the transmission pipeline industry.
This paper looks at the use of flexible composite pipe technology on operator systems, the selection criteria involved in determining where installation would be most advantageous to an operator, and the long-term benefits offered by the installation of flexible composite pipe during a time where the ability to navigate through the energy transition towards a carbon neutral industry is critical. Worldwide demand for energy will continue to increase with growth in population and standards of living. As pipeline operators look to the future, flexible composite pipe is sure to play a critical role in ensuring the continued safe operation of high-pressure pipelines.
A Simple Baseline of Pipeline Data Simulation Algorithm Based on DGM
Authors: Hu Xu , Wang Hengyu , Zhao Hongyang , Liu Gaoling , Wang Di 
Published: December 2022

Abstract
Data is the cornerstone of data science development. This implies the significance of emphasizing information protection found in oil and gas pipeline operating data generated throughout the development of digitalization in relevant companies. Despite of the abundance of sensitive information contained in real data, the availability of open public data sets for professionals in the industry is considerly scarce. This has in turn become the greatest obstacle in producing any forms of research achievements in the industry. At the same time, the sensor deviation leads to a weak reference of the simulation data obtained by the traditional physical formula. Generative deep learning networks are able to directly learn from data and generate high-fidelity as well as diversified samples, allowing them to complete data set generation and information desensitization. This paper presents the application of two deep generative model algorithms, i.e., VAE (Variational Auto-Encoder) and GAN (Generative Adversarial Networks), for pipeline operating data generation. Three main contributions have been made with this approach: (1) Research and release the pipeline operation simulation algorithm generated by the deep generation model based on the big historical data. (2) the algorithms were found to be capable of exporting operating data as a reference for the pumps according to specific pipeline parameters, e.g., pressure corresponding to a certain flow. A data set with the same probability distribution as the actual pipeline operation data could be generated; (3) data-distribution-based detection of abnormalities in pipeline operating conditions using a GAN algorithm identifier was proposed for the very first time. The experimental results presented &lt; 1% mean square error (MSE) between the optimal model and the normalized real data — 0.4% to be more specific, verifying the algorithm’s capability of generating a desensitized data set similar to the real data. Moreover, a classifier trained with the generated data using the GAN algorithm identifier was able to detect as much as 69% abnormal operating conditions, further verifying the effectiveness of the proposed algorithm. Code are publicly available in https://github.com/ShawnHoo7256/BOGC_Project.