Application of AI in monitoring hydrogen pipelines

The School of Computing, Engineering & Digital Technologies at Teesside University in collaboration with the Tshwane University of Technology AI Hub in South Africa invites applications for a full-time PhD studentship.

Hydrogen, as a clean and efficient energy carrier, holds immense potential for reducing carbon emissions. However, the low viscosity and highly flammable nature of hydrogen necessitates stringent safety measures, particularly in its transport through pipelines. This PhD position focuses on the application of artificial intelligence (AI) to enhance the monitoring and safety of hydrogen pipelines, addressing critical aspects of this emerging infrastructure.

The research will be structured around three core pillars.

First, an experimental investigation will be conducted to study hydrogen leaks from pipelines under controlled laboratory conditions. This will involve performing various leak scenarios to gather detailed data on leak characteristics and behaviour. Second, computational fluid dynamics (CFD) modelling will be employed to further understand the mechanisms and parameters affecting hydrogen leaks. This modelling will provide insights into the dynamics of hydrogen flow and dispersion, aiding in the development of more accurate predictive models. Third, machine learning (ML) techniques will be implemented to detect and characterise leaks in real-time. By analysing vast datasets from numerical and experimental studies, ML algorithms can identify patterns and anomalies that signify potential leaks, enabling prompt and efficient responses.

This interdisciplinary research will integrate experimental, computational, and AI-driven approaches to create a comprehensive pipeline monitoring system. You will collaborate with experts in AI, engineering, and energy systems, utilising state-of-the-art facilities and datasets.

You should have a strong background in fluid mechanics and dynamics, and experience in CDF modelling, along with the ability to develop skills in analytical data, AI, and ML technologies.

This project will involve international collaboration with Tshwane University of Technology AI Hub, working closely with the research teams led by Professor Anish Kurien and Dr Coneth Richards. Opportunities for spending time at TUT will be explored. Additionally, you have the opportunity to work at Teesside University’s newly established Net Zero Industry Innovation Centre with fully equipped laboratories for CCUS, H2 innovation, smart energy integration and modelling, and circular economy.

You will be supported in presenting research outcomes at review meetings, disseminating results at international conferences, and publishing peer-reviewed journal papers.

The supervisor is Dr Sina Rezaei Gomari from the Centre for Sustainable Engineering.

Funding

The fully-funded PhD studentship covers tuition fees for the period of a full-time PhD Registration of up to four years and provides an annual tax-free stipend of £18,622 for three years, subject to satisfactory progress.

Entry requirements

You should hold or expect to obtain a good honours degree (2:1 or above) in a relevant discipline. A master’s level qualification in a relevant discipline is desirable, but not mandatory. International students will be subject to the standard entry criteria relating to English language ability, ATAS clearance and, when relevant, UK visa requirements and procedures.

Applications are welcome from UK and international students.

How to apply

Application is online.

Key dates

• Application closing date: 5.00pm, 29 November 2024.
• Shortlisting and interviews: December 2024.
• Start date: March 2025.