Abstract

Large diameter steel pipelines for gas transportation may experience extreme overloads due to external actions such as soil sliding, faults movements, third part interactions. In these scenarios the material undergoes severe plastic strains which locally may reach the fracture limits. Due to the manufacturing process, the steels used in such applications have an anisotropic behavior both for plasticity and fracture. In this paper two steel grades have been characterized in view of anisotropic plastic fracture. Fracture tests have been planned to characterize the fracture behavior under different stress states and in different directions to define the anisotropic sensitivity. Finite element modelling, incorporating an anisotropic plasticity formulation, has been used to calculate the local fracture parameters in the specimens and to define the complete ductile fracture locus. An uncoupled damage evolution law has been finally used to evaluate the fracture limits on real pipelines failed in full scale laboratory tests. The strain to fracture prediction has been verified by local strain measurements on the fractured pipes. The model robustness has been also verified on global parameter predictions, such us the burst pressure.

Abstract

The transport of hazardous materials by pipeline is widely used for the transfer of significant quantities of oil and chemicals. Due to the extremely low frequency of spills, pipelines are considered the safest mode for the land transportation of hazardous substances. Accident records, while confirming that Loss of Containment (LOC) events are rare, also point out the major-accident hazard of pipelines, due to the extremely severe potential consequences of spills. Quantitative Risk Analysis (QRA) techniques have been applied to pipelines since many years with the aim of evaluating risk for workers or exposed population. However, releases of liquids, as oil and oil products, also create an hazard to the environment, due to the potential of extensive soil and groundwater contamination. An integrated model was developed for the environmental Risk Analysis of spills from pipelines. Specific environmental risk indexes were defined, expressing the risk of soil and groundwater contamination, both in physical and economic terms. A case-study is presented and discussed to illustrate the features of the methodology. The results confirmed that the proposed model may be considered an important tool within a comprehensive approach to the management of risk related to onshore pipelines.

Abstract

Major accidents may cause both direct damages to the exposed population and damage to the environment, indirectly affecting the population by the contamination of land, surface water and groundwater. A wide attention was paid to date to the assessment of the direct risk for the population deriving from major accidents (fires, explosions, toxic releases). Less work was devoted to the quantitative assessment of the risk due to the environmental consequences of major accidents. In the present study, an innovative GIS-based approach was developed for the quantitative assessment of the risk caused by damage to the environment deriving from major accidents involving pipelines. The method allows the calculation of local and overall environmental risk indexes, expressed both in physical and monetary terms. These are structured so that in perspective they can be combined with the risk obtained for the exposed population, providing a comprehensive risk figure of the potential consequences of major accidents involving oil pipelines. A specific software tool was developed to support the application of the methodology. A real-life case-study is presented and discussed in order to assess the potentiality of the approach. The results confirm that, in the frame of safety guidelines and good practices for pipelines, the proposed methodology represents a useful tool to fulfil requirements concerning the comprehensive risk assessment of pipeline operation, providing useful information on safety-critical segments and on the expected severity and economic impact of spill scenarios. © 2018 Elsevier Ltd