# Inspection of Coated Hydrogen Transportation Pipelines
## 3 Pipeline Inspection
### Prediction Models  
This section will summarise recent trends in prediction models--the second key step in pipeline integrity management. A model has been developed to analyse the kinetics of fracture in protective coatings/delamination growth of metal and steel bodies [89]. It considers a \"penny-shaped\" crack propagating parallel to the pipe wall, and uses the fact that the \"driving force\" for such cracks is the \"internal pressure of accumulated hydrogen gas in the delamination cavity\" [89]. Critically, the importance of this study is on account of the fact that HIC growth was considered under \"real\" gas conditions as opposed to \"ideal\" gas conditions [89]. This enables the model to be used to make higher accuracy predictions to be made about the lifetime of pipelines. A different approach involved attempting to use cohesive zone modelling (CZM) alongside hydrogen diffusion to model \"hydrogen-induced fracture initiation in a hot rolled bonded clad steel pipe [90].\" This involves considering a traction separation law (TSL) to describe the response of \"cohesive elements\" along a fracture path [90]. The TSL in turn is characterised by cohesive parameters known as the critical cohesive stress (\(\sigma_{\text{c}}\)), the critical separation (\(\delta_{\text{c}}\)) and the cohesive energy (\(\Gamma_{\text{c}}\)) [90]. Depending on the concept being used to describe the effect of hydrogen on steel (e.g. HEDE, HELP, or combined) two out of the three cohesive parameters can be independently varied to account for changes in hydrogen concentration [91]. 2D coupled hydrogen diffusion and CZM were used and it was determined that for a pipe with made API X60 with a 316L clad, best fit to experimental results was achieved when cohesive stiffness \((\kappa_{n})=4\cdot 10^{6}\) MPa/mm and \(\sigma_{\text{c}}=1210\) MPa [90]. A possible extension to this could be using a 3D modelling approach to investigate the lack of agreement between experimental and predicted fracture initiation points in air and \"hydrogen influence\" [90]. Providing a more comprehensive review of CZM, [PERSON] et al. [91] reported that the discussed predictive method of coupled diffusion and CZM works well for replicating \"single experimental results\" by adjustment of the cohesive parameters, but encounters difficulties when transferred to other hydrogen systems. Examples of this include the method not being able to rationalize enhanced crack growth under higher pressures and higher than predicted levels of local hydrogen concentration due to dislocation transport. It is suggested that better agreement with results could be achieved by determining the input parameters for the system under study. This seemingly implies having to conduct extensive testing for every new model under study. A possible direction to explore could be a review to identify systems that encounter similar difficulties with the method and provide a quantification of the degree of disagreement between experimental and predicted results. Now, in the context of corrosion, there was a distinction drawn between \"deterministic\" and \"probabilistic\" models for pipeline corrosion growth [92]. These models largely describe the growth rates of pitting--the most serious risk in pipeline integrity [92]. The models discussed and a brief description of them are as follows [92]:  
* \"Single-value corrosion growth rate model\": Utilises a corrosion growth rate that is constant for modelling over the required period. * \"Linear corrosion growth rate model\": Assumes corrosion growth is a linear function of time. * \"Non-linear corrosion growth rate model\": Assumes corrosion growth is a nonlinear function of time with soil and pipe material being parameters that can be controlled. * \"Markov model: Uses a \"continuous-time, non-homogeneous linear growth approach\" using \"initial pit-depth distribution\" and a \"soil-pipe dependent parameter\".