bluuebunny/crossref_metadata_2025_split huggingface dataset:
Estimating Measurement Performance With Truncated Data Sets
Authors: Skow Jason , Krynicki Joseph W. , Fraser Alex , Gonzalez Gustavo 
Published: December 2022

Abstract
In September 2021, the API released the third edition of the 1163 Standard “In-line Inspection Systems Qualification”. This edition brought many improvements over previous versions, including more detail in Section 8 “System Results Validation”, which defines the methodologies used to validate ILI run tolerances. The standard describes three levels of validation, with ‘Level 3’ requiring the operator calculate ILI tool measurement performance with real-world data measured in validation spools and excavation sites. Real-world, inspection data sets have some characteristics that make them difficult to use to accurately estimate measurement performance, one of which is ‘truncation’, that is data with a lower- or upper-bound threshold above which no data is reported. For example, most UTCD ILI tools have a lower truncation level, such as 1 mm for crack height, which represents a signal threshold below which measurements are either not reliable, or not reported. Although small features below the reporting threshold exist on the pipeline, they are not normally reported by the ILI tool.
This paper describes a model to estimate ILI tool performance using API 1163 Level 3 methods when the data set has a lower-truncation threshold. The model is tested with simulation data to show how it responds over a wide range of feature population characteristics, and then applied to two real field data sets. Comparisons are made between the truncation algorithm and the standard non-truncated version of the algorithm, to show where the new algorithm performs best and is most useful to implement pipeline integrity mitigations. The model used in this study is consistent with the example documented in API 1163 - Appendix C, the Bayesian inference method. The results of the model produce measurement performance specifications that can be used as inputs in a pipeline risk or reliability analysis. The influence of truncated data sets is common in the field of inspection and NDE (including thickness measurements), as it reflects the reality that there are features below reporting threshold. The steps required to format the results for use, and achieve more accurate measurement performance results (e.g., unity charts), are described in this paper.
Distribution Pipeline Risk Framework
Authors: Skow Jason , Stewart Ryan , McPherson Rob , Schoenroth Kent 
Published: December 2022

Abstract
By nature, gas distribution is a network system; it does not fit well with traditional pipeline risk models that assume a linear geometry. Distribution system growth is multigenerational and often leads to mixed assets in the same area where transmission pipeline segments are often constructed within shorter time frames and more uniform materials. Slow, sporadic growth leads to varied record availability and quality that might not readily support commercially available risk models. The project described in this paper was initiated to develop predictive methods to prioritize mitigation and replacement activities for distribution networks. Priority is assigned to areas by risk, equipment characteristics and environmental attributes.
In a previous IPC paper, the authors developed a histori-calbased predictive model but applied it to a single city area. This work has been extended to cover the entire province of Saskatchewan. The model relies on logistic regression and a machine learning algorithm to associate the historical failure rate with the asset type, age, pipe material, diameter, pressure, and an array of geographical-dependent attributes such as soil properties and climate events. The output of the model allows integrity engineers to consider predicted failure rates to complement the lagging performance indicators used to develop integrity program planning. This model demonstrates the advantage of using available distribution system records to develop a custom historicalbased predictive model.
Consequence estimates for distribution networks are also described. Distribution leaks are often classified into hazard levels that differentiate operational response. These are assigned based on incident data records and SME input to develop an event tree for the consequence of a distribution leak. This paper summarizes the work performed during the project to calculate distribution asset probability of failure and consequences.
Implementation of Ductility and Microstructural Attributes for Evaluation of Fracture and Fatigue Performance of API X Grades in High Pressure Gaseous Hydrogen Transmission Pipeline Environments
Authors: Stalheim Douglas , Slifka Andrew , Connolly Matthew , Lucon Enrico , Litschewski Aaron , Uranga Pello 
Published: December 2022

Abstract
There is a strong interest in hydrogen as an energy source to contribute to combatting climate change. Hydrogen diffusion into the steel with assistance through various mechanisms of corrosion and pressure will degrade the mechanical properties, primarily critical ductility properties of fracture toughness and fatigue, through embrittlement or hydrogen induced cracking. Fracture toughness as a measure of crack arrest performance through required Charpy (TCVN) performance represents a principal mechanical property requirement of the pipeline. Ductility performance, regardless of the environment, which consists of % RA, fracture toughness, fatigue, etc. is driven primarily by metallurgical components of the through-thickness microstructure such as average high angle grain boundary (HAGB) size and homogeneity of the HAGB’s . A relationship can perhaps be developed of ductility attributes such as TCVN performance in air vs. fracture toughness ductility performance in hydrogen. This relationship of TCVN ductility performance in conjunction with through-thickness microstructural components with fracture toughness performance in hydrogen will be used to propose an additional “Option C” qualification to the ASME B31.12 Code for Hydrogen Piping and Pipelines. This paper will present the background analysis, evaluation, development of the logic, proposed B31.12 code language and how to implement the logic.
Modification of Existing Pipeline Corrosion Assessment Methods for Combined Internal Pressure and Compressive Loading - An Update
Authors: Owens Christopher , Patterson Angus , Arias Arlene , Brett Alex , Russell Andy 
Published: December 2022

Abstract
Corrosion anomalies in pipelines are typically assessed using methods such as ASME B31G. These methods were developed to consider the axial extent and depth of the anomaly in relation to internal pressure loading only. For the majority of pipelines internal pressure will be the primary loading; however, pipelines can also be subject to additional axial compressive stresses (e.g. thermal stresses). When these additional axial compressive stresses become significant, they can interact with the applied internal pressure to lower the failure pressure of the anomaly. ASME B31G, which now incorporates Modified B31G and Detailed RStreng, acknowledges the need to account for significant axial compressive stresses but it does not include a codified procedure to account for combined loading.
This paper considers an approach to modify these widely used existing assessment methods in order to account for the potential effects of combined loading. The approach used to modify the methods was based on the global collapse method developed for DNVGL-RP-F101, which uses the Tresca yield criterion. To validate that the modified assessment methods would provide safe failure pressure predictions, the results were compared against existing full-scale test data. This was further supported by carrying out finite element analysis (FEA) simulations to estimate plastic collapse and local failure pressures, in order to consider the impact of different corrosion profiles on predictions using effective area calculations.
This work follows on from a previous paper and includes additional FEA simulations to consider the influence of the loading order on the failure pressure. In addition, a case study is presented showing the potential benefit of using an effective area method when compressive loading is significant.
Key Considerations for Elastic Finite-Element Modeling of Pipeline Dents for Fatigue Assessments
Authors: Sager Ryan , Curiel Fernando , Holliday Chris 
Published: December 2022

Abstract
The assessment of the remaining life of dents in pipelines generally relies on characterizing the structural response to pressure loading and combining a known pressure history with S-N curves to determine a fatigue life. A robust method for determining the structural response of a dent to pressure loading is through the determination of a Stress-Concentration Factor (SCF) derived from the modelling of the dent using Finite-Element Analysis (FEA). For simplicity, most SCF assessments rely on the use of unrestrained models derived directly from deflection data recorded by ILI or laser scan; however, this application can lead to overly high predictions of SCF values when evaluating restrained dents. Explicit modelling of restraint using bespoke indenter profiles and elastic-plastic material models can be used to derive more appropriate SCF values for restrained dents; however, this requires significantly more analytical effort and can sacrifice the fidelity of the shape for complex geometry. An approach that utilizes the efficient modeling and high fidelity of unrestrained elastic models would provide the industry with a reliable and repeatable process for evaluating the fatigue response of restrained dents. The methodology presented within this paper will seek to validate reasonable bounds for unrestrained elastic models that can be applied to cases where restrained dents are indicated. This paper will investigate the feasibility of a plasticity-restraint correction factor that could be applied to elastic SCFs and discuss the implications for dent fatigue assessments. The response of restrained elastic-plastic models will be compared to the response to elastic models for a range of indenter shapes to show the feasibility of this correction factor.
Relative Risk of Alternating Current Power Line Faults Affecting Nearby Pipelines
Authors: Stewart Ryan , Bear Devin , Skow Jason 
Published: December 2022

Abstract
The co-location of pipelines and alternating current (AC) transmission lines can lead to electrical hazards on a pipeline. One example is a transient voltage that electrifies a nearby pipeline during a power line to ground fault. A power line fault, typically caused by a lightning strike, cut power line, or windstorm, results in electrical potential being transferred to ground. A buried pipeline near a fault acts as a grounding conductor, carrying energy to an area of lower potential than the incident location. Current carried through a pipe is a hazard to people and equipment. A current travelling to an above ground structure could lead to an individual becoming part of an electrical circuit if they touch the structure and the possibility of a high electrical current flowing through an individual’s entire body.
While current literature describes how to mitigate the effects of power line faults, there are limited sources that describe a process to quantify the probability of power line faults affecting pipelines.
In this paper, a method to assess the frequency of AC powerline faults and their potential impact to pipeline infrastructure is described. The model incorporates spatial and historical factors to evaluate the exposure of individual assets to AC power line faults. It estimates the powerline fault frequency and the area of ground potential rise that could lead to safety consequences for workers or members of the public. The collection of fault frequency data, the calculation of fault current from transient voltage hazards, and the estimated area of potential harm from transient voltage hazards are discussed.
The model was developed to rank the risk of power line fault incidents across a company’s pipeline system. The results of the assessment help prioritize locations to perform more detailed site-specific analysis for the design and installation of mitigation systems.
A Transparent ASME B31.8-Based Strain Assessment Method Using 3D Measurement of Dent Morphology
Authors: Zhang Shenwei , Zhang Billy , Wang Rick 
Published: December 2022

Abstract
This paper presents a comprehensive methodology to evaluate the geometric strain of pipeline in a dented area caused by mechanical damage. This methodology was formulated based on the approach recommended by ASME B31.8 and built the transparency of the entire process of dent strain assessment using three-dimensional (3D) measurement of dent morphology reported by the Caliper tools from in-line inspection (i.e., Caliper data). The 2D Fourier Transform in conjunction with band rejection filtering method was used to filter the signal noise and smooth the 3D morphology of dent. The cubic spline was utilized to characterize the discrete 2D longitudinal and circumferential profiles for curvature and arch length calculations, which were used to evaluate the bending strain and membrane strain, respectively. The effective strain was then calculated using the method recommended by ASME B31.8. To demonstrate the application of the methodology, a tool with user-friendly interface and powerful visualization and reporting functions was developed using the methodologies reported in this paper. The reported methodology enables development of dent strain assessment tool and benefit pipeline operators to facilitate dent integrity management program.
Effects of Hydrogen Embrittlement on the Fracture Toughness of High-Strength Steel Structures
Authors: Agbo Sylvester , Davaripour Farhad , Roy Kshama 
Published: December 2022

Abstract
Blending hydrogen into existing natural gas pipelines is being pursued as a means of delivering hydrogen to markets. However, as stated in ASME B31.12, high-strength steel pipelines under stress can be susceptible to hydrogen embrittlement, which is a phenomenon that could induce brittle fracture in steel. This study proposes a numerical framework using phase-field fracture modelling techniques to model the hydrogen embrittlement phenomenon in high-strength steels. The proposed numerical framework is validated against a Compact Tension experimental test specimen, which is deemed suitable to capture the crack-tip constraint observed in high strength steel. The finite element results show a good agreement with experimental results, which demonstrate the capability of the phase-field fracture model in reasonably predicting hydrogen embrittlement in high-strength steel. As such, the proposed numerical modelling framework could also be applicable to typical high strength steel pipelines.
Reliability-Based Self-Imposed Pressure Restriction / Derate Pressure Estimation for Corrosion and Crack
Authors: Yan Jason , Zhang Shenwei , Saunders Joe , Blackwell Chris 
Published: December 2022

Abstract
Corrosion and crack anomalies are the major threats to the safety and structural integrity of oil and gas transmission pipelines. Pipeline operators commonly manage the corrosion and crack threats by regular in-line inspection.
After inspection, operators need to identify critical anomalies and plan mitigation works. Traditionally, a deterministic approach is used to assess anomalies using characteristic values of pipe properties, anomaly size, growth rate, and considering a minimum required safety factor (e.g., 1.25). TC Energy has used a full reliability-based method to determine the mitigation plan for corrosion and stress corrosion cracking (SCC) anomalies considering all the uncertainties associated with pipe geometry, material properties, anomaly size, growth rate and assessment model error explicitly. This method enables TC Energy to maintain the annual probability of failure of all known anomalies with the same location class not exceeding a consistent threshold (e.g., 1E−3 per anomaly per year).
Anomalies that do not meet the minimum safety margin (e.g., deterministic safety factor or reliability-based threshold) and cannot be mitigated timely, are usually managed by applying short-term self-imposed pressure restriction (derate). Derate pressure is typically calculated deterministically with conservative anomaly size, growth rate and a global safety factor. To account for potential parameter variation, conservative inputs often lead to conservative derate pressure. There is inconsistency between a full reliability-based mitigation plan and a deterministic short-term derate plan.
This study introduces a new efficient reliability-based approach using a Monte Carlo simulation technique to determine the derate schedule (e.g., the minimum required derate pressure for each month) to maintain the system to a consistent safety level. Two case studies, one MFL and one EMAT inspection with reported critical corrosion and crack anomalies, are conducted to demonstrate the advantage of fully reliability-based derate approach. The optimized derate plan minimizes the economical business impact to operators. The proposed framework in this study can be widely used to improve derate programs.
Comparison of Machine Learning Models for Quantitative Risk Modelling of Pipeline Systems
Authors: Bandstra Daryl , Rojas Juan S. , Fraser Alex , Shironishi Mari 
Published: December 2022

Abstract
Over the past decade, machine learning models have enabled significant technical achievements in a variety of fields, however the application of these models is an area of active research and development in conventional and regulated industries, which are often more cautious to adopt new technologies. In this paper, a case study is presented where various statistical and machine learning models, including logistic regression, random forest, gradient-boosted decision trees, and artificial neural networks are trained and validated using a historical incident record dataset to quantify the probability of pipe failure on a distribution pipeline system. The relative performance of each model type is compared against a held-out test dataset using an evaluation framework that utilizes lift charts to quantify each model’s performance. Observed strengths and limitations of the different model types are discussed with respect to performance, interpretability, and ease of incorporating additional data, along with key considerations for fitting and evaluating models. Additional case studies are also presented to illustrate how model performance depends on the quantity of training data and predictor features. These additional cases illustrate the benefit of continually collecting and leveraging asset data, as well as the benefit of augmenting existing asset data with external datasets, such as those obtained from public geospatial datasets. The results of this study will provide operators with additional insights and guidance in developing and evaluating machine learning models for pipeline risk assessment and integrity management.
A More Efficient Effective Area Method Algorithm for Corrosion Assessment (Faster RSTRENG)
Authors: Yan Jason , Lu Dongliang , Khou Ian , Zhang Shenwei 
Published: December 2022

Abstract
Corrosion is one of the major threats to the safety and structural integrity of oil and gas transmission pipelines. The corrosion threat is usually managed by regular in-line inspection (ILI).
The effective area method (RSTRENG) is the most popular corrosion assessment model to convert the measured corrosion size to predicted burst pressure. Given a detailed corrosion measurement profile, the effective area method involves an iterative process to find the minimum burst pressure. As stated in ASME B31G, “for a corroded profile defined by n measurements of depth of corrosion including the end points at nominally full wall thickness, n!/2(n − 2)! iterations are required to examine all possible combinations of local metal loss with respect to surrounding remaining material”, the widely used effective area algorithm has at least an order of n-square time complexity (O(n2)). As n increases, the computation time increases nonlinearly.
This paper reviewed the traditional RSTRENG algorithm first, and demonstrated that it is not necessary to always loop through all the combinations and check the corresponding burst pressure one by one. Because some combinations with shallower and shorter corrosion size are certainly not the final critical combination corresponding to the minimum burst pressure. A more efficient algorithm (Faster RSTRENG) is proposed and presented in this paper, which can reduce the algorithm computation time significantly.
While the impact of efficiency of the algorithm on the integrity assessment process is insignificant if solely conducting burst pressure calculation in a deterministic way, a highly efficient algorithm is desired when assessing a large volume of corrosion anomalies by the reliability-based (probabilistic) assessment method using Monte Carlo simulation technique where millions of simulations are required.
In addition, TC Energy has developed a more accurate and precise corrosion assessment model, i.e., plausible profiles (Psqr) model, published in IPC 2018 and 2020, and reviewed by industry experts through PRCI. The use of Psqr model needs to generate hundreds of profiles for one corrosion anomaly and repeatedly uses the effective area algorithm. This needs extensive computing efforts. When Psqr model was built into the probabilistic assessment framework, the computing efforts were dramatically increased. Therefore, it is of great importance to have a more efficient effective area algorithm to facilitate the probabilistic assessment using Psqr model.
A case study was used to demonstrate the efficacy of the developed algorithm by comparing the computation time using different effective area algorithms. Engineers who are already familiar with RSTRENG model, might jump to the Faster RSTRENG section and Annex A directly.