bluuebunny/crossref_metadata_2025 huggingface dataset:
Energy Consumption Prediction Method of Oilfield Gathering System Based on Multi-Level Covariates
Authors: Liu Jiaquan , Hou Lei , Zhang Xinru , Zhu Zuoliang , Wang Mincong , Wang Wenjun
Published: December 2024

The oilfield gathering system converts electric energy and chemical energy from fuel into kinetic energy and thermal energy from fluids through rotating equipment and the heat exchanger, which is the main part of the energy consumption of the oilfield. To control the increase in energy consumption, it is necessary to predict the energy consumption in the future of the system. With the advancement of oilfield digitalization, data-driven intelligent prediction methods have received widespread attention due to their ability to effectively extract hidden features from energy consumption data. The data are analyzed to generate multiple covariates, including data from multiple pipeline network nodes and data from the union plant. The energy consumption prediction method based on multi-level covariates is proposed. Aiming at gas consumption prediction in an oilfield union plant, multivariable features are extracted from multi-level historical and future covariates by the recurrent neural network. The experimental results of actual production data show that the gas consumption in the gathering system can be predicted accurately. The proposed method can make full use of the collected multivariable data to achieve energy consumption prediction, which is helpful for oilfield staff to take pre-stage measures to achieve energy consumption reduction.
Quantifying Corrosion Patterns: A Study of Corrosion Clustering Around Elevation Valleys With a Large Inline Inspection Dataset
Authors: Fadic Anton , Murray Michael
Published: December 2024

Elevation valleys are suspected to play a role in pipeline corrosion. One proposed mechanism is water and solids accumulation at these valley locations, which play a role in combination with other variables such as flowrate and pipe geometry, among others. From our literature review no studies have been published that show the relationship between valley locations and corrosion anomalies using real world inspection data at large scale. This topic has been researched rather indirectly, typically by the study of water accumulation in simulated settings, using two immiscible fluids of different densities, frequently using a combination of some sort of oil and water. These studies are not designed to analyze corrosion effects on the pipe, limiting their ability to predict and quantify where corrosion is more likely to occur, which is a critical aspect of pipeline maintenance.

In this paper we examine corrosion clustering around valley locations using inline inspection (ILI) data originated from operating pipelines, which supports the causality path of corrosion assisted by water accumulation at valley locations. We quantify statistically significant excess corrosion count density (CCD) for each assessment by comparing elevation valleys to non-valley locations and to local elevation maxima (peaks). A permutation method gives the likelihood of randomly observing the valley corrosion density at non-valley locations. We studied 1,083 ILI assessments of 557 pipeline systems, totaling 28,067 assessment miles, and 11,834 miles of independent systems transporting crude oil. A strong association between elevation valleys and significant excess corrosion density was demonstrated in several pipeline systems. Peaks did not show a statistically significant correlation. For assessments with over 100 corrosion counts, the corrosion density was found to be up to 18 times higher at valleys than the rest of the assessed system, and 44% of the systems had at least one assessment that presented a significant pattern of corrosion clustering around valleys.

The stability of the generated signal was studied over time for systems with multiple assessments, confirming the consistency of the results. The consistency of this metric applied to a large dataset justifies its use as an indicator of anomalous internal corrosion in a system, potentially helping pipeline operators to identify systems that are or may soon be affected by excess internal corrosion.
Risk Modeling for Rupture Mitigation Valve
Authors: Woll Alex , Liu Guanlan , Zhang Zhuoran
Published: December 2024

Per PHMSAs recent additions to 192.935 (c), if an operator determines that a Rupture Mitigation Valve (RMV) would be an efficient means of adding protection to their High Consequence Areas (HCAs) then they must install them. In order to determine if an RMV would be an efficient means of adding HCA protection, a risk analysis approach must be devised which considers the impacts of installing additional RMVs. RMV installation can improve both failure response time and valve spacing, both of which have an impact on the total time that a rupture with ignition can be sustained.

PHMSAs definition of Potential Impact Radius (PIR) in 192.903 is associated with a sustained heat flux for a thirty second timeframe which results in a one percent likelihood of mortality. Because the PHMSA defined PIR has a fixed timeframe of concern and an RMV installation can impact the time that a rupture with ignition is maintained, in order to assess the impacts of an RMV, we cannot rely upon PHMSA PIR definition for this analysis. Instead, a correlation between heat flux over time (heat dosage) and distance with the likelihood of mortality and building ignition need be established to assess the impacts of RMV installation on reducing consequences associated with a sustained rupture with ignition. In developing that correlation, an operator can then evaluate if the installation of an RMV would be an efficient means of protecting their HCAs.

An RMV risk modeling tool was developed to help operators minimize the consequences of a pipeline incident surrounding their HCAs. This presentation will cover the flow modeling approach, heat flux calculations, approximation of the transient state, and consequence modeling included in our RMV approach. This model supports operators in selecting optimal RMV spacing and locations surrounding their HCAs to most effectively protect public safety.
HyTap-In-Service Welding: Tapping and Stoppling of a 66 Bar (950 Psi) Hydrogen Line
Authors: Huising Otto Jan , Stordeur David , Vrolyk Chris
Published: December 2024

HyTap is a collaborative project undertaken by N.V. Nederlandse Gasunie and T.D. Williamson aimed at establishing safe working methods for in-service welding, hot tapping, and stoppling on hydrogen lines. The project involved a comprehensive analysis of materials and work methods to assess the implications of transitioning from natural gas to hydrogen. Based on these analyses, adapted methods were employed to conduct a full-scale experiment on a DN 500 (20″) 7.8 mm (0.307″) pipe. Throughout the operations, the pipe was pressurized with hydrogen at 99.5% purity and pressures ranging from 60 to 66 bar (870 to 957 psi). Equipment compatibility with hydrogen was carefully evaluated, leading to the use of sour service plugging heads for the isolation operation, while all other equipment remained consistent with natural gas conditions. Welding procedures were adjusted to limit the inside wall temperature to 700°C (1292°F). Of paramount importance was the inerting procedure, ensuring the absence of any explosive atmosphere at any stage of the operation, which proved to have the most significant impact. The HyTap experiment, conducted with these adaptations, successfully demonstrated that, with modifications to existing natural gas procedures, hydrogen lines can be welded, hot tapped, and isolated while in service.
Usage of Isotropic Hardening Model Enhanced by Power Law in Simulation of Pipe Material
Authors: Behseta Khosrow , Agbo Sylvester , Adeeb Samer
Published: December 2024

Analysis of in-service pressure vessels, pressurized components, and buried pipelines made from carbon steels with high tensile properties and a narrow range between their ultimate stress and yield stress are subject to crack-like flaws. Analysis of these structures requires consideration of various mechanical loads and environmental factors such as temperature, internal pressure, soil pressure, and ground movement. These structures often are subject to design features that can generate or enlarge stress concentrations or deformation over time, potentially resulting in failure. Current standards and assessment procedures offer methodologies for evaluating structural integrity and addressing flaws. The finite element method (FEM) is a powerful tool used for analyzing these structures, but its capability to predict fracture onset, especially in ductile and brittle materials, remains limited. To overcome these limitations, the extended finite element method (XFEM) has been developed, allowing for more accurate modelling of crack propagation and interaction with the surrounding material. However, widespread adoption is hindered by challenges in obtaining experimentally verified material properties tailored for XFEM analysis. This study aims to enhance traditional plasticity models and employ XFEM coupled with the cohesive zone model (CZM) to accurately simulate fracture criteria, providing a promising approach for evaluating flaw behaviour in pipeline steel specimens with different geometric configurations.

Force-displacement data were obtained from previous experimental and numerical investigations of pipeline materials using X65 material with round and flat specimens. We integrated various specimen geometries into the Abaqus program with dimensions identical to the published data. Symmetry was utilized whenever appropriate to reduce computational time.

Our results indicate that the isotropic hardening model can replicate the force-displacement behaviour of a variety of specimens with various groove radii, up to a particular strain limit, which is dependent on the specimen geometry and stress state. Beyond this limit, the simulations deviate from experimental observations. However, by enhancing the material data through the power law, a higher limit can be obtained. Furthermore, we demonstrate that through the established plasticity platform and by using XFEM-CZM, the necking section can be modelled correctly without the need for damage mechanics models, providing a verification base for the XFEM-CZM methodology.
Determination of Safe Excavation Pressure During Hoe Ramming Activities
Authors: Saunders Joe , Jobin Mathew , SanJuan Riverol Elvis , Chune Ron , Zhang Ken , Milligan Ryan
Published: December 2024

Hoe-ramming is a form of rock excavation, often used when an excavation area is too large for a jackhammer, or where blasting is not possible. A percussion hammer fitted to an excavator is used to break up and remove rock from the area surrounding a pipeline. During integrity excavations, hoe ramming is typically used to remove rock around in-service natural gas pipelines to allow for access to complete integrity assessment activities. To determine safe operating pressure of the pipeline, currently, a conservative approach is used that usually yields significant pressure reduction that may be unnecessarily required. Reductions in operating pressure to achieve safe excavation pressure can have impacts to typical pipeline operation. Opportunity exists to gain a greater understanding of the loading on the pipeline to allow for a more accurate safe excavation pressure recommendation.

In this study, a full-scale testing and dynamic finite element analysis (FEA) were used to quantify the effects of hoe ramming activities to natural gas pipelines. Testing was completed in December 2022 at the Pipeline Research Council International’s (PRCI) Technology Development Center in Houston, Texas. The test included NPS 24 × 6.35mm NWT, Grade 359 test pipe. Some of the variables controlled during the testing were proximity of hoe ramming to the test pipe, internal pressure (hydro) of test pipe, and configuration of the granite block and test pipe. Two configurations of granite blocks were subject to hoe ramming while in contact with the pipe were tested: including, I) Test pipe on top of two granite blocks, and ii) test pipe on side of one granite block. Accelerometers and strain gauges were instrumented on both granite blocks and the test pipe. Temperature, test pipe acceleration, test pipe strain, and internal pressure data were collected while the granite blocks were subject to hoe ramming. The data was processed and analyzed to quantify the effects to the test pipe during hoe ramming effects on the pipe.

When reviewing stress levels because of hoe ramming, both testing and the dynamic FEA supported that there was no detrimental effect to the test pipe. Further dependencies such as proximity of hoe ramming to the pipeline and internal pressure were also investigated. The test results were used to validate the FEA model of the tested configurations, which can subsequently expand to parametrical models to cover additional scenarios and understand the influence of critical variables. Outcomes of this study include development a pressure-equivalent method to determine safe operating pressure during hoe ramming activities. Details of the testing and assessment are summarized in this paper.
Methods Selection for Natural Gas Pipeline Patrolling Operation Using Technical and Economic Decision
Authors: Tansiriyakul Chavalit , Yanpirat Patcharaporn , Supapa Sansanee , Yindee Chatri
Published: December 2024

Natural gas is a source of clean energy and is the main fuel used for generating electricity in Thailand. Natural gas is transported from production to end users through pipeline systems. Therefore, pipeline patrolling and inspection is extremely important for maintaining pipeline integrity. This paper describes a case study incorporating a proposed framework for making decisions concerning selection of patrolling methods in terms of technical and capital investment criteria. For technical context, multiple criteria decision analysis (combining Voting Analytic Hierarchy Process (VAHP) and Fuzzy Analytic Hierarchy Process (FAHP)) is implemented to determine importance weights of selected expert and performance criteria respectively. For ranking patrolling methods, Fuzzy Technique of Order Preference Similarity to the Ideal Solution (FTOPSIS) is employed. In the context of capital investment evaluation of the patrolling methods, the equivalence uniform annual worth is used for ranking. A sensitivity analysis is also conducted by varying the importance weights of the technical performance criteria. Regarding technical and capital investment contexts, the results reveal that increasing patrolling frequency through outsourcing is the most suitable method for performing natural gas pipeline patrolling.
Best Practices in Geohazard Data Management
Authors: Theriault Bailey , Johnson Clayton , Brooks Justin , Taylor Justin , Mckenzie-Johnson Alex
Published: December 2024

In 2023, the Interstate Natural Gas Association of America Foundation (INGAA) sponsored a Joint Industry Project to develop and publish two documents: 1) Framework for Geohazard Management and 2) Recommended Practice for Pipeline Integrity Management of Landslide Hazards. Both papers identify data management as a key component to a successful pipeline Geohazards Management Program (GMP). This paper expands upon the INGAA publications to provide a more comprehensive overview of geohazard data management best practices, examples of the importance of data management in a GMP, and additional guidance on key components and methods.

The importance of data management in the success of a GMP can often be overlooked or undervalued. Data are central to the outcomes of a GMP in that they provide the basis for nearly all decision-making. Data help Operators determine where threats are located, the nature of the threats, the types of responses that are warranted, and whether additional data are needed. Unnecessary risks and uncertainty develop where data are not properly or consistently compiled or filed, resulting in potential for misunderstanding and mismanagement of threats, over- or under-responding to threats, or costly or unnecessary work.

Data pertaining to geohazard management are generated and collected throughout the life cycle of a pipeline, from a variety of sources and in a variety of formats, which can present challenges to development and maintenance of comprehensive repositories for relevant data. However, it is imperative that critical data are not only maintained, but also organized such that they can be rapidly accessed and analyzed when needed, for either emergent local concerns or for a system-wide review and assessment.

A variety of approaches and platforms are available and used by Operators to manage data. Platform and technology choices are typically driven by available resources such as internal and external hardware, software, and personnel. There are numerous configurations that can accomplish critical key objectives, including: publicly available software to proprietary solutions; local to cloud-based data storage; and small to large internal and/or external teams of data managers, data generators, and data users. This paper does not seek to provide a specific roadmap to data management. Instead, it seeks to layout the core components of data management that are essential for a GMP and to define the objectives of each.

An example of an ideal baseline data management system will be presented, based on real-world Operator systems.
Knowledge-Informed Semi-Supervised Robust Modeling for Mixed Oil Length Prediction in Multi-Product Pipelines Based on Student’s-T Mixture Model
Authors: Yuan Ziyun , Chen Lei , Liu Gang , Li Zukui , Zhang Yuhan
Published: December 2024

Multi-product pipelines usually transport various petroleum products in certain batch, leading to inevitable mixed oil segment. Current soft sensor modeling methods for predicting mixed oil length face challenges characterized by nonlinearity, scarcity of labeled samples and interference from outliers. We propose a semi-supervised robust soft sensor called the KISSVBSMR. It employs the Semi-supervised Variational Bayesian Student’s-t mixture regression to empower the usage of unlabeled data, and it strategically selects the key variable based on physical significance to enhance mode identification. Additionally, by transforming the relationship between input and output variables derived from theoretical equation and incorporating a Bayesian approach, the KISSVBSMR can explore the prior knowledge regarding the regression coefficient and efficiently against outliers. Evaluation through numerical and real-life industrial datasets reveals the shortcomings of traditional methods and the superiority of KISSVBSMR in model performance. This novel approach improves the predictive accuracy of mixed oil lengths, optimizing multi-product pipeline operations and advancing knowledge-data hybrid modeling techniques.
A Neural Network-Enhanced Finite Difference Approach for Strain Demand Prediction of Inelastic Pipes Subjected to Ground Displacement
Authors: Ji Beilei , Zheng Qian , Mei Qipei , Yoosef-Ghodsi Nader , Adeeb Samer
Published: December 2024

Permanent ground displacement induced by geohazards poses a significant threat to the integrity of pipelines due to the potential for excessive strain. Accurately predicting strain demand is critical for guiding the design of new pipelines and assessing the risks associated with existing ones crossing geohazard zones. Previously, a finite difference approach for strain demand prediction in pipes subjected to permanent ground displacement was developed by the authors. It has been proven to be a simple and valuable technique for practical use in the pipeline industry, compared with conservative empirical formulas and time-consuming finite element modeling. However, the existing method relies on explicit expressions for axial force and bending moment, derived under the assumption of a bilinear stress-strain curve for the material, which restricts its applicability when dealing with more complex constitutive models that require numerical integration. To remedy this situation, a novel approach that models constitutive law using deep neural networks is proposed, serving as an alternative means for capturing stress-strain relationship. This novel approach is integrated into the finite difference scheme to overcome the constraints of the original method, thereby enhancing its applicability. A comprehensive case study was conducted to evaluate the effectiveness of the proposed neural network-enhanced finite difference approach in comparison to the original method. Results from this study demonstrated that the proposed method can achieve comparable accuracy to the original finite difference method when dealing with small ground displacements. The finding indicates the potential advantages of the proposed method in efficiently handling more complex constitutive relations, which will be explored in future work.
Construction Pipe Settlement: Causes and Mitigations
Authors: Phillips Ryan , Martens Michael , Thompson Shawn , Barrett John
Published: December 2024

With pipelines, as with any new construction some settlement of the foundation is expected. An allowance is made during design for pipe settlement associated with trenching and backfilling construction activities. However, additional unexplained settlements can occur and become problematic, potentially overstressing a pipeline. These issues are exaggerated at pipeline facilities. An evaluation of current construction guidelines and practices along with additional case study and literature reviews was utilized to determine potential factors contributing to this settlement. Several factors were identified, revolving primarily around trench movements and backfilling quality. Various factors can contribute to trench movements, including elastic and consolidation movements of the surrounding soil due to overburden removal, trench wall movements due to frost heave or water entry while the trench is open. The pattern and magnitude of these movements will depend on soil types, trench support and trench geometry. Winter construction can create frost heaving in both the trench base and walls, followed by settlements during thawing. While consolidation of trench soils due to the increased loading from the new pipeline is considered, the combined result of this swelling is often not accounted for in design. Beyond this, the backfill and its handling can alter the settlement response during and immediately post construction. Controlled granular backfills, compacted with near optimum water contents may provide the highest level of predictability post construction, but will still settle under water wetting. Controlling backfill quality, material, water contents and compaction assurance, and trench swelling prior to pipeline construction, may provide the best path to controlled, predictable and quantifiable pipeline construction settlements. More economic pipeline designs will result if pipeline movements due to external effects can be reduced.
Assessing Likelihood of Failure for Unpigged Pipelines Using Supervised Machine Learning
Authors: Xiang Wei , Tayyab Hassan , Lu Dongliang , Dooley Colin , Lucut Sergiu
Published: December 2024

System-wide risk assessment is an integral process for quantitatively evaluating the risk levels of pipeline segments. This involves utilizing the best available information, including inline inspection (ILI) data, survey data, pipeline attributes, historical mitigation information and environmental properties pertinent to the integrity threats. The assessed risk provides the basis for planning mitigation activities, and ensuring that the risk level is maintained at an acceptable level. Estimation of likelihood of failure (LOF) is a crucial component of the risk assessment, which is subsequently combined with the consequence of that failure to assess risk. In the absence of ILI data, the LOF for unpigged pipelines were often estimated using conventional statistical models. These models delineate the relationship between historical failure rates and the factors influencing the occurrence or prevention of integrity threats. While such traditional regression models offer the advantage of interpretability, they are constrained in capturing the intricate nonlinear relationship between the LOF and pertinent variables. Additionally, they lack the flexibility to characterize the complex interactions among multiple predictor variables.

To improve the accuracy of LOF assessment for unpigged pipeline segments exposed to external corrosion, this paper introduces a multi-layer model that was developed using supervised machine learning techniques and structural reliability method. The model consists of three layers. In the initial layer, a series of machine learning models are employed to predict key statistics that characterize the corrosion severity of the pipeline segments. These machine learning models were trained and validated using pigged pipeline segments, with ILI data considered as the ground truth for the corrosion severity. The predictor variables utilized by the model include pipeline attributes, factors contributing to corrosion, factors resisting corrosion, and survey data (e.g., DCVG). In the second layer, the previously predicted corrosion states serve as the input for probabilistic corrosion assessment models, facilitating the evaluation of the probability of leak (POL) and probability of burst failure (POF) through Monte Carlo simulation. In the final layer, the assessed POL and POF are aggregated into the LOF.

This paper describes the framework of the multi-layer model, outlines the data requirement for model development, and illustrates the process of model calibration and validation. Furthermore, practical considerations in the model development are discussed, ensuring the general alignment between model predictions and engineering judgements. The enhanced LOF accuracy will enable the operators to make more cost-effective mitigation decisions for unpigged pipelines based on the results of risk assessments.
Opportunities and Challenges in Repurposing Canadian Natural Gas Transmission Pipelines for Hydrogen Service – A Regulatory, Standards, and Technical Exploration
Authors: Dinata Randy , Finneran Shane
Published: December 2024

In decarbonizing Canada’s energy systems, utilizing hydrogen as a low-carbon fuel is growing in interest, and repurposing in-service natural gas transmission pipelines to transport large volumes of hydrogen can be a key solution.

Existing intraprovincial natural gas transmission pipelines, such as those in Alberta, can be potential candidates for conversion into hydrogen service in Canada due to factors like steel grades used, pipe hoop stresses, and year of construction. However, all pipelines intended for conversion into hydrogen service must undergo an engineering assessment as outlined in the CSA Z662 to ensure the integrity of the pipeline system and safe operations. While challenges for such conversion exist, discussed in this study, such as high pipe hoop stresses in long-distance interprovincial natural gas transmission pipelines, high specified minimum yield strength, and unavailability of required pipe data, when mitigated, the engineering assessment may determine the pipelines are fit-for-service for hydrogen. This applies not only to line pipe but also to other existing components within the pipeline system that will be exposed to hydrogen, such as gas compressors, meters, fittings, valves, and flanges.
Evaluation of Fracture Toughness of Welded Line Pipe Steels for Hydrogen Gas Transportation Based on ASME B31.12 and Alternative Test Method Development
Authors: Seo Eun Jung , Bag Amrita , Gaudet Michael J. , Chen Shaojie , Lehnhoff Greg , Rashid Muhammad , Arafin Muhammad
Published: December 2024

A high-strength line pipe steel grade, namely API X65, has been developed and qualified for its use under pressurized hydrogen gas following the ASME B31.12 code. The bolt-load compact specimens taken from the base metal, heat-affected zone, and weld seam of the electric resistance welded (ERW) pipes were tested using a constant displacement method in 100% hydrogen at pressure up to 13.8 MPa (2000 psi) for 1000 hours. All fracture toughness testing was conducted at RINA Consulting – Centro Sviluppo Materiali SpA and EWI Hydrogen Environment Testing Lab, using approximately 50 specimens from different heats produced at Evraz North America (ENA). At the fracture surface of the tested specimens, no significant crack extension was observed; the crack extension beyond the fatigue pre-crack was smaller than 0.25 mm after preloading and hydrogen exposure. Scanning electron microscopy (SEM) fractographs revealed a dimpled fracture surface in front of the fatigue pre-crack, i.e. no hydrogen-associated brittle fracture feature was noted. Based on these results, the minimum value of the threshold stress intensity factor, KIH, was calculated to be 70–80 MPa√m for all the specimens, i.e., fulfilling the qualification criteria (KIH > 55 MPa√m) described in the code ASME B31.12 Option B. The lessons learned during the qualification testing, ongoing efforts to develop alternative testing methods, including elastic-plastic fracture testing (i.e., ASTM E1820) and implications for the future will be discussed.
Development of a Laser Tracking System Based AI for Automatic Root Pass Welding in Pipes
Authors: Galeazzi Daniel , Henrique Gonçalves e Silva Régis
Published: December 2024

Today, the demands for sustainability, safety, productivity, and quality are pressing production systems, and the industry is sparing no effort to meet them. This paradigm shift towards digitalization, automation, and interconnectivity is crucial for developing smarter, more efficient manufacturing processes, in the scope of trend scenarios of Advanced Manufacturing or Industry 4.0. In this context, robotics and AI offer great solutions, that can benefit pipeline construction projects. The very viability of the new pipelines projects is affected by productivity and costs. Also, there is a strong correlation between pipeline construction and environmental issues, as well as with worker (welder) safety issues. This paper focuses on developing an AI-based laser tracking system for root pass welding in pipes, utilizing a controlled short-circuiting GMAW technology. The study employed a dedicated 7-axis anthropomorphic robot integrated with a laser sensor. The primary goal was to develop a robust integration between the robot and the laser sensor, enabling the creation of a weld seam tracking algorithm to locate and adjust the torch path along the welding of the joint. This algorithm utilized tracking points, which describe the inflection points of a previously set groove geometry. Additionally, the laser sensor system provides joint dimension data, such as bottom and top width, height, and area, which are input into an AI system to adjust welding parameters in real-time (Adaptive Welding). The AI algorithm was trained with welding parameters from experiments varying root openings and welding positions. For each condition, parameters like the controlled short-circuit current waveform, wire feed speed, travel speed, and waving parameters were optimized. Final tests were conducted on pipe sections with a V-joint to evaluate the performance and system’s robustness for both algorithms path and weld parameters correction. The results demonstrated satisfactory performance: the path correction algorithm was robust, the system was capable to overcome significant geometrical variations of the root opening (1 to 4.5 mm) and pipe mismatch, and the AI algorithm performed well even in out-of-position welding, providing robustness and adequate quality to the root pass.
Material Performance of Line Pipe Steels for the Hydrogen Infrastructure
Authors: Höhler Susanne , Wanzenberg Elke , Jacob Nikolai , Bosch Christoph , Brauer Holger , Mirkovic Djordje , Muthmann Elke
Published: December 2024

Since the upcoming hydrogen infrastructure will set high demands on efficient pipelines and thus on the line pipe material as well, test series are presented to investigate in detail the material behavior of typical line pipe steels.

Various steels from pipes from different production routes with a range of steel grades from X52 to X70 were selected and tested under gaseous hydrogen. Hydrogen impact on the mechanical behavior of these standard steels is estimated by different test series on base material and weld material. Slow strain rate tests under quasi-static loading are used to evaluate the hydrogen effects on the stress-strain behavior with focus on yield strength, ultimate tensile strength, uniform elongation, and the ductility ratios derived by the comparison of tests performed in hydrogen and inert gas (nitrogen). The materials tested reach high ductility ratios for all steels considered, irrespective of steel grade, production route or microstructure. Further on, the threshold stress intensity factor KIH required in the current ASME B31.12 code is experimentally determined under severe test conditions (high pressure 180 bar). Test procedure, results and validity are evaluated and discussed.
A Short Formula for Hydrogen
Authors: Cosham Andrew
Published: December 2024

The Short Formula was developed by the Battelle Columbus Laboratories for the then Pipeline Research Committee of the American Gas Association in the mid 1970s. It is a simple approximation to the Two Curve Model.

The Short Formula is only applicable to a lean gas. It is conservative when applied to hydrogen.

A short formula for hydrogen has been developed. Firstly, the derivation of the Short Formula has been (approximately) duplicated. Secondly, the implications of using a decompression curve for methane, rather than the decompression curve for an ideal gas, with a constant initial speed of sound, as used in the derivation of the Short Formula, have been investigated. Thirdly, and finally, a short formula for hydrogen has been developed using a decompression curve for hydrogen.

Diameters from 323.9 to 1422.0 mm, grades from Grade L245 to L550, and hoop stresses up to 80% SMYS, inclusive, have been considered.

The accuracy of the short formula for hydrogen is similar to that of the Short Formula.
Application of a Newly Standardized Risk-Based Pressure Design Approach – Implications From Pilot Studies
Authors: McAllister Lowell , Svitich Aiden , Adianto Riski , Wiechnik Cory , Ezeiruaku Emeka , Lu Dongliang
Published: December 2024

A risk-based pressure design approach has been developed as an alternative to the class location approach currently used in the Canadian Standards Association’s (CSA’s) Standard Z662. This new approach was adopted in the non-mandatory Annex C of the 2023 edition of CSA Z662.

The risk-based design approach uses a set of hoop stress factors to calculate the minimum wall thickness from the pipe’s pressure, diameter, and specified minimum yield strength. The hoop stress factors are calibrated to meet reliability targets based on undamaged pipe burst and third-party mechanical damage failure limit states. These reliability targets are defined for a set of consequence-based safety classes to achieve a consistent, broadly acceptable, level of risk for all pipelines.

Since the approach was adopted in CSA Z662 in 2023, several pilot studies, as described in this paper, have applied it to segments of high-pressure transmission pipelines in Canada. While this approach can also apply to new designs, the pilot studies described in this paper consider scenarios in which existing designs must be re-evaluated, including for class location changes due to population encroachment and the construction of road crossings.

This paper describes the results of these pilot studies and demonstrates the safety and financial implications of adopting the new risk-based pressure design approach at such sites that need re-evaluating. This is done by comparing the design requirements under the new risk-based approach, such as pressure and wall thickness, with the requirements of the existing class location approach. In some cases, the pilot studies demonstrate that the new risk-based approach can reduce over-conservatism with less-restrictive design requirements, resulting in a positive financial benefit while maintaining broadly acceptable levels of safety. The benefit of using alternative mitigation options, such as mechanical damage prevention measures, is also explored in some of the pilot studies.
Assessing Hit Rate Reduction Benefits of Mechanical Damage Prevention for Application in Risk-Based Pressure Design
Authors: McAllister Lowell , Svitich Aiden , Adianto Riski , Ezeiruaku Emeka , Lu Dongliang
Published: December 2024

A risk-based pressure design approach has been developed as an alternative to the class location approach currently used in the Canadian Standards Association’s (CSA’s) Standard Z662. This new approach was adopted in Annex C of the 2023 edition of CSA Z662 as an optional alternative to the pressure design approach in the main body of the standard.

The risk-based design approach uses a set of hoop stress factors to calculate the minimum wall thickness from the pipe’s pressure, diameter, and specified minimum yield strength. The hoop stress factors are calibrated to meet reliability targets based on undamaged pipe burst and third-party mechanical damage failure limit states. These reliability targets are defined for a set of consequence-based safety classes to achieve a consistent, broadly acceptable, level of risk for all pipelines. Since expected failure rates due to third-party mechanical damage were directly used in developing this approach, the benefits of enhanced mechanical damage prevention measures, such as deeper cover depth, additional signage, and installation of mechanical protection, can be reflected in the pressure design.

The benefits of enhanced mechanical damage prevention are accounted for via a “hit rate factor,” which can increase the total hoop stress factor, allowing for the use of smaller wall thicknesses. The value of the hit rate factor is dependent on the “hit rate reduction factor,” which is a ratio quantifying the reduction in expected hit rate from third-party activities on the pipeline alignment given the design’s mechanical damage prevention measures, as compared to the minimum requirements.

In the 2023 edition, Annex C of CSA Z662 provides little prescriptive guidance on how to estimate the hit rate reduction factor. However, the hit rate fault tree approach is identified as an appropriate option. This paper describes estimates of the hit rate reduction benefits of various mechanical damage prevention measures in terms of a hit rate reduction factor using a fault tree model. The predictions of multiple industry-leading fault tree models are compared, and the pressure design implications are quantified for representative scenarios in terms of the resulting risk-based hoop stress factors.
Correlation of IMU Bending Strain Features to Geohazard Locations: An Update
Authors: McKenzie-Johnson Alexander , Theriault Bailey , Dotson Rhett , Hart James , Varela Patricia
Published: December 2024

This paper presents an update to the results of Theriault et al. (2020) on the correlation of single-run IMU bending strain features to geohazard locations. Theriault et al. reviewed over 4,600 IMU-identified bending strain features from a single pipeline operator located in a variety of geographic settings and concluded that while the overall correlation between ILI vendor bending strain features and geohazards is low, higher maximum magnitude and in particular, higher horizontal magnitude, as reported by the ILI vendors, are strongly correlative to geohazard occurrence.

Based on the review of over 17,000 bending strain features for this paper, similar results were observed to Theriault et al., but with lower correlation percentages at higher magnitudes. While the overall conclusions support the prior work by Theriault et al., the results of this analysis suggest that the conclusions of Theriault et al. may have been skewed by a relatively small sample size, particularly at higher magnitudes, and that while the overall correlation between high maximum magnitude and horizontal magnitude and geohazards is strong, geohazards are not the only sources of such conditions. As more data are collected and analyzed, a better representation of the correlation between ILI vendor-reported IMU bending strain features, geohazard occurrence, and other causes can be established.

The paper provides further discussion and analysis of the correlation with individual geohazard types, the relative prevalence of reported IMU bending strain features by magnitude, and where multiple IMU runs have been performed, the correlation between reported strain change features and geohazards.
Development of an Advanced 3D Profile Matching Approach for Pipeline Dent FEA Assessment
Authors: Xu Luyao , Brust Alexander , Kemp David , Wu Shanshan , Finneran Shane , Bratton Joseph P.
Published: December 2024

Mechanical damage, particularly in the form of dents, is identified as a major threat to the structural integrity of pipelines. Finite Element Analysis (FEA) modeling has gained prominence for its reliability in evaluating the fitness-for-service (FFS) compared to the more conservative Level 2 assessments. During the dent FEA modeling process, acceptable dent geometry profile agreement between the FEA model and In-Line Inspection (ILI) data is critical to capture the appropriate stresses and strains associated with the dent formation in the FEA model.

Conventional FEA modeling approaches commonly utilize rigid ring, ball, idealized rigid shell shape indenters, or a combination of multiple rigid shells as the indenters. The resulting dent profiles from the FEA model are then compared with ILI caliper data through two-dimensional (2D) profile matching. This approach is adequate for most of simple shape or symmetrical shaped dents. However, for dents with complex morphologies, the 2D profile matching method can lead to significant variations between the FEA modeled and ILI measured dent shape, leading to inaccurate stress and strain distributions in the dented region. Additionally, the conventional dent FEA modeling approach is inefficient as it requires extensive iterative adjustments to indenter shape and indentation depth.

This paper presents an advanced approach to customize indenter shape for dent FEA modeling by integrating machine learning techniques, advanced indenter shape adjustment algorithms, and 3D visualization techniques. This approach ensures a satisfactory 3D dent profile matching between the FEA and ILI profiles whilst significantly reducing the time and effort required for modeling adjustments.
A Direct Assessment ‘Style’ Methodology for Evaluating Type B Sleeves
Authors: Morris Greg , McMahan Tara Podnar , Bubenik Thomas , Bartal Nick
Published: December 2024

Pressure containing (Type B) full encirclement steel repair sleeves are a widely used and versatile repair method for defects in oil and gas pipelines. With proper design, materials, installation, and maintenance, these repairs can operate safely and reliably over the life of the pipeline. However, like any other repair technique, if installed improperly, problems can arise over time. The objective of this paper is to describe a direct assessment ‘style’ process that could be used to evaluate previously installed Type B repair sleeves within a pipeline system for quality and long-term reliability. This process includes a potential prioritization method, as well as techniques for in-situ examination of sleeves excavated through targeted or opportunistic digs, and destructive examination of sleeves removed from service.
Historical Perspective on Wind-Induced Vibration of Above-Ground Pipeline Configurations on the Alaskan North Slope
Authors: Hart James D. , Zulfiqar Nasir
Published: December 2024

Steady arctic winds blowing across the flat topography of Alaska’s North Slope oil fields often induce vertical oscillations in above-ground pipelines, as a result of cyclic lift forces associated with the vortex shedding phenomenon. Extensive studies have been undertaken to better understand and control this complicated aerodynamic phenomenon. This paper provides a 30 plus year historical perspective on wind-induced vibration (WIV) of above-ground, cross-county pipeline configurations on the North Slope of Alaska. The paper includes an overview of the dynamic characteristics (e.g., mode shapes and frequencies) of typical “generic” multi-span cross-county pipeline configurations, the WIV phenomenon and the results of field instrumentation programs including free-vibration testing and long-term WIV monitoring. The paper illustrates a relatively simple framework for screening pipelines for WIV exposure as a function of azimuth orientation that utilizes publicly available, historical North Slope wind speed and direction observations. The paper also describes how systems of auxiliary mass damper (AMD) devices tuned to the WIV susceptible pipeline vibration frequencies are used to provide highly effective WIV mitigation over a broad frequency range. Relative motion across the dissipative elements of the tuned AMD devices which are attached to the pipeline at anti-node locations results in hysteretic energy dissipation which can dramatically increase the effective modal damping ratios of the lightly damped pipeline system and proportionately decrease the corresponding modal WIV response amplitudes. The effectiveness of AMDs is supported by data from laboratory tests over a wide range of temperatures and frequencies, field free-vibration tests and WIV monitoring programs. The paper concludes with a summary of how pipeline WIV has been successfully and widely mitigated across a large inventory of WIV-susceptible North Slope pipeline configurations using a triple-tuned and spatially distributed family of AMD devices spanning a broad-band of vibration frequencies for mitigation of primary (and if necessary, secondary) mode WIV.