Risk Management最新文献

{"title":"Exploratory Data Analyses on CFRP Wrapped HDD Overbend Subjected to Combined Loading","authors":"Farhad Davaripour, K. Roy, P. Maghoul","doi":"10.1115/ipc2022-87299","DOIUrl":"https://doi.org/10.1115/ipc2022-87299","url":null,"abstract":"\u0000 Horizontal directional drilling (HDD) is one of the popular pipeline trenchless construction techniques for sites where surface excavations and conventional trenching are not desirable. An integral part of the pipeline design and construction process is to perform stress analysis on the HDD overbends, which can be subjected to significant cross-sectional deformations due to stresses/strains imposed by thermal expansion and internal pressure. This paper proposes a novel approach to reduce the stress range in the HDD overbends using carbon fibre reinforced polymer (CFRP) wraps. Although this reinforcement technique is primarily used in the pipeline industry for repairing damaged pipes, there is a handful of recent studies that showed the promising effect of using CFRP reinforcement on undamaged pipe bends. A total of 259 finite element analyses are conducted with a different combination of pipe diameter to thickness ratio, CFRP length and thickness, fibre orientation, and internal pressure. An exploratory data analysis is then performed to demonstrate the impact of each variable on the maximum equivalent stresses imposed on the HDD overbend. The finite element results show that multi-directional fibre orientation leads to the highest reduction of peak equivalent stress on the HDD overbend. Besides, an increase in CFRP thickness results in a greater reduction of stresses on the HDD overbend. However, CFRP length does not have a noticeable effect on decreasing the stresses on the HDD overbend.","PeriodicalId":21327,"journal":{"name":"Risk Management","volume":"24 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2022-09-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"85698580","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":"Reframing PSMS in the Context of Operational Risk Management and ESG Sustainability","authors":"Michael Marshall, M. Fingerhut","doi":"10.1115/ipc2022-87773","DOIUrl":"https://doi.org/10.1115/ipc2022-87773","url":null,"abstract":"\u0000 Current Environmental, Health, and Safety (EHS) and Asset Integrity/Performance Management (AIM/APM) platforms fail to properly aggregate data from multiple Pipeline Safety Management System (PSMS) workflows into a single database which can be queried to inform real-time, risk-based analyses and decision-making relative to profitability impacts.\u0000 With predictive analytics at the core of an asset integrity and PSMS framework intent upon achieving holistic, enterprise-wide visibility and accountability for Environmental, Social, and Governance (ESG) program effectiveness and sustainability, this paper proposes an ideal solution designed around the following core functions:\u0000 • Reframing EHS and AIM/APM in the context of Operational Risk Management (ORM) by normalizing data relative to performance and process-related parameters\u0000 • Categorizing, prioritizing, and risk ranking incidents by economic impact (specifically lost production), enabling problem solving teams to resolve high value deep-dive systemic problems\u0000 • Satisfying the need for a one-stop system that has the highly interlinked EHS, compliance and enterprise risk management systems all in one framework\u0000 • Linking to data historians like OSIsoft PI to “give voice to equipment” for predictive analytics as necessitated by today’s digital transformation movement\u0000 • Featuring incident investigation, reporting and failure modes decision support functionality based on industry best practice standards including API 754 Process Safety Performance Indicators for Refining and Petrochemical Industries, which is also directly applicable to petroleum pipeline industry operating systems and processes where loss of containment may occur\u0000 • Offering a highly configurable user interface for key performance indicator (KPI) trending, reporting, alerts/notifications, action planning and follow-up","PeriodicalId":21327,"journal":{"name":"Risk Management","volume":"14 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2022-09-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"78086220","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":"Estimating Pipeline Probability of Failure Due to External Interference Damage Using Machine Learning Algorithms Trained on In-Line Inspection Data","authors":"James White, Katherine Taylor, Jonathan Martin, Steven Carrell, R. Palmer-Jones","doi":"10.1115/ipc2022-87093","DOIUrl":"https://doi.org/10.1115/ipc2022-87093","url":null,"abstract":"\u0000 External interference damage is one of the main causes of pipeline failure reported in publicly available industry statistics from agencies such as the Canada Energy Regulator (CER) and the United States Pipeline and Hazardous Materials Safety Administration (PHMSA). Thus, failures due to external interference are often the most significant contributors to pipeline probability of failure in risk assessments and can play a significant role in operator decisions regarding risk-control expenditures, for example when it comes to the installation of additional impact protection, pipeline diversion or pressure restrictions.\u0000 The probability of failure due to external interference damage can be estimated by combining the probability that damage occurs (i.e. that the pipeline is hit), the probability that the impact is sufficient to cause instant failure and the probability of degradation to failure, given that damage has occurred. Degradation to failure is assessed using industry standard engineering models (such as the limit state functions given in Annex O of CSA Z662-19 [1]). However, the key challenge is predicting where, when, and with what energy the external interference damage may happen.\u0000 The prediction of a “hit rate,” or impact frequency, can often be subjective or based on statistics, which may not always be applicable or accurate for use on the pipeline under assessment. Top-of-line (TOL) deformation damage (dents) reported by in-line inspection (ILI) are a clear indicator of past external interference, which could have been introduced by third parties, contractors or the operator themselves. ILI data from ROSEN’s Integrity Data Warehouse (IDW) — which at the time of writing contains results from over 18,000 inspections — has been used to train machine learning models to estimate the frequency of external interference damage (per km-year). The distribution of dent sizes combined with pipe parameters is used to estimate a distribution of dent force.\u0000 The following may all influence the likelihood and energy of external interference damage and may be considered as predictor variables in a machine learning model:\u0000 • Local population density\u0000 • Land use\u0000 • Excavator types (typical bucket dimensions)\u0000 • Frequency of crossings (road, rail, other services)\u0000 • Pipeline burial depth\u0000 • Additional impact protection\u0000 • Pipeline markers and warning tape\u0000 • Patrol and surveillance frequency\u0000 • Operational control activities\u0000 • Pipeline material properties\u0000 This paper presents an approach to estimate the probability of failure due to external interface damage that use more accurate and justifiable impact frequency statistics, which are generated using worldwide ILI data and additional influencing factors based on pipeline exposure, resistance and mitigations.","PeriodicalId":21327,"journal":{"name":"Risk Management","volume":"187 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2022-09-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"81096758","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":"Ingenuity and Curiosity to Supercharge Your Pipeline Safety Management System","authors":"Frank S. Gareau, A. Ilbagi, Brian Dew","doi":"10.1115/ipc2022-87750","DOIUrl":"https://doi.org/10.1115/ipc2022-87750","url":null,"abstract":"\u0000 Everyone working in the pipeline industry knows that they “Don’t Know What They Don’t Know”. Our behaviours and actions to address this simple phrase have led to significant successes.\u0000 Pipeline Safety Management Systems and Integrity Management Programs have evolved over the last 40 years. This evolution has been a result of adopting quality management systems, learnings from failures and incidents, and regulatory involvement. These advances and areas of improvement are investigated through examples and observations made by the authors.\u0000 The examples and observations in this presentation will demonstrate how organizations of various sizes have successfully addressed safety and integrity challenges over the past forty years. Examples will be discussed from small, medium, and large sized organizations. The management systems have continually improved; these advancements have enabled some of these systems to provide significant value to the pipeline system operators.\u0000 The following will be included in the presentation:\u0000 a) important elements required to meet policy requirements associated with a pipeline safety management system,\u0000 b) the advantages and disadvantages of changing versus constant management system requirements defined within a regulatory framework,\u0000 c) compliance versus beyond-compliance approaches,\u0000 d) the importance of integrated management systems,\u0000 e) the importance of planning and performance verification to meet goals and targets, and\u0000 f) examples to demonstrate continual improvement and alignment with corporate goals.\u0000 Continual improvement in the ISO 9000 series of standards for quality management systems have preceded changes in pipeline safety management systems. This presentation will show correlations and relationships between Quality Management Systems and Pipeline Safety Management Systems. Forecasts about the future of Pipeline Safety Management Systems will also be presented. The examples and observations in this presentation are intended to promote ingenuity and curiosity as methods to supercharge pipeline safety management systems.","PeriodicalId":21327,"journal":{"name":"Risk Management","volume":"201 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2022-09-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"81065971","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":"Building Digital Competencies and Cultivating Innovation in an Integrity Environment","authors":"Karmun Doucette, Janine Woo","doi":"10.1115/ipc2022-87051","DOIUrl":"https://doi.org/10.1115/ipc2022-87051","url":null,"abstract":"\u0000 Integrity programs utilize advanced inspection technology that generate gigabytes to terabytes of information for each inspection performed. Discussions of “Big Data” have permeated across all major platforms in the pipeline industry, from academic institutions, industry associations, to even commercial integrity management solution providers.\u0000 While the management and governance of data is typically in the domain of Information Technology (IT) services, organizations are facing a data consumption problem: they are not able to fully realize the business value in their data. Data is generated at a far greater pace than most organizations can keep up with. There is a widening gap between the potential value suggested by the data, and the actual value in the outcomes achieved from the data itself.\u0000 Bridging the value gap requires an innovative mindset that can conceive new approaches towards the application of data. Innovative solutions to existing problems can help organizations enhance their safety culture and work effectively towards achieving Environmental, Social, and Governance (ESG) goals. However, cultivating that mindset can be challenging in fast-paced, safety-critical environments where workday hours are filled with multiple priorities and stakeholder requests. Furthermore, the consumption of data is not without its risks. Aside from broader issues such as information security and ethical abuse, the unintentional misinterpretation of data is a concern that directly impacts the ability of operators to manage the safety of their pipeline systems. While technology and software applications can help mitigate risks associated with data misuse, a culture promoting data literacy and experimentation fosters a higher-level of care and ownership towards the responsible use of data.\u0000 This paper presents the outcomes from a 2021 pilot program that combines data competency building with the cultivation of an innovative mindset. The program used a team-based “hackathon” like competition to provide a dedicated time and safe space for responsible, lean experimentation of digital problems. In this environment, teams explored innovative solutions to their day-to-day integrity challenges. The program develops technical competencies in data literacy, digital applications, scripting, and analytics; and soft skills including unstructured teamwork, communication, leadership, and a growth mindset. Projects leveraged solutions in areas of data visualization, analytics, automation, and machine learning to drive improvements in effective and efficient integrity management.\u0000 Along with describing the framework of the program, the paper will also cover learnings from the experience, which highlight the importance of long-term investment in building digital competencies and effective, collaborative problem-solving skills. By empowering talent within an organization to drive their own innovative solutions, organizations can improve employee engagement and cultivate a","PeriodicalId":21327,"journal":{"name":"Risk Management","volume":"24 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2022-09-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"84754314","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":"Pipe-CLSM Interface Bond Strength From Axial Pullout Testing","authors":"Caroline Zulkoski, D. Wijewickreme, D. Honegger","doi":"10.1115/ipc2022-86117","DOIUrl":"https://doi.org/10.1115/ipc2022-86117","url":null,"abstract":"\u0000 Buried pipeline systems form the backbone of the oil and gas transportation infrastructure, and the performance of these systems located in areas subject to potential ground movements is a critical consideration in engineering design. In mitigating against future or on-going ground displacement hazards, there are instances where the axial soil restraint (soil anchoring capacity) needs to be increased to avoid transferring loads to adjacent potentially vulnerable components in the pipeline system. One method to increase axial soil restraint is to increase the effective diameter of the pipeline. This can be done by encasing the pipeline in controlled, low-strength material (CLSM). The use of CLSM to increase axial soil restraint on buried pipelines requires that the axial load to produce pipe-CLSM interface bond failure be greater than that required for failure at the CLSM-soil interface. To advance the state of knowledge of the axial failure mechanisms of the soil-CLSM-pipe composite, a systematic full-scale testing program was undertaken using the Advanced Soil Pipe Interaction Research (ASPIRe™) modeling chamber at the University of British Columbia. Research findings from 22 axial pullout tests that were completed to assess the bond strength at the interface between CLSM and NPS 8 steel pipe specimens with various coatings are presented. The tests reveal that the bond strengths as a percentage of compressional strength measured in studies of CLSM cast around cold-formed steel align closely to the values measured from these tests.","PeriodicalId":21327,"journal":{"name":"Risk Management","volume":"70 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2022-09-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"83802685","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 Ductility and Microstructural Attributes for Evaluation of Fracture and Fatigue Performance of API X Grades in High Pressure Gaseous Hydrogen Transmission Pipeline Environments","authors":"D. Stalheim, A. Slifka, M. Connolly, E. Lucon, Aaron Litschewski, P. Uranga","doi":"10.1115/ipc2022-87069","DOIUrl":"https://doi.org/10.1115/ipc2022-87069","url":null,"abstract":"\u0000 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.","PeriodicalId":21327,"journal":{"name":"Risk Management","volume":"49 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2022-09-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"79371556","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":"Bayesian Failure Rate Estimation for the Reliability and Risk Assessment of Energy Pipelines","authors":"M. Dann, D. Lu, C. Dooley, Hassan Tayyab","doi":"10.1115/ipc2022-87113","DOIUrl":"https://doi.org/10.1115/ipc2022-87113","url":null,"abstract":"\u0000 Failure rates, which quantify the normalized likelihood of pipeline failure, are an integral part of assessing the reliability and risk of pipelines. The industry-wide trend of utilizing probabilistic methods for estimating failure rates raises the question whether the frequentist or Bayesian definition of probability is more suitable. The paper illustrates some limitations of the frequentist probability definition for pipeline risk assessment and supports the Bayesian approach for analyzing pipeline failure rates. The Bayesian quantification of probabilities leads to coherent uncertainty assessment and propagation even if evidence is combined from different sources either through a repetition of the prior-likelihood model or a multi-level / hierarchical approach that integrates all available data and information in one model. Selecting or disregarding data for estimating failure rates is no longer necessary as they all contribute to the result based on their relative uncertainties. Examples are provided in the paper to illustrate the benefits of the Bayesian probability approach.","PeriodicalId":21327,"journal":{"name":"Risk Management","volume":"32 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2022-09-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"75805011","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":"Systematic Assessment of Risk Control Effectiveness","authors":"E. Grant, Shreya Ambasta, Mark S. Jean","doi":"10.1115/ipc2022-87280","DOIUrl":"https://doi.org/10.1115/ipc2022-87280","url":null,"abstract":"\u0000 The inherent risks associated with pipeline operations are significant. Companies dedicate countless resources to identifying, assessing, and controlling risks across their operations. Risk management activities are completed by personnel at all levels, from field staff to senior management. This ensures that risks are identified and managed at all levels within the company to align with company risk tolerance. Where risks are identified that are higher than company tolerance levels, additional controls are typically developed. For most risks, a series of controls is developed to protect in different ways or in different scenarios. In many cases, a control may protect against multiple different risks.\u0000 When risk assessments are completed, there is the possibility that the effectiveness of controls that have been developed to manage the risk are incorrectly considered [1]. Individuals or teams completing the review of controls are assessing their effectiveness higher or lower than they actually are [2]. This is typically the result of a controls assessment that does not fully consider the functionality, availability, and reliability of the control. The result is the potential for a risk being accepted that may be beyond company risk tolerance or the allocation of additional resources on risks that are already well controlled. To account for a control’s partial effectiveness, they are often layered, with multiple controls working together to mitigate a risk [3]. In these instances, if one control is unable to manage the risk, another would be available to provide additional mitigation to reduce the possibility or consequence of a major risk event.\u0000 With the combination of thousands of hazards that can lead to different major risk events with hundreds of unique controls, it can be difficult to quantify the degree of risk to which a company is exposed. This paper explores the approach to systematically assessing risk controls, enabling improved understanding and ability to communicate the overall organizational risk and prioritization of improvements for the most critical controls.","PeriodicalId":21327,"journal":{"name":"Risk Management","volume":"60 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2022-09-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"78338489","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":"Machine Learning-Based Severity Assessment of Pipeline Dents","authors":"Huang Tang, Jialin Sun, Martin Di Blasi","doi":"10.1115/ipc2022-87211","DOIUrl":"https://doi.org/10.1115/ipc2022-87211","url":null,"abstract":"\u0000 One challenge to pipeline operators is to identify potentially injurious dents among thousands of reported deformation features using limited information (e.g., reported dent’s length, width, and depth) and to prioritize the efforts and allocate the resources to obtain additional more detailed information (e.g., dent profiles) for those potentially severe dents. An innovative approach based on machine learning predictions stemming from a representative dictionary of finite element analysis (FEA) generated prototypes was developed. The proposed approach predicts multiple severity-based indicators for each dent, then combines them in an overall severity score, which finally is used to prioritize the acquisition of dent profiles. Once the dent profiles are available, detailed level 3 FEA quantitative reliability analyses, following previously developed and published methodology (QuAD) [1], is performed allowing pipeline operators to confirm dent’s severity more accurately and perform an integrity risk informed decision (IRIDM) leading to a safer and more efficient integrity management.\u0000 Three severity indicators were considered herein and intended to address both formation-induced and service-induced failure mechanisms. The maximum dent formation plastic strain and accumulated ductile failure damage were used for evaluating the likelihood of forming a crack during indentation. The third indicator was the stress concentration factors (SCFs) to assess the potential of service-induced failure due to fatigue.\u0000 A machine learning model, as an emulator, trained and tested using ∼4000 FEA-based dent prototypes was shown to be able to effectively predict dent severity indicators previously referred to. These predicted dent severity indicators are combined to produce an overall severity score, which was finally used to prioritize the acquisition of the detailed dent profiles. Once profiles are obtained, detailed FEA quantitative reliability assessments will ultimately confirm the severity and hence drive repair/no repair decisions, enabling in this way an efficient and effective allocation of resources.","PeriodicalId":21327,"journal":{"name":"Risk Management","volume":"18 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2022-09-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"91014659","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}