Abstract
Ageing affects the safety in chemical and oil industry, in particular the equipment containing dangerous substances. It could give rise to serious accidental scenarios, such as dispersions of toxic substances, fires, and explosions, as well as environmental contamination. In the next future, this criticality is expected to increase due to huge number of facilities that will not be replaced because of the dismission of several industries. Therefore, it is essential for both managers and supervisory authorities to plan the most efficient strategies for their management and maintenance before to put them out of service. Particular attention must be given to large atmospheric tanks used for the storage of fuels; their main cause of damage is corrosion, but the control of the bottom integrity is particularly complicated, as it is necessary to empty and clear the tank before allowing the inspector to enter inside it. To inspect the bottom is quite expensive and, in addition, it must be put out-service for a long period. Recently, a methodology has been developed to estimate the residual lifetime of storage tanks and predict the progress of corrosion with the aim to optimize the management of the maintenance. The method makes use of data collected during previous inspections and it has been implemented in a hardware and software system called "virtual sensor". A map representing the isolevel thickness curves is used as initial information to visualize the current damage state and predicted the future one. In order to better visualize the deterioration of the tank bottom, the selection of the best interpolation approach has been done by comparing deterministic and stochastic methods. A validation has been carried out to verify the best interpolating approach, which is used in the predicting model.
