Volume 2: Pipeline and Facilities Integrity最新文献

{"title":"Overcoming Challenges for Quantitative Risk Modeling Using Machine Learned Data Correlations and Predictive Modeling","authors":"S. Biagiotti, Dan Williams, Sergiy Kondratyuk, Brett Johnson","doi":"10.1115/ipc2022-87236","DOIUrl":"https://doi.org/10.1115/ipc2022-87236","url":null,"abstract":"\u0000 After 20 years of learnings and successful risk reduction, the pipeline industry is striving to achieve the next step change in risk performance by migrating from relative index-based risk models toward probabilistic approaches across all threats and all pipeline segments for system-wide risk assessment. While the quantification of pipeline risk can be readily supported by in-line inspection (ILI) results coupled with probabilistic limit state modeling for certain threats and pipeline segments where this information is available, where such data is lacking for other pipeline segments or threats, it is necessary to apply a meaningful methodology to establish the probability of failure for all dynamic segments used to quantify risk.\u0000 The process for establishing probability-based threat assessments for these other segments involves several stages: (1) identify correlations based on ILI historical results (i.e., create the “training” dataset); (2) leverage classification trees to identify statistically relevant data observations of key variables; (3) apply machine learning techniques to develop probabilistic and/or causal models that predict target outcomes from the combinations of key variables; and, (4) apply the relationships established in stages 1, 2 and 3 to all assets lacking ILI results. Although seemingly straightforward, several challenges exist for achieving seamless implementation.\u0000 This paper will review each process step and provide guidance on preparing and tackling common data intelligence challenges. The paper will also propose strategies for classifying assets, other than indexing, for application in those situations where machine learning does not indicate statistically significant variable correlations or yield strong predictions of target outcomes. Although still early in the understanding of migrating from relative index-based to probabilistic risk algorithms, the value provided in this paper is the sharing of lessons learned regarding “how” to gather the “evidence” necessary to identify statistical dependencies, how to apply data confidence metrics within the decision process, the challenges in data preparation/QC and interpretation techniques, and suggestions for determining the necessary limitations that should be applied to the outcomes toward the objective of quantifying the risk.","PeriodicalId":264830,"journal":{"name":"Volume 2: Pipeline and Facilities Integrity","volume":"41 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-09-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125857273","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Using Advanced Probability of Exceedance Methods for Defining Remediation Options","authors":"T. Bubenik, B. Hanna, W. Harper, Matthew A. Ellinger","doi":"10.1115/ipc2022-87108","DOIUrl":"https://doi.org/10.1115/ipc2022-87108","url":null,"abstract":"\u0000 The Probability of Exceedance (POE) methodology is used by pipeline operators to manage corrosion. It prioritizes anomalies identified by an in-line inspection (ILI) based on their likelihood of exceeding one or more failure thresholds. Two types of thresholds are commonly used: leak and rupture. The calculations represent the likelihood an anomaly will leak or rupture as a function of time. By assessing the likelihood of such a release as a function of time, an operator can design rational and statistically valid remediation programs.\u0000 In this study, the likelihood that an anomaly will cause a leak or rupture was based on the ILI dimensions, the ILI system’s accuracies, and the corrosion growth rate at the anomaly location. The ILI dimensions were adjusted by the mean error as determined using ILI-to-field comparison data. The same ILI-to-field data were used to determine the scatter (standard deviation) in reported dimensions for different categories of anomalies.\u0000 The POE (likelihood) of a leak or rupture was taken as a function of the mean and standard deviation of a corrosion growth rate at the anomaly location. Anomalies were “grown” using mean growth rates that were established by performing ILI run-to-run comparisons. By using accurate growth rates and ILI performance characteristics, realistic estimates were made of the POE of an anomaly, pipe joint, pipe segment, and the overall pipeline itself.\u0000 This paper discusses improved methods of calculating leak and rupture POEs using realistic assumptions on how anomaly growth occurs as a function of time. Case studies are used to demonstrate the effectiveness of the advanced POE method.\u0000 The introduction and select portions of this paper are based, in part, on “Advanced Probability of Exceedance Method Overcomes Previous Weaknesses,” by the authors,1Pipeline Pigging and Integrity Management Conference, February 2–4, 2022.","PeriodicalId":264830,"journal":{"name":"Volume 2: Pipeline and Facilities Integrity","volume":"2009 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-09-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125590914","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Explained: Ultrasonic Self-Propelled Robotic Inspection Solution for Unpiggable Dock Line","authors":"Corey Richards, Cedric Bolduc, Børge Hamnes","doi":"10.1115/ipc2022-86889","DOIUrl":"https://doi.org/10.1115/ipc2022-86889","url":null,"abstract":"\u0000 While under various banners, Valero Energy Inc. has been a staple in the refining and marketing of products since 1961. Key facilities such as the Montreal East Terminal and the St-Romuald Refinery supply their carriers and customers (resellers and wholesalers) in the regions of Southern Quebec, the Maritimes, and the Greater Ottawa and Toronto areas, with smaller terminals in these areas serving the Northeastern United States market.\u0000 Guaranteeing that delivery orders are met and critical product is delivered on schedule requires Valero’s terminals to have comprehensive integrity programs in place. Comprehensive programs, which include risk modeling, in-line inspections and tank inspections, to name a few, help to ensure there is no unexpected downtime due to incidents.\u0000 While ensuring the integrity of any oil and gas pipeline network contains its own challenges, facility or terminal piping does not often contain the typical infrastructure to employ standard technologies. Accordingly, specialty solutions are often required. Such is the case for Valero’s 960-meter, 10inch dock line at the Gaspé Terminal, which is a critical supply link transporting refined products from shipping vessels to the terminal.\u0000 The technical challenges that needed to be overcome for the inspection of this underground dock line included:\u0000 • No pig launcher and pig receiver present; dock line not designed for conventional pigging\u0000 • Dock line only has flow when unloading to ships\u0000 • In-service operating conditions prohibited conventional ILI tool inspection\u0000 • Limited space available for equipment to support standard pigging operation\u0000 • Staging of equipment on the dock would pose additional risks for the environment in the event of loss of containment for any supporting pumping equipment\u0000 This paper will outline the validation, testing and execution of a self-propelled robotic tethered solution in combination with an ultrasonic wall measurement (UTWM) system capable of navigating the complexities of the Gaspé dock line. The inspection solution outlined in the paper did not require any major modifications to the dock line system, nor did any equipment need to be present on the dock side. The utilization of dedicated crawler units eliminated the requirements for flow or pressure in the dock line to propel the tool during inspection.\u0000 Overall technical and operations benefits of this solution are:\u0000 • Accurate and precise feature classification and sizing by quantitative ultrasonic measurement\u0000 • Two sets of data (from both the inbound and outbound run) with the outbound run providing a further verification for the inbound run\u0000 • Real-time data analysis and preliminary report on-site, followed by a thoroughly reviewed final report\u0000 The online self-propelled tethered crawler inspection system contained the actual inspection tool, the drive unit, the umbilical winch and a computer system to communicate with and control the inspection vehicle. The paper will outline in detail","PeriodicalId":264830,"journal":{"name":"Volume 2: Pipeline and Facilities Integrity","volume":"29 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-09-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114904159","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Long Seam Characterization by Means of a Phased Array Based Inline Inspection","authors":"Victor Haro, Katja Traeumner, Christina Jung, Gerhard Kopp, M. Urrea","doi":"10.1115/ipc2022-87416","DOIUrl":"https://doi.org/10.1115/ipc2022-87416","url":null,"abstract":"\u0000 Pipelines can show imperfections at the longitudinal weld. These imperfections are often introduced by the welding process in the pipe mill and can differ from mill to mill and welding technology. Some of those imperfections are acceptable variations within the manufacturing specifications of the longitudinal seam, either on the internal or external weld trim or cap. Others may exceed acceptable tolerances and introduce a risk for safe operation. In addition, sometimes radial offsets, misalignment, peaking and flat spots can occur. All those variations can lead to signals wrongly classified as crack-like defects, leading to unnecessary repair activities or shading of real flaws.\u0000 A phased array based ILI tool can map and accurately measure localized wall thicknesses and surface variations. Phased array elements typically have a width of 0.4 mm (16 mils) to 0.8 mm (32 mils), which enables high circumferential resolution compared to the latest generation of traditional single sensor ultrasonic tools of 2 mm (79 mils), while the ILI industry standard has a circumferential resolution around 4 mm (158 mils). This increase in resolution can be used to reconstruct the inner surface, the wall thickness and outer surface of the long seam itself and the vicinity. This includes misalignment, the weld cap height and width, potential trim issues, and similar effects.\u0000 The authors will show and explain the robustness of the measurement methodology based on laboratory/test data and real-world pipeline inspection. Furthermore, the benefit of knowing accurately the local seam wall thickness will be discussed, as a higher wall thickness reduces the severity of defects. For a selected set of anomalies, it can be shown that a significant number that may exceed acceptable limits (actionable anomalies) can be treated as non-critical considering the ILI measured local WT.\u0000 Finally, the authors show how the gathered data can be used to build 3D models and perform simulations with different flaws to further optimize the inspection tool and utilize the phased array tool to its maximum benefit.","PeriodicalId":264830,"journal":{"name":"Volume 2: Pipeline and Facilities Integrity","volume":"123 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-09-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123929447","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Development of a Near-Neutral pH Stress Corrosion Cracking Growth Model for Pipelines Using Machine Learning Algorithms","authors":"Haotian Sun, Wenxing Zhou, Jidong Kang","doi":"10.1115/ipc2022-87207","DOIUrl":"https://doi.org/10.1115/ipc2022-87207","url":null,"abstract":"\u0000 Near-neutral pH stress corrosion cracking (NNpHSCC) is one of the leading causes of failure for buried pipelines. Characterizing the NNpHSCC growth rate accurately remains a challenging task for the pipeline industry. In this study, an NNpHSCC growth model for buried pipelines is developed based on experimental data obtained from full-scale tests conducted at the CanmetMATERIALS of Natural Resources Canada of pipe specimens that are in contact with near-neutral pH environment and subjected to cyclic internal pressures. Four machine learning algorithms, namely the random forest (RF), extremely randomized trees (ET), gradient boosting (GB) and extreme gradient boosting (XGB), are employed to estimate the crack growth rates da/dN from input variables characterizing the pipe geometry, internal pressure and environmental condition. The machine learning models are trained through hyperparameter tuning and k-fold cross validation to improve the model robustness. Model performances are validated and compared using an independent test dataset. This study provides an initial step in using machine learning tools to develop robust NNpHSCC growth models suitable for practical applications.","PeriodicalId":264830,"journal":{"name":"Volume 2: Pipeline and Facilities Integrity","volume":"249 2","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-09-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134427820","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Implementation of API 1183 Recommended Practice for Reliability-Based Assessment of Dents in Liquid Pipelines","authors":"Muntaseer Kainat, A. Virk, N. Yoosef-Ghodsi, S. Bott","doi":"10.1115/ipc2022-87320","DOIUrl":"https://doi.org/10.1115/ipc2022-87320","url":null,"abstract":"\u0000 Prior to the publication of API 1183 (Recommended Practice for Assessment and Management of Pipeline Dents) in 2020, there was no industry consensus on one method to evaluate the Fitness for Purpose for dents to be implemented in integrity management programs. Regulations in Canada and the United States regarding the repair of dents are primarily based on depth and interaction with stress risers. API 1183 has put forth specific methodologies for screening and detailed assessment of dents which consider both strain-based and fatigue-based failure mechanisms.\u0000 Enbridge Liquid Pipelines had previously presented a framework to support systemwide dent assessment with an efficient reliability-based approach. Following the publication of API 1183, this approach has been further modified to comply with the API recommendations for dent assessment. Both the screening and detailed analyses within this framework account for the properties of the pipe, dent, and interacting features, the operating condition and history of the line, restraint condition, and associated uncertainties. These analysis techniques combine inline inspection results and engineering analysis with their uncertainties, providing a means for quantitative assessment of dents. This paper demonstrates the alignment of Enbridge’s dent management framework with API 1183 recommendations, and discusses the modifications made for probabilistic assessment of dents. In the absence of specific guidelines for probabilistic assessment in API 1183, Enbridge relied on relevant publications and industry best practices for considering uncertainties within the probabilistic assessment. This framework has been implemented for systemwide analysis with over 5,000 geometric anomalies assessed to date. From this implementation experience, the challenges with probabilistic analysis and potential areas of further improvement have been identified and discussed in detail in this paper. In particular, the recommendations in API 1183 regarding dent fatigue assessment, and the fatigue life reduction factor due to weld interaction are observed to be overly conservative. Overall, the reliability-based dent management framework following API 1183 recommendations have proven to be effective, but inefficient due to being overly conservative. Efforts have been made to validate, and where possible, to calibrate the techniques through comparison to experimental results, field findings, and historical failures. These efforts have enabled Enbridge to tackle the over-conservatism of the models for certain combinations and ranges of operating parameters through novel techniques, which are described in this paper.","PeriodicalId":264830,"journal":{"name":"Volume 2: Pipeline and Facilities Integrity","volume":"12 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-09-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133555687","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Progress of Assessment Model Development for Determining Remaining Strength of Corroded Pipelines","authors":"Xian-Kui Zhu, B. Wiersma","doi":"10.1115/ipc2022-86922","DOIUrl":"https://doi.org/10.1115/ipc2022-86922","url":null,"abstract":"\u0000 A technical review is presented of corrosion assessment models for determining the remaining strength of pipelines containing metal loss or corrosion defects. Initially, burst pressure prediction models for defect-free pipes, including strength and flow theory determined burst solutions and their experimental validations were considered. Next more accurate burst pressure predictions that cover a wide range of pipeline grades were discussed by comparing thick wall burst solutions and machine learning models with full-scale burst data that cover a wide range of pipeline grades up to X120.\u0000 Corrosion assessment models were categorized into three generations with respect to the reference stress. The 1st, 2nd, and 3rd generation models correspond to the flow stress, UTS, and both UTS and strain hardening rate. Seventeen corrosion models were evaluated and compared with full-scale burst data for a wide range of pipeline steels from low to high grades. The focus was on validating two recently developed 3rd-generation models that can determine more accurate burst strength for corroded thin-wall pipes. As the 4th-generation models, three typical thick-wall corrosion assessment models and machine learning models were introduced to predict more accurate results for corroded thick-wall pipes.\u0000 After that, advances in corrosion model development were discussed, including constraint effect, bulging factor and defect width effect. Finally, major technical challenges in development of corrosion assessment models were discussed with regard to full-scale experimental tests, numerical simulations, material failure criteria and real corrosion defect assessment.","PeriodicalId":264830,"journal":{"name":"Volume 2: Pipeline and Facilities Integrity","volume":"99 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-09-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132085605","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Probabilistic Flaw Growth Rate Estimates Using Multiple Inline Inspection Tool Run Data Analyses","authors":"Colin Scott, K. Philpott","doi":"10.1115/ipc2022-87054","DOIUrl":"https://doi.org/10.1115/ipc2022-87054","url":null,"abstract":"\u0000 Many pipeline operators perform run comparisons (or “run-corns”) during assessment of their inline inspection data. Analysts match corrosion pit depths reported in back-to-back tool runs and estimate corrosion growth rates, remaining lives, and appropriate reinspection intervals. This approach is generally deemed more accurate than using an assumed constant growth rate for all reported features. However, the accuracy of each estimate is subject to the depth sizing error inherent in the measurements. The larger a dataset, the higher the likelihood of many calculated corrosion growth rates being misleading. This is due to there being a higher likelihood of extreme depth sizing errors. A first run undercall followed by a second run overcall compounds the depth sizing error and may result in an overly conservative decision. A first run overcall followed by a second run undercall and may result in a missed defect. Both scenarios can lead to a misuse of resources.\u0000 This work is a statistical analysis of flaw growth that considers and accommodates for depth sizing errors. The result is that the growth rate for each ILI reported flaw is considered probabilistically. Advanced data ingestion algorithms allow analysts to align multiple ILI tool run data sets quickly and conveniently, opening the door to advanced data analytics, including work with non-linear flaw growth rates. This work looks at corrosion and SCC growth rates (approximated as linear) and fatigue crack growth rates that follow established Paris Law behavior (non-linear).","PeriodicalId":264830,"journal":{"name":"Volume 2: Pipeline and Facilities Integrity","volume":"94 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-09-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123605955","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A Comprehensive New Look at Type B Sleeves","authors":"David B. Futch, C. Denowh, J. Wilson","doi":"10.1115/ipc2022-87078","DOIUrl":"https://doi.org/10.1115/ipc2022-87078","url":null,"abstract":"\u0000 Type B full encirclement steel sleeves have been used for the past fifty-plus years as a viable repair method for most, if not all, features encountered on a pipeline. A Type B sleeve includes an in-service weld at both ends of the sleeve. The science behind performing these welds in a safe manner has greatly evolved over the past 20+ years. However, many of the original concepts regarding the design and application of a steel sleeve have not been further examined since the original research on the subject.\u0000 This paper investigates a series of sleeve circumstances to better understand the long-term integrity of the common repair method. The circumstances examined within this paper include: the effect of a fabricated sleeve vs split pipe, the influence of the Bauschinger effect on fabricated sleeve properties, the effect of filler material applied within a dent, the effect of steel sleeve fit-up, and the influence of a mill groove relief for a longitudinal backing strip. All test configurations examined confirm the long-term integrity of a Type B sleeve, however, the information presented in this paper from the above tests can be used when utilizing a Type B sleeve as a permanent repair.\u0000 A combination of sub-scale and full-scale tests were performed to fully investigate the circumstances mentioned above. Sub-scale tests were performed to evaluate the Bauschinger effect, which indicated minimal effect from the fabrication processes of the sleeve. Full-scale tests were performed for the remaining circumstances. Through a series of one-for-one comparison tests, a fabricated steel sleeve performed in an equivalent manner to split pipe. The application of filler material, and the application of a suitable filler material, had a large effect on the load sharing of the repair. During this test protocol, tight fitting sleeves resulted in a life approximately 3.5 times longer than one installed in a loose manner. While a mill groove did not affect the life of the sleeve, it does result in a tighter fitting sleeve, shown to have a significant benefit if the sleeve becomes pressurized.","PeriodicalId":264830,"journal":{"name":"Volume 2: Pipeline and Facilities Integrity","volume":"14 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-09-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131092849","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Use of Inertial Measurement Unit In-Line Inspection Data to Support Code Stress Compliance and Integrity Evaluations","authors":"J. Prescott, Curtis Patterson, A. Najeeb","doi":"10.1115/ipc2022-87046","DOIUrl":"https://doi.org/10.1115/ipc2022-87046","url":null,"abstract":"\u0000 Pipelines are an essential segment of infrastructure required to transport a variety of products to markets in our economies. The integrity and safe operation of those pipeline necessitates that pipeline operators have a thorough understanding of their pipeline systems, their configuration, and the changing operating condition within their pipeline networks. Inertial measurement unit (IMU), a technology that can measure the angular rate and acceleration and when combined with global positioning and navigation equipment such as pipeline above ground markers, can calculate position and orientation with 6 degrees of freedom: x, y, z, and pitch, roll, and yaw. IMU launched within the pipeline via in-line inspection tool trains, can be used to develop accurate three-dimensional geometry of the pipelines they inspect. This information can be used to confirm the geometry of the pipeline (i.e. degree of roping, bend angle, bend radius, and other abnormalities observed within the generated centerline from the inspection based on conventional construction practices). Therefore, the application of IMU technology within pipeline design and integrity work can be a useful tool in providing the necessary input information which can support ongoing studies such as verification of maximum operating thermal differentials which can be imposed on a pipeline to remain compliant with governing pipeline codes, and/or the information can be used to perform gap analysis studies with other integrity records (alignment sheets, as-built pipe tallies), or to support other pipeline integrity evaluations. When IMU data is processed with mathematical techniques essential information from IMU data can be obtained such as bend angle, bend radius, and degree of installed curvature. A case study showing the results of the application of processed IMU data for as-built evaluation is presented and its use to help support a variety of decision making is discussed. The IMU data is a key data input when constructing detailed finite element models for on-going stress analysis studies.","PeriodicalId":264830,"journal":{"name":"Volume 2: Pipeline and Facilities Integrity","volume":"2014 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-09-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130922901","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}