In years of increased interest in Carbon Capture and Storage technologies and projects, safety and operability of CO₂ pipelines are crucial for successful transportation from emitters to storage sites. Within this framework, due to its potentially catastrophic consequences and lack of fully validated and recognised design methods, Ductile Fracture Propagation represents a key issue.

First, existing technical literature and standards – especially ISO 27913 and DNV-RP-F104 – are reviewed and outlined. The simplified models they propose, generally derived from Natural Gas applications, are critically discussed, alongside the underlying experimental activities for their development. Gaps and inconsistencies persist in areas like: the validity limits and applicability of each model, especially where the experimental validation appears to be lacking (e.g. small diameter pipelines); the definition and selection of input parameters (for instance, representative flow pressure and temperature); the requalification of existing assets, where fracture toughness of the material might be low and defining an adequate safety level may not be straightforward. Despite the limitations, these models are much cheaper, simpler, and less time consuming than other possible approaches such as coupled Computational Fluid Dynamics / Finite Elements simulations or full-scale propagation tests.

Because of this, they have been used as the main reference for the design and development of in-house engineering tools, which are briefly discussed, validated against published experimental data and designs, and subsequently applied to a heterogeneous set of case studies, comprising new and existing pipelines, transporting both gas- and dense-phase CO₂. From their results, the paper aims to propose a workflow to generalise and standardise the approach to the issue of Ductile Fracture Propagation in CO₂ pipelines, providing a comprehensive frame based on current, state-of-the-art knowledge. This can simplify engineering activities, ultimately ensuring replicability of results, assets’ safety, and cost savings.