Special issue on artificial intelligence (AI) applications in pipeline reliability engineering and maintenance

Pipelines play an important role in the transport of energy resources such as oil, natural gas, biofuels and hydrogen. Pipeline integrity, security and safety are a top priority in the energy sector. For example, ensuring the continuous operation of a pipeline is linked to a better economy of scale and lower costs. In addition, it protects the environment. The pipeline industry has adopted benchmarks and guidelines to analyze, monitor, predict and mitigate various types of pipeline failure, including ones triggered by design parameters, operational conditions, weather, materials and incidents/accidents. Increasingly, they are using information technology and smart tools to help them do this, through the collection and analysis of data generated by inline inspections, condition monitoring and maintenance/repair activities, as well as failure response. Considering the geographical dispersion of pipelines, and their continuous operation, the volume of data they are collecting and storing is vast.  The question now is how they can best use these big data to support intelligent asset management practices, improving their operational efficiency, enhancing the integrity of pipeline assets, and mitigating risks for the environment and communities.

This special issue will explore the various applications of emerging artificial intelligence (AI) tools and technologies in maintenance and reliability engineering of pipelines. We invite contributions from academic researchers and industry practitioners in the form of research papers, state-of-the-art reviews and case studies.

Topics covered:

The topics include (but are not limited to) AI applications in:

• Pipeline condition monitoring and assessment
• Predictive maintenance tools and technologies
• Failure mapping, modelling and analysis
• Maintenance scheduling and resource planning
• Maintenance logistics and supply chain management
• Reliability-based maintenance management
• Availability-based maintenance for critical pipelines
• Pipeline risk modelling, assessment and analysis
• Use of sensing and imaging technologies for failure detection and diagnosis
• Resilience modelling and analysis of pipelines subject to natural hazards
• Crisis management and risk response planning
• Capital planning and costing for pipeline maintenance and rehabilitation

Important deadlines:

• Submission deadline: 30 June 2022
• Publication date: 30 September 2022

Submission instructions:

Please read the Guide for Authors before submitting. All articles should be submitted online; please select SI: AIAPREM on submission. All submissions will undergo a normal peer-review process. If the manuscript is accepted, the article will be published open access with no fee payable by the author.

Guest Editor:

• Fuzhan Nasiri, Concordia University, Canada. Email: fuzhan.nasiri@concordia.ca