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Proceedings Papers

Consequence Modeling of Hypothetical Releases From Carbon Dioxide (CO 2 ) Transport Pipelines

Jeremy Fontenault, Tara Franey
Proc. ASME. IPC2022, Volume 1: Pipeline Safety Management Systems; Project Management, Design, Construction, and Environmental Issues; Strain-Based Design and Assessment; Risk and Reliability; Emerging Fuels and Greenhouse Gas Emissions, V001T08A010, September 26–30, 2022
Paper No: IPC2022-87131
DOI: https://doi.org/10.1115/IPC2022-87131
View Paper titled, Consequence Modeling of Hypothetical Releases From Carbon Dioxide (CO 2 ) Transport Pipelines
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Topics: Carbon capture and storage, Carbon dioxide, Modeling, Pipelines, Risk
Proceedings Papers

Estimating Measurement Performance With Truncated Data Sets

Jason Skow, Joseph W. Krynicki, Alex Fraser, Gustavo Gonzalez
Proc. ASME. IPC2022, Volume 2: Pipeline and Facilities Integrity, V002T03A026, September 26–30, 2022
Paper No: IPC2022-87060
DOI: https://doi.org/10.1115/IPC2022-87060
View Paper titled, Estimating Measurement Performance With Truncated Data Sets
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Topics: Algorithms, American Petroleum Institute, Errors, Event history analysis, Fracture (Materials), Inspection, Nondestructive evaluation, Pipeline integrity, Pipelines, Risk
Proceedings Papers

Optimizing the Prioritization of First-Time ILIs Using Quantitative Risk and Machine Learning

Brenn Snider, Wei Xiang, Billy Zhang, Sergiu Lecut
Proc. ASME. IPC2022, Volume 1: Pipeline Safety Management Systems; Project Management, Design, Construction, and Environmental Issues; Strain-Based Design and Assessment; Risk and Reliability; Emerging Fuels and Greenhouse Gas Emissions, V001T07A030, September 26–30, 2022
Paper No: IPC2022-87309
DOI: https://doi.org/10.1115/IPC2022-87309
View Paper titled, Optimizing the Prioritization of First-Time ILIs Using Quantitative Risk and Machine Learning
Click here to open pdf in another window PDF for Optimizing the Prioritization of First-Time ILIs Using Quantitative Risk and Machine Learning
Topics: Machine learning, Risk, Risk assessment, Risk reduction
Proceedings Papers

Systematic Assessment of Risk Control Effectiveness

Eric Grant, Shreya Ambasta, Mark Jean
Proc. ASME. IPC2022, Volume 1: Pipeline Safety Management Systems; Project Management, Design, Construction, and Environmental Issues; Strain-Based Design and Assessment; Risk and Reliability; Emerging Fuels and Greenhouse Gas Emissions, V001T07A029, September 26–30, 2022
Paper No: IPC2022-87280
DOI: https://doi.org/10.1115/IPC2022-87280
View Paper titled, Systematic Assessment of Risk Control Effectiveness
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Topics: Risk assessment, Risk, Hazards, Pipelines, Reliability, Risk control, Risk management, Teams
Proceedings Papers

Bayesian Failure Rate Estimation for the Reliability and Risk Assessment of Energy Pipelines

Markus Dann, Dongliang Lu, Colin Dooley, Hassan Tayyab
Proc. ASME. IPC2022, Volume 1: Pipeline Safety Management Systems; Project Management, Design, Construction, and Environmental Issues; Strain-Based Design and Assessment; Risk and Reliability; Emerging Fuels and Greenhouse Gas Emissions, V001T07A010, September 26–30, 2022
Paper No: IPC2022-87113
DOI: https://doi.org/10.1115/IPC2022-87113
View Paper titled, Bayesian Failure Rate Estimation for the Reliability and Risk Assessment of Energy Pipelines
Click here to open pdf in another window PDF for Bayesian Failure Rate Estimation for the Reliability and Risk Assessment of Energy Pipelines
Topics: Failure, Pipelines, Reliability, Risk assessment, Probability, Uncertainty, Risk
Proceedings Papers

Risk Based Asset Management Model for a Natural Gas Transmission Pipeline

Martin Hommes, Eric Jager, Paul Kassenberg, Oleg Borisov, Jan Ribberink
Proc. ASME. IPC2022, Volume 1: Pipeline Safety Management Systems; Project Management, Design, Construction, and Environmental Issues; Strain-Based Design and Assessment; Risk and Reliability; Emerging Fuels and Greenhouse Gas Emissions, V001T01A008, September 26–30, 2022
Paper No: IPC2022-85980
DOI: https://doi.org/10.1115/IPC2022-85980
View Paper titled, Risk Based Asset Management Model for a Natural Gas Transmission Pipeline
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Topics: Natural gas, Pipelines, Risk
Proceedings Papers

Onshore Pipeline Safety Consequence Modelling in Support of the Development of a Risk-Based Safety Class System

Mark Stephens, Howard Yue, Ann Halford, Niall Foster
Proc. ASME. IPC2022, Volume 1: Pipeline Safety Management Systems; Project Management, Design, Construction, and Environmental Issues; Strain-Based Design and Assessment; Risk and Reliability; Emerging Fuels and Greenhouse Gas Emissions, V001T07A020, September 26–30, 2022
Paper No: IPC2022-87217
DOI: https://doi.org/10.1115/IPC2022-87217
View Paper titled, Onshore Pipeline Safety Consequence Modelling in Support of the Development of a Risk-Based Safety Class System
Click here to open pdf in another window PDF for Onshore Pipeline Safety Consequence Modelling in Support of the Development of a Risk-Based Safety Class System
Topics: Hazards, Modeling, Pipelines, Risk, Safety
Proceedings Papers

A Risk-Based Safety Class System for Onshore Pipelines

Maher Nessim, Mark Stephens, Howard Yue
Proc. ASME. IPC2022, Volume 1: Pipeline Safety Management Systems; Project Management, Design, Construction, and Environmental Issues; Strain-Based Design and Assessment; Risk and Reliability; Emerging Fuels and Greenhouse Gas Emissions, V001T01A011, September 26–30, 2022
Paper No: IPC2022-87099
DOI: https://doi.org/10.1115/IPC2022-87099
View Paper titled, A Risk-Based Safety Class System for Onshore Pipelines
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Topics: Design, Pipelines, Pressure, Risk, Safety
Proceedings Papers

Reliability Model to Predict Likelihood of Failure of Facility Auxiliary Piping Assets

Syed Haider, Millan Sen, Doug Lawrence
Proc. ASME. IPC2022, Volume 1: Pipeline Safety Management Systems; Project Management, Design, Construction, and Environmental Issues; Strain-Based Design and Assessment; Risk and Reliability; Emerging Fuels and Greenhouse Gas Emissions, V001T07A028, September 26–30, 2022
Paper No: IPC2022-87276
DOI: https://doi.org/10.1115/IPC2022-87276
View Paper titled, Reliability Model to Predict Likelihood of Failure of Facility Auxiliary Piping Assets
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Topics: Failure, Pipes, Reliability, Inspection, Fittings, Flanges, Flow (Dynamics), Leakage, Architecture, Corrosion
Proceedings Papers

Advanced Reliability Analysis at Slope Crossings

Matthew Fowler, Kachi Ndubuaku, Nader Yoosef-Ghodsi
Proc. ASME. IPC2022, Volume 1: Pipeline Safety Management Systems; Project Management, Design, Construction, and Environmental Issues; Strain-Based Design and Assessment; Risk and Reliability; Emerging Fuels and Greenhouse Gas Emissions, V001T07A006, September 26–30, 2022
Paper No: IPC2022-86908
DOI: https://doi.org/10.1115/IPC2022-86908
View Paper titled, Advanced Reliability Analysis at Slope Crossings
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Topics: Computer simulation, Computer software, Deformation, Engineering simulation, Event history analysis, Experimental design, Failure, Finite element analysis, Finite element model, Geohazards
Proceedings Papers

Balancing Hydrogen Networks Safely: A Method for Calculating Linepack Potential Without Causing Integrity Risk Due to Hydrogen-Enhanced Fatigue

Onno Wesselink, Alfons Krom, Martin van Agteren
Proc. ASME. IPC2022, Volume 1: Pipeline Safety Management Systems; Project Management, Design, Construction, and Environmental Issues; Strain-Based Design and Assessment; Risk and Reliability; Emerging Fuels and Greenhouse Gas Emissions, V001T08A003, September 26–30, 2022
Paper No: IPC2022-86674
DOI: https://doi.org/10.1115/IPC2022-86674
View Paper titled, Balancing Hydrogen Networks Safely: A Method for Calculating Linepack Potential Without Causing Integrity Risk Due to Hydrogen-Enhanced Fatigue
Click here to open pdf in another window PDF for Balancing Hydrogen Networks Safely: A Method for Calculating Linepack Potential Without Causing Integrity Risk Due to Hydrogen-Enhanced Fatigue
Topics: Fatigue, Fluctuations (Physics), Hydrogen, Pipeline integrity, Pressure, Risk
Proceedings Papers

Explained: Ultrasonic Self-Propelled Robotic Inspection Solution for Unpiggable Dock Line

Corey Richards, Cedric Bolduc, Børge Hamnes
Proc. ASME. IPC2022, Volume 2: Pipeline and Facilities Integrity, V002T03A007, September 26–30, 2022
Paper No: IPC2022-86889
DOI: https://doi.org/10.1115/IPC2022-86889
View Paper titled, Explained: Ultrasonic Self-Propelled Robotic Inspection Solution for Unpiggable Dock Line
Click here to open pdf in another window PDF for Explained: Ultrasonic Self-Propelled Robotic Inspection Solution for Unpiggable Dock Line
Topics: Inspection, Robotics, Flow (Dynamics), Testing, Computers, Containment, Downtime, Modeling, Pipelines, Pipes
Proceedings Papers

Considering Roadway Traffic in Quantitative Risk Assessment for Natural Gas Pipelines

Dongliang Lu, Tammeen Siraj, Karen Warhurst, Konstantinos Dimitriadis, Matt Towers
Proc. ASME. IPC2022, Volume 1: Pipeline Safety Management Systems; Project Management, Design, Construction, and Environmental Issues; Strain-Based Design and Assessment; Risk and Reliability; Emerging Fuels and Greenhouse Gas Emissions, V001T07A022, September 26–30, 2022
Paper No: IPC2022-87251
DOI: https://doi.org/10.1115/IPC2022-87251
View Paper titled, Considering Roadway Traffic in Quantitative Risk Assessment for Natural Gas Pipelines
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Topics: Natural gas distribution, Risk, Risk assessment, Roads, Traffic
Proceedings Papers

Management System Enabled ESG Performance

Mark S. Jean, Eric Grant
Proc. ASME. IPC2022, Volume 1: Pipeline Safety Management Systems; Project Management, Design, Construction, and Environmental Issues; Strain-Based Design and Assessment; Risk and Reliability; Emerging Fuels and Greenhouse Gas Emissions, V001T01A004, September 26–30, 2022
Paper No: IPC2022-86870
DOI: https://doi.org/10.1115/IPC2022-86870
View Paper titled, Management System Enabled ESG Performance
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Topics: Accounting, Climate, Columns (Structural), Insurance, Leadership, Pipelines, Risk, Sustainability, Transparency
Proceedings Papers

Overcoming Challenges for Quantitative Risk Modeling Using Machine Learned Data Correlations and Predictive Modeling

Stephen F. Biagiotti, Jr, Dan Williams, Sergiy Kondratyuk, Brett Johnson
Proc. ASME. IPC2022, Volume 2: Pipeline and Facilities Integrity, V002T03A004, September 26–30, 2022
Paper No: IPC2022-87236
DOI: https://doi.org/10.1115/IPC2022-87236
View Paper titled, Overcoming Challenges for Quantitative Risk Modeling Using Machine Learned Data Correlations and Predictive Modeling
Click here to open pdf in another window PDF for Overcoming Challenges for Quantitative Risk Modeling Using Machine Learned Data Correlations and Predictive Modeling
Topics: Machine learning, Machinery, Modeling, Risk
Proceedings Papers

Characterization of Through-Wall Cracks and Resulting Leakage Rates in Pipelines

Elaheh Ebrahimnia, Shawn Prasad, Amandeep Virk, Khurram Shahzad, Muntaseer Kainat, Saheed Akonko
Proc. ASME. IPC2022, Volume 1: Pipeline Safety Management Systems; Project Management, Design, Construction, and Environmental Issues; Strain-Based Design and Assessment; Risk and Reliability; Emerging Fuels and Greenhouse Gas Emissions, V001T07A026, September 26–30, 2022
Paper No: IPC2022-87262
DOI: https://doi.org/10.1115/IPC2022-87262
View Paper titled, Characterization of Through-Wall Cracks and Resulting Leakage Rates in Pipelines
Click here to open pdf in another window PDF for Characterization of Through-Wall Cracks and Resulting Leakage Rates in Pipelines
Topics: Computational fluid dynamics, Finite element analysis, Fracture (Materials), Leakage, Pipelines, Surface roughness, Wall thickness, Pressure, Turbulence, Risk
Proceedings Papers

Comparison of Machine Learning Models for Quantitative Risk Modelling of Pipeline Systems

Daryl Bandstra, Juan S. Rojas, Alex Fraser, Mari Shironishi
Proc. ASME. IPC2022, Volume 1: Pipeline Safety Management Systems; Project Management, Design, Construction, and Environmental Issues; Strain-Based Design and Assessment; Risk and Reliability; Emerging Fuels and Greenhouse Gas Emissions, V001T07A025, September 26–30, 2022
Paper No: IPC2022-87258
DOI: https://doi.org/10.1115/IPC2022-87258
View Paper titled, Comparison of Machine Learning Models for Quantitative Risk Modelling of Pipeline Systems
Click here to open pdf in another window PDF for Comparison of Machine Learning Models for Quantitative Risk Modelling of Pipeline Systems
Topics: Machine learning, Modeling, Pipeline systems, Risk, Artificial neural networks, Failure, Fittings, Industrial research, Pipelines, Pipes
Proceedings Papers

Probabilistic Analysis Applied to the Risk of SCC Failure

Scott Riccardella, Owen Malinowski, Pete Riccardella, Steve Potts, Sean Moran, Kelly Thompson, Ann Reo
Proc. ASME. IPC2022, Volume 1: Pipeline Safety Management Systems; Project Management, Design, Construction, and Environmental Issues; Strain-Based Design and Assessment; Risk and Reliability; Emerging Fuels and Greenhouse Gas Emissions, V001T07A005, September 26–30, 2022
Paper No: IPC2022-86906
DOI: https://doi.org/10.1115/IPC2022-86906
View Paper titled, Probabilistic Analysis Applied to the Risk of SCC Failure
Click here to open pdf in another window PDF for Probabilistic Analysis Applied to the Risk of SCC Failure
Topics: Artificial neural networks, Failure, Machine learning, Risk, Probability, Algorithms, Coating processes, Coatings, Compressors, Fracture mechanics
Proceedings Papers

Structured, Systematic Threat Based Approach to Evaluate and Improve Data Quality to Facilitate Digital Transformation

Pushpendra Tomar, Betsy Kruse, Samah Hasan, Sergiy Kondratyuk
Proc. ASME. IPC2022, Volume 2: Pipeline and Facilities Integrity, V002T03A005, September 26–30, 2022
Paper No: IPC2022-87872
DOI: https://doi.org/10.1115/IPC2022-87872
View Paper titled, Structured, Systematic Threat Based Approach to Evaluate and Improve Data Quality to Facilitate Digital Transformation
Click here to open pdf in another window PDF for Structured, Systematic Threat Based Approach to Evaluate and Improve Data Quality to Facilitate Digital Transformation
Topics: Cloud computing, Coating processes, Coatings, Data storage systems, Machine learning, Pipeline integrity, Pipelines, Reliability, Risk, Risk assessment
Proceedings Papers

Chasing Ghosts: An Integrative Approach to Properly Qualify a Pipeline Threat

Michael Turnquist
Proc. ASME. IPC2022, Volume 2: Pipeline and Facilities Integrity, V002T03A030, September 26–30, 2022
Paper No: IPC2022-87120
DOI: https://doi.org/10.1115/IPC2022-87120
View Paper titled, Chasing Ghosts: An Integrative Approach to Properly Qualify a Pipeline Threat
Click here to open pdf in another window PDF for Chasing Ghosts: An Integrative Approach to Properly Qualify a Pipeline Threat
Topics: Pipelines, Testing, Crack detection, Nondestructive evaluation, Cracking (Materials), Electrical resistance, Fatigue testing, Fracture (Process), Inspection, Materials properties