Existing hydrogen transmission codes (ASME B31.12, IGEM TD/1 Supp. 2) are applicable to any blend regardless of %H2. These codes require fracture and fatigue assessments on the pipeline to enable operation above 0.5 Design Factor. Indicative pipeline assessments undertaken in the NTS Materials Testing to Enable Hydrogen Injection in High Pressure Pipelines NIA project suggested that many National Transmission System (NTS) pipelines would require reductions of pressure from their current MOPs and/or changes in operational conditions (e.g. reduced pressure cycling) to pass these assessments.
This project will undertake assessments (fracture and fatigue) across the entire NTS to determine the potential impact of hydrogen on pipeline operation. With the results informing the 2% blend safety case submission and Project Unite and Project Union.
Benefits
This project will provide first pass assessment on the impact of hydrogen and hydrogen-natural gas blends on the operation of the national transmission system (NTS). This will inform the roll out of network-level blending (Project Unite) and 100% hydrogen networks (Project Union), and feed into the 2% blend safety case. Furthermore, the work undertaken in this project will provide justification for future projects/data gathering exercises to enable optimised network operation.
Learnings
Outcomes
Work Package 1: Data Collection and Processing
· Information Gathering
o Collected and processed GIS data for 28 active NTS feeders
o Ensured compatibility with DNV’s Synergi Pipeline tool for dynamic segmentation and analysis
o Addressed data inconsistencies (e.g., route overlaps).
· Pressure Sensor Data
o Integrated large volume of hourly pressure data covering 2019 to 2023 from sensors across the National Transmission System (NTS).
o Cleaned and aligned data to pipeline segments for fatigue analysis.
o Enabled visualisation and cycle counting within Synergi Pipeline.
Work Package 2: Fracture Mechanics Analysis
· Objective
o Assess capability of NTS pipeline seam and girth welds for hydrogen transmission using a fracture mechanics approach in accordance with BS 7910.
· Key Inputs:
o Pipe geometry, material grade, starting flaw size, welding residual stress, weld misalignment, fracture toughness, and pressure cycling data.
o Assumptions made in absence of measured data. Different scenarios assessed to reflect current state of data and possible future states following further data generation/collation.
· Assessment Scenarios
o 100% Hydrogen
§ ‘Best Estimate’ and ‘Upper Bound’ assumption cases run enabled determination of operational parameters for all NTS pipelines. These results will be utilised internally to network design and operation.
o 5% Hydrogen Blend
§ Modelled the ‘Best Estimate’ with a 20% uplift in fracture toughness – based on data from NIA NGT0213: Characteristics of hydrogen and natural gas blends in the NTS.
§ Assessment showed benefit of increased fracture toughness in terms of operational parameters on critical pipelines.
· Sensitivity Analyses
o Fatigue Crack Growth Rate
§ NG’s data-driven curve showed significant improvement over IGEM/TD/1.
o Pressure Cycle Data Cleaning
§ Removing anomalous data improved acceptable pressures significantly for those pipelines limited by fatigue.
o Cycle Management
§ Reducing high-magnitude cycles was shown to be a potential mechanism to increase fatigue life and enable higher MAOPs.
Work Package 3: Network Impact
· Zone-Based Assessment:
o Compared calculated “Zone Effective MOP” to current MAOP across 7 zones of the National Transmission System.
o Identified zones with potential reinforcement needs due to pressure reductions.
· Reinforcement Confidence Levels:
o The exact reinforcement requirements can only be determined following detailed network modelling which was deemed inappropriate at this stage. Instead, the National Gas Network Modelling team estimated a confidence level as to the extent of reinforcement that would be needed based on the fracture assessment scenarios calculated in WP2.
o It was found that some level of reinforcement of the network would likely be required in the majority of zones.
o Reinforcement could involve changes to network operation (e.g. reduce pressure cycling), reconfiguration of compressors or new pipeline builds.
· Sensitivity with NG Fatigue Curve:
o The use of a fatigue crack growth curve based on National Gas test data, was shown to reduce fatigue-dominated pipeline count by 83, leading to improved Zone Effective MOPs, thereby reducing reinforcement needs.
· 100% Hydrogen Scenario:
o Not directly assessed due to different operational assumptions.
o Furthermore, the pipeline operational conditions in a 100% hydrogen network would be designed to account for the pipeline capability
Recommendations
· Data and Methodology Enhancements:
o Develop a standard fatigue crack growth curve using NG and industry data.
o Improve pressure cycle data quality and management or generate more detailed pressure cycling forecasting models to feed into pipeline assessments.
· Future Work Areas:
o Additional assessments (e.g., assess axial stresses, explore probabilistic methods).
o Refined input data (e.g., confirm hydrogen blend effects of fracture toughness values, capture additional pipe mill and in-field weld data).
o Methodology updates (e.g., understand implication of sub-critical crack growth in hydrogen pipeline design and operation).
o Update network modelling based on refined results.
The project value tracking is listed below:
· Maturity
o TRL 4-5. Assessments used existing approaches.
· Innovation Opportunity
o 100% of single asset class. All pipelines were considered.
· Deployment Costs
o £0.00. No direct deployment costs associated with this project.
· Innovation Cost
o £ 213,333.33. Supplier and internal costs.
· Financial Saving
o £ 0.00. Assessment will help establish safe operating regime for NTS pipelines in hydrogen and hydrogen-natural gas blends. No direct cost saving expected.
· Safety
o 0%. Assessment will help establish safe operating regime for NTS pipelines in hydrogen and hydrogen-natural gas blends. Without these assessment NTS pipelines might be at risk of failure due to hydrogen embrittlement.
· Environment
o 0.0 tonnes CO2e. Assessment will help establish safe operating regime for NTS pipelines in hydrogen and hydrogen-natural gas blends. No direct environmental saving expected, although CO2 saving would occur with the addition of H2 to natural gas.
· Compliance
o Ensures compliance. Assessments are required as part of our new TR/10 repurposing process and aligns with requirements of the latest ASME hydrogen pressure code.
· Skills & Competencies
o Individuals. Will develop knowledge of individuals working on the project.
· Future Proof
o Must Have for the business strategy. Assessments are required to enable business strategy of enabling hydrogen blends onto the NTS.
Lessons Learnt
Initial concerns raised by National Gas with respect to the complexity of previous results and how to interpret these results in the context of likely success of being able to repurpose for hydrogen operation. These concerns were taken on board and through a combination of regular meetings to discuss the assumptions utilised, the methodology, approach and the impact of these results, it was agreed that whilst a worst case/conservative assessment was required to be considered, it was also likely that not all the worst case assumptions would likely be coincident and hence other intermediate scenarios were considered and a most realistic “Best Estimate” case was presented. This approach has hopefully helped National Gas to explain the findings to other stakeholders and has assisted in the messaging regarding converting the National Transmission System to hydrogen operation.
The flexible approach taken to substitute the planned DNV network modelling activities with a qualitative/semi-quantitative assessment by National Gas Network Modelling SMEs was very successful in ensuring the findings could be contextualised appropriately. This kind of approach is recommended for future projects where possible.
The availability and quality of the data inputs was another critical aspect of this project. There was significant success in providing data to DNV during the project, however, if the data quality could be checked and ensured prior to sharing, then future projects would run more smoothly with fewer queries over the accuracy and completeness of project outputs.